Subthreshold mechanisms underlying state-dependent modulation of visual responses
Open accessAbstract
The processing of sensory information varies widely across behavioral states. However, little is known about how behavioral states modulate the intracellular activity of cortical neurons to effect changes in sensory responses. Here, we performed whole-cell recordings from neurons in upper-layer primary visual cortex of awake mice during locomotion and quiet wakefulness. We found that the signal-to-noise ratio for sensory responses was improved during locomotion by two mechanisms: (1) a decrease in membrane potential variability leading to a reduction in background firing rates and (2) an enhancement in the amplitude and reliability of visually evoked subthreshold responses mediated by an increase in total conductance and a depolarization of the stimulus-evoked reversal potential. Consistent with the enhanced signal-to-noise ratio for visual responses during locomotion, we demonstrate that performance is improved in a visual detection task during this behavioral state.
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In awake head-fixed rodents during quiet wakefulness without overt movement, large low-frequency (<10 Hz) fluctuations in synaptic activity occur in somatosensory, visual, and auditory cortical neurons, and these oscillations are strongly suppressed by whisking or locomotion.
“During periods of quiet wakefulness (lacking overt movement), large low-frequency (< 10 Hz) fluctuations in the synaptic activity of somatosensory, visual, and auditory cortical neurons are frequently observed, and these oscillations are strongly suppressed by the initiation of whisking or locomotion”
From Waking state: rapid variations modulate neural and behavioral responses (2015) · cites this paper as Bennett et al., 2013
Active behaviors such as locomotion and whisking are associated with reduced low-frequency rhythmic activity.
“Previous studies had shown that active behaviors such as locomotion and whisking were associated with a reduction in low-frequency rhythmic activity”
From Waking state: rapid variations modulate neural and behavioral responses (2015) · cites this paper as Bennett et al., 2013
The transition from quiet awake state to movement in head-fixed mice is always preceded by strong suppression of cortical slow rhythms at action potential, membrane potential, and field potential levels.
“The transition from the quiet awake state to movement (locomotion and/or whisking) in head-fixed mice is always preceded by a strong suppression of cortical slow rhythms at the action potential, membrane potential, and field potential, levels”
From Waking state: rapid variations modulate neural and behavioral responses (2015) · cites this paper as Bennett et al., 2013
Effects of locomotion on spontaneous discharge rates of presumed pyramidal neurons in other layers are more diverse.
“However, the effects of locomotion on the spontaneous discharge rates of presumed pyramidal neurons recorded in other layers is more diverse”
From Waking state: rapid variations modulate neural and behavioral responses (2015) · cites this paper as Bennett et al., 2013
In V1, locomotion causes both multiplicative and additive enhancements of responses to drifting gratings.
“In V1, locomotion causes both multiplicative and additive enhancements of responses to drifting gratings”
From Waking state: rapid variations modulate neural and behavioral responses (2015) · cites this paper as Bennett et al., 2013
In mouse visual cortex, the signal-to-noise ratio is small at low arousal and increases at high arousal and during locomotion.
“In mouse visual cortex, the S/N is small at low arousal levels, and increases at high arousal levels and during locomotion”
From Waking state: rapid variations modulate neural and behavioral responses (2015) · cites this paper as Bennett et al., 2013
Locomotion is associated with suppression of slow rhythmic activity in cortical networks, depolarization of cortical neurons closer to action potential threshold, and enhanced visually evoked responses.
“Locomotion, as we have mentioned, is associated with a suppression of slow rhythmic activity in cortical networks, a depolarization of cortical neurons closer to action potential threshold, and enhanced visually evoked responses (Bennett et al., 2013; Polack et al., 2013; Reimer et al., 2014).”
From Waking state: rapid variations modulate neural and behavioral responses (2015) · cites this paper as Bennett et al., 2013
Mice trained to discriminate the orientation of moving bars exhibited improved performance when locomoting compared to sitting quietly.
“In a visual response task, mice trained to discriminate the orientation of moving bars exhibited improvement in performance when the animals were locomoting in comparison to when they were sitting quietly (Bennett et al., 2013).”
From Waking state: rapid variations modulate neural and behavioral responses (2015) · cites this paper as Bennett et al., 2013
Contrast-invariant tuning is an example of gain modulation induced by changes in sensory stimulation, in which neurons respond to stimuli of different contrast while preserving selectivity for other properties such as orientation and spatial frequency.
“Contrast-invariant tuning is an example of gain modulation that is induced by changes in sensory stimulation, in which neurons respond to stimuli of different levels of contrast while preserving their selectivity for other properties, such as orientation and spatial frequency27–29.”
From Mechanisms underlying gain modulation in the cortex (2020) · cites this paper as [29]
The degree to which the synaptic input underlying Vm fluctuations is temporally correlated can vary with overall drive to a network or with firing rates and is regulated by behavioural state transitions during wakefulness.
“The degree to which the synaptic input underlying Vm fluctuations is temporally correlated can vary with overall drive to a network or with firing rates70 and is regulated by behavioural state transitions during wakefulness29,71–74.”
From Mechanisms underlying gain modulation in the cortex (2020) · cites this paper as [29]
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- Authors
- Bennett, C., Arroyo, S., & Hestrin, S.
- Affiliations
- Stanford Medicine (US)
- Corresponding author
- Hestrin, Shaul
- Venue
- Neuron
- Publisher
- Elsevier BV
- Published
- 2013-10
- Volume
- 80
- Issue
- 2
- Pages
- 350-357
- ISSN
- 0896-6273 (ISSN-L)
- PMC
- PMC3806653
- OpenAlex
- W1996856166
- Cited by
- 292
- References
- 43
- Citations by year
- 2026: 10 · 2025: 15 · 2024: 24 · 2023: 34 · 2022: 21 · 2021: 24 · 2020: 23 · 2019: 26 · 2018: 29 · 2017: 25 · 2016: 21 · 2015: 18 · 2014: 22
- FWCI
- 11.11
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Licence
- Locations
- Neuron (publishedVersion)
- PubMed (publishedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
- Funders
- National Institute of Mental Health (T32MH020016)
- National Eye Institute (R01EY012114, EY012114)
- National Institute of Neurological Disorders and Stroke (F31NS078814)
- Topics
- Life Sciences › Neuroscience › Cognitive Neuroscience › Neural dynamics and brain function
- Life Sciences › Neuroscience › Cognitive Neuroscience › Visual perception and processing mechanisms
- Life Sciences › Neuroscience › Cellular and Molecular Neuroscience › Neuroscience and Neuropharmacology Research
- Keywords
- behavioral state, locomotion, primary visual cortex, signal-to-noise ratio, subthreshold responses, reversal potential, visual detection, awake mice, cortical neurons
- MeSH terms
- Animals, Evoked Potentials, Visual, Locomotion, Membrane Potentials, Neurons, Photic Stimulation, Visual Cortex, Visual Perception, Wakefulness, Mice, Signal-To-Noise Ratio, Neurophysiological Monitoring
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