CNS 2017 Workshop Cerebellum
This is a one-day workshop at the Computational Neuroscience meeting in Antwerp, Belgium to be held on 19 July 2017: “Computational and experimental advances in cerebellum research”, organized by Erik De Schutter and Yunliang Zang.
With the improvement of experimental techniques, like in vivo patch-clamp recording and calcium imaging, we have gained a deeper understanding of information processing in the cerebellum. However, experiment driven computational modeling is still an indispensable tool to explore the implications of these findings. The purpose of this workshop is to foster an active dialogue between experimentalists and modelers about cerebellar physiology and function. Sufficient time will also be reserved to discuss how modeling and experiments can provide interesting data relevant to each other.
Both experimental and computational work at the level of cerebellar single cell and network studies are included in the workshop.
09:00 - 09:45 Arnd Roth (UCL, London, UK)
Untangling cerebellar circuits with scanning electron microscopy and focused ion beam milling.
09:45 - 10:30 Alessandro Barri (Institut Pasteur, Paris, France)
Temporal processing in the cerebellar cortex enabled by dynamical synapses.
10:30 - 11:00 Coffee Break
11:00 - 11:45 Philippe Isope (CNRS, Strasbourg, France)
How presynaptic short term dynamics influence Purkinje cell discharge in the cerebellum.
11:45 - 12:30 Mario Negrello (Erasmus MC, Rotterdam, Netherland)
The Origin of Complex Spike Synchrony.
12:30 - 14:00 Lunch
14:00 - 14:45 Ian Duguid (University of Edinburgh, Edinburgh, UK)
Purkinje cell dendritic responses during self-paced locomotion.
14:45 - 15:30 Yunliang Zang (OIST, Okinawa, Japan)
Voltage- and branch-dependent complex spike responses in Purkinje neurons.
15:30 - 16:00 Coffee Break
16:00 - 16:45 Brandon Stell (CNRS, Paris, France)
In vivo imaging of Purkinje cell simple spikes.
16:45 - 17:30 Paul Chadderton (Imperial College London, London, UK)
Cerebellar processing of kinematic signals during active whisking.
Temporal processing in the cerebellar cortex enabled by dynamical synapses
The cerebellar cortex (CC) is considered to be essential for learning precisely timed tasks on the order of tens of milliseconds to few seconds. Cerebellar adaptive filter models generally consider the CC as a three layered feed-forward network where mossy fibers (MFs) and Purkinje cells (PCs) form the input and output layer, respectively, and granule cells (GCs) constitute a hidden layer. In this framework, for PCs to learn time-varying signals it is necessary that the GC population responds to MF inputs with sufficiently diverse response time courses. It remains an open question by which mechanisms these time varying GC signals can be produced.
Recent findings have established that synaptic transmission between MFs and GCs expresses various forms of synaptic short-term plasticity (STP). Here we show that these synaptic dynamics can provide a sufficiently rich temporal modulation of GC activity to enable temporal learning by PCs on behaviorally relevant timescales. First, we re-analyzed data from MF-GC dual-cell recordings from Chabrol et al. (2015) and extracted parameters associated with pre-synaptic depression, facilitation and post-synaptic receptor desensitization. This revealed the existence of a rich reservoir of synaptic time-constants ranging from a few milliseconds to seconds.
In a second step, we used the measured synaptic parameter distributions to constrain a firing-rate-based model of the CC. In this model, GCs exhibit sharp transient firing rate modulations in response to step changes in MF activity. Due to the diversity of the synaptic parameters, GC transients exhibit a broad diversity across cells. Interestingly, during these transients the GC population is densely activated as suggested by recent in vivo recordings (Giovannucci et al. 2017). Furthermore, GC transients elicited strong modulations of model PC firing rates, similar to experimental findings (Bosman et al. 2010).
We also showed that GC firing transients form a temporal basis that is sufficient to enable PCs to encode stimulus duration and interval length, a critical requirement for short time scale auditory perception. We then took advantage of classical supervised learning to demonstrate that GC firing response diversity could also be used to teach PCs to predict delayed stimuli, as in the classical eye-blink conditioning paradigm.
Our theoretical study demonstrates that the distribution of STP at the input layer of the CC is sufficient to elicit temporal computations in a purely feed-forward manner.
How presynaptic short term dynamics influence Purkinje cell discharge in the cerebellum
Many experimental and theoretical studies have demonstrated that the balance between excitation and inhibition in neuronal networks tightly controls principal cell firing rate using simple network organization. I will present here how the granule cell - molecular interneuron - Purkinje cell pathway that controls Purkinje cell discharge can be driven by an interplay between excitatory and inhibitory short term synaptic plasticity and expand Purkinje cell dynamic range. Using a combination of electrophysiological recordings, optogenetic stimulation and modelling, we demonstrated that burst of granule cell stimulation can increase or decrease PC firing rate in a predictable manner and that the number of stimulation control the sign of the net effect. We therefore postulate that Purkinje cells encode granule cell stimulations in a precise and reliable pattern of discharge that describe a large dictionary of coding possibilities.
The Origin of Complex Spike Synchrony
The inferior olive is a center piece of the cerebellar system and is thought to produce teaching signals to for cerebellar motor learning. Its intrinsic oscillators receive converging glutamatergic and gabaergic input, from the cerebellum, and the diencephalic junction respectively. These inputs encounter the ongoing dynamics of the inferior olivary neurons, which they shape and modulate through phase shifts and resets.
From a detailed computational model of olivary tissue, strongly constrained by anatomical and physiological data this research focuses on the interaction between the spiking streams as they arrive differentially on the somata, dendrites and glomeruli of the inferior olivary neurons. The Hodgkin-Huxley type network model includes all neurons in one half of the inferior olive nuclei, with somata positions, dendritic fields and gap junctions derived from large-scale anatomical reconstructions of both the inferior olivary neurons, as well as the descending axonal arborizations from gabaergic and glutamatergic projections.
The modeling experiments, which inquire on the interaction between these input streams, produce strong predictions about a cohort of enigmatic aspects of olivary dynamics, i.e., the low firing rates (~1Hz), unreliable response to sensory stimulus(<<50% of trials), and the shape of the olivary Calcium spike (i.e., spikelets).
The model is embedded within a view of cerebellar function that purports to explain motor function of inferior olive on the scales of motor behavior and adaptation. The results allow me to propose integrative hypotheses about the most clinically relevant aspects of cerebellar dysfunction represented in hypertonias, hypotonias and intentional tremors.
Purkinje cell dendritic responses during self-paced locomotion
Feedforward excitatory and inhibitory circuits regulate cerebellar output, but how these circuits interact to shape the somatodendritic excitability of Purkinje cells during motor behaviour remains unresolved. To address this issue we performed dendritic and somatic patch-clamp recordings combined with optogenetic silencing of interneurons in head-restrained mice during periods of rest and bouts of self-paced, voluntary locomotion. Our data suggest that feedforward excitatory input to Purkinje cell dendrites is counterbalanced by variable levels of inhibition from local molecular layer interneurons and that subtle changes in the dendritic excitation-inhibition balance generates robust, bidirectional changes in simple spike output. Disrupting this balance by selectively silencing molecular layer interneurons results in unidirectional firing rate changes, increased SSp regularity and disrupted locomotor behaviour. Thus, recruitment of feedforward excitatory and inhibitory circuits provides a dynamic ‘push-pull’ mechanism to shape PC input–output transformations during voluntary motor behaviour.
Voltage- and branch-dependent complex spike responses in Purkinje neurons
Purkinje neurons receive powerful climbing fiber (CF) input from Inferior Olive (IO) neurons to provide an instructive signal for cerebellar learning. The initial observation that CF input causes all or none responses has been questioned in recent years. However, the mechanisms of initiation and propagation of dendritic calcium spikes evoked by CF input are still poorly understood. Here, we build a new Purkinje cell model based on available experimental data to explore dendritic and somatic responses to CF input in the Purkinje cell under different conditions. All the ionic current models are well constrained according to the experimental data.
Model ionic currents regulate the electrophysiological properties of the Purkinje cell consistent with experimental observations. Our model reproduces a plethora of experimentally observed properties that are critical for the model to be able to predict responses to excitatory and inhibitory inputs. Both simple spike and complex spikes initiate first in the axonal initial segment (AIS). The first derivative and second derivative of the somatic simple spike are in agreement with experimental data.
Using this model, we can explain the discrepancies between experimental observations from different groups about the spatial propagation range of dendritic calcium spikes. Dendritic spikelets can initiate and propagate in a branch-specific manner and depolarization of dendrites can cause secondary spikelets. We find that the timing of occurrence of the secondary spikelet is critical to determine whether it can affect somatic firing or not. The branch-specific dendritic spikelets can combine with contaminant excitatory input and inhibitory inputs to affect somatic firing output more efficiently. Our results indicate that voltage-dependent and branch specific spikelets may enrich CF instructive signals for cerebellar learning.
Cerebellar processing of kinematic signals during active whisking
The cerebellum or ‘little brain’ is a major site of sensorimotor integration and contains more than half of all the neurons in the mammalian brain. The elegant repeating circuitry of the cerebellar cortex has led to its description as ‘a neuronal machine’, but we know surprising little about its function. In particular our understanding of how the circuit encodes associated sensory and motor information during behaviour remains limited. We have approached this problem by using a well-defined model, the mouse vibrissae system, to study how sensorimotor signals are represented by the activity of individual neurons within the lateral cerebellum. In this talk I will describe how whisking behaviour is encoded by neurons in both input and output layers of the cerebellar cortex. Our results reveal that cells in the cerebellum use a simple code to represent whisker position during voluntary movement and provide a powerful new platform to explore neural computations underlying sensorimotor behavior.