108 research outputs found
Nonspecific synaptic plasticity improves the recognition of sparse patterns degraded by local noise
Safaryan, K. et al. Nonspecific synaptic plasticity improves the recognition of sparse patterns degraded by local noise. Sci. Rep. 7, 46550; doi: 10.1038/srep46550 (2017). This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ © The Author(s) 2017.Many forms of synaptic plasticity require the local production of volatile or rapidly diffusing substances such as nitric oxide. The nonspecific plasticity these neuromodulators may induce at neighboring non-active synapses is thought to be detrimental for the specificity of memory storage. We show here that memory retrieval may benefit from this non-specific plasticity when the applied sparse binary input patterns are degraded by local noise. Simulations of a biophysically realistic model of a cerebellar Purkinje cell in a pattern recognition task show that, in the absence of noise, leakage of plasticity to adjacent synapses degrades the recognition of sparse static patterns. However, above a local noise level of 20 %, the model with nonspecific plasticity outperforms the standard, specific model. The gain in performance is greatest when the spatial distribution of noise in the input matches the range of diffusion-induced plasticity. Hence non-specific plasticity may offer a benefit in noisy environments or when the pressure to generalize is strong.Peer reviewe
Restoration of Contralateral Representation in the Mouse Somatosensory Cortex after Crossing Nerve Transfer
Avulsion of spinal nerve roots in the brachial plexus (BP) can be repaired by crossing nerve transfer via a nerve graft to connect injured nerve ends to the BP contralateral to the lesioned side. Sensory recovery in these patients suggests that the contralateral primary somatosensory cortex (S1) is activated by afferent inputs that bypassed to the contralateral BP. To confirm this hypothesis, the present study visualized cortical activity after crossing nerve transfer in mice through the use of transcranial flavoprotein fluorescence imaging. In naïve mice, vibratory stimuli applied to the forepaw elicited localized fluorescence responses in the S1 contralateral to the stimulated side, with almost no activity in the ipsilateral S1. Four weeks after crossing nerve transfer, forepaw stimulation in the injured and repaired side resulted in cortical responses only in the S1 ipsilateral to the stimulated side. At eight weeks after crossing nerve transfer, forepaw stimulation resulted in S1 cortical responses of both hemispheres. These cortical responses were abolished by cutting the nerve graft used for repair. Exposure of the ipsilateral S1 to blue laser light suppressed cortical responses in the ipsilateral S1, as well as in the contralateral S1, suggesting that ipsilateral responses propagated to the contralateral S1 via cortico-cortical pathways. Direct high-frequency stimulation of the ipsilateral S1 in combination with forepaw stimulation acutely induced S1 bilateral cortical representation of the forepaw area in naïve mice. Cortical responses in the contralateral S1 after crossing nerve transfer were reduced in cortex-restricted heterotypic GluN1 (NMDAR1) knockout mice. Functional bilateral cortical representation was not clearly observed in genetically manipulated mice with impaired cortico-cortical pathways between S1 of both hemispheres. Taken together, these findings strongly suggest that activity-dependent potentiation of cortico-cortical pathways has a critical role for sensory recovery in patients after crossing nerve transfer
Adaptive Robotic Control Driven by a Versatile Spiking Cerebellar Network
The cerebellum is involved in a large number of different neural processes, especially in associative learning and in fine motor control. To develop a comprehensive theory of sensorimotor learning and control, it is crucial to determine the neural basis of coding and plasticity embedded into the cerebellar neural circuit and how they are translated into behavioral outcomes in learning paradigms. Learning has to be inferred from the interaction of an embodied system with its real environment, and the same cerebellar principles derived from cell physiology have to be able to drive a variety of tasks of different nature, calling for complex timing and movement patterns. We have coupled a realistic cerebellar spiking neural network (SNN) with a real robot and challenged it in multiple diverse sensorimotor tasks. Encoding and decoding strategies based on neuronal firing rates were applied. Adaptive motor control protocols with acquisition and extinction phases have been designed and tested, including an associative Pavlovian task (Eye blinking classical conditioning), a vestibulo-ocular task and a perturbed arm reaching task operating in closed-loop. The SNN processed in real-time mossy fiber inputs as arbitrary contextual signals, irrespective of whether they conveyed a tone, a vestibular stimulus or the position of a limb. A bidirectional long-term plasticity rule implemented at parallel fibers-Purkinje cell synapses modulated the output activity in the deep cerebellar nuclei. In all tasks, the neurorobot learned to adjust timing and gain of the motor responses by tuning its output discharge. It succeeded in reproducing how human biological systems acquire, extinguish and express knowledge of a noisy and changing world. By varying stimuli and perturbations patterns, real-time control robustness and generalizability were validated. The implicit spiking dynamics of the cerebellar model fulfill timing, prediction and learning functions.European Union (Human Brain Project)
REALNET FP7-ICT270434
CEREBNET FP7-ITN238686
HBP-60410
Diversification of behavior and postsynaptic properties by netrin-G presynaptic adhesion family proteins
Optical imaging of the spatiotemporal dynamics of cerebral blood flow and oxidative metabolism in the rat barrel cortex
Bidirectional Coupling between Astrocytes and Neurons Mediates Learning and Dynamic Coordination in the Brain: A Multiple Modeling Approach
In recent years research suggests that astrocyte networks, in addition to nutrient and waste processing functions, regulate both structural and synaptic plasticity. To understand the biological mechanisms that underpin such plasticity requires the development of cell level models that capture the mutual interaction between astrocytes and neurons. This paper presents a detailed model of bidirectional signaling between astrocytes and neurons (the astrocyte-neuron model or AN model) which yields new insights into the computational role of astrocyte-neuronal coupling. From a set of modeling studies we demonstrate two significant findings. Firstly, that spatial signaling via astrocytes can relay a “learning signal” to remote synaptic sites. Results show that slow inward currents cause synchronized postsynaptic activity in remote neurons and subsequently allow Spike-Timing-Dependent Plasticity based learning to occur at the associated synapses. Secondly, that bidirectional communication between neurons and astrocytes underpins dynamic coordination between neuron clusters. Although our composite AN model is presently applied to simplified neural structures and limited to coordination between localized neurons, the principle (which embodies structural, functional and dynamic complexity), and the modeling strategy may be extended to coordination among remote neuron clusters
Electrophysiological function of the retina and optic nerve in patients with atrial fibrillation
Altered excitatory-inhibitory balance within somatosensory cortex is associated with enhanced plasticity and pain sensitivity in a mouse model of multiple sclerosis
Experimental Study on Predicting Skin Flap Necrosis by Fluorescence in the FAD and NADH Bands During Surgery
- …