The DOI matches its Crossref record; 43 of the 43 references it cites were found in a registry or an index.
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.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
In the citing paper
“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
In the citing paper
“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
In the citing paper
“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
In the citing paper
“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 the citing paper
“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 the citing paper
“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
In the citing paper
“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
In the citing paper
“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
In the citing paper
“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]
In the citing paper
“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]
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Über das Elektrenkephalogramm des Menschen
Berger, H. (1929) · European Archives of Psychiatry and Clinical Neuroscience · doi:10.1007/bf01797193 · Cited by 4,266
Aston-Jones, G., & Bloom, F. (1981) · The Journal of Neuroscience · doi:10.1523/jneurosci.01-08-00876.1981 · Cited by 1,960
How Inhibition Shapes Cortical Activity
Isaacson, J. S., & Scanziani, M. (2011) · Neuron · doi:10.1016/j.neuron.2011.09.027 · Cited by 1,678
Modulation of visual responses by behavioral state in mouse visual cortex
Niell, C. M., & Stryker, M. P. (2010) · Neuron · doi:10.1016/j.neuron.2010.01.033 · Cited by 1,483
Acetylcholine as a Neuromodulator: Cholinergic Signaling Shapes Nervous System Function and Behavior
Picciotto, M. R., Higley, M. J., & Mineur, Y. S. (2012) · Neuron · doi:10.1016/j.neuron.2012.08.036 · Cited by 1,404
Natural waking and sleep states: a view from inside neocortical neurons
Steriade, M., Timofeev, I., & Grenier, F. (2001) · Journal of Neurophysiology · doi:10.1152/jn.2001.85.5.1969 · Cited by 1,296
Elementary Signal Detection Theory
Wickens, T. D. (2001) · Oxford University Press eBooks · doi:10.1093/acprof:oso/9780195092509.001.0001 · Cited by 1,276
Imaging large-scale neural activity with cellular resolution in awake, mobile mice
Dombeck, D. A., Khabbaz, A. N., Collman, F., Adelman, T. L., & Tank, D. W. (2007) · Neuron · doi:10.1016/j.neuron.2007.08.003 · Cited by 1,099
Nucleus basalis and thalamic control of neocortical activity in the freely moving rat
Buzsáki, G., Bickford, R. G., Ponomareff, G., Thal, L. J., Mandel, R. J., & Gage, F. H. (1988) · Journal of Neuroscience · doi:10.1523/jneurosci.08-11-04007.1988 · Cited by 1,039
Haider, B., Duque, A., Hasenstaub, A. R., & McCormick, D. A. (2006) · The Journal of Neuroscience · doi:10.1523/jneurosci.5297-05.2006 · Cited by 962
Cited by
Sorted by citations
The neocortical circuit: themes and variations
Harris, K. D., & Shepherd, G. M. G. (2015) · Nature Neuroscience · doi:10.1038/nn.3917 · Cited by 1,215
Pupil fluctuations track rapid changes in adrenergic and cholinergic activity in cortex
Reimer, J., McGinley, M. J., Liu, Y., Rodenkirch, C., Wang, Q., McCormick, D. A., & Tolias, A. S. (2016) · Nature Communications · doi:10.1038/ncomms13289 · Cited by 926
Arousal and Locomotion Make Distinct Contributions to Cortical Activity Patterns and Visual Encoding
Vinck, M., Batista-Brito, R., Knoblich, U., & Cardin, J. A. (2015) · Neuron · doi:10.1016/j.neuron.2015.03.028 · Cited by 819
Waking state: rapid variations modulate neural and behavioral responses
McGinley, M. J., Vinck, M., Reimer, J., Batista-Brito, R., Zagha, E., Cadwell, C. R., Tolias, A. S., Cardin, J. A., & McCormick, D. A. (2015) · Neuron · doi:10.1016/j.neuron.2015.09.012 · Cited by 801
“In mouse visual cortex, the S/N is small at low arousal levels, and increases at high arousal levels and during locomotion (Figures 5, 6) (Bennett et al., 2013; Niell and Stryker, 2010; Vinck et al., 2015).”
InfluentialCortical membrane potential signature of optimal states for sensory signal detection
McGinley, M. J., David, S. V., & McCormick, D. A. (2015) · Neuron · doi:10.1016/j.neuron.2015.05.038 · Cited by 728
Metadata
- 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
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
