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Low-noise encoding of active touch by layer 4 in the somatosensory cortex.

Hires SA, Gutnisky DA, Yu J, O'Connor DH, Svoboda K - Elife (2015)

Bottom Line: The amount of irreducible internal noise in spike trains, an important constraint on models of cortical networks, has been difficult to estimate, since behavior and brain state must be precisely controlled or tracked.The variance of touch responses was smaller than expected from Poisson processes, often reaching the theoretical minimum.Layer 4 spike trains thus reflect the millisecond-timescale structure of tactile input with little noise.

View Article: PubMed Central - PubMed

Affiliation: Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, United States.

ABSTRACT
Cortical spike trains often appear noisy, with the timing and number of spikes varying across repetitions of stimuli. Spiking variability can arise from internal (behavioral state, unreliable neurons, or chaotic dynamics in neural circuits) and external (uncontrolled behavior or sensory stimuli) sources. The amount of irreducible internal noise in spike trains, an important constraint on models of cortical networks, has been difficult to estimate, since behavior and brain state must be precisely controlled or tracked. We recorded from excitatory barrel cortex neurons in layer 4 during active behavior, where mice control tactile input through learned whisker movements. Touch was the dominant sensorimotor feature, with >70% spikes occurring in millisecond timescale epochs after touch onset. The variance of touch responses was smaller than expected from Poisson processes, often reaching the theoretical minimum. Layer 4 spike trains thus reflect the millisecond-timescale structure of tactile input with little noise.

No MeSH data available.


Temporal decoding error.Heatmap of touch time decoding RMS error with respect to both population size and temporal position of analysis window.DOI:http://dx.doi.org/10.7554/eLife.06619.013
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fig4s1: Temporal decoding error.Heatmap of touch time decoding RMS error with respect to both population size and temporal position of analysis window.DOI:http://dx.doi.org/10.7554/eLife.06619.013

Mentions: We used a simple model based on resampling the recorded spike trains measured in L4 neurons (‘Materials and methods’). Pooling activity from only fifteen L4 neurons (out of approximately 1600 [Lefort et al., 2009]) in C2 was sufficient to detect 95% of touches (integration time, 10 ms) (Figure 4A). Touch detection by neurons from surrounding barrels (>200 µm from the principal whisker) was poor (Figure 4A). Beyond detection, a group of 200 neurons in C2, integrating in 10 ms windows after touch, also allowed decoding of elapsed time from touch with high precision (minimum 0.55 ms uncertainty with 95% confidence at 10 ms post-touch onset using a naïve Bayes decoder [Duda et al., 2001]) (Figure 4B; Figure 4—figure supplement 1). This implies that a decoder reading L4 activity can determine which whisker makes contact with millisecond temporal precision (Panzeri et al., 2014).10.7554/eLife.06619.012Figure 4.Decoding of touch and phase from L4 spikes.


Low-noise encoding of active touch by layer 4 in the somatosensory cortex.

Hires SA, Gutnisky DA, Yu J, O'Connor DH, Svoboda K - Elife (2015)

Temporal decoding error.Heatmap of touch time decoding RMS error with respect to both population size and temporal position of analysis window.DOI:http://dx.doi.org/10.7554/eLife.06619.013
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4525079&req=5

fig4s1: Temporal decoding error.Heatmap of touch time decoding RMS error with respect to both population size and temporal position of analysis window.DOI:http://dx.doi.org/10.7554/eLife.06619.013
Mentions: We used a simple model based on resampling the recorded spike trains measured in L4 neurons (‘Materials and methods’). Pooling activity from only fifteen L4 neurons (out of approximately 1600 [Lefort et al., 2009]) in C2 was sufficient to detect 95% of touches (integration time, 10 ms) (Figure 4A). Touch detection by neurons from surrounding barrels (>200 µm from the principal whisker) was poor (Figure 4A). Beyond detection, a group of 200 neurons in C2, integrating in 10 ms windows after touch, also allowed decoding of elapsed time from touch with high precision (minimum 0.55 ms uncertainty with 95% confidence at 10 ms post-touch onset using a naïve Bayes decoder [Duda et al., 2001]) (Figure 4B; Figure 4—figure supplement 1). This implies that a decoder reading L4 activity can determine which whisker makes contact with millisecond temporal precision (Panzeri et al., 2014).10.7554/eLife.06619.012Figure 4.Decoding of touch and phase from L4 spikes.

Bottom Line: The amount of irreducible internal noise in spike trains, an important constraint on models of cortical networks, has been difficult to estimate, since behavior and brain state must be precisely controlled or tracked.The variance of touch responses was smaller than expected from Poisson processes, often reaching the theoretical minimum.Layer 4 spike trains thus reflect the millisecond-timescale structure of tactile input with little noise.

View Article: PubMed Central - PubMed

Affiliation: Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, United States.

ABSTRACT
Cortical spike trains often appear noisy, with the timing and number of spikes varying across repetitions of stimuli. Spiking variability can arise from internal (behavioral state, unreliable neurons, or chaotic dynamics in neural circuits) and external (uncontrolled behavior or sensory stimuli) sources. The amount of irreducible internal noise in spike trains, an important constraint on models of cortical networks, has been difficult to estimate, since behavior and brain state must be precisely controlled or tracked. We recorded from excitatory barrel cortex neurons in layer 4 during active behavior, where mice control tactile input through learned whisker movements. Touch was the dominant sensorimotor feature, with >70% spikes occurring in millisecond timescale epochs after touch onset. The variance of touch responses was smaller than expected from Poisson processes, often reaching the theoretical minimum. Layer 4 spike trains thus reflect the millisecond-timescale structure of tactile input with little noise.

No MeSH data available.