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Neural correlations, population coding and computation
How the brain encodes information in population activity, and how it combines and manipulates that activity as it carries out computations, are questions that lie at the heart of systemsExpand
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Bayesian inference with probabilistic population codes
TLDR
We show that the Poisson-like variability observed in cortex reduces a broad class of Bayesian inference to simple linear combinations of populations of neural activity. Expand
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The Bayesian brain: the role of uncertainty in neural coding and computation
To use sensory information efficiently to make judgments and guide action in the world, the brain must represent and use information about uncertainty in its computations for perception and action.Expand
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Spatial Transformations in the Parietal Cortex Using Basis Functions
TLDR
Basis function decomposition is a general method for approximating nonlinear functions that is computationally efficient and well suited for adaptive modification. Expand
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Probabilistic Population Codes for Bayesian Decision Making
When making a decision, one must first accumulate evidence, often over time, and then select the appropriate action. Here, we present a neural model of decision making that can perform both evidenceExpand
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The Cost of Accumulating Evidence in Perceptual Decision Making
Decision making often involves the accumulation of information over time, but acquiring information typically comes at a cost. Little is known about the cost incurred by animals and humans forExpand
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Reference frames for representing visual and tactile locations in parietal cortex
The ventral intraparietal area (VIP) receives converging inputs from visual, somatosensory, auditory and vestibular systems that use diverse reference frames to encode sensory information. A keyExpand
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Reading population codes: a neural implementation of ideal observers
Many sensory and motor variables are encoded in the nervous system by the activities of large populations of neurons with bell-shaped tuning curves. Extracting information from these population codesExpand
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Computational approaches to sensorimotor transformations
TLDR
We review models of sensorimotor transformations that use a flexible intermediate representation that relies on basis functions. Expand
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A computational perspective on the neural basis of multisensory spatial representations
We argue that current theories of multisensory representations are inconsistent with the existence of a large proportion of multimodal neurons with gain fields and partially shifting receptiveExpand
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