Dr Robin Ince
- Research Fellow (Centre for Cognitive Neuroimaging)
I develop and apply statistical methods for analysing data from behavioural, neuroimaging and electrophysiological experiments. I have a particular interest in practical applications of information theoretic methods.
I am interested in how information theory can let us relate different experimental variables to each other, quantifying redundant or synergistic representational interactions. For example, redundancy quantifies how much information about a stimulus overlaps between two neuroimaging recordings (e.g. different frequency bands, or different regions of the brain), or between a neuroimaging recording the participants behaviour. Synergy quantifies how much information available about the stimulus is available not from either response alone, but only when they are observed simultaneously, i.e. the relationship between them encodes or represents the stimulus. These tools can be combined with methods from machine learning and applied to applications such as multi-modal data fusion, quantifying behaviourally relevant neural representations, and measuring functional connectivity about specific stimulus features (e.g. communication).
- RAA Ince, BL Giordano, C Kayser, GA Rousselet, J Gross, PG Schyns
A statistical framework for neuroimaging data analysis based on mutual information estimated via a Gaussian copula
Human Brain Mapping (2017) 38 (3) p. 1541-1573
I am also interested in statistical methods that focus on effects within participants, rather than considering only the population mean as is common in the fields of psychology and neuroimaging.
- RAA Ince, JW Kay, PG Schyns
Bayesian inference of population prevalence
Grants and Awards listed are those received whilst working with the University of Glasgow.
- State of the art MEG-TRIUX-neo for advancing multi-modal neuroimaging techniques in Scotland
2020 - 2025
- Beyond Pairwise Connectivity: developing an information theoretic hypergraph methodology for multi-modal resting state neuroimaging analysis
2019 - 2021
Supervised Postgraduate Students
- Emra Baker (Postgraduate)
- Gina Brunner (Postgraduate)
- Xuan Cui (Postgraduate)
- Christoph Daube (Postgraduate)
- Yaocong Duan (Non Ψ Postgraduate)
- Edyta Koper (Postgraduate)
- Greta Mohr (Postgraduate)
- Haonan Niu (Postgraduate)
- Mahnaz Ashrafi Varnosfaderani (External Collaborator)
- Bruno Giordano (External Collaborator)
- Laura Imperatori (Visiting Researcher)
- Philippe G. Schyns