Substance use disorder exacerbates brain electrophysiological abnormalities in a psychiatrically-ill population.

OBJECTIVE: To assess by brain electrical activity mapping whether cocaine and alcohol abuse and dependence would exacerbate electro-physiological abnormalities in a psychiatrically-ill population. DESIGN, SETTING, AND PARTICIPANTS: Utilizing a brain mapping system, we assessed EEG, Spectral Analysis (Quantitative EEG[QEEG]). Evoked Potentials (Auditory and Visual), and P300 (cognitive evoked potential), in a total of 111 probands divided into three groups: controls (N = 16), psychiatrically-ill without comorbid substance use disorder (N = 34), and psychiatrically-ill with comorbid substance use disorder (cocaine and alcohol abuse and dependence) (N = 61), at an outpatient neuropsychiatric clinic. With regard to demographic data, the group participating in this study did not differ significantly. A comparison was made among the groups to assist in differentiating the effects of substance use disorder compared to psychiatric disease on brain electrical activity. MAIN OUTCOME MEASURES: An assessment of electrophysiological abnormalities and their brain location in psychiatric and substance use disorder patients was done with a brain electrical activity mapping test. MAIN
RESULTS: Among the non-substance use disorder, psychiatrically-ill (PI) and substance use disorder, psychiatrically-ill (PI/SD) groups, significantly different brain map abnormalities were observed relative to an assessed normal population MANOVA (P = .017). Moreover, with regard to Spectral Analysis, ANOVA was significant at a P = .038, and we found a weighted linear trend of increased abnormal total spectral analysis (P = .0113), whereby substance use was significantly worse than controls. Moreover among the PI and PI/SD groups, significantly greater total evoked potential (EP) brain trap abnormalities were observed when compared with a characterized normal population (P = .0023) with increasing abnormalities as a function of substance use disorder as measured by a weighted linear trend (P = .0022). In order to determine the site of the EPS abnormalities, we evaluated these abnormalities by location. In this regard, we found all temporal abnormalities (AVBITA, see Table 2) among the PI and PI/SD groups to be significantly greater relative to an assessed normal population (P = .0026). Furthermore, we observed a linear trend of increased temporal abnormalities with increasing substance use disorder (P < .0008). In terms of bitemporal abnormalities (AVBIT) among the PI and PI/SD groups, we also found significantly more bitemporal lobe abnormalities in the PI/SD group compared to our control population (P = .009). Additionally, a weighted linear trend of increased abnormal bitemporal lobe abnormalities was observed with increasing substance use disorder (P = .0022). In the frontal lobe similar findings were observed. With AVBIFA the ANOVA was P < .011, with a weighted linear trend of P < .005 and the PI/SD group were significantly more abnormal than PI or CS on a Duncan Range test. It is noteworthy that in a selected group of depressed (Major Depressive Disorder Recurrent, 296.3) patients, we found profound abnormalities in the various brain map parameters tested. MANOVA and Univariate ANOVA's revealed significantly greater abnormalities in the PI and PI/SD groups compared to assessed controls. A MANOVA for total brain abnormalities was significant at P = .043 and univariate ANOVA's for composite measurements of TSA (P = .017), EPS (P = .0002), AVBITA (P = .000015), and AVBIT (P < .00002) are also significant. With regard to EPS and AVBITA a weighted linear trend was observed where there were increasing abnormalities with increasing substance use disorder, P = .0001 and P = .000003, respectively. Most importantly we found that in addition to increased abnormalities with increasing substance use disorder the PI/SD group had significantly more abnormalities compared to the PI group with regard to both the TSA (P < .05) and AVBIT (P < .05) composite parameters as meas