Souza, A. C. | bioRxiv Science

bioRxiv2026

EARLY-LIFE STRESS INDUCES SEXUALLY DIMORPHIC BRAIN AGING VIA MESOLIMBIC ALTERATIONS AND FRONTO-STRIATAL DYSFUNCTION

Prenatal stress influences brain development; however, its long-term, region-specific effects on brain aging in males and females remain insufficiently characterized. This study examined the impact of unpredictable mild prenatal stress on behavior, cognition, and maternal care in C57BL/6J mice at middle (12 months) and old (18 months) ages. Stressed dams showed fragmented, unpredictable maternal behaviors, creating a stressful postnatal environment without impairing caregiving capacity. Both male and female offspring were born with lower birth weights and showed rapid postnatal growth, a trajectory associated with central insulin resistance and hippocampal signaling deficits. Sex-specific behavioral differences emerged with age. Middle-aged stressed males exhibited anhedonia, which progressed to hyperactivity, stereotypy, and persistent spatial memory deficits in old age. These outcomes corresponded with accelerated fronto-striatal decline, likely mediated by insulin resistance and increased rigidity of medial prefrontal cortex structures due to diminished local estrogenic activity. In contrast, middle-aged stressed females displayed hypoactivity and reduced anxiety, later developing anhedonia in old age while maintaining hippocampus-dependent memory. In females, this pattern supports a model in which a neuroestrogen - and growth factor-dependent feedback loop transiently preserves hippocampal plasticity but compromises dopaminergic function in reward circuits. This balance may deteriorate with reproductive senescence. Both sexes retained cognitive flexibility, indicating domain-specific rather than global cognitive impairment. These findings demonstrate that excessive prenatal glucocorticoid exposure and unpredictable postnatal care produce a combined hormonal and metabolic insult, resulting in sexually divergent trajectories of brain aging. The results underscore the necessity of incorporating sex as a biological variable in fetal programming research across the lifespan.

neuroscience↗

bioRxiv2022

Multi-tasking Deep Network for Tinnitus Classification and Severity Prediction from Multimodal Structural Images

Subjective tinnitus is an auditory phantom perceptual disorder without an objective biomarker. Fast and efficient diagnostic tools will advance clinical practice by detecting or confirming the condition, tracking change in severity, and monitoring treatment response. Motivated by evidence of subtle anatomical or functional morphological information in magnetic resonance images (MRI) of the brain, we examined data-driven machine learning methods for joint tinnitus classification (tinnitus or no tinnitus) and tinnitus severity prediction. We propose a deep multi-task multi-modal framework for joint functionalities using structural MRI (sMRI) data. To leverage cross-information multimodal neuroimaging data, we integrated two modalities of 3-dimensional sMRI - T1 weighted (T1w) and T2 weighted (T2w) images. To explore the key components in the MR images that drove task performance, we segmented both T1w and T2w images into three different components - cerebrospinal fluid (CSF), grey matter (GM) and white matter (WM), and examined performance of each segmented image. Results demonstrate that our multimodal framework capitalizes on the information across both modalities (T1w and T2w) for the joint task of tinnitus classification and severity prediction. Our model outperforms existing learning-based and conventional methods in terms of accuracy, sensitivity, specificity, and negative predictive value.

neuroscience↗