Biology subjects

Baracchini, G.

Publications and source records attributed to Baracchini, G..

8 recordsLinked to original sources

bioRxiv2025

Locus coeruleus degeneration is associated with cortical tau deposition and cognitive decline in older adults at familial risk of Alzheimer's disease

INTRODUCTIONThe locus coeruleus (LC) is among the first sites of tau pathology in Alzheimers disease (AD) and may seed neocortical tau. METHODSWe used longitudinal neuromelanin-sensitive MRI to assess LC integrity in vivo in a cohort of cognitively unimpaired older adults with familial risk of AD in relation to tau and amyloid PET and long-term cognitive trajectories. RESULTSWe showed that both LC integrity at baseline and its rate of degeneration over time independently predicted a neocortical pattern of tau deposition. In keeping with the known function of the LC, neuropsychological tests showed that LC integrity at baseline predicted changes in attention. Finally, we found that longitudinal LC degeneration correlated with memory decline in people with elevated neocortical amyloid burden. DISCUSSIONOur findings underscore the importance of LC in AD pathogenesis. Longitudinal measurement of LC degeneration may help distinguish trajectories of age-related cognitive decline and early AD.

neuroscience↗

bioRxiv2025

Compositional Recombination Relies on a Distributed Cortico-Cerebellar Network

Human cognition depends on the ability to flexibly recombine existing knowledge in new ways. Although this capacity for compositionality has traditionally been attributed to cortical networks, its broader neural basis remains unclear. Here, we combined dimensionality reduction of task-based fMRI with recurrent neural network modelling to dissociate two processes underlying compositional cognition: the recruitment of specialised components; and the more general process of recombination. Across 87 participants performing a well-established compositional task, component processes were supported by domain-selective cortical and anterior cerebellar regions, whereas recombination engaged a distributed cortico-cerebellar network that was low-dimensional, highly integrated, and generalised across contexts. Similar functional signatures were also observed in recurrent neural networks trained to perform multiple cognitive tasks, suggesting that low-dimensional recombination is a general solution for flexible compositional cognition. Our findings revise existing models of compositional cognition by highlighting cortico-cerebellar interactions as a mechanism for flexible, integrative task generalisation.

neuroscience↗

bioRxiv2025

Transdiagnostic Profiles of BOLD Signal Variability in Autism and Schizophrenia Spectrum Disorders: Associations with Cognition and Functioning

BackgroundAutism spectrum disorder (autism) and schizophrenia spectrum disorders (schizophrenia) exhibit overlapping social and neurocognitive impairment and considerable neurobiological heterogeneity. Blood-oxygen-level-dependent (BOLD) signal variability captures the brains moment-to-moment fluctuations, offering a dynamic marker of neural flexibility that is sensitive to cognitive capacity. This study aimed to examine intra-regional BOLD signal variability during rest and task across schizophrenia, autism, and typically developing controls (TDC) to explore transdiagnostic patterns of brain signal variability and their relationship with cognitive and functional outcomes. MethodsIntra-regional BOLD variability, measured by mean squared successive difference (MSSD), was obtained from resting-state and Empathic Accuracy task fMRI in 176 SSD, 89 autism, and 149 TDC participants. ANCOVAs, controlling for age, sex, and motion, assessed group differences in regional and network-level BOLD variability and dimensional associations with social cognition, neurocognition, social functioning, and symptom severity. ResultsBoth autism and schizophrenia exhibited lower BOLD signal variability than TDC across rest and task, with reduced variability observed in somatomotor, visual, and auditory networks (pFDR < 0.01). Greater network variability was positively associated with better social cognitive, neurocognitive, and functional scores across the sample. Resting-state variability showed stronger group-based differences and cognitive associations than task-based variability. ConclusionsBOLD signal variability is positively associated with social cognition, neurocognition, and social functioning across groups, suggesting that variability impacts cognitive efficiency and behaviour. Reduced variability in autism and schizophrenia may indicate similar patterns of neural rigidity among these related conditions, positioning BOLD variability as a potential biomarker for neural flexibility and a valuable target for future transdiagnostic clinical interventions.

neuroscience↗

bioRxiv2025

Cerebellar and Subcortical Contributions to Working Memory Manipulation

Working memory enables us to temporarily store and manipulate information, a crucial function for problem-solving. However, most working memory models emphasize cortical interactions ignoring contributions from subcortical and cerebellar regions. Given the dense connectivity between the cerebellum, subcortex, and cortex, we hypothesize that these regions provide unique contributions during working memory manipulation. We tested this hypothesis using functional Magnetic Resonance Imaging (fMRI) to measure blood oxygen-level dependent (BOLD) activity during a mental rotation task, where participants judged whether rotated pairs of three-dimensional stimuli were identical. Our results revealed a distributed network spanning the cortex, subcortex, and cerebellum that differentiates rotated from non-rotated stimuli and correct from incorrect responses. BOLD recruitment in these regions increased with larger angles of rotation. We observed delayed responses in premotor, subcortical, and cerebellar regions during incorrect trials. These findings suggest that cerebellar and subcortical regions support working memory manipulation, highlighting a broader mechanism by which distributed brain regions interact to coordinate higher cognitive functions.

neuroscience↗

bioRxiv2024

Thalamic Control Over Laminar Cortical Dynamics Across Conscious States

The human brain must support both stable and flexible neural dynamics in order to adapt to changing contexts that are inherently non-linear. The thalamus has been linked to the coordination of these opposing dynamical regimens in the cerebral cortex, however existing methodological approaches have not integrated sufficient neurobiological details with a sensitive measure of neural dynamics that permits sensitivity to time-series non-linearities. Inspired by the field of fluid dynamics, we use a novel approach to show that spontaneous fMRI data exhibits non-trivial fluctuations in predictability over time, akin to a river that has sections of smooth and predictable (laminar) versus rough and unpredictable (non-laminar) fluid flow. We use a combination of pharmacological fMRI, macaque electrophysiology and a large-scale biophysical model of the thalamocortical system to provide robust evidence that the thalamus provides versatile control over globally linear dynamics in the cerebral cortex that characterize conscious states.

neuroscience↗

bioRxiv2023

The biological role of local and global fMRI BOLD signal variability in human brain organization

Variability drives the organization and behavior of complex systems, including the human brain. Understanding the variability of brain signals is thus necessary to broaden our window into brain function and behavior. Few empirical investigations of macroscale brain signal variability have yet been undertaken, given the difficulty in separating biological sources of variance from artefactual noise. Here, we characterize the temporal variability of the most predominant macroscale brain signal, the fMRI BOLD signal, and systematically investigate its statistical, topographical and neurobiological properties. We contrast fMRI acquisition protocols, and integrate across histology, microstructure, transcriptomics, neurotransmitter receptor and metabolic data, fMRI static connectivity, and empirical and simulated magnetoencephalography data. We show that BOLD signal variability represents a spatially heterogeneous, central property of multi-scale multi-modal brain organization, distinct from noise. Our work establishes the biological relevance of BOLD signal variability and provides a lens on brain stochasticity across spatial and temporal scales.

neuroscience↗

bioRxiv2023

Ventromedial Frontoinsular Connectivity is Associated with Long-term Smoking Behavior Change in Aging

A central question in the field of cognitive aging and behavioral neuroscience is what enables some individuals to successfully change their behavior more than others? Smoking is a significant risk factor for cognitive decline, particularly in vulnerable populations, including those who are at an elevated risk for Alzheimers disease (AD). Developing effective smoking reduction strategies is therefore a public health priority. The goal of the current study is to better understand the brain mechanisms underlying long-term smoking behavior change in cognitively normal, but at-risk, older adults. Neuroimaging and human lesional studies have implicated the insula and its functional network in subjective interoceptive awareness of cigarette craving and smoking-cue reactivity. We sought to characterize the extent to which anterior insular resting-state functional connectivity MRI predicted long-term smoking reduction (mean: 2.7 years, range 8 months - 4 years) using a seed-to-voxel approach. Twenty-three (18 women; 26% APOE4 carriers; 61.5 years, SD = 3.7) cognitively unimpaired older individuals who smoked cigarettes at their baseline visit and have a first-degree family history of AD (at least one parent or multiple siblings affected) were included from a prospective longitudinal cohort, PREVENT-AD (Pre-symptomatic Evaluation of Experimental or Novel Treatments for Alzheimer Disease) in the current study. We found that reduced long-term smoking behavior was associated with diminished functional connectivity between bilateral anterior insula and ventromedial prefrontal cortex (vmPFC). In a second pre-registered replication study within a larger, independent sample of one hundred and eighteen cognitively normal older adults who smoked cigarettes at baseline from the UK Biobank (73 women; 27.9 % APOE4 carriers; 60.3 years, SD = 2.7), we found that baseline diminished resting-state functional connectivity between anterior insula and vmPFC predicted long-term smoking reduction (mean 5.2 years; ranging from 3 years to 7 years). To our knowledge, this is the largest study to examine the neural substrates of long-term smoking cessation in human aging. Our results suggest that frontoinsular circuits may be a therapeutic target for smoking reduction and disease prevention in older adults at risk for AD.

neuroscience↗

bioRxiv2021

Functional architecture of the aging brain

The intrinsic functional organization of the brain changes into older adulthood. Age differences are observed at multiple spatial scales, from global reductions in modularity and segregation of distributed brain systems, to network-specific patterns of dedifferentiation. Whether dedifferentiation reflects an inevitable, global shift in brain function with age, circumscribed, experience dependent changes, or both, is uncertain. We employed a multi-method strategy to interrogate dedifferentiation at multiple spatial scales. Multi-echo (ME) resting-state fMRI was collected in younger (n=181) and older (n=120) healthy adults. Cortical parcellation sensitive to individual variation was implemented for precision functional mapping of each participant, while preserving group-level parcel and network labels. ME-fMRI processing and gradient mapping identified global and macroscale network differences. Multivariate functional connectivity methods tested for microscale, edge-level differences. Older adults had lower BOLD signal dimensionality, consistent with global network dedifferentiation. Gradients were largely age-invariant. Edge-level analyses revealed discrete, network-specific dedifferentiation patterns in older adults. Visual and somatosensory regions were more integrated within the functional connectome; default and frontoparietal control network regions showed greater connectivity; and the dorsal attention network was more integrated with heteromodal regions. These findings highlight the importance of multi-scale, multi-method approaches to characterize the architecture of functional brain aging.

neuroscience↗