Biology subjects

Sourty, M.

Publications and source records attributed to Sourty, M..

4 recordsLinked to original sources

bioRxiv2026

Acute lysergic acid diethylamide induces a time-dependent shift toward hippocampal control of default mode network reorganization

Background Classical psychedelics induce profound changes in brain function, yet the temporal organization of these effects remains incompletely understood. Methods We investigated the effects of acute lysergic acid diethylamide (LSD) on large-scale brain connectivity in nine male Long-Evans rats using resting-state functional magnetic resonance imaging. Following a 15-min baseline acquisition, rats received LSD (500 g/kg, i.p.), and imaging continued during two consecutive 15-min post-injection periods. Network reorganization was assessed using independent component analysis (ICA), seed-to-voxel mapping, stationary seed-to-seed connectivity, dynamic graph-based metrics, and dynamic causal modeling. Results LSD produced widespread but regionally heterogeneous changes across default mode network related, cortical, striatal, thalamic, sensory, and limbic systems. During the early post-injection window, ICA revealed a predominance of increased functional coupling, while dynamic analyses showed prominent fluctuations in hippocampal coupling strength and medial frontal network centrality. Dynamic causal modeling identified a false discovery rate-corrected reduction in retrosplenial-to-infralimbic influence, accompanied by a broader descriptive pattern of reduced posterior- and hippocampal-to-frontal coupling. During the later window, ICA showed a relative shift toward connectivity decreases, while complementary analyses revealed more selective hippocampal and parahippocampal involvement. Conclusions Across complementary analyses, acute LSD induced a temporally structured reorganization of brain hierarchy, characterized by an early weakening of directed cortical interactions followed by a later shift toward hippocampal-centered network control. These findings identify a dynamic shift in effective network organization and provide a mechanistic framework for psychedelic-induced default mode network reconfiguration.

neuroscience↗

bioRxiv2025

Network Signatures of Disease Progression and Core Symptoms in Dementia with Lewy Bodies Distinct from Alzheimer's Disease

BackgroundResting-state fMRI studies in dementia with Lewy bodies (DLB) and Alzheimers disease (AD) have described connectivity alterations in large-scale brain networks. However, little is known about functional changes across disease stages, particularly in DLB. ObjectiveTo investigate functional connectivity of key brain networks in DLB patients at different stages, compare them to AD and healthy controls (HC) and examine associations with core clinical symptoms. MethodsNinety DLB patients, comprising 63 with mild cognitive impairment (MCI-DLB) and 27 with dementia (d-DLB), along with 25 AD patients (11 MCI-AD and 14 d-AD) and 34 HC underwent clinical, neuropsychological and resting-state fMRI assessment. ROI-to-ROI analyses were performed using the CONN toolbox, (pFDR<0.05). ResultsThe DLB group showed reduced functional connectivity within the salience network (SN) compared with HC, but did not differ from AD. While MCI-DLB patients showed no significant differences, d-DLB patients showed reduced SN and frontoparietal network (FPN) connectivity compared to HC and AD. SN connectivity was associated with severity of fluctuations and FPN connectivity with REM sleep behavior disorder and cognitive decline in DLB. In contrast, in the AD group, decreased default mode network (DMN) connectivity was associated with lower MMSE scores. ConclusionSN and FPN connectivity impairments relate to disease progression and core clinical features in DLB, whereas DMN connectivity is linked to cognitive decline in AD. These distinct patterns highlight divergent paths of network dysfunction in the two diseases, offering insight into their underlying mechanisms and clinical expression.

neuroscience↗

bioRxiv2025

Exploring sex-specific alterations in early Alzheimer's disease using network MRI analyses

Alzheimers disease (AD) is characterized by the accumulation of amyloid-{beta} plaques and tau neurofibrillary tangles, leading to progressive cognitive decline. Subtle cognitive and neural adaptations mark the preclinical stage of AD, occurring years before mild cognitive impairment and AD diagnosis. Throughout the continuum of AD, women ([~]60% of AD cases) demonstrate faster rates of cognitive decline, greater hippocampal atrophy, and more extensive tau pathology compared to men. This is particularly evident in early AD phases. Therefore, investigating early sex-specific changes is crucial for identifying biomarkers and developing targeted interventions. In the present study, we conducted a longitudinal investigation on the AppNL-F/MAPT double knock-in (dKI) mouse model, to identify sex-specific resting-state functional connectivity (FC) patterns associated with early cognitive deficits. Male and female wild-type and dKI mice were tested for associative and long-term memory deficits, followed by resting-state functional magnetic resonance imaging to examine the default mode network (DMN) connectivity at 2 and 4 months of age. Female dKI mice exhibited earlier and more pronounced memory impairments, with deficits apparent at 2 months, while male deficits emerged at 4 months. FC analyses revealed distinct sex-specific alterations within DMN and between DMN hubs and memory processing nodes. Notably, female dKI mice showed hypersynchrony between the retrosplenial cortex (RSP) and key memory-related regions such as the entorhinal cortex (ENT) and hippocampus (HIP), but also towards subcortical regions overlapping thalamic nuclei, amygdala, and substantia nigra. Meanwhile, male dKI mice exhibited hypoconnectivity along RSP-HIP axis, RSP-reuniens nucleus, and RSP-sensorimotor cortex. Our data particularly highlight sexually dimorphic RSP-ENT and RSP-HIP connectivity. These results underscore the critical role of sex in shaping neural network reorganization and cognitive decline during preclinical AD. These findings position neural network connectivity as a sensitive biomarker of early memory dysfunction and highlight the need for sex-specific investigations and potentially tailored therapeutic strategies in AD.

neuroscience↗

bioRxiv2020

A functional-structural connectivity metric detects ipsilateral connections with distinct functional specialisation in each hemisphere

We introduce a connectomics metric that integrates information on structural connectivity (SC) from diffusion MRI tractography and functional connectivity (FC) from resting-state functional MRI, at individual subject level. The metric is based on the ability of SC to broadly predict FC using a simple linear predictive model; for each connection in the brain, the metric quantifies the deviation from that model. For the metric to capture underlying physiological properties, we minimise systematic measurement errors and processing biases in both SC and FC, and address several challenges with the joint analysis. This also includes a data-driven normalisation approach. The combined metric may provide new information by indirectly assessing white matter structural properties that cannot be inferred from diffusion MRI alone, and/or complex interregional neural interactions that cannot be inferred from functional MRI alone. To demonstrate the utility of the metric, we used young adult data from the Human Connectome Project to examine all bilateral pairs of ipsilateral connections, i.e. each left-hemisphere connection in the brain was paired with its right-hemisphere homologue. We detected a minority of bilateral pairs where the metric value is significantly different across hemispheres, which we suggest reflects cases of ipsilateral connections that have distinct functional specialisation in each hemisphere. The pairs with significant effects spanned all cortical lobes, and also included several cortico-subcortical connections. Our findings highlight the potential in a joint analysis of structural and functional measures of connectivity, both for clinical applications and to help in the interpretation of results from standard functional connectivity analysis. Significance StatementBased on the notion that structure predicts function, the scientific community sought to demonstrate that structural information on fibre bundles that connect brain regions is sufficient to estimate the strength of interregional interactions. However, an accurate prediction using MRI has proved elusive. This paper posits that the failure to predict function from structure originates from limitations in measurement or interpretation of either diffusion MRI (to assess fibre bundles), fMRI (to assess functional interactions), or both. We show that these limitations can be nevertheless beneficial, as the extent of divergence between the two modalities may reflect hard-to-measure properties of interregional connections, such as their functional role in the brain. This provides many insights, including into the division of labour between hemispheres.

neuroscience↗