Cognitive Neurodynamics Journal Impact Factor & Information

Publisher: Springer Verlag

Journal description

Current impact factor: 1.77

Impact Factor Rankings

2015 Impact Factor Available summer 2015
2013 / 2014 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 1.73
Cited half-life 3.20
Immediacy index 0.45
Eigenfactor 0.00
Article influence 0.36
ISSN 1871-4080
OCLC 219471552
Material type Periodical, Internet resource
Document type Journal / Magazine / Newspaper, Internet Resource

Publisher details

Springer Verlag

  • Pre-print
    • Author can archive a pre-print version
  • Post-print
    • Author can archive a post-print version
  • Conditions
    • Author's pre-print on pre-print servers such as arXiv.org
    • Author's post-print on author's personal website immediately
    • Author's post-print on any open access repository after 12 months after publication
    • Publisher's version/PDF cannot be used
    • Published source must be acknowledged
    • Must link to publisher version
    • Set phrase to accompany link to published version (see policy)
    • Articles in some journals can be made Open Access on payment of additional charge
  • Classification
    ​ green

Publications in this journal

  • [Show abstract] [Hide abstract]
    ABSTRACT: The presence of cross-modal stochastic resonance in different noise environments has been proved in previous behavioral and event-related potential studies, while it was still unclear whether the gamma-band oscillation study was another evidence of cross-modal stochastic resonance. The multisensory gain of gamma-band activity between the audiovisual (AV) and auditory-only conditions in different noise environments was analyzed. Videos of face motion articulating words concordant with different levels of pink noise were used as stimuli. Signal-to-noise ratios (SNRs) of 0, −4, −8, −12 and −16 dB were selected to measure the speech recognition accuracy and EEG activity for 20 healthy subjects. The power and phase of EEG gamma-band oscillations increased in a time window of 50-90 ms. The multisensory gains of evoked and total activity, as well as phase-locking factor, were greatest at the −12 dB SNR, which were consistent with the behavioral result. The multisensory gain of gamma-band activity showed an inverted U-shaped curve as a function of SNR. This finding confirmed the presence of cross-modal stochastic resonance. In addition, there was a significant correlation between evoked activity and phase-locking factor of gamma-band at five different SNRs. Gamma-band oscillation was believed to play a role in the rapid processing and information linkage strengthening of AV modalities in the early stage of cognitive processes.
    Cognitive Neurodynamics 08/2015; 9(4). DOI:10.1007/s11571-015-9333-5
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    ABSTRACT: In this paper, a nonlinear model for genetic regulator networks (GRNs) with SUM regulatory logic is presented. Four sufficient and necessary conditions of global asymptotical stability and global exponential stability for the equilibrium point of the GRNs are proposed, respectively. Specifically, three weak sufficient conditions and corresponding corollaries are derived by using comparing theorem and Dini derivative method. Then, a famous GRN model is used as the example to illustrate the effectiveness of our theoretical results. Comparing to the results in the previous literature, some novel ideas, study methods and interesting results are explored.
    Cognitive Neurodynamics 08/2015; 9(4). DOI:10.1007/s11571-015-9341-5
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    ABSTRACT: Brain activity is a cooperative process among neurons and involves the coupling relationship, which is crucial to perform operational tasks in various specialized areas of the nervous system. A finite signal transmission speed along the axons results in a space-dependent time delay. The central pattern generator (CPG) can in principle produce basic locomotor rhythm in the absence of inputs from higher brain centers and peripheral sensory feedback. To study the dynamic performance of CPG with time delay and its coupling relationship with the cerebral cortex, a new CPG model with time delay and a model of the neural mass model (NMM) and the CPG are developed. The coupling model is based on biological experimental results. Bifurcation theories and maximal Lyapunov exponent are used to analyze the dynamic performance. From the results, some CPGs are suggested to be embedded in limbs and composed of the parameters space which corresponds to the one of the cerebral cortex. This embodiment of humans can reduce the burden of the brain and simplify the control of the locomotion. The results also show that the phase diagram of the CPG cannot keep the limit cycle, and that the state of the NMM becomes increasingly chaotic as time delay increases. This finding implies that a person with slow reaction can easily lose the stability of his or her locomotion.
    Cognitive Neurodynamics 08/2015; 9(4). DOI:10.1007/s11571-015-9338-0
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    ABSTRACT: The current event-related potential study investigated the modulation effects of different emotion regulation strategies on electrocortical responses. When watching negative or neutral pictures, participants were instructed to perform three tasks: cognitive reappraisal, expressive suppression and passive viewing. We found that negative pictures elicited a larger late positive potential (LPP) than neutral pictures. Moreover, processes involved in strategy also had an effect on LPP amplitude, which was indicated by a larger LPP in reappraisal compared with suppression and viewing tasks when neutral pictures were presented. After the influence of processes on LPP was excluded, results showed that reappraisal effectively decreased the emotion-enhanced LPP than suppression and viewing. The difference in regulatory effect may be determined by the underlying processing mechanism. A larger frontal-central component, N2, was observed in suppression than reappraisal and viewing, which suggested that it involved the processes focusing on behavioral response. While the larger LPP found in reappraisal implicated that it recruited cognitive processes focusing on the picture meaning.
    Cognitive Neurodynamics 08/2015; 9(4). DOI:10.1007/s11571-015-9339-z
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    ABSTRACT: In this paper, we investigate the abnormalities of electroencephalograph (EEG) signals in the Alzheimer's disease (AD) by analyzing 16-scalp electrodes EEG signals and make a comparison with the normal controls. The power spectral density (PSD) which represents the power distribution of EEG series in the frequency domain is used to evaluate the abnormalities of AD brain. Spectrum analysis based on autoregressive Burg method shows that the relative PSD of AD group is increased in the theta frequency band while significantly reduced in the alpha2 frequency bands, particularly in parietal, temporal, and occipital areas. Furthermore, the coherence of two EEG series among different electrodes is analyzed in the alpha2 frequency band. It is demonstrated that the pair-wise coherence between different brain areas in AD group are remarkably decreased. Interestingly, this decrease of pair-wise electrodes is much more significant in inter-hemispheric areas than that in intra-hemispheric areas. Moreover, the linear cortico-cortical functional connectivity can be extracted based on coherence matrix, from which it is shown that the functional connections are obviously decreased, the same variation trend as relative PSD. In addition, we combine both features of the relative PSD and the normalized degree of functional network to discriminate AD patients from the normal controls by applying a support vector machine model in the alpha2 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. The obtained results show that analysis of PSD and coherence-based functional network can be taken as a potential comprehensive measure to distinguish AD patients from the normal, which may benefit our understanding of the disease.
    Cognitive Neurodynamics 06/2015; 9(3):291-304. DOI:10.1007/s11571-014-9325-x
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    ABSTRACT: The cerebral cortex, thalamus and basal ganglia together form an important network in the brain, which is closely related to several nerve diseases, such as parkinson disease, epilepsy seizure and so on. Absence seizure can be characterized by 2-4 Hz oscillatory activity, and it can be induced by abnormal interactions between the cerebral cortex and thalamus. Many experimental results have also shown that basal ganglia are a key neural structure, which closely links the corticothalamic system in the brain. Presently, we use a corticothalamic-basal ganglia model to study which pathways in corticothalamic system can induce absence seizures and how these oscillatory activities can be controlled by projections from the substantia nigra pars reticulata (SNr) to the thalamic reticular nucleus (TRN) or the specific relay nuclei (SRN) of the thalamus. By tuning the projection strength of the pathway "Excitatory pyramidal cortex-SRN", "SRN-Excitatory pyramidal cortex" and "SRN-TRN" respectively, different firing states including absence seizures can appear. This indicates that absence seizures can be induced by tuning the connection strength of the considered pathway. In addition, typical absence epilepsy seizure state "spike-and-slow wave discharges" can be controlled by adjusting the activation level of the SNr as the pathways SNr-SRN and SNr-TRN open independently or together. Our results emphasize the importance of basal ganglia in controlling absence seizures in the corticothalamic system, and can provide a potential idea for the clinical treatment.
    Cognitive Neurodynamics 06/2015; 9(3):279-89. DOI:10.1007/s11571-014-9321-1
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    ABSTRACT: Steady-state visually evoked potentials (SSVEP) have been widely used in the neural engineering and cognitive neuroscience researches. Previous studies have indicated that the SSVEP fundamental frequency responses are correlated with the topological properties of the functional networks entrained by the periodic stimuli. Given the different spatial and functional roles of the fundamental frequency and harmonic responses, in this study we further investigated the relation between the harmonic responses and the corresponding functional networks, using the graph theoretical analysis. We found that the second harmonic responses were positively correlated to the mean functional connectivity, clustering coefficient, and global and local efficiencies, while negatively correlated with the characteristic path lengths of the corresponding networks. In addition, similar pattern occurred with the lowest stimulus frequency (6.25 Hz) at the third harmonic responses. These findings demonstrate that more efficient brain networks are related to larger SSVEP responses. Furthermore, we showed that the main connection pattern of the SSVEP harmonic response networks originates from the interactions between the frontal and parietal-occipital regions. Overall, this study may bring new insights into the understanding of the brain mechanisms underlying SSVEP.
    Cognitive Neurodynamics 06/2015; 9(3). DOI:10.1007/s11571-015-9327-3
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    ABSTRACT: The paper is devoted to the investigation of synchronization for an array of linearly and diffusively coupled inertial delayed neural networks (DNNs). By placing feedback control on a small fraction of network nodes, the entire coupled DNNs can be synchronized to a common objective trajectory asymptotically. Two different analysis methods, including matrix measure strategy and Lyapunov–Krasovskii function approach, are employed to provide sufficient criteria for the synchronization control problem. Comparisons of these two techniques are given at the end of the paper. Finally, an illustrative example is provided to show the effectiveness of the obtained theoretical results.
    Cognitive Neurodynamics 06/2015; 9(3). DOI:10.1007/s11571-014-9322-0
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    ABSTRACT: It has been shown that, by adding a chaotic sequence to the weight update during the training of neural networks, the chaos injection-based gradient method (CIBGM) is superior to the standard backpropagation algorithm. This paper presents the theoretical convergence analysis of CIBGM for training feedforward neural networks. We consider both the case of batch learning as well as the case of online learning. Under mild conditions, we prove the weak convergence, i.e., the training error tends to a constant and the gradient of the error function tends to zero. Moreover, the strong convergence of CIBGM is also obtained with the help of an extra condition. The theoretical results are substantiated by a simulation example.
    Cognitive Neurodynamics 06/2015; 9(3):331-40. DOI:10.1007/s11571-014-9323-z
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    ABSTRACT: Based on the neural efficiency hypothesis and task-induced EEG gamma-band response (GBR), this study investigated the brain regions where neural resource could be most efficiently recruited by the math-gifted adolescents in response to varying cognitive demands. In this experiment, various GBR-based mental states were generated with three factors (level of mathematical ability, task complexity, and short-term learning) modulating the level of neural activation. A feature subset selection method based on the sequential forward floating search algorithm was used to identify an “optimal” combination of EEG channel locations, where the corresponding GBR feature subset could obtain the highest accuracy in discriminating pairwise mental states influenced by each experiment factor. The integrative results from multi-factor selections suggest that the right-lateral fronto-parietal system is highly involved in neural efficiency of the math-gifted brain, primarily including the bilateral superior frontal, right inferior frontal, right-lateral central and right temporal regions. By means of the localization method based on single-trial classification of mental states, new GBR features and EEG channel-based brain regions related to mathematical giftedness were identified, which could be useful for the brain function improvement of children/adolescents in mathematical learning through brain-computer interface systems.
    Cognitive Neurodynamics 05/2015; DOI:10.1007/s11571-015-9345-1
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    ABSTRACT: In this paper, a new synchronization problem for the collective dynamics among genetic oscillators with unbounded time-varying delay is investigated. The dynamical system under consideration consists of an array of linearly coupled identical genetic oscillators with each oscillators having unbounded time-delays. A new concept called power-rate synchronization, which is different from both the asymptotical synchronization and the exponential synchronization, is put forward to facilitate handling the unbounded time-varying delays. By using a combination of the Lyapunov functional method, matrix inequality techniques and properties of Kronecker product, we derive several sufficient conditions that ensure the coupled genetic oscillators to be power-rate synchronized. The criteria obtained in this paper are in the form of matrix inequalities. Illustrative example is presented to show the effectiveness of the obtained results.
    Cognitive Neurodynamics 05/2015; DOI:10.1007/s11571-015-9344-2
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    ABSTRACT: We continuously receive the external information from multiple sensors simultaneously. The brain must judge a source event of these sensory informations and integrate them. It is thought that judging the simultaneity of such multisensory stimuli is an important cue when we discriminate whether the stimuli are derived from one event or not. Although previous studies have investigated the correspondence between an auditory-visual (AV) simultaneity perceptions and the neural responses, there are still few studies of this. Electrophysiological studies have reported that ongoing oscillations in human cortex affect perception. Especially, the phase resetting of ongoing oscillations has been examined as it plays an important role in multisensory integration. The aim of this study was to investigate the relationship of phase resetting for the judgment of AV simultaneity judgement tasks. The subjects were successively presented with auditory and visual stimuli with intervals that were controlled as \(\mathrm{SOA_{50\%}}\) and they were asked to report whether they perceived them simultaneously or not. We investigated the effects of the phase of ongoing oscillations on simultaneity judgments with AV stimuli with SOAs in which the detection rate of asynchrony was 50 %. It was found that phase resetting at the beta frequency band in the brain area that related to the modality of the following stimulus occurred after preceding stimulus onset only when the subjects perceived AV stimuli as simultaneous. This result suggested that beta phase resetting occurred in areas that are related to the subsequent stimulus, supporting perception multisensory stimuli as simultaneous.
    Cognitive Neurodynamics 05/2015; DOI:10.1007/s11571-015-9342-4
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    ABSTRACT: A reactive brain-computer interface using electroencephalography (EEG) relies on the classification of evoked ERP responses. As the trial-to-trial variation is evitable in EEG signals, it is a challenge to capture the consistent classification features distribution. Clustering EEG trials with similar features and utilizing a specific classifier adjusted to each cluster can improve EEG classification. In this paper, instead of measuring the similarity of ERP features, the brain states during image stimuli presentation that evoked N1 responses were used to group EEG trials. The correlation between momentary phases of pre-stimulus EEG oscillations and N1 amplitudes was analyzed. The results demonstrated that the phases of time–frequency points about 5.3 Hz and 0.3 s before the stimulus onset have significant effect on the ERP classification accuracy. Our findings revealed that N1 components in ERP fluctuated with momentary phases of EEG. We also further studied the influence of pre-stimulus momentary phases on classification of N1 features. Results showed that linear classifiers demonstrated outstanding classification performance when training and testing trials have close momentary phases. Therefore, this gave us a new direction to improve EEG classification by grouping EEG trials with similar pre-stimulus phases and using each to train unit classifiers respectively.
    Cognitive Neurodynamics 04/2015; 9(2). DOI:10.1007/s11571-014-9317-x
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    ABSTRACT: In chronic renal failure there is a gradual retention of substances in the tissues and body fluids, called as uremic retention toxins, which can bring about a number of biochemical activities in the body. Chronic renal insufficiency also leads to progressive behavioural conflict. Uremic toxins can affect both the central and the peripheral nervous system. Uremic encephalopathy is also associated with problems in cognition and memory. To study the psychomotor functional disorders in rats with progressive chronic renal failure surgical nephrectomy was done by resection method. The animals were grouped into two control groups, Sham control (SC) and normal control (NC) and two uremic groups, moderate uremia (GM) and severe uremia (GS). Psychomotor analysis was done by passive avoidance and open field in these animals at 4, 8, 12, and 16 weeks. After the incubation period, the nephrectomised groups (GM and GS) showed significant changes in exploratory, locomotor and emotional behaviour when compared to the controls (NC and SC). Psychomotor changes involve poor cognition, reduced memory, reduced locomotor activity and decreased exploratory drive and emotional disturbance like increased fear during the initial stages. During the later stages a restless behaviour was noticed, associated with diminished fear.
    Cognitive Neurodynamics 04/2015; 9(2). DOI:10.1007/s11571-014-9315-z