Thalamic Spike Research Articles

Thalamic epileptic spikes disrupt sleep spindles in patients with epileptic encephalopathy.

In severe epileptic encephalopathies, epileptic activity contributes to progressive cognitive dysfunction. Epileptic encephalopathies share the trait of spike-wave activation during non-REM sleep (EE-SWAS), a sleep stage dominated by sleep spindles, which are brain oscillations known to coordinate offline memory consolidation. Epileptic activity has been proposed to hijack the circuits driving these thalamocortical oscillations, thereby contributing to cognitive impairment. Using a unique dataset of simultaneous human thalamic and cortical recordings in subjects with and without EE-SWAS, we provide evidence for epileptic spike interference of thalamic sleep spindle production in patients with EE-SWAS. First, we show that epileptic spikes and sleep spindles are both predicted by slow oscillations during stage two sleep (N2), but at different phases of the slow oscillation. Next, we demonstrate that sleep-activated cortical epileptic spikes propagate to the thalamus (thalamic spike rate increases after a cortical spike, P ≈ 0). We then show that epileptic spikes in the thalamus increase the thalamic spindle refractory period (P ≈ 0). Finally, we show that in three patients with EE-SWAS, there is a downregulation of sleep spindles for 30 s after each thalamic spike (P < 0.01). These direct human thalamocortical observations support a proposed mechanism for epileptiform activity to impact cognitive function, wherein epileptic spikes inhibit thalamic sleep spindles in epileptic encephalopathy with spike and wave activation during sleep.

Spike timing-based regulation of thalamocortical signaling

For decades, thalamic burst and tonic spiking modes have been theorized to regulate sensory signaling in the thalamocortical circuit. In this issue of Neuron, Borden etal. demonstrate a timing-based mechanism by which thalamic spiking mode controls sensory responses in the awake cortex.

Temporal dynamics of the cerebello-cortical convergence in ventro-lateral motor thalamus.

Key points Ventrolateral thalamus (VL) integrates information from cerebellar nuclei and motor cortical layer VI.Inputs from the cerebellar nuclei evoke large‐amplitude responses that depress upon repetitive stimulation while layer VI inputs from motor cortex induce small‐amplitude facilitating responses.We report that the spiking of VL neurons can be determined by the thalamic membrane potential, the frequency of cerebellar inputs and the duration of pauses after cerebellar high frequency stimulation.Inputs from motor cortical layer VI shift the VL membrane potential and modulate the VL spike output in response to cerebellar stimulation. These results help us to decipher how the cerebellar output is integrated in VL and modulated by motor cortical input. Orchestrating complex movements requires well‐timed interaction of cerebellar, thalamic and cerebral structures, but the mechanisms underlying the integration of cerebro‐cerebellar information in motor thalamus remain largely unknown. Here we investigated how excitatory inputs from cerebellar nuclei (CN) and primary motor cortex layer VI (M1‐L6) neurons may regulate the activity of neurons in the mouse ventrolateral (VL) thalamus. Using dual‐optical stimulation of the CN and M1‐L6 axons and in vitro whole‐cell recordings of the responses in VL neurons, we studied the individual responses as well as the effects of combined CN and M1‐L6 stimulation. Whereas CN inputs evoked large‐amplitude responses that were depressed upon repetitive stimulation, M1‐L6 inputs elicited small‐amplitude responses that were facilitated upon repetitive stimulation. Moreover, pauses in CN stimuli could directly affect VL spiking probability, an effect that was modulated by VL membrane potential. When CN and M1‐L6 pathways were co‐activated, motor cortical afferents increased the thalamic spike output in response to cerebellar stimulation, indicating that CN and M1 synergistically, yet differentially, control the membrane potential and spiking pattern of VL neurons.

Interactions Between Motor Thalamic Field Potentials and Single-Unit Spiking Are Correlated With Behavior in Rats.

Field potential (FP) oscillations are believed to coordinate brain activity over large spatiotemporal scales, with specific features (e.g., phase and power) in discrete frequency bands correlated with motor output. Furthermore, complex correlations between oscillations in distinct frequency bands (phase-amplitude, amplitude-amplitude, and phase-phase coupling) are commonly observed. However, the mechanisms underlying FP-behavior correlations and cross-frequency coupling remain unknown. The thalamus plays a central role in generating many circuit-level neural oscillations, and single-unit activity in motor thalamus (Mthal) is correlated with behavioral output. We, therefore, hypothesized that motor thalamic spiking coordinates motor system FPs and underlies FP-behavior correlations. To investigate this possibility, we recorded wideband motor thalamic (Mthal) electrophysiology as healthy rats performed a two-alternative forced-choice task. Delta (1–4 Hz), beta (13–30 Hz), low gamma (30–70 Hz), and high gamma (70–200 Hz) power were strongly modulated by task performance. As in the cortex, the delta phase was correlated with beta/low gamma power and reaction time. Most interestingly, subpopulations of Mthal neurons defined by their relationship to the behavior exhibited distinct relationships with FP features. Specifically, neurons whose activity was correlated with action selection and movement speed were entrained to delta oscillations. Furthermore, changes in their activity anticipated power fluctuations in beta/low gamma bands. These complex relationships suggest mechanisms for commonly observed FP-FP and spike-FP correlations, as well as subcortical influences on motor output.

Context-dependent and dynamic functional influence of corticothalamic pathways to first- and higher-order visual thalamus

Layer 6 (L6) is the sole purveyor of corticothalamic (CT) feedback to first-order thalamus and also sends projections to higher-order thalamus, yet how it engages the full corticothalamic circuit to contribute to sensory processing in an awake animal remains unknown. We sought to elucidate the functional impact of L6CT projections from the primary visual cortex to the dorsolateral geniculate nucleus (first-order) and pulvinar (higher-order) using optogenetics and extracellular electrophysiology in awake mice. While sustained L6CT photostimulation suppresses activity in both visual thalamic nuclei in vivo, moderate-frequency (10 Hz) stimulation powerfully facilitates thalamic spiking. We show that each stimulation paradigm differentially influences the balance between monosynaptic excitatory and disynaptic inhibitory corticothalamic pathways to the dorsolateral geniculate nucleus and pulvinar, as well as the prevalence of burst versus tonic firing. Altogether, our results support a model in which L6CTs modulate first- and higher-order thalamus through parallel excitatory and inhibitory pathways that are highly dynamic and context-dependent.

Feedforward Thalamocortical Connectivity Preserves Stimulus Timing Information in Sensory Pathways.

Reliable timing of cortical spikes in response to visual events is crucial in representing visual inputs to the brain. Spikes in the primary visual cortex (V1) need to occur at the same time within a repeated visual stimulus. Two classical mechanisms are employed by the cortex to enhance reliable timing. First, cortical neurons respond reliably to a restricted set of stimuli through their preference for certain patterns of membrane potential due to their intrinsic properties. Second, intracortical networking of excitatory and inhibitory neurons induces lateral inhibition that, through the timing and strength of IPSCs and EPSCs, produces sparse and reliably timed cortical neuron spike trains to be transmitted downstream. Here, we describe a third mechanism that, through preferential thalamocortical synaptic connectivity, enhances the trial-to-trial timing precision of cortical spikes in the presence of spike train variability within each trial that is introduced between LGN neurons in the retino-thalamic pathway. Applying experimentally recorded LGN spike trains from the anesthetized cat to a detailed model of a spiny stellate V1 neuron, we found that output spike timing precision improved with increasing numbers of convergent LGN inputs. The improvement was consistent with the predicted proportionality of [Formula: see text] for n LGN source neurons. We also found connectivity configurations that maximize reliability and that generate V1 cell output spike trains quantitatively similar to the experimental recordings. Our findings suggest a general principle, namely intra-trial variability among converging inputs, that increases stimulus response precision and is widely applicable to synaptically connected spiking neurons.SIGNIFICANCE STATEMENT The early visual pathway of the cat is favorable for studying the effects of trial-to-trial variability of synaptic inputs and intra-trial variability of thalamocortical connectivity on information transmission into the visual cortex. We have used a detailed model to show that there are preferred combinations of the number of thalamic afferents and the number of synapses per afferent that maximize the output reliability and spike-timing precision of cortical neurons. This provides additional insights into how synchrony in thalamic spike trains can reduce trial-to-trial variability to produce highly reliable reporting of sensory events to the cortex. The same principles may apply to other converging pathways where temporally jittered spike trains can reliably drive the downstream neuron and improve temporal precision.

A functional micro-electrode mapping of ventral thalamus in essential tremor.

Deep brain stimulation enables the delivery of therapeutic interventions to otherwise inaccessible areas of the brain while, at the same time, offering the unique opportunity to record from these same regions in awake patients. The posterior ventrolateral thalamus has become a reliable deep brain stimulation target for medically-refractory patients suffering from essential tremor. However, the contribution of the thalamus in essential tremor, and even whether posterior ventrolateral thalamus is the optimal target, remains a matter of ongoing debate. There are several lines of evidence supporting clusters of activity within the posterior ventrolateral thalamus that are important for tremor emergence. In this study we sought to map the functional properties of these clusters through microelectrode recordings during deep brain stimulation surgery. Data were obtained from 10 severely affected patients with essential tremor (12 hemispheres) undergoing deep brain stimulation surgery. Our results demonstrate power and coherence maxima located in the inferior posterior ventrolateral thalamus and immediate ventral region. Moreover, we identified distinct yet overlapping clusters of predominantly efferent (driving) and afferent (feedback) activity, with a preference for more efferent contributors, consistent with a net role in the driving of tremor output. Finally, we demonstrate that resolvable thalamic spiking activity directly relates to background activity and that the strength of tremor may be dictated by phase relationships between efferent and afferent pockets in the posterior ventrolateral thalamus. Taken together, these results provide important evidence for the role of the inferior posterior ventrolateral thalamus and its border region in essential tremor pathophysiology. Such results progress our mechanistic understanding and promote the adoption of next-generation therapies such as high resolution segregated deep brain stimulation electrodes.

Electrical synapses between inhibitory neurons shape the responses of principal neurons to transient inputs in the thalamus: a modeling study

As multimodal sensory information proceeds to the cortex, it is intercepted and processed by the nuclei of the thalamus. The main source of inhibition within thalamus is the reticular nucleus (TRN), which collects signals both from thalamocortical relay neurons and from thalamocortical feedback. Within the reticular nucleus, neurons are densely interconnected by connexin36-based gap junctions, known as electrical synapses. Electrical synapses have been shown to coordinate neuronal rhythms, including thalamocortical spindle rhythms, but their role in shaping or modulating transient activity is less understood. We constructed a four-cell model of thalamic relay and TRN neurons, and used it to investigate the impact of electrical synapses on closely timed inputs delivered to thalamic relay cells. We show that the electrical synapses of the TRN assist cortical discrimination of these inputs through effects of truncation, delay or inhibition of thalamic spike trains. We expect that these are principles whereby electrical synapses play similar roles in regulating the processing of transient activity in excitatory neurons across the brain.

The Thalamus as a Low Pass Filter: Filtering at the Cellular Level does Not Equate with Filtering at the Network Level.

In the mammalian central nervous system, most sensory information passes through primary sensory thalamic nuclei, however the consequence of this remains unclear. Various propositions exist, likening the thalamus to a gate, or a high pass filter. Here, using a simple leaky integrate and fire model based on physiological parameters, we show that the thalamus behaves akin to a low pass filter. Specifically, as individual cells in the thalamus rely on consistent drive to spike, stimuli that is rapidly and continuously changing over time such that it activates sensory cells with different receptive fields are unable to drive thalamic spiking. This means that thalamic encoding is robust to sensory noise, however it induces a lag in sensory representation. Thus, the thalamus stabilizes encoding of sensory information, at the cost of response rate.

Integration of cortical and pallidal inputs in the basal ganglia-recipient thalamus of singing birds.

The basal ganglia-recipient thalamus receives inhibitory inputs from the pallidum and excitatory inputs from cortex, but it is unclear how these inputs interact during behavior. We recorded simultaneously from thalamic neurons and their putative synaptically connected pallidal inputs in singing zebra finches. We find, first, that each pallidal spike produces an extremely brief (∼5 ms) pulse of inhibition that completely suppresses thalamic spiking. As a result, thalamic spikes are entrained to pallidal spikes with submillisecond precision. Second, we find that the number of thalamic spikes that discharge within a single pallidal interspike interval (ISI) depends linearly on the duration of that interval but does not depend on pallidal activity prior to the interval. In a detailed biophysical model, our results were not easily explained by the postinhibitory "rebound" mechanism previously observed in anesthetized birds and in brain slices, nor could most of our data be characterized as "gating" of excitatory transmission by inhibitory pallidal input. Instead, we propose a novel "entrainment" mechanism of pallidothalamic transmission that highlights the importance of an excitatory conductance that drives spiking, interacting with brief pulses of pallidal inhibition. Building on our recent finding that cortical inputs can drive syllable-locked rate modulations in thalamic neurons during singing, we report here that excitatory inputs affect thalamic spiking in two ways: by shortening the latency of a thalamic spike after a pallidal spike and by increasing thalamic firing rates within individual pallidal ISIs. We present a unifying biophysical model that can reproduce all known modes of pallidothalamic transmission--rebound, gating, and entrainment--depending on the amount of excitation the thalamic neuron receives.

A cortical motor nucleus drives the basal ganglia-recipient thalamus in singing birds

The pallido-recipient thalamus transmits information from the basal ganglia (BG) to the cortex and plays a critical role motor initiation and learning. Thalamic activity is strongly inhibited by pallidal inputs from the BG, but the role of non-pallidal inputs, such as excitatory inputs from cortex, is unclear. We have recorded simultaneously from presynaptic pallidal axon terminals and postsynaptic thalamocortical neurons in a BG-recipient thalamic nucleus necessary for vocal variability and learning in zebra finches. We found that song-locked rate modulations in the thalamus could not be explained by pallidal inputs alone, and persisted following pallidal lesion. Instead, thalamic activity was likely driven by inputs from a motor ‘cortical’ nucleus also necessary for singing. These findings suggest a role for cortical inputs to the pallido-recipient thalamus in driving premotor signals important for exploratory behavior and learning.

Input-rate modulation of gamma oscillations is sensitive to network topology, delays and short-term plasticity

Simulated networks of excitatory and inhibitory neurons have previously been shown to reproduce critical features of experimental data regarding neural coding in V1, such as a positive relationship between thalamic input spike rate and the power of gamma frequency oscillations. This effect, referred to as modulated gamma power, could represent a neural code in V1 for stimulus characteristics that affect thalamic spike rate such as contrast or intensity. The simulated network's assumptions included homogeneous random connectivity, equal synaptic delays after spike arrival, and constant synaptic efficacies. Plausible alternative assumptions include small world connectivity, a wide distribution of axonal propagation delays, and short term synaptic plasticity, and here we assess the individual impact of each of these on the model's success in reproducing modulated gamma power. First, we developed several alternative algorithms for simulating directed networks with clustered connectivity and balanced excitation and inhibition. We found that modulated gamma power was absent in all small-world networks that had a relatively low abundance of reciprocal connectivity, which suggests that such motifs are present in V1 cortical networks at levels at least equal to those found in random networks. We also found in a different network type that the balance of excitation and inhibition could be destroyed when the network was in the small-world regime. Given all neurons had identical in-degrees, this result suggests that balance relies on motif distributions as well as mean connectivity. Second, altering the distribution of axonal delays had little effect, but increasing the mean delay led to a secondary gamma modulation at harmonics of the main peak, and since this is not observed experimentally, it suggests a mean delay in V1 networks less than 2ms. Finally, we compared two types of excitatory synaptic plasticity, and found that modulated beta power emerged in addition to gamma power for one type, in the presence of short term depression in interneurons.This article is part of a Special Issue entitled “Neural Coding”.

Temporal Precision in the Visual Pathway through the Interplay of Excitation and Stimulus-Driven Suppression

Visual neurons can respond with extremely precise temporal patterning to visual stimuli that change on much slower time scales. Here, we investigate how the precise timing of cat thalamic spike trains-which can have timing as precise as 1 ms-is related to the stimulus, in the context of both artificial noise and natural visual stimuli. Using a nonlinear modeling framework applied to extracellular data, we demonstrate that the precise timing of thalamic spike trains can be explained by the interplay between an excitatory input and a delayed suppressive input that resembles inhibition, such that neuronal responses only occur in brief windows where excitation exceeds suppression. The resulting description of thalamic computation resembles earlier models of contrast adaptation, suggesting a more general role for mechanisms of contrast adaptation in visual processing. Thus, we describe a more complex computation underlying thalamic responses to artificial and natural stimuli that has implications for understanding how visual information is represented in the early stages of visual processing.

Correlation transfer from basal ganglia to thalamus in Parkinson's disease

Spike trains from neurons in the basal ganglia of parkinsonian primates show increased pairwise correlations, oscillatory activity, and burst rate compared to those from neurons recorded during normal brain activity. However, it is not known how these changes affect the behavior of downstream thalamic neurons. To understand how patterns of basal ganglia population activity may affect thalamic spike statistics, we study pairs of model thalamocortical (TC) relay neurons receiving correlated inhibitory input from the internal segment of the globus pallidus (GPi), a primary output nucleus of the basal ganglia. We observe that the strength of correlations of TC neuron spike trains increases with the GPi correlation level, and bursty firing patterns such as those seen in the parkinsonian GPi allow for stronger transfer of correlations than do firing patterns found under normal conditions. We also show that the T-current in the TC neurons does not significantly affect correlation transfer, despite its pronounced effects on spiking. Oscillatory firing patterns in GPi are shown to affect the timescale at which correlations are best transferred through the system. To explain this last result, we analytically compute the spike count correlation coefficient for oscillatory cases in a reduced point process model. Our analysis indicates that the dependence of the timescale of correlation transfer is robust to different levels of input spike and rate correlations and arises due to differences in instantaneous spike correlations, even when the long timescale rhythmic modulations of neurons are identical. Overall, these results show that parkinsonian firing patterns in GPi do affect the transfer of correlations to the thalamus.

Retinal oscillations carry visual information to cortex

Thalamic relay cells fire action potentials that transmit information from retina to cortex. The amount of information that spike trains encode is usually estimated from the precision of spike timing with respect to the stimulus. Sensory input, however, is only one factor that influences neural activity. For example, intrinsic dynamics, such as oscillations of networks of neurons, also modulate firing pattern. Here, we asked if retinal oscillations might help to convey information to neurons downstream. Specifically, we made whole-cell recordings from relay cells to reveal retinal inputs (EPSPs) and thalamic outputs (spikes) and then analyzed these events with information theory. Our results show that thalamic spike trains operate as two multiplexed channels. One channel, which occupies a low frequency band (<30 Hz), is encoded by average firing rate with respect to the stimulus and carries information about local changes in the visual field over time. The other operates in the gamma frequency band (40–80 Hz) and is encoded by spike timing relative to retinal oscillations. At times, the second channel conveyed even more information than the first. Because retinal oscillations involve extensive networks of ganglion cells, it is likely that the second channel transmits information about global features of the visual scene.

The role of the thalamus and basal ganglia in parkinsonian tremor.

The mechanism of parkinsonian tremor may involve a central oscillator, peripheral feedback to the central nervous system (CNS), or both. The thalamus or the globus pallidus is the most likely site for a central oscillator and would be predicted to generate thalamic tremor-related activity characterized, respectively, by calcium spike-associated bursts and by maximal tremor-related activity in the pallidal relay nucleus of thalamus. Thalamic spike trains demonstrate neither of these characteristics. However, cross-correlation, latency, and transfer function analysis indicate that sensory feedback is a critical element in the relationship between thalamic activity and parkinsonian tremor. Therefore, thalamic spike train activity is most consistent with parkinsonian tremor being mediated by peripheral inputs involved in either an unstable reflex loop or sensory modulation of a central oscillator.

Auditory Thalamocortical Transmission Is Reliable and Temporally Precise

We have used the auditory thalamocortical slice to characterize thalamocortical transmission in primary auditory cortex (ACx) of the juvenile mouse. "Minimal" stimulation was used to activate medial geniculate neurons during whole cell recordings from regular-spiking (RS cells; mostly pyramidal) and fast-spiking (FS, putative inhibitory) neurons in ACx layers 3 and 4. Excitatory postsynaptic potentials (EPSPs) were considered monosynaptic (thalamocortical) if they met three criteria: low onset latency variability (jitter), little change in latency with increased stimulus intensity, and little change in latency during a high-frequency tetanus. Thalamocortical EPSPs were reliable (probability of postsynaptic responses to stimulation was approximately 1.0) as well as temporally precise (low jitter). Both RS and FS neurons received thalamocortical input, but EPSPs in FS cells had faster rise times, shorter latencies to peak amplitude, and shorter durations than EPSPs in RS cells. Thalamocortical EPSPs depressed during repetitive stimulation at rates (2-300 Hz) consistent with thalamic spike rates in vivo, but at stimulation rates > or = 40 Hz, EPSPs also summed to activate N-methyl-D-aspartate receptors and trigger long-lasting polysynaptic activity. We conclude that thalamic inputs to excitatory and inhibitory neurons in ACx activate reliable and temporally precise monosynaptic EPSPs that in vivo may contribute to the precise timing of acoustic-evoked responses.

Pain and Temperature Encoding in the Human Thalamic Somatic Sensory Nucleus (Ventral caudal): Inhibition-Related Bursting Evoked by Somatic Stimuli

Stimulus-evoked inhibitory events have not been demonstrated in thalamic spike trains encoding of pain and temperature stimuli. We have now tested the hypothesis that the human thalamic response to mechanical and thermal stimuli is characterized by low-threshold calcium spike (LTS)-associated bursts of high-frequency action potentials preceded by prolonged inhibition. The results included 57 neurons recorded in the human thalamic principal somatic sensory nucleus (ventral caudal, Vc) of 24 patients during awake surgery. Neurons were classified by the grading of their response with stimulus intensity into the painful range (graded or non-graded) and the stimulus response (to mechanical, cold, or heat stimuli). Firing rates were analyzed by the response to all stimuli combined (stimuli overall) and to the stimulus characteristic of the stimulus response type (optimal stimulus), e.g., cold stimuli for neurons of the cold stimulus response type. All neuronal categories had clear stimulus-evoked LTS bursting as identified by the criteria for selecting bursts in the spike train, by significant preburst inhibition, and by preburst inter-spike interval not significantly <100 ms. Stimulus-evoked LTS burst rates were significantly higher for neurons in the cold stimulus response type independent of the firing rate between bursts. The parameters of preburst inhibition were largely independent of the neuronal category and the stimuli included in the analysis, which suggests inhibitory mechanisms are similar across neuronal types. Therefore LTS bursting is a substantial, nonlinear component of the spontaneous and stimulus-evoked activity of thalamic neurons in awake humans.

Unitary IPSPs Drive Precise Thalamic Spiking in a Circuit Required for Learning

Song learning in birds requires a basal ganglia-thalamo-pallial loop that contains a calyceal GABAergic synapse in the thalamus. Information processing within this circuit is critical for proper song development; however, it is unclear whether activation of the inhibitory output of the basal ganglia structure Area X can drive sustained activity in its thalamic target, the medial portion of the dorsolateral thalamic nucleus (DLM). We show that high-frequency, random activation of this GABAergic synapse can drive precisely timed firing in DLM neurons in brain slices in the absence of excitatory input. Complex IPSP trains, including spike trains recorded in vivo, drive spiking in slices with high reproducibility, even between animals. Using a simple model, we can predict much of DLM's response to natural stimulus trains. These data elucidate basic rules by which thalamic relay neurons translate IPSPs into suprathreshold output and demonstrate extrathalamic GABAergic activation of thalamus.

Single-neuron analysis of human thalamus in patients with intention tremor and other clinical signs of cerebellar disease.

Tremor that occurs as a result of a cerebellar lesion, cerebellar tremor, is characteristically an intention tremor. Thalamic activity may be related to cerebellar tremor because transmission of some cerebellar efferent signals occurs via the thalamus and cortex to the periphery. We have now studied thalamic neuronal activity in a cerebellar relay nucleus (ventral intermediate-Vim) and a pallidal relay nucleus (ventralis oral posterior-Vop) during thalamotomy in patients with intention tremor and other clinical signs of cerebellar disease (tremor patients). The activity of single neurons and the simultaneous electromyographic (EMG) activity of the contralateral upper extremity in tremor patients performing a pointing task were analyzed by spectral cross-correlation analysis. EMG spectra during intention tremor often showed peaks of activity in the tremor-frequency range (1.9-5.8 Hz). There were significant differences in thalamic neuronal activity between tremor patients and controls. Neurons in Vim and Vop had significantly lower firing rates in tremor patients than in patients undergoing thalamic surgery for pain (pain controls). Other studies have shown that inputs to Vim from the cerebellum are transmitted through excitatory connections. Therefore the present results suggest that tremor in these tremor patients is associated with deafferentation of the thalamus from cerebellar efferent pathways. The thalamic X EMG cross-correlation functions were studied for cells located in Vim and Vop. Neuronal and EMG activity were as likely to be significantly correlated for cells in Vim as for those in Vop. Cells in Vim were more likely to have a phase lag relative to EMG than were cells in Vop. In monkeys, cells in the cerebellar relay nucleus of the thalamus, corresponding to Vim, are reported to lead movement during active oscillations at the wrist. In view of these monkey studies, the present results suggest that cells in Vim are deafferented and have a phase lag relative to tremor that is not found in normal active oscillations. The difference in phase of thalamic spike X EMG activity between Vim and Vop may contribute to tremor because lesions of pallidum or Vop are reported to relieve cerebellar tremor.