BACKGROUND:Specific cognitive difficulties are common in major depressive disorder, impacting functioning and quality of life. Yet, the timing of their emergence and longitudinal course remains poorly understood. This study aimed to characterise longitudinal cognitive functioning following recent onset depression and its association with changes in depressive symptoms. METHODS:Longitudinal data from the PRONIA (Personalised Prognostic Tools for Early Psychosis Management) cohort recruited from ten European sites were used to evaluate trajectory differences between Healthy Controls (HC) and individuals experiencing recent onset depression (ROD). Linear mixed effect models were used with group-by-time interaction term for trajectory differences between baseline and nine-month follow-up, and the associations between changes in depression symptoms and cognitive functioning among ROD. RESULTS:The sample comprised 420 participants (ROD, N = 151; HC, N = 269) aged 15-40 years (M = 25.4, SD = 6.1; 55% female). Two distinct group-level cognitive trajectories were observed. First, a similar trajectory (i.e., no difference) to HC in visual memory, attention span, verbal learning and memory, visuospatial working memory, emotion recognition, and processing speed. A stable deficit trajectory was observed in mental flexibility, auditory verbal working memory, phonetic and semantic verbal fluency among the ROD group. Analysis within ROD group suggested that these outcomes were unrelated to reductions in depressive symptoms. Changes in visual memory, visuospatial working memory, sustained attention, and processing speed were associated with changes in depressive symptoms, despite being unrelated to baseline variations in depressive symptoms, possibly suggesting a sensitivity to state effects of illness, regardless of baseline severity. CONCLUSIONS:Specific cognitive difficulties are already evident at the first depressive episode and may endure in the short-medium term, irrespective of depressive course. Tailored treatment addressing cognition should be provided early to promote cognitive health and functional recovery.
Background Friedreich ataxia (FRDA) is an inherited, progressive neurodegenerative disease. Interindividual heterogeneity in the rate and phenotypic profile of disease progression indicates a biologic variability in the pattern and spatial evolution of underlying changes, but the occurrence of possible FRDA subgroups, which could aid in clinical trial design and treatment, are still unknown. Purpose To obtain a structural MRI-based stratification of participants with FRDA using the Subtype and Stage Inference (SuStaIn) algorithm and determine whether these subgroups are biologically meaningful and clinically relevant. Materials and Methods This multicenter secondary analysis of prospectively acquired data included structural MRI and clinical-demographic data from participants from the ENIGMA-Ataxia working group. MRI biomarkers were analyzed using the SuStaIn algorithm to identify subgroups with distinct patterns and disease stages. The clinical and genetic relevance of these subgroups were assessed within a linear model framework. Results This study included 565 participants (mean age, 32 years ± 13.1 [SD]; 286 women; 275 participants with FRDA and 290 healthy controls). SuStaIn identified three subtypes: (a) a classical subtype (66.5% [183 of 275 participants]), characterized by an ascending gradient of damage from brainstem to cerebellar cortex to cerebrum; (b) an early cerebral subtype (25.8% [71 of 275 participants]) with cerebral atrophy preceding the involvement of cerebellar cortex; and (c) and an early cerebellar subtype (7.64% [21 of 275 participants]) showing cerebellar lobule atrophy before upper brainstem or cerebral involvement. More advanced disease stages (MRI-based SuStaIn stages) correlated with greater symptom duration (unstandardized coefficient B = 0.422, standard error = 0.065, P < .001) and severity (B = 1.404, standard error = 0.201, P < .001), and these relationships were moderated by subtype, with biologic stage progression in the early cerebral subtype mapping less strongly to clinical variables relative to the others (interaction term early cerebral subtype × stage: B = -0.925, standard error = 0.410, P = .02). Conclusion Using the SuStaIn algorithm, three distinct structural MRI-based subtypes of FRDA were identified, with different patterns of brain degeneration and associations with clinical severity. © RSNA, 2026 Supplemental material is available for this article.
This paper describes the development, fabrication and testing of Playcuff, a wearable device designed to act as a videogame controller for children with motor disabilities, which also provides an orthotic action to improve the control of the upper limb. The aim of this device is to empower children with motor impairment and enable them to access and enjoy gaming despite their disabilities. The videogame controller function was achieved through on-board gesture classification using a two-tiered Fine Tree machine learning algorithm integrated into the device’s firmware. Based on features extracted from two inertial sensors present on the device, the classifier was trained to identify in real time 22 classes representing different postures and movements of forearm and wrist, showing an accuracy higher than 94
BACKGROUND Screening is now worldwide recognised as essential for early detection of neurodevelopmental divergences, and telemedicine is increasingly proving to be a valuable resource in this area. Our retrospective observational study aimed to assess the ability of the Strengths and Difficulties Questionnaire (SDQ 2–4) as a measure to distinguish autism spectrum disorder from other neurodevelopmental disorders in clinical and typically developing populations of preschoolers by remote data collection. METHODS Data from 343 preschoolers, including 93 children with autism spectrum disorder (ASD), 28 neurotypical children (NT), 167 children with developmental language disorder (DLD), and 55 children with developmental delay (DD), were collected through the MEDea Information and Clinical Assessment on-Line (MedicalBIT) platform. RESULTS Our results showed higher scores on all SDQ 2–4 scales for the ASD group vs the NT group, except for a scale scored in reverse (Prosocial Behaviour Scales) that had lower scores in children with ASD than NT children. Total Problems, Peer Problems, Hyperactivity, and Prosocial Behaviour Scales could more significantly differentiate the ASD group from the NT group. When comparing ASD group with other neurodevelopmental conditions (DLD, DD), the most significant results were found for the Total Problems, Peer Problems and Prosocial Behaviour Scales. CONCLUSIONS We concluded that these scales were more effective in differentiating children with autism spectrum disorder from children with developmental language disorder and from children with developmental delay, as well as from neurotypical children. We proved the SDQ 2–4 to be a valid short screening tool for use in preschoolers, to differentiate between ASD and other conditions by remote data collection.
