A parallel neuronal network architecture ensures control of basic feeding reflex circuits via integration of crossmodal sensory information to filter multiple biological events and enhance meaningful behavioral choice.
Inspired by the sparse, sequential neural activity patterns observed in striatum, a new circuit model implements variable-speed activity, the encoding of multiple sequences, and a tutor/student relationship between cortex and striatum.
Emerging evidence suggests a broad role for cerebellar circuits in generating and testing predictions about movement, reward, and diverse cognitive processes.
Quantitative analysis of behavior coupled with computational modeling reveal the set of circuit-level principles that underlie cerebellar-dependent motor learning in smooth pursuit eye movements of monkeys across timescales.
Neuronal participation in generation of motor patterns in the spinal circuits is lognormal, which is an indication of a rich diversity of activity within the mean-driven as well as the fluctuation-driven regimes.
By demonstrating song learning-related synaptic strengthening and pruning in the vocal control circuits of songbirds, and showing how such changes can reduce the sensitivity of the circuit to ‘noisy’ inputs, a simple neural circuit mechanism for regulating motor variability during motor skill learning is identified.
Fly protein families Dprs and DIPs can create a multitude of complementary interfaces for homo- and heterophilic adhesion complexes, resulting in instructive roles for connectivity in the motor neuron circuitry.
Systematic analysis of descending neuron anatomy reveals the basic functional map of descending sensory-motor pathways in flies and provides genetic tools for targeted interrogation of neural circuits.
The neuromodulator acetylcholine contributes to state-dependent modulation of motor vigor and variability by direct action on songbird premotor cortex, bypassing basal ganglia circuitry.
