Single-unit Activity Research Articles

Effect of Reverberation on Neural Responses to Natural Speech in Rabbit Auditory Midbrain: No Evidence for a Neural Dereverberation Mechanism.

Reverberation is ubiquitous in everyday acoustic environments. It degrades both binaural cues and the envelope modulations of sounds and thus can impair speech perception. Still, both humans and animals can accurately perceive reverberant stimuli in most everyday settings. Previous neurophysiological and perceptual studies have suggested the existence of neural mechanisms that partially compensate for the effects of reverberation. However, these studies were limited by their use of either highly simplified stimuli or rudimentary reverberation simulations. To further characterize how reverberant stimuli are processed by the auditory system, we recorded single-unit (SU) and multiunit (MU) activity from the inferior colliculus (IC) of unanesthetized rabbits in response to natural speech utterances presented with no reverberation ("dry") and in various degrees of simulated reverberation (direct-to-reverberant energy ratios (DRRs) ranging from 9.4 to -8.2 dB). Linear stimulus reconstruction techniques (Mesgarani et al., 2009) were used to quantify the amount of speech information available in the responses of neural ensembles. We found that high-quality spectrogram reconstructions could be obtained for dry speech and in moderate reverberation from ensembles of 25 units. However, spectrogram reconstruction quality deteriorated in severe reverberation for both MUs and SUs such that the neural degradation paralleled the degradation in the stimulus spectrogram. Furthermore, spectrograms reconstructed from responses to reverberant stimuli resembled spectrograms of reverberant speech better than spectrograms of dry speech. Overall, the results provide no evidence for a dereverberation mechanism in neural responses from the rabbit IC when studied with linear reconstruction techniques.

Comparison of the effects of two anesthetics, isoflurane and urethane, on bladder function in rats

We compared the effects of two anesthetics, isoflurane and urethane on bladder function in rats. Arterial pressure, cystometry (CMG), and rhythmic bladder contractions (RBCs) under isovolumetric conditions, mechanosensitive single-unit afferent activities (SAAs), bladder compliance and bladder myogenic microcontractions (bladder microcontractions), and bladder blood flow, and blood and urine biochemical tests were investigated in isoflurane- or urethane-anesthetized female rats. In results of the CMG, 3/8 rats in the isoflurane group and 7/7 rats in the urethane group showed constant bladder neurogenic contractions for micturition, whereas 5/8 rats in the isoflurane group showed unstable contractions or overflow incontinence. The RBCs appeared in the urethane group but not in the isoflurane group, and SAAs in both the Aδ- and C-fibers, bladder compliance, and bladder microcontractions in the isoflurane group were higher than those in the urethane group during bladder distension. The blood biochemical test showed that the serum calcium level was higher in the isoflurane group. The mean arterial pressure and bladder blood flow were not different between the groups. The results showed that urethane anesthesia more retains bladder neurogenic contractions for micturition compared to isoflurane. In contrast, isoflurane anesthesia more retains bladder function during the storage phase compared to urethane.

Co-variations of cerebral blood volume and single neurons discharge during resting state and visual cognitive tasks in non-human primates

To better understand how the brain allows primates to perform various sets of tasks, the ability to simultaneously record neural activity at multiple spatiotemporal scales is challenging but necessary. However, the contribution of single-unit activities (SUAs) to neurovascular activity remains to be fully understood. Here, we combine functional ultrasound imaging of cerebral blood volume (CBV) and SUA recordings in visual and fronto-medial cortices of behaving macaques. We show that SUA provides a significant estimate of the neurovascular response below the typical fMRI spatial resolution of 2mm3. Furthermore, our results also show that SUAs and CBV activities are statistically uncorrelated during the resting state but correlate during tasks. These results have important implications for interpreting functional imaging findings while one constructs inferences of SUA during resting state or tasks.

Responses of Cortical Neurons to Intracortical Microstimulation in Awake Primates.

Intracortical microstimulation (ICMS) is commonly used in many experimental and clinical paradigms; however, its effects on the activation of neurons are still not completely understood. To document the responses of cortical neurons in awake nonhuman primates to stimulation, we recorded single-unit activity while delivering single-pulse stimulation via Utah arrays implanted in primary motor cortex (M1) of three macaque monkeys. Stimuli between 5 and 50 μA delivered to single channels reliably evoked spikes in neurons recorded throughout the array with delays of up to 12 ms. ICMS pulses also induced a period of inhibition lasting up to 150 ms that typically followed the initial excitatory response. Higher current amplitudes led to a greater probability of evoking a spike and extended the duration of inhibition. The likelihood of evoking a spike in a neuron was dependent on the spontaneous firing rate as well as the delay between its most recent spike time and stimulus onset. Tonic repetitive stimulation between 2 and 20 Hz often modulated both the probability of evoking spikes and the duration of inhibition; high-frequency stimulation was more likely to change both responses. On a trial-by-trial basis, whether a stimulus evoked a spike did not affect the subsequent inhibitory response; however, their changes over time were often positively or negatively correlated. Our results document the complex dynamics of cortical neural responses to electrical stimulation that need to be considered when using ICMS for scientific and clinical applications.

Spike rates of frontal eye field neurons predict reaction times in a spatial attention task

Which neuronal signal(s) predict reaction times when subjects respond to a target at covertly attended locations? Although recent studies showed that spike rates are not predictive, it remains a highly contested question. Therefore, we record single-unit activity from frontal eye field (FEF) neurons while macaques are performing a covert spatial attention task. We find that the attentional modulation of spike rates of FEF neurons is strongly correlated with behavioral reaction times. Moreover, this correlation already emerges 1s before target dimming, which triggers the behavioral responses. This prediction of reaction times by spike rates is found in neurons showing attention-dependent enhanced and suppressed activity for targets and distractors, respectively, yet in varying degrees across subjects. Thus, spike rates of FEF neurons can predict reaction times persistently and well before the operant behavior during selective attention tasks. Such long prediction windows will be useful for developing spike-based brain-machine interfaces.

Goal Choices Modify Frontotemporal Memory Representations.

Adapting flexibly to changing circumstances is guided by memory of past choices, their outcomes in similar circumstances, and a method for choosing among potential actions. The hippocampus (HPC) is needed to remember episodes, and the prefrontal cortex (PFC) helps guide memory retrieval. Single-unit activity in the HPC and PFC correlates with such cognitive functions. Previous work recorded CA1 and mPFC activity as male rats performed a spatial reversal task in a plus maze that requires both structures, found that PFC activity helps reactivate HPC representations of pending goal choices but did not describe frontotemporal interactions after choices. We describe these interactions after choices here. CA1 activity tracked both current goal location and the past starting location of single trials; PFC activity tracked current goal location better than past start location. CA1 and PFC reciprocally modulated representations of each other both before and after goal choices. After choices, CA1 activity predicted changes in PFC activity in subsequent trials, and the magnitude of this prediction correlated with faster learning. In contrast, PFC start arm activity more strongly modulated CA1 activity after choices correlated with slower learning. Together, the results suggest post-choice HPC activity conveys retrospective signals to the PFC, which combines different paths to common goals into rules. In subsequent trials, prechoice mPFC activity modulates prospective CA1 signals informing goal selection.SIGNIFICANCE STATEMENT HPC and PFC activity supports cognitive flexibility in changing circumstances. HPC signals represent behavioral episodes that link the start, choice, and goal of paths. PFC signals represent rules that guide goal-directed actions. Although prior studies described HPC-PFC interactions preceding decisions in the plus maze, post-decision interactions were not investigated. Here, we show post-choice HPC and PFC activity distinguished the start and goal of paths, and CA1 signaled the past start of each trial more accurately than mPFC. Postchoice CA1 activity modulated subsequent PFC activity, so rewarded actions were more likely to occur. Together, the results show that in changing circumstances, HPC retrospective codes modulate subsequent PFC coding, which in turn modulates HPC prospective codes that predict choices.

Serotonergic modulation of local network processing in V1 mirrors previously reported signatures of local network modulation by spatial attention.

Sensory processing is influenced by neuromodulators such as serotonin, thought to relay behavioural state. Recent work has shown that the modulatory effect of serotonin itself differs with the animal's behavioural state. In primates, including humans, the serotonin system is anatomically important in the primary visual cortex (V1). We previously reported that in awake fixating macaques, serotonin reduces the spiking activity by decreasing response gain in V1. But the effect of serotonin on the local network is unknown. Here, we simultaneously recorded single-unit activity and local field potentials (LFPs) while iontophoretically applying serotonin in V1 of alert monkeys fixating on a video screen for juice rewards. The reduction in spiking response we observed previously is the opposite of the known increase of spiking activity with spatial attention. Conversely, in the local network (LFP), the application of serotonin resulted in changes mirroring the local network effects of previous reports in macaques directing spatial attention to the receptive field. It reduced the LFP power and the spike-field coherence, and the LFP became less predictive of spiking activity, consistent with reduced functional connectivity. We speculate that together, these effects may reflect the sensory side of a serotonergic contribution to quiet vigilance: The lower gain reduces the salience of stimuli to suppress an orienting reflex to novel stimuli, whereas at the network level, visual processing is in a state comparable to that of spatial attention.

Coherent mapping of position and head direction across auditory and visual cortex.

Neurons in primary visual cortex (V1) may not only signal current visual input but also relevant contextual information such as reward expectancy and the subject's spatial position. Such contextual representations need not be restricted to V1 but could participate in a coherent mapping throughout sensory cortices. Here, we show that spiking activity coherently represents a location-specific mapping across auditory cortex (AC) and lateral, secondary visual cortex (V2L) of freely moving rats engaged in a sensory detection task on a figure-8 maze. Single-unit activity of both areas showed extensive similarities in terms of spatial distribution, reliability, and position coding. Importantly, reconstructions of subject position based on spiking activity displayed decoding errors that were correlated between areas. Additionally, we found that head direction, but not locomotor speed or head angular velocity, was an important determinant of activity in AC and V2L. By contrast, variables related to the sensory task cues or to trial correctness and reward were not markedly encoded in AC and V2L. We conclude that sensory cortices participate in coherent, multimodal representations of the subject's sensory-specific location. These may provide a common reference frame for distributed cortical sensory and motor processes and may support crossmodal predictive processing.

A C-shaped miniaturized coil for transcranial magnetic stimulation in rodents

Objective. Transcranial magnetic stimulation (TMS) is a non-invasive technique widely used for neuromodulation. Animal models are essential for investigating the underlying mechanisms of TMS. However, the lack of miniaturized coils hinders the TMS studies in small animals, since most commercial coils are designed for humans and thus incapable of focal stimulation in small animals. Furthermore, it is difficult to perform electrophysiological recordings at the TMS focal point using conventional coils. Approach. We designed, fabricated, and tested a novel miniaturized TMS coil (4-by-7 mm) that consisted of a C-shaped iron powder core and insulated copper wires (30 turns). The resulting magnetic and electric fields were characterized with experimental measurements and finite element modeling. The efficacy of this coil in neuromodulation was validated with electrophysiological recordings of single-unit activities (SUAs), somatosensory evoked potentials (SSEPs), and motor evoked potentials (MEPs) in rats (n = 32) following repetitive TMS (rTMS; 3 min, 10 Hz). Main results. This coil could generate a maximum magnetic field of 460 mT and an electric field of 7.2 V m−1 in the rat brain according to our simulations. With subthreshold rTMS focally delivered over the sensorimotor cortex, mean firing rates of primary somatosensory and motor cortical neurons significantly increased (154 5% and 160 9% from the baseline level, respectively); MEP and SSEP amplitude significantly increased (136 9%) and decreased (74 4%), respectively. Significance. This miniaturized C-shaped coil enabled focal TMS and concurrent electrophysiological recording/stimulation at the TMS focal point. It provided a useful tool to investigate the neural responses and underlying mechanisms of TMS in small animal models. Using this paradigm, we for the first time observed distinct modulatory effects on SUAs, SSEPs, and MEPs with the same rTMS protocol in anesthetized rats. These results suggested that multiple neurobiological mechanisms in the sensorimotor pathways were differentially modulated by rTMS.

Differential Encoding of Trace and Delay Fear Memory in the Entorhinal Cortex.

Trace fear conditioning is characterized by a stimulus-free trace interval (TI) between the conditioned stimulus (CS) and the unconditioned stimulus (US), which requires an array of brain structures to support the formation and storage of associative memory. The entorhinal cortex (EC) has been proposed to provide essential neural code for resolving temporal discontinuity in conjunction with the hippocampus. However, how the CS and TI are encoded at the neuronal level in the EC is not clear. In Exp. 1, we tested the effect of bilateral pre-training electrolytic lesions of EC on trace vs. delay fear conditioning using rats as subjects. We found that the lesions impaired the acquisition of trace but not delay fear conditioning confirming that EC is a critical brain area for trace fear memory formation. In Exp. 2, single-unit activities from EC were recorded during the pre-training baseline and post-training retention sessions following trace or delay conditioning. The recording results showed that a significant proportion of the EC neurons modulated their firing during TI after the trace conditioning, but not after the delay fear conditioning. Further analysis revealed that the majority of modulated units decreased the firing rate during the TI or the CS. Taken together, these results suggest that EC critically contributes to trace fear conditioning by modulating neuronal activity during the TI to facilitate the association between the CS and US across a temporal gap.

Edge computing on TPU for brain implant signal analysis

The ever-increasing number of recording sites of silicon-based probes imposes a great challenge for detecting and evaluating single-unit activities in an accurate and efficient manner. Currently separate solutions are available for high precision offline evaluation and separate solutions for embedded systems where computational resources are more limited.We propose a deep learning-based spike sorting system, that utilizes both unsupervised and supervised paradigms to learn a general feature embedding space and detect neural activity in raw data as well as predict the feature vectors for sorting. The unsupervised component uses contrastive learning to extract features from individual waveforms, while the supervised component is based on the MobileNetV2 architecture. One of the key advantages of our system is that it can be trained on multiple, diverse datasets simultaneously, resulting in greater generalizability than previous deep learning-based models.We demonstrate that the proposed model does not only reaches the accuracy of current state-of-art offline spike sorting methods but has the unique potential to run on edge Tensor Processing Units (TPUs), specialized chips designed for artificial intelligence and edge computing. We compare our model performance with state of art solutions on paired datasets as well as on hybrid recordings as well. The herein demonstrated system paves the way to the integration of deep learning-based spike sorting algorithms into wearable electronic devices, which will be a crucial element of high-end brain–computer interfaces.

Neural correlates of cognitively controlled vocalizations in a corvid songbird

The neuronal basis of the songbird's song system is well understood. However, little is known about the neuronal correlates of the executive control of songbird vocalizations. Here, we record single-unit activity from the pallial endbrain region "nidopallium caudolaterale" (NCL) of crows that vocalize to the presentation of a visual go-cue but refrain from vocalizing during trials without a go-cue. We find that the preparatory activity of single vocalization-correlated neurons, but also of the entire population of NCL neurons, before vocal onset predicts whether or not the crows will produce an instructed vocalization. Fluctuations in baseline neuronal activity prior to the go-cue influence the premotor activity of such vocalization-correlated neurons and seemingly bias the crows' decision to vocalize. Neuronal response modulation significantly differs between volitional and task-unrelated vocalizations. This suggests that the NCL can take control over the vocal motor network during the production of volitional vocalizations in a corvid songbird.

Vestibular Contributions to Primate Neck Postural Muscle Activity during Natural Motion.

To maintain stable posture of the head and body during our everyday activities, the brain integrates information across multiple sensory systems. Here, we examined how the primate vestibular system, independently and in combination with visual sensory input, contributes to the sensorimotor control of head posture across the range of dynamic motion experienced during daily life. We recorded activity of single motor units in the splenius capitis and sternocleidomastoid muscles in rhesus monkeys during yaw rotations spanning the physiological range of self-motion (up to 20 Hz) in darkness. Splenius capitis motor unit responses continued to increase with frequency up to 16 Hz in normal animals, and were strikingly absent following bilateral peripheral vestibular loss. To determine whether visual information modulated these vestibular-driven neck muscle responses, we experimentally controlled the correspondence between visual and vestibular cues of self-motion. Surprisingly, visual information did not influence motor unit responses in normal animals, nor did it substitute for absent vestibular feedback following bilateral peripheral vestibular loss. A comparison of muscle activity evoked by broadband versus sinusoidal head motion further revealed that low-frequency responses were attenuated when low- and high-frequency self-motion were experienced concurrently. Finally, we found that vestibular-evoked responses were enhanced by increased autonomic arousal, quantified via pupil size. Together, our findings directly establish the vestibular system's contribution to the sensorimotor control of head posture across the dynamic motion range experienced during everyday activities, as well as how vestibular, visual, and autonomic inputs are integrated for postural control.SIGNIFICANCE STATEMENT Our sensory systems enable us to maintain control of our posture and balance as we move through the world. Notably, the vestibular system senses motion of the head and sends motor commands, via vestibulospinal pathways, to axial and limb muscles to stabilize posture. By recording the activity of single motor units, here we show, for the first time, that the vestibular system contributes to the sensorimotor control of head posture across the dynamic motion range experienced during everyday activities. Our results further establish how vestibular, autonomic, and visual inputs are integrated for postural control. This information is essential for understanding both the mechanisms underlying the control of posture and balance, and the impact of the loss of sensory function.

Encoding of dynamic facial information in the middle dorsal face area

Faces in motion reveal a plethora of information through visual dynamics. Faces can move in complex patterns while transforming facial shape, e.g., during the generation of different emotional expressions. While motion and shape processing have been studied extensively in separate research enterprises, much less is known about their conjunction during biological motion. Here, we took advantage of the discovery in brain-imaging studies of an area in the dorsal portion of the macaque monkey superior temporal sulcus (STS), the middle dorsal face area (MD), with selectivity for naturalistic face motion. To gain mechanistic insights into the coding of facial motion, we recorded single-unit activity from MD, testing whether and how MD cells encode face motion. The MD population was highly sensitive to naturalistic facial motion and facial shape. Some MD cells responded only to the conjunction of facial shape and motion, others were selective for facial shape even without movement, and yet others were suppressed by facial motion. We found that this heterogeneous MD population transforms face motion into a higher dimensional activity space, a representation that would allow for high sensitivity to relevant small-scale movements. Indeed, we show that many MD cells carry such sensitivity for eye movements. We further found that MD cells encode motion of head, mouth, and eyes in a separable manner, requiring the use of multiple reference frames. Thus, MD is a bona fide face-motion area that uses highly heterogeneous cell populations to create codes capturing even complex facial motion trajectories.

Consensus for experimental design in electromyography (CEDE) project: Single motor unit matrix.

The analysis of single motor unit (SMU) activity provides the foundation from which information about the neural strategies underlying the control of muscle force can be identified, due to the one-to-one association between the action potentials generated by an alpha motor neuron and those received by the innervated muscle fibers. Such a powerful assessment has been conventionally performed with invasive electrodes (i.e., intramuscular electromyography (EMG)), however, recent advances in signal processing techniques have enabled the identification of single motor unit (SMU) activity in high-density surface electromyography (HDsEMG) recordings. This matrix, developed by the Consensus for Experimental Design in Electromyography (CEDE) project, provides recommendations for the recording and analysis of SMU activity with both invasive (needle and fine-wire EMG) and non-invasive (HDsEMG) SMU identification methods, summarizing their advantages and disadvantages when used during different testing conditions. Recommendations for the analysis and reporting of discharge rate and peripheral (i.e., muscle fiber conduction velocity) SMU properties are also provided. The results of the Delphi process to reach consensus are contained in an appendix. This matrix is intended to help researchers to collect, report, and interpret SMU data in the context of both research and clinical applications.

Hippocampal Neuronal Activity Preceding Stimulus Predicts Later Memory Success.

Hippocampal neuronal activity at a time preceding stimulus onset affects episodic memory performance. We hypothesized that neuronal activity preceding an event supports successful memory formation; therefore, we explored whether a characterized encoding-associated brain activity, viz. the neuronal activity preceding a stimulus, predicts subsequent memory formation. To address this issue, we assessed the activity of single neurons recorded from the hippocampus in humans, while participants performed word memory tasks. Human hippocampal single-unit activity elicited by a fixation cue preceding words increased the firing rates (FRs) and predicted whether the words are recalled in a subsequent memory test; this indicated that successful memory formation in humans can be predicted by a preceding stimulus activity during encoding. However, the predictive effect of preceding stimulus activity did not occur during retrieval. These findings suggest that the preparative arrangement of brain activity before stimulus encoding improves subsequent memory performance.

Effects of neuromodulation-inspired mechanisms on the performance of deep neural networks in a spatial learning task

In recent years, the biological underpinnings of adaptive learning have been modeled, leading to faster model convergence and various behavioral benefits in tasks including spatial navigation and cue-reward association. Furthermore, studies have investigated how the neuromodulatory system, a major driver of synaptic plasticity and state-dependent changes in the brain neuronal activities, plays a role in training deep neural networks (DNNs). In this study, we extended previous studies on neuromodulation-inspired DNNs and explored the effects of neuromodulatory components on learning and single unit activities in a spatial learning task. Under the multiscale neuromodulatory framework, plastic components, dropout probability modulation, and learning rate decay were added to the single unit, layer, and whole network levels of DNN models, respectively. We observed behavioral benefits including faster learning and smaller error of ambulation. We then concluded that neuromodulatory components can affect learning trajectories, outcomes, and single unit activities, in a component- and hyperparameter-dependent manner.

Thin flexible arrays for long-term multi-electrode recordings in macaque primary visual cortex

Objective. Basic, translational and clinical neuroscience are increasingly focusing on large-scale invasive recordings of neuronal activity. However, in large animals such as nonhuman primates and humans—in which the larger brain size with sulci and gyri imposes additional challenges compared to rodents, there is a huge unmet need to record from hundreds of neurons simultaneously anywhere in the brain for long periods of time. Here, we tested the electrical and mechanical properties of thin, flexible multi-electrode arrays (MEAs) inserted into the primary visual cortex of two macaque monkeys, and assessed their magnetic resonance imaging (MRI) compatibility and their capacity to record extracellular activity over a period of 1 year. Approach. To allow insertion of the floating arrays into the visual cortex, the 20 by 100 µm2 shafts were temporarily strengthened by means of a resorbable poly(lactic-co-glycolic acid) coating. Main results. After manual insertion of the arrays, the ex vivo and in vivo MRI compatibility of the arrays proved to be excellent. We recorded clear single-unit activity from up to 50% of the electrodes, and multi-unit activity (MUA) on 60%–100% of the electrodes, which allowed detailed measurements of the receptive fields and the orientation selectivity of the neurons. Even 1 year after insertion, we obtained significant MUA responses on 70%–100% of the electrodes, while the receptive fields remained remarkably stable over the entire recording period. Significance. Thus, the thin and flexible MEAs we tested offer several crucial advantages compared to existing arrays, most notably in terms of brain tissue compliance, scalability, and brain coverage. Future brain-machine interface applications in humans may strongly benefit from this new generation of chronically implanted MEAs.

Encoding of conditioned inhibitors of fear in the infralimbic cortex.

Cues in the environment signaling the absence of threat, i.e. safety, can influence both fear and reward-seeking behaviors. Heightened and maladaptive fear is associated with reduced activity in the medial prefrontal cortex. We have previously shown in male rats that the infralimbic (IL) prefrontal cortex is necessary for suppressing fear during a safety cue. The objective of the present study was to determine if there was safety cue-specific neural activity within the IL using a Pavlovian conditioning paradigm, where a fear cue was paired with shock, a safety cue was paired with no shock, and a reward cue was paired with sucrose. To investigate how safety cues can suppress fear, the fear and safety cues were presented together as a compound fear + safety cue. Single-unit activity showed a large proportion of neurons with excitatory responses to the fear + safety cue specifically, a separate group of neurons with excitatory responses to both the reward and fear + safety cues, and bidirectional neurons with excitation to the fear + safety cue and inhibition to the fear cue. Neural activity was also found to be negatively correlated with freezing during the fear + safety cue. Together, these data implicate the IL in encoding specific aspects of conditioned inhibitors when fear is being actively suppressed.

Conserved Population Dynamics in the Cerebro-Cerebellar System between Waking and Sleep.

Despite the importance of the cerebellum for motor learning, and the recognized role of sleep in motor memory consolidation, surprisingly little is known about neural activity in the sleeping cerebro-cerebellar system. Here, we used wireless recording from primary motor cortex (M1) and the cerebellum in three female monkeys to examine the relationship between patterns of single-unit spiking activity observed during waking behavior and in natural sleep. Across the population of recorded units, we observed similarities in the timing of firing relative to local field potential features associated with both movements during waking and up state during sleep. We also observed a consistent pattern of asymmetry in pairwise cross-correlograms, indicative of preserved sequential firing in both wake and sleep at low frequencies. Despite the overall similarity in population dynamics between wake and sleep, there was a global change in the timing of cerebellar activity relative to motor cortex, from contemporaneous in the awake state to motor cortex preceding the cerebellum in sleep. We speculate that similar population dynamics in waking and sleep may imply that cerebellar internal models are activated in both states, despite the absence of movement when asleep. Moreover, spindle frequency coherence between the cerebellum and motor cortex may provide a mechanism for cerebellar computations to influence sleep-dependent learning processes in the motor cortex.SIGNIFICANCE STATEMENT It is well known that sleep can lead to improved motor performance. One possibility is that off-line learning results from neural activity during sleep in brain areas responsible for the control of movement. In this study we show for the first time that neuronal patterns in the cerebro-cerebellar system are conserved during both movements and sleep up-states, albeit with a shift in the relative timing between areas. Additionally, we show the presence of simultaneous M1-cerebellar spike coherence at spindle frequencies associated with up-state replay and postulate that this is a mechanism whereby a cerebellar internal model can shape plasticity in neocortical circuits during sleep.