Technical Program

Paper Detail

Paper: PS-2A.25
Session: Poster Session 2A
Location: Symphony/Overture
Session Time: Friday, September 7, 17:15 - 19:15
Presentation Time:Friday, September 7, 17:15 - 19:15
Presentation: Poster
Publication: 2018 Conference on Cognitive Computational Neuroscience, 5-8 September 2018, Philadelphia, Pennsylvania
Paper Title: Linking neural representations for decision-making between monkey and human cortex
Manuscript:  Click here to view manuscript
Authors: Paula Kaanders, Hamed Nili, Tim Behrens, Laurence Hunt, University of Oxford, United Kingdom
Abstract: Neuroscience has struggled to link animal models to human brain functioning. Hunt et al. (2017) identified a triple functional dissociation in prefrontal cortex (PFC) using single-cell recordings from macaque during an information gathering task. We attempt to find a similar dissociation in the human brain using functional magnetic resonance imaging (fMRI) during a similar task using two approaches: mass univariate analysis and representational similarity analysis (RSA). In a mass univariate analysis, we find evidence of a belief confirmation signal in ACC, consistent with that identified in single cell recordings in the same task. Using RSA, we successfully produced clear representational geometries in primary visual cortex and the fusiform gyrus for spatial location and cue type (face/house) respectively. However, we found no clear relationships between RSA matrices in anatomical regions of interest for dlPFC, OFC or ACC, in contrast to what was found in the macaque data. These findings do not completely rule out RSA as a means of mapping animal and human data to a common space in PFC, as there is still much space for further exploration of the data.