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Computational neuroscience

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https://www.readbyqxmd.com/read/29028209/digital-implementation-of-the-two-compartmental-pinsky-rinzel-pyramidal-neuron-model
#1
Elahe Rahimian, Soheil Zabihi, Mahmood Amiri, Bernabe Linares-Barranco
It is believed that brain-like computing system can be achieved by the fusion of electronics and neuroscience. In this way, the optimized digital hardware implementation of neurons, primary units of nervous system, play a vital role in neuromorphic applications. Moreover, one of the main features of pyramidal neurons in cortical areas is bursting activities that has a critical role in synaptic plasticity. The Pinsky-Rinzel model is a nonlinear two-compartmental model for CA3 pyramidal cell that is widely used in neuroscience...
October 12, 2017: IEEE Transactions on Biomedical Circuits and Systems
https://www.readbyqxmd.com/read/29024649/obsessing-about-uncertainty
#2
Jacqueline Scholl, Matthew F S Rushworth
A striking observation in obsessive-compulsive disorder is that patients know that their obsessions and compulsions are excessive, but their symptoms nevertheless persist. Drawing on computational models from basic neuroscience, Vaghi and colleagues (2017) suggest a quantitative account of this clinical finding.
October 11, 2017: Neuron
https://www.readbyqxmd.com/read/29018336/encoding-and-decoding-models-in-cognitive-electrophysiology
#3
REVIEW
Christopher R Holdgraf, Jochem W Rieger, Cristiano Micheli, Stephanie Martin, Robert T Knight, Frederic E Theunissen
Cognitive neuroscience has seen rapid growth in the size and complexity of data recorded from the human brain as well as in the computational tools available to analyze this data. This data explosion has resulted in an increased use of multivariate, model-based methods for asking neuroscience questions, allowing scientists to investigate multiple hypotheses with a single dataset, to use complex, time-varying stimuli, and to study the human brain under more naturalistic conditions. These tools come in the form of "Encoding" models, in which stimulus features are used to model brain activity, and "Decoding" models, in which neural features are used to generated a stimulus output...
2017: Frontiers in Systems Neuroscience
https://www.readbyqxmd.com/read/29016105/aggregation-induced-emission-luminogen-with-deep-red-emission-for-through-skull-three-photon-fluorescence-imaging-of-mouse
#4
Yalun Wang, Ming Chen, Nuernisha Alifu, Shiwu Li, Wei Qin, Anjun Qin, Ben Zhong Tang, Jun Qian
Imaging the brain with high integrity is of great importance to neuroscience and related applications. X-ray computed tomography (CT) and magnetic resonance imaging (MRI) are two clinically used modalities for deep-penetration brain imaging. However, their spatial resolution is quite limited. Two-photon fluorescence microscopic (2PFM) imaging with its femtosecond (fs) excitation wavelength in the traditional near-infrared (NIR) region (700-1000 nm) is able to realize deep-tissue and high-resolution brain imaging...
October 12, 2017: ACS Nano
https://www.readbyqxmd.com/read/28989749/a-geometric-method-for-eigenvalue-problems-with-low-rank-perturbations
#5
Thomas J Anastasio, Andrea K Barreiro, Jared C Bronski
We consider the problem of finding the spectrum of an operator taking the form of a low-rank (rank one or two) non-normal perturbation of a well-understood operator, motivated by a number of problems of applied interest which take this form. We use the fact that the system is a low-rank perturbation of a solved problem, together with a simple idea of classical differential geometry (the envelope of a family of curves) to completely analyse the spectrum. We use these techniques to analyse three problems of this form: a model of the oculomotor integrator due to Anastasio & Gad (2007 J...
September 2017: Royal Society Open Science
https://www.readbyqxmd.com/read/28988827/self-as-object-emerging-trends-in-self-research
#6
REVIEW
Jie Sui, Xiaosi Gu
Self representation is fundamental to mental functions. While the self has mostly been studied in traditional psychophilosophical terms ('self as subject'), recent laboratory work suggests that the self can be measured quantitatively by assessing biases towards self-associated stimuli ('self as object'). Here, we summarize new quantitative paradigms for assessing the self, drawn from psychology, neuroeconomics, embodied cognition, and social neuroscience. We then propose a neural model of the self as an emerging property of interactions between a core 'self network' (e...
October 5, 2017: Trends in Neurosciences
https://www.readbyqxmd.com/read/28981612/local-global-parcellation-of-the-human-cerebral-cortex-from-intrinsic-functional-connectivity-mri
#7
Alexander Schaefer, Ru Kong, Evan M Gordon, Timothy O Laumann, Xi-Nian Zuo, Avram J Holmes, Simon B Eickhoff, B T Thomas Yeo
A central goal in systems neuroscience is the parcellation of the cerebral cortex into discrete neurobiological "atoms". Resting-state functional magnetic resonance imaging (rs-fMRI) offers the possibility of in vivo human cortical parcellation. Almost all previous parcellations relied on 1 of 2 approaches. The local gradient approach detects abrupt transitions in functional connectivity patterns. These transitions potentially reflect cortical areal boundaries defined by histology or visuotopic fMRI. By contrast, the global similarity approach clusters similar functional connectivity patterns regardless of spatial proximity, resulting in parcels with homogeneous (similar) rs-fMRI signals...
July 18, 2017: Cerebral Cortex
https://www.readbyqxmd.com/read/28972845/the-strength-of-social-norms-across-human-groups
#8
Michele J Gelfand, Jesse R Harrington, Joshua Conrad Jackson
Social norms are a defining feature of human psychology, yet our understanding of them is still underdeveloped. In this article, we present our own cross-cultural research program on tightness-looseness (TL)-which draws on field, experimental, computational, and neuroscience methods-to illustrate how going beyond Western borders is critical for understanding social norms' functions and their multilevel consequences. Cross-cultural research enables us to account for the universal features of norm psychology but also explains the great cultural diversity we see in social norms around the globe...
September 2017: Perspectives on Psychological Science: a Journal of the Association for Psychological Science
https://www.readbyqxmd.com/read/28972125/sub-millisecond-optogenetic-control-of-neuronal-firing-with-two-photon-holographic-photoactivation-of-chronos
#9
E Ronzitti, R Conti, V Zampini, D Tanese, A J Foust, N Klapoetke, E S Boyden, E Papagiakoumou, V Emiliani
Optogenetic neuronal network manipulation promises to unravel a long-standing mystery in neuroscience: how does microcircuit activity causally relate to behavioral and pathological states? The challenge to evoke spikes with high spatial and temporal complexity necessitates further joint development of light-delivery approaches and custom opsins. Two-photon light-targeting strategies demonstrated, in-depth generation of action potentials in photosensitive neurons both in-vitro and in-vivo, but thus far lack the temporal precision necessary to induce precisely timed spiking events...
October 2, 2017: Journal of Neuroscience: the Official Journal of the Society for Neuroscience
https://www.readbyqxmd.com/read/28968384/a-theoretical-framework-for-analyzing-coupled-neuronal-networks-application-to-the-olfactory-system
#10
Andrea K Barreiro, Shree Hari Gautam, Woodrow L Shew, Cheng Ly
Determining how synaptic coupling within and between regions is modulated during sensory processing is an important topic in neuroscience. Electrophysiological recordings provide detailed information about neural spiking but have traditionally been confined to a particular region or layer of cortex. Here we develop new theoretical methods to study interactions between and within two brain regions, based on experimental measurements of spiking activity simultaneously recorded from the two regions. By systematically comparing experimentally-obtained spiking statistics to (efficiently computed) model spike rate statistics, we identify regions in model parameter space that are consistent with the experimental data...
October 2017: PLoS Computational Biology
https://www.readbyqxmd.com/read/28968248/shortest-path-based-network-analysis-to-characterize-cognitive-load-states-of-human-brain-using-eeg-based-functional%C3%A2-brain-networks
#11
M Thilaga, R Vijayalakshmi, R Nadarajan, D Nandagopal
Understanding and analyzing the dynamic interactions among the millions of spatially distributed and functionally connected regions in the human brain constituting a massively parallel communication system is one of the major challenges in computational neuroscience. Many studies in the recent past have employed graph theory to efficiently model, quantitatively analyze and understand the brain's electrical activity. Since, the human brain is believed to broadcast information with reduced material and metabolic costs, identifying various brain regions in the shortest pathways of information dissemination becomes essential to understand the intricacies of brain functioning...
September 28, 2017: Journal of Integrative Neuroscience
https://www.readbyqxmd.com/read/28967376/a-very-early-rehabilitation-trial-after-stroke-avert-a-phase-iii-multicentre-randomised-controlled-trial
#12
Peter Langhorne, Olivia Wu, Helen Rodgers, Ann Ashburn, Julie Bernhardt
BACKGROUND: Mobilising patients early after stroke [early mobilisation (EM)] is thought to contribute to the beneficial effects of stroke unit care but it is poorly defined and lacks direct evidence of benefit. OBJECTIVES: We assessed the effectiveness of frequent higher dose very early mobilisation (VEM) after stroke. DESIGN: We conducted a parallel-group, single-blind, prospective randomised controlled trial with blinded end-point assessment using a web-based computer-generated stratified randomisation...
September 2017: Health Technology Assessment: HTA
https://www.readbyqxmd.com/read/28966147/understanding-psychiatric-disease-by-capturing-ecologically-relevant-features-of-learning-and-decision-making
#13
REVIEW
Jacqueline Scholl, Miriam Klein-Flügge
Recent research in cognitive neuroscience has begun to uncover the processes underlying increasingly complex voluntary behaviours, including learning and decision-making. Partly this success has been possible by progressing from simple experimental tasks to paradigms that incorporate more ecological features. More specifically, the premise is that to understand cognitions and brain functions relevant for real life, we need to introduce some of the ecological challenges that we have evolved to solve. This often entails an increase in task complexity, which can be managed by using computational models to help parse complex behaviours into specific component mechanisms...
September 28, 2017: Behavioural Brain Research
https://www.readbyqxmd.com/read/28965665/editorial-overview-computational-neuroscience
#14
EDITORIAL
Christian Machens, Adrienne Fairhall
No abstract text is available yet for this article.
September 28, 2017: Current Opinion in Neurobiology
https://www.readbyqxmd.com/read/28960497/using-spatiotemporal-source-separation-to-identify-prominent-features-in-multichannel-data-without-sinusoidal-filters
#15
Michael X Cohen
The number of simultaneously recorded electrodes in neuroscience is steadily increasing, providing new opportunities for understanding brain function, but also new challenges for appropriately dealing with the increase in dimensionality. Multivariate source-separation analysis methods have been particularly effective at improving signal-to-noise ratio while reducing the dimensionality of the data, and are widely used for cleaning, classifying, and source-localizing multichannel neural time series data. Most source-separation methods produce a spatial component (that is, a weighted combination of channels to produce one time series); here, this is extended to apply source-separation to a time series, with the idea of obtaining a weighted combination of successive time points, such that the weights are optimized to satisfy some criteria...
September 27, 2017: European Journal of Neuroscience
https://www.readbyqxmd.com/read/28957020/capturing-the-dynamical-repertoire-of-single-neurons-with-generalized-linear-models
#16
Alison I Weber, Jonathan W Pillow
A key problem in computational neuroscience is to find simple, tractable models that are nevertheless flexible enough to capture the response properties of real neurons. Here we examine the capabilities of recurrent point process models known as Poisson generalized linear models (GLMs). These models are defined by a set of linear filters and a point nonlinearity and are conditionally Poisson spiking. They have desirable statistical properties for fitting and have been widely used to analyze spike trains from electrophysiological recordings...
September 28, 2017: Neural Computation
https://www.readbyqxmd.com/read/28941805/foundations-of-anticipatory-logic-in-biology-and-physics
#17
REVIEW
Jesse S Bettinger, Timothy E Eastman
Recent advances in modern physics and biology reveal several scenarios in which top-down effects (Ellis, 2016) and anticipatory systems (Rosen, 1980) indicate processes at work enabling active modeling and inference such that anticipated effects project onto potential causes. We extrapolate a broad landscape of anticipatory systems in the natural sciences extending to computational neuroscience of perception in the capacity of Bayesian inferential models of predictive processing. This line of reasoning also comes with philosophical foundations, which we develop in terms of counterfactual reasoning and possibility space, Whitehead's process thought, and correlations with Eastern wisdom traditions...
September 20, 2017: Progress in Biophysics and Molecular Biology
https://www.readbyqxmd.com/read/28926765/texture-and-art-with-deep-neural-networks
#18
REVIEW
Leon A Gatys, Alexander S Ecker, Matthias Bethge
Although the study of biological vision and computer vision attempt to understand powerful visual information processing from different angles, they have a long history of informing each other. Recent advances in texture synthesis that were motivated by visual neuroscience have led to a substantial advance in image synthesis and manipulation in computer vision using convolutional neural networks (CNNs). Here, we review these recent advances and discuss how they can in turn inspire new research in visual perception and computational neuroscience...
September 16, 2017: Current Opinion in Neurobiology
https://www.readbyqxmd.com/read/28920892/computationally-efficient-algorithms-for-sparse-dynamic-solutions-to-the-eeg-source-localization-problem
#19
Elvira Pirondini, Behtash Babadi, Gabriel Obregon-Henao, Camilo Lamus, Wasim Q Malik, Matti S Hamalainen, Patrick L Purdon
OBJECTIVE: Electroencephalography (EEG) and magnetoencephalography (MEG) non-invasively record scalp electromagnetic fields generated by cerebral currents, revealing millisecond-level brain dynamics useful for neuroscience and clinical applications. Estimating the currents that generate these fields, i.e., source localization, is an ill-conditioned inverse problem. Solutions to this problem have focused on spatial continuity constraints, dynamic modeling, or sparsity constraints. The combination of these key ideas could offer significant performance improvements, but substantial computational costs pose a challenge for practical application of such approaches...
September 14, 2017: IEEE Transactions on Bio-medical Engineering
https://www.readbyqxmd.com/read/28910997/paediatric-nuclear-medicine-imaging
#20
Lorenzo Biassoni, Marina Easty
Background: Nuclear medicine imaging explores tissue viability and function by using radiotracers that are taken up at cellular level with different mechanism. This imaging technique can also be used to assess blood flow and transit through tubular organs. Nuclear medicine imaging has been used in paediatrics for decades and this field is continuously evolving. Sources of data: The data presented comes from clinical experience and some milestone papers on the subject...
September 1, 2017: British Medical Bulletin
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