Higuchi’s fractal dimension, but not frontal or posterior alpha asymmetry, predicts PID-5 anxiousness more than depressivity

Kawe, Tame Ngahiwi James; Shadli, Shabah M.; McNaughton, Neil

doi:10.1038/s41598-019-56229-w

Cited by 19 publications

(8 citation statements)

References 53 publications

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“… Shadli et al (2018) found no significant HFD differences between pre- and post-ketamine administration at any dosage. In contrary, we found significant differences in HFD at the lateral channels (F7 and F8) between anxiety patients and controls, consistent with our earlier findings ( Kawe et al, 2019 ). These results suggest that a shift from an anxious to a non-anxious state is related to a reduction in HFD at the lateral channels, corresponding to left and right prefrontal sites.…”

Section: Discussionsupporting

confidence: 93%

Right Frontal Theta: Is It a Response Biomarker for Ketamine’s Therapeutic Action in Anxiety Disorders?

et al. 2022

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Anxiety disorders are the most prevalent mental disorders in the world, creating huge economic burdens on health systems and impairing the quality of life for those affected. Recently, ketamine has emerged as an effective anxiolytic even in cases resistant to conventional treatments (TR); but its therapeutic mechanism is unknown. Previous data suggest that ketamine anxiety therapy is mediated by reduced right frontal electroencephalogram (EEG) theta power measured during relaxation. Here we test for a similar theta reduction between population-sample, presumed treatment-sensitive, (TS) anxiety patients and healthy controls. Patients with TS DSM-5 anxiety disorder and healthy controls provided EEG during 10 min of relaxation and completed anxiety-related questionnaires. Frontal delta, theta, alpha1, alpha2, beta, and gamma power, Higuchi’s fractal dimension (HFD) and frontal alpha asymmetry (FAA) values were extracted to match ketamine testing; and we predicted that the controls would have less theta power at F4, relative to the TS anxious patients, and no differences in HFD or FAA. We provide graphical comparisons of our frontal band power patient-control differences with previously published post-pre ketamine TR differences. As predicted, theta power at F4 was significantly lower in controls than patients and FAA was not significantly different. However, HFD was unexpectedly reduced at lateral sites. Gamma power did not increase between controls and patients suggesting that the increased gamma produced by ketamine relates to dissociation rather than therapy. Although preliminary, and indirect, our results suggest that the anxiolytic action of ketamine is mediated through reduced right frontal theta power.

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Section: Discussionsupporting

confidence: 93%

Right Frontal Theta: Is It a Response Biomarker for Ketamine’s Therapeutic Action in Anxiety Disorders?

et al. 2022

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“…The dynamic marker HFD is the marker of the highest effectiveness and is expected to incorporate a maximal part of the information from the EEG signal. This conclusion is supported by many studies where HFD has been successfully used for the detection of small alterations in EEG related to different factors such as depression, anxiety, or microwave radiation 22,[37][38][39][40] . The traditional EEG band power marker ABP is the most commonly used band power marker which has shown good sensitivity in various applications 2,4,6,7 .…”

Section: Discussionunclassified

Correlation between electroencephalographic markers in the healthy brain

Päeske

Uudeberg

Hinrikus

et al. 2023

Sci Rep

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Mental disorders have an increasing tendency and represent the main burden of disease to society today. A wide variety of electroencephalographic (EEG) markers have been successfully used to assess different symptoms of mental disorders. Different EEG markers have demonstrated similar classification accuracy, raising a question of their independence. The current study is aimed to investigate the hypotheses that different EEG markers reveal partly the same EEG features reflecting brain functioning and therefore provide overlapping information. The assessment of the correlations between EEG signal frequency band power, dynamics, and functional connectivity markers demonstrates that a statistically significant correlation is evident in 37 of 66 (56%) comparisons performed between 12 markers of different natures. A significant correlation between the majority of the markers supports the similarity of information in the markers. The results of the performed study confirm the hypotheses that different EEG markers reflect partly the same features in brain functioning. Higuchi’s fractal dimension has demonstrated a significant correlation with the 82% of other markers and is suggested to reveal a wide spectrum of various brain disorders. This marker is preferable in the early detection of symptoms of mental disorders.

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“…SM3. Software packages for physiological data analysis [ 154 , 155 , 156 , 157 , 158 , 159 , 160 , 161 , 162 , 163 , 164 , 165 , 166 , 167 , 168 , 169 , 170 , 171 , 172 , 173 , 174 , 175 , 176 , 177 , 178 , 179 , 180 , 181 , 182 , 183 , 184 , 185 , 186 , 187 , 188 , 189 , 190 , 191 , 192 , 193 , 194 , 195 , 196 , 197 , 198 , 199 , 200 , 201 , 202 , 203 , 204 , 205 , 206 , 207 ...…”

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CEPS: An Open Access MATLAB Graphical User Interface (GUI) for the Analysis of Complexity and Entropy in Physiological Signals

Mayor

Panday

Kandel

et al. 2021

Entropy

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Background: We developed CEPS as an open access MATLAB® GUI (graphical user interface) for the analysis of Complexity and Entropy in Physiological Signals (CEPS), and demonstrate its use with an example data set that shows the effects of paced breathing (PB) on variability of heart, pulse and respiration rates. CEPS is also sufficiently adaptable to be used for other time series physiological data such as EEG (electroencephalography), postural sway or temperature measurements. Methods: Data were collected from a convenience sample of nine healthy adults in a pilot for a larger study investigating the effects on vagal tone of breathing paced at various different rates, part of a development programme for a home training stress reduction system. Results: The current version of CEPS focuses on those complexity and entropy measures that appear most frequently in the literature, together with some recently introduced entropy measures which may have advantages over those that are more established. Ten methods of estimating data complexity are currently included, and some 28 entropy measures. The GUI also includes a section for data pre-processing and standard ancillary methods to enable parameter estimation of embedding dimension m and time delay τ (‘tau’) where required. The software is freely available under version 3 of the GNU Lesser General Public License (LGPLv3) for non-commercial users. CEPS can be downloaded at https://bitbucket.org/deepak_panday/ceps/src/pipeline_v2/. In our illustration on PB, most complexity and entropy measures decreased significantly in response to breathing at 7 breaths per minute, differentiating more clearly than conventional linear, time- and frequency-domain measures between breathing states. In contrast, Higuchi fractal dimension increased during paced breathing. Conclusions: We have developed CEPS software as a physiological data visualiser able to integrate state of the art techniques. The interface is designed for clinical research and has a structure designed for integrating new tools. The aim is to strengthen collaboration between clinicians and the biomedical community, as demonstrated here by using CEPS to analyse various physiological responses to paced breathing.

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Higuchi’s fractal dimension, but not frontal or posterior alpha asymmetry, predicts PID-5 anxiousness more than depressivity

Cited by 19 publications

References 53 publications

Right Frontal Theta: Is It a Response Biomarker for Ketamine’s Therapeutic Action in Anxiety Disorders?

Right Frontal Theta: Is It a Response Biomarker for Ketamine’s Therapeutic Action in Anxiety Disorders?

Correlation between electroencephalographic markers in the healthy brain

CEPS: An Open Access MATLAB Graphical User Interface (GUI) for the Analysis of Complexity and Entropy in Physiological Signals

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