Maneesh Sahani mostly deals with Neuroscience, Stimulus, Auditory cortex, Receptive field and Premotor cortex. His Neuroscience study integrates concerns from other disciplines, such as Artificial intelligence and Dynamics. His research in Stimulus intersects with topics in Visual perception, Sensory system and Visualization.
Maneesh Sahani focuses mostly in the field of Auditory cortex, narrowing it down to topics relating to Neural coding and, in certain cases, Modulation, Cortical Synchronization, Cortex, Sensory processing and Contrast. His work carried out in the field of Receptive field brings together such families of science as Natural sounds, Cortical neurons and Spectrogram. His Premotor cortex study deals with Movement intersecting with Neural correlates of consciousness, Motor cortex and Electrophysiology.
His primary areas of study are Artificial intelligence, Neuroscience, Stimulus, Probabilistic logic and Pattern recognition. He combines subjects such as Machine learning and Computer vision with his study of Artificial intelligence. His studies in Auditory cortex, Sensory system, Macaque, Posterior parietal cortex and Inhibitory postsynaptic potential are all subfields of Neuroscience research.
His research investigates the connection between Inhibitory postsynaptic potential and topics such as Tonotopy that intersect with issues in Biological neural network. The Stimulus study combines topics in areas such as Speech recognition, World Wide Web and Visual cortex. His Probabilistic logic study incorporates themes from Algorithm and Statistical model.
His scientific interests lie mostly in Neuroscience, Artificial intelligence, Sensory system, Inference and Gaussian process. His Neuroscience study focuses mostly on Inhibitory postsynaptic potential, Inhibitory control, Stimulus, Macaque and Mirror neuron. His Artificial intelligence research integrates issues from Machine learning, Computation and Computer vision.
He has researched Sensory system in several fields, including Neurotypical, Receptive field, Perception and Auditory cortex. His Auditory cortex study combines topics from a wide range of disciplines, such as Ketamine and Neural correlates of consciousness. The study incorporates disciplines such as Algorithm, Probabilistic logic, Postdiction and Random variable in addition to Inference.
His primary areas of investigation include Neuroscience, Inference, Sensory system, Artificial intelligence and Gaussian process. Maneesh Sahani integrates Neuroscience and Calcium imaging in his studies. His Inference research incorporates elements of Algorithm, Posterior probability, Autoencoder and Latent variable.
His Sensory system study incorporates themes from Structure and Receptive field. His work on MNIST database and Representation as part of general Artificial intelligence research is frequently linked to Systems neuroscience and Pupillary response, thereby connecting diverse disciplines of science. Maneesh Sahani combines subjects such as Neural correlates of consciousness and Speech recognition with his study of Perception.
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Temporal structure in neuronal activity during working memory in macaque parietal cortex
Bijan Pesaran;John S. Pezaris;John S. Pezaris;Maneesh Sahani;Partha P. Mitra.
Nature Neuroscience (2002)
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.
Nature Neuroscience (2010)
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.
neural information processing systems (2008)
Cortical control of arm movements: a dynamical systems perspective.
Krishna V. Shenoy;Maneesh Sahani;Mark M. Churchland.
Annual Review of Neuroscience (2013)
Localization bias and spatial resolution of adaptive and non-adaptive spatial filters for MEG source reconstruction
Kensuke Sekihara;Maneesh Sahani;Srikantan S. Nagarajan.
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.
Journal of Neurophysiology (2003)
Learning Enhances Sensory and Multiple Non-sensory Representations in Primary Visual Cortex.
Jasper Poort;Adil G. Khan;Marius Pachitariu;Abdellatif Nemri;Abdellatif Nemri.
Empirical models of spiking in neural populations
Jakob H Macke;Lars Buesing;John P Cunningham;Byron M Yu.
neural information processing systems (2011)
Latent variable models for neural data analysis
R. A. Andersen;Maneesh Sahani.
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.
Current Opinion in Neurobiology (2007)
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