St-Amand, D. | Search bioRxiv

bioRxiv2021

Transient inhibition to light explains stronger V1 responses to dark stimuli

Neurons in the primary visual cortex (V1) receive excitation and inhibition from distinct parallel pathways processing lightness (ON) and darkness (OFF). V1 neurons overall respond more strongly to dark than light stimuli, consistent with a preponderance of darker regions in natural images, as well as human psychophysics. However, it has been unclear whether this "dark-dominance" is due to more excitation from the OFF pathway or more inhibition from the ON pathway. To understand the mechanisms behind dark-dominance, we record electrophysiological responses of individual simple-type V1 neurons to natural image stimuli and then train biologically inspired convolutional neural networks to predict the neurons responses. Analyzing a sample of 74 neurons (in anesthetized, paralyzed cats) has revealed their responses to be more driven by dark than light stimuli, consistent with previous investigations. We show that this asymmetry is predominantly due to slower inhibition to dark stimuli rather than to stronger excitation from the thalamocortical OFF pathway. Consistent with dark-dominant neurons having faster responses than light-dominant neurons, we find dark-dominance to solely occur in the early latencies of neurons responses. Neurons that are strongly dark-dominated also tend to be less orientation selective. This novel approach gives us new insight into the dark-dominance phenomenon and provides an avenue to address new questions about excitatory and inhibitory integration in cortical neurons. SignificanceNeurons in the early visual cortex respond on average more strongly to dark than to light stimuli, but the mechanisms behind this bias have been unclear. Here we address this issue by combining single-unit electrophysiology with a novel machine learning model to analyze neurons responses to natural image stimuli in primary visual cortex. Using these techniques, we find slower inhibition to light than to dark stimuli to be the leading mechanism behind stronger dark responses. This slower inhibition to light might help explain other empirical findings, such as why orientation selectivity is weaker at earlier response latencies. These results demonstrate how imbalances in excitation vs. inhibition can give rise to response asymmetries in cortical neuron responses.

neuroscience↗

bioRxiv2021

Visual perception of texture regularity: conjoint measurements and a wavelet response-distribution model

Texture regularity, such as the repeating pattern in a carpet, brickwork or tree bark, is a ubiquitous feature of the visual world. The perception of regularity has generally been studied using multi-element textures in which the degree of regularity has been manipulated by adding random jitter to the elements positions. Here we used three-factor Maximum Likelihood Conjoint Measurement (MLCM) to investigate the encoding of regularity information under more complex conditions in which element spacing and size, in addition to positional jitter, were manipulated. Human observers were presented with large numbers of pairs of multi-element stimuli with varying levels of the three factors, and indicated on each trial which stimulus appeared more regular. All three factors contributed to regularity perception. Jitter, as expected, strongly affected regularity perception. This effect of jitter on regularity perception is strongest at small element spacing and large texture element size, suggesting that the visual system utilizes the edge-to-edge distance between elements as the basis for regularity judgments. We then examined how the responses of a bank of Gabor wavelet spatial filters might account for our results. Our analysis indicates that SF-peakedness, a previously favored proposal, is insufficient for regularity encoding since it varied more with element spacing and size than with jitter. Instead, our results support the idea that the visual system may extract texture regularity information from the moments of the SF-distribution across orientation. In our best-performing model, the variance of SF-distribution skew across orientations can explain 70% of the variance of estimated texture regularity from our data, suggesting that it could provide a candidate readout for perceived regularity. Author SummaryWe investigated human perception of texture regularity, in which subjects made comparative judgements of regularity in pairs of texture stimuli with differing levels of three parameters of texture construction - spacing and size of texture elements, and their positional jitter. We analyzed the data using a novel approach involving three-factor Maximum Likelihood Conjoint Measurement (MLCM). We utilized a novel analysis-of-variance approach in MLCM to evaluate the effect size and significance of the three factors as well as their interactions. We found that all three factors contributed to perceived regularity, with significant main effects and interactions between factors, in a manner suggesting edge-to-edge distances between elements might contribute importantly to regularity judgments. Using a bank of Gabor wavelet spatial filters to model the response of the human visual system to our textures, we compared four types of ways that the distribution of wavelet responses could account for our measured data on perceived regularity. Our results suggest that the orientation as well as spatial frequency information from the wavelet filters also contributes importantly - in particular, the skew of the variance of the SF-distribution across orientation provides a candidate basis for perceived texture regularity.

neuroscience↗