bims-climfi Biomed News
on Cerebellar cortical circuitry
Issue of 2019‒06‒30
two papers selected by
Jun Maruta
Mount Sinai Health System


  1. J Neurosci. 2019 Jun 24. pii: 0086-19. [Epub ahead of print]
    Markwalter KH, Yang Y, Holy TE, Bonni A.
      The vermal cerebellum is a hub of sensorimotor integration critical for postural control and locomotion, but the nature and developmental organization of afferent information to this region have remained poorly understood in vivo Here, we employ in vivo two-photon calcium imaging of the vermal cerebellum in awake behaving male and female mice to record granule neuron responses to diverse sensorimotor cues targeting visual, auditory, somatosensory, and motor domains. Use of an activity-independent marker revealed that approximately half (54%) of vermal granule neurons were activated during these recordings. A multi-kernel linear model distinguished the relative influences of external stimuli and co-occurring movements on neural responses, indicating that among the subset of activated granule neurons, locomotion (44-56%) and facial air puffs (50%) were more commonly and reliably encoded than visual (31-32%) and auditory (19-28%) stimuli. Strikingly, we also uncover populations of granule neurons that respond differentially to voluntary and forced locomotion whereas other granule neurons in the same region respond similarly to locomotion in both conditions. Finally, by combining two-photon calcium imaging with birthdate labeling of granule neurons via in vivo electroporation, we find that early and late born granule neurons convey similarly diverse sensorimotor information to spatially distinct regions of the molecular layer. Collectively, our findings elucidate the nature and developmental organization of sensorimotor information in vermal granule neurons of the developing mammalian brain.SIGNIFICANCE STATEMENTCerebellar granule neurons comprise over half the neurons in the brain and their coding properties have been the subject of theoretical and experimental interest for over a half-century. In this study, we directly test long-held theories about encoding of sensorimotor stimuli in the cerebellum and compare the in vivo coding properties of early and late born granule neurons. Strikingly, we identify populations of granule neurons that differentially encode voluntary and forced locomotion and find that although the birth order of granule neurons specifies the positioning of their parallel fiber axons, both early and late born granule neurons convey a functionally diverse sensorimotor code. These findings constitute important conceptual advances in understanding the principles underlying cerebellar circuit development and function.
    DOI:  https://doi.org/10.1523/JNEUROSCI.0086-19.2019
  2. Front Comput Neurosci. 2019 ;13 35
    Geminiani A, Casellato C, D'Angelo E, Pedrocchi A.
      The neurons of the olivocerebellar circuit exhibit complex electroresponsive dynamics, which are thought to play a fundamental role for network entraining, plasticity induction, signal processing, and noise filtering. In order to reproduce these properties in single-point neuron models, we have optimized the Extended-Generalized Leaky Integrate and Fire (E-GLIF) neuron through a multi-objective gradient-based algorithm targeting the desired input-output relationships. In this way, E-GLIF was tuned toward the unique input-output properties of Golgi cells, granule cells, Purkinje cells, molecular layer interneurons, deep cerebellar nuclei cells, and inferior olivary cells. E-GLIF proved able to simulate the complex cell-specific electroresponsive dynamics of the main olivocerebellar neurons including pacemaking, adaptation, bursting, post-inhibitory rebound excitation, subthreshold oscillations, resonance, and phase reset. The integration of these E-GLIF point-neuron models into olivocerebellar Spiking Neural Networks will allow to evaluate the impact of complex electroresponsive dynamics at the higher scales, up to motor behavior, in closed-loop simulations of sensorimotor tasks.
    Keywords:  neuron model simplification; neuronal electroresponsiveness; neuronal modeling; olivocerebellar neurons; point neuron
    DOI:  https://doi.org/10.3389/fncom.2019.00035