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https://www.readbyqxmd.com/read/28533456/colour-vision-and-coevolution-in-avian-brood-parasitism
#1
REVIEW
Mary Caswell Stoddard, Mark E Hauber
The coevolutionary interactions between avian brood parasites and their hosts provide a powerful system for investigating the diversity of animal coloration. Specifically, reciprocal selection pressure applied by hosts and brood parasites can give rise to novel forms and functions of animal coloration, which largely differ from those that arise when selection is imposed by predators or mates. In the study of animal colours, avian brood parasite-host dynamics therefore invite special consideration. Rapid advances across disciplines have paved the way for an integrative study of colour and vision in brood parasite-host systems...
July 5, 2017: Philosophical Transactions of the Royal Society of London. Series B, Biological Sciences
https://www.readbyqxmd.com/read/28524068/detection-of-magnetic-field-properties-using-distributed-sensing-a-computational-neuroscience-approach
#2
Brian K Taylor, Sönke Johnsen, Kenneth J Lohmann
Diverse taxa use Earth's magnetic field to aid both short- and long-distance navigation. Study of these behaviors has led to a variety of postulated sensory and processing mechanisms that remain unconfirmed. Although several models have been proposed to explain and understand these mechanisms' underpinnings, they have not necessarily connected a putative sensory signal to the nervous system. Using mathematical software simulation, hardware testing and the computational neuroscience tool of dynamic neural fields, the present work implements a previously developed conceptual model for processing magnetite-based magnetosensory data...
May 19, 2017: Bioinspiration & Biomimetics
https://www.readbyqxmd.com/read/28521007/computing-the-social-brain-connectome-across-systems-and-states
#3
Daniel Alcalá-López, Jonathan Smallwood, Elizabeth Jefferies, Frank Van Overwalle, Kai Vogeley, Rogier B Mars, Bruce I Turetsky, Angela R Laird, Peter T Fox, Simon B Eickhoff, Danilo Bzdok
Social skills probably emerge from the interaction between different neural processing levels. However, social neuroscience is fragmented into highly specialized, rarely cross-referenced topics. The present study attempts a systematic reconciliation by deriving a social brain definition from neural activity meta-analyses on social-cognitive capacities. The social brain was characterized by meta-analytic connectivity modeling evaluating coactivation in task-focused brain states and physiological fluctuations evaluating correlations in task-free brain states...
May 18, 2017: Cerebral Cortex
https://www.readbyqxmd.com/read/28507240/mathematical-methods-in-medicine-neuroscience-cardiology-and-pathology
#4
José M Amigó, Michael Small
The application of mathematics, natural sciences and engineering to medicine is gaining momentum as the mutual benefits of this collaboration become increasingly obvious. This theme issue is intended to highlight the trend in the case of mathematics. Specifically, the scope of this theme issue is to give a general view of the current research in the application of mathematical methods to medicine, as well as to show how mathematics can help in such important aspects as understanding, prediction, treatment and data processing...
June 28, 2017: Philosophical Transactions. Series A, Mathematical, Physical, and Engineering Sciences
https://www.readbyqxmd.com/read/28507239/pulsatile-flow-in-ventricular-catheters-for-hydrocephalus
#5
Á Giménez, M Galarza, U Thomale, M U Schuhmann, J Valero, J M Amigó
The obstruction of ventricular catheters (VCs) is a major problem in the standard treatment of hydrocephalus, the flow pattern of the cerebrospinal fluid (CSF) being one important factor thereof. As a first approach to this problem, some of the authors studied previously the CSF flow through VCs under time-independent boundary conditions by means of computational fluid dynamics in three-dimensional models. This allowed us to derive a few basic principles which led to designs with improved flow patterns regarding the obstruction problem...
June 28, 2017: Philosophical Transactions. Series A, Mathematical, Physical, and Engineering Sciences
https://www.readbyqxmd.com/read/28507237/multiscale-ordinal-network-analysis-of-human-cardiac-dynamics
#6
M McCullough, M Small, H H C Iu, T Stemler
In this study, we propose a new information theoretic measure to quantify the complexity of biological systems based on time-series data. We demonstrate the potential of our method using two distinct applications to human cardiac dynamics. Firstly, we show that the method clearly discriminates between segments of electrocardiogram records characterized by normal sinus rhythm, ventricular tachycardia and ventricular fibrillation. Secondly, we investigate the multiscale complexity of cardiac dynamics with respect to age in healthy individuals using interbeat interval time series and compare our findings with a previous study which established a link between age and fractal-like long-range correlations...
June 28, 2017: Philosophical Transactions. Series A, Mathematical, Physical, and Engineering Sciences
https://www.readbyqxmd.com/read/28507232/energy-landscape-analysis-of-neuroimaging-data
#7
Takahiro Ezaki, Takamitsu Watanabe, Masayuki Ohzeki, Naoki Masuda
Computational neuroscience models have been used for understanding neural dynamics in the brain and how they may be altered when physiological or other conditions change. We review and develop a data-driven approach to neuroimaging data called the energy landscape analysis. The methods are rooted in statistical physics theory, in particular the Ising model, also known as the (pairwise) maximum entropy model and Boltzmann machine. The methods have been applied to fitting electrophysiological data in neuroscience for a decade, but their use in neuroimaging data is still in its infancy...
June 28, 2017: Philosophical Transactions. Series A, Mathematical, Physical, and Engineering Sciences
https://www.readbyqxmd.com/read/28507231/biological-modelling-of-a-computational-spiking-neural-network-with-neuronal-avalanches
#8
Xiumin Li, Qing Chen, Fangzheng Xue
In recent years, an increasing number of studies have demonstrated that networks in the brain can self-organize into a critical state where dynamics exhibit a mixture of ordered and disordered patterns. This critical branching phenomenon is termed neuronal avalanches. It has been hypothesized that the homeostatic level balanced between stability and plasticity of this critical state may be the optimal state for performing diverse neural computational tasks. However, the critical region for high performance is narrow and sensitive for spiking neural networks (SNNs)...
June 28, 2017: Philosophical Transactions. Series A, Mathematical, Physical, and Engineering Sciences
https://www.readbyqxmd.com/read/28507230/computational-design-of-treatment-strategies-for-proactive-therapy-on-atopic-dermatitis-using-optimal-control-theory
#9
Panayiotis Christodoulides, Yoshito Hirata, Elisa Domínguez-Hüttinger, Simon G Danby, Michael J Cork, Hywel C Williams, Kazuyuki Aihara, Reiko J Tanaka
Atopic dermatitis (AD) is a common chronic skin disease characterized by recurrent skin inflammation and a weak skin barrier, and is known to be a precursor to other allergic diseases such as asthma. AD affects up to 25% of children worldwide and the incidence continues to rise. There is still uncertainty about the optimal treatment strategy in terms of choice of treatment, potency, duration and frequency. This study aims to develop a computational method to design optimal treatment strategies for the clinically recommended 'proactive therapy' for AD...
June 28, 2017: Philosophical Transactions. Series A, Mathematical, Physical, and Engineering Sciences
https://www.readbyqxmd.com/read/28507228/understanding-principles-of-integration-and-segregation-using-whole-brain-computational-connectomics-implications-for-neuropsychiatric-disorders
#10
REVIEW
Louis-David Lord, Angus B Stevner, Gustavo Deco, Morten L Kringelbach
To survive in an ever-changing environment, the brain must seamlessly integrate a rich stream of incoming information into coherent internal representations that can then be used to efficiently plan for action. The brain must, however, balance its ability to integrate information from various sources with a complementary capacity to segregate information into modules which perform specialized computations in local circuits. Importantly, evidence suggests that imbalances in the brain's ability to bind together and/or segregate information over both space and time is a common feature of several neuropsychiatric disorders...
June 28, 2017: Philosophical Transactions. Series A, Mathematical, Physical, and Engineering Sciences
https://www.readbyqxmd.com/read/28506440/the-wistar-audiogenic-rat-war-strain-and-its-contributions-to-epileptology-and-related-comorbidities-history-and-perspectives
#11
Norberto Garcia-Cairasco, Eduardo H L Umeoka, José A Cortes de Oliveira
In the context of modeling epilepsy and neuropsychiatric comorbidities, we review the Wistar Audiogenic Rat (WAR), first introduced to the neuroscience international community more than 25years ago. The WAR strain is a genetically selected reflex model susceptible to audiogenic seizures (AS), acutely mimicking brainstem-dependent tonic-clonic seizures and chronically (by audiogenic kindling), temporal lobe epilepsy (TLE). Seminal neuroethological, electrophysiological, cellular, and molecular protocols support the WAR strain as a suitable and reliable animal model to study the complexity and emergent functions typical of epileptogenic networks...
May 11, 2017: Epilepsy & Behavior: E&B
https://www.readbyqxmd.com/read/28502662/-what-not-detectors-help-the-brain-see-in-depth
#12
Nuno R Goncalves, Andrew E Welchman
Binocular stereopsis is one of the primary cues for three-dimensional (3D) vision in species ranging from insects to primates. Understanding how the brain extracts depth from two different retinal images represents a tractable challenge in sensory neuroscience that has so far evaded full explanation. Central to current thinking is the idea that the brain needs to identify matching features in the two retinal images (i.e., solving the "stereoscopic correspondence problem") so that the depth of objects in the world can be triangulated...
May 22, 2017: Current Biology: CB
https://www.readbyqxmd.com/read/28500933/functional-consequences-of-inhibitory-plasticity-homeostasis-the-excitation-inhibition-balance-and-beyond
#13
REVIEW
Henning Sprekeler
Computational neuroscience has a long-standing tradition of investigating the consequences of excitatory synaptic plasticity. In contrast, the functions of inhibitory plasticity are still largely nebulous, particularly given the bewildering diversity of interneurons in the brain. Here, we review recent computational advances that provide first suggestions for the functional roles of inhibitory plasticity, such as a maintenance of the excitation-inhibition balance, a stabilization of recurrent network dynamics and a decorrelation of sensory responses...
May 10, 2017: Current Opinion in Neurobiology
https://www.readbyqxmd.com/read/28496401/monitoring-the-right-collection-the-central-cholinergic-neurons-as-an-instructive-example
#14
Katalin Sviatkó, Balázs Hangya
Some neurons are more equal than others: neuroscience relies heavily on the notion that there is a division of labor among different subtypes of brain cells. Therefore, it is important to recognize groups of neurons that participate in the same computation or share similar tasks. However, what the best ways are to identify such collections is not yet clear. Here, we argue that monitoring the activity of genetically defined cell types will lead to new insights about neural mechanisms and improve our understanding of disease vulnerability...
2017: Frontiers in Neural Circuits
https://www.readbyqxmd.com/read/28488252/multiscale-modeling-in-the-clinic-diseases-of-the-brain-and-nervous-system
#15
REVIEW
William W Lytton, Jeff Arle, Georgiy Bobashev, Songbai Ji, Tara L Klassen, Vasilis Z Marmarelis, James Schwaber, Mohamed A Sherif, Terence D Sanger
Computational neuroscience is a field that traces its origins to the efforts of Hodgkin and Huxley, who pioneered quantitative analysis of electrical activity in the nervous system. While also continuing as an independent field, computational neuroscience has combined with computational systems biology, and neural multiscale modeling arose as one offshoot. This consolidation has added electrical, graphical, dynamical system, learning theory, artificial intelligence and neural network viewpoints with the microscale of cellular biology (neuronal and glial), mesoscales of vascular, immunological and neuronal networks, on up to macroscales of cognition and behavior...
May 9, 2017: Brain Informatics
https://www.readbyqxmd.com/read/28483721/large-scale-sparse-functional-networks-from-resting-state-fmri
#16
Hongming Li, Theodore D Satterthwaite, Yong Fan
Delineation of large-scale functional networks (FNs) from resting state functional MRI data has become a standard tool to explore the functional brain organization in neuroscience. However, existing methods sacrifice subject specific variation in order to maintain the across-subject correspondence necessary for group-level analyses. In order to obtain subject specific FNs that are comparable across subjects, existing brain decomposition techniques typically adopt heuristic strategies or assume a specific statistical distribution for the FNs across subjects, and therefore might yield biased results...
May 5, 2017: NeuroImage
https://www.readbyqxmd.com/read/28479315/quantum-field-theory-and-coalgebraic-logic-in-theoretical-computer-science
#17
REVIEW
Gianfranco Basti, Antonio Capolupo, Giuseppe Vitiello
We suggest that in the framework of the Category Theory it is possible to demonstrate the mathematical and logical dual equivalence between the category of the q-deformed Hopf Coalgebras and the category of the q-deformed Hopf Algebras in quantum field theory (QFT), interpreted as a thermal field theory. Each pair algebra-coalgebra characterizes a QFT system and its mirroring thermal bath, respectively, so to model dissipative quantum systems in far-from-equilibrium conditions, with an evident significance also for biological sciences...
May 4, 2017: Progress in Biophysics and Molecular Biology
https://www.readbyqxmd.com/read/28475155/new-frontiers-for-applications-of-thermal-infrared-imaging-devices-computational-psychopshysiology-in-the-neurosciences
#18
REVIEW
Daniela Cardone, Arcangelo Merla
Thermal infrared imaging has been proposed, and is now used, as a tool for the non-contact and non-invasive computational assessment of human autonomic nervous activity and psychophysiological states. Thanks to a new generation of high sensitivity infrared thermal detectors and the development of computational models of the autonomic control of the facial cutaneous temperature, several autonomic variables can be computed through thermal infrared imaging, including localized blood perfusion rate, cardiac pulse rate, breath rate, sudomotor and stress responses...
May 5, 2017: Sensors
https://www.readbyqxmd.com/read/28471714/circuits-and-mechanisms-for-surround-modulation-in-visual-cortex
#19
Alessandra Angelucci, Maryam Bijanzadeh, Lauri Nurminen, Frederick Federer, Sam Merlin, Paul C Bressloff
Surround modulation (SM) is a fundamental property of sensory neurons in many species and sensory modalities. SM is the ability of stimuli in the surround of a neuron's receptive field (RF) to modulate (typically suppress) the neuron's response to stimuli simultaneously presented inside the RF, a property thought to underlie optimal coding of sensory information and important perceptual functions. Understanding the circuit and mechanisms for SM can reveal fundamental principles of computations in sensory cortices, from mouse to human...
May 3, 2017: Annual Review of Neuroscience
https://www.readbyqxmd.com/read/28459860/nucleotide-time-alignment-for-molecular-recorders
#20
Thaddeus R Cybulski, Edward S Boyden, George M Church, Keith E J Tyo, Konrad P Kording
Using a DNA polymerase to record intracellular calcium levels has been proposed as a novel neural recording technique, promising massive-scale, single-cell resolution monitoring of large portions of the brain. This technique relies on local storage of neural activity in strands of DNA, followed by offline analysis of that DNA. In simple implementations of this scheme, the time when each nucleotide was written cannot be determined directly by post-hoc DNA sequencing; the timing data must be estimated instead...
May 2017: PLoS Computational Biology
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