Fast convergence of learning requires plasticity between inferior olive and deep cerebellar nuclei in a manipulation task: a closed-loop robotic simulation

Luque, Niceto R.; Garrido, Jesús; Carrillo, Richard R.; D’Angelo, Egidio; Ros, Eduardo

doi:10.3389/fncom.2014.00097

Cited by 38 publications

(51 citation statements)

References 86 publications

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“…Spinal neurons can directly connect to cerebellar nuclei, especially the interposed nucleus, via the spinocerebellar tracts and spinoreticulocerebellar tracts. 23 Moreover, the cerebellar nuclei also indirectly connect with spinal neurons via the cerebellar cortices 24 and brain stem nuclei, such as the inferior olive, 25 lateral reticular nucleus, 26 red nucleus, 27 and vestibular nuclei. 28 Based on the direct and indirect connections between the cerebellar nuclei and spinal neurons, the axonal degeneration secondary to spinal cord damage may explain why the NAGM volume of the cerebellar nuclei is reduced in NMOSD.…”

Section: Discussionmentioning

confidence: 99%

Normal-Appearing Cerebellar Damage in Neuromyelitis Optica Spectrum Disorder

Sun¹,

Zhang²,

Wang³

et al. 2019

AJNR Am J Neuroradiol

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BACKGROUND AND PURPOSE:The cerebellum plays an important role in motor and cognitive functions. However, whether and how the normal-appearing cerebellum is impaired in patients with neuromyelitis optica spectrum disorders remain unknown. We aimed to identify the occult structural damage of the cerebellum in neuromyelitis optica spectrum disorder and its possible causes at the level of substructures. MATERIALS AND METHODS:Normal-appearing gray matter volume of the cerebellar lobules and nuclei and normal-appearing white matter volume of the cerebellar peduncles were compared between patients with neuromyelitis optica spectrum disorder and healthy controls. RESULTS:The cerebellar damage of patients with neuromyelitis optica spectrum disorder in the hemispheric lobule VI, vermis lobule VI, and all cerebellar nuclei and peduncles was related only to spinal lesions; and cerebellar damage in the hemispheric lobules VIII and X was related only to the aquaporin-4 antibody. The mixed cerebellar damage in the hemispheric lobules V and IX and vermis lobule Crus I was related mainly to spinal lesions; and mixed cerebellar damage in the hemispheric lobule VIIb was related mainly to the aquaporin-4 antibody. Other cerebellar substructures showed no significant cerebellar damage. CONCLUSIONS:We have shown that the damage in cerebellar normal-appearing white matter and normal-appearing gray matter is associated with aquaporin-4 -mediated primary damage or axonal degeneration secondary to spinal lesions or both. The etiologic classifications of substructure-specific occult cerebellar damage may facilitate developing neuroimaging markers for assessing the severity and the results of therapy of neuromyelitis optica spectrum disorder occult cerebellar damage. ABBREVIATIONS:AQP4-Ab ϭ aquaporin-4 antibody; HC ϭ healthy control; ICP ϭ inferior cerebellar peduncle; LSCL ϭ length of the spinal cord lesion; MCP ϭ middle cerebellar peduncle; NAGM ϭ normal-appearing gray matter; NAWM ϭ normal-appearing white matter; NMOSD ϭ neuromyelitis optica spectrum disorder; SCI ϭ spinal cord injury; SCN ϭ spinal cord normal; SCP ϭ superior cerebellar peduncle; SUIT ϭ Spatially Unbiased Atlas Template of the Cerebellum and Brainstem Indicates open access to non-subscribers at www.ajnr.org Indicates article with supplemental on-line appendix and tables.

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Section: Discussionmentioning

confidence: 99%

Normal-Appearing Cerebellar Damage in Neuromyelitis Optica Spectrum Disorder

Sun¹,

Zhang²,

Wang³

et al. 2019

AJNR Am J Neuroradiol

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“…We assessed whether the specific CNN classes that have been described for young animals in vitro [12,23–27] could also be identified in vivo in adult animals. Since recordings in vitro are likely to show less variation in physiological properties compared to the in vivo situation [32], we expected to obtain additional information on the cellular properties of CNNs, allowing fine-tuning of local computational CN network models and scale computational modeling networks of the olivocerebellar system as a whole [40–43]. Our recordings point towards several main interpretations that may further elucidate the underpinnings of cerebellar motor coordination [30, 34–37].…”

Section: Discussionmentioning

confidence: 99%

“…In this respect, they stand in marked contrast to those of cortical structures, where neurons can often be characterized well by both unique axonal and dendritic trees and related succinct physiological properties [33–39]. Indeed, the cyto-architecture and related cell physiological properties of a neuron largely determine its specific computational capabilities [40–47]. Thus to prepare a solid ground for realistic modeling of CNNs we set out to do a systematic and comprehensive survey examining all types of CNNs in vivo in P21-42 old mice using standardized and blind conditions.…”

Section: Introductionmentioning

confidence: 99%

“…Thus to prepare a solid ground for realistic modeling of CNNs we set out to do a systematic and comprehensive survey examining all types of CNNs in vivo in P21-42 old mice using standardized and blind conditions. We deem this information to be particularly relevant for large scale computational modeling of the olivocerebellar system [40–43], linking the cellular responses of CNNs to sensorimotor and behavioral parameters [44–47]. We describe whole-cell activity of more than hundred CNNs in vivo distributed across the different CN with most of our recordings being performed in the nucleus interpositus.…”

Section: Introductionmentioning

confidence: 99%

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Whole-Cell Properties of Cerebellar Nuclei Neurons In Vivo

2016

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Cerebellar nuclei neurons integrate sensorimotor information and form the final output of the cerebellum, projecting to premotor brainstem targets. This implies that, in contrast to specialized neurons and interneurons in cortical regions, neurons within the nuclei encode and integrate complex information that is most likely reflected in a large variation of intrinsic membrane properties and integrative capacities of individual neurons. Yet, whether this large variation in properties is reflected in a heterogeneous physiological cell population of cerebellar nuclei neurons with well or poorly defined cell types remains to be determined. Indeed, the cell electrophysiological properties of cerebellar nuclei neurons have been identified in vitro in young rodents, but whether these properties are similar to the in vivo adult situation has not been shown. In this comprehensive study we present and compare the in vivo properties of 144 cerebellar nuclei neurons in adult ketamine-xylazine anesthetized mice. We found regularly firing (N = 88) and spontaneously bursting (N = 56) neurons. Membrane-resistance, capacitance, spike half-width and firing frequency all widely varied as a continuum, ranging from 9.63 to 3352.1 MΩ, from 6.7 to 772.57 pF, from 0.178 to 1.98 ms, and from 0 to 176.6 Hz, respectively. At the same time, several of these parameters were correlated with each other. Capacitance decreased with membrane resistance (R2 = 0.12, P<0.001), intensity of rebound spiking increased with membrane resistance (for 100 ms duration R2 = 0.1503, P = 0.0011), membrane resistance decreased with membrane time constant (R2 = 0.045, P = 0.031) and increased with spike half-width (R2 = 0.023, P<0.001), while capacitance increased with firing frequency (R2 = 0.29, P<0.001). However, classes of neuron subtypes could not be identified using merely k-clustering of their intrinsic firing properties and/or integrative properties following activation of their Purkinje cell input. Instead, using whole-cell parameters in combination with morphological criteria revealed by intracellular labelling with Neurobiotin (N = 18) allowed for electrophysiological identification of larger (29.3–50 μm soma diameter) and smaller (< 21.2 μm) cerebellar nuclei neurons with significant differences in membrane properties. Larger cells had a lower membrane resistance and a shorter spike, with a tendency for higher capacitance. Thus, in general cerebellar nuclei neurons appear to offer a rich and wide continuum of physiological properties that stand in contrast to neurons in most cortical regions such as those of the cerebral and cerebellar cortex, in which different classes of neurons operate in a narrower territory of electrophysiological parameter space. The current dataset will help computational modelers of the cerebellar nuclei to update and improve their cerebellar motor learning and performance models by incorporating the large variation of the in vivo properties of cerebellar nuclei neurons. The cellular complexity of cerebellar nuclei neurons m...

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“…Plasticity between IOs and DCNs has been predicted to accelerate learning toward biological levels. 83 It will also be useful to extend modeling to other mechanisms typical of cerebellar diseases: irregular firing patterns of PCs have been recognized in animal models of dystonia 84 , and oscillations in the Inferior Olive have been demonstrated in case of Essential Tremor. 85 This more complex role of IOs will make it necessary to introduce dynamic properties in the IO circuit (e.g.…”

Section: Advances and Limitations Of The Present Studymentioning

confidence: 99%

A Multiple-Plasticity Spiking Neural Network Embedded in a Closed-Loop Control System to Model Cerebellar Pathologies

Geminiani

Casellato

Antonietti

et al. 2018

Int. J. Neur. Syst.

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The cerebellum plays a crucial role in sensorimotor control and cerebellar disorders compromise adaptation and learning of motor responses. However, the link between alterations at network level and cerebellar dysfunction is still unclear. In principle, this understanding would benefit of the development of an artificial system embedding the salient neuronal and plastic properties of the cerebellum and operating in closed-loop. To this aim, we have exploited a realistic spiking computational model of the cerebellum to analyse the network correlates of cerebellar impairment. The model was modified to reproduce three different damages of the cerebellar cortex: (i) a loss of the main output neurons (Purkinje Cells), (ii) a lesion to the main cerebellar afferents (Mossy Fibers), and (iii) a damage to a major mechanism of synaptic plasticity (Long Term Depression). The modified network models were challenged with an Eye-Blink Classical Conditioning test, a standard learning paradigm used to evaluate cerebellar impairment, in which the outcome was compared to reference results obtained in human or animal experiments. In all cases, the model reproduced the partial and delayed conditioning typical of the pathologies, indicating that an intact cerebellar cortex functionality is required to accelerate learning by transferring acquired information to the cerebellar nuclei. Interestingly, depending on the type of lesion, the redistribution of synaptic plasticity and response timing varied greatly generating specific adaptation patterns. Thus, not only the present work extends the generalization capabilities of the cerebellar spiking model to pathological cases, but also predicts how changes at the neuronal level are distributed across the network, making it usable to infer cerebellar circuit alterations occurring in cerebellar pathologies.

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Fast convergence of learning requires plasticity between inferior olive and deep cerebellar nuclei in a manipulation task: a closed-loop robotic simulation

Cited by 38 publications

References 86 publications

Normal-Appearing Cerebellar Damage in Neuromyelitis Optica Spectrum Disorder

Normal-Appearing Cerebellar Damage in Neuromyelitis Optica Spectrum Disorder

Whole-Cell Properties of Cerebellar Nuclei Neurons In Vivo

A Multiple-Plasticity Spiking Neural Network Embedded in a Closed-Loop Control System to Model Cerebellar Pathologies

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