Research

Our mission is to identify the neural principles governing skilled action control in humans, and reverse-engineer these insights into brain-computer interfaces and assistive technologies that drive recovery and flexibility in patient rehabilitation and robotic systems. By integrating motor learning and control paradigms with multimodal measures - including fMRI, MEG/EEG, EMG, eye-tracking, kinematics and brain stimulation - the lab investigates the complex interactions between brain, muscle and behaviour for skilled motor control. We apply multivariate analyses and AI to these datasets to characterise the neural architecture of skilled actions, and collaborate with partners across animal neurophysiology, computer science, robotics and neurology to translate these results for real world impact.

Planning of movement sequences

What happens in our brain before we initiate a skilled sequence of movements, like typing a message on a phone, playing a melody on the piano, or uttering a sentence? Does our brain play back each action one-by-one as its activity cascades through a series of states, or does it prepare individual actions in parallel before we start the movement? We established tools to read out the neural organisation of sequential actions during motor planning non-invasively using MEG, fMRI, as behaviourally. These approaches provide a window into the structure and content of sequence planning and how it affect subsequent performance. Our goal is to develop non-invasive neurotechnological tools to modify neural patterns before movement starts to enhance skilled action learning and control to boost neurorehabilitation after stroke and in Parkinson's disease.

Yin Z*, Liu J, Kornysheva K* (2025). Neural state switch underlies the transition from movement preparation to execution in humans. bioRxiv. https://www.biorxiv.org/content/10.64898/2025.12.09.693175v1
Wright-Wieckowski H, Friedman J, Galea JM, Kornysheva K* (2025). Competitive pre-ordering during planning persists in kinematically fused sequential movements. bioRxiv. https://www.biorxiv.org/content/10.1101/2025.08.18.670892v1
Yewbrey R, Kornysheva K* (2024). The hippocampus pre-orders movements for skilled action sequences. Journal of Neuroscience. https://doi.org/10.1523/JNEUROSCI.0832-24.2024
Yewbrey R, Mantziara M, Kornysheva K* (2023). Cortical patterns shift from sequence feature separation during planning to integration during execution. Journal of Neuroscience. https://doi.org/10.1523/JNEUROSCI.1628-22.2023
Mantziara M, Ivanov T, Houghton G, Kornysheva K* (2021). Competitive state of movements during planning predicts sequence execution accuracy. Journal of Neurophysiology 125(4):1251-1268. https://doi.org/10.1152/jn.00645.2020
Kornysheva K*, Bush D, Meyer S, Sadnicka A, Burgess N, Barnes G (2019). Neural competitive queuing of ordinal structure underlies skilled sequential action. Neuron 101:1166-1180.e3. https://doi.org/10.1016/j.neuron.2019.01.018

Neural representation of skilled motor timing

Speaking, playing a musical instrument, using a tool - these skilled movements require a high degree of temporal precision to be performed successfully. How does the brain enable us to learn and store these patterns of movement timing? We aim to address the underlying neural mechanisms at the neuroimaging level in humans (fMRI, MEG, EEG) and at the single-cell level in the mouse model. Together with our collaborators, we are studying how different brain areas encode skilled timing and parse a complex action into its constituent components .

Kornysheva K* (2016). Encoding the temporal features of skilled movements - what, whether and how? Progress in Motor Control: Theories and Translations. Adv. Exp. Med. Biol. 957:35-54. https://doi.org/10.1007/978-3-319-47313-0_3
Diedrichsen J, Kornysheva K (2015). Motor skill learning between selection and execution. Trends in Cognitive Sciences 19(4):227-233. https://doi.org/10.1016/j.tics.2015.02.003
ten Brinke MM, Boele H-J, Spanke JK, Potters J-W, Kornysheva K, Wulff P, IJpelaar ACHG, Koekkoek SKE, De Zeeuw CI* (2015). Evolving models of Pavlovian conditioning: cerebellar cortical dynamics in awake behaving mice. Cell Reports 13(9):1977-1988. https://doi.org/10.1016/j.celrep.2015.10.057[cite: 1]
Kornysheva K*, Diedrichsen J (2014). Human premotor areas parse sequences into their spatial and temporal features. eLife 3:e03043. https://doi.org/10.7554/eLife.03043
Kornysheva K*, Sierk A, Diedrichsen J (2013). Interaction of temporal and ordinal representations in movement sequences. Journal of Neurophysiology 109(5):1416-1424. https://doi.org/10.1152/jn.00507.2012

Task-dependent dystonia

Together with collaborators at UCL/St George's, we are studying a condition that affects highly skilled action sequences selectively – task-specific dystonia (e.g. writer’s cramp, musician’s dystonia) – with no treatment being predictively effective. Our new framework considers task-specific dystonia in the context of motor skill representations in health, with the important implication for prevention and retraining.

Sadnicka A*, Kornysheva K*, Rothwell J, Edwards M (2018). A unifying motor control framework for task-specific dystonia. Nature Reviews Neurology 14(2):116-124. https://doi.org/10.1038/nrneurol.2017.146

Non-invasive brain-computer-interfaces for neurofeedback and prosthetics

In a cross-disciplinary seed collaboration funded by ESRC/MRC N-Code Seed we made a first step towards developing an EEG neurofeedback application that allows participants to monitor and learn to control action planning activity in real-time with the goal to optimise action performance (GitHub).

There is a major bottleneck of using EEG for skilled hand and arm neuroprosthetic control, often considered insurmountable. Our goal is to unlock the precision and scalability of non-invasive BCI research project funded by ARIA Opportunity Seed Scalable Neural Interfaces. This project is undertaken in collaboration with Oiwi Parker Jones and Ole Jensen from the University of Oxford.

Neural basis of sequence planning in Developmental Coordination Disorders/dyspraxia

Disorders of motor coordination such as dyspraxia/DCD affect the learning and control of skilled multi-movement sequences, as opposed to single movements. Unfortunately, current understanding of the neural etiology of DCD remains limited. Our goal is to utilise analytical approaches developed recently in our lab to assess the disruptions in motor planning by enabling a behavioural and neural ‘readout’ of the organisation of sequential movements before execution takes place. This line of work aims to prepare the ground for new occupational and non-invasive brain-computer-interface based interventions targeting the neural organisation of movements prior to execution.

Wright-Wieckowski H, Wilmut K, Kornysheva K* (2026). Developmental coordination disorder affects the pre-ordering of sequential movements. bioRxiv. https://www.biorxiv.org/content/10.64898/2026.06.12.731668v1

Auditory-motor integration of musical timing

Why do humans tend to move in synchrony with an auditory pulse, e.g. when they listen to music? What neural mechanisms give rise to the urge and ability to accurately couple one's own movements to an auditory rhythm?

We used functional magnetic resonance imaging (fMRI) and transcranial magnetic stimulation (TMS) to investigate how a motor-related brain region with prominent connections to auditory areas - the ventral premotor cortex (PMv) - contributes to auditory-motor integration of musical rhythm. Our findings demonstrate a critical role of the PMv in both perceptual preference of and motor coupling to a musical rhythm . By combining TMS and fMRI we could also reveal compensatory neural mechanisms after PMv disruption. PhD thesis

Kornysheva K*, Schubotz RI (2011). Impairment of auditory-motor timing and compensatory reorganization after ventral premotor cortex stimulation. PLOS ONE 6(6):e21421. https://doi.org/10.1371/journal.pone.0021421
Kornysheva K*, Schiffer AM, Schubotz RI (2011). Inhibitory stimulation of the ventral premotor cortex temporarily interferes with musical beat rate preference. Human Brain Mapping 32(8):1300-1310. https://doi.org/10.1002/hbm.21110
Kornysheva K*, von Cramon DY, Jacobsen T, Schubotz RI (2010). Tuning-in to the beat: Aesthetic appreciation of musical rhythms correlates with a premotor activity boost. Human Brain Mapping 31(1):48-64. https://doi.org/10.1002/hbm.20844

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