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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.


Behavior during cell-attached recordings.(A) Histogram of performing trials analyzed per session; x indicates mean value in all plots. (B) Histogram of behavioral performance for each session. (C) Histogram of the number of touches before the response time across all sessions. (D) Histogram of time between onset of first touch to first lick across all sessions. (E) Histogram of the maximum amplitude of each whisking bout across all sessions. (F) Histogram of the duration of each whisking bout across all sessions. (G) Histogram of the frequency of whisking (1/cycle length) for each whisk cycle across all sessions.DOI:http://dx.doi.org/10.7554/eLife.06619.004
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fig1s1: Behavior during cell-attached recordings.(A) Histogram of performing trials analyzed per session; x indicates mean value in all plots. (B) Histogram of behavioral performance for each session. (C) Histogram of the number of touches before the response time across all sessions. (D) Histogram of time between onset of first touch to first lick across all sessions. (E) Histogram of the maximum amplitude of each whisking bout across all sessions. (F) Histogram of the duration of each whisking bout across all sessions. (G) Histogram of the frequency of whisking (1/cycle length) for each whisk cycle across all sessions.DOI:http://dx.doi.org/10.7554/eLife.06619.004

Mentions: We trained mice to locate an object by active touch with a single whisker (C2) (O'Connor et al., 2010a; O'Connor et al., 2013) (n = 21 mice, 52 sessions; fraction of trials correct, 0.740 ± 0.086; mean ± s.d.; Figure 1A; Figure 1—figure supplement 1). Single whisker experiments allowed us to track the relevant tactile variables with high precision during behavior. In each trial, during a sample epoch lasting a few seconds (1.54–4.05, mean 2.39 s), a pole appeared in one of two locations on the right side of the head. High-speed videography and automated whisker tracking quantified whisker movement (azimuthal angle, θ; whisking phase, ϕ), changes in curvature caused by the forces exerted by the pole on the whisker (change in curvature, ∆κ) (Birdwell et al., 2007; Pammer et al., 2013), and contact time, all with 1 millisecond temporal precision (Clack et al., 2012; O'Connor et al., 2013) (Figure 1A,B). Mice whisked in bouts (mean bout duration, 261 ms; peak-to-peak amplitude, 15.7°; frequency, 15.4 Hz) interspersed with periods of rest. Mice touched the pole multiple times (mean number of touches, 2.33) before reporting perceived object location with licking (mean reaction time 367 ± 234 ms; mean ± s.d.) (Figure 1—figure supplement 1).10.7554/eLife.06619.003Figure 1.Activity during tactile behavior in a layer 4 excitatory cell.


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)

Behavior during cell-attached recordings.(A) Histogram of performing trials analyzed per session; x indicates mean value in all plots. (B) Histogram of behavioral performance for each session. (C) Histogram of the number of touches before the response time across all sessions. (D) Histogram of time between onset of first touch to first lick across all sessions. (E) Histogram of the maximum amplitude of each whisking bout across all sessions. (F) Histogram of the duration of each whisking bout across all sessions. (G) Histogram of the frequency of whisking (1/cycle length) for each whisk cycle across all sessions.DOI:http://dx.doi.org/10.7554/eLife.06619.004
© Copyright Policy
Related In: Results  -  Collection

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

fig1s1: Behavior during cell-attached recordings.(A) Histogram of performing trials analyzed per session; x indicates mean value in all plots. (B) Histogram of behavioral performance for each session. (C) Histogram of the number of touches before the response time across all sessions. (D) Histogram of time between onset of first touch to first lick across all sessions. (E) Histogram of the maximum amplitude of each whisking bout across all sessions. (F) Histogram of the duration of each whisking bout across all sessions. (G) Histogram of the frequency of whisking (1/cycle length) for each whisk cycle across all sessions.DOI:http://dx.doi.org/10.7554/eLife.06619.004
Mentions: We trained mice to locate an object by active touch with a single whisker (C2) (O'Connor et al., 2010a; O'Connor et al., 2013) (n = 21 mice, 52 sessions; fraction of trials correct, 0.740 ± 0.086; mean ± s.d.; Figure 1A; Figure 1—figure supplement 1). Single whisker experiments allowed us to track the relevant tactile variables with high precision during behavior. In each trial, during a sample epoch lasting a few seconds (1.54–4.05, mean 2.39 s), a pole appeared in one of two locations on the right side of the head. High-speed videography and automated whisker tracking quantified whisker movement (azimuthal angle, θ; whisking phase, ϕ), changes in curvature caused by the forces exerted by the pole on the whisker (change in curvature, ∆κ) (Birdwell et al., 2007; Pammer et al., 2013), and contact time, all with 1 millisecond temporal precision (Clack et al., 2012; O'Connor et al., 2013) (Figure 1A,B). Mice whisked in bouts (mean bout duration, 261 ms; peak-to-peak amplitude, 15.7°; frequency, 15.4 Hz) interspersed with periods of rest. Mice touched the pole multiple times (mean number of touches, 2.33) before reporting perceived object location with licking (mean reaction time 367 ± 234 ms; mean ± s.d.) (Figure 1—figure supplement 1).10.7554/eLife.06619.003Figure 1.Activity during tactile behavior in a layer 4 excitatory cell.

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.