Article

[Event-related potentials in major depressive disorder: the relationship between P300 and treatment response].

Girne Military Hospital, Department of Psychiatry, Girne.
Turk psikiyatri dergisi = Turkish journal of psychiatry (Impact Factor: 0.43). 01/2012; 23(1):33-9. DOI: 10.5080/u6650
Source: PubMed

ABSTRACT Although conflicting results have been obtained regarding P300 amplitude and latency in major depressive patients, most studies have reported that major depressive patients have smaller P300 amplitudes and longer latencies than healthy people. This study aimed to investigate the relationship between P300 and treatment response in major depressive disorder patients.
Twenty-eight patients suffering from major depression who completed 12 weeks of follow-up appointments and 28 healthy people, whose age and gender were matched with patients, were included in the study. Event-related potentials (P300) were recorded for patients before and after treatment with sertraline (50-200 mg/day) for 12 weeks. Treatment response was defined as a 50% or greater decrease in a given patient's total Hamilton Depression Rating Scale score. Pre-treatment and post-treatment P300 amplitude and latency values were compared for responders (n=18), non-responders (n=10) and healthy subjects.
No significant difference was found between the P300 amplitude values of responders, non-responders and healthy subjects before or after treatment. Pre-treatment P300 latencies of non-responders were significantly longer than latencies of responders and healthy subjects. After treatment for depression, P300 latency values of responders were normalized, but non-responders still maintained longer P300 latencies than responders and healthy subjects.
These findings suggest that delayed P300 latency may be related to a non-response to sertraline treatment. No relation was found between P300 amplitude and treatment response.

0 Followers
 · 
127 Views
  • [Show abstract] [Hide abstract]
    ABSTRACT: Event-related potentials (ERPs), derived from electroencephalographic (EEG) recordings, can index electrocortical activity related to cognitive operations. The fronto-central P3a ERP is involved in involuntary processing of novel auditory information, whereas the parietal P3b indexes controlled attention processing. The amplitude of the auditory P3b has been found to be decreased in major depressive disorder (MDD). However, few studies have examined the relations between the P3b, the related P3a, and antidepressant treatment response. We tested 53 unmedicated individuals (25 females) with MDD, as well as 43 non-depressed controls (23 females) on the novelty oddball task, wherein infrequent deviant (target) and frequent standard (non-target) tones were presented, along with infrequent novel (non-target/distractor) sounds. The P3a and P3b ERPs were assessed to novel and target sounds, respectively, as were their accompanying behavioral performance measures. Depression ratings and the antidepressant response status were assessed following 12 weeks of pharmacotherapy with three different regimens. Antidepressant treatment non-responders had smaller baseline P3a/b amplitudes than responders and healthy controls. Baseline P3b amplitude also weakly predicted the extent of depression rating changes by week 12. Females exhibited larger P3a/b amplitudes than males. With respect to task performance, controls had more target hits than treatment non-responders. ERP measures correlated with clinical changes in males and with behavioral measures in females. These results suggest that greater (or control-like) baseline P3a/b amplitudes are associated with a positive antidepressant response, and that gender differences characterize the P3 and, by extension, basic attentive processes.
    European neuropsychopharmacology: the journal of the European College of Neuropsychopharmacology 05/2013; 23(11). DOI:10.1016/j.euroneuro.2013.03.003 · 5.40 Impact Factor
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: Abstract Major depressive disorder (MDD) has high population prevalence and is associated with substantial impact on quality of life, not least due to an unsatisfactory time span of sometimes several weeks from initiation of treatment to clinical response. Therefore extensive research focused on the identification of cost-effective and widely available electroencephalogram (EEG)-based biomarkers that not only allow distinguishing between patients and healthy controls but also have predictive value for treatment response for a variety of treatments. In this comprehensive overview on EEG research on MDD, biomarkers that are either assessed at baseline or during the early course of treatment and are helpful in discriminating patients from healthy controls and assist in predicting treatment outcome are reviewed, covering recent decades up to now. Reviewed markers include quantitative EEG (QEEG) measures, connectivity measures, EEG vigilance-based measures, sleep-EEG-related measures and event-related potentials (ERPs). Further, the value and limitations of these different markers are discussed. Finally, the need for integrated models of brain function and the necessity for standardized procedures in EEG biomarker research are highlighted to enhance future research in this field.
    International Review of Psychiatry 10/2013; 25(5):604-18. DOI:10.3109/09540261.2013.816269 · 1.80 Impact Factor
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: Despite the significance of major depressive disorder, objective procedures for selecting optimal treatments are lacking, there is a need for reliable and objective measures capable of differentiating between those who may or may not respond to specific treatments. Studies using neuroimaging, neurocognitive, and electrophysiologic measures have found that pre-treatment differences among depressed patients are related to subsequent clinical response to antidepressant drugs. Besides some clinical features and biological markers, the modern methods of brain imaging and quantitative electroencephalogram might be useful in prediction of treatment response. INTRODUCTION In industrialized countries, mental illnesses may account for about 16% of total health care costs and 30% of disability claims [1]. A tool capable of differentiating between those who may or may not respond to specific treatments is needed. Such a measure should be reliable, objective, and readily available.