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Computational neurobiology

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https://www.readbyqxmd.com/read/28641107/the-persistence-and-transience-of-memory
#1
REVIEW
Blake A Richards, Paul W Frankland
The predominant focus in the neurobiological study of memory has been on remembering (persistence). However, recent studies have considered the neurobiology of forgetting (transience). Here we draw parallels between neurobiological and computational mechanisms underlying transience. We propose that it is the interaction between persistence and transience that allows for intelligent decision-making in dynamic, noisy environments. Specifically, we argue that transience (1) enhances flexibility, by reducing the influence of outdated information on memory-guided decision-making, and (2) prevents overfitting to specific past events, thereby promoting generalization...
June 21, 2017: Neuron
https://www.readbyqxmd.com/read/28634148/iodine-and-freeze-drying-enhanced-high-resolution-microct-imaging-for-reconstructing-3d-intraneural-topography-of-human-peripheral-nerve-fascicles
#2
Liwei Yan, Yongze Guo, Jian Qi, Qingtang Zhu, Liqiang Gu, Canbin Zheng, Tao Lin, Yutong Lu, Zitao Zeng, Sha Yu, Shuang Zhu, Xiang Zhou, Xi Zhang, Yunfei Du, Zhi Yao, Yao Lu, Xiaolin Liu
BACKGROUND: The precise annotation and accurate identification of the topography of fascicles to the end organs are prerequisites for studying human peripheral nerves. NEW METHOD: In this study, we present a feasible imaging method that acquires 3D high-resolution (HR) topography of peripheral nerve fascicles using an iodine and freeze-drying (IFD) micro-computed tomography (microCT) method to greatly increase the contrast of fascicle images. RESULTS: The enhanced microCT imaging method can facilitate the reconstruction of high-contrast HR fascicle images, fascicle segmentation and extraction, feature analysis, and the tracing of fascicle topography to end organs, which define fascicle functions...
June 17, 2017: Journal of Neuroscience Methods
https://www.readbyqxmd.com/read/28581274/comparison-of-electroencephalography-eeg-coherence-between-major-depressive-disorder-mdd-without-comorbidity-and-mdd-comorbid-with-internet-gaming-disorder
#3
Joohyung Youh, Ji Sun Hong, Doug Hyun Han, Un Sun Chung, Kyoung Joon Min, Young Sik Lee, Sun Mi Kim
Internet gaming disorder (IGD) has many comorbid psychiatric problems including major depressive disorder (MDD). In the present study, we compared the neurobiological differences between MDD without comorbidity (MDD-only) and MDD comorbid with IGD (MDD+IGD) by analyzing the quantitative electroencephalogram (QEEG) findings. We recruited 14 male MDD+IGD (mean age, 20.0 ± 5.9 years) and 15 male MDD-only (mean age, 20.3 ± 5.5 years) patients. The electroencephalography (EEG) coherences were measured using a 21-channel digital EEG system and computed to assess synchrony in the frequency ranges of alpha (7...
July 2017: Journal of Korean Medical Science
https://www.readbyqxmd.com/read/28555104/tdcs-over-the-motor-cortex-shows-differential-effects-on-action-and-object-words-in-associative-word-learning-in-healthy-aging
#4
Meret Branscheidt, Julia Hoppe, Nils Freundlieb, Pienie Zwitserlood, Gianpiero Liuzzi
Healthy aging is accompanied by a continuous decline in cognitive functions. For example, the ability to learn languages decreases with age, while the neurobiological underpinnings for the decline in learning abilities are not known exactly. Transcranial direct current stimulation (tDCS), in combination with appropriate experimental paradigms, is a well-established technique to investigate the mechanisms of learning. Based on previous results in young adults, we tested the suitability of an associative learning paradigm for the acquisition of action- and object-related words in a cohort of older participants...
2017: Frontiers in Aging Neuroscience
https://www.readbyqxmd.com/read/28553839/a-primer-on-foraging-and-the-explore-exploit-trade-off-for-psychiatry-research
#5
REVIEW
M A Addicott, J M Pearson, M M Sweitzer, D L Barack, M L Platt
Foraging is a fundamental behavior, and many types of animals appear to have solved foraging problems using a shared set of mechanisms. Perhaps the most common foraging problem is the choice between exploiting a familiar option for a known reward and exploring unfamiliar options for unknown rewards-the so-called explore-exploit trade-off. This trade-off has been studied extensively in behavioral ecology and computational neuroscience, but is relatively new to the field of psychiatry. Explore/exploit paradigms can offer psychiatry research a new approach to studying motivation, outcome valuation, and effort-related processes, which are disrupted in many mental and emotional disorders...
May 29, 2017: Neuropsychopharmacology: Official Publication of the American College of Neuropsychopharmacology
https://www.readbyqxmd.com/read/28536046/neural-substrates-of-updating-the-prediction-through-prediction-error-during-decision-making
#6
Ying Wang, Ning Ma, Xiaosong He, Nan Li, Zhengde Wei, Lizhuang Yang, Rujing Zha, Long Han, Xiaoming Li, Daren Zhang, Ying Liu, Xiaochu Zhang
Learning of prediction error (PE), including reward PE and risk PE, is crucial for updating the prediction in reinforcement learning (RL). Neurobiological and computational models of RL have reported extensive brain activations related to PE. However, the occurrence of PE does not necessarily predict updating the prediction, e.g., in a probability-known event. Therefore, the brain regions specifically engaged in updating the prediction remain unknown. Here, we conducted two functional magnetic resonance imaging (fMRI) experiments, the probability-unknown Iowa Gambling Task (IGT) and the probability-known risk decision task (RDT)...
May 20, 2017: NeuroImage
https://www.readbyqxmd.com/read/28530717/sparse-coding-with-memristor-networks
#7
Patrick M Sheridan, Fuxi Cai, Chao Du, Wen Ma, Zhengya Zhang, Wei D Lu
Sparse representation of information provides a powerful means to perform feature extraction on high-dimensional data and is of broad interest for applications in signal processing, computer vision, object recognition and neurobiology. Sparse coding is also believed to be a key mechanism by which biological neural systems can efficiently process a large amount of complex sensory data while consuming very little power. Here, we report the experimental implementation of sparse coding algorithms in a bio-inspired approach using a 32 × 32 crossbar array of analog memristors...
May 22, 2017: Nature Nanotechnology
https://www.readbyqxmd.com/read/28530428/short-term-memory-and-long-term-memory-are-still-different
#8
Dennis Norris
A commonly expressed view is that short-term memory (STM) is nothing more than activated long-term memory. If true, this would overturn a central tenet of cognitive psychology-the idea that there are functionally and neurobiologically distinct short- and long-term stores. Here I present an updated case for a separation between short- and long-term stores, focusing on the computational demands placed on any STM system. STM must support memory for previously unencountered information, the storage of multiple tokens of the same type, and variable binding...
May 22, 2017: Psychological Bulletin
https://www.readbyqxmd.com/read/28527790/visual-cortex-signals-a-mismatch-between-regularity-of-auditory-and-visual-streams
#9
Michael Andric, Ben Davis, Uri Hasson
Understanding how humans code for and respond to environmental uncertainty/regularity is a question shared by current computational and neurobiological approaches to human cognition. To date, studies investigating neurobiological systems that track input uncertainty have examined responses to uni-sensory streams. It is not known, however, whether there exist brain systems that combine information about the regularity of input streams presented to different senses. We report an fMRI study that aimed to identify brain systems that relate statistical information across sensory modalities...
May 17, 2017: NeuroImage
https://www.readbyqxmd.com/read/28520803/multiple-modality-biomarker-prediction-of-cognitive-impairment-in-prospectively-followed-de-novo-parkinson-disease
#10
Chelsea Caspell-Garcia, Tanya Simuni, Duygu Tosun-Turgut, I-Wei Wu, Yu Zhang, Mike Nalls, Andrew Singleton, Leslie A Shaw, Ju-Hee Kang, John Q Trojanowski, Andrew Siderowf, Christopher Coffey, Shirley Lasch, Dag Aarsland, David Burn, Lana M Chahine, Alberto J Espay, Eric D Foster, Keith A Hawkins, Irene Litvan, Irene Richard, Daniel Weintraub
OBJECTIVES: To assess the neurobiological substrate of initial cognitive decline in Parkinson's disease (PD) to inform patient management, clinical trial design, and development of treatments. METHODS: We longitudinally assessed, up to 3 years, 423 newly diagnosed patients with idiopathic PD, untreated at baseline, from 33 international movement disorder centers. Study outcomes were four determinations of cognitive impairment or decline, and biomarker predictors were baseline dopamine transporter (DAT) single photon emission computed tomography (SPECT) scan, structural magnetic resonance imaging (MRI; volume and thickness), diffusion tensor imaging (mean diffusivity and fractional anisotropy), cerebrospinal fluid (CSF; amyloid beta [Aβ], tau and alpha synuclein), and 11 single nucleotide polymorphisms (SNPs) previously associated with PD cognition...
2017: PloS One
https://www.readbyqxmd.com/read/28507228/understanding-principles-of-integration-and-segregation-using-whole-brain-computational-connectomics-implications-for-neuropsychiatric-disorders
#11
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/28455204/light-controlled-gene-expression-in-yeast-using-photocaged-cu-2
#12
Peter M Kusen, Georg Wandrey, Vera Krewald, Martina Holz, Sonja Meyer Zu Berstenhorst, Jochen Büchs, Jörg Pietruszka
The manipulation of cellular function, such as the regulation of gene expression, is of great interest to many biotechnological applications and often achieved by the addition of small effector molecules. By combining effector molecules with photolabile protecting groups that mask their biological activity until they are activated by light, precise, yet minimally invasive, photocontrol is enabled. However, applications of this trendsetting technology are limited by the small number of established caged compound-based expression systems...
April 25, 2017: Journal of Biotechnology
https://www.readbyqxmd.com/read/28434615/searching-for-cross-diagnostic-convergence-neural-mechanisms-governing-excitation-and-inhibition-balance-in-schizophrenia-and-autism-spectrum-disorders
#13
REVIEW
Jennifer H Foss-Feig, Brendan D Adkinson, Jie Lisa Ji, Genevieve Yang, Vinod H Srihari, James C McPartland, John H Krystal, John D Murray, Alan Anticevic
Recent theoretical accounts have proposed excitation and inhibition (E/I) imbalance as a possible mechanistic, network-level hypothesis underlying neural and behavioral dysfunction across neurodevelopmental disorders, particularly autism spectrum disorder (ASD) and schizophrenia (SCZ). These two disorders share some overlap in their clinical presentation as well as convergence in their underlying genes and neurobiology. However, there are also clear points of dissociation in terms of phenotypes and putatively affected neural circuitry...
May 15, 2017: Biological Psychiatry
https://www.readbyqxmd.com/read/28420150/virtual-reality-for-research-in-social-neuroscience
#14
Thomas D Parsons, Andrea Gaggioli, Giuseppe Riva
The emergence of social neuroscience has significantly advanced our understanding of the relationship that exists between social processes and their neurobiological underpinnings. Social neuroscience research often involves the use of simple and static stimuli lacking many of the potentially important aspects of real world activities and social interactions. Whilst this research has merit, there is a growing interest in the presentation of dynamic stimuli in a manner that allows researchers to assess the integrative processes carried out by perceivers over time...
April 16, 2017: Brain Sciences
https://www.readbyqxmd.com/read/28417684/toward-a-multiscale-modeling-framework-for-understanding-serotonergic-function
#15
KongFatt Wong-Lin, Da-Hui Wang, Ahmed A Moustafa, Jeremiah Y Cohen, Kae Nakamura
Despite its importance in regulating emotion and mental wellbeing, the complex structure and function of the serotonergic system present formidable challenges toward understanding its mechanisms. In this paper, we review studies investigating the interactions between serotonergic and related brain systems and their behavior at multiple scales, with a focus on biologically-based computational modeling. We first discuss serotonergic intracellular signaling and neuronal excitability, followed by neuronal circuit and systems levels...
April 1, 2017: Journal of Psychopharmacology
https://www.readbyqxmd.com/read/28340582/optimisation-of-an-exemplar-oculomotor-model-using-multi-objective-genetic-algorithms-executed-on-a-gpu-cpu-combination
#16
Eleftherios Avramidis, Ozgur E Akman
BACKGROUND: Parameter optimisation is a critical step in the construction of computational biology models. In eye movement research, computational models are increasingly important to understanding the mechanistic basis of normal and abnormal behaviour. In this study, we considered an existing neurobiological model of fast eye movements (saccades), capable of generating realistic simulations of: (i) normal horizontal saccades; and (ii) infantile nystagmus - pathological ocular oscillations that can be subdivided into different waveform classes...
March 24, 2017: BMC Systems Biology
https://www.readbyqxmd.com/read/28324757/perceptual-category-learning-and-visual-processing-an-exercise-in-computational-cognitive-neuroscience
#17
George Cantwell, Maximilian Riesenhuber, Jessica L Roeder, F Gregory Ashby
The field of computational cognitive neuroscience (CCN) builds and tests neurobiologically detailed computational models that account for both behavioral and neuroscience data. This article leverages a key advantage of CCN-namely, that it should be possible to interface different CCN models in a plug-and-play fashion-to produce a new and biologically detailed model of perceptual category learning. The new model was created from two existing CCN models: the HMAX model of visual object processing and the COVIS model of category learning...
May 2017: Neural Networks: the Official Journal of the International Neural Network Society
https://www.readbyqxmd.com/read/28318539/a-revival-of-the-homo-loquens-as-a-builder-of-labeled-structures-neurocognitive-considerations
#18
REVIEW
T Goucha, E Zaccarella, A D Friederici
The core capacity of human language is described as the faculty to combine words into hierarchical structures. This review aims to isolate the fundamental computation behind the language faculty together with its neural implementation. First, we present our central hypothesis by confronting recent linguistic theory with evolutionary arguments: linguistic humaniqueness is reflected in the labeling of word combinations forming asymmetric hierarchical structures. Second, we review the neurolinguistic literature, especially focusing on dual-stream connectivity models...
March 16, 2017: Neuroscience and Biobehavioral Reviews
https://www.readbyqxmd.com/read/28291690/social-cognitive-brain-function-and-connectivity-during-visual-perspective-taking-in-autism-and-schizophrenia
#19
Shaun M Eack, Jessica A Wojtalik, Matcheri S Keshavan, Nancy J Minshew
BACKGROUND: Autism spectrum disorder (ASD) and schizophrenia are neurodevelopmental conditions that are characterized by significant social impairment. Emerging genomic and neurobiological evidence has increasingly pointed to shared pathophysiologic mechanisms in the two disorders. Overlap in social impairment may reflect similar underlying neural dysfunction in social-cognitive brain networks, yet few studies have directly compared brain function and communication between those with ASD and schizophrenia...
May 2017: Schizophrenia Research
https://www.readbyqxmd.com/read/28275544/polygenic-risk-for-five-psychiatric-disorders-and-cross-disorder-and-disorder-specific-neural-connectivity-in-two-independent-populations
#20
Tianqi Wang, Xiaolong Zhang, Ang Li, Meifang Zhu, Shu Liu, Wen Qin, Jin Li, Chunshui Yu, Tianzi Jiang, Bing Liu
Major psychiatric disorders, including attention deficit hyperactivity disorder (ADHD), autism (AUT), bipolar disorder (BD), major depressive disorder (MDD), and schizophrenia (SZ), are highly heritable and polygenic. Evidence suggests that these five disorders have both shared and distinct genetic risks and neural connectivity abnormalities. To measure aggregate genetic risks, the polygenic risk score (PGRS) was computed. Two independent general populations (N = 360 and N = 323) were separately examined to investigate whether the cross-disorder PGRS and PGRS for a specific disorder were associated with individual variability in functional connectivity...
2017: NeuroImage: Clinical
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