Predictability-dependent encoding of statistical regularities in the early visual cortex

Previous research recognized that humans could extract statistical regularities of the environment to automatically predict upcoming events. However, it has remained unexplored how the brain encodes the distribution of statistical regularities if it continuously changes. To investigate this question, we devised an fMRI paradigm where participants (N = 32) completed a visual four-choice reaction time (RT) task consisting of statistical regularities. Two types of blocks involving the same perceptual elements alternated with one another throughout the task: While the distribution of statistical regularities was predictable in one block type, it was unpredictable in the other. Participants were unaware of the presence of statistical regularities and of their changing distribution across the subsequent task blocks. Based on the RT results, although statistical regularities were processed similarly in both the predictable and unpredictable blocks, participants acquired less statistical knowledge in the unpredictable as compared with the predictable blocks. Whole-brain random-effects analyses showed increased activity in the early visual cortex and decreased activity in the precuneus for the predictable as compared with the unpredictable blocks. Therefore, the actual predictability of statistical regularities is likely to be represented already at the early stages of visual cortical processing. However, decreased precuneus activity suggests that these representations are imperfectly updated to track the multiple shifts in predictability throughout the task. The results also highlight that the processing of statistical regularities in a changing environment could be habitual.

Neurons in the pigeon visual network discriminate between faces, scrambled faces, and sine grating images

Discriminating between object categories (e.g., conspecifics, food, potential predators) is a critical function of the primate and bird visual systems. We examined whether a similar hierarchical organization in the ventral stream that operates for processing faces in monkeys also exists in the avian visual system. We performed electrophysiological recordings from the pigeon Wulst of the thalamofugal pathway, in addition to the entopallium (ENTO) and mesopallium ventrolaterale (MVL) of the tectofugal pathway, while pigeons viewed images of faces, scrambled controls, and sine gratings. A greater proportion of MVL neurons fired to the stimuli, and linear discriminant analysis revealed that the population response of MVL neurons distinguished between the stimuli with greater capacity than ENTO and Wulst neurons. While MVL neurons displayed the greatest response selectivity, in contrast to the primate system no neurons were strongly face-selective and some responded best to the scrambled images. These findings suggest that MVL is primarily involved in processing the local features of images, much like the early visual cortex.

Relative precision of top-down attentional modulations is lower in early visual cortex compared to mid- and high-level visual areas

Top-down spatial attention enhances cortical representations of behaviorally relevant visual information and increases the precision of perceptual reports. However, little is known about the relative precision of top-down attentional modulations in different visual areas, especially compared to the highly precise stimulus-driven responses that are observed in early visual cortex. For example, the precision of attentional modulations in early visual areas may be limited by the relatively coarse spatial selectivity and the anatomical connectivity of the areas in prefrontal cortex that generate and relay the top-down signals. Here, we used fMRI and human participants to assess the precision of bottom-up spatial representations evoked by high contrast stimuli across the visual hierarchy. Then, we examined the relative precision of top-down attentional modulations in the absence of spatially-specific bottom-up drive. While V1 showed the largest relative difference between the precision of top-down attentional modulations and the precision of bottom-up modulations, mid-level areas such as V4 showed relatively smaller differences between the precision of top-down and bottom-up modulations. Overall, this interaction between visual areas (e.g. V1 vs V4) and the relative precision of top-down and bottom-up modulations suggests that the precision of top-down attentional modulations is limited by the representational fidelity of areas that generate and relay top-down feedback signals.

Benchmarking GE-BOLD, SE-BOLD, and SS-SI-VASO sequences for depth-dependent separation of feedforward and feedback signals in high-field MRI

Recent advances in high-field fMRI have allowed differentiating feedforward and feedback information in the grey matter of the human brain. For continued progress in this endeavor, it is critical to understand how MRI data acquisition parameters impact the read-out of information from laminar response profiles. Here, we benchmarked three different MR-sequences at 7T - gradient-echo (GE), spin-echo (SE) and vascular space occupancy imaging (VASO) - in differentiating feedforward and feedback signals in human early visual cortex (V1). The experiment (N=4) consisted of two complementary tasks: a perception task that predominantly evokes feedforward signals and a working memory task that relies on feedback signals. In the perception task, participants saw flickering oriented gratings while detecting orthogonal color-changes. In the working memory task, participants memorized the precise orientation of a grating. We used multivariate pattern analysis to read out the perceived (feedforward) and memorized (feedback) grating orientation from neural signals across cortical depth. Analyses across all the MR-sequences revealed perception signals predominantly in the middle cortical compartment of area V1 and working memory signals in the deep compartment. Despite an overall consistency across sequences, SE-EPI was the only sequence where both feedforward and feedback information were differently pronounced across cortical depth in a statistically robust way. We therefore suggest that in the context of a typical cognitive neuroscience experiment as the one benchmarked here, SE-EPI may provide a favorable trade-off between spatial specificity and signal sensitivity.

Human visual gamma for color stimuli: When LGN drive is equalized, red is not special

Strong gamma-band oscillations in primate early visual cortex can be induced by spatially homogeneous, high-contrast stimuli, such as color surfaces. Compared to other hues, particularly strong gamma oscillations have been reported for red stimuli. However, precortical color processing and the resultant strength of input to V1 has often not been fully controlled for. This leaves the possibility that stronger responses to some hues were due to differences in V1 input strength. We presented stimuli that had equal luminance and color contrast levels in a color coordinate system based on color responses of the lateral geniculate nucleus, the main input source for area V1. With these stimuli, we recorded magnetoencephalography in 30 human subjects. We found narrowband color-induced gamma oscillations in early visual cortex, which, contrary to previous reports, did not differ between red and green stimuli of equal L-M cone contrast. Notably, blue stimuli with contrast exclusively on the S cone axis induced very weak gamma responses, as well as smaller event-related fields and poorer change detection performance. The strength of human color gamma responses could be well explained by the strength of thalamic input induced by each hue and does not show a clear red bias when this input strength is properly equalized.

Visual exposure enhances stimulus encoding and persistence in primary cortex

The brain adapts to the sensory environment. For example, simple sensory exposure can modify the response properties of early sensory neurons. How these changes affect the overall encoding and maintenance of stimulus information across neuronal populations remains unclear. We perform parallel recordings in the primary visual cortex of anesthetized cats and find that brief, repetitive exposure to structured visual stimuli enhances stimulus encoding by decreasing the selectivity and increasing the range of the neuronal responses that persist after stimulus presentation. Low-dimensional projection methods and simple classifiers demonstrate that visual exposure increases the segregation of persistent neuronal population responses into stimulus-specific clusters. These observed refinements preserve the representational details required for stimulus reconstruction and are detectable in postexposure spontaneous activity. Assuming response facilitation and recurrent network interactions as the core mechanisms underlying stimulus persistence, we show that the exposure-driven segregation of stimulus responses can arise through strictly local plasticity mechanisms, also in the absence of firing rate changes. Our findings provide evidence for the existence of an automatic, unguided optimization process that enhances the encoding power of neuronal populations in early visual cortex, thus potentially benefiting simple readouts at higher stages of visual processing.

Top-down predictions of visual features dynamically reverse their bottom-up processing in the occipito-ventral pathway to facilitate stimulus disambiguation and behavior

The prevalent conception of vision-for-categorization suggests an interplay of two dynamic flows of information within the occipito-ventral pathway. The bottom-up flow progressively reduces the high-dimensional input into a lower-dimensional representation that is compared with memory to produce categorization behavior. The top-down flow predicts category information (i.e. features) from memory that propagates down the same hierarchy to facilitate input processing and behavior. However, the neural mechanisms that support such dynamic feature propagation up and down the visual hierarchy and how they facilitate behavior remain unclear. Here, we studied them using a prediction experiment that cued participants (N = 11) to the spatial location (left vs. right) and spatial frequency (SF, Low, LSF, vs. High, HSF) contents of an upcoming Gabor patch. Using concurrent MEG recordings of each participant's neural activity, we compared the top-down flow of representation of the predicted Gabor contents (i.e. left vs. right; LSF vs. HSF) to their bottom-up flow. We show (1) that top-down prediction improves speed of categorization in all participants, (2) the top-down flow of prediction reverses the bottom-up representation of the Gabor stimuli, going from deep right fusiform gyrus sources down to occipital cortex sources contra-lateral to the expected Gabor location and (3) that predicted Gabors are better represented when the stimulus is eventually shown, leading to faster categorizations. Our results therefore trace the dynamic top-down flow of a predicted visual content that chronologically and hierarchically reversed bottom-up processing, further facilitates visual representations in early visual cortex and subsequent categorization behavior.