Neocortical networks entrain neuronal circuits in cerebellar cortex

The cerebellum converts input data into a hyper low-resolution granule cell code with spatial dimensions: a hypothesis

We present a theory of the inner layer of the cerebellar cortex, the granular layer, where the main excitatory input to the cerebellum is received. We ask how input signals are converted into an internal code and what form that has. While there is a computational element, and the ideas are quantified with a computer simulation, the approach is primarily evidence-led and aimed at experimenters rather than the computational community. Network models are often simplified to provide a noiseless medium for sophisticated computations. We propose, with evidence, the reverse: physiology is highly adapted to provide a noiseless medium for straightforward computations. We find that input data are converted to a hyper low-resolution internal code. Information is coded in the joint activity of large cell groups and therefore has minimum spatial dimensions-the dimensions of a code group. The conversion exploits statistical effects of random sampling. Code group dimensions are an effect of topography, cell morphologies and granular layer architecture. The activity of a code group is the smallest unit of information but not the smallest unit of code-the same information is coded in any random sample of signals. Code in this form is unexpectedly wasteful-there is a huge sacrifice of resolution-but may be a solution to fundamental problems involved in the biological representation of information.

The cerebellum monitors errors and entrains executive networks

Frontal midline θ (Fmθ) activity occurs in medial prefrontal cortices (mPFC), when expected and actual outcomes conflict. Cerebellar forward models could inform the mPFC about this mismatch. To verify this hypothesis we correlated the mPFC activation during a visuomotor tracking task (VM) with performance accuracy, in control and cerebellum-lesioned participants. Additionally, purely visual (V), motor (M) and a motor plus visual tasks (V + M) were performed. An Independent Component, with a mid-frontal topography scalp map and equivalent dipole location in the dorsal anterior cingulate cortex accounted for Fmθ. In control participants Fmθ power increased during VM, when the error level crossed a threshold, but not during V + M, M and V. This increase scaled with tracking error. Fmθ power failed to increase during VM in cerebellar participants, even at highest tracking errors. Thus, in control participants, activation of mPFC is induced when a continuous monitoring effort for online error detection is required. The presence of a threshold error for enhancing Fmθ, suggests the switch from an automatic to an executive tracking control, which recruits the mPFC. Given that the cerebellum stores forward models, the absence of Fmθ increases during tracking errors in cerebellar participants indicates that cerebellum is necessary for supplying the mPFC with prediction error-related information. This occurs when automatic control falters, and a deliberate correction mechanism needs to be triggered. Further studies are needed to verify if this alerting function also occurs in the context of the other cognitive and non-cognitive functions in which the cerebellum is involved.

Neocortical and cerebellar malformations affect flurothyl-induced seizures in female C57BL/6J mice

Brain malformations cause cognitive disability and seizures in both human and animal models. Highly laminated structures such as the neocortex and cerebellum are vulnerable to malformation, affecting lamination and neuronal connectivity as well as causing heterotopia. The objective of the present study was to determine if sporadic neocortical and/or cerebellar malformations in C57BL/6J mice are correlated with reduced seizure threshold. The inhaled chemi-convulsant flurothyl was used to induce generalized, tonic-clonic seizures in male and female C57BL/6J mice, and the time to seizure onset was recorded as a functional correlate of brain excitability changes. Following seizures, mice were euthanized, and brains were extracted for histology. Cryosections of the neocortex and cerebellar vermis were stained and examined for the presence of molecular layer heterotopia as previously described in C57BL/6J mice. Over 60% of mice had neocortical and/or cerebellar heterotopia. No sex differences were observed in the prevalence of malformations. Significantly reduced seizure onset time was observed dependent on sex and the type of malformation present. These results raise important questions regarding the presence of malformations in C57BL/6J mice used in the study of brain development, epilepsy, and many other diseases of the nervous system.

A multi-layer mean-field model of the cerebellum embedding microstructure and population-specific dynamics

Mean-field (MF) models are computational formalism used to summarize in a few statistical parameters the salient biophysical properties of an inter-wired neuronal network. Their formalism normally incorporates different types of neurons and synapses along with their topological organization. MFs are crucial to efficiently implement the computational modules of large-scale models of brain function, maintaining the specificity of local cortical microcircuits. While MFs have been generated for the isocortex, they are still missing for other parts of the brain. Here we have designed and simulated a multi-layer MF of the cerebellar microcircuit (including Granule Cells, Golgi Cells, Molecular Layer Interneurons, and Purkinje Cells) and validated it against experimental data and the corresponding spiking neural network (SNN) microcircuit model. The cerebellar MF was built using a system of equations, where properties of neuronal populations and topological parameters are embedded in inter-dependent transfer functions. The model time constant was optimised using local field potentials recorded experimentally from acute mouse cerebellar slices as a template. The MF reproduced the average dynamics of different neuronal populations in response to various input patterns and predicted the modulation of the Purkinje Cells firing depending on cortical plasticity, which drives learning in associative tasks, and the level of feedforward inhibition. The cerebellar MF provides a computationally efficient tool for future investigations of the causal relationship between microscopic neuronal properties and ensemble brain activity in virtual brain models addressing both physiological and pathological conditions.

Effects of continuous positive airway pressure treatment on sleep architecture in adults with obstructive sleep apnea and type 2 diabetes

Obstructive sleep apnea (OSA) severely impacts sleep and has long-term health consequences. Treating sleep apnea with continuous positive airway pressure (CPAP) not only relieves obstructed breathing, but also improves sleep. CPAP improves sleep by reducing apnea-induced awakenings. CPAP may also improve sleep by enhancing features of sleep architecture assessed with electroencephalography (EEG) that maximize sleep depth and neuronal homeostasis, such as the slow oscillation and spindle EEG activity, and by reducing neurophysiological arousal during sleep (i.e., beta EEG activity). We examined cross-sectional differences in quantitative EEG characteristics of sleep, assessed with power spectral analysis, in 29 adults with type 2 diabetes treated with CPAP and 24 adults undergoing SHAM CPAP treatment (total n = 53). We then examined changes in spectral characteristics of sleep as the SHAM group crossed over to active CPAP treatment (n = 19). Polysomnography (PSG) from the CPAP titration night was used for the current analyses. Analyses focused on EEG frequencies associated with sleep maintenance and arousal. These included the slow oscillation (0.5–1 Hz), sigma activity (12–16 Hz, spindle activity), and beta activity (16–20 Hz) in F3, F4, C3, and C4 EEG channels. Whole night non-rapid eye movement (NREM) sleep and the first period of NREM spectral activity were examined. Age and sex were included as covariates. There were no group differences between CPAP and SHAM in spectral characteristics of sleep architecture. However, SHAM cross-over to active CPAP was associated with an increase in relative 12–16 Hz sigma activity across the whole night and a decrease in average beta activity across the whole night. Relative slow oscillation power within the first NREM period decreased with CPAP, particularly for frontal channels. Sigma and beta activity effects did not differ by channel. These findings suggest that CPAP may preferentially enhance spindle activity and mitigate neurophysiological arousal. These findings inform the neurophysiological mechanisms of improved sleep with CPAP and the utility of quantitative EEG measures of sleep as a treatment probe of improvements in neurological and physical health with CPAP.

Mice Lacking Cerebellar Cortex and Related Structures Show a Decrease in Slow-Wave Activity With Normal Non-REM Sleep Amount and Sleep Homeostasis

In addition to the well-known motor control, the cerebellum has recently been implicated in memory, cognition, addiction, and social behavior. Given that the cerebellum contains more neurons than the cerebral cortex and has tight connections to the thalamus and brainstem nuclei, it is possible that the cerebellum also regulates sleep/wakefulness. However, the role of the cerebellum in sleep was unclear, since cerebellar lesion studies inevitably involved massive inflammation in the adjacent brainstem, and sleep changes in lesion studies were not consistent with each other. Here, we examine the role of the cerebellum in sleep and wakefulness using mesencephalon- and rhombomere 1-specific Ptf1a conditional knockout (Ptf1a cKO) mice, which lack the cerebellar cortex and its related structures, and exhibit ataxic gait. Ptf1a cKO mice had similar wake and non-rapid eye movement sleep (NREMS) time as control mice and showed reduced slow wave activity during wakefulness, NREMS and REMS. Ptf1a cKO mice showed a decrease in REMS time during the light phase and had increased NREMS delta power in response to 6 h of sleep deprivation, as did control mice. Ptf1a cKO mice also had similar numbers of sleep spindles and fear memories as control mice. Thus, the cerebellum does not appear to play a major role in sleep-wake control, but may be involved in the generation of slow waves.

Cerebellar Coordination of Neuronal Communication in Cerebral Cortex

Cognitive processes involve precisely coordinated neuronal communications between multiple cerebral cortical structures in a task specific manner. Rich new evidence now implicates the cerebellum in cognitive functions. There is general agreement that cerebellar cognitive function involves interactions between the cerebellum and cerebral cortical association areas. Traditional views assume reciprocal interactions between one cerebellar and one cerebral cortical site, via closed-loop connections. We offer evidence supporting a new perspective that assigns the cerebellum the role of a coordinator of communication. We propose that the cerebellum participates in cognitive function by modulating the coherence of neuronal oscillations to optimize communications between multiple cortical structures in a task specific manner.

Cortical and subcortical hemodynamic changes during sleep slow waves in human light sleep

EEG slow waves, the hallmarks of NREM sleep are thought to be crucial for the regulation of several important processes, including learning, sensory disconnection and the removal of brain metabolic wastes. Animal research indicates that slow waves may involve complex interactions within and between cortical and subcortical structures. Conventional EEG in humans, however, has a low spatial resolution and is unable to accurately describe changes in the activity of subcortical and deep cortical structures. To overcome these limitations, here we took advantage of simultaneous EEG-fMRI recordings to map cortical and subcortical hemodynamic (BOLD) fluctuations time-locked to slow waves of light sleep. Recordings were performed in twenty healthy adults during an afternoon nap. Slow waves were associated with BOLD-signal increases in the posterior brainstem and in portions of thalamus and cerebellum characterized by preferential functional connectivity with limbic and somatomotor areas, respectively. At the cortical level, significant BOLD-signal decreases were instead found in several areas, including insula and somatomotor cortex. Specifically, a slow signal increase preceded slow-wave onset and was followed by a delayed, stronger signal decrease. Similar hemodynamic changes were found to occur at different delays across most cortical brain areas, mirroring the propagation of electrophysiological slow waves, from centro-frontal to inferior temporo-occipital cortices. Finally, we found that the amplitude of electrophysiological slow waves was positively related to the magnitude and inversely related to the delay of cortical and subcortical BOLD-signal changes. These regional patterns of brain activity are consistent with theoretical accounts of the functions of sleep slow waves.

Medium spiny neurons activity reveals the discrete segregation of mouse dorsal striatum

Behavioral studies differentiate the rodent dorsal striatum (DS) into lateral and medial regions; however, anatomical evidence suggests that it is a unified structure. To understand striatal dynamics and basal ganglia functions, it is essential to clarify the circuitry that supports this behavioral-based segregation. Here, we show that the mouse DS is made of two non-overlapping functional circuits divided by a boundary. Combining in vivo optopatch-clamp and extracellular recordings of spontaneous and evoked sensory activity, we demonstrate different coupling of lateral and medial striatum to the cortex together with an independent integration of the spontaneous activity, due to particular corticostriatal connectivity and local attributes of each region. Additionally, we show differences in slow and fast oscillations and in the electrophysiological properties between striatonigral and striatopallidal neurons. In summary, these results demonstrate that the rodent DS is segregated in two neuronal circuits, in homology with the caudate and putamen nuclei of primates.

Stellate cell computational modeling predicts signal filtering in the molecular layer circuit of cerebellum

The functional properties of cerebellar stellate cells and the way they regulate molecular layer activity are still unclear. We have measured stellate cells electroresponsiveness and their activation by parallel fiber bursts. Stellate cells showed intrinsic pacemaking, along with characteristic responses to depolarization and hyperpolarization, and showed a marked short-term facilitation during repetitive parallel fiber transmission. Spikes were emitted after a lag and only at high frequency, making stellate cells to operate as delay-high-pass filters. A detailed computational model summarizing these physiological properties allowed to explore different functional configurations of the parallel fiber-stellate cell-Purkinje cell circuit. Simulations showed that, following parallel fiber stimulation, Purkinje cells almost linearly increased their response with input frequency, but such an increase was inhibited by stellate cells, which leveled the Purkinje cell gain curve to its 4 Hz value. When reciprocal inhibitory connections between stellate cells were activated, the control of stellate cells over Purkinje cell discharge was maintained only at very high frequencies. These simulations thus predict a new role for stellate cells, which could endow the molecular layer with low-pass and band-pass filtering properties regulating Purkinje cell gain and, along with this, also burst delay and the burst-pause responses pattern.

Unravelling the enigma of cortical tremor and other forms of cortical myoclonus

Cortical tremor is a fine rhythmic oscillation involving distal upper limbs, linked to increased sensorimotor cortex excitability, as seen in cortical myoclonus. Cortical tremor is the hallmark feature of autosomal dominant familial cortical myoclonic tremor and epilepsy (FCMTE), a syndrome not yet officially recognized and characterized by clinical and genetic heterogeneity. Non-coding repeat expansions in different genes have been recently recognized to play an essential role in its pathogenesis. Cortical tremor is considered a rhythmic variant of cortical myoclonus and is part of the 'spectrum of cortical myoclonus', i.e. a wide range of clinical motor phenomena, from reflex myoclonus to myoclonic epilepsy, caused by abnormal sensorimotor cortical discharges. The aim of this update is to provide a detailed analysis of the mechanisms defining cortical tremor, as seen in FCMTE. After reviewing the clinical and genetic features of FCMTE, we discuss the possible mechanisms generating the distinct elements of the cortical myoclonus spectrum, and how cortical tremor fits into it. We propose that the spectrum is due to the evolution from a spatially limited focus of excitability to recruitment of more complex mechanisms capable of sustaining repetitive activity, overcoming inhibitory mechanisms that restrict excitatory bursts, and engaging wide areas of cortex. Finally, we provide evidence for a possible common denominator of the elements of the spectrum, i.e. the cerebellum, and discuss its role in FCMTE, according to recent genetic findings.

Cerebellar Cortex 4-12 Hz Oscillations and Unit Phase Relation in the Awake Rat

Oscillations in the granule cell layer (GCL) of the cerebellar cortex have been related to behavior and could facilitate communication with the cerebral cortex. These local field potential (LFP) oscillations, strong at 4–12 Hz in the rodent cerebellar cortex during awake immobility, should also be an indicator of an underlying influence on the patterns of the cerebellar cortex neuronal firing during rest. To address this hypothesis, cerebellar cortex LFPs and simultaneous single-neuron activity were collected during LFP oscillatory periods in the GCL of awake resting rats. During these oscillatory episodes, different types of units across the GCL and Purkinje cell layers showed variable phase-relation with the oscillatory cycles. Overall, 74% of the Golgi cell firing and 54% of the Purkinje cell simple spike (SS) firing were phase-locked with the oscillations, displaying a clear phase relationship. Despite this tendency, fewer Golgi cells (50%) and Purkinje cell’s SSs (25%) showed an oscillatory firing pattern. Oscillatory phase-locked spikes for the Golgi and Purkinje cells occurred towards the peak of the LFP cycle. GCL LFP oscillations had a strong capacity to predict the timing of Golgi cell spiking activity, indicating a strong influence of this oscillatory phenomenon over the GCL. Phase-locking was not as prominent for the Purkinje cell SS firing, indicating a weaker influence over the Purkinje cell layer, yet a similar phase relation. Overall, synaptic activity underlying GCL LFP oscillations likely exert an influence on neuronal population firing patterns in the cerebellar cortex in the awake resting state and could have a preparatory neural network shaping capacity serving as a neural baseline for upcoming cerebellar operations.

Firing rate-dependent phase responses of Purkinje cells support transient oscillations

Both spike rate and timing can transmit information in the brain. Phase response curves (PRCs) quantify how a neuron transforms input to output by spike timing. PRCs exhibit strong firing-rate adaptation, but its mechanism and relevance for network output are poorly understood. Using our Purkinje cell (PC) model, we demonstrate that the rate adaptation is caused by rate-dependent subthreshold membrane potentials efficiently regulating the activation of Na+ channels. Then, we use a realistic PC network model to examine how rate-dependent responses synchronize spikes in the scenario of reciprocal inhibition-caused high-frequency oscillations. The changes in PRC cause oscillations and spike correlations only at high firing rates. The causal role of the PRC is confirmed using a simpler coupled oscillator network model. This mechanism enables transient oscillations between fast-spiking neurons that thereby form PC assemblies. Our work demonstrates that rate adaptation of PRCs can spatio-temporally organize the PC input to cerebellar nuclei.

Cerebellar Lobulus Simplex and Crus I Differentially Represent Phase and Phase Difference of Prefrontal Cortical and Hippocampal Oscillations

The cerebellum has long been implicated in tasks involving precise temporal control, especially in the coordination of movements. Here we asked whether the cerebellum represents temporal aspects of oscillatory neuronal activity, measured as instantaneous phase and difference between instantaneous phases of oscillations in two cerebral cortical areas involved in cognitive function. We simultaneously recorded Purkinje cell (PC) single-unit spike activity in cerebellar lobulus simplex (LS) and Crus I and local field potential (LFP) activity in the medial prefrontal cortex (mPFC) and dorsal hippocampus CA1 region (dCA1). Purkinje cells in cerebellar LS and Crus I differentially represented specific phases and phase differences of mPFC and dCA1 LFP oscillations in a frequency-specific manner, suggesting a site- and frequency-specific cerebellar representation of temporal aspects of neuronal oscillations in non-motor cerebral cortical areas. These findings suggest that cerebellar interactions with cerebral cortical areas involved in cognitive functions might involve temporal coordination of neuronal oscillations.

The cerebellum has long been implicated in tasks involving precise temporal control, especially in the coordination of movements. McAfee et al. show that the cerebellar principal neurons, Purkinje cells, represent precise temporal information about the phase and phase differences of neuronal oscillations occurring in two non-motor-related cerebral cortical structures.

Multiple signals evoked by unisensory stimulation converge onto cerebellar granule and Purkinje cells in mice

The cerebellum receives signals directly from peripheral sensory systems and indirectly from the neocortex. Even a single tactile stimulus can activate both of these pathways. Here we report how these different types of signals are integrated in the cerebellar cortex. We used in vivo whole-cell recordings from granule cells and unit recordings from Purkinje cells in mice in which primary somatosensory cortex (S1) could be optogenetically inhibited. Tactile stimulation of the upper lip produced two-phase granule cell responses (with latencies of ~8 ms and 29 ms), for which only the late phase was S1 dependent. In Purkinje cells, complex spikes and the late phase of simple spikes were S1 dependent. These results indicate that individual granule cells combine convergent inputs from the periphery and neocortex and send their outputs to Purkinje cells, which then integrate those signals with climbing fiber signals from the neocortex.

Optimization of Efficient Neuron Models With Realistic Firing Dynamics. The Case of the Cerebellar Granule Cell

Biologically relevant large-scale computational models currently represent one of the main methods in neuroscience for studying information processing primitives of brain areas. However, biologically realistic neuron models tend to be computationally heavy and thus prevent these models from being part of brain-area models including thousands or even millions of neurons. The cerebellar input layer represents a canonical example of large scale networks. In particular, the cerebellar granule cells, the most numerous cells in the whole mammalian brain, have been proposed as playing a pivotal role in the creation of somato-sensorial information representations. Enhanced burst frequency (spiking resonance) in the granule cells has been proposed as facilitating the input signal transmission at the theta-frequency band (4–12 Hz), but the functional role of this cell feature in the operation of the granular layer remains largely unclear. This study aims to develop a methodological pipeline for creating neuron models that maintain biological realism and computational efficiency whilst capturing essential aspects of single-neuron processing. Therefore, we selected a light computational neuron model template (the adaptive-exponential integrate-and-fire model), whose parameters were progressively refined using an automatic parameter tuning with evolutionary algorithms (EAs). The resulting point-neuron models are suitable for reproducing the main firing properties of a realistic granule cell from electrophysiological measurements, including the spiking resonance at the theta-frequency band, repetitive firing according to a specified intensity-frequency (I-F) curve and delayed firing under current-pulse stimulation. Interestingly, the proposed model also reproduced some other emergent properties (namely, silent at rest, rheobase and negligible adaptation under depolarizing currents) even though these properties were not set in the EA as a target in the fitness function (FF), proving that these features are compatible even in computationally simple models. The proposed methodology represents a valuable tool for adjusting AdEx models according to a FF defined in the spiking regime and based on biological data. These models are appropriate for future research of the functional implication of bursting resonance at the theta band in large-scale granular layer network models.

Perspective on the Multiple Pathways to Changing Brain States

In this review article, we highlight several disparate ideas that are linked to changes in brain state (i.e., sleep to arousal, Down to Up, synchronized to de-synchronized). In any discussion of the brain state, we propose that the cortical pyramidal neuron has a central position. EEG recordings, which typically assess brain state, predominantly reflect the activity of cortical pyramidal neurons. This means that the dominant rhythmic activity that characterizes a particular brain state ultimately has to manifest globally across the pyramidal neuron population. During state transitions, it is the long-range connectivity of these neurons that broadcast the resultant changes in activity to many subcortical targets. Structures like the thalamus, brainstem/hypothalamic neuromodulatory systems, and respiratory systems can also strongly influence brain state, and for many decades we have been uncovering bidirectional pathways that link these structures to state changes in the cerebral cortex. More recently, movement and active behaviors have emerged as powerful drivers of state changes. Each of these systems involve different circuits distributed across the brain. Yet, for a system-wide change in brain state, there must be a collaboration between these circuits that reflects and perhaps triggers the transition between brain states. As we expand our understanding of how brain state changes, our current challenge is to understand how these diverse sets of circuits and pathways interact to produce the changes observed in cortical pyramidal neurons.

Resistance, vulnerability and resilience: A review of the cognitive cerebellum in aging and neurodegenerative diseases

In the context of neurodegeneration and aging, the cerebellum is an enigma. Genetic markers of cellular aging in cerebellum accumulate more slowly than in the rest of the brain, and it generates unknown factors that may slow or even reverse neurodegenerative pathology in animal models of Alzheimer's Disease (AD). Cerebellum shows increased activity in early AD and Parkinson's disease (PD), suggesting a compensatory function that may mitigate early symptoms of neurodegenerative pathophysiology. Perhaps most notably, different parts of the brain accumulate neuropathological markers of AD in a recognized progression and generally, cerebellum is the last brain region to do so. Taken together, these data suggest that cerebellum may be resistant to certain neurodegenerative mechanisms. On the other hand, in some contexts of accelerated neurodegeneration, such as that seen in chronic traumatic encephalopathy (CTE) following repeated traumatic brain injury (TBI), the cerebellum appears to be one of the most susceptible brain regions to injury and one of the first to exhibit signs of pathology. Cerebellar pathology in neurodegenerative disorders is strongly associated with cognitive dysfunction. In neurodegenerative or neurological disorders associated with cerebellar pathology, such as spinocerebellar ataxia, cerebellar cortical atrophy, and essential tremor, rates of cognitive dysfunction, dementia and neuropsychiatric symptoms increase. When the cerebellum shows AD pathology, such as in familial AD, it is associated with earlier onset and greater severity of disease. These data suggest that when neurodegenerative processes are active in the cerebellum, it may contribute to pathological behavioral outcomes. The cerebellum is well known for comparing internal representations of information with observed outcomes and providing real-time feedback to cortical regions, a critical function that is disturbed in neuropsychiatric disorders such as intellectual disability, schizophrenia, dementia, and autism, and required for cognitive domains such as working memory. While cerebellum has reciprocal connections with non-motor brain regions and likely plays a role in complex, goal-directed behaviors, it has proven difficult to establish what it does mechanistically to modulate these behaviors. Due to this lack of understanding, it's not surprising to see the cerebellum reflexively dismissed or even ignored in basic and translational neuropsychiatric literature. The overarching goals of this review are to answer the following questions from primary literature: When the cerebellum is affected by pathology, is it associated with decreased cognitive function? When it is intact, does it play a compensatory or protective role in maintaining cognitive function? Are there theoretical frameworks for understanding the role of cerebellum in cognition, and perhaps, illnesses characterized by cognitive dysfunction? Understanding the role of the cognitive cerebellum in neurodegenerative diseases has the potential to offer insight into origins of cognitive deficits in other neuropsychiatric disorders, which are often underappreciated, poorly understood, and not often treated.

Region-specific adenosinergic modulation of the slow-cortical rhythm in urethane-anesthetized rats

Slow cortical rhythm (SCR) is a rhythmic alternation of UP and DOWN states during sleep and anesthesia. SCR-associated slow waves reflect homeostatic sleep functions. Adenosine accumulating during prolonged wakefulness and sleep deprivation (SD) may play a role in the delta power increment during recovery sleep. NREM sleep is a local, use-dependent process of the brain. In the present study, direct effect of adenosine on UP and DOWN states was tested by topical application to frontal, somatosensory and visual cortices, respectively, in urethane-anesthetized rats. Local field potentials (LFPs) were recorded using an electrode array inserted close to the location of adenosine application. Multiple unit activity (MUA) was measured from layer V-VI in close proximity of the recording array. In the frontal and somatosensory cortex, adenosine modulated SCR with slow kinetics on the LFP level while MUA remained mostly unaffected. In the visual cortex, adenosine modulated SCR with fast kinetics. In each region, delta power increment was based on the increased frequency of state transitions as well as increased height of UP-state associated slow waves. These results show that adenosine may directly modulate SCR in a complex and region-specific manner which may be related to the finding that restorative processes may take place with varying duration and intensity during recovery sleep in different cortical regions. Adenosine may play a direct role in the increment of the slow wave power observed during local sleep, furthermore it may shape the region-specific characteristics of the phenomenon.

State-Dependent Entrainment of Prefrontal Cortex Local Field Potential Activity Following Patterned Stimulation of the Cerebellar Vermis

The cerebellum is involved in sensorimotor, cognitive, and emotional functions through cerebello-cerebral connectivity. Cerebellar neurostimulation thus likely affects cortical circuits, as has been shown in studies using cerebellar stimulation to treat neurological disorders through modulation of frontal EEG oscillations. Here we studied the effects of different frequencies of cerebellar stimulation on oscillations and coherence in the cerebellum and prefrontal cortex in the urethane-anesthetized rat. Local field potentials were recorded in the right lateral cerebellum (Crus I/II) and bilaterally in the prefrontal cortex (frontal association area, FrA) in adult male Sprague-Dawley rats. Stimulation was delivered to the cerebellar vermis (lobule VII) using single pulses (0.2 Hz for 60 s), or repeated pulses at 1 Hz (30 s), 5 Hz (10 s), 25 Hz (2 s), and 50 Hz (1 s). Effects of stimulation were influenced by the initial state of EEG activity which varies over time during urethane-anesthesia; 1 Hz stimulation was more effective when delivered during the slow-wave state (Stage 1), while stimulation with single-pulse, 25, and 50 Hz showed stronger effects during the activated state (Stage 2). Single-pulses resulted in increases in oscillatory power in the delta and theta bands for the cerebellum, and in frequencies up to 80 Hz in cortical sites. 1 Hz stimulation induced a decrease in 0–30 Hz activity and increased activity in the 30–200 Hz range, in the right FrA. 5 Hz stimulation reduced power in high frequencies in Stage 1 and induced mixed effects during Stage 2.25 Hz stimulation increased cortical power at low frequencies during Stage 2, and increased power in higher frequency bands during Stage 1. Stimulation at 50 Hz increased delta-band power in all recording sites, with the strongest and most rapid effects in the cerebellum. 25 and 50 Hz stimulation also induced state-dependent effects on cerebello-cortical and cortico-cortical coherence at high frequencies. Cerebellar stimulation can therefore entrain field potential activity in the FrA and drive synchronization of cerebello-cortical and cortico-cortical networks in a frequency-dependent manner. These effects highlight the role of the cerebellar vermis in modulating large-scale synchronization of neural networks in non-motor frontal cortex.

LFP clustering in cortex reveals a taxonomy of Up states and near-millisecond, ordered phase-locking in cortical neurons

During slow-wave sleep and anesthesia, mammalian cortex exhibits a synchronized state during which neurons shift from a largely nonfiring to a firing state, known as an Up-state transition. Up-state transitions may constitute the default activity pattern of the entire cortex (Neske GT. Front Neural Circuits 9: 88, 2016) and could be critical to understanding cortical function, yet the genesis of such transitions and their interaction with single neurons is not well understood. It was recently shown that neurons firing at rates >2 Hz fire spikes in a stereotyped order during Up-state transitions (Luczak A, McNaughton BL, Harris KD. Nat Rev Neurosci 16: 745-755, 2015), yet it is still unknown if Up states are homogeneous and whether spiking order is present in neurons with rates <2 Hz (the majority). Using extracellular recordings from anesthetized cats and mice and from naturally sleeping rats, we show for the first time that Up-state transitions can be classified into several types based on the shape of the local field potential (LFP) during each transition. Individual LFP events could be localized in time to within 1-4 ms, more than an order of magnitude less than in previous studies. The majority of recorded neurons synchronized their firing to within ±5-15 ms relative to each Up-state transition. Simultaneous electrophysiology and wide-field imaging in mouse confirmed that LFP event clusters are cortex-wide phenomena. Our findings show that Up states are of different types and point to the potential importance of temporal order and millisecond-scale signaling by cortical neurons.NEW & NOTEWORTHY During cortical Up-state transitions in sleep and anesthesia, neurons undergo brief periods of increased firing in an order similar to that occurring in awake states. We show that these transitions can be classified into distinct types based on the shape of the local field potential. Transition times can be defined to <5 ms. Most neurons synchronize their firing to within ±5-15 ms of the transitions and fire in a consistent order.

Cerebellar D1DR-expressing neurons modulate the frontal cortex during timing tasks

Converging lines of evidence suggest that the cerebellum plays an integral role in cognitive function through its interactions with association cortices like the medial frontal cortex (MFC). It is unknown precisely how the cerebellum influences the frontal cortex and what type of information is reciprocally relayed between these two regions. A subset of neurons in the cerebellar dentate nuclei, or the homologous lateral cerebellar nuclei (LCN) in rodents, express D1 dopamine receptors (D1DRs) and may play a role in cognitive processes. We investigated how pharmacologically blocking LCN D1DRs influences performance in an interval timing task and impacts neuronal activity in the frontal cortex. Interval timing requires executive processes such as working memory, attention, and planning and is known to rely on both the frontal cortex and cerebellum. In our interval timing task, male rats indicated their estimates of the passage of a period of several seconds by making lever presses for a water reward. We have shown that a cue-evoked burst of low-frequency activity in the MFC initiates ramping activity (i.e., monotonic increases or decreases of firing rate over time) in single MFC neurons. These patterns of activity are associated with successful interval timing performance. Here we explored how blocking right LCN D1DRs with the D1DR antagonist SCH23390 influences timing performance and neural activity in the contralateral (left) MFC. Our results indicate that blocking LCN D1DRs impaired some measures of interval timing performance. Additionally, ramping activity of MFC single units was significantly attenuated. These data provide insight into how catecholamines in the LCN may drive MFC neuronal dynamics to influence cognitive function.

Quasiperiodic rhythms of the inferior olive

Inferior olivary activity causes both short-term and long-term changes in cerebellar output underlying motor performance and motor learning. Many of its neurons engage in coherent subthreshold oscillations and are extensively coupled via gap junctions. Studies in reduced preparations suggest that these properties promote rhythmic, synchronized output. However, the interaction of these properties with torrential synaptic inputs in awake behaving animals is not well understood. Here we combine electrophysiological recordings in awake mice with a realistic tissue-scale computational model of the inferior olive to study the relative impact of intrinsic and extrinsic mechanisms governing its activity. Our data and model suggest that if subthreshold oscillations are present in the awake state, the period of these oscillations will be transient and variable. Accordingly, by using different temporal patterns of sensory stimulation, we found that complex spike rhythmicity was readily evoked but limited to short intervals of no more than a few hundred milliseconds and that the periodicity of this rhythmic activity was not fixed but dynamically related to the synaptic input to the inferior olive as well as to motor output. In contrast, in the long-term, the average olivary spiking activity was not affected by the strength and duration of the sensory stimulation, while the level of gap junctional coupling determined the stiffness of the rhythmic activity in the olivary network during its dynamic response to sensory modulation. Thus, interactions between intrinsic properties and extrinsic inputs can explain the variations of spiking activity of olivary neurons, providing a temporal framework for the creation of both the short-term and long-term changes in cerebellar output.

Activity of the inferior olive, transmitted via climbing fibers to the cerebellum, regulates initiation and amplitude of movements, signals unexpected sensory feedback, and directs cerebellar learning. It is characterized by widespread subthreshold oscillations and synchronization promoted by strong electrotonic coupling. In brain slices, subthreshold oscillations gate which inputs can be transmitted by inferior olivary neurons and which will not—dependent on the phase of the oscillation. We tested whether the subthreshold oscillations had a measurable impact on temporal patterning of climbing fiber activity in intact, awake mice. We did so by recording neural activity of the postsynaptic Purkinje cells, in which complex spike firing faithfully represents climbing fiber activity. For short intervals (<300 ms) many Purkinje cells showed spontaneously rhythmic complex spike activity. However, our experiments designed to evoke conditional responses indicated that complex spikes are not predominantly predicated on stimulus history. Our realistic network model of the inferior olive explains the experimental observations via continuous phase modulations of the subthreshold oscillations under the influence of synaptic fluctuations. We conclude that complex spike activity emerges from a quasiperiodic rhythm that is stabilized by electrotonic coupling between its dendrites, yet dynamically influenced by the status of their synaptic inputs.

Ephaptic Coupling Promotes Synchronous Firing of Cerebellar Purkinje Cells

Correlated neuronal activity at various timescales plays an important role in information transfer and processing. We find that in awake-behaving mice, an unexpectedly large fraction of neighboring Purkinje cells (PCs) exhibit sub-millisecond synchrony. Correlated firing usually arises from chemical or electrical synapses, but, surprisingly, neither is required to generate PC synchrony. We therefore assessed ephaptic coupling, a mechanism in which neurons communicate via extracellular electrical signals. In the neocortex, ephaptic signals from many neurons summate to entrain spiking on slow timescales, but extracellular signals from individual cells are thought to be too small to synchronize firing. Here we find that a single PC generates sufficiently large extracellular potentials to open sodium channels in nearby PC axons. Rapid synchronization is made possible because ephaptic signals generated by PCs peak during the rising phase of action potentials. These findings show that ephaptic coupling contributes to the prevalent synchronization of nearby PCs.

Decoding Speech With Integrated Hybrid Signals Recorded From the Human Ventral Motor Cortex

Restoration of speech communication for locked-in patients by means of brain computer interfaces (BCIs) is currently an important area of active research. Among the neural signals obtained from intracranial recordings, single/multi-unit activity (SUA/MUA), local field potential (LFP), and electrocorticography (ECoG) are good candidates for an input signal for BCIs. However, the question of which signal or which combination of the three signal modalities is best suited for decoding speech production remains unverified. In order to record SUA, LFP, and ECoG simultaneously from a highly localized area of human ventral sensorimotor cortex (vSMC), we fabricated an electrode the size of which was 7 by 13 mm containing sparsely arranged microneedle and conventional macro contacts. We determined which signal modality is the most capable of decoding speech production, and tested if the combination of these signals could improve the decoding accuracy of spoken phonemes. Feature vectors were constructed from spike frequency obtained from SUAs and event-related spectral perturbation derived from ECoG and LFP signals, then input to the decoder. The results showed that the decoding accuracy for five spoken vowels was highest when features from multiple signals were combined and optimized for each subject, and reached 59% when averaged across all six subjects. This result suggests that multi-scale signals convey complementary information for speech articulation. The current study demonstrated that simultaneous recording of multi-scale neuronal activities could raise decoding accuracy even though the recording area is limited to a small portion of cortex, which is advantageous for future implementation of speech-assisting BCIs.

EEG Spectral Generators Involved in Motor Imagery: A swLORETA Study

In order to characterize the neural generators of the brain oscillations related to motor imagery (MI), we investigated the cortical, subcortical, and cerebellar localizations of their respective electroencephalogram (EEG) spectral power and phase locking modulations. The MI task consisted in throwing a ball with the dominant upper limb while in a standing posture, within an ecological virtual reality (VR) environment (tennis court). The MI was triggered by the visual cues common to the control condition, during which the participant remained mentally passive. As previously developed, our paradigm considers the confounding problem that the reference condition allows two complementary analyses: one which uses the baseline before the occurrence of the visual cues in the MI and control resting conditions respectively; and the other which compares the analog periods between the MI and the control resting-state conditions. We demonstrate that MI activates specific, complex brain networks for the power and phase modulations of the EEG oscillations. An early (225 ms) delta phase-locking related to MI was generated in the thalamus and cerebellum and was followed (480 ms) by phase-locking in theta and alpha oscillations, generated in specific cortical areas and the cerebellum. Phase-locking preceded the power modulations (mainly alpha-beta ERD), whose cortical generators were situated in the frontal BA45, BA11, BA10, central BA6, lateral BA13, and posterior cortex BA2. Cerebellar-thalamic involvement through phase-locking is discussed as an underlying mechanism for recruiting at later stages the cortical areas involved in a cognitive role during MI.

The Sleeping Cerebellum

We sleep almost one-third of our lives and sleep plays an important role in critical brain functions like memory formation and consolidation. The role of sleep in cerebellar processing, however, constitutes an enigma in the field of neuroscience; we know little about cerebellar sleep-physiology, cerebro-cerebellar interactions during sleep, or the contributions of sleep to cerebellum-dependent memory consolidation. Likewise, we do not understand why cerebellar malfunction can lead to changes in the sleep-wake cycle and sleep disorders. In this review, we evaluate how sleep and cerebellar processing may influence one another and highlight which scientific routes and technical approaches could be taken to uncover the mechanisms underlying these interactions.

"Cerebellar contribution to visuo-attentional alpha rhythm: insights from weightlessness"

Human brain adaptation in weightlessness follows the necessity to reshape the dynamic integration of the neural information acquired in the new environment. This basic aspect was here studied by the electroencephalogram (EEG) dynamics where oscillatory modulations were measured during a visuo-attentional state preceding a visuo-motor docking task. Astronauts in microgravity conducted the experiment in free-floating aboard the International Space Station, before the space flight and afterwards. We observed stronger power decrease (~ERD: event related desynchronization) of the ~10 Hz oscillation from the occipital-parietal (alpha ERD) to the central areas (mu ERD). Inverse source modelling of the stronger alpha ERD revealed a shift from the posterior cingulate cortex (BA31, from the default mode network) on Earth to the precentral cortex (BA4, primary motor cortex) in weightlessness. We also observed significant contribution of the vestibular network (BA40, BA32, and BA39) and cerebellum (lobule V, VI). We suggest that due to the high demands for the continuous readjustment of an appropriate body posture in free-floating, this visuo-attentional state required more contribution from the motor cortex. The cerebellum and the vestibular network involvement in weightlessness might support the correction signals processing necessary for postural stabilization, and the increased demand to integrate incongruent vestibular information.

The Contribution of the Cerebellum in the Hierarchial Development of the Self

What distinguishes human beings from other living organisms is that a human perceives himself as a "self". The self is developed hierarchially in a multi-layered process, which is based on the evolutionary maturation of the nervous system and patterns according to the rules and demands of the external world. Many researchers have attempted to explain the different aspects of the self, as well as the related neural substrates. In this paper, we first review the previously proposed ideas regarding the neurobiology of the self. We then suggest a new hypothesis regarding the hierarchial self, which proposes that the self is developed at three stages: subjective, objective, and reflective selves. In the second part, we attempt to answer the question "Why do we need a self?" We therefore explain that different parts of the self developed in an effort to identify stability in space, stability against constantly changing objects, and stability against changing cognitions. Finally, we discuss the role of the cerebellum as the neural substrate for the self.

Multiplexed coding by cerebellar Purkinje neurons

Purkinje cells (PC), the sole output neurons of the cerebellar cortex, encode sensorimotor information, but how they do it remains a matter of debate. Here we show that PCs use a multiplexed spike code. Synchrony/spike time and firing rate encode different information in behaving monkeys during saccadic eye motion tasks. Using the local field potential (LFP) as a probe of local network activity, we found that infrequent pause spikes, which initiated or terminated intermittent pauses in simple spike trains, provide a temporally reliable signal for eye motion onset, with strong phase-coupling to the β/γ band LFP. Concurrently, regularly firing, non-pause spikes were weakly correlated with the LFP, but were crucial to linear encoding of eye movement kinematics by firing rate. Therefore, PC spike trains can simultaneously convey information necessary to achieve precision in both timing and continuous control of motion.

DOI:http://dx.doi.org/10.7554/eLife.13810.001

The cerebellum is a part of the brain that uses information from the senses to coordinate movement. Cells called Purkinje neurons in the cerebellum produce the final ‘output’ of its cortex. Therefore, Purkinje neurons have to communicate precise information about different aspects of the movement, such as its speed and timing. This information is likely to be represented by patterns of electrical activity within Purkinje neurons, but these patterns are still not fully understood.

Hong et al. recorded and analyzed electrical ‘spikes’, the output activity of Purkinje neurons, while monkeys made rapid eye movements. The recordings showed that occasional pauses in the otherwise regularly firing spikes of Purkinje neurons signaled the start of the eye movements. The pauses were accompanied by a sharp change in the local field potential, another electrical signal that comes from many neurons in the neighborhood. In the same cells, the rate of regularly firing spikes increased and decreased with the direction and speed of eye movements, following a simple relationship and independently of the local field potential.

Purkinje neurons therefore appear to use both the timing and the rate of their spiking activity to represent movement. This resolves conflicting reports in the literature claiming that either rates of spiking or their timing code essential information about movements: both are important. This way of representing information by combining more than one source is known as multiplexed coding.

Next, experiments recording electrical activity from many cells in the cerebellum at the same time are needed to find out how multiple Purkinje neurons can pause their spiking activity at the same time. Future experiments should also uncover how pauses in spiking and firing rates change with learning.

DOI:http://dx.doi.org/10.7554/eLife.13810.002

In vivo differences in inputs and spiking between neurons in lobules VI/VII of neocerebellum and lobule X of archaeocerebellum

The cerebellum plays an important role in the coordination and refinement of movements and cognitive processes. Recently, it has been shown that the main output neuron of the cerebellar cortex, i.e., the Purkinje cell, can show a different firing behavior dependent on its intrinsic electrophysiological properties. Yet, to what extent a different nature of mossy fiber inputs can influence the firing behavior of cerebellar cortical neurons remains to be elucidated. Here, we compared the firing rate and regularity of mossy fibers and neurons in two different regions of cerebellar cortex. One region intimately connected with the cerebral cortex, i.e., lobules VI/VII of the neocerebellum, and another one strongly connected with the vestibular apparatus, i.e., lobule X of the archaeocerebellum. Given their connections, we hypothesized that activity in neurons in lobules VI/VII and lobule X may be expected to be more phasic and tonic, respectively. Using whole-cell and cell-attached recordings in vivo in anesthetized mice, we show that the mossy fiber inputs to these functionally distinct areas of the cerebellum differ in that the irregularity and bursty character of their firing is significantly greater in lobules VI/VII than in lobule X. Importantly, this difference in mossy fiber regularity is propagated through the granule cells at the input stage to the Purkinje cells and molecular layer interneurons, ultimately resulting in different regularity of simple spikes. These data show that the firing behavior of cerebellar cortical neurons does not only reflect particular intrinsic properties but also an interesting interplay with the innate activity at the input stage.

Abnormal UP/DOWN Membrane Potential Dynamics Coupled with the Neocortical Slow Oscillation in Dentate Granule Cells during the Latent Phase of Temporal Lobe Epilepsy

The dentate gyrus, a major entry point to the hippocampus, gates (or filters) incoming information from the cortex. During sleep or anesthesia, the slow-wave oscillation (SWO) orchestrates hippocampus-neocortex communication, which is important for memory formation. The dentate gate is altered in temporal lobe epilepsy (TLE) early during epileptogenesis, which favors the propagation of pathological activities. Yet, whether the gating of physiological SWO by dentate granule cells (DGCs) is altered in TLE has remained unexplored. We combined intracellular recordings of membrane potential (V m) of DGCs and local field potential recordings of the SWO in parietal cortex in anesthetized rats early during epileptogenesis [post-status epilepticus (SE) rats]. As expected, in control rats, the V m of DGCs weakly and rarely oscillated in the SWO frequency range. In contrast, in post-SE rats, the V m of DGCs displayed strong and long-lasting SWO. In these cells, clear UP and DOWN states, in phase with the neocortical SWO, led to a bimodal V m distribution. In post-SE rats, the firing of DGCs was increased and more temporally modulated by the neocortical SWO. We conclude that UP/DOWN state dynamics dominate the V m of DGCs and firing early during epileptogenesis. This abnormally strong neocortical influence on the dynamics of DGCs may profoundly modify the hippocampus-neocortex dialogue during sleep and associated cognitive functions.

Auditory Tones and Foot-Shock Recapitulate Spontaneous Sub-Threshold Activity in Basolateral Amygdala Principal Neurons and Interneurons

In quiescent states such as anesthesia and slow wave sleep, cortical networks show slow rhythmic synchronized activity. In sensory cortices this rhythmic activity shows a stereotypical pattern that is recapitulated by stimulation of the appropriate sensory modality. The amygdala receives sensory input from a variety of sources, and in anesthetized animals, neurons in the basolateral amygdala (BLA) show slow rhythmic synchronized activity. Extracellular field potential recordings show that these oscillations are synchronized with sensory cortex and the thalamus, with both the thalamus and cortex leading the BLA. Using whole-cell recording in vivo we show that the membrane potential of principal neurons spontaneously oscillates between up- and down-states. Footshock and auditory stimulation delivered during down-states evokes an up-state that fully recapitulates those occurring spontaneously. These results suggest that neurons in the BLA receive convergent input from networks of cortical neurons with slow oscillatory activity and that somatosensory and auditory stimulation can trigger activity in these same networks.

Impaired Serotonergic Brainstem Function during and after Seizures

Impaired breathing, cardiac function, and arousal during and after seizures are important causes of morbidity and mortality. Previous work suggests that these changes are associated with depressed brainstem function in the ictal and post-ictal periods. Lower brainstem serotonergic systems are postulated to play an important role in cardiorespiratory changes during and after seizures, whereas upper brainstem serotonergic and other systems regulate arousal. However, direct demonstration of seizure-associated neuronal activity changes in brainstem serotonergic regions has been lacking. Here, we performed multiunit and single-unit recordings from medullary raphe and midbrain dorsal raphe nuclei in an established rat seizure model while measuring changes in breathing rate and depth as well as heart rate. Serotonergic neurons were identified by immunohistochemistry. Respiratory rate, tidal volume, and minute ventilation were all significantly decreased during and after seizures in this model. We found that population firing of neurons in the medullary and midbrain raphe on multiunit recordings was significantly decreased during the ictal and post-ictal periods. Single-unit recordings from identified serotonergic neurons in the medullary raphe revealed highly consistently decreased firing during and after seizures. In contrast, firing of midbrain raphe serotonergic neurons was more variable, with a mixture of increases and decreases. The markedly suppressed firing of medullary serotonergic neurons supports their possible role in simultaneously impaired cardiorespiratory function in seizures. Decreased arousal likely arises from depressed population activity of several neuronal pools in the upper brainstem and forebrain. These findings have important implications for preventing morbidity and mortality in people living with epilepsy.

SIGNIFICANCE STATEMENT

Seizures often cause impaired breathing, cardiac dysfunction, and loss of consciousness. The brainstem and, specifically, brainstem serotonin neurons are thought to play an important role in controlling breathing, cardiac function, and arousal. We used an established rat seizure model to study the overall neuronal activity in the brainstem as well as firing of specific serotonin neurons while measuring cardiorespiratory function. Our results demonstrated overall decreases in brainstem neuronal activity and marked downregulation of lower brainstem serotonin neuronal firing in association with decreased breathing and heart rate during and after seizures. These findings point the way toward new treatments to augment brainstem function and serotonin, aiming to prevent seizure complications and reduce morbidity and mortality in people living with epilepsy.

The cerebellum linearly encodes whisker position during voluntary movement

Active whisking is an important model sensorimotor behavior, but the function of the cerebellum in the rodent whisker system is unknown. We have made patch clamp recordings from Purkinje cells in vivo to identify whether cerebellar output encodes kinematic features of whisking including the phase and set point. We show that Purkinje cell spiking activity changes strongly during whisking bouts. On average, the changes in simple spike rate coincide with or slightly precede movement, indicating that the synaptic drive responsible for these changes is predominantly of efferent (motor) rather than re-afferent (sensory) origin. Remarkably, on-going changes in simple spike rate provide an accurate linear read-out of whisker set point. Thus, despite receiving several hundred thousand discrete synaptic inputs across a non-linear dendritic tree, Purkinje cells integrate parallel fiber input to generate precise information about whisking kinematics through linear changes in firing rate.

DOI:http://dx.doi.org/10.7554/eLife.10509.001

Many animals actively move their whiskers back and forth to explore their surroundings and search for objects of interest. This behavior is important for navigation and the animals’ sense of touch. It relies on specialized circuits of cells in the brain to carry information about whisker movement patterns and process the touch signals. A region of the brain called the cerebellum is highly connected to these circuits, but its role in the voluntary movement of whiskers is not clear.

Chen et al. aimed to address this question by using a technique called patch clamping to measure the electrical activity of individual neurons in the mouse cerebellum. The experiments revealed that individual cells in the cerebellum called Purkinje cells track whisker movements in real time, and with virtually no delay, through both increases and decreases in their activity. Also, Chen et al. found that the patterns of electrical activity in these cells closely mimicked the positions of the whiskers as they moved. These results tell us that cells in the cerebellum use a simple code to represent whisker position during voluntary movement.

Chen et al.’s findings present the first experimental evidence that the cerebellum applies a type of code known as a linear code to represent the voluntary movements of whiskers. The next challenge is to find out how contact with whiskers alters movement-related signals in the cerebellum.

DOI:http://dx.doi.org/10.7554/eLife.10509.002

The Slow Oscillation in Cortical and Thalamic Networks: Mechanisms and Functions

During even the most quiescent behavioral periods, the cortex and thalamus express rich spontaneous activity in the form of slow (<1 Hz), synchronous network state transitions. Throughout this so-called slow oscillation, cortical and thalamic neurons fluctuate between periods of intense synaptic activity (Up states) and almost complete silence (Down states). The two decades since the original characterization of the slow oscillation in the cortex and thalamus have seen considerable advances in deciphering the cellular and network mechanisms associated with this pervasive phenomenon. There are, nevertheless, many questions regarding the slow oscillation that await more thorough illumination, particularly the mechanisms by which Up states initiate and terminate, the functional role of the rhythmic activity cycles in unconscious or minimally conscious states, and the precise relation between Up states and the activated states associated with waking behavior. Given the substantial advances in multineuronal recording and imaging methods in both in vivo and in vitro preparations, the time is ripe to take stock of our current understanding of the slow oscillation and pave the way for future investigations of its mechanisms and functions. My aim in this Review is to provide a comprehensive account of the mechanisms and functions of the slow oscillation, and to suggest avenues for further exploration.

Waking State: Rapid Variations Modulate Neural and Behavioral Responses

The state of the brain and body constantly varies on rapid and slow timescales. These variations contribute to the apparent noisiness of sensory responses at both the neural and the behavioral level. Recent investigations of rapid state changes in awake, behaving animals have provided insight into the mechanisms by which optimal sensory encoding and behavioral performance are achieved. Fluctuations in state, as indexed by pupillometry, impact both the "signal" (sensory evoked response) and the "noise" (spontaneous activity) of cortical responses. By taking these fluctuations into account, neural response (co)variability is significantly reduced, revealing the brain to be more reliable and predictable than previously thought.

Intrinsic coupling modes reveal the functional architecture of cortico-tectal networks

In the absence of sensory stimulation or motor output, the brain exhibits complex spatiotemporal patterns of intrinsically generated neural activity. Analysis of ongoing brain dynamics has identified the prevailing modes of cortico-cortical interaction; however, little is known about how such patterns of intrinsically generated activity are correlated between cortical and subcortical brain areas. We investigate the correlation structure of ongoing cortical and superior colliculus (SC) activity across multiple spatial and temporal scales. Ongoing cortico-tectal interaction was characterized by correlated fluctuations in the amplitude of delta, spindle, low gamma, and high-frequency oscillations (>100 Hz). Of these identified coupling modes, topographical patterns of high-frequency coupling were the most consistent with patterns of anatomical connectivity, reflecting synchronized spiking within cortico-tectal networks. Cortico-tectal coupling at high frequencies was temporally parcellated by the phase of slow cortical oscillations and was strongest for SC-cortex channel pairs that displayed overlapping visual spatial receptive fields. Despite displaying a high degree of spatial specificity, cortico-tectal coupling in lower-frequency bands did not match patterns of cortex-to-SC anatomical connectivity. Collectively, our findings demonstrate that neural activity is spontaneously coupled between cortex and SC, with high- and low-frequency modes of coupling reflecting direct and indirect cortico-tectal interactions, respectively.

High frequency synchrony in the cerebellar cortex during goal directed movements

The cerebellum is involved in sensory-motor integration and cognitive functions. The origin and function of the field potential oscillations in the cerebellum, especially in the high frequencies, have not been explored sufficiently. The primary objective of this study was to investigate the spatio-temporal characteristics of high frequency field potentials (150–350 Hz) in the cerebellar cortex in a behavioral context. To this end, we recorded from the paramedian lobule in rats using micro electro-corticogram (μ-ECoG) electrode arrays while the animal performed a lever press task using the forelimb. The phase synchrony analysis shows that the high frequency oscillations recorded at multiple points across the paramedian cortex episodically synchronize immediately before and desynchronize during the lever press. The electrode contacts were grouped according to their temporal course of phase synchrony around the time of lever press. Contact groups presented patches with slightly stronger synchrony values in the medio-lateral direction, and did not appear to form parasagittal zones. The size and location of these patches on the cortical surface are in agreement with the sensory evoked granular layer patches originally reported by Welker's lab (Shambes et al., 1978). Spatiotemporal synchrony of high frequency field potentials has not been reported at such large-scales previously in the cerebellar cortex.

Decreased subcortical cholinergic arousal in focal seizures

Impaired consciousness in temporal lobe seizures has a major negative impact on quality of life. The prevailing view holds that this disorder impairs consciousness by seizure spread to the bilateral temporal lobes. We propose instead that seizures invade subcortical regions and depress arousal, causing impairment through decreases rather than through increases in activity. Using functional magnetic resonance imaging in a rodent model, we found increased activity in regions known to depress cortical function, including lateral septum and anterior hypothalamus. Importantly, we found suppression of intralaminar thalamic and brainstem arousal systems and suppression of the cortex. At a cellular level, we found reduced firing of identified cholinergic neurons in the brainstem pedunculopontine tegmental nucleus and basal forebrain. Finally, we used enzyme-based amperometry to demonstrate reduced cholinergic neurotransmission in both cortex and thalamus. Decreased subcortical arousal is a critical mechanism for loss of consciousness in focal temporal lobe seizures.

Myoclonic Twitching and Sleep-Dependent Plasticity in the Developing Sensorimotor System

As bodies grow and change throughout early development and across the lifespan, animals must develop, refine, and maintain accurate sensorimotor maps. Here we review evidence that myoclonic twitches-brief and discrete contractions of the muscles, occurring exclusively during REM (or active) sleep, that result in jerks of the limbs-help animals map their ever-changing bodies by activating skeletal muscles to produce corresponding sensory feedback, or reafference. First, we highlight the spatiotemporal characteristics of twitches. Second, we review findings in infant rats regarding the multitude of brain areas that are activated by twitches during sleep. Third, we discuss evidence demonstrating that the sensorimotor processing of twitches is different from that of wake movements; this state-related difference in sensorimotor processing provides perhaps the strongest evidence yet that twitches are uniquely suited to drive certain aspects of sensorimotor development. Finally, we suggest that twitching may help inform our understanding of neurodevelopmental disorders, perhaps even providing opportunities for their early detection and treatment.

Brain state dependent activity in the cortex and thalamus

Cortical and thalamocortical activity is highly state dependent, varying between patterns that are conducive to accurate sensory-motor processing, to states in which the brain is largely off-line and generating internal rhythms irrespective of the outside world. The generation of rhythmic activity occurs through the interaction of stereotyped patterns of connectivity together with intrinsic membrane and synaptic properties. One common theme in the generation of rhythms is the interaction of a positive feedback loop (e.g., recurrent excitation) with negative feedback control (e.g., inhibition, adaptation, or synaptic depression). The operation of these state-dependent activities has wide ranging effects from enhancing or blocking sensory-motor processing to the generation of pathological rhythms associated with psychiatric or neurological disorders.

Neuronal oscillations in Golgi cells and Purkinje cells are accompanied by decreases in Shannon information entropy

Neuronal oscillations have been shown to contribute to the function of the cerebral cortex by coordinating the neuronal activities of distant cortical regions via a temporal synchronization of neuronal discharge patterns. This can occur regardless whether these regions are linked by cortico-cortical pathways or not. Less is known concerning the role of neuronal oscillations in the cerebellum. Golgi cells and Purkinje cells are both principal cell types in the cerebellum. Purkinje cells are the sole output cells of the cerebellar cortex while Golgi cells contribute to information processing at the input stage of the cerebellar cortex. Both cell types have large cell bodies, as well as dendritic structures, that can generate large currents. The discharge patterns of both these cell types also exhibit oscillations. In view of the massive afferent information conveyed by the mossy fiber-granule cell system to different and distant areas of the cerebellar cortex, it is relevant to inquire the role of cerebellar neuronal oscillations in information processing. In this study, we compared the discharge patterns of Golgi cells and Purkinje cells in conscious rats and in rats anesthetized with urethane. We assessed neuronal oscillations by analyzing the regularity in the timing of individual spikes within a spike train by using autocorrelograms and fast-Fourier transform. We measured the differences in neuronal oscillations and the amount of information content in a spike train (defined by Shannon entropy processed per unit time) in rats under anesthesia and in conscious, awake rats. Our findings indicated that anesthesia caused more prominent neuronal oscillations in both Golgi cells and Purkinje cells accompanied by decreases in Shannon information entropy in their spike trains.

Diurnal influences on electrophysiological oscillations and coupling in the dorsal striatum and cerebellar cortex of the anesthetized rat

Circadian rhythms modulate behavioral processes over a 24 h period through clock gene expression. What is largely unknown is how these molecular influences shape neural activity in different brain areas. The clock gene Per2 is rhythmically expressed in the striatum and the cerebellum and its expression is linked with daily fluctuations in extracellular dopamine levels and D2 receptor activity. Electrophysiologically, dopamine depletion enhances striatal local field potential (LFP) oscillations. We investigated if LFP oscillations and synchrony were influenced by time of day, potentially via dopamine mechanisms. To assess the presence of a diurnal effect, oscillatory power and coherence were examined in the striatum and cerebellum of rats under urethane anesthesia at four different times of day zeitgeber time (ZT1, 7, 13 and 19—indicating number of hours after lights turned on in a 12:12 h light-dark cycle). We also investigated the diurnal response to systemic raclopride, a D2 receptor antagonist. Time of day affected the proportion of LFP oscillations within the 0–3 Hz band and the 3–8 Hz band. In both the striatum and the cerebellum, slow oscillations were strongest at ZT1 and weakest at ZT13. A 3–8 Hz oscillation was present when the slow oscillation was lowest, with peak 3–8 Hz activity occurring at ZT13. Raclopride enhanced the slow oscillations, and had the greatest effect at ZT13. Within the striatum and with the cerebellum, 0–3 Hz coherence was greatest at ZT1, when the slow oscillations were strongest. Coherence was also affected the most by raclopride at ZT13. Our results suggest that neural oscillations in the cerebellum and striatum, and the synchrony between these areas, are modulated by time of day, and that these changes are influenced by dopamine manipulation. This may provide insight into how circadian gene transcription patterns influence network electrophysiology. Future experiments will address how these network alterations are linked with behavior.