Behaviour is the expression of movement. We study how we transform the goals of our movement into actual movement, and the processes underpinning recovery of movement after stroke.
Our research is organised along several complementary themes:
- Computational Neurostimulation
- Control of Human Movement
- Neuromodulation and action
- Stroke & NeuroRehabilitation
We approach each theme with a variety of techniques:
- High-precision Magnetoencephalography
- Non-invasive brain stimulation (NIBS)
Our collaborators at UCL:
- Gareth Barnes
- Nick Ward
- Karl Friston
Global Collaborators:
- Marom Bikson (City College of New York)
- John Krakauer, Johns Hopkins University
- Antonio Oliviero (Toledo, Madrid)
- Bryan Strange (UPM, Madrid)
- Joe Galea (University of Birmingham)
- Charlie Stagg (fmrib, Oxford)
- Chris Chambers (CUBRIC, Cardiff)
- Matthew Brookes (Sir Peter Mansfield Imaging Centre, Nottingham)
Computational Neurostimulation
Non-invasive brain stimulation (NIBS) allows for directly interacting with neural activity. NIBS can provide powerful ways to study behaviour, but i can possibly also have beneficial effects in disease. Strikingly, however, we still do not know how different forms of NIBS work and lead to the behavioural changes we often observe.
We develop new NIBS approaches for better and more reliable delivery of NIBS in both health and disease.
To this end, we employ "computational neurostimulation" approaches to explain the effects of NIBS. See our edited book in Prog Brain Res on this topic
Relevant papers:
Bestmann S, Walsh V. Primer: transcranial electrical stimulation. Curr Biol free copy here
Bestmann S, Ward N (2017) Are current flow models for transcranial electrical stimulation fit for purpose? Brain Stimul pii: S1935-861X(17)30660-5 free copy here
Rawiji V, Ciocca M, Zacharia A, Soares D, Truong D, Bikson M, Rothwell JC, Bestmann S. tDCS changes in motor excitability are specific to orientation of current flow. Brain Stim open access
Bonaiuto J, de Berker AO, Bestmann S (2016) Response repetition biases in human perceptual decisions are explained by activity decay in competitive attractor models. eLife doi: 10.7554/eLife.20047 full text here
Hammerer D, Bonaiuto J, Klein-Flugge M, Bikson M, Bestmann (2016). Selective alteration of human value decisions with medial frontal tDCS is predicted by changes in attractor dynamics. Nature Sci Rep DOI: 10.1038/srep25160 free pdf here
Bestmann S (2015). Computational Neurostimulation in basic and translational research. Prog Brain Res 222:xv-xx doi: 10.1016/S0079-6123(15)00159-4 find the paper here
Bonaiuto J, Bestmann S (2015). Understanding the nonlinear physiological and behavioral effects of tDCS through computational neurostimulation. Progress Brain Res 222:75-103 find the paper here
Bestmann S, de Berker AO, Bonaiuto J (2015). Understanding the behavioural consequences of non-invasive brain stimulation. Trends in Cognitive Sciences 19:13-20. full text here
Little S, Bestmann S (2015). Computational Neurostimulation for Parkinson’s Disease. Prog Brain Res 222:163-90 full text here
De Berker AO, Bikson M, Bestmann S (2013). Predicting the behavioural impact of transcranial direct current stimulation: issues and limitations. Frontiers Hum Neurosci 7:613 free pdf here
Control of Human Movement
We study how we move. How do we determine the goals of our movements, and how do we then turn these into actual movement? How different decision variables, such as reward, surprise, physical effort, or stress, influence our actions? And how do we learn, and re-learn, movements in response to new events or new challenges?
This research will ultimately help to understand how and why movement is impaired in so many neurological and psychiatric conditions, and how to develop better therapies and treatments to reinstantiate the control of movement.
Relevant papers:
Klein-Flügge MC, Friston K, Kennerley S, Bestmann S (2016) Neural Signatures of Value Comparison in Human Cingulate Cortex during Decisions Requiring an Effort-Reward Trade-off. J Neurosci 36:10002-10015 free pdf here
Chen X, Rutledge RB, Brown HR, Dolan RJ, Bestmann S, Galea JM (2018). Age-dependent Pavlovian biases influence motor decision-making. PLoS Comp Biol 14(7):e1006304. open access
de Berker, Tirole M, Rutledge R, Cross G, Dolan R, Bestmann S (2016). Stress selectively impairs learning to act. Nature Sci Rep 6:29816 download here
Bestmann S, Ruge D, Rothwell JC, Galea J (2015). The role of dopamine in motor flexibility. J Cogn Neurosci 27:365-76 find the paper here
Galea J, Ruge D, Buijink A, Bestmann S, Rothwell JC (2013) Punishment induced behavioural and neurophysiological variability reveals dopamine-dependent selection of kinematic movement parameters. Journal of Neuroscience 33:3981-8 free copy here
Klein-Flugge M, Bestmann S (2012). Time-dependent changes in human cortico spinal excitability reveal value-based competition for action during decision processing. J Neurosci 32:8373-82 free pdf
Klein-Flugge M, Nobbs D, Pitcher J, Bestmann S (2013). Variability of human cortico-spinal excitability tracks the state of action preparation. Journal of Neuroscience 33:5564-72 find the paper here
Neuromodulation and action
The neurotransmitter Dopamine, Noradrenaline and Acetylcholine have been implicated in a bewildering variety of processes and pathologies in the human brain; ranging from cortical excitability to attentional deficits; from motor control to akinesia and set switching deficits in Parkinson’s disease; from working memory to schizophrenia; from reinforcement learning to addiction; and the processing of different types of environmental uncertainty and learning. How these systems contribute to the formation of action goals, and movement in general, remains unclear. We use pharmacological manipulations in healthy participants to study the specific role of these different neurotransmitters for action selection and execution
Relevant papers:
Yebra M, Galarza-Vallejo A, Soto-Leon V, Gonzalez-Rosa JJ, de Berker AO, Bestmann S, Oliviero A, Kroes MCW, Strange BA (2019) .Action boosts episodic memory encoding in humans via engagement of a noradrenergic system. Nat Commun. doi: 10.1038/s41467--8 open access
Marshall M, Mathys C, Ruge D, de Berker A, Dayan P, Stephan KE, Bestmann S. Pharmacological fingerprints of contextual uncertainty. PLOS Biology free copy here
Tomassini A, Ruge D, Galea JM, Penny W, Bestmann S. The role of dopamine in temporal uncertainty. J Cogn Neurosci 24:1-15 free paper here
de Berker AO, Rutledge RB, Mathys C, Marshall L, Cross GF, Dolan RJ, Bestmann S (2016). Computations of uncertainty mediate acute stress responses in humans. Nat Commun. 7:10996. free copy here
Bestmann S, Ruge D, Rothwell JC, Galea J (2015). The role of dopamine in motor flexibility. J Cogn Neurosci 27:365-76 find the paper here
Galea J, Ruge D, Buijink A, Bestmann S, Rothwell JC. Punishment induced behavioural and neurophysiological variability reveals dopamine-dependent selection of kinematic movement parameters. J Neurosci 33:3981-3999 free paper here
Friston K, Shiner T, Fitzgerald T, Galea J, Adams R, Brown H, Dolan R, Moran R, Stephan KE, Bestmann S. Dopamine, precision and affordance in active inference. PLoS Comp Biol 8(1):e1002327 free copy here
Galea J*, Bestmann S*, Beigi M, Jahanshahi M, Rothwell JC (2012). Action reprogramming in Parkinson's disease: response to prediction error is modulated by levels of dopamine. J Neurosci. 32:542-50 free copy here
Stroke & NeuroRehabilitation
Predicting long-term outcome after neurologic injury is a fundamental goal of our lab. We will identify the tools with which to build appropriate predictive models of long-term outcome after neurologic injury in multiple domains, to the benefit of patients, carers and clinicians in decision making, and stratification in restorative clinical trials for the first time.
We also strive to determine the active ingredients of behavioural therapy in motor, language and cognitive domains. We study the key components of successful behavioural therapy so that they might be tested and refined.
Finally, we ask whether brain plasticity can be modulated with drugs, non-invasive brain stimulation or environmental manipulation to maximise the effect of behavioural training? Moreover, can we understand better who is most likely to benefit from these interventions?
Quattrocchi G, Greenwood R, Rothwell JC, Galea JM, Bestmann S, Galea JM (2017) Role of dopamine in motor adaptation under reward and punishment. JNNP 88(9):730-736 download paper here
Galea J, Ruge D, Buijink A, Bestmann S, Rothwell JC (2013). Punishment induced behavioural and neurophysiological variability reveals dopamine-dependent selection of kinematic movement parameters. J Neurosci 33:3981-3999 free copy here
High-precision Magnetoencephalography
The magnetoencephalogram is a direct measurement of brain activity able to resolve electrical current change over milliseconds. Because the measurement is direct (and not constrained by intermediate physiology like vasculature) the achievable spatial resolution is theoretically limitless.
We developed novel approaches for obtaining high precision neurophysiological measurements in humans. For example, wearable room-temperature MEG, so-called optically-pumped magnetometers (OPMs), now allow for the possibility to study naturalistic movement in health and disease (Boto et al, Nature 2018).
Relevant papers:
Little S, Bonaiuto J, Barnes G, Bestmann S (2019). Human motor cortical beta bursts relate to movement planning and response errors. PLoS Biol. 2019 doi: 10.1371/journal.pbio.3000479. open access
Boto E, Holmes N, Leggett J, Roberts G, Shah V, Meyer SS, Duque Muñoz L, Mullinger KJ, Tierney TM, Bestmann S, Barnes GR, Bowtell R, Brookes MJ (2018). Moving magnetoencephalography towards real-world applications with a wearable system. Nature doi:10.1038/nature26147 link
Bonaiuto JJ, Meyer S, Little S, Rossiter H, Callaghan M, Dick F, Barnes G, Bestmann S. Laminar-specific cortical dynamics in human visual and sensorimotor cortices. Elife. 2018 Oct 22;7. pii: e33977. doi: 10.7554/eLife.33977. download the paper here
Bonaiuto JJ, Rossiter HE, Meyer S, Adams N, Little S, Callaghan M, Dick F, Bestmann S, Barnes GR (2017). Non-invasive laminar inference with MEG: Comparison of methods and source inversion algorithms. NeuroImage 167:372-383 free copy here
Little S, Bonaiuto JJ, Meyer SS, Lopez J, Bestmann S, Barnes G (2017). Quantifying the performance of MEG source reconstruction using resting state data. Neuroimage. 2018 Nov 1;181:453-460. doi: 10.1016/j.neuroimage.2018.07.030. open access paper
Meyer S, Rossiter H, Brookes M, Woolrich M, Burgess N, Bestmann S, Barnes G (2017). Is it really the hippocampus? Using MEG generative models to make probabilistic statements on hippocampal engagement. NeuroImage 149:468-482 open access here
Meyer SS, Bonaiuto J, Lim M, Rossiter H, Waters S, Bradbury D, Bestmann S, Brookes M, Callaghan MF, Weiskopf N, Barnes GR (2016) Flexible head-casts for high spatial precision MEG. J Neurosci Methods 276, 38-45 free copy here
Troebinger L, López JD, Lutti A, Bestmann S, Barnes G (2014) Discrimination of cortical laminae using MEG. Neuroimage doi: 10.1016/j.neuroimage.2014.07.015 free article here
Troebinger L, López JD, Lutti A, Bradbury D, Bestmann S, Barnes G.High precision anatomy for MEG. Neuroimage. 86:583-91 free article here
Non-invasive brain stimulation (NIBS)
https://www.sciencedirect.com/science/article/pii/S1053811918306451?via%3Dihub
Non-invasive brain stimulation (NIBS) allows for directly interacting with neural activity. Different NIBS approaches in humans provide controlled inputs into the operations of cortical regions, with highly specific behavioral consequences, and possibly beneficial impact in pathology. We are interested in understanding the basic mechsanism of action of two types of NIBS: transcranial magnetic stimulation (TMS), and transcranial electrical stimulation (tES), which includes transcranial direct current stimulation (tDCS).
To this end, we employ a combination of human electrophysiology, neuroimaging, and computational neurostimulation to address how one can employ NIBS for studies of cognition and potential clinical interventions.
Relavant papers:
Evans C, Bachmann C, Lee JSA, Gregoriou E, Ward N, Bestmann S (2019) Dose-controlled tDCS reduces electric field intensity variability at a cortical target site. Brain Stimul. 2019 doi: 10.1016/j.brs.2019.10.004 open access version
Bestmann S, de Berker AO, Bonaiuto J (2015). Understanding the behavioural consequences of non-invasive brain stimulation. Trends in Cognitive Sciences 2015 19:13-20. full pdf hereBestmann S, Walsh V. Transcranial electrical stimulation. Curr Biol. 2017 27:R1258-R1262 Full text here
Esmaeilpour Z, Marangolo P, Hampstead BM, Bestmann S, Galletta E, Knotkova H, Bikson M (2018). Incomplete evidence that increasing current intensity of tDCS boosts outcomes. Brain Stimul. 11:310-321 link
Rawiji V, Ciocca M, Zacharia A, Soares D, Truong D, Bikson M, Rothwell JC, Bestmann S. tDCS changes in motor excitability are specific to orientation of current flow. Brain Stim free copy here
Bonaiuto J, de Berker AO, Bestmann S (2016) Response repetition biases in human perceptual decisions are explained by activity decay in competitive attractor models. eLife doi: 10.7554/eLife.20047 free copy here
Bonaiuto J, Bestmann S. Understanding the nonlinear physiological and behavioral effects of tDCS through computational neurostimulation. Progress Brain Res (in press) find the paper here
Bestmann S, Duque J (2015) Transcranial Magnetic Stimulation: Decomposing the Processes Underlying Action Preparation. The Neuroscientist. find the paper here
Bestmann S, Krakauer JW (2015). The uses and interpretations of the motor-evoked potential for understanding behaviour. Exp Brain Res. 233:679-89. doi: 10.1007/s00221--7. free pdf here
Nitsche M, Bikson M, Bestmann S. On the use of meta-analysis in neuromodulatory non-invasive brain stimulation. Brain Stimulation free pdf here
Hammerer D, Bonaiuto J, Klein-Flugge M, Bikson M, Bestmann S. Biasing human value-based decision making with non-invasive brain stimulation. Nature Sci Rep 6:25160. doi: 10.1038/srep25160 download here
Romei V, Bauer M, Brooks J, Economides M, Penny W, Thut G, Bestmann S (2015) Causal evidence that intrinsic beta frequency is relevant for enhanced signal propagation in the motor system as shown through rhythmic TMS. NeuroImage 126:120-130 full pdf here
Safety and consensus papers:
Rossi S, Hallett M, Rossini PM, Pascual-Leone A, Avanzini G, Bestmann S, et al. (2008) Safety, Ethical Considerations, and Application Guidelines for the Use of Transcranial Magnetic Stimulation in Clinical Practice and Research. Clin Neurophysiol 120:2008-2039 free copy here
Siebner HR, Bergmann TO, Bestmann S, et al. Consensus paper: Combining transcranial magnetic stimulation with neuroimaging. Brain Stimulation 2:58-80 pubmed