Abstract
Accurate estimation of neuronal receptive fields is essential for understanding sensory processing in the early visual system. Yet a full characterization of receptive fields is still incomplete, especially with regard to natural visual stimuli and in complete populations of cortical neurons. While previous work has incorporated known structural properties of the early visual system, such as lateral connectivity, or imposing simple-cell-like receptive field structure, no study has exploited the fact that nearby V1 neurons share common feed-forward input from thalamus and other upstream cortical neurons. We introduce a new method for estimating receptive fields simultaneously for a population of V1 neurons, using a model-based analysis incorporating knowledge of the feed-forward visual hierarchy. We assume that a population of V1 neurons shares a common pool of thalamic inputs, and consists of two layers of simple and complex-like V1 neurons. When fit to recordings of a local population of mouse layer 2/3 V1 neurons, our model offers an accurate description of their response to natural images and significant improvement of prediction power over the current state-of-the-art methods. We show that the responses of a large local population of V1 neurons with locally diverse receptive fields can be described with surprisingly limited number of thalamic inputs, consistent with recent experimental findings. Our structural model not only offers an improved functional characterization of V1 neurons, but also provides a framework for studying the relationship between connectivity and function in visual cortical areas.
Highlights
The fundamental assumption underlying early sensory processing is that different external stimuli elicit distinct activity patterns that encode the content of the stimuli
Many models have been proposed in the past; these models have largely ignored the known architecture of primary visual cortex revealed in experimental studies, limiting their ability to PLOS Computational Biology | DOI:10.1371/journal.pcbi
We propose a model of primary visual cortex that takes into account the known architecture of visual cortex, the fact that only a limited number of thalamic inputs with stereotypical receptive fields are shared within a local area of visual cortex, and the hierarchical progression from neurons with linear receptive fields to neurons with non-linear receptive fields
Summary
The fundamental assumption underlying early sensory processing is that different external stimuli elicit distinct activity patterns that encode the content of the stimuli. The accuracy of the model can be determined by comparing the predicted and actual activities in responses to a novel stimulus set. This data-driven approach to describing stimulus response functions (e.g. spatio-temporal response functions, STRFs) of neurons in the visual system has been refined over the last four decades. Studies advanced to describing the response functions of less linear neurons (complex cells in primary visual cortex, and neurons in V2) [7,8] while using stimuli more representative of the natural environment, such as sequences or movies of natural scenes [9,10,11,12]. Even in V1, the modest response prediction accuracy from these models indicates that our current ability to characterize the stimulus response functions is incomplete [8,10,13]
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