Complex dynamics in simplified neuronal models: reproducing Golgi cell electroresponsiveness

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

Modeling the Cerebellar Microcircuit: New Strategies for a Long-Standing Issue

The cerebellar microcircuit has been the work bench for theoretical and computational modeling since the beginning of neuroscientific research. The regular neural architecture of the cerebellum inspired different solutions to the long-standing issue of how its circuitry could control motor learning and coordination. Originally, the cerebellar network was modeled using a statistical-topological approach that was later extended by considering the geometrical organization of local microcircuits. However, with the advancement in anatomical and physiological investigations, new discoveries have revealed an unexpected richness of connections, neuronal dynamics and plasticity, calling for a change in modeling strategies, so as to include the multitude of elementary aspects of the network into an integrated and easily updatable computational framework. Recently, biophysically accurate realistic models using a bottom-up strategy accounted for both detailed connectivity and neuronal non-linear membrane dynamics. In this perspective review, we will consider the state of the art and discuss how these initial efforts could be further improved. Moreover, we will consider how embodied neurorobotic models including spiking cerebellar networks could help explaining the role and interplay of distributed forms of plasticity. We envisage that realistic modeling, combined with closed-loop simulations, will help to capture the essence of cerebellar computations and could eventually be applied to neurological diseases and neurorobotic control systems

Gating of Long-Term Potentiation by Nicotinic Acetylcholine Receptors at the Cerebellum Input Stage

The brain needs mechanisms able to correlate plastic changes with local circuit activity and internal functional states. At the cerebellum input stage, uncontrolled induction of long-term potentiation or depression (LTP or LTD) between mossy fibres and granule cells can saturate synaptic capacity and impair cerebellar functioning, which suggests that neuromodulators are required to gate plasticity processes. Cholinergic systems innervating the cerebellum are thought to enhance procedural learning and memory. Here we show that a specific subtype of acetylcholine receptors, the α7-nAChRs, are distributed both in cerebellar mossy fibre terminals and granule cell dendrites and contribute substantially to synaptic regulation. Selective α7-nAChR activation enhances the postsynaptic calcium increase, allowing weak mossy fibre bursts, which would otherwise cause LTD, to generate robust LTP. The local microperfusion of α7-nAChR agonists could also lead to in vivo switching of LTD to LTP following sensory stimulation of the whisker pad. In the cerebellar flocculus, α7-nAChR pharmacological activation impaired vestibulo-ocular-reflex adaptation, probably because LTP was saturated, preventing the fine adjustment of synaptic weights. These results show that gating mechanisms mediated by specific subtypes of nicotinic receptors are required to control the LTD/LTP balance at the mossy fibre-granule cell relay in order to regulate cerebellar plasticity and behavioural adaptation

Cooperative coincidence detectors control mixed pre-and postsynaptic expression of spike-timing dependent plasticity at the cerebellar input stage

Excitatory central synapses show a special form of persistent change, spike-timing dependent plasticity (STDP), in which long-term potentiation and depression (LTP and LTD) are related to the relative phase of occurrence of EPSPs and action potentials. At the cerebellar mossy fiber - granule cell synapse, LTP and LTD have been previously related to the duration and frequency of input busts but their EPSP-spike phase sensitivity was unknown. Here we show that EPSP-spike pairing on the 6 Hz band can reliably induce STDP in this synapse. LTP was confined to the +5/+20 ms time-window, while LTD occurred at longer positive phases and at negative phases revealing a high temporal precision for LTP induction. STDP as a whole required NMDA receptor activation and calcium release from intracellular stores, but LTP also required mGluR activation and higher calcium levels. Importantly, STDP was 2–3 times larger than any forms of long-term synaptic plasticity previously reported at this same synapse (LTP:+61.4 % ± 20.2 %, n = 5, t < 0.05; LTD:-50.6 % ± 12.6 %, n = 5, t < 0.05). While LTP and LTD induced by modulated burst duration and frequency were uniquely expressed by a release probability change, STDP showed a mixed pre- and postsynaptic expression attested by consistent changes in EPSC amplitude and coefficient of variation, EPSC paired-pulse ratio (PPR; LTP:-32.3 % ± 4.9 %, n = 5, t < 0.001; LTD:+21.0 % ± 14.9 %, n = 5, t < 0.05) and minis amplitude (LTP:+23.4 % ± 9.9 %, n = 5, t < 0.05; LTD:-16.1 % ± 5.2 %, n = 5, t < 0.05) and frequency (LTP:+18.1 % ± 8.7 %, n = 5, t < 0.05; LTD:-30.7 % ± 8.6 %, n = 5, t < 0.05). Therefore STDP appears a powerful form of plasticity that binds LTP to the mossy fiber burst phase on the millisecond time-scale and could control granular layer functions binding it tightly to ongoing brain temporal dynamics

Hebbian spike-timing dependent plasticity at the cerebellar input stage

Spike-timing-dependent plasticity (STDP) is a form of long-term synaptic plasticity exploiting the time relationship between postsynaptic action potentials (APs) and EPSPs. Surprisingly enough, very little was known about STDP in the cerebellum, although it is thought to play a critical role for learning appropriate timing of actions. We speculated that low-frequency oscillations observed in the granular layer may provide a reference for repetitive EPSP/AP phase coupling. Here we show that EPSP-spike pairing at 6 Hz can optimally induce STDP at the mossy fiber-granule cell synapse in rats. Spike timing-dependent long-term potentiation and depression (st-LTP and st-LTD) were confined to a ±25 ms time-window. Because EPSPs led APs in st-LTP while APs led EPSPs in st-LTD, STDP was Hebbian in nature. STDP occurred at 6-10 Hz but vanished >50 Hz or <1 Hz (where only LTP or LTD occurred). STDP disappeared with randomized EPSP/AP pairing or high intracellular Ca2+ buffering, and its sign was inverted by GABA-A receptor activation. Both st-LTP and st-LTD required NMDA receptors, but st-LTP also required reinforcing signals mediated by mGluRs and intracellular calcium store

Anti-hebbian long-term synaptic plasticity at the mossy fiber- Golgi cell synapse of cerebellum

This study is focused on synaptic properties of Golgi cells (GoCs), the main inhibitory neurons of cerebellar granular layer, and the presence of long-term synaptic plasticity at the mossy fibers- Golgi cell (MFs-GoC) synapses was evaluated. GoCs are characterized by an irregular soma with a diameter of 20–40 μm from which radiate several basal dendrites, two to three apical dendrites and an extensively ramified axon [1]. The most relevant excitatory input to GoCs comes from the MFs arriving to the glomeruli, thus forming synapses on basal dendrites and allowing them to mediate feedforward inhibition (MFs→GoC→GrC). Moreover, the GoCs receives connection from GrCs principally through the PFs or, in alternative, through synapses en passant along their ascending axon, enabling a feedback inhibition (MFs→GrC→GoC→GrC). GoCs also receive inhibitory signals from molecular layer neurons [5-6]. Finally, recent studies revealed the existence of inhibitory GoC-GoC communication through gap-junctions [10]. Cerebellar inhibition results from feedback and feedforward loops shaping the temporal aspect and spatial organization of signals relayed to the molecular layer. Over the years, the cerebellum has been object of many investigations on different forms of synaptic plasticity and their mechanisms of induction, which grant a critical contribution to motor learning and have the function to regulate the overall level of activity in the cerebellar circuitry. In particular, studies revealed the existence of multiple forms of long-term plasticity in the molecular layer, granular layer and DCN, thus demonstrating that the plastic capability of the cerebellum is more complex and extended than initially expected.[2]. Therefore, considering the functional implications of GoCs for granular layer network, and the importance of plasticity at other synapses, it becomes crucial to evaluate the existence of forms of plasticity at the MF-GoC synapses

Autism and genius: is there a link? The involvement of central brain loops and hypotheses for functional testing

Mental processing is the product of the huge number of synaptic interactions that occur in the brain. It is easier to understand how brain functions can deteriorate than how they might be boosted. Lying at the border between the humanities, cognitive science and neurophysiology, some mental diseases offer new angles on this problematic issue. Despite their social deficits, autistic subjects can display unexpected and extraordinary skills in numerous fields, including music, the arts, calculation and memory. The advanced skills found in a subgroup of people with autism may be explained by their special mental functioning, in particular by their weak central coherence, one of the pivotal characteristics of the disorder. As a result of the increasing interest in autistic talent, there has recently emerged a tendency to screen any eccentric artist or scientist for traits of the autistic spectrum. Following this trend, we analyze the eccentricity of the popular pianist Glenn Gould and briefly discuss the major functional hypotheses on autistic hyperfunctioning, advancing proposals for functional testing. In particular, the potential involvement of rhythm-entrained systems and cerebro-cerebellar loops opens up new perspectives for the investigation of autistic disorders and brain hyperfunctioning

The Cerebellar Involvement in Autism Spectrum Disorders: From the Social Brain to Mouse Models

Autism spectrum disorders (ASD) are pervasive neurodevelopmental disorders that include a variety of forms and clinical phenotypes. This heterogeneity complicates the clinical and experimental approaches to ASD etiology and pathophysiology. To date, a unifying theory of these diseases is still missing. Nevertheless, the intense work of researchers and clinicians in the last decades has identified some ASD hallmarks and the primary brain areas involved. Not surprisingly, the areas that are part of the so-called &ldquo;social brain&rdquo;, and those strictly connected to them, were found to be crucial, such as the prefrontal cortex, amygdala, hippocampus, limbic system, and dopaminergic pathways. With the recent acknowledgment of the cerebellar contribution to cognitive functions and the social brain, its involvement in ASD has become unmistakable, though its extent is still to be elucidated. In most cases, significant advances were made possible by recent technological developments in structural/functional assessment of the human brain and by using mouse models of ASD. Mouse models are an invaluable tool to get insights into the molecular and cellular counterparts of the disease, acting on the specific genetic background generating ASD-like phenotype. Given the multifaceted nature of ASD and related studies, it is often difficult to navigate the literature and limit the huge content to specific questions. This review fulfills the need for an organized, clear, and state-of-the-art perspective on cerebellar involvement in ASD, from its connections to the social brain areas (which are the primary sites of ASD impairments) to the use of monogenic mouse models

J Neurophysiol 90: 2478–2483, 2003; 10.1152/jn.00399.2003. NO Enhances Presynaptic Currents During Cerebellar Mossy Fiber—

currents during cerebellar mossy fiber: granule cell LTP.