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Shifts in Coding Properties and Maintenance of Information Transmission during Adaptation in Barrel Cortex

Author

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  • Miguel Maravall
  • Rasmus S Petersen
  • Adrienne L Fairhall
  • Ehsan Arabzadeh
  • Mathew E Diamond

Abstract

Neuronal responses to ongoing stimulation in many systems change over time, or “adapt.” Despite the ubiquity of adaptation, its effects on the stimulus information carried by neurons are often unknown. Here we examine how adaptation affects sensory coding in barrel cortex. We used spike-triggered covariance analysis of single-neuron responses to continuous, rapidly varying vibrissa motion stimuli, recorded in anesthetized rats. Changes in stimulus statistics induced spike rate adaptation over hundreds of milliseconds. Vibrissa motion encoding changed with adaptation as follows. In every neuron that showed rate adaptation, the input–output tuning function scaled with the changes in stimulus distribution, allowing the neurons to maintain the quantity of information conveyed about stimulus features. A single neuron that did not show rate adaptation also lacked input–output rescaling and did not maintain information across changes in stimulus statistics. Therefore, in barrel cortex, rate adaptation occurs on a slow timescale relative to the features driving spikes and is associated with gain rescaling matched to the stimulus distribution. Our results suggest that adaptation enhances tactile representations in primary somatosensory cortex, where they could directly influence perceptual decisions. Author Summary: Neuronal responses to continued stimulation change over time, or “adapt.” Adaptation can be crucial to our brain's ability to successfully represent the environment: for example, when we move from a dim to a bright scene adaptation adjusts neurons' response to a given light intensity, enabling them to be maximally sensitive to the current range of stimulus variations. We analyzed how adaptation affects sensory coding in the somatosensory “barrel” cortex of the rat, which represents objects touched by the rat's whiskers, or vibrissae. Whiskers endow these nocturnal animals with impressive discrimination abilities: a rat can discern differences in texture as fine as we can distinguish using our fingertips. Neurons in the somatosensory cortex represent whisker vibrations by responding to “kinetic features,” particularly velocity fluctuations. We recorded responses of barrel cortex neurons to carefully controlled whisker motion and slowly varied the overall characteristics of the motion to provide a changing stimulus “context.” We found that stimulus–response relationships change in a particular way: the “tuning functions” that predict a neuron's response to fluctuations in whisker motion rescale according to the current stimulus distribution. The rescaling is just enough to maintain the information conveyed by the response about the stimulus. Cortical neurons adapt their responses to changes in the input statistics of a stimulus, suggesting adaptation enhances stimulus discrimination and perception.

Suggested Citation

  • Miguel Maravall & Rasmus S Petersen & Adrienne L Fairhall & Ehsan Arabzadeh & Mathew E Diamond, 2007. "Shifts in Coding Properties and Maintenance of Information Transmission during Adaptation in Barrel Cortex," PLOS Biology, Public Library of Science, vol. 5(2), pages 1-12, January.
  • Handle: RePEc:plo:pbio00:0050019
    DOI: 10.1371/journal.pbio.0050019
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    References listed on IDEAS

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    Cited by:

    1. Omer Mano & Damon A Clark, 2017. "Graphics Processing Unit-Accelerated Code for Computing Second-Order Wiener Kernels and Spike-Triggered Covariance," PLOS ONE, Public Library of Science, vol. 12(1), pages 1-11, January.
    2. Jerome Carriot & Graham McAllister & Hamed Hooshangnejad & Isabelle Mackrous & Kathleen E. Cullen & Maurice J. Chacron, 2022. "Sensory adaptation mediates efficient and unambiguous encoding of natural stimuli by vestibular thalamocortical pathways," Nature Communications, Nature, vol. 13(1), pages 1-15, December.
    3. Jian K Liu & Tim Gollisch, 2015. "Spike-Triggered Covariance Analysis Reveals Phenomenological Diversity of Contrast Adaptation in the Retina," PLOS Computational Biology, Public Library of Science, vol. 11(7), pages 1-30, July.
    4. Gabriel D Puccini & Albert Compte & Miguel Maravall, 2006. "Stimulus Dependence of Barrel Cortex Directional Selectivity," PLOS ONE, Public Library of Science, vol. 1(1), pages 1-6, December.
    5. Sungho Hong & Brian Nils Lundstrom & Adrienne L Fairhall, 2008. "Intrinsic Gain Modulation and Adaptive Neural Coding," PLOS Computational Biology, Public Library of Science, vol. 4(7), pages 1-11, July.
    6. Johnatan Aljadeff & Ronen Segev & Michael J Berry II & Tatyana O Sharpee, 2013. "Spike Triggered Covariance in Strongly Correlated Gaussian Stimuli," PLOS Computational Biology, Public Library of Science, vol. 9(9), pages 1-12, September.
    7. Klaus Wimmer & K Jannis Hildebrandt & R Matthias Hennig & Klaus Obermayer, 2008. "Adaptation and Selective Information Transmission in the Cricket Auditory Neuron AN2," PLOS Computational Biology, Public Library of Science, vol. 4(9), pages 1-18, September.
    8. Matthew F. Tang & Ehsan Kheradpezhouh & Conrad C. Y. Lee & J. Edwin Dickinson & Jason B. Mattingley & Ehsan Arabzadeh, 2023. "Expectation violations enhance neuronal encoding of sensory information in mouse primary visual cortex," Nature Communications, Nature, vol. 14(1), pages 1-14, December.
    9. Jeffrey D Fitzgerald & Ryan J Rowekamp & Lawrence C Sincich & Tatyana O Sharpee, 2011. "Second Order Dimensionality Reduction Using Minimum and Maximum Mutual Information Models," PLOS Computational Biology, Public Library of Science, vol. 7(10), pages 1-9, October.

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