Intracranial source activity (eLORETA) related to scalp‐level asymmetry scores and depression status

Abstract

Frontal EEG alpha asymmetry provides a promising index of depression risk, yet very little is known about the neural sources of alpha asymmetry. To identify these sources, this study examined alpha asymmetry using a distributed inverse solution: exact low resolution brain electromagnetic tomography (eLORETA). Findings implicated a generator in lateral midfrontal regions that contributed to both surface asymmetry and depression risk. Participants with any lifetime history of depressive episodes were characterized by less left than right activity in the precentral gyrus and midfrontal gyrus. Anhedonia accounted for a significant portion of the relationship between alpha asymmetry and lifetime major depressive disorder. Results are suggestive of convergence between motivational and capability models of asymmetry and replicate results from experimental studies in a large resting-state data set. The capability model of frontal alpha asymmetry is contextualized in terms of motor preparedness following emotional mobilization.

Frontal EEG alpha asymmetry and emotion: From neural underpinnings and methodological considerations to psychopathology and social cognition

“…Transforming data using the surface Laplacian (i.e., current source density, CSD) can mitigate contamination of alpha at frontal sites from nonfrontal alpha sources that may be unrelated to motivational/emotional states and traits of interest (Allen & Reznik, 2015;Hagemann, Naumann, Thayer, & Bartussek, 2001;Smith et al, 2017;Stewart, Bismark, Towers, Coan, & Allen, 2010). By ensuring that metrics of frontal alpha in fact reflect predominantly frontal alpha, theoretical links to frontal brain systems can be better substantiated, and efforts for identifying the neural correlates of frontal EEG asymmetry may be facilitated (e.g., Smith, Cavanagh, & Allen, 2018).…”

“…Among these considerations are several particularly influential issues (Smith et al, 2017): (a) the choice of reference (or CSD transformation), (b) the selection of methods for handling artifacts, (c) using designs with resting state versus experimental challenges, and (d) specifying models explicitly for testing mediating and moderating relationships of frontal asymmetry with individual differences or experimental manipulations. In this issue, several articles include exemplary treatment of these issues including the use of the CSD transformation (Rodrigues, M€ uller, M€ uhlberger, & Hewig, 2018;Smith, Cavanagh, & Allen, 2018) and experimental state manipulations (Meyer et al, 2018;Nelson, Kessel, Klein, & Shankman, 2018;Rodrigues et al, 2018;Schmid, Hackel, Jasperse, & Amodio, 2018;Wacker, 2018).…”

“…The results also suggest that it is required to implement specific clinical diagnostic procedures when examining prisoners, as heterogeneous psychopathology could affect the relation between alpha asymmetry and behavioral traits of interest. Smith et al (2018) related surface asymmetry to intracranial asymmetry modeled using a distributed inverse solution. In a large data set of individuals with current depression, previous (but not current depression), and no history of depression, they examined (a) asymmetry in intracranial regions of interest (ROIs) that were related to surface frontal EEG alpha asymmetry, (b) intracranial ROIs that were related to any history of depression, and (c) regions where these ROIs overlapped.…”

Comparison of Frontal Alpha Asymmetry Among Schizophrenia Patients, Major Depressive Disorder, and Healthy Controls

“…Although electroencephalographic frontal alpha asymmetry (FAA) has been suggested to be a clinical biomarker for the abnormal behavioral phenotype of major depressive disorder (MDD) [1][2][3][4][5][6][7][8][9], con icting results in prior research have contested this view [10,11]. A previous meta-analysis of 1,883 individuals with MDD and 2,161 controls found that FAA's diagnostic value was not signi cant [11].…”

Abnormal approach-related motivation but spared reinforcement learning in MDD: Evidence from fronto-midline Theta oscillations and frontal Alpha asymmetry

“…Alpha power contributing to frontal asymmetry effects is commonly reported from a set of homologous frontal leads along the coronal axis (in particular F8-F7, F6-F5, F4-F3 and F2-F1; see Stewart, Bismark, Towers, Coan, & Allen, 2010) and is thought to be generated mostly (but not only) from the proximal dorsolateral prefrontal cortex (dlPFC) (Pizzagalli, Sherwood, Henriques, & Davidson, 2005), even though a clear regional specificity remains difficult to establish. With regard to MDD, anhedonic symptoms, such as loss of interest, reduced hedonic capacity, and decline of goal-related motivation, have been linked to a putative hypoactive approachmotivation system, as reflected by lower left prefrontal activity at rest (Davidson, 1998b;Henriques and Davidson, 1991;Nusslock et al, 2015;Pizzagalli et al, 2005;see Thibodeau et al, 2006 for a meta-analysis) and source-estimated in the precentral and midfrontal gyri (Smith, Cavanagh, & Allen, 2017). Although such a broad dichotomy of frontal lobes specialization might be too coarse (Miller, Crocker, Spielberg, Infantolino, & Heller, 2013), and a recent meta-analysis showed that traditional ways of assessing Alpha asymmetry have limited diagnostic value for MDD (van der Vinne, Vollebregt, van Putten, & Arns, 2017), recently important methodological advances have been introduced to increase the robustness and heuristic promise of this metric (Smith, Reznik, Stewart, & Allen, 2017).…”