Abstract Component-based software engineering is currently a development strategy used to improve complex embedded systems. The engineers have to deal with a large number of quality requirements (e.g. safety, security, availability, reliability, maintainability, portability, performance, and temporal correctness requirements), hence the development of complex embedded systems is becoming a challenging

Abstract There are evidences that the region of hippocampus is affected in the early stage of Alzheimer’s disease (AD). Moreover, the hippocampal pyramidal neurons receive cholinergic input from the medial septum. Thus, this study, based on the results of electrophysiological experiments, first constructs a modified hippocampal CA1 pyramidal neuronal model by introducing two new currents of M-current

Abstract Investigating human brain activity during expressing emotional states provides deep insight into complex cognitive functions and neurological correlations inside the brain. To be able to resemble the brain function in the best manner, a complex and natural stimulus should be applied as well, the method used for data analysis should have fewer assumptions, simplifications, and parameter adjustment

Abstract Reliable diagnosis of depressive disorder is essential for both optimal treatment and prevention of fatal outcomes. This study aimed to elucidate the effectiveness of two non-linear measures, Higuchi’s Fractal Dimension (HFD) and Sample Entropy (SampEn), in detecting depressive disorders when applied on EEG. HFD and SampEn of EEG signals were used as features for seven machine learning algorithms

Abstract Understanding the neural mechanisms associated with time to contact (TTC) estimation is an intriguing but challenging task. Despite the importance of TTC estimation in our everyday life, few studies have been conducted on it, and there are still a lot of unanswered questions and unknown aspects of this issue. In this study, we intended to address one of these unknown aspects. We used independent

Abstract How to better suppress the interference from the non-target language when switching from one language to the other in bilingual production? The current study applied transcranial direct current stimulation over the right dorsolateral prefrontal cortex to modulate language control measured by cross-frequency coupling. We found that switching to L2 was more modulated by F4–F3 alpha–beta phase-amplitude

Abstract Mental imagery has long been of interest to the cognitive and neurosciences, but how it manifests itself in the mind and brain still remains unresolved. In pursuit of this, we built a spiking neural model that can perform mental rotation and mental map scanning using strategies informed by the psychology and neuroscience literature. Results: When performing mental map scanning, reaction times

Abstract Humans use binocular disparity to extract depth information from two-dimensional retinal images in a process called stereopsis. Previous studies usually introduce the standard univariate analysis to describe the correlation between disparity level and brain activity within a given brain region based on functional magnetic resonance imaging (fMRI) data. Recently, multivariate pattern analysis

Abstract Bipolar disorder is characterized by mood swings—oscillations between manic and depressive states. The swings (oscillations) mark the length of an episode in a patient’s mood cycle (period), and can vary from hours to years. The proposed modeling study uses decision making framework to investigate the role of basal ganglia network in generating bipolar oscillations. In this model, the basal

Abstract Working memory (WM) refers to a memory system with limited energy for short-term maintenance and plays an important role in cognitive functions. At present, research regarding WM mostly focuses on the coordination between neural signals in the signal microelectrode channel. However, how neural signals coordinate the coding of WM at the network level is rarely studied. Cross-frequency coupling

Abstract Motor imagery (MI) is a mental representation of motor behavior and has been widely used in electroencephalogram based brain–computer interfaces (BCIs). Several studies have demonstrated the efficacy of MI-based BCI-feedback training in post-stroke rehabilitation. However, in the earliest stage of the training, calibration data typically contain insufficient discriminability, resulting in

Abstract When a bistable visual image, such as the Necker cube, is continuously viewed, the percept of the image endogenously alternates between one possible percept and the other. However, perceptual alternation can also be induced by an exogenous perturbation. For example, a typical external perturbation is the flashlight, which is expected to pervasively activate many brain regions. Therefore, the

Abstract Cerebrovascular accident (CVA) is one of the leading causes of death and disability worldwide, as well as a major financial burden for health care systems. CVA rodent models provide experimental support to determine possible in vivo therapies to reduce brain injury and consequent sequelae. This study analyzed nociceptive, motor, cognitive and mood functions in mice submitted to distal middle

Abstract In order to overcome the security weakness of the discrete chaotic sequence caused by small Lyapunov exponent and keyspace, a general chaotic construction method by cascading multiple high-dimensional isomorphic maps is presented in this paper. Compared with the original map, the parameter space of the resulting chaotic map is enlarged many times. Moreover, the cascaded system has larger chaotic

Abstract Transient, task related synchronous activity within neural populations has been recognized as the substrate of temporal coding in the brain. The mechanisms underlying inducing and propagation of transient synchronous activity are still unknown, and we propose that short-term plasticity (STP) of neural circuits may serve as a supplemental mechanism therein. By computational modeling, we showed

Abstract We consider a two-population network consisting of both inhibitory (I) interneurons and excitatory (E) pyramidal cells. This I–E neuronal network has adaptive dynamic I to E and E to I interpopulation synaptic strengths, governed by interpopulation spike-timing-dependent plasticity (STDP). In previous works without STDPs, fast sparsely synchronized rhythms, related to diverse cognitive functions

Abstract The brain is the most important organ of the human body, and the conversations between the brain and an apparatus can not only reveal a normally functioning or a dysfunctional brain but also can modulate the brain. Here, the apparatus may be a nonbiological instrument, such as a computer, and the consequent brain–computer interface is now a very popular research area with various applications

Abstract Epilepsy involves a diverse group of abnormalities, including molecular and cellular disorders. These abnormalities prove to be associated with the changes in local excitability and synaptic dynamics. Correspondingly, the epileptic processes including onset, propagation and generalized seizure may be related with the alterations of excitability and synapse. In this paper, three regions, epileptogenic

Abstract The effects of network topologies on signal propagation are studied in noisy feedforward neural network in detail, where the network topologies are modulated by changing both the in-degree and out-degree distributions of FFNs as identical, uniform and exponential respectively. Stochastic resonance appeared in three FFNs when the same external stimuli and noise are applied to the three different

Abstract We developed a brain–computer interface (BCI) able to continuously monitor working memory (WM) load in real-time (considering the last 2.5 s of brain activity). The BCI is based on biomarkers derived from spectral properties of non-invasive electroencephalography (EEG), subsequently classified by a linear discriminant analysis classifier. The BCI was trained on a visual WM task, tested in

Abstract In this paper, we construct an inertial two-neuron system with multiple delays, which is described by three first-order delayed differential equations. The neural system presents dynamical coexistence with equilibria, periodic orbits, and even quasi-periodic behavior by employing multiple types of bifurcations. To this end, the pitchfork bifurcation of trivial equilibrium is analyzed firstly

Abstract Neuroscientists draw lines of separation among structures and functions that they judge different, arbitrarily excluding or including issues in our description, to achieve positive demarcations that permits a pragmatic treatment of the nervous activity based on regularity and uniformity. However, uncertainty due to disconnectedness, lack of information and absence of objects’ sharp boundaries

Abstract It is well known in clinical practice that Alzheimer’s disease (AD) is closely associated with brain insulin resistance, and the cerebral insulin pathway has been proven to play a critical role in the pathogenesis of AD. However, finding the most efficient way to improve brain insulin resistance remains challenging. Peripheral administration of insulin does not have the desired therapeutic

Abstract Neurons in the brain receive thousands of synaptic inputs from other neurons. This afferent information is processed by neurons through synaptic integration, which is an important information processing mechanism in biological neural networks. Synaptic currents integrated from spiking trains of presynaptic neurons have complex nonlinear dynamics which endow neurons with significant computational

Abstract To study the effect of electromagnetic induction on the electric activities of neuron, memristive neuron models have been proposed by coupling membrane potential with magnetic flux. In this paper, on the basis of memristive Hindmarsh-Rose neuron model, time-delay memristive Hindmarsh-Rose neuron model is described and the responses of neuron in electrical activities are detected. The effect

Abstract Frequency coupling in nervous system is believed to be associated with normal and impaired brain functions. However, most of the existing experiments have been concentrated on the coupling strength within frequency bands, while the coupling strength between different bands is ignored. In this work, we apply phase synchronization index (PSI) to investigate the cross-frequency coupling (CFC)

Abstract Absence epileptiform activities are traditionally considered to be primarily induced by abnormal interactions between the cortical and thalamic neurons, which form the thalamocortical circuit in the brain. The basal ganglia, as an organizational unit in the brain, has close input and output relationships with the thalamocortical circuit. Although several studies report that the basal ganglia

Abstract Neuronal membrane and synapse polarities have been attracting considerable interest in recent years. Certain functional roles for such polarities have been suggested, yet, they have largely remained a subject for speculation and debate. Here, we note that neural circuit polarity codes, defined as sets of polarity permutations, divide into primal-size circuit polarity subcodes, which, sharing

Abstract The human brain goes through numerous cognitive states, most of these being hidden or implicit while performing a task, and understanding them is of great practical importance. However, identifying internal mental states is quite challenging as these states are difficult to label, usually short-lived, and generally, overlap with other tasks. One such problem pertains to bistable perception

Abstract Many studies reported that ERP-based BCIs can provide communication for some people with amyotrophic lateral sclerosis (ALS). ERP-based BCIs often present characters within a matrix that occupies the center of the visual field. However, several studies have identified some concerns with the matrix-based approach. This approach may lead to fatigue and errors resulting from flashing adjacent

Abstract Uncontrolled seizures may lead to irreversible damages in the brain and various limitations in the patient’s life. There exist experimental studies to stabilize the patient seizures. However, the experimental setups have many sensory devices to measure the dynamics of the brain cortex. These equipments prevent to produce small portable stabilizers for patients in everyday life. Recently, a

Abstract Retrieval of unintelligible speech is a basic need for speech impaired and is under research for several decades. But retrieval of random words from thoughts needs a substantial and consistent approach. This work focuses on the preliminary steps of retrieving vowels from Electroencephalography (EEG) signals acquired while speaking and imagining of speaking a consonant–vowel–consonant (CVC)

Apolipoprotein E (ApoE) ε4 allele and cerebral blood flow (CBF) changes are related to the increased risk of cognitive impairment independently. However, whether there are interactions between ApoE ε4 and CBF on memory performance in older adults with normal cognition remains unknown. This study determined whether the association between CBF and memory performance could be moderated by ApoE ε4 within

Watching an ambiguous image leads to the bistability of its perception, that randomly oscillates between two possible interpretations. The relevant evolution of the neuron system is usually described with the equation of its "movement" over the nonuniform energy landscape under the action of the stochastic force, corresponding to noise perturbations. We utilize the alternative (and simpler) approach

Visual attention is a selective process of visual information and improves perceptual performance by modulating activities of neurons in the visual system. It has been reported that attention increased firing rates of neurons, reduced their response variability and improved reliability of coding relevant stimuli. Recent neurophysiological studies demonstrated that attention also enhanced the synaptic

Neuron shows distinct dependence of electrical activities on membrane patch temperature, and the mode transition of electrical activity is induced by the patch temperature through modulating the opening and closing rates of ion channels. In this paper, inspired by the physical effect of memristor, the potassium and sodium ion channels embedded in the membrane patch are updated by using memristor-based

Detachment (self-focused) and positive reinterpretation (situation-focused) are two important forms of cognitive reappraisal during emotion regulation. Previous research shows situation-focused reappraisal to be more effective than self-focused reappraisal for intentional emotion regulation. How the two differ in emotional consequences as components of automatic emotion regulation is however unclear

Classifying different object categories is one of the most important aims of brain-computer interface researches. Recently, interactions between brain regions were studied using different methods, such as functional and effective connectivity techniques. Functional and effective connectivity techniques are applied to estimate human brain areas connectivity. The main purpose of this study is to compare

Quantifying brain dynamics during anesthesia is an important challenge for understanding the neurophysiological mechanisms of anesthetic drug effect. Several single channel Electroencephalogram (EEG) indices have been proposed for monitoring anesthetic drug effect. The most commonly used single channel commercial index is the Bispectral index (BIS). However, this monitor has shown some drawbacks. In

The gender recognition is an important research field to study evidence regarding some personal characteristics in the information and data society. However, some current traditional methods such as vision and sound have been exposed their own security weaknesses. Recently, biometric gender recognition based on Electroencephalography (EEG) signals has been widely used in information safety and medical

Methamphetamine (meth) is potently addictive and is closely linked to high crime rates in the world. Since meth withdrawal is very painful and difficult, most abusers relapse to abuse in traditional treatments. Therefore, developing accurate data-driven methods based on brain functional connectivity could be helpful in classifying and characterizing the neural features of meth dependence to optimize

Event-related potentials (ERPs) and oscillations (EROs) are reliable measures of cognition, but they require time-locked electroencephalographic (EEG) data to repetitive triggers that are not available in continuous sensory input streams. However, such real-life-like stimulation by videos or virtual-reality environments may serve as powerful means of creating specific cognitive or affective states

In this paper, the real-valued memristive neural networks (MNNs) are extended to quaternion field, a new class of neural networks named quaternion-valued memristive neural networks (QVMNNs) is then established. The problem of master-slave synchronization of this type of networks is investigated in this paper. Two types of controllers are designed: the traditional feedback controller and the event-triggered

Memristor is a nanoscale circuit element with nonvolatile, binary, multilevel and analog states. Its conductance (resistance) plasticity is similar to biological synapses. Information sparse coding is considered as the key mechanism of biological neural systems to process mass complex perception data, which is applied in the fields of signal processing, computer vision and so on. This paper proposes

Epilepsy is a chronic disorder, which causes strange perceptions, muscle spasms, sometimes seizures, and loss of awareness, associated with abnormal neuronal activity in the brain. The goal of this study is to investigate how effective connectivity (EC) changes effect on unexpected seizures prediction, as this will authorize the patients to play it safe and avoid risk. We approve the hypothesis that

In mapping the human structural connectome, we are in a very fortunate situation: one can compute and compare graphs, describing the cerebral connections between the very same, anatomically identified small regions of the gray matter among hundreds of human subjects. The comparison of these graphs has led to numerous recent results, as the (1) discovery that women's connectomes have deeper and richer

We developed a framework to study brain dynamics under cognition. In particular, we investigated the spatiotemporal properties of brain state switches under cognition. The lack of electroencephalography stationarity is exploited as one of the signatures of the metastability of brain states. We correlated power law exponents in the variables that we proposed to describe brain states, and dynamical properties

Contemporary neuroscience research primarily focuses on the identification of brain activation patterns commonly deviant across participant groups or experimental conditions. This approach inherently underestimates potentially meaningful intra- and inter-individual variability present in brain physiological measures. We propose a parameter referred to as 'individuality index (II)' that takes individual

Starting from the tenets of human imagination, i.e., the concepts of lines, points and infinity, we provide a biological demonstration that the skeptical claim "human beings cannot attain knowledge of the world" holds true. We show that the Euclidean account of the point as "that of which there is no part" is just a conceptual device produced by our brain, untenable in our physical/biological realm:

In this work we present a group of theoretical models for reaction times arising from simple-choice task tests. In particular, we argue for the inclusion of a shifted version of the Gamma distribution as a theoretical model based on a mathematical result on first hitting times. We contrast the goodness-of-fit of those models with the Ex-Gaussian distribution, using data from recently published experiments

Electrical activities of excitable cells produce diverse spiking-bursting patterns. The dynamics of the neuronal responses can be changed due to the variations of ionic concentrations between outside and inside the cell membrane. We investigate such type of spiking-bursting patterns under the effect of an electromagnetic induction on an excitable neuron model. The effect of electromagnetic induction

It is well known that neuronal networks are capable of transmitting complex spatiotemporal information in the form of precise sequences of neuronal discharges characterized by recurrent patterns. At the same time, the synchronized activity of large ensembles produces local field potentials that propagate through highly dynamic oscillatory waves, such that, at the whole brain scale, complex spatiotemporal

In this paper, the problem of robust consensus for multi-agent systems affected by external disturbances is discussed. A novel consensus control is developed by using a feedback controller based on disturbance rejection and Smith predictor scheme. Specifically, the disturbance rejection performance of the uncertain multi-agent systems is improved according to the estimation of equivalent-input-disturbance

Accumulating evidence suggest that excessive reactive oxygen species-induced oxidative damage may underlie neurodegeneration and cognitive impairment in several disorders including schizophrenia. In this study we examined the association of oxidative stress with cognitive deficits in first-episode drug-naïve (FEDN) patients with schizophrenia. We recruited 54 FEDN patients and 50 age- and sex-matched

Behavioral studies using the flanker 2-1 mapping task suggest that both stimulus and response conflicts contribute to flanker conflict effect. However, both are intertwined with distraction effect. Their underlying neural mechanisms remain unclear. We applied a perceptual flanker 2-1 mapping task to 24 healthy young adults, while the event-related potentials were recorded. The task included stimulus-incongruent

The automatic detection of seizures bears a considerable significance in epileptic diagnosis as it can efficiently lead to a considerable reduction of the workload of the medical staff. The present study aims at automatic detecting epileptic seizures in epileptic rats. To this end, seizures were induced in rats implementing the pentylenetetrazole model, with the electrocorticogram (ECoG) signals during

Small nuclear RNAs (snRNAs) and other RNA spliceosomal components are involved in neurological and psychiatric disorders. U1 snRNA has recently been demonstrated to be altered in pathology in some neurodegenerative diseases, but whether it has a causative role is not clear. Here we have studied this by overexpressing U1 snRNA in mice and measured their hippocampal oscillatory patterns and brain functions

Random pulses contribute to stochastic resonance in neuron models, whereas common random pulses cause stochastic-synchronized excitation in uncoupled neuron models. We studied concurrent phenomena contributing to phase synchronization and stochastic resonance following induction by a weak common random pulse in uncoupled non-identical Hodgkin-Huxley type neuron models. The common random pulse was selected

The present study aimed to identify the mechanism of tactile sensation by analyzing the regularity of the firing pattern of Merkel cell-neurite complex (MCNC) under the stimulation of different compression depths. The fingertips were exposed to the contact pressure of a spherical object to sense external stimuli in this study. The distribution structure of slowly adapting type I (SAI) mechanoreceptors

Multiple sclerosis (MS) is an autoimmune condition influenced by both genetic and environmental factors. Dirty electricity generated by electronic equipment is one of the environmental factors that may directly or indirectly impact MS susceptibility. The current Study aimed to evaluate the relationship between the usage time of electronic equipment and susceptibility to MS in North-West Iranian people