Alpha Peak Frequency Shift as an Alternative Cognitive Marker for Depression
Poster No:
648
Submission Type:
Abstract Submission
Authors:
Sangwon Yu1, Minsok Koo1, Sang Ah Lee1
Institutions:
1Seoul National University, Gwanak-gu, Seoul
First Author:
Co-Author(s):
Introduction:
Various oscillatory activities in the brain have been studied as neural markers for affective disorders (1). A considerable number of studies have reported an alteration of alpha waves (8~13 Hz) in depression, but a change in its peak frequency has not been explored in full, particularly in relation to cognition. Increased alpha peak frequency is associated with relaxation, resilience, and mood (2,3,4). At the same time, some argue that a gradual decrease of alpha frequency from posterior to anterior regions represents cortical hierarchies that form a frequency gradient that enables cortical traveling waves involved in cognition (5,6,7). This study investigates the link between the dynamics of alpha peak frequency and depression symptoms in subclinical adults, shedding new light on the neural basis of the interaction between depressive symptoms and cognitive impairments.
Methods:
We recorded rest-state EEG signals from 38 participants (female = 20, age range = 20-32) for five minutes, and while they performed an emotional scene-based memory task. During the encoding phase, 144 images of positive, negative, or neutral events (48 images for each condition) were presented in pseudorandom order. Following the stimulus presentation, participants rated the valence (i.e., how positive or negative) and arousal (i.e., how exciting or calming) of each scene on a scale from 1–9. After the entire encoding phase, participants performed a scene recognition test. Alpha peak frequency was calculated with a Fitting Oscillations and One Over F (FOOOF) algorithm, dissociating the periodic components of the EEG power spectrum from the aperiodic component.
Results:
During rest, we found significant increases of alpha peak frequency in the frontal regions for the depressed group compared to the non-depressed group (F(1,36) = 1.00, p<0.0001). This result was replicated across in an openneuro public dataset of 122 participants (female = 47, age range = 18-20, F(1,120) = 7.30, p<0.0001).The topographic patterns, showing an alpha peak frequency decrease from posterior to anterior regions, were similar between our lab's dataset and the public dataset. These resting-state findings largely replicate previous MEG experiments (5) and extend them to scalp EEG.
Furthermore, during the encoding of emotional scenes, the depressed group showed no change (from pre- to post-stimulus periods) in alpha peak frequency in the frontal regions when presented with emotional scenes (F(1,16) = 0.15, p>0.5). In contrast, the non-depressed group showed a significantly decreased frontal alpha frequency while viewing scenes (F(1,18) = 5.06, p<0.05).
We tested for a possible functional correlation between valence ratings and frontal peak frequency change during the encoding phase and found that an increase in the peak frequency in the depressed group was correlated with their rating of emotional scenes as less emotional, according to their valence and arousal ratings (r=-0.55, p<0.05). These results may indicate the need for greater frontal regulation of emotional scene content that also disrupts the posterior to anterior gradient for perceptual information processing.
Furthermore, during the encoding of emotional scenes, the depressed group showed no change (from pre- to post-stimulus periods) in alpha peak frequency in the frontal regions when presented with emotional scenes (F(1,16) = 0.15, p>0.5). In contrast, the non-depressed group showed a significantly decreased frontal alpha frequency while viewing scenes (F(1,18) = 5.06, p<0.05).
We tested for a possible functional correlation between valence ratings and frontal peak frequency change during the encoding phase and found that an increase in the peak frequency in the depressed group was correlated with their rating of emotional scenes as less emotional, according to their valence and arousal ratings (r=-0.55, p<0.05). These results may indicate the need for greater frontal regulation of emotional scene content that also disrupts the posterior to anterior gradient for perceptual information processing.
·Alpha Frequency During Resting State Between The Depressed and Non-depressed group
·Alpha Frequency Change During The Encoding Phase Between The Depressed and Non-depressed group
Conclusions:
We propose that an alpha peak shift may reflect a neural change in individuals with symptoms of depression, and that the upward shift in alpha frequency may be indicative of abnormal neurocognitive function. One possible mechanism that may explain the increase, rather than decrease, of alpha peak frequency upon emotional stimulus is a potential emotional regulatory mechanism that perturbs the frequency gradient that promotes information flow from the posterior visual regions to the frontal regions of the cortex. Further studies are needed to test this hypothesis in detail.
Disorders of the Nervous System:
Psychiatric (eg. Depression, Anxiety, Schizophrenia) 1
Emotion, Motivation and Social Neuroscience:
Emotional Perception 2
Learning and Memory:
Long-Term Memory (Episodic and Semantic)
Modeling and Analysis Methods:
EEG/MEG Modeling and Analysis
Neuroanatomy, Physiology, Metabolism and Neurotransmission:
Cortical Anatomy and Brain Mapping
Keywords:
Affective Disorders
Cognition
Electroencephaolography (EEG)
Emotions
Memory
Other - Emotional Scene Memory ; Emotional Processing ; Freuquency Gradient
1|2Indicates the priority used for review
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(2) Kostyunina, M.B., Kulikov, M.A. (1996). Frequency characteristics of EEG spectra in the emotions. Neurosci Behav Physiol 26, 340–343 .
(3) Lechinger, J., Bothe, K., Pichler, G. et al. (2013). CRS-R score in disorders of consciousness is strongly related to spectral EEG at rest. J Neurol 260, 2348–2356.
(4) Mierau, A., et al. (2017). State-dependent alpha peak frequency shifts: Experimental evidence, potential mechanisms and functional implications. Neuroscience 360, 146-154.
(5) Mahjoory, K., et al. (2020). The frequency gradient of human resting-state brain oscillations follows cortical hierarchies. eLife 9.
(6) Zanos TP, elt al. (2015). A sensorimotor role for traveling waves in primate visual cortex. Neuron 85(3), 615-27.
(7) Zhang, H., et al. (2018). Theta and alpha oscillations are traveling waves in the human neocortex. Neuron 98(6), 1269-1281.