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Neural architecture human

Douglas H Schultz, Michael W Cole
Spontaneous fluctuations in neural activity and connectivity are thought to support cognition and behavior. In this issue of Neuron, Shine et al. (2016) describe a possible mechanism responsible for fluctuations in the human brain's network architecture that are related to rapid shifts in cognitive state.
October 19, 2016: Neuron
Xiang Li, Ling Peng, Yuan Hu, Jing Shao, Tianhe Chi
With the rapid development of urbanization and industrialization, many developing countries are suffering from heavy air pollution. Governments and citizens have expressed increasing concern regarding air pollution because it affects human health and sustainable development worldwide. Current air quality prediction methods mainly use shallow models; however, these methods produce unsatisfactory results, which inspired us to investigate methods of predicting air quality based on deep architecture models. In this paper, a novel spatiotemporal deep learning (STDL)-based air quality prediction method that inherently considers spatial and temporal correlations is proposed...
October 13, 2016: Environmental Science and Pollution Research International
Jessica J DeWitt, Nicole Grepo, Brent Wilkinson, Oleg V Evgrafov, James A Knowles, Daniel B Campbell
We previously identified the long noncoding RNA (lncRNA) MSNP1AS (moesin pseudogene 1, antisense) as a functional element revealed by genome wide significant association with autism spectrum disorder (ASD). MSNP1AS expression was increased in the postmortem cerebral cortex of individuals with ASD and particularly in individuals with the ASD-associated genetic markers on chromosome 5p14.1. Here, we mimicked the overexpression of MSNP1AS observed in postmortem ASD cerebral cortex in human neural progenitor cell lines to determine the impact on neurite complexity and gene expression...
2016: Genes
James C Knight, Steve B Furber
While the adult human brain has approximately 8.8 × 10(10) neurons, this number is dwarfed by its 1 × 10(15) synapses. From the point of view of neuromorphic engineering and neural simulation in general this makes the simulation of these synapses a particularly complex problem. SpiNNaker is a digital, neuromorphic architecture designed for simulating large-scale spiking neural networks at speeds close to biological real-time. Current solutions for simulating spiking neural networks on SpiNNaker are heavily inspired by work on distributed high-performance computing...
2016: Frontiers in Neuroscience
Saeed R Kheradpisheh, Masoud Ghodrati, Mohammad Ganjtabesh, Timothée Masquelier
View-invariant object recognition is a challenging problem that has attracted much attention among the psychology, neuroscience, and computer vision communities. Humans are notoriously good at it, even if some variations are presumably more difficult to handle than others (e.g., 3D rotations). Humans are thought to solve the problem through hierarchical processing along the ventral stream, which progressively extracts more and more invariant visual features. This feed-forward architecture has inspired a new generation of bio-inspired computer vision systems called deep convolutional neural networks (DCNN), which are currently the best models for object recognition in natural images...
2016: Frontiers in Computational Neuroscience
Louis Gagnon, Amy F Smith, David A Boas, Anna Devor, Timothy W Secomb, Sava Sakadžić
Oxygen is delivered to brain tissue by a dense network of microvessels, which actively control cerebral blood flow (CBF) through vasodilation and contraction in response to changing levels of neural activity. Understanding these network-level processes is immediately relevant for (1) interpretation of functional Magnetic Resonance Imaging (fMRI) signals, and (2) investigation of neurological diseases in which a deterioration of neurovascular and neuro-metabolic physiology contributes to motor and cognitive decline...
2016: Frontiers in Computational Neuroscience
Saeed Reza Kheradpisheh, Masoud Ghodrati, Mohammad Ganjtabesh, Timothée Masquelier
Deep convolutional neural networks (DCNNs) have attracted much attention recently, and have shown to be able to recognize thousands of object categories in natural image databases. Their architecture is somewhat similar to that of the human visual system: both use restricted receptive fields, and a hierarchy of layers which progressively extract more and more abstracted features. Yet it is unknown whether DCNNs match human performance at the task of view-invariant object recognition, whether they make similar errors and use similar representations for this task, and whether the answers depend on the magnitude of the viewpoint variations...
2016: Scientific Reports
Peter T Bell, James M Shine
Higher brain function requires integration of distributed neuronal activity across large-scale brain networks. Recent scientific advances at the interface of subcortical brain anatomy and network science have highlighted the possible contribution of subcortical structures to large-scale network communication. We begin our review by examining neuroanatomical literature suggesting that diverse neural systems converge within the architecture of the basal ganglia and thalamus. These findings dovetail with those of recent network analyses that have demonstrated that the basal ganglia and thalamus belong to an ensemble of highly interconnected network hubs...
August 31, 2016: Neuroscience and Biobehavioral Reviews
Allison Fitch, Hayley Smith, Sylvia B Guillory, Zsuzsa Kaldy
Current neuroscientific models describe the functional neural architecture of visual working memory (VWM) as an interaction of the frontal-parietal control network and more posterior areas in the ventral visual stream (Jonides et al., 2008; D'Esposito and Postle, 2015; Eriksson et al., 2015). These models are primarily based on adult neuroimaging studies. However, VWM undergoes significant development in infancy and early childhood, and the goal of this mini-review is to examine how recent findings from neuroscientific studies of early VWM development can be reconciled with this model...
2016: Frontiers in Systems Neuroscience
Chandler Sours, Prashant Raghavan, W Alex Foxworthy, M Alex Meredith, Dina El Metwally, Jiachen Zhuo, John H Gilmore, Alexandre E Medina, Rao P Gullapalli
How the newborn brain adapts to its new multisensory environment has been a subject of debate. Although an early theory proposed that the brain acquires multisensory features as a result of postnatal experience, recent studies have demonstrated that the neonatal brain is already capable of processing multisensory information. For multisensory processing to be functional, it is a prerequisite that multisensory convergence among neural connections occur. However, multisensory connectivity has not been examined in human neonates nor are its location(s) or afferent sources understood...
August 31, 2016: Brain Imaging and Behavior
Manuela Chessa, Guido Maiello, Peter J Bex, Fabio Solari
We implement a neural model for the estimation of the focus of radial motion (FRM) at different retinal locations and assess the model by comparing its results with respect to the precision with which human observers can estimate the FRM in naturalistic motion stimuli. The model describes the deep hierarchy of the first stages of the dorsal visual pathway and is space variant, since it takes into account the retino-cortical transformation of the primate visual system through log-polar mapping. The log-polar transform of the retinal image is the input to the cortical motion-estimation stage, where optic flow is computed by a three-layer neural population...
January 1, 2016: Journal of Vision
A A Martins, P O Favaron, L de Jesus Oliveira, B T Schäfer, F D Oliveira, M A Miglino
Dogs have been studied for several reasons, such as the genetic improvement, their use as experimental models, in zoonotic research, cell therapy and as a model for human diseases. However, many features relating to the embryonic development of dogs remain unknown because of the absence of embryological studies. Considering the importance of the cardiorespiratory system in the development of embryos, the aim of this study was to investigate the development of the main cardiorespiratory organs of dog embryos and foetuses with estimated gestational ages from 16 to 46 days using macro- and microscopic descriptions...
October 2016: Reproduction in Domestic Animals, Zuchthygiene
Francisco Maciá-Pérez, Leandro Zambrano-Mendez, José-Vicente Berna-Martínez, Roberto Sepúlveda-Lima
The neuroregulator system in humans controls organ and system functioning. This system comprises a set of neural centres that are distributed along the spinal cord and act independently together with their nerve interconnections. The centres involved in this task were isolated in previous studies through investigations of the functioning and composition of the neuroregulator system of the lower urinary tract to elucidate their individual performances and enable the creation of a general neuroregulator system model capable of operating at the neuronal level...
October 1, 2016: Computers in Biology and Medicine
R Bianco, G Novembre, P E Keller, Kim Seung-Goo, F Scharf, A D Friederici, A Villringer, D Sammler
The ability to predict upcoming structured events based on long-term knowledge and contextual priors is a fundamental principle of human cognition. Tonal music triggers predictive processes based on structural properties of harmony, i.e., regularities defining the arrangement of chords into well-formed musical sequences. While the neural architecture of structure-based predictions during music perception is well described, little is known about the neural networks for analogous predictions in musical actions and how they relate to auditory perception...
August 16, 2016: NeuroImage
Inchul Lee
Human pancreatic islets show unique architecture in which α and δ cells are mostly at the peripheral and perivascular areas. It has remained unknown how such prototype is realized in every islet. Here, I report that fetal islets develop first in two distinct types consisting of β or α/δ cells, respectively. The α/δ islets are variable in shape, composed of α and δ cells evenly intermixed. They are vascularized better but encapsulated poorer than β islets in general. During the development, the β and α/δ islets adjoin and fuse with each other in such a way that α and δ cells form a crescent on β cells and, then, progress to encompass and encroach into β cells...
October 2016: Development, Growth & Differentiation
Ryan Chrenek, Laura M Magnotti, Gabriella R Herrera, Ruchira M Jha, David L Cardozo
Neural stem cells (NSCs) reside in a unique microenvironment within the central nervous system (CNS) called the NSC niche. Although they are relatively rare, niches have been previously characterized in both the brain and spinal cord of adult animals. Recently, another potential NSC niche has been identified in the filum terminale (FT), which is a thin band of tissue at the caudal end of the spinal cord. While previous studies have demonstrated that NSCs can be isolated from the FT, the in vivo architecture of this tissue and its relation to other NSC niches in the CNS has not yet been established...
August 11, 2016: Journal of Comparative Neurology
Seong Gon Kim, Nawanol Theera-Ampornpunt, Chih-Hao Fang, Mrudul Harwani, Ananth Grama, Somali Chaterji
BACKGROUND: Gene expression is mediated by specialized cis-regulatory modules (CRMs), the most prominent of which are called enhancers. Early experiments indicated that enhancers located far from the gene promoters are often responsible for mediating gene transcription. Knowing their properties, regulatory activity, and genomic targets is crucial to the functional understanding of cellular events, ranging from cellular homeostasis to differentiation. Recent genome-wide investigation of epigenomic marks has indicated that enhancer elements could be enriched for certain epigenomic marks, such as, combinatorial patterns of histone modifications...
2016: BMC Systems Biology
Gopalakrishnan Srinivasan, Abhronil Sengupta, Kaushik Roy
Spiking Neural Networks (SNNs) have emerged as a powerful neuromorphic computing paradigm to carry out classification and recognition tasks. Nevertheless, the general purpose computing platforms and the custom hardware architectures implemented using standard CMOS technology, have been unable to rival the power efficiency of the human brain. Hence, there is a need for novel nanoelectronic devices that can efficiently model the neurons and synapses constituting an SNN. In this work, we propose a heterostructure composed of a Magnetic Tunnel Junction (MTJ) and a heavy metal as a stochastic binary synapse...
2016: Scientific Reports
Elisabeth A Karuza, Sharon L Thompson-Schill, Danielle S Bassett
A core question in cognitive science concerns how humans acquire and represent knowledge about their environments. To this end, quantitative theories of learning processes have been formalized in an attempt to explain and predict changes in brain and behavior. We connect here statistical learning approaches in cognitive science, which are rooted in the sensitivity of learners to local distributional regularities, and network science approaches to characterizing global patterns and their emergent properties...
August 2016: Trends in Cognitive Sciences
Sharon L Hollins, Murray J Cairns
The developmental processes that establish the synaptic architecture of the brain while retaining capacity for activity-dependent remodeling, are complex and involve a combination of genetic and epigenetic influences. Dysregulation of these processes can lead to problems with neural circuitry which manifest in humans as a range of neurodevelopmental syndromes, such as schizophrenia, bipolar disorder and fragile X mental retardation. Recent studies suggest that prenatal, postnatal and intergenerational environmental factors play an important role in the aetiology of stress-related psychopathology...
August 2016: Progress in Neurobiology
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