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  1. Article ; Online: Topographically Localized Modulation of Tectal Cell Spatial Tuning by Complex Natural Scenes.

    Sainsbury, Thomas T J / Diana, Giovanni / Meyer, Martin P

    eNeuro

    2023  Volume 10, Issue 1

    Abstract: The tuning properties of neurons in the visual system can be contextually modulated by the statistics of the area surrounding their receptive field (RF), particularly when the surround contains natural features. However, stimuli presented in specific ... ...

    Abstract The tuning properties of neurons in the visual system can be contextually modulated by the statistics of the area surrounding their receptive field (RF), particularly when the surround contains natural features. However, stimuli presented in specific egocentric locations may have greater behavioral relevance, raising the possibility that the extent of contextual modulation may vary with position in visual space. To explore this possibility, we utilized the small size and optical transparency of the larval zebrafish to describe the form and spatial arrangement of contextually modulated cells throughout an entire tectal hemisphere. We found that the spatial tuning of tectal neurons to a prey-like stimulus sharpens when the stimulus is presented against a background with the statistics of complex natural scenes, relative to a featureless background. These neurons are confined to a spatially restricted region of the tectum and have receptive fields centered within a region of visual space in which the presence of prey preferentially triggers hunting behavior. Our results suggest that contextual modulation of tectal neurons by complex backgrounds may facilitate prey-localization in cluttered visual environments.
    MeSH term(s) Animals ; Superior Colliculi/physiology ; Zebrafish ; Vision, Ocular ; Neurons/physiology ; Photic Stimulation
    Language English
    Publishing date 2023-01-06
    Publishing country United States
    Document type Journal Article ; Research Support, Non-U.S. Gov't
    ZDB-ID 2800598-3
    ISSN 2373-2822 ; 2373-2822
    ISSN (online) 2373-2822
    ISSN 2373-2822
    DOI 10.1523/ENEURO.0223-22.2022
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  2. Article ; Online: Bayesian inference of neuronal assemblies.

    Diana, Giovanni / Sainsbury, Thomas T J / Meyer, Martin P

    PLoS computational biology

    2019  Volume 15, Issue 10, Page(s) e1007481

    Abstract: In many areas of the brain, both spontaneous and stimulus-evoked activity can manifest as synchronous activation of neuronal assemblies. The characterization of assembly structure and dynamics provides important insights into how brain computations are ... ...

    Abstract In many areas of the brain, both spontaneous and stimulus-evoked activity can manifest as synchronous activation of neuronal assemblies. The characterization of assembly structure and dynamics provides important insights into how brain computations are distributed across neural networks. The proliferation of experimental techniques for recording the activity of neuronal assemblies calls for a comprehensive statistical method to describe, analyze and characterize these high dimensional datasets. The performance of existing methods for defining assemblies is sensitive to noise and stochasticity in neuronal firing patterns and assembly heterogeneity. To address these problems, we introduce a generative hierarchical model of synchronous activity to describe the organization of neurons into assemblies. Unlike existing methods, our analysis provides a simultaneous estimation of assembly composition, dynamics and within-assembly statistical features, such as the levels of activity, noise and assembly synchrony. We have used our method to characterize population activity throughout the tectum of larval zebrafish, allowing us to make statistical inference on the spatiotemporal organization of tectal assemblies, their composition and the logic of their interactions. We have also applied our method to functional imaging and neuropixels recordings from the mouse, allowing us to relate the activity of identified assemblies to specific behaviours such as running or changes in pupil diameter.
    MeSH term(s) Action Potentials/physiology ; Animals ; Bayes Theorem ; Data Interpretation, Statistical ; Larva ; Models, Neurological ; Models, Statistical ; Nerve Net/metabolism ; Nerve Net/physiology ; Neurons/physiology ; Zebrafish
    Language English
    Publishing date 2019-10-31
    Publishing country United States
    Document type Journal Article ; Research Support, Non-U.S. Gov't
    ZDB-ID 2193340-6
    ISSN 1553-7358 ; 1553-734X
    ISSN (online) 1553-7358
    ISSN 1553-734X
    DOI 10.1371/journal.pcbi.1007481
    Database MEDical Literature Analysis and Retrieval System OnLINE

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    This service is chargeable due to the Delivery terms set by subito. Orders including an article and supplementary material will be classified as separate orders. In these cases, fees will be demanded for each order.

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