Prompt execution of planned motor action is essential for survival. The interactions between frontal cortical circuits and the basal ganglia are central to goal-oriented action selection and initiation.1–4 In rodents, the ventromedial thalamic nucleus (VM) is one of the critical nodes that conveys the output of the basal ganglia to the frontal cortical areas including the anterior lateral motor cortex (ALM).5–9 Recent studies showed the critical role of ALM and its interplay with the motor thalamus in preparing sensory-cued rewarded movements, specifically licking.10–12 Work in primates suggests that the basal ganglia output to the motor thalamus transmits an urgency or vigor signal,13–15 which leads to shortened reaction times and faster movement initiation. As yet, little is known about what signals are transmitted from the motor thalamus to the cortex during cued movements and how these signals contribute to movement initiation. In the present study, we employed a tactile-cued licking task in mice while monitoring reaction times of the initial lick. We found that inactivation of ALM delayed the initiation of cued licking. Two-photon Ca2+ imaging of VM axons revealed that the majority of the axon terminals in ALM were transiently active during licking. Their activity was predictive of the time of the first lick. Chemogenetic and optogenetic manipulation of VM axons in ALM indicated that VM inputs facilitate the initiation of cue-triggered and impulsive licking in trained mice. Our results suggest that VM thalamocortical inputs increase the probability and vigor of initiating planned motor responses.

The ventromedial (VM)/ventro-anterior-lateral (VAL) motor thalamus is a key junction within the brain circuits sustaining normal and pathologic motor control functions and decision-making. In this area of thalamus, on one hand, the inhibitory nigro-thalamic pathway provides a main output from the basal ganglia, and, on the other hand, motor thalamo-cortical loops are involved in the maintenance of ramping preparatory activity before goal-directed movements. To better understand the nigral impact on thalamic activity, we recorded electrophysiological responses from VM/VAL neurons while male and female mice were performing a delayed right/left decision licking task. Analysis of correct (corr) and error trials revealed that thalamic ramping activity was stronger for premature licks (impulsive action) and weaker for trials with no licks [omission (omi)] compared with correct trials. Suppressing ramping activity through optogenetic activation of nigral terminals in the motor thalamus during the delay epoch of the task led to a reduced probability of impulsive action and an increased amount of omissions trials. We propose a parsimonious model explaining our data and conclude that a thalamic ramping mechanism contributes to the control of proper timing of action release and that inhibitory nigral inputs are sufficient to interrupt this mechanism and modulate the amount of motor impulsivity in this task.

Small conductance Ca2+-activated potassium (SK) current provides an important modulator of excitatory synaptic transmission, which undergoes plastic regulation via multiple mechanisms. We examined whether inhibitory input processing is also dependent on SK current in the cerebellar nuclei (CN) where inhibition provides the only route of information transfer from the cerebellar cortical Purkinje cells. We employed dynamic clamping in conjunction with computer simulations to address this question. We found that SK current plays a critical role in the inhibitory synaptic control of spiking output. Specifically, regulation of SK current density resulted in a gain control of spiking output, such that low SK current promoted large output signaling for large inhibitory cell input fluctuations due to Purkinje cell synchronization. In contrast, smaller nonsynchronized Purkinje cell input fluctuations were not amplified. Regulation of SK density in the CN therefore would likely lead to important consequences for the transmission of synchronized Purkinje cell activity to the motor system.

Functional aspects of network integration in the cerebellar cortex have been studied experimentally and modeled in much detail ever since the early work by theoreticians such as Marr, Albus and Braitenberg more than 40years ago. In contrast, much less is known about cerebellar processing at the output stage, namely in the cerebellar nuclei (CN). Here, input from Purkinje cells converges to control CN neuron spiking via GABAergic inhibition, before the output from the CN reaches cerebellar targets such as the brainstem and the motor thalamus. In this article we review modeling studies that address how the CN may integrate cerebellar cortical inputs, and what kind of signals may be transmitted. Specific hypotheses in the literature contrast rate coding and temporal coding of information in the spiking output from the CN. One popular hypothesis states that post-inhibitory rebound spiking may be an important mechanism by which Purkinje cell inhibition is turned into CN output spiking, but this hypothesis remains controversial. Rate coding clearly does take place, but in what way it may be augmented by temporal codes remains to be more clearly established. Several candidate mechanisms distinct from rebound spiking are discussed, such as the significance of spike time correlations between Purkinje cell pools to determine CN spike timing, irregularity of Purkinje cell spiking as a determinant of CN firing rate, and shared brief pauses between Purkinje cell pools that may trigger individual CN spikes precisely.

The slow fluctuations of the blood-oxygenation-level dependent (BOLD) signal in resting-state fMRI are widely utilized as a surrogate marker of ongoing neural activity. Spontaneous neural activity includes a broad range of frequencies, from infraslow (< 0.5. Hz) fluctuations to fast action potentials. Recent studies have demonstrated a correlative relationship between the BOLD fluctuations and power modulations of the local field potential (LFP), particularly in the gamma band. However, the relationship between the BOLD signal and the infraslow components of the LFP, which are directly comparable in frequency to the BOLD fluctuations, has not been directly investigated. Here we report a first examination of the temporal relation between the resting-state BOLD signal and infraslow LFPs using simultaneous fMRI and full-band LFP recording in rat. The spontaneous BOLD signal at the recording sites exhibited significant localized correlation with the infraslow LFP signals as well as with the slow power modulations of higher-frequency LFPs (1-100. Hz) at a delay comparable to the hemodynamic response time under anesthesia. Infraslow electrical activity has been postulated to play a role in attentional processes, and the findings reported here suggest that infraslow LFP coordination may share a mechanism with the large-scale BOLD-based networks previously implicated in task performance, providing new insight into the mechanisms contributing to the resting state fMRI signal.

Functional connectivity measurements from resting state blood-oxygen level dependent (BOLD) functional magnetic resonance imaging (fMRI) are proving a powerful tool to probe both normal brain function and neuropsychiatric disorders. However, the neural mechanisms that coordinate these large networks are poorly understood, particularly in the context of the growing interest in network dynamics. Recent work in anesthetized rats has shown that the spontaneous BOLD fluctuations are tightly linked to infraslow local field potentials (LFPs) that are seldom recorded but comparable in frequency to the slow BOLD fluctuations. These findings support the hypothesis that long-range coordination involves low frequency neural oscillations and establishes infraslow LFPs as an excellent candidate for probing the neural underpinnings of the BOLD spatiotemporal patterns observed in both rats and humans. To further examine the link between large-scale network dynamics and infraslow LFPs, simultaneous fMRI and microelectrode recording were performed in anesthetized rats. Using an optimized filter to isolate shared components of the signals, we found that time-lagged correlation between infraslow LFPs and BOLD is comparable in spatial extent and timing to a quasi-periodic pattern (QPP) found from BOLD alone, suggesting that fMRI-measured QPPs and the infraslow LFPs share a common mechanism. As fMRI allows spatial resolution and whole brain coverage not available with electroencephalography, QPPs can be used to better understand the role of infraslow oscillations in normal brain function and neurological or psychiatric disorders.

Functional connectivity between brain regions, measured with resting state functional magnetic resonance imaging, holds great potential for understanding the basis of behavior and neuropsychiatric diseases. Recently it has become clear that correlations between the blood oxygenation level dependent (BOLD) signals from different areas vary over the course of a typical scan (6-10. min in length), though the changes are obscured by standard methods of analysis that assume the relationships are stationary. Unfortunately, because similar variability is observed in signals that share no temporal information, it is unclear which dynamic changes are related to underlying neural events. To examine this question, BOLD data were recorded simultaneously with local field potentials (LFP) from interhemispheric primary somatosensory cortex (SI) in anesthetized rats. LFP signals were converted into band-limited power (BLP) signals including delta, theta, alpha, beta and gamma. Correlation between signals from interhemispheric SI was performed in sliding windows to produce signals of correlation over time for BOLD and each BLP band. Both BOLD and BLP signals showed large changes in correlation over time and the changes in BOLD were significantly correlated to the changes in BLP. The strongest relationship was seen when using the theta, beta and gamma bands. Interestingly, while steady-state BOLD and BLP correlate with the global fMRI signal, dynamic BOLD becomes more like dynamic BLP after the global signal is regressed. As BOLD sliding window connectivity is partially reflecting underlying LFP changes, the present study suggests it may be a valuable method of studying dynamic changes in brain states.

Correlated firing among populations of neurons is present throughout the brain and is often rhythmic in nature, observable as an oscillatory fluctuation in the local field potential. Although rhythmic population activity is believed to be critical for normal function in many brain areas, synchronized neural oscillations are associated with disease states in other cases. In the globus pallidus (GP in rodents, homolog of the primate GPe), pairs of neurons generally have uncorrelated firing in normal animals despite an anatomical organization suggesting that they should receive substantial common input. By contrast, correlated and rhythmic GP firing is observed in animal models of Parkinson's disease (PD). Based in part on these findings it has been proposed that an important part of basal ganglia function is active decorrelation, whereby redundant information is compressed. Mechanisms that implement active decorrelation, and changes that cause it to fail in PD, are subjects of great interest. Rat GP neurons express fast, transient voltage-dependent sodium channels (NaF channels) in their dendrites, with the expression level being highest near asymmetric synapses. We recently showed that the dendritic NaF density strongly influences the responsiveness of model GP neurons to synchronous excitatory inputs. In the present study we use rat GP neuron models to show that dendritic NaF channel expression is a potential cellular mechanism of active decorrelation. We further show that model neurons with lower dendritic NaF channel expression have a greater tendency to phase lock with oscillatory synaptic input patterns like those observed in PD.

Synchronization of globus pallidus (GP) neurons and cortically-entrained oscillations between GP and other basal ganglia nuclei are key features of the pathophysiology of Parkinson's disease. Phase response curves (PRCs), which tabulate the effects of phasic inputs within a neuron's spike cycle on output spike timing, are efficient tools for predicting the emergence of synchronization in neuronal networks and entrainment to periodic input. In this study we apply physiologically realistic synaptic conductance inputs to a full morphological GP neuron model to determine the phase response properties of the soma and different regions of the dendritic tree. We find that perisomatic excitatory inputs delivered throughout the inter-spike interval advance the phase of the spontaneous spike cycle yielding a type I PRC. In contrast, we demonstrate that distal dendritic excitatory inputs can either delay or advance the next spike depending on whether they occur early or late in the spike cycle. We find this latter pattern of responses, summarized by a biphasic (type II) PRC, was a consequence of dendritic activation of the small conductance calcium-activated potassium current, SK. We also evaluate the spike-frequency dependence of somatic and dendritic PRC shapes, and we demonstrate the robustness of our results to variations of conductance densities, distributions, and kinetic parameters. We conclude that the distal dendrite of GP neurons embodies a distinct dynamical subsystem that could promote synchronization of pallidal networks to excitatory inputs. These results highlight the need to consider different effects of perisomatic and dendritic inputs in the control of network behavior.

The globus pallidus (GP) predominantly contains GABAergic projection neurons that occupy a central position in the indirect pathway of the basal ganglia. They have long dendrites that can extend through half the diameter of the GP in rats, potentially enabling convergence and interaction between segregated basal ganglia circuits. Because of the length and fine diameter of GP dendrites, however, it is unclear how much influence distal synapses have on spiking activity. Dendritic expression of fast voltage-dependent Na+ channels (NaF channels) can enhance the importance of distal excitatory synapses by allowing for dendritic spike initiation and by subthreshold boosting of EPSPs. Antibody labeling has demonstrated the presence of NaF channel proteins in GP dendrites but the quantitative expression density of the channels remains unknown. We built a series of 9 GP neuron models that differed only in their dendritic NaF channel expression level to assess the functional impact of this parameter. The models were all similar in their basic electrophysiological features; however, higher expression levels of dendritic NaF channels increased the relative effectiveness of distal inputs for both excitatory and inhibitory synapses, broadening the effective extent of the dendritic tree. Higher dendritic NaF channel expression also made the neurons more resistant to tonic inhibition and highly sensitive to clustered synchronous excitation. The dendritic NaF channel expression pattern may therefore be a critical determinant of convergence for both the striatopallidal and subthalamopallidal projections, while also dictating which spatiotemporal input patterns are most effective at driving GP neuron output.