About

Jennifer R. Goldschmied is an Assistant Professor of Psychiatry at the Hospital of the University of Pennsylvania within the Department of Psychiatry at the Perelman School of Medicine. She completed her B.A. in Psychology at the University of Pennsylvania in 2006, followed by an M.S. in Clinical Psychology from the University of Michigan in 2012, and earned her Ph.D. in Clinical Psychology from the University of Michigan in 2016. Her clinical expertise includes insomnia, anxiety, and major depressive disorder. Her research focuses on sleep, neuroplasticity, and major depressive disorder, with particular interest in sleep slow-wave activity, glymphatic clearance during sleep, and neuroplasticity mechanisms. She has contributed to understanding sleep disturbances in depression and developing biomarkers related to sleep and mental health. Her work also explores innovative methods such as wearable EEG during IVF and machine learning classification of depression. Dr. Goldschmied has authored multiple publications in sleep medicine and psychiatry, emphasizing the intersection of sleep physiology and mental health.

Research topics

• Psychology
• Psychiatry
• Clinical psychology
• Medicine
• Audiology

Selected publications

• Selective disruption of sleep slow-waves increases motor cortical excitability in major depressive disorder

  Clinical Neurophysiology · 2026-04-26

  articleOpen access1st authorCorresponding

  OBJECTIVE: Major depressive disorder (MDD) may involve dysregulation of excitatory/inhibitory balance. Because sleep slow-waves facilitate homeostatic downscaling of excitatory synaptic strength, this study examined whether slow-wave disruption (SWD) could alter motor cortical excitability in individuals with and without MDD. METHODS: Thirty-seven adults (13 healthy controls [HC]; 24 with MDD) completed two overnight laboratory sessions (baseline and SWD, order counterbalanced). Slow-waves were reduced using auditory stimulation. Motor cortical excitability was assessed the following morning using transcranial magnetic stimulation (TMS)-generated single- and paired-pulse motor evoked potentials (MEPs). RESULTS: SWD increased MEPs during both single-pulse and paired-pulse TMS in individuals with MDD, whereas HC showed a pattern of decreased MEPs. At baseline, both groups exhibited reliable intracortical facilitation (ICF) and inhibition (ICI). Following SWD, facilitation patterns were preserved in both groups, while inhibitory effects were weakened in the HC but preserved in the MDD group. Relative values of ICF and ICI were unchanged following SWD in both groups. CONCLUSIONS: SWD increased motor cortical excitability in individuals with MDD, consistent with disruption of sleep-dependent synaptic downscaling. Because relative ICF and ICI remained unchanged despite shifts in raw MEP amplitude, these findings suggest that the heightened excitability may be driven by α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid (AMPA)-mediated mechanisms. SIGNIFICANCE: Slow-wave modulation may represent a non-pharmacologic approach to increasing motor cortical excitability and normalizing excitatory/inhibitory balance in MDD.

  PublisherDOI

• Novel TMS-derived metrics enable machine learning classification of major depressive disorder

  NPP—Digital Psychiatry and Neuroscience · 2026-01-12

  articleOpen accessSenior author

  Abstract No validated biomarker currently exists for early detection or personalized treatment of major depressive disorder (MDD). Transcranial magnetic stimulation (TMS) is widely used in clinical and research settings and holds promise for biomarker discovery. We assessed two novel TMS-derived cortical excitability metrics, $$\delta$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mi>δ</mml:mi> </mml:math> and $$\varrho$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mi>ϱ</mml:mi> </mml:math> , for distinguishing individuals with MDD from healthy controls. Motor-evoked potentials (MEPs) were recorded from the left abductor pollicis brevis during TMS of the right primary motor cortex in twenty-six unmedicated MDD patients and seventeen never-depressed controls. $$\delta$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mi>δ</mml:mi> </mml:math> and $$\varrho$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mi>ϱ</mml:mi> </mml:math> were computed from peak-to-peak MEP amplitudes. A Gradient Boosting classifier predicted diagnostic status using raw MEPs, $$\delta$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mi>δ</mml:mi> </mml:math> and $$\varrho$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mi>ϱ</mml:mi> </mml:math> , or their combination. While MEPs alone were non-predictive, $$\delta$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mi>δ</mml:mi> </mml:math> and $$\varrho$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mi>ϱ</mml:mi> </mml:math> significantly improved accuracy. Combining MEPs with $$\delta$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mi>δ</mml:mi> </mml:math> and $$\varrho$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mi>ϱ</mml:mi> </mml:math> yielded 83.3% accuracy and 82.3% balanced accuracy. These results suggest $$\delta$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mi>δ</mml:mi> </mml:math> and $$\varrho$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mi>ϱ</mml:mi> </mml:math> effectively capture neurophysiological alterations in MDD and support their potential as candidate biomarkers for MDD.

  PublisherOA PDFDOI

• Sleep health and mental health: A position statement from the National Sleep Foundation

  Sleep Health · 2026-04-01

  article
  PublisherDOI

• Perseverative Thinking in Depression and Insomnia

  CBT: science into practice · 2025-01-01

  book-chapterSenior author
  PublisherDOI

• Investigating Links Between Callous Traits and Slow-Wave Sleep

  ScholarlyCommons (University of Pennsylvania) · 2025-09-15

  otherOpen accessSenior author

  Slow-wave sleep (SWS) is essential for physical recovery and emotional regulation (Shapiro et al., 1981; Santos et al., 2021). Additionally, SWS has been posited to be reduced in those with major depressive disorder (MDD) (Benca et al., 1992). Some externalizing traits of depression include aggression and irritability, which overlap with psychopathic traits, which have also been linked to altered sleep patterns (Rahafar et al., 2022; Genunchi, M., 2015). This study focused on exploring these traits and their relationship to SWS in individuals with MDD. Given that sex differences often play a role in both depression and psychopathy, this study also investigated differences between males and females (Plante et al., 2012; Sanz-García et al., 2021).

  Publisher

• CBT-I can be delivered by a range of healthcare providers

  SLEEP · 2025-06-24

  article1st authorCorresponding
  PublisherDOI

• Treatment of Insomnia with Zaleplon in HIV+ Significantly Improves Sleep and Depression

  Psychopharmacology Bulletin · 2025-08-12 · 6 citations

  articleOpen access1st authorCorresponding

  More than 50% of individuals who are HIV positive report insomnia, which can reduce HIV treatment adherence, impair quality of life, and contribute to metabolic dysfunction. Major depressive disorder is also highly comorbid in this population, leading to further impairment. There is evidence that treating insomnia may improve not only sleep, but depression and metabolic function, as well. The present study aimed to examine the effects of pharmacotherapeutic treatment of insomnia on sleep, depression, and metabolic functioning in individuals with HIV. 20 individuals with asymptomatic seropositive HIV and comorbid insomnia and depression were administered zaleplon for 6 weeks. Insomnia severity was assessed using the Insomnia Severity Index and Epworth Sleepiness Scale, and depression severity was assessed using the Quick Inventory of Depression, both prior to treatment and 6 weeks post treatment. Metabolomic changes were assessed using a comprehensive platform measuring ~2000 lipid features and polar metabolites. Linear mixed effects models demonstrated that 6 weeks of treatment with zaleplon significantly improved symptoms of both insomnia and depression. Metabolomic analyses also demonstrated that changes in insomnia severity were associated with significant changes in key branched chain amino acid metabolites. Our results show that improvement in insomnia is associated with reduced depressive symptoms and beneficial metabolomic changes. Additionally, changes in key branched chain amino acid metabolites following treatment may serve as useful biomarkers of treatment response.

  PublisherOA PDFDOI

• Effects of acute sleep deprivation and recovery sleep on cognitive performance in depressed individuals

  Journal of Psychiatric Research · 2025-09-26

  articleOpen access
  PublisherOA PDFDOI

• Sleep Slow-Wave Activity Modulation as a Potential Therapeutic Target to Enhance Cortical Excitability in Major Depression

  SSRN Electronic Journal · 2024-01-01

  preprintOpen access1st authorCorresponding
  PublisherDOI

• Seasonal variation in mood among individuals with and without bipolar disorder

  Journal of Affective Disorders · 2024-10-22 · 4 citations

  articleOpen access1st authorCorresponding
  PublisherOA PDFDOI

Recent grants

• Investigating the Role of Slow-wave Activity as a Marker of Impaired Plasticity in Major Depressive Disorder

  NIH · $732k · 2019–2024

Frequent coauthors

• Philip Gehrman

  University of Pennsylvania

  36 shared

• Elaine M. Boland

  California University of Pennsylvania

  22 shared

• Patricia J. Deldin

  15 shared

• Philip Cheng

  Henry Ford Health + Michigan State University Health Sciences

  11 shared

• Emma Palermo

  McLean Hospital

  9 shared

• Roseanne Armitage

  University of Michigan–Ann Arbor

  9 shared

• Michael E. Thase

  California University of Pennsylvania

  7 shared

• Hengyi Rao

  University of Pennsylvania

  6 shared