Cognitive Neurodynamics (COGN NEURODYNAMICS)

Publisher: Springer Verlag

Current impact factor: 1.67

Impact Factor Rankings

2016 Impact Factor Available summer 2017
2014 / 2015 Impact Factor 1.671
2013 Impact Factor 1.77
2012 Impact Factor 1.742
2011 Impact Factor 0.985
2010 Impact Factor 1.625
2009 Impact Factor 2.263

Impact factor over time

Impact factor
Year

Additional details

5-year impact 1.77
Cited half-life 4.00
Immediacy index 0.22
Eigenfactor 0.00
Article influence 0.38
ISSN 1871-4080
OCLC 219471552
Material type Periodical, Internet resource
Document type Journal / Magazine / Newspaper, Internet Resource

Publisher details

Springer Verlag

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  • Classification
    green

Publications in this journal

  • [Show abstract] [Hide abstract]
    ABSTRACT: The interplay between the prefrontal cortex (PFC) and striatum has an important role in cognitive processes. To investigate interactive functions between the two areas in reward processing, we recorded local field potentials (LFPs) simultaneously from the two areas of two monkeys performing a reward prediction task (large reward vs small reward). The power of the LFPs was calculated in three frequency bands: the beta band (15–29 Hz), the low gamma band (30–49 Hz), and the high gamma band (50–100 Hz). We found that both the PFC and striatum encoded the reward information in the beta band. The reward information was also found in the high gamma band in the PFC, not in the striatum. We further calculated the phase-locking value (PLV) between two LFP signals to measure the phase synchrony between the PFC and striatum. It was found that significant differences occurred between PLVs in different task periods and in different frequency bands. The PLVs in small reward condition were significant higher than that in large reward condition in the beta band. In contrast, the PLVs in the high gamma band were stronger in large reward trials than in small trials. These results suggested that the functional connectivity between the PFC and striatum depended on the task periods and reward conditions. The beta synchrony between the PFC and striatum may regulate behavioral outputs of the monkeys in the small reward condition.
    No preview · Article · Jan 2016 · Cognitive Neurodynamics
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    ABSTRACT: Recent studies show right hemisphere has a unique contribution to emotion processing. The present study investigated EEG using non-linear measures during emotional processing in PD patients with respect to motor symptom asymmetry (i.e., most affected body side). We recorded 14-channel wireless EEGs from 20 PD patients and 10 healthy age-matched controls (HC) by eliciting emotions such as happiness, sadness, fear, anger, surprise and disgust. PD patients were divided into two groups, based on most affected body side and unilateral motor symptom severity: left side-affected (LPD, n = 10) or right side-affected PD patients (RPD, n = 10). Nonlinear analysis of these emotional EEGs were performed by using approximate entropy, correlation dimension, detrended fluctuation analysis, fractal dimension, higher order spectra, hurst exponent (HE), largest Lyapunov exponent and sample entropy. The extracted features were ranked using analysis of variance based on F value. The ranked features were then fed into classifiers namely fuzzy K-nearest neighbor and support vector machine to obtain optimal performance using minimum number of features. From the experimental results, we found that (a) classification performance across all frequency bands performed well in recognizing emotional states of LPD, RPD, and HC; (b) the emotion-specific features were mainly related to higher frequency bands; and (c) predominantly LPD patients (inferred right-hemisphere pathology) were more impaired in emotion processing compared to RPD, as showed by a poorer classification performance. The results suggest that asymmetric neuronal degeneration in PD patients may contribute to the impairment of emotional communication.
    No preview · Article · Jan 2016 · Cognitive Neurodynamics
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    ABSTRACT: Background EEG activity is considered an index of functional state of brain. Chemotherapy (CT), used for non-central nervous system (CNS) cancer, can cross the blood brain barrier and contribute to changes in the functional state of brain that can alter background EEG activity. Quantitative EEG (qEEG) is superior to conventional EEG in the detection of subtle alterations of EEG background activity and for this reason, the use of qEEG might assist the clinician in evaluating the possible effect of CT on the CNS. The nucleoside analog cytosine arabinoside (Ara-C) is one of the milestone chemotherapeutic agents used for treatment of acute myeloid leukemia (AML). Our observational study evaluates the possible effect of Ara-C on the qEEG of patients with AML, without CNS involvement. We conducted an observational study on newly diagnosed AML patients without CNS involvement, undergoing treatment with Ara-C to analyze the possible effect of Ara-C high doses on EEG background activity using qEEG analyses. A total of nine AML patients, 5 with Ara-C i.v. high dose (≥3 g/m2 die), 4 with standard dose (100 mg/m2 die) underwent qEEG (at rest, during hyperpnoea, mental arithmetic task and blocking reaction). We compared the EEG background activity of the two groups at baseline and after 6 months. Statistical analysis showed no significant differences between the two groups in mean relative power for all frequency bands, at rest and during hyperpnoea, mental arithmetic task and blocking reaction. Our data indicate that high dose Ara-C i.v. did not induce significant changes on EEG background activity in our patients. Future research in this area could include prospective studies that would combine qEEG and neuropsychological testing to assess the impact of CT on brain functions.
    No preview · Article · Jan 2016 · Cognitive Neurodynamics
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    ABSTRACT: In this paper, the (Formula presented.) filtering problem is treated for N coupled genetic oscillator networks with time-varying delays and extrinsic molecular noises. Each individual genetic oscillator is a complex dynamical network that represents the genetic oscillations in terms of complicated biological functions with inner or outer couplings denote the biochemical interactions of mRNAs, proteins and other small molecules. Throughout the paper, first, by constructing appropriate delay decomposition dependent Lyapunov–Krasovskii functional combined with reciprocal convex approach, improved delay-dependent sufficient conditions are obtained to ensure the asymptotic stability of the filtering error system with a prescribed (Formula presented.) performance. Second, based on the above analysis, the existence of the designed (Formula presented.) filters are established in terms of linear matrix inequalities with Kronecker product. Finally, numerical examples including a coupled Goodwin oscillator model are inferred to illustrate the effectiveness and less conservatism of the proposed techniques.
    No preview · Article · Jan 2016 · Cognitive Neurodynamics
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    ABSTRACT: An increasing number of studies pays attention to cross-frequency coupling in neuronal oscillations network, as it is considered to play an important role in exchanging and integrating of information. In this study, two generalized algorithms, phase–amplitude coupling-evolution map approach and phase–amplitude coupling-conditional mutual information which have been developed and applied originally in an identical rhythm, are generalized to measure cross-frequency coupling. The effectiveness of quantitatively distinguishing the changes of coupling strength from the measurement of phase–amplitude coupling (PAC) is demonstrated based on simulation data. The data suggest that the generalized algorithms are able to effectively evaluate the strength of PAC, which are consistent with those traditional approaches, such as PAC-PLV and PAC-MI. Experimental data, which are local field potentials obtained from anaesthetized SD rats, have also been analyzed by these two generalized approaches. The data show that the theta–low gamma PAC in the hippocampal CA3–CA1 network is significantly decreased in the glioma group compared to that in the control group. The results, obtained from either simulation data or real experimental signals, are consistent with that of those traditional approaches PAC-MI and PAC-PLV. It may be considered as a proper indicator for the cross frequency coupling in sub-network, such as the hippocampal CA3 and CA1.
    No preview · Article · Jan 2016 · Cognitive Neurodynamics
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    ABSTRACT: Many saliency computational models have been proposed to simulate bottom-up visual attention mechanism of human visual system. However, most of them only deal with certain kinds of images or aim at specific applications. In fact, human beings have the ability to correctly select attentive focuses of objects with arbitrary sizes within any scenes. This paper proposes a new bottom-up computational model from the perspective of frequency domain based on the biological discovery of non-Classical Receptive Field (nCRF) in the retina. A saliency map can be obtained according to the idea of Extended Classical Receptive Field. The model is composed of three major steps: firstly decompose the input image into several feature maps representing different frequency bands that cover the whole frequency domain by utilizing Gabor wavelet. Secondly, whiten the feature maps to highlight the embedded saliency information. Thirdly, select some optimal maps, simulating the response of receptive field especially nCRF, to generate the saliency map. Experimental results show that the proposed algorithm is able to work with stable effect and outstanding performance in a variety of situations as human beings do and is adaptive to both psychological patterns and natural images. Beyond that, biological plausibility of nCRF and Gabor wavelet transform make this approach reliable.
    No preview · Article · Jan 2016 · Cognitive Neurodynamics

  • No preview · Article · Jan 2016 · Cognitive Neurodynamics
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    ABSTRACT: Accumulating evidence of population association studies support the hypothesis that the high heritability of major psychiatric disorders is a combination of relatively common alleles of modest effect, and rare alleles some with relatively larger effects. We have previously reported low frequency mutations in the proximal promoter of the human calreticulin (CALR) gene that co-occur with the spectrum of major psychiatric disorders. One of those mutations at −205C>T (rs556992558) was detected in an isolate case of schizoaffective disorder. In the current study, the functional implication of mutation −205T is studied in the human neuronal cell lines LAN-5, BE(2)-C and HEK-293. In contrast with other mutations in the promoter region which increase gene expression activity, the −205T mutation significantly decreased gene expression in those cell lines in comparison with the wild-type −205C nucleotide (p < 0.000001, p < 0.0005, and p < 0.017, respectively). Treatment of the cell lines with the mood-stabilizing drug, valproic acid (VPA) resulted in differential gene expression activity in the mutant −205T versus the wild-type −205C construct. VPA increased gene expression activity in both constructs, while a significantly higher expression activity was observed in the mutant construct (p < 0.01), indicative of the creation of a positive effector binding site for VPA as a result of the −205T mutation. We conclude that deviation from normalcy in the level of CALR in either direction is associated with major psychiatric disorders.
    No preview · Article · Nov 2015 · Cognitive Neurodynamics
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    ABSTRACT: In this article, the high codimension bifurcations of a six-neuron BAM neural network system with multiple delays are addressed. We first deduce the existence conditions under which the origin of the system is a Bogdanov–Takens singularity with multiplicities two or three. By choosing the connection coefficients as bifurcation parameters and using the formula derived from the normal form theory and the center manifold, the normal forms of Bogdanov–Takens and triple zero bifurcations are presented. Some numerical examples are shown to support our main results.
    No preview · Article · Nov 2015 · Cognitive Neurodynamics
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    ABSTRACT: To investigate the electroencephalograph (EEG) background activity in patients with Alzheimer’s disease (AD), power spectrum density (PSD) and Lempel–Ziv (LZ) complexity analysis are proposed to extract multiple effective features of EEG signals from AD patients and further applied to distinguish AD patients from the normal controls. Spectral analysis based on autoregressive Burg method is first used to quantify the power distribution of EEG series in the frequency domain. Compared with the control group, the relative PSD of AD group is significantly higher in the theta frequency band while lower in the alpha frequency bands. In order to explore the nonlinear information, Lempel–Ziv complexity (LZC) and multi-scale LZC is further applied to all electrodes for the four frequency bands. Analysis results demonstrate that the group difference is significant in the alpha frequency band by LZC and multi-scale LZC analysis. However, the group difference of multi-scale LZC is much more remarkable, manifesting as more channels undergo notable changes, particularly in electrodes O1 and O2 in the occipital area. Moreover, the multi-scale LZC value provided a better classification between the two groups with an accuracy of 85.7 %. In addition, we combine both features of the relative PSD and multi-scale LZC to discriminate AD patients from the normal controls by applying a support vector machine model in the alpha frequency band. It is indicated that the two groups can be clearly classified by the combined feature. Importantly, the accuracy of the classification is higher than that of any one feature, reaching 91.4 %. The obtained results show that analysis of PSD and multi-scale LZC can be taken as a potential comprehensive measure to distinguish AD patients from the normal controls, which may benefit our understanding of the disease.
    No preview · Article · Nov 2015 · Cognitive Neurodynamics
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    ABSTRACT: A spinal cord injury (SCI) is one of the most common neurological disorders. In this paper, we examined the consequences of upper SCI in a male participant on the cerebral blood flow velocity. In particular, transcranial Doppler was used to study these effects through middle cerebral arteries (MCA) during resting-state periods and during cognitive challenges (non-verbal word-generation tasks and geometric-rotation tasks). Signal characteristics were analyzed from raw signals and envelope signals (maximum velocity) in the time domain, the frequency domain and the time-frequency domain. The frequency features highlighted an increase of the peak frequency in L-MCA and R-MCA raw signals, which revealed stronger cerebral blood flow during geometric/verbal processes respectively. This underlined a slight dominance of the right hemisphere during word-generation periods and a slight dominance of the left hemisphere during geometric processes. This finding was confirmed by cross-correlation in the time domain and by the entropy rate in information-theoretic domain. A comparison of our results to other neurological disorders (Alzheimer's disease, Parkinson's disease, autism, epilepsy, traumatic brain injury) showed that the SCI had similar effects such as general decreased cerebral blood flow and similar regular hemispheric dominance in a few cases.
    No preview · Article · Nov 2015 · Cognitive Neurodynamics
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    ABSTRACT: The primary aim of this study was to establish whether the decline of the memory of an angular displacement, detected by the semicircular canals, is best characterized by an exponential function or by a power function. In 27 subjects a conflict was created between the semicircular canals and the graviceptive systems. Subjects were seated, facing forwards, in the gondola of a large centrifuge. The centrifuge was accelerated from stationary to 2.5Gz. While the swing out of the gondola (66°) during acceleration constitutes a frontal plane angular-displacement stimulus to the semicircular canals, the graviceptive systems persistently signal that the subject is upright. During 6 min at 2.5Gz the perceived head and body position was recorded; in darkness the subject repeatedly adjusted the orientation of a luminous line so that it appeared to be horizontal. Acceleration of the centrifuge induced a sensation of tilt which declined with time in a characteristic way. A three-parameter exponential function (Y = Ae−bt + C) and a power function (Y = At−b + C) were fitted to the data points. The inter-individual variability was considerable. In the vast majority of cases, however, the exponential function provided a better fit (in terms of RMS error) than the power function. The mean exponential function was: y = 27.8e−0.018t + 0.5°, where t is time in seconds. Findings are discussed with connection to possible underlying neural mechanisms; in particular, the head-direction system and short-term potentiation and persistent action potential firing in the hippocampus are considered.
    No preview · Article · Nov 2015 · Cognitive Neurodynamics
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    ABSTRACT: Recognition and identification of aesthetic preference is indispensable in industrial design. Humans tend to pursue products with aesthetic values and make buying decisions based on their aesthetic preferences. The existence of neuromarketing is to understand consumer responses toward marketing stimuli by using imaging techniques and recognition of physiological parameters. Numerous studies have been done to understand the relationship between human, art and aesthetics. In this paper, we present a novel preference-based measurement of user aesthetics using electroencephalogram (EEG) signals for virtual 3D shapes with motion. The 3D shapes are designed to appear like bracelets, which is generated by using the Gielis superformula. EEG signals were collected by using a medical grade device, the B-Alert X10 from advance brain monitoring, with a sampling frequency of 256 Hz and resolution of 16 bits. The signals obtained when viewing 3D bracelet shapes were decomposed into alpha, beta, theta, gamma and delta rhythm by using time–frequency analysis, then classified into two classes, namely like and dislike by using support vector machines and K-nearest neighbors (KNN) classifiers respectively. Classification accuracy of up to 80 % was obtained by using KNN with the alpha, theta and delta rhythms as the features extracted from frontal channels, Fz, F3 and F4 to classify two classes, like and dislike.
    No preview · Article · Nov 2015 · Cognitive Neurodynamics
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    ABSTRACT: Extreme learning machine (ELM) is a novel and fast learning method to train single layer feed-forward networks. However due to the demand for larger number of hidden neurons, the prediction speed of ELM is not fast enough. An evolutionary based ELM with differential evolution (DE) has been proposed to reduce the prediction time of original ELM. But it may still get stuck at local optima. In this paper, a novel algorithm hybridizing DE and metaheuristic coral reef optimization (CRO), which is called differential evolution coral reef optimization (DECRO), is proposed to balance the explorative power and exploitive power to reach better performance. The thought and the implement of DECRO algorithm are discussed in this article with detail. DE, CRO and DECRO are applied to ELM training respectively. Experimental results show that DECRO-ELM can reduce the prediction time of original ELM, and obtain better performance for training ELM than both DE and CRO.
    No preview · Article · Oct 2015 · Cognitive Neurodynamics