Biasing influences on the motor system during action preparation: a multimodal neuroimaging-computationally informed approach
Lead Research Organisation:
University College London
Department Name: Institute of Neurology
Abstract
In almost every aspect of life, adequate behavior first requires the processing of incoming sensory information. We then must weigh its relevance, decide between alternative movements, and select the most appropriate behavior. For example, a goalkeeper facing a penalty kick needs to observe player and ball, estimate the likely trajectory of the ball based on experience and postural cues from the player, and finally decide in which direction to move as fast as possible. We therefore use our experience for preparing the appropriate movements, yet it is still poorly understood how information such as past experience gets funnelled into our actual movements. Previous research suggests that the processes underlying perception and movement overlap in the brain, both anatomically and in time. However, the brain activity patterns, rules and computations exchanged by different brain regions to accomplish this influence remain largely undetermined. The central goal of my proposal is to reveal how different brain regions interact with the motor system to use past experience and prior information for movement selection. In my experiments, participants prepare movements based on visual cues. These cues indicate which movement is required (e.g. button presses) when a subsequent visual go-signal is presented. When cues are reliably predicting the required movement, responses are fast. This suggests that we use our experience about the reliability of visual information available to us to prepare movements efficiently. By changing the validity of these visual cues, one can change the uncertainty about which movement will have to be performed. In this way, we can address the question how our experience about the world influences our actions, and our brain. First, non-invasive brain stimulation will measure the activation state of the motor system during movement preparation in these experiments. This safe method for causing brain activity provides a direct read-out of the state of a brain region. I will then combine this brain stimulation with neuroimaging. I have recently developed this combined technique which allows for measuring the impact of brain stimulation on activity across the entire brain with high anatomical precision. Brain regions involved in preparing movements will be stimulated. At the same time, neuroimaging will measure the resulting activity changes in connected brain regions. This will reveal the brain regions relevant for making movements based on sensory experience, and disclose the influences among them which are required to bind together our experience with our actions. Finally, Magnetoencephalography non-invasively detects electrical brain signals in humans, and will reveal the timecourse of brain activity during preparation for movements based on experience and past information. It may seem obvious that the brain uses past information to guide our future movements. However, few studies have formally tried to quantify how our experience about sensory information shapes the motor system over time. One can quantify this experience by using simple mathematical models. These provide so-called computationally informed time-evolving representations of experience, and can be applied to test for corresponding brain activity changes. Using such computationally informed representations, for example, about the uncertainty of visual information, is exciting because it overcomes one of the central limitations that has bedevilled cognitive psychology for the past 100 years: the actual computations of the brain are hidden to us, and only by formal representation can we understand the processes that the brain embellishes for specifying movements efficiently in an uncertain world.
Technical Summary
Decisions for actions are often guided by sensory input and past experiences, and we must learn from experience to specify and prepare actions in advance of an event. A central question in cognitive neuroscience is how we use past experience to implement actions at the level of the motor system? Recent findings show that perceptual inference, learning, and action selection occur in parallel, overlapping topographically and in time across the brain. Accordingly, new theories predict that the motor system is continuously biased by the affordances of the present situation, such as prior information, perceptual integration, or reward, to form decisions for actions. However, these predictions have not been tested in humans. The causal interplay and state-dependence of inter-cortical interactions underlying biasing influences are largely unknown. The proposed research will measure causal functional influences among brain regions during preparation of actions using a multimodal neuroimaging approach. Transcranial magnetic stimulation (TMS) and Magnetoencephalography (MEG) will test for the temporal organisation of causal influences from association cortex to M1 during action preparation. Concurrent TMS-functional magnetic resonance imaging (fMRI) will reveal the functional neuroanatomy of causal inter-regional influences during motor preparation. These experimental approaches will be complemented by computationally informed quantifications of the time-evolving (rather than average) changes of visual information. Using computational models such as information theory closes an important gap: they represent the dynamic, not just average, evolution of how experience or prior information might bias be represented in an action-dependent way. Together, the proposal will address how different brain regions interact with the motor system on a trial-by-trial basis, to transform prior information and experience into actions.
People |
ORCID iD |
Sven Bestmann (Principal Investigator) |
Publications
Bestmann S
(2013)
Combined neurostimulation and neuroimaging in cognitive neuroscience: past, present, and future.
in Annals of the New York Academy of Sciences
Blankenburg F
(2010)
Studying the role of human parietal cortex in visuospatial attention with concurrent TMS-fMRI.
in Cerebral cortex (New York, N.Y. : 1991)
Brown H
(2011)
Active inference, attention, and motor preparation.
in Frontiers in psychology
Charlotte Stagg (Co-Author)
(2011)
A multimodal approach to investigating human motor cortical excitability and inhibition
in Journal of Physiology
Driver J
(2010)
New approaches to the study of human brain networks underlying spatial attention and related processes.
in Experimental brain research
Freund P
(2011)
Corticomotor representation to a human forearm muscle changes following cervical spinal cord injury.
in The European journal of neuroscience
Friston KJ
(2012)
Dopamine, affordance and active inference.
in PLoS computational biology
Galea JM
(2012)
Action reprogramming in Parkinson's disease: response to prediction error is modulated by levels of dopamine.
in The Journal of neuroscience : the official journal of the Society for Neuroscience
Harrison LM
(2011)
Time scales of representation in the human brain: weighing past information to predict future events.
in Frontiers in human neuroscience
Hartwigsen G
(2012)
Left dorsal premotor cortex and supramarginal gyrus complement each other during rapid action reprogramming.
in The Journal of neuroscience : the official journal of the Society for Neuroscience
Description | The work of the fellowship has addressed the fundamental question on how our brain processes information from the outside world and turns this information into meaningful, precise and timely movements. Initially, this work has focussed on two of the key variables that influence which movements we make: event uncertainty and reward. We know that our expectations about what will happen in the outside world, as well as the expected rewards we can obtain influences our preferences and decisions, but how these processes interact with the motor system to guide the selection and execution of our movements was less clear. In the work of this proposal we have shown that 1) the human motor system distinguishes the forthcoming choice before completion of the decision process, based on the subjective value-difference between chosen and unchosen actions, thus providing the first evidence that internally generated value-based decisions influence the competition between action representations in motor cortex before the decision process is complete (Klein-Flugge and Bestmann, J Neurosci 2012) 2) that mechanistically, this finding may be underpinned by the optimization of preparatory population activity, with this optimization being controlled by decision variables such as expected value of an action (Klein-Flugge et al., J Neurosci 2013); 3) that not only reward but also punishment influences the optimization of movement representations in the human motor system, and that this is furthermore controlled by the neurotransmitter Dopamine (Galea et al., J Neurosci 2013); 4) the reward influence on the motor system is mediated by ventromedial prefrontal cortex, via projections to intraparietal cortex, but this influence is only evident when the reward-based decision process is directly linked to a subsequent actions (Klein-Flugge et al., in preparation; Society of Neuroscience abstract 2011); 5) that more generally, causal influences onto the human motor system during action selection are muscle-specific and driven via dorsolateral prefrontal (Hasan et al., J Cogn Neurosci 2013), premotor and supramarginal gyrus activity (Hartwigsen et al., J Neurosci 2012); 6) that with respect to 5), the causal role of premotor cortex becomes more important following damage to the contralateral motor and premotor cortex (Bestmann et al., J Neurosci 2010); 7) influences on the motor system occur before the decision process (e.g. value-based decision making) is complete, supporting a more integrated and parallel organisation of decision making and action selection (Klein-Flugge et al J Neurosci 2012; J Neurosci 2013) 8) the neurotransmitter dopamine has an important role in the reprogramming of actions when changes in the environment cause prediction errors about forthcoming movements (Friston et al Plos Comp Biol 2012; Galea et al J Neurosci 2012). This can explain the specific impairments to react to unexpected events as seen in Parkinson's Disease (Galea et al 2012). Mechanistically, we have suggested that one additional role of dopamine is to control behavioural variability in reinforcement-type action selection (Galea et al J Neurosci, 2013). The role of dopamine for controlling or encoding uncertainty was furthermore assessed in a series of pharmacological experiments that revealed that a) responses to unexpected surprising events are specifically impaired under dopamine depletion, with a probable role of D1 receptor activity, as assessed through a pharmacological combination-model (Bestmann et al., J Cogn Neurosci, 2015), and b) that dopamine controls the precision of temporal uncertainty, i.e. the uncertainty associated with the passage of time, which is a fundamental feature of successful action preparation and selection (Tomassini et al., 2016) |
Exploitation Route | New technology for combined brain stimulation and neuroimaging is gaining more widespread interest. partnerships have started to result in novel methods development |
Sectors | Education Healthcare |
Description | Action Selection under Contextual Uncertainty: the Role of Learning and Effective Connectivity in the Human Brain |
Amount | £939,933 (GBP) |
Funding ID | 260424 |
Organisation | Biotechnology and Biological Sciences Research Council (BBSRC) |
Sector | Public |
Country | United Kingdom |
Start | 09/2008 |
End | 09/2013 |
Description | Establishing a trans-atlantic partnership for studying the neural networks for motor skill learning in the human brain |
Amount | £46,000 (GBP) |
Funding ID | BB/I026162/1 |
Organisation | Biotechnology and Biological Sciences Research Council (BBSRC) |
Sector | Public |
Country | United Kingdom |
Start | 03/2011 |
End | 03/2015 |
Description | Starter Grant |
Amount | € 1,350,000 (EUR) |
Organisation | European Research Council (ERC) |
Sector | Public |
Country | Belgium |
Start | 05/2011 |
End | 06/2016 |
Title | High resolution MEG |
Description | New head-cast system for high resolution magnetoencephalography |
Type Of Material | Technology assay or reagent |
Year Produced | 2014 |
Provided To Others? | Yes |
Impact | development allows for MEG measures at unprecedented resolution |
Title | new TMS coils for MRI |
Description | Development of novel TMS coil arrangements for use in MRI environment |
Type Of Material | Technology assay or reagent |
Year Produced | 2013 |
Provided To Others? | Yes |
Impact | New TMS coil and MRI head coil arrangements for concurrent TMS-fMRI |
Description | Johns Hopkins partnership |
Organisation | Johns Hopkins Medicine |
Country | United States |
Sector | Hospitals |
PI Contribution | Organisation of two meetings, one in London one in Baltimore; student/post-doc exchanges; grant applications; joint papers and reviews |
Collaborator Contribution | Organisation of two meetings, one in London one in Baltimore; student/post-doc exchanges; grant applications; joint papers and reviews |
Impact | Two joint meetings Organisation of two meetings, one in London one in Baltimore; student/post-doc exchanges; grant applications; joint papers and reviews |
Start Year | 2010 |
Description | Technical development |
Organisation | University of Vienna |
Country | Austria |
Sector | Academic/University |
PI Contribution | Development of novel TMS-fMRI coils. Own role as expert in the field |
Collaborator Contribution | Technical development and testing |
Impact | [8] Navarro de Lara, Windischberger C, Kuehne A, Sieg, J, Bestmann S, Weiskopf N, Strasser B, Moser E, Laistler E. A novel coil array for combined TMS/fMRI experiments at 3 T Magn Res Med |
Start Year | 2011 |
Description | Technical development |
Organisation | Utrecht University |
Country | Netherlands |
Sector | Academic/University |
PI Contribution | Consultancy, experimental planning, expert opinion |
Collaborator Contribution | Testing, technical setup |
Impact | [10] De Weijer AD, Sommer IEC, Bakker EJ, Bloemendaal M, Bakker CJ, Klomp DWJ, Bestmann S, Neggers SFW. A setup for administering TMS to medial and lateral cortical areas during whole brain fMRI recording. J Clin Neurophysiology 31:474-487 |
Start Year | 2011 |