Brainmarker-I Differentially Predicts Remission to Various Attention-Deficit/Hyperactivity Disorder Treatments: A Discovery, Transfer, and Blinded Validation Study.

BACKGROUND: Attention-deficit/hyperactivity disorder is characterized by neurobiological heterogeneity, possibly explaining why not all patients benefit from a given treatment. As a means to select the right treatment (stratification), biomarkers may aid in personalizing treatment prescription, thereby increasing remission rates. METHODS: The biomarker in this study was developed in a heterogeneous clinical sample (N = 4249) and first applied to two large transfer datasets, a priori stratifying young males (<18 years) with a higher individual alpha peak frequency (iAPF) to methylphenidate (N = 336) and those with a lower iAPF to multimodal neurofeedback complemented with sleep coaching (N = 136). Blinded, out-of-sample validations were conducted in two independent samples. In addition, the association between iAPF and response to guanfacine and atomoxetine was explored. RESULTS: Retrospective stratification in the transfer datasets resulted in a predicted gain in normalized remission of 17% to 30%. Blinded out-of-sample validations for methylphenidate (n = 41) and multimodal neurofeedback (n = 71) corroborated these findings, yielding a predicted gain in stratified normalized remission of 36% and 29%, respectively. CONCLUSIONS: This study introduces a clinically interpretable and actionable biomarker based on the iAPF assessed during resting-state electroencephalography. Our findings suggest that acknowledging neurobiological heterogeneity can inform stratification of patients to their individual best treatment and enhance remission rates.

The two decades brainclinics research archive for insights in neurophysiology (TDBRAIN) database.

In neuroscience, electroencephalography (EEG) data is often used to extract features (biomarkers) to identify neurological or psychiatric dysfunction or to predict treatment response. At the same time neuroscience is becoming more data-driven, made possible by computational advances. In support of biomarker development and methodologies such as training Artificial Intelligent (AI) networks we present the extensive Two Decades-Brainclinics Research Archive for Insights in Neurophysiology (TDBRAIN) EEG database. This clinical lifespan database (5-89 years) contains resting-state, raw EEG-data complemented with relevant clinical and demographic data of a heterogenous collection of 1274 psychiatric patients collected between 2001 to 2021. Main indications included are Major Depressive Disorder (MDD; N = 426), attention deficit hyperactivity disorder (ADHD; N = 271), Subjective Memory Complaints (SMC: N = 119) and obsessive-compulsive disorder (OCD; N = 75). Demographic-, personality- and day of measurement data are included in the database. Thirty percent of clinical and treatment outcome data will remain blinded for prospective validation and replication purposes. The TDBRAIN database and code are available on the Brainclinics Foundation website at www.brainclinics.com/resources and on Synapse at www.synapse.org/TDBRAIN .

Long-term effects of left frontal rTMS on EEG and ERPs in patients with depression.

Repetitive transcranial magnetic stimulation (rTMS) treatment for depression has been under investigation in many controlled studies over the last 20 years. Little is known about the neurobiological action of rTMS in patients. We therefore investigated pre- and post-treatment effects on QEEG, ERP's and behavior (BDI and NEO-FFI). rTMS treatment was applied in 8 subjects for an average of 21 sessions to the left Dorsolateral Prefrontal Cortex (left DLPFC). Clients were assessed on a QEEG and Oddball ERP evaluation pre- and post-treatment. Clients were stimulated over the left DLPFC with 10 Hz rTMS (100% MT). Furthermore, rTMS treatment was complimented by psychotherapy. All subjects showed full remission within 20 sessions and there was a significant reduction in depressive symptomatology (BDI score) after 10 and 15 sessions and a clear decrease in the Neuroticism and an increase on the extraversion scale of the NEO-FFI personality questionnaire. Pre- and post-QEEG measurements did not reveal treatment specific effects, but only an indirect right frontal increase in delta power. On the other hand, ERP measures did reveal treatment specific effects by showing an increased positivity in the post-treatment ERP's specifically left frontal. The P2 amplitude demonstrated a significant left frontal increase in amplitude, whereas for the negative N1 and N2 a significant decrease in amplitude was observed. The results of this pilot study demonstrate that rTMS can be a safe and efficacious treatment modality for depression. Furthermore, a specific left frontal increase in positivity for the ERP's was found (increased P2 and decreased N1 and N2 components) most likely related to the rTMS over the left DLPFC. Furthermore, there was no change in the alpha asymmetry lending support to the fact that frontal alpha asymmetry can be considered a trait marker for depression. The findings from this pilot study require future replication with larger sample sizes.