On the Most Informative Slice of Bicoherence That Characterizes Resting State Brain Connectivity

Kandemir, Ahmet Levent
Özkurt, Tolga Esat
Bicoherence is a useful tool to detect nonlinear interactions within the brain with high computational cost. Latest attempts to reduce this computational cost suggest calculating a particular 'slice' of the bicoherence matrix. In this study, we investigate the information content of the bicoherence matrix in resting state. We use publicly available Human Connectome Project data in our calculations. We show that the most prominent information of the bicoherence matrix is concentrated on the main diagonal, i.e., f(1)=f(2).
European Signal Processing Conference (EUSIPCO)


Estimation of nonlinear neural source interactions via sliced bicoherence
Özkurt, Tolga Esat (2016-09-01)
Neural oscillations and their spatiotemporal interactions are of interest for the description of brain mechanisms. This study offers a novel third order spectral coupling measure named "sliced bicoherence". It is the diagonal slice of cross-bicoherence allowing an efficient quantification of the nonlinear interactions between neural sources. Our methodology comprises an indirect estimation method, a parametric confidence level formula and a subtracted version for robustness to volume conduction. The methodo...
The role of synchronization of neural structures on neuron dynamics Nöral yapilarda senkronizasyonun hücre dinamikleri üzerine etkisi
Karabacak, Ozkan; Elibol, Rahmi; Şengör, Neslihan Serap (2014-01-01)
Due to the measurement techniques developed, it is now possible to observe signals at different levels in neural structures. These observations give rise to increasing works dealing with setting up the relation between such signals and cognitive processes, neurodegenerative diseases and neurobehavioral disorders. Computational neuroscience is becoming more influential in investigating the mechanisms underlining these signals. Especially oscillations in different neural structures and the role of these oscil...
A comparative stationarity analysis of EEG signals
RASOULZADEH, VESAL; Erkuş, Ekin Can; Yoğurt, Taha Alper; Ulusoy, İlkay; Zergeroglu, S. Aykan (2017-11-01)
While developing models of brain functioning by using time series data, the stationary interval of the time series should be used to model the corresponding state of the brain. Here it is assumed that at the borders of stationarity, brain changes its state where a state is considered as a group of brain regions working together. If the whole nonstationary time series is used, many different brain states could be included in one model. However, it is very hard to decide the stationary intervals for such a co...
Improving Perceptual Quality of Spatially Transformed Adversarial Examples
Aydın, Ayberk; Temizel, Alptekin; Department of Modeling and Simulation (2022-8)
Deep neural networks are known to be vulnerable to additive adversarial perturbations. The amount of these additive perturbations are generally quantified using Lp metrics over the difference between adversarial and benign examples. However, even when the measured perturbations are small, they tend to be noticeable by human observers since Lp distance metrics are not representative of human perception. Spatially transformed examples work by distorting pixel locations instead of applying an additive perturba...
Classification in Frequency Domain of EEG Signals of Motor Imagery for Brain Computer Interfaces
Halıcı, Uğur (2009-05-22)
In this study the classification of the EEG signals recorded during motor imagery for curser movement in brain computer interfaces is examined, in which the feature vectors obtained in frequency domain is used and then the linear transformations are applied for reducing the size of the feature vectors.
Citation Formats
A. L. Kandemir and T. E. Özkurt, “On the Most Informative Slice of Bicoherence That Characterizes Resting State Brain Connectivity,” presented at the European Signal Processing Conference (EUSIPCO), Rome, ITALY, 2018, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/55963.