Biology subjects

Auerbach, R. P.

Publications and source records attributed to Auerbach, R. P..

6 recordsLinked to original sources

bioRxiv2026

Feasibility of Precision Functional Mapping in Youth Multi-Echo fMRI Data

There is growing interest in identifying brain function underlying adolescent cognition, personality, and psychopathology. One promising approach is Precision Functional Mapping (PFM) of MRI functional connectivity, a data-intensive method for characterizing individualized brain networks. Foundational studies suggest that PFM can detect stable, task-responsive, and clinically relevant networks. Studies demonstrate that both functional connectivity reliability and network stability improve with increasing data quantity, although benchmark estimates vary across populations, preprocessing pipelines, and MRI acquisition approaches. Accordingly, it is important to understand how PFM performs in adolescent populations and with multi-echo fMRI acquisition. In a case study of eight youth (ages 10-17), we applied PFM to 80-minutes of combined resting-state and task-based fMRI. The resulting networks were highly modular, consistent with adult templates, and without evidence of structural registration artifacts. Functional connectivity reliability compared favorably to prior single-echo studies, with multivariate similarity and ICC estimates showing early stabilization around 10-15 minutes despite continued improvement with additional data. Trait-like stability increased gradually with acquisition time and a Bayesian algorithm (MS-HBM) demonstrated higher stability than Infomap. Across algorithms, stability was greatest in sensory networks (somatomotor, auditory, visual). Furthermore, when evaluating task-based responses to threat and attention paradigms, only the auditory network consistently benefited from individualized mapping over group template networks. These findings suggest that, with constrained scanning time, PFM is especially effective for characterizing sensory and perceptual networks in adolescents. Bridging the methodological divide between deeply sampled individual cases and large-scale developmental studies will require further innovation and validation.

neuroscience↗

bioRxiv2026

Investigating the Dynamic Relationship Between Anxiety and Spatial Memory Using Autonomous Ecological Momentary Assessment

Anxiety has been extensively studied in relation to memory, yet its dynamic association with spatial episodic memory in naturalistic clinical settings remains largely unexplored. We developed an anxiety-spatial-memory EMA protocol (asm-EMA) and deployed it in 30 epilepsy patients undergoing inpatient EEG monitoring, delivering combined momentary anxiety ratings and a validated spatial memory task pseudo-randomly every 90-150 minutes across multiple days. Subject-level asm-EMA means and session-to-session variability both correlated significantly with standard neuropsychological assessments, supporting the clinical validity of our design. Elevated within-person STAI-6 was selectively associated with faster retrieval responses, yet spatial memory accuracy was independent of all three anxiety measures, suggesting a shift in response strategy rather than memory impairment. Within-day anxiety showed short-term carryover between consecutive sessions, with little persistence beyond the next session. The asm-EMA protocol provides a feasible, autonomous framework for capturing moment-to-moment anxiety-memory dynamics in naturalistic settings.

neuroscience↗

bioRxiv2026

When attention falters: brain, breathing, and behavioral signals of lapses in interoceptive attention

Mindlbody practices like meditation and yoga involve paying attention to breathing sensations. During these practices, individuals report "interoceptive lapses," moments when attention drifts away from internal bodily sensations. While lapses in attention to the external world have been widely studied, little is known about the physiological and neural mechanisms of interoceptive lapses. Interoceptive lapses may share markers with exteroceptive lapses--such as reaction time variability and default-mode network (DMN) connectivity--but may also depend on distinct brain systems and breathing physiology. Here we examined behavioral, physiological and neural signals preceding lapses in a sample of 93 adolescents enriched for GAD and depression symptoms. Participants performed a 20-minute breath counting task in the fMRI scanner with simultaneous breath recordings. Lapses were defined as moments when counting errors occurred. The sample was split into training and validation sets to test machine learning models predicting attentional lapses. The strongest predictors were timing and variability of button responses (AUCs > 0.75). Breathing variability and breathing-behavior synchronization showed smaller but generalizable predictive value (AUCs < 0.65). Whole-brain connectivity models also predicted lapses (AUC {approx} 0.65), incorporating the DMN, dorsal and ventral attention, and somatomotor networks. Further, models that included brain connectivity marginally outperformed behavior-only models. Comparisons to previous exteroceptive findings indicate some common markers (e.g., reaction time variability) and some unique markers (e.g., selective perceptual coupling with attentional networks). Although limited by the clinical sample and lack of a control task, these results highlight brain-body markers of interoceptive attention that may inform real-time monitoring during mind-body interventions.

neuroscience↗

bioRxiv2025

Limited generalizability of dynamic fMRI correlates of adolescent rumination

Rumination, or perseverative negative self-referential thinking, is a hallmark of depression. In adults, a dynamic resting-state fMRI model of trait rumination was recently identified through predictive modelling. In adolescents, a development period during which rumination and depression increase, the neurobiological correlates of ruminative thinking are less clear. In the current preregistered study, we examine dynamic connectivity correlates of self-reported rumination in the largest sample of adolescents to date (n = 443, containing clinical and non-clinical individuals). Notably, the adult model failed to generalize to our sample. In addition, linear models trained on default-mode network (DMN) connectivity, as well as whole-brain connectome models, failed to generalize to held-out data. In an exploratory random forest analysis, we found significant prediction performance of a model where increased variability between DMN-cerebellum, DMN-dorsal attention network, and DMN-DMN connections was nominally associated with higher rumination. However, the model did not generalize to an external sample with lower rumination scores and a distinct scanner protocol. Our findings illustrate the difficulty of characterizing the neurodevelopment of risk factors for depression.

neuroscience↗

bioRxiv2024

Mindfulness-based Neurofeedback: A Systematic Review of EEG and fMRI studies

Neurofeedback concurrent with mindfulness meditation may reveal meditation effects on the brain and facilitate improved mental health outcomes. Here, we systematically reviewed EEG and fMRI studies of mindfulness meditation with neurofeedback (mbNF) and followed PRISMA guidelines. We identified 10 fMRI reports, consisting of 177 unique participants, and 9 EEG reports, consisting of 242 participants. Studies of fMRI focused primarily on downregulating the default-mode network (DMN). Although studies found decreases in DMN activations during neurofeedback, there is a lack of evidence for transfer effects, and the majority of studies did not employ adequate controls, e.g. sham neurofeedback. Accordingly, DMN decreases may have been confounded by general task-related deactivation. EEG studies typically examined alpha, gamma, and theta frequency bands, with the most robust evidence supporting the modulation of theta band activity. Both EEG and fMRI mbNF have been implemented with high fidelity in clinical populations. However, the mental health benefits of mbNF have not been established. In general, mbNF studies would benefit from sham-controlled RCTs, as well as clear reporting (e.g. CRED-NF).

neuroscience↗

bioRxiv2022

Targeting default mode network connectivity with mindfulness-based fMRI neurofeedback: A pilot study among adolescents with affective disorder history

Adolescents experience alarmingly high rates of major depressive disorder (MDD), however, gold-standard treatments are only effective for ~50% of youth. Accordingly, there is a critical need to develop novel interventions, particularly ones that target neural mechanisms believed to potentiate depressive symptoms. Directly addressing this gap, we developed a mindfulness-based fMRI neurofeedback (mbNF) for adolescents that targets default mode network (DMN) hyperconnectivity, which has been implicated in the onset and maintenance of MDD. In this proof-of-concept study, adolescents (n = 9) with a lifetime history of depression and/or anxiety were administered clinical interviews and self-report questionnaires, and then, each participants DMN and central executive network (CEN) were personalized using a resting state fMRI localizer. After the localizer scan, adolescents completed a brief mindfulness training followed by a mbNF session in the scanner wherein they were instructed to volitionally reduce DMN relative to CEN activation by practicing mindfulness meditation. Several promising findings emerged. First, mbNF successfully engaged the target brain state during neurofeedback; participants spent more time in the target state with DMN activation lower than CEN activation. Second, in each of the nine adolescents, mbNF led to significantly reduced within-DMN connectivity, which correlated with post-mbNF increases in state mindfulness. Last, a reduction of within-DMN connectivity mediated the association between better mbNF performance and increased state mindfulness. These findings demonstrate that personalized mbNF can effectively and non-invasively modulate the intrinsic networks known to be associated with the emergence and persistence of depressive symptoms during adolescence.

neuroscience↗