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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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“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
Experimental — accuracy not yet measuredThe source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“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
Experimental — accuracy not yet measuredThe 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 [67]
In the citing paper
“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
In the citing paper
“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
In the citing 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”
From Waking state: rapid variations modulate neural and behavioral responses (2015) · cites this paper as McGinley et al., 2015
In the citing paper
“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
In the citing paper
“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
In the citing 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”
From Waking state: rapid variations modulate neural and behavioral responses (2015) · cites this paper as McGinley et al., 2015
In the citing paper
“During periods of quiet wakefulness (lacking overt movement), large low-frequency (< 10 Hz) fluctuations in the synaptic activity of somatosensory, visual, and auditory cortical neurons are frequently observed, and these oscillations are strongly suppressed by the initiation of whisking or locomotion”
From Waking state: rapid variations modulate neural and behavioral responses (2015) · cites this paper as McGinley et al., 2015
In the citing paper
“The transition from the quiet awake state to movement (locomotion and/or whisking) in head-fixed mice is always preceded by a strong suppression of cortical slow rhythms at the action potential, membrane potential, and field potential, levels”
From Waking state: rapid variations modulate neural and behavioral responses (2015) · cites this paper as McGinley et al., 2015
In the citing paper
“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
In the citing paper
“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
In the citing paper
“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
In the citing 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.”
From Waking state: rapid variations modulate neural and behavioral responses (2015) · cites this paper as McGinley et al., 2015
In the citing paper
“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
In the citing paper
“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
In the citing 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.”
From Waking state: rapid variations modulate neural and behavioral responses (2015) · cites this paper as McGinley et al., 2015
In the citing paper
“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
In the citing 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”
From Waking state: rapid variations modulate neural and behavioral responses (2015) · cites this paper as McGinley et al., 2015
In the citing paper
“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
In the citing 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”
From Waking state: rapid variations modulate neural and behavioral responses (2015) · cites this paper as McGinley et al., 2015
In the citing 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”
From Waking state: rapid variations modulate neural and behavioral responses (2015) · cites this paper as McGinley et al., 2015
In the citing paper
“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
In the citing paper
“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
In the citing 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”
From Waking state: rapid variations modulate neural and behavioral responses (2015) · cites this paper as McGinley et al., 2015
In the citing paper
“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
In the citing paper
“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 the citing 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”
From Waking state: rapid variations modulate neural and behavioral responses (2015) · cites this paper as McGinley et al., 2015
In the citing paper
“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
In the citing 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”
From Waking state: rapid variations modulate neural and behavioral responses (2015) · cites this paper as McGinley et al., 2015
In the citing 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”
From Waking state: rapid variations modulate neural and behavioral responses (2015) · cites this paper as McGinley et al., 2015
In the citing paper
“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 the citing paper
“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
In the citing paper
“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
In the citing 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).”
From Waking state: rapid variations modulate neural and behavioral responses (2015) · cites this paper as McGinley et al., 2015
In the citing 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).”
From Waking state: rapid variations modulate neural and behavioral responses (2015) · cites this paper as McGinley et al., 2015
In the citing paper
“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
In the citing paper
“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
In the citing 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.”
From Waking state: rapid variations modulate neural and behavioral responses (2015) · cites this paper as McGinley et al., 2015
In the citing 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).”
From Waking state: rapid variations modulate neural and behavioral responses (2015) · cites this paper as McGinley et al., 2015
In the citing paper
“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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Metadata
- 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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