Introduction Cognitive rehabilitation (CR) enhances the autonomy of patients with Alzheimer’s disease. Their daily activities are likely dependent on attention networks. Method This pilot resting-state fMRI study investigated the cerebral correlates of CR in participants with mild Alzheimer disease (n = 22), compared to a control intervention in patients (n = 21) and in healthy participants (n = 27). Connectivity changes between dorsal and ventral attention networks were expected after 3 months of rehabilitation. Results A mixed ANOVA comparing pre- and post-intervention data across groups revealed increased connectivity between the dorsal and the ventral attention network following CR (FDR-corrected P = .0072). A post hoc correlation analysis of post-intervention data in the CR group showed that greater autonomy in daily activities was associated with stronger functional relationship between the two attention networks (FDR-corrected P = .0001). Conclusion Enhanced connectivity between attention networks may be a characteristic of CR benefits in individuals with mild Alzheimer disease.

This study applied multivariate ANOVA to investigate age-related microstructural changes in the brain tissues driven primarily by myelin, iron, and water content, as observed in MRI (semi-)quantitative R1, R2*, MTsat and PD maps. This is effectively a re-analysis of the data analyzed in a univariate way in a previous publication. Voxel-wise analyses were performed on gray matter (GM) and white matter (WM), in addition to region of interest (ROI) analyses. The multivariate approach identified brain regions showing coordinated alterations in multiple tissue properties and demonstrated bidirectional correlations between age and all examined modalities in various brain regions, including the caudate nucleus, putamen, insula, cerebellum, lingual gyri, hippocampus, and olfactory bulb. The multivariate model was more sensitive than univariate analyses, as evidenced by detecting a larger number of significant voxels within clusters in the supplementary motor area, frontal cortex, hippocampus, amygdala, occipital cortex, and cerebellum bilaterally. Though when cross validating the results by splitting the data into 2 subsets, sensitivity is strongly reduced, even more so for the multivariate approach. The examination of normalized, smoothed, and z-transformed maps within the ROIs revealed concurrent age-dependent alterations in myelin, iron, and water content. These findings contribute to our understanding of age-related brain differences and provide insights into the underlying mechanisms of aging. The study emphasizes the importance of multivariate analysis for detecting subtle microstructural changes associated with aging when dealing with multiple quantitative MRI parameter maps.

Background: Light plays a significant role in regulating various non-visual biological processes, such as stimulating alertness and cognition. However, the precise subcortical neural pathways are not fully established, including within the hypothalamus. In particular, how the hypothalamus processes are modulated by time-of-day and developmental stages, remains poorly understood. Methods: In this study, we used 7 Tesla functional magnetic resonance imaging to examine in vivo the impact of different light illuminance (0.16, 37, 92, and 190 melanopic equivalent daylight illuminance: mel-EDI lux) on the activity of the hypothalamus of healthy young adults (N=33; 20 women; 24.3 +/- 3.2y) and adolescents (N=16; 5 women; 16.8 +/- 1.1y) while they completed an auditory executive task, in the morning or in the evening. Results: Performance to the task improved with increasing illuminance irrespective of time of day and age group. When focusing on time-of-day differences in young adults, we found that the regional impact of light illuminance on the activity of the hypothalamus was consistent between the morning and the evening, with the posterior and anterior hypothalamus, respectively, showing increased and decreased activity with increasing illuminance. When focusing on developmental stages differences, during the evening session only, we found similar regional patterns in adolescents and young adult. The magnitude of the response at the highest illuminance was, however, larger in adolescents, with a larger deactivation of the superior-anterior and inferior-tubular hypothalamus. Conclusions: These findings reveal a complex and non-uniform impact of light on hypothalamus activity and provide novel insights into how light influences vary with developmental stages. ### Competing Interest Statement The authors have declared no competing interest. Fonds National de la Recherche Scientifique European Union’s Horizon 2020, 860613 Fondation Léon Frédéricq University of Liège, https://ror.org/00afp2z80 European Regional Development Fund Foundation Recherche Alzheimer, SAO-FRA 2022/0014 EU Joint Programme Neurodegenerative Disease Research, IRONSLEEP, SCAIFIELD

Quantitative MRI (qMRI) measures relaxation rates, exchange rates, and proton densities that reflect biophysical properties of tissue and are ideally free from protocol- and scanner-dependence. In practice, qMRI has not yet achieved this level of independence from sequence and hardware choice, and quantitative estimates often differ across sites and acquisition schemes. At the same time, pooling data across different sources can be beneficial to statistical power of longitudinal, cross-sectional, or case-control studies. Here, we investigate how protocol and hardware differences can affect pooling data from different sources in large ultra high field (UHF) qMRI studies in the context of healthy aging. We combine the openly available aging UHF qMRI MP2RAGEME-based dataset with two different multiparameter mapping (MPM)-based sets of qMRI data. We evaluate how pooling affects age dependence of qMRI parameters and investigate protocol-related biases, with a particular focus on subcortical structures. We focus the analysis, first, on replication and expansion of the previously published qMRI dataset on normative aging, second, the examination of the protocol influence on the estimated qMRI values, and third, on detecting the protocol effect on the age dependence inferred from the data. We find that the age-related changes in the pooled dataset for R1 measure around 4-17% of the lifespan mean in different structures. Similarly, age-related R2* variation in different structures constitutes around 6-30% of the lifespan mean in the pooled dataset. Subcortical structure volume change is on the order of 5-26%. We further observe larger relative difference between protocols for R1 and volume, while R2* remains more consistent for most regions. We show how pooling the UHF qMRI data from different sites and collected with different quantitative protocols can be both detrimental and beneficial for the analysis outcomes.

OBJECTIVE:Parkinson's disease (PD) is one of the rare diseases in which sleep alteration is a true marker of disease outcome. Yet, how the association between sleep and PD emerges over the healthy lifetime is not established. We examined the association between the polygenic risk score (PRS) for PD and the variability in the electrophysiology of rapid eye movement (REM) sleep in 433 younger (18-31 years) healthy individuals and 85 late-midlife (50-69 years) healthy individuals. METHODS:In this prospective cross-sectional study, in-lab electroencephalography recordings of sleep were recorded to extract REM sleep metrics. PRS was computed using SBayesR approach. RESULTS:Generalized additive model for location, scale, and shape analysis showed significant association of REM duration (pcorrected = 0.03) and theta energy in REM (pcorrected = 0.004) with PRS for PD in interaction with the age group. In the younger subsample, REM duration and theta energy were positively associated with PD PRS. In contrast, in the late-midlife subsample, the same associations were negative (although only qualitatively for REM theta energy) and may differ between men and women. INTERPRETATION:REM sleep is associated with the PRS for PD in early adulthood, 2 to 5 decades before typical symptoms onset. The association changes from positive in younger individuals, presumably free of alpha-synuclein, to negative in late-midlife individuals, possibly because of the progressive presence of alpha-synuclein aggregates or of the repeated increased oxidative metabolism imposed by REM sleep. Our findings may unravel core associations between PD and sleep and may contribute to novel intervention targets to prevent or delay PD. ANN NEUROL 2026;99:922-934.

Multiple Kernel Learning (MKL) models combine several kernels in supervised and unsupervised settings to integrate multiple data representations or sources, each represented by a different kernel. MKL seeks an optimal linear combination of base kernels that maximizes a generalized performance measure under a regularization constraint. Various norms have been used to regularize the kernel weights, including l1, l2 and lp, as well as the "elastic-net" penalty, which combines l1- and l2-norm to promote both sparsity and the selection of correlated kernels. This property makes elastic-net regularized MKL (ENMKL) especially valuable when model interpretability is critical and kernels capture correlated information, such as in neuroimaging. Previous ENMKL methods have followed a two-stage procedure: fix kernel weights, train a support vector machine (SVM) with the weighted kernel, and then update the weights via gradient descent, cutting-plane methods, or surrogate functions. Here, we introduce an alternative ENMKL formulation that yields a simple analytical update for the kernel weights. We derive explicit algorithms for both SVM and kernel ridge regression (KRR) under this framework, and implement them in the open-source Pattern Recognition for Neuroimaging Toolbox (PRoNTo). We evaluate these ENMKL algorithms against l1-norm MKL and against SVM (or KRR) trained on the unweighted sum of kernels across three neuroimaging applications. Our results show that ENMKL matches or outperforms l1-norm MKL in all tasks and only underperforms standard SVM in one scenario. Crucially, ENMKL produces sparser, more interpretable models by selectively weighting correlated kernels.

Animal studies show that sleep regulation depends on subcortical networks, but whether the connectivity between subcortical areas contributes to human sleep variability remains unclear. We investigated whether the effective connectivity between the LC and hypothalamic subparts during wakefulness relates to sleep electrophysiology. Thirty-three younger (~22 y, 27 women) and 18 late middle-aged (~61 y, 14 women) healthy individuals underwent 7-Tesla functional MRI during wakefulness to assess LC–hypothalamus effective connectivity. Additionally, sleep EEG was recorded at night in the lab to examine the relationships between effective connectivity measures and REM sleep theta energy as well as sigma power prior to REM. Connectivity analyses revealed strong mutual positive influences between the LC and both the anterior–superior and posterior hypothalamus, consistent with animal studies. Aging was negatively associated with the connectivity from the anterior–superior hypothalamus (including the preoptic area) to the LC. In late middle-aged adults, but not younger adults, stronger effective connectivity from the anterior–superior hypothalamus to the LC was associated with lower REM theta energy. This association extended to other low-frequency bands during REM and NREM sleep. These findings highlight the age-dependent modulation of LC–hypothalamus interactions and their potential roles in sleep regulation, providing new insights into neural mechanisms underlying age-related sleep changes.

Resting-state functional connectivity (rsFC) is a highly dynamic process that varies across different times of the day within each individual. Although this variability was long considered to be noise, recent evidence suggests it may allow for an optimal adaptation to changes in the environment. However, the way rsFC is shaped on a circadian scale and its association with cognition are still unclear. We analyzed data from 90 late middle-aged participants from the Cognitive Fitness in Aging study (61 women; 50–69 years). Participants completed five electroencephalographic (EEG) recordings of spontaneous resting-state activity spread over 20 h of prolonged wakefulness. Using a temporal multilayer network approach, we characterized the diurnal variations of the dynamic recruitment and integration of resting-state brain networks. We focused on the theta and gamma frequency bands within the default mode network (DMN), central executive network (CEN), and salience network (SN). Additionally, we investigated the relationship between the recruitment and integration of these networks with baseline cognitive performance and at a 7-year longitudinal follow-up, as well as with positron emission tomography (PET) early neuropathological markers of Alzheimer’s disease such as β-amyloid and tau/neuroinflammation. Diurnal changes in theta and gamma dynamics were associated with distinct cognitive aspects. Specifically, higher baseline memory performance was associated with higher theta dynamic integration of the SN and the CEN, as well as higher theta dynamic recruitment of the DMN. Moreover, lower longitudinal memory decline at 7 years was associated with higher theta dynamic integration of the SN, CEN, and DMN. In contrast, higher gamma diurnal dynamic integration of the SN and the CEN was associated with lower executive and attentional performance, as well as higher early β-amyloid accumulation, at baseline. These findings suggest that maintaining a balance between network flexibility and stability throughout the diurnal phase of the circadian cycle may play a crucial role in cognitive aging, with stable theta-band connectivity supporting memory, whereas excessive gamma-band stability in the SN and CEN may contribute to executive decline and early amyloid accumulation. These insights highlight the importance of considering time-of-day in brain rsFC studies, calling for a temporal multilayer approach to capture these dynamic patterns more effectively.

Context The cerebral substrates of fatigue in patients with Multiple Sclerosis (pwMS) are not elucidated yet. This study aims at exploring the disease-specific functional brain substrates of fatigue in pwMS with a recent disease history Methods Sixteen pwMS (disease history < 5 years) and 17 matched Healthy Controls (HC) performed a N-Back task with three difficulty levels during fMRI acquisitions following high vs. low fatigue induction. Measures of subjective trait and state fatigue were also recorded. Behavioral performance at n-back task and evolution of subjective fatigue states were analyzed by means of Bayesian repeated measures analyses of variance. Functional MRI data were analyzed to determine between-group differences (1) in task-related brain activity, independently of trait fatigue score; (2) in the association between trait fatigue and brain activity Results A similar trajectory was observed in the two groups for subjective and task-related measures following fatigue induction. No between-group difference was observed in brain activity unrelated to fatigue score. However, negative associations between trait fatigue score and brain activity were observed in pwMS, while the associations are positive in HC. Specifically, interactions between group and task difficulty were observed in regions belonging to the Striato-Thalamo-Cortical (STC) network and the fronto-parietal cortex Conclusion Group-specific patterns of brain activity related to fatigue were identified in pwMS and HC in the STC circuitry, despite similar behavioral performance and subjective fatigue level. This confirms the implication of the STC loops in fatigue pathophysiology, occurring from the early stages of the disease. ### Competing Interest Statement The authors have declared no competing interest. * CIS : Clinically Isolated Syndrome HC : Healthy Controls DAN : Dorsal Attention Network HCL : High Cognitive Load IPS : Intraparietal Sulcus ITS : Inferior Temporal Sulcus LCL : Low Cognitive Load MS : Multiple Sclerosis pwMS : people with Multiple Sclerosis RR : Relapsing-Remitting STC : Striato-Thalamo-Cortical STD : Stimulus Time Duration STS : Superior Temporal Sulcus TLDB : Time Load Dual Back; Fonds National de la Recherche Scientifique (FNRS), Belgium University of Liège, Belgium Fauconnier and Sallets Fund from the King Baudouin Fundation (KBF-FRB), Belgium

Animal studies established that the locus coeruleus (LC) plays important roles in sleep and wakefulness regulation. Whether it contributes to sleep variability in humans is not yet established. Here, we investigated if the in vivo activity of the LC is related to the variability in the quality of Rapid Eye Movement (REM) sleep. We assessed the LC activity of 34 healthy younger ( 22y) and 18 older ( 61y) individuals engaged in bottom-up and top-down cognitive tasks using 7-Tesla functional Magnetic Resonance Imaging (fMRI). We further recorded their sleep electroencephalogram (EEG) to evaluate associations between LC fMRI measures and REM sleep EEG metrics. Theta oscillation energy during REM sleep was positively associated with LC response in the top-down task. In contrast, REM sleep theta energy was negatively associated with LC activity in older individuals during the bottom-up task. Importantly, sigma oscillations power immediately preceding a REM sleep episode was positively associated with LC activity in the top-down task. LC activity during wakefulness was related to REM sleep intensity and to a transient EEG change preceding REM sleep, a feature causally related to LC activity in animal studies. The associations depend on the cognitive task, suggesting that a balanced level of LC tonic activity during wakefulness is required for optimal expression of REM sleep. The findings may have implications for the high prevalence of sleep complaints reported in aging and for disorders such as insomnia, Alzheimer’s, and Parkinson’s disease, for which the LC may play pivotal roles through sleep.

The brain mechanisms through which changes in season and light exposure modulate mood may involve different nuclei of the amygdala. We aimed to test this hypothesis using 7 Tesla functional magnetic resonance imaging in 29 healthy young adults. We first considered time-of-year changes in activity that are related to the slow change in photoperiod. We find that the response to emotional stimuli of selected medial and superior nuclei of the amygdala peaked around the start of winter or increased with worse mood status. We further assessed how alternating short exposures to light of different illuminance acutely affected the regional activity of the amygdala. We show that the same areas showed a linear reduction of activity when exposed to increasing light illuminance, specifically when processing emotional stimuli. Importantly, the impact of light on part of these nuclei peaked around the start of summer or decreased with worse mood. These findings provide additional evidence that humans show seasonality and that, for mood, it involves parts of the amygdala. The results bring insights into the mechanisms that underlie the long-term and acute impact of light on mood and that may contribute to the benefits of light therapy in the treatment of mood disorders.

Study Objectives Animal research has demonstrated that sleep regulation heavily depends on a network of subcortical nuclei. In particular, whether the crosstalk between the Locus Coeruleus (LC) and hypothalamic nuclei influences sleep variability and age-related changes in humans remains unexplored. This study investigated whether the effective connectivity between the LC and subparts of the hypothalamus is associated with the electrophysiology of rapid eye movement sleep (REMS). Methods Thirty-three healthy younger (∼22y, 27 women) and 18 older (∼61y, 14 women) individuals underwent 7-Tesla functional magnetic resonance imaging during wakefulness to investigate the effective connectivity between LC and distinct hypothalamus subparts encompassing several nuclei. Additionally, we recorded their sleep electroencephalogram (EEG) to explore relationships between effective connectivity measures and REMS theta energy and sigma power prior to REMS episodes. Results The effective connectivity analysis revealed robust evidence of a mutual positive influence between the LC and the anterior-superior and posterior hypothalamus, supporting the idea that the connectivity patterns observed in animal models are also present in humans. Furthermore, our results suggest that in older adults, stronger effective connectivity from the anterior-superior hypothalamus, including the preoptic area, to the LC is associated with reduced REM theta energy. Specificity analysis showed that this association was not limited to REM theta energy but also extended to specific lower-frequency bands during REMS and NREMS. Conclusions These findings highlight the complex age-dependent modulation of the LC circuitry and its role in sleep regulation. Understanding these neural interactions offers valuable insight into the mechanisms driving age-related sleep changes. ### Competing Interest Statement The authors have declared no competing interest. The processed data and analysis scripts supporting the results included in this manuscript are publicly available via the following open repository: (to be defined upon acceptance of the paper). The raw data could be identified and linked to a single subject and represent a large amount of data and cannot be openly shared. Researchers willing to access to the raw data should send a request to the corresponding author (GV). Data sharing will require evaluation of the request by the local Research Ethics Board and the signature of a data transfer agreement (DTA).

The question of whether cognitive control is specific to certain domains or domain-general remains an extensively debated question at both cognitive and neural levels. This study examined the neural substrates associated with resistance to interference (RI) in phonological, semantic, and visual domains by using strictly matched tasks and determining the domain-general or domain-specific manner in which aging affects the neural substrates associated with RI. In an fMRI experiment, young and older participants performed a similarity judgment task with phonological, semantic, or visual interference buildup. For both age groups, domain-specific RI effects were observed at the univariate level, with increased involvement in the phonological domain of the right angular gyrus and the right lingual gyrus, in the semantic domain of the bilateral inferior frontal gyrus, the bilateral superior parietal and angular gyri and the left middle temporal gyrus, and in the visual domain of the middle/superior frontal gyri and occipital gyri. At the multivariate level, although RI effects could be decoded from neural patterns in the bilateral inferior frontal gyrus for all domains and age groups, between-domain prediction of RI conditions was associated with Bayesian evidence for the null hypothesis. This study supports the domain specificity of neural substrates associated with RI while stressing its age independency.

Light affects not only vision but also attention, alertness, and cognition, primarily through intrinsically photosensitive retinal ganglion cells sensitive to blue-wavelength light. While previous research has shown that light influences brain regional activity, its impact on brain connectivity remains unclear. Using 7-Tesla fMRI, this study examined how light modulates thalamo-cortical connectivity during an auditory executive task involving the thalamus, the prefrontal cortex (in supramarginal gyrus : SMG), and parietal cortex (in the inferior frontal junction : IFJ). Fifty-five participants, including young adults (19-30y: scanned in the morning or evening) and adolescents (15-16y: scanned in the evening), were studied. Across all groups, moderate blue-enriched light strengthened SMG-to-IFJ connectivity, while low-illuminance orange light enhanced thalamus-to-SMG connectivity. High-illuminance blue-enriched light strengthened thalamus-to-IFJ connectivity only in the morning for young adults, while moderate blue-enriched light enhanced thalamus-to-SMG connectivity in adolescents in the evening. These findings suggest that the thalamus plays a key role in mediating light’s cognitive effects and timing and age influence non-image-forming responses. ### Competing Interest Statement The authors have declared no competing interest.

Cognitive function alterations are a feature of the cognitive aging process. Additionally, aging is marked by macro- and micro-structural changes in the brain, such as gray matter (GM) atrophy, iron accumulation, and demyelination. This study explores the association between cognitive function and cooccurrence of brain micro- and macro-structural changes in healthy older adults. One hundred and one participants (32% men, age range: 50-69 years) were included in this study. All participants completed a cognitive assessment resulting in composite scores with mean = 0.00, s.d. = 0.99 for attention, executive functions, and memory. The preclinical Alzheimer’s cognitive composite (PACC5) was calculated for all participants (mean = 0.00, s.d. = 2.99). Quantitative magnetic resonance imaging (MRI) data were obtained using multiparametric mapping protocol. The association between cognitive composite scores and combinations of tissue properties was tested using multivariate generalized linear models (GLM) in Statistical Parametric Mapping (SPM) software. Voxel-wise multivariate GLM analyses revealed significant associations after family-wise error rate correction between executive functions and the combination of macro- and micro-structural changes within the cerebellum including right crus I and II, VII-b (see Figure 1-A). As illustrated in Figure 1, panels B and C, we also detected a correlation between memory and combined microstructural alterations in the in the left Cerebellum VIII-b, as well as bilaterally within the cingulate gyrus and insula. These findings highlight the role of the cerebellum in cognition besides the complex relationship between cognition and brain micro- and macro-structural properties in aging. As such, the involvement of the cerebellum in motor coordination and procedural memory may potentially influence executive functions

Light, particularly blue-wavelength light exerts a broad range of non-image forming (NIF) effects including the stimulation of cognition and alertness and the regulation of mood, sleep and circadian rhythms. However, its underlying brain mechanisms are not fully elucidated. Likewise, whether adolescents show a different NIF sensitivity to light compared to adults is not established. Here, we investigated whether cortical excitability, a basic aspect of brain function that depends on sleep-wake regulation, is affected by blue light and whether the effect is similar in young adults and adolescents. We used transcranial magnetic stimulation coupled to high-density electroencephalography (TMS-EEG) in healthy young adults (N = 13, 24.2 ± 3.4 y) and in adolescents (N = 15, 16.9 ± 1.1 y). Our results showed that, in young adults, blue light affected cortical excitability following an apparent inverted-U relationship, while adolescents' cortical excitability was not significantly different under blue light compared to orange light. In addition, although light did not affect performance on a visuomotor vigilance task completed during the TMS-EEG recordings, cortical excitability was positively correlated to task performance in both age groups. This study provides valuable insights into the complex interplay between light, cortical excitability, and behavior. Our findings highlight the role of age in NIF effects of light, suggesting that brain responses to light differ during developmental periods.

Circadian rhythms shape the temporal organization of sleep and wakefulness and evolve throughout the adult lifespan, leading to higher sleep-wake cycle fragmentation with ageing. The increasing prevalence of daytime napping represents a visible manifestation of such fragmentation and has been suggested to forecast age-related cognitive decline. Here, we assessed the impact of napping on functional brain correlates of performance on a Sternberg working memory (WM) task using functional magnetic resonance imaging in 60 healthy older individuals, prospectively recruited with respect to their napping habits (39 females, age: 59–82y). As compared to non-nappers, nappers showed reduced hemispheric asymmetry in the dorsolateral prefrontal cortex (DLPFC, p< 0.001) and decreased performance at high WM load levels. Only in non-nappers was increased ipsilateral activation in the DLPFC associated with better performance at high WM load levels (p < 0.05), while contralateral activation across all WM load levels was not associated with better performance. These findings indicate that functional brain compensation and dedifferentiation processes vary according to an individual’s napping phenotype, potentially serving as a marker of inter-individual differences in cognitive and brain aging. ### Competing Interest Statement The authors have declared no competing interest. This study was supported by the European Research Council (ERC, ERC-StG‐COGNAP) under the European Union’s Horizon 2020 research and innovation program (Grant Agreement No. 757763). This study was also supported by the Fonds National de la Recherche Scientifique–FNRS under Grant nr T.0220.20 and by research grant from the University of Liège. C. S. and G. V. are research associates and M.De., M.Do. and S.D. received PhD grants from the Fonds de la Recherche Scientifique–FNRS, Belgium.