Is the homunculus "aware" of sensory adaptation?

Peggy Seriès, Alan A. Stocker, Eero Simoncelli

Research output: Contribution to journalArticle

Abstract

Neural activity and perception are both affected by sensory history. The work presented here explores the relationship between the physiological effects of adaptation and their perceptual consequences. Perception is modeled as arising from an encoder-decoder cascade, in which the encoder is defined by the probabilistic response of a population of neurons, and the decoder transforms this population activity into a perceptual estimate. Adaptation is assumed to produce changes in the encoder, and we examine the conditions under which the decoder behavior is consistent with observed perceptual effects in terms of both bias and discriminability. We show that for all decoders, discriminability is bounded from below by the inverse Fisher information. Estimation bias, on the other hand, can arise for a variety of different reasons and can range from zero to substantial. We specifically examine biases that arise when the decoder is fixed, "unaware" of the changes in the encoding population (as opposed to "aware" of the adaptation and changing accordingly). We simulate the effects of adaptation on two well-studied sensory attributes, motion direction and contrast, assuming a gain change description of en- coder adaptation. Although we cannot uniquely constrain the source of decoder bias, we find for both motion and contrast that an "unaware" decoder that maximizes the likelihood of the percept given by the preadap-tation encoder leads to predictions that are consistent with behavioral data. This model implies that adaptation-induced biases arise as a result of temporary suboptimality of the decoder.

Original languageEnglish (US)
Pages (from-to)3271-3304
Number of pages34
JournalNeural computation
Volume21
Issue number12
DOIs
StatePublished - Dec 2009

Fingerprint

Population
Physiological Adaptation
History
Neurons
Direction compound

ASJC Scopus subject areas

  • Cognitive Neuroscience

Cite this

Is the homunculus "aware" of sensory adaptation? / Seriès, Peggy; Stocker, Alan A.; Simoncelli, Eero.

In: Neural computation, Vol. 21, No. 12, 12.2009, p. 3271-3304.

Research output: Contribution to journalArticle

Seriès, Peggy ; Stocker, Alan A. ; Simoncelli, Eero. / Is the homunculus "aware" of sensory adaptation?. In: Neural computation. 2009 ; Vol. 21, No. 12. pp. 3271-3304.
@article{1da4e59c607c43ab9abb2b488a6d7b0a,
title = "Is the homunculus {"}aware{"} of sensory adaptation?",
abstract = "Neural activity and perception are both affected by sensory history. The work presented here explores the relationship between the physiological effects of adaptation and their perceptual consequences. Perception is modeled as arising from an encoder-decoder cascade, in which the encoder is defined by the probabilistic response of a population of neurons, and the decoder transforms this population activity into a perceptual estimate. Adaptation is assumed to produce changes in the encoder, and we examine the conditions under which the decoder behavior is consistent with observed perceptual effects in terms of both bias and discriminability. We show that for all decoders, discriminability is bounded from below by the inverse Fisher information. Estimation bias, on the other hand, can arise for a variety of different reasons and can range from zero to substantial. We specifically examine biases that arise when the decoder is fixed, {"}unaware{"} of the changes in the encoding population (as opposed to {"}aware{"} of the adaptation and changing accordingly). We simulate the effects of adaptation on two well-studied sensory attributes, motion direction and contrast, assuming a gain change description of en- coder adaptation. Although we cannot uniquely constrain the source of decoder bias, we find for both motion and contrast that an {"}unaware{"} decoder that maximizes the likelihood of the percept given by the preadap-tation encoder leads to predictions that are consistent with behavioral data. This model implies that adaptation-induced biases arise as a result of temporary suboptimality of the decoder.",
author = "Peggy Seri{\`e}s and Stocker, {Alan A.} and Eero Simoncelli",
year = "2009",
month = "12",
doi = "10.1162/neco.2009.09-08-869",
language = "English (US)",
volume = "21",
pages = "3271--3304",
journal = "Neural computation",
issn = "0899-7667",
number = "12",

}

TY - JOUR

T1 - Is the homunculus "aware" of sensory adaptation?

AU - Seriès, Peggy

AU - Stocker, Alan A.

AU - Simoncelli, Eero

PY - 2009/12

Y1 - 2009/12

N2 - Neural activity and perception are both affected by sensory history. The work presented here explores the relationship between the physiological effects of adaptation and their perceptual consequences. Perception is modeled as arising from an encoder-decoder cascade, in which the encoder is defined by the probabilistic response of a population of neurons, and the decoder transforms this population activity into a perceptual estimate. Adaptation is assumed to produce changes in the encoder, and we examine the conditions under which the decoder behavior is consistent with observed perceptual effects in terms of both bias and discriminability. We show that for all decoders, discriminability is bounded from below by the inverse Fisher information. Estimation bias, on the other hand, can arise for a variety of different reasons and can range from zero to substantial. We specifically examine biases that arise when the decoder is fixed, "unaware" of the changes in the encoding population (as opposed to "aware" of the adaptation and changing accordingly). We simulate the effects of adaptation on two well-studied sensory attributes, motion direction and contrast, assuming a gain change description of en- coder adaptation. Although we cannot uniquely constrain the source of decoder bias, we find for both motion and contrast that an "unaware" decoder that maximizes the likelihood of the percept given by the preadap-tation encoder leads to predictions that are consistent with behavioral data. This model implies that adaptation-induced biases arise as a result of temporary suboptimality of the decoder.

AB - Neural activity and perception are both affected by sensory history. The work presented here explores the relationship between the physiological effects of adaptation and their perceptual consequences. Perception is modeled as arising from an encoder-decoder cascade, in which the encoder is defined by the probabilistic response of a population of neurons, and the decoder transforms this population activity into a perceptual estimate. Adaptation is assumed to produce changes in the encoder, and we examine the conditions under which the decoder behavior is consistent with observed perceptual effects in terms of both bias and discriminability. We show that for all decoders, discriminability is bounded from below by the inverse Fisher information. Estimation bias, on the other hand, can arise for a variety of different reasons and can range from zero to substantial. We specifically examine biases that arise when the decoder is fixed, "unaware" of the changes in the encoding population (as opposed to "aware" of the adaptation and changing accordingly). We simulate the effects of adaptation on two well-studied sensory attributes, motion direction and contrast, assuming a gain change description of en- coder adaptation. Although we cannot uniquely constrain the source of decoder bias, we find for both motion and contrast that an "unaware" decoder that maximizes the likelihood of the percept given by the preadap-tation encoder leads to predictions that are consistent with behavioral data. This model implies that adaptation-induced biases arise as a result of temporary suboptimality of the decoder.

UR - http://www.scopus.com/inward/record.url?scp=72249098338&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=72249098338&partnerID=8YFLogxK

U2 - 10.1162/neco.2009.09-08-869

DO - 10.1162/neco.2009.09-08-869

M3 - Article

VL - 21

SP - 3271

EP - 3304

JO - Neural computation

JF - Neural computation

SN - 0899-7667

IS - 12

ER -