The DOI matches its Crossref record; 173 of the 176 references it cites were found in a registry or an index; none of the 299 sources its claims cite is checked for support yet.
Waking State: Rapid Variations Modulate Neural and Behavioral Responses
Open accessAbstract
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.
Overview
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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.
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Claims the paper makes
0 of 299 cited sources checked · 0 supported · 0 flagged
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“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.”
§ Waking State: Rapid Variations Modulate Neural and Behavioral Responses > Abstract
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In the paper
“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.”
§ Waking State: Rapid Variations Modulate Neural and Behavioral Responses > Introduction
What the sources say
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In the paper
“New animal studies reveal that rapid, ongoing, and behaviorally-relevant variations in waking state are not the exception, but rather the rule”
§ Waking State: Rapid Variations Modulate Neural and Behavioral Responses > Introduction
What the sources say
Load-bearingStrength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesA conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“These variations contribute to the apparent noisiness of sensory responses at both the neural and behavioral level.”
§ Waking State: Rapid Variations Modulate Neural and Behavioral Responses > Abstract
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In the paper
“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.”
§ Waking State: Rapid Variations Modulate Neural and Behavioral Responses > Introduction > State Dependent Brain Activity
What the sources say
Strength:plain· not yet calibratedCausal:correlational· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes? Load-bearing: unclear✓ Based: passesIn the paper
“Intracellular recordings in cortical neurons of cats reveal that the waking state involves suppression of the inactive, or Down, periods of cortical activity, resulting in a continuous depolarization of neurons towards firing threshold, even in quietly awake animals”
§ Waking State: Rapid Variations Modulate Neural and Behavioral Responses > Introduction > State Dependent Brain Activity
What the sources say
- Not checked yetcites Steriade et al., 2001 source
Strength:plain· not yet calibratedCausal:direct· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes? Load-bearing: unclear✓ Based: passesNone of the sources cited for this claim have been checked yet.
In the paper
“These variations in state exert an effect on sensory evoked neural activity that can be as significant as variations in the sensory stimulus itself”
§ Waking State: Rapid Variations Modulate Neural and Behavioral Responses > Introduction
What the sources say
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesNone of the sources cited for this claim have been checked yet.
In the paper
“These changes are sometimes coupled with overt movements such as whisking or locomotion”
§ Waking State: Rapid Variations Modulate Neural and Behavioral Responses > Introduction
What the sources say
Strength:hedged· not yet calibratedCausal:correlational· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes? Load-bearing: unclear✓ Based: passesNone of the sources cited for this claim have been checked yet.
In the paper
“In human studies, drowsiness during the performance of a routine task, such as simulated driving, can be associated with wide variations in arousal and performance that are reflected by large fluctuations in pupil diameter”
§ Waking State: Rapid Variations Modulate Neural and Behavioral Responses > Variations in Pupil Diameter Track Changes in Brain State
What the sources say
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesNone of the sources cited for this claim have been checked yet.
In the paper
“It has become increasingly clear that the waking state contains continuous transitions between numerous sub-states that are associated with significant changes in sensory-motor processing and behavioral performance”
§ Waking State: Rapid Variations Modulate Neural and Behavioral Responses > Introduction > State Dependent Brain Activity
What the sources say
- Not checked yetcites Buzsaki, 2006
- Not checked yetcites Cohen and Maunsell, 2010
- Not checked yetcites McGinley et al., 2015 source
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passes
- It may state two separate claims as one. 66
- Probably not a substantial claim. 9
None of the sources cited for this claim have been checked yet.
In the paper
“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”
§ Waking State: Rapid Variations Modulate Neural and Behavioral Responses > Introduction
What the sources say
Strength:plain· not yet calibratedCausal:direct· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes? Load-bearing: unclear✓ Based: passesIt may state two separate claims as one.
None of the sources cited for this claim have been checked yet.
In the paper
“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”
§ Waking State: Rapid Variations Modulate Neural and Behavioral Responses > Introduction
What the sources say
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
None of the sources cited for this claim have been checked yet.
In the paper
“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”
§ Waking State: Rapid Variations Modulate Neural and Behavioral Responses > Introduction
What the sources say
- Not checked yetcites Harris and Thiele, 2011
- Not checked yetcites Zagha and McCormick, 2014
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
None of the sources cited for this claim have been checked yet.
In the 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”
§ Waking State: Rapid Variations Modulate Neural and Behavioral Responses > Introduction > State Dependent Brain Activity
What the sources say
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
None of the sources cited for this claim have been checked yet.
In the paper
“This slow oscillation is cortically generated but influences activity throughout the brain”
§ Waking State: Rapid Variations Modulate Neural and Behavioral Responses > Introduction > State Dependent Brain Activity
What the sources say
Strength:plain· not yet calibratedCausal:direct· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes? Load-bearing: unclear✓ Based: passesIt may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“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.”
§ Waking State: Rapid Variations Modulate Neural and Behavioral Responses > Introduction
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
In the paper
“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”
§ Waking State: Rapid Variations Modulate Neural and Behavioral Responses > Introduction > State Dependent Brain Activity
What the sources say
- Not checked yetcites Kryger et al., 2010
Strength:plain· not yet calibratedCausal:correlational· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passesProbably not a substantial claim. The paper’s conclusions may not depend on it. It may state two separate claims as one.
None of the sources cited for this claim have been checked yet.
In the paper
“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”
§ Waking State: Rapid Variations Modulate Neural and Behavioral Responses > Variations in Pupil Diameter Track Changes in Brain State
What the sources say
- Not checked yetcites Alnaes et al., 2014
- Not checked yetcites Bradley et al., 2008 source
- Not checked yetcites Kahneman and Beatty, 1966
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
None of the sources cited for this claim have been checked yet.
In the paper
“This work has revealed that spontaneous and sensory-evoked activity varies continuously and rapidly during wakefulness.”
§ Waking State: Rapid Variations Modulate Neural and Behavioral Responses > Introduction
What the sources say
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
In the paper
“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”
§ Waking State: Rapid Variations Modulate Neural and Behavioral Responses > Variations in Pupil Diameter Track Changes in Brain State
What the sources say
- Not checked yetcites McGinley et al., 2015 source
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
None of the sources cited for this claim have been checked yet.
In the paper
“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.”
§ Waking State: Rapid Variations Modulate Neural and Behavioral Responses > Variations in Pupil Diameter Track Changes in Brain State
What the sources say
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
In the paper
“At these intermediate arousal levels, the average membrane potential of infragranular cortical neurons is at its most hyperpolarized, and least variable, level”
§ Waking State: Rapid Variations Modulate Neural and Behavioral Responses > Variations in Pupil Diameter Track Changes in Brain State
What the sources say
- Not checked yetcites McGinley et al., 2015 source
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
In the paper
“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”
§ Waking State: Rapid Variations Modulate Neural and Behavioral Responses > Variations in Pupil Diameter Track Changes in Brain State
What the sources say
- Not checked yetcites McGinley et al., 2015 source
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
None of the sources cited for this claim have been checked yet.
In the paper
“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).”
§ Waking State: Rapid Variations Modulate Neural and Behavioral Responses > Variations in Pupil Diameter Track Changes in Brain State
What the sources say
- Not checked yetcites Kahneman and Beatty, 1966
- Not checked yetcites Einhauser et al., 2010
- Not checked yetcites Einhauser et al., 2008 source
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
In the paper
“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”
§ Waking State: Rapid Variations Modulate Neural and Behavioral Responses > Variations in Pupil Diameter Track Changes in Brain State
What the sources say
- Not checked yetcites McGinley et al., 2015 source
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
None of the sources cited for this claim have been checked yet.
In the paper
“Previous studies had shown that active behaviors such as locomotion and whisking were associated with a reduction in low-frequency rhythmic activity”
§ Waking State: Rapid Variations Modulate Neural and Behavioral Responses > Variations in Pupil Diameter Track Changes in Brain State
What the sources say
- Not checked yetcites Bennett et al., 2013 source
- Not checked yetcites Crochet and Petersen, 2006
- Not checked yetcites Niell and Stryker, 2010
Strength:plain· not yet calibratedCausal:correlational· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passesProbably not a substantial claim. The paper’s conclusions may not depend on it.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“In short, locomotion and whisking require arousal, but arousal does not necessitate movement”
§ Waking State: Rapid Variations Modulate Neural and Behavioral Responses > Brain State and Exploratory Behaviors > States defined by pupillometry and locomotion in head-fixed mice
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
None of the sources cited for this claim have been checked yet.
In the paper
“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.”
§ Waking State: Rapid Variations Modulate Neural and Behavioral Responses > Brain State and Exploratory Behaviors > States defined by pupillometry and locomotion in head-fixed mice
What the sources say
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
None of the sources cited for this claim have been checked yet.
In the paper
“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”
§ Waking State: Rapid Variations Modulate Neural and Behavioral Responses > Brain State and Exploratory Behaviors > States defined by pupillometry and locomotion in head-fixed mice
What the sources say
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
In the paper
“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.”
§ Waking State: Rapid Variations Modulate Neural and Behavioral Responses > Brain State and Exploratory Behaviors > States defined by pupillometry and locomotion in head-fixed mice
What the sources say
- Not checked yetcites Vinck et al., 2015 source
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
In the paper
“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”
§ Waking State: Rapid Variations Modulate Neural and Behavioral Responses > Brain State and Exploratory Behaviors > States defined by pupillometry and locomotion in head-fixed mice
What the sources say
- Not checked yetcites Vinck et al., 2015 source
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“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.”
§ Waking State: Rapid Variations Modulate Neural and Behavioral Responses > Brain State and Exploratory Behaviors > Mice Exhibit Large, Rapid and Frequent State Changes
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesProbably not a substantial claim. It may state two separate claims as one.
In the paper
“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).”
§ Waking State: Rapid Variations Modulate Neural and Behavioral Responses > Brain State and Exploratory Behaviors > Mice Exhibit Large, Rapid and Frequent State Changes
What the sources say
- Not checked yetcites Van Twyver, 1969 source
Strength:plain· not yet calibratedCausal:correlational· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes? Load-bearing: unclear✓ Based: passesIt may state two separate claims as one.
None of the sources cited for this claim have been checked yet.
In the paper
“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”
§ Waking State: Rapid Variations Modulate Neural and Behavioral Responses > Brain State and Exploratory Behaviors > States defined by pupillometry and locomotion in head-fixed mice
What the sources say
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
In the paper
“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”
§ Waking State: Rapid Variations Modulate Neural and Behavioral Responses > Brain State and Exploratory Behaviors > States defined by pupillometry and locomotion in head-fixed mice
What the sources say
- Not checked yetcites Vinck et al., 2015 source
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
In the paper
“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”
§ Waking State: Rapid Variations Modulate Neural and Behavioral Responses > Brain State and Exploratory Behaviors > Mice Exhibit Large, Rapid and Frequent State Changes
What the sources say
- Not checked yetcites Van Twyver, 1969 source
Strength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes? Load-bearing: unclear✓ Based: passesIt may state two separate claims as one.
None of the sources cited for this claim have been checked yet.
In the paper
“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.”
§ Waking State: Rapid Variations Modulate Neural and Behavioral Responses > Brain State and Exploratory Behaviors > States defined by pupillometry and locomotion in head-fixed mice
What the sources say
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
In the paper
“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”
§ Waking State: Rapid Variations Modulate Neural and Behavioral Responses > Brain State and Exploratory Behaviors > States defined by pupillometry and locomotion in head-fixed mice
What the sources say
- Not checked yetcites Jando et al., 1995 source
Strength:hedged· not yet calibratedCausal:direct· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes? Load-bearing: unclear✓ Based: passesIt may state two separate claims as one.
None of the sources cited for this claim have been checked yet.
In the paper
“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).”
§ Waking State: Rapid Variations Modulate Neural and Behavioral Responses > Brain State Shapes Sensory Responses > Effects of State on Neuronal Variability
What the sources say
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
None of the sources cited for this claim have been checked yet.
In the paper
“Behavioral state is an important determinant of both the temporal precision of sensory responses and gamma-band synchronization.”
§ Waking State: Rapid Variations Modulate Neural and Behavioral Responses > Brain State Shapes Sensory Responses > Effects of State on Response Timing
What the sources say
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
None of the sources cited for this claim have been checked yet.
In the paper
“In mouse visual cortex, the S/N is small at low arousal levels, and increases at high arousal levels and during locomotion”
§ Waking State: Rapid Variations Modulate Neural and Behavioral Responses > Brain State Shapes Sensory Responses > Effect of State on Signal-to-Noise Ratio
What the sources say
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
In the paper
“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”
§ Waking State: Rapid Variations Modulate Neural and Behavioral Responses > Brain State Shapes Sensory Responses > Effect of State on Signal-to-Noise Ratio
What the sources say
- Not checked yetcites Livingstone and Hubel, 1981
Strength:plain· not yet calibratedCausal:direct· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes? Load-bearing: unclear✓ Based: passesIt may state two separate claims as one.
In the paper
“In contrast, in auditory cortex, the S/N peaks at intermediate arousal levels and may decrease strongly at high arousal levels and during locomotion”
§ Waking State: Rapid Variations Modulate Neural and Behavioral Responses > Brain State Shapes Sensory Responses > Effect of State on Signal-to-Noise Ratio
What the sources say
- Not checked yetcites McGinley et al., 2015 source
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
None of the sources cited for this claim have been checked yet.
In the paper
“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”
§ Waking State: Rapid Variations Modulate Neural and Behavioral Responses > Brain State Shapes Sensory Responses > Effects of State on Response Timing
What the sources say
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
In the paper
“Changes in arousal result in marked multiplicative gain modulation of auditory cortical responses, with the largest responses being evoked at intermediate levels of arousal”
§ Waking State: Rapid Variations Modulate Neural and Behavioral Responses > Brain State Shapes Sensory Responses > Effects of State on Response Magnitude
What the sources say
- Not checked yetcites McGinley et al., 2015 source
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
None of the sources cited for this claim have been checked yet.
In the paper
“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”
§ Waking State: Rapid Variations Modulate Neural and Behavioral Responses > Brain State Shapes Sensory Responses > Effects of State on Response Timing
What the sources say
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
In the paper
“Pupil dilations during quiet wakefulness also correspond to an increase in visual responsiveness along with an enhancement of selectivity”
§ Waking State: Rapid Variations Modulate Neural and Behavioral Responses > Brain State Shapes Sensory Responses > Effects of State on Response Magnitude
What the sources say
- Not checked yetcites Vinck et al., 2015 source
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
None of the sources cited for this claim have been checked yet.
In the paper
“In V1, locomotion causes both multiplicative and additive enhancements of responses to drifting gratings”
§ Waking State: Rapid Variations Modulate Neural and Behavioral Responses > Brain State Shapes Sensory Responses > Effects of State on Response Magnitude
What the sources say
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
None of the sources cited for this claim have been checked yet.
In the paper
“The degradation of sensory responses by slow wave sleep and anesthesia, in comparison to waking, are well known”
§ Waking State: Rapid Variations Modulate Neural and Behavioral Responses > Brain State Shapes Sensory Responses > Effects of State on Response Magnitude
What the sources say
- Not checked yetcites Livingstone and Hubel, 1981
- Not checked yetcites Marguet and Harris, 2011
Strength:boosted· not yet calibratedCausal:direct· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passesProbably not a substantial claim. The paper’s conclusions may not depend on it.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Together, these findings across waking states show substantial modulation of sensory response magnitude that can be well predicted by variations in arousal.”
§ Waking State: Rapid Variations Modulate Neural and Behavioral Responses > Brain State Shapes Sensory Responses > Effects of State on Response Magnitude
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
None of the sources cited for this claim have been checked yet.
In the paper
“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”
§ Waking State: Rapid Variations Modulate Neural and Behavioral Responses > Brain State Shapes Sensory Responses
What the sources say
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
None of the sources cited for this claim have been checked yet.
In the paper
“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).”
§ Waking State: Rapid Variations Modulate Neural and Behavioral Responses > Brain State Shapes Sensory Responses > Effects of State on Neuronal Variability
What the sources say
- Not checked yetcites Arieli et al., 1996 source
- Not checked yetcites Ecker and Tolias, 2014
- Not checked yetcites Goard and Dan, 2009
Strength:hedged· not yet calibratedCausal:conditional· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes? Load-bearing: unclear✓ Based: passesIt may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“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.”
§ Waking State: Rapid Variations Modulate Neural and Behavioral Responses > Brain State Shapes Sensory Responses > Effects of State on Noise Correlations
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“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.”
§ Waking State: Rapid Variations Modulate Neural and Behavioral Responses > Brain State Shapes Sensory Responses > Attentional States are Sub-states of Waking
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In the paper
“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).”
§ Waking State: Rapid Variations Modulate Neural and Behavioral Responses > Neural Correlates of State-Dependent Optimal Performance
What the sources say
- Not checked yetcites Aston-Jones and Cohen, 2005 source
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
In the paper
“(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).”
§ Waking State: Rapid Variations Modulate Neural and Behavioral Responses > Neural Correlates of State-Dependent Optimal Performance
What the sources say
- Not checked yetcites Sachidhanandam et al., 2013 source
Strength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passesProbably not a substantial claim. The paper’s conclusions may not depend on it.
None of the sources cited for this claim have been checked yet.
In the paper
“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)”
§ Waking State: Rapid Variations Modulate Neural and Behavioral Responses > Brain State Shapes Sensory Responses > Attentional States are Sub-states of Waking
What the sources say
- Not checked yetcites Luck et al., 1997 source
- Not checked yetcites McAdams and Maunsell, 1999b
- Not checked yetcites Reynolds et al., 1999
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
None of the sources cited for this claim have been checked yet.
In the paper
“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)).”
§ Waking State: Rapid Variations Modulate Neural and Behavioral Responses > Neural Correlates of State-Dependent Optimal Performance
What the sources say
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
In the paper
“Locomotion increases response amplitude and decreases response variability in V1 (Figure 5) (Erisken et al., 2014)”
§ Waking State: Rapid Variations Modulate Neural and Behavioral Responses > Brain State Shapes Sensory Responses > Effects of State on Neuronal Variability
What the sources say
- Not checked yetcites Erisken et al., 2014 source
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
In the paper
“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.”
§ Waking State: Rapid Variations Modulate Neural and Behavioral Responses > Neural Correlates of State-Dependent Optimal Performance
What the sources say
- Not checked yetcites Yerkes and Dodson, 1908 source
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
In the paper
“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).”
§ Waking State: Rapid Variations Modulate Neural and Behavioral Responses > Neural Correlates of State-Dependent Optimal Performance
What the sources say
- Not checked yetcites He and Zempel, 2013
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
In the paper
“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).”
§ Waking State: Rapid Variations Modulate Neural and Behavioral Responses > Neural Correlates of State-Dependent Optimal Performance
What the sources say
- Not checked yetcites McGinley et al., 2015 source
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
In the paper
“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).”
§ Waking State: Rapid Variations Modulate Neural and Behavioral Responses > Neural Correlates of State-Dependent Optimal Performance
What the sources say
- Not checked yetcites McGinley et al., 2015 source
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
None of the sources cited for this claim have been checked yet.
In the paper
“The locus coeruleus provides the source of noradrenergic, and the basal forebrain the source of cholinergic, innervation of the cerebral cortex.”
§ Waking State: Rapid Variations Modulate Neural and Behavioral Responses > Cellular and Network Mechanisms of State Control > Neural Control of Waking State – Neuromodulatory Influences
What the sources say
- Not checked yetcites Saper et al., 2010 source
- Not checked yetcites Steriade and McCarley, 2005
Strength:plain· not yet calibratedCausal:direct· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes? Load-bearing: unclear✓ Based: passesIt may state two separate claims as one.
None of the sources cited for this claim have been checked yet.
In the paper
“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).”
§ Waking State: Rapid Variations Modulate Neural and Behavioral Responses > Cellular and Network Mechanisms of State Control > Intracellular Mechanisms of Variations in the Waking State
What the sources say
Strength:hedged· not yet calibratedCausal:conditional· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes? Load-bearing: unclear✓ Based: passesIt may state two separate claims as one.
None of the sources cited for this claim have been checked yet.
In the 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).”
§ Waking State: Rapid Variations Modulate Neural and Behavioral Responses > Neural Correlates of State-Dependent Optimal Performance
What the sources say
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
None of the sources cited for this claim have been checked yet.
In the paper
“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”
§ Waking State: Rapid Variations Modulate Neural and Behavioral Responses > Cellular and Network Mechanisms of State Control > Neural Control of Waking State – Neuromodulatory Influences
What the sources say
Strength:hedged· not yet calibratedCausal:conditional· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes? Load-bearing: unclear✓ Based: passesIt may state two separate claims as one.
In the paper
“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.”
§ Waking State: Rapid Variations Modulate Neural and Behavioral Responses > Neural Correlates of State-Dependent Optimal Performance
What the sources say
- Not checked yetcites McGinley et al., 2015 source
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“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.”
§ Waking State: Rapid Variations Modulate Neural and Behavioral Responses > Cellular and Network Mechanisms of State Control > Intracellular Mechanisms of Variations in the Waking State
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✗ Based: failsProbably not a substantial claim. The paper may give no reason why it holds.
In the paper
“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).”
§ Waking State: Rapid Variations Modulate Neural and Behavioral Responses > Neural Correlates of State-Dependent Optimal Performance
What the sources say
- Not checked yetcites McGinley et al., 2015 source
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“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).”
§ Waking State: Rapid Variations Modulate Neural and Behavioral Responses > Neural Correlates of State-Dependent Optimal Performance
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
In the paper
“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).”
§ Waking State: Rapid Variations Modulate Neural and Behavioral Responses > Neural Correlates of State-Dependent Optimal Performance
What the sources say
- Not checked yetcites Murphy et al., 2011 source
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
In the paper
“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.”
§ Waking State: Rapid Variations Modulate Neural and Behavioral Responses > Cellular and Network Mechanisms of State Control > Neural Control of Waking State – Neuromodulatory Influences
What the sources say
- Not checked yetcites McCormick, 1992 source
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
In the paper
“Stimulation of the locus coeruleus can markedly enhance auditory cortical responses and increase learning induced plasticity (Martins and Froemke, 2015).”
§ Waking State: Rapid Variations Modulate Neural and Behavioral Responses > Cellular and Network Mechanisms of State Control > Neural Control of Waking State – Neuromodulatory Influences
What the sources say
- Not checked yetcites Martins and Froemke, 2015 source
Strength:plain· not yet calibratedCausal:direct· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes? Load-bearing: unclear✓ Based: passesIt may state two separate claims as one.
None of the sources cited for this claim have been checked yet.
In the paper
“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.”
§ Waking State: Rapid Variations Modulate Neural and Behavioral Responses > Cellular and Network Mechanisms of State Control > Neural Control of Waking State – Neuromodulatory Influences
What the sources say
- Not checked yetcites Fu et al., 2014
- Not checked yetcites Griguoli and Cherubini, 2012
- Not checked yetcites Jakab and Goldman-Rakic, 2000
Strength:hedged· not yet calibratedCausal:conditional· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes? Load-bearing: unclear✓ Based: passesIt may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“These diverse findings strongly support a prominent role for both the central cholinergic and noradrenergic pathways in the rapid modulation of cortical state.”
§ Waking State: Rapid Variations Modulate Neural and Behavioral Responses > Cellular and Network Mechanisms of State Control > Neural Control of Waking State – Neuromodulatory Influences
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
None of the sources cited for this claim have been checked yet.
In the paper
“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”
§ Waking State: Rapid Variations Modulate Neural and Behavioral Responses > Cellular and Network Mechanisms of State Control > Neural Control of Waking State – Neuromodulatory Influences
What the sources say
- Not checked yetcites Eggermann et al., 2014 source
- Not checked yetcites Jacobs and Fornal, 1993
- Not checked yetcites Reimer et al., unpublished
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“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.”
§ Waking State: Rapid Variations Modulate Neural and Behavioral Responses > Cellular and Network Mechanisms of State Control > Neural Control of Waking State – Neuromodulatory Influences
Strength:hedged· not yet calibratedCausal:conditional· not yet calibratedTests✓ Asserted: passes✗ Checkable: fails✗ Load-bearing: fails✓ Based: passesProbably not a substantial claim. It may be too vague to check against evidence. The paper’s conclusions may not depend on it.
None of the sources cited for this claim have been checked yet.
In the paper
“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”
§ Waking State: Rapid Variations Modulate Neural and Behavioral Responses > Cellular and Network Mechanisms of State Control > Neural Control of Waking State – Neuromodulatory Influences
What the sources say
- Not checked yetcites Aston-Jones and Cohen, 2005 source
- Not checked yetcites Murphy et al., 2014a
- Not checked yetcites Liu et al., 2014
Strength:plain· not yet calibratedCausal:direct· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes? Load-bearing: unclear✓ Based: passesIt may state two separate claims as one.
In the paper
“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).”
§ Waking State: Rapid Variations Modulate Neural and Behavioral Responses > Cellular and Network Mechanisms of State Control > Neural Control of Waking State – Neuromodulatory Influences
What the sources say
- Not checked yetcites Aston-Jones and Cohen, 2005 source
Strength:hedged· not yet calibratedCausal:conditional· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passesProbably not a substantial claim. The paper’s conclusions may not depend on it.
None of the sources cited for this claim have been checked yet.
In the paper
“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).”
§ Waking State: Rapid Variations Modulate Neural and Behavioral Responses > Cellular and Network Mechanisms of State Control > Neural Control of Waking State – Local Circuit Mechanisms
What the sources say
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
None of the sources cited for this claim have been checked yet.
In the paper
“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.”
§ Waking State: Rapid Variations Modulate Neural and Behavioral Responses > Cellular and Network Mechanisms of State Control > Neural Control of Waking State – Local Circuit Mechanisms
What the sources say
- Not checked yetcites Fu et al., 2014
- Not checked yetcites Lee et al., 2013 source
- Not checked yetcites Pi et al., 2013
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“allow for a more accurate exploration of the neural mechanisms of behavior at all levels, from sensory coding, decision, to motor response”
§ Waking State: Rapid Variations Modulate Neural and Behavioral Responses > Conclusions
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesProbably not a substantial claim.
- Rests on an assumption: The awake brain exhibits ever-changing activity patterns, many of which are state changes.
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”
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?
The cited source says what the claim attributes to it.
In the citing paper
“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]
In the citing paper
“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
In the citing paper
“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
In the citing paper
“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
In the citing paper
“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
MinorThe 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.
“In a visual detection task, the reaction time of human subjects exhibited an inverted-U relationship with the degree to which ECoG activity prior to cue onset was similar to the average ECoG level.”
“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).”
Citations
Cites
Neural Mechanisms of Selective Visual Attention
Desimone, R., & Duncan, J. (1995) · Annual Review of Neuroscience · doi:10.1146/annurev.ne.18.030195.001205 · Cited by 8,388 · cited 3×
“One focuses on the information transfer between downstream target and distractor populations (e.g. area V1), who compete for the resources of upstream populations responding to both target and distractor stimuli (e.g. area V4; (Desimone and Duncan, 1995)).”
The relation of strength of stimulus to rapidity of habit formation
Yerkes, R. M., & Dodson, J. D. (1908) · Journal of Comparative Neurology and Psychology · doi:10.1002/cne.920180503 · Cited by 6,911
Spontaneous fluctuations in brain activity observed with functional magnetic resonance imaging
Fox, M. D., & Raichle, M. E. (2007) · Nature Reviews Neuroscience · doi:10.1038/nrn2201 · Cited by 6,700 · cited 1×
“…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 (Boly et al., 2007; Fox and Raichle, 2007; He, 2013; Hesselmann et al., 2008a; Hesselmann et al., 2008b; Palva and Palva, 2011).”
Principles and Practice of Sleep Medicine
Kryger, M. H., Roth, T. G., & Dement, W. C. (2011) · Elsevier eBooks · doi:10.1016/c2009-0-59875-3 · Cited by 5,118
Buzsáki, G. (2006) · doi:10.1093/acprof:oso/9780195301069.001.0001 · Cited by 4,873 · cited 6×
“Transitions from locomotion to quiescence, or from externally oriented movements (e.g. exploration) towards internally oriented movements (e.g. grooming, consuming) are associated with a rapid decrease of theta activity in the hippocampus (Buzsaki, 2006; Buzsaki et al., 2003).”
InfluentialAston-Jones, G., & Cohen, J. D. (2005) · Annual Review of Neuroscience · doi:10.1146/annurev.neuro.28.061604.135709 · Cited by 4,472 · cited 5×
“Pharmacological manipulations of cholinergic and noradrenergic receptors can dramatically alter cortical responsiveness and behavioral performance in a manner consistent with cortical activation by these two neuromodulators (Aston-Jones and Cohen, 2005).”
InfluentialThalamocortical oscillations in the sleeping and aroused brain
Steriade, M., McCormick, D. A., & Sejnowski, T. J. (1993) · Science · doi:10.1126/science.8235588 · Cited by 3,564 · cited 1×
“This slow oscillation is cortically generated but influences activity throughout the brain (Figure 1A) (Ros et al., 2009; Steriade et al., 1993; Steriade et al., 2001).”
Self-citationStress signalling pathways that impair prefrontal cortex structure and function
Arnsten, A. F. T. (2009) · Nature Reviews Neuroscience · doi:10.1038/nrn2648 · Cited by 3,299 · cited 2×
“Pharmacological investigations indicate that this relationship depends upon the level of release of neuromodulators, such as dopamine and norepinephrine (Arnsten, 2009; Arnsten et al., 2012).”
Modulation of Oscillatory Neuronal Synchronization by Selective Visual Attention
Fries, P., Reynolds, J. H., Rorie, A. E., & Desimone, R. (2001) · Science · doi:10.1126/science.1055465 · Cited by 2,786 · cited 1×
“…(Cohen and Maunsell, 2009; Mitchell et al., 2009), 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), and enhances gamma-synchronization (Fries et al., 2001; Gregoriou et al., 2009).”
Canonical Microcircuits for Predictive Coding
Bastos, A. M., Usrey, W. M., Adams, R. A., Mangun, G. R., Fries, P., & Friston, K. J. (2012) · Neuron · doi:10.1016/j.neuron.2012.10.038 · Cited by 2,421 · cited 1×
“In addition to arousal effects, this increase in activity may also represent pre-movement preparatory signals (Bastos et al., 2012; Bruce and Goldberg, 1985; Carvell et al., 1996; Georgopoulos et al., 1982).”
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Neural Circuitry of Wakefulness and Sleep
Scammell, T. E., Arrigoni, E., & Lipton, J. O. (2017) · Neuron · doi:10.1016/j.neuron.2017.01.014 · Cited by 966
“Blue circles with hatching denote NREM sleep-promoting nuclei. much less sleep after lesions of the anterior hypothalamus (McGinty and Sterman, 1968).”
Shine, J. M., Bissett, P. G., Bell, P. T., Koyejo, O., Balsters, J. H., Gorgolewski, K. J., Moodie, C. A., & Poldrack, R. A. (2016) · Neuron · doi:10.1016/j.neuron.2016.09.018 · Cited by 886
“In our final experiment, we demonstrated that the fluctuations in network cartography in the resting state correlate with changes in pupil diameter (Figure 4), which itself is a marker of arousal and behavioral engagement (McGinley et al., 2015).”
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
Self-citationElectrophysiological, transcriptomic and morphologic profiling of single neurons using Patch-seq
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Self-citationPupil-linked arousal is driven by decision uncertainty and alters serial choice bias
Urai, A. E., Braun, A., & Donner, T. H. (2017) · Nature Communications · doi:10.1038/ncomms14637 · Cited by 466
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Self-citationGeneral anesthesia decouples cortical pyramidal neurons
Suzuki, M., & Larkum, M. E. (2020) · Cell · doi:10.1016/j.cell.2020.01.024 · Cited by 348
Dynamic modulation of decision biases by brainstem arousal systems
de Gee, J. W., Colizoli, O., Kloosterman, N. A., Knapen, T. H. J., Nieuwenhuis, S., & Donner, T. H. (2017) · eLife · doi:10.7554/elife.23232 · Cited by 312
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BackgroundMethodResultInfluentialLarge-scale neural recordings call for new insights to link brain and behavior
Urai, A. E., Doiron, B., Leifer, A. M., & Churchland, A. K. (2022) · Nature Neuroscience · doi:10.1038/s41593-021-00980-9 · Cited by 347
“Recent work has increasingly appreciated the large role of internal states 147,148 and rich, spontaneous behaviors 18,28,109 as crucial predictors of trial-to-trial neural variability (Figure 4g).”
BackgroundNeuromodulatory Influences on Integration and Segregation in the Brain
Shine, J. M. (2019) · Trends in Cognitive Sciences · doi:10.1016/j.tics.2019.04.002 · Cited by 328
“, inhibited or ‘Down’) membrane potentials, respectively [33,37].”
Mechanisms underlying gain modulation in the cortex
Ferguson, K. A., & Cardin, J. A. (2020) · Nature Reviews Neuroscience · doi:10.1038/s41583-019-0253-y · Cited by 327
Self-citationBehavior needs neural variability
Waschke, L., Kloosterman, N. A., Obleser, J., & Garrett, D. D. (2021) · Neuron · doi:10.1016/j.neuron.2021.01.023 · Cited by 317
Layer-specific modulation of neocortical dendritic inhibition during active wakefulness
Muñoz, W., Tremblay, R., Levenstein, D., & Rudy, B. (2017) · Science · doi:10.1126/science.aag2599 · Cited by 305
Neuromodulation of brain state and behavior
McCormick, D. A., Nestvogel, D. B., & He, B. J. (2020) · Annual Review of Neuroscience · doi:10.1146/annurev-neuro-100219-105424 · Cited by 303
Self-citationArousal Effects on Pupil Size, Heart Rate, and Skin Conductance in an Emotional Face Task
Wang, C., Baird, T., Huang, J. C. H., Coutinho, J., Brien, D. C., & Munoz, D. P. (2018) · Frontiers in Neurology · doi:10.3389/fneur.2018.01029 · Cited by 340
Sensorimotor processing in the rodent barrel cortex
Petersen, C. C. H. (2019) · Nature reviews. Neuroscience · doi:10.1038/s41583-019-0200-y · Cited by 283
Video-rate volumetric functional imaging of the brain at synaptic resolution
Lu, R., Sun, W., Liang, Y., Kerlin, A., Bierfeld, J., Seelig, J. D., Wilson, D. E., Scholl, B., Mohar, B., Tanimoto, M., et al. (2017) · Nature Neuroscience · doi:10.1038/nn.4516 · Cited by 277
Global waves synchronize the brain’s functional systems with fluctuating arousal
Raut, R. V., Snyder, A. Z., Mitra, A., Yellin, D., Fujii, N., Malach, R., & Raichle, M. E. (2021) · Science Advances · doi:10.1126/sciadv.abf2709 · Cited by 267
“Nonetheless, we expect that the persistence of these waves during task states is likely to account for a substantial fraction of variability observed in task-evoked brain responses and behavioral performance (2, 28, 82).”
BackgroundNeuronal Mechanisms for Sleep/Wake Regulation and Modulatory Drive
Eban-Rothschild, A., Appelbaum, L., & de Lecea, L. (2018) · Neuropsychopharmacology · doi:10.1038/npp.2017.294 · Cited by 282
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The mechanics of state-dependent neural correlations
Doiron, B., Litwin-Kumar, A., Rosenbaum, R., Ocker, G. K., & Josić́, K. (2016) · Nature Neuroscience · doi:10.1038/nn.4242 · Cited by 240
The Input-Output Relationship of the Cholinergic Basal Forebrain
Gielow, M. R., & Záborszky, L. (2017) · Cell Reports · doi:10.1016/j.celrep.2017.01.060 · Cited by 243
“…scenario that is characterized by a continuum of states rather than sharp transitions and, both in SWS and waking, finer distinctions can be made in terms of internal cortical dynamics and responsiveness to external stimuli (Harris and Thiele, 2011; McGinley et al., 2015; Vyazovskiy et al., 2011).”
BackgroundInfluentialLocus coeruleus norepinephrine activity mediates sensory-evoked awakenings from sleep
Hayat, H., Regev, N., Matosevich, N., Sales, A. C., Paredes-Rodriguez, E., Krom, A. J., Bergman, L., Li, Y., Lavigne, M., Kremer, E. J., et al. (2020) · Science Advances · doi:10.1126/sciadv.aaz4232 · Cited by 268
Computational models link cellular mechanisms of neuromodulation to large-scale neural dynamics
Shine, J. M., Müller, E. J., Munn, B., Cabral, J., Moran, R., & Breakspear, M. J. (2021) · Nature Neuroscience · doi:10.1038/s41593-021-00824-6 · Cited by 249
“3a) such as sensory perception 52,53 and apprehension 49 .”
BackgroundThe emergence and influence of internal states
Flavell, S. W., Gogolla, N., Lovett-Barron, M., & Zelikowsky, M. (2022) · Neuron · doi:10.1016/j.neuron.2022.04.030 · Cited by 246
“For instance, the response rate and reaction time to sensory stimuli can be used to infer arousal or alertness across species (Harris and Thiele, 2011; Lovett-Barron et al., 2017; Maimon, 2011; McGinley et al., 2015b;Moore and Zirnsak, 2017; Musall et al., 2019).”
BackgroundInfluentialState-dependent effects of neural stimulation on brain function and cognition
Bradley, C., Nydam, A. S., Dux, P. E., & Mattingley, J. B. (2022) · Nature reviews. Neuroscience · doi:10.1038/s41583-022-00598-1 · Cited by 263
Pupillometry as an integrated readout of distinct attentional networks
Strauch, C., Wang, C., Einhäuser, W., der Stigchel, S. V., & Naber, M. (2022) · Trends in Neurosciences · doi:10.1016/j.tins.2022.05.003 · Cited by 255
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Amygdala ensembles encode behavioral states
Gründemann, J., Bitterman, Y., Lu, T., Krabbe, S., Grewe, B. F., Schnitzer, M. J., & Lüthi, A. (2019) · Science · doi:10.1126/science.aav8736 · Cited by 234
Ancestral Circuits for the Coordinated Modulation of Brain State
Lovett-Barron, M., Andalman, A. S., Allen, W. E., Vesuna, S., Kauvar, I., Burns, V. M., & Deisseroth, K. (2017) · Cell · doi:10.1016/j.cell.2017.10.021 · Cited by 212
“…et al., 2015); 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…”
InfluentialLiu, Y., Rodenkirch, C., Moskowitz, N., Schriver, B. J., & Wang, Q. (2017) · Cell Reports · doi:10.1016/j.celrep.2017.08.094 · Cited by 212
“…respectively, which is comparable with the latency between pupil microdilations and the associated depolarization of transmembrane potentials, as reported in previous work (McGinley et al., 2015a), and the latency between pupil dilation and activation of cortical NE axons (Reimer et al., 2016).”
InfluentialInception loops discover what excites neurons most using deep predictive models
Walker, E. Y., Sinz, F. H., Cobos, E., Muhammad, T., Froudarakis, E., Fahey, P. G., Ecker, A. S., Reimer, J., Pitkow, X., & Tolias, A. S. (2019) · Nature Neuroscience · doi:10.1038/s41593-019-0517-x · Cited by 236
Self-citationEstimation of Current and Future Physiological States in Insular Cortex
Livneh, Y., Sugden, A. U., Madara, J. C., Essner, R. A., Flores, V. I., Sugden, L. A., Resch, J. M., Lowell, B. B., & Andermann, M. L. (2020) · Neuron · doi:10.1016/j.neuron.2019.12.027 · Cited by 209
“To more directly test whether InsCtx ongoing activity represents physiological states or related internal states such as arousal or motivation, we asked whether ongoing activity dynamics (as reflected in dynamics of classifier state estimation) could be predicted by a combination of four parameters: (1) cumulative amo…”
BackgroundMethodLocomotion Enhances Neural Encoding of Visual Stimuli in Mouse V1
Dadarlat, M. C., & Stryker, M. P. (2017) · The Journal of Neuroscience · doi:10.1523/jneurosci.2728-16.2017 · Cited by 205
“Overall, quick shifts in wakefulness of the animal could have inflated our estimates of noise correlations, both while mice are at rest and during loco-motion (Reimer et al., 2014; McGinley et al., 2015; Vinck et al., 2015).”
BackgroundBojarskaite, L., Bjørnstad, D. M., Pettersen, K. H., Cunen, C., Hermansen, G. H., Åbjørsbråten, K. S., Chambers, A. R., Sprengel, R., Vervaeke, K., Tang, W., et al. (2020) · Nature Communications · doi:10.1038/s41467-020-17062-2 · Cited by 228
Standardized and reproducible measurement of decision-making in mice
Aguillon-Rodriguez, V., Angelaki, D. E., Bayer, H. M., Bonacchi, N., Carandini, M., Cazettes, F., Chapuis, G. A., Churchland, A. K., Dan, Y., DeWitt, E. E. J., et al. (2021) · eLife · doi:10.7554/elife.63711 · Cited by 246
Cognitive and Ocular Factors Jointly Determine Pupil Responses under Equiluminance
Knapen, T. H. J., de Gee, J. W., Brascamp, J. W., Nuiten, S. A., Hoppenbrouwers, S. S., & Theeuwes, J. (2016) · PLoS ONE · doi:10.1371/journal.pone.0155574 · Cited by 183
Nelson, A., & MOONEY, R. D. (2016) · Neuron · doi:10.1016/j.neuron.2016.03.031 · Cited by 192
Specific basal forebrain-cortical cholinergic circuits coordinate cognitive operations
Záborszky, L., Gombkoto, P., Varsanyi, P., Gielow, M. R., Poe, G., Role, L. W., Ananth, M., Rajebhosale, P., Talmage, D. A., Hasselmo, M. E., et al. (2018) · The Journal of Neuroscience · doi:10.1523/jneurosci.1676-18.2018 · Cited by 202
Movement and Performance Explain Widespread Cortical Activity in a Visual Detection Task
Salkoff, D. B., Zagha, E., McCarthy, E., & McCormick, D. A. (2019) · Cerebral Cortex · doi:10.1093/cercor/bhz206 · Cited by 157
Self-citationMultistable Perception and the Role of the Frontoparietal Cortex in Perceptual Inference
Brascamp, J. W., Sterzer, P., Blake, R., & Knapen, T. H. J. (2017) · Annual Review of Psychology · doi:10.1146/annurev-psych-010417-085944 · Cited by 173
A transcriptomic axis predicts state modulation of cortical interneurons
Bugeon, S., Duffield, J. A. M., Dipoppa, M., Ritoux, A., Prankerd, I., Nicoloutsopoulos, D., Orme, D., Shinn, M., Peng, H., Forrest, H., et al. (2022) · Nature · doi:10.1038/s41586-022-04915-7 · Cited by 185
Schneider, M., Broggini, A. C., Dann, B., Τζάνου, Α., Uran, C., Sheshadri, S., Scherberger, H., & Vinck, M. A. (2021) · Neuron · doi:10.1016/j.neuron.2021.09.037 · Cited by 167
Self-citationSubcortical Source and Modulation of the Narrowband Gamma Oscillation in Mouse Visual Cortex
Saleem, A. B., Lien, A. D., Krumin, M., Haider, B., Rosón, M. R., Ayaz, A., Reinhold, K., Busse, L., Carandini, M., & Harris, K. D. (2017) · Neuron · doi:10.1016/j.neuron.2016.12.028 · Cited by 154
Circuit Models of Low-Dimensional Shared Variability in Cortical Networks
Huang, C., Ruff, D. A., Pyle, R., Rosenbaum, R., Cohen, M. R., & Doiron, B. (2018) · Neuron · doi:10.1016/j.neuron.2018.11.034 · Cited by 144
“346 Neuron 101, 337–348, January 16, 2019 reflection of the quenching of these external fluctuations (McGinley et al., 2015).”
BackgroundWhy is everyone talking about brain state?
Greene, A. S., Horien, C. L., Barson, D. G., Scheinost, D., & Constable, R. T. (2023) · Trends in Neurosciences · doi:10.1016/j.tins.2023.04.001 · Cited by 161
“spontaneous activity [61] (although notably some cell types exhibit higher levels of activity [62]), and increased task engagement [57,58]; an inverse relationship between arousal and BOLD and global signal amplitude has similarly been noted in humans [63,64].”
BackgroundThe brain’s action-mode network
Dosenbach, N. U. F., Raichle, M. E., & Gordon, E. M. (2025) · Nature reviews. Neuroscience · doi:10.1038/s41583-024-00895-x · Cited by 224
“However, in practice, awake animals are not always behaviourally striving, but often spend time resting 38 — a very distinct pattern of behaviour that must be just as critical for survival.”
InfluentialArousal Modulates Retinal Output
Schröder, S., Steinmetz, N. A., Krumin, M., Pachitariu, M., Rizzi, M., Lagnado, L., Harris, K. D., & Carandini, M. (2020) · Neuron · doi:10.1016/j.neuron.2020.04.026 · Cited by 149
“We measured bouton activity in darkness and related it to the animal’s running speed, a common measure of arousal (McGinley et al., 2015).”
BackgroundLocomotion-dependent remapping of distributed cortical networks
Clancy, K. B., Oršolić, I., & Mrsic‐Flogel, T. D. (2019) · Nature Neuroscience · doi:10.1038/s41593-019-0357-8 · Cited by 134
What is the dynamical regime of cerebral cortex?
Ahmadian, Y., & Miller, K. D. (2021) · Neuron · doi:10.1016/j.neuron.2021.07.031 · Cited by 146
Gjorgjieva, J., Drion, G., & Marder, E. (2016) · Current Opinion in Neurobiology · doi:10.1016/j.conb.2015.12.008 · Cited by 127
“Recent studies have underscored the widely variable internal dynamics and responsiveness to external stimuli across different behavioral contexts and brain states [90].”
BackgroundCorrelated Neural Activity across the Brains of Socially Interacting Bats
Zhang, W., & Yartsev, M. M. (2019) · Cell · doi:10.1016/j.cell.2019.05.023 · Cited by 143
“These results are consistent with the known effects of behavioral states on LFP power and spiking activity, which are readily observed in widespread brain regions (Gervasoni et al., 2004; McGinley et al., 2015).”
Slow Drift of Neural Activity as a Signature of Impulsivity in Macaque Visual and Prefrontal Cortex
Cowley, B. R., Snyder, A. C., Acar, K., Williamson, R. C., Yu, B. M., & Smith, M. A. (2020) · Neuron · doi:10.1016/j.neuron.2020.07.021 · Cited by 137
Spatiotemporally heterogeneous coordination of cholinergic and neocortical activity
Lohani, S., Moberly, A. H., Benisty, H., Landa, B., Jing, M., Li, Y., Higley, M. J., & Cardin, J. A. (2022) · Nature Neuroscience · doi:10.1038/s41593-022-01202-6 · Cited by 150
Self-citationPupil-linked phasic arousal predicts a reduction of choice bias across species and decision domains
de Gee, J. W., Tsetsos, K., Schwabe, L., Urai, A. E., McCormick, D. A., McGinley, M. J., & Donner, T. H. (2020) · eLife · doi:10.7554/elife.54014 · Cited by 135
“, 2013), their arousal systems are organized homologously with those of humans (Amaral and Sinnamon, 1977; Berridge and Waterhouse, 2003), and pupil dilation reports arousal also in rodents (McGinley et al., 2015b; Reimer et al., 2014; Vinck et al., 2015).”
BackgroundMethodInfluentialSelf-citationLocus coeruleus-norepinephrine modulation of sensory processing and perception: A focused review
McBurney-Lin, J., Lu, J., Zuo, Y., & Yang, H. (2019) · Neuroscience & Biobehavioral Reviews · doi:10.1016/j.neubiorev.2019.06.009 · Cited by 142
Switching between internal and external modes: A multiscale learning principle
Honey, C. J., Newman, E. L., & Schapiro, A. C. (2017) · Network Neuroscience · doi:10.1162/netn_a_00024 · Cited by 115
“…over milliseconds (Hasselmo, 2006; Hasselmo, Bodelón, & Wyble, 2002) and seconds (Douchamps, Jeewajee, Blundell, Burgess, & Lever, 2013; Duncan, Sadanand, & Davachi 2012); and overall arousal fluctuates within the waking state (McGinley et al., 2015b) as well as on the timescale of wake and sleep.”
BackgroundInfluentialThe Cortical States of Wakefulness
Poulet, J. F. A., & Crochet, S. (2019) · Frontiers in Systems Neuroscience · doi:10.3389/fnsys.2018.00064 · Cited by 126
How Movement Modulates Hearing
Schneider, D. M., & MOONEY, R. D. (2018) · Annual Review of Neuroscience · doi:10.1146/annurev-neuro-072116-031215 · Cited by 113
“Additionally, movements increase during states of arousal, and arousal engages neuromodulatory pathways that can strongly affect sensory processing (Kuchibhotla et al. 2017, Lee & Dan 2012, McGinley et al. 2015a, Nelson & Mooney 2016).”
BackgroundInfluentialNorepinephrine links astrocytic activity to regulation of cortical state
Reitman, M. E., Tse, V., Mi, X., Willoughby, D. D., Peinado, A., Aivazidis, A., Myagmar, B., Simpson, P. C., Bayraktar, O. A., Yu, G., et al. (2023) · Nature Neuroscience · doi:10.1038/s41593-023-01284-w · Cited by 132
Rodenkirch, C., Liu, Y., Schriver, B. J., & Wang, Q. (2018) · Nature Neuroscience · doi:10.1038/s41593-018-0283-1 · Cited by 118
Vassalli, A., & Franken, P. (2017) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1700983114 · Cited by 124
“Rodent waking is often divided into quiet and active wake based on whether the animal is still or exhibits exploratory movements (1, 19).”
BackgroundWaschke, L., Tune, S., & Obleser, J. (2019) · eLife · doi:10.7554/elife.51501 · Cited by 106
“, 2016) has been shown to influence sensory evoked activity (McGinley et al., 2015a; McGinley et al., 2015b; GelbardSagiv et al., 2018) and the processing of task-relevant information (Murphy et al.”
BackgroundInfluentialBehavioral origin of sound-evoked activity in mouse visual cortex
Bimbard, C., Sit, T. P. H., Lebedeva, A., Reddy, C. B., Harris, K. D., & Carandini, M. (2023) · Nature Neuroscience · doi:10.1038/s41593-022-01227-x · Cited by 119
“For instance, the activity of V1 neurons carries strong signals related to running 10,11 , pupil dilation 11,12 , whisking 13 , and other movements 14 .”
Inhibitory control of correlated intrinsic variability in cortical networks
Stringer, C., Pachitariu, M., Steinmetz, N. A., Okun, M., Barthó, P., Harris, K. D., Sahani, M., & Lesica, N. A. (2016) · eLife · doi:10.7554/elife.19695 · Cited by 103
Selective Modulation of the Pupil Light Reflex by Microstimulation of Prefrontal Cortex
Ebitz, R. B., & Moore, T. (2017) · Journal of Neuroscience · doi:10.1523/jneurosci.2433-16.2017 · Cited by 117
“Activity in many brain regions is correlated with or predicts changes in pupil size under constant A B C luminance (Ebitz and Platt, 2015; Joshi et al., 2015; McGinley et al., 2015).”
BackgroundPupil size tracks attentional performance in Attention-Deficit/Hyperactivity disorder
Wainstein, G., Rojas-Líbano, D., Crossley, N. A., Carrasco, X., Aboitiz, F., & Ossandón, T. (2017) · Scientific Reports · doi:10.1038/s41598-017-08246-w · Cited by 116
Cognitive fluctuations in Lewy body dementia: towards a pathophysiological framework
Matar, E., Shine, J. M., Halliday, G. M., & Lewis, S. J. G. (2019) · Brain · doi:10.1093/brain/awz311 · Cited by 130
Graded recruitment of pupil-linked neuromodulation by parametric stimulation of the vagus nerve
Mridha, Z., de Gee, J. W., Shi, Y., Alkashgari, R., Williams, J. C., Suminski, A. J., Ward, M. P., Zhang, W., & McGinley, M. J. (2021) · Nature Communications · doi:10.1038/s41467-021-21730-2 · Cited by 119
“6 Because there are large, ongoing fluctuations in pupil size, which reflect changes in brain state (see Figure 1H) [28], we wondered if the magnitude of the VNS-evoked pupil dilation depended on pre-stimulation pupil-indexed state.”
BackgroundSelf-citationInterstitial ions: A key regulator of state-dependent neural activity?
Rasmussen, R. N., O’Donnell, J., Ding, F., & Nedergaard, M. (2020) · Progress in Neurobiology · doi:10.1016/j.pneurobio.2020.101802 · Cited by 122
Cortex-wide BOLD fMRI activity reflects locally-recorded slow oscillation-associated calcium waves
Schwalm, M., Schmid, F., Wachsmuth, L., Backhaus, H., Kronfeld, A., Aedo-Jury, F., Prouvot, P.-H., Fois, C., Albers, F., van Alst, T. M., et al. (2017) · eLife · doi:10.7554/elife.27602 · Cited by 106
Effects of Arousal on Mouse Sensory Cortex Depend on Modality
Shimaoka, D., Harris, K. D., & Carandini, M. (2018) · Cell Reports · doi:10.1016/j.celrep.2018.02.092 · Cited by 110
“It also appears consistent with the view that locomotion reduces response variability over time in both the auditory and visual cortex (McGinley et al., 2015a; Polack et al., 2013; Schneider et al., 2014).”
BackgroundMethodInfluentialBottom-up and top-down modulation of multisensory integration
Choi, I., Lee, J. Y., & Lee, S. (2018) · Current Opinion in Neurobiology · doi:10.1016/j.conb.2018.05.002 · Cited by 118
Eye pupil signals information gain
Zénon, A. (2019) · Proceedings of the Royal Society B Biological Sciences · doi:10.1098/rspb.2019.1593 · Cited by 110
“Large phasic responses occur when baseline firing rates of noradrenergic neurons are low and would correspond to small tonic pupil size, whereas large baseline noradrenergic activity would be associated with large tonic pupil size but small phasic responses [29,47,63,71,72].”
BackgroundMusic chills: The eye pupil as a mirror to music’s soul
Laeng, B., Eidet, L. M., Sulutvedt, U., & Panksepp, J. (2016) · Consciousness and Cognition · doi:10.1016/j.concog.2016.07.009 · Cited by 115
Thalamocortical excitability modulation guides human perception under uncertainty
Kosciessa, J. Q., Lindenberger, U., & Garrett, D. D. (2021) · Nature Communications · doi:10.1038/s41467-021-22511-7 · Cited by 102
Pfeffer, T. A., Keitel, C., Kluger, D. S., Keitel, A., Russmann, A., Thut, G., Donner, T. H., & Groß, J. (2022) · eLife · doi:10.7554/elife.71890 · Cited by 116
“Our findings are consistent with previously reported links between both locomotion-related and pupil-related changes in arousal and LFP recordings in sensory cortices of rodents ( McGinley et al., 2015a ; Reimer et al., 2014 ; Reimer et al., 2016 ).”
Influentialvan Kempen, J., Loughnane, G. M., Newman, D. P., Kelly, S. P., Thiele, A., O’Connell, R. G., & Bellgrove, M. A. (2019) · eLife · doi:10.7554/elife.42541 · Cited by 92
Visual thalamocortical mechanisms of waking state-dependent activity and alpha oscillations
Nestvogel, D., & McCormick, D. A. (2021) · Neuron · doi:10.1016/j.neuron.2021.10.005 · Cited by 97
Self-citationPupil diameter is not an accurate real-time readout of locus coeruleus activity
Megemont, M., McBurney-Lin, J., & Yang, H. (2022) · eLife · doi:10.7554/elife.70510 · Cited by 127
Development of Activity in the Mouse Visual Cortex
Shen, J., & Colonnese, M. T. (2016) · Journal of Neuroscience · doi:10.1523/jneurosci.1903-16.2016 · Cited by 97
“In both rats and human preterm infants, spindle burst/delta brushes are triggered by sensory input in somatosensory (Khazipov et al., 2004; Milh et al., 2007), motor (An et al., 2014), and auditory (Chipaux et al., 2013) cortex and by hippocampal input to prefrontal cortex (Brockmann et al., 2011).”
BackgroundWaterhouse, B. D., & Navarra, R. L. (2018) · Brain Research · doi:10.1016/j.brainres.2018.08.032 · Cited by 121
Locomotor activity modulates associative learning in mouse cerebellum
Albergaria, C., Silva, N. T., Pritchett, D. L., & Carey, M. R. (2018) · Nature Neuroscience · doi:10.1038/s41593-018-0129-x · Cited by 97
“…to an auditory CS were negatively modulated by arousal, consistent with previous findings that have shown differential effects of arousal on auditory vs visual cortical responses (McGinley et al., 2015a; McGinley et al., 2015b; Niell and Stryker, 2010; Schneider et al., 2014; Zhou et al., 2014).”
InfluentialAstrocytes amplify neurovascular coupling to sustained activation of neocortex in awake mice
Institóris, Á., Vandal, M., Peringod, G., Catalano, C., Tran, C. H. T., Yu, X., Visser, F., Breiteneder, C., Molina, L. A., Khakh, B. S., et al. (2022) · Nature Communications · doi:10.1038/s41467-022-35383-2 · Cited by 109
Confidence predicts speed-accuracy tradeoff for subsequent decisions
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Baker, J., Ryou, J.-W., Wei, X. F., Butson, C. R., Schiff, N. D., & Purpura, K. P. (2016) · Journal of Neurophysiology · doi:10.1152/jn.01129.2015 · Cited by 99
Attenuation of responses to self-generated sounds in auditory cortical neurons
Rummell, B. P., Klee, J. L., & Sigurdsson, T. (2016) · The Journal of Neuroscience · doi:10.1523/jneurosci.1564-16.2016 · Cited by 103
Sensation during Active Behaviors
Busse, L., Cardin, J. A., Chiappe, M. E., Halassa, M. M., McGinley, M. J., Yamashita, T., & Saleem, A. B. (2017) · Journal of Neuroscience · doi:10.1523/jneurosci.1828-17.2017 · Cited by 84
Self-citationAttention model of binocular rivalry
Li, H.-H., Rankin, J., Rinzel, J., Carrasco, M., & Heeger, D. J. (2017) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1620475114 · Cited by 85
“Attention and arousal are known to vary over time during an experiment (55, 56).”
Adaptive circuit dynamics across human cortex during evidence accumulation in changing environments
Murphy, P. R., Wilming, N., Hernandez-Bocanegra, D. C., Prat-Ortega, G., & Donner, T. H. (2021) · Nature Neuroscience · doi:10.1038/s41593-021-00839-z · Cited by 105
Catecholaminergic manipulation alters dynamic network topology across cognitive states
Shine, J. M., van den Brink, R. L., Hernaus, D., Nieuwenhuis, S., & Poldrack, R. A. (2018) · Network Neuroscience · doi:10.1162/netn_a_00042 · Cited by 95
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Grimm, C., Duss, S. N., Privitera, M., Munn, B., Karalis, N., Frässle, S., Wilhelm, M., Patriarchi, T., Razansky, D., Wenderoth, N., et al. (2024) · Nature Neuroscience · doi:10.1038/s41593-024-01755-8 · Cited by 138
“In future studies conducted in the awake state, these activity patterns may be attenuated because of the interplay between the LC–NA system and other neuromodulators that contribute to arousal and are more active during wakefulness 60 .”
BackgroundKafashan, M., Jaffe, A. W., Chettih, S. N., Nogueira, R., Arandia-Romero, I., Harvey, C. D., Moreno-Bote, R., & Drugowitsch, J. (2021) · Nature Communications · doi:10.1038/s41467-020-20722-y · Cited by 96
Cicco, V. D., Fantozzi, M. P. T., Cataldo, E., Barresi, M., Bruschini, L., Faraguna, U., & Manzoni, D. (2018) · Frontiers in Neuroanatomy · doi:10.3389/fnana.2017.00130 · Cited by 95
“…mydriasis is one of the most characteristic signs of arousal (Bradshaw, 1967; Bradley et al., 2008), it represents a fine indicator of brain state (McGinley et al., 2015) and, together with purposeful eyes motion, it has been taken has an indicator of persistent awakening status in the midpontine…”
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Brainstem Modulation of Large-Scale Intrinsic Cortical Activity Correlations
van den Brink, R. L., Pfeffer, T. A., & Donner, T. H. (2019) · Frontiers in Human Neuroscience · doi:10.3389/fnhum.2019.00340 · Cited by 85
Precisely Timed Nicotinic Activation Drives SST Inhibition in Neocortical Circuits
Urban-Ciecko, J., Jouhanneau, J.-S., Myal, S. E., Poulet, J. F. A., & Barth, A. L. (2018) · Neuron · doi:10.1016/j.neuron.2018.01.037 · Cited by 93
“For example, attention and arousal are associated with the desynchronization of cortical activity (McGinley et al., 2015; Poulet and Petersen, 2008), an effect that has been generally attributed to altered inhibition”
BackgroundVisual physiology of the layer 4 cortical circuit in silico
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Metadata
- 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)
- 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
- bronze
- doi.org
- 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.
A language model drew the claims from the paper on 2026-10-07, under version 3 of the claim definition (model deepseek-v4.1-flash, prompt extract-v3).
A second model labelled each claim on 2026-10-07 (model jev-1.13-20260917, definition revision gold-guideline-v0.2).
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 ›
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