H. B. Barlow. Redundancy reduction revisited. Network: Computation in Neural Systems, 12:241--253, 2001.  Home/Search   Document Not in Database   Summary   Related Articles   Check

.... nor does it provide any way of coding the uncertainty of the value (the width of the peak) Many other proposed neural representations of probabilities face similar problems [11] however, see [15] for a recent interesting approach to representing distributions) Indeed, it has been said [10, 16] that how probabilities actually are represented in the brain is one of the most important unanswered questions in the probabilistic approach to perception. In the next section we suggest an answer based on the idea that probability distributions might be represented using response variability. 3 ....

H. B. Barlow. Redundancy reduction revisited. Network: Computation in Neural Systems, 12:241--253, 2001.

.... nor does it provide any way of coding the uncertainty of the value (the width of the peak) Many other proposed neural representations of probabilities face similar problems [11] however, see [15] for a recent interesting approach to representing distributions) Indeed, it has been said [10, 16] that how probabilities actually are represented in the brain is one of the most important unanswered questions in the probabilistic approach to perception. In the next section we suggest an answer based on the idea that probability distributions might be represented using response variability. 3 ....

H. B. Barlow. Redundancy reduction revisited. Network: Computation in Neural Systems, 12:241--253, 2001.

....complex aspects of sensory inputs. The changes in representations of stimuli along the sensory pathway re ect the information processing performed by the system. Several computational principles that govern these changes were suggested, such as information maximization and redundancy reduction [2, 3, 11]. In order to investigate such changes in practice, it is necessary to develop methods to quantify information content and redundancies among groups of neurons, and trace these measures along the sensory pathway. Interactions and high order correlations between neurons were mostly investigated ....

....less information but are more independent, thus allowing information to be summed almost linearly when considering groups of few tens of neurons. The results provide for the rst time direct evidence for redundancy reduction along the ascending auditory pathway, as has been hypothesized by Barlow [2, 3]. The redundancy e ects under the single spikes coding paradigm are signi cant only for groups larger than ten cells, and cannot be revealed with the standard redundancy measures that use only pairs of cells. Our results suggest that transformations leading to redundancy reduction are not ....

H.B. Barlow. Redundancy reduction revisited. Network: Computation in neural systems, 12:241-253, 2001.

....Our results suggest that the essential need to deal with uncertain data (see section 6. 1) makes it likely that redundancy preservation might also be an important statistical principle in cortical processes to overcome the ambiguity of local feature processing (see also the discussion in [66, 3]) To put it in even stronger terms, redundancies in early vision are necessary for the applicability of Gestalt principles and the applicability of modality fusion since the elimination of redundancies would disable any predictions between visual entities or across modalities at all (see also [3, ....

.... 3] To put it in even stronger terms, redundancies in early vision are necessary for the applicability of Gestalt principles and the applicability of modality fusion since the elimination of redundancies would disable any predictions between visual entities or across modalities at all (see also [3, 37, 57]) An open question remains which a priori settings are sensible and what role learning has in the development of early and intermediate visual prossessing as opposed to or supplementing pre wiring mechanisms. Whatever answer one may prefer, we think the preservation of redundancies plays an ....

H. Barlow. Redundancy reduction revisited. Network: Computation in Neural Systems, 12(3):241-254, 2001.

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H. B. Barlow. Redundancy reduction revisited. Network: Computation in Neural Systems, 12:241--253, 2001.

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H.B. Barlow, Redundancy Reduction Revisited, Network: Computation in Neural Systems, Vol. 12, pp. 241 -- 253, 2001

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H. B. Barlow. Redundancy reduction revisited. Network: Computation in Neural Systems, 12:241--253, 2001.

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