Abstract
A neural field model is presented that captures the essential non-linear characteristics of activity dynamics across several millimeters of visual cortex in response to local flashed and moving stimuli. We account for physiological data obtained by voltage-sensitive dye (VSD) imaging which reports mesoscopic population activity at high spatio-temporal resolution. Stimulation included a single flashed square, a single flashed bar, the line-motion paradigm – for which psychophysical studies showed that flashing a square briefly before a bar produces sensation of illusory motion within the bar – and moving squares controls. We consider a two-layer neural field (NF) model describing an excitatory and an inhibitory layer of neurons as a coupled system of non-linear integro-differential equations. Under the assumption that the aggregated activity of both layers is reflected by VSD imaging, our phenomenological model quantitatively accounts for the observed spatio-temporal activity patterns. Moreover, the model generalizes to novel similar stimuli as it matches activity evoked by moving squares of different speeds. Our results indicate that feedback from higher brain areas is not required to produce motion patterns in the case of the illusory line-motion paradigm. Physiological interpretation of the model suggests that a considerable fraction of the VSD signal may be due to inhibitory activity, supporting the notion that balanced intra-layer cortical interactions between inhibitory and excitatory populations play a major role in shaping dynamic stimulus representations in the early visual cortex.
Highlights
Visual cortical activity does not exclusively mirror visual input but rather reflects the contribution of additional recurrent processes involving lateral and local feedback couplings
This study shows 1) how a concise neural field model can simulate voltage-sensitive dye (VSD) data quantitatively in space and time by identifying the underlying non-linear dynamics, 2) how such a model can support hypotheses about visual information processing, and 3) how the model can be linked to the neuronal architecture
Our proposed dynamical system is an abstract functional description of in vivo recorded VSD dynamics that correlate with changes in potentials across neuronal membranes and reflect the mass activity of a large pool of neurons
Summary
Visual cortical activity does not exclusively mirror visual input but rather reflects the contribution of additional recurrent processes involving lateral and local feedback couplings. Understanding cortical processing requires a theoretical understanding of the underlying activity dynamics, which can be attained by modeling at various levels of abstraction. The activity patterns observed using voltage-sensitive dye (VSD) imaging reflect population activity at the mesoscopic (intra-areal) level [2,3]. This suggests the application of mean-field models in which large numbers of neurons are averaged. The model is an abstract functional description of VSDrecorded dynamics. It is in the first place phenomenological. Its interpretation in biological terms allows to link its structure and parameters to the neuronal functional architecture
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