Biology subjects

Kogler, L.

Publications and source records attributed to Kogler, L..

4 recordsLinked to original sources

bioRxiv2026

Menstrual cycle phase and premenstrual symptoms in relation with the stress response: an fMRI study

Objective: Women with premenstrual syndrome (PMS) experience affective lability, irritability, depressed mood, and anxiety during the late luteal phase of the menstrual cycle. Stress reactivity may contribute to the development of these symptoms, yet neural correlates remain unexplored. We examined neural, behavioral and endocrine stress responses across menstrual cycle phases in women with and without PMS. Methods: 26 women with PMS and 24 women without PMS participated in two fMRI sessions, during the mid-follicular (days 5 to 11) and late-luteal phases (days -7 to -1). Participants completed the Montreal Imaging Stress Task (MIST). Subjective stress ratings and salivary cortisol were collected at six time points before and after stress induction. Stress-related brain activation was assessed using whole-brain and region-of-interest analyses. Results: Subjective stress ratings increased as expected from before to after the MIST, with no group or phase differences. Salivary cortisol was significantly higher during the mid-follicular phase, with no group effect or significant pre-post MIST difference. While the stress task elicited activation patterns in stress-related regions, whole-brain analysis revealed no significant effects of group (PMS vs. no PMS) or menstrual cycle phase (follicular vs. luteal) on the neural stress response. Considering premenstrual symptom severity as a predictor revealed significant group-by-symptom severity interactions in the right inferior frontal gyrus and the right superior temporal gyrus. Conclusion: Using a within-subject repeated-measures design, we found neural responses to psychosocial stress to be stable across menstrual cycle phases. Individual differences in symptom severity may nevertheless be associated with differences in stress-related brain activation.

neuroscience↗

bioRxiv2026

Stronger brain responses to acute stress reflect greater everyday stress variability

Laboratory stress tasks are widely used to assess individual differences in acute stress reactivity, yet it remains unclear how these responses correspond to stress experienced in everyday life. Here, we combined the Montreal imaging stress task (MIST) with ecological momentary assessment (EMA) over three months to assess acute and everyday stress in 67 healthy women. Greater within-person variability in everyday stress, but not average stress levels, were associated with stronger overall stress-related brain responses (b = 0.73, p = .039), with a whole-brain association particularly evident in the bilateral caudate (rROI = .32, pcluster.FWE < .001). Greater everyday stress variability was also associated with stronger stress-related functional connectivity between the ventromedial prefrontal cortex (vmPFC) and parietal and posterior medial regions (pcluster.FWE < .001). We conclude that acute neural stress responses relate more closely to fluctuations in perceived stress than to how stressed an individual feels on average. This suggests that laboratory stress tasks capture acute stress responsivity that is distinct from average stress exposure, highlighting the importance of considering what these tasks measure when interpreting individual differences in acute stress responses.

neuroscience↗

bioRxiv2025

Social stress, cortisol awakening response and sex: Impact on hippocampus and amygdala volume

ObjectiveVolumes of the hippocampus and amygdala, both major hubs for neural stress regulation amongst others, are influenced by social stressors, cortisol awakening response (CAR) and sex, i.e. psychological and physiological stress factors. Importantly, the interplay of these different factors in affecting the morphology of both brain regions remains unclear. This study aimed to elucidate the intricate influence of these factors on grey matter volumes (GMV) of the hippocampus and amygdala. MethodsWe analyzed associations between structural brain data, self-reported chronic social stress (including subscales on social tension, social overload, lack of social recognition and social isolation) and CAR of 83 healthy participants (40 females) with multiple regression analyses. ResultsIn males, but not females, higher social tension predicted lower bilateral hippocampus GMV. In individuals not showing the typical CAR, higher social tension predicted reduced bilateral hippocampus GMV. Amygdala GMV was also related to social stress and CAR, with social overload associated with reduced amygdala GMV in individuals not showing the typical CAR, while the opposite pattern emerged in those with an atypical CAR. ConclusionsChronic social stress is associated with hippocampus and amygdala volumes, interacting with CAR and sex. The brain morphology in males and in individuals with atypical CAR seems to be more vulnerable to chronic social stress. Our findings enhance our understanding of how brain architecture, social stress, CAR patterns and sex shape individual stress responses.

neuroscience↗

bioRxiv2020

Connectivity patterns of task-specific brain networks allow individual prediction of cognitive symptom dimension of schizophrenia and link to molecular architecture

BackgroundDespite the marked inter-individual variability in the clinical presentation of schizophrenia, it remains unclear the extent to which individual dimensions of psychopathology may be reflected in variability across the collective set of functional brain connections. Here, we address this question using network-based predictive modeling of individual psychopathology along four data-driven symptom dimensions. Follow-up analyses assess the molecular underpinnings of predictive networks by relating them to neurotransmitter-receptor distribution patterns. MethodsWe investigated resting-state fMRI data from 147 schizophrenia patients recruited at seven sites. Individual expression along negative, positive, affective, and cognitive symptom dimensions was predicted using relevance vector machine based on functional connectivity within 17 meta-analytic task-networks following a repeated 10-fold cross-validation and leave-one-site-out analyses. Results were validated in an independent sample. Networks robustly predicting individual symptom dimensions were spatially correlated with density maps of nine receptors/transporters from prior molecular imaging in healthy populations. ResultsTen-fold and leave-one-site-out analyses revealed five predictive network-symptom associations. Connectivity within theory-of-mind, cognitive reappraisal, and mirror neuron networks predicted negative, positive, and affective symptom dimensions, respectively. Cognitive dimension was predicted by theory-of-mind and socio-affective-default networks. Importantly, these predictions generalized to the independent sample. Intriguingly, these two networks were positively associated with D1 dopamine receptor and serotonin reuptake transporter densities as well as dopamine-synthesis-capacity. ConclusionsWe revealed a robust association between intrinsic functional connectivity within networks for socio-affective processes and the cognitive dimension of psychopathology. By investigating the molecular architecture, the present work links dopaminergic and serotonergic systems with the functional topography of brain networks underlying cognitive symptoms in schizophrenia.

neuroscience↗