Biology subjects

Guinjoan, S. M.

Publications and source records attributed to Guinjoan, S. M..

8 recordsLinked to original sources

bioRxiv2026

Dose-Dependent Effects of Low-Intensity Focused Ultrasound on Human Deep White Matter Tracts

Background: Low-intensity focused ultrasound (LIFU) is emerging as a method for anatomically specific, noninvasive, and reversible neuromodulation of deep brain structures relevant to psychopathology. A key requirement for clinical translation is evidence of graded target engagement. We examined whether LIFU applied to deep white matter tracts produces dose-dependent functional connectivity changes in healthy adults. Methods: In this preregistered, double-blind, randomized study, 35 healthy adults underwent LIFU targeting (80 s, 10% duty cycle, estimated ISPPA 2.26 W/cm2, 0.5 MHz, in a {theta}-burst pattern) of individually modeled right thalamo-prefrontal white matter tracts under two dose conditions: one and three consecutive sonications. Dose-dependent changes in resting-state functional connectivity were examined during a 30-minute poststimulation period in 31 participants. Results: One sonication acutely increased right thalamic functional connectivity with the left thalamus (28 voxels; Z = 5.48, Cohen's d = 0.61), whereas three sonications decreased connectivity with the right dorsolateral prefrontal cortex (Z = -4.05, Cohen's d = -0.45). Poststimulation time-course analysis revealed a 3-LIFU-specific linear recovery trend in the left cerebellum (Z = 4.14, d = 0.48), reflecting initial suppression followed by progressive recovery across 30 minutes. Stronger thalamo-prefrontal structural connectivity was associated with condition-specific functional connectivity changes (left frontal pole; F = 14.73, {rho}2 = 0.41). Conclusions: These findings provide initial human evidence that LIFU is well tolerated and produces dose-dependent changes in functional connectivity associated with deep white matter tract stimulation, informing parameter selection for future circuit-based mechanistic and clinical studies.

neuroscience↗

bioRxiv2026

Distinct Multimodal Imaging Correlates of Depression in Middle-Aged Adults With and Without a Family History of Alzheimer Disease

BackgroundDepression is associated with risk for late-onset Alzheimers disease (LOAD), but its underlying pathogenesis in at-risk individuals remains unclear. We examined multimodal imaging correlates of depressive symptoms in cognitively normal middle-aged offspring of patients with LOAD (O-LOAD) compared with control individuals without LOAD history up to a 4th degree of kinship (HC). MethodsParticipants (n=58; 52{+/-}3 years; 74% female) underwent assessment with the Beck Depression Inventory-II (BDI), structural MRI, resting-state fMRI, FDG-PET, and PiB-PET. Resting-state fMRI data were available for 28 O-LOAD and 24 HC; PET data for 24 O-LOAD and 22 HC. General linear models tested associations between imaging measures and BDI, including group interactions. ResultsIn O-LOAD, higher BDI scores were associated with reduced cortical thickness in the left postcentral gyrus. Resting-state fMRI revealed significant group-by-BDI interactions involving cingulate and orbitofrontal networks. In O-LOAD, greater depressive symptom severity was associated with reduced cingulate connectivity across distributed corticolimbic, prefrontal, insular, occipital, and cerebellar regions ({beta} range -0.10 to -0.18). In HC, depressive symptoms were associated with reduced right orbitofrontal and somatosensory-medial orbitofrontal connectivity ({beta}=-0.13), with divergent patterns of cingulate connectivity. FDG-PET showed no significant associations with depressive symptoms. PiB-PET demonstrated regionally specific associations between amyloid signal and BDI in HC, involving an inverse pattern in anterior and posterior insular cortices. ConclusionsDepressive symptoms in middle-aged individuals at familial risk for LOAD are associated with distinct structural and functional alterations, involving circuitry subserving salience and reward, and suggesting early network-level mechanisms linking affective symptoms with vulnerability to neurodegeneration.

neuroscience↗

bioRxiv2026

Disrupted Emotional Neural Synchrony in Schizophrenia Revealed by Intersubject Correlation of Naturalistic fMRI

BackgroundSchizophrenia is marked by impairments in emotional processing and social cognition, yet traditional neuroimaging paradigms often lack the ecological validity to capture these deficits in real-world contexts. MethodsIn this study, we used intersubject correlation (ISC) analysis of functional MRI data to examine shared neural representations of naturalistic visual narratives in individuals with schizophrenia and healthy controls. Participants viewed short films designed to evoke happy, sad, and emotionally neutral responses, allowing us to compare how synchronized brain activity varied with emotional content across and within groups. ResultsHealthy controls showed greater ISC in regions associated with affective salience, emotion recognition, and social understanding, including the amygdala, insula, and temporal cortices. In contrast, participants with schizophrenia displayed higher synchrony in visual, subcortical, and frontal areas, suggesting a reliance on perceptual and executive systems. To isolate the effects of emotion from general visual processing, we compared ISC during emotional clips relative to neutral videos. This revealed significantly reduced synchrony in the bilateral amygdala in patients, highlighting a core dysfunction in affective engagement. Interestingly, neutral stimuli elicited unexpectedly strong synchronization in frontal and limbic regions in the schizophrenia group, possibly reflecting altered salience attribution to ambiguous or emotionally ambiguous content. ConclusionsThese results point to a functional reorganization of affective processing in schizophrenia, where impaired limbic recruitment is accompanied by compensatory engagement of perceptual and cognitive control networks. ISC during naturalistic stimulation emerges as a powerful tool for capturing subtle disruptions in shared emotional experience in psychiatric populations.

neuroscience↗

bioRxiv2025

Structural Connectivity Correlates of Response to Electroconvulsive Therapy in Treatment-Resistant Depression

BackgroundElectroconvulsive therapy (ECT) is the most effective option for treatment resistant depression (TRD). In this study, we sought to explore if structural connectivity of limbic networks has an association with response to ECT. MethodsWe studied 23 patients with TRD who underwent a course of bifrontal ECT, employing probabilistic tractography at baseline to assess structural connectivity between the thalamus (THA), posterior (PCC), subgenual cingulate cortices, anterior insula (aINS), amygdala and orbitofrontal and ventrolateral prefrontal cortices, hypothesizing that these hubs participate in the formation and refractoriness of depression symptoms. We also include 21 healthy subject as controls group (HC). ResultsConnectivity between left THA and left PCC was related to both baseline depression severity (R=0.504; p= 0.017) and clinical response (R=0.452; p=0.004). Right aINS-prefrontal connectivity was associated with less clinical response. Structural connectivity was globally higher in patients than in HC (F=2.488; p=0.007). ConclusionsThe association of ECT response with stronger structural connectivity between hubs supporting self-referential bodily experience as well as autobiographical memory encoding and retrieval deserves exploration as a predictor in persons with TRD. In turn, the right aINS is a major hub for the salience network and is involved in repetitive negative mentation. Stronger structural connectivity of this region may be a heuristically valid biomarker for refractory TRD. We discuss the potential of the present findings for the design of anatomically precise neuromodulation interventions that would be useful to treat TRD while circumventing cognitive side effects of ECT.

neuroscience↗

bioRxiv2024

Clinical Response to Neurofeedback in Major Depression Relates to Subtypes of Whole-Brain Activation Patterns During Training

Major Depressive Disorder (MDD) poses a significant public health challenge due to its high prevalence and the substantial burden it places on individuals and healthcare systems. Real-time functional magnetic resonance imaging neurofeedback (rtfMRI-NF) shows promise as a treatment for this disorder, although its mechanisms of action remain unclear. This study investigated whole-brain response patterns during rtfMRI-NF training to explain interindividual variability in clinical efficacy in MDD. We analyzed data from 95 participants (67 active, 28 control) with MDD from previous rtfMRI-NF studies designed to increase left amygdala activation through positive autobiographical memory recall. Significant symptom reduction was observed in the active group (t=-4.404, d=-0.704, p<0.001) but not in the control group (t=-1.609, d=-0.430, p=0.111). However, left amygdala activation did not account for the variability in clinical efficacy. To elucidate the brain training process underlying the clinical effect, we examined whole-brain activation patterns during two critical phases of the neurofeedback procedure: activation during the self-regulation period, and transient responses to feedback signal presentations. Using a systematic process involving feature selection, manifold extraction, and clustering with cross-validation, we identified two subtypes of regulation activation and three subtypes of brain responses to feedback signals. These subtypes were significantly associated with the clinical effect (regulation subtype: F=8.735, p=0.005; feedback response subtype: F=5.326, p=0.008; subtypes interaction: F=3.471, p=0.039). Subtypes associated with significant symptom reduction were characterized by selective increases in control regions, including lateral prefrontal areas, and decreases in regions associated with self-referential thinking, such as default mode areas. These findings suggest that large-scale brain activity during training is more critical for clinical efficacy than the level of activation in the neurofeedback target region itself. Tailoring neurofeedback training to incorporate these patterns could significantly enhance its therapeutic efficacy.

neuroscience↗

bioRxiv2023

Whole-brain Mechanism of Neurofeedback Therapy: Predictive Modeling of Neurofeedback Outcomes on Repetitive Negative Thinking in Depression

Real-time fMRI neurofeedback (rtfMRI-NF) has emerged as a promising intervention for psychiatric disorders, yet its clinical efficacy remains underexplored due to limited controls and an incomplete mechanistic understanding. This study aimed to elucidate the whole-brain mechanisms underpinning the effects of rtfMRI-NF on repetitive negative thinking in depression. In a double-blind randomized controlled trial, forty-three depressed individuals underwent NF training targeting the functional connectivity (FC) between the posterior cingulate cortex and the right temporoparietal junction, linked to rumination severity. Participants were randomly assigned to active or sham groups, with the sham group receiving synthesized feedback mimicking real NF signal patterns. The active group demonstrated a significant reduction in brooding rumination scores (p<0.001, d=-1.52), whereas the sham group did not (p=0.503, d=- 0.23). While the target FC did not show discernible training effects or group differences, we found that the interaction between brain activities during regulation and the response to the feedback signal was the critical factor in explaining treatment outcomes. Connectome-based predictive modeling (CPM) analysis, incorporating this interaction, successfully predicted rumination changes across both groups. The FCs significantly contributing to the prediction were distributed across broad brain regions, notably the frontal control, salience network, and subcortical reward processing areas. These results underscore the importance of considering the interplay between brain regulation activities and brain response to the feedback signal in understanding the therapeutic mechanisms of rtfMRI-NF. The study not only affirms the potential of rtfMRI-NF as a therapeutic intervention for repetitive negative thinking in depression but also highlights the need for a more nuanced understanding of the whole-brain mechanisms contributing to its efficacy.

neuroscience↗

bioRxiv2023

The unique face of anxious depression: Increased sustained threat circuitry response during fear acquisition

BackgroundSensitivity to threat with dysregulation of fear learning is thought to contribute to the development of psychiatric disorders, including anxiety disorders (AD) and major depressive disorder (MDD). However, fewer studies have examined fear learning in MDD than in AD. Nearly half of individuals with MDD have an AD and the comorbid diagnosis has worse outcomes. The current study used propensity matching to examine the hypothesis that AD+MDD shows greater neural correlates of fear learning than MDD, suggesting that the co-occurrence of AD+MDD is exemplified by exaggerated defense related processes. Methods195 individuals with MDD (N = 65) or AD+MDD (N=130) were recruited from the community and completed multi-level assessments, including a Pavlovian fear learning task during functional imaging. ResultsMDD and AD+MDD showed significantly different patterns of activation for [CSplus- CSminus] in the medial amygdala ({eta}p2=0.009), anterior insula ({eta}p2=0.01), dorsolateral prefrontal cortex ({eta}p2=0.002), dorsal anterior cingulate cortex ({eta}p2=0.01), mid-cingulate cortex ({eta}p2=0.01) and posterior cingulate cortex ({eta}p2=0.02). These differences were driven by greater activation to the CS+ in late conditioning phases in ADD+MDD relative to MDD. ConclusionsAD+MDD showed a pattern of increased sustained activation in regions identified with fear learning. Effects were consistently driven by the threat condition, further suggesting fear signaling as the emergent target process. Differences emerged in regions associated with salience processing, attentional orienting/conflict, and self-relevant processing. These findings help to elucidate the fear signaling mechanisms involved in the pathophysiology of comorbid anxiety and depression, thereby highlighting promising treatment targets for this prevalent treatment group.

neuroscience↗

bioRxiv2023

Trait repetitive negative thinking in depression is associated with functional connectivity in negative thinking state, not resting state

Resting-state functional connectivity (RSFC) has been proposed as a potential indicator of repetitive negative thinking (RNT) in depression. However, identifying the specific functional process associated with RSFC alterations is challenging, and it remains unclear whether alterations in RSFC for depressed individuals are directly related to the RNT process or to individual characteristics distinct from the negative thinking process per se. To investigate the relationship between RSFC alterations and the RNT process in individuals with major depressive disorder (MDD), we compared RSFC with functional connectivity during an induced negative-thinking state (NTFC) in terms of their predictability of RNT traits and associated whole-brain connectivity patterns using connectome-based predictive modeling (CPM) and connectome-wide association (CWA) analyses. Thirty-six MDD participants and twenty-six healthy control participants underwent both resting state and induced negative thinking state fMRI scans. Both RSFC and NTFC distinguished between healthy and depressed individuals with CPM. However, trait RNT in depressed individuals, as measured by the Ruminative Responses Scale-Brooding subscale, was only predictable from NTFC, not from RSFC. CWA analysis revealed that negative thinking in depression was associated with higher functional connectivity between the default mode and executive control regions, which was not observed in RSFC. These findings suggest that RNT in depression involves an active mental process encompassing multiple brain regions across functional networks, which is not represented in the resting state. Although RSFC indicates brain functional alterations in MDD, they may not directly reflect the negative thinking process.

neuroscience↗