Biology subjects

Mayberg, H. S.

Publications and source records attributed to Mayberg, H. S..

10 recordsLinked to original sources

bioRxiv2026

Single neurons in the human substantia nigra encode social learning signals

Humans are remarkable at adapting to changing norms, yet we know little about how the human brain encodes these social signals at the single neuron level. Here, we recorded the activity of single neurons in the substantia nigra and globus pallidus in neurosurgical participants as they played an iterative ultimatum game versus human and computer avatars. Using computational modeling of behavior, we found that putative dopaminergic units in the substantia nigra tracked the valence of norm prediction errors, with greater encoding during gameplay with human versus computer avatars. Analogous analyses in the globus pallidus, a nucleus adjacent to the substantia nigra, found no significant effect. Our results identify a novel role for the substantia nigra in encoding social learning signals.

neuroscience↗

bioRxiv2025

Dopamine and serotonin transients predict depressive symptom relief following deep brain stimulation of human subcallosal cingulate cortex

Recent advances in deep brain stimulation (DBS) of the subcallosal cingulate (SCC) show promise in mitigating the symptoms of treatment-resistant depression (TRD) in humans1-3. Monoamines, such as dopamine and serotonin, mediate the effects of pharmacological treatments of depression. However, their roles in recovery following DBS remain elusive, largely due to technical limitations of measuring these neurotransmitters in the living human brain. Here, by leveraging machine learning-enhanced electrochemistry4-7, we show that dopamine and serotonin signaling following DBS to the SCC predicted later depressive symptom relief in humans with TRD. We found that both dopamine and serotonin levels increased following subtherapeutic intraoperative SCC stimulation, with each neurotransmitter showing selective responses to distinct decision-making tasks. Furthermore, acute dopamine increases predicted later mood improvements during a social decision-making task, while serotonin enhancement predicted faster responses during a non-social learning task longitudinally. Critically, changes in dopamine and serotonin levels during the social decision-making task jointly predicted depressive symptom remission at 6-month follow-up. These findings illustrate the contribution of both dopamine and serotonin signaling in predicting behavioral improvement and depressive symptom remission in humans with TRD. Such neurochemical plasticity may serve as potential mechanistic biomarkers for SCC DBS mechanism and TRD treatment response. Significance statementO_LIDopamine and serotonin levels increased following acute DBS to the SCC in humans. C_LIO_LIAcute dopamine and serotonin changes predicted later mood and response speed changes. C_LIO_LISustained TRD recovery was predicted by acute increases in both dopamine and serotonin estimates. C_LI

neuroscience↗

bioRxiv2024

Association of Bile Acids with Connectivity of Executive Control and Default Mode Networks in Patients with Major Depression

Objective: Bile acids may contribute to pathophysiologic markers of Alzheimers disease, including disruptions of the executive control network (ECN) and the default mode network (DMN). Cognitive dysfunction is common in major depressive disorder (MDD), but whether bile acids impact these networks in MDD patients is unknown. Methods: Resting state functional magnetic resonance imaging (fMRI) scans and blood measures of four bile acids from 74 treatment-naive adults with MDD were analyzed. Dorsolateral prefrontal cortex (DLPFC) seeds were used to examine connectivity of the ECN and posterior cingulate cortex (PCC) seeds were used for the DMN. Using a whole-brain analysis, the functional connectivity of these seeds was correlated with serum levels chenodeoxycholic acid (CDCA) and its bacterially-derived secondary bile acid, lithocholic acid (LCA). Results: CDCA levels were strongly and inversely correlated with connectivity between DLPFC regions of the ECN (R2= .401, p<.001). LCA levels were strongly and positively correlated with connectivity of the DLPFC and left inferior temporal cortex of the ECN (R2=.263, p<.001). The LCA/CDCA ratio was strongly and positively correlated with connectivity of the DLPFC with two components of the ECN: bilateral inferior temporal cortex and the left superior and inferior parietal lobules (all R2>.24, all p<.001). For the DMN, the LCA/CDCA ratio was strongly and negatively correlated with connectivity of the PCC with multiple bilateral insula regions (all R2>0.25, all p<.001). Conclusions: The relationship between LCA and CDCA levels and functional connectivity of the ECN and DMN suggests potential shared pathophysiologic processes between Alzheimers disease and MDD.

neuroscience↗

bioRxiv2024

Refining Brain Stimulation Therapies: An Active Learning Approach to Personalization

Brain stimulation holds promise for treating brain disorders, but personalizing therapy remains challenging. Effective treatment requires establishing a functional link between stimulation parameters and brain response, yet traditional methods like random sampling (RS) are inefficient and costly. To overcome this, we developed an active learning (AL) framework that identifies optimal relationships between stimulation parameters and brain response with fewer experiments. We validated this framework through three experiments: (1) in silico modeling with synthetic data from a Parkinsons disease model, (2) in silico modeling with real data from a non-human primate, and (3) in vivo modeling with a real-time rat optogenetic stimulation experiment. In each experiment, we compared AL models to RS models, using various query strategies and stimulation parameters (amplitude, frequency, pulse width). AL models consistently outperformed RS models, achieving lower error on unseen test data in silico (p<0.0056, N=1,000) and in vivo (p=0.0036, N=20). This approach represents a significant advancement in brain stimulation, potentially improving both research and clinical applications by making them more efficient and effective. Our findings suggest that AL can substantially reduce the cost and time required for developing personalized brain stimulation therapies, paving the way for more effective and accessible treatments for brain disorders.

neuroscience↗

bioRxiv2024

Deep brain stimulation induces white matter remodeling and functional changes to brain-wide networks

Deep brain stimulation (DBS) is an emerging therapeutic option for treatment resistant neurological and psychiatric disorders, most notably depression. Despite this, little is known about the anatomical and functional mechanisms that underlie this therapy. Here we targeted stimulation to the white matter adjacent to the subcallosal anterior cingulate cortex (SCC-DBS) in macaques, modeling the location in the brain proven effective for depression. We demonstrate that SCC-DBS has a selective effect on white matter macro- and micro-structure in the cingulum bundle distant to where stimulation was delivered. SCC-DBS also decreased functional connectivity between subcallosal and posterior cingulate cortex, two areas linked by the cingulum bundle and implicated in depression. Our data reveal that white matter remodeling as well as functional effects contribute to DBSs therapeutic efficacy.

neuroscience↗

bioRxiv2023

Neural Interoceptive Processing is Modulated by Deep Brain Stimulation for Treatment Resistant Depression

BackgroundA critical advance in depression research is to clarify the hypothesized role of interoceptive processing in neural mechanisms of treatment efficacy. This study tests whether cortical interoceptive processing, as indexed by the heartbeat-evoked potential (HEP), is modulated by deep brain stimulation (DBS) to the subcallosal cingulate (SCC) for treatment resistant depression (TRD). MethodsEight patients with TRD were enrolled in a study of SCC DBS safety and efficacy. Electroencephalography (EEG) and symptom severity measures were sampled in a laboratory setting over the course of a six-month treatment protocol. The primary outcome measure was an EEG-derived HEP, which reflects cortical processing of heartbeat sensation. Cluster-based permutation analyses were used to test the effect of stimulation and time in treatment on the HEP. The change in signal magnitude after treatment was correlated with change in depression severity as measured by the 17-item Hamilton Depression Rating Scale. ResultsHEP amplitude was greater after 24 weeks of treatment (t(7)=-4.40, p=.003, g=-1.38, 95% Cl [-2.3, -0.42]), and this change was inversely correlated with latency of treatment response (rho = -0.75, 95% Cl [-0.95, -0.11], p=.03). An acute effect of DBS was also observed, but as a decrease in HEP amplitude (t(6) =6.66, p<.001, g=2.19, 95% Cl [0.81, 3.54]). HEP differences were most pronounced over left posterior sensors from 405-425 ms post-stimulus. ConclusionBrain-based evidence substantiates a theorized link between interoception and depression, and suggests an interoceptive contribution to the mechanism of treatment efficacy with deep brain stimulation for severe depression.

neuroscience↗

bioRxiv2022

CRF neurons of the BNST promote resilience by blunting the internal experience of aversion.

The Bed Nucleus of the Stria Terminalis (BNST) has been studied extensively for its coordination of opposing adaptive behaviors. Previously, we uncovered a critical role for Corticotropin-Releasing Factor (CRF)-expressing neurons of the oval nucleus of the BNST (BNSTovCRF) in maintaining resilience to social defeat through stress-dependent self-sustaining neuronal activity.1 However, as mice develop resilience, it is not well-understood how affect and motivation are altered to achieve adaptive behavior in the face of ongoing threat. Here, we explore how this neuronal population exerts a powerful influence over internal state in various stress contexts to promote adaptive social responding. Using cell-type-selective optogenetics, a suite of behavioral paradigms, and transgenic Crf-ChR2 mice, we show that BNSTovCRF neurons induce resiliency by altering the encoding of psychosocial stress, enhancing the appetitiveness of social interaction, and enhancing tolerability to physical stress. Adaptive responses to stress typically emanate as a response to negative internal states by external stimuli; here, we show that in resilient mice, stressful environments are less aversive than susceptible mice, suggesting a different motivational capacity to endure stress in this group. Thus, we describe a novel role for BNSTovCRF neurons in resisting the emotional effects of cumulative stress by reducing the internal experience of aversion

neuroscience↗

bioRxiv2021

Dynamic functional connectivity links with treatment response of electroconvulsive therapy in major depressive disorder

BackgroundElectroconvulsive Therapy (ECT) is one of the most effective treatments for major depressive disorder (DEP). There is recently increasing attention to evaluate ECTs effect on resting-state functional magnetic resonance imaging (rs-fMRI). This study aims to compare rs-fMRI of DEP patients with healthy participants, investigate whether dynamic functional network connectivity network (dFNC) estimated from rs-fMRI predicts the ECT outcome, and explore the effect of ECT on brain network states. MethodResting-state fMRI data were collected from 119 patients with depression or DEP (76 females), and 61 Healthy (HC) participants (34 females) with an age mean of 52.25 (N=180) years old. The pre-ECT and post-ECT Hamilton Depression Rating Scale (HDRS) were 25.59{+/-}6.14 and 11.48{+/-}9.07, respectively. Twenty-four independent components from default mode (DMN) and cognitive control network (CCN) were extracted using group-independent component analysis from pre-ECT and post-ECT rs-fMRI. Then, the sliding window approach was used to estimate the pre-and post-ECT dFNC of each participant. Next, k-means clustering was separately applied to pre-ECT dFNC and post-ECT dFNC to assess three distinct states from each participant. We calculated the amount of time each individual spends in each state, called occupancy rate or OCR. Next, we compared OCR values between HC and DEP participants. We also calculated the partial correlation between pre-ECT OCRs and HDRS change while controlling for age, gender, number of treatment, and site. Finally, we evaluated the effectiveness of ECT by comparing pre-and post-ECT OCR of DEP and HC participants. ResultsThe main findings include: 1) DEP patients had significantly lower OCR values than the HC group in a state, where connectivity between CCN and DMN was relatively higher than other states (corrected p= 0.015), 2) Pre-ECT OCR of state, with more negative connectivity between CCN and DMN components, predicted the HDRS changes (R=0.23 corrected p=0.03). This means that those DEP patients who spend less time in this state showed more HDRS change, and 3) The post-ECT OCR analysis suggested that ECT increased the amount of time DEP patients spend in state 2 (corrected p=0.03). Finally, we found ECT increases the total traveled distance in DEP. ConclusionOur finding suggests that dFNC features, estimated from CCN and DMN, show promise as a predictive biomarker of the ECT outcome of DEP patients. Also, this study identified a possible underlying mechanism associated with the ECT effect in DEP patients.

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bioRxiv2020

Indoxyl sulfate, a gut microbiome-derived uremic toxin, is associated with psychic anxiety and its functional magnetic resonance imaging-based neurologic signature

BackgroundIt is unknown whether indoles, metabolites of tryptophan that are derived entirely from bacterial metabolism in the gut, are associated with symptoms of depression and anxiety. MethodsSerum samples (baseline, 12 weeks) were drawn from participants (n=196) randomized to treatment with cognitive behavioral therapy (CBT), escitalopram, or duloxetine for major depressive disorder. ResultsBaseline indoxyl sulfate abundance was positively correlated with severity of psychic anxiety and total anxiety and with resting state functional connectivity to a network that processes aversive stimuli (which includes the subcallosal cingulate cortex (SCC-FC), bilateral anterior insula, right anterior midcingulate cortex, and the right premotor areas). The relation between indoxyl sulfate and psychic anxiety was mediated only through the metabolites effect on the SCC-FC with the premotor area. Baseline indole abundances were unrelated to post-treatment outcome measures, which suggests that CBT and antidepressant medications relieve anxiety via mechanisms unrelated to gut microbiota. ConclusionsA peripheral gut microbiome-derived metabolite was associated with altered neural processing and with psychiatric symptom (anxiety) in humans, which provides further evidence that gut microbiome disruption can contribute to neuropsychiatric disorders that may require different therapeutic approaches.

neuroscience↗

bioRxiv2019

Pilot Study of Metabolomic Clusters as State Markers of Major Depression and Outcomes to CBT Treatment

Major depressive disorder (MDD) is a common and disabling syndrome with multiple etiologies that is defined by clinically elicited signs and symptoms. In hopes of developing a list of candidate biological measures that reflect and relate closely to the severity of depressive symptoms, so-called \"state-dependent\" biomarkers of depression, this pilot study explored the biochemical underpinnings of treatment response to cognitive behavior therapy (CBT) in medication-freeMDD outpatients. Plasma samples were collected at baseline and week 12 from a subset of MDD patients (N=26) who completed a course of CBT treatment as part of the Predictors of Remission in Depression to Individual and Combined Treatments (PReDICT) study. Targeted metabolomic profiling using the the AbsoluteIDQ(R) p180 Kit and LC-MS identified eight \"co-expressed\" metabolomic modules. Of these eight, three were significantly associated with change in depressive symptoms over the course of the 12-weeks. Metabolites found to be most strongly correlated with change in depressive symptoms were branched chain amino acids, acylcarnitines, methionine sulfoxide, and -aminoadipic acid (negative correlations with symptom change) as well as several lipids, particularly the phosphatidlylcholines (positive correlation). These results implicate disturbed bioenergetics as an important state marker in the pathobiology of MDD. Exploratory analyses contrasting remitters to CBT versus those who failed the treatment further suggest these metabolites may serve as mediators of recovery during CBT treatment. Larger studies examining metabolomic change patterns in patients treated with pharmacotherapy or psychotherapy will be necessary to elucidate the biological underpinnings of MDD and the -specific biologies of treatment response.

neuroscience↗