1
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Ociepka M, Chinta SR, Basoń P, Chuderski A. No effects of the theta-frequency transcranial electrical stimulation for recall, attention control, and relation integration in working memory. Front Hum Neurosci 2024; 18:1354671. [PMID: 38439936 PMCID: PMC10910036 DOI: 10.3389/fnhum.2024.1354671] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/12/2023] [Accepted: 02/05/2024] [Indexed: 03/06/2024] Open
Abstract
Introduction Recent studies have suggested that transcranial alternating current stimulation (tACS), and especially the theta-frequency tACS, can improve human performance on working memory tasks. However, evidence to date is mixed. Moreover, the two WM tasks applied most frequently, namely the n-back and change-detection tasks, might not constitute canonical measures of WM capacity. Method In a relatively large sample of young healthy participants (N = 62), we administered a more canonical WM task that required stimuli recall, as well as we applied two WM tasks tapping into other key WM functions: attention control (the antisaccade task) and relational integration (the graph mapping task). The participants performed these three tasks three times: during the left frontal 5.5-Hz and the left parietal 5.5-Hz tACS session as well as during the sham session, with a random order of sessions. Attentional vigilance and subjective experience were monitored. Results For each task administered, we observed significant gains in accuracy neither for the frontal tACS session nor for the parietal tACS session, as compared to the sham session. By contrast, the scores on each task positively inter-correlated across the three sessions. Discussion The results suggest that canonical measures of WM capacity are strongly stable in time and hardly affected by theta-frequency tACS. Either the tACS effects observed in the n-back and change detection tasks do not generalize onto other WM tasks, or the tACS method has limited effectiveness with regard to WM, and might require further methodological advancements.
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Affiliation(s)
- Michał Ociepka
- Department of Cognitive Science, Institute of Philosophy, Jagiellonian University, Kraków, Poland
| | | | - Paweł Basoń
- Department of Cognitive Science, Institute of Philosophy, Jagiellonian University, Kraków, Poland
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2
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Aydın S. Investigation of global brain dynamics depending on emotion regulation strategies indicated by graph theoretical brain network measures at system level. Cogn Neurodyn 2023; 17:331-344. [PMID: 37007189 PMCID: PMC10050309 DOI: 10.1007/s11571-022-09843-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/09/2022] [Revised: 06/03/2022] [Accepted: 07/01/2022] [Indexed: 11/26/2022] Open
Abstract
In the present study, new findings reveal the close association between graph theoretic global brain connectivity measures and cognitive abilities the ability to manage and regulate negative emotions in healthy adults. Functional brain connectivity measures have been estimated from both eyes-opened and eyes-closed resting-state EEG recordings in four groups including individuals who use opposite Emotion Regulation Strategies (ERS) as follow: While 20 individuals who frequently use two opposing strategies, such as rumination and cognitive distraction, are included in 1st group, 20 individuals who don't use these cognitive strategies are included in 2nd group. In 3rd and 4th groups, there are matched individuals who use both Expressive Suppression and Cognitive Reappraisal strategies together frequently and never use them, respectively. EEG measurements and psychometric scores of individuals were both downloaded from a public dataset LEMON. Since it is not sensitive to volume conduction, Directed Transfer Function has been applied to 62-channel recordings to obtain cortical connectivity estimations across the whole cortex. Regarding well defined threshold, connectivity estimations have been transformed into binary numbers for implementation of Brain Connectivity Toolbox. The groups are compared to each other through both statistical logistic regression models and deep learning models driven by frequency band specific network measures referring segregation, integration and modularity of the brain. Overall results show that high classification accuracies of 96.05% (1st vs 2nd) and 89.66% (3rd vs 4th) are obtained in analyzing full-band ( 0.5 - 45 H z ) EEG. In conclusion, negative strategies may upset the balance between segregation and integration. In particular, graphical results show that frequent use of rumination induces the decrease in assortativity referring network resilience. The psychometric scores are found to be highly correlated with brain network measures of global efficiency, local efficiency, clustering coefficient, transitivity and assortativity in even resting-state.
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Affiliation(s)
- Serap Aydın
- Medical Faculty, Biophysics Department, Hacettepe University, Ankara, Turkey
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3
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Zhang W, Guo L, Liu D. Concurrent interactions between prefrontal cortex and hippocampus during a spatial working memory task. Brain Struct Funct 2022; 227:1735-1755. [DOI: 10.1007/s00429-022-02469-y] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/07/2021] [Accepted: 01/28/2022] [Indexed: 11/02/2022]
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4
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Liu Y, Xu X, Zhou Y, Xu J, Dong X, Li X, Yin S, Wen D. Coupling feature extraction method of resting state EEG Signals from amnestic mild cognitive impairment with type 2 diabetes mellitus based on weight permutation conditional mutual information. Cogn Neurodyn 2021; 15:987-997. [PMID: 34790266 PMCID: PMC8572246 DOI: 10.1007/s11571-021-09682-1] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2021] [Revised: 03/28/2021] [Accepted: 04/19/2021] [Indexed: 01/06/2023] Open
Abstract
This study aimed to find a good coupling feature extraction method to effectively analyze resting state EEG signals (rsEEG) of amnestic mild cognitive impairment(aMCI) with type 2 diabetes mellitus(T2DM) and normal control (NC) with T2DM. A method of EEG signal coupling feature extraction based on weight permutation conditional mutual information (WPCMI) was proposed in this research. With the WPCMI method, coupling feature strength of two time series in Alpha1, Alpha2, Beta1, Beta2 and Gamma bands for aMCI with T2DM and NC with T2DM could be extracted respectively. Then selected three frequency bands coupling feature matrix with the help of multi-spectral image transformation method to map it as spectral image characteristics. And finally classified these characteristics through the convolution neural network method(CNN). For aMCI with T2DM and NC with T2DM, the highest classification accuracy of 96%, 95%, 95% could be achieved respectively in the combination of three frequency bands (Alpha1, Alpha2, Gamma), (Beta1, Beta2 and Gamma) and (Alpha2, Beta1, Beta2). This WPCMI method highlighted the coupling dynamic characteristics of EEG signals, and its classification performance was better than all previous methods in aMCI with T2DM diagnosis field. WPCMI method could be used as an effective biomarker to distinguish EEG signals of aMCI with T2DM and NC with T2DM. The coupling feature extraction method used in this paper provided a new perspective for the EEG analysis of aMCI with T2DM.
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Affiliation(s)
- Yijun Liu
- School of Science, Yanshan University, Qinhuangdao, China
- School of Information Science and Engineering, Yanshan University, Qinhuangdao, China
| | - Xiaodong Xu
- School of Information Science and Engineering, Yanshan University, Qinhuangdao, China
| | - Yanhong Zhou
- School of Mathematics and Information Science and Technology, Hebei Normal University of Science and Technology, Qinhuangdao, China
| | - Jian Xu
- School of Information Science and Engineering, Yanshan University, Qinhuangdao, China
| | - Xianling Dong
- Department of Biomedical Engineering, Chengde Medical University, Chengde, China
| | - Xiaoli Li
- The National Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China
| | - Shimin Yin
- Department of Neurology, The Rocket Force Hospital of Chinese People’s Liberation Army, Beijing, China
| | - Dong Wen
- Institute of Artificial Intelligence, University of Science and Technology Beijing, Beijing, China
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5
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Rogala J, Dreszer J, Malinowska U, Waligóra M, Pluta A, Antonova I, Wróbel A. Stronger connectivity and higher extraversion protect against stress-related deterioration of cognitive functions. Sci Rep 2021; 11:17452. [PMID: 34465808 PMCID: PMC8408208 DOI: 10.1038/s41598-021-96718-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/26/2021] [Accepted: 08/13/2021] [Indexed: 11/09/2022] Open
Abstract
Here we attempted to define the relationship between: EEG activity, personality and coping during lockdown. We were in a unique situation since the COVID-19 outbreak interrupted our independent longitudinal study. We already collected a significant amount of data before lockdown. During lockdown, a subgroup of participants willingly continued their engagement in the study. These circumstances provided us with an opportunity to examine the relationship between personality/cognition and brain rhythms in individuals who continued their engagement during lockdown compared to control data collected well before pandemic. The testing consisted of a one-time assessment of personality dimensions and two sessions of EEG recording and deductive reasoning task. Participants were divided into groups based on the time they completed the second session: before or during the COVID-19 outbreak ‘Pre-pandemic Controls’ and ‘Pandemics’, respectively. The Pandemics were characterized by a higher extraversion and stronger connectivity, compared to Pre-pandemic Controls. Furthermore, the Pandemics improved their cognitive performance under long-term stress as compared to the Pre-Pandemic Controls matched for personality traits to the Pandemics. The Pandemics were also characterized by increased EEG connectivity during lockdown. We posit that stronger EEG connectivity and higher extraversion could act as a defense mechanism against stress-related deterioration of cognitive functions.
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Affiliation(s)
- Jacek Rogala
- Bioimaging Research Center, World Hearing Center, Institute of Physiology and Pathology of Hearing, Warsaw, Poland. .,The Center for Systemic Risk Analysis, Faculty of "Artes Liberales", University of Warsaw, Warsaw, Poland.
| | - Joanna Dreszer
- The Center for Systemic Risk Analysis, Faculty of "Artes Liberales", University of Warsaw, Warsaw, Poland.,Institute of Psychology, Faculty of Philosophy and Social Sciences, Nicolaus Copernicus University in Toruń, Toruń, Poland
| | - Urszula Malinowska
- Instytut Biologii Doświadczalnej Im. Marcelego Nenckiego, Warsaw, Poland
| | - Marek Waligóra
- Instytut Biologii Doświadczalnej Im. Marcelego Nenckiego, Warsaw, Poland
| | - Agnieszka Pluta
- Faculty of Psychology, The University of Warsaw, Warsaw, Poland
| | - Ingrida Antonova
- Instytut Biologii Doświadczalnej Im. Marcelego Nenckiego, Warsaw, Poland
| | - Andrzej Wróbel
- The Center for Systemic Risk Analysis, Faculty of "Artes Liberales", University of Warsaw, Warsaw, Poland.,Instytut Biologii Doświadczalnej Im. Marcelego Nenckiego, Warsaw, Poland.,Institute of Philosophy, Faculty of Epistemology, University of Warsaw, Warsaw, Poland
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6
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Kaminski M, Brzezicka A, Kaminski J, Blinowska KJ. Coupling Between Brain Structures During Visual and Auditory Working Memory Tasks. Int J Neural Syst 2019; 29:1850046. [DOI: 10.1142/s0129065718500466] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/07/2023]
Abstract
Transmission of EEG activity during a visual and auditory version of the working memory task based on the paradigm of linear syllogism was investigated. Our aim was to find possible similarities and differences in the synchronization patterns between brain structures during the same mental activity performed on different modality stimuli. The EEG activity transmission was evaluated by means of full frequency Directed Transfer Function (ffDTF) and short-time Directed Transfer Function (SDTF). SDTF provided information on dynamical propagation of EEG activity. The assortative mixing approach was applied to quantify coupling between regions of interest encompassing frontal, central and two posterior modules. The results showed similar schemes of coupling for both modalities with stronger coupling within the regions of interests than between them, which is concordant with the theories concerning efficient wiring and metabolic energy saving. The patterns of transmission showed main sources of activity in the anterior and posterior regions communicating intermittently in a broad frequency range. The differences between the patterns of transmission between the visual and auditory versions of working memory tasks were subtle and involved bigger propagation from the posterior electrodes towards the frontal ones during the visual task as well as from the temporal sites to the frontal ones during the auditory task.
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Affiliation(s)
- Maciej Kaminski
- Department of Biomedical Physics, University of Warsaw, Warsaw, Poland
| | - Aneta Brzezicka
- Department of Psychology, SWPS University of Social, Sciences and Humanities, Warsaw, Poland
| | - Jan Kaminski
- Department of Neurosurgery, Cedars-Sinai Medical Center, Los Angeles, USA
- Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, USA
| | - Katarzyna J. Blinowska
- Department of Biomedical Physics, University of Warsaw, Warsaw, Poland
- Nalecz Institute of Biocybernetics and Biomedical Engineering, Polish Academy of Sciences, Warsaw, Poland
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7
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Kasum O, Perović A, Jovanović A. Measures and Metrics of Biological Signals. Front Physiol 2018; 9:1707. [PMID: 30564137 PMCID: PMC6288820 DOI: 10.3389/fphys.2018.01707] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/14/2018] [Accepted: 11/13/2018] [Indexed: 11/13/2022] Open
Abstract
The concept of biological signals is becoming broader. Some of the challenges are: searching for inner and structural characteristics; selecting appropriate modeling to enhance perceived properties in the signals; extracting the representative components, identifying their mathematical correspondents; and performing necessary transformations in order to obtain form for subtle analysis, comparisons, derived recognition, and classification. There is that unique moment when we correspond the adequate mathematical structures to the observed phenomena. It allows application of various mathematical constructs, transformations and reconstructions. Finally, comparisons and classifications of the newly observed phenomena often lead to enrichment of the existing models with some additional structurality. For a specialized context the modeling takes place in a suitable set of mathematical representations of the same kind, a set of models M, where the mentioned transformations take place. They are used for determination of structures M, where mathematical finalization processes are preformed. Normalized representations of the initial content are measured in order to determine the key invariants (characterizing characteristics). Then, comparisons are preformed for specialized or targeted purposes. The process converges to the measures and distance measurements in the space M. Thus, we are dealing with measure and metric spaces, gaining opportunities that have not been initially available. Obviously, the different aspects in the research or diagnostics will demand specific spaces. In our practice we faced a large variety of problems in analysis of biological signals with very rich palette of measures and metrics. Even when a unique phenomena are observed for slightly different aspects of their characteristics, the corresponding measurements differ, or are refinements of the initial structures. Certain criteria need to be fulfilled. Namely, characterization and semantic stability. The small changes in the structures have to induce the small changes in measures and metrics. We offer a collection of the models that we have been involved in, together with the problems we met and their solutions, with representative visualizations.
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Affiliation(s)
- Obrad Kasum
- Group for Intelligent Systems (GIS), Faculty of Mathematics, University of Belgrade, Belgrade, Serbia
| | - Aleksandar Perović
- Group for Intelligent Systems (GIS), Faculty of Mathematics, University of Belgrade, Belgrade, Serbia.,Faculty of Transport and Traffic Engineering, University of Belgrade, Belgrade, Serbia
| | - Aleksandar Jovanović
- Group for Intelligent Systems (GIS), Faculty of Mathematics, University of Belgrade, Belgrade, Serbia
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8
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Wen D, Jia P, Hsu SH, Zhou Y, Lan X, Cui D, Li G, Yin S, Wang L. Estimating coupling strength between multivariate neural series with multivariate permutation conditional mutual information. Neural Netw 2018; 110:159-169. [PMID: 30562649 DOI: 10.1016/j.neunet.2018.11.006] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/21/2018] [Revised: 10/05/2018] [Accepted: 11/20/2018] [Indexed: 02/03/2023]
Abstract
Recently, coupling between groups of neurons or different brain regions has been widely studied to provide insights into underlying mechanisms of brain functions. To comprehensively understand the effect of such coupling, it is necessary to accurately extract the coupling strength information among multivariate neural signals from the whole brain. This study proposed a new method named multivariate permutation conditional mutual information (MPCMI) to quantitatively estimate the coupling strength of multivariate neural signals (MNS). The performance of the MPCMI method was validated on the simulated MNS generated by multi-channel neural mass model (MNMM). The coupling strength feature of simulated MNS extracted by MPCMI showed better performance compared with standard methods, such as permutation conditional mutual information (PCMI), multivariate Granger causality (MVGC), and Granger causality analysis (GCA). Furthermore, the MPCMI was applied to estimate the coupling strengths of two-channel resting-state electroencephalographic (rsEEG) signals from different brain regions of 19 patients with amnestic mild cognitive impairment (aMCI) with type 2 diabetes mellitus (T2DM) and 20 normal control (NC) with T2DM in Alpha1 and Alpha2 frequency bands. Empirical results showed that the MPCMI could effectively extract the coupling strength features that were significantly different between the aMCI and the NC. Hence, the proposed MPCMI method could be an effective estimate of coupling strengths of MNS, and might be a viable biomarker for clinical applications.
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Affiliation(s)
- Dong Wen
- School of Information Science and Engineering, Yanshan University, Qinhuangdao 066004, China; The Key Laboratory for Computer Virtual Technology and System Integration of Hebei Province, Yanshan University, Qinhuangdao 066004, China; The Key Laboratory for Software Engineering of Hebei Province, Yanshan University, Qinhuangdao 066004, China.
| | - Peilei Jia
- School of Information Science and Engineering, Yanshan University, Qinhuangdao 066004, China; The Key Laboratory for Computer Virtual Technology and System Integration of Hebei Province, Yanshan University, Qinhuangdao 066004, China; The Key Laboratory for Software Engineering of Hebei Province, Yanshan University, Qinhuangdao 066004, China
| | - Sheng-Hsiou Hsu
- Swartz Center for Computational Neuroscience, University of California San Diego, La Jolla, CA, 92093, United States
| | - Yanhong Zhou
- School of Information Science and Engineering, Yanshan University, Qinhuangdao 066004, China; School of Mathematics and Information Science and Technology, Hebei Normal University of Science and Technology, Qinhuangdao 066004, China.
| | - Xifa Lan
- Department of Neurology, First Hospital of Qinhuangdao, Qinhuangdao 066000, China
| | - Dong Cui
- School of Information Science and Engineering, Yanshan University, Qinhuangdao 066004, China; The Key Laboratory for Computer Virtual Technology and System Integration of Hebei Province, Yanshan University, Qinhuangdao 066004, China
| | - Guolin Li
- School of Mathematics and Information Science and Technology, Hebei Normal University of Science and Technology, Qinhuangdao 066004, China
| | - Shimin Yin
- Department of Neurology, The Rocket Force General Hospital of Chinese People's Liberation Army, Beijing 100088, China
| | - Lei Wang
- Department of Neurology, The Rocket Force General Hospital of Chinese People's Liberation Army, Beijing 100088, China
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9
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Lioi G, Bell SL, Smith DC, Simpson DM. Measuring depth of anaesthesia using changes in directional connectivity: a comparison with auditory middle latency response and estimated bispectral index during propofol anaesthesia. Anaesthesia 2018; 74:321-332. [PMID: 30556186 DOI: 10.1111/anae.14535] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 11/14/2018] [Indexed: 12/20/2022]
Abstract
General anaesthesia is associated with changes in connectivity between different regions of the brain, the assessment of which has the potential to provide a novel marker of anaesthetic effect. We propose an index that quantifies the strength and direction of information flow in electroencephalographic signals collected across the scalp, assess its performance in discriminating 'wakefulness' from 'anaesthesia', and compare it with estimated bispectral index and the auditory middle latency response. We used a step-wise slow induction of anaesthesia in 10 patients to assess graded changes in electroencephalographic directional connectivity at propofol effect-site concentrations of 2 μg.ml-1 , 3 μg.ml-1 and 4 μg.ml-1 . For each stable effect-site concentration, connectivity was estimated from multichannel electroencephalograms using directed coherence, together with middle latency response and estimated bispectral index. We used a linear support vector machine classifier to compare the performance of the different electroencephalographic features in discriminating wakefulness from anaesthesia. We found a significant reduction in the strength of long-range connectivity (interelectrode distance > 10 cm) (p < 0.008), and a reversal of information flow from markedly postero-frontal to fronto-posterior (p < 0.006) between wakefulness and a propofol effect-site concentration of 2 μg.ml-1 . This then remained relatively constant as effect-site concentration increased, consistent with a step change in directed coherence with anaesthesia. This contrasted with the gradual change with increasing anaesthetic dose observed for estimated bispectral index and middle latency response. Directed coherence performed best in discriminating wakefulness from anaesthesia with an accuracy of 95%, indicating the potential of this new method (on its own or combined with others) for monitoring adequacy of anaesthesia.
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Affiliation(s)
- G Lioi
- Institute of Sound and Vibration Research, University of Southampton, Southampton, UK.,Post-Doc Univ Rennes, Inria, CNRS, IRISA, VisAGeS Project Team, F-35000, Rennes, France
| | - S L Bell
- Institute of Sound and Vibration Research, University of Southampton, Southampton, UK
| | - D C Smith
- Southampton General Hospital, University of Southampton, Southampton, UK
| | - D M Simpson
- Institute of Sound and Vibration Research, University of Southampton, Southampton, UK
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10
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Wertheim J, Ragni M. The Neural Correlates of Relational Reasoning: A Meta-analysis of 47 Functional Magnetic Resonance Studies. J Cogn Neurosci 2018; 30:1734-1748. [DOI: 10.1162/jocn_a_01311] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/04/2022]
Abstract
It is a core cognitive ability of humans to represent and reason about relational information, such as “the train station is north of the hotel” or “Charles is richer than Jim.” However, the neural processes underlying the ability to draw conclusions about relations are still not sufficiently understood. Central open questions are as follows: (1) What are the neural correlates of relational reasoning? (2) Where can deductive and inductive reasoning be localized? (3) What is the impact of different informational types on cerebral activity? For that, we conducted a meta-analysis of 47 neuroimaging studies. We found activation of the frontoparietal network during both deductive and inductive reasoning, with additional activation in an extended network during inductive reasoning in the basal ganglia and the inferior parietal cortex. Analyses revealed a double dissociation concerning the lateral and medial Brodmann's area 6 during deductive and inductive reasoning, indicating differences in terms of processing verbal information in deductive and spatial information in inductive tasks. During semantic and symbolic tasks, the frontoparietal network was found active, whereas geometric tasks only elicited prefrontal activation, which can be explained by the reduced demand for the construction of a mental representation in geometric tasks. Our study provides new insights into the cognitive mechanisms underlying relational reasoning and clarifies previous controversies concerning involved brain areas.
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11
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Lioi G, Bell SL, Smith DC, Simpson DM. Directional connectivity in the EEG is able to discriminate wakefulness from NREM sleep. Physiol Meas 2017; 38:1802-1820. [PMID: 28737503 DOI: 10.1088/1361-6579/aa81b5] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Abstract
A reliable measure of consciousness is of great interest for various clinical applications including sleep studies and the assessment of depth of anaesthesia. A number of measures of consciousness based on the EEG have been proposed in the literature and tested in studies of dreamless sleep, general anaesthesia and disorders of consciousness. However, reliability has remained a persistent challenge. Despite considerable theoretical and experimental effort, the neural mechanisms underlying consciousness remain unclear, but connectivity between brain regions is thought to be disrupted, impairing information flow. OBJECTIVE The objective of the current work was to assess directional connectivity between brain regions using directed coherence and propose and assess an index that robustly reflects changes associated with non-REM sleep. APPROACH We tested the performance on polysomnographic recordings from ten healthy subjects and compared directed coherence (and derived features) with more established measures calculated from EEG spectra. We compared the performance of the different indexes to discriminate the level of consciousness at group and individual level. MAIN RESULTS At a group level all EEG measures could significantly discriminate NREM sleep from waking, but there was considerable individual variation. Across all individuals, normalized power, the strength of long-range connections and the direction of functional links strongly correlate with NREM sleep stages over the experimental timeline. At an individual level, of the EEG measures considered, the direction of functional links constitutes the most reliable index of the level of consciousness, highly correlating with the individual experimental time-line of sleep in all subjects. SIGNIFICANCE Directed coherence provides a promising new means of assessing level of consciousness, firmly based on current physiological understanding of consciousness.
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Affiliation(s)
- G Lioi
- Institute for Sound and Vibration Research, University of Southampton, Southampton, United Kingdom
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12
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Kaminski M, Blinowska KJ. The Influence of Volume Conduction on DTF Estimate and the Problem of Its Mitigation. Front Comput Neurosci 2017; 11:36. [PMID: 28553220 PMCID: PMC5427064 DOI: 10.3389/fncom.2017.00036] [Citation(s) in RCA: 25] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/03/2017] [Accepted: 04/26/2017] [Indexed: 11/13/2022] Open
Affiliation(s)
- Maciej Kaminski
- Department of Biomedical Physics, Faculty of Physics, University of WarsawWarsaw, Poland
| | - Katarzyna J Blinowska
- Department of Biomedical Physics, Faculty of Physics, University of WarsawWarsaw, Poland.,Institute of Biocybernetics and Biomedical Engineering of Polish Academy of SciencesWarsaw, Poland
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13
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Žarić G, Correia JM, Fraga González G, Tijms J, van der Molen MW, Blomert L, Bonte M. Altered patterns of directed connectivity within the reading network of dyslexic children and their relation to reading dysfluency. Dev Cogn Neurosci 2017; 23:1-13. [PMID: 27919003 PMCID: PMC6987659 DOI: 10.1016/j.dcn.2016.11.003] [Citation(s) in RCA: 19] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/13/2016] [Revised: 09/26/2016] [Accepted: 11/15/2016] [Indexed: 11/25/2022] Open
Abstract
Reading is a complex cognitive skill subserved by a distributed network of visual and language-related regions. Disruptions of connectivity within this network have been associated with developmental dyslexia but their relation to individual differences in the severity of reading problems remains unclear. Here we investigate whether dysfunctional connectivity scales with the level of reading dysfluency by examining EEG recordings during visual word and false font processing in 9-year-old typically reading children (TR) and two groups of dyslexic children: severely dysfluent (SDD) and moderately dysfluent (MDD) dyslexics. Results indicated weaker occipital to inferior-temporal connectivity for words in both dyslexic groups relative to TRs. Furthermore, SDDs exhibited stronger connectivity from left central to right inferior-temporal and occipital sites for words relative to TRs, and for false fonts relative to both MDDs and TRs. Importantly, reading fluency was positively related with forward and negatively with backward connectivity. Our results suggest disrupted visual processing of words in both dyslexic groups, together with a compensatory recruitment of right posterior brain regions especially in the SDDs during word and false font processing. Functional connectivity in the brain's reading network may thus depend on the level of reading dysfluency beyond group differences between dyslexic and typical readers.
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Affiliation(s)
- Gojko Žarić
- Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht University, Oxfordlaan 55, 6229EV Maastricht, Netherlands; Maastricht Brain Imaging Center (M-BIC), Oxfordlaan 55, 6229EV Maastricht, Netherlands.
| | - João M Correia
- Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht University, Oxfordlaan 55, 6229EV Maastricht, Netherlands; Maastricht Brain Imaging Center (M-BIC), Oxfordlaan 55, 6229EV Maastricht, Netherlands.
| | - Gorka Fraga González
- Department of Developmental Psychology, University of Amsterdam, Nieuwe Achtergracht 129, 1018 WS Amsterdam, Netherlands; Rudolf Berlin Center, Valckenierstraat 65-67, 1018 XE Amsterdam, Netherlands.
| | - Jurgen Tijms
- Department of Developmental Psychology, University of Amsterdam, Nieuwe Achtergracht 129, 1018 WS Amsterdam, Netherlands; IWAL Institute, Prins Hendrikkade 84, 1012 AE Amsterdam, Netherlands.
| | - Maurtis W van der Molen
- Department of Developmental Psychology, University of Amsterdam, Nieuwe Achtergracht 129, 1018 WS Amsterdam, Netherlands; Amsterdam Brain and Cognition, University of Amsterdam, Nieuwe Achtergracht 129B 1018WS Amsterdam, The Netherlands.
| | - Leo Blomert
- Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht University, Oxfordlaan 55, 6229EV Maastricht, Netherlands; Maastricht Brain Imaging Center (M-BIC), Oxfordlaan 55, 6229EV Maastricht, Netherlands
| | - Milene Bonte
- Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht University, Oxfordlaan 55, 6229EV Maastricht, Netherlands; Maastricht Brain Imaging Center (M-BIC), Oxfordlaan 55, 6229EV Maastricht, Netherlands.
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14
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Kaminski M, Brzezicka A, Kaminski J, Blinowska KJ. Measures of Coupling between Neural Populations Based on Granger Causality Principle. Front Comput Neurosci 2016; 10:114. [PMID: 27833546 PMCID: PMC5080292 DOI: 10.3389/fncom.2016.00114] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/25/2016] [Accepted: 10/12/2016] [Indexed: 12/18/2022] Open
Abstract
This paper shortly reviews the measures used to estimate neural synchronization in experimental settings. Our focus is on multivariate measures of dependence based on the Granger causality (G-causality) principle, their applications and performance in respect of robustness to noise, volume conduction, common driving, and presence of a “weak node.” Application of G-causality measures to EEG, intracranial signals and fMRI time series is addressed. G-causality based measures defined in the frequency domain allow the synchronization between neural populations and the directed propagation of their electrical activity to be determined. The time-varying G-causality based measure Short-time Directed Transfer Function (SDTF) supplies information on the dynamics of synchronization and the organization of neural networks. Inspection of effective connectivity patterns indicates a modular structure of neural networks, with a stronger coupling within modules than between them. The hypothetical plausible mechanism of information processing, suggested by the identified synchronization patterns, is communication between tightly coupled modules intermitted by sparser interactions providing synchronization of distant structures.
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Affiliation(s)
- Maciej Kaminski
- Department of Biomedical Physics, Faculty of Physics, University of Warsaw Warsaw, Poland
| | - Aneta Brzezicka
- Department of Psychology, University of Social Sciences and Humanities Warsaw, Poland
| | - Jan Kaminski
- Centre for Modern Interdisciplinary Technologies, Nicolaus Copernicus University Torun, Poland
| | - Katarzyna J Blinowska
- Department of Biomedical Physics, Faculty of Physics, University of WarsawWarsaw, Poland; Institute of Biocybernetics and Biomedical Engineering of Polish Academy of SciencesWarsaw, Poland
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15
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Babiloni C, Lizio R, Marzano N, Capotosto P, Soricelli A, Triggiani AI, Cordone S, Gesualdo L, Del Percio C. Brain neural synchronization and functional coupling in Alzheimer's disease as revealed by resting state EEG rhythms. Int J Psychophysiol 2016; 103:88-102. [PMID: 25660305 DOI: 10.1016/j.ijpsycho.2015.02.008] [Citation(s) in RCA: 207] [Impact Index Per Article: 25.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
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16
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Brzezicka A, Kamiński J, Kamińska OK, Wołyńczyk-Gmaj D, Sedek G. Frontal EEG alpha band asymmetry as a predictor of reasoning deficiency in depressed people. Cogn Emot 2016; 31:868-878. [PMID: 27089304 DOI: 10.1080/02699931.2016.1170669] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/01/2023]
Abstract
Cognitive deficits in depression are mostly apparent in executive functions, especially when integration of information and reasoning is required. In parallel, there are also numerous studies pointing to the frontal alpha band asymmetry as a psychophysiological marker of depression. In this study, we explored the role of frontal alpha asymmetry as a potential factor explaining the cognitive problems accompanying depression. Twenty-six depressed and 26 control participants completed a reasoning task and underwent 5 minutes of electroencephalography recording. In line with the previous studies, depressed people showed difficulties with reasoning but we did not observe the relationship between frontal asymmetry in the alpha band and depression. However, we found that in the depressed group the frontal alpha asymmetry index was characterised by larger variance than in the control group, and it was also a strong predictor of cognitive functioning exclusively in the depressed group. Our results point to the disruption of a psychophysiological balance, reflected in changed frontal alpha asymmetry (into more left-sided frontal asymmetry in the alpha band, reflecting more right-sided cortical activity) as a possible brain correlate of cognitive disturbances present in depressive disorders.
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Affiliation(s)
- Aneta Brzezicka
- a Department of Psychology , SWPS University of Social Sciences and Humanities , Warsaw , Poland.,b Centre for Modern Interdisciplinary Technologies , Nicolaus Copernicus University , Torun , Poland
| | - Jan Kamiński
- b Centre for Modern Interdisciplinary Technologies , Nicolaus Copernicus University , Torun , Poland.,c Department of Neurosurgery , Cedars-Sinai Medical Center , Los Angeles , CA , USA.,d Division of Biology and Biological Engineering , California Institute of Technology , Los Angeles , CA , USA
| | - Olga Katarzyna Kamińska
- a Department of Psychology , SWPS University of Social Sciences and Humanities , Warsaw , Poland
| | | | - Grzegorz Sedek
- a Department of Psychology , SWPS University of Social Sciences and Humanities , Warsaw , Poland
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17
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Graph theoretical analysis of EEG effective connectivity in vascular dementia patients during a visual oddball task. Clin Neurophysiol 2016; 127:324-334. [DOI: 10.1016/j.clinph.2015.04.063] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/07/2014] [Revised: 03/30/2015] [Accepted: 04/20/2015] [Indexed: 11/22/2022]
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18
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Ligeza TS, Wyczesany M, Tymorek AD, Kamiński M. Interactions Between the Prefrontal Cortex and Attentional Systems During Volitional Affective Regulation: An Effective Connectivity Reappraisal Study. Brain Topogr 2015; 29:253-61. [PMID: 26440605 PMCID: PMC4754317 DOI: 10.1007/s10548-015-0454-2] [Citation(s) in RCA: 25] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/18/2015] [Accepted: 09/26/2015] [Indexed: 11/17/2022]
Abstract
Reappraisal is an emotion regulation strategy used to change reactions to emotion-related stimuli by reinterpreting their meaning. During down-regulation of negative emotions, wide areas of the prefrontal cortex (PFC) inhibit emotion-related brain areas such as the amygdala. Little is known, however, about how this control activity influences the earliest stages of affective responses by modulating perceptual and attentional areas. The aim of this study is to identify the connectivity patterns between the PFC and the core regions of two well-known attentional networks: the dorsal attentional network (which controls attention volitionally) and the ventral attentional network (which controls attention spontaneously) during reappraisal. We used a novel method to study emotional control processes: the directed transfer function, an autoregressive effective connectivity method based on Granger causality. It was applied to EEG recordings to quantify the direction and intensity of information flow during passively watching (control condition) or reappraising (experimental condition) negative film clips. Reappraisal was mostly associated with increased top-down influences from the right dorsolateral PFC over attentional and perceptual areas, reaching areas including dorsal attentional regions. The left dorsolateral PFC was associated with the activation of the ventral attentional network. Passively watching clips (control condition) resulted in increased flow from attentional areas to the left dorsolateral PFC, what is interpreted as a monitoring process. Thus, reappraisal seems to be related to both volitional and automatic control of attention, triggered by the right and left dorsolateral PFC respectively.
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Affiliation(s)
- Tomasz S Ligeza
- Psychophysiology Laboratory, Institute of Psychology, Jagiellonian University, Ingardena 6, 30060, Kraków, Poland.
| | - Miroslaw Wyczesany
- Psychophysiology Laboratory, Institute of Psychology, Jagiellonian University, Ingardena 6, 30060, Kraków, Poland.
| | - Agnieszka D Tymorek
- Institute of Zoology, Jagiellonian University, Gronostajowa 9, 30387, Kraków, Poland.
| | - Maciej Kamiński
- Department of Biomedical Physics, Faculty of Physics, University of Warsaw, Pasteura 5, 02093, Warsaw, Poland.
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19
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Tivarus ME, Pester B, Schmidt C, Lehmann T, Zhu T, Zhong J, Leistritz L, Schifitto G. Are Structural Changes Induced by Lithium in the HIV Brain Accompanied by Changes in Functional Connectivity? PLoS One 2015; 10:e0139118. [PMID: 26436895 PMCID: PMC4593570 DOI: 10.1371/journal.pone.0139118] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/13/2014] [Accepted: 09/09/2015] [Indexed: 01/12/2023] Open
Abstract
Lithium therapy has been shown to affect imaging measures of brain function and microstructure in human immunodeficiency virus (HIV)-infected subjects with cognitive impairment. The aim of this proof-of-concept study was to explore whether changes in brain microstructure also entail changes in functional connectivity. Functional MRI data of seven cognitively impaired HIV infected individuals enrolled in an open-label lithium study were included in the connectivity analysis. Seven regions of interest (ROI) were defined based on previously observed lithium induced microstructural changes measured by Diffusion Tensor Imaging. Generalized partial directed coherence (gPDC), based on time-variant multivariate autoregressive models, was used to quantify the degree of connectivity between the selected ROIs. Statistical analyses using a linear mixed model showed significant differences in the average node strength between pre and post lithium therapy conditions. Specifically, we found that lithium treatment in this population induced changes suggestive of increased strength in functional connectivity. Therefore, by exploiting the information about the strength of functional interactions provided by gPDC we can quantify the connectivity changes observed in relation to a given intervention. Furthermore, in conditions where the intervention is associated with clinical changes, we suggest that this methodology could enable an interpretation of such changes in the context of disease or treatment induced modulations in functional networks.
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Affiliation(s)
- Madalina E. Tivarus
- Department of Imaging Sciences, University of Rochester Medical Center, Rochester, New York, United States of America
| | - Britta Pester
- Institute of Medical Statistics, Computer Sciences and Documentation, Jena University Hospital, Friedrich Schiller University, Jena, Germany
| | - Christoph Schmidt
- Institute of Medical Statistics, Computer Sciences and Documentation, Jena University Hospital, Friedrich Schiller University, Jena, Germany
| | - Thomas Lehmann
- Institute of Medical Statistics, Computer Sciences and Documentation, Jena University Hospital, Friedrich Schiller University, Jena, Germany
| | - Tong Zhu
- Department of Radiation Oncology, University of Michigan, Ann Arbor, Michigan, United States of America
| | - Jianhui Zhong
- Department of Imaging Sciences, University of Rochester Medical Center, Rochester, New York, United States of America
| | - Lutz Leistritz
- Institute of Medical Statistics, Computer Sciences and Documentation, Jena University Hospital, Friedrich Schiller University, Jena, Germany
- * E-mail:
| | - Giovanni Schifitto
- Department of Imaging Sciences, University of Rochester Medical Center, Rochester, New York, United States of America
- Department of Neurology, University of Rochester Medical Center, Rochester New York, United States of America
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Wang C, Xu J, Lou W, Zhao S. Dynamic information flow analysis in Vascular Dementia patients during the performance of a visual oddball task. Neurosci Lett 2014; 580:108-13. [DOI: 10.1016/j.neulet.2014.07.056] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/04/2014] [Revised: 07/07/2014] [Accepted: 07/29/2014] [Indexed: 11/28/2022]
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21
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Xu J, Lou W, Zhao S, Wang C. Altered Directed Connectivity in Patients with Early Vascular Dementia During a Visual Oddball Task. Brain Topogr 2014; 28:330-9. [DOI: 10.1007/s10548-014-0385-3] [Citation(s) in RCA: 9] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/19/2013] [Accepted: 07/16/2014] [Indexed: 11/29/2022]
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22
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Kaminski M, Blinowska KJ. Directed Transfer Function is not influenced by volume conduction-inexpedient pre-processing should be avoided. Front Comput Neurosci 2014; 8:61. [PMID: 24959136 PMCID: PMC4050361 DOI: 10.3389/fncom.2014.00061] [Citation(s) in RCA: 65] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/03/2013] [Accepted: 05/20/2014] [Indexed: 12/02/2022] Open
Affiliation(s)
- Maciej Kaminski
- Department of Biomedical Physics, Faculty of Physics, University of Warsaw Warsaw, Poland
| | - Katarzyna J Blinowska
- Department of Biomedical Physics, Faculty of Physics, University of Warsaw Warsaw, Poland
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23
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Xu X, Tian Y, Li S, Li Y, Wang G, Tian X. Inhibition of propofol anesthesia on functional connectivity between LFPs in PFC during rat working memory task. PLoS One 2013; 8:e83653. [PMID: 24386243 PMCID: PMC3873953 DOI: 10.1371/journal.pone.0083653] [Citation(s) in RCA: 10] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/08/2013] [Accepted: 11/06/2013] [Indexed: 11/20/2022] Open
Abstract
Working memory (WM) refers to the temporary storage and manipulation of information necessary for performance of complex cognitive tasks. There is a growing interest in whether and how propofol anesthesia inhibits WM function. The aim of this study is to investigate the possible inhibition mechanism of propofol anesthesia based on the functional connections of multi-local field potentials (LFPs) and behavior during WM tasks. Adult SD rats were randomly divided into 3 groups: pro group (0.5 mg·kg−1·min−1,2 h), PRO group (0.9 mg·kg−1·min−1, 2 h) and control group. The experimental data were 16-channel LFPs obtained at prefrontal cortex with implanted microelectrode array in SD rats during WM tasks in Y-maze at 24, 48, 72, 96, 120 hours (day 1-day 5) after propofol anesthesia, and the behavior results of WM were recoded at the same time. Directed transfer function (DTF) method was applied to analyze the connections among LFPs directly. Furthermore, the causal networks were identified by DTF. The clustering coefficient (C), network density (D) and global efficiency (Eglobal) were selected to describe the functional connectivity quantitatively. The results show that: comparing with the control group, the LFPs functional connectivity in pro group were no significantly difference (p>0.05); the connectivity in PRO group were significantly decreased (p<0.05 at 24 hours, p<0.05 at 48 hours), while no significant difference at 72, 96 and 120 hours for rats (p>0.05), which were consistent with the behavior results. These findings could lead to improved understanding the mechanism of inhibition of anesthesia on WM functions from the view of connections among LFPs.
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Affiliation(s)
- Xinyu Xu
- School of Biomedical Engineering, Tianjin Medical University, Tianjin, China
| | - Yu Tian
- School of Biomedical Engineering, Tianjin Medical University, Tianjin, China
| | - Shuangyan Li
- School of Biomedical Engineering, Tianjin Medical University, Tianjin, China
| | - Yize Li
- Department of Anesthesiology, Tianjin Medical University General Hospital, Tianjin, China
| | - Guolin Wang
- Department of Anesthesiology, Tianjin Medical University General Hospital, Tianjin, China
| | - Xin Tian
- School of Biomedical Engineering, Tianjin Medical University, Tianjin, China
- * E-mail:
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24
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Blinowska KJ, Kaminski M. Functional brain networks: random, "small world" or deterministic? PLoS One 2013; 8:e78763. [PMID: 24205313 PMCID: PMC3813572 DOI: 10.1371/journal.pone.0078763] [Citation(s) in RCA: 25] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/08/2013] [Accepted: 09/15/2013] [Indexed: 12/05/2022] Open
Abstract
Lately the problem of connectivity in brain networks is being approached frequently by graph theoretical analysis. In several publications based on bivariate estimators of relations between EEG channels authors reported random or “small world” structure of networks. The results of these works often have no relation to other evidence based on imaging, inverse solutions methods, physiological and anatomical data. Herein we try to find reasons for this discrepancy. We point out that EEG signals are very much interdependent, thus bivariate measures applied to them may produce many spurious connections. In fact, they may outnumber the true connections. Giving all connections equal weights, as it is usual in the framework of graph theoretical analysis, further enhances these spurious links. In effect, close to random and disorganized patterns of connections emerge. On the other hand, multivariate connectivity estimators, which are free of the artificial links, show specific, well determined patterns, which are in a very good agreement with other evidence. The modular structure of brain networks may be identified by multivariate estimators based on Granger causality and formalism of assortative mixing. In this way, the strength of coupling may be evaluated quantitatively. During working memory task, by means of multivariate Directed Transfer Function, it was demonstrated that the modules characterized by strong internal bonds exchange the information by weaker connections.
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Affiliation(s)
- Katarzyna J. Blinowska
- Department of Biomedical Physics, Faculty of Physics, Warsaw University, Warsaw, Poland
- * E-mail:
| | - Maciej Kaminski
- Department of Biomedical Physics, Faculty of Physics, Warsaw University, Warsaw, Poland
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25
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Blinowska KJ, Kamiński M, Brzezicka A, Kamiński J. Application of directed transfer function and network formalism for the assessment of functional connectivity in working memory task. PHILOSOPHICAL TRANSACTIONS. SERIES A, MATHEMATICAL, PHYSICAL, AND ENGINEERING SCIENCES 2013; 371:20110614. [PMID: 23858482 DOI: 10.1098/rsta.2011.0614] [Citation(s) in RCA: 20] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/06/2023]
Abstract
The dynamic pattern of functional connectivity during a working memory task was investigated by means of the short-time directed transfer function. A clear-cut picture of transmissions was observed with the main centres of propagation located in the frontal and parietal regions, in agreement with imaging studies and neurophysiological hypotheses concerning the mechanisms of working memory. The study of the time evolution revealed that most of the time short-range interactions prevailed, whereas the communication between the main centres of activity occurred more sparsely and changed dynamically in time. The patterns of connectivity were quantified by means of a network formalism based on assortative mixing--an approach novel in the field of brain networks study. By means of application of the above method, we have demonstrated the existence of a modular structure of brain networks. The strength of interaction inside the modules was higher than between modules. The obtained results are compatible with theories concerning metabolic energy saving and efficient wiring in the brain, which showed that preferred organization includes modular structure with dense connectivity inside the modules and more sparse connections between the modules. The presented detailed temporal and spatial patterns of propagation are in line with the neurophysiological hypotheses concerning the role of gamma and theta activity in information processing during a working memory task.
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26
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Abstract
Theta and gamma frequency oscillations occur in the same brain regions and interact with each other, a process called cross-frequency coupling. Here, we review evidence for the following hypothesis: that the dual oscillations form a code for representing multiple items in an ordered way. This form of coding has been most clearly demonstrated in the hippocampus, where different spatial information is represented in different gamma subcycles of a theta cycle. Other experiments have tested the functional importance of oscillations and their coupling. These involve correlation of oscillatory properties with memory states, correlation with memory performance, and effects of disrupting oscillations on memory. Recent work suggests that this coding scheme coordinates communication between brain regions and is involved in sensory as well as memory processes.
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Affiliation(s)
- John E. Lisman
- Brandeis University, Biology Department & Volen Center for Complex Systems, 415 South Street-MS 008, Waltham, MA 02454-9110, 781-736-3145
| | - Ole Jensen
- Radboud University Nijmegen, Donders Institute for Brain, Cognition and Behaviour, Kapittelweg 29, 6525 EN Nijmegen, The Netherlands
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27
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Vecchio F, Babiloni C, Lizio R, Fallani FDV, Blinowska K, Verrienti G, Frisoni G, Rossini PM. Resting state cortical EEG rhythms in Alzheimer's disease: toward EEG markers for clinical applications: a review. SUPPLEMENTS TO CLINICAL NEUROPHYSIOLOGY 2013; 62:223-36. [PMID: 24053043 DOI: 10.1016/b978-0-7020-5307-8.00015-6] [Citation(s) in RCA: 100] [Impact Index Per Article: 9.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/08/2023]
Abstract
The human brain contains an intricate network of about 100 billion neurons. Aging of the brain is characterized by a combination of synaptic pruning, loss of cortico-cortical connections, and neuronal apoptosis that provoke an age-dependent decline of cognitive functions. Neural/synaptic redundancy and plastic remodeling of brain networking, also secondary to mental and physical training, promote maintenance of brain activity and cognitive status in healthy elderly subjects for everyday life. However, age is the main risk factor for neurodegenerative disorders such as Alzheimer's disease (AD) that impact on cognition. Growing evidence supports the idea that AD targets specific and functionally connected neuronal networks and that oscillatory electromagnetic brain activity might be a hallmark of the disease. In this line, digital electroencephalography (EEG) allows noninvasive analysis of cortical neuronal synchronization, as revealed by resting state brain rhythms. This review provides an overview of the studies on resting state eyes-closed EEG rhythms recorded in amnesic mild cognitive impairment (MCI) and AD subjects. Several studies support the idea that spectral markers of these EEG rhythms, such as power density, spectral coherence, and other quantitative features, differ among normal elderly, MCI, and AD subjects, at least at group level. Regarding the classification of these subjects at individual level, the most previous studies showed a moderate accuracy (70-80%) in the classification of EEG markers relative to normal and AD subjects. In conclusion, resting state EEG makers are promising for large-scale, low-cost, fully noninvasive screening of elderly subjects at risk of AD.
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Affiliation(s)
- Fabrizio Vecchio
- A.Fa.R., Dipartimento di Neuroscienze, Ospedale Fatebenefratelli, Isola Tiberina, 00186 Rome, Italy
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28
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Blinowska KJ. Review of the methods of determination of directed connectivity from multichannel data. Med Biol Eng Comput 2011; 49:521-9. [PMID: 21298355 PMCID: PMC3097342 DOI: 10.1007/s11517-011-0739-x] [Citation(s) in RCA: 154] [Impact Index Per Article: 11.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/18/2010] [Accepted: 01/13/2011] [Indexed: 11/24/2022]
Abstract
The methods applied for estimation of functional connectivity from multichannel data are described with special emphasis on the estimators of directedness such as directed transfer function (DTF) and partial directed coherence. These estimators based on multivariate autoregressive model are free of pitfalls connected with application of bivariate measures. The examples of applications illustrating the performance of the methods are given. Time-varying estimators of directedness: short-time DTF and adaptive methods are presented.
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