In the last thirty years we have learned a great deal from functional brain imaging about the neurobiology of language. Much of this knowledge has been derived from asking participants to attend to a particular kind of stimulus or task and observing where brain activity is increased relative to doing nothing or attending to a different stimulus or task. This is useful as it tells us which brain areas are associated with different tasks and stimuli, but it doesn't tell us much about how cognition emerges from neural activity.
Recent advances in human functional brain imaging, that draw upon the fields of machine learning and artificial intelligence, allow us to test hypotheses concerning the function of different brain regions using computational models derived from theory, behaviour and stimulus features. This allows us to move beyond the simple mapping of tasks and stimuli to particular brain areas, to ask what kind of information is represented in activated brain regions and to test our predictions of how we think the brain works.
We apply these techniques to provide novel insights into how the brain comprehends language, specifically auditory speech, visual speech and sign language. We address this from two perspectives: (1) How the brain adapts to different language signals and (2) How brain systems differ between individuals.
Recent advances in human functional brain imaging, that draw upon the fields of machine learning and artificial intelligence, allow us to test hypotheses concerning the function of different brain regions using computational models derived from theory, behaviour and stimulus features. This allows us to move beyond the simple mapping of tasks and stimuli to particular brain areas, to ask what kind of information is represented in activated brain regions and to test our predictions of how we think the brain works.
We apply these techniques to provide novel insights into how the brain comprehends language, specifically auditory speech, visual speech and sign language. We address this from two perspectives: (1) How the brain adapts to different language signals and (2) How brain systems differ between individuals.
Key publications:
Evans, S., Price, C.J., Diedrichsen, J., Gutierrez-Sigut, E. & MacSweeney, M. 2019. Evidence for shared representations for sign and speech. BioRxiv.
Evans, S. and McGettigan, C. 2017. Comprehending auditory speech: previous and potential contributions of functional MRI. Language, Cognition and Neuroscience. 32 (7), pp. 829-846.
Evans, S. and Davis, M.H. 2015. Hierarchical organization of auditory and motor representations in speech perception: Evidence from searchlight similarity analysis. Cerebral Cortex. 25 (12), pp. 4772-4788.
*Evans, S., *Kyong, J.S., Rosen, S., Golestani, N., Warren, J.E., McGettigan, C., Mourão-Miranda, J., Wise, R.J.S. and Scott, S.K. 2014. The Pathways for Intelligible Speech: Multivariate and Univariate Perspectives . Cerebral Cortex. 24 (9).
Evans, S., Price, C.J., Diedrichsen, J., Gutierrez-Sigut, E. & MacSweeney, M. 2019. Evidence for shared representations for sign and speech. BioRxiv.
Evans, S. and McGettigan, C. 2017. Comprehending auditory speech: previous and potential contributions of functional MRI. Language, Cognition and Neuroscience. 32 (7), pp. 829-846.
Evans, S. and Davis, M.H. 2015. Hierarchical organization of auditory and motor representations in speech perception: Evidence from searchlight similarity analysis. Cerebral Cortex. 25 (12), pp. 4772-4788.
*Evans, S., *Kyong, J.S., Rosen, S., Golestani, N., Warren, J.E., McGettigan, C., Mourão-Miranda, J., Wise, R.J.S. and Scott, S.K. 2014. The Pathways for Intelligible Speech: Multivariate and Univariate Perspectives . Cerebral Cortex. 24 (9).