Faculty Bibliography

BACKGROUND:Transcranial electrical stimulation (tES) shows promise to treat neurological disorders. Knowledge of how the orthogonal components of the electric field (E-field) alter neuronal activity is required for strategic placement of transcranial electrodes. Yet, essentially no information exists on this relationship for mammalian cerebellum in vivo, despite the cerebellum being a target for clinical tES studies. OBJECTIVE:/Hypothesis: To characterize how cerebellar Purkinje cell (PC) activity varies with the intensity, frequency, and direction of applied AC and DC E-fields. METHODS:Extracellular recordings were obtained from vermis lobule 7 PCs in anesthetized rats. AC (2-100 Hz) or DC E-fields were generated in a range of intensities (0.75-30 mV/mm) in three orthogonal directions. Field-evoked PC simple spike activity was characterized in terms of firing rate modulation and phase-locking as a function of these parameters. t-tests were used for statistical comparisons. RESULTS:The effect of applied E-fields was direction and intensity dependent, with rostrocaudally directed fields causing stronger modulations than dorsoventral fields and mediolaterally directed ones causing little to no effect, on average. The directionality dependent modulation suggests that PC is the primary cell type affected the most by electric stimulation, and this effect was probably given rise by a large dendritic tree and a soma. AC stimulation entrained activity in a frequency dependent manner, with stronger phase-locking to the stimulus cycle at higher frequencies. DC fields produced a modulation consisting of strong transients at current onset and offset with an intervening plateau. CONCLUSION/CONCLUSIONS:(s): Orientation of the exogenous E-field critically determines the modulation depth of cerebellar cortical output. With properly oriented fields, PC simple spike activity can strongly be entrained by AC fields, overriding the spontaneous firing pattern.

We previously proposed, on theoretical grounds, that the cerebellum must regulate the dimensionality of its neuronal activity during motor learning and control to cope with the low firing frequency of inferior olive neurons, which form one of two major inputs to the cerebellar cortex. Such dimensionality regulation is possible via modulation of electrical coupling through the gap junctions between inferior olive neurons by inhibitory GABAergic synapses. In addition, we previously showed in simulations that intermediate coupling strengths induce chaotic firing of inferior olive neurons and increase their information carrying capacity. However, there is no in vivo experimental data supporting these two theoretical predictions. Here, we computed the levels of synchrony, dimensionality, and chaos of the inferior olive code by analyzing in vivo recordings of Purkinje cell complex spike activity in three different coupling conditions: carbenoxolone (gap junctions blocker), control, and picrotoxin (GABA-A receptor antagonist). To examine the effect of electrical coupling on dimensionality and chaotic dynamics, we first determined the physiological range of effective coupling strengths between inferior olive neurons in the three conditions using a combination of a biophysical network model of the inferior olive and a novel Bayesian model averaging approach. We found that effective coupling co-varied with synchrony and was inversely related to the dimensionality of inferior olive firing dynamics, as measured via a principal component analysis of the spike trains in each condition. Furthermore, for both the model and the data, we found an inverted U-shaped relationship between coupling strengths and complexity entropy, a measure of chaos for spiking neural data. These results are consistent with our hypothesis according to which electrical coupling regulates the dimensionality and the complexity in the inferior olive neurons in order to optimize both motor learning and control of high dimensional motor systems by the cerebellum.

Tremor is the most common movement disorder; however, we are just beginning to understand the brain circuitry that generates tremor. Various neuroimaging, neuropathological, and physiological studies in human tremor disorders have been performed to further our knowledge of tremor. But, the causal relationship between these observations and tremor is usually difficult to establish and detailed mechanisms are not sufficiently studied. To overcome these obstacles, animal models can provide an important means to look into human tremor disorders. In this manuscript, we will discuss the use of different species of animals (mice, rats, fruit flies, pigs, and monkeys) to model human tremor disorders. Several ways to manipulate the brain circuitry and physiology in these animal models (pharmacology, genetics, and lesioning) will also be discussed. Finally, we will discuss how these animal models can help us to gain knowledge of the pathophysiology of human tremor disorders, which could serve as a platform towards developing novel therapies for tremor.

The rules governing cerebellar output are not fully understood, but must involve Purkinje cell (PC) activity, as PCs are the major input to deep cerebellar nuclear (DCN) cells (which form the majority of cerebellar output). Here, the influence of PC complex spikes (CSs) was investigated by simultaneously recording DCN activity with CSs from PC arrays in anesthetized rats. Crosscorrelograms were used to identify PCs that were presynaptic to recorded DCN cells (presynaptic PCs). Such PCs were located within rostrocaudal cortical strips and displayed synchronous CS activity. CS-associated modulation of DCN activity included a short-latency post-CS inhibition and long-latency excitations before and after the CS. The amplitudes of the post-CS responses correlated with the level of synchronization among presynaptic PCs. A temporal precision of ≤10 ms was generally required for CSs to be maximally effective. The results suggest that CS synchrony is a key control parameter of cerebellar output.

The multielectrode technique described here was developed for simultaneously recording complex spike activity from arrays of Purkinje cells in anesthetized rodents. The technique involves placing a platform on the surface of the brain and implanting microelectrodes through this platform, which then serves to hold the individual electrodes in place and to protect the brain surface. With this technique, stable recordings of complex spike activity for over 24 h have been achieved. Typical arrays consist of ~40 electrodes that are arranged as a 4 x 10 matrix with electrodes spaced by ~250 mum; however, denser and larger arrays are possible. The technique was designed for recording complex spike activity in anesthetized animals. However, it has also been successfully used to record Purkinje cell simple spikes and activity from other neurons. Moreover, it is possible to use this approach with awake, head-fixed animals performing behavioral tasks.

Purkinje cells (PCs) generate two types of action potentials, called simple and complex spikes (SSs and CSs). We first investigated the CS-associated modulation of SS activity and its relationship to the zebrin status of the PC. The modulation pattern consisted of a pre-CS rise in SS activity, and then, following the CS, a pause, a rebound, and finally a late inhibition of SS activity for both zebrin positive (Z+) and negative (Z-) cells, though the amplitudes of the phases were larger in Z+ cells. Moreover, the amplitudes of the pre-CS rise with the late inhibitory phase of the modulation were correlated across PCs. In contrast, correlations between modulation phases across CSs of individual PCs were generally weak. Next, the relationship between CS spikelets and SS activity was investigated. The number of spikelets/CS correlated with the average SS firing rate only for Z+ cells. In contrast, correlations across CSs between spikelet numbers and the amplitudes of the SS modulation phases were generally weak. Division of spikelets into likely axonally propagated and non-propagated groups (based on their interspikelet interval) showed that the correlation of spikelet number with SS firing rate primarily reflected a relationship with non-propagated spikelets. In sum, the results show that both zebrin-related and non-zebrin-related physiological heterogeneity in SS-CS interactions among PCs, which suggests that the cerebellar cortex is more functionally diverse than is assumed by standard theories of cerebellar function

For many decades, the predominant view in the cerebellar field has been that the olivocerebellar system's primary function is to induce plasticity in the cerebellar cortex, specifically, at the parallel fiber-Purkinje cell synapse. However, it has also long been proposed that the olivocerebellar system participates directly in motor control by helping to shape ongoing motor commands being issued by the cerebellum. Evidence consistent with both hypotheses exists; however, they are often investigated as mutually exclusive alternatives. In contrast, here, we take the perspective that the olivocerebellar system can contribute to both the motor learning and motor control functions of the cerebellum and might also play a role in development. We then consider the potential problems and benefits of it having multiple functions. Moreover, we discuss how its distinctive characteristics (e.g., low firing rates, synchronization, and variable complex spike waveforms) make it more or less suitable for one or the other of these functions, and why having multiple functions makes sense from an evolutionary perspective. We did not attempt to reach a consensus on the specific role(s) the olivocerebellar system plays in different types of movements, as that will ultimately be determined experimentally; however, collectively, the various contributions highlight the flexibility of the olivocerebellar system, and thereby suggest that it has the potential to act in both the motor learning and motor control functions of the cerebellum.

Purkinje cells are central to cerebellar function as they form the sole output of the cerebellar cortex. They exhibit two distinct types of action potential: simple spikes and complex spikes, and it is widely accepted that interaction between these two types of impulse is central to cerebellar cortical information processing. Previous investigations of the interactions between simple spikes and complex spikes have mainly considered complex spikes as unitary events. However, complex spikes are composed of an initial large spike followed by a number of secondary components, termed spikelets. The number of spikelets within individual complex spikes is highly variable and the extent to which differences in complex spike spikelet number affects simple spike activity (and vice versa) remains poorly understood. In anaesthetized adult rats we have found that Purkinje cells recorded from the posterior lobe vermis and hemisphere that have high simple spike firing frequencies precede complex spikes with greater numbers of spikelets. This finding was also evident in a small sample of Purkinje cells recorded from the posterior lobe hemisphere in awake cats. In addition, complex spikes with a greater number of spikelets were associated with a subsequent reduction in simple spike firing rate. We therefore suggest that one important function of spikelets is the modulation of Purkinje cell simple spike firing frequency, which has implications for controlling cerebellar cortical output and motor learning

The control of deep cerebellar nuclear (DCN) neuronal firing is central to cerebellar function but is not well understood. The large majority of synapses onto DCN neurons derive from Purkinje cells (PCs), suggesting that PC activity is an important determinant of DCN firing; however, PCs fire both simple and complex spikes (CSs), and little is known about how the latter's action affects DCN activity. Thus, here, we explored the effects of CSs on DCN activity. CSs were recorded from PC arrays along with individual DCN neurons. Presumed synaptically connected PC-DCN cell pairs were identified using CS-triggered correlograms of DCN activity, which also showed that CS activity was associated with a predominantly inhibitory effect on DCN activity. The strength of the CS effect varied as a function of synchrony, such that isolated CSs produced only weak inhibition of DCN activity, whereas highly synchronous CSs caused a larger drop in firing levels. Although the present findings were obtained in anesthetized animals, similar CS synchrony levels exist in awake animals, and changes in synchrony level have been observed in association with movements in awake animals. Thus, the present data suggest that synchronous CS activity may be a mechanism for shaping DCN output related to motor commands.