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Cognitive Neurodynamics

Emmanuelle Tognoli, Guillaume Dumas, J A Scott Kelso
To complement experimental efforts toward understanding human social interactions at both neural and behavioral levels, two computational approaches are presented: (1) a fully parameterizable mathematical model of a social partner, the Human Dynamic Clamp which, by virtue of experimentally controlled interactions between Virtual Partners and real people, allows for emergent behaviors to be studied; and (2) a multiscale neurocomputational model of social coordination that enables exploration of social self-organization at all levels-from neuronal patterns to people interacting with each other...
February 2018: Cognitive Neurodynamics
Ruoyu Wei, Jinde Cao, Ahmed Alsaedi
This paper investigates the finite-time synchronization and fixed-time synchronization problems of inertial memristive neural networks with time-varying delays. By utilizing the Filippov discontinuous theory and Lyapunov stability theory, several sufficient conditions are derived to ensure finite-time synchronization of inertial memristive neural networks. Then, for the purpose of making the setting time independent of initial condition, we consider the fixed-time synchronization. A novel criterion guaranteeing the fixed-time synchronization of inertial memristive neural networks is derived...
February 2018: Cognitive Neurodynamics
Bing Hu, Yu Guo, Xiaoqiang Zou, Jing Dong, Long Pan, Min Yu, Zhejia Yang, Chaowei Zhou, Zhang Cheng, Wanyue Tang, Haochen Sun
Based on a classical model of the basal ganglia thalamocortical network, in this paper, we employed a type of the deep brain stimulus voltage on the subthalamic nucleus to study the control mechanism of absence epilepsy seizures. We found that the seizure can be well controlled by turning the period and the duration of current stimulation into suitable ranges. It is the very interesting bidirectional periodic adjustment phenomenon. These parameters are easily regulated in clinical practice, therefore, the results obtained in this paper may further help us to understand the treatment mechanism of the epilepsy seizure...
February 2018: Cognitive Neurodynamics
Adil Deniz Duru, Moataz Assem
Neural efficiency is proposed as one of the neural mechanisms underlying elite athletic performances. Previous sports studies examined neural efficiency using tasks that involve motor functions. In this study we investigate the extent of neural efficiency beyond motor tasks by using a mental subtraction task. A group of elite karate athletes are compared to a matched group of non-athletes. Electroencephalogram is used to measure cognitive dynamics during resting and increased mental workload periods. Mainly posterior alpha band power of the karate players was found to be higher than control subjects under both tasks...
February 2018: Cognitive Neurodynamics
Minqiang Huang, Jing Jin, Yu Zhang, Dewen Hu, Xingyu Wang
Recently, many auditory BCIs are using beeps as auditory stimuli, while beeps sound unnatural and unpleasant for some people. It is proved that natural sounds make people feel comfortable, decrease fatigue, and improve the performance of auditory BCI systems. Drip drop is a kind of natural sounds that makes humans feel relaxed and comfortable. In this work, three kinds of drip drops were used as stimuli in an auditory-based BCI system to improve the user-friendness of the system. This study explored whether drip drops could be used as stimuli in the auditory BCI system...
February 2018: Cognitive Neurodynamics
D M Mateos, R Guevara Erra, R Wennberg, J L Perez Velazquez
Quantification of complexity in neurophysiological signals has been studied using different methods, especially those from information or dynamical system theory. These studies have revealed a dependence on different states of consciousness, and in particular that wakefulness is characterized by a greater complexity of brain signals, perhaps due to the necessity for the brain to handle varied sensorimotor information. Thus, these frameworks are very useful in attempts to quantify cognitive states. We set out to analyze different types of signals obtained from scalp electroencephalography (EEG), intracranial EEG and magnetoencephalography recording in subjects during different states of consciousness: resting wakefulness, different sleep stages and epileptic seizures...
February 2018: Cognitive Neurodynamics
Yu-Cheng Liu, Chi-Cheng Chang, Yu-Hsuan Sylvia Yang, Chaoyun Liang
Understanding the cognitive processes used in creative practices is essential to design research. In this study, electroencephalography was applied to investigate the brain activations of visual designers when they responded to various types of word stimuli during design thinking. Thirty visual designers were recruited, with the top third and bottom third of the participants divided into high-creativity (HC) and low-creativity (LC) groups. The word stimuli used in this study were two short poems, adjectives with similar meanings, and adjectives with opposing meanings...
February 2018: Cognitive Neurodynamics
Noha Mohsen Zommara, Muneyoshi Takahashi, Johan Lauwereyns
When faced with familiar versus novel options, animals may exploit the acquired action-outcome associations or attempt to form new associations. Little is known about which factors determine the strategy of choice behavior in partially comprehended environments. Here we examine the influence of multiple action-outcome associations on choice behavior in the context of rewarding outcomes (food) and aversive outcomes (electric foot-shock). We used a nose-poke paradigm with rats, incorporating a dilemma between a familiar option and a novel, higher-value option...
February 2018: Cognitive Neurodynamics
Nasibeh Talebi, Ali Motie Nasrabadi, Iman Mohammad-Rezazadeh
Studies on interactions between brain regions estimate effective connectivity, (usually) based on the causality inferences made on the basis of temporal precedence. In this study, the causal relationship is modeled by a multi-layer perceptron feed-forward artificial neural network, because of the ANN's ability to generate appropriate input-output mapping and to learn from training examples without the need of detailed knowledge of the underlying system. At any time instant, the past samples of data are placed in the network input, and the subsequent values are predicted at its output...
February 2018: Cognitive Neurodynamics
Ahmad Rauf Subhani, Nidal Kamel, Mohamad Naufal Mohamad Saad, Nanda Nandagopal, Kenneth Kang, Aamir Saeed Malik
Complaints of stress are common in modern life. Psychological stress is a major cause of lifestyle-related issues, contributing to poor quality of life. Chronic stress impedes brain function, causing impairment of many executive functions, including working memory, decision making and attentional control. The current study sought to describe newly developed stress mitigation techniques, and their influence on autonomic and endocrine functions. The literature search revealed that the most frequently studied technique for stress mitigation was biofeedback (BFB)...
February 2018: Cognitive Neurodynamics
Yesim Güzey Aras, Abdülkadir Tunç, Belma Doğan Güngen, Adil Can Güngen, Yusuf Aydemir, Bekir Enes Demiyürek
The purpose of this study was to investigate the effects of depression, anxiety and sleep disturbances on cognitive functions in chronic obstructive pulmonary disease (COPD) patients. In this prospective case-control study, demographic data, smoking history, depression, anxiety, sleep quality and cognitive status of 48 COPD patients and 36 healthy volunteers aged 40-90 years were recorded. The Beck depression inventory (BDI), the Beck anxiety inventory (BAI), and Pittsburgh Sleep Quality Index (PSQI) were used to assess depression, anxiety and sleep quality, respectively in COPD patients...
December 2017: Cognitive Neurodynamics
Jingyi Qu, Rubin Wang
In this paper, the collective behaviors of a small-world neuronal network motivated by the anatomy of a mammalian cortex based on both Izhikevich model and Rulkov model are studied. The Izhikevich model can not only reproduce the rich behaviors of biological neurons but also has only two equations and one nonlinear term. Rulkov model is in the form of difference equations that generate a sequence of membrane potential samples in discrete moments of time to improve computational efficiency. These two models are suitable for the construction of large scale neural networks...
December 2017: Cognitive Neurodynamics
Eva Déli, Arturo Tozzi, James F Peters
Brain electric activity exhibits two important features: oscillations with different timescales, characterized by diverse functional and psychological outcomes, and a temporal power law distribution. In order to further investigate the relationships between low- and high- frequency spikes in the brain, we used a variant of the Borsuk-Ulam theorem which states that, when we assess the nervous activity as embedded in a sphere equipped with a fractal dimension, we achieve two antipodal points with similar features (the slow and fast, scale-free oscillations)...
December 2017: Cognitive Neurodynamics
Dongzhe Hou, Chunfang Wang, Yuanyuan Chen, Weijie Wang, Jingang Du
Abnormal long-range temporal correlation (LRTC) in EEG oscillation has been observed in several brain pathologies and mental disorders. This study examined the relationship between the LRTC of broadband EEG oscillation and depression following cerebral infarction with different hemispheric lesions to provide a novel insight into such depressive disorders. Resting EEGs of 16 channels in 18 depressed (9 left and 9 right lesions) and 21 non-depressed (11 left and 10 right lesions) subjects following cerebral infarction and 19 healthy control subjects were analysed by means of detrended fluctuation analysis, a quantitative measurement of LRTC...
December 2017: Cognitive Neurodynamics
Jong Ho Hwang, Kyoung Won Nam, Dong Pyo Jang, In Young Kim
There have been few reports that investigated the effects of the degree and pattern of a spectral smearing of stimuli due to deteriorated hearing ability on the performance of auditory brain-computer interface (BCI) systems. In this study, we assumed that such spectral smearing of stimuli may affect the performance of an auditory steady-state response (ASSR)-based BCI system and performed subjective experiments using 10 normal-hearing subjects to verify this assumption. We constructed smearing-reflected stimuli using an 8-channel vocoder with moderate and severe hearing loss setups and, using these stimuli, performed subjective concentration tests with three symmetric and six asymmetric smearing patterns while recording electroencephalogram signals...
December 2017: Cognitive Neurodynamics
A Khasnobish, S Datta, R Bose, D N Tibarewala, A Konar
Tactual exploration of objects produce specific patterns in the human brain and hence objects can be recognized by analyzing brain signals during tactile exploration. The present work aims at analyzing EEG signals online for recognition of embossed texts by tactual exploration. EEG signals are acquired from the parietal region over the somatosensory cortex of blindfolded healthy subjects while they tactually explored embossed texts, including symbols, numbers, and alphabets. Classifiers based on the principle of supervised learning are trained on the extracted EEG feature space, comprising three features, namely, adaptive autoregressive parameters, Hurst exponents, and power spectral density, to recognize the respective texts...
December 2017: Cognitive Neurodynamics
Yasar Dasdemir, Esen Yildirim, Serdar Yildirim
In this study, we investigate the brain networks during positive and negative emotions for different types of stimulus (audio only, video only and audio + video) in [Formula: see text], and [Formula: see text] bands in terms of phase locking value, a nonlinear method to study functional connectivity. Results show notable hemispheric lateralization as phase synchronization values between channels are significant and high in right hemisphere for all emotions. Left frontal electrodes are also found to have control over emotion in terms of functional connectivity...
December 2017: Cognitive Neurodynamics
Csaba Kerepesi, Balázs Szalkai, Bálint Varga, Vince Grolmusz
Based on the data of the NIH-funded Human Connectome Project, we have computed structural connectomes of 426 human subjects in five different resolutions of 83, 129, 234, 463 and 1015 nodes and several edge weights. The graphs are given in anatomically annotated GraphML format that facilitates better further processing and visualization. For 96 subjects, the anatomically classified sub-graphs can also be accessed, formed from the vertices corresponding to distinct lobes or even smaller regions of interests of the brain...
October 2017: Cognitive Neurodynamics
Xiaoqing Li, Yuping Zhang, Lin Li, Haiyan Zhao, Xiufang Du
The present electroencephalogram study used an attention probe paradigm to investigate how semantic and acoustic structures constrain temporal attention during speech comprehension. Spoken sentences were used as stimuli, with each one containing a four-character critical phrase, of which the third character was the target character. We manipulated not only the semantic relationship between the target character and the immediately preceding two characters, but also the presence/absence of a pitch accent on the first character...
October 2017: Cognitive Neurodynamics
Zhiyong Yang, Taohong Zhang, Jingcheng Lu, Yuan Su, Dezheng Zhang, Yaowu Duan
This paper studies the joint effect of V-matrix, a recently proposed framework for statistical inferences, and extreme learning machine (ELM) on regression problems. First of all, a novel algorithm is proposed to efficiently evaluate the V-matrix. Secondly, a novel weighted ELM algorithm called V-ELM is proposed based on the explicit kernel mapping of ELM and the V-matrix method. Though V-matrix method could capture the geometrical structure of training data, it tends to assign a higher weight to instance with smaller input value...
October 2017: Cognitive Neurodynamics
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