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Journal ArticleDOI

The Bayesian brain: the role of uncertainty in neural coding and computation

David C. Knill, +1 more
- 01 Dec 2004 - 
- Vol. 27, Iss: 12, pp 712-719
TLDR
A major challenge for neuroscientists is to test ideas for how this might be achieved in populations of neurons experimentally, and so determine whether and how neurons code information about sensory uncertainty.
About
This article is published in Trends in Neurosciences.The article was published on 2004-12-01. It has received 2067 citations till now. The article focuses on the topics: Neural coding & Bayes' theorem.

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Citations
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Journal ArticleDOI

The free-energy principle: a unified brain theory?

TL;DR: This Review looks at some key brain theories in the biological and physical sciences from the free-energy perspective, suggesting that several global brain theories might be unified within a free- energy framework.
Journal ArticleDOI

Whatever next? Predictive brains, situated agents, and the future of cognitive science

TL;DR: This target article critically examines this "hierarchical prediction machine" approach, concluding that it offers the best clue yet to the shape of a unified science of mind and action.
Journal ArticleDOI

Canonical Microcircuits for Predictive Coding

TL;DR: This analysis discloses a remarkable correspondence between the microcircuitry of the cortical column and the connectivity implied by predictive coding and provides some intuitive insights into the functional asymmetries between feedforward and feedback connections and the characteristic frequencies over which they operate.

Commentary A default mode of brain function: A brief history of an evolving idea

TL;DR: The concept of a default mode of brain function arose out of a focused need to explain the appearance of activity decreases in functional neuroimaging data when the control state was passive visual fixation or eyes closed resting as discussed by the authors.
Journal ArticleDOI

A default mode of brain function: a brief history of an evolving idea.

TL;DR: This work determined that activity decreases in functional neuroimaging data did not arise from activations in the resting state, and thereby implied the existence of a default mode of brain function.
References
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Book

Probabilistic Reasoning in Intelligent Systems: Networks of Plausible Inference

TL;DR: Probabilistic Reasoning in Intelligent Systems as mentioned in this paper is a complete and accessible account of the theoretical foundations and computational methods that underlie plausible reasoning under uncertainty, and provides a coherent explication of probability as a language for reasoning with partial belief.
Journal ArticleDOI

Receptive fields, binocular interaction and functional architecture in the cat's visual cortex

TL;DR: This method is used to examine receptive fields of a more complex type and to make additional observations on binocular interaction and this approach is necessary in order to understand the behaviour of individual cells, but it fails to deal with the problem of the relationship of one cell to its neighbours.
Journal ArticleDOI

C ONDENSATION —Conditional Density Propagation forVisual Tracking

TL;DR: The Condensation algorithm uses “factored sampling”, previously applied to the interpretation of static images, in which the probability distribution of possible interpretations is represented by a randomly generated set.
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Humans integrate visual and haptic information in a statistically optimal fashion.

TL;DR: The nervous system seems to combine visual and haptic information in a fashion that is similar to a maximum-likelihood integrator, and this model behaved very similarly to humans in a visual–haptic task.
Journal ArticleDOI

An Internal Model for Sensorimotor Integration

TL;DR: A sensorimotor integration task was investigated in which participants estimated the location of one of their hands at the end of movements made in the dark and under externally imposed forces, providing direct support for the existence of an internal model.
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