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Cited by 933Neural dynamics and brain functionSleep and Wakefulness ResearchVisual perception and processing mechanisms

Waking state: rapid variations modulate neural and behavioral responses

Open access
McGinley, Matthew J., Vinck, Martin, Reimer, Jacob, Batista-Brito, Renata, Zagha, Edward, Cadwell, Cathryn R., Tolias, Andreas S., Cardin, Jessica A. +1 more·2015·Neuron
DOI 10.1016/j.neuron.2015.09.012PMC PMC4718218
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Abstract

The state of the brain and body constantly varies on rapid and slow time scales. These variations contribute to the apparent noisiness of sensory responses at both the neural and behavioral level. Recent investigations of rapid state changes in awake, behaving animals have provided insight into the mechanisms by which optimal sensory encoding and behavioral performance are achieved. Fluctuations in state, as indexed by pupillometry, impact both the “signal” (sensory evoked response) and the “noise” (spontaneous activity) of cortical responses. By taking these fluctuations into account, neural response (co-)variability is significantly reduced, revealing the brain to be more reliable and predictable than previously thought.

AI snapshot

Written from the paper’s full text.

TL;DR

This review argues that waking brain state changes rapidly and continuously, and that pupil diameter plus movement can index these substates. Accounting for such fluctuations reduces apparent neural variability and shows that sensory encoding and behavioral performance often peak at intermediate arousal rather than at the highest arousal.

Key findings

  • Pupil diameter tracks rapid cortical state: dilation is linked to suppression of low-frequency (about 2–10 Hz) membrane-potential/LFP rhythms and enhancement of gamma (30–80 Hz) activity, while constriction is linked to stronger low-frequency activity below a critical pupil size. This relationship appears across visual, somatosensory, and auditory cortex and also with hippocampal sharp-wave ripples.
  • State modulates sensory responses along five dimensions: response magnitude, signal-to-noise ratio, timing, variability, and noise correlations. For example, visual cortical responses are enhanced by locomotion, auditory cortical responses are largest at intermediate arousal, and noise correlations are lower during locomotion than during quiescence.
  • Behavioral performance can follow an inverted-U with arousal. In an auditory tone-in-noise detection task, mice showed maximal hit rate, shortest lick latency, best discrimination, and least bias at intermediate pupil diameters; further dilation, including during locomotion, reduced performance. Human oddball and primate saccade studies similarly showed optimal performance at mid-level pupil-indexed arousal.
  • Mice exhibit frequent state changes: the review cites more than 100 sleep–wake transitions per 24 hours, with average sleep or waking bouts lasting under 10 minutes. It also contrasts two models of arousal-dependent cortical control: a sigmoidal model and a U-shaped model of average membrane potential versus arousal.

Methods

  • Narrative review synthesizing recent work, largely in behaving mice, with relevant primate and human literature; no new primary data are reported.
  • Evidence discussed includes intracellular membrane-potential recordings, local field potentials, single-unit spiking, pupillometry, locomotion/whisking monitoring, and behavioral tasks such as auditory signal detection, visual discrimination, and saccade tasks.
  • Main analysis is conceptual integration across studies, including proposed sigmoidal and U-shaped models of arousal-dependent cortical activity and a disinhibitory VIP–SOM/PV circuit mechanism.

Limitations

  • The paper states that the study of waking substates is still in its infancy, with no consensus on how many substates exist or how to define them; it also says the review cannot account for all or even many waking substates.
  • The paper states that the precise mechanisms controlling state are not fully known, the pathways linking pupil diameter to arousal are unknown, and reasons for cell-to-cell variation in arousal responses remain unresolved.
  • Evident from the text: this is a narrative review rather than a systematic or quantitative synthesis, and many conclusions rely on cited studies in head-fixed mice, so generality across species, tasks, and cortical areas is not fully established.

Model-written summary. Check it against the paper before relying on it.

Integrity signals

Registry

Crossref · 10.1016/j.neuron.2015.09.012

Cites

173 of 173 references verified0 citation errors · 0 not checkable

Statistics

Nothing to recompute.

Claims the paper makes

0 of 299 cited sources checked · 0 supported · 0 flagged

  • Interpretationreasoning

    Taking state fluctuations into account reduces neural response variability and covariability, making the brain appear more reliable and predictable than previously thought.

    “By taking these fluctuations into account, neural response (co-)variability is significantly reduced, revealing the brain to be more reliable and predictable than previously thought.”
    Quote in the paperSubstantial claim
  • Premisecitation

    Internal brain state can fluctuate even without overt behavioral changes, as in sleep-wake transitions and within sleep stages.

    “Internal brain state can fluctuate even in the absence of overt behavioral changes – most notably in the well-characterized transitions between sleep and waking and within different stages of sleep.”
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    • cites Destexhe et al., 1999 source

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    • cites Steriade et al., 2001 source

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  • Premisecitation

    Rapid, ongoing, behaviorally relevant variations in waking state are the rule rather than the exception in animals.

    “New animal studies reveal that rapid, ongoing, and behaviorally-relevant variations in waking state are not the exception, but rather the rule”
    Quote in the paperSubstantial claim0 of 3 sources checked
    • cites Cohen and Maunsell, 2010

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    • cites McGinley et al., 2015 source

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    • cites Reimer et al., 2014 source

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  • Interpretationreasoning

    Fluctuations in brain state contribute to the apparent noisiness of sensory responses at both neural and behavioral levels.

    “These variations contribute to the apparent noisiness of sensory responses at both the neural and behavioral level.”
    Quote in the paperSubstantial claim
  • Premisecitation

    Low-frequency field potential components during slow-wave sleep correspond to alternating active (Up) and inactive (Down) periods recurring at 0.2-2 Hz.

    “Intracellular recordings in cortical neurons reveal that the low-frequency components of the field potential during slow-wave sleep correspond to alternating active (Up) and inactive (Down) periods, recurring at 0.2–2 Hz.”
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    • cites Steriade et al., 1993 source

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  • Classified as probably not a substantial claim. 9

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    Premisecitation

    Falling asleep or moving from slow-wave sleep to REM sleep produces profound changes in brain operation, including spontaneous activity, motor command execution, sensory responses, and the fidelity of internal representations.

    “Falling asleep, or moving from slow wave sleep into rapid eye movement sleep, results in profound changes in the operation of the brain (Figure 1), including changes in spontaneous activity, the ability to execute motor commands, responses to sensory stimuli and the fidelity of internal representations of the world”
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    Premisecitation

    Spontaneous variations in the human waking state markedly affect cortical responses and perceptual abilities.

    “Recently, the marked impact of apparent spontaneous variations in the human waking state on both cortical responses and perceptual abilities has begun to be more widely appreciated”
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    • cites Boly et al., 2007 source

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    • cites Fox and Raichle, 2007 source

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    • cites He, 2013

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    Premisecitation

    Waking-state variations due to arousal, attention, and awareness are less dramatic than sleep-wake changes, which has made their mechanisms more elusive.

    “By comparison, the variations in neural activity within the waking state due to changes in factors such as arousal, attention, and awareness are ostensibly less dramatic and therefore the mechanisms of waking state variations have remained more elusive”
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    • cites Harris and Thiele, 2011

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    • cites Zagha and McCormick, 2014

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    Premisecitation

    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”
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    • cites Bennett et al., 2013 source

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    • cites Crochet and Petersen, 2006

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    • cites McGinley et al., 2015 source

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    Premisecitation

    The slow oscillation is generated in cortex but influences activity throughout the brain.

    “This slow oscillation is cortically generated but influences activity throughout the brain”
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    Interpretationreasoning

    Biomarkers of waking state predict changes in animals' ability to represent and respond to stimuli and account for a significant fraction of variability in spontaneous and stimulus-driven activity and behavior.

    “All together, these biomarkers for waking states predict changes in the capability of animals to represent and respond to stimuli, and account for a significant fraction of the variability in spontaneous and stimulus-driven activity and behavior.”
    Quote in the paperSubstantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

    Premisecitation

    Slow-wave sleep is characterized by high cortical field potential power at 0.5-4 Hz, reduced muscle tone, and rolling eye movements, while waking is associated with suppressed low-frequency activity, increased muscle tone, and behaviorally relevant eye movements.

    “Classically, slow wave sleep is characterized by a high density of cortical field potential power at 0.5–4 Hz, reduced muscle tone, and rolling eye movements, while waking is associated with a relative suppression of low frequency activity (usually termed “activation” or “desynchronization”), increased muscle tone, and behaviorally relevant eye movements”
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    • cites Kryger et al., 2010

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    Premisecitation

    Changes in pupil diameter, after controlling for luminance and depth accommodation, correlate with arousal, attention, emotion, cognitive perception, brain gain, heart rate, and galvanic skin reflex, indicating tight coupling between central and peripheral nervous systems.

    “Human and animal studies have shown that changes in pupil diameter (after controlling for changes associated with luminance and depth accommodation) are correlated with arousal, attention, emotion, cognitive perception, “brain gain”, as well as heart rate and galvanic skin reflex, indicating a tight coupling between the state of the central and peripheral nervous systems”
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    • cites Alnaes et al., 2014

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    • cites Bradley et al., 2008 source

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    • cites Kahneman and Beatty, 1966

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    Premisecitation

    Spontaneous and sensory-evoked activity varies continuously and rapidly during wakefulness.

    “This work has revealed that spontaneous and sensory-evoked activity varies continuously and rapidly during wakefulness.”
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    • cites McGinley et al., 2015 source

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    • cites Reimer et al., 2014 source

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    • cites Vinck et al., 2015 source

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    Premisecitation

    The relationship between cortical membrane potential and pupil diameter depends on arousal state, with slow oscillations at low arousal and strong synaptic barrages or tonic depolarization at high arousal.

    “Additionally, the relationship between cortical membrane potential and pupil diameter is influenced by the presence of slow oscillations at low arousal states and strong barrages of synaptic activity and/or tonic depolarization at high arousal states”
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    • cites McGinley et al., 2015 source

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    Premisecitation

    Even without movement, increases in pupil diameter are associated with increased cortical activation and suppression of low-frequency rhythms.

    “Even in the absence of movement, increases in pupil diameter (dilation) were found to be associated with increases in cortical activation and suppression of low frequency rhythms.”
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    • cites McGinley et al., 2015 source

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    Premisecitation

    At intermediate arousal, infragranular cortical neurons have their most hyperpolarized and least variable average membrane potential.

    “At these intermediate arousal levels, the average membrane potential of infragranular cortical neurons is at its most hyperpolarized, and least variable, level”
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    • cites McGinley et al., 2015 source

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    Premisecitation

    Increasing arousal from intermediate to high levels, associated with brief or long-lasting pupil dilation often with locomotion, depolarizes membrane potential and increases high-frequency fluctuations from synaptic barrages.

    “Increases from intermediate to high arousal associated with brief (microdilations) or long-lasting increases in pupil diameter (often associated with locomotion), result in a depolarization of the membrane potential and increases in high-frequency membrane potential fluctuations from synaptic barrages”
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    • cites McGinley et al., 2015 source

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    Premisecitation

    Even in stable emotional states, pupil diameter fluctuates with task effort, timing of mental decisions, and changes in perception such as binocular rivalry.

    “Even in seemingly stable emotional states, pupil diameter can fluctuate with effort on a task (e.g. difficulty of performing a mathematical calculation) (Kahneman and Beatty, 1966), the timing of mental decisions (Einhauser et al., 2010), or changes in perception (e.g. with binocular rivalry) (Einhauser et al., 2008).”
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    Premisecitation

    Increasing arousal from low to intermediate levels suppresses low-frequency (1-10 Hz) activity, decreases membrane potential fluctuations, and decreases spontaneous activity.

    “Increases in arousal from low to intermediate levels result in a suppression of these low (1–10 Hz) frequency activities, a decrease in membrane potential fluctuations, and thus a decrease in spontaneous activity”
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    • cites McGinley et al., 2015 source

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    Premisecitation

    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”
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    Interpretationreasoning

    Locomotion and whisking require arousal, but arousal does not necessitate movement.

    “In short, locomotion and whisking require arousal, but arousal does not necessitate movement”
    Quote in the paperSubstantial claim

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    Premiseown data

    Initiation of locomotion is preceded by a substantial increase in pupil diameter, concurrent with reduced low-frequency cortical LFP synchronization and reduced hippocampal sharp wave and ripple oscillations.

    “Interestingly, the initiation of locomotion is preceded by a substantial increase in pupil diameter (Figures 2–4), concurrent with the reduction of low-frequency cortical local field potential synchronization and reduced hippocampal sharp wave and ripple oscillations.”
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    Interpretationreasoning

    Motor processes themselves may also regulate low-frequency synchronization in sensory cortex, or states associated with constricting and dilating pupils are distinct even at the same pupil diameter.

    “This suggests that motor processes themselves may also regulate low-frequency synchronization in sensory cortex (Schneider et al., 2014; Zagha et al., 2013) or that states associated with constricting and dilating pupils are distinct, even at the same pupil diameter”
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    Premisecitation

    Air puff-induced arousal elicits an average decrease in discharge rate of many cortical neurons, unlike the increase in neuronal activity prior to movement.

    “However, in contrast with the increase in neuronal activity period prior to movement, air puff-induced arousal elicits an average decrease in the discharge rate of many cortical neurons.”
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    • cites Vinck et al., 2015 source

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    Premisecitation

    Applying the same arousing stimulus during locomotion, when average neuronal activity is elevated, does not suppress firing, whereas a transition to locomotion following induced arousal increases neuronal discharge.

    “Application of the same arousing stimulus during locomotion, when average neuronal activity is elevated, does not result in a suppression of firing, whereas a transition to locomotion that occurs following induced arousal results in an increase in neuronal discharge”
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    Interpretationreasoning

    The variety and speed of state transitions and the ability to manipulate the probability of certain states by varying experiment timing relative to the light cycle make mice useful for further investigation.

    “The variety and speed of transitions between these states and the ability to manipulate the probability of certain states by varying the timing of the experiments relative to the light cycle make mice a useful species for further investigation along these lines.”
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    Premisecitation

    The length of sleep or active periods and the rate of transition depend on time relative to the light cycle, with frequency and duration of exploratory activity bouts greater at the beginning than at the ending of the active period.

    “The length of sleep or active periods and the rate of transition between these depends on time relative to the light cycle, with the frequency and duration of bouts of exploratory activity being much greater at the beginning, than the ending, of the active period (lights off).”
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    • cites Van Twyver, 1969 source

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    Premisecitation

    Even in the quiescent state without overt movement, pupil dilation is associated with suppression of low-frequency and enhancement of gamma-frequency cortical network activities, occurring as rapid switching or graded continuous change.

    “As described above, even in the quiescent state devoid of overt movements, pupil dilation is associated with suppression of low-frequency, and enhancement of gamma-frequency, cortical network activities that can occur as either a rapid switching (Figure 2A) or as a graded and continuous change”
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    Premisecitation

    Eliciting arousal by air puff in a quiescent mouse significantly increases pupil diameter and strongly suppresses slow rhythmic activity.

    “eliciting an increase in arousal through the delivery of an air puff to a quiescent mouse results in a significant increase in pupil diameter and strong suppression of slow rhythmic activity”
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    • cites Vinck et al., 2015 source

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    Premisecitation

    Free-ranging mice exhibit over 100 transitions between sleep and wakefulness per 24-hour period, with average sleep or waking period lasting less than 10 minutes.

    “In general, free ranging mice exhibit over 100 transitions between sleep and wakefulness per 24 hour period, with the average sleep or waking period lasting <10 minutes”
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    Premisecitation

    During movement such as whisking or locomotion, neurons in somatosensory, visual, motor, and auditory cortex maintain elevated firing rates, with the degree varying across cell types.

    “During the period of movement (whisking or locomotion), neurons in somatosensory, visual, motor, and auditory cortex maintain an elevated firing rate, the degree of which varies across cell types.”
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    Premisecitation

    In rodents, brief periods of 6-10 Hz thalamocortical oscillations known as high voltage spindles appear in the quiet resting state and are enhanced by cessation of locomotion.

    “In rodents, brief (seconds) periods of 6–10 Hz thalamocortical oscillations known as high voltage spindles can appear in the quiet resting state and are enhanced by the cessation of locomotion”
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    • cites Jando et al., 1995 source

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    Premisecitation

    Non-sensory factors such as behavioral state, motor activity, and cross-modal influences affect sensory processing and may together increase response variability.

    “Many non-sensory factors affect sensory processing, including behavioral state, motor activity and cross-modal influences (Gur et al., 1997), and their effects may collectively promote response variability (Ecker and Tolias, 2014; Goris et al., 2014; I-Chun et al., 2015).”
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    Premisecitation

    Behavioral state is an important determinant of both the temporal precision of sensory responses and gamma-band synchronization.

    “Behavioral state is an important determinant of both the temporal precision of sensory responses and gamma-band synchronization.”
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    Premisecitation

    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”
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    Premisecitation

    In cat V1, the signal-to-noise ratio (evoked/spontaneous activity) increases during waking versus sleeping, due in part to increases in spontaneous activity during sleep.

    “In cat V1, the signal-to-noise ratio (S/N; evoked/spontaneous activity) increases during waking versus sleeping, due in part to increases in spontaneous activity during sleep”
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    Premisecitation

    In auditory cortex, the signal-to-noise ratio peaks at intermediate arousal and may decrease strongly at high arousal and during locomotion.

    “In contrast, in auditory cortex, the S/N peaks at intermediate arousal levels and may decrease strongly at high arousal levels and during locomotion”
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    • cites McGinley et al., 2015 source

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    Premisecitation

    Spontaneous or causally induced increases in arousal are associated with a monotonic increase in gamma-band synchronization in LFP and relative membrane potential power, and in spike-LFP phase locking.

    “Spontaneous or causally induced increases in arousal are associated with a monotonic increase in gamma-band synchronization both in terms of local field potential and relative membrane potential power (Lee et al., 2014; Lima et al., 2011; McGinley et al., 2015; Reimer et al., 2014; Vinck et al., 2015), and spike-local field potential phase locking”
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    Premisecitation

    Changes in arousal produce marked multiplicative gain modulation of auditory cortical responses, with the largest responses at intermediate arousal.

    “Changes in arousal result in marked multiplicative gain modulation of auditory cortical responses, with the largest responses being evoked at intermediate levels of arousal”
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    • cites McGinley et al., 2015 source

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    Premisecitation

    Gamma-band (30-80 Hz) synchronization is beneficial for information coding, inter-areal transmission, and behavioral performance.

    “Several theoretical and empirical studies have suggested that one important temporal feature of cortical sensory processing is gamma-band (30–80 Hz) synchronization, which is beneficial for information coding (Vinck et al., 2010; Womelsdorf et al., 2012), inter-areal transmission (Bosman et al., 2012; Womelsdorf et al., 2007) and behavioral performance”
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    Premisecitation

    Pupil dilations during quiet wakefulness correspond to increased visual responsiveness and enhanced selectivity.

    “Pupil dilations during quiet wakefulness also correspond to an increase in visual responsiveness along with an enhancement of selectivity”
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    • cites Vinck et al., 2015 source

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    Premisecitation

    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”
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    Premisecitation

    Degradation of sensory responses by slow wave sleep and anesthesia compared to waking is well known.

    “The degradation of sensory responses by slow wave sleep and anesthesia, in comparison to waking, are well known”
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    • cites Livingstone and Hubel, 1981

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    Interpretationreasoning

    Across waking states, sensory response magnitude is substantially modulated and can be well predicted by variations in arousal.

    “Together, these findings across waking states show substantial modulation of sensory response magnitude that can be well predicted by variations in arousal.”
    Quote in the paperSubstantial claim

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    Premisecitation

    In states with prominent low frequencies in cortical network activity, sensory stimuli may trigger responses that are inappropriately weak or strong and do not optimally represent the spatiotemporal features of the stimulus.

    “In contrast, in states with prominent low frequencies in cortical network activity, sensory stimuli may trigger responses that are either inappropriately weak or strong, and which do not optimally represent the spatiotemporal features of the stimulus”
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    • cites Hasenstaub et al., 2007 source

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    Premisecitation

    Neuronal variability in firing rates is particularly high during anesthesia, possibly due to enhanced slow fluctuations.

    “Neuronal variability in firing rates is particularly high during anesthesia, possibly as a result of enhanced slow fluctuations (Arieli et al., 1996; Ecker and Tolias, 2014; Goard and Dan, 2009; Goris et al., 2014; Hasenstaub et al., 2007; I-Chun et al., 2015; Marguet and Harris, 2011; Scholvinck et al., 2015; Zagha et al., 2013).”
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    Interpretationreasoning

    A precise analysis of behavioral state explains considerable variability in noise correlations, and poor control or knowledge of behavioral state can lead to artificial inflation.

    “Thus, a precise analysis of behavioral state seems to explain considerable variability in noise correlations, and poor control or knowledge of behavioral state can lead to artificial inflation.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Interpretationreasoning

    The effects of attention and global arousal converge, suggesting that their underlying cellular/network mechanisms may be related.

    “These findings reveal a strong convergence between the effects of attention and global arousal and suggest that the underlying cellular/network mechanisms may be related.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Premisecitation

    Moderate increases in LC activity enhance cortical S/N ratio and set conditions for optimal neural and behavioral performance, but further increases to high levels can have detrimental effects.

    “Moderate increases in LC activity enhance the cortical S/N ratio and set the conditions for optimal neural and behavioral performance, but further increasing LC discharge rates to high levels can have detrimental effects (Aston-Jones and Cohen, 2005).”
    Quote in the paperSubstantial claim0 of 1 sources checked
    • cites Aston-Jones and Cohen, 2005 source

      Not checked in the free run.

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Premisecitation

    In another study, the presence of slow oscillatory events in somatosensory cortex was not detrimental to performance of a touch detection task, although the stimulus was supramaximal at all arousal levels.

    “(however, in another recent study the presence of slow oscillatory events in the somatosensory cortex was not detrimental to the performance of a touch detection task, although the strength of stimulus used was supramaximal at all arousal levels) (Sachidhanandam et al., 2013).”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites Sachidhanandam et al., 2013 source

      Not checked in the free run.

  • May combine two claims.

    Premisecitation

    Selective attention increases the S/N and both spontaneous and evoked firing rates.

    “increases the S/N and both spontaneous and evoked firing rates (Luck et al., 1997; McAdams and Maunsell, 1999b; Reynolds et al., 1999; Reynolds and Desimone, 1999)”
    Quote in the paperSubstantial claim0 of 3 sources checked
    • cites Luck et al., 1997 source

      Not checked in the free run.

    • cites McAdams and Maunsell, 1999b

      Not checked in the free run.

    • cites Reynolds et al., 1999

      Not checked in the free run.

  • May combine two claims.

    Premisecitation

    Activation of receptors for these neuromodulators at intermediate levels may enhance performance on PFC-dependent tasks, whereas further increases may impair behavioral performance and reduce neural representation in the PFC.

    “Activation of receptors for these neuromodulators at intermediate levels may enhance performance on PFC dependent tasks, whereas further increases may result in a decrement in behavioral performance and reduced neural representation of that performance in the PFC (reviewed in (Arnsten, 2009; Arnsten et al., 2012)).”
    Quote in the paperSubstantial claim0 of 2 sources checked
    • cites Arnsten, 2009 source

      Not checked in the free run.

    • cites Arnsten et al., 2012 source

      Not checked in the free run.

  • May combine two claims.

    Premisecitation

    Locomotion increases response amplitude and decreases response variability in V1.

    “Locomotion increases response amplitude and decreases response variability in V1 (Figure 5) (Erisken et al., 2014)”
    Quote in the paperSubstantial claim0 of 1 sources checked
    • cites Erisken et al., 2014 source

      Not checked in the free run.

  • May combine two claims.

    Premisecitation

    Increases in arousal/stress from low to moderate levels can facilitate performance on a difficult behavioral task, whereas further increases from moderate to severe can impair performance.

    “More than a century ago, Robert Yerkes and John Dodson (Yerkes and Dodson, 1908) proposed that increases in arousal/stress from low to moderate levels can facilitate performance on a difficult behavioral task, whereas further increases from moderate to severe can impair performance.”
    Quote in the paperSubstantial claim0 of 1 sources checked
    • cites Yerkes and Dodson, 1908 source

      Not checked in the free run.

  • May combine two claims.

    Premisecitation

    The more similar the pattern of ECoG activity to the average of all trials, the better the performance on the visual detection task, with significant decrements when ECoG activity deviated in either direction from average.

    “The more similar the pattern of ECoG activity to the average of all trials, the better the performance on the visual detection task, with significant decrements in performance when the ECoG activity deviated in either direction from average (He and Zempel, 2013).”
    Quote in the paperSubstantial claim0 of 1 sources checked
    • cites He and Zempel, 2013

      Not checked in the free run.

  • May combine two claims.

    Premiseown data

    The performance of mice on an auditory detection task was highly state dependent, with maximal hit rate, shortest lick latency, maximal discrimination, and least behavioral bias all occurring at intermediate pupil diameters.

    “Importantly, the performance of mice on this auditory detection task was highly state dependent, with maximal hit rate, shortest lick latency, maximal discrimination, and least behavioral bias all occurring at intermediate pupil diameters (Figure 7C).”
    Quote in the paperSubstantial claim0 of 1 sources checked
    • cites McGinley et al., 2015 source

      Not checked in the free run.

  • May combine two claims.

    Premisecitation

    Increases in arousal from low to intermediate were associated with a large increase in task performance, while further increases from intermediate to large were associated with a strong decrement in performance, regardless of walking.

    “Increases in arousal from low to intermediate, as indicated by increases in pupil diameter from small to medium, were associated with a large increase in task performance, while further increases in pupil diameter from intermediate to large were associated with a strong decrement in performance, whether or not the animal was walking at these large pupil diameters (Figure 7C).”
    Quote in the paperSubstantial claim0 of 1 sources checked
    • cites McGinley et al., 2015 source

      Not checked in the free run.

  • May combine two claims.

    Premisecitation

    The locus coeruleus provides the source of noradrenergic innervation, and the basal forebrain the source of cholinergic innervation, of the cerebral cortex.

    “The locus coeruleus provides the source of noradrenergic, and the basal forebrain the source of cholinergic, innervation of the cerebral cortex.”
    Quote in the paperNot a substantial claim0 of 2 sources checked
    • cites Saper et al., 2010 source

      Not checked in the free run.

    • cites Steriade and McCarley, 2005

      Not checked in the free run.

  • May combine two claims.

    Interpretationcitation

    It is likely that cell type, laminar location, behavioral context, and perhaps region of cortex are important variables in the variation between recorded cells in their response to arousal or locomotion.

    “It is likely that cell type, laminar location, behavioral context, and perhaps region of cortex are important variables (Beloozerova et al., 2003; Gentet et al., 2010; Reimer et al., 2014).”
    Quote in the paperNot a substantial claim0 of 3 sources checked
    • cites Beloozerova et al., 2003 source

      Not checked in the free run.

    • cites Gentet et al., 2010 source

      Not checked in the free run.

    • cites Reimer et al., 2014 source

      Not checked in the free run.

  • May combine two claims.

    Premisecitation

    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).”
    Quote in the paperSubstantial claim0 of 3 sources checked
    • cites Bennett et al., 2013 source

      Not checked in the free run.

    • cites Polack et al., 2013 source

      Not checked in the free run.

    • cites Reimer et al., 2014 source

      Not checked in the free run.

  • May combine two claims.

    Premisecitation

    Effects consistent with a role in arousal of pyramidal cell networks include depolarization of cortical neurons through reduction of membrane K+ currents, modulation of the h-current, and control of synaptic transmission.

    “Effects that are consistent with a role in arousal of pyramidal cell networks include depolarization of cortical neurons through the reduction of a variety of membrane K+ currents (McCormick, 1992), modulation of the h-current (Wang et al., 2007), which controls neuronal and dendritic excitability (Magee, 2000), and control of synaptic transmission, through the modulation of presynaptic terminals”
    Quote in the paperNot a substantial claim0 of 3 sources checked
    • cites McCormick, 1992 source

      Not checked in the free run.

    • cites Wang et al., 2007 source

      Not checked in the free run.

    • cites Magee, 2000 source

      Not checked in the free run.

  • May combine two claims.

    Premisecitation

    Locomotion, as a sub-state of hyper-arousal, was associated with a strong decrease in behavioral performance compared to intermediate arousal levels, which always occurred during stillness.

    “Interestingly, locomotion, as a sub-state of hyper-arousal, was associated with a strong decrease in behavioral performance, in comparison to intermediate arousal levels, which always occurred during stillness.”
    Quote in the paperSubstantial claim0 of 1 sources checked
    • cites McGinley et al., 2015 source

      Not checked in the free run.

  • Probably not a substantial claim: may not pass S4 (based).

    Interpretationreasoning

    Not tracking the beginning and ending points of changes in arousal may contribute significantly to the wide variations observed between studies in the effects of arousal on spontaneous cortical discharge rates.

    “Not tracking the beginning and ending points of changes in arousal may contribute significantly to the wide variations observed between studies in the effects of arousal on spontaneous cortical discharge rates.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Premiseown data

    All three measures exhibited an inverted U relationship with arousal, with the largest, most reliable, and highest S/N ratio responses occurring at the same intermediate pupil diameters that revealed optimal performance on the auditory tone-in-complex sound detection task.

    “All three measures exhibited an inverted U relationship with arousal, with the largest, most reliable, and highest S/N ratio responses occurring at the same intermediate pupil diameters that revealed optimal performance on the auditory tone-in-complex sound detection task (Figure 7).”
    Quote in the paperSubstantial claim0 of 1 sources checked
    • cites McGinley et al., 2015 source

      Not checked in the free run.

  • May combine two claims.

    Interpretationown data

    Arousal level robustly influences behavioral performance, and this influence can take the form of an inverted U in this task, as predicted by the curvilinear component of the Yerkes-Dodson relationship.

    “These results indicate that arousal level robustly influences behavioral performance, and this influence can take the form of an inverted U in this task, as predicted by the curvilinear component of the Yerkes-Dodson relationship (Figure 7C).”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Premisecitation

    In an auditory odd-ball task, response latency upon detection of the correct stimulus was shortest at mid-pupil diameters in human subjects and the P3 evoked potential was also maximal at this level of arousal, resulting in U (latency) and inverted-U (P3 amplitude) relationships with pupil-indexed arousal.

    “In an auditory odd-ball task, response latency upon detection of the correct stimulus was shortest at mid-pupil diameters in human subjects and the P3 evoked potential was also maximal at this level of arousal, resulting in U (latency) and inverted-U (evoked cortical field potential P3 amplitude) relationships with pupil-indexed arousal (Murphy et al., 2011).”
    Quote in the paperSubstantial claim0 of 1 sources checked
    • cites Murphy et al., 2011 source

      Not checked in the free run.

  • May combine two claims.

    Premisecitation

    Through modulation of ionic currents, release of norepinephrine or acetylcholine can control membrane potential and excitability of cortical neurons and strongly suppress generation of slow oscillations.

    “Through the modulation of ionic currents, the release of norephinephrine or acetylcholine can not only control the membrane potential and excitability of cortical neurons, but also strongly suppress the generation of slow oscillations.”
    Quote in the paperSubstantial claim0 of 1 sources checked
    • cites McCormick, 1992 source

      Not checked in the free run.

  • May combine two claims.

    Premisecitation

    Stimulation of the locus coeruleus can markedly enhance auditory cortical responses and increase learning induced plasticity.

    “Stimulation of the locus coeruleus can markedly enhance auditory cortical responses and increase learning induced plasticity (Martins and Froemke, 2015).”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites Martins and Froemke, 2015 source

      Not checked in the free run.

  • May combine two claims.

    Premisecitation

    In cortical networks, nicotinic and 5HT3A receptors are often located on particular subpopulations of GABAergic interneurons and may contribute to modulation of waking state activities through disinhibition.

    “In cortical networks, nicotinic and 5HT3A receptors are often (but not exclusively) located on particular subpopulations of GABAergic interneurons (Fu et al., 2014; Griguoli and Cherubini, 2012; Jakab and Goldman-Rakic, 2000) and may contribute to modulation of waking state activities through disinhibition.”
    Quote in the paperNot a substantial claim0 of 3 sources checked
    • cites Fu et al., 2014

      Not checked in the free run.

    • cites Griguoli and Cherubini, 2012

      Not checked in the free run.

    • cites Jakab and Goldman-Rakic, 2000

      Not checked in the free run.

  • May combine two claims.

    Interpretationreasoning

    These diverse findings strongly support a prominent role for both the central cholinergic and noradrenergic pathways in the rapid modulation of cortical state.

    “These diverse findings strongly support a prominent role for both the central cholinergic and noradrenergic pathways in the rapid modulation of cortical state.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Premisecitation

    Both cholinergic and serotoninergic systems can activate kinetically fast excitatory postsynaptic potentials in postsynaptic targets through nicotinic and 5HT3A receptors, respectively, and the discharges of both cholinergic and serotonergic neurons are strongly modulated by movement.

    “Both cholinergic and serotoninergic systems can activate kinetically fast excitatory postsynaptic potentials in postsynaptic targets through nicotinic and 5HT3A receptors, respectively, and the discharges of both cholinergic (e.g. Figure 9C) and serotonergic neurons are strongly modulated by movement (Eggermann et al., 2014; Jacobs and Fornal, 1993) (Reimer, McGinley, McCormick, Tolias, unpub”
    Quote in the paperSubstantial claim0 of 3 sources checked
    • cites Eggermann et al., 2014 source

      Not checked in the free run.

    • cites Jacobs and Fornal, 1993

      Not checked in the free run.

    • cites Reimer et al., unpublished

      Not checked in the free run.

  • Probably not a substantial claim: may not pass S2 (checkable), S3 (load-bearing).

    Interpretationreasoning

    Such fast actions may be particularly beneficial where rapid modulations in local or long range network processing are required, such as alterations in attention or in motor planning/execution.

    “Such fast actions may be particularly beneficial where rapid modulations in local or long range network processing are required, such as alterations in attention or in motor planning/execution.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Premisecitation

    Locus coeruleus neurons have been reported to discharge in close relation to pupil diameter on a time scale of tens of seconds, and electrical stimulation in the region of the locus coeruleus results in pupil dilation.

    “While the pathways that link changes in pupil diameter with arousal are currently unknown, locus coeruleus neurons have been reported to discharge in close relation to pupil diameter on a time scale of tens of seconds (Aston-Jones and Cohen, 2005; Murphy et al., 2014a) and electrical stimulation in the region of the locus coeruleus results in pupil dilation (Liu, Li, Wang, Society for Neuroscience”
    Quote in the paperNot a substantial claim0 of 3 sources checked
    • cites Aston-Jones and Cohen, 2005 source

      Not checked in the free run.

    • cites Murphy et al., 2014a

      Not checked in the free run.

    • cites Liu et al., 2014

      Not checked in the free run.

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Premisecitation

    The locus coeruleus receives synaptic inputs from multiple brain regions, such as the frontal cortex, that may be involved in arousal responses to complex stimuli, including those requiring high level cognition.

    “The locus coeruleus receives synaptic inputs from multiple brain regions, such as the frontal cortex, that may be involved in arousal responses to complex stimuli, including those requiring high level cognition(Aston-Jones and Cohen, 2005).”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites Aston-Jones and Cohen, 2005 source

      Not checked in the free run.

  • May combine two claims.

    Premisecitation

    VIP-containing cortical inhibitory interneurons project to both somatostatin and parvalbumin containing interneurons and have an inhibitory action on these cell types.

    “VIP-containing cortical inhibitory interneurons project to both somatostatin (e.g. Martinotti) and parvalbumin (e.g. basket cells) containing interneurons and have an inhibitory action on these cell types (David et al., 2007; Jiang et al., 2013; Lee et al., 2013; Pi et al., 2013).”
    Quote in the paperSubstantial claim0 of 3 sources checked
    • cites David et al., 2007 source

      Not checked in the free run.

    • cites Jiang et al., 2013 source

      Not checked in the free run.

    • cites Lee et al., 2013 source

      Not checked in the free run.

  • May combine two claims.

    Premisecitation

    VIP-containing neurons show rapid depolarization to serotoninergic and cholinergic inputs from subcortical pathways and glutamatergic inputs from higher cortical areas, positioning these interneurons as possible effectors of multiple modulatory inputs.

    “Interestingly, VIP-containing neurons show rapid depolarization to serotoninergic and cholinergic inputs from subcortical pathways and glutamatergic inputs from higher cortical areas, positioning these interneurons as possible effectors of multiple modulatory inputs.”
    Quote in the paperSubstantial claim0 of 3 sources checked
    • cites Fu et al., 2014

      Not checked in the free run.

    • cites Lee et al., 2013 source

      Not checked in the free run.

    • cites Pi et al., 2013

      Not checked in the free run.

  • Classified as probably not a substantial claim.

    Interpretationreasoning

    Accounting for rapid state fluctuations permits a more accurate investigation of the neural mechanisms underlying behavior, including sensory coding, decision-making, and motor responses.

    “allow for a more accurate exploration of the neural mechanisms of behavior at all levels, from sensory coding, decision, to motor response”
    Quote in the paperSubstantial claim
    • Rests on an assumption: The awake brain exhibits ever-changing activity patterns, many of which are state changes.
73 of 73

  • The paper relies on this without support.

    The conventional division of wakefulness into quiet and active periods fails to capture the full granularity of behavior and neural activity.

    “the prevailing approach in rodent research of dividing wakefulness into quiet and active awake periods, depending on whether animals are standing still or exhibiting exploratory movements (e.g. whisking or locomotion) almost certainly fails to capture the full granularity of both behavior and neural activity”

  • The paper relies on this without support.

    Arousal and locomotion can be partially separated in head-fixed mice by monitoring treadmill activity, pupil size, and neural activity.

    “Monitoring treadmill activity, pupil size, and neural activity has made it possible to partially disambiguate the effects of locomotion from the changes in arousal”

  • The paper relies on this without support.

    Firing rates are highly dependent on behavioral state.

    “Because firing rates are highly dependent on behavioral state, pooling neuronal responses across states is likely to dramatically increase observed neuronal variability.”

  • The paper relies on this without support.

    The waking state constantly fluctuates, even on a second by second basis.

    “Given that the waking state constantly fluctuates, even on a second by second basis, it is imperative to examine the relationship between the state of the brain/animal and its performance on behavioral tasks.”

  • The paper relies on this without support.

    Arousal, stress, and their effects on behavior are interrelated but separable.

    “Arousal, stress, and their effects on behavior are interrelated but separable.”

  • The paper relies on this without support.

    In rodents, the density and prevalence of low frequency rhythms increase over the course of the 12 hour active period since lights off.

    “For example, in rodents the density and prevalence of low frequency rhythms (Figure 1B) increase over the course of the 12 hour active period since lights off.”

  • The paper relies on this without support.

    The awake brain exhibits ever-changing activity patterns, many of which are state changes.

    “neuroscientists are faced with ever-changing patterns of activity in the awake brain, many of which take the form of state changes”
7 of 7

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?

  • Head-restrained preparations have shown that behavioral state fluctuations have a strong impact on neuronal gain and coding properties in primary sensory areas and modulate neuronal firing within brain-wide neuronal networks.

    “By employing head-restrained preparations, a growing body of work has demonstrated that behavioral state fluctuations have a strong impact on neuronal gain and coding properties in primary sensory areas36,43,66–70 and modulate neuronal firing within brain-wide neuronal networks44,71–74.”

    From Place and behavioral modulation of hippocampal neurons during immobility (2026) · cites this paper as [72]

  • Non-luminance-related pupil diameter fluctuations track neural firing in ascending neuromodulatory systems such as the locus coeruleus, and pupil diameter is a surrogate for arousal and task engagement.

    “Recent invasive electrophysiological recordings in non-human primates have shown that non-luminance-related fluctuations pupil diameter tracks with neural firing in ascending neuromodulatory systems, such as the locus coeruleus, confirming the well-established proposal (Kahneman, 1973) that pupil diameter is a surrogate measure for arousal and task engagement (McGinley et al., 2015).”

    From The Dynamics of Functional Brain Networks: Integrated Network States during Cognitive Task Performance (2016) · cites this paper as McGinley et al., 2015

  • A high-alertness state can increase sensory gain and improve behavioral performance, often quantified as shorter reaction times, during stimulus-detection tasks.

    “a high-alertness state can increase sensory gain and improve behavioral performance (Harris and Thiele, 2011; Maimon, 2011; McGinley et al., 2015)—often quantified as shorter reaction times (RTs)—during stimulus-detection tasks (Freeman, 1933; Broadbent, 1971; Aston-Jones and Cohen, 2005)”

    From Ancestral Circuits for the Coordinated Modulation of Brain State (2017) · cites this paper as McGinley et al., 2015

  • Hyper-arousal can be detrimental to performance in more complex tasks.

    “although hyper-arousal can be detrimental to performance in more complex tasks (Diamond et al., 2007; McGinley et al., 2015).”

    From Ancestral Circuits for the Coordinated Modulation of Brain State (2017) · cites this paper as McGinley et al., 2015

  • High levels of arousal did not impair performance in either task, suggesting the simple RT behavior does not exhibit the inverted U-shaped arousal-response relationship characteristic of more complex behaviors requiring decision making.

    “High levels of arousal did not impair performance in either task, suggesting that the simple RT behavior we examine here does not exhibit the inverted U-shaped arousal-response relationship that would be characteristic of more complex behaviors that require decision making (Diamond et al., 2007; McGinley et al., 2015).”

    From Ancestral Circuits for the Coordinated Modulation of Brain State (2017) · cites this paper as McGinley et al., 2015

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

Each contradiction between two passages listed here was confirmed by an independent check.

  • Reaction-time curve conflicts with the stated performance pattern

    Minor

    The text calls the relationship between reaction time and similarity to average ECoG activity an inverted U, but then says performance is best near the average and worsens with deviations in either direction. If better performance means shorter reaction time, the described reaction-time pattern has a minimum near the average, not a maximum.

1 of 1

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Related

Authors
McGinley, M. J., Vinck, M., Reimer, J., Batista-Brito, R., Zagha, E., Cadwell, C. R., Tolias, A. S., Cardin, J. A., & McCormick, D. A.
Affiliations
  • Yale University (US)
  • Baylor College of Medicine (US)
Corresponding author
  • Tolias, Andreas S.
  • Cardin, Jessica A.
  • McCormick, David A.
ORCID
Venue
Neuron
Publisher
Elsevier BV
Published
2015-09
Volume
87
Issue
6
Pages
1143-1161
ISSN
0896-6273 (ISSN-L)
DOI
10.1016/j.neuron.2015.09.012
PMC
PMC4718218
OpenAlex
W2116679324
Semantic Scholar
9951ccf408273066281346c5a29f0478117b4e37
Cited by
801
References
176
Citations by year
2026: 71 · 2025: 61 · 2024: 88 · 2023: 93 · 2022: 86 · 2021: 100 · 2020: 76 · 2019: 69 · 2018: 67 · 2017: 52 · 2016: 36 · 2015: 2
FWCI
5.15
Type
journal article
Language
en
Open access
Licence
Locations
  • Neuron (publishedVersion)
  • PubMed (publishedVersion)
  • PubMed Central (acceptedVersion)
  • eScholarship (California Digital Library) (submittedVersion)
Funders
  • Institute of Museum and Library Services
  • McKnight Foundation
  • Yale University
  • National Alliance for Research on Schizophrenia and Depression
  • National Institutes of Health (5R01N2026143, 1dp1od008301-01)
  • U.S. Public Health Service (5R01N2026143)
  • National Institute of Mental Health (F30MH095440)
  • National Eye Institute (DP1EY023176, T32 EY07001, EY022951, P30EY002520, R00EY018407, T32EY007001, R01EY022951)
  • National Institute on Deafness and Other Communication Disorders (R01DC015803, F32DC012449)
  • National Institute of General Medical Sciences (T32GM007330)
  • National Institute of Neurological Disorders and Stroke (R01NS026143)
  • National Institute of Biomedical Imaging and Bioengineering (T32EB006350)
  • National Center for Chronic Disease Prevention and Health Promotion (DP1EY023176)
Topics
  • Life Sciences › Neuroscience › Cognitive Neuroscience › Neural dynamics and brain function
  • Life Sciences › Neuroscience › Cognitive Neuroscience › Sleep and Wakefulness Research
  • Life Sciences › Neuroscience › Cognitive Neuroscience › Visual perception and processing mechanisms
Keywords
pupillometry, sensory coding, spontaneous neuronal activity, behavioral performance, neural reliability, awake behaving animals, sensory noise
MeSH terms
Action Potentials, Animals, Brain, Humans, Motor Activity, Nerve Net, Neurons, Time Factors, Wakefulness

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.

Claims read by deepseek-v4.1-flash under definition version 3 (extract-v3) on 2026-10-07.

Classified by jev-1.13-20260917 (gold-guideline-v0.2) on 2026-10-07.

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