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Neural Plasticity for Rich and Uncertain Robotic Information Streams

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Book Series: Frontiers Research Topics ISSN: 16648714 ISBN: 9782889199952 Year: Pages: 83 DOI: 10.3389/978-2-88919-995-2 Language: English
Publisher: Frontiers Media SA
Subject: Science (General) --- Neurology
Added to DOAB on : 2016-01-19 14:05:46
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Models of adaptation and neural plasticity are often demonstrated in robotic scenarios with heavily pre-processed and regulated information streams to provide learning algorithms with appropriate, well timed, and meaningful data to match the assumptions of learning rules. On the contrary, natural scenarios are often rich of raw, asynchronous, overlapping and uncertain inputs and outputs whose relationships and meaning are progressively acquired, disambiguated, and used for further learning. Therefore, recent research efforts focus on neural embodied systems that rely less on well timed and pre-processed inputs, but rather extract autonomously relationships and features in time and space. In particular, realistic and more complete models of plasticity must account for delayed rewards, noisy and ambiguous data, emerging and novel input features during online learning. Such approaches model the progressive acquisition of knowledge into neural systems through experience in environments that may be affected by ambiguities, uncertain signals, delays, or novel features.

Building the gateway to consciousness - about the development of the thalamus

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Book Series: Frontiers Research Topics ISSN: 16648714 ISBN: 9782889194704 Year: Pages: 107 DOI: 10.3389/978-2-88919-470-4 Language: English
Publisher: Frontiers Media SA
Subject: Neurology --- Science (General)
Added to DOAB on : 2016-03-10 08:14:32
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Since years, patterning and function of some brain parts such as the cortex in the forebrain and the optical tectum or cerebellum in the midbrain/hindbrain region are under strong investigation. Interestingly the diencephalon located in the caudal forebrain has been ignored for decades. Consequently, the existing knowledge from the development of this region to function in the mature brain is very fragmented. The central part of the diencephalon is the thalamus. This central relay station plays a crucial role in distributing incoming sensory information to appropriate regions of the cortex. The thalamus develops in the posterior part of the embryonic forebrain, where early cell fate decisions are controlled by local signaling centers. In this Research Topic we discuss recent achievements elucidating thalamic neurogenesis - from neural progenitor cells to highly specialized neurons with cortical target cells in great distance. In parallel, we highlight developmental aspects leading from the early thalamic anlage to the late the organization of the complex relay station of the brain.

Towards an Integrated Approach to Measurement, Analysis and Modeling of Cortical Networks

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Book Series: Frontiers Research Topics ISSN: 16648714 ISBN: 9782889197620 Year: Pages: 264 DOI: 10.3389/978-2-88919-762-0 Language: English
Publisher: Frontiers Media SA
Subject: Neurology --- Science (General)
Added to DOAB on : 2016-04-07 11:22:02
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The amount of data being produced by neuroscientists is increasing rapidly, driven by advances in neuroimaging and recording techniques spanning multiple scales of resolution. The availability of such data poses significant challenges for their processing and interpretation. To gain a deeper understanding of the surrounding issues, the Editors of this e-Book reached out to an interdisciplinary community, and formed the Cortical Networks Working Group. The genesis of this e-Book thus began with this Working Group through support from the National Institute for Mathematical and Biological Synthesis in the USA. The Group consisted of scientists from neuroscience, physics, psychology and computer science, and meetings were held in person (a detailed list of the group members is presented in the Editorial that follows). At the time we started, in 2010, the term “big data” was hardly in existence, though the volume of data we were handling would certainly have qualified. Furthermore, there was significant interest in harnessing the power of supercomputers to perform large scale neuronal simulations, and in creating specialized hardware to mimic neural function. We realized that the various disciplines represented in our Group could and should work together to accelerate progress in Neuroscience. We searched for common threads that could define the foundation for an integrated approach to solve important problems in the field. We adopted a network-centric perspective to address these challenges, as the data are derived from structures that are themselves network-like. We proposed three inter-twined threads, consisting of measurement of neural activity, analysis of network structures deduced from this activity, and modeling of network function, leading to theoretical insights. This approach formed the foundation of our initial call for papers. When we issued the call for papers, we were not sure how many papers would fall into each of these threads. We were pleased that we found significant interest in each thread, and the number of submissions exceeded our expectations. This is an indication that the field of neuroscience is ripe for the type of integration and interchange that we had anticipated. We first published a special topics issue after we received a sufficient number of submissions. This is now being converted to an e-book to strengthen the coherence of its contributions. One of the strong themes emerging in this e-book is that network-based measures capture better the dynamics of brain processes, and provide features with greater discriminative power than point-based measures. Another theme is the importance of network oscillations and synchrony. Current research is shedding light on the principles that govern the establishment and maintenance of network oscillation states. These principles could explain why there is impaired synchronization between different brain areas in schizophrenics and Parkinson’s patients. Such research could ultimately provide the foundation for an understanding of other psychiatric and neurodegenerative conditions. The chapters in this book cover these three main threads related to cortical networks. Some authors have combined two or more threads within a single chapter. We expect the availability of related work appearing in a single e-book to help our readers see the connection between different research efforts, and spur further insights and research.

Traumatic Brain Injury as a Systems Neuroscience Problem

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Book Series: Frontiers Research Topics ISSN: 16648714 ISBN: 9782889450985 Year: Pages: 167 DOI: 10.3389/978-2-88945-098-5 Language: English
Publisher: Frontiers Media SA
Subject: Neurology --- Science (General)
Added to DOAB on : 2017-07-06 13:27:36
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Traumatic brain injury (TBI) is traditionally viewed as an anatomic and neuropathological condition. Caring for TBI patients is a matter of defining the extent of an anatomical lesion, managing this lesion, and minimizing secondary brain injury. On the research side, the effects of TBI often are studied in the context of neuronal and axonal degeneration and the subsequent deposition of abnormal proteins such as tau. These approaches form the basis of our current understanding of TBI, but they pay less attention to the function of the affected organ, the brain. Much can be learned about TBI by studying this disorder on a systems neuroscience level and correlating changes in neural circuitry with neurological and cognitive function. There are several aspects of TBI that are a natural fit for this perspective, including post-traumatic epilepsy, consciousness, and cognitive sequelae. How individual neurons contribute to network activity and how network function responds to injury are key concepts in examining these areas. In recent years, the available tools for studying the role of neuronal assemblies in TBI have become increasingly sophisticated, ranging from optogenetic and electrophysiological techniques to advanced imaging modalities such as functional magnetic resonance imaging and magnetoencephalography. Further progress in understanding the disruption and subsequent reshaping of networks is likely to have substantial benefits in the treatment of patients with TBI-associated deficits. In this Frontiers Topic, we intend to highlight the systems neuroscience approach to studying TBI. In addition to analyzing the clinical sequelae of TBI in this context, this series of articles explores the pathophysiological mechanisms underlying network dysfunction, including alterations in synaptic activity, changes in neural oscillation patterns, and disruptions in functional connectivity. We also include articles on treatment options for TBI patients that modulate network function. It is our hope that this Frontiers Topic will increase the clinical and scientific communities’ awareness of this viable framework for deepening our knowledge of TBI and improving patient outcomes.

Neural Masses and Fields: Modelling the Dynamics of Brain Activity

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Book Series: Frontiers Research Topics ISSN: 16648714 ISBN: 9782889194278 Year: Pages: 237 DOI: 10.3389/978-2-88919-427-8 Language: English
Publisher: Frontiers Media SA
Subject: Neurology --- Science (General)
Added to DOAB on : 2016-01-19 14:05:46
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Biophysical modelling of brain activity has a long and illustrious history and has recently profited from technological advances that furnish neuroimaging data at an unprecedented spatiotemporal resolution. Neuronal modelling is a very active area of research, with applications ranging from the characterization of neurobiological and cognitive processes, to constructing artificial brains in silico and building brain-machine interface and neuroprosthetic devices. Biophysical modelling has always benefited from interdisciplinary interactions between different and seemingly distant fields; ranging from mathematics and engineering to linguistics and psychology. This Research Topic aims to promote such interactions by promoting papers that contribute to a deeper understanding of neural activity as measured by fMRI or electrophysiology.In general, mean field models of neural activity can be divided into two classes: neural mass and neural field models. The main difference between these classes is that field models prescribe how a quantity characterizing neural activity (such as average depolarization of a neural population) evolves over both space and time as opposed to mass models, which characterize activity over time only; by assuming that all neurons in a population are located at (approximately) the same point. This Research Topic focuses on both classes of models and considers several aspects and their relative merits that: span from synapses to the whole brain; comparisons of their predictions with EEG and MEG spectra of spontaneous brain activity; evoked responses, seizures, and fitting data - to infer brain states and map physiological parameters.

Theories of Visual Attention - linking cognition, neuropsychology, and neurophysiology

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Book Series: Frontiers Research Topics ISSN: 16648714 ISBN: 9782889196371 Year: Pages: 112 DOI: 10.3389/978-2-88919-637-1 Language: English
Publisher: Frontiers Media SA
Subject: Science (General) --- Psychology
Added to DOAB on : 2016-08-16 10:34:25
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The Neural Theory of Visual Attention of Bundesen, Habekost, and Kyllingsbæk (2005) was proposed as a neural interpretation of Bundesen’s (1990) theory of visual attention (TVA). In NTVA, visual attention functions via two mechanisms: by dynamic remapping of receptive fields of cortical cells such that more cells are devoted to behaviorally important objects than to less important ones (filtering) and by multiplicative scaling of the level of activation in cells coding for particular features (pigeonholing). NTVA accounts for a wide range of known attentional effects in human performance and a wide range of effects observed in firing rates of single cells in the primate visual system and thus provides a mathematical framework to unify the 2 fields of research. In this Research Topic of Frontiers in Psychology, some of the leading theories of visual attention at both the cognitive, neuropsychological, and neurophysiological levels are presented and evaluated. In addition, the Research Topic encompasses application of the framework of NTVA to various patient populations and to neuroimaging as well as genetic and psychopharmacological studies.

Keywords

neural --- visual --- Attention --- computational --- Model

Artificial Neural Networks as Models of Neural Information Processing

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Book Series: Frontiers Research Topics ISSN: 16648714 ISBN: 9782889454013 Year: Pages: 220 DOI: 10.3389/978-2-88945-401-3 Language: English
Publisher: Frontiers Media SA
Subject: Science (General) --- Neurology
Added to DOAB on : 2018-11-16 17:17:57
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Modern neural networks gave rise to major breakthroughs in several research areas. In neuroscience, we are witnessing a reappraisal of neural network theory and its relevance for understanding information processing in biological systems. The research presented in this book provides various perspectives on the use of artificial neural networks as models of neural information processing. We consider the biological plausibility of neural networks, performance improvements, spiking neural networks and the use of neural networks for understanding brain function.

Neural information processing with dynamical synapses

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Book Series: Frontiers Research Topics ISSN: 16648714 ISBN: 9782889193837 Year: Pages: 178 DOI: 10.3389/978-2-88919-383-7 Language: English
Publisher: Frontiers Media SA
Subject: Neurology --- Science (General)
Added to DOAB on : 2015-12-03 13:02:24
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Experimental data have consistently revealed that the neuronal connection weight, which models the efficacy of the firing of a pre-synaptic neuron in modulating the state of a post-synaptic one, varies on short time scales, ranging from hundreds to thousands of milliseconds. This is called short-term plasticity (STP). Two types of STP, with opposite effects on the connection efficacy, have been observed in experiments. They are short-term depression (STD) and short-term facilitation (STF). Computational studies have explored the impact of STP on network dynamics, and found that STP can generate very rich intrinsic dynamical behaviors, including damped oscillations, state hopping with transient population spikes, traveling fronts and pulses, spiral waves, rotating bump states, robust self-organized critical activities and so on. These studies also strongly suggest that STP can play many important roles in neural computation. For instances, STD may provide a dynamic control mechanism that allows equal fractional changes on rapidly and slowly firing afferents to produce post-synaptic responses, realizing Weber's law; STD may provide a mechanism to close down network activity naturally, achieving iconic sensory memory; and STF may provide a mechanism for implementing work-memory not relying on persistent neural firing. From the computational point of view, the time scale of STP resides between fast neural signaling (in the order of milliseconds) and rapid learning (in the order of minutes or above), which is the time scale of many important temporal processes occurring in our daily lives, such as motion control and working memory. Thus, STP may serve as a substrate for neural systems manipulating temporal information on the relevant time scales. This Research Topic aims to present the recent progress in understanding the roles of STP in neural information processing. It includes, but no exclusively, the studies on investigating various computational roles of STP, the modeling studies on exploring new dynamical behaviors generated by STP, and the experimental works which help us to understand the functional roles of STP.

Supraspinal Control of Automatic Postural Responses Which Pathway Does What?

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Book Series: Frontiers Research Topics ISSN: 16648714 ISBN: 9782889452309 Year: Pages: 105 DOI: 10.3389/978-2-88945-230-9 Language: English
Publisher: Frontiers Media SA
Subject: Neurology --- Science (General)
Added to DOAB on : 2017-10-13 14:57:01
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Rapid corrective actions, termed automatic postural responses, are essential to counter the destabilizing effect of mechanical perturbations during natural behaviors. Previous research has demonstrated that automatic postural responses of the limbs and body share a number of capabilities in adapting to the prevailing circumstances and these abilities reflect contributions from multiple supraspinal pathways, including brainstem nuclei, basal ganglia, and primary motor cortex. However, we do not know the context-dependent contribution from specific generators, whether different neural pathways have a common role across different effectors, and how sensory and central deficits in one pathway are accommodated by those remaining. Bridging these gaps is essential to integrate the diverse set of studies, develop general theories of motor control, and explicate how the nervous system addresses the partially distinct behavioral demands of co-evolved effector system. The considerable flexibility and multiple interacting pathways of automatic postural responses also make it ideal for understanding how powerful formal theories, like optimal feedback control, are achieved by a distributed hierarchical neural network.

Keywords

reflex --- posture --- supraspinal --- feedback --- neural control

Enabling Technologies for Very Large-Scale Synaptic Electronics

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Book Series: Frontiers Research Topics ISSN: 16648714 ISBN: 9782889455089 Year: Pages: 105 DOI: 10.3389/978-2-88945-508-9 Language: English
Publisher: Frontiers Media SA
Subject: Science (General) --- Neurology
Added to DOAB on : 2019-01-23 14:53:42
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An important part of the colossal effort associated with the understanding of the brain involves using electronics hardware technology in order to reproduce biological behavior in ‘silico’. The idea revolves around leveraging decades of experience in the electronics industry as well as new biological findings that are employed towards reproducing key behaviors of fundamental elements of the brain (notably neurons and synapses) at far greater speed-scale products than any software-only implementation can achieve for the given level of modelling detail. So far, the field of neuromorphic engineering has proven itself as a major source of innovation towards the ‘silicon brain’ goal, with the methods employed by its community largely focused on circuit design (analogue, digital and mixed signal) and standard, commercial, Complementary Metal-Oxide Silicon (CMOS) technology as the preferred `tools of choice’ when trying to simulate or emulate biological behavior. However, alongside the circuit-oriented sector of the community there exists another community developing new electronic technologies with the express aim of creating advanced devices, beyond the capabilities of CMOS, that can intrinsically simulate neuron- or synapse-like behavior. A notable example concerns nanoelectronic devices responding to well-defined input signals by suitably changing their internal state (‘weight’), thereby exhibiting `synapse-like’ plasticity. This is in stark contrast to circuit-oriented approaches where the `synaptic weight’ variable has to be first stored, typically as charge on a capacitor or digitally, and then appropriately changed via complicated circuitry. The shift of very much complexity from circuitry to devices could potentially be a major enabling factor for very-large scale `synaptic electronics’, particularly if the new devices can be operated at much lower power budgets than their corresponding 'traditional' circuit replacements. To bring this promise to fruition, synergy between the well-established practices of the circuit-oriented approach and the vastness of possibilities opened by the advent of novel nanoelectronic devices with rich internal dynamics is absolutely essential and will create the opportunity for radical innovation in both fields. The result of such synergy can be of potentially staggering impact to the progress of our efforts to both simulate the brain and ultimately understand it. In this Research Topic, we wish to provide an overview of what constitutes state-of-the-art in terms of enabling technologies for very large scale synaptic electronics, with particular stress on innovative nanoelectronic devices and circuit/system design techniques that can facilitate the development of very large scale brain-inspired electronic systems

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