Cortical membrane potential signature of optimal states for sensory signal detection
Open accessAbstract
The neural correlates of optimal states for signal detection task performance are largely unknown. One hypothesis holds that optimal states exhibit tonically depolarized cortical neurons with enhanced spiking activity, such as occur during movement. We recorded membrane potentials of auditory cortical neurons in mice trained on a challenging tone-in-noise detection task while assessing arousal with simultaneous pupillometry and hippocampal recordings. Arousal measures accurately predicted multiple modes of membrane potential activity, including rhythmic slow oscillations at low arousal, stable hyperpolarization at intermediate arousal, and depolarization during phasic or tonic periods of hyper-arousal. Walking always occurred during hyper-arousal. Optimal signal detection behavior and sound-evoked responses, at both sub-threshold and spiking levels, occurred at intermediate arousal when pre-decision membrane potentials were stably hyperpolarized. These results reveal a cortical physiological signature of the classically observed inverted-U relationship between task performance and arousal and that optimal detection exhibits enhanced sensory-evoked responses and reduced background synaptic activity.
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Head-restrained preparations have shown that behavioral state fluctuations have a strong impact on neuronal gain and coding properties in primary sensory areas and modulate neuronal firing within brain-wide neuronal networks.
“By employing head-restrained preparations, a growing body of work has demonstrated that behavioral state fluctuations have a strong impact on neuronal gain and coding properties in primary sensory areas36,43,66–70 and modulate neuronal firing within brain-wide neuronal networks44,71–74.”
From Place and behavioral modulation of hippocampal neurons during immobility (2026) · cites this paper as [67]
Waking-state changes are sometimes coupled with overt movements such as whisking or locomotion.
“These changes are sometimes coupled with overt movements such as whisking or locomotion”
From Waking state: rapid variations modulate neural and behavioral responses (2015) · cites this paper as McGinley et al., 2015
Waking-state changes can be predicted with high accuracy by pupil diameter or muscle tone while animals sit quietly.
“and can also be predicted with high accuracy by changes in pupil diameter or muscle tone while animals are sitting quietly”
From Waking state: rapid variations modulate neural and behavioral responses (2015) · cites this paper as McGinley et al., 2015
The waking state contains continuous transitions between numerous sub-states associated with significant changes in sensory-motor processing and behavioral performance.
“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”
From Waking state: rapid variations modulate neural and behavioral responses (2015) · cites this paper as McGinley et al., 2015
Rapid, ongoing, behaviorally relevant variations in waking state are the rule rather than the exception in animals.
“New animal studies reveal that rapid, ongoing, and behaviorally-relevant variations in waking state are not the exception, but rather the rule”
From Waking state: rapid variations modulate neural and behavioral responses (2015) · cites this paper as McGinley et al., 2015
Spontaneous and sensory-evoked activity varies continuously and rapidly during wakefulness.
“This work has revealed that spontaneous and sensory-evoked activity varies continuously and rapidly during wakefulness.”
From Waking state: rapid variations modulate neural and behavioral responses (2015) · cites this paper as McGinley et al., 2015
State variations affect sensory evoked neural activity as much as variations in the sensory stimulus itself.
“These variations in state exert an effect on sensory evoked neural activity that can be as significant as variations in the sensory stimulus itself”
From Waking state: rapid variations modulate neural and behavioral responses (2015) · cites this paper as McGinley et al., 2015
In awake head-fixed rodents during quiet wakefulness without overt movement, large low-frequency (<10 Hz) fluctuations in synaptic activity occur in somatosensory, visual, and auditory cortical neurons, and these oscillations are strongly suppressed by whisking or locomotion.
“During periods of quiet wakefulness (lacking overt movement), large low-frequency (< 10 Hz) fluctuations in the synaptic activity of somatosensory, visual, and auditory cortical neurons are frequently observed, and these oscillations are strongly suppressed by the initiation of whisking or locomotion”
From Waking state: rapid variations modulate neural and behavioral responses (2015) · cites this paper as McGinley et al., 2015
The transition from quiet awake state to movement in head-fixed mice is always preceded by strong suppression of cortical slow rhythms at action potential, membrane potential, and field potential levels.
“The transition from the quiet awake state to movement (locomotion and/or whisking) in head-fixed mice is always preceded by a strong suppression of cortical slow rhythms at the action potential, membrane potential, and field potential, levels”
From Waking state: rapid variations modulate neural and behavioral responses (2015) · cites this paper as McGinley et al., 2015
Simultaneous intracellular membrane potential and LFP recordings with pupil diameter in head-fixed mice revealed a marked relationship between pupil size, low-frequency (2-10 Hz) membrane potential/LFP fluctuations, and exploratory behaviors such as whisking and locomotion.
“Recently, intracellular membrane potential (Vm) and local field potential (LFP) recordings from cortical neurons collected simultaneously with pupil diameter in head-fixed, spontaneously locomoting or whisking mice revealed a marked relationship between 1) pupil size, 2) low frequency (2–10 Hz) fluctuations in membrane potential/LFP, and 3) exploratory behaviors (whisking and locomotion)”
From Waking state: rapid variations modulate neural and behavioral responses (2015) · cites this paper as McGinley et al., 2015
At intermediate arousal, infragranular cortical neurons have their most hyperpolarized and least variable average membrane potential.
“At these intermediate arousal levels, the average membrane potential of infragranular cortical neurons is at its most hyperpolarized, and least variable, level”
From Waking state: rapid variations modulate neural and behavioral responses (2015) · cites this paper as McGinley et al., 2015
The relationship between pupil diameter and cortical network activity has been observed in visual, somatosensory, and auditory cortical areas.
“has been observed in visual, somatosensory, and auditory cortical areas”
From Waking state: rapid variations modulate neural and behavioral responses (2015) · cites this paper as McGinley et al., 2015
Initiation of locomotion is preceded by a substantial increase in pupil diameter, concurrent with reduced low-frequency cortical LFP synchronization and reduced hippocampal sharp wave and ripple oscillations.
“Interestingly, the initiation of locomotion is preceded by a substantial increase in pupil diameter (Figures 2–4), concurrent with the reduction of low-frequency cortical local field potential synchronization and reduced hippocampal sharp wave and ripple oscillations.”
From Waking state: rapid variations modulate neural and behavioral responses (2015) · cites this paper as McGinley et al., 2015
At low arousal, cortical neurons show a high density of large, slow, rhythmic synaptic activity fluctuations.
“At low levels of arousal, cortical neurons exhibit a high density of large, slow, rhythmic fluctuations in synaptic activity”
From Waking state: rapid variations modulate neural and behavioral responses (2015) · cites this paper as McGinley et al., 2015
Low-frequency cortical activity is enhanced during pupillary constriction, especially below a critical pupil diameter.
“Likewise, low-frequency cortical activity is enhanced during pupillary constriction, especially below a critical level of pupil diameter.”
From Waking state: rapid variations modulate neural and behavioral responses (2015) · cites this paper as McGinley et al., 2015
Even without movement, increases in pupil diameter are associated with increased cortical activation and suppression of low-frequency rhythms.
“Even in the absence of movement, increases in pupil diameter (dilation) were found to be associated with increases in cortical activation and suppression of low frequency rhythms.”
From Waking state: rapid variations modulate neural and behavioral responses (2015) · cites this paper as McGinley et al., 2015
In deep layer neurons of auditory cortex, arousal and average cortical membrane potential have a U-shaped relationship.
“For example, the presence of these different types of synaptic and membrane potential dynamics at low and high arousal states results in a U-shaped relationship between arousal and average cortical membrane potential in deep layer neurons of the auditory cortex”
From Waking state: rapid variations modulate neural and behavioral responses (2015) · cites this paper as McGinley et al., 2015
The relationship between cortical membrane potential and pupil diameter depends on arousal state, with slow oscillations at low arousal and strong synaptic barrages or tonic depolarization at high arousal.
“Additionally, the relationship between cortical membrane potential and pupil diameter is influenced by the presence of slow oscillations at low arousal states and strong barrages of synaptic activity and/or tonic depolarization at high arousal states”
From Waking state: rapid variations modulate neural and behavioral responses (2015) · cites this paper as McGinley et al., 2015
Pupil diameter correlates with the rate of hippocampal sharp-wave ripples.
“The correlation between pupil diameter and the rate of sharp-wave ripples in the hippocampus (Figure 2D), further underscores the generality of this effect.”
From Waking state: rapid variations modulate neural and behavioral responses (2015) · cites this paper as McGinley et al., 2015
Increasing arousal from low to intermediate levels suppresses low-frequency (1-10 Hz) activity, decreases membrane potential fluctuations, and decreases spontaneous activity.
“Increases in arousal from low to intermediate levels result in a suppression of these low (1–10 Hz) frequency activities, a decrease in membrane potential fluctuations, and thus a decrease in spontaneous activity”
From Waking state: rapid variations modulate neural and behavioral responses (2015) · cites this paper as McGinley et al., 2015
Increasing arousal from intermediate to high levels, associated with brief or long-lasting pupil dilation often with locomotion, depolarizes membrane potential and increases high-frequency fluctuations from synaptic barrages.
“Increases from intermediate to high arousal associated with brief (microdilations) or long-lasting increases in pupil diameter (often associated with locomotion), result in a depolarization of the membrane potential and increases in high-frequency membrane potential fluctuations from synaptic barrages”
From Waking state: rapid variations modulate neural and behavioral responses (2015) · cites this paper as McGinley et al., 2015
Changes in pupil diameter are reliably correlated with the average subthreshold membrane potential of at least some cortical neuron subtypes, even without overt movement.
“In addition to predicting changes in oscillatory network dynamics, changes in pupil diameter are reliably correlated with the average subthreshold membrane potential of at least some subtypes of neurons of the cortex, even in the absence of overt movement”
From Waking state: rapid variations modulate neural and behavioral responses (2015) · cites this paper as McGinley et al., 2015
The transition from sitting quietly to exploratory behaviors such as whisking and locomotion is intertwined with changes in arousal tracked by pupillometry.
“The transition from sitting quietly to exploratory behaviors (whisking and locomotion) is intertwined with changes in arousal tracked by pupillometry.”
From Waking state: rapid variations modulate neural and behavioral responses (2015) · cites this paper as McGinley et al., 2015
Even in the quiescent state without overt movement, pupil dilation is associated with suppression of low-frequency and enhancement of gamma-frequency cortical network activities, occurring as rapid switching or graded continuous change.
“As described above, even in the quiescent state devoid of overt movements, pupil dilation is associated with suppression of low-frequency, and enhancement of gamma-frequency, cortical network activities that can occur as either a rapid switching (Figure 2A) or as a graded and continuous change”
From Waking state: rapid variations modulate neural and behavioral responses (2015) · cites this paper as McGinley et al., 2015
During movement such as whisking or locomotion, neurons in somatosensory, visual, motor, and auditory cortex maintain elevated firing rates, with the degree varying across cell types.
“During the period of movement (whisking or locomotion), neurons in somatosensory, visual, motor, and auditory cortex maintain an elevated firing rate, the degree of which varies across cell types.”
From Waking state: rapid variations modulate neural and behavioral responses (2015) · cites this paper as McGinley et al., 2015
A subset of layer 5 pyramidal neurons throughout cortex is activated by movement.
“For example, a subset of layer 5 pyramidal neurons throughout the cortex is activated by movement”
From Waking state: rapid variations modulate neural and behavioral responses (2015) · cites this paper as McGinley et al., 2015
Following cessation of locomotion, head-fixed mice typically transition from high to moderate or low arousal over seconds or longer, as measured by pupil diameter.
“Following the cessation of locomotion, head-fixed mice typically exhibit a transition from high arousal to moderate or low arousal, as measured by pupil diameter, over a period of seconds or longer.”
From Waking state: rapid variations modulate neural and behavioral responses (2015) · cites this paper as McGinley et al., 2015
A gradual decrease in pupil diameter after locomotion is associated with increased prevalence of low-frequency oscillations.
“This gradual decrease in pupil diameter is associated with an increase in the prevalence of low-frequency oscillations”
From Waking state: rapid variations modulate neural and behavioral responses (2015) · cites this paper as McGinley et al., 2015
In auditory cortex, the signal-to-noise ratio peaks at intermediate arousal and may decrease strongly at high arousal and during locomotion.
“In contrast, in auditory cortex, the S/N peaks at intermediate arousal levels and may decrease strongly at high arousal levels and during locomotion”
From Waking state: rapid variations modulate neural and behavioral responses (2015) · cites this paper as McGinley et al., 2015
Behavioral state is an important determinant of both the temporal precision of sensory responses and gamma-band synchronization.
“Behavioral state is an important determinant of both the temporal precision of sensory responses and gamma-band synchronization.”
From Waking state: rapid variations modulate neural and behavioral responses (2015) · cites this paper as McGinley et al., 2015
Spontaneous or causally induced increases in arousal are associated with a monotonic increase in gamma-band synchronization in LFP and relative membrane potential power, and in spike-LFP phase locking.
“Spontaneous or causally induced increases in arousal are associated with a monotonic increase in gamma-band synchronization both in terms of local field potential and relative membrane potential power (Lee et al., 2014; Lima et al., 2011; McGinley et al., 2015; Reimer et al., 2014; Vinck et al., 2015), and spike-local field potential phase locking”
From Waking state: rapid variations modulate neural and behavioral responses (2015) · cites this paper as McGinley et al., 2015
Changes in arousal produce marked multiplicative gain modulation of auditory cortical responses, with the largest responses at intermediate arousal.
“Changes in arousal result in marked multiplicative gain modulation of auditory cortical responses, with the largest responses being evoked at intermediate levels of arousal”
From Waking state: rapid variations modulate neural and behavioral responses (2015) · cites this paper as McGinley et al., 2015
Compensating for rapid variations in state can significantly reduce variability in the amplitude and timing of both sensory evoked and behavioral responses.
“Indeed, compensating for these rapid variations in state can significantly reduce variability in the amplitude and timing of both sensory evoked and behavioral responses (McGinley et al., 2015; Reimer et al., 2014).”
From Waking state: rapid variations modulate neural and behavioral responses (2015) · cites this paper as McGinley et al., 2015
In L5 of auditory cortex, variability is increased during low and high arousal but reduced at intermediate arousal.
“in L5 of auditory cortex, variability is increased during low and high arousal (either during quiet or active waking), but reduced at intermediate arousal (McGinley et al., 2015).”
From Waking state: rapid variations modulate neural and behavioral responses (2015) · cites this paper as McGinley et al., 2015
A significant fraction of trial-to-trial variability in sensory evoked responses may result from rapid variations in state.
“Monitoring of state through pupillometry reveals rapid (seconds) and continuous changes (Figure 2–4), indicating that a significant fraction of trial-to-trial variability in sensory evoked responses may be the result of variations in state.”
From Waking state: rapid variations modulate neural and behavioral responses (2015) · cites this paper as McGinley et al., 2015
All three measures exhibited an inverted U relationship with arousal, with the largest, most reliable, and highest S/N ratio responses occurring at the same intermediate pupil diameters that revealed optimal performance on the auditory tone-in-complex sound detection task.
“All three measures exhibited an inverted U relationship with arousal, with the largest, most reliable, and highest S/N ratio responses occurring at the same intermediate pupil diameters that revealed optimal performance on the auditory tone-in-complex sound detection task (Figure 7).”
From Waking state: rapid variations modulate neural and behavioral responses (2015) · cites this paper as McGinley et al., 2015
The performance of mice on an auditory detection task was highly state dependent, with maximal hit rate, shortest lick latency, maximal discrimination, and least behavioral bias all occurring at intermediate pupil diameters.
“Importantly, the performance of mice on this auditory detection task was highly state dependent, with maximal hit rate, shortest lick latency, maximal discrimination, and least behavioral bias all occurring at intermediate pupil diameters (Figure 7C).”
From Waking state: rapid variations modulate neural and behavioral responses (2015) · cites this paper as McGinley et al., 2015
At present, intracellular recordings from cortical neurons support both the sigmoidal and U model of arousal.
“At present, intracellular recordings from cortical neurons support both the sigmoidal and U model of arousal (e.g. Figure 1–3).”
From Waking state: rapid variations modulate neural and behavioral responses (2015) · cites this paper as McGinley et al., 2015
Intracellular recordings in awake behaving rodents can reveal a pattern more consistent with a U-shaped dependence of average membrane potential and cortical activation on arousal.
“In contrast to the sigmoidal model of activation, intracellular recordings in awake behaving rodents can reveal a pattern that is more consistent with a U-shaped dependence of average membrane potential and cortical activation on arousal (McGinley et al., 2015) (Figures 3C, 8C).”
From Waking state: rapid variations modulate neural and behavioral responses (2015) · cites this paper as McGinley et al., 2015
Locomotion, as a sub-state of hyper-arousal, was associated with a strong decrease in behavioral performance compared to intermediate arousal levels, which always occurred during stillness.
“Interestingly, locomotion, as a sub-state of hyper-arousal, was associated with a strong decrease in behavioral performance, in comparison to intermediate arousal levels, which always occurred during stillness.”
From Waking state: rapid variations modulate neural and behavioral responses (2015) · cites this paper as McGinley et al., 2015
Increases in arousal from low to intermediate were associated with a large increase in task performance, while further increases from intermediate to large were associated with a strong decrement in performance, regardless of walking.
“Increases in arousal from low to intermediate, as indicated by increases in pupil diameter from small to medium, were associated with a large increase in task performance, while further increases in pupil diameter from intermediate to large were associated with a strong decrement in performance, whether or not the animal was walking at these large pupil diameters (Figure 7C).”
From Waking state: rapid variations modulate neural and behavioral responses (2015) · cites this paper as McGinley et al., 2015
Sound evoked responses in auditory cortex exhibited a strong relationship between arousal (pupil diameter) and the gain, amplitude, and reliability of these responses.
“Interestingly, sound evoked responses in the auditory cortex also exhibited a strong relationship between arousal (pupil diameter) and the gain, amplitude, and reliability of these responses (Figure 7D).”
From Waking state: rapid variations modulate neural and behavioral responses (2015) · cites this paper as McGinley et al., 2015
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Catecholamines alter the intrinsic variability of cortical population activity and perception
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- Authors
- McGinley, M. J., David, S. V., & McCormick, D. A.
- Affiliations
- Yale University (US)
- Oregon Health & Science University (US)
- Corresponding author
- McGinley, Matthew J.
- McCormick, David A.
- Venue
- Neuron
- Publisher
- Elsevier BV
- Published
- 2015-07
- Volume
- 87
- Issue
- 1
- Pages
- 179-192
- ISSN
- 0896-6273 (ISSN-L)
- PMC
- PMC4631312
- OpenAlex
- W1519578210
- Cited by
- 728
- References
- 57
- Citations by year
- 2026: 58 · 2025: 73 · 2024: 80 · 2023: 89 · 2022: 67 · 2021: 73 · 2020: 61 · 2019: 53 · 2018: 64 · 2017: 52 · 2016: 48 · 2015: 10
- FWCI
- 34.90
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Licence
- Locations
- Neuron (publishedVersion)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- Funders
- U.S. Public Health Service (5R01N2026143)
- National Institute on Deafness and Other Communication Disorders (R01DC015803, 1F132DC012449, F32DC012449, R00DC010439)
- National Institute of Neurological Disorders and Stroke (R01NS026143)
- Topics
- Life Sciences › Neuroscience › Cognitive Neuroscience › Neural dynamics and brain function
- Life Sciences › Neuroscience › Cognitive Neuroscience › Neuroscience and Music Perception
- Life Sciences › Neuroscience › Cognitive Neuroscience › Memory and Neural Mechanisms
- Keywords
- signal detection, arousal, inverted U-shaped relationship, auditory cortex, tone-in-noise detection, pupillometry, slow oscillations, hyperpolarization, depolarization, synaptic activity
- MeSH terms
- Animals, Arousal, Auditory Cortex, Auditory Perception, Membrane Potentials, Neurons, Signal Detection, Psychological, Mice
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