Transcranial magnetic stimulation (TMS) is an effective intervention approach for patients with psychiatric disorders such as major depressive disorder (MDD) and general anxiety disorder (GAD). This case study highlights how BNA™ can guide personalized TMS treatment protocols to maximize patient outcomes.
Psychiatric disorders exhibit diverse symptom profiles and underlying neurobiological mechanisms, making them multifaceted conditions. Utilizing a one-size-fits-all approach to TMS treatment may fail to consider the inherent variations among patients. Moreover, it is crucial to track the progress of patients undergoing TMS therapy to evaluate its efficacy and potentially adjust interventions if needed. Brain networks analytics (BNA™) presents an innovative method for facilitating baseline assessment, tailoring TMS protocols, and assessing treatment outcomes. By employing EEG-based technology, clinicians can analyze the electrophysiological dynamics in the brain before and after TMS treatment. By focusing on specific neural circuits displaying electrophysiological deviations, clinicians can personalize the TMS protocol to ameliorate symptoms. Comparing pre- and post-treatment brain functions allows clinicians to gain insights into the neural changes associated with symptom improvement, providing objective evidence of treatment effectiveness.
The Case
At the outset of treatment, a 20-year-old male was coping with MDD, GAD, and substance abuse. Following the assessment of baseline BNA™ data, the Delray Center for Brain Science implemented a personalized TMS protocol. This customized approach involved administering fast stimulation to the dorsolateral prefrontal cortex and applying slow-frequency stimulation to the right parietal lobe. Upon completion of the treatment after 36 TMS treatment sessions, significant alleviation of the patient’s depressive symptoms was observed, as evidenced by a reduction in the Patient Health Questionnaire (PHQ-9) score from 19 to 8. Furthermore, his Anxiety symptomatology reduced on the General Anxiety Disorder scale from 14 to 7. Notable behavioral improvements in inhibitory control were also observed.
BNA™ Results
Resting State – Quantitative EEG Analysis Results
BNA’s quantitative analysis of the resting state task revealed notable overactivity in the relative delta band within the frontotemporal and posterior regions. Increases in slow wave activity, such as the delta band, are commonly observed in patients with MDD1,2. Furthermore, the patient displayed heightened relative beta power in the parietal regions during the baseline assessment. This pattern of brain activity is frequently observed in individuals diagnosed with MDD and comorbid anxiety disorders 3, as is evident in this case. Moreover, during the initial BNA™ recording, the patient exhibited increased hemispheric asymmetry in the frontal regions. This pattern has been reported in studies investigating MDD4. Encouragingly, by the second visit, all of these patterns had shown regulation towards healthy levels.
Auditory Oddball ERP Results
The results show before and after customized TMS treatment.
The patient showed a noticeable increase in auditory neural consistency from the first to the second recording. Neural consistency refers to the stability and reliability of neural activity patterns over time within an individual’s brain. It is the ability of the brain to consistently activate specific neural circuits or networks in response to the same stimulus across repeated trials. High neural consistency suggests robust and reliable neural processing, while low neural consistency may indicate variability or instability in the underlying neural processes. The observed increase in neural consistency is in line with the significant behavioral improvements, showing faster reaction times, and lower response variability while maintaining good accuracy by the second visit.
Visual Go No-Go ERP Results
LEFT: Screenshot of the Neural Consistency score from the summary report at the first and second visit. RIGHT: The percentage of correct rejections at the first and second visit.
The N200 latency score at visit 1 and visit 2 as visualized in the BNA™ ERP Report.
Consistent with the findings from the auditory oddball task, the patient exhibited a slight increase in neural consistency during the visual go no-go task, as well. Notably, during the baseline assessment, the N200 component displayed a delay, but this delay was resolved by the second visit. The N200 component is widely recognized for its association with impulse control, a crucial factor in addictive behavior. When experiencing a delay, it may suggest challenges in inhibitory control and executive functioning5 as had been reported for this patient at baseline. The impression of improved inhibitory control is further support by the reduction in commission errors by the second visit.
Physician Conclusion
The treating physician found the BNA™ results to be representative of the clinical condition of the patient while providing additional insights into the exact underlying neural dynamics. Based on these findings the physician customized the TMS protocol to target the frontal lobe with fast stimulation (18 Hz pulses) and slow-frequency (1 Hz pulses) to the parietal lobe. This protocol achieved a substantial improvement both on a symptom level, as well as on an electrophysiological level as measured by BNA™. The objective evidence of treatment effectiveness provided by BNA™ measurements strengthens the case for its use in monitoring treatment outcomes and optimizing interventions. Finally, continuous monitoring of progress using objective tools may also enhance patient compliance in the prescribed treatment regiments.
The treating clinician at the Delray Center for Brain Science noted on this case:
“The use of BNA™-guided TMS treatment for this patient proved to be highly successful and ultimately life-changing. The patient had many co-occurring symptoms at baseline and had become frustrated with their lack of response to numerous prior treatments. The information provided by the BNA™ helped us and the patient to gain a better understanding of the patient’s unique electrophysiological profile and how this was contributing to various symptoms and maladaptive behaviors in their life. We customized the TMS protocol based on the BNA™ results and the patient was completely committed to the process because it was guided by an objective neurological assessment tool. Following 36 treatments of TMS, the patient experienced alleviation of their depression and anxiety, was able to obtain an employment opportunity, and most importantly, felt far more comfortable socializing with others.”
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References
- McVoy M, Aebi ME, Loparo K, et al. Resting-state quantitative electroencephalography demonstrates differential connectivity in adolescents with major depressive disorder. J Child Adolesc Psychopharmacol. 2019;29(5):370-377. doi:10.1089/cap.2018.0166
- Begić D, Popović-Knapić V, Grubišin J, et al. Quantitative electroencephalography in schizophrenia and depression. Psychiatr Danub. 2011;23(4):355-362. http://www.ncbi.nlm.nih.gov/pubmed/22075736
- Grin-Yatsenko VA, Baas I, Ponomarev VA, Kropotov JD. Independent component approach to the analysis of EEG recordings at early stages of depressive disorders. Clinical Neurophysiology. 2010;121(3):281-289. doi:10.1016/j.clinph.2009.11.015
- Quinn CR, Rennie CJ, Harris AWF, Kemp AH. The impact of melancholia versus non-melancholia on resting-state, EEG alpha asymmetry: Electrophysiological evidence for depression heterogeneity. Psychiatry Res. 2014;215(3):614-617. doi:10.1016/j.psychres.2013.12.049
- Sokhadze E, Stewart C, Hollifield M, Tasman A. Event-Related Potential Study of Executive Dysfunctions in a Speeded Reaction Task in Cocaine Addiction. J Neurother. 2008;12(4):185-204. doi:10.1080/10874200802502144
