Nicholas L. Balderston
· Ph.D.VerifiedUniversity of Pennsylvania · Rehabilitation Medicine
Active 2010–2026
About
Nicholas L. Balderston, Ph.D., is an Assistant Professor of Psychiatry at the University of Pennsylvania's Perelman School of Medicine. He is a faculty member at the Center for Neuromodulation in Depression and Stress, the Institute for Translational Medicine and Therapeutics, and the Penn Brain Science, Translation, Innovation, and Modulation Center. Dr. Balderston's research focuses on anxiety, utilizing psychophysiology, neuroimaging, and neuromodulation techniques to develop and test brain-behavior hypotheses aimed at understanding the mechanisms that mediate clinical anxiety. His work prior to joining the CNDS faculty included a postdoctoral fellowship at the NIMH Intramural Research Program working with Christian Grillon. He holds a B.A. in Psychology from the University of West Florida, an M.S. in Experimental Psychology, and a Ph.D. in Experimental Psychiatry/Neuroscience from the University of Wisconsin-Milwaukee.
Research topics
- Psychiatry
- Psychology
- Computer Science
- Medicine
- Data science
- Social psychology
- Clinical psychology
- Cognitive psychology
Selected publications
medRxiv · 2026-01-01
articleOpen accessABSTRACT Background An accelerated schedule of intermittent theta burst stimulation (aiTBS) has been shown to improve clinical efficacy of transcranial magnetic stimulation for bipolar disorder (BD) and major depressive disorder (MDD). We investigated the functional connectivity changes underpinning clinical effects of aiTBS on transdiagnostic treatment-resistant depression (TRD). Methods Data were collected from two studies: an open-label active aiTBS study for MDD and a double-blind, randomized control aiTBS study for BD. Thirty-four participants (18 female/16 male) with transdiagnostic TRD currently experiencing moderate to severe depressive episodes (Montgomery-Åsberg Rating Scale [MADRS] score ≥ 20). Participants received active (22 total; 12 BD/10MDD) or sham (12 BD) aiTBS delivered to personalized left dorsolateral prefrontal cortical targets. Participants completed MRI scans before and after ten sessions of active or sham aiTBS per day for five days. Within each aiTBS group (active/sham), connectivity changes within the default mode network (DMN) following aiTBS and their correlations with MADRS scores were evaluated. Results Immediately following aiTBS, active group members had lower within-DMN connectivity ( p = .01, d = –0.62) and lower MADRS scores ( p < .0001) than at baseline; these changes were correlated ( r = .47, p = .03). They also reported decreased insomnia ( p < .0001) and suicidality ( p < .0001). These changes were not present in the sham BD group ( p s = .29– .92). Conclusions aiTBS was associated with decreased within-DMN connectivity among people with transdiagnostic TRD, which could underlie depression improvement. The study is registered on ClinicalTrials.gov (study identifier NCT05228457 ). https://clinicaltrials.gov/study/NCT05228457
Biological Psychiatry · 2026-04-25
articleSenior authorBrain age prediction in generalized anxiety disorder using a convolutional neural network
Translational Psychiatry · 2026-05-23
articleOpen accessHigher predicted brain age difference has been associated with several psychiatric disorders. Generalized anxiety disorder (GAD) is associated with markers of accelerated aging. In this study, we determined brain predicted age difference (PAD) in individuals with GAD and healthy controls (HC) as well as group differences in PAD variability using voxel-wise structural MRI. The training dataset included 3511 controls, and the testing dataset included 1595 individuals with GAD and 4552 HC from the ENIGMA-Anxiety GAD Working Group. A convolutional neural network model using four input modalities per subject and a model ensemble approach was used to predict brain age. The PAD was then calculated by subtracting chronological age from the predicted age. Model performance was consistent with other image-based brain age prediction models with similar accuracy across the training set (mean absolute error (MAE) = 2.95 years) and HC in the testing set (MAE = 2.94). We found no evidence of accelerated brain aging in individuals with GAD compared to individuals without GAD, though we did find evidence for greater variation in PAD for individuals with GAD (Levene's test: W = 442.98, p < 0.001) and evidence for greater variability in PAD of those with GAD over 25 years of age. In several exploratory analyses, we found that symptom severity related significantly to PAD, even after controlling for medication and comorbid diagnoses, echoing previous brain age research. These findings underscore the need for consideration of heterogeneity and dimensionality of psychopathology when examining brain age predicted differences.
bioRxiv (Cold Spring Harbor Laboratory) · 2026-01-09
articleOpen accessAbstract Causal modulation of autonomic outflow could yield new therapeutic targets for autonomic hyperactivation. We employed three natural experiments in which different brain regions were targeted using transcranial magnetic stimulation (TMS) (n=139 sites, n=14 individuals), deep brain stimulation (n=392 sites, n=58 individuals), or low-intensity focused ultrasound (n=46 sites, n=23 individuals) with subsequent autonomic measurements. Using a human connectome database (n=1000) as a wiring diagram, we identified a convergent brain circuit that, when focally modulated, transiently reduces autonomic arousal. This circuit significantly resembled previously reported causal circuits for posttraumatic stress disorder (PTSD) and anxiety. In independent datasets, TMS to the autonomic arousal circuit reduced laboratory startle in healthy volunteers (n=28), lesions to this circuit reduced exaggerated startle in PTSD (n=193), and TMS to this circuit reduced anxiety-related autonomic symptoms in patients with clinically significant anxiety (n=30). Thus, the convergent circuit may serve as a potential neuromodulation target for autonomic hyperactivation.
343. Using Parameterized Search to Identify Reliable RTMS Targeting Methods
Biological Psychiatry · 2026-04-25
articleSenior authorBiological Psychiatry · 2026-04-25
articleBiological Psychiatry · 2026-04-25
articleAutonomic Outflow as a Rapid Read-Out of Brain Stimulation Targets for Anxious Arousal
Biological Psychiatry · 2026-04-25
articleTranscranial magnetic stimulation . · 2026-01-29
articleOpen accessBrain stimulation · 2025-01-01
articleOpen accessSenior authorConclusion:Based on these considerations, we present specific candidate TMS-EEG markers correlating with the excitability of specific circuits relevant to the expression of anxiety.We expect that this result will support the development of future more effective personalized brain stimulation paradigms for the treatment of anxiety.
Recent grants
Frequent coauthors
- 93 shared
Monique Ernst
National Institutes of Health
- 82 shared
Christian Grillon
National Institute of Mental Health
- 36 shared
Abigail Hsiung
Duke University
- 30 shared
Christian Grillon
National Institutes of Health
- 29 shared
Zhi‐De Deng
- 25 shared
Yvette I. Sheline
- 24 shared
Daniel S. Pine
The University of Texas Rio Grande Valley
- 22 shared
Neil Burgess
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