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https://www.readbyqxmd.com/read/27909395/reversal-learning-in-humans-and-gerbils-dynamic-control-network-facilitates-learning
#1
Christian Jarvers, Tobias Brosch, André Brechmann, Marie L Woldeit, Andreas L Schulz, Frank W Ohl, Marcel Lommerzheim, Heiko Neumann
Biologically plausible modeling of behavioral reinforcement learning tasks has seen great improvements over the past decades. Less work has been dedicated to tasks involving contingency reversals, i.e., tasks in which the original behavioral goal is reversed one or multiple times. The ability to adjust to such reversals is a key element of behavioral flexibility. Here, we investigate the neural mechanisms underlying contingency-reversal tasks. We first conduct experiments with humans and gerbils to demonstrate memory effects, including multiple reversals in which subjects (humans and animals) show a faster learning rate when a previously learned contingency re-appears...
2016: Frontiers in Neuroscience
https://www.readbyqxmd.com/read/27890749/the-medial-and-lateral-lemnisci-anatomically-adjoined-but-functionally-distinct-fiber-tracts
#2
Ruben Rodríguez-Mena, Uğur Türe
OBJECTIVE: The dense and complex distribution of neural structures in the brain stem makes it challenging to understand their real configuration. We used the fiber microdissection technique to reveal the course of the medial and lateral lemnisci within the brain stem. Although these structures seem anatomically alike, they are functionally distinct. METHODS: Fifteen human brain stems and eight brain hemispheres (formalin-fixed and previously frozen) were dissected and studied under the operating microscope by applying the fiber microdissection technique...
November 24, 2016: World Neurosurgery
https://www.readbyqxmd.com/read/27886714/classification-of-ct-brain-images-based-on-deep-learning-networks
#3
Xiaohong W Gao, Rui Hui, Zengmin Tian
While computerised tomography (CT) may have been the first imaging tool to study human brain, it has not yet been implemented into clinical decision making process for diagnosis of Alzheimer's disease (AD). On the other hand, with the nature of being prevalent, inexpensive and non-invasive, CT does present diagnostic features of AD to a great extent. This study explores the significance and impact on the application of the burgeoning deep learning techniques to the task of classification of CT brain images, in particular utilising convolutional neural network (CNN), aiming at providing supplementary information for the early diagnosis of Alzheimer's disease...
January 2017: Computer Methods and Programs in Biomedicine
https://www.readbyqxmd.com/read/27886204/characterization-of-structural-connectivity-of-the-default-mode-network-in-dogs-using-diffusion-tensor-imaging
#4
Jennifer L Robinson, Madhura Baxi, Jeffrey S Katz, Paul Waggoner, Ronald Beyers, Edward Morrison, Nouha Salibi, Thomas S Denney, Vitaly Vodyanoy, Gopikrishna Deshpande
Diffusion tensor imaging (DTI) provides us an insight into the micro-architecture of white-matter tracts in the brain. This method has proved promising in understanding and investigating the neuronal tracts and structural connectivity between the brain regions in primates as well as rodents. The close evolutionary relationship between canines and humans may have spawned a unique bond in regard to social cognition rendering them useful as an animal model in translational research. In this study, we acquired diffusion data from anaesthetized dogs and created a DTI-based atlas for a canine model which could be used to investigate various white matter diseases...
November 25, 2016: Scientific Reports
https://www.readbyqxmd.com/read/27856312/empirical-validation-of-directed-functional-connectivity
#5
Ravi D Mill, Anto Bagic, Andreea Bostan, Walter Schneider, Michael W Cole
Mapping directions of influence in the human brain connectome represents the next phase in understanding its functional architecture. However, a host of methodological uncertainties have impeded the application of directed connectivity methods, which have primarily been validated via "ground truth" connectivity patterns embedded in simulated functional MRI (fMRI) and magneto-/electro-encephalography (MEG/EEG) datasets. Such simulations rely on many generative assumptions, and we hence utilized a different strategy involving empirical data in which a ground truth directed connectivity pattern could be anticipated with confidence...
November 14, 2016: NeuroImage
https://www.readbyqxmd.com/read/27825537/functional-connectivity-of-the-human-brain-in-utero
#6
REVIEW
Marion I van den Heuvel, Moriah E Thomason
The brain is subject to dramatic developmental processes during the prenatal period. Nevertheless, information about the development of functional brain networks during gestation is scarce. Until recently it has not been possible to probe function in the living human fetal brain. Advances in functional MRI have changed the paradigm, making it possible to measure spontaneous activity in the fetal brain and to cross-correlate functional signals to attain information about neural connectional architecture across human gestation...
December 2016: Trends in Cognitive Sciences
https://www.readbyqxmd.com/read/27825385/neurogenomics-and-the-role-of-a-large-mutational-target-on-rapid-behavioral-change
#7
Craig E Stanley, Rob J Kulathinal
BACKGROUND: Behavior, while complex and dynamic, is among the most diverse, derived, and rapidly evolving traits in animals. The highly labile nature of heritable behavioral change is observed in such evolutionary phenomena as the emergence of converged behaviors in domesticated animals, the rapid evolution of preferences, and the routine development of ethological isolation between diverging populations and species. In fact, it is believed that nervous system development and its potential to evolve a seemingly infinite array of behavioral innovations played a major role in the successful diversification of metazoans, including our own human lineage...
November 8, 2016: Biology Direct
https://www.readbyqxmd.com/read/27821758/mapping-human-temporal-and-parietal-neuronal-population-activity-and-functional-coupling-during-mathematical-cognition
#8
Amy L Daitch, Brett L Foster, Jessica Schrouff, Vinitha Rangarajan, Itır Kaşikçi, Sandra Gattas, Josef Parvizi
Brain areas within the lateral parietal cortex (LPC) and ventral temporal cortex (VTC) have been shown to code for abstract quantity representations and for symbolic numerical representations, respectively. To explore the fast dynamics of activity within each region and the interaction between them, we used electrocorticography recordings from 16 neurosurgical subjects implanted with grids of electrodes over these two regions and tracked the activity within and between the regions as subjects performed three different numerical tasks...
November 7, 2016: Proceedings of the National Academy of Sciences of the United States of America
https://www.readbyqxmd.com/read/27806376/single-cell-rna-seq-supports-a-developmental-hierarchy-in-human-oligodendroglioma
#9
Itay Tirosh, Andrew S Venteicher, Christine Hebert, Leah E Escalante, Anoop P Patel, Keren Yizhak, Jonathan M Fisher, Christopher Rodman, Christopher Mount, Mariella G Filbin, Cyril Neftel, Niyati Desai, Jackson Nyman, Benjamin Izar, Christina C Luo, Joshua M Francis, Aanand A Patel, Maristela L Onozato, Nicolo Riggi, Kenneth J Livak, Dave Gennert, Rahul Satija, Brian V Nahed, William T Curry, Robert L Martuza, Ravindra Mylvaganam, A John Iafrate, Matthew P Frosch, Todd R Golub, Miguel N Rivera, Gad Getz, Orit Rozenblatt-Rosen, Daniel P Cahill, Michelle Monje, Bradley E Bernstein, David N Louis, Aviv Regev, Mario L Suvà
Although human tumours are shaped by the genetic evolution of cancer cells, evidence also suggests that they display hierarchies related to developmental pathways and epigenetic programs in which cancer stem cells (CSCs) can drive tumour growth and give rise to differentiated progeny. Yet, unbiased evidence for CSCs in solid human malignancies remains elusive. Here we profile 4,347 single cells from six IDH1 or IDH2 mutant human oligodendrogliomas by RNA sequencing (RNA-seq) and reconstruct their developmental programs from genome-wide expression signatures...
November 2, 2016: Nature
https://www.readbyqxmd.com/read/27801899/analysis-of-induced-pluripotent-stem-cells-carrying-22q11-2-deletion
#10
M Toyoshima, W Akamatsu, Y Okada, T Ohnishi, S Balan, Y Hisano, Y Iwayama, T Toyota, T Matsumoto, N Itasaka, S Sugiyama, M Tanaka, M Yano, B Dean, H Okano, T Yoshikawa
Given the complexity and heterogeneity of the genomic architecture underlying schizophrenia, molecular analyses of these patients with defined and large effect-size genomic defects could provide valuable clues. We established human-induced pluripotent stem cells from two schizophrenia patients with the 22q11.2 deletion (two cell lines from each subject, total of four cell lines) and three controls (total of four cell lines). Neurosphere size, neural differentiation efficiency, neurite outgrowth, cellular migration and the neurogenic-to-gliogenic competence ratio were significantly reduced in patient-derived cells...
November 1, 2016: Translational Psychiatry
https://www.readbyqxmd.com/read/27798142/longitudinal-study-of-the-emerging-functional-connectivity-asymmetry-of-primary-language-regions-during-infancy
#11
Robert W Emerson, Wei Gao, Weili Lin
: Asymmetry in the form of left-hemisphere lateralization is a striking characteristic of the cerebral regions involved in the adult language network. In this study, we leverage a large sample of typically developing human infants with longitudinal resting-state functional magnetic resonance imaging scans to delineate the trajectory of interhemispheric functional asymmetry in language-related regions during the first 2 years of life. We derived the trajectory of interhemispheric functional symmetry of the inferior frontal gyrus (IFG) and superior temporal gyrus (STG), the sensory and visual cortices, and two higher-order regions within the intraparietal sulcus and dorsolateral prefrontal cortex...
October 19, 2016: Journal of Neuroscience: the Official Journal of the Society for Neuroscience
https://www.readbyqxmd.com/read/27797550/the-cognitive-architecture-of-anxiety-like-behavioral-inhibition
#12
Dominik R Bach
The combination of reward and potential threat is termed approach/avoidance conflict and elicits specific behaviors, including passive avoidance and behavioral inhibition (BI). Anxiety-relieving drugs reduce these behaviors, and a rich psychological literature has addressed how personality traits dominated by BI predispose for anxiety disorders. Yet, a formal understanding of the cognitive inference and planning processes underlying anxiety-like BI is lacking. Here, we present and empirically test such formalization in the terminology of reinforcement learning...
October 31, 2016: Journal of Experimental Psychology. Human Perception and Performance
https://www.readbyqxmd.com/read/27780529/self-similarity-and-recursion-as-default-modes-in-human-cognition
#13
Florian P Fischmeister, Mauricio J D Martins, Roland Beisteiner, W Tecumseh Fitch
Humans generate recursive hierarchies in a variety of domains, including linguistic, social and visuo-spatial modalities. The ability to represent recursive structures has been hypothesized to increase the efficiency of hierarchical processing. Theoretical work together with recent empirical findings suggests that the ability to represent the self-similar structure of hierarchical recursive stimuli may be supported by internal neural representations that compress raw external information and increase efficiency...
September 23, 2016: Cortex; a Journal Devoted to the Study of the Nervous System and Behavior
https://www.readbyqxmd.com/read/27764661/integrated-brain-network-architecture-supports-cognitive-task-performance
#14
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
https://www.readbyqxmd.com/read/27734318/deep-learning-architecture-for-air-quality-predictions
#15
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
https://www.readbyqxmd.com/read/27690106/impact-of-the-autism-associated-long-noncoding-rna-msnp1as-on-neuronal-architecture-and-gene-expression-in-human-neural-progenitor-cells
#16
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...
September 28, 2016: Genes
https://www.readbyqxmd.com/read/27683540/synapse-centric-mapping-of-cortical-models-to-the-spinnaker-neuromorphic-architecture
#17
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
https://www.readbyqxmd.com/read/27642281/humans-and-deep-networks-largely-agree-on-which-kinds-of-variation-make-object-recognition-harder
#18
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
https://www.readbyqxmd.com/read/27630556/modeling-of-cerebral-oxygen-transport-based-on-in-vivo-microscopic-imaging-of-microvascular-network-structure-blood-flow-and-oxygenation
#19
REVIEW
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
https://www.readbyqxmd.com/read/27601096/deep-networks-can-resemble-human-feed-forward-vision-in-invariant-object-recognition
#20
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
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