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The Frequent Complete Subgraphs in the Human ConnectomeMar 14 2019While it is still not possible to describe the neural-level connections of the human brain, we can map the human connectome with several hundred vertices, by the application of diffusion-MRI based techniques. In these graphs, the nodes correspond to anatomically ... More
Recurrence required to capture the dynamic computations of the human ventral visual streamMar 14 2019The visual system is an intricate network of brain regions that enables us to recognize the world around us. Despite its abundant lateral and feedback connections, human object processing is commonly viewed and studied as a feedforward process. Here, ... More
How Can Memories Last for Days, Years, or a Lifetime? Proposed Mechanisms for Maintaining Synaptic Potentiation and MemoryMar 13 2019With memory encoding reliant on persistent changes in the properties of synapses, a key question is how can memories be maintained from days to months or a lifetime given molecular turnover? It is likely that positive feedback loops are necessary to persistently ... More
Noisy network attractor models for transitions between EEG microstatesMar 13 2019The brain is intrinsically organized into large-scale networks that constantly re-organize on multiple timescales, even when the brain is at rest. The timing of these dynamics is crucial for sensation, perception, cognition and ultimately consciousness, ... More
Effect of Interpopulation Spike-Timing-Dependent Plasticity on Synchronized Rhythms in Neuronal Networks with Inhibitory and Excitatory PopulationsMar 13 2019We consider clustered small-world networks (SWNs) with two inhibitory (I) and excitatory (E) populations. This I-E neuronal network has adaptive dynamic I to E and E to I interpopulation synaptic strengths, governed by interpopulation spike-timing-dependent ... More
25 years of criticality in neuroscience -- established results, open controversies, novel conceptsMar 12 2019Twenty-five years ago, Dunkelmann and Radons (1994) proposed that neural networks should self-organize to a critical state. In models, criticality offers a number of computational advantages. Thus this hypothesis, and in particular the experimental work ... More
Emergence of Brain Rhythms: Model Interpretation of EEG DataMar 11 2019Electroencephalography (EEG) monitors ---by either intrusive or noninvasive electrodes--- time and frequency variations and spectral content of voltage fluctuations or waves, known as brain rhythms, which in some way uncover activity during both rest ... More
Continual Learning via Neural PruningMar 11 2019We introduce Continual Learning via Neural Pruning (CLNP), a new method aimed at lifelong learning in fixed capacity models based on neuronal model sparsification. In this method, subsequent tasks are trained using the inactive neurons and filters of ... More
SleepNet: Automated Sleep Disorder Detection via Dense Convolutional Neural NetworkMar 11 2019In this work, a dense recurrent convolutional neural network (DRCNN) was constructed to detect sleep disorders including arousal, apnea and hypopnea using available Polysomnography (PSG) measurement channels provided in the 2018 PhysioNet challenge database. ... More
Labeler-hot Detection of EEG Epileptic TransientsMar 11 2019Preventing early progression of epilepsy and so the severity of seizures requires effective diagnosis. Epileptic transients indicate the ability to develop seizures but humans easily overlook such brief events in an electroencephalogram (EEG) what compromises ... More
A causal role of sensory cortices in behavioral benefits of 'learning by doing'Mar 11 2019Despite a rise in the use of "learning by doing" pedagogical methods in praxis, little is known as to why these methods may improve learning outcomes. This is surprising given that an increased mechanistic knowledge of learning by doing-based improvements ... More
Identical ideal individualsMar 10 2019Based on the behavior coordinate system, ideal individual model and quantum probability, the state of an ideal individual is assumed to be described by the behavior state function. Then we present a conjecture that the ideal individuals can be identical. ... More
SeizureNet: A Deep Convolutional Neural Network for Accurate Seizure Type Classification and Seizure DetectionMar 08 2019Automatic epileptic seizure analysis is important because the differentiation of neural patterns among different patients can be used to classify people with specific types of epilepsy. This could enable more efficient management of the disease. Automatic ... More
What the odor is not: Estimation by eliminationMar 06 2019The olfactory system uses the responses of a small number of broadly sensitive receptors to combinatorially encode a vast number of odors. Here, we propose a method for decoding such a distributed representation. Our main idea is that a receptor that ... More
SpykeTorch: Efficient Simulation of Convolutional Spiking Neural Networks with at most one Spike per NeuronMar 06 2019Application of deep convolutional spiking neural networks (SNNs) to artificial intelligence (AI) tasks has recently gained a lot of interest since SNNs are hardware-friendly and energy-efficient. Unlike the non-spiking counterparts, most of the existing ... More
NeuroPath2Path: Classification and elastic morphing between neuronal arbors using path-wise similarityMar 06 2019The shape and connectivity of a neuron determine its function. Modern imaging methods have proven successful at extracting such information. However, in order to analyze this type of data, neuronal morphology needs to be encoded in a graph-theoretic method. ... More
Systems of Oscillators Designed for a Specific Conscious PerceptMar 05 2019As put forward by neuroscientists, the mechanisms of consciousness can be elucidated by revealing correlations between neural dynamics and specific conscious percepts. Recently, I have elaborated on the mathematical formulation for a system of processes ... More
Approximations of Shannon Mutual Information for Discrete Variables with Applications to Neural Population CodingMar 04 2019Although Shannon mutual information has been widely used, its effective calculation is often difficult for many practical problems, including those in neural population coding. Asymptotic formulas based on Fisher information sometimes provide accurate ... More
On genetic correlation estimation with summary statistics from genome-wide association studiesMar 04 2019Genome-wide association studies (GWAS) have been widely used to examine the association between single nucleotide polymorphisms (SNPs) and complex traits, where both the sample size n and the number of SNPs p can be very large. Recently, cross-trait polygenic ... More
Deep Learning for Cognitive NeuroscienceMar 04 2019Neural network models can now recognise images, understand text, translate languages, and play many human games at human or superhuman levels. These systems are highly abstracted, but are inspired by biological brains and use only biologically plausible ... More
Autocurricula and the Emergence of Innovation from Social Interaction: A Manifesto for Multi-Agent Intelligence ResearchMar 02 2019Evolution has produced a multi-scale mosaic of interacting adaptive units. Innovations arise when perturbations push parts of the system away from stable equilibria into new regimes where previously well-adapted solutions no longer work. Here we explore ... More
Desynchronization dynamics of the Kuramoto model on connectome graphsMar 01 2019The time dependent behavior of the Kuramoto model, describing synchronization, has been studied numerically on small-world graphs. We determined the desynchronziation behavior, by solving this model via the 4th order Runge-Kutta algorithm on a large, ... More
Desynchronization dynamics of the Kuramoto model on connectome graphsMar 01 2019Mar 12 2019The time dependent behavior of the Kuramoto model, describing synchronization, has been studied numerically on small-world graphs. We determined the desynchronziation behavior, by solving this model via the 4th order Runge-Kutta algorithm on a large, ... More
Spared cognitive and behavioral functions prior to epilepsy onset in a rat model of 2 subcortical band heteropiaMar 01 201913 Subcortical band heterotopia (SBH), also known as doublecortex syndrome, is a 14 malformation of cortical development resulting from mutations in the doublecortin gene 15 (DCX). It is characterized by a lack of migration of cortical neurons that accumulate ... More
Quantifying High-order Interdependencies via Multivariate Extensions of the Mutual InformationFeb 28 2019This article introduces a model-agnostic approach to study statistical synergy, a form of emergence in which patterns at large scales are not traceable from lower scales. Our framework leverages various multivariate extensions of Shannon's mutual information, ... More
Principal Component Analysis for seizure characterization in EEG signalsFeb 28 2019A large variety of methods has been proposed for automatic seizure detection in EEG signals. Those achieving maximal performance are based on machine-learning techniques, which require long training sessions with large labelled databases, and produce ... More
The principles of adaptation in organisms and machines I: machine learning, information theory, and thermodynamicsFeb 28 2019How do organisms recognize their environment by acquiring knowledge about the world, and what actions do they take based on this knowledge? This article examines hypotheses about organisms' adaptation to the environment from machine learning, information-theoretic, ... More
Monotonic Gaussian Process for Spatio-Temporal Trajectory Separation in Brain Imaging DataFeb 28 2019We introduce a probabilistic generative model for disentangling spatio-temporal disease trajectories from series of high-dimensional brain images. The model is based on spatio-temporal matrix factorization, where inference on the sources is constrained ... More
Multiscale Fluctuation-based Dispersion Entropy and its Applications to Neurological DiseasesFeb 27 2019Fluctuation-based dispersion entropy (FDispEn) is a new approach to estimate the dynamical variability of the fluctuations of signals. It is based on Shannon entropy and fluctuation-based dispersion patterns. To quantify the physiological dynamics over ... More
Regularity Normalization: Constraining Implicit Space with Minimum Description LengthFeb 27 2019Feb 28 2019Inspired by the adaptation phenomenon of biological neuronal firing rate, we propose regularity normalization: a reparameterization of the activation in the neural network that take into account the statistical regularity in the implicit space. By considering ... More
Regularity Normalization: Constraining Implicit Space with Minimum Description LengthFeb 27 2019Inspired by the adaptation phenomenon of biological neuronal firing rate, we propose regularity normalization: a reparametrization of the activation in the neural network that take into account the statistical regularity in the implicit space. The implicit ... More
A tutorial on group effective connectivity analysis, part 1: first level analysis with DCM for fMRIFeb 27 2019Dynamic Causal Modelling (DCM) is the predominant method for inferring effective connectivity from neuroimaging data. In the 15 years since its introduction, the neural models and statistical routines in DCM have developed in parallel, driven by the needs ... More
Timeseries thresholding and the definition of avalanche sizeFeb 27 2019Avalanches whose sizes and durations are distributed as power laws appear in many contexts. Here, we show that there is a hidden peril in thresholding continuous times series --either from empirical or synthetic data-- for the detection of avalanches. ... More
Cortical recruitment and functional dynamics in postural control adaptation and habituation during vibratory proprioceptive stimulationFeb 27 2019Maintaining upright posture is a complex task governed by the integration of afferent sensorimotor and visual information with compensatory neuromuscular reactions. The objective of this work was to characterize the visual dependency and functional dynamics ... More
Accurate Target Localization by using Artificial Pinnae of brown long-eared batFeb 27 2019Echolocating bats locate the targets by echolocation. Many theoretical frameworks have been suggested the abilities of bats are related to the shapes of bats ears, but few artificial bat-like ears have been made to mimic the abilities, the difficulty ... More
Robust motifs of threshold-linear networksFeb 27 2019Robust motifs are graphs associated to threshold-linear networks (TLNs) for which the structure of fixed points is independent of the choice of connectivity matrix $W$. In this work we describe infinite families of robust motifs, and use them to completely ... More
Self-Organization in Spontaneous Movements of Neonates generates Self-specifying Sensory ExperiencesFeb 26 2019Movement experience and the coordination of perception and action are the basis of developing body awareness, emotion, motivation and cognition and the sense of self. The four limbs play a key role in the developing sense of body ownership, agency and ... More
Cortical Mirror-System Activation During Real-Life Game Playing: An Intracranial Electroencephalography (EEG) StudyFeb 25 2019Analogous to the mirror neuron system repeatedly described in monkeys as a possible substrate for imitation learning and/or action understanding, a neuronal execution/observation matching system (OEMS) is assumed in humans, but little is known to what ... More
A visual encoding model based on deep neural networks and transfer learningFeb 23 2019Background: Building visual encoding models to accurately predict visual responses is a central challenge for current vision-based brain-machine interface techniques. To achieve high prediction accuracy on neural signals, visual encoding models should ... More
Slow Waves Analysis Pipeline for extracting the Features of the Bi-Modality from the Cerebral Cortex of Anesthetized MiceFeb 22 2019Cortical slow oscillations are an emergent property of the cortical network, hallmark of low complexity brain states like sleep, and representing a default activity pattern. Here, we present a methodological approach for quantifying the spatial and temporal ... More
Slow Waves Analysis Pipeline for extracting the Features of the Bi-Modality from the Cerebral Cortex of Anesthetized MiceFeb 22 2019Mar 08 2019Cortical slow oscillations are an emergent property of the cortical network, a hallmark of low complexity brain states like sleep, and represent a default activity pattern. Here, we present a methodological approach for quantifying the spatial and temporal ... More
Gauging functional brain activity: from distinguishability to accessibilityFeb 22 2019Standard neuroimaging techniques provide non-invasive access not only to human brain anatomy but also to its physiology. The activity recorded with these techniques is generally called functional imaging, but what is observed per se is an instance of ... More
Probabilistic Inference of Binary Markov Random Fields in Spiking Neural Networks through Mean-field ApproximationFeb 22 2019Recent studies have suggested that the cognitive process of the human brain is realized as probabilistic inference and can be further modeled by probabilistic graphical models like Markov random fields. Nevertheless, it remains unclear how probabilistic ... More
Scaling of a large-scale simulation of synchronous slow-wave and asynchronous awake-like activity of a cortical model with long-range interconnectionsFeb 22 2019Cortical synapse organization supports a range of dynamic states on multiple spatial and temporal scales, from synchronous slow wave activity (SWA), characteristic of deep sleep or anesthesia, to fluctuating, asynchronous activity during wakefulness (AW). ... More
Deep CNN-based Speech Balloon Detection and Segmentation for Comic BooksFeb 21 2019We develop a method for the automated detection and segmentation of speech balloons in comic books, including their carrier and tails. Our method is based on a deep convolutional neural network that was trained on annotated pages of the Graphic Narrative ... More
Assessing Olfaction Using Ultrasonic Vocalization Recordings in Mouse Pups with a Sono-olfactometerFeb 21 2019Olfaction is the first sensory modality to develop during fetal life in mammals, and plays a key role in the various behaviors of neonates such as feeding and social interaction. Odorant cues (i.e., mother or predator scents) can trigger potentiation ... More
Adaptive frequency-based modeling of whole-brain oscillations: Predicting regional vulnerability and hazardousness ratesFeb 21 2019Whole-brain computational modeling based on structural connectivity measures has shown great promise in successfully simulating fMRI BOLD signals that includes temporal co-activation patterns that are highly similar to empirical functional connectivity ... More
Cross-frequency interactions during diffusion on complex brain networks are facilitated by scale-free propertiesFeb 21 2019Mar 14 2019We studied the interactions between different temporal scales of diffusion processes on complex networks and found them to be stronger in scale-free (SF) than in Erdos-Renyi (ER) networks, especially for the case of phase-amplitude coupling (PAC)-the ... More
Cross-frequency interactions during diffusion on complex networks are facilitated by scale-free propertiesFeb 21 2019We studied the interactions between different temporal scales of diffusion processes on complex networks and found them to be stronger in scale-free (SF) than in Erdos-Renyi (ER) networks, especially for the case of phase-amplitude coupling (PAC)-the ... More
Stress-induced analgesia in patients with chronic musculoskeletal pain and healthy controlsFeb 20 2019Introduction: Individuals with chronic musculoskeletal pain show impairments in their pain-modulatory capacity. Stress-induced analgesia (SIA) is a paradigm of endogenous pain inhibition mainly tested in animals. It has not been tested in patients with ... More
Auditory information loss in real-world listening environmentsFeb 20 2019Whether animal or speech communication, environmental sounds, or music -- all sounds carry some information. Sound sources are embedded in acoustic environments that contain any number of additional sources that emit sounds that reach the listener's ears ... More
Graph Spectral Characterization of Brain Cortical MorphologyFeb 19 2019The human brain cortical layer has a convoluted morphology that is unique to each individual. Characterization of the cortical morphology is necessary in longitudinal studies of structural brain change, as well as in discriminating individuals in health ... More
Assessment of cortical reorganization and preserved function in phantom limb pain: a methodological perspectiveFeb 19 2019Phantom limb pain (PLP) has been associated with both the reorganization of the somatotopic map in primary somatosensory cortex (S1) and preserved S1 function. Here we assessed the nature of the information (sensory, motor) that reaches S1 and methodological ... More
Assessment of cortical reorganization and preserved function in phantom limb pain: a methodological perspectiveFeb 19 2019Mar 05 2019Phantom limb pain (PLP) has been associated with both the reorganization of the somatotopic map in primary somatosensory cortex (S1) and preserved S1 function. Here we assessed the nature of the information (sensory, motor) that reaches S1 and methodological ... More
Identifying nonlinear dynamical systems via generative recurrent neural networks with applications to fMRIFeb 19 2019A major tenet in theoretical neuroscience is that cognitive and behavioral processes are ultimately implemented in terms of the neural system dynamics. Accordingly, a major aim for the analysis of neurophysiological measurements should lie in the identification ... More
Stochastic bursting in unidirectionally delay-coupled noisy excitable systemsFeb 19 2019We show that \emph{stochastic bursting} is observed in a ring of unidirectional delay-coupled noisy excitable systems, thanks to the combinational action of time-delayed coupling and noise. Under the approximation of timescale separation, i.e., when the ... More
Large-scale directed network inference with multivariate transfer entropy and hierarchical statistical testingFeb 18 2019Network inference algorithms are valuable tools for the study of large-scale neuroimaging datasets. Multivariate transfer entropy is well suited for this task, being a model-free measure that captures nonlinear and lagged dependencies between time series ... More
A computational model for grid maps in neural populationsFeb 18 2019Feb 19 2019Grid cells in the entorhinal cortex, together with place, speed and border cells, are major contributors to the organization of spatial representations in the brain. In this contribution we introduce a novel theoretical and algorithmic framework able ... More
A computational model for grid maps in neural populationsFeb 18 2019Grid cells in the entorhinal cortex, together with place, speed and border cells, are major contributors to the organization of spatial representations in the brain. In this contribution we introduce a novel theoretical and algorithmic framework able ... More
Metabolic basis of brain-like electrical signalling in bacterial communitiesFeb 17 2019Information processing in the mammalian brain relies on a careful regulation of the membrane potential dynamics of its constituent neurons, which propagates across the neuronal tissue via electrical signalling. We recently reported the existence of electrical ... More
Afferent Fiber Activity-Induced Cytoplasmic Calcium Signaling in Parvalbumin-Positive Inhibitory Interneurons of the Spinal Cord Dorsal HornFeb 17 2019Neuronal calcium (Ca2+) signaling represents a molecular trigger for diverse central nervous system adaptations and maladaptions. The altered function of dorsal spinal inhibitory interneurons is strongly implicated in the mechanisms underlying central ... More
Power contours: optimising sample size and precision in experimental psychology and human neuroscienceFeb 16 2019When designing experimental studies with human participants, experimenters must decide how many trials each participant will complete, as well as how many participants to test. Most discussion of statistical power (the ability of a study design to detect ... More
Power contours: optimising sample size and precision in experimental psychology and human neuroscienceFeb 16 2019Feb 22 2019When designing experimental studies with human participants, experimenters must decide how many trials each participant will complete, as well as how many participants to test. Most discussion of statistical power (the ability of a study design to detect ... More
Disruption of the prefrontal cortex improves implicit contextual memory-guided attention: combined behavioural and electrophysiological evidenceFeb 15 2019Many studies have shown that the dorsolateral prefrontal cortex (DLPFC) plays an important role in top-down cognitive control over intentional and deliberate behavior. However, recent studies have reported that DLPFC-mediated top-down control interferes ... More
Gamma band oscillations reflect sensory and affective dimensions of painFeb 15 2019Pain is a multidimensional process, which can be modulated by emotions, however, the mechanisms underlying this modulation are unknown. We used pictures with different emotional valence (negative, positive, neutral) as primes and applied electrical painful ... More
Assessing the Level of Autonomic Nervous Activity for Effective Biofeedback TrainingFeb 15 2019This paper proposes a prototype of a new biofeedback training based on mathematical models of cardiovascular control. For this purpose we develop a low-cost device that is able to record and process arterial pulse wave via photoplethysmograph and skin ... More
A Convolutional Network for Sleep Stages ClassificationFeb 15 2019Sleep stages classification is a crucial task in the context of sleep studies. It involves the simultaneous analysis of multiple signals recorded during sleep. However, it is complex and tedious, and even the trained expert can spend several hours scoring ... More
Tractography and machine learning: Current state and open challengesFeb 14 2019Supervised machine learning (ML) algorithms have recently been proposed as an alternative to traditional tractography methods in order to address some of their weaknesses. They can be path-based and local-model-free, and easily incorporate anatomical ... More
Influence of nicotine and alcohol on sleep and implications on insomnia: the reward-attention circuit modelFeb 14 2019Dopamine, a neurotransmitter well known for regulating movement, reward, and learning, is emerging as one of the neuromodulators of wakefulness. Drugs that increase the level of dopamine in the brain (including, but not limited to, nicotine) also increase ... More
Which Neural Network Architecture matches Human Behavior in Artificial Grammar Learning?Feb 13 2019In recent years artificial neural networks achieved performance close to or better than humans in several domains: tasks that were previously human prerogatives, such as language processing, have witnessed remarkable improvements in state of the art models. ... More
Neural network models and deep learning - a primer for biologistsFeb 13 2019Originally inspired by neurobiology, deep neural network models have become a powerful tool of machine learning and artificial intelligence, where they are used to approximate functions and dynamics by learning from examples. Here we give a brief introduction ... More
The Phi measure of integrated information is not well-defined for general physical systemsFeb 12 2019According to the Integrated Information Theory of Consciousness, consciousness is a fundamental observer-independent property of physical systems, and the measure Phi of integrated information is identical to the quantity or level of consciousness. For ... More
Interspike interval correlations in networks of inhibitory integrate-and-fire neuronsFeb 11 2019We study temporal correlations of interspike intervals (ISIs), quantified by the network-averaged serial correlation coefficient (SCC), in networks of both current- and conductance-based purely inhibitory integrate-and-fire neurons. Numerical simulations ... More
Neural Activity of Heterogeneous Inhibitory Spiking Networks with DelayFeb 11 2019We study a network of spiking neurons with heterogeneous excitabilities connected via inhibitory delayed pulses. For globally coupled systems the increase of the inhibitory coupling reduces the number of firing neurons by following a Winner Takes All ... More
Discovering dynamic functional networks in the human neonatal brain with electric source imagingFeb 11 2019When the human brain manifests the birth of organised communication among local and large-scale neuronal populations activity remains undescribed. We report, in resting-state EEG source-estimates of 100 infants at term age, the existence of macro-scale ... More
Linear Dynamics & Control of Brain NetworksFeb 08 2019The brain is an intricately structured organ responsible for the rich emergent dynamics that support the complex cognitive functions we enjoy as humans. With around $10^{11}$ neurons and $10^{15}$ synapses, understanding how the human brain works has ... More
Prediction of Dashed Café Wall illusion by the Classical Receptive Field ModelFeb 08 2019The Caf\'e Wall illusion is one of a class of tilt illusions where lines that are parallel appear to be tilted. We demonstrate that a simple Differences of Gaussian model provides an explanatory mechanism for the illusory tilt perceived in a family of ... More
Informing Computer Vision with Optical IllusionsFeb 08 2019Illusions are fascinating and immediately catch people's attention and interest, but they are also valuable in terms of giving us insights into human cognition and perception. A good theory of human perception should be able to explain the illusion, and ... More
Mobile Artificial Intelligence Technology for Detecting Macula Edema and Subretinal Fluid on OCT Scans: Initial Results from the DATUM alpha StudyFeb 08 2019Importance: Artificial Intelligence (AI) is necessary to address the large and growing deficit in retina and healthcare access globally. Mobile AI diagnostic platforms running in the Cloud may effectively and efficiently distribute such AI capability. ... More
Mobile Artificial Intelligence Technology for Detecting Macula Edema and Subretinal Fluid on OCT Scans: Initial Results from the DATUM alpha StudyFeb 08 2019Feb 12 2019Artificial Intelligence (AI) is necessary to address the large and growing deficit in retina and healthcare access globally. And mobile AI diagnostic platforms running in the Cloud may effectively and efficiently distribute such AI capability. Here we ... More
Dynamical learning of dynamicsFeb 07 2019The ability of humans and animals to quickly adapt to novel tasks is difficult to reconcile with the standard paradigm of learning by slow synaptic weight modification. Here we show that already static neural networks can learn to generate required dynamics ... More
Identification of epileptic regions from electroencephalographic data: Feigenbaum graphsFeb 07 2019Diagnosing epilepsy is a problem of crucial importance. So analysing EEG data is of much importance to help this diagnosis. Assembling the Feigenbaum graphs for EEG signals. And calculating their average clustering, average degree, and average shortest ... More
Can biological quantum networks solve NP-hard problems?Feb 07 2019There is a widespread view that the human brain is so complex that it cannot be efficiently simulated by universal Turing machines, let alone ordinary classical computers. During the last decades the question has therefore been raised whether we need ... More
Information Flow in Computational SystemsFeb 06 2019Feb 07 2019We develop a theoretical framework for defining and identifying flows of information in computational systems. Here, a computational system is assumed to be a directed graph, with "clocked" nodes that send transmissions to each other along the edges of ... More
Suppression and facilitation of motion perception in humans: a reply to Schallmo & Murray (2018)Feb 05 2019In a recent publication (Tzvetanov (2018), bioRxiv 465807), I made an extensive analysis with computational modelling and psychophysics of the simple experimental design of Dr. D.Tadin (Tadin, Lappin, Gilroy and Blake (2003), Nature, 424:312-315) about ... More
Performance of normative and approximate evidence accumulation on the dynamic clicks taskFeb 05 2019The aim of a number of psychophysics tasks is to uncover how mammals make decisions in a world that is in flux. Here we examine the characteristics of ideal and near--ideal observers in a task of this type. We ask when and how performance depends on task ... More
Morphological and functional networks' coupling by cortical lobesFeb 04 2019In this short communication I present a study on cortical thickness and functional networks' coupling topology by cortical lobes. First, I demonstrated modular organisation of these networks by the cortical surface frontal, temporal, parietal and occipital ... More
Comparison of brain connectomes using geodesic distance on manifold:a twin studyFeb 04 2019fMRI is a unique non-invasive approach for understanding the functional organization of the human brain, and task-based fMRI promotes identification of functionally relevant brain regions associated with a given task. Here, we use fMRI (using the Poffenberger ... More
Neural dynamics of emotion and cognition: from trajectories to underlying neural geometryFeb 01 2019This paper describes the outlines of a research program for understanding the cognitive-emotional brain, with an emphasis on the issue of dynamics: How can we study, characterize, and understand the neural underpinnings of cognitive-emotional behaviors ... More
Epileptiform spikes in specific left temporal and mesial temporal structures disrupt verbal episodic memory encodingJan 31 2019Patients diagnosed with epilepsy experience cognitive dysfunction that may be due to a transient cognitive/memory impairment (TCI/TMI) caused by spontaneous epileptiform spikes. We asked in a cohort of 166 adult patients with medically refractory focal ... More
Epileptiform spikes in specific left temporal and mesial temporal structures disrupt verbal episodic memory encodingJan 31 2019Feb 18 2019Patients diagnosed with epilepsy experience cognitive dysfunction that may be due to a transient cognitive/memory impairment (TCI/TMI) caused by spontaneous epileptiform spikes. We asked in a cohort of 166 adult patients with medically refractory focal ... More
Rhythm Zone Theory: Speech Rhythms are Physical after allJan 31 2019Speech rhythms have been dealt with in three main ways: from the introspective analyses of rhythm as a correlate of syllable and foot timing in linguistics and applied linguistics, through analyses of durations of segments of utterances associated with ... More
Sequential Bayesian Detection of Spike Activities from Fluorescence ObservationsJan 31 2019Extracting and detecting spike activities from the fluorescence observations is an important step in understanding how neuron systems work. The main challenge lies in that the combination of the ambient noise with dynamic baseline fluctuation, often contaminates ... More
Bayesian parameter estimation for the SWIFT model of eye-movement control during readingJan 30 2019Feb 01 2019Process-oriented theories of cognition must be evaluated against time-ordered observations. Here we present a representative example for data assimilation of the SWIFT model, a dynamical model of the control of spatial fixation position and fixation duration ... More
High gamma and beta band oscillations in left ventral posterior parietal cortex are regionally dissociated during verbal episodic encoding and recallJan 30 2019The posterior parietal cortex (PPC) has a unique role in memory retrieval: fMRI and electrocorticography studies suggest that within the ventral PPC (VPC) specifically, there is an anterior-posterior functional divergence between externally-oriented and ... More
High gamma and beta band oscillations in left ventral posterior parietal cortex are regionally dissociated during verbal episodic encoding and recallJan 30 2019Feb 08 2019The posterior parietal cortex (PPC) has a unique role in memory retrieval: fMRI and electrocorticography studies suggest that within the ventral PPC (VPC) specifically, there is an anterior-posterior functional divergence between externally-oriented and ... More
CoreNEURON : An Optimized Compute Engine for the NEURON SimulatorJan 30 2019The NEURON simulator has been developed over the past three decades and is widely used by neuroscientists to model the electrical activity of neuronal networks. Large network simulation projects using NEURON have supercomputer allocations that individually ... More
A morphospace framework to assess cognitive flexibility based on brain functional networksJan 30 2019Unfolding how the brain functionally shifts within the cognitive space remains an unresolved question. From a brain connectivity perspective, there exist two main concepts: cognitive shifts and cognitive flexibility. Although the former is the proxy of ... More
Minimax-optimal decoding of movement goals from local field potentials using complex spectral featuresJan 29 2019We consider the problem of predicting eye movement goals from local field potentials (LFP) recorded through a multielectrode array in the macaque prefrontal cortex. The monkey is tasked with performing memory-guided saccades to one of eight targets during ... More
Spectral Dynamic Causal Modelling of Resting-State fMRI: Relating Effective Brain Connectivity in the Default Mode Network to GeneticsJan 28 2019Jan 30 2019We conduct a novel imaging genetics study of the Alzheimer's Disease Neuroimaging Initiative based on resting-state fMRI (rs-fMRI) and genetic data obtained from 112 subjects, where each subject is classified as either cognitively normal (CN), as having ... More