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Leventhal, D.

Publications and source records attributed to Leventhal, D..

3 recordsLinked to original sources

Precisely-timed dopamine signals establish distinct kinematic representations of skilled movements

Brain dopamine is critical for normal motor control, as evidenced by its importance in Parkinson Disease and related disorders. Current hypotheses are that dopamine influences motor control by "invigorating" movements and regulating motor learning. Most evidence for these aspects of dopamine function comes from simple tasks (e.g., lever pressing). Therefore, the influence of dopamine on motor skills requiring multi-joint coordination is unknown. To determine the effects of precisely-timed dopamine manipulations on the performance of a complex, finely coordinated dexterous skill, we optogenetically stimulated or inhibited midbrain dopamine neurons as rats performed a skilled reaching task. We found that reach kinematics and coordination between gross and fine movements progressively changed with repeated manipulations. However, once established, rats transitioned abruptly between aberrant and baseline reach kinematics in a dopamine-dependent manner. These results suggest that precisely-timed dopamine signals have immediate and long-term influences on motor skill performance, distinct from simply "invigorating" movement.

neuroscience↗

Interactions between motor thalamic field potentials and single unit spiking predict behavior in rats

The thalamus plays a central role in generating circuit-level neural oscillations believed to coordinate brain activity over large spatiotemporal scales. Such thalamic influences are well-documented for sleep rhythms and in sensory systems, but the relationship between thalamic activity, motor circuit local field potential (LFP) oscillations, and behavior is unknown. We recorded wideband motor thalamic (Mthal) electrophysiology as healthy rats performed a two-alternative forced choice task. The power of delta (1-4 Hz), beta (13-30 Hz), low gamma (30-70 Hz), and high gamma (70-200 Hz) oscillations were strongly modulated by task performance. As in cortex, delta phase predicted beta/low gamma power and reaction time. Furthermore, delta phase differentially predicted spike timing in functionally distinct populations of Mthal neurons, which also predicted task performance and beta power. These complex relationships suggest mechanisms for commonly observed LFP-LFP and spike-LFP interactions, as well as subcortical influences on motor output.

neuroscience↗

Sensorimotor Processing In The Basal Ganglia Leads To Transient Beta Oscillations During Behavior

Brief epochs of beta oscillations have been implicated in sensorimotor control in the basal ganglia of task-performing healthy animals. However, which neural processes underlie their generation and how they are affected by sensorimotor processing remains unclear. To determine the mechanisms underlying transient beta oscillations in the local field potential (LFP), we combined computational modeling of the subthalamo-pallidal network for the generation of beta oscillations with realistic stimulation patterns derived from single unit data. The single unit data were recorded from different basal ganglia subregions in rats performing a cued choice task. In the recordings we found distinct firing patterns in the striatum, globus pallidus and subthalamic nucleus related to sensory and motor events during the behavioral task. Using these firing patterns to generate realistic inputs to our network model lead to transient beta oscillations with the same time course as the rat LFP data. In addition, our model can account for further non-intuitive aspects of beta modulation, including beta phase resets following sensory cues and correlations with reaction time. Overall, our model can explain how the combination of temporally regulated sensory responses of the subthalamic nucleus, ramping activity of the subthalamic nucleus, and movement-related activity of the globus pallidus, leads to transient beta oscillations during behavior.\n\nSignificance StatementTransient beta oscillations emerge in the normal functioning cortico-basal ganglia loop during behavior. In this work we employ a unique approach connecting a computational model closely with experimental data. In this way we achieve a simulation environment for our model that mimics natural input patterns in awake behaving animals. Using this approach we demonstrate that a computational model for beta oscillations in Parkinsons disease can also account for complex patterns of transient beta oscillations in healthy animals. Therefore, we propose that transient beta oscillations in healthy animals share the same mechanism with pathological beta oscillations in Parkinsons disease. This important result connects functional and pathological roles of beta oscillations in the basal ganglia.

neuroscience↗