MR1: Methods and Statistics

Lead Research Organisation: MRC Cognition and Brain Sciences Unit

Abstract

The core scientific programmes of the MRC Cognition and Brain Sciences Unit call for the development of new, efficient and effective methods for measuring, evaluating and modelling human cognitive behaviour and its correlates in brain function. ||The work of the methods group draws on the fields of physics, physiology, mathematics, statistics, signal processing and graphical modelling in order to provide appropriate support towards this. ||Potential beneficiaries of clinical applications of these methodological advances include patients learning to use auditory brain-stem implants, patients with brain damage, and young people with problems of cognitive coordination.

Technical Summary

The research programme of the methods group is framed round the creation and implementation of a number of methodological advances that have been identified as offering important support to the main scientific programmes of the MRC Cognition and Brain Sciences Unit. ||One grouping of projects is directed towards improving the methods that underpin the use of functional magnetic resonance imaging (fMRI), and its scope, from initial raw data capture to interpretation via improved image processing to access previously hard-to-image regions, and to handle non-standard brains such as those with lesions. ||A second grouping of projects seeks to tailor the modelling of brain activity associated with lexical tasks to a range of modalities and experimental paradigms (fMRI, EEG, MEG). ||A third grouping of projects is framed to create new statistical methods to support a range of specialist needs, including the standardisation of psychometric tests for clinical use, and the optimisation of auditory brain-stem implants.

Organisations

Publications

10 25 50

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Adlam AL (2006) Semantic knowledge in mild cognitive impairment and mild Alzheimer's disease. in Cortex; a journal devoted to the study of the nervous system and behavior

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Avril S (2012) In vivo measurements of blood viscosity and wall stiffness in the carotid using PC-MRI in European Journal of Computational Mechanics

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Berry E (2009) The neural basis of effective memory therapy in a patient with limbic encephalitis. in Journal of neurology, neurosurgery, and psychiatry

 
Title A framework for the design of flexible cross-talk functions for spatial filtering of EEG/MEG data: DeFleCT. 
Description Brain activation estimated from EEG and MEG data is the basis for a number of time-series analyses. In these applications, it is essential to minimize "leakage" or "cross-talk" of the estimates among brain areas. Here, we present a novel framework that allows the design of flexible cross-talk functions (DeFleCT), combining three types of constraints: (1) full separation of multiple discrete brain sources, (2) minimization of contributions from other (distributed) brain sources, and (3) minimization of the contribution from measurement noise. Our framework allows the design of novel estimators by combining knowledge about discrete sources with constraints on distributed source activity and knowledge about noise covariance. These estimators will be useful in situations where assumptions about sources of interest need to be combined with uncertain information about additional sources that may contaminate the signal (e.g. distributed sources), and for which existing methods may not yield optimal solutions. We also show how existing estimators, such as maximum-likelihood dipole estimation, L2 minimum-norm estimation, and linearly-constrained minimum variance as well as null-beamformers, can be derived as special cases from this general formalism. The performance of the resulting estimators is demonstrated for the estimation of discrete sources and regions-of-interest in simulations of combined EEG/MEG data. Our framework will be useful for EEG/MEG studies applying time-series analysis in source space as well as for the evaluation and comparison of linear estimators. 
Type Of Material Improvements to research infrastructure 
Year Produced 2014 
Provided To Others? Yes  
Impact The paper describing the methods has been published in Human Brain Mapping (2014): http://www.ncbi.nlm.nih.gov/pubmed/23616402 Code and data are available from the CBU Wiki: http://imaging.mrc-cbu.cam.ac.uk/meg/AnalyzingData/DeFleCT_SpatialFiltering_Tools The DeFleCT methods has been implemented in the SPM beamforming toolbox by Dr. Vladimir Litvak: https://code.google.com/p/spm-beamforming-toolbox/source/browse/trunk/private/DeFleCT.m?spec=svn95&r=95 It is about to be implemented in MNE-Python. 
 
Title Automatic Analysis (aa) Software 
Description Automatic analysis (aa) is a framework for medical image analysis designed to allow users to achieve an efficient analysis workflow, whether analyzing a single dataset or creating a complex pipeline with many thousands of acquisitions. aa uses Matlab, and brings together many of the best tools for fMRI analysis (e.g., from SPM5/8/12, FSL and Freesurfer), and MEG/EEG (EEGlab). 
Type Of Material Improvements to research infrastructure 
Year Produced 2006 
Provided To Others? Yes  
Impact In the Unit,aa is the backbone of analysing fMRI,DTI, MTR and structural data from Siemens 3T (Trio, Prisma) MRI scanner, Elekta Neuromag Vectorview MEG scanner and Brain Products BrainAmp EEG. New colleagues are introducedto aa right from the start by means of workshops, which allow them to perform analysis quite early on. A highlighted project, the Cambridge Centre for Aging and Neuroscience (CamCAN), involving multiple sessions of hundreds of subjects, also employs aa, which ensures both high consistency via standardized user scripts and tasklists and high processing speed via parallelization. In addition, aa has been installed an configured at many sites both within (e.g. Behavioural and Clinical Neuroscience Institute) and outside (e.g. Hungarian Academy of Sciences, Research Centre for Natural Sciences, Brain Imaging Centre) of Cambridge. Automatic analysis (aa): Efficient neuroimaging workflows and parallel processing using Matlab and XML. Available from: https://www.researchgate.net/publication/270893904_Automatic_analysis_aa_Efficient_neuroimaging_workflows_and_parallel_processing_using_Matlab_and_XML [accessed Feb 9, 2016]. Indexed publication: DOI: 10.3389/fninf.2014.00090 
URL http://automaticanalysis.org
 
Title CBU Methods/Imaging/MEG Wiki pages 
Description Our Wiki pages provide a wealth of information on data acquisition, analysis, experimental design and formalities related to the research carried out at the Cognition and Brain Sciences Unit. Most of this information is available to everyone. An overview of our Wiki pages can be found here: http://www.mrc-cbu.cam.ac.uk/methods-and-resources/imaginganalysis/ 
Type Of Material Improvements to research infrastructure 
Year Produced 2006 
Provided To Others? Yes  
Impact Our Wiki pages get hundreds of hits a day, and are visited from all over the world. We have received enthusiastic feedback from other researchers, and some of our Wiki pages get cited in publications. These pages facilitate research for a large number of researchers, for whom it would otherwise be very difficult of impossible to find this kind of information. Our Wikis demonstrate the CBU's role as a "knowledge hub" within and beyond the Cambridge cognitive neuroscience community. 
URL http://www.mrc-cbu.cam.ac.uk/methods-and-resources/imaginganalysis/
 
Title CBU Statistical Wiki pages 
Description Web pages with EXCEL spreadsheet, R and SPSS programs for computing statistics which have been requested by CBSU unit staff and students. There are also slides for Graduate talks for Cognitive Psychologists Lectures and Demos and a bibliography of statistical texts which are available for borrowing from the CBSU library. 
Type Of Material Improvements to research infrastructure 
Year Produced 2006 
Provided To Others? Yes  
Impact (1) Marcel Meyer (Andrew Lawrence's Cardiff student) told me he was citing my webpage for his FDR SPSS calculation in January 2013. The citation will be of form: Watson, P.C. (2012). SPSS code to perform the Benjamini and Hochberg procedure [Computer software]. Retrieved day, month, year, from http://imaging.mrc-cbu.cam.ac.uk/statswiki/FAQ/FDR. Mike Dadds (UNSW psychology) also used the FDR program for his research in 2012. 
URL http://imaging.mrc-cbu.cam.ac.uk/statswiki/
 
Title Cross-talk and point-spread functions for linear EEG/MEG source estimation 
Description Cross-talk and point-spread functions (CTFs, PSFs) describe the spatial resolution and localisation accuracy of linear source estimation methods for EEG/MEG. They are not available in most standard software packages. We implemented them for the EEG/MEG analysis package MNE-Python 
Type Of Material Improvements to research infrastructure 
Year Produced 2014 
Provided To Others? Yes  
Impact The tools are implemented in the open-source software package MNE-Python (http://journal.frontiersin.org/Journal/10.3389/fnins.2013.00267/full): https://github.com/mne-tools/mne-python/blob/master/mne/minimum_norm/psf_ctf.py 
 
Title DiPy Software 
Description Open source scientific software toolbox (dipy - diffusion imaging in python) for analysis of diffusion magnetic resonance imaging data written in the python language: see www.dipy.org 
Type Of Material Improvements to research infrastructure 
Year Produced 2009 
Provided To Others? Yes  
Impact Has been the springboard for establishing collaborations with laboratories in USA, France, Switzerland and Germany in addition to the UK. 
URL http://www.dipy.org
 
Title MarsBaR software 
Description Software to assist 'regions of interest' fMRI/PET data analysis 
Type Of Material Improvements to research infrastructure 
Year Produced 2006 
Provided To Others? Yes  
Impact Several 100s of software downloads and citations 
URL http://marsbar.sourceforge.net/
 
Title Mix-and-Match tools for experimental stimulus generation and randomisation 
Description Mix and Match are tools to support experimental research. Mix will allow experimental stimuli to be pseudo-randomised, according to constraints supplied by the user in a simple script. Match can match the conditions of factorial experiments. Both utilities have the ability to significantly speed up the development, and even improve the quality and power of your experiments. 
Type Of Material Improvements to research infrastructure 
Year Produced 2007 
Provided To Others? Yes  
Impact Two papers have resulted from this describing the methods in Behavioral Research Methods: http://www.ncbi.nlm.nih.gov/pubmed/17393828 http://www.ncbi.nlm.nih.gov/pubmed/18183914 A mailing list exists that provides a forum for users: http://www.mrc-cbu.cam.ac.uk/people/maarten.van-casteren/mixandmatch/ 
 
Title United Diffusion Kurtosis Imaging (UDKI) toolbox 
Description United Diffusion Kurtosis Imaging toolbox (UDKI) is a toolbox for Diffusion Kurtosis Imaging (DKI) data processing. It includes fundamental DKI pre-processing steps and modules to estimate the kurtosis tensor and standard diffusion and kurtosis rotational invariant measures. This toolbox also includes DKI biological modelling for estimates estimation of axonal water fraction and also DKI based tractography. UDKI is fully implemented in MATLAB and it is compatible with any operating system (Window, Linux or Mac OS X) with a base installation of MATLAB (version 7.8 onwards). The base MATLAB license is not provided with this toolbox. UDKI functionalities are grouped in six modules: pre-processing; DTI/DKI model fitting; estimation of diffusion tensor rotational invariant measures estimation; estimation of kurtosis tensor rotational invariant measures estimation; fitting of DKI biophysical models fitting; and DKI based tractography reconstruction. 
Type Of Material Improvements to research infrastructure 
Year Produced 2016 
Provided To Others? Yes  
Impact A peer-reviewed research paper an a conference abstract have been publish describing the methods included in the UDKI toolbox. The toolbox has also been distributed to several other research groups, making our work available to the neuroimaging community worldwide. 
 
Title VoiceKey program for off-line voicekey measurements 
Description The VoiceKey program can perform off-line voicekey measurements on wav files, for example those produced by E-Prime in naming experiments. Off-line software voicekeys have many advantages over electronic on-line voicekey devices. The VoiceKey program can be much more precise and will allow fine-tuning of the voicekey parameters on a level that is not possible with electronic voicekey devices. The only reason to use an electronic, online device is when you need the output of the voicekey to trigger a subsequent event in your experiment or to provide some kind of feedback. When this is not necessary it is vastly preferable to record the responses and use off-line voicekey software instead. 
Type Of Material Improvements to research infrastructure 
Year Produced 2012 
Provided To Others? Yes  
Impact This software is described and can be downloaded from here: http://www.mrc-cbu.cam.ac.uk/people/maarten-van-casteren/the-voicekey-program/ 
 
Description A Randomised Controlled Feasibility Trial of a Novel Transdiagnostic Psychological Intervention for Mood and Anxiety Disorders. The proposed study would aim to conduct a feasibility trial of a transdiagnostic psychological treatment protocol. 
Organisation Cambridgeshire and Peterborough NHS Foundation Trust
Country United Kingdom 
Sector Public 
PI Contribution Statistical analyses implementation planning
Collaborator Contribution Help with patient recruitment and specialist advice about the handling of patients and the testing procedure and measures used.
Impact The collaboration has only received funding as of January 2015 (for three years) so too early to say.
Start Year 2015
 
Description A Randomised Controlled Feasibility Trial of a Novel Transdiagnostic Psychological Intervention for Mood and Anxiety Disorders. The proposed study would aim to conduct a feasibility trial of a transdiagnostic psychological treatment protocol. 
Organisation University of Cambridge
Country United Kingdom 
Sector Academic/University 
PI Contribution Statistical analyses implementation planning
Collaborator Contribution Help with patient recruitment and specialist advice about the handling of patients and the testing procedure and measures used.
Impact The collaboration has only received funding as of January 2015 (for three years) so too early to say.
Start Year 2015
 
Description A Randomised Controlled Feasibility Trial of a Novel Transdiagnostic Psychological Intervention for Mood and Anxiety Disorders. The proposed study would aim to conduct a feasibility trial of a transdiagnostic psychological treatment protocol. 
Organisation University of Cambridge
Country United Kingdom 
Sector Academic/University 
PI Contribution Statistical analyses implementation planning
Collaborator Contribution Help with patient recruitment and specialist advice about the handling of patients and the testing procedure and measures used.
Impact The collaboration has only received funding as of January 2015 (for three years) so too early to say.
Start Year 2015
 
Description A Randomised Controlled Feasibility Trial of a Novel Transdiagnostic Psychological Intervention for Mood and Anxiety Disorders. The proposed study would aim to conduct a feasibility trial of a transdiagnostic psychological treatment protocol. 
Organisation University of Exeter
Country United Kingdom 
Sector Academic/University 
PI Contribution Statistical analyses implementation planning
Collaborator Contribution Help with patient recruitment and specialist advice about the handling of patients and the testing procedure and measures used.
Impact The collaboration has only received funding as of January 2015 (for three years) so too early to say.
Start Year 2015
 
Description A Randomised Controlled Feasibility Trial of a Novel Transdiagnostic Psychological Intervention for Mood and Anxiety Disorders. The proposed study would aim to conduct a feasibility trial of a transdiagnostic psychological treatment protocol. 
Organisation University of New South Wales
Country Australia 
Sector Academic/University 
PI Contribution Statistical analyses implementation planning
Collaborator Contribution Help with patient recruitment and specialist advice about the handling of patients and the testing procedure and measures used.
Impact The collaboration has only received funding as of January 2015 (for three years) so too early to say.
Start Year 2015
 
Description Automatic analysis (aa): Efficient neuroimaging workflows and parallel processing using Matlab 
Organisation Radboud University Nijmegen
Department Donders Institute for Brain, Cognition and Behaviour
Country Netherlands 
Sector Academic/University 
PI Contribution Automatic analysis (aa) is a framework for medical image analysis designed to allow users to achieve an efficient analysis workflow, whether analyzing a single dataset or creating a complex pipeline with many thousands of acquisitions. aa uses Matlab, and brings together many of the best tools for fMRI analysis (e.g., from SPM5/8/12, FSL and Freesurfer), and MEG/EEG (EEGlab). Publications: see below
Collaborator Contribution Automatic analysis (aa) is a framework for medical image analysis designed to allow users to achieve an efficient analysis workflow, whether analyzing a single dataset or creating a complex pipeline with many thousands of acquisitions. aa uses Matlab, and brings together many of the best tools for fMRI analysis (e.g., from SPM5/8/12, FSL and Freesurfer), and MEG/EEG (EEGlab). Publications: see below
Impact GitHub repository: https://github.com/rhodricusack/automaticanalysis Indexed publication: DOI: 10.3389/fninf.2014.00090
Start Year 2012
 
Description Automatic analysis (aa): Efficient neuroimaging workflows and parallel processing using Matlab 
Organisation Washington University in St Louis
Country United States 
Sector Academic/University 
PI Contribution Automatic analysis (aa) is a framework for medical image analysis designed to allow users to achieve an efficient analysis workflow, whether analyzing a single dataset or creating a complex pipeline with many thousands of acquisitions. aa uses Matlab, and brings together many of the best tools for fMRI analysis (e.g., from SPM5/8/12, FSL and Freesurfer), and MEG/EEG (EEGlab). Publications: see below
Collaborator Contribution Automatic analysis (aa) is a framework for medical image analysis designed to allow users to achieve an efficient analysis workflow, whether analyzing a single dataset or creating a complex pipeline with many thousands of acquisitions. aa uses Matlab, and brings together many of the best tools for fMRI analysis (e.g., from SPM5/8/12, FSL and Freesurfer), and MEG/EEG (EEGlab). Publications: see below
Impact GitHub repository: https://github.com/rhodricusack/automaticanalysis Indexed publication: DOI: 10.3389/fninf.2014.00090
Start Year 2012
 
Description Automatic analysis (aa): Efficient neuroimaging workflows and parallel processing using Matlab 
Organisation Western University
Country Canada 
Sector Academic/University 
PI Contribution Automatic analysis (aa) is a framework for medical image analysis designed to allow users to achieve an efficient analysis workflow, whether analyzing a single dataset or creating a complex pipeline with many thousands of acquisitions. aa uses Matlab, and brings together many of the best tools for fMRI analysis (e.g., from SPM5/8/12, FSL and Freesurfer), and MEG/EEG (EEGlab). Publications: see below
Collaborator Contribution Automatic analysis (aa) is a framework for medical image analysis designed to allow users to achieve an efficient analysis workflow, whether analyzing a single dataset or creating a complex pipeline with many thousands of acquisitions. aa uses Matlab, and brings together many of the best tools for fMRI analysis (e.g., from SPM5/8/12, FSL and Freesurfer), and MEG/EEG (EEGlab). Publications: see below
Impact GitHub repository: https://github.com/rhodricusack/automaticanalysis Indexed publication: DOI: 10.3389/fninf.2014.00090
Start Year 2012
 
Description Brain Imaging Data Structure to organize and describe your neuroimaging and behavioral data in simple and intuitive way 
Organisation Stanford University
Department Stanford Center for Reproducible Neuroscience
Country United States 
Sector Academic/University 
PI Contribution I have been contributing to building the BIDS models and a BIDS App for automatic analysis and I have contributed to the manuscripts with DOIs of 10.1038/sdata.2016.44 and 10.1371/journal.pcbi.1005209
Collaborator Contribution They have been contributing to building the BIDS models and various BIDS App and they have contributed to the manuscripts with DOIs of 10.1038/sdata.2016.44 and 10.1371/journal.pcbi.1005209
Impact BIDS model (http://bids.neuroimaging.io): multi-disciplinary (IT, data science, neuroimaging) BIDS Apps (http://bids-apps.neuroimaging.io/): multi-disciplinary (IT, programming, neuorimaging, statistics)
Start Year 2015
 
Description CamCAN 
Organisation University of Cambridge
Country United Kingdom 
Sector Academic/University 
PI Contribution Marta Correia Optimisation of MRI acquisition sequences. Development of analysis pipeline for DKI data. Supervising masters student in 2011/2012 and PhD student (started in 2013). Co-writing of manuscripts. Rafael Henriques Development of method for analysis of DKI data. Co-writing of manuscripts. Tibor Auer Support in implementation of automated pipelines for data analysis.
Collaborator Contribution MRI data. Co-writing of manuscripts.
Impact Indexed manuscripts: DOI: 10.1016/j.neuroimage.2015.09.018 Abstract presented at the ESMRM annual meeting 2012. Full manuscript in preparation.
Start Year 2010
 
Description Center-TBI 
Organisation University of Cambridge
Country United Kingdom 
Sector Academic/University 
PI Contribution Development of analysis tools for multi-center MRI data of acute and chronic TBI patients. Supervising masters student.
Collaborator Contribution Center-TBI and the participating institutions will provide the patient data.
Impact None as yet.
Start Year 2014
 
Description DIffusion Tensor Imaging of aphasia and stroke 
Organisation University College London
Country United Kingdom 
Sector Academic/University 
PI Contribution Analysis of DTI data from stroke patients with aphasia. Co-writing of manuscripts.
Collaborator Contribution Provided the patient data. Statistical analysis of cognitive data. Co-writing of manuscripts.
Impact One peer reviewed publication: http://www.tandfonline.com/doi/abs/10.1080/02687038.2010.534803#.VGFNlDSsX0g One publication under review with Human Brain Mapping.
Start Year 2012
 
Description DIffusion Tensor Imaging of aphasia and stroke 
Organisation University of Cambridge
Country United Kingdom 
Sector Academic/University 
PI Contribution Analysis of DTI data from stroke patients with aphasia. Co-writing of manuscripts.
Collaborator Contribution Provided the patient data. Statistical analysis of cognitive data. Co-writing of manuscripts.
Impact One peer reviewed publication: http://www.tandfonline.com/doi/abs/10.1080/02687038.2010.534803#.VGFNlDSsX0g One publication under review with Human Brain Mapping.
Start Year 2012
 
Description Development of Diffusion Kurtosis Imaging (DKI) Methods 
Organisation University of Lisbon
Country Portugal 
Sector Academic/University 
PI Contribution Co-supervising a masters student in 2011/2012 working on optimisation of analysis pipelines for DKI. Supervising a PhD student working on biophysical models for DKI data. Data sharing agreement for MRI data. Co-writing of a publication.
Collaborator Contribution Co-supervising a masters student in 2011/2012. Co-writing a publication. Preparation and submission of a patent with the INPI (Portuguese Institute for Intellectual Property).
Impact Patent submitted with the INPI (Portuguese Institute for Intellectual Property). Publication submitted to Neuroimage (currently under review).
Start Year 2011
 
Description Development of fMRI acquistion sequences 
Organisation Siemens Healthcare
Department Siemens Medical Solutions
Country Germany 
Sector Private 
PI Contribution Development of an efficient acquisition scheme for whole brain fMRI.
Impact Patent for Single shot partial dial echo (SPADE) EPI - An efficient acquisition scheme for whole brain fMRI. Filed in UK and USA.
Start Year 2006
 
Description EEG/MEG studies on language production 
Organisation Columbia University
Country United States 
Sector Academic/University 
PI Contribution The MRC-CBU provided the data acquisition facilities (EEG/MEG) and computing infrastructure. Dr. Olaf Hauk supervised data acquisition and performed most of the data analysis, and contributed to the writing up of the results.
Collaborator Contribution Dr. Michele Miozzo initiated these studies, contributed stimuli and large parts of the experimental design, and first-authored one and possible other papers.
Impact Paper in Cerebral Cortex (2014): http://www.ncbi.nlm.nih.gov/pubmed/25005037 Conference Abstract (2010): http://www.frontiersin.org/10.3389/conf.fnins.2010.06.00238/event_abstract Masters Thesis of Christina Schuster at MRC-CBU
Start Year 2009
 
Description Grant co-applicant: A Randomised Controlled Feasibility Trial of a Novel Transdiagnostic Psychological Intervention for Mood and Anxiety Disorders. 
Organisation University of Cambridge
Country United Kingdom 
Sector Academic/University 
PI Contribution Preparation of the statistical sections of application and on-going statistical support during the 36 months of the study.
Collaborator Contribution Statistical support with randomisation and analysis.
Impact No outcomes as yet but it is hoped that this clinical research work will be help people and their families who have mood disorders.
Start Year 2016
 
Description MEG study on free will with Greg Davies 
Organisation University of Cambridge
Country United Kingdom 
Sector Academic/University 
PI Contribution Olaf Hauk provided advice on experimental design and data analysis, training a post-doc
Collaborator Contribution The project is part of Greg Davies' grant on the neuroscience of free will. One post-doc is currently working on the project.
Impact No outcomes yet
Start Year 2013
 
Description MR sepctroscopy of GABA 
Organisation University of Utah
Country United States 
Sector Academic/University 
PI Contribution MRS data acquisition and analysis. Co-writing of a conference abstract and a manuscript.
Collaborator Contribution Andrew Prescot from the University of Utah has provided the MRS acquisition sequence and analysis software.
Impact Abstract accepted for presentation at the SfN meeting 2014. Full manuscript in preparation.
Start Year 2013
 
Description MRI of Traumatic Brain Injury 
Organisation University of Cambridge
Country United Kingdom 
Sector Academic/University 
PI Contribution Supervising a masters student working on MRI data calibration methods for multi-center studies. Analysis of MRI data. Co-writing of manuscripts.
Collaborator Contribution The University of Cambridge has provided the patient data. Co-writing of manuscripts.
Impact Several abstracts presented at relevant conferences, including ISMRM and HBM. One peer reviwed publication http://www.nature.com/jcbfm/journal/v34/n10/full/jcbfm2014123a.html and another one under review.
Start Year 2009
 
Description Multimodal imaging of stroke recovery 
Organisation University of the Basque Country
Country Spain 
Sector Academic/University 
PI Contribution Host PhD-Student: Rosalia Dacosta Aguayo Publications (see below)
Collaborator Contribution Methodological support Publications (see below)
Impact Indexed publications: PubmedIDs: 25324040, 24523262, 24475078
Start Year 2012
 
Description Natural reading in EEG/MEG 
Organisation Humboldt University of Berlin
Country Germany 
Sector Academic/University 
PI Contribution Analysed EEG data using regression and mixed-effects modelling. Contributed to manuscripts and conference abstracts. Several talks and lab visits.
Collaborator Contribution The colleagues at HU Berlin provided the EEG and eye-tracking data and ran several types of analysis, and contributed to a manuscript.
Impact Abstract at Neurobiology of Language conference 2012: http://www.neurolang.org/programs/NLC2012_Program.pdf Results have been presented in several talks
Start Year 2010
 
Description Neuro-cognitive foundations of combinatorial grammar 
Organisation University of Cambridge
Department Cambridge Institute for Medical Research (CIMR)
Country United Kingdom 
Sector Academic/University 
PI Contribution Co-authored ESRC Research Grant application, particularly on EEG/MEG studies.
Collaborator Contribution Dr. Bozic is main grant applicant.
Impact Grant application and reply to reviewer comments.
Start Year 2014
 
Description Neurofeedback using real-time fMRI 
Organisation Maastricht University (UM)
Country Netherlands 
Sector Academic/University 
PI Contribution Setting up, maintaining and developing a rea-time fMRI system. Hosting PhD-student: Wan Ilma Dewiputri Publications (see below)
Collaborator Contribution Co-supervising PhD-student: Wan Ilma Dewiputri Providing a faster and more reliable way to obtain acquired images in real-time. Publications (see below)
Impact PhD-Project: Wan Ilma Dewiputri Indexed publications: PMCID: PMC3957350 DOI: 10.3389/fnhum.2014.00990 DOI: 10.3389/fnhum.2015.00547 Conference presentations: Auer T, Schweizer R, Frahm J. Neural circuits underlying the neurofeedback training, 2014 Meeting of the Society of Applied Neurosciences, 2014, Utrecht, The Netherlands Auer T, Schweizer R, Frahm J. The role of the anterior midcingulate cortex in neurofeedback training, 19th Annual Meeting of the Organization for Human Brain Mapping, 2013, Seattle, USA Auer T, Frahm J. Confounding factors in Neurofeedback training based on fMRI of motor imagery, 2011 Meeting of the Society of Applied Neurosciences, 2011, Thessaloniki, Greece
Start Year 2012
 
Description Neurofeedback using real-time fMRI 
Organisation Max Planck Society
Department Max Planck Institute for Biophysical Chemistry Goettingen
Country Germany 
Sector Public 
PI Contribution Setting up, maintaining and developing a rea-time fMRI system. Hosting PhD-student: Wan Ilma Dewiputri Publications (see below)
Collaborator Contribution Co-supervising PhD-student: Wan Ilma Dewiputri Providing a faster and more reliable way to obtain acquired images in real-time. Publications (see below)
Impact PhD-Project: Wan Ilma Dewiputri Indexed publications: PMCID: PMC3957350 DOI: 10.3389/fnhum.2014.00990 DOI: 10.3389/fnhum.2015.00547 Conference presentations: Auer T, Schweizer R, Frahm J. Neural circuits underlying the neurofeedback training, 2014 Meeting of the Society of Applied Neurosciences, 2014, Utrecht, The Netherlands Auer T, Schweizer R, Frahm J. The role of the anterior midcingulate cortex in neurofeedback training, 19th Annual Meeting of the Organization for Human Brain Mapping, 2013, Seattle, USA Auer T, Frahm J. Confounding factors in Neurofeedback training based on fMRI of motor imagery, 2011 Meeting of the Society of Applied Neurosciences, 2011, Thessaloniki, Greece
Start Year 2012
 
Description Neuroimaging Data Model (NIDM): standardising the description of the neuroimaging data, the processing pipeline and the results. 
Organisation Columbia University
Country United States 
Sector Academic/University 
PI Contribution The Neuroimaging Data Model (NIDM) is a collection of specification documents that define extensions the the W3C PROV standard for the domain of human brain mapping. NIDM uses provenance information as means to link components from different stages of the scientific research process from dataset descriptors and computational workflow, to derived data and publication. Publication (see below)
Collaborator Contribution The Neuroimaging Data Model (NIDM) is a collection of specification documents that define extensions the the W3C PROV standard for the domain of human brain mapping. NIDM uses provenance information as means to link components from different stages of the scientific research process from dataset descriptors and computational workflow, to derived data and publication. Publication (see below)
Impact Indexed abstracts: DOI: 10.3389/conf.fninf.2014.18.00031 DOI: 10.3389/conf.fnins.2015.91.00004
Start Year 2013
 
Description Neuroimaging Data Model (NIDM): standardising the description of the neuroimaging data, the processing pipeline and the results. 
Organisation Concordia University
Department PERFORM Centre and Department of Psychology
Country Canada 
Sector Academic/University 
PI Contribution The Neuroimaging Data Model (NIDM) is a collection of specification documents that define extensions the the W3C PROV standard for the domain of human brain mapping. NIDM uses provenance information as means to link components from different stages of the scientific research process from dataset descriptors and computational workflow, to derived data and publication. Publication (see below)
Collaborator Contribution The Neuroimaging Data Model (NIDM) is a collection of specification documents that define extensions the the W3C PROV standard for the domain of human brain mapping. NIDM uses provenance information as means to link components from different stages of the scientific research process from dataset descriptors and computational workflow, to derived data and publication. Publication (see below)
Impact Indexed abstracts: DOI: 10.3389/conf.fninf.2014.18.00031 DOI: 10.3389/conf.fnins.2015.91.00004
Start Year 2013
 
Description Neuroimaging Data Model (NIDM): standardising the description of the neuroimaging data, the processing pipeline and the results. 
Organisation Georgia State University
Country United States 
Sector Academic/University 
PI Contribution The Neuroimaging Data Model (NIDM) is a collection of specification documents that define extensions the the W3C PROV standard for the domain of human brain mapping. NIDM uses provenance information as means to link components from different stages of the scientific research process from dataset descriptors and computational workflow, to derived data and publication. Publication (see below)
Collaborator Contribution The Neuroimaging Data Model (NIDM) is a collection of specification documents that define extensions the the W3C PROV standard for the domain of human brain mapping. NIDM uses provenance information as means to link components from different stages of the scientific research process from dataset descriptors and computational workflow, to derived data and publication. Publication (see below)
Impact Indexed abstracts: DOI: 10.3389/conf.fninf.2014.18.00031 DOI: 10.3389/conf.fnins.2015.91.00004
Start Year 2013
 
Description Neuroimaging Data Model (NIDM): standardising the description of the neuroimaging data, the processing pipeline and the results. 
Organisation Massachusetts General Hospital
Country United States 
Sector Hospitals 
PI Contribution The Neuroimaging Data Model (NIDM) is a collection of specification documents that define extensions the the W3C PROV standard for the domain of human brain mapping. NIDM uses provenance information as means to link components from different stages of the scientific research process from dataset descriptors and computational workflow, to derived data and publication. Publication (see below)
Collaborator Contribution The Neuroimaging Data Model (NIDM) is a collection of specification documents that define extensions the the W3C PROV standard for the domain of human brain mapping. NIDM uses provenance information as means to link components from different stages of the scientific research process from dataset descriptors and computational workflow, to derived data and publication. Publication (see below)
Impact Indexed abstracts: DOI: 10.3389/conf.fninf.2014.18.00031 DOI: 10.3389/conf.fnins.2015.91.00004
Start Year 2013
 
Description Neuroimaging Data Model (NIDM): standardising the description of the neuroimaging data, the processing pipeline and the results. 
Organisation Massachusetts Institute of Technology
Country United States 
Sector Academic/University 
PI Contribution The Neuroimaging Data Model (NIDM) is a collection of specification documents that define extensions the the W3C PROV standard for the domain of human brain mapping. NIDM uses provenance information as means to link components from different stages of the scientific research process from dataset descriptors and computational workflow, to derived data and publication. Publication (see below)
Collaborator Contribution The Neuroimaging Data Model (NIDM) is a collection of specification documents that define extensions the the W3C PROV standard for the domain of human brain mapping. NIDM uses provenance information as means to link components from different stages of the scientific research process from dataset descriptors and computational workflow, to derived data and publication. Publication (see below)
Impact Indexed abstracts: DOI: 10.3389/conf.fninf.2014.18.00031 DOI: 10.3389/conf.fnins.2015.91.00004
Start Year 2013
 
Description Neuroimaging Data Model (NIDM): standardising the description of the neuroimaging data, the processing pipeline and the results. 
Organisation Stanford University
Department Department of Biology
Country United States 
Sector Academic/University 
PI Contribution The Neuroimaging Data Model (NIDM) is a collection of specification documents that define extensions the the W3C PROV standard for the domain of human brain mapping. NIDM uses provenance information as means to link components from different stages of the scientific research process from dataset descriptors and computational workflow, to derived data and publication. Publication (see below)
Collaborator Contribution The Neuroimaging Data Model (NIDM) is a collection of specification documents that define extensions the the W3C PROV standard for the domain of human brain mapping. NIDM uses provenance information as means to link components from different stages of the scientific research process from dataset descriptors and computational workflow, to derived data and publication. Publication (see below)
Impact Indexed abstracts: DOI: 10.3389/conf.fninf.2014.18.00031 DOI: 10.3389/conf.fnins.2015.91.00004
Start Year 2013
 
Description Neuroimaging Data Model (NIDM): standardising the description of the neuroimaging data, the processing pipeline and the results. 
Organisation University College London
Department Institute of Neurology
Country United Kingdom 
Sector Academic/University 
PI Contribution The Neuroimaging Data Model (NIDM) is a collection of specification documents that define extensions the the W3C PROV standard for the domain of human brain mapping. NIDM uses provenance information as means to link components from different stages of the scientific research process from dataset descriptors and computational workflow, to derived data and publication. Publication (see below)
Collaborator Contribution The Neuroimaging Data Model (NIDM) is a collection of specification documents that define extensions the the W3C PROV standard for the domain of human brain mapping. NIDM uses provenance information as means to link components from different stages of the scientific research process from dataset descriptors and computational workflow, to derived data and publication. Publication (see below)
Impact Indexed abstracts: DOI: 10.3389/conf.fninf.2014.18.00031 DOI: 10.3389/conf.fnins.2015.91.00004
Start Year 2013
 
Description Neuroimaging Data Model (NIDM): standardising the description of the neuroimaging data, the processing pipeline and the results. 
Organisation University of California
Country United States 
Sector Academic/University 
PI Contribution The Neuroimaging Data Model (NIDM) is a collection of specification documents that define extensions the the W3C PROV standard for the domain of human brain mapping. NIDM uses provenance information as means to link components from different stages of the scientific research process from dataset descriptors and computational workflow, to derived data and publication. Publication (see below)
Collaborator Contribution The Neuroimaging Data Model (NIDM) is a collection of specification documents that define extensions the the W3C PROV standard for the domain of human brain mapping. NIDM uses provenance information as means to link components from different stages of the scientific research process from dataset descriptors and computational workflow, to derived data and publication. Publication (see below)
Impact Indexed abstracts: DOI: 10.3389/conf.fninf.2014.18.00031 DOI: 10.3389/conf.fnins.2015.91.00004
Start Year 2013
 
Description Neuroimaging Data Model (NIDM): standardising the description of the neuroimaging data, the processing pipeline and the results. 
Organisation University of California
Country United States 
Sector Academic/University 
PI Contribution The Neuroimaging Data Model (NIDM) is a collection of specification documents that define extensions the the W3C PROV standard for the domain of human brain mapping. NIDM uses provenance information as means to link components from different stages of the scientific research process from dataset descriptors and computational workflow, to derived data and publication. Publication (see below)
Collaborator Contribution The Neuroimaging Data Model (NIDM) is a collection of specification documents that define extensions the the W3C PROV standard for the domain of human brain mapping. NIDM uses provenance information as means to link components from different stages of the scientific research process from dataset descriptors and computational workflow, to derived data and publication. Publication (see below)
Impact Indexed abstracts: DOI: 10.3389/conf.fninf.2014.18.00031 DOI: 10.3389/conf.fnins.2015.91.00004
Start Year 2013
 
Description Neuroimaging Data Model (NIDM): standardising the description of the neuroimaging data, the processing pipeline and the results. 
Organisation University of California, Berkeley
Department Helen Wills Neuroscience Institute
Country United States 
Sector Academic/University 
PI Contribution The Neuroimaging Data Model (NIDM) is a collection of specification documents that define extensions the the W3C PROV standard for the domain of human brain mapping. NIDM uses provenance information as means to link components from different stages of the scientific research process from dataset descriptors and computational workflow, to derived data and publication. Publication (see below)
Collaborator Contribution The Neuroimaging Data Model (NIDM) is a collection of specification documents that define extensions the the W3C PROV standard for the domain of human brain mapping. NIDM uses provenance information as means to link components from different stages of the scientific research process from dataset descriptors and computational workflow, to derived data and publication. Publication (see below)
Impact Indexed abstracts: DOI: 10.3389/conf.fninf.2014.18.00031 DOI: 10.3389/conf.fnins.2015.91.00004
Start Year 2013
 
Description Neuroimaging Data Model (NIDM): standardising the description of the neuroimaging data, the processing pipeline and the results. 
Organisation University of California, San Diego (UCSD)
Department Qualcomm Institute
Country United States 
Sector Academic/University 
PI Contribution The Neuroimaging Data Model (NIDM) is a collection of specification documents that define extensions the the W3C PROV standard for the domain of human brain mapping. NIDM uses provenance information as means to link components from different stages of the scientific research process from dataset descriptors and computational workflow, to derived data and publication. Publication (see below)
Collaborator Contribution The Neuroimaging Data Model (NIDM) is a collection of specification documents that define extensions the the W3C PROV standard for the domain of human brain mapping. NIDM uses provenance information as means to link components from different stages of the scientific research process from dataset descriptors and computational workflow, to derived data and publication. Publication (see below)
Impact Indexed abstracts: DOI: 10.3389/conf.fninf.2014.18.00031 DOI: 10.3389/conf.fnins.2015.91.00004
Start Year 2013
 
Description Neuroimaging Data Model (NIDM): standardising the description of the neuroimaging data, the processing pipeline and the results. 
Organisation University of Southern California
Department Information Sciences Institute (ISI)
Country United States 
Sector Academic/University 
PI Contribution The Neuroimaging Data Model (NIDM) is a collection of specification documents that define extensions the the W3C PROV standard for the domain of human brain mapping. NIDM uses provenance information as means to link components from different stages of the scientific research process from dataset descriptors and computational workflow, to derived data and publication. Publication (see below)
Collaborator Contribution The Neuroimaging Data Model (NIDM) is a collection of specification documents that define extensions the the W3C PROV standard for the domain of human brain mapping. NIDM uses provenance information as means to link components from different stages of the scientific research process from dataset descriptors and computational workflow, to derived data and publication. Publication (see below)
Impact Indexed abstracts: DOI: 10.3389/conf.fninf.2014.18.00031 DOI: 10.3389/conf.fnins.2015.91.00004
Start Year 2013
 
Description Neuroimaging Data Model (NIDM): standardising the description of the neuroimaging data, the processing pipeline and the results. 
Organisation University of Warwick
Country United Kingdom 
Sector Academic/University 
PI Contribution The Neuroimaging Data Model (NIDM) is a collection of specification documents that define extensions the the W3C PROV standard for the domain of human brain mapping. NIDM uses provenance information as means to link components from different stages of the scientific research process from dataset descriptors and computational workflow, to derived data and publication. Publication (see below)
Collaborator Contribution The Neuroimaging Data Model (NIDM) is a collection of specification documents that define extensions the the W3C PROV standard for the domain of human brain mapping. NIDM uses provenance information as means to link components from different stages of the scientific research process from dataset descriptors and computational workflow, to derived data and publication. Publication (see below)
Impact Indexed abstracts: DOI: 10.3389/conf.fninf.2014.18.00031 DOI: 10.3389/conf.fnins.2015.91.00004
Start Year 2013
 
Description Neuroimaging Data Model (NIDM): standardising the description of the neuroimaging data, the processing pipeline and the results. 
Organisation University of Washington
Country United States 
Sector Academic/University 
PI Contribution The Neuroimaging Data Model (NIDM) is a collection of specification documents that define extensions the the W3C PROV standard for the domain of human brain mapping. NIDM uses provenance information as means to link components from different stages of the scientific research process from dataset descriptors and computational workflow, to derived data and publication. Publication (see below)
Collaborator Contribution The Neuroimaging Data Model (NIDM) is a collection of specification documents that define extensions the the W3C PROV standard for the domain of human brain mapping. NIDM uses provenance information as means to link components from different stages of the scientific research process from dataset descriptors and computational workflow, to derived data and publication. Publication (see below)
Impact Indexed abstracts: DOI: 10.3389/conf.fninf.2014.18.00031 DOI: 10.3389/conf.fnins.2015.91.00004
Start Year 2013
 
Description Neuroimaging Data Model to describe neuroimaging dataset, computational workflow and derived data for publication 
Organisation International Neuroinformatics Coordinating Facility
Country Sweden 
Sector Multiple 
PI Contribution I have been contributing to building the NIDM-Results and NIDM-Workflow models and I have contributed to various conference abstracts and the manuscript with DOI: doi:10.1038/sdata.2016.102
Collaborator Contribution They have been contributing to building the NIDM-Experint, NIDM-Results and NIDM-Workflow models and they have contributed to various conference abstracts and the manuscript with DOI: doi:10.1038/sdata.2016.102
Impact NIDM-Results (http://nidm.nidash.org/specs/nidm-results.html): multi-discplinary (physics, statistics, IT)
Start Year 2014
 
Description On Interview panel for RA position that Peter Watson will be co-supervising 
Organisation University of Cambridge
Department Cambridge Intellectual & Developmental Disabilities Research Group (CIDDRG)
Country United Kingdom 
Sector Academic/University 
PI Contribution I will be co-supervising a RA at Douglas House looking at statistical aspects of a longitudinal study assessing treatment for transcutaneous vagus nerve stimulation as part of a team who have experience in intellectual disabilities. The initial stage is the interview process taking place on 12th August 2016 where as part of a panel I will have an input into the appointment.
Collaborator Contribution The partners are psychiatrists who will enable access of the RA to patients who we hope can benefit from the proposed treatment.
Impact This is just at the interview stage but it is envisaged that we will have publications and the successful applicant will obtain a PhD thesis fro the research.
Start Year 2016
 
Description PTSD grant co-applicant 2013-2016 
Organisation King's College London
Country United Kingdom 
Sector Academic/University 
PI Contribution A pilot randomised clinical trial of trauma-focused cognitive behaviour therapy for posttraumatic stress disorder (PTSD) in young children aged 3-8 years PB-PG-0211-24045 with T. Dalgleish, R. Meiser-Stedman, A. Humphries, A. McKinnon, A. Werner.Seidler, C. Dixon, A, Humphrey, P.Smith, T. Eley and S. Schweizer
Collaborator Contribution Responsible for randomisation of volunteers to groups and for statistical analyses
Impact Currently recruiting volunteers
Start Year 2013
 
Description PTSD grant co-applicant 2013-2016 
Organisation University of Cambridge
Department Autism Research Centre (ARC)
Country United Kingdom 
Sector Academic/University 
PI Contribution A pilot randomised clinical trial of trauma-focused cognitive behaviour therapy for posttraumatic stress disorder (PTSD) in young children aged 3-8 years PB-PG-0211-24045 with T. Dalgleish, R. Meiser-Stedman, A. Humphries, A. McKinnon, A. Werner.Seidler, C. Dixon, A, Humphrey, P.Smith, T. Eley and S. Schweizer
Collaborator Contribution Responsible for randomisation of volunteers to groups and for statistical analyses
Impact Currently recruiting volunteers
Start Year 2013
 
Description PTSD grant co-applicant 2013-2016 
Organisation University of Cambridge
Department Cambridge Clinical Research Centre for Affective Disorders
Country United Kingdom 
Sector Academic/University 
PI Contribution A pilot randomised clinical trial of trauma-focused cognitive behaviour therapy for posttraumatic stress disorder (PTSD) in young children aged 3-8 years PB-PG-0211-24045 with T. Dalgleish, R. Meiser-Stedman, A. Humphries, A. McKinnon, A. Werner.Seidler, C. Dixon, A, Humphrey, P.Smith, T. Eley and S. Schweizer
Collaborator Contribution Responsible for randomisation of volunteers to groups and for statistical analyses
Impact Currently recruiting volunteers
Start Year 2013
 
Description Spatial filtering of EEG/MEG data 
Organisation Aalto University
Country Finland 
Sector Academic/University 
PI Contribution Supervised post-doc Dr. Matti Stenroos (Aalto) during his 2-year stay at MRC CBU. I provided theoretical input and co-wrote manuscripts, the CBU provided data and computing infrastructure.
Collaborator Contribution Dr. Matti Stenroos worked as a self-funded post-doc at the CBU. He provided theoretical tools, ran computer simulations and co-wrote manuscripts.
Impact Peer reviewed papers: Human Brain Mapping (2014): http://www.ncbi.nlm.nih.gov/pubmed/23616402 Neuroimage (2013): http://www.ncbi.nlm.nih.gov/pubmed/23639259 Several conference abstracts and talks The DeFleCT method (HBM 2014) has been implemented in the SPM beamforming toolbox by Dr. Vladimir Litvak: https://code.google.com/p/spm-beamforming-toolbox/source/browse/trunk/private/DeFleCT.m?spec=svn95&r=95
Start Year 2010
 
Description The Brain Imaging Data Structure (BIDS): a standard for organizing and describing outputs of neuroimaging experiments 
Organisation Child Mind Institute
Country United States 
Sector Hospitals 
PI Contribution We describe a simple and easy to adopt way of organizing neuroimaging and behavioral data. BIDS is heavily inspired by the format used internally by OpenfMRI.org. While working on BIDS we consulted many neuroscientists to make sure it covers most common experiments, but at the same time is intuitive and easy to adopt. The specification is intentionally based simple file formats and folder structures to reflect current lab practices and make it accessible to wide range of scientists coming from different backgrounds. Publications: see below
Collaborator Contribution We describe a simple and easy to adopt way of organizing neuroimaging and behavioral data. BIDS is heavily inspired by the format used internally by OpenfMRI.org. While working on BIDS we consulted many neuroscientists to make sure it covers most common experiments, but at the same time is intuitive and easy to adopt. The specification is intentionally based simple file formats and folder structures to reflect current lab practices and make it accessible to wide range of scientists coming from different backgrounds. Publications: see below
Impact Indexed abstract: DOI: 10.3389/conf.fnins.2015.91.00056
Start Year 2015
 
Description The Brain Imaging Data Structure (BIDS): a standard for organizing and describing outputs of neuroimaging experiments 
Organisation Dartmouth College
Department Department of Psychological and Brain Sciences
Country United Kingdom 
Sector Academic/University 
PI Contribution We describe a simple and easy to adopt way of organizing neuroimaging and behavioral data. BIDS is heavily inspired by the format used internally by OpenfMRI.org. While working on BIDS we consulted many neuroscientists to make sure it covers most common experiments, but at the same time is intuitive and easy to adopt. The specification is intentionally based simple file formats and folder structures to reflect current lab practices and make it accessible to wide range of scientists coming from different backgrounds. Publications: see below
Collaborator Contribution We describe a simple and easy to adopt way of organizing neuroimaging and behavioral data. BIDS is heavily inspired by the format used internally by OpenfMRI.org. While working on BIDS we consulted many neuroscientists to make sure it covers most common experiments, but at the same time is intuitive and easy to adopt. The specification is intentionally based simple file formats and folder structures to reflect current lab practices and make it accessible to wide range of scientists coming from different backgrounds. Publications: see below
Impact Indexed abstract: DOI: 10.3389/conf.fnins.2015.91.00056
Start Year 2015
 
Description The Brain Imaging Data Structure (BIDS): a standard for organizing and describing outputs of neuroimaging experiments 
Organisation Massachusetts Institute of Technology
Country United States 
Sector Academic/University 
PI Contribution We describe a simple and easy to adopt way of organizing neuroimaging and behavioral data. BIDS is heavily inspired by the format used internally by OpenfMRI.org. While working on BIDS we consulted many neuroscientists to make sure it covers most common experiments, but at the same time is intuitive and easy to adopt. The specification is intentionally based simple file formats and folder structures to reflect current lab practices and make it accessible to wide range of scientists coming from different backgrounds. Publications: see below
Collaborator Contribution We describe a simple and easy to adopt way of organizing neuroimaging and behavioral data. BIDS is heavily inspired by the format used internally by OpenfMRI.org. While working on BIDS we consulted many neuroscientists to make sure it covers most common experiments, but at the same time is intuitive and easy to adopt. The specification is intentionally based simple file formats and folder structures to reflect current lab practices and make it accessible to wide range of scientists coming from different backgrounds. Publications: see below
Impact Indexed abstract: DOI: 10.3389/conf.fnins.2015.91.00056
Start Year 2015
 
Description The Brain Imaging Data Structure (BIDS): a standard for organizing and describing outputs of neuroimaging experiments 
Organisation McGill University
Country Canada 
Sector Academic/University 
PI Contribution We describe a simple and easy to adopt way of organizing neuroimaging and behavioral data. BIDS is heavily inspired by the format used internally by OpenfMRI.org. While working on BIDS we consulted many neuroscientists to make sure it covers most common experiments, but at the same time is intuitive and easy to adopt. The specification is intentionally based simple file formats and folder structures to reflect current lab practices and make it accessible to wide range of scientists coming from different backgrounds. Publications: see below
Collaborator Contribution We describe a simple and easy to adopt way of organizing neuroimaging and behavioral data. BIDS is heavily inspired by the format used internally by OpenfMRI.org. While working on BIDS we consulted many neuroscientists to make sure it covers most common experiments, but at the same time is intuitive and easy to adopt. The specification is intentionally based simple file formats and folder structures to reflect current lab practices and make it accessible to wide range of scientists coming from different backgrounds. Publications: see below
Impact Indexed abstract: DOI: 10.3389/conf.fnins.2015.91.00056
Start Year 2015
 
Description The Brain Imaging Data Structure (BIDS): a standard for organizing and describing outputs of neuroimaging experiments 
Organisation National Institutes of Health (NIH)
Department National Institute of Mental Health (NIMH)
Country United States 
Sector Public 
PI Contribution We describe a simple and easy to adopt way of organizing neuroimaging and behavioral data. BIDS is heavily inspired by the format used internally by OpenfMRI.org. While working on BIDS we consulted many neuroscientists to make sure it covers most common experiments, but at the same time is intuitive and easy to adopt. The specification is intentionally based simple file formats and folder structures to reflect current lab practices and make it accessible to wide range of scientists coming from different backgrounds. Publications: see below
Collaborator Contribution We describe a simple and easy to adopt way of organizing neuroimaging and behavioral data. BIDS is heavily inspired by the format used internally by OpenfMRI.org. While working on BIDS we consulted many neuroscientists to make sure it covers most common experiments, but at the same time is intuitive and easy to adopt. The specification is intentionally based simple file formats and folder structures to reflect current lab practices and make it accessible to wide range of scientists coming from different backgrounds. Publications: see below
Impact Indexed abstract: DOI: 10.3389/conf.fnins.2015.91.00056
Start Year 2015
 
Description The Brain Imaging Data Structure (BIDS): a standard for organizing and describing outputs of neuroimaging experiments 
Organisation Ohio State University
Department Center for Cognitive and Behavioral Brain Imaging (CCBBI)
Country United States 
Sector Academic/University 
PI Contribution We describe a simple and easy to adopt way of organizing neuroimaging and behavioral data. BIDS is heavily inspired by the format used internally by OpenfMRI.org. While working on BIDS we consulted many neuroscientists to make sure it covers most common experiments, but at the same time is intuitive and easy to adopt. The specification is intentionally based simple file formats and folder structures to reflect current lab practices and make it accessible to wide range of scientists coming from different backgrounds. Publications: see below
Collaborator Contribution We describe a simple and easy to adopt way of organizing neuroimaging and behavioral data. BIDS is heavily inspired by the format used internally by OpenfMRI.org. While working on BIDS we consulted many neuroscientists to make sure it covers most common experiments, but at the same time is intuitive and easy to adopt. The specification is intentionally based simple file formats and folder structures to reflect current lab practices and make it accessible to wide range of scientists coming from different backgrounds. Publications: see below
Impact Indexed abstract: DOI: 10.3389/conf.fnins.2015.91.00056
Start Year 2015
 
Description The Brain Imaging Data Structure (BIDS): a standard for organizing and describing outputs of neuroimaging experiments 
Organisation SRI International (inc)
Country United States 
Sector Charity/Non Profit 
PI Contribution We describe a simple and easy to adopt way of organizing neuroimaging and behavioral data. BIDS is heavily inspired by the format used internally by OpenfMRI.org. While working on BIDS we consulted many neuroscientists to make sure it covers most common experiments, but at the same time is intuitive and easy to adopt. The specification is intentionally based simple file formats and folder structures to reflect current lab practices and make it accessible to wide range of scientists coming from different backgrounds. Publications: see below
Collaborator Contribution We describe a simple and easy to adopt way of organizing neuroimaging and behavioral data. BIDS is heavily inspired by the format used internally by OpenfMRI.org. While working on BIDS we consulted many neuroscientists to make sure it covers most common experiments, but at the same time is intuitive and easy to adopt. The specification is intentionally based simple file formats and folder structures to reflect current lab practices and make it accessible to wide range of scientists coming from different backgrounds. Publications: see below
Impact Indexed abstract: DOI: 10.3389/conf.fnins.2015.91.00056
Start Year 2015
 
Description The Brain Imaging Data Structure (BIDS): a standard for organizing and describing outputs of neuroimaging experiments 
Organisation Squishymedia
Country United States 
Sector Private 
PI Contribution We describe a simple and easy to adopt way of organizing neuroimaging and behavioral data. BIDS is heavily inspired by the format used internally by OpenfMRI.org. While working on BIDS we consulted many neuroscientists to make sure it covers most common experiments, but at the same time is intuitive and easy to adopt. The specification is intentionally based simple file formats and folder structures to reflect current lab practices and make it accessible to wide range of scientists coming from different backgrounds. Publications: see below
Collaborator Contribution We describe a simple and easy to adopt way of organizing neuroimaging and behavioral data. BIDS is heavily inspired by the format used internally by OpenfMRI.org. While working on BIDS we consulted many neuroscientists to make sure it covers most common experiments, but at the same time is intuitive and easy to adopt. The specification is intentionally based simple file formats and folder structures to reflect current lab practices and make it accessible to wide range of scientists coming from different backgrounds. Publications: see below
Impact Indexed abstract: DOI: 10.3389/conf.fnins.2015.91.00056
Start Year 2015
 
Description The Brain Imaging Data Structure (BIDS): a standard for organizing and describing outputs of neuroimaging experiments 
Organisation Stanford University
Department Department of Psychology
Country United States 
Sector Academic/University 
PI Contribution We describe a simple and easy to adopt way of organizing neuroimaging and behavioral data. BIDS is heavily inspired by the format used internally by OpenfMRI.org. While working on BIDS we consulted many neuroscientists to make sure it covers most common experiments, but at the same time is intuitive and easy to adopt. The specification is intentionally based simple file formats and folder structures to reflect current lab practices and make it accessible to wide range of scientists coming from different backgrounds. Publications: see below
Collaborator Contribution We describe a simple and easy to adopt way of organizing neuroimaging and behavioral data. BIDS is heavily inspired by the format used internally by OpenfMRI.org. While working on BIDS we consulted many neuroscientists to make sure it covers most common experiments, but at the same time is intuitive and easy to adopt. The specification is intentionally based simple file formats and folder structures to reflect current lab practices and make it accessible to wide range of scientists coming from different backgrounds. Publications: see below
Impact Indexed abstract: DOI: 10.3389/conf.fnins.2015.91.00056
Start Year 2015
 
Description The Brain Imaging Data Structure (BIDS): a standard for organizing and describing outputs of neuroimaging experiments 
Organisation Stanford University
Country United States 
Sector Academic/University 
PI Contribution We describe a simple and easy to adopt way of organizing neuroimaging and behavioral data. BIDS is heavily inspired by the format used internally by OpenfMRI.org. While working on BIDS we consulted many neuroscientists to make sure it covers most common experiments, but at the same time is intuitive and easy to adopt. The specification is intentionally based simple file formats and folder structures to reflect current lab practices and make it accessible to wide range of scientists coming from different backgrounds. Publications: see below
Collaborator Contribution We describe a simple and easy to adopt way of organizing neuroimaging and behavioral data. BIDS is heavily inspired by the format used internally by OpenfMRI.org. While working on BIDS we consulted many neuroscientists to make sure it covers most common experiments, but at the same time is intuitive and easy to adopt. The specification is intentionally based simple file formats and folder structures to reflect current lab practices and make it accessible to wide range of scientists coming from different backgrounds. Publications: see below
Impact Indexed abstract: DOI: 10.3389/conf.fnins.2015.91.00056
Start Year 2015
 
Description The Brain Imaging Data Structure (BIDS): a standard for organizing and describing outputs of neuroimaging experiments 
Organisation The National Institute for Research in Computer Science and Control (INRIA)
Department Saclay
Country France 
Sector Charity/Non Profit 
PI Contribution We describe a simple and easy to adopt way of organizing neuroimaging and behavioral data. BIDS is heavily inspired by the format used internally by OpenfMRI.org. While working on BIDS we consulted many neuroscientists to make sure it covers most common experiments, but at the same time is intuitive and easy to adopt. The specification is intentionally based simple file formats and folder structures to reflect current lab practices and make it accessible to wide range of scientists coming from different backgrounds. Publications: see below
Collaborator Contribution We describe a simple and easy to adopt way of organizing neuroimaging and behavioral data. BIDS is heavily inspired by the format used internally by OpenfMRI.org. While working on BIDS we consulted many neuroscientists to make sure it covers most common experiments, but at the same time is intuitive and easy to adopt. The specification is intentionally based simple file formats and folder structures to reflect current lab practices and make it accessible to wide range of scientists coming from different backgrounds. Publications: see below
Impact Indexed abstract: DOI: 10.3389/conf.fnins.2015.91.00056
Start Year 2015
 
Description The Brain Imaging Data Structure (BIDS): a standard for organizing and describing outputs of neuroimaging experiments 
Organisation The Otto-von-Guericke University Magdeburg
Department Institute of Psychology
Country Germany 
Sector Academic/University 
PI Contribution We describe a simple and easy to adopt way of organizing neuroimaging and behavioral data. BIDS is heavily inspired by the format used internally by OpenfMRI.org. While working on BIDS we consulted many neuroscientists to make sure it covers most common experiments, but at the same time is intuitive and easy to adopt. The specification is intentionally based simple file formats and folder structures to reflect current lab practices and make it accessible to wide range of scientists coming from different backgrounds. Publications: see below
Collaborator Contribution We describe a simple and easy to adopt way of organizing neuroimaging and behavioral data. BIDS is heavily inspired by the format used internally by OpenfMRI.org. While working on BIDS we consulted many neuroscientists to make sure it covers most common experiments, but at the same time is intuitive and easy to adopt. The specification is intentionally based simple file formats and folder structures to reflect current lab practices and make it accessible to wide range of scientists coming from different backgrounds. Publications: see below
Impact Indexed abstract: DOI: 10.3389/conf.fnins.2015.91.00056
Start Year 2015
 
Description The Brain Imaging Data Structure (BIDS): a standard for organizing and describing outputs of neuroimaging experiments 
Organisation University College London
Country United Kingdom 
Sector Academic/University 
PI Contribution We describe a simple and easy to adopt way of organizing neuroimaging and behavioral data. BIDS is heavily inspired by the format used internally by OpenfMRI.org. While working on BIDS we consulted many neuroscientists to make sure it covers most common experiments, but at the same time is intuitive and easy to adopt. The specification is intentionally based simple file formats and folder structures to reflect current lab practices and make it accessible to wide range of scientists coming from different backgrounds. Publications: see below
Collaborator Contribution We describe a simple and easy to adopt way of organizing neuroimaging and behavioral data. BIDS is heavily inspired by the format used internally by OpenfMRI.org. While working on BIDS we consulted many neuroscientists to make sure it covers most common experiments, but at the same time is intuitive and easy to adopt. The specification is intentionally based simple file formats and folder structures to reflect current lab practices and make it accessible to wide range of scientists coming from different backgrounds. Publications: see below
Impact Indexed abstract: DOI: 10.3389/conf.fnins.2015.91.00056
Start Year 2015
 
Description The Brain Imaging Data Structure (BIDS): a standard for organizing and describing outputs of neuroimaging experiments 
Organisation University of California, Berkeley
Department Helen Wills Neuroscience Institute
Country United States 
Sector Academic/University 
PI Contribution We describe a simple and easy to adopt way of organizing neuroimaging and behavioral data. BIDS is heavily inspired by the format used internally by OpenfMRI.org. While working on BIDS we consulted many neuroscientists to make sure it covers most common experiments, but at the same time is intuitive and easy to adopt. The specification is intentionally based simple file formats and folder structures to reflect current lab practices and make it accessible to wide range of scientists coming from different backgrounds. Publications: see below
Collaborator Contribution We describe a simple and easy to adopt way of organizing neuroimaging and behavioral data. BIDS is heavily inspired by the format used internally by OpenfMRI.org. While working on BIDS we consulted many neuroscientists to make sure it covers most common experiments, but at the same time is intuitive and easy to adopt. The specification is intentionally based simple file formats and folder structures to reflect current lab practices and make it accessible to wide range of scientists coming from different backgrounds. Publications: see below
Impact Indexed abstract: DOI: 10.3389/conf.fnins.2015.91.00056
Start Year 2015
 
Description The Brain Imaging Data Structure (BIDS): a standard for organizing and describing outputs of neuroimaging experiments 
Organisation University of California, Irvine
Department Department of Psychiatry and Human Behavior
Country United States 
Sector Academic/University 
PI Contribution We describe a simple and easy to adopt way of organizing neuroimaging and behavioral data. BIDS is heavily inspired by the format used internally by OpenfMRI.org. While working on BIDS we consulted many neuroscientists to make sure it covers most common experiments, but at the same time is intuitive and easy to adopt. The specification is intentionally based simple file formats and folder structures to reflect current lab practices and make it accessible to wide range of scientists coming from different backgrounds. Publications: see below
Collaborator Contribution We describe a simple and easy to adopt way of organizing neuroimaging and behavioral data. BIDS is heavily inspired by the format used internally by OpenfMRI.org. While working on BIDS we consulted many neuroscientists to make sure it covers most common experiments, but at the same time is intuitive and easy to adopt. The specification is intentionally based simple file formats and folder structures to reflect current lab practices and make it accessible to wide range of scientists coming from different backgrounds. Publications: see below
Impact Indexed abstract: DOI: 10.3389/conf.fnins.2015.91.00056
Start Year 2015
 
Description The Brain Imaging Data Structure (BIDS): a standard for organizing and describing outputs of neuroimaging experiments 
Organisation University of New Mexico
Country United States 
Sector Academic/University 
PI Contribution We describe a simple and easy to adopt way of organizing neuroimaging and behavioral data. BIDS is heavily inspired by the format used internally by OpenfMRI.org. While working on BIDS we consulted many neuroscientists to make sure it covers most common experiments, but at the same time is intuitive and easy to adopt. The specification is intentionally based simple file formats and folder structures to reflect current lab practices and make it accessible to wide range of scientists coming from different backgrounds. Publications: see below
Collaborator Contribution We describe a simple and easy to adopt way of organizing neuroimaging and behavioral data. BIDS is heavily inspired by the format used internally by OpenfMRI.org. While working on BIDS we consulted many neuroscientists to make sure it covers most common experiments, but at the same time is intuitive and easy to adopt. The specification is intentionally based simple file formats and folder structures to reflect current lab practices and make it accessible to wide range of scientists coming from different backgrounds. Publications: see below
Impact Indexed abstract: DOI: 10.3389/conf.fnins.2015.91.00056
Start Year 2015
 
Description The Brain Imaging Data Structure (BIDS): a standard for organizing and describing outputs of neuroimaging experiments 
Organisation University of Oxford
Department Oxford Centre for Functional MRI of the Brain (FMRIB)
Country United Kingdom 
Sector Academic/University 
PI Contribution We describe a simple and easy to adopt way of organizing neuroimaging and behavioral data. BIDS is heavily inspired by the format used internally by OpenfMRI.org. While working on BIDS we consulted many neuroscientists to make sure it covers most common experiments, but at the same time is intuitive and easy to adopt. The specification is intentionally based simple file formats and folder structures to reflect current lab practices and make it accessible to wide range of scientists coming from different backgrounds. Publications: see below
Collaborator Contribution We describe a simple and easy to adopt way of organizing neuroimaging and behavioral data. BIDS is heavily inspired by the format used internally by OpenfMRI.org. While working on BIDS we consulted many neuroscientists to make sure it covers most common experiments, but at the same time is intuitive and easy to adopt. The specification is intentionally based simple file formats and folder structures to reflect current lab practices and make it accessible to wide range of scientists coming from different backgrounds. Publications: see below
Impact Indexed abstract: DOI: 10.3389/conf.fnins.2015.91.00056
Start Year 2015
 
Description The Brain Imaging Data Structure (BIDS): a standard for organizing and describing outputs of neuroimaging experiments 
Organisation University of Warwick
Department Department of Statistics
Country United Kingdom 
Sector Academic/University 
PI Contribution We describe a simple and easy to adopt way of organizing neuroimaging and behavioral data. BIDS is heavily inspired by the format used internally by OpenfMRI.org. While working on BIDS we consulted many neuroscientists to make sure it covers most common experiments, but at the same time is intuitive and easy to adopt. The specification is intentionally based simple file formats and folder structures to reflect current lab practices and make it accessible to wide range of scientists coming from different backgrounds. Publications: see below
Collaborator Contribution We describe a simple and easy to adopt way of organizing neuroimaging and behavioral data. BIDS is heavily inspired by the format used internally by OpenfMRI.org. While working on BIDS we consulted many neuroscientists to make sure it covers most common experiments, but at the same time is intuitive and easy to adopt. The specification is intentionally based simple file formats and folder structures to reflect current lab practices and make it accessible to wide range of scientists coming from different backgrounds. Publications: see below
Impact Indexed abstract: DOI: 10.3389/conf.fnins.2015.91.00056
Start Year 2015
 
Description The Brain Imaging Data Structure (BIDS): a standard for organizing and describing outputs of neuroimaging experiments 
Organisation University of Warwick
Department Warwick Manufacturing Group
Country United Kingdom 
Sector Academic/University 
PI Contribution We describe a simple and easy to adopt way of organizing neuroimaging and behavioral data. BIDS is heavily inspired by the format used internally by OpenfMRI.org. While working on BIDS we consulted many neuroscientists to make sure it covers most common experiments, but at the same time is intuitive and easy to adopt. The specification is intentionally based simple file formats and folder structures to reflect current lab practices and make it accessible to wide range of scientists coming from different backgrounds. Publications: see below
Collaborator Contribution We describe a simple and easy to adopt way of organizing neuroimaging and behavioral data. BIDS is heavily inspired by the format used internally by OpenfMRI.org. While working on BIDS we consulted many neuroscientists to make sure it covers most common experiments, but at the same time is intuitive and easy to adopt. The specification is intentionally based simple file formats and folder structures to reflect current lab practices and make it accessible to wide range of scientists coming from different backgrounds. Publications: see below
Impact Indexed abstract: DOI: 10.3389/conf.fnins.2015.91.00056
Start Year 2015
 
Description The Brain Imaging Data Structure (BIDS): a standard for organizing and describing outputs of neuroimaging experiments 
Organisation University of Washington
Department eScience Institute
Country United States 
Sector Academic/University 
PI Contribution We describe a simple and easy to adopt way of organizing neuroimaging and behavioral data. BIDS is heavily inspired by the format used internally by OpenfMRI.org. While working on BIDS we consulted many neuroscientists to make sure it covers most common experiments, but at the same time is intuitive and easy to adopt. The specification is intentionally based simple file formats and folder structures to reflect current lab practices and make it accessible to wide range of scientists coming from different backgrounds. Publications: see below
Collaborator Contribution We describe a simple and easy to adopt way of organizing neuroimaging and behavioral data. BIDS is heavily inspired by the format used internally by OpenfMRI.org. While working on BIDS we consulted many neuroscientists to make sure it covers most common experiments, but at the same time is intuitive and easy to adopt. The specification is intentionally based simple file formats and folder structures to reflect current lab practices and make it accessible to wide range of scientists coming from different backgrounds. Publications: see below
Impact Indexed abstract: DOI: 10.3389/conf.fnins.2015.91.00056
Start Year 2015
 
Description The EEG/MEG Inverse Problem 
Organisation University of Cambridge
Country United Kingdom 
Sector Academic/University 
PI Contribution We EEG/MEG data for methodological proof-of-concept studies available, and provided practical advice on data analysis. We contributed to manuscript preparation for papers, proceedings etc.
Collaborator Contribution Professors Thanasis Fokas (Cambridge) and Volker Michel (Siegen) provided the mathematical tools, post-doc Dr. Parham Hashemzadeh (Cambridge) and PhD student Sarah Ozlowski (Siegen) are currently working on their implementation.
Impact Paper in Inverse Problems (2009): http://iopscience.iop.org/0266-5611/28/3/035009/pdf/ip12_3_035009.pdf Conference Proceedings (2014): http://lib.amcl.tuc.gr/handle/triton/44
Start Year 2009
 
Description The EEG/MEG Inverse Problem 
Organisation University of Siegen
Country Germany 
Sector Academic/University 
PI Contribution We EEG/MEG data for methodological proof-of-concept studies available, and provided practical advice on data analysis. We contributed to manuscript preparation for papers, proceedings etc.
Collaborator Contribution Professors Thanasis Fokas (Cambridge) and Volker Michel (Siegen) provided the mathematical tools, post-doc Dr. Parham Hashemzadeh (Cambridge) and PhD student Sarah Ozlowski (Siegen) are currently working on their implementation.
Impact Paper in Inverse Problems (2009): http://iopscience.iop.org/0266-5611/28/3/035009/pdf/ip12_3_035009.pdf Conference Proceedings (2014): http://lib.amcl.tuc.gr/handle/triton/44
Start Year 2009
 
Title Method for determination of metrics and fibers in Diffusion Kurtosis Imaging 
Description Development of a novel algorithm to extract scalar metrics and fibre orientation distributions from Diffusion Kurtosis data. The patent submission has yet to be approved. 
IP Reference  
Protection Copyrighted (e.g. software)
Year Protection Granted
Licensed No
Impact A publication is currently under review with Neuroimage. A toolbox making the algorithm available to the wider DKI community is in preparation.
 
Title Single shot partial dual echo (SPADE) EPI 
Description An efficient acquisition scheme for whole brain fMRI PATENT APPLICATION CEASED 2009 
IP Reference GB0807027.8 
Protection Patent application published
Year Protection Granted 2008
Licensed Yes
Impact This has allowed imaging studies to be performed with reduced inhomogeneity artifacts in the areas that are normally affected conbined with high signal-to-noise ratio in other parts of the brain.
 
Description 19th Annual Meeting of the Organization for Human Brain Mapping, 2013, Seattle, USA 
Form Of Engagement Activity A talk or presentation
Part Of Official Scheme? Yes
Geographic Reach International
Primary Audience Professional Practitioners
Results and Impact Talk:
Auer T, Schweizer R, Frahm J. The role of the anterior midcingulate cortex in neurofeedback training

Posters:
Schweizer R, Auer T, Frahm J. White matter changes associated with a fMRI neurofeedback training
Dewiputri WI, Schweizer R, Auer T, Frahm J. Uncoupling task and feedback processing during cognitive fMRI neurofeedback training

Broadcast work to a larger audience which has helped inform future direction in research
Year(s) Of Engagement Activity 2013
 
Description 20th Annual Meeting of the Organization for Human Brain Mapping, 2014, Hamburg, Germany 
Form Of Engagement Activity A talk or presentation
Part Of Official Scheme? Yes
Geographic Reach International
Primary Audience Professional Practitioners
Results and Impact Posters:
Auer T, Schweizer R, Frahm J. The influence of cognitive components in a fMRI neurofeedback training targeting the motor system
Auer T, Vicente-Grabovetsky A, Mitchell DJ, Wild C, Linke AC, Peelle JE, Cusack R. Automatic analysis (aa) pipelines: new features for large, multimodal datasets
Dewiputri WI, Schweizer R, Auer T, Frahm J. Uncoupling task and feedback-processing is promising in fMRI neurofeedback of a cognitive brain area
Hauk O, Auer T, Pulvermüller F. Task modulation of LIFG activation in written nonword but not word processing

Broadcast work to a larger audience which has helped inform future direction in research
Year(s) Of Engagement Activity 2014
 
Description Action Editor for Language, Cognition and Neuroscience, Olaf Hauk 
Form Of Engagement Activity A magazine, newsletter or online publication
Part Of Official Scheme? No
Geographic Reach International
Primary Audience Professional Practitioners
Results and Impact I am on the Editorial Board of the peer-reviewed journal Language, Cognition and Neuroscience:
http://www.tandfonline.com/action/journalInformation?show=editorialBoard&journalCode=plcp21#.VtCISuaN07E
In this function, I edit and review manuscripts, organise special issues and write commentaries.
Year(s) Of Engagement Activity 2013,2014,2015,2016
URL http://www.tandfonline.com/action/journalInformation?show=editorialBoard&journalCode=plcp21#.VtCISua...
 
Description Automatic analysis (aa): efficient and transparent multimodal neuroimaging workflows 
Form Of Engagement Activity A talk or presentation
Part Of Official Scheme? No
Geographic Reach International
Primary Audience Professional Practitioners
Results and Impact The annual INCF Congress provides a meeting place for researchers in the emerging field of neuroinformatics. Particpiants represent all fields related to neuroinformatics, including data- and knowledge-bases of the nervous system from molecular to behavioral levels; tools for the acquisition, analysis, and visualization of nervous system data; and theoretical, computational, and simulation environments for modeling the brain. This meeting is especially useful for anyone who is developing neuroscience tools and methods; working on better ways to handle neuroscience data; or looking for cross-disciplinary collaborations.
Year(s) Of Engagement Activity 2016
URL http://neuroinformatics2016.org/
 
Description Cambridge Methods Day 
Form Of Engagement Activity Participation in an activity, workshop or similar
Part Of Official Scheme? No
Geographic Reach Regional
Primary Audience Other audiences
Results and Impact Cambridge Methods Day provides a day of lectures from scientists around Cambridge on methods development activities in cognitive neuroscience. It was intended to inspire novel lines of research, particularly for PhD students and post-docs, and to create new collaborations.
Year(s) Of Engagement Activity 2016,2017
URL http://imaging.mrc-cbu.cam.ac.uk/methods/MethodsDaySchedule
 
Description Co-author (Peter Watson) on poster entitled 'Measuring autistic traits in the general population: a systematic review of the Autism-Spectrum Quotient (AQ) in a nonclinical population sample of 6900 typical adult males and females' given at IMFAR 2015. 
Form Of Engagement Activity A talk or presentation
Part Of Official Scheme? No
Type Of Presentation poster presentation
Geographic Reach International
Primary Audience Professional Practitioners
Results and Impact My activity resulting in co-authorship on this poster (Ruzich, E., Allison, C., Smith, P., Watson, P., Auyeung, B., Ring, H. and Baron-Cohen, S.) was providing advice on weightings of means for the meta-analysis. The poster was then presented by Emily Ruzich (first author) at the 2015 IMFAR (International Meeting for Autism Research) in Salt Lake City in May 2015.

Increases interest in autism research by the psychiatry groups at Cambridge University including the Intellectual and Developmental Disabilities Research Group and Autism Research Centre, both at the Department of Psychiatry, University of Cambridge.
Year(s) Of Engagement Activity 2015
URL http://www.autism-insar.org/imfar-annual-meeting/imfar-2015
 
Description Educational Talk at MEG-UK 2014 by Olaf Hauk 
Form Of Engagement Activity A talk or presentation
Part Of Official Scheme? No
Geographic Reach National
Primary Audience Other academic audiences (collaborators, peers etc.)
Results and Impact Informed beginners of EEG/MEG analysis about EEG/MEG analysis.

The talk sparked questions and discussions.
Year(s) Of Engagement Activity 2014
URL http://www.nottingham.ac.uk/conference/fac-sci/physics/meg-uk-conference/index.aspx
 
Description How cognitive science research on imagery can help women traumatised by an emergency cesarean section. 
Form Of Engagement Activity A talk or presentation
Part Of Official Scheme? No
Geographic Reach National
Primary Audience Professional Practitioners
Results and Impact Poster given on 24th April 2017 at the Royal Society meeting in London (Of mice and mental health: facilitating dialogue between basic and clinical neuroscientists, 24th -25th April 2017).
Year(s) Of Engagement Activity 2017
URL https://royalsociety.org/science-events-and-lectures/2017/04/mental-health/
 
Description Introduction to Neuroimaging Methods Workshops 
Form Of Engagement Activity Participation in an activity, workshop or similar
Part Of Official Scheme? No
Geographic Reach Regional
Primary Audience Postgraduate students
Results and Impact The workshop series "Introduction to Neuroimaging Methods" at the Cognition and Brain Sciences Unit provides junior researchers with novel research methods, a better understanding of neuroimaging analysis methods, and transferrable skills. We collect regular feedback, which has been highly positive.
Year(s) Of Engagement Activity 2015,2016,2017,2018
URL http://imaging.mrc-cbu.cam.ac.uk/methods/IntroductionNeuroimagingLectures
 
Description Introduction to Scientific Computing and Matlab workshop series 
Form Of Engagement Activity Participation in an activity, workshop or similar
Part Of Official Scheme? No
Geographic Reach Regional
Primary Audience Postgraduate students
Results and Impact The workshop series "Introduction to Scientific Computing and Matlab" (http://imaging.mrc-cbu.cam.ac.uk/methods/MatlabLecturesSchedule) provides junior researchers with fundamentals of Matlab programming and scientific computing (e.g. Linux). It helps junior researchers to quickly develop the necessary skills for neuroimaging data analysis.
Year(s) Of Engagement Activity 2012,2013,2014,2015,2016
URL http://imaging.mrc-cbu.cam.ac.uk/methods/MatlabLecturesSchedule
 
Description Introduction to Signal Analysis in Matlab workshop series 
Form Of Engagement Activity Participation in an activity, workshop or similar
Part Of Official Scheme? No
Geographic Reach Local
Primary Audience Postgraduate students
Results and Impact The workshop series "Introduction to Signal Analysis in Matlab" at the Cognition and Brain Sciences Unit (http://imaging.mrc-cbu.cam.ac.uk/methods/SignalAnalysisMatlabSchedule) teaches the fundamentals of signal analysis relevant for neuroimaging using the Matlab programming language. It provides junior researchers with novel data analysis methods and will make them more efficient.
Year(s) Of Engagement Activity 2015,2016,2017,2018
URL http://imaging.mrc-cbu.cam.ac.uk/methods/SignalAnalysisMatlabSchedule
 
Description Invited Talk at Best practice in EEG and TMS Research workshop, University of Canterbury, by Olaf Hauk 
Form Of Engagement Activity A talk or presentation
Part Of Official Scheme? No
Geographic Reach International
Primary Audience Other academic audiences (collaborators, peers etc.)
Results and Impact The talk sparked questions and discussions.
Year(s) Of Engagement Activity 2014
URL http://www.kent.ac.uk/psychology/research/cognitive/eeg-tms-workshop.html
 
Description Invited talk at BACN conference, York, October 2014, by Olaf Hauk 
Form Of Engagement Activity A talk or presentation
Part Of Official Scheme? No
Geographic Reach International
Primary Audience Other academic audiences (collaborators, peers etc.)
Results and Impact Sparked discussion after the talk.
Year(s) Of Engagement Activity 2014
URL http://www.bacn.co.uk/2014_conference.html
 
Description Invited talk at Matlab Workshop for Neuroimagers, University of Birmingham 
Form Of Engagement Activity Participation in an activity, workshop or similar
Part Of Official Scheme? No
Geographic Reach National
Primary Audience Undergraduate students
Results and Impact I introduced and demonstrated Automatic Analysis (aa) for analysing neuroimaging data using MATLAB.
Year(s) Of Engagement Activity 2014
 
Description Invited talk at the opening ceremony of a primary school laboratory for natural sciences 
Form Of Engagement Activity A talk or presentation
Part Of Official Scheme? No
Geographic Reach Regional
Primary Audience Schools
Results and Impact Over 100 (primary school pupils, teachers) attended my talk about my reasearch field and results.
Year(s) Of Engagement Activity 2014
 
Description Invited talk: Benedictine Free University by Tibor Auer 
Form Of Engagement Activity A talk or presentation
Part Of Official Scheme? Yes
Geographic Reach Local
Primary Audience Schools
Results and Impact Over 200 (high school pupils, teachers, townsfolk) attended my talk about my reasearch field and results.

The talk stimulated discussions with teachers and questions from student about career path, required studies,.
Year(s) Of Engagement Activity 2014
URL http://www.czuczor.hu/esemenyek/ablak-az-agyra
 
Description Journal refereeing by Peter Watson 
Form Of Engagement Activity A magazine, newsletter or online publication
Part Of Official Scheme? No
Geographic Reach International
Primary Audience Professional Practitioners
Results and Impact I have been an on-going statistical referee for submissions to BMJ Open but also Journal of Intellectual Disability Research and Behavior Research Methods since 2007. In 2015 I also provided a job reference and reviewed a Routledge book.

Improved use and description of statistical methods in psychological and medical research.
Year(s) Of Engagement Activity 2007,2008,2009,2010,2011
 
Description Journal refereeing by Tibor Auer 
Form Of Engagement Activity A magazine, newsletter or online publication
Part Of Official Scheme? No
Geographic Reach International
Primary Audience Professional Practitioners
Results and Impact I have been a scientific referee for submissions to
European Radiology since 2010
Journal of Neuroscience Methods in 2013 and 2014
NeuroImage in 2014
Brain and Language in 2014
PlosOne since 2014
Circulation in 2015
European Journal of Neuroscience in 2015

Improved scienitif practice (espacially methods-realted) in psychological and medical research.
Year(s) Of Engagement Activity 2010,2011,2012,2013,2015
 
Description MEG-UK poster "A Survey On Methods Skills In Cognitive Neuroscience" 
Form Of Engagement Activity A talk or presentation
Part Of Official Scheme? No
Geographic Reach National
Primary Audience Professional Practitioners
Results and Impact Poster on a survey on methods skill in cognitive neuroscience that will shape the way we and others will provide neuroimaging methods training in the future.
Year(s) Of Engagement Activity 2017
 
Description MSc Neuroimaging Workshop for the Department of Neuroimaging, King's College London Institute of Psychiatry 
Form Of Engagement Activity A formal working group, expert panel or dialogue
Part Of Official Scheme? No
Geographic Reach Regional
Primary Audience Undergraduate students
Results and Impact EEG/MEG training workshop for neuroimaging master's students of King's College London. Students asked questions and discussed ideas after the lectures and lab tour. We received very positive feedback after each event, and they always ask to do it again next year.

For several years they have asked us to do it again.
Year(s) Of Engagement Activity 2012,2013,2014,2015,2016
 
Description Member of Alzheimer's Research UK Clinical Trials Advisory Panel (ARUK (CTAP) 
Form Of Engagement Activity A formal working group, expert panel or dialogue
Part Of Official Scheme? Yes
Geographic Reach International
Primary Audience Professional Practitioners
Results and Impact Funding for new areas involving Alzheimer's Research.

Dissemination of results and improved quality of life for Alzheimer's sufferers and their carers.
Year(s) Of Engagement Activity 2015,2016,2017,2018
 
Description Newspaper Interview of Tibor Auer 
Form Of Engagement Activity A press release, press conference or response to a media enquiry/interview
Part Of Official Scheme? No
Geographic Reach National
Primary Audience Media (as a channel to the public)
Results and Impact Tibor Auer gave an interview to a regional magazine about my career path and the field I am working on.

It sparked further enquiries for talks to primary and high school students.
Year(s) Of Engagement Activity 2014
URL https://www.facebook.com/media/set/?set=a.554413778038826.1073741845.495951857218352&type=1
 
Description Oral presentation at 15th biannual congress of the Swiss Psychological Society (Peter Watson is a co-author) 
Form Of Engagement Activity A talk or presentation
Part Of Official Scheme? No
Geographic Reach International
Primary Audience Professional Practitioners
Results and Impact Co-author presented results from our 2017 paper in a presentation entitled "Development of an early intervention to prevent postnatal posttraumatic stress symptoms" which was accepted for oral presentation at the 15th biannual congress of the Swiss Psychological Society, September 4 and 5, 2017 in Lausanne.
Year(s) Of Engagement Activity 2017
URL https://www.ssp-sgp2017.ch/cms/home
 
Description Oral presentation at conference (Peter Watson is a co-author) 
Form Of Engagement Activity A talk or presentation
Part Of Official Scheme? No
Geographic Reach International
Primary Audience Professional Practitioners
Results and Impact The talk is entitled 'Consequences of posttraumatic stress disorder after childbirth and treatment developments' and was accepted for the Society of Reproductive and Infant Psychology conference in York in September 2017 (Peter Watson is a listed co-author).
Year(s) Of Engagement Activity 2006,2017
URL http://www.srip.ac.uk/conference.php
 
Description Organiser of Cambridge Statistics Discussion Group talks 
Form Of Engagement Activity A talk or presentation
Part Of Official Scheme? No
Geographic Reach Regional
Primary Audience Professional Practitioners
Results and Impact The six talks on various (mainly medical) aspects of applications of statistical methods are held in each academic year in Cambridge and spark discussions and questions. Talk slides are placed on-line with audio .mp3 files, where appropriate, of the talk and discussion.

Contacts are made between practitioners and people interested in their work.
Year(s) Of Engagement Activity Pre-2006,2006,2007,2008,
URL http://www.mrc-cbu.cam.ac.uk/people/peter.watson/csdg
 
Description Organiser of SPSS Users conference 
Form Of Engagement Activity Participation in an activity, workshop or similar
Part Of Official Scheme? No
Type Of Presentation workshop facilitator
Geographic Reach International
Primary Audience Professional Practitioners
Results and Impact Talks and courses prompted questions and discussion.

As a result of previous workshops this produced contacts who were able to come and present a one-day R course at CBSU. People also use the methods they have learnt to improve the efficiency of programs they use in their own work e.g. by using macros.
Year(s) Of Engagement Activity Pre-2006,2006,2007,2008,
URL http://www.spssusers.co.uk/
 
Description Peter Watson co-authored poster presentation at conference May 2016 
Form Of Engagement Activity A talk or presentation
Part Of Official Scheme? No
Geographic Reach International
Primary Audience Professional Practitioners
Results and Impact A co-authored poster entitled 'A Simple Cognitive-Task Intervention to Reduce Intrusive Memories after a Traumatic Event: Feasibility and Patient Experience from a Randomised Controlled Trial in an Emergency Department' was accepted for presentation at the Association for Psychological Science convention on 26th-29th May 2016.
Year(s) Of Engagement Activity 2016
URL http://www.psychologicalscience.org/index.php/convention/archive
 
Description Poster co-author on 'Comparing MEG with MRI for Early Detection of Alzheimer's Disease' at HBM 2015 conference in Hawaii. 
Form Of Engagement Activity A talk or presentation
Part Of Official Scheme? No
Geographic Reach International
Primary Audience Professional Practitioners
Results and Impact Computed and gave advice on computation of error rates for the poster entitled Comparing MEG with MRI for Early Detection of Alzheimer's Disease by Blanco, C., Greve, A., Brindley, L., Cooper, E., Taylor, J., Olichney, J., Watson, P. , Nestor, P., Henson, R. at the Human Brain Mapping 2015 conference. The first author, Cristina Blanco-Duque, presented the poster at the 2015 conference in June 2015.

Further collaborations, planning of future research and networking.
Year(s) Of Engagement Activity 2015
URL http://ohbm.loni.usc.edu/wp-content/uploads/2015/04/Posters-for-web.pdf
 
Description Poster given at Royal Society meeting in London (Peter Watson is a co-author) 
Form Of Engagement Activity A talk or presentation
Part Of Official Scheme? No
Geographic Reach International
Primary Audience Professional Practitioners
Results and Impact (with A. Horsch, Y. Vial, C. Favrod, M. M. Harari, S. E. Blackwell, L. Iyadurai, M. B. Bonsall and E. A. Holmes) How cognitive science research on imagery can help women traumatised by an emergency caesarean section. Poster given on 24th April 2017 at the Royal Society meeting in London (Of mice and mental health: facilitating dialogue between basic and clinical neuroscientists, 24th -25th April 2017).
Year(s) Of Engagement Activity 2017
URL https://royalsociety.org/science-events-and-lectures/2017/04/mental-health/
 
Description Poster presentation 
Form Of Engagement Activity A talk or presentation
Part Of Official Scheme? No
Geographic Reach National
Primary Audience Professional Practitioners
Results and Impact Carroll, C., Clare, I.C.H., Watson, P., Spoudeas, H.A., Walker, D., Hawkins, M.M., Holland, A.J. & Ring, H.A. (2013). IQ Correlates of early childhood Posterior Fossa Tumours. Poster & Oral presentation at British Neuropsychiatry Association AGM, London.

Co-author on the poster given by Cliodhna in 2013.

Broadcast work to a larger audience which has helped inform future direction in research
Year(s) Of Engagement Activity 2013
 
Description Poster presentation of co-authored paper (Peter Watson) in June 2016 
Form Of Engagement Activity Participation in an activity, workshop or similar
Part Of Official Scheme? No
Geographic Reach International
Primary Audience Professional Practitioners
Results and Impact David Walker to present an abstract at the 17th International Symposium on Pediatric Neuro-Oncology (ISPNO 2016) being held in Liverpool between 12-15th June 2016 on 'Long-term cognitive outcome in adult survivors of an early childhood posterior fossa brain tumour' co-authored by Carroll, C., Wagner, A., Watson, P., Spoudeas, H., Hawkins, M., Walker D., (Presenting), Clare, I., Holland, T. and Ring, H.
Year(s) Of Engagement Activity 2016
URL http://www.ispno2016.com
 
Description Posters at Neurobiology of Language Conference, London 
Form Of Engagement Activity A talk or presentation
Part Of Official Scheme? No
Geographic Reach International
Primary Audience Professional Practitioners
Results and Impact Two posters as first author, one senior-authored (by PhD student Rezvan Farahibozorg), one co-authored (Lucy McGregor).
Year(s) Of Engagement Activity 2016
 
Description Presentation at British Association for Behavioural and Cognitive Psychotherapies 2017 conference (Peter Watson is a co-author) 
Form Of Engagement Activity A talk or presentation
Part Of Official Scheme? No
Geographic Reach International
Primary Audience Professional Practitioners
Results and Impact The presentation entitled 'Development of an early intervention to prevent posttraumatic stress symptoms after traumatic childbirth' was based upon the paper which Peter Watson co-authored. This talk was presented at the 2017 British Association for Behavioural and Cognitive Psychotherapies (BABCP) conference in Manchester on 25th-28th July during a symposium on "Trauma and intrusive memories: emerging approaches to prevention and early intervention".
Year(s) Of Engagement Activity 2017
URL http://www.babcp.com/Training/Conferences.aspx
 
Description Quantum Technology Workshop for Health Applications - MEG 
Form Of Engagement Activity Participation in an activity, workshop or similar
Part Of Official Scheme? No
Geographic Reach National
Primary Audience Policymakers/politicians
Results and Impact I was invited to attend a one-day workshop "Quantum Technology Workshop for Health Applications - MEG" organised by the Knowledge Transfer Network as part of the Blackett Review for Quantum Technologies, Nottingham,1.9.2016. We discussed the impact of new MEG hardware (high-temperature sensors) on future applications of MEG methodology, e.g. for medial diagnosis, and its economic implications (e.g. future market for MEG systems).
Year(s) Of Engagement Activity 2016
URL https://connect.innovateuk.org/web/quantum-technology/events-view/-/events/33304741?_8_redirect=http...
 
Description Royal Society Summer Science Festival 
Form Of Engagement Activity Participation in an activity, workshop or similar
Part Of Official Scheme? No
Geographic Reach National
Primary Audience Public/other audiences
Results and Impact Many people watched our video 'Surfing the Brain Superhighways': www.youtube.com/watch?v=tNB0sM7JJqg and talked to the student who created it.

New collaborations with other research laboratorie
Year(s) Of Engagement Activity 2010
 
Description SPSS COURSE IN YORK given by Peter Watson 
Form Of Engagement Activity A talk or presentation
Part Of Official Scheme? No
Geographic Reach International
Primary Audience Professional Practitioners
Results and Impact Teaching and sharing computer programming using SPSS in the form of macros to run commonly used syntax more efficiently and understandably.

One of the attenders said she would be using the macros that she had learnt about to run syntax files in her place of work (University of Central Lancashire).
Year(s) Of Engagement Activity 2015
URL http://www.spssusers.co.uk/Events/2015/confprog.html
 
Description SPSS Courses organiser (excluding annual conference), Peter Watson 
Form Of Engagement Activity Participation in an activity, workshop or similar
Part Of Official Scheme? No
Type Of Presentation workshop facilitator
Geographic Reach National
Primary Audience Professional Practitioners
Results and Impact Over 50 mainly University but also staff from outside academia such as, for example, IPSOS-MORI and Yorkshire Water attend a series of courses at various venues in addition to the annual York one-day conference. These courses I organise in my role as chair of the SPSS users group (ASSESS). These one day courses use SPSS. I gave a SPSS macros one day course from 2006-2010 at UK universities (and revived this for the York conference in 2015).

Increases understanding and better use of statistical methods and understanding of using SPSS and R statistical software. I was invited to and wrote a book chapter as a result of a contact I made through the group and got an acknowledgement in a paper 2011 by Len Usvyat and collagues at the Renal Rsearch Institute in New York for a talk I gave in my pre-organising days. We obtain valuable learning materials for helping staff and students at the unit from speakers at these meetings.
Year(s) Of Engagement Activity 2006,2007,2008,2009,2010
URL http://www.spssusers.co.uk/
 
Description SPSS Exploratory Data Analysis Course in 2016 organised by Peter Watson 
Form Of Engagement Activity Participation in an activity, workshop or similar
Part Of Official Scheme? No
Geographic Reach National
Primary Audience Professional Practitioners
Results and Impact I organised a one-day course given by Andy Field of University of Sussex using SPSS to facilitate understanding of the testing, evaluation and handling of distributional assumptions connected with analysis of groups using means and variances by means of sets of techniques which comprise exploratory data analysis.
Year(s) Of Engagement Activity 2016
URL http://www.spssusers.co.uk/Events/2016/workshopannounce.html
 
Description SPSS one day course for complete beginners given in Cambridge on 26th June 2018 organiser and co-tutor 
Form Of Engagement Activity Participation in an activity, workshop or similar
Part Of Official Scheme? No
Geographic Reach National
Primary Audience Postgraduate students
Results and Impact The course is aimed at anyone new to the software who wishes to see what it an do in a real world context.
Year(s) Of Engagement Activity 2018
URL http://www.spssusers.co.uk/
 
Description SPSS one day course for complete beginners in Manchester on 10th July 2018 organiser and co-tutor 
Form Of Engagement Activity Participation in an activity, workshop or similar
Part Of Official Scheme? No
Geographic Reach National
Primary Audience Postgraduate students
Results and Impact Upto 15 delegates attending one day SPSS course for complete beginners at Manchester. This course is aimed at introducing social scientists to the software.
Year(s) Of Engagement Activity 2018
URL http://www.spssusers.co.uk/
 
Description School visit: King's College London 
Form Of Engagement Activity Participation in an open day or visit at my research institution
Part Of Official Scheme? No
Geographic Reach National
Primary Audience Schools
Results and Impact I have demonstrated the mock scanner to over 20 students while explaining them the basics and application of MRI.
Year(s) Of Engagement Activity 2015
 
Description School visit: Leys school 
Form Of Engagement Activity Participation in an open day or visit at my research institution
Part Of Official Scheme? No
Geographic Reach Local
Primary Audience Schools
Results and Impact I have talked about basics and application of fMRI to over 20 students, and showed them the mock scanner. Feedback was very positive.
Year(s) Of Engagement Activity 2015,2016
 
Description SfN poster "A Survey On Methods Skills In Cognitive Neuroscience" 
Form Of Engagement Activity A talk or presentation
Part Of Official Scheme? No
Geographic Reach International
Primary Audience Professional Practitioners
Results and Impact Poster presentation on ongoing study on methods skills in cognitive neuroscience. This will influence our future neuroimaging methods training programme, and lead to a publication.
Year(s) Of Engagement Activity 2017
 
Description SfN poster "Extracting Single-Trial Time Courses From EEG/MEG Data Using Spatial Filtering" 
Form Of Engagement Activity A talk or presentation
Part Of Official Scheme? No
Geographic Reach International
Primary Audience Professional Practitioners
Results and Impact Scientific poster presentation on on-going research project, discussion with scientific experts.
Year(s) Of Engagement Activity 2017
 
Description Society of Applied Neuroscience (SAN) Meeting, 2014, Utrecht, The Netherlands 
Form Of Engagement Activity A talk or presentation
Part Of Official Scheme? Yes
Geographic Reach International
Primary Audience Professional Practitioners
Results and Impact Talk:
Auer T. Neural circuits underlying the neurofeedback training

Broadcast work to a larger audience which has helped inform future direction in research
Year(s) Of Engagement Activity 2014
 
Description Statistics talks at CBSU 
Form Of Engagement Activity A talk or presentation
Part Of Official Scheme? No
Geographic Reach Local
Primary Audience Postgraduate students
Results and Impact The audience mainly of Cognitive Psychologist PhDs from CBSU and the University ask questions during the talks concerning best ways of analysing their clinical data.

E-mail from attender asking for further information on post-hoc testing to explain an interaction on his genetics data.
Year(s) Of Engagement Activity 2015,2016,2017
URL http://imaging.mrc-cbu.cam.ac.uk/statswiki/StatsCourse2015
 
Description Support and participation for "MEG and me" media event 
Form Of Engagement Activity A press release, press conference or response to a media enquiry/interview
Part Of Official Scheme? No
Geographic Reach Regional
Primary Audience Public/other audiences
Results and Impact The "MEG and me" was a public engagement event funded by a grant to Drs Tim Rittman and Saber Sami (University of Cambridge), which included the planning, setting up and running of an MEG experiment with members of the general public. It also included a filming session, which produced a movie that was for example shown at the Science Festival. I provided support and advice for the project and was interviewed for the movie.
Year(s) Of Engagement Activity 2015
URL https://vimeo.com/user34508878
 
Description Survey on Methods Skills in Cognitive Neuroscience 
Form Of Engagement Activity Engagement focused website, blog or social media channel
Part Of Official Scheme? No
Geographic Reach International
Primary Audience Postgraduate students
Results and Impact Online survey on methods skills in cognitive neuroscience. The survey consisted of 18 analysis-methods-related questions relevant to cognitive neuroscience, plus questions on demographics etc. It was distributed mostly via software mailing lists. Over 500 participants have responded so far. The results will influence the way we design future skills-oriented training in our institution.
Year(s) Of Engagement Activity 2015,2016,2017
URL https://www.surveymonkey.com/r/3JL2CZX?sm=0LHJUgVc5leXXTTT1QHF2w%3d%3d
 
Description Talk at RefNet Round Table Discussion, Aberdeen 
Form Of Engagement Activity A talk or presentation
Part Of Official Scheme? No
Geographic Reach International
Primary Audience Other audiences
Results and Impact Invited talk on neuroscience of semantic word processing at RefNet Round Table Discussion, University of Aberdeen, January 2016
Year(s) Of Engagement Activity 2016
URL http://www.matt.qa/refnet/
 
Description Talk at the Neuroscience Centre of the University of Geneva, Olaf Hauk 
Form Of Engagement Activity A talk or presentation
Part Of Official Scheme? No
Geographic Reach International
Primary Audience Professional Practitioners
Results and Impact Invited 45-minute talk "Finding meaning in the brain: EEG/MEG evidence for early and flexible
lexico-semantic word processing", Olaf Hauk. Lab visit that resulted in exchange of ideas for example with respect to analysis methods.
Year(s) Of Engagement Activity 2015
 
Description Workshop series: Introduction to Neuroimaging Methods 
Form Of Engagement Activity Participation in an activity, workshop or similar
Part Of Official Scheme? No
Geographic Reach Local
Primary Audience Postgraduate students
Results and Impact We offer a series of hands-on workshops and lectures on important topics related to neuroimaging data analysis. A previous schedule can be found here:
http://imaging.mrc-cbu.cam.ac.uk/methods/IntroductionNeuroimagingLectures
Students and post-docs will be able to do their research more independently and creatively as a result of attending these workshops. We have attracted a number of students and post-docs from several institutes within Cambridge.
This will be part of the official PhD training programme at the CBU from 2015.


We obtain formal feedback from attendees, which so far has been very positive. We attracted a number of students and post-docs from outside the CBU, who clearly made an effort to attend (attendance is voluntary).
Year(s) Of Engagement Activity 2013,2014
URL http://imaging.mrc-cbu.cam.ac.uk/imaging/CbuImaging
 
Description •Invited talk in "Mind-Brain Lecture" at Free University and Humboldt University Berlin 
Form Of Engagement Activity A talk or presentation
Part Of Official Scheme? No
Geographic Reach International
Primary Audience Other audiences
Results and Impact Invited talk "Can I have a quick word" on neuroscience of language in "Mind-Brain Lecture" at Free University and Humboldt University Berlin, 3 May 2016
Year(s) Of Engagement Activity 2016
URL http://www.mind-and-brain.de/events/detail/?tx_mbevents_pi1%5BbackPid%5D=37&tx_mbevents_pi1%5Bid%5D=...