We measure human brain activity with high temporal and spatial resolution using electroencephalography (EEG), magnetoencephalography (MEG) and functional magnetic resonance imaging (fMRI). Working with our collaborators in Oxford and further afield, we also explore brain activity recorded directly with intracranial electrodes. By exploiting convergent methodologies, we are better able to overcome specific limitations inherent to any single approach.

The results of our research will provide a richer understanding of the fundamental neural mechanisms of attention and working memory, how they interact and how they influence perception and decision-making. Insights gained from this research will help inform neurophysiological accounts of high-level cognition, and help to develop new computational models grounded by the neurophysiology.

Selected Publications

Hall-McMaster, S., Muhle-Karbe,P. S., Myers, N. E., & Stokes, M. G. (2019). Reward boosts neural coding of task rules to optimise cognitive flexibility. bioRxiv,578468.

Wasmuht, D. F., Spaak, E., Buschman, T. J., Miller, E. K., & Stokes, M. G. (2018). Intrinsic neuronal dynamics predict distinct functional roles during working memory. Nature communications, 9(1), 3499.

Wolff, M. J., Jochim, J., Akyürek, E. G., & Stokes, M. G. (2017). Dynamic hidden states underlying working-memory-guided behavior. Nature neuroscience, 20(6), 864.

Spaak, E., Watanabe, K., Funahashi, S., & Stokes, M. G. (2017). Stable and dynamic coding for working memory in primate prefrontal cortex. Journal of Neuroscience, 3364-16.

Below is reported a short narrated video for Cognitive Neuroscience Compendium, in which Professor Mark Stokes illustrates that the retention of information in working memory may be accomplished by temporary changes in synaptic weights, creating so-called “hidden states,” a radical alternative to the traditional idea that the neural basis for short-term and working memory is sustained, elevated activity:
Relevant Paper:

Stokes, M. G., Kusunoki, M., Sigala, N., Nili, H., Gaffan, D., & Duncan, J. (2013). Dynamic coding for cognitive control in prefrontal cortex. Neuron, 78(2), 364-375.