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Cortical plasticity as a mechanism for storing Bayesian priors in sensory perception.

Köver H, Bao S - PLoS ONE (2010)

Bottom Line: Human perception of ambiguous sensory signals is biased by prior experiences.It is not known how such prior information is encoded, retrieved and combined with sensory information by neurons.For the case of auditory perception, we use a computational model to show that prior information about sound frequency distributions may be stored in the size of primary auditory cortex frequency representations, read-out by elevated baseline activity in all neurons and combined with sensory-evoked activity to generate a perception that conforms to Bayesian integration theory.

View Article: PubMed Central - PubMed

Affiliation: Helen Wills Neuroscience Institute, University of California, Berkeley, California, United States of America.

ABSTRACT
Human perception of ambiguous sensory signals is biased by prior experiences. It is not known how such prior information is encoded, retrieved and combined with sensory information by neurons. Previous authors have suggested dynamic encoding mechanisms for prior information, whereby top-down modulation of firing patterns on a trial-by-trial basis creates short-term representations of priors. Although such a mechanism may well account for perceptual bias arising in the short-term, it does not account for the often irreversible and robust changes in perception that result from long-term, developmental experience. Based on the finding that more frequently experienced stimuli gain greater representations in sensory cortices during development, we reasoned that prior information could be stored in the size of cortical sensory representations. For the case of auditory perception, we use a computational model to show that prior information about sound frequency distributions may be stored in the size of primary auditory cortex frequency representations, read-out by elevated baseline activity in all neurons and combined with sensory-evoked activity to generate a perception that conforms to Bayesian integration theory. Our results suggest an alternative neural mechanism for experience-induced long-term perceptual bias in the context of auditory perception. They make the testable prediction that the extent of such perceptual prior bias is modulated by both the degree of cortical reorganization and the magnitude of spontaneous activity in primary auditory cortex. Given that cortical over-representation of frequently experienced stimuli, as well as perceptual bias towards such stimuli is a common phenomenon across sensory modalities, our model may generalize to sensory perception, rather than being specific to auditory perception.

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Modeling tonal frequency representations in the primary auditory cortex.(a, b) Representative tuning curves of the naïve (a) and the 7-kHz-over-represented (b) model AI. The histograms in the lower part of the graphs show distributions of CFs.
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pone-0010497-g001: Modeling tonal frequency representations in the primary auditory cortex.(a, b) Representative tuning curves of the naïve (a) and the 7-kHz-over-represented (b) model AI. The histograms in the lower part of the graphs show distributions of CFs.

Mentions: To replicate frequency representations seen in AI of naïve animals and animals with extensive prior experience of a specific tone (7 kHz) [7], model characteristic frequencies (CFs) were either uniformly distributed on a logarithmic scale in the range of 1–32 kHz (naïve) or skewed such that more neurons were tuned to 7kHz (7-kHz-over-represented) (Fig. 1). For the 7kHz-over-represented AI, CFs from 5 to 10 kHz were shifted to have a Gaussian distribution centered at 7kHz and with a standard deviation of 0.1 octave (Fig. 1). Consistent with our experimental findings the bandwidths of neurons in the over-represented range were slightly smaller (Table 1) [7].


Cortical plasticity as a mechanism for storing Bayesian priors in sensory perception.

Köver H, Bao S - PLoS ONE (2010)

Modeling tonal frequency representations in the primary auditory cortex.(a, b) Representative tuning curves of the naïve (a) and the 7-kHz-over-represented (b) model AI. The histograms in the lower part of the graphs show distributions of CFs.
© Copyright Policy
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC2864750&req=5

pone-0010497-g001: Modeling tonal frequency representations in the primary auditory cortex.(a, b) Representative tuning curves of the naïve (a) and the 7-kHz-over-represented (b) model AI. The histograms in the lower part of the graphs show distributions of CFs.
Mentions: To replicate frequency representations seen in AI of naïve animals and animals with extensive prior experience of a specific tone (7 kHz) [7], model characteristic frequencies (CFs) were either uniformly distributed on a logarithmic scale in the range of 1–32 kHz (naïve) or skewed such that more neurons were tuned to 7kHz (7-kHz-over-represented) (Fig. 1). For the 7kHz-over-represented AI, CFs from 5 to 10 kHz were shifted to have a Gaussian distribution centered at 7kHz and with a standard deviation of 0.1 octave (Fig. 1). Consistent with our experimental findings the bandwidths of neurons in the over-represented range were slightly smaller (Table 1) [7].

Bottom Line: Human perception of ambiguous sensory signals is biased by prior experiences.It is not known how such prior information is encoded, retrieved and combined with sensory information by neurons.For the case of auditory perception, we use a computational model to show that prior information about sound frequency distributions may be stored in the size of primary auditory cortex frequency representations, read-out by elevated baseline activity in all neurons and combined with sensory-evoked activity to generate a perception that conforms to Bayesian integration theory.

View Article: PubMed Central - PubMed

Affiliation: Helen Wills Neuroscience Institute, University of California, Berkeley, California, United States of America.

ABSTRACT
Human perception of ambiguous sensory signals is biased by prior experiences. It is not known how such prior information is encoded, retrieved and combined with sensory information by neurons. Previous authors have suggested dynamic encoding mechanisms for prior information, whereby top-down modulation of firing patterns on a trial-by-trial basis creates short-term representations of priors. Although such a mechanism may well account for perceptual bias arising in the short-term, it does not account for the often irreversible and robust changes in perception that result from long-term, developmental experience. Based on the finding that more frequently experienced stimuli gain greater representations in sensory cortices during development, we reasoned that prior information could be stored in the size of cortical sensory representations. For the case of auditory perception, we use a computational model to show that prior information about sound frequency distributions may be stored in the size of primary auditory cortex frequency representations, read-out by elevated baseline activity in all neurons and combined with sensory-evoked activity to generate a perception that conforms to Bayesian integration theory. Our results suggest an alternative neural mechanism for experience-induced long-term perceptual bias in the context of auditory perception. They make the testable prediction that the extent of such perceptual prior bias is modulated by both the degree of cortical reorganization and the magnitude of spontaneous activity in primary auditory cortex. Given that cortical over-representation of frequently experienced stimuli, as well as perceptual bias towards such stimuli is a common phenomenon across sensory modalities, our model may generalize to sensory perception, rather than being specific to auditory perception.

Show MeSH
Related in: MedlinePlus