Publicaciones

Lower reward sensitivity in frontostriatal stroke: Infuence of depression and resting‑state functional connectivity

Sánchez-Kuhn A, Fernández-Martín P, Rodríguez-Herrera R et al. Cogn Affect Behav Neurosci. 2025 Jun 6. doi: 10.3758/s13415-025-01318-9. Online ahead of print.PMID: 40481315

https://pubmed.ncbi.nlm.nih.gov/40481315/

Abstract: Stroke patients have shown low reward sensitivity, which is a transdiagnostic dimension that defnes the extent to which a person actively pursues rewarding stimuli. Low reward sensitivity has been related to depression and dysregulation of the frontostriatal network. To date, studies have addressed this dimension in heterogenic stroke lesions and the underlying mechanisms of frontostriatal stroke patients are still unknown. This study included 54 participants (32 chronic frontostriatal stroke patients and 22 healthy controls). Reward sensitivity was assessed using the probabilistic reversal learning task. Depressive symptoms were measured with the Adult Self-Report, and resting-state functional connectivity (rsFC) was examined using functional near-infrared spectroscopy (fNIRS) in prefrontal, motor, and parietal cortices. Group diferences and predictors of reward sensitivity were analyzed using Bayesian ANCOVA and multiple regression models. Stroke patients displayed lower reward sensitivity, higher depressive problems, and lower resting-state functional connectivity between the right orbitrofrontal cortex and the left dorsolateral prefrontal cortex, the right orbitrofrontal cortex and the right dorsolateral prefrontal, and the right dorsolateral prefrontal cortex and right premotor cortex and supplementary motor area. In stroke patients, lower reward sensitivity was predicted by higher depressive problems and lower resting-state functional connectivity between the right dorsolateral prefrontal cortex and the right premotor cortex and the right supplementary motor area. This work showed the relevance of reward sensitivity in frontostriatal post-stroke patients and its relationship with depression, and supports the resting-state functional connectivity measurement for characterizing abnormalities in connectivity in stroke patients

Funding for open access publishing: Universidad de Almería/ CBUA. This work was supported by the Ministry of Science, Innovation and Universities (grant numbers PID2019-108423RB-100 and PID2023-147063 NB-I00), the Carlos III Institute of Health (grant number RICORS-ICTUS; RD21/0006/0010) and PPIT-UAL, Junta de Andalucía-ERDF 2021–2027. Objective RSO1.1. Programme: 54.A.

Contingency-based flexibility mechanisms through a reinforcement learning model in adults with attention-deficit/hyperactivity disorder and obsessive-compulsive disorder

Rodríguez-Herrera R, León JJ, Fernández-Martín P et al. Compr Psychiatry. 2025 May;139:152589. doi: 10.1016/j.comppsych.2025.152589. Epub 2025 Mar 13. PMID: 40112625

https://pubmed.ncbi.nlm.nih.gov/40112625

Abstract: Motor and cognitive dysfunction occur frequently after stroke, severely affecting a patient´s quality of life. Recently, non-invasive brain stimulation (NIBS) has emerged as a promising treatment option for improving stroke recovery. In this context, animal models are needed to improve the therapeutic use of NIBS after stroke. A systematic review was conducted based on the PRISMA statement. Data from 26 studies comprising rodent models of ischemic stroke treated with different NIBS techniques were included. The SYRCLE tool was used to assess study bias. The results suggest that both repetitive transcranial magnetic stimulation (rTMS) and transcranial direct current stimulation (tDCS) improved overall neurological, motor, and cognitive functions and reduced infarct size both in the short- and long-term. For tDCS, it was observed that either ipsilesional inhibition or contralesional stimulation consistently led to functional recovery. Additionally, the application of early tDCS appeared to be more effective than late stimulation, and tDCS may be slightly superior to rTMS. The optimal stimulation protocol and the ideal time window for intervention remain unresolved. Future directions are discussed for improving study quality and increasing their translational potential.

Funding: This work was funded by two grants awarded by the Consejería de Salud de la Junta de Andalucía (Ministry of Health of the Andalusian Regional Government), RH-0054-2021 (Torrecardenas University Hospital and University of Almería) and CSyF 2021-Postdoctorales (RPS 24665). Furthermore, this study is part of the Spanish Health Outcomes-Oriented Cooperative Research Networks (RICORS-ICTUS), Instituto de Salud Carlos III (Carlos III Health Institute), Ministerio de Ciencia e Innovación (Ministry of Science and Innovation).

 

Cryptogenic strokes and neurological symptoms of Fabry disease

Ruiz-Franco ML, Vélez-Gómez B, Martínez-Sánchez P et al. Front Neurol. 2025 Mar 5;16:1529267. doi: 10.3389/fneur.2025.1529267. eCollection 2025. PMID: 40109843.

https://pubmed.ncbi.nlm.nih.gov/40109843/

Introduction: Fabry disease (FD) is the second most common lysosomal storage disorder. It mainly affects young people. FD can be characterized by neurological symptoms that can occur in both the central and peripheral nervous systems. Cerebrovascular involvement is common in FD and is considered an important cause of cryptogenic strokes. This study aimed to describe the neurological symptoms in patients with FD in general and, specifically, to determine the frequency of association between this disease and cerebrovascular manifestations in our environment.

Materials and methods: This retrospective, observational, cross-sectional study included all patients in the FD registry of the nephrology and cardiology Departments of our center. A descriptive analysis of demographic, neurological, clinical, and neuroimaging variables was performed, with a particular focus on their association with stroke or other cerebrovascular events prior to diagnosis.

Results: A total of 25 patients were included, with 14 (68%) of them being women. The median age of the patients was 52 years (relative intensity of collaboration [RIC] = 24.5). The patients belonged to five families with specific galactosidase alpha gene (GLA) mutations. Neuroimaging was performed in 13 (52%) patients, most of whom did not have neurological symptoms but had normal imaging results. Only 2 (8%) patients had nonspecific white matter hyperintensities. Among the 11 (44%) patients with neurological involvement, the most common symptom was pain in the extremities (32%). Stroke was identified in only one patient (4%), which occurred prior to the diagnosis of FD and was determined to be of cardioembolic etiology.

Discussion: FD is found to be associated with several neurological symptoms. In our study, the most common neurological symptom was limb pain, which had varied characteristics. On the other hand, the incidence of stroke was significantly lower than that expected.

Funding: The author(s) declare financial support was received for the research, authorship, and/or publication of this article. This study was supported by the Fundación Andaluza para la Investigación Biosanitaria de Andalucía Oriental-Alejandro Otero, C.I.F. G18374199, Avda. de Madrid, 15; Pabellón de Consultas Externas II, 2ª Planta (Antigua Área de Dirección) 18012-Granada. This study is part of the Spanish Health Outcomes-Oriented Cooperative Research Networks (RICORS-ICTUS), Instituto de Salud Carlos III (Carlos III Health Institute), Ministerio de Ciencia e Innovación (Ministry of Science and Innovation), RD21/0006/0010 (Torrecardenas University Hospital). This study was also funded by the European Union – NextGenerationEU. Recovery, Transformation, and Resilience Plan.

 

Ledged Beam Walking Test Automatic Tracker: Artificial intelligence-based functional evaluation in a stroke model

Ruiz-Vitte A, Gutiérrez-Fernández M, Laso-García F et al. Comput Biol Med. 2025 Mar;186:109689. doi: 10.1016/j.compbiomed.2025.109689. Epub 2025 Jan 24. PMID: 39862465.

https://pubmed.ncbi.nlm.nih.gov/39862465/

Abstract: The quantitative evaluation of motor function in experimental stroke models is essential for the preclinical assessment of new therapeutic strategies that can be transferred to clinical research; however, conventional assessment tests are hampered by the evaluator’s subjectivity. We present an artificial intelligence-based system for the automatic, accurate, and objective analysis of target parameters evaluated by the ledged beam walking test, which offers higher sensitivity than the current methodology based on manual and visual counting. This system employs a residual deep network model, trained with DeepLabCut (DLC) to extract target paretic hindlimb coordinates, which are categorized to provide a ratio measurement of the animal’s neurological deficit. The results correlate with the measurements performed by a professional observer and have greater reproducibility, easing the analysis of motor deficits and providing a reliable and useful tool applicable to other diseases causing motor deficits.

Funding: This study was supported by the Instituto de Salud Carlos III (ISCIII) PI20/00243, co-funded by the European Union; RICORS network RD21/ 0006/0012 and the Next Generation EU funding that finances the actions of the Recovery and Resilience Mechanism; Miguel Servet CPII20/ 00002 to MG-F; FI18/00026 to FL-G. and FI17/00188 to MCG-F and by the Spanish Ministry of University, Recovery, Transformation and Resilience Plan and the Universidad Aut´ onoma de Madrid under grant CA1/RSUE/2021-00753 to DP-A.