A new method of the description of the information flow in the brain structures
Abstract
The paper describes the method of determining direction and frequency content of the brain activity flow. The method was formulated in the framework of the AR model. The transfer function matrix was found for multichannel EEG process. Elements of this matrix, properly normalized, appeared to be good estimators of the propagation direction and spectral properties of the investigated signals. Simulation experiments have shown that the estimator proposed by us unequivocally reveals the direction of the signal flow and is able to distinguish between direct and indirect transfer of information. The method was applied to the signals recorded in the brain structures of the experimental animals and also to the human normal and epileptic EEG. The sensitivity of the method and its usefulness in the neurological and clinical applications was demonstrated.
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Algorithms have been developed for estimating functional connectivity from electrophysiological source signals derived from EEG or MEG, including directed transfer function, adaptive directed transfer function, direct directed transfer function, and partial directed coherence.
“Algorithms have been developed for estimating functional connectivity from electrophysiological source signals derived from EEG (or MEG), including directed transfer function (DTF) algorithm (98), the adaptive DTF (ADTF) (99–101), direct DTF (dDTF) (102), and partial directed coherence (PDC) (103).”
From Electrophysiological source imaging: A noninvasive window to brain dynamics (2018) · cites this paper as [98]
Cites
EEG alpha map series: brain micro-states by space-oriented adaptive segmentation
Lehmann, D., Ozaki, H., & Pal, I. (1987) · Electroencephalography and Clinical Neurophysiology · doi:10.1016/0013-4694(87)90025-3 · Cited by 917 · see citing works
Cortico-cortical associations and EEG coherence: A two-compartmental model
Thatcher, R. W., Krause, P. J., & Hrybyk, M. (1986) · Electroencephalography and Clinical Neurophysiology · doi:10.1016/0013-4694(86)90107-0 · Cited by 630 · see citing works
Franaszczuk, P. J., Blinowska, K. J., & Kowalczyk, M. (1985) · Biological Cybernetics · doi:10.1007/bf00337149 · Cited by 138 · see citing works
Self-citationRecent Advances in EEG and EMG Data Processing
Willison, R. G. (1982) · Journal of Neurology Neurosurgery & Psychiatry · doi:10.1136/jnnp.45.2.192-b · Cited by 116 · see citing works
Recent advances in EEG and EMG data processing
Pockberger, H. (1982) · Electroencephalography and Clinical Neurophysiology · doi:10.1016/0013-4694(82)90189-4 · Cited by 98 · see citing works
Detection of feedback in the central nervous system using system identification techniques
Schnider, S., Kwong, R. H. S., Lenz, F. A., et al. (1989) · Biological Cybernetics · doi:10.1007/bf00207288 · Cited by 46 · see citing works
A time‐series analysis method based on the directed transinformation
Kamitake, T., Harashima, H., & Miyakawa, H. (1984) · Electronics and Communications in Japan (Part I Communications) · doi:10.1002/ecja.4400670602 · Cited by 44 · see citing works
EEG data reduction by means of autoregressive representation and discriminant analysis procedures
Blinowska, K. J., Czerwosz, L. T., Drabik, W., et al. (1981) · Electroencephalography and Clinical Neurophysiology · doi:10.1016/0013-4694(81)90209-1 · Cited by 34 · see citing works
Self-citationSigns of Model Making by the Human Brain
Gevins, A. S. (1989) · Springer series in brain dynamics · doi:10.1007/978-3-642-74557-7_32 · Cited by 10 · see citing works
A new method of presentation of the average spectral properties of the EEG time series
Blinowska, K. J., Franaszczuk, P. J., & Mitraszewski, P. (1988) · International Journal of Bio-Medical Computing · doi:10.1016/0020-7101(88)90046-3 · Cited by 7 · see citing works
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Bridging emotion theory and neurobiology through dynamic systems modeling
Lewis, M. D. (2005) · Behavioral and Brain Sciences · doi:10.1017/s0140525x0500004x · Cited by 618 · see citing works
Babiloni, F., Cincotti, F., Babiloni, C., Carducci, F., Mattia, D., Astolfi, L., Basilisco, A., Rossini, P. M., Ding, L., Ni, Y., et al. (2005) · NeuroImage · doi:10.1016/j.neuroimage.2004.09.036 · Cited by 412 · see citing works
van Diessen, E., Numan, T., van Dellen, E., van der Kooi, A. W., Boersma, M., Hofman, D., van Lutterveld, R., van Dijk, B. W., van Straaten, E. C. W., Hillebrand, A., et al. (2015) · Clinical Neurophysiology · doi:10.1016/j.clinph.2014.11.018 · Cited by 417 · see citing works
Korzeniewska, A., Mańczak, M., Kamiński, M., Blinowska, K. J., & Kasicki, S. (2003) · Journal of Neuroscience Methods · doi:10.1016/s0165-0270(03)00052-9 · Cited by 375 · see citing works
Self-citationElectrophysiological source imaging: A noninvasive window to brain dynamics
He, B., Sohrabpour, A., Brown, E., & Liu, Z. (2018) · Annual Review of Biomedical Engineering · doi:10.1146/annurev-bioeng-062117-120853 · Cited by 297 · see citing works
Electrophysiological Imaging of Brain Activity and Connectivity—Challenges and Opportunities
He, B., Yang, L., Wilke, C., & Yuan, H. (2011) · IEEE Transactions on Biomedical Engineering · doi:10.1109/tbme.2011.2139210 · Cited by 300 · see citing works
eConnectome: A MATLAB toolbox for mapping and imaging of brain functional connectivity
He, B., Dai, Y., Astolfi, L., Babiloni, F., Yuan, H., & Yang, L. (2011) · Journal of Neuroscience Methods · doi:10.1016/j.jneumeth.2010.11.015 · Cited by 229 · see citing works
Schelter, B., Timmer, J., & Eichler, M. (2009) · Journal of Neuroscience Methods · doi:10.1016/j.jneumeth.2009.01.006 · Cited by 214 · see citing works
Tracking the Time-Varying Cortical Connectivity Patterns by Adaptive Multivariate Estimators
Astolfi, L., Cincotti, F., Mattia, D., De Vico Fallani, F., Tocci, A., Colosimo, A., Salinari, S., Marciani, M. G., Hesse, W., Witte, H., et al. (2008) · IEEE Transactions on Biomedical Engineering · doi:10.1109/tbme.2007.905419 · Cited by 179 · see citing works
Ictal source analysis: Localization and imaging of causal interactions in humans
Ding, L., Worrell, G. A., Lagerlund, T. D., & He, B. (2007) · NeuroImage · doi:10.1016/j.neuroimage.2006.09.042 · Cited by 183 · see citing works
Multimodal Functional Neuroimaging: Integrating Functional MRI and EEG/MEG
He, B., & Liu, Z. (2008) · IEEE Reviews in Biomedical Engineering · doi:10.1109/rbme.2008.2008233 · Cited by 171 · see citing works
Wilke, C., Ding, L., & He, B. (2008) · IEEE Transactions on Biomedical Engineering · doi:10.1109/tbme.2008.919885 · Cited by 159 · see citing works
Decoding Covert Speech From EEG-A Comprehensive Review
Panachakel, J. T., & Ramakrishnan, A. G. (2021) · Frontiers in Neuroscience · doi:10.3389/fnins.2021.642251 · Cited by 156 · see citing works
Havlicek, M., Jan, J., Brazdil, M., & Calhoun, V. D. (2010) · NeuroImage · doi:10.1016/j.neuroimage.2010.05.063 · Cited by 106 · see citing works
Ossadtchi, A., Baillet, S., Mosher, J. C., Thyerlei, D., Sutherling, W., & Leahy, R. M. (2004) · Clinical Neurophysiology · doi:10.1016/j.clinph.2003.10.036 · Cited by 104 · see citing works
Lu, Y., Yang, L., Worrell, G. A., & He, B. (2012) · Clinical Neurophysiology · doi:10.1016/j.clinph.2011.11.007 · Cited by 98 · see citing works
Coito, A., Michel, C. M., van Mierlo, P., Vulliemoz, S., & Plomp, G. (2016) · IEEE Transactions on Biomedical Engineering · doi:10.1109/tbme.2016.2619665 · Cited by 75 · see citing works
Sohrabpour, A., Ye, S., Worrell, G. A., Zhang, W., & He, B. (2016) · IEEE Transactions on Biomedical Engineering · doi:10.1109/tbme.2016.2616474 · Cited by 59 · see citing works
Systems Neuroengineering: Understanding and Interacting with the Brain
Edelman, B. J., Johnson, N., Sohrabpour, A., Tong, S., Thakor, N., & He, B. (2015) · Engineering · doi:10.15302/j-eng-2015078 · Cited by 45 · see citing works
Ligeza, T. S., Wyczesany, M., Tymorek, A. D., & Kamiński, M. (2016) · Brain Topography · doi:10.1007/s10548-015-0454-2 · Cited by 43 · see citing works
Estimating Directed Connectivity from Cortical Recordings and Reconstructed Sources
Papadopoulou, M., Friston, K., & Marinazzo, D. (2019) · Brain Topography · doi:10.1007/s10548-015-0450-6 · Cited by 40 · see citing works
Stress and Perception of Emotional Stimuli: Long-Term Stress Rewiring the Brain
Khosrowabadi, R., & Institute for Cognitive and Brain Sciences, S. B. U. (2018) · Basic and Clinical Neuroscience Journal · doi:10.29252/nirp.bcn.9.2.107 · Cited by 39 · see citing works
- Authors
- Kaminski, M. J., & Blinowska, K. J.
- Affiliations
- University of Warsaw (PL)
- ORCID
- Blinowska, K. J.
- Venue
- Biological Cybernetics
- Published
- 1991-07
- Volume
- 65
- Issue
- 3
- Pages
- 203-210
- ISSN
- 0340-1200 (ISSN-L)
- 1432-0770
- OpenAlex
- W2009914532
- Cited by
- 1,047
- References
- 10
- Citations by year
- 2026: 19 · 2025: 27 · 2024: 51 · 2023: 29 · 2022: 51 · 2021: 52 · 2020: 46 · 2019: 44 · 2018: 59 · 2017: 47 · 2016: 64 · 2015: 52 · 2014: 76 · 2013: 65 · 2012: 41
- FWCI
- 1.17
- Type
- journal article
- Language
- en
- Open access
- closed
- Licence
- www.springer.com/tdm (tdm)
- Locations
- Biological Cybernetics (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Life Sciences › Neuroscience › Cognitive Neuroscience › EEG and Brain-Computer Interfaces
- Life Sciences › Neuroscience › Cognitive Neuroscience › Neural dynamics and brain function
- Physical Sciences › Computer Science › Signal Processing › Direction-of-Arrival Estimation Techniques
- Keywords
- EEG, autoregressive models, transfer function matrix, spectral analysis, epilepsy, multichannel EEG
- MeSH terms
- Animals, Brain, Electroencephalography, Epilepsy, Hippocampus, Humans, Hypothalamus, Mathematics, Models, Neurological, Motor Activity, Reference Values
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