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https://www.readbyqxmd.com/read/28821672/audio-visual-modulation-in-mouse-v1-depends-on-cross-modal-stimulus-configuration-and-congruency
#1
Guido T Meijer, Jorrit S Montijn, Cyriel M A Pennartz, Carien S Lansink
The sensory neocortex is a highly connected associative network, in which information from multiple senses is integrated, even at the level of the primary sensory areas. Although this view is supported by a growing body of empirical evidence, the neural mechanisms of cross-modal integration in primary sensory areas, such as the primary visual cortex (V1), are still largely unknown. Using two-photon calcium imaging in awake mice, we show that the encoding of audio-visual stimuli in V1 neuronal populations is highly dependent on the features of the stimulus constituents...
August 8, 2017: Journal of Neuroscience: the Official Journal of the Society for Neuroscience
https://www.readbyqxmd.com/read/28821649/effector-invariant-movement-encoding-in-the-human-motor-system
#2
Shlomi Haar, Ilan Dinstein, Ilan Shelef, Opher Donchin
Ipsilateral motor areas of cerebral cortex are active during arm movements and even reliably predict movement direction. Is coding similar during ipsilateral and contralateral movements? If so, is it in extrinsic (world-centered) or intrinsic (joint-configuration) coordinates? We addressed these questions by examining the similarity of multi-voxel fMRI patterns in visuomotor cortical regions during unilateral reaching movements with both arms. The results of three complementary analyses revealed that fMRI response patterns were similar across right and left arm movements to identical targets (extrinsic coordinates) in visual cortices, and across movements with equivalent joint-angles (intrinsic coordinates) in motor cortices...
August 16, 2017: Journal of Neuroscience: the Official Journal of the Society for Neuroscience
https://www.readbyqxmd.com/read/28821642/super-optimal-perceptual-integration-suggests-a-place-based-representation-of-pitch-at-high-frequencies
#3
Bonnie K Lau, Anahita H Mehta, Andrew J Oxenham
Pitch, the perceptual correlate of sound repetition rate or frequency, plays an important role in speech perception, music perception, and listening in complex acoustic environments. Despite its perceptual importance, the neural mechanisms underlying pitch remain poorly understood. Although cortical regions responsive to pitch have been identified, little is known about how pitch information is extracted from the inner ear itself. The two primary theories of peripheral pitch coding involve stimulus-driven spike timing, or phase locking, in the auditory nerve (time code), and the spatial distribution of responses along the length of the cochlear partition (place code)...
August 17, 2017: Journal of Neuroscience: the Official Journal of the Society for Neuroscience
https://www.readbyqxmd.com/read/28814638/field-repetition-and-local-mapping-in-the-hippocampus-and-medial-entorhinal-cortex
#4
Roddy M Grieves, Éléonore Duvelle, Emma R Wood, Paul Anthony Dudchenko
Hippocampal place cells support spatial cognition and are thought to form the neural substrate of a global 'cognitive map'. A widely held view is that parts of the hippocampus also underlie the ability to separate patterns, or to provide different neural codes for distinct environments. However, a number of studies have shown that in environments composed of multiple, repeating compartments, place cells and other spatially modulated neurons show the same activity in each local area. This repetition of firing fields may reflect pattern completion, and may make it difficult for animals to distinguish similar local environments...
August 16, 2017: Journal of Neurophysiology
https://www.readbyqxmd.com/read/28813643/multi-connection-pattern-analysis-decoding-the-representational-content-of-neural-communication
#5
Yuanning Li, R Mark Richardson, Avniel Singh Ghuman
The lack of multivariate methods for decoding the representational content of interregional neural communication has left it difficult to know what information is represented in distributed brain circuit interactions. Here we present Multi-Connection Pattern Analysis (MCPA), which works by learning mappings between the activity patterns of the populations as a factor of the information being processed. These maps are used to predict the activity from one neural population based on the activity from the other population...
August 13, 2017: NeuroImage
https://www.readbyqxmd.com/read/28811461/sparse-orthogonal-population-representation-of-spatial-context-in-the-retrosplenial-cortex
#6
Dun Mao, Steffen Kandler, Bruce L McNaughton, Vincent Bonin
Sparse orthogonal coding is a key feature of hippocampal neural activity, which is believed to increase episodic memory capacity and to assist in navigation. Some retrosplenial cortex (RSC) neurons convey distributed spatial and navigational signals, but place-field representations such as observed in the hippocampus have not been reported. Combining cellular Ca(2+) imaging in RSC of mice with a head-fixed locomotion assay, we identified a population of RSC neurons, located predominantly in superficial layers, whose ensemble activity closely resembles that of hippocampal CA1 place cells during the same task...
August 15, 2017: Nature Communications
https://www.readbyqxmd.com/read/28811258/category-selective-human-brain-processes-elicited-in-fast-periodic-visual-stimulation-streams-are-immune-to-temporal-predictability
#7
Genevieve L Quek, Bruno Rossion
Recording direct neural activity when periodically inserting exemplars of a particular category in a rapid visual stream of other objects offers an objective and efficient way to quantify perceptual categorization and characterize its spatiotemporal dynamics. However, since periodicity entails predictability, perceptual categorization processes identified within this framework may be partly generated or modulated by temporal expectations. Here we present a stringent test of the hypothesis that temporal predictability generates or modulates category-selective neural processes as measured in a rapid periodic visual stimulation stream...
August 12, 2017: Neuropsychologia
https://www.readbyqxmd.com/read/28810905/omni-polya-a-method-and-tool-for-accurate-recognition-of-poly-a-signals-in-human-genomic-dna
#8
Arturo Magana-Mora, Manal Kalkatawi, Vladimir B Bajic
BACKGROUND: Polyadenylation is a critical stage of RNA processing during the formation of mature mRNA, and is present in most of the known eukaryote protein-coding transcripts and many long non-coding RNAs. The correct identification of poly(A) signals (PAS) not only helps to elucidate the 3'-end genomic boundaries of a transcribed DNA region and gene regulatory mechanisms but also gives insight into the multiple transcript isoforms resulting from alternative PAS. Although progress has been made in the in-silico prediction of genomic signals, the recognition of PAS in DNA genomic sequences remains a challenge...
August 15, 2017: BMC Genomics
https://www.readbyqxmd.com/read/28809708/on-multiple-aer-handshaking-channels-over-high-speed-bit-serial-bidirectional-lvds-links-with-flow-control-and-clock-correction-on-commercial-fpgas-for-scalable-neuromorphic-systems
#9
Amirreza Yousefzadeh, Miroslaw Jablonski, Taras Iakymchuk, Alejandro Linares-Barranco, Alfredo Rosado, Luis A Plana, Steve Temple, Teresa Serrano-Gotarredona, Steve B Furber, Bernabe Linares-Barranco
Address event representation (AER) is a widely employed asynchronous technique for interchanging "neural spikes" between different hardware elements in neuromorphic systems. Each neuron or cell in a chip or a system is assigned an address (or ID), which is typically communicated through a high-speed digital bus, thus time-multiplexing a high number of neural connections. Conventional AER links use parallel physical wires together with a pair of handshaking signals (request and acknowledge). In this paper, we present a fully serial implementation using bidirectional SATA connectors with a pair of low-voltage differential signaling (LVDS) wires for each direction...
August 14, 2017: IEEE Transactions on Biomedical Circuits and Systems
https://www.readbyqxmd.com/read/28806715/recurrent-networks-with-soft-thresholding-nonlinearities-for-lightweight-coding
#10
MohammadMehdi Kafashan, ShiNung Ching
A long-standing and influential hypothesis in neural information processing is that early sensory networks adapt themselves to produce efficient codes of afferent inputs. Here, we show how a nonlinear recurrent network provides an optimal solution for the efficient coding of an afferent input and its history. We specifically consider the problem of producing lightweight codes, ones that minimize both ℓ1 and ℓ2 constraints on sparsity and energy, respectively. When embedded in a linear coding paradigm, this problem results in a non-smooth convex optimization problem...
July 22, 2017: Neural Networks: the Official Journal of the International Neural Network Society
https://www.readbyqxmd.com/read/28801591/new-variant-and-expression-studies-provide-further-insight-into-the-genotype-phenotype-correlation-in-yap1-related-developmental-eye-disorders
#11
R Holt, F Ceroni, D A Bax, S Broadgate, D Gold Diaz, C Santos, D Gerrelli, N K Ragge
YAP1, which encodes the Yes-associated protein 1, is part of the Hippo pathway involved in development, growth, repair and homeostasis. Nonsense YAP1 mutations have been shown to co-segregate with autosomal dominantly inherited coloboma. Therefore, we screened YAP1 for variants in a cohort of 258 undiagnosed UK patients with developmental eye disorders, including anophthalmia, microphthalmia and coloboma. We identified a novel 1 bp deletion in YAP1 in a boy with bilateral microphthalmia and bilateral chorioretinal coloboma...
August 11, 2017: Scientific Reports
https://www.readbyqxmd.com/read/28801251/modeling-correlated-noise-is-necessary-to-decode-uncertainty
#12
REVIEW
R S van Bergen, J F M Jehee
Brain decoding algorithms form an important part of the arsenal of analysis tools available to neuroscientists, allowing for a more detailed study of the kind of information represented in patterns of cortical activity. While most current decoding algorithms focus on estimating a single, most likely stimulus from the pattern of noisy fMRI responses, the presence of noise causes this estimate to be uncertain. This uncertainty in stimulus estimates is a potentially highly relevant aspect of cortical stimulus processing, and features prominently in Bayesian or probabilistic models of neural coding...
August 8, 2017: NeuroImage
https://www.readbyqxmd.com/read/28801185/neuroimaging-epigenetics-challenges-and-recommendations-for-best-practices
#13
REVIEW
Katie Lancaster, James P Morris, Jessica J Connelly
Neuroimaging epigenetics is an interdisciplinary application of epigenetics to cognitive neuroscience that seeks to identify molecular and neural predictors of human behavior. This approach can be sensitive to the dynamic interaction between biological predisposition and environmental influences, and is potentially more informative than an approach using static genetic code. Recent work in this field has generated considerable enthusiasm, yet caution is warranted since any novel cross-disciplinary approach lacks a set of established conventions or standards...
August 8, 2017: Neuroscience
https://www.readbyqxmd.com/read/28797034/unsupervised-learning-of-temporal-features-for-word-categorization-in-a-spiking-neural-network-model-of-the-auditory-brain
#14
Irina Higgins, Simon Stringer, Jan Schnupp
The nature of the code used in the auditory cortex to represent complex auditory stimuli, such as naturally spoken words, remains a matter of debate. Here we argue that such representations are encoded by stable spatio-temporal patterns of firing within cell assemblies known as polychronous groups, or PGs. We develop a physiologically grounded, unsupervised spiking neural network model of the auditory brain with local, biologically realistic, spike-time dependent plasticity (STDP) learning, and show that the plastic cortical layers of the network develop PGs which convey substantially more information about the speaker independent identity of two naturally spoken word stimuli than does rate encoding that ignores the precise spike timings...
2017: PloS One
https://www.readbyqxmd.com/read/28796619/unsupervised-t-distributed-video-hashing-and-its-deep-hashing-extension
#15
Yanbin Hao, Tingting Mu, John Y Goulermas, Jianguo Jiang, Richang Hong, Meng Wang
In this work, a novel unsupervised hashing algorithm, referred to as t-USMVH, and its extension to unsupervised deep hashing, referred to as t-UDH, are proposed to support large-scale video-to-video retrieval. To improve robustness of the unsupervised learning, t-USMVH combines multiple types of feature representations and effectively fuses them by examining a continuous relevance score based on a Gaussian estimation over pairwise distances, and also a discrete neighbor score based on the cardinality of reciprocal neighbors...
August 7, 2017: IEEE Transactions on Image Processing: a Publication of the IEEE Signal Processing Society
https://www.readbyqxmd.com/read/28783639/supervised-learning-based-on-temporal-coding-in-spiking-neural-networks
#16
Hesham Mostafa
Gradient descent training techniques are remarkably successful in training analog-valued artificial neural networks (ANNs). Such training techniques, however, do not transfer easily to spiking networks due to the spike generation hard nonlinearity and the discrete nature of spike communication. We show that in a feedforward spiking network that uses a temporal coding scheme where information is encoded in spike times instead of spike rates, the network input-output relation is differentiable almost everywhere...
August 1, 2017: IEEE Transactions on Neural Networks and Learning Systems
https://www.readbyqxmd.com/read/28782642/great-expectations-is-there-evidence-for-predictive-coding-in-auditory-cortex
#17
REVIEW
Micha Heilbron, Maria Chait
Predictive coding is possibly one of the most influential, comprehensive, and controversial theories of neural function. Whilst proponents praise its explanatory potential, critics object that key tenets of the theory are untested or even untestable. The present article critically examines existing evidence for predictive coding in the auditory modality. Specifically, we identify five key assumptions of the theory and evaluate each in the light of animal, human and modelling studies of auditory pattern processing...
August 3, 2017: Neuroscience
https://www.readbyqxmd.com/read/28782181/public-regulatory-databases-as-a-source-of-insight-for-neuromodulation-devices-stimulation-parameters
#18
REVIEW
Doe Kumsa, G Karl Steinke, Gregory F Molnar, Eric M Hudak, Fred W Montague, Shawn C Kelley, Darrel F Untereker, Alan Shi, Benjamin P Hahn, Chris Condit, Hyowon Lee, Dawn Bardot, Jose A Centeno, Victor Krauthamer, Pavel A Takmakov
OBJECTIVE: The Shannon model is often used to define an expected boundary between non-damaging and damaging modes of electrical neurostimulation. Numerous preclinical studies have been performed by manufacturers of neuromodulation devices using different animal models and a broad range of stimulation parameters while developing devices for clinical use. These studies are mostly absent from peer-reviewed literature, which may lead to this information being overlooked by the scientific community...
August 7, 2017: Neuromodulation: Journal of the International Neuromodulation Society
https://www.readbyqxmd.com/read/28777636/neural-decoder-for-topological-codes
#19
Giacomo Torlai, Roger G Melko
We present an algorithm for error correction in topological codes that exploits modern machine learning techniques. Our decoder is constructed from a stochastic neural network called a Boltzmann machine, of the type extensively used in deep learning. We provide a general prescription for the training of the network and a decoding strategy that is applicable to a wide variety of stabilizer codes with very little specialization. We demonstrate the neural decoder numerically on the well-known two-dimensional toric code with phase-flip errors...
July 21, 2017: Physical Review Letters
https://www.readbyqxmd.com/read/28771497/sinc-saliency-injected-neural-codes-for-representation-and-efficient-retrieval-of-medical-radiographs
#20
Jamil Ahmad, Muhammad Sajjad, Irfan Mehmood, Sung Wook Baik
Medical image collections contain a wealth of information which can assist radiologists and medical experts in diagnosis and disease detection for making well-informed decisions. However, this objective can only be realized if efficient access is provided to semantically relevant cases from the ever-growing medical image repositories. In this paper, we present an efficient method for representing medical images by incorporating visual saliency and deep features obtained from a fine-tuned convolutional neural network (CNN) pre-trained on natural images...
2017: PloS One
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