bims-climfi Biomed news
on Cerebellar cortical circuitry
Issue of 2018‒12‒23
two papers selected by
Jun Maruta
Mount Sinai Health System


  1. Front Neuroinform. 2018 ;12 88
    Geminiani A, Casellato C, Locatelli F, Prestori F, Pedrocchi A, D'Angelo E.
      Brain neurons exhibit complex electroresponsive properties - including intrinsic subthreshold oscillations and pacemaking, resonance and phase-reset - which are thought to play a critical role in controlling neural network dynamics. Although these properties emerge from detailed representations of molecular-level mechanisms in "realistic" models, they cannot usually be generated by simplified neuronal models (although these may show spike-frequency adaptation and bursting). We report here that this whole set of properties can be generated by the extended generalized leaky integrate-and-fire (E-GLIF) neuron model. E-GLIF derives from the GLIF model family and is therefore mono-compartmental, keeps the limited computational load typical of a linear low-dimensional system, admits analytical solutions and can be tuned through gradient-descent algorithms. Importantly, E-GLIF is designed to maintain a correspondence between model parameters and neuronal membrane mechanisms through a minimum set of equations. In order to test its potential, E-GLIF was used to model a specific neuron showing rich and complex electroresponsiveness, the cerebellar Golgi cell, and was validated against experimental electrophysiological data recorded from Golgi cells in acute cerebellar slices. During simulations, E-GLIF was activated by stimulus patterns, including current steps and synaptic inputs, identical to those used for the experiments. The results demonstrate that E-GLIF can reproduce the whole set of complex neuronal dynamics typical of these neurons - including intensity-frequency curves, spike-frequency adaptation, post-inhibitory rebound bursting, spontaneous subthreshold oscillations, resonance, and phase-reset - providing a new effective tool to investigate brain dynamics in large-scale simulations.
    Keywords:  Golgi cell; cerebellum; leaky integrate-and-fire; model simplification; neuronal electroresponsiveness; neuronal modeling; point neuron
    DOI:  https://doi.org/10.3389/fninf.2018.00088
  2. Elife. 2018 Dec 18. pii: e38852. [Epub ahead of print]7
    Romano V, De Propris L, Bosman LW, Warnaar P, Ten Brinke MM, Lindeman S, Ju C, Velauthapillai A, Spanke JK, Middendorp Guerra E, Hoogland TM, Negrello M, D Angelo E, De Zeeuw CI.
      Cerebellar plasticity underlies motor learning. However, how the cerebellum operates to enable learned changes in motor output is largely unknown. We developed a sensory-driven adaptation protocol for reflexive whisker protraction and recorded Purkinje cell activity from crus 1 and 2 of awake mice. Before training, simple spikes of individual Purkinje cells correlated during reflexive protraction with the whisker position without lead or lag. After training, simple spikes and whisker protractions were both enhanced with the spiking activity now leading behavioral responses. Neuronal and behavioral changes did not occur in two cell-specific mouse models with impaired long-term potentiation at their parallel fiber to Purkinje cell synapses. Consistent with cerebellar plasticity rules, increased simple spike activity was prominent in cells with low complex spike response probability. Thus, potentiation at parallel fiber to Purkinje cell synapses may contribute to reflex adaptation and enable expression of cerebellar learning through increases in simple spike activity.
    Keywords:  mouse; neuroscience
    DOI:  https://doi.org/10.7554/eLife.38852