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https://www.readbyqxmd.com/read/29122586/the-evolutionary-dynamics-of-language
#1
REVIEW
Luc Steels, Eörs Szathmáry
The well-established framework of evolutionary dynamics can be applied to the fascinating open problems how human brains are able to acquire and adapt language and how languages change in a population. Schemas for handling grammatical constructions are the replicating unit. They emerge and multiply with variation in the brains of individuals and undergo selection based on their contribution to needed expressive power, communicative success and the reduction of cognitive effort. Adopting this perspective has two major benefits...
November 6, 2017: Bio Systems
https://www.readbyqxmd.com/read/29100819/behavioural-and-computational-methods-reveal-differential-effects-for-how-delayed-and-rapid-onset-antidepressants-effect-decision-making-in-rats
#2
Claire A Hales, Conor J Houghton, Emma S J Robinson
Major depressive disorder (MDD) is one of the most prevalent psychiatric disorders. Until the recent discovery of the rapid onset antidepressant action of ketamine, pharmacological treatments for MDD were limited to conventional antidepressant drugs with delayed clinical efficacy. Using a judgement bias task, this study has investigated whether the temporal differences observed in patients would be reflected in affective biases and decision making behaviour in rodents. The diffusion model was also used to investigate the underlying decision making processes...
October 31, 2017: European Neuropsychopharmacology: the Journal of the European College of Neuropsychopharmacology
https://www.readbyqxmd.com/read/29066078/computational-neuroscience-across-the-lifespan-promises-and-pitfalls
#3
REVIEW
Wouter van den Bos, Rasmus Bruckner, Matthew R Nassar, Rui Mata, Ben Eppinger
In recent years, the application of computational modeling in studies on age-related changes in decision making and learning has gained in popularity. One advantage of computational models is that they provide access to latent variables that cannot be directly observed from behavior. In combination with experimental manipulations, these latent variables can help to test hypotheses about age-related changes in behavioral and neurobiological measures at a level of specificity that is not achievable with descriptive analysis approaches alone...
October 13, 2017: Developmental Cognitive Neuroscience
https://www.readbyqxmd.com/read/29045575/shared-and-disorder-specific-neurocomputational-mechanisms-of-decision-making-in-autism-spectrum-disorder-and-obsessive-compulsive-disorder
#4
Christina O Carlisi, Luke Norman, Clodagh M Murphy, Anastasia Christakou, Kaylita Chantiluke, Vincent Giampietro, Andrew Simmons, Michael Brammer, Declan G Murphy, David Mataix-Cols, Katya Rubia
Autism spectrum disorder (ASD) and obsessive-compulsive disorder (OCD) often share phenotypes of repetitive behaviors, possibly underpinned by abnormal decision-making. To compare neural correlates underlying decision-making between these disorders, brain activation of boys with ASD (N = 24), OCD (N = 20) and typically developing controls (N = 20) during gambling was compared, and computational modeling compared performance. Patients were unimpaired on number of risky decisions, but modeling showed that both patient groups had lower choice consistency and relied less on reinforcement learning compared to controls...
December 1, 2017: Cerebral Cortex
https://www.readbyqxmd.com/read/29041860/maternal-behavior-of-the-mouse-dam-toward-pups-implications-for-maternal-separation-model-of-early-life-stress
#5
Rodrigo Orso, Luis Eduardo Wearick-Silva, Kerstin Camile Creutzberg, Anderson Centeno-Silva, Laura Glusman Roithmann, Rafaelly Pazzin, Saulo Gantes Tractenberg, Fernando Benetti, Rodrigo Grassi-Oliveira
Maternal care is essential for an adequate pup development, as well as for the health of the dam. Exposure to stress in early stages of life can disrupt this dam-pup relationship promoting altered neurobiological and behavioral phenotypes. However, there is a lack of consensus regarding the effects of daily maternal separation (MS) on the pattern of maternal behavior. The aim of this study is to compare the patterns of maternal behavior between mice exposed to MS and controls. BALB/c mice were subjected to MS for a period of 180 min/day from postnatal day 2-7 (n = 17) or designated to be standard animal facility reared (AFR) controls (n = 19)...
October 18, 2017: Stress: the International Journal on the Biology of Stress
https://www.readbyqxmd.com/read/29031703/comparative-approximations-of-criticality-in-a-neural-and-quantum-regime
#6
REVIEW
Jesse Sterling Bettinger
Under a variety of conditions, non-linear systems with many degrees of freedom tend to evolve towards complexity and criticality. Over the last few decades, a steady proliferation of models re: nonlinear and far-from-equilibrium thermodynamics of metastable, many-valued systems arose, serving as attributes of a 'critical' attractor landscape. Building off recent data citing trademark aspects of criticality in the brain-including: power-laws, scale-free (1/f) behavior (scale invariance, or scale independence, critical slowing, and avalanches-it has been conjectured that operating at criticality entails functional advantages such as: optimized neural computation and information processing; memory; large dynamical ranges; long-range communication; and "enhanced ability to react to highly diverse stimuli...
October 11, 2017: Progress in Biophysics and Molecular Biology
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/28955272/recurrent-convolutional-neural-networks-a-better-model-of-biological-object-recognition
#8
Courtney J Spoerer, Patrick McClure, Nikolaus Kriegeskorte
Feedforward neural networks provide the dominant model of how the brain performs visual object recognition. However, these networks lack the lateral and feedback connections, and the resulting recurrent neuronal dynamics, of the ventral visual pathway in the human and non-human primate brain. Here we investigate recurrent convolutional neural networks with bottom-up (B), lateral (L), and top-down (T) connections. Combining these types of connections yields four architectures (B, BT, BL, and BLT), which we systematically test and compare...
2017: Frontiers in Psychology
https://www.readbyqxmd.com/read/28953764/the-relative-contribution-of-goal-directed-and-habit-systems-to-psychiatric-disorders
#9
Sophie Woodhead, Trevor Robbins
Psychiatric disorders may be caused by underlying imbalances between goal-directed and habit systems in the brain. Numerous studies have aimed to establish whether this is because of a goal-directed system deficit, enhanced habit system, or both. This transdiagnostic approach to studying psychiatric disorders is increasingly popular. Maladaptive habitual behaviour is present in many disorders. It is the principal observation in disorders of compulsivity and is also present in other psychiatric disorders that are not primarily characterised by compulsive behaviour...
September 2017: Psychiatria Danubina
https://www.readbyqxmd.com/read/28951611/sensory-perception-in-autism
#10
REVIEW
Caroline E Robertson, Simon Baron-Cohen
Autism is a complex neurodevelopmental condition, and little is known about its neurobiology. Much of autism research has focused on the social, communication and cognitive difficulties associated with the condition. However, the recent revision of the diagnostic criteria for autism has brought another key domain of autistic experience into focus: sensory processing. Here, we review the properties of sensory processing in autism and discuss recent computational and neurobiological insights arising from attention to these behaviours...
November 2017: Nature Reviews. Neuroscience
https://www.readbyqxmd.com/read/28945744/relating-dynamic-brain-states-to-dynamic-machine-states-human-and-machine-solutions-to-the-speech-recognition-problem
#11
Cai Wingfield, Li Su, Xunying Liu, Chao Zhang, Phil Woodland, Andrew Thwaites, Elisabeth Fonteneau, William D Marslen-Wilson
There is widespread interest in the relationship between the neurobiological systems supporting human cognition and emerging computational systems capable of emulating these capacities. Human speech comprehension, poorly understood as a neurobiological process, is an important case in point. Automatic Speech Recognition (ASR) systems with near-human levels of performance are now available, which provide a computationally explicit solution for the recognition of words in continuous speech. This research aims to bridge the gap between speech recognition processes in humans and machines, using novel multivariate techniques to compare incremental 'machine states', generated as the ASR analysis progresses over time, to the incremental 'brain states', measured using combined electro- and magneto-encephalography (EMEG), generated as the same inputs are heard by human listeners...
September 2017: PLoS Computational Biology
https://www.readbyqxmd.com/read/28942354/the-priming-of-basic-combinatory-responses-in-meg
#12
Esti Blanco-Elorrieta, Victor S Ferreira, Paul Del Prato, Liina Pylkkänen
Priming has been a powerful tool for the study of human memory and especially the memory representations relevant for language. However, although it is well established that lexical access can be primed, we do not know exactly what types of computations can be primed above the word level. This work took a neurobiological approach and assessed the ways in which the complex representation of a minimal combinatory phrase, such as red boat, can be primed, as evidenced by the spatiotemporal profiles of magnetoencephalography (MEG) signals...
September 21, 2017: Cognition
https://www.readbyqxmd.com/read/28933068/functional-neuroimaging-in-obesity-research
#13
Liliana Letra, Daniela Pereira, Miguel Castelo-Branco
Functional neuroimaging is beginning to yield valuable insights into the neurobiological underpinnings of the effects of obesity on neural circuits. Functional magnetic resonance imaging (fMRI), positron emission tomography (PET), and single-photon emission computed tomography (SPECT) studies have been used to identify aberrant activation patterns in regions implicated in reward (e.g., striatum, orbitofrontal cortex, insula), emotion and memory (e.g., amygdala, hippocampus), sensory and motor processing (e...
2017: Advances in Neurobiology
https://www.readbyqxmd.com/read/28892737/misdeed-of-the-need-towards-computational-accounts-of-transition-to-addiction
#14
REVIEW
Mehdi Keramati, Serge H Ahmed, Boris S Gutkin
Drug addiction is a complex behavioral and neurobiological disorder which, in an emergent brain-circuit view, reflects a loss of prefrontal top-down control over subcortical circuits governing drug-seeking and drug-taking. We first review previous computational accounts of addiction, focusing on cocaine addiction and on prevalent dopamine-based positive-reinforcement and negative-reinforcement computational models. Then, we discuss a recent computational proposal that the progression to addiction is unlikely to result from a complete withdrawal of the goal-oriented decision system in favor the habitual one...
October 2017: Current Opinion in Neurobiology
https://www.readbyqxmd.com/read/28891515/a-computational-approach-towards-the-microscale-mouse-brain-connectome-from-the-mesoscale
#15
Tielin Zhang, Yi Zeng, Bo Xu
The wiring diagram of the mouse brain presents an indispensable foundation for the research on basic and applied neurobiology. It is also essential as a structural foundation for computational simulation of the brain. Different scales of the connectome give us different hints and clues to understand the functions of the nervous system and how they process information. However, compared to the macroscale and most recent mesoscale mouse brain connectome studies, there is no complete whole brain microscale connectome available because of the scalability and accuracy of automatic recognition techniques...
2017: Journal of Integrative Neuroscience
https://www.readbyqxmd.com/read/28887785/bioplausible-multiscale-filtering-in-retino-cortical-processing-as-a-mechanism-in-perceptual-grouping
#16
Nasim Nematzadeh, David M W Powers, Trent W Lewis
Why does our visual system fail to reconstruct reality, when we look at certain patterns? Where do Geometrical illusions start to emerge in the visual pathway? How far should we take computational models of vision with the same visual ability to detect illusions as we do? This study addresses these questions, by focusing on a specific underlying neural mechanism involved in our visual experiences that affects our final perception. Among many types of visual illusion, 'Geometrical' and, in particular, 'Tilt Illusions' are rather important, being characterized by misperception of geometric patterns involving lines and tiles in combination with contrasting orientation, size or position...
September 8, 2017: Brain Informatics
https://www.readbyqxmd.com/read/28887227/probabilistic-language-models-in-cognitive-neuroscience-promises-and-pitfalls
#17
REVIEW
Kristijan Armeni, Roel M Willems, Stefan L Frank
Cognitive neuroscientists of language comprehension study how neural computations relate to cognitive computations during comprehension. On the cognitive part of the equation, it is important that the computations and processing complexity are explicitly defined. Probabilistic language models can be used to give a computationally explicit account of language complexity during comprehension. Whereas such models have so far predominantly been evaluated against behavioral data, only recently have the models been used to explain neurobiological signals...
September 5, 2017: Neuroscience and Biobehavioral Reviews
https://www.readbyqxmd.com/read/28873968/high-precision-registration-between-zebrafish-brain-atlases-using-symmetric-diffeomorphic-normalization
#18
Gregory D Marquart, Kathryn M Tabor, Eric J Horstick, Mary Brown, Alexandra K Geoca, Nicholas F Polys, Damian Dalle Nogare, Harold A Burgess
Atlases provide a framework for spatially mapping information from diverse sources into a common reference space. Specifically, brain atlases allow annotation of gene expression, cell morphology, connectivity, and activity. In larval zebrafish, advances in genetics, imaging, and computational methods now allow the collection of such information brain-wide. However, due to technical considerations, disparate datasets may use different references and may not be aligned to the same coordinate space. Two recent larval zebrafish atlases exemplify this problem: Z-Brain, containing gene expression, neural activity, and neuroanatomical segmentations, was acquired using immunohistochemical stains, while the Zebrafish Brain Browser (ZBB) was constructed from live scans of fluorescent reporters in transgenic larvae...
August 1, 2017: GigaScience
https://www.readbyqxmd.com/read/28868531/a-control-theory-model-of-smoking
#19
Georgiy Bobashev, John Holloway, Eric Solano, Boris Gutkin
We present a heuristic control theory model that describes smoking under restricted and unrestricted access to cigarettes. The model is based on the allostasis theory and uses a formal representation of a multiscale opponent process. The model simulates smoking behavior of an individual and produces both short-term ("loading up" after not smoking for a while) and long-term smoking patterns (e.g., gradual transition from a few cigarettes to one pack a day). By introducing a formal representation of withdrawal- and craving-like processes, the model produces gradual increases over time in withdrawal- and craving-like signals associated with abstinence and shows that after 3 months of abstinence, craving disappears...
June 2017: Methods Report
https://www.readbyqxmd.com/read/28867653/comprehensive-review-computational-modelling-of-schizophrenia
#20
REVIEW
Vincent Valton, Liana Romaniuk, J Douglas Steele, Stephen Lawrie, Peggy Seriès
Computational modelling has been used to address: (1) the variety of symptoms observed in schizophrenia using abstract models of behavior (e.g. Bayesian models - top-down descriptive models of psychopathology); (2) the causes of these symptoms using biologically realistic models involving abnormal neuromodulation and/or receptor imbalance (e.g. connectionist and neural networks - bottom-up realistic models of neural processes). These different levels of analysis have been used to answer different questions (i...
September 1, 2017: Neuroscience and Biobehavioral Reviews
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