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Computer Science

D-Index
55
Citations
11900
World Ranking
4324
National Ranking
266

Overview

Maneesh Sahani is affiliated with University College London in the United Kingdom. Their research spans the fields of neuroscience and computer science, with a strong focus on cognitive neuroscience and artificial intelligence among other subfields.

The scientist has published extensively, contributing notably to several research venues. Frequent publication venues include:

  • arXiv (Cornell University)
  • bioRxiv (Cold Spring Harbor Laboratory)
  • Neuron
  • 2022 Conference on Cognitive Computational Neuroscience
  • Zenodo (CERN European Organization for Nuclear Research)

Maneesh Sahani's work covers multiple main fields and subfields of study, including:

  • Neuroscience
  • Computer Science
  • Cognitive Neuroscience
  • Artificial Intelligence
  • Cellular and Molecular Neuroscience
  • Molecular Biology
  • Statistics and Probability

The major topics addressed in their research include:

  • Neural dynamics and brain function
  • Neural Networks and Applications
  • Neuroscience and Neuropharmacology Research
  • Functional Brain Connectivity Studies
  • Visual perception and processing mechanisms
  • Reinforcement Learning in Robotics
  • EEG and Brain-Computer Interfaces

Recent papers by Maneesh Sahani include:

  • Deep learning, reinforcement learning, and world models, 2022, Neural Networks
  • Learning and attention increase visual response selectivity through distinct mechanisms, 2021, Neuron
  • Dendritic calcium signals in rhesus macaque motor cortex drive an optical brain-computer interface, 2021, Nature Communications
  • Dynamics on the manifold: Identifying computational dynamical activity from neural population recordings, 2021, Current Opinion in Neurobiology
  • Direct neural perturbations reveal a dynamical mechanism for robust computation, 2022, bioRxiv (Cold Spring Harbor Laboratory)

Collaborations play a significant role in their research output. Frequent co-authors include:

  • Thomas D. Mrsic-Flogel
  • Valerio Mante
  • Jasper Poort
  • Antonin Blot
  • Angus Chadwick

Best Publications

  • Stimulus onset quenches neural variability: a widespread cortical phenomenon

    Mark M. Churchland;Byron M. Yu;Byron M. Yu;John P. Cunningham;Leo P. Sugrue;Leo P. Sugrue

  • Cortical control of arm movements: a dynamical systems perspective.

    Krishna V. Shenoy;Maneesh Sahani;Mark M. Churchland

  • Gaussian-process factor analysis for low-dimensional single-trial analysis of neural population activity

    Byron M Yu;John P Cunningham;Gopal Santhanam;Stephen I. Ryu

  • Localization bias and spatial resolution of adaptive and non-adaptive spatial filters for MEG source reconstruction

    Kensuke Sekihara;Maneesh Sahani;Srikantan S. Nagarajan

  • Deep learning, reinforcement learning, and world models

    Unknown

  • Learning Enhances Sensory and Multiple Non-sensory Representations in Primary Visual Cortex.

    Jasper Poort;Adil G. Khan;Marius Pachitariu;Abdellatif Nemri;Abdellatif Nemri

  • Spectrotemporal Structure of Receptive Fields in Areas AI and AAF of Mouse Auditory Cortex

    Jennifer F Linden;Robert C Liu;Maneesh Sahani;Maneesh Sahani;Christoph E Schreiner

  • Single-Trial Neural Correlates of Arm Movement Preparation

    Afsheen Afshar;Gopal Santhanam;Byron M. Yu;Byron M. Yu;Stephen I. Ryu;Stephen I. Ryu

  • Distinct learning-induced changes in stimulus selectivity and interactions of GABAergic interneuron classes in visual cortex

    Adil G Khan;Adil G Khan;Jasper Poort;Angus Chadwick;Antonin Blot;Antonin Blot

  • Empirical models of spiking in neural populations

    Jakob H Macke;Lars Buesing;John P Cunningham;Byron M Yu

  • Techniques for extracting single-trial activity patterns from large-scale neural recordings

    Mark M Churchland;Byron M Yu;Byron M Yu;Maneesh Sahani;Krishna V Shenoy

  • Two problems with variational expectation maximisation for time-series models

    Richard Eric Turner;Maneesh Sahani

  • Mixture of trajectory models for neural decoding of goal-directed movements

    Byron M. Yu;Caleb Kemere;Gopal Santhanam;Afsheen Afshar

  • Latent variable models for neural data analysis

    R. A. Andersen;Maneesh Sahani

  • Nonlinearities and contextual influences in auditory cortical responses modeled with multilinear spectrotemporal methods.

    Misha B. Ahrens;Jennifer F. Linden;Maneesh Sahani

  • How Linear are Auditory Cortical Responses

    Maneesh Sahani;Jennifer F. Linden

  • State-Dependent Population Coding in Primary Auditory Cortex

    Marius Pachitariu;Dmitry R. Lyamzin;Maneesh Sahani;Nicholas A. Lesica

  • A Head-Mounted Camera System Integrates Detailed Behavioral Monitoring with Multichannel Electrophysiology in Freely Moving Mice

    Arne F. Meyer;Jasper Poort;John O’Keefe;Maneesh Sahani

  • Outlier responses reflect sensitivity to statistical structure in the human brain

    Marta I. Garrido;Marta I. Garrido;Maneesh Sahani;Raymond J. Dolan

  • Implicit knowledge of visual uncertainty guides decisions with asymmetric outcomes

    Louise Whiteley;Maneesh Sahani

  • Doubly distributional population codes: simultaneous representation of uncertainty and multiplicity

    Maneesh Sahani;Peter Dayan

  • Adaptation and Unsupervised Learning

    Peter Dayan;Maneesh Sahani;Gregoire Deback

Frequent Co-Authors

Krishna V. Shenoy
Krishna V. Shenoy Stanford University
Byron M. Yu
Byron M. Yu Carnegie Mellon University
Misha B. Ahrens
Misha B. Ahrens Howard Hughes Medical Institute
Richard E. Turner
Richard E. Turner University of Cambridge
Stephen I. Ryu
Stephen I. Ryu Stanford University
Richard A. Andersen
Richard A. Andersen California Institute of Technology
John P. Cunningham
John P. Cunningham Columbia University
Michael M. Merzenich
Michael M. Merzenich University of California, San Francisco
Raymond J. Dolan
Raymond J. Dolan University College London
Jonathan W. Pillow
Jonathan W. Pillow Princeton University

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