Neural control of brain state

Apical drive-A cellular mechanism of dreaming?

Dreams are internally generated experiences that occur independently of current sensory input. Here we argue, based on cortical anatomy and function, that dream experiences are tightly related to the workings of a specific part of cortical pyramidal neurons, the apical integration zone (AIZ). The AIZ receives and processes contextual information from diverse sources and could constitute a major switch point for transitioning from externally to internally generated experiences such as dreams. We propose that during dreams the output of certain pyramidal neurons is mainly driven by input into the AIZ. We call this mode of functioning "apical drive". Our hypothesis is based on the evidence that the cholinergic and adrenergic arousal systems, which show different dynamics between waking, slow wave sleep, and rapid eye movement sleep, have specific effects on the AIZ. We suggest that apical drive may also contribute to waking experiences, such as mental imagery. Future studies, investigating the different modes of apical function and their regulation during sleep and wakefulness are likely to be richly rewarded.

Complementary Ca2+ Activity of Sensory Activated and Suppressed Layer 6 Corticothalamic Neurons Reflects Behavioral State

Layer 6 (L6) corticothalamic neurons project to thalamus, where they are thought to regulate sensory information transmission to cortex. However, the activity of these neurons during different behavioral states has not been described. Here, we imaged calcium changes in visual cortex L6 primary corticothalamic neurons with two-photon microscopy in head-fixed mice in response to passive viewing during a range of behavioral states, from locomotion to sleep. In addition to a substantial fraction of quiet neurons, we found sensory-activated and suppressed neurons, comprising two functionally distinct L6 feedback channels. Quiet neurons could be dynamically recruited to one or another functional channel, and the opposite, functional neurons could become quiet under different stimulation conditions or behavior states. The state dependence of neuronal activity was heterogeneous with respect to locomotion or level of alertness, although the average activity was largest during highest vigilance within populations of functional neurons. Interestingly, complementary activity of these distinct populations kept the overall corticothalamic feedback relatively constant during any given behavioral state. Thereby, in addition to sensory and non-sensory information, a constant activity level characteristic of behavioral state is conveyed to thalamus, where it can regulate signal transmission from the periphery to cortex.

The Spectrum of Asynchronous Dynamics in Spiking Networks as a Model for the Diversity of Non-rhythmic Waking States in the Neocortex

The awake cortex exhibits diverse non-rhythmic network states. However, how these states emerge and how each state impacts network function is unclear. Here, we demonstrate that model networks of spiking neurons with moderate recurrent interactions display a spectrum of non-rhythmic asynchronous dynamics based on the level of afferent excitation, from afferent input-dominated (AD) regimes, characterized by unbalanced synaptic currents and sparse firing, to recurrent input-dominated (RD) regimes, characterized by balanced synaptic currents and dense firing. The model predicted regime-specific relationships between different neural biophysical properties, which were all experimentally validated in the somatosensory cortex (S1) of awake mice. Moreover, AD regimes more precisely encoded spatiotemporal patterns of presynaptic activity, while RD regimes better encoded the strength of afferent inputs. These results provide a theoretical foundation for how recurrent neocortical circuits generate non-rhythmic waking states and how these different states modulate the processing of incoming information.

Shaping the Cortical Landscape: Functions and Mechanisms of Top-Down Cortical Feedback Pathways

Cortical feedback pathways are proposed to guide cognition and behavior according to context and goal-direction. At the cellular level, cortical feedback pathways target multiple excitatory and inhibitory populations. However, we currently lack frameworks that link how the cellular mechanisms of cortical feedback pathways underlie their cognitive/behavioral functions. To establish this link, we expand on the framework of signal routing, the ability of cortical feedback pathways to proactively modulate how feedforward signals are propagated throughout the cortex. We propose that cortical feedback modulates routing through multiple mechanisms: preparing intended motor representations, setting the trigger conditions for evoking cortical outputs, altering coupling strengths between cortical regions, and suppressing expected sensory representations. In developing this framework, we first define the anatomy of cortical feedback pathways and identify recent advances in studying their functions at high specificity and resolution. Second, we review the diverse functions of cortical feedback pathways throughout the cortical hierarchy and evaluate these functions from the framework of signal routing. Third, we review the conserved cellular targets and circuit impacts of cortical feedback. Fourth, we introduce the concept of the “cortical landscape,” a graphical depiction of the routes through cortex that are favored at a specific moment in time. We propose that the cortical landscape, analogous to energy landscapes in physics and chemistry, can capture important features of signal routing including coupling strength, trigger conditions, and preparatory states. By resolving the cortical landscape, we may be able to quantify how the cellular processes of cortical feedback ultimately shape cognition and behavior.

Three brain states in the hippocampus and cortex

Contemporary brain research seeks to understand how cognition is reducible to neural activity. Crucially, much of this effort is guided by a scientific paradigm that views neural activity as essentially driven by external stimuli. In contrast, recent perspectives argue that this paradigm is by itself inadequate and that understanding patterns of activity intrinsic to the brain is needed to explain cognition. Yet, despite this critique, the stimulus-driven paradigm still dominates-possibly because a convincing alternative has not been clear. Here, we review a series of findings suggesting such an alternative. These findings indicate that neural activity in the hippocampus occurs in one of three brain states that have radically different anatomical, physiological, representational, and behavioral correlates, together implying different functional roles in cognition. This three-state framework also indicates that neural representations in the hippocampus follow a surprising pattern of organization at the timescale of ∼1 s or longer. Lastly, beyond the hippocampus, recent breakthroughs indicate three parallel states in the cortex, suggesting shared principles and brain-wide organization of intrinsic neural activity.

Up and Down States and Memory Consolidation Across Somatosensory, Entorhinal, and Hippocampal Cortices

In the course of a day, brain states fluctuate, from conscious awake information-acquiring states to sleep states, during which previously acquired information is further processed and stored as memories. One hypothesis is that memories are consolidated and stored during "offline" states such as sleep, a process thought to involve transfer of information from the hippocampus to other cortical areas. Up and Down states (UDS), patterns of activity that occur under anesthesia and sleep states, are likely to play a role in this process, although the nature of this role remains unclear. Here we review what is currently known about these mechanisms in three anatomically distinct but interconnected cortical areas: somatosensory cortex, entorhinal cortex, and the hippocampus. In doing so, we consider the role of this activity in the coordination of "replay" during sleep states, particularly during hippocampal sharp-wave ripples. We conclude that understanding the generation and propagation of UDS may provide key insights into the cortico-hippocampal dialogue linking archi- and neocortical areas during memory formation.

Stability in the Face of Change: Lifelong Experience-Dependent Plasticity in the Sensory Cortex

Plasticity is a fundamental property of the nervous system that enables its adaptations to the ever-changing environment. Heightened plasticity typical for developing circuits facilitates their robust experience-dependent functional maturation. This plasticity wanes during adolescence to permit the stabilization of mature brain function, but abundant evidence supports that adult circuits exhibit both transient and long-term experience-induced plasticity. Cortical plasticity has been extensively studied throughout the life span in sensory systems and the main distinction between development and adulthood arising from these studies is the concept that passive exposure to relevant information is sufficient to drive robust plasticity early in life, while higher-order attentional mechanisms are necessary to drive plastic changes in adults. Recent work in the primary visual and auditory cortices began to define the circuit mechanisms that govern these processes and enable continuous adaptation to the environment, with transient circuit disinhibition emerging as a common prerequisite for both developmental and adult plasticity. Drawing from studies in visual and auditory systems, this review article summarizes recent reports on the circuit and cellular mechanisms of experience-driven plasticity in the developing and adult brains and emphasizes the similarities and differences between them. The benefits of distinct plasticity mechanisms used at different ages are discussed in the context of sensory learning, as well as their relationship to maladaptive plasticity and neurodevelopmental brain disorders. Knowledge gaps and avenues for future work are highlighted, and these will hopefully motivate future research in these areas, particularly those about the learning of complex skills during development.

Neuromodulation of Brain State and Behavior

Neural activity and behavior are both notoriously variable, with responses differing widely between repeated presentation of identical stimuli or trials. Recent results in humans and animals reveal that these variations are not random in their nature, but may in fact be due in large part to rapid shifts in neural, cognitive, and behavioral states. Here we review recent advances in the understanding of rapid variations in the waking state, how variations are generated, and how they modulate neural and behavioral responses in both mice and humans. We propose that the brain has an identifiable set of states through which it wanders continuously in a nonrandom fashion, owing to the activity of both ascending modulatory and fast-acting corticocortical and subcortical-cortical neural pathways. These state variations provide the backdrop upon which the brain operates, and understanding them is critical to making progress in revealing the neural mechanisms underlying cognition and behavior.

Cortical state transitions and stimulus response evolve along stiff and sloppy parameter dimensions, respectively

Previous research showed that spontaneous neuronal activity presents sloppiness: the collective behavior is strongly determined by a small number of parameter combinations, defined as ‘stiff’ dimensions, while it is insensitive to many others (‘sloppy’ dimensions). Here, we analyzed neural population activity from the auditory cortex of anesthetized rats while the brain spontaneously transited through different synchronized and desynchronized states and intermittently received sensory inputs. We showed that cortical state transitions were determined by changes in stiff parameters associated with the activity of a core of neurons with low responses to stimuli and high centrality within the observed network. In contrast, stimulus-evoked responses evolved along sloppy dimensions associated with the activity of neurons with low centrality and displaying large ongoing and stimulus-evoked fluctuations without affecting the integrity of the network. Our results shed light on the interplay among stability, flexibility, and responsiveness of neuronal collective dynamics during intrinsic and induced activity.

On the emergence of cognition: from catalytic closure to neuroglial closure

In an analogous manner as occurred during the development of a connected metabolism that at some point reached characteristics associated with what is called "life"-due mainly to a catalytic closure phenomenon when chemicals started to autocatalyze themselves forming a closed web of chemical reactions-it is here proposed that cognition and consciousness (or features associated with them) arose as a consequence of another type of closure within the nervous system, the brain especially. Proper brain function requires an efficient web of connections and once certain complexity is attained due to the number and coordinated activities of the brain cell networks, the emergent properties of cognition and consciousness take place. Seeking to identify main features of the nervous system organization for optimal function, it is here proposed that while catalytic closure yielded life, neuroglial closure produced cognition/consciousness.

Local cortical desynchronization and pupil-linked arousal differentially shape brain states for optimal sensory performance

Instantaneous brain states have consequences for our sensation, perception, and behaviour. Fluctuations in arousal and neural desynchronization likely pose perceptually relevant states. However, their relationship and their relative impact on perception is unclear. We here show that, at the single-trial level in humans, local desynchronization in sensory cortex (expressed as time-series entropy) versus pupil-linked arousal differentially impact perceptual processing. While we recorded electroencephalography (EEG) and pupillometry data, stimuli of a demanding auditory discrimination task were presented into states of high or low desynchronization of auditory cortex via a real-time closed-loop setup. Desynchronization and arousal distinctly influenced stimulus-evoked activity and shaped behaviour displaying an inverted u-shaped relationship: States of intermediate desynchronization elicited minimal response bias and fastest responses, while states of intermediate arousal gave rise to highest response sensitivity. Our results speak to a model in which independent states of local desynchronization and global arousal jointly optimise sensory processing and performance.

Arousal regulates frequency tuning in primary auditory cortex

Changes in brain state modulate how information is processed in sensory cortical areas. Here we use population imaging and intracellular recording to show that arousal regulates frequency tuning in layer 2/3 of primary auditory cortex. Increased arousal reduces lateral inhibition, broadens frequency tuning and enhances cortical representations of pure tones. Despite the arousal-dependent reduction in stimulus selectivity, frequency discrimination by cell ensembles improves due to a reduction in correlated variability (noise correlations).

Changes in arousal influence cortical sensory representations, but the synaptic mechanisms underlying arousal-dependent modulation of cortical processing are unclear. Here, we use 2-photon Ca²⁺ imaging in the auditory cortex of awake mice to show that heightened arousal, as indexed by pupil diameter, broadens frequency-tuned activity of layer 2/3 (L2/3) pyramidal cells. Sensory representations are less sparse, and the tuning of nearby cells more similar when arousal increases. Despite the reduction in selectivity, frequency discrimination by cell ensembles improves due to a decrease in shared trial-to-trial variability. In vivo whole-cell recordings reveal that mechanisms contributing to the effects of arousal on sensory representations include state-dependent modulation of membrane potential dynamics, spontaneous firing, and tone-evoked synaptic potentials. Surprisingly, changes in short-latency tone-evoked excitatory input cannot explain the effects of arousal on the broadness of frequency-tuned output. However, we show that arousal strongly modulates a slow tone-evoked suppression of recurrent excitation underlying lateral inhibition [H. K. Kato, S. K. Asinof, J. S. Isaacson, Neuron, 95, 412–423, (2017)]. This arousal-dependent “network suppression” gates the duration of tone-evoked responses and regulates the broadness of frequency tuning. Thus, arousal can shape tuning via modulation of indirect changes in recurrent network activity.

Cognitive fluctuations in Lewy body dementia: towards a pathophysiological framework

Fluctuating cognition is a complex and disabling symptom that is seen most frequently in the context of Lewy body dementias encompassing dementia with Lewy bodies and Parkinson’s disease dementia. In fact, since their description over three decades ago, cognitive fluctuations have remained a core diagnostic feature of dementia with Lewy bodies, the second most common dementia in the elderly. In the absence of reliable biomarkers for Lewy body pathology, the inclusion of such patients in therapeutic trials depends on the accurate identification of such core clinical features. Yet despite their diagnostic relevance, cognitive fluctuations remain poorly understood, in part due to the lack of a cohesive clinical and scientific explanation of the phenomenon itself. Motivated by this challenge, the present review examines the history, clinical phenomenology and assessment of cognitive fluctuations in the Lewy body dementias. Based on these data, the key neuropsychological, neurophysiological and neuroimaging correlates of cognitive fluctuations are described and integrated into a novel testable heuristic framework from which new insights may be gained.

Dynamic- and Frequency-Specific Regulation of Sleep Oscillations by Cortical Potassium Channels

Primary electroencephalographic (EEG) features of sleep arise in part from thalamocortical neural assemblies, and cortical potassium channels have long been thought to play a critical role. We have exploited the regionally dynamic nature of sleep EEG to develop a novel screening strategy and used it to conduct an adeno-associated virus (AAV)-mediated RNAi screen for cellular roles of 31 different voltage-gated potassium channels in modulating cortical EEG features across the circadian sleep-wake cycle. Surprisingly, a majority of channels modified only electroencephalographic frequency bands characteristic of sleep, sometimes diurnally or even in specific vigilance states. Confirming our screen for one channel, we show that depletion of the KCa1.1 (or "BK") channel reduces EEG power in slow-wave sleep by slowing neuronal repolarization. Strikingly, this reduction completely abolishes transcriptomic changes between sleep and wake. Thus, our data establish an unexpected connection between transcription and EEG power controlled by specific potassium channels. We postulate that additive dynamic roles of individual potassium channels could integrate different influences upon sleep and wake within single neurons.

Probing spatial inhomogeneity of cholinergic changes in cortical state in rat

Acetylcholine (ACh) plays an essential role in cortical information processing. Cholinergic changes in cortical state can fundamentally change how the neurons encode sensory input and motor output. Traditionally, ACh distribution in cortex and associated changes in cortical state have been assumed to be spatially diffuse. However, recent studies demonstrate a more spatially inhomogeneous structure of cholinergic projections to cortex. Moreover, many experimental manipulations of ACh have been done at a single spatial location, which inevitably results in spatially non-uniform ACh distribution. Such non-uniform application of ACh across the spatial extent of a cortical microcircuit could have important impacts on how the firing of groups of neurons is coordinated, but this remains largely unknown. Here we describe a method for applying ACh at different spatial locations within a single cortical circuit and measuring the resulting differences in population neural activity. We use two microdialysis probes implanted at opposite ends of a microelectrode array in barrel cortex of anesthetized rats. As a demonstration of the method, we applied ACh or neostigmine in different spatial locations via the microdialysis probes while we concomitantly recorded neural activity at 32 locations with the microelectrode array. First, we show that cholinergic changes in cortical state can vary dramatically depending on where the ACh was applied. Second, we show that cholinergic changes in cortical state can vary dramatically depending on where the state-change is measured. These results suggests that previous work with single-site recordings or single-site ACh application should be interpreted with some caution, since the results could change for different spatial locations.

Neuromodulatory Influences on Integration and Segregation in the Brain

Cognitive function relies on the dynamic cooperation of specialized regions of the brain; however, the elements of the system responsible for coordinating this interaction remain poorly understood. In this Opinion article I argue that this capacity is mediated in part by competitive and cooperative dynamic interactions between two prominent metabotropic neuromodulatory systems - the cholinergic basal forebrain and the noradrenergic locus coeruleus (LC). I assert that activity in these projection nuclei regulates the amount of segregation and integration within the whole brain network by modulating the activity of a diverse set of specialized regions of the brain on a timescale relevant for cognition and attention.

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.

Is There a Future for Non-invasive Brain Stimulation as a Therapeutic Tool?

Several techniques and protocols of non-invasive transcranial brain stimulation (NIBS), including transcranial magnetic and electrical stimuli, have been developed in the past decades. These techniques can induce long lasting changes in cortical excitability by promoting synaptic plasticity and thus may represent a therapeutic option in neuropsychiatric disorders. On the other hand, despite these techniques have become popular, the fragility and variability of the after effects are the major challenges that non-invasive transcranial brain stimulation currentlyfaces. Several factors may account for such a variability such as biological variations, measurement reproducibility, and the neuronal state of the stimulated area. One possible strategy, to reduce this variability is to monitor the neuronal state in real time using EEG and trigger TMS pulses only at pre-defined state. In addition, another strategy under study is to use the spaced application of multiple NIBS protocols within a session to improve the reliability and extend the duration of NIBS effects. Further studies, although time consuming, are required for improving the so far limited effect sizes of NIBS protocols for treatment of neurological or psychiatric disorders.

State-Dependent Changes in Brain Glycogen Metabolism

A fundamental understanding of glycogen structure, concentration, polydispersity and turnover is critical to qualify the role of glycogen in the brain. These molecular and metabolic features are under the control of neuronal activity through the interdependent action of neuromodulatory tone, ionic homeostasis and availability of metabolic substrates, all variables that concur to define the state of the system. In this chapter, we briefly describe how glycogen responds to selected behavioral, nutritional, environmental, hormonal, developmental and pathological conditions. We argue that interpreting glycogen metabolism through the lens of brain state is an effective approach to establish the relevance of energetics in connecting molecular and cellular neurophysiology to behavior.

Data-Driven Modeling of Cholinergic Modulation of Neural Microcircuits: Bridging Neurons, Synapses and Network Activity

Neuromodulators, such as acetylcholine (ACh), control information processing in neural microcircuits by regulating neuronal and synaptic physiology. Computational models and simulations enable predictions on the potential role of ACh in reconfiguring network activity. As a prelude into investigating how the cellular and synaptic effects of ACh collectively influence emergent network dynamics, we developed a data-driven framework incorporating phenomenological models of the physiology of cholinergic modulation of neocortical cells and synapses. The first-draft models were integrated into a biologically detailed tissue model of neocortical microcircuitry to investigate the effects of levels of ACh on diverse neuron types and synapses, and consequently on emergent network activity. Preliminary simulations from the framework, which was not tuned to reproduce any specific ACh-induced network effects, not only corroborate the long-standing notion that ACh desynchronizes spontaneous network activity, but also predict that a dose-dependent activation of ACh gives rise to a spectrum of neocortical network activity. We show that low levels of ACh, such as during non-rapid eye movement (nREM) sleep, drive microcircuit activity into slow oscillations and network synchrony, whereas high ACh concentrations, such as during wakefulness and REM sleep, govern fast oscillations and network asynchrony. In addition, spontaneous network activity modulated by ACh levels shape spike-time cross-correlations across distinct neuronal populations in strikingly different ways. These effects are likely due to the regulation of neurons and synapses caused by increasing levels of ACh, which enhances cellular excitability and decreases the efficacy of local synaptic transmission. We conclude by discussing future directions to refine the biological accuracy of the framework, which will extend its utility and foster the development of hypotheses to investigate the role of neuromodulators in neural information processing.

Tune it in: mechanisms and computational significance of neuron-autonomous plasticity

The activity of a neural network is a result of synaptic signals that convey the communication between neurons and neuron-based intrinsic currents that determine the neuron’s input-output transfer function. Ample studies have demonstrated that cell-based excitability, and in particular intrinsic excitability, is modulated by learning and that these modifications play a key role in learning-related behavioral changes. The field of cell-based plasticity is largely growing, and it entails numerous experimental findings that demonstrate a large diversity of currents that are affected by learning. The diverse effect of learning on the neuron’s excitability emphasizes the need for a framework under which cell-based plasticity can be categorized to enable the assessment of the computational roles of the intrinsic modifications. We divide the domain of cell-based plasticity into three main categories, where the first category entails the currents that mediate the passive properties and single-spike generation, the second category entails the currents that mediate spike frequency adaptation, and the third category entails a novel learning-induced mechanism where all excitatory and inhibitory synapses double their strength. Curiously, this elementary division enables a natural categorization of the computational roles of these learning-induced plasticities. The computational roles are diverse and include modification of the neuronal mode of action, such as bursting, prolonged, and fast responsive; attention-like effect where the signal detection is improved; transfer of the network into an active state; biasing the competition for memory allocation; and transforming an environmental cue into a dominant cue and enabling a quicker formation of new memories.

Cortical signatures of wakeful somatosensory processing

Sensory inputs carry critical information for the survival of an organism. In mice, tactile information conveyed by the whiskers is of high behavioural relevance, and is broadcasted across cortical areas beyond the primary somatosensory cortex. Mesoscopic voltage sensitive dye imaging (VSDI) of cortical population response to whisker stimulations has shown that seemingly 'simple' sensory stimuli can have extended impact on cortical circuit dynamics. Here we took advantage of genetically encoded voltage indicators (GEVIs) that allow for cell type-specific monitoring of population voltage dynamics in a chronic dual-hemisphere transcranial windowed mouse preparation to directly compare the cortex-wide broadcasting of sensory information in wakening (lightly anesthetized to sedated) and awake mice. Somatosensory-evoked cortex-wide dynamics is altered across brain states, with anatomically sequential hyperpolarising activity observed in the awake cortex. GEVI imaging revealed cortical activity maps with increased specificity, high spatial coverage, and at the timescale of cortical information processing.

Arousal dependent modulation of thalamo-cortical functional interaction

Ongoing changes in arousal influence sensory processing and behavioral performance. Yet the circuit-level correlates for this influence remain poorly understood. Here, we investigate how functional interaction between posterior parietal cortex (PPC) and lateral posterior (LP)/Pulvinar is influenced by ongoing fluctuations in pupil-linked arousal, which is a non-invasive measure of neuromodulatory tone in the brain. We find that fluctuations in pupil-linked arousal correlate with changes to PPC to LP/Pulvinar oscillatory interaction, with cortical alpha oscillations driving activity during low arousal states, and LP/Pulvinar driving PPC in the theta frequency band during higher arousal states. Active visual exploration by saccadic eye movements elicits similar transitions in thalamo-cortical interaction. Furthermore, the presentation of naturalistic video stimuli induces thalamo-cortical network states closely resembling epochs of high arousal in the absence of visual input. Thus, neuromodulators may play a role in dynamically sculpting the patterns of thalamo-cortical functional interaction that underlie visual processing.

Synaptic Release of Acetylcholine Rapidly Suppresses Cortical Activity by Recruiting Muscarinic Receptors in Layer 4

Cholinergic afferents from the basal forebrain (BF) can influence cortical activity on rapid time scales, enabling sensory information processing and exploratory behavior. However, our understanding of how synaptically released acetylcholine (ACh) influences cellular targets in distinct cortical layers remains incomplete. Previous studies have shown that rapid changes in cortical dynamics induced by phasic BF activity can be mediated by the activation of nicotinic ACh receptors (nAChRs) expressed in distinct types of GABAergic interneurons. In contrast, muscarinic ACh receptors (mAChRs) are assumed to be involved in slower and more diffuse ACh signaling following sustained increases in afferent activity. Here, we examined the mechanisms underlying fast cholinergic control of cortical circuit dynamics by pairing optical stimulation of cholinergic afferents with evoked activity in somatosensory cortical slices of mice of either sex. ACh release evoked by single stimuli led to a rapid and persistent suppression of cortical activity, mediated by mAChRs expressed in layer 4 and to a lesser extent, by nAChRs in layers 1-3. In agreement, we found that cholinergic inputs to layer 4 evoked short-latency and long-lasting mAChR-dependent inhibition of the large majority of excitatory neurons, whereas inputs to layers 1-3 primarily evoked nAChR-dependent excitation of different classes of interneurons. Our results indicate that the rapid cholinergic control of cortical network dynamics is mediated by both nAChRs and mAChRs-dependent mechanisms, which are expressed in distinct cortical layers and cell types.SIGNIFICANCE STATEMENT Acetylcholine (ACh) release from basal forebrain (BF) afferents to cortex influences a variety of cognitive functions including attention, sensory processing, and learning. Cholinergic control occurs on the time scale of seconds and is mediated by BF neurons that generate action potentials at low rates, indicating that ACh acts as a point-to-point neurotransmitter. Our findings highlight that even brief activation of cholinergic afferents can recruit both nicotinic and muscarinic ACh receptors expressed in several cell types, leading to modulation of cortical activity on distinct time scales. Furthermore, they indicate that the initial stages of cortical sensory processing are under direct cholinergic control.

Switchable slow cellular conductances determine robustness and tunability of network states

Neuronal information processing is regulated by fast and localized fluctuations of brain states. Brain states reliably switch between distinct spatiotemporal signatures at a network scale even though they are composed of heterogeneous and variable rhythms at a cellular scale. We investigated the mechanisms of this network control in a conductance-based population model that reliably switches between active and oscillatory mean-fields. Robust control of the mean-field properties relies critically on a switchable negative intrinsic conductance at the cellular level. This conductance endows circuits with a shared cellular positive feedback that can switch population rhythms on and off at a cellular resolution. The switch is largely independent from other intrinsic neuronal properties, network size and synaptic connectivity. It is therefore compatible with the temporal variability and spatial heterogeneity induced by slower regulatory functions such as neuromodulation, synaptic plasticity and homeostasis. Strikingly, the required cellular mechanism is available in all cell types that possess T-type calcium channels but unavailable in computational models that neglect the slow kinetics of their activation.

Brain information processing involves electrophysiological signals at multiple temporal and spatial timescales, from the single neuron level to whole brain areas. A fast and local control of these signals by neurochemicals called neuromodulators is essential in complex tasks such as movement initiation and attentional focus. The neuromodulators act at the cellular scale to control signals that propagate at potentially much larger scales. The present paper highlights the critical role of a cellular switch of excitability for the fast and localized control of cellular and network states. By turning ON and OFF the cellular switch, neuromodulators can robustly switch large populations between distinct network states. We stress the importance of controlling the switch at a cellular level and independently of the connectivity to allow for tunable spatiotemporal signatures of the network states.

Big data and the industrialization of neuroscience: A safe roadmap for understanding the brain?

New technologies in neuroscience generate reams of data at an exponentially increasing rate, spurring the design of very-large-scale data-mining initiatives. Several supranational ventures are contemplating the possibility of achieving, within the next decade(s), full simulation of the human brain.

New waves: Rhythmic electrical field stimulation systematically alters spontaneous slow dynamics across mouse neocortex

The signature rhythm of slow-wave forebrain activity is the large amplitude, slow oscillation (SO: ∼1 Hz) made up of alternating synchronous periods of activity and silence at the single cell and network levels. On each wave, the SO originates at a unique location and propagates across the neocortex. Attempts to manipulate SO activity using electrical fields have been shown to entrain cortical networks and enhance memory performance. However, neural activity during this manipulation has remained elusive due to methodological issues in typical electrical recordings. Here we took advantage of voltage-sensitive dye (VSD) imaging in a bilateral cortical preparation of urethane-anesthetized mice to track SO cortical activity and its modulation by sinusoidal electrical field stimulation applied to frontal regions. We show that under spontaneous conditions, the SO propagates in two main opposing directional patterns along an anterior lateral - posterior medial axis, displaying a rich variety of possible trajectories on any given wave. Under rhythmic field stimulation, new propagation patterns emerge, which are not observed under spontaneous conditions, reflecting stimulus-entrained activity with distributed and varied anterior initiation zones and a consistent termination zone in the posterior somatosensory cortex. Furthermore, stimulus-induced activity patterns tend to repeat cycle after cycle, showing higher stereotypy than during spontaneous activity. Our results show that slow electrical field stimulation robustly entrains and alters ongoing slow cortical dynamics during sleep-like states, suggesting a mechanism for targeting specific cortical representations to manipulate memory processes.

A Systems Neuroscience Approach to Migraine

Migraine is an extremely common but poorly understood nervous system disorder. We conceptualize migraine as a disorder of sensory network gain and plasticity, and we propose that this framing makes it amenable to the tools of current systems neuroscience.

The influence of locomotion on sensory processing and its underlying neuronal circuits

Processing of sensory information can be modulated in both cortex and thalamus by behavioral context, such as locomotion. During active behaviors, coding of sensory stimuli and perception are improved, in particular during physical activity of moderate intensity. These locomotion-related modulations seem to arise from a combination of mechanisms, including neuromodulation, the recruitment of inhibitory interneurons, and specific top-down or motor-related inputs. The application of new experimental methods in mice during walking under head-fixation on treadmills made it possible to study the circuit and cellular basis underlying modulations by behavioral context with unprecedented detail. This article reviews the current state of these studies and highlights some important open questions.

Brain entropy and human intelligence: A resting-state fMRI study

Human intelligence comprises comprehension of and reasoning about an infinitely variable external environment. A brain capable of large variability in neural configurations, or states, will more easily understand and predict variable external events. Entropy measures the variety of configurations possible within a system, and recently the concept of brain entropy has been defined as the number of neural states a given brain can access. This study investigates the relationship between human intelligence and brain entropy, to determine whether neural variability as reflected in neuroimaging signals carries information about intellectual ability. We hypothesize that intelligence will be positively associated with entropy in a sample of 892 healthy adults, using resting-state fMRI. Intelligence is measured with the Shipley Vocabulary and WASI Matrix Reasoning tests. Brain entropy was positively associated with intelligence. This relation was most strongly observed in the prefrontal cortex, inferior temporal lobes, and cerebellum. This relationship between high brain entropy and high intelligence indicates an essential role for entropy in brain functioning. It demonstrates that access to variable neural states predicts complex behavioral performance, and specifically shows that entropy derived from neuroimaging signals at rest carries information about intellectual capacity. Future work in this area may elucidate the links between brain entropy in both resting and active states and various forms of intelligence. This insight has the potential to provide predictive information about adaptive behavior and to delineate the subdivisions and nature of intelligence based on entropic patterns.

The Mutual Interaction Between Sleep and Epilepsy on the Neurobiological Basis and Therapy

BACKGROUND

Sleep and epilepsy are mutually related in a complex, bidirectional manner. However, our understanding of this relationship remains unclear.

RESULTS

The literatures of the neurobiological basis of the interactions between sleep and epilepsy indicate that non rapid eye movement sleep and idiopathic generalized epilepsy share the same thalamocortical networks. Most of neurotransmitters and neuromodulators such as adenosine, melatonin, prostaglandin D2, serotonin, and histamine are found to regulate the sleep-wake behavior and also considered to have antiepilepsy effects; antiepileptic drugs, in turn, also have effects on sleep. Furthermore, many drugs that regulate the sleep-wake cycle can also serve as potential antiseizure agents. The nonpharmacological management of epilepsy including ketogenic diet, epilepsy surgery, neurostimulation can also influence sleep.

CONCLUSION

In this paper, we address the issues involved in these phenomena and also discuss the various therapies used to modify them.

Sleep- and Wake-Like States in Small Networks In Vivo and In Vitro

Wakefulness and sleep are highly complex and heterogeneous processes, involving multiple neurotransmitter systems and a sophisticated interplay between global and local networks of neurons and non-neuronal cells. Macroscopic approaches applied at the level of the whole organism, view sleep as a global behaviour and allow for investigation into aspects such as the effects of insufficient or disrupted sleep on cognitive function, metabolism, thermoregulation and sensory processing. While significant progress has been achieved using such large-scale approaches, the inherent complexity of sleep-wake regulation has necessitated the development of methods which tackle specific aspects of sleep in isolation. One way this may be achieved is by investigating specific cellular or molecular phenomena in the whole organism in situ, either during spontaneous or induced sleep-wake states. This approach has greatly advanced our knowledge about the electrophysiology and pharmacology of ion channels, specific receptors, intracellular pathways and the small networks implicated in the control and regulation of the sleep-wake cycle. Importantly though, there are a variety of external and internal factors that influence global behavioural states which are difficult to control for using these approaches. For this reason, over the last few decades, ex vivo experimental models have become increasingly popular and have greatly advanced our understanding of many fundamental aspects of sleep, including the neuroanatomy and neurochemistry of sleep states, sleep regulation, the origin and dynamics of specific sleep oscillations, network homeostasis as well as the functional roles of sleep. This chapter will focus on the use of small neuronal networks as experimental models and will highlight the most significant and novel insights these approaches have provided.

Dynamical networks: Finding, measuring, and tracking neural population activity using network science

Systems neuroscience is in a headlong rush to record from as many neurons at the same time as possible. As the brain computes and codes using neuron populations, it is hoped these data will uncover the fundamentals of neural computation. But with hundreds, thousands, or more simultaneously recorded neurons come the inescapable problems of visualizing, describing, and quantifying their interactions. Here I argue that network science provides a set of scalable, analytical tools that already solve these problems. By treating neurons as nodes and their interactions as links, a single network can visualize and describe an arbitrarily large recording. I show that with this description we can quantify the effects of manipulating a neural circuit, track changes in population dynamics over time, and quantitatively define theoretical concepts of neural populations such as cell assemblies. Using network science as a core part of analyzing population recordings will thus provide both qualitative and quantitative advances to our understanding of neural computation.

Sensation during Active Behaviors

A substantial portion of our sensory experience happens during active behaviors such as walking around or paying attention. How do sensory systems work during such behaviors? Neural processing in sensory systems can be shaped by behavior in multiple ways ranging from a modulation of responsiveness or sharpening of tuning to a dynamic change of response properties or functional connectivity. Here, we review recent findings on the modulation of sensory processing during active behaviors in different systems: insect vision, rodent thalamus, and rodent sensory cortices. We discuss the circuit-level mechanisms that might lead to these modulations and their potential role in sensory function. Finally, we highlight the open questions and future perspectives of this exciting new field.

Dynamic reconfiguration of cortical functional connectivity across brain states

Throughout each day, the brain displays transient changes in state, as evidenced by shifts in behavior and vigilance. While the electrophysiological correlates of brain states have been studied for some time, it remains unclear how large-scale cortico-cortical functional connectivity systematically reconfigures across states. Here, we investigate state-dependent shifts in cortical functional connectivity by recording local field potentials (LFPs) during spontaneous behavioral transitions in the ferret using chronically implanted micro-electrocorticographic (µECoG) arrays positioned over occipital, parietal, and temporal cortical regions. To objectively classify brain state, we describe a data-driven approach that projects time-varying LFP spectral properties into brain state space. Distinct brain states displayed markedly different patterns of cross-frequency phase-amplitude coupling and inter-electrode phase synchronization across several LFP frequency bands. The largest across-state differences in functional connectivity were observed between periods of presumed slow-wave and rapid-eye-movement-sleep/active-state, which were characterized by the contrasting phenomena of cortical network fragmentation and global synchronization, respectively. Collectively, our data provide strong evidence that large-scale functional interactions in the brain dynamically reconfigure across behavioral states.

Mesoscale-duration activated states gate spiking in response to fast rises in membrane voltage in the awake brain

Seconds-scale network states, affecting many neurons within a network, modulate neural activity by complementing fast integration of neuron-specific inputs that arrive in the milliseconds before spiking. Nonrhythmic subthreshold dynamics at intermediate timescales, however, are less well characterized. We found, using automated whole cell patch clamping in vivo, that spikes recorded in CA1 and barrel cortex in awake mice are often preceded not only by monotonic voltage rises lasting milliseconds but also by more gradual (lasting tens to hundreds of milliseconds) depolarizations. The latter exert a gating function on spiking, in a fashion that depends on the gradual rise duration: the probability of spiking was higher for longer gradual rises, even when controlled for the amplitude of the gradual rises. Barrel cortex double-autopatch recordings show that gradual rises are shared across some, but not all, neurons. The gradual rises may represent a new kind of state, intermediate both in timescale and in proportion of neurons participating, which gates a neuron's ability to respond to subsequent inputs.NEW & NOTEWORTHY We analyzed subthreshold activity preceding spikes in hippocampus and barrel cortex of awake mice. Aperiodic voltage ramps extending over tens to hundreds of milliseconds consistently precede and facilitate spikes, in a manner dependent on both their amplitude and their duration. These voltage ramps represent a "mesoscale" activated state that gates spike production in vivo.

Spontaneous cortical activity is transiently poised close to criticality

Brain activity displays a large repertoire of dynamics across the sleep-wake cycle and even during anesthesia. It was suggested that criticality could serve as a unifying principle underlying the diversity of dynamics. This view has been supported by the observation of spontaneous bursts of cortical activity with scale-invariant sizes and durations, known as neuronal avalanches, in recordings of mesoscopic cortical signals. However, the existence of neuronal avalanches in spiking activity has been equivocal with studies reporting both its presence and absence. Here, we show that signs of criticality in spiking activity can change between synchronized and desynchronized cortical states. We analyzed the spontaneous activity in the primary visual cortex of the anesthetized cat and the awake monkey, and found that neuronal avalanches and thermodynamic indicators of criticality strongly depend on collective synchrony among neurons, LFP fluctuations, and behavioral state. We found that synchronized states are associated to criticality, large dynamical repertoire and prolonged epochs of eye closure, while desynchronized states are associated to sub-criticality, reduced dynamical repertoire, and eyes open conditions. Our results show that criticality in cortical dynamics is not stationary, but fluctuates during anesthesia and between different vigilance states.

Ca2+-dependent hyperpolarization hypothesis for mammalian sleep

The detailed molecular mechanisms underlying the regulation of sleep/wake cycles in mammals are elusive. In this regulation, at least two mechanisms with fast and slow time scales are involved. In the faster time scale, a state of non-rapid-eye-movement (NREM) sleep can be microscopically characterized by the millisecond-to-second-order electrical behavior of neurons, namely slow-wave oscillations described by electrophysiology. In the slower time scale, the total duration of NREM sleep is homeostatically regulated by sleep pressure (the need for sleep), which is usually sustained for hours or even days and can be macroscopically described by electroencephalogram (EEG). The longer dynamics of sleep regulation are often explained by the accumulation of sleep-inducing substances (SISs). However, we still do not have a concrete model to connect fast, microscopic dynamics and slow, macroscopic dynamics. In this review, we introduce a recent Ca²⁺-dependent hyperpolarization hypothesis, in which the Ca²⁺-dependent hyperpolarization of cortical-membrane potential induces slow-wave oscillation. Slow dynamics of the Ca²⁺-dependent hyperpolarization pathway might be regulated by recently identified sleep-promoting kinases as well as classical SISs. Therefore, cortical Ca²⁺-dependent hyperpolarization may be a fundamental mechanism connecting fast neural activity to the slow dynamics of sleep pressure.

Relationship between cortical state and spiking activity in the lateral geniculate nucleus of marmosets

KEY POINTS

How parallel are the primate visual pathways? In the present study, we demonstrate that parallel visual pathways in the dorsal lateral geniculate nucleus (LGN) show distinct patterns of interaction with rhythmic activity in the primary visual cortex (V1). In the V1 of anaesthetized marmosets, the EEG frequency spectrum undergoes transient changes that are characterized by fluctuations in delta-band EEG power. We show that, on multisecond timescales, spiking activity in an evolutionary primitive (koniocellular) LGN pathway is specifically linked to these slow EEG spectrum changes. By contrast, on subsecond (delta frequency) timescales, cortical oscillations can entrain spiking activity throughout the entire LGN. Our results are consistent with the hypothesis that, in waking animals, the koniocellular pathway selectively participates in brain circuits controlling vigilance and attention.

ABSTRACT

The major afferent cortical pathway in the visual system passes through the dorsal lateral geniculate nucleus (LGN), where nerve signals originating in the eye can first interact with brain circuits regulating visual processing, vigilance and attention. In the present study, we investigated how ongoing and visually driven activity in magnocellular (M), parvocellular (P) and koniocellular (K) layers of the LGN are related to cortical state. We recorded extracellular spiking activity in the LGN simultaneously with local field potentials (LFP) in primary visual cortex, in sufentanil-anaesthetized marmoset monkeys. We found that asynchronous cortical states (marked by low power in delta-band LFPs) are linked to high spike rates in K cells (but not P cells or M cells), on multisecond timescales. Cortical asynchrony precedes the increases in K cell spike rates by 1-3 s, implying causality. At subsecond timescales, the spiking activity in many cells of all (M, P and K) classes is phase-locked to delta waves in the cortical LFP, and more cells are phase-locked during synchronous cortical states than during asynchronous cortical states. The switch from low-to-high spike rates in K cells does not degrade their visual signalling capacity. By contrast, during asynchronous cortical states, the fidelity of visual signals transmitted by K cells is improved, probably because K cell responses become less rectified. Overall, the data show that slow fluctuations in cortical state are selectively linked to K pathway spiking activity, whereas delta-frequency cortical oscillations entrain spiking activity throughout the entire LGN, in anaesthetized marmosets.

Does Global Astrocytic Calcium Signaling Participate in Awake Brain State Transitions and Neuronal Circuit Function?

We continuously need to adapt to changing conditions within our surrounding environment, and our brain needs to quickly shift between resting and working activity states in order to allow appropriate behaviors. These global state shifts are intimately linked to the brain-wide release of the neuromodulators, noradrenaline and acetylcholine. Astrocytes have emerged as a new player participating in the regulation of brain activity, and have recently been implicated in brain state shifts. Astrocytes display global Ca²⁺ signaling in response to activation of the noradrenergic system, but whether astrocytic Ca²⁺ signaling is causative or correlative for shifts in brain state and neural activity patterns is not known. Here we review the current available literature on astrocytic Ca²⁺ signaling in awake animals in order to explore the role of astrocytic signaling in brain state shifts. Furthermore, we look at the development and availability of innovative new methodological tools that are opening up for new ways of visualizing and perturbing astrocyte activity in awake behaving animals. With these new tools at hand, the field of astrocyte research will likely be able to elucidate the causal and mechanistic roles of astrocytes in complex behaviors within a very near future.

Guiding transcranial brain stimulation by EEG/MEG to interact with ongoing brain activity and associated functions: A position paper

Non-invasive transcranial brain stimulation (NTBS) techniques have a wide range of applications but also suffer from a number of limitations mainly related to poor specificity of intervention and variable effect size. These limitations motivated recent efforts to focus on the temporal dimension of NTBS with respect to the ongoing brain activity. Temporal patterns of ongoing neuronal activity, in particular brain oscillations and their fluctuations, can be traced with electro- or magnetoencephalography (EEG/MEG), to guide the timing as well as the stimulation settings of NTBS. These novel, online and offline EEG/MEG-guided NTBS-approaches are tailored to specifically interact with the underlying brain activity. Online EEG/MEG has been used to guide the timing of NTBS (i.e., when to stimulate): by taking into account instantaneous phase or power of oscillatory brain activity, NTBS can be aligned to fluctuations in excitability states. Moreover, offline EEG/MEG recordings prior to interventions can inform researchers and clinicians how to stimulate: by frequency-tuning NTBS to the oscillation of interest, intrinsic brain oscillations can be up- or down-regulated. In this paper, we provide an overview of existing approaches and ideas of EEG/MEG-guided interventions, and their promises and caveats. We point out potential future lines of research to address challenges.

Real Time Multiplicative Memory Amplification Mediated by Whole-Cell Scaling of Synaptic Response in Key Neurons

Intense spiking response of a memory-pattern is believed to play a crucial role both in normal learning and pathology, where it can create biased behavior. We recently proposed a novel model for memory amplification where the simultaneous two-fold increase of all excitatory (AMPAR-mediated) and inhibitory (GABA_AR-mediated) synapses in a sub-group of cells that constitutes a memory-pattern selectively amplifies this memory. Here we confirm the cellular basis of this model by validating its major predictions in four sets of experiments, and demonstrate its induction via a whole-cell transduction mechanism. Subsequently, using theory and simulations, we show that this whole-cell two-fold increase of all inhibitory and excitatory synapses functions as an instantaneous and multiplicative amplifier of the neurons’ spiking. The amplification mechanism acts through multiplication of the net synaptic current, where it scales both the average and the standard deviation of the current. In the excitation-inhibition balance regime, this scaling creates a linear multiplicative amplifier of the cell’s spiking response. Moreover, the direct scaling of the synaptic input enables the amplification of the spiking response to be synchronized with rapid changes in synaptic input, and to be independent of previous spiking activity. These traits enable instantaneous real-time amplification during brief elevations of excitatory synaptic input. Furthermore, the multiplicative nature of the amplifier ensures that the net effect of the amplification is large mainly when the synaptic input is mostly excitatory. When induced on all cells that comprise a memory-pattern, these whole-cell modifications enable a substantial instantaneous amplification of the memory-pattern when the memory is activated. The amplification mechanism is induced by CaMKII dependent phosphorylation that doubles the conductance of all GABA_A and AMPA receptors in a subset of neurons. This whole-cell transduction mechanism enables both long-term induction of memory amplification when necessary and extinction when not further required.

Amplifying the strength of a neuronal assembly that underlies a behavioral choice can lead to a particularly long lasting dominant memory. We report experimental and theoretical evidence for a long-term mechanism that amplifies the response of a neuronal assembly which we termed “memory amplification mechanism”. The amplification mechanism is mediated by doubling the strength of all inhibitory and all excitatory synapses in the cell and is induced by whole-cell phosphorylation of all inhibitory and excitatory synaptic receptors in a subset of cells, via a process that is distinct from memory formation. Computationally, the inherent scaling of both excitation and inhibition yields a robust and stable amplifier of the neuron’s response. When such an amplifier is induced in a set of cells that compose a memory-pattern, it can selectively amplify the response of this memory. The memory amplification mechanism is independent from associative learning. Thus, while associative learning forms a memory that encodes new associations, the amplification mechanism can promote an already formed memory to a dominant memory.

Pupil fluctuations track rapid changes in adrenergic and cholinergic activity in cortex

Rapid variations in cortical state during wakefulness have a strong influence on neural and behavioural responses and are tightly coupled to changes in pupil size across species. However, the physiological processes linking cortical state and pupil variations are largely unknown. Here we demonstrate that these rapid variations, during both quiet waking and locomotion, are highly correlated with fluctuations in the activity of corticopetal noradrenergic and cholinergic projections. Rapid dilations of the pupil are tightly associated with phasic activity in noradrenergic axons, whereas longer-lasting dilations of the pupil, such as during locomotion, are accompanied by sustained activity in cholinergic axons. Thus, the pupil can be used to sensitively track the activity in multiple neuromodulatory transmitter systems as they control the state of the waking brain.

In addition to light intensity, changes in pupil diameter are correlated with mental effort, attention and levels of arousal. Reimer et al. report that across behavioural states, fluctuations in pupil diameter are highly correlated with activity of noradrenergic and cholinergic projection neurons.

Rapid Sensory Adaptation Redux: A Circuit Perspective

Adaptation is fundamental to life. All organisms adapt over timescales that span from evolution to generations and lifetimes to moment-by-moment interactions. The nervous system is particularly adept at rapidly adapting to change, and this in fact may be one of its fundamental principles of organization and function. Rapid forms of sensory adaptation have been well documented across all sensory modalities in a wide range of organisms, yet we do not have a comprehensive understanding of the adaptive cellular mechanisms that ultimately give rise to the corresponding percepts, due in part to the complexity of the circuitry. In this Perspective, we aim to build links between adaptation at multiple scales of neural circuitry by investigating the differential adaptation across brain regions and sub-regions and across specific cell types, for which the explosion of modern tools has just begun to enable. This investigation points to a set of challenges for the field to link functional observations to adaptive properties of the neural circuit that ultimately underlie percepts.

Stereotypic wheel running decreases cortical activity in mice

Prolonged wakefulness is thought to gradually increase ‘sleep need' and influence subsequent sleep duration and intensity, but the role of specific waking behaviours remains unclear. Here we report the effect of voluntary wheel running during wakefulness on neuronal activity in the motor and somatosensory cortex in mice. We find that stereotypic wheel running is associated with a substantial reduction in firing rates among a large subpopulation of cortical neurons, especially at high speeds. Wheel running also has longer-term effects on spiking activity across periods of wakefulness. Specifically, cortical firing rates are significantly higher towards the end of a spontaneous prolonged waking period. However, this increase is abolished when wakefulness is dominated by running wheel activity. These findings indicate that wake-related changes in firing rates are determined not only by wake duration, but also by specific waking behaviours.

Sleep need is thought to accumulate gradually over waking periods and is associated with changes in neuronal activity. Here the authors show that in mice cortical firing rates increase between the beginning and end of wakefulness periods but this increase is not seen in waking periods with voluntary stereotypic wheel running.

Slow Bursting Neurons of Mouse Cortical Layer 6b Are Depolarized by Hypocretin/Orexin and Major Transmitters of Arousal

Neurons firing spontaneously in bursts in the absence of synaptic transmission have been previously recorded in different layers of cortical brain slices. It has been suggested that such neurons could contribute to the generation of alternating UP and DOWN states, a pattern of activity seen during slow-wave sleep. Here, we show that in layer 6b (L6b), known from our previous studies to contain neurons highly responsive to the wake-promoting transmitter hypocretin/orexin (hcrt/orx), there is a set of neurons, endowed with distinct intrinsic properties, which displayed a strong propensity to fire spontaneously in rhythmic bursts. In response to small depolarizing steps, they responded with a delayed firing of action potentials which, upon higher depolarizing steps, invariably inactivated and were followed by a depolarized plateau potential and a depolarizing afterpotential. These cells also displayed a strong hyperpolarization-activated rectification compatible with the presence of an I_h current. Most L6b neurons with such properties were able to fire spontaneously in bursts. Their bursting activity was of intrinsic origin as it persisted not only in presence of blockers of ionotropic glutamatergic and GABAergic receptors but also in a condition of complete synaptic blockade. However, a small number of these neurons displayed a mix of intrinsic bursting and synaptically driven recurrent UP and DOWN states. Most of the bursting L6b neurons were depolarized and excited by hcrt/orx through a direct postsynaptic mechanism that led to tonic firing and eventually inactivation. Similarly, they were directly excited by noradrenaline, histamine, dopamine, and neurotensin. Finally, the intracellular injection of these cells with dye and their subsequent Neurolucida reconstruction indicated that they were spiny non-pyramidal neurons. These results lead us to suggest that the propensity for slow rhythmic bursting of this set of L6b neurons could be directly impeded by hcrt/orx and other wake-promoting transmitters.