MRC TS Award: Dynamic Neuromodulation
Lead Research Organisation:
Imperial College London
Department Name: Bioengineering
Abstract
Brief neural rhythms, coordinated across multiple brain regions, control our everyday actions from reaching for a glass of water to making decisions. Dysfunction of this fundamental neural property has been linked to common conditions such as Parkinson's disease, Essential Tremor, and Dystonia, which impact more than one million people across the UK. Understanding the role of neural coordination in health and disease is key for the development of effective therapies.
My research programme uses brain stimulation to establish the role of neural coordination in Parkinson's disease and Essential Tremor.
During my Career Development Award, I worked towards:
Theme 1: Establishing how the current state of a disease circuit influences the most effective stimulation strategy.
Theme 2: Determining how selectively modulating neural coordination impacts goal-directed behaviour.
Theme 3: Establishing the mechanisms through which our brains naturally control neural coordination.
Theme 4: Determining whether it is possible to regulate neural coordination with brain stimulation by mimicking mechanisms through which our brains naturally control coordination.
We have made good progress with Themes 1-3 and (a) implemented experimental tasks to better understand the link between symptom severity and movement, (b) built realistic computational models that capture the mechanisms underlying Essential Tremor and Parkinson's disease and (c) developed invasive and non-invasive stimulation strategies to reduce tremor and influence goal-directed behaviour.
Due to several mitigating circumstances, we are still at the beginning stages of Theme 4 and require additional time. The Transition Support Award will be used to support this important body of work and consolidate my intermediate fellowship by supporting a key member of my team and protecting my research time.
My research programme uses brain stimulation to establish the role of neural coordination in Parkinson's disease and Essential Tremor.
During my Career Development Award, I worked towards:
Theme 1: Establishing how the current state of a disease circuit influences the most effective stimulation strategy.
Theme 2: Determining how selectively modulating neural coordination impacts goal-directed behaviour.
Theme 3: Establishing the mechanisms through which our brains naturally control neural coordination.
Theme 4: Determining whether it is possible to regulate neural coordination with brain stimulation by mimicking mechanisms through which our brains naturally control coordination.
We have made good progress with Themes 1-3 and (a) implemented experimental tasks to better understand the link between symptom severity and movement, (b) built realistic computational models that capture the mechanisms underlying Essential Tremor and Parkinson's disease and (c) developed invasive and non-invasive stimulation strategies to reduce tremor and influence goal-directed behaviour.
Due to several mitigating circumstances, we are still at the beginning stages of Theme 4 and require additional time. The Transition Support Award will be used to support this important body of work and consolidate my intermediate fellowship by supporting a key member of my team and protecting my research time.
Technical Summary
My research programme leverages brain stimulation to establish the functional role of neural synchrony in goal-directed behaviour, and its pathological role in Parkinson's disease and Essential Tremor.
During my Career Development Award, I
[Theme 1] established that the dynamic state of a disease circuit influences the most effective stimulation strategy. Building on our computational and experimental observations, we developed a time-varying stimulation controller that could maintain optimal stimulation performance in the face of fluctuating physiological demands as expected from factors such as disease progression, medication, or circadian rhythms.
[Theme 2] determined the effect of non-invasive brain stimulation on goal-directed behaviour using different stimulation patterns such as random noise and alternating current stimulation.
[Theme 3] explored the mechanisms through which our brains naturally control neural synchrony using biophysical computational models and experimental recordings that leverage cutting edge neuroimaging techniques such as optically pumped magnetometers.
Due to several mitigating circumstances, we are still at the beginning stages of Theme 4 and require additional time to develop this important translational element of the programme. With the funding provided by the Transition Support award, I aim to complete key experimental work, and determine whether it is possible to selectively modulate neural synchrony for therapeutic gain using brain stimulation. To this end, I will use non-invasive brain stimulation to mimic spatiotemporal signatures associated with spontaneous tremor suppression. This work will consolidate our outputs from Themes 1-3 and provide the necessary momentum to enable me to take my next career step.
During my Career Development Award, I
[Theme 1] established that the dynamic state of a disease circuit influences the most effective stimulation strategy. Building on our computational and experimental observations, we developed a time-varying stimulation controller that could maintain optimal stimulation performance in the face of fluctuating physiological demands as expected from factors such as disease progression, medication, or circadian rhythms.
[Theme 2] determined the effect of non-invasive brain stimulation on goal-directed behaviour using different stimulation patterns such as random noise and alternating current stimulation.
[Theme 3] explored the mechanisms through which our brains naturally control neural synchrony using biophysical computational models and experimental recordings that leverage cutting edge neuroimaging techniques such as optically pumped magnetometers.
Due to several mitigating circumstances, we are still at the beginning stages of Theme 4 and require additional time to develop this important translational element of the programme. With the funding provided by the Transition Support award, I aim to complete key experimental work, and determine whether it is possible to selectively modulate neural synchrony for therapeutic gain using brain stimulation. To this end, I will use non-invasive brain stimulation to mimic spatiotemporal signatures associated with spontaneous tremor suppression. This work will consolidate our outputs from Themes 1-3 and provide the necessary momentum to enable me to take my next career step.
People |
ORCID iD |
| Hayriye Cagnan (Principal Investigator / Fellow) |
Publications
Fleming JE
(2023)
From dawn till dusk: Time-adaptive bayesian optimization for neurostimulation.
in PLoS computational biology
Grennan I
(2024)
Beta bursts in the parkinsonian cortico-basal ganglia network form spatially discrete ensembles.
in Neurobiology of disease
He S
(2024)
Cortico-thalamic tremor circuits and their associations with deep brain stimulation effects in essential tremor.
in Brain : a journal of neurology
Mandali A
(2024)
Tuning the brakes - Modulatory role of transcranial random noise stimulation on inhibition.
in Brain stimulation
Silveira De Arruda B
(2024)
Developing a non-invasive approach for the treatment of pathological tremor
| Description | Director of Masters in research in Neurotechnology |
| Geographic Reach | Multiple continents/international |
| Policy Influence Type | Influenced training of practitioners or researchers |
| Impact | Through this role, I am directly leading the training of the next generation of researchers in the field of Neurotechnology. |
| Description | Elsie Widdowson |
| Amount | £50,000 (GBP) |
| Organisation | Imperial College London |
| Sector | Academic/University |
| Country | United Kingdom |
| Start | 06/2024 |
| End | 07/2025 |
| Description | Neuromod+ project grant |
| Amount | £80,000 (GBP) |
| Funding ID | N/A |
| Organisation | Imperial College London |
| Sector | Academic/University |
| Country | United Kingdom |
| Start | 05/2024 |
| End | 12/2024 |
| Title | Electroencephalogram (EEG) and behavioural data concerning the Go/NoGo/Conflict task |
| Description | Electroencephalogram (EEG) and behavioural data (joystick) was collected from 15 healthy participants who completed a modified version of a Go/No-go task. This dataset consists of raw data, pre-processed EEG and behavioural data, along with impulsivity scores in a .csv file. The pre-processed data is in MATLAB .mat format. Raw Data The EEG and behavioural data (Joystick) along with trigger data was collected using a TMSi Porti amplifier with a sampling rate of 2,048Hz and is in .een format. The raw EEG files contain brain activity recorded in the first 16 channels and last 2 channels (channels 17 and 18) correspond to Joystick and Trigger information (used to identify the type of event - Go/Conflict/NoGo) respectively. The Raw data is segregated into 2 folders- Active and Sham which is further divided into baseline and after stimulation conditions. The main behavioural outcome is the change in NoGo errors (pre-processed folder- Figure 1C in from the article 'Tuning the brakes - Modulatory role of transcranial random noise stimulation on inhibition,' Brain Stimulation, 2024), comparing baseline and after-stimulation in sham and active conditions. Metadata corresponding to impulsivity scores and the change in NoGo behaviour are provided in 'UPPS_nogo.csv' (used for Figure 1D). The EEG data was recorded while the participants completed the task during baseline and after stimulation, and was used to calculate the spectral power (Figure 1E). The study also presents intermittent bursts from the EEG data, comparing the average burst durations at baseline and after-stimulation (Figure 1F) in sham and active stimulation conditions. Code All data were analysed in MATLAB (2018b) using a combination of EEGLAB, ERP LAB and FieldTrip packages. Installation guides can be found on https://sccn.ucsd.edu/eeglab/index.php https://matlab.mathworks.com/ https://erpinfo.org/erplab https://www.fieldtriptoolbox.org/download/ The behavioural data plots use the software IOSR toolbox : https://github.com/IoSR-Surrey/MatlabToolbox Code_figure_IC.m: This script plots the NoGo error rates in baseline and after stimulation in sham and active conditions. This script uses the mat file 'Nogo_behav_pre_post.mat' Code_figure_1E.m: This script plots the spectral power and grand average of the after-stimulation EEG data with clusters obtained from a non-parametric analysis. This script uses the mat file 'data_psd_trns_pre_post.mat'. Code_figure_1F.m: This script plots the intermittent burst durations during sham and active conditions and uses the file 'Nogo_bursts_pre_post.mat' |
| Type Of Material | Database/Collection of data |
| Year Produced | 2024 |
| Provided To Others? | Yes |
| Impact | This will contribute to open science and reproducibility. |
| URL | https://ora.ox.ac.uk/objects/uuid:77840faf-e8ed-47cc-9934-9b9ca21e421b |
| Title | Essential tremor disrupts rhythmic brain networks during naturalistic movement |
| Description | This is linked to our recent publication on "Essential tremor disrupts rhythmic brain networks during naturalistic movement" |
| Type Of Material | Computer model/algorithm |
| Year Produced | 2025 |
| Provided To Others? | Yes |
| Impact | This model will contribute to open science and reproducibility. |
| URL | https://doi.org/10.5281/zenodo.14973441 |
| Title | High density human neuroimaging data from healthy controls and patients with Essential Tremor engaged in an upper-limb reaching task |
| Description | This dataset consists of human neuroimaging data recorded from human cohorts of healthy controls and patients diagnosed with Essential Tremor (ET). Participants were recorded in an experimental paradigm consisting of an upper limb, centre-out reaching task.High density EEG (128 channels; HD-EEG). This data was recorded using a Brain Products DC amplifier and gel based active electrodes mounted in the standard 10-10 system with an actiCAP. 11 healthy controls and 12 patients with ET.Optically pumped magnetoencephalography (OP-MEG). This data was recorded using combinations of 2nd and 3rd generation QuSpin sensors (dual- and tri-axial sensors, respectively) mounted in rigid 3D-printed casts custom-built to each participant's scalp shape determined from structural magnetic resonance images (MRIs). 5 healthy controls and 4 patients with ET.The complete dataset comprises:Raw OP-MEG data provided in The Brain Imaging Data Structure (BIDS) formatRaw HD-EEG data provided in BrainVision formats: '.eeg'; '.vhdr'; '.vmrk'.Triaxial accelerometry recorded as auxiliary channels in the raw data.Task markers provided as DC step signal recorded as auxiliary channels in the raw data.Task related information - condition ordering, screen positions, etc. in '.csv'Structural neuroimaging- MRIs of brain anatomy. 3D FLASH protocol supplied in NIfTI '.nii' format.3D motion capture data supplied as Motive '.tak' data.Processed data is provided in the Fieldtrip Data structure and saved as MATLAB '.mat' files, and available across different levels of analysis indicated by the suffix:'*_rawdata' - imported data.'*_pp' - epoched and preprocessed.'*_pp_ar' - artefact rejected.'*_freq' - frequency domain representation.'*_VC' - projected as virtual channels in the source domain. |
| Type Of Material | Database/Collection of data |
| Year Produced | 2025 |
| Provided To Others? | Yes |
| Impact | This will contribute to open science and reproducibility. |
| URL | https://data.mrc.ox.ac.uk/data-set/human-neuroimaging-essential-tremor |
| Title | TV-Bayes Opt |
| Description | This model is linked to the publication and patent application on Time Varying Bayes Optimization. |
| Type Of Material | Computer model/algorithm |
| Year Produced | 2023 |
| Provided To Others? | Yes |
| Impact | This will contribute to open science, reproducibility and the research field of Neurotechnology. |
| URL | https://process.innovation.ox.ac.uk/software/p/21242/tv-bayesopt-academic-use/1 |
| Description | Imperial College Hospitals |
| Organisation | Imperial College Healthcare NHS Trust |
| Country | United Kingdom |
| Sector | Hospitals |
| PI Contribution | I will be contributing technical expertise and computational modelling to a range of projects with immediate clinical implications. |
| Collaborator Contribution | My collaborators will be supporting our research through patient recruitment. |
| Impact | No outputs generated. This collaboration has resulted in recruitment of 2 PhD students, one programme grant application and one PhD funding application. |
| Start Year | 2024 |
| Description | Multi-site stimulation for tremor control (Farina and Drakakis) |
| Organisation | Imperial College London |
| Country | United Kingdom |
| Sector | Academic/University |
| PI Contribution | We are currently setting up a collaboration with Dr Farina and Dr Drakakis at Imperial College to develop a multi site brain stimulation device for tremor control. We are currently in the process of applying for grants to fund this research. |
| Collaborator Contribution | Dr Farina will contribute peripheral control of stimulation while Dr Drakakis will be supporting device design. |
| Impact | No outputs generated at this point. This collaboration has resulted in recruitment of one MRes student. |
| Start Year | 2024 |
| Description | Neuromod + |
| Organisation | Imperial College London |
| Country | United Kingdom |
| Sector | Academic/University |
| PI Contribution | Contributed to a grant application for an EPSRC/MRC Network + creation |
| Collaborator Contribution | Contributed to a grant application for an EPSRC/MRC Network + creation |
| Impact | The EPSRC & MRC NEUROMOD+ Network is a new UK network aiming to build capacity and bring together multidisciplinary stakeholder groups to support the co-creation of novel neuromodulation therapies. NEUROMOD+ will promote and facilitate discussion between stakeholders, and instigate new collaborative research partnerships, through a range of activities including co-creation events, workshops and funding calls. We have recently launched the network and had our first event. |
| Start Year | 2022 |
| Description | Optically Pumped Magnetometers - Gareth Barnes and Simon Farmer (University College London) |
| Organisation | University College London |
| Country | United Kingdom |
| Sector | Academic/University |
| PI Contribution | This project involves the use of a novel neuroimaging system, optically pumped magnetometers, to better understand the disease circuit underlying pathological tremor (e.g. Essential Tremor and Parkinson's disease). My research team has contributed to the study design and has completed the ethics application, which has been approved by the local ethics committee. Marielle Stam and Deniz Kucukahmetler who worked as interns in my research group designed the task which will be used in these experiments in collaboration with my postdoctoral research associate Timothy West. Timothy West is also building a new theoretical model of the tremor circuit which will be used to further explore this dataset. |
| Collaborator Contribution | Prof Barnes and Prof Farmer contributed to study design, and Prof Farmer will be identifying patients recruited for the study. |
| Impact | This collaboration is bringing together the following fields: neuroscience, engineering and medicine. This project has resulted in the recruitment of two interns (Marielle Stam and Deniz Kucukahmetler). Due to Covid-19, patient recruitment and recording have been on hold for a significant period of time and further delays were experienced for research approvals (linked to pandemic related backlog), which has significantly impacted the project timeline. This is in particular a significant set-back for my postdoc Timothy West who needed an extension of his contract in order to complete this project. We are currently writing up this work. |
| Start Year | 2018 |
| Description | Optically Pumped Magnetometers - Gareth Barnes and Simon Farmer (University College London) |
| Organisation | University College London |
| Country | United Kingdom |
| Sector | Academic/University |
| PI Contribution | This project involves the use of a novel neuroimaging system, optically pumped magnetometers, to better understand the disease circuit underlying pathological tremor (e.g. Essential Tremor and Parkinson's disease). My research team has contributed to the study design and has completed the ethics application, which has been approved by the local ethics committee. Marielle Stam and Deniz Kucukahmetler who worked as interns in my research group designed the task which will be used in these experiments in collaboration with my postdoctoral research associate Timothy West. Timothy West is also building a new theoretical model of the tremor circuit which will be used to further explore this dataset. |
| Collaborator Contribution | Prof Barnes and Prof Farmer contributed to study design, and Prof Farmer will be identifying patients recruited for the study. |
| Impact | This collaboration is bringing together the following fields: neuroscience, engineering and medicine. This project has resulted in the recruitment of two interns (Marielle Stam and Deniz Kucukahmetler). Due to Covid-19, patient recruitment and recording have been on hold for a significant period of time and further delays were experienced for research approvals (linked to pandemic related backlog), which has significantly impacted the project timeline. This is in particular a significant set-back for my postdoc Timothy West who needed an extension of his contract in order to complete this project. We are currently writing up this work. |
| Start Year | 2018 |
| Description | Personalised Parkinson's Project |
| Organisation | Radboud University Nijmegen |
| Country | Netherlands |
| Sector | Academic/University |
| PI Contribution | My research group has developed an analysis pipeline for further exploration of this unique dataset which follows 500 patients diagnosed with Parkinson's disease patients longitudinally. |
| Collaborator Contribution | My collaborators are sharing data collected from patients together with contributing to scientific direction. |
| Impact | This collaboration will enable us to study longitudinal changes in patient's symptoms based on wearable sensors. We will aim to classify patients into different groups based on their symptom manifestation and use these insights to explore underlying neural dynamics at the group level. This research brings together bioinformatics and clinical neuroscience and aims to leverage modern analysis techniques for handling large datasets in order to better understand variabilities in disease manifestation across patient populations. As a result of this collaboration, we have recently secured additional funding from the Michael J Fox Foundation and are currently planning to make an additional grant application. |
| Start Year | 2020 |
| Title | SYSTEMS AND METHODS FOR GENERATING A STIMULATION SIGNAL FOR BRAIN OR NERVE STIMULATION AND FOR PERFORMING BRAIN OR NERVE STIMULATION |
| Description | Systems and methods for generating stimulation signals for brain or nerve stimulation are disclosed. In one arrangement, a signal generation unit generates a stimulation signal and transmits the stimulation signal to a stimulation unit. The stimulation unit applies the stimulation to a biological system. The stimulation signal is defined by at least one stimulation parameter. A data receiving unit receives time series biomarker data comprising measurement samples representing one or more biomarkers indicative of a condition of the biological system that is affected by applied stimulation based on the stimulation signal. A controller controls generation of the stimulation signal based on the received biomarker data. The controller uses a model of the biological system to estimate an optimal value of the at least one stimulation parameter using the biomarker data. The model defines strengths of contribution of measurement samples to the estimate based on the times at which the measurement samples were obtained. |
| IP Reference | WO2025022112 |
| Protection | Patent / Patent application |
| Year Protection Granted | 2025 |
| Licensed | No |
| Description | Imperial Lates: Weird Science |
| 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 | Public/other audiences |
| Results and Impact | This public engagement event is dedicated for 18+ general public to find out more about research taking place at Imperial college. |
| Year(s) Of Engagement Activity | 2025 |
| URL | https://www.imperial.ac.uk/events/186774/lates-weird-science/ |
| Description | talk - imperial college Neurotech Society |
| Form Of Engagement Activity | A talk or presentation |
| Part Of Official Scheme? | No |
| Geographic Reach | Local |
| Primary Audience | Undergraduate students |
| Results and Impact | I gave a talk to the Imperial College Neurotech society - an undergraduate society run by a group of engineering students to inform them about the latest research in the field. |
| Year(s) Of Engagement Activity | 2024 |