548 research outputs found
The cerebellar network: revisiting the critical issues
No full textThe cerebellum forms one of the main neuronal circuits of the brain. It is involved in motor control and its dysfunction causes the well known neurological syndrome called ataxia. However, despite decades of research, its mechanisms of function still remain elusive. This faith is peculiar indeed, if one considers the remarkable prediction made in the 1980s that cerebellum was soon going to be understood in principle (Sir J.C. Eccles in Ito, 1984). The fact is that, once scientists moved from anatomy-based models (e.g. the renowned motor learning theory of D. Marr; Marr, 1969) to cellular physiology, the cerebellar circuit became quite hard to understand. Cerebellar neurons have dynamic properties, which are not yet fully resolved and complicate (not to say often conflict with) theoretical predictions (reviewed in D'Angelo et al. 2010
Fast convergence of learning requires plasticity between inferior olive and deep cerebellar nuclei in a manipulation task: a closed-loop robotic simulation
No full textThe cerebellum is known to play a critical role in learning relevant patterns of activity for adaptive motor control, but the underlying network mechanisms are only partly understood. The classical long-term synaptic plasticity between parallel fibers (PFs) and Purkinje cells (PCs), which is driven by the inferior olive (IO), can only account for limited aspects of learning. Recently, the role of additional forms of plasticity in the granular layer, molecular layer and deep cerebellar nuclei (DCN) has been considered. In particular, learning at DCN synapses allows for generalization, but convergence to a stable state requires hundreds of repetitions. In this paper we have explored the putative role of the IO-DCN connection by endowing it with adaptable weights and exploring its implications in a closed-loop robotic manipulation task. Our results show that IO-DCN plasticity accelerates convergence of learning by up to two orders of magnitude without conflicting with the generalization properties conferred by DCN plasticity. Thus, this model suggests that multiple distributed learning mechanisms provide a key for explaining the complex properties of procedural learning and open up new experimental questions for synaptic plasticity in the cerebellar network.This work was supported by grants from the European Union, Egidio D'Angelo and Eduardo Ros (CEREBNET FP7-ITN238686, REALNET FP7-ICT270434) and by grants from the Italian Ministry of Health to Egidio D'Angelo (RF-2009-1475845) and the Spanish Regional Government, Niceto R. Luque (PYR-2014-16). We thank G. Ferrari and M. Rossin for their technical support
Neural circuits of the cerebellum: hypothesis for function
No full textThe rapid growth of cerebellar research is going to clarify several aspects of cellular and circuit physiology. However, the concepts about cerebellar mechanisms of function are still largely related to clinical observations and to models elaborated before the last discoveries appeared. In this paper, the major issues are revisited, suggesting that previous concepts can now be refined and modified. The cerebellum is fundamentally involved in timing and in controlling the ordered and precise execution of motor sequences. The fast reaction of the cerebellum to the inputs is sustained by specific cellular mechanisms ensuring precision on the millisecond scale. These include burst-burst reconversion in the granular layer and instantaneous frequency modulation on the 100-Hz band in Purkinje and deep cerebellar nuclei cells. Precisely timed signals can be used for perceptron operations in Purkinje cells and to establish appropriate correlations with climbing fiber signals inducing learning at parallel fiber synapses. In the granular layer, plasticity turns out to be instrumental to timing, providing a conceptual solution to the discrepancy between cerebellar learning and timing. The granular layer sub-circuit can be tuned by long-term synaptic plasticity and synaptic inhibition to delay the incoming signals over a 100-ms range. For longer sequences, large circuit sections can be entrained into coherent activity in 100-ms cycles. These dynamic aspects, which have not been accounted for by original theories, could in fact represent the essence of cerebellar functioning. It is suggested that the cerebellum can, in this way, operate the realignment of temporally incongruent signals, allowing their binding and pattern recognition in Purkinje cells. The demonstration of these principles, their behavioral relevance and their relationship with internal model theories represent a challenge for future cerebellar researc
Toward the connectomic era
No full textNeuroscience recently embarked on a new landmark era: in the wake of the decade of the brain (1991-2000) and the decade of behavior (2001-2010), it has now entered the decade of the mind (2011-2020
Editorial to the special issue of Frontiers in Cellular Neuroscience: Rebuilding cerebellar network computations from cellular neurophysiology
No full textThis schematic drawing shows the most relevant connections
within a cerebellar module. The mossy fibers contact granule
cells (GrC) and deep cerebellar nuclei (DCN) cells which, in turn, receive inhibition from the same common set of Purkinje cells (PC). Moreover, the interior olive (IO) cells emit climbing fibers that contact DCN cells and Purkinje cells (PC), which also project to the same DCN cells. An activate group of GrCs is in (red), while others (yellow) are laterally inhibited by the GoCs. The active GrCs excite the overlaying PCs (dark red) according to a vertical organization pattern (Bower and Woolston, 1983). The PCs inhibit DCN neurons which in turn inhibit the IO neurons. Note that, within a cerebellar module, different circuit elements communicate in closed loops. The mossy fibers contact granule cells and DCN cells which, in turn, receive inhibition from the same common set of Purkinje cells. Moreover, the IO cells emit climbing fibers that contact DCN and PC, which also project to the same DCN cells
The Organization of Plasticity in the Cerebellar Cortex: From Synapses to Control Cerebellar Learning
No full textThe cerebellum is thought to play a critical role in procedural learning, but the relationship between this function and the underlying cellular and synaptic mechanisms remains largely speculative. At present, at least nine forms of long-term synaptic and nonsynaptic plasticity (some of which are bidirectional) have been reported in the cerebellar cortex and deep cerebellar nuclei. These include long-term potentiation (LTP) and long-term depression at the mossy fiber-granule cell synapse, at the synapses formed by parallel fibers, climbing fibers, and molecular layer interneurons on Purkinje cells, and at the synapses formed by mossy fibers and Purkinje cells on deep cerebellar nuclear cells, as well as LTP of intrinsic excitability in granule cells, Purkinje cells, and deep cerebellar nuclear cells. It is suggested that the complex properties of cerebellar learning would emerge from the distribution of plasticity in the network and from its dynamic remodeling during the different phases of learning. Intrinsic and extrinsic factors may hold the key to explain how the different forms of plasticity cooperate to select specific transmission channels and to regulate the signal-to-noise ratio through the cerebellar cortex. These factors include regulation of neuronal excitation by local inhibitory networks, engagement of specific molecular mechanisms by spike bursts and theta-frequency oscillations, and gating by external neuromodulators. Therefore, a new and more complex view of cerebellar plasticity is emerging with respect to that predicted by the original "Motor Learning Theory," opening issues that will require experimental and computational testin
Physiology of the cerebellum
No full textThe cerebellum is a central brain structure deeply integrated into major loops with the cerebral cortex, brainstem, and spinal cord. The cerebellum shows a complex regional organization consisting of modules with sagittal orientation. The cerebellum takes part in motor control and its lesions cause a movement incoordination syndrome called ataxia. Recent observations also imply involvement of the cerebellum in cognition and executive control, with an impact on pathologies like dyslexia and autism. The cerebellum operates as a forward controller learning to predict the precise timing of correlated events. The physiologic mechanisms of cerebellar functioning are still the object of intense research. The signals entering the cerebellum through the mossy fibers are processed in the granular layer and transmitted to Purkinje cells, while a collateral pathway activates the deep cerebellar nuclei (DCN). Purkinje cells in turn inhibit DCN, so that the cerebellar cortex operates as a side loop controlling the DCN. Learning is now known to occur through synaptic plasticity at multiple synapses in the granular layer, molecular layer, and DCN, extending the original concept of the Motor Learning Theory that predicted a single form of plasticity at the synapse between parallel fibers and Purkinje cells under the supervision of climbing fibers deriving from the inferior olive. Coordination derives from the precise regulation of timing and gain in the different cerebellar modules. The investigation of cerebellar dynamics using advanced physiologic recordings and computational models is now providing new clues on how the cerebellar network performs its internal computations
Neuronal circuit function and dysfunction in the cerebellum: from neurons to integrated control
No full textThis special issue follows the meeting The Cerebellum: From Neurons to Higher Control and Cognition held in Pavia, Italy, on 8-9 July 2010.1
Ever since the early anatomical discoveries by Golgi and Ramon Y Cajal (1-3), cerebellar neuroscience has provided pioneering observations on the nature of ionic channels, synaptic transmission and circuit organization, expanding to such an extent that it still represents a benchmark for brain sciences (2). Cerebellar investigations are providing amongst the highest resolution recordings at cellular and subcellular level, innovative techniques for neuronal circuit analysis and functional imaging of higher control functions. This stimulating experimental activity is supported by remarkable attempts to develop realistic computational models and multi-scale brain theories, projecting cerebellum neuroscience towards the integration of molecular-cellular mechanisms into circuit and systemic level dynamics. The clinical interest in the cerebellum has also been revitalized by this structure’s core involvement not just in motor pathologies like ataxia but also in cognitive pathologies like autism and dyslexi
Magnetic stimulation of the cerebellum. Moving towards the clinic
No full textTranscranical magnetic stimulation (TMS) is a brain stimulation technique that is attracting growing interest due to its potential for intervention in various neurological and psychiatric condition
Long-Term Spatiotemporal Reconfiguration of Neuronal Activity Revealed by Voltage-Sensitive Dye Imaging in the Cerebellar Granular Layer
No full textUnderstanding the spatiotemporal organization of long-term synaptic plasticity in neuronal networks demands techniques capable of monitoring changes in synaptic responsiveness over extended multineuronal structures. Among these techniques, voltage-sensitive dye imaging (VSD imaging) is of particular interest due to its good spatial resolution. However, improvements of the technique are needed in order to overcome limits imposed by its low signal-to-noise ratio. Here, we show that VSD imaging can detect long-term potentiation (LTP) and long-term depression (LTD) in acute cerebellar slices. Combined VSD imaging and patch-clamp recordings revealed that the most excited regions were predominantly associated with granule cells (GrCs) generating EPSP-spike complexes, while poorly responding regions were associated with GrCs generating EPSPs only. The correspondence with cellular changes occurring during LTP and LTD was highlighted by a vector representation obtained by combining amplitude with time-to-peak of VSD signals. This showed that LTP occurred in the most excited regions lying in the core of activated areas and increased the number of EPSP-spike complexes, while LTD occurred in the less excited regions lying in the surround. VSD imaging appears to be an efficient tool for investigating how synaptic plasticity contributes to the reorganization of multineuronal activity in neuronal circuits
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