Browsing by Author "Nigam, Sunny"

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    A distinct population of heterogeneously color-tuned neurons in macaque visual cortex
    (AAAS, 2021) Nigam, Sunny; Pojoga, Sorin; Dragoi, Valentin
    Color is a key feature of natural environments that higher mammals routinely use to detect food, avoid predators, and interpret social signals. The distribution of color signals in natural scenes is widely variable, ranging from uniform patches to highly nonuniform regions in which different colors lie in close proximity. Whether individual neurons are tuned to this high degree of variability of color signals is unknown. Here, we identified a distinct population of cells in macaque visual cortex (area V4) that have a heterogeneous receptive field (RF) structure in which individual subfields are tuned to different colors even though the full RF is only weakly tuned. This spatial heterogeneity in color tuning indicates a higher degree of complexity of color-encoding mechanisms in visual cortex than previously believed to efficiently extract chromatic information from the environment. Diverse color tuning in V4 receptive fields points to its possible role in encoding complex color stimuli in natural environment. Diverse color tuning in V4 receptive fields points to its possible role in encoding complex color stimuli in natural environment.
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    Adaptive coding across visual features during free-viewing and fixation conditions
    (Springer Nature, 2023) Nigam, Sunny; Milton, Russell; Pojoga, Sorin; Dragoi, Valentin
    Theoretical studies have long proposed that adaptation allows the brain to effectively use the limited response range of sensory neurons to encode widely varying natural inputs. However, despite this influential view, experimental studies have exclusively focused on how the neural code adapts to a range of stimuli lying along a single feature axis, such as orientation or contrast. Here, we performed electrical recordings in macaque visual cortex (area V4) to reveal significant adaptive changes in the neural code of single cells and populations across multiple feature axes. Both during free viewing and passive fixation, populations of cells improved their ability to encode image features after rapid exposure to stimuli lying on orthogonal feature axes even in the absence of initial tuning to these stimuli. These results reveal a remarkable adaptive capacity of visual cortical populations to improve network computations relevant for natural viewing despite the modularity of the functional cortical architecture.