Vasoactive intestinal peptide-expressing interneurons modulate the effect of behavioral state on cortical activity.

Animals live in a complex and changing environment with various degrees of behavioral demands. Behavioral states affect the activity of cortical neurons and the dynamics of neuronal populations, however not much is known about the cortical circuitry behind the modulation of neuronal activity across behavioral states. Here we show that a class of GABAergic inhibitory interneurons that express vasoactive intestinal peptide-expressing interneurons (VIP), namely VIP interneurons, play a key role in the circuits involved in the modulation of cortical activity by behavioral state, as reflected in the mice facial motion. We show that inhibition of VIP interneurons reduces the correlated activity between the behavioral state of the animal and the spiking of individual neurons. We also show that VIP inhibition during the quiet state decreases the synchronous spiking of the neurons but increases delta power and phase locking of spiking to the delta-band activity. Taken together our data show that VIP interneurons modulate the behavioral state-dependency of cortical activity across different time scales.

A machine learning approach for real-time cortical state estimation.

Objective.Cortical function is under constant modulation by internally-driven, latent variables that regulate excitability, collectively known as 'cortical state'. Despite a vast literature in this area, the estimation of cortical state remains relatively ad hoc, and not amenable to real-time implementation. Here, we implement robust, data-driven, and fast algorithms that address several technical challenges for online cortical state estimation.Approach. We use unsupervised Gaussian mixture models to identify discrete, emergent clusters in spontaneous local field potential signals in cortex. We then extend our approach to a temporally-informed hidden semi-Markov model (HSMM) with Gaussian observations to better model and infer cortical state transitions. Finally, we implement our HSMM cortical state inference algorithms in a real-time system, evaluating their performance in emulation experiments.Main results. Unsupervised clustering approaches reveal emergent state-like structure in spontaneous electrophysiological data that recapitulate arousal-related cortical states as indexed by behavioral indicators. HSMMs enable cortical state inferences in a real-time context by modeling the temporal dynamics of cortical state switching. Using HSMMs provides robustness to state estimates arising from noisy, sequential electrophysiological data.Significance. To our knowledge, this work represents the first implementation of a real-time software tool for continuously decoding cortical states with high temporal resolution (40 ms). The software tools that we provide can facilitate our understanding of how cortical states dynamically modulate cortical function on a moment-by-moment basis and provide a basis for state-aware brain machine interfaces across health and disease.

Local extracellular K+ in cortex regulates norepinephrine levels, network state, and behavioral output.

Extracellular potassium concentration ([K+]e) is known to increase as a function of arousal. [K+]e is also a potent modulator of transmitter release. Yet, it is not known whether [K+]e is involved in the neuromodulator release associated with behavioral transitions. We here show that manipulating [K+]e controls the local release of monoaminergic neuromodulators, including norepinephrine (NE), serotonin, and dopamine. Imposing a [K+]e increase is adequate to boost local NE levels, and conversely, lowering [K+]e can attenuate local NE. Electroencephalography analysis and behavioral assays revealed that manipulation of cortical [K+]e was sufficient to alter the sleep-wake cycle and behavior of mice. These observations point to the concept that NE levels in the cortex are not solely determined by subcortical release, but that local [K+]e dynamics have a strong impact on cortical NE. Thus, cortical [K+]e is an underappreciated regulator of behavioral transitions.

Distinct ensembles in the noradrenergic locus coeruleus are associated with diverse cortical states.

The noradrenergic locus coeruleus (LC) is a controller of brain and behavioral states. Activating LC neurons en masse by electrical or optogenetic stimulation promotes a stereotypical "activated" cortical state of high-frequency oscillations. However, it has been recently reported that spontaneous activity of LC cell pairs has sparse yet structured time-averaged cross-correlations, which is unlike the highly synchronous neuronal activity evoked by stimulation. Therefore, LC population activity could consist of distinct multicell ensembles each with unique temporal evolution of activity. We used nonnegative matrix factorization (NMF) to analyze large populations of simultaneously recorded LC single units in the rat LC. NMF identified ensembles of spontaneously coactive LC neurons and their activation time courses. Since LC neurons selectively project to specific forebrain regions, we hypothesized that distinct ensembles activate during different cortical states. To test this hypothesis, we calculated band-limited power and spectrograms of local field potentials in cortical area 24a aligned to spontaneous activations of distinct LC ensembles. A diversity of state modulations occurred around activation of different LC ensembles, including a typical activated state with increased high-frequency power as well as other states including decreased high-frequency power. Thus­in contrast to the stereotypical activated brain state evoked by en masse LC stimulation­spontaneous activation of distinct LC ensembles is associated with a multitude of cortical states.

Coupling of pupil- and neuronal population dynamics reveals diverse influences of arousal on cortical processing.

Fluctuations in arousal, controlled by subcortical neuromodulatory systems, continuously shape cortical state, with profound consequences for information processing. Yet, how arousal signals influence cortical population activity in detail has so far only been characterized for a few selected brain regions. Traditional accounts conceptualize arousal as a homogeneous modulator of neural population activity across the cerebral cortex. Recent insights, however, point to a higher specificity of arousal effects on different components of neural activity and across cortical regions. Here, we provide a comprehensive account of the relationships between fluctuations in arousal and neuronal population activity across the human brain. Exploiting the established link between pupil size and central arousal systems, we performed concurrent magnetoencephalographic (MEG) and pupillographic recordings in a large number of participants, pooled across three laboratories. We found a cascade of effects relative to the peak timing of spontaneous pupil dilations: Decreases in low-frequency (2-8 Hz) activity in temporal and lateral frontal cortex, followed by increased high-frequency (>64 Hz) activity in mid-frontal regions, followed by monotonic and inverted U relationships with intermediate frequency-range activity (8-32 Hz) in occipito-parietal regions. Pupil-linked arousal also coincided with widespread changes in the structure of the aperiodic component of cortical population activity, indicative of changes in the excitation-inhibition balance in underlying microcircuits. Our results provide a novel basis for studying the arousal modulation of cognitive computations in cortical circuits.

Amphetamine Promotes Cortical Up State in Part Via Dopamine Receptors.

Cortical neurons oscillate between Up and Down states during slow wave sleep and general anesthesia. Recent studies show that Up/Down oscillations also occur during quiet wakefulness. Arousal eliminates Down states and transforms Up/Down oscillations to a persistent Up state. Further evidence suggests that Up/Down oscillations are crucial to memory consolidation, whereas their transition to a persistent Up state is essential for arousal and attention. We have shown that D-amphetamine promotes cortical Up state, and the effect depends on activation of central α1A adrenergic receptors. Here, we report that dopamine also plays a role in D-amphetamine's effect. Thus, using local-field-potential recording in the prefrontal cortex in chloral hydrate-anesthetized rats, we showed that the Up-state promoting effect of D-amphetamine was attenuated by antagonists at either D1 or D2-like dopamine receptors. The effect was also partially mimicked by co-activation of D1 and D2-like receptors. These results are consistent with the fact that D-amphetamine increases the release of both norepinephrine and dopamine. They are also in agreement with studies showing that dopamine promotes wakefulness and mediates D-amphetamine-induced emergence from general anesthesia. The effect of D-amphetamine was not mimicked, however, by activation of either D1 or D2-like receptors alone, indicating an interdependence between D1 and D2-like receptors. The dopamine/norepinephrine precursor L-DOPA also failed to promote the Up state. While more studies are needed to understand the difference between L-DOPA and D-amphetamine, our finding may provide an explanation for why L-DOPA lacks significant psychostimulant properties and is ineffective in treating attention-deficit/hyperactivity disorder.

Multi-structure Cortical States Deduced From Intracellular Representations of Fixed Tactile Input Patterns.

The brain has a never-ending internal activity, whose spatiotemporal evolution interacts with external inputs to constrain their impact on brain activity and thereby how we perceive them. We used reproducible touch-related spatiotemporal sensory inputs and recorded intracellularly from rat (Sprague-Dawley, male) neocortical neurons to characterize this interaction. The synaptic responses, or the summed input of the networks connected to the neuron, varied greatly to repeated presentations of the same tactile input pattern delivered to the tip of digit 2. Surprisingly, however, these responses tended to sort into a set of specific time-evolving response types, unique for each neuron. Further, using a set of eight such tactile input patterns, we found each neuron to exhibit a set of specific response types for each input provided. Response types were not determined by the global cortical state, but instead likely depended on the time-varying state of the specific subnetworks connected to each neuron. The fact that some types of responses recurred indicates that the cortical network had a non-continuous landscape of solutions for these tactile inputs. Therefore, our data suggest that sensory inputs combine with the internal dynamics of the brain networks, thereby causing them to fall into one of the multiple possible perceptual attractor states. The neuron-specific instantiations of response types we observed suggest that the subnetworks connected to each neuron represent different components of those attractor states. Our results indicate that the impact of cortical internal states on external inputs is substantially more richly resolvable than previously shown.

Changes in cortical, cardiac, and respiratory activities in relation to spontaneous rhythmic jaw movements in ketamine-anesthetized guinea pigs.

It has been reported that rhythmic jaw movements (RJMs) spontaneously occur in ketamine-anesthetized animals. The present study investigated the physiological processes that occur during the cortical, cardiac, and respiratory events which contribute to the genesis of RJMs in animals after supplemental ketamine injections. Fourteen guinea pigs were prepared to allow electroencephalographic, electrocardiographic, and electromyographic activities to be recorded from the digastric muscle, measurement of jaw movements, and nasal expiratory airflow under ketamine-xylazine anesthesia. Rhythmic jaw movements spontaneously occurred with rhythmic digastric muscle contractions, 23-29 minutes after injection of supplemental ketamine (12.5 and 25.0 mg kg-1 , intravenously). The cycle length of RJMs did not differ significantly between the two doses of ketamine (mean±SD: 12.5 mg kg-1 , 326.5 ± 60.0 ms; 25 mg kg-1 , 278.5 ± 45.1 ms). Following injection of ketamine, digastric muscle activity, heart and respiratory rates, and cortical beta power significantly decreased, while cortical delta and theta power significantly increased. These changes were significantly larger in animals given 25.0 mg kg-1 of ketamine than in those given 12.5 mg kg-1 . With the onset of RJMs, the levels of these variables returned to pre-injection levels, regardless of the dose of ketamine administered. These results suggest that, following supplemental ketamine injections, spontaneous RJMs occur during a specific period when the pharmacological effects of ketamine wear off, and that these RJMs are characterized by stereotypical changes in cardiac, respiratory, and cortical activities.

Top-down coordination of local cortical state during selective attention.

Spontaneous fluctuations in cortical excitability influence sensory processing and behavior. These fluctuations, long thought to reflect global changes in cortical state, were recently found to be modulated locally within a retinotopic map during spatially selective attention. We report that periods of vigorous (On) and faint (Off) spiking activity, the signature of cortical state fluctuations, are coordinated across brain areas with retinotopic precision. Top-down attention enhanced interareal local state coordination, traversing along the reverse cortical hierarchy. The extent of local state coordination between areas was predictive of behavioral performance. Our results show that cortical state dynamics are shared across brain regions, modulated by cognitive demands and relevant for behavior.

Modulation of Prefrontal Cortex Slow Oscillations by Phasic Activation of the Locus Coeruleus.

Cortical slow rhythmic activity, a hallmark of deep sleep, is observed under urethane anesthesia. Synchronized fluctuations of the membrane excitability of a large neuronal population are reflected in the extracellular Local Field Potential (LFP), as high-amplitude slow (∼1 Hz) oscillations (SO). The SO-phase indicates the presence (Up) or absence (Down) of neuronal spiking. The cortical state is controlled by the input from thalamic and neuromodulatory centers, including the brainstem noradrenergic nucleus Locus Coeruleus (LC). The bidirectional modulation of neuronal excitability by noradrenaline (NA) is well known. We have previously shown that LC phasic activation caused transient excitability increase in the medial prefrontal cortex (mPFC). In the present study, we characterized the effect of LC phasic activation on the prefrontal population dynamics at a temporal scale of a single SO cycle. We applied short (0.2 s) trains of electric pulses (0.02-0.05 mA at 20-50 Hz) to the LC cell bodies and monitored a broadband (0.1 Hz-8 kHz) mPFC LFP in urethane-anesthetized rats. The direct electrical stimulation of LC (LC-DES), applied during the Up-phase, enhanced the firing probability in the mPFC by ∼20% and substantially prolonged Up-states in 56% of trials. The LC-DES applied during Down-phase caused a rapid Down-to-Up transition in 81.5% of trials. The LC-DES was more effective at a higher frequency, but not at a higher current. Our results suggest that transient NA release, coupled to SO, may promote synaptic plasticity and memory consolidation by sustaining a depolarized state in the mPFC neurons.

Noise induced quiescence of epileptic spike generation in patients with epilepsy.

Clinical scalp electroencephalographic recordings from patients with epilepsy are distinguished by the presence of epileptic discharges i.e. spikes or sharp waves. These often occur randomly on a background of fluctuating potentials. The spike rate varies between different brain states (sleep and awake) and patients. Epileptogenic tissue and regions near these often show increased spike rates in comparison to other cortical regions. Several studies have shown a relation between spike rate and background activity although the underlying reason for this is still poorly understood. Both these processes, spike occurrence and background activity show evidence of being at least partly stochastic processes. In this study we show that epileptic discharges seen on scalp electroencephalographic recordings and background activity are driven at least partly by a common biological noise. Furthermore, our results indicate noise induced quiescence of spike generation which, in analogy with computational models of spiking, indicate spikes to be generated by transitions between semi-stable states of the brain, similar to the generation of epileptic seizure activity. The deepened physiological understanding of spike generation in epilepsy that this study provides could be useful in the electrophysiological assessment of different therapies for epilepsy including the effect of different drugs or electrical stimulation.

State-Dependent Changes in Perception and Coding in the Mouse Somatosensory Cortex.

An animal's behavioral state is reflected in the dynamics of cortical population activity and its capacity to process sensory information. To better understand the relationship between behavioral states and information processing, mice are trained to detect varying amplitudes of whisker-deflection under two-photon calcium imaging. Layer 2/3 neurons in the vibrissal primary somatosensory cortex are imaged across different behavioral states, defined based on detection performance (low to high-state) and pupil diameter. The neurometric curve in each behavioral state mirrors the corresponding psychometric performance, with calcium signals predictive of the animal's choice. High behavioral states are associated with lower network synchrony, extending over shorter cortical distances. The decrease in correlation across neurons in high state results in enhanced information transmission capacity at the population level. The observed state-dependent changes suggest that the coding regime within the first stage of cortical processing may underlie adaptive routing of relevant information through the sensorimotor system.

Neural networks of different species, brain areas and states can be characterized by the probability polling state.

Cortical networks are complex systems of a great many interconnected neurons that operate from collective dynamical states. To understand how cortical neural networks function, it is important to identify their common dynamical operating states from the probabilistic viewpoint. Probabilistic characteristics of these operating states often underlie network functions. Here, using multi-electrode data from three separate experiments, we identify and characterize a cortical operating state (the "probability polling" or "p-polling" state), common across mouse and monkey with different behaviors. If the interaction among neurons is weak, the p-polling state provides a quantitative understanding of how the high dimensional probability distribution of firing patterns can be obtained by the low-order maximum entropy formulation, effectively utilizing a low dimensional stimulus-coding structure. These results show evidence for generality of the p-polling state and in certain situations its advantage of providing a mathematical validation for the low-order maximum entropy principle as a coding strategy.

Whisking Asymmetry Signals Motor Preparation and the Behavioral State of Mice.

A central function of the brain is to plan, predict, and imagine the effect of movement in a dynamically changing environment. Here we show that in mice head-fixed in a plus-maze, floating on air, and trained to pick lanes based on visual stimuli, the asymmetric movement, and position of whiskers on the two sides of the face signals whether the animal is moving, turning, expecting reward, or licking. We show that (1) whisking asymmetry is coordinated with behavioral state, and that behavioral state can be decoded and predicted based on asymmetry, (2) even in the absence of tactile input, whisker positioning and asymmetry nevertheless relate to behavioral state, and (3) movement of the nose correlates with asymmetry, indicating that facial expression of the mouse is itself correlated with behavioral state. These results indicate that the movement of whiskers, a behavior that is not instructed or necessary in the task, can inform an observer about what a mouse is doing in the maze. Thus, the position of these mobile tactile sensors reflects a behavioral and movement-preparation state of the mouse.SIGNIFICANCE STATEMENT Behavior is a sequence of movements, where each movement can be related to or can trigger a set of other actions. Here we show that, in mice, the movement of whiskers (tactile sensors used to extract information about texture and location of objects) is coordinated with and predicts the behavioral state of mice: that is, what mice are doing, where they are in space, and where they are in the sequence of behaviors.

Cortex-wide Changes in Extracellular Potassium Ions Parallel Brain State Transitions in Awake Behaving Mice.

Brain state fluctuations modulate sensory processing, but the factors governing state-dependent neural activity remain unclear. Here, we tracked the dynamics of cortical extracellular K+ concentrations ([K+]o) during awake state transitions and manipulated [K+]o in slices, during visual processing, and during skilled motor execution. When mice transitioned from quiescence to locomotion, [K+]o increased by 0.6-1.0 mM in all cortical areas analyzed, and this preceded locomotion by 1 s. Emulating the state-dependent [K+]o increase in cortical slices caused neuronal depolarization and enhanced input-output transformation. In vivo, locomotion increased the gain of visually evoked responses in layer 2/3 of visual cortex; this effect was recreated by imposing a [K+]o increase. Elevating [K+]o in the motor cortex increased movement-induced neuronal spiking in layer 5 and improved motor performance. Thus, [K+]o increases in a cortex-wide state-dependent manner, and this [K+]o increase affects both sensory and motor processing through the dynamic modulation of neural activity.

Corrigendum: Theta Oscillations Alternate With High Amplitude Neocortical Population Within Synchronized States.

[This corrects the article DOI: 10.3389/fnins.2019.00316.].

Theta Oscillations Alternate With High Amplitude Neocortical Population Within Synchronized States.

Synchronized states are marked by large-amplitude low-frequency oscillations in the cortex. These states can be seen during quiet waking or slow-wave sleep. Within synchronized states, previous studies have noted a plethora of different types of activity, including delta oscillations (0.5-4 Hz) and slow oscillations (<1 Hz) in the neocortex and large- and small- irregular activity in the hippocampus. However, it is not still fully characterized how neural populations contribute to the synchronized state. Here we apply independent component analysis to parse which populations are involved in different kinds of neocortical activity, and find two populations that alternate throughout synchronized states. One population broadly affects neocortical deep layers, and is associated with larger amplitude slower neocortical oscillations. The other population exhibits theta-frequency oscillations that are not easily observed in raw field potential recordings. These theta oscillations apparently come from below the neocortex, suggesting hippocampal origin, and are associated with smaller amplitude faster neocortical oscillations. Relative involvement of these two alternating populations may indicate different modes of operation within synchronized states.

State-dependent geometry of population activity in rat auditory cortex.

The accuracy of the neural code depends on the relative embedding of signal and noise in the activity of neural populations. Despite a wealth of theoretical work on population codes, there are few empirical characterizations of the high-dimensional signal and noise subspaces. We studied the geometry of population codes in the rat auditory cortex across brain states along the activation-inactivation continuum, using sounds varying in difference and mean level across the ears. As the cortex becomes more activated, single-hemisphere populations go from preferring contralateral loud sounds to a symmetric preference across lateralizations and intensities, gain-modulation effectively disappears, and the signal and noise subspaces become approximately orthogonal to each other and to the direction corresponding to global activity modulations. Level-invariant decoding of sound lateralization also becomes possible in the active state. Our results provide an empirical foundation for the geometry and state-dependence of cortical population codes.

Occurrence of Hippocampal Ripples is Associated with Activity Suppression in the Mediodorsal Thalamic Nucleus.

Forming reliable memories requires coordinated activity within distributed brain networks. At present, neural mechanisms underlying systems-level consolidation of declarative memory beyond the hippocampal-prefrontal interactions remain largely unexplored. The mediodorsal thalamic nucleus (MD) is reciprocally connected with the medial prefrontal cortex (mPFC) and also receives inputs from parahippocampal regions. The MD may thus modulate functional connectivity between the hippocampus and the mPFC at different stages of information processing. Here, we characterized, in freely behaving Sprague Dawley male rats, the MD neural activity around hippocampal ripples, indicators of memory replay and hippocampal-cortical information transfer. Overall, the MD firing rate was transiently (0.76 ± 0.06 s) decreased around ripples, with the MD activity suppression preceding the ripple onset for 0.41 ± 0.04 s (range, 0.01-0.95 s). The degree of MD modulation correlated with ripple amplitude, differed across behavioral states, and also depended on the dynamics of hippocampal-cortical population activity. The MD suppression was the strongest and the most consistent during awake ripples. During non-rapid eye movement sleep, MD firing rate decreased around spindle-uncoupled ripples, but increased around spindle-coupled ripples. Our results suggest a competitive interaction between the thalamocortical and hippocampal-cortical networks supporting "on-line" and "off-line" information processing, respectively. We hypothesize that thalamic activity suppression during spindle-uncoupled ripples is favorable for memory replay, as it reduces interference from sensory relay. In turn, the thalamic input during hippocampal-cortical communication, as indicated by spindle/ripple coupling, may contribute to selectivity and reliability of information transfer. Both predictions need to be tested in future experiments.SIGNIFICANCE STATEMENT Systems mechanisms of declarative memory consolidation beyond the hippocampal-prefrontal interactions remain largely unexplored. The connectivity of the mediodorsal thalamic nucleus (MD) with extrahippocampal regions and with medial prefrontal cortex underlies its role in execution of diverse cognitive functions. However, little is known about the MD involvement in "off-line" consolidation. We found that MD neural activity was transiently suppressed around hippocampal ripples, except for ripples co-occurring with sleep spindles, when the MD activity was elevated. The thalamic activity suppression at times of spindle-uncoupled ripples may be favorable for memory replay, as it reduces interference with sensory relay. In turn, the thalamic input during hippocampal-cortical communication, as indicated by spindle/ripple coupling, may contribute to selectivity and reliability of information transfer.

Effects of Arousal on Mouse Sensory Cortex Depend on Modality.

Changes in arousal modulate the activity of mouse sensory cortex, but studies in different mice and different sensory areas disagree on whether this modulation enhances or suppresses activity. We measured this modulation simultaneously in multiple cortical areas by imaging mice expressing voltage-sensitive fluorescent proteins (VSFP). VSFP imaging estimates local membrane potential across large portions of cortex. We used temporal filters to predict local potential from running speed or from pupil dilation, two measures of arousal. The filters provided good fits and revealed that the effects of arousal depend on modality. In the primary visual cortex (V1) and auditory cortex (Au), arousal caused depolarization followed by hyperpolarization. In the barrel cortex (S1b) and a secondary visual area (LM), it caused only hyperpolarization. In all areas, nonetheless, arousal reduced the phasic responses to trains of sensory stimuli. These results demonstrate diverse effects of arousal across sensory cortex but similar effects on sensory responses.