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Riccelli, T.

Publications and source records attributed to Riccelli, T..

2 recordsLinked to original sources

Multifactorial motor behavior assessment for real-time evaluation of emerging therapeutics to treat neurologic impairments

Integrating multiple assessment parameters of motor behavior is critical for understanding neural activity dynamics during motor control in both intact and dysfunctional nervous systems. Here, we described a novel approach (termed Multifactorial Behavioral Assessment (MfBA)) to integrate, in real-time, electrophysiological and biomechanical properties of rodent spinal sensorimotor network activity with behavioral aspects of motor task performance. Specifically, the MfBA simultaneously records limb kinematics, multi-directional forces and electrophysiological metrics, such as high-fidelity chronic intramuscular electromyography synchronized in time to spinal stimulation in order to characterize spinal cord functional motor evoked potentials (fMEPs). Additionally, we designed the MfBA to incorporate a body weight support system to allow bipedal and quadrupedal stepping on a treadmill and in an open field environment to assess function in rodent models of neurologic disorders that impact motor activity This novel approach was validated using, a neurologically intact cohort, a cohort with unilateral Parkinsonian motor deficits due to midbrain lesioning, and a cohort with complete hind limb paralysis due to T8 spinal cord transection. In the SCI cohort, lumbosacral epidural electrical stimulation (EES) was applied, with and without administration of the serotonergic agonist Quipazine, to enable hind limb motor functions following paralysis. The results presented herein demonstrate the MfBA is capable of integrating multiple metrics of motor activity in order to characterize relationships between EES inputs that modulate mono- and polysynaptic outputs from spinal circuitry which in turn, can be used to elucidate underlying electrophysiologic mechanisms of motor behavior by synchronizing these datasets to metrics of movement and behavior. These results also demonstrate that proposed MfBA is an effective tool to integrate biomechanical and electrophysiology metrics, synchronized to therapeutic inputs such as EES or pharmacology, during body weight supported treadmill or open field motor activities, to target a high range of variations in motor behavior as a result of neurological deficit at the different levels of CNS.

neuroscience↗

A circuit motif in the songbird basal ganglia for computing predicted performance quality

Ventral tegmental area (VTA) dopamine neurons signal prediction error, the difference between actual and predicted outcome, but it remains unclear how error is computed. Here we identify in songbirds a ventral basal ganglia (vBG) region that is required for song learning and that sends prediction error signals to VTA. During singing, vBG neurons heterogeneously encoded song timing, auditory error, predicted error, and the difference between the two (prediction error). Viral tracing revealed inputs to vBG from auditory and vocal motor thalamus, auditory and vocal motor cortex, and VTA. Our findings reveal a classic actor-critic circuit motif in which a ventral critic learns the prediction component of a prediction error signal that is relayed by VTA to a dorsal actor (the vocal motor BG nucleus Area X). A circuit motif for computing reward prediction error can compute predicted performance quality during motor sequence learning.

neuroscience↗