Dynamic causal modelling of lateral interactions in the visual cortex

• Published in: NeuroImage (Orlando, Fla.) Vol. 66; pp. 563 - 576
• Main Authors: Pinotsis, D.A., Schwarzkopf, D.S., Litvak, V., Rees, G., Barnes, G., Friston, K.J.
• Format: Journal Article
• Language: English
• Published: Amsterdam Elsevier Inc 01.02.2013; Elsevier; Elsevier Limited; Academic Press
• Subjects: Algorithms; Biological and medical sciences; Brain Mapping; Circuits; Computer Simulation; Connectivity; Dynamic causal modelling; Electrophysiology; Eye and associated structures. Visual pathways and centers. Vision; Fundamental and applied biological sciences. Psychology; Humans; Magnetoencephalography; MEG; Models, Neurological; Neural field theory; Neurosciences; Population; Propagation; Sensors; Vertebrates: nervous system and sense organs; Visual cortex; Visual Cortex - physiology; Electrophysiology; Connectivity; Visual cortex; Neural field theory; MEG; Dynamic causal modelling; Visual pathway; Magnetoencephalography; Central nervous system; Encephalon
• ISSN: 1053-8119; 1095-9572; 1095-9572
• DOI: 10.1016/j.neuroimage.2012.10.078

This paper presents a dynamic causal model based upon neural field models of the Amari type. We consider the application of these models to non-invasive data, with a special focus on the mapping from source activity on the cortical surface to a single channel. We introduce a neural field model based upon the canonical microcircuit (CMC), in which neuronal populations are assigned to different cortical layers. We show that DCM can disambiguate between alternative (neural mass and field) models of cortical activity. However, unlike neural mass models, DCM with neural fields can address questions about neuronal microcircuitry and lateral interactions. This is because they are equipped with interlaminar connections and horizontal intra-laminar connections that are patchy in nature. These horizontal or lateral connections can be regarded as connecting macrocolumns with similar feature selectivity. Crucially, the spatial parameters governing horizontal connectivity determine the separation (width) of cortical macrocolumns. Thus we can estimate the width of macro columns, using non-invasive electromagnetic signals. We illustrate this estimation using dynamic causal models of steady-state or ongoing spectral activity measured using magnetoencephalography (MEG) in human visual cortex. Specifically, we revisit the hypothesis that the size of a macrocolumn is a key determinant of neuronal dynamics, particularly the peak gamma frequency. We are able to show a correlation, over subjects, between columnar size and peak gamma frequency — that fits comfortably with established correlations between peak gamma frequency and the size of visual cortex defined retinotopically. We also considered cortical excitability and assessed its relative influence on observed gamma activity. This example highlights the potential utility of dynamic causal modelling and neural fields in providing quantitative characterisations of spatially extended dynamics on the cortical surface — that are parameterised in terms of horizontal connections, implicit in the cortical micro-architecture and its synaptic parameters. ► New neural field model of canonical cortical microcircuitry ► Modelling of vertical interlaminar and horizontal intralaminar connections ► Estimation of the width of macrocolumns using non-invasive (MEG) signals ► Assessment of influence of cortical excitability and microcircuitry to gamma peak ► Mechanistic approach to correlations among cortical structure and function.