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Rocca, M. A.

Publications and source records attributed to Rocca, M. A..

6 recordsLinked to original sources

A Virtual Reality Dataset to Support Hand Action Observation in Rehabilitation and Motor Learning Studies

The recovery of motor function is increasingly understood as a process influenced not only by physical training but also by perceptual and cognitive strategies. Action Observation Treatment (AOT), a neurorehabilitation approach in which patients observe goal-directed motor actions before executing them, has demonstrated clinical benefits; however, its wider implementation is hindered by a lack of standardized procedures. We present an open-access dataset of 33 upper limb gestures specifically developed to support the administration of Virtual Reality-based AOT (VR-AOT). The gestures were selected in collaboration with expert physiotherapists to ensure clinical relevance, and are provided as motion capture recordings along with Unity-based 3D animations embedded in configurable virtual scenes. The dataset is designed for flexibility, allowing users to modify parameters such as viewpoint, laterality, and repetition count. Technical validation confirms its usability and therapeutic applicability across multiple clinical and research contexts. This dataset offers a standardized yet customizable resource for developing and comparing VR-AOT protocols, with potential applications in neurorehabilitation and motor learning research.

neuroscience↗

Neural precursor cells contribute to decision-making by tuning striatal connectivity via secretion of IGFBPL-1

The adult brain retains endogenous neural stem/precursors cells (eNPCs) in two major neurogenic niches, the subgranular zone (SGZ) in the hippocampus and the subventricular zone (SVZ). While in humans and rodents the SGZ contributes to memory functions by generating new neurons that integrate into hippocampal circuitry, the role of eNPCs of the SVZ is less clear. SVZ-eNPCs contribute to the generation of new neurons fated to the olfactory bulb (OB) in rodents but not in humans where they are thought to contribute to striatal neurogenesis as a result of tissue damage. Here, we show in mice and humans a novel non-neurogenic physiological role of adult SVZ-eNPCs in supporting cognitive functions by regulating striatal neuronal activity. We first provide evidence that GABAergic transmission between parvalbumin-expressing fast-spiking interneurons (FSIs) and medium spiny neurons (MSNs) is tuned by SVZ-eNPCs via secretion of Insulin-Like Growth Factor Binding Protein Like 1 (IGFBPL-1) that, in turn, regulates the Insulin-Like Growth Factor (IGF-1) signalling cascade. Consistently, selective ablation of SVZ-eNPCs and in vivo disruption of the IGF-signalling determine the impairment of intrastriatal coherence. A finding associated with a higher failure rate of GABAergic transmission mediated by FSIs and with striatum-related behavioural dysfunctions impairing decision making. Human validation studies revealed IGFBPL-1 expression in the SVZ and in foetal and induced-pluripotent stem cell-derived NPCs as well as a strong correlation in neurological patients between SVZ pathological damage, reduction of striatum volume and impairment of information processing speed. All in all, our results highlight a novel non-neurogenic homeostatic role exerted by SVZ-eNPCs on striatal GABAergic neurons that might contribute to cognitive processes involving decisions-making tasks.

neuroscience↗

Accelerated brain ageing and disability in multiple sclerosis

BackgroundBrain atrophy occurs in both normal ageing and in multiple sclerosis (MS), but it occurs at a faster rate in MS, where it is the major driver of disability progression. Here, we employed a neuroimaging biomarker of structural brain ageing to explore how MS influences the brain ageing process.\n\nMethodsIn a longitudinal, multi-centre sample of 3,565 MRI scans in 1,204 MS/clinically isolated syndrome (CIS) patients and 150 healthy controls (HCs) (mean follow-up time: patients 3*41 years, HCs 1*97 years) we measured brain-predicted age using T1-weighted MRI. Brain-predicted age difference (brain-PAD) was calculated as the difference between the brain-predicted age and chronological age. Positive brain-PAD indicates a brain appears older than its chronological age. We compared brain-PAD between MS/CIS patients and HCs, and between disease subtypes. In patients, the relationship between brain-PAD and Expanded Disability Status Scale (EDSS) at study entry and over time was explored.\n\nFindingsAdjusted for age, sex, intracranial volume, cohort and scanner effects MS/CIS patients had markedly older-appearing brains than HCs (mean brain-PAD 11*8 years [95% CI 9*1--14*5] versus -0*01 [-3*0--3*0], p<0*0001). All MS subtypes had greater brain-PAD scores than HCs, with the oldest-appearing brains in secondary-progressive MS (mean brain-PAD 18*0 years [15*4--20*5], p<0*05). At baseline, higher brain-PAD was associated with a higher EDSS, longer time since diagnosis and a younger age at diagnosis. Brain-PAD at study entry significantly predicted time-to-EDSS progression (hazard ratio 1*02 [1*01--1*03], p<0*0001): for every 5 years of additional brain-PAD, the risk of progression increased by 14*2%.\n\nInterpretationMS increases brain ageing across all MS subtypes. An older-appearing brain at baseline was associated with more rapid disability progression, suggesting brain-age could be an individualised prognostic biomarker from a single, cross-sectional assessment.\n\nFundingUK MS Society; National Institute for Health Research University College London Hospitals Biomedical Research Centre.

neuroscience↗

Abundance drives generalisation in hummingbird-plant pollination networks

Abundant pollinators are often more generalised than rare pollinators. This could be because abundance drives generalisation: neutral effects suggest that more abundant species will be more generalised simply because they have more chance encounters with potential interaction partners. On the other hand, generalisation could drive abundance, as generalised species could have a competitive advantage over specialists, being able to exploit a wider range of resources and gain a more balanced nutrient intake. Determining the direction of the abundance-generalisation relationship is therefore a chicken-and-egg dilemma. Here we determine the direction of the relationship between abundance and generalisation in plant-hummingbird pollination networks sampled from a variety of locations across the Americas. For the first time we resolve the direction of the abundance-generalisation relationship using independent data on animal abundance. We find evidence that hummingbird pollinators are generalised because they are abundant, and little evidence that hummingbirds are abundant because they are generalised. Additionally, a null model analysis suggests this pattern is due to neutral processes: most patterns of species-level abundance and generalisation were well explained by a null model that assumed interaction neutrality. These results suggest that neutral processes play a key role in driving broad patterns of generalisation in animal pollinators across large spatial scales.\n\nDeclarationsFunding - BIS is supported by the Natural Environment Research Council as part of the Cambridge Earth System Science NERC DTP [NE/L002507/1]. JVB was funded by CERL - Engineer Research and Development Center. PKM was funded by the Sao Paulo Research Foundation (FAPESP grant #2015/21457-4). PAC was funded by the David Lack studentship from the British Ornithologists Union and Wolfson College, University of Oxford. CL was funded by the ESDEPED-UAT grant. MAM acknowledges the Consejo Nacional para Investigaciones Cientificas y Tecnologicas (Costa Rica), German Academic Exchange Service and the research funding program LOEWE-Landes-Offensive zur Entwicklung Wissenschaftlicho konomischer Exzellenz of Hesses Ministry of Higher Education, Research, and the Arts (Germany). ROP was funded by CONACyT (project 258364). MAR was supported by the State of Sao Paulo Research Foundation (FAPESP) within the BIOTA/FAPESP, The Biodiversity Institute Program (www.biota.org.br) and the Parcelas Permanentes project, as well as by Coordenacao de Pessoal de Nivel Superior (CAPES), Fundo de Apoio ao Ensino e a Pesquisa (FAEP)/Funcamp/Unicamp and The Nature Conservancy (TNC) of Brazil. LCR was supported by CNPq and Capes. MS was funded by CNPq (grant #302781/2016-1). AMMG is supported through a Marie Skodowska-Curie Individual Fellowship (H2020-MSCA-IF-2016-704409). LVD was supported by the Natural Environment Research Council (grants NE/K015419/1 and NE/N014472/1). AMMG, JS, CR and BD thank the Danish National Research Foundation for its support of the Center for Macroecology, Evolution and Climate (grant no. DNRF96). WJS is funded by Arcadia.

ecology↗

Progression of regional grey matter atrophy in multiple sclerosis

Grey matter atrophy is present from the earliest clinical stages of multiple sclerosis (MS), but the temporal ordering is poorly understood. We aimed to determine the sequence in which grey matter regions become atrophic in MS, and its association with disability accumulation.\n\nIn this longitudinal study, we included 1,417 subjects: 253 with clinically-isolated syndrome (CIS), 708 relapsing-remitting MS (RRMS), 128 secondary-progressive MS (SPMS), 125 primary-progressive MS (PPMS), and 203 healthy controls from 7 European centres. Subjects underwent repeated MRI scanning (total number of scans 3,604); the mean follow-up for patients was 2.41yrs (SD{+/-}1.97). Disability was scored using the Expanded Disability Status Scale (EDSS). We calculated the volume of brain grey matter regions and brainstem using an unbiased within-subject template. We used an established data-driven event-based model (EBM) to determine the sequence of occurrence of atrophy and its uncertainty. We assigned each subject to a specific EBM stage, based on the number of their atrophic regions. We used nested linear mixed-effects regression models to explore the associations between the rate of increase in the EBM stages over time, disease duration and annual rate of EDSS gain.\n\nThe first regions to become atrophic in CIS and relapse-onset MS patients (RRMS and SPMS) were the posterior cingulate cortex and precuneus, followed by the middle cingulate cortex, brainstem and thalamus. The sequence of atrophy in PPMS showed a similar involvement of the thalamus, cuneus, precuneus, and pallidum, followed by the brainstem and posterior cingulate cortex. The cerebellum, caudate and putamen showed early atrophy in relapse-onset MS and late atrophy in PPMS. Patients with SPMS showed the highest EBM stages (highest number of atrophic regions, all p<0.001) at study entry. Rates of increase in EBM stages were significantly different from healthy controls in all MS phenotypes, except for CIS. The increase in the number of atrophic regions (EBM stage) was associated with disease duration in all patients. EBM stage was associated with disability accumulation in RRMS independent of disease duration (p<0.0001).\n\nThis data-driven staging of atrophy progression in a large MS sample demonstrates that grey matter atrophy spreads to involve more regions over time. The sequence in which regions become atrophic is reasonably consistent across MS phenotypes. The spread of atrophy was associated with disease duration, and disability accumulation in RRMS.\n\nAbbreviations

neuroscience↗

Deep grey matter volume loss drives disability worsening in multiple sclerosis

ObjectiveGrey matter (GM) atrophy occurs in all multiple sclerosis (MS) phenotypes. We investigated whether there is a spatiotemporal pattern of GM atrophy that is associated with faster disability accumulation in MS.\n\nMethodsWe analysed 3,604 brain high-resolution T1-weighted MRI scans from 1,417 participants: 1,214 MS patients (253 clinically-isolated syndrome[CIS], 708 relapsingremitting[RRMS], 128 secondary-progressive[SPMS], 125 primary-progressive[PPMS]), over an average follow-up of 2.41 years (standard deviation[SD]=1.97), and 203 healthy controls (HCs) [average follow-up=1.83 year, SD=1.77], attending 7 European centres. Disability was assessed with the Expanded-Disability Status Scale (EDSS). We obtained volumes of the deep GM (DGM), temporal, frontal, parietal, occipital and cerebellar GM, brainstem and cerebral white matter. Hierarchical mixed-models assessed annual percentage rate of regional tissue loss and identified regional volumes associated with time-to-EDSS progression.\n\nResultsSPMS showed the lowest baseline volumes of cortical GM and DGM. Of all baseline regional volumes, only that of the DGM predicted time-to-EDSS progression (hazard ratio=0.73, 95% CIs 0.65, 0.82; p<0.001): for every standard deviation decrease in baseline DGM volume, the risk of presenting a shorter time to EDSS worsening during follow-up increased by 27%. Of all longitudinal measures, DGM showed the fastest annual rate of atrophy, which was faster in SPMS (-1.45%), PPMS (-1.66%), and RRMS (-1.34%) than CIS (-0.88%) and HCs (-0.94%)[p<0.01]. The rate of temporal GM atrophy in SPMS (-1.21%) was significantly faster than RRMS (-0.76%), CIS (-0.75%), and HCs (-0.51%). Similarly, the rate of parietal GM atrophy in SPMS (-1.24-%) was faster than CIS (-0.63%) and HCs (-0.23%) (all p values <0.05). Only the atrophy rate in DGM in patients was significantly associated with disability accumulation (beta=0.04, p<0.001).\n\nInterpretationThis large multi-centre and longitudinal study shows that DGM volume loss drives disability accumulation in MS, and that temporal cortical GM shows accelerated atrophy in SPMS than RRMS. The difference in regional GM atrophy development between phenotypes needs to be taken into account when evaluating treatment effect of therapeutic interventions.

neuroscience↗