Search for: models--neurological
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    Failure tolerance of spike phase synchronization in coupled neural networks

    , Article Chaos (Woodbury, N.Y.) ; Volume 21, Issue 3 , 2011 , Pages 033126- ; 10897682 (ISSN) Jalili, M ; Sharif University of Technology
    Neuronal synchronization plays an important role in the various functionality of nervous system such as binding, cognition, information processing, and computation. In this paper, we investigated how random and intentional failures in the nodes of a network influence its phase synchronization properties. We considered both artificially constructed networks using models such as preferential attachment, Watts-Strogatz, and Erdo{combining double acute accent} s-Rényi as well as a number of real neuronal networks. The failure strategy was either random or intentional based on properties of the nodes such as degree, clustering coefficient, betweenness centrality, and vulnerability. Hindmarsh-Rose... 

    Early detection of apnea-bradycardia episodes in preterm infants based on coupled hidden Markov model

    , Article IEEE International Symposium on Signal Processing and Information Technology, IEEE ISSPIT 2013 ; 2013 , Pages 243-248 Masoudi, S ; Montazeri, N ; Shamsollahi, M. B ; Ge, D ; Beuchee, A ; Pladys, P ; Hernandez, A. I ; Sharif University of Technology
    IEEE Computer Society  2013
    The incidence of apnea-bradycardia episodes in preterm infants may lead to neurological disorders. Prediction and detection of these episodes are an important task in healthcare systems. In this paper, a coupled hidden Markov model (CHMM) based method is applied to detect apnea-bradycardia episodes. This model is evaluated and compared with two other methods based on hidden Markov model (HMM) and hidden semi-Markov model (HSMM). Evaluation and comparison are performed on a dataset of 233 apnea-bradycardia episodes which have been manually annotated. Observations are composed of RR-interval time series and QRS duration time series. The performance of each method was evaluated in terms of... 

    EEG-based functional brain networks: does the network size matter?

    , Article PloS one ; Volume 7, Issue 4 , 2012 ; 19326203 (ISSN) Joudaki, A ; Salehi, N ; Jalili, M ; Knyazeva, M. G ; Sharif University of Technology
    PLOS  2012
    Functional connectivity in human brain can be represented as a network using electroencephalography (EEG) signals. These networks--whose nodes can vary from tens to hundreds--are characterized by neurobiologically meaningful graph theory metrics. This study investigates the degree to which various graph metrics depend upon the network size. To this end, EEGs from 32 normal subjects were recorded and functional networks of three different sizes were extracted. A state-space based method was used to calculate cross-correlation matrices between different brain regions. These correlation matrices were used to construct binary adjacency connectomes, which were assessed with regards to a number of... 

    Individual differences in nucleus accumbens dopamine receptors predict development of addiction-like behavior: A computational approach

    , Article Neural Computation ; Volume 22, Issue 9 , 2010 , Pages 2334-2368 ; 08997667 (ISSN) Piray, P ; Keramati, M. M ; Dezfouli, A ; Lucas, C ; Mokri, A ; Sharif University of Technology
    Clinical and experimental observations show individual differences in the development of addiction. Increasing evidence supports the hypothesis that dopamine receptor availability in the nucleus accumbens (NAc) predisposes drug reinforcement. Here, modeling striatal-midbrain dopaminergic circuit, we propose a reinforcement learning model for addiction based on the actor-critic model of striatum. Modeling dopamine receptors in the NAc as modulators of learning rate for appetitive-but not aversive-stimuli in the critic-but not the actor-we define vulnerability to addiction as a relatively lower learning rate for the appetitive stimuli, compared to aversive stimuli, in the critic. We... 

    Synchronizing hindmarsh-rose neurons over newman-watts networks

    , Article Chaos ; Volume 19, Issue 3 , 2009 ; 10541500 (ISSN) Jalili, M ; Sharif University of Technology
    American Institute of Physics Inc  2009
    In this paper, the synchronization behavior of the Hindmarsh-Rose neuron model over Newman-Watts networks is investigated. The uniform synchronizing coupling strength is determined through both numerically solving the network's differential equations and the master-stability-function method. As the average degree is increased, the gap between the global synchronizing coupling strength, i.e., the one obtained through the numerical analysis, and the strength necessary for the local stability of the synchronization manifold, i.e., the one obtained through the master-stability-function approach, increases. We also find that this gap is independent of network size, at least in a class of networks... 

    Adjustable primitive pattern generator: A novel cerebellar model for reaching movements

    , Article Neuroscience Letters ; Volume 406, Issue 3 , 2006 , Pages 232-234 ; 03043940 (ISSN) Vahdat, S ; Maghsoudi, A ; Haji Hasani, M ; Towhidkhah, F ; Gharibzadeh, S ; Jahed, M ; Sharif University of Technology
    Cerebellum has been assumed as an array of adjustable pattern generators (APGs). In recent years, electrophysiological researches have suggested the existence of modular structures in spinal cord called motor primitives. In our proposed model, each "adjustable primitive pattern generator" (APPG) module in the cerebellum is consisted of a large number of parallel APGs, the output of each module being the weighted sum of the outputs of these APGs. Each spinal field is tuned by a coefficient, representing a descending supraspinal command, which is modulated by ith APPG correspondingly. According to this model, motor control can be interpreted in terms of the modification of these coefficients.... 

    Spike phase synchronization in delayed-coupled neural networks: Uniform vs. non-uniform transmission delay

    , Article Chaos ; Volume 23, Issue 1 , 2013 ; 10541500 (ISSN) Jalili, M ; Sharif University of Technology
    In this paper, we investigated phase synchronization in delayed dynamical networks. Non-identical spiking Hindmarsh-Rose neurons were considered as individual dynamical systems and coupled through a number of network structures such as scale-free, Erdos-Rényi, and modular. The individual neurons were coupled through excitatory chemical synapses with uniform or distributed time delays. The profile of spike phase synchrony was different when the delay was uniform across the edges as compared to the case when it was distributed, i.e., different delays for the edges. When an identical transmission delay was considered, a quasi-periodic pattern was observed in the spike phase synchrony. There... 

    Neural fields with fast learning dynamic kernel

    , Article Biological Cybernetics ; Volume 106, Issue 1 , January , 2012 , Pages 15-26 ; 03401200 (ISSN) Abbassian, A. H ; Fotouhi, M ; Heidari, M ; Sharif University of Technology
    We introduce a modified-firing-rate model based on Hebbian-type changing synaptic connections. The existence and stability of solutions such as rest state, bumps, and traveling waves are shown for this type of model. Three types of kernels, namely exponential, Mexican hat, and periodic synaptic connections, are considered. In the former two cases, the existence of a rest state solution is proved and the conditions for their stability are found. Bump solutions are shown for two kinds of synaptic kernels, and their stability is investigated by constructing a corresponding Evans function that holds for a specific range of values of the kernel coefficient strength (KCS). Applying a similar... 

    Constructing brain functional networks from EEG: Partial and unpartial correlations

    , Article Journal of Integrative Neuroscience ; Volume 10, Issue 2 , 2011 , Pages 213-232 ; 02196352 (ISSN) Jalili, M ; Knyazeva, M. G ; Sharif University of Technology
    We consider electroencephalograms (EEGs) of healthy individuals and compare the properties of the brain functional networks found through two methods: unpartialized and partialized cross-correlations. The networks obtained by partial correlations are fundamentally different from those constructed through unpartial correlations in terms of graph metrics. In particular, they have completely different connection efficiency, clustering coefficient, assortativity, degree variability, and synchronization properties. Unpartial correlations are simple to compute and they can be easily applied to large-scale systems, yet they cannot prevent the prediction of non-direct edges. In contrast, partial... 

    Estimation of phase signal change in neuronal current MRI for evoke response of tactile detection with realistic somatosensory laminar network model

    , Article Australasian Physical and Engineering Sciences in Medicine ; Volume 39, Issue 3 , 2016 , Pages 717-726 ; 01589938 (ISSN) BagheriMofidi, S. M ; Pouladian, M ; Jameie, S. B ; Abbaspour Tehrani Fard, A ; Sharif University of Technology
    Springer Netherlands  2016
    Magnetic field generated by neuronal activity could alter magnetic resonance imaging (MRI) signals but detection of such signal is under debate. Previous researches proposed that magnitude signal change is below current detectable level, but phase signal change (PSC) may be measurable with current MRI systems. Optimal imaging parameters like echo time, voxel size and external field direction, could increase the probability of detection of this small signal change. We simulate a voxel of cortical column to determine effect of such parameters on PSC signal. We extended a laminar network model for somatosensory cortex to find neuronal current in each segment of pyramidal neurons (PN). 60,000... 

    Dynamic stability of spine using stability-based optimization and muscle spindle reflex

    , Article IEEE Transactions on Neural Systems and Rehabilitation Engineering ; Volume 16, Issue 1 , 2008 , Pages 106-118 ; 15344320 (ISSN) Zeinali Davarani, S ; Hemami, H ; Barin, K ; Shirazi Adl, A ; Parnianpour, M ; Sharif University of Technology
    A computational method for simulation of 3-D movement of the trunk under the control of 48 anatomically oriented muscle actions was developed. Neural excitation of muscles was set based on inverse dynamics approach along with the stability-based optimization. The effect of muscle spindle reflex response on the trunk movement stability was evaluated upon the application of a perturbation moment. The method was used to simulate the trunk movement from the upright standing to 60° of flexion. Incorporation of the stability condition as an additional constraint in the optimization resulted in an increase in antagonistic activities demonstrating that the antagonistic co-activation acts to increase... 

    Using distance on the Riemannian manifold to compare representations in brain and in models

    , Article NeuroImage ; Volume 239 , 2021 ; 10538119 (ISSN) Shahbazi, M ; Shirali, A ; Aghajan, H ; Nili, H ; Sharif University of Technology
    Academic Press Inc  2021
    Representational similarity analysis (RSA) summarizes activity patterns for a set of experimental conditions into a matrix composed of pairwise comparisons between activity patterns. Two examples of such matrices are the condition-by-condition inner product and correlation matrix. These representational matrices reside on the manifold of positive semidefinite matrices, called the Riemannian manifold. We hypothesize that representational similarities would be more accurately quantified by considering the underlying manifold of the representational matrices. Thus, we introduce the distance on the Riemannian manifold as a metric for comparing representations. Analyzing simulated and real fMRI... 

    Stimulus presentation can enhance spiking irregularity across subcortical and cortical regions

    , Article PLoS Computational Biology ; Volume 18, Issue 7 , 2022 ; 1553734X (ISSN) Fayaz, S ; Fakharian, M. A ; Ghazizadeh, A ; Sharif University of Technology
    Public Library of Science  2022
    Stimulus presentation is believed to quench neural response variability as measured by fano-factor (FF). However, the relative contributions of within-trial spike irregularity and trial-to-trial rate variability to FF fluctuations have remained elusive. Here, we introduce a principled approach for accurate estimation of spiking irregularity and rate variability in time for doubly stochastic point processes. Consistent with previous evidence, analysis showed stimulus-induced reduction in rate variability across multiple cortical and subcortical areas. However, unlike what was previously thought, spiking irregularity, was not constant in time but could be enhanced due to factors such as... 

    EEG-based functional networks in schizophrenia

    , Article Computers in Biology and Medicine ; Volume 41, Issue 12 , 2011 , Pages 1178-1186 ; 00104825 (ISSN) Jalili, M ; Knyazeva, M. G ; Sharif University of Technology
    Schizophrenia is often considered as a dysconnection syndrome in which, abnormal interactions between large-scale functional brain networks result in cognitive and perceptual deficits. In this article we apply the graph theoretic measures to brain functional networks based on the resting EEGs of fourteen schizophrenic patients in comparison with those of fourteen matched control subjects. The networks were extracted from common-average-referenced EEG time-series through partial and unpartial cross-correlation methods. Unpartial correlation detects functional connectivity based on direct and/or indirect links, while partial correlation allows one to ignore indirect links. We quantified the... 

    Speed/accuracy trade-off between the habitual and the goal-directed processes

    , Article PLoS Computational Biology ; Volume 7, Issue 5 , 2011 ; 1553734X (ISSN) Keramati, M ; Dezfouli, A ; Piray, P ; Sharif University of Technology
    Instrumental responses are hypothesized to be of two kinds: habitual and goal-directed, mediated by the sensorimotor and the associative cortico-basal ganglia circuits, respectively. The existence of the two heterogeneous associative learning mechanisms can be hypothesized to arise from the comparative advantages that they have at different stages of learning. In this paper, we assume that the goal-directed system is behaviourally flexible, but slow in choice selection. The habitual system, in contrast, is fast in responding, but inflexible in adapting its behavioural strategy to new conditions. Based on these assumptions and using the computational theory of reinforcement learning, we... 

    ECG classification algorithm based on STDP and R-STDP neural networks for real-time monitoring on ultra low-power personal wearable devices

    , Article IEEE Transactions on Biomedical Circuits and Systems ; Volume 13, Issue 6 , 2021 , Pages 1483-1493 ; 19324545 (ISSN) Amirshahi, A ; Hashemi, M ; Sharif University of Technology
    Institute of Electrical and Electronics Engineers Inc  2021
    This paper presents a novel ECG classification algorithm for inclusion as part of real-time cardiac monitoring systems in ultra low-power wearable devices. The proposed solution is based on spiking neural networks which are the third generation of neural networks. In specific, we employ spike-timing dependent plasticity (STDP), and reward-modulated STDP (R-STDP), in which the model weights are trained according to the timings of spike signals, and reward or punishment signals. Experiments show that the proposed solution is suitable for real-time operation, achieves comparable accuracy with respect to previous methods, and more importantly, its energy consumption in real-time classification... 

    Interpolation of orientation distribution functions in diffusion weighted imaging using multi-tensor model

    , Article Journal of Neuroscience Methods ; Volume 253 , 2015 , Pages 28-37 ; 01650270 (ISSN) Afzali, M ; Fatemizadeh, E ; Soltanian Zadeh, H ; Sharif University of Technology
    Background: Diffusion weighted imaging (DWI) is a non-invasive method for investigating the brain white matter structure and can be used to evaluate fiber bundles. However, due to practical constraints, DWI data acquired in clinics are low resolution. New method: This paper proposes a method for interpolation of orientation distribution functions (ODFs). To this end, fuzzy clustering is applied to segment ODFs based on the principal diffusion directions (PDDs). Next, a cluster is modeled by a tensor so that an ODF is represented by a mixture of tensors. For interpolation, each tensor is rotated separately. Results: The method is applied on the synthetic and real DWI data of control and... 

    Mathematical modeling of CSF pulsatile hydrodynamics based on fluid-solid interaction

    , Article IEEE Transactions on Biomedical Engineering ; Volume 57, Issue 6 , 2010 , Pages 1255-1263 ; 00189294 (ISSN) Masoumi, N ; Bastani, D ; Najarian, S ; Ganji, F ; Farmanzad, F ; Seddighi, A. S ; Sharif University of Technology
    Intracranial pressure (ICP) is derived from cerebral blood pressure and cerebrospinal fluid (CSF) circulatory dynamics and can be affected in the course of many diseases. Computer analysis of the ICP time pattern plays a crucial role in the diagnosis and treatment of those diseases. This study proposes the application of Linninger et al.s [IEEE Trans. Biomed. Eng. , vol. 52, no. 4, pp. 557565, Apr. 2005] fluidsolid interaction model of CSF hydrodynamic in ventricular system based on our clinical data from a group of patients with brain parenchyma tumor. The clinical experiments include the arterial blood pressure (ABP), venous blood pressure, and ICP in the subarachnoid space (SAS). These... 

    A novel nonlinear function evaluation approach for efficient fpga mapping of neuron and synaptic plasticity models

    , Article IEEE Transactions on Biomedical Circuits and Systems ; Volume 13, Issue 2 , 2019 , Pages 454-469 ; 19324545 (ISSN) Jokar, E ; Abolfathi, H ; Ahmadi, A ; Sharif University of Technology
    Institute of Electrical and Electronics Engineers Inc  2019
    Efficient hardware realization of spiking neural networks is of great significance in a wide variety of applications, such as high-speed modeling and simulation of large-scale neural systems. Exploiting the key features of FPGAS, this paper presents a novel nonlinear function evaluation approach, based on an effective uniform piecewise linear segmentation method, to efficiently approximate the nonlinear terms of neuron and synaptic plasticity models targeting low-cost digital implementation. The proposed approach takes advantage of a high-speed and extremely simple segment address encoder unit regardless of the number of segments, and therefore is capable of accurately approximating a given... 

    Neuromuscular control of the point to point and oscillatory movements of a sagittal arm with the actor-critic reinforcement learning method

    , Article Computer Methods in Biomechanics and Biomedical Engineering ; Volume 8, Issue 2 , 2005 , Pages 103-113 ; 10255842 (ISSN) Golkhou, V ; Parnianpour, M ; Lucas, C ; Sharif University of Technology
    In this study, we have used a single link system with a pair of muscles that are excited with alpha and gamma signals to achieve both point to point and oscillatory movements with variable amplitude and frequency. The system is highly nonlinear in all its physical and physiological attributes. The major physiological characteristics of this system are simultaneous activation of a pair of nonlinear musclelike- actuators for control purposes, existence of nonlinear spindle-like sensors and Golgi tendon organlike sensor, actions of gravity and external loading. Transmission delays are included in the afferent and efferent neural paths to account for a more accurate representation of the reflex...