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Thalamic Function - Beyond a Simple Relay

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Book Series: Frontiers Research Topics ISSN: 16648714 ISBN: 9782889198429 Year: Pages: 231 DOI: 10.3389/978-2-88919-842-9 Language: English
Publisher: Frontiers Media SA
Subject: Neurology --- Science (General)
Added to DOAB on : 2016-01-19 14:05:46
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The thalamus is often described as a relay. Typified by sensory pathways, this concept leads to thalamic nuclei being viewed as areas that passively streams information from a single source to the cortex, without affecting the nature of that information. However, diverse intrathalamic connections, the varying synaptic and membrane properties of thalamic neurons and the large number of inputs from non-sensory sources make the idea that the thalamus is just a passive relay unlikely. Furthermore, a large number of thalamic nuclei are not primarily driven by sensory signals nor do they exclusively target the cortex, meaning the thalamus must do more than simply pass sensory signals to the cortex. Finally, there is a wealth of research demonstrating that the thalamus does indeed function in ways that are not captured by the concept of a simple relay. So why, given all of this, is the primary paradigm for describing the thalamus, a relay? This Research Topic covers original research, reviews and hypotheses on thalamic function that explore the concept that the thalamus performs computational tasks other than simply passively relaying information.

Spiking Neural Network Connectivity and its Potential for Temporal Sensory Processing and Variable Binding

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Book Series: Frontiers Research Topics ISSN: 16648714 ISBN: 9782889192397 Year: Pages: 123 DOI: 10.3389/978-2-88919-239-7 Language: English
Publisher: Frontiers Media SA
Subject: Neurology --- Science (General)
Added to DOAB on : 2015-11-16 15:44:59
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The most biologically-inspired artificial neurons are those of the third generation, and are termed spiking neurons, as individual pulses or spikes are the means by which stimuli are communicated. In essence, a spike is a short-term change in electrical potential and is the basis of communication between biological neurons. Unlike previous generations of artificial neurons, spiking neurons operate in the temporal domain, and exploit time as a resource in their computation. In 1952, Alan Lloyd Hodgkin and Andrew Huxley produced the first model of a spiking neuron; their model describes the complex electro-chemical process that enables spikes to propagate through, and hence be communicated by, spiking neurons. Since this time, improvements in experimental procedures in neurobiology, particularly with in vivo experiments, have provided an increasingly more complex understanding of biological neurons. For example, it is now well understood that the propagation of spikes between neurons requires neurotransmitter, which is typically of limited supply. When the supply is exhausted neurons become unresponsive. The morphology of neurons, number of receptor sites, amongst many other factors, means that neurons consume the supply of neurotransmitter at different rates. This in turn produces variations over time in the responsiveness of neurons, yielding various computational capabilities. Such improvements in the understanding of the biological neuron have culminated in a wide range of different neuron models, ranging from the computationally efficient to the biologically realistic. These models enable the modelling of neural circuits found in the brain. In recent years, much of the focus in neuron modelling has moved to the study of the connectivity of spiking neural networks. Spiking neural networks provide a vehicle to understand from a computational perspective, aspects of the brain's neural circuitry. This understanding can then be used to tackle some of the historically intractable issues with artificial neurons, such as scalability and lack of variable binding. Current knowledge of feed-forward, lateral, and recurrent connectivity of spiking neurons, and the interplay between excitatory and inhibitory neurons is beginning to shed light on these issues, by improved understanding of the temporal processing capabilities and synchronous behaviour of biological neurons. This research topic aims to amalgamate current research aimed at tackling these phenomena.

Modeling of Visual Cognition, Body Sense, Motor Control and Their Integrations

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Book Series: Frontiers Research Topics ISSN: 16648714 ISBN: 9782889451098 Year: Pages: 134 DOI: 10.3389/978-2-88945-109-8 Language: English
Publisher: Frontiers Media SA
Subject: Neurology --- Science (General)
Added to DOAB on : 2017-07-06 13:27:36
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The interdisciplinary studies between neuroscience and information science have greatly promoted the development of these two fields. The achievements of these studies can help humans understand the essence of biological systems, provide computational platforms for biological experiments, and improve the intelligence and performance of the algorithms in information science. This research topic is focused on the computational modeling of visual cognition, body sense, motor control and their integrations. Firstly, the modeling and simulation of vision and body sense are achieved by 1) understanding neural mechanism underlying sensory perception and cognition, and 2) mimicking accordingly the structures and mechanisms of their signal propagation pathways. The achievement of this procedure could provide neural findings for better encoding and decoding visual and somatosensory perception of humans, and help robots or systems build humanoid robust vision, body sensing, and various emotions. Secondly, the modeling and simulation of the motor system of the primate are achieved by mimicking the coordination of bones, muscles and joints and the control mechanisms of the neural system in the brain and spinal cord. This procedure could help robots achieve fast, robust and accurate manipulations and be used for safe human-computer interaction. Finally, by integrating them, more complete and intelligent systems/robots could be built to accomplish various tasks self-adaptively and automatically.

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