The Experts below are selected from a list of 98154 Experts worldwide ranked by ideXlab platform

Mark T. Harnett - One of the best experts on this subject based on the ideXlab platform.

  • representation of visual landmarks in retrosplenial cortex
    eLife, 2020
    Co-Authors: Lukas F Fischer, Friederike Buck, Raul Mojica Sotoalbors, Mark T. Harnett
    Abstract:

    The process by which visual information is incorporated into the brain's spatial framework to represent landmarks is poorly understood. Studies in humans and rodents suggest that retrosplenial cortex (RSC) plays a key role in these computations. We developed an RSC-dependent Behavioral Task in which head-fixed mice learned the spatial relationship between visual landmark cues and hidden reward locations. Two-photon imaging revealed that these cues served as dominant reference points for most Task-active neurons and anchored the spatial code in RSC. This encoding was more robust after Task acquisition. Decoupling the virtual environment from mouse behavior degraded spatial representations and provided evidence that supralinear integration of visual and motor inputs contributes to landmark encoding. V1 axons recorded in RSC were less modulated by Task engagement but showed surprisingly similar spatial tuning. Our data indicate that landmark representations in RSC are the result of local integration of visual, motor, and spatial information.

  • Representation of Visual Landmarks in Retrosplenial Cortex
    2019
    Co-Authors: Lukas F Fischer, Raul Mojica Soto-albors, Friederike Buck, Mark T. Harnett
    Abstract:

    Abstract The process by which visual information is incorporated into the brain’s spatial framework to represent landmarks is poorly understood. Studies in humans and rodents suggest that retrosplenial cortex (RSC) plays a key role in these computations. We developed an RSC-dependent Behavioral Task in which head-fixed mice learned the spatial relationship between visual landmark cues and hidden reward locations. Two-photon imaging revealed that these cues served as dominant reference points for most Task-active neurons and anchored the spatial code in RSC. Presenting the same environment but decoupled from mouse behavior degraded encoding fidelity. Analyzing visual and motor responses showed that landmark codes were the result of supralinear integration. Surprisingly, V1 axons recorded in RSC showed similar receptive fields. However, they were less modulated by Task engagement, indicating that landmark representations in RSC are the result of local computations. Our data provide cellular- and network-level insight into how RSC represents landmarks.

Maneesh Sahani - One of the best experts on this subject based on the ideXlab platform.

  • learning enhances sensory and multiple non sensory representations in primary visual cortex
    Neuron, 2015
    Co-Authors: Jasper Poort, Adil G Khan, Marius Pachitariu, Abdellatif Nemri, Ivana Orsolic, Julija Krupic, Marius Bauza, Maneesh Sahani
    Abstract:

    We determined how learning modifies neural representations in primary visual cortex (V1) during acquisition of a visually guided Behavioral Task. We imaged the activity of the same layer 2/3 neuronal populations as mice learned to discriminate two visual patterns while running through a virtual corridor, where one pattern was rewarded. Improvements in Behavioral performance were closely associated with increasingly distinguishable population-level representations of Task-relevant stimuli, as a result of stabilization of existing and recruitment of new neurons selective for these stimuli. These effects correlated with the appearance of multiple Task-dependent signals during learning: those that increased neuronal selectivity across the population when expert animals engaged in the Task, and those reflecting anticipation or Behavioral choices specifically in neuronal subsets preferring the rewarded stimulus. Therefore, learning engages diverse mechanisms that modify sensory and non-sensory representations in V1 to adjust its processing to Task requirements and the Behavioral relevance of visual stimuli.

Adil G Khan - One of the best experts on this subject based on the ideXlab platform.

  • learning enhances sensory and multiple non sensory representations in primary visual cortex
    Neuron, 2015
    Co-Authors: Jasper Poort, Adil G Khan, Marius Pachitariu, Abdellatif Nemri, Ivana Orsolic, Julija Krupic, Marius Bauza, Maneesh Sahani
    Abstract:

    We determined how learning modifies neural representations in primary visual cortex (V1) during acquisition of a visually guided Behavioral Task. We imaged the activity of the same layer 2/3 neuronal populations as mice learned to discriminate two visual patterns while running through a virtual corridor, where one pattern was rewarded. Improvements in Behavioral performance were closely associated with increasingly distinguishable population-level representations of Task-relevant stimuli, as a result of stabilization of existing and recruitment of new neurons selective for these stimuli. These effects correlated with the appearance of multiple Task-dependent signals during learning: those that increased neuronal selectivity across the population when expert animals engaged in the Task, and those reflecting anticipation or Behavioral choices specifically in neuronal subsets preferring the rewarded stimulus. Therefore, learning engages diverse mechanisms that modify sensory and non-sensory representations in V1 to adjust its processing to Task requirements and the Behavioral relevance of visual stimuli.

Abdellatif Nemri - One of the best experts on this subject based on the ideXlab platform.

  • learning enhances sensory and multiple non sensory representations in primary visual cortex
    Neuron, 2015
    Co-Authors: Jasper Poort, Adil G Khan, Marius Pachitariu, Abdellatif Nemri, Ivana Orsolic, Julija Krupic, Marius Bauza, Maneesh Sahani
    Abstract:

    We determined how learning modifies neural representations in primary visual cortex (V1) during acquisition of a visually guided Behavioral Task. We imaged the activity of the same layer 2/3 neuronal populations as mice learned to discriminate two visual patterns while running through a virtual corridor, where one pattern was rewarded. Improvements in Behavioral performance were closely associated with increasingly distinguishable population-level representations of Task-relevant stimuli, as a result of stabilization of existing and recruitment of new neurons selective for these stimuli. These effects correlated with the appearance of multiple Task-dependent signals during learning: those that increased neuronal selectivity across the population when expert animals engaged in the Task, and those reflecting anticipation or Behavioral choices specifically in neuronal subsets preferring the rewarded stimulus. Therefore, learning engages diverse mechanisms that modify sensory and non-sensory representations in V1 to adjust its processing to Task requirements and the Behavioral relevance of visual stimuli.

Lukas F Fischer - One of the best experts on this subject based on the ideXlab platform.

  • representation of visual landmarks in retrosplenial cortex
    eLife, 2020
    Co-Authors: Lukas F Fischer, Friederike Buck, Raul Mojica Sotoalbors, Mark T. Harnett
    Abstract:

    The process by which visual information is incorporated into the brain's spatial framework to represent landmarks is poorly understood. Studies in humans and rodents suggest that retrosplenial cortex (RSC) plays a key role in these computations. We developed an RSC-dependent Behavioral Task in which head-fixed mice learned the spatial relationship between visual landmark cues and hidden reward locations. Two-photon imaging revealed that these cues served as dominant reference points for most Task-active neurons and anchored the spatial code in RSC. This encoding was more robust after Task acquisition. Decoupling the virtual environment from mouse behavior degraded spatial representations and provided evidence that supralinear integration of visual and motor inputs contributes to landmark encoding. V1 axons recorded in RSC were less modulated by Task engagement but showed surprisingly similar spatial tuning. Our data indicate that landmark representations in RSC are the result of local integration of visual, motor, and spatial information.

  • Representation of Visual Landmarks in Retrosplenial Cortex
    2019
    Co-Authors: Lukas F Fischer, Raul Mojica Soto-albors, Friederike Buck, Mark T. Harnett
    Abstract:

    Abstract The process by which visual information is incorporated into the brain’s spatial framework to represent landmarks is poorly understood. Studies in humans and rodents suggest that retrosplenial cortex (RSC) plays a key role in these computations. We developed an RSC-dependent Behavioral Task in which head-fixed mice learned the spatial relationship between visual landmark cues and hidden reward locations. Two-photon imaging revealed that these cues served as dominant reference points for most Task-active neurons and anchored the spatial code in RSC. Presenting the same environment but decoupled from mouse behavior degraded encoding fidelity. Analyzing visual and motor responses showed that landmark codes were the result of supralinear integration. Surprisingly, V1 axons recorded in RSC showed similar receptive fields. However, they were less modulated by Task engagement, indicating that landmark representations in RSC are the result of local computations. Our data provide cellular- and network-level insight into how RSC represents landmarks.