Eilon Vaadia

Physiological aspects of information processing in the basal ganglia of normal and parkinsonian primates

There are two views as to the character of basal-ganglia processing - processing by segregated parallel circuits or by information sharing. To distinguish between these views, we studied the simultaneous activity of neurons in the output stage of the basal ganglia with cross-correlation techniques. The firing of neurons in the globus pallidus of normal monkeys is almost always uncorrelated. However, after dopamine depletion and induction of parkinsonism by treatment with 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP), oscillatory activity appeared and the firing of many neurons became correlated. We conclude that the normal dopaminergic system supports segregation of the functional subcircuits of the basal ganglia, and that a breakdown of this independent processing is a hallmark of Parkinsons disease.

Firing Patterns and Correlations of Spontaneous Discharge of Pallidal Neurons in the Normal and the Tremulous 1-Methyl-4- Phenyl-1,2,3,6-Tetrahydropyridine Vervet Model of Parkinsonism

To investigate the role of the basal ganglia in parkinsonian tremor, we recorded hand tremor and simultaneous activity of several neurons in the external and internal segments of the globus pallidus (GPe and GPi) in two vervet monkeys, before and after systemic treatment with 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP) and development of parkinsonism with tremor of 5 and 11 Hz. In healthy monkeys, only 11% (20/174) of the GPe cells and 3% (1/29) of the GPi cells displayed significant 3–19 Hz oscillations. After MPTP treatment, 39% (107/271) of the GPe cells and 43% (26/61) of the GPi cells developed significant oscillations. Oscillation frequencies of single cells after MPTP treatment were bimodally distributed around 7 and 13 Hz. For 10% of the oscillatory cells that were recorded during tremor periods, there was a significant tendency for the tremor and neuronal oscillations to appear simultaneously. Cross-correlation analysis revealed a very low level of correlated activity between pallidal neurons in the normal state; 95.6% (477/499) of the pairs were not correlated, and oscillatory cross-correlograms were found in only 1% (5/499) of the pairs. After MPTP treatment, the correlations increased dramatically, and 40% (432/1080) of the cross-correlograms had significant oscillations, centered around 13–14 Hz. Phase shifts of the cross-correlograms of GPe pairs, but not of GPi, were clustered around 0°. The results illustrate that MPTP treatment changes the pattern of activity and synchronization in the GPe and GPi. These changes are related to the symptoms of Parkinsons disease and especially to the parkinsonian tremor.

Closed-Loop Deep Brain Stimulation Is Superior in Ameliorating Parkinsonism

Continuous high-frequency deep brain stimulation (DBS) is a widely used therapy for advanced Parkinsons disease (PD) management. However, the mechanisms underlying DBS effects remain enigmatic and are the subject of an ongoing debate. Here, we present and test a closed-loop stimulation strategy for PD in the 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP) primate model of PD. Application of pallidal closed-loop stimulation leads to dissociation between changes in basal ganglia (BG) discharge rates and patterns, providing insights into PD pathophysiology. Furthermore, cortico-pallidal closed-loop stimulation has a significantly greater effect on akinesia and on cortical and pallidal discharge patterns than standard open-loop DBS and matched control stimulation paradigms. Thus, closed-loop DBS paradigms, by modulating pathological oscillatory activity rather than the discharge rate of the BG-cortical networks, may afford more effective management of advanced PD. Such strategies have the potential to be effective in additional brain disorders in which a pathological neuronal discharge pattern can be recognized.

Inference of hand movements from local field potentials in monkey motor cortex.

The spiking of neuronal populations in motor cortex provides accurate information about movement parameters. Here we show that hand movement target and velocity can be inferred from multiple local field potentials (LFPs) in single trials approximately as efficiently as from multiple single-unit activity (SUA) recorded from the same electrodes. Our results indicate that LFPs can be used as an additional signal for decoding brain activity, particularly for new neuroprosthetic applications.

Midbrain dopamine neurons encode decisions for future action

Current models of the basal ganglia and dopamine neurons emphasize their role in reinforcement learning. However, the role of dopamine neurons in decision making is still unclear. We recorded from dopamine neurons in monkeys engaged in two types of trial: reference trials in an instructed-choice task and decision trials in a two-armed bandit decision task. We show that the activity of dopamine neurons in the decision setting is modulated according to the value of the upcoming action. Moreover, analysis of the probability matching strategy in the decision trials revealed that the dopamine population activity and not the reward during reference trials determines choice behavior. Because dopamine neurons do not have spatial or motor properties, we conclude that immediate decisions are likely to be generated elsewhere and conveyed to the dopamine neurons, which play a role in shaping long-term decision policy through dynamic modulation of the efficacy of basal ganglia synapses.

Encoding of Movement Direction in Different Frequency Ranges of Motor Cortical Local Field Potentials

Recent studies showed that the low-frequency component of local field potentials (LFPs) in monkey motor cortex carries information about parameters of voluntary arm movements. Here, we studied how different signal components of the LFP in the time and frequency domains are modulated during center-out arm movements. Analysis of LFPs in the time domain showed that the amplitude of a slow complex waveform beginning shortly before the onset of arm movement is modulated with the direction of the movement. Examining LFPs in the frequency domain, we found that direction-dependent modulations occur in three frequency ranges, which typically increased their amplitudes before and during movement execution: ≤4, 6–13, and 63–200 Hz. Cosine-like tuning was prominent in all signal components analyzed. In contrast, activity in a frequency band ≈30 Hz was not modulated with the direction of movement and typically decreased its amplitude during the task. This suggests that high-frequency oscillations have to be divided into at least two functionally different regimes: one ≈30 Hz and one >60 Hz. Furthermore, using multiple LFPs, we could show that LFP amplitude spectra can be used to decode movement direction, with the best performance achieved by the combination of different frequency ranges. These results suggest that using the different frequency components in the LFP is useful in improving inference of movement parameters from local field potentials.

Primary motor cortex is involved in bimanual coordination

Many voluntary movements involve coordination between the limbs,. However, there have been very few attempts to study the neuronal mechanisms that mediate this coordination. Here we have studied the activity of cortical neurons while monkeys performed tasks that required coordination between the two arms. We found that most neurons in the primary motor cortex (MI) show activity specific to bimanual movements (bimanual-related activity), which is strikingly different from the activity of the same neurons during unimanual movements. Moreover, units in the supplementary motor area (SMA; the area of cortex most often associated with bimanual coordination) showed no more bimanual-related activity than units in MI. Our results challenge the classic view that MI controls the contralateral (opposite) side of the body and that SMA is responsible for the coordination of the arms. Rather, our data suggest that both cortical areas share the control of bilateral coordination.

Midbrain Dopaminergic Neurons and Striatal Cholinergic Interneurons Encode the Difference between Reward and Aversive Events at Different Epochs of Probabilistic Classical Conditioning Trials

Midbrain dopaminergic neurons (DANs) typically increase their discharge rate in response to appetitive predictive cues and outcomes, whereas striatal cholinergic tonically active interneurons (TANs) decrease their rate. This may indicate that the activity of TANs and DANs is negatively correlated and that TANs can broaden the basal ganglia reinforcement teaching signal, for instance by encoding worse than predicted events. We studied the activity of 106 DANs and 180 TANs of two monkeys recorded during the performance of a classical conditioning task with cues predicting the probability of food, neutral, and air puff outcomes. DANs responded to all cues with elevations of discharge rate, whereas TANs depressed their discharge rate. Nevertheless, although dopaminergic responses to appetitive cues were larger than their responses to neutral or aversive cues, the TAN responses were more similar. Both TANs and DANs responded faster to an air puff than to a food outcome; however, DANs responded with a discharge elevation, whereas the TAN responses included major negative and positive deflections. Finally, food versus air puff omission was better encoded by TANs. In terms of the activity of single neurons with distinct responses to the different behavioral events, both DANs and TANs were more strongly modulated by reward than by aversive related events and better reflected the probability of reward than aversive outcome. Thus, TANs and DANs encode the task episodes differentially. The DANs encode mainly the cue and outcome delivery, whereas the TANs mainly encode outcome delivery and omission at termination of the behavioral trial episode.

Preparatory activity in motor cortex reflects learning of local visuomotor skills

In humans, learning to produce correct visually guided movements to adapt to new sensorimotor conditions requires the formation of an internal model that represents the new transformation between visual input and the required motor command. When the new environment requires adaptation to directional errors, learning generalizes poorly to untrained locations and directions, indicating that such learning is local. Here we replicated these behavioral findings in rhesus monkeys using a visuomotor rotation task and simultaneously recorded neuronal activity. Specific changes in activity were observed only in a subpopulation of cells in the motor cortex with directional properties corresponding to the locally learned rotation. These changes adhered to the dynamics of behavior during learning and persisted between learning and relearning of the same rotation. These findings suggest a neural mechanism for the locality of newly acquired sensorimotor tasks and provide electrophysiological evidence for their retention in working memory.

Spike Synchronization in the Cortex-Basal Ganglia Networks of Parkinsonian Primates Reflects Global Dynamics of the Local Field Potentials

Cortical local field potentials (LFPs) reflect synaptic potentials and accordingly correlate with neuronal discharge. Because LFPs are coherent across substantial cortical areas, we hypothesized that cortical spike correlations could be predicted from them. Because LFPs recorded in the basal ganglia (BG) are also correlated with neuronal discharge and are clinically accessible in Parkinsons disease patients, we were interested in testing this hypothesis in the BG, as well. We recorded LFPs and unit discharge from multiple electrodes, which were placed in primary motor cortex or in the basal ganglia (striatum and pallidum) of two monkeys before and after rendering them parkinsonian with 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine. We used the method of partial spectra to construct LFP predictors of the spike cross-correlation functions (CCFs). The predicted CCF is an estimate of the correlation between two neurons under the assumption that their association is explained solely by the association of each with the LFP recorded on a third electrode. In the normal condition, the predictors account for cortical rate covariations but not for the association among the tonically active neurons of the striatum. In the parkinsonian condition, with the appearance of 10 Hz oscillations throughout the cortex-basal ganglia networks, the LFP predictors account remarkably better for the CCFs in both the cortex and the basal ganglia. We propose that, in the parkinsonian condition, the cortex-basal ganglia networks are more tightly related to global modes of brain dynamics that are echoed in the LFP.