Abstract
The way the cerebellar granular layer transforms incoming mossy fiber signals into new spike patterns to be related to Purkinje cells is not yet clear. Here, a realistic computational model of the granular layer was developed and used to address four main functional hypotheses: center-surround organization, time-windowing, high-pass filtering in responses to spike bursts and coherent oscillations in response to diffuse random activity. The model network was activated using patterns inspired by those recorded in vivo. Burst stimulation of a small mossy fiber bundle resulted in granule cell bursts delimited in time (time windowing) and space (center-surround) by network inhibition. This burst–burst transmission showed marked frequency-dependence configuring a high-pass filter with cut-off frequency around 100 Hz. The contrast between center and surround properties was regulated by the excitatory–inhibitory balance. The stronger excitation made the center more responsive to 10–50 Hz input frequencies and enhanced the granule cell output (with spikes occurring earlier and with higher frequency and number) compared to the surround. Finally, over a certain level of mossy fiber background activity, the circuit generated coherent oscillations in the theta-frequency band. All these processes were fine-tuned by NMDA and GABA-A receptor activation and neurotransmitter vesicle cycling in the cerebellar glomeruli. This model shows that available knowledge on cellular mechanisms is sufficient to unify the main functional hypotheses on the cerebellum granular layer and suggests that this network can behave as an adaptable spatio-temporal filter coordinated by theta-frequency oscillations.
Highlights
The cerebellum, owing to its regular structure, has inspired several theoretical models emphasizing the combinatorial properties of the network (Marr, 1969; Albus, 1971; Tyrrell and Willshaw, 1992; Dean et al, 2010)
RESPONSE OF SINGLE granule cell (GrC) AND Golgi cell (GoC) EMBEDDED INTO THE GRANULAR LAYER NETWORK Once embedded into the network, single neurons receive a continuous barrage of excitatory and inhibitory synaptic inputs driven by network-dependent activity
The intrinsic responsiveness and synaptic activation of single GrCs and GoCs was assessed in model neurons embedded into the simulated granular layer network (Figures 2–4), which generated a continuous background activity
Summary
The cerebellum, owing to its regular structure, has inspired several theoretical models emphasizing the combinatorial properties of the network (Marr, 1969; Albus, 1971; Tyrrell and Willshaw, 1992; Dean et al, 2010). Simplified spiking models have been developed (Maex and De Schutter, 1998; Medina and Mauk, 2000). By taking advantage of recent advances in single cell and granular layer circuit physiology, a new computational model is developed that incorporates a much higher level of realism than previously possible. The model has been used to investigate granular layer spatio-temporal dynamics and evaluate the main functional hypotheses suggested by biological investigations. Recordings in vivo have shown the behavior of single granular
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