Exploring spatiotemporal neural dynamics of the human visual cortex

Abstract

The human visual cortex is organized in a hierarchical manner. Although previous evidence supporting this hypothesis has been accumulated, specific details regarding the spatiotemporal information flow remain open. Here we present detailed spatiotemporal correlation profiles of neural activity with low‐level and high‐level features derived from an eight‐layer neural network pretrained for object recognition. These correlation profiles indicate an early‐to‐late shift from low‐level features to high‐level features and from low‐level regions to higher‐level regions along the visual hierarchy, consistent with feedforward information flow. Additionally, we computed three sets of features from the low‐ and high‐level features provided by the neural network: object‐category‐relevant low‐level features (the common components between low‐level and high‐level features), low‐level features roughly orthogonal to high‐level features (the residual Layer 1 features), and unique high‐level features that were roughly orthogonal to low‐level features (the residual Layer 7 features). Contrasting the correlation effects of the common components and the residual Layer 1 features, we observed that the early visual cortex (EVC) exhibited a similar amount of correlation with the two feature sets early in time, but in a later time window, the EVC exhibited a higher and longer correlation effect with the common components (i.e., the low‐level object‐category‐relevant features) than with the low‐level residual features—an effect unlikely to arise from purely feedforward information flow. Overall, our results indicate that non‐feedforward processes, for example, top‐down influences from mental representations of categories, may facilitate differentiation between these two types of low‐level features within the EVC.

Memory influences visual cognition across multiple functional states of interactive cortical dynamics

“…MUSI and related accounts propose that higher-order or complex cognition, decisions, fine discriminations, and awareness (e.g., phenomenological consciousness) require additional neural computations involving later local recurrent, feedback and inter-areal contributions to perceptual information processing (Bradski & Grossberg, 1995;David et al, 2005;Enns & Lleras, 2008;Grossberg, 1999;Hochstein & Ahissar, 2002;Lamme, 2003;T. S. Lee, Yang, Romero, & Mumford, 2002;Lowe, 2000;Mumford, 1992;Treisman, 2006;Ullman, 1995;Yang, Tarr, Kass, & Aminoff, 2019). The initial feedforward sweep through the ventral visual stream does not, itself, compute the actual target or category decision.…”

“…These limitations led some to suggest that the bottom-up pathway provides the initial input and object hypothesis to test using subsequent top-down processes of PHT (Serre, Wolf, et al, 2007). Further, computational modeling increasingly supports a critical role for top-down influences about category knowledge on lower-level cortex (e.g., Yang et al, 2019).…”

Brainprints: identifying individuals from magnetoencephalograms

“…It would be a stronger piece of evidence if we show that brainprints can identify individuals during two visits to different centers with different recording modalities. We looked at MEG and EEG (electroencephalography) data of 14 participants viewing scene images (362 trials for each individual, one trial lasted 1 s), obtained from [32]. Both MEG and EEG were recorded for the exact same stimuli, but on different days for each participant, making it an ideal testbed to verify the consistency of brainprints across different imaging modalities.…”

Cross-Population Amplitude Coupling in High-Dimensional Oscillatory Neural Time Series

“…7b? It is possible, but it would be surprising, especially when we consider contemporary ideas about beta oscillations during working memory tasks (Miller, Lundqvist and Bastos, 2018) along with the well-identified distinction between early and late visual processing, e.g., Yang et al (2019). The alternative we mentioned, that PFC and V4 are involved, together, in goaldirected visual processing and memory, with PFC influencing V4 early and the two areas acting bidirectionally later, seems a credible possibility.…”