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Abstract Healthy aging often entails a decline in cognitive and motor functions, affecting independence and quality of life in older adults. Brain stimulation shows potential to enhance these functions, but studies show variable effects. Previous studies have tried to identify responders and non-responders through correlations between behavioral change and baseline parameters, but results lack generalization to independent cohorts. We propose a method to predict an individual’s likelihood of benefiting from stimulation, based on baseline performance of a sequential motor task. Our results show that individuals with less efficient learning mechanisms benefit from stimulation, while those with optimal learning strategies experience none or even detrimental effects. This differential effect, first identified in a public dataset and replicated here in an independent cohort, was linked to one’s ability to integrate task-relevant information and not age. This study constitutes a further step towards personalized clinical-translational interventions based on brain stimulation.

Aging populations face significant cognitive challenges, particularly in working memory (WM). Transcranial alternating current stimulation (tACS) offer promising avenues for cognitive enhancement, especially when inspired by brain physiology. This study (NCT04986787) explores the effect of multifocal tACS on WM performance in healthy older adults, focusing on fronto-parietal network modulation. Individualized physiology-inspired tACS applied to the fronto-parietal network was investigated in two blinded cross-over experiments. The first experiment involved monofocal/bifocal theta-tACS to the fronto-parietal network, while in the second experiment cross-frequency theta-gamma interactions between these regions were explored. Participants have done online WM tasks under the stimulation conditions. Network connectivity was assessed via rs-fMRI and multichannel electroencephalography. Prefrontal monofocal theta tACS modestly improved WM accuracy over sham (d = 0.30). Fronto-parietal stimulation enhanced WM task processing speed, with the strongest effects for bifocal in-phase theta tACS (d = 0.41). Cross-frequency stimulations modestly boosted processing speed with or without impairing task accuracy depending on the stimulation protocol. This research adds to the understanding of physiology-inspired brain stimulation for cognitive enhancement in older subjects.

Abstract Stroke is one of the main causes of long-term disability worldwide, placing a large burden on individuals and society. Rehabilitation after stroke consists of an iterative process involving assessments and specialized training, aspects often constrained by limited resources of healthcare centers. Wearable technology has the potential to objectively assess and monitor patients inside and outside clinical environments, enabling a more detailed evaluation of the impairment and allowing the individualization of rehabilitation therapies. The present review aims to provide an overview of wearable sensors used in stroke rehabilitation research, with a particular focus on the upper extremity. We summarize results obtained by current research using a variety of wearable sensors and use them to critically discuss challenges and opportunities in the ongoing effort towards reliable and accessible tools for stroke rehabilitation. Finally, suggestions concerning data acquisition and processing to guide future studies performed by clinicians and engineers alike are provided.

In hemiparetic stroke, functional recovery of paretic limb may occur with the reorganization of neural networks in the brain. Neuroimaging techniques, such as magnetic resonance imaging (MRI), have a high spatial resolution which can be used to reveal anatomical changes in the brain following a stroke. However, low temporal resolution of MRI provides less insight of dynamic changes of brain activity. In contrast, electro-neurophysiological techniques, such as electroencephalography (EEG), have an excellent temporal resolution to measure such transient events, however are hindered by its low spatial resolution. This proof-of-principle study assessed a novel multimodal brain imaging technique namely Variational Bayesian Multimodal Encephalography (VBMEG), which aims to improve the spatial resolution of EEG for tracking the information flow inside the brain and its changes following a stroke. The limitations of EEG are complemented by constraints derived from anatomical MRI and diffusion weighted imaging (DWI). EEG data were acquired from individuals suffering from a stroke as well as able-bodied participants while electrical stimuli were delivered sequentially at their index finger in the left and right hand, respectively. The locations of active sources related to this stimulus were precisely identified, resulting in high Variance Accounted For (VAF above 80%). An accurate estimation of dynamic information flow between sources was achieved in this study, showing a high VAF (above 90%) in the cross-validation test. The estimated dynamic information flow was compared between chronic hemiparetic stroke and able-bodied individuals. The results demonstrate the feasibility of VBMEG method in revealing the changes of information flow in the brain after stroke. This study verified the VBMEG method as an advanced computational approach to track the dynamic information flow in the brain following a stroke. This may lead to the development of a quantitative tool for monitoring functional changes of the cortical neural networks after a unilateral brain injury and therefore facilitate the research into, and the practice of stroke rehabilitation.

Aging populations face significant cognitive challenges, particularly in working memory (WM). Transcranial alternating current stimulation (tACS) offer promising avenues for cognitive enhancement, especially when inspired by brain physiology. This study (NCT04986787) explores the effect of multifocal tACS on WM performance in healthy older adults, focusing on fronto-parietal network modulation. Individualized physiology-inspired tACS applied to the fronto-parietal network was investigated in two blinded cross-over experiments. The first experiment involved monofocal/bifocal theta-tACS to the fronto-parietal network, while in the second experiment cross-frequency theta-gamma interactions between these regions were explored. Participants have done online WM tasks under the stimulation conditions. Network connectivity was assessed via rs-fMRI and multichannel electroencephalography. Prefrontal monofocal theta tACS modestly improved WM accuracy over sham (d = 0.30). Fronto-parietal stimulation enhanced WM task processing speed, with the strongest effects for bifocal in-phase theta tACS (d = 0.41). Cross-frequency stimulations modestly boosted processing speed with or without impairing task accuracy depending on the stimulation protocol. This research adds to the understanding of physiology-inspired brain stimulation for cognitive enhancement in older subjects., Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (© 2024 The Authors.)

Motor skill learning is a crucial process at all ages. However, healthy aging is often accompanied by a reduction in motor learning capabilities. This study characterized the brain dynamics of healthy older adults during motor skill acquisition and identified brain regions associated with changes in different components of performance. Forty-three subjects participated in a functional magnetic resonance imaging study during which they learned a sequential grip force modulation task. We evaluated the continuous changes in brain activation during practice as well as the continuous performance-related changes in brain activation. Practice of the motor skill was accompanied by increased activation in secondary motor and associative areas. In contrast, visual and frontal areas were less recruited as task execution progressed. Subjects showed significant improvements on the motor skill. While faster execution relied on parietal areas and was inversely associated with frontal activation, accuracy was related to activation in primary and secondary motor areas. Better performance was achieved by the contribution of parietal regions responsible for efficient visuomotor processing and cortical motor regions involved in the correct action selection. The results add to the understanding of online motor learning in healthy older adults, showing complementary roles of specific networks for implementing changes in precision and speed., (© The Author(s) 2023. Published by Oxford University Press.)

Practicing a previously unknown motor sequence often leads to the consolidation of motor chunks, which enable its accurate execution at increasing speeds. Recent imaging studies suggest the function of these structures to be more related to the encoding, storage, and retrieval of sequences rather than their sole execution. We found that optimal motor skill acquisition prioritizes the storage of the spatial features of the sequence in memory over its rapid execution early in training, as proposed by Hikosaka in 1999. This process, seemingly diminished in older adults, was partially restored by anodal transcranial direct current stimulation over the motor cortex, as shown by a sharp improvement in accuracy and an earlier yet gradual emergence of motor chunks. These results suggest that the emergence of motor chunks is preceded by the storage of the sequence in memory but is not its direct consequence; rather, these structures depend on, and result from, motor practice.

A key feature of a successful game is its ability to provide the player with an adequate level of challenge. However, the objective of difficulty adaptation in serious games is not only to maintain the player's motivation by challenging, but also to ensure the completion of training objectives.This paper describes our proposed upper-limb rehabilitation game with tangible robots and investigates the effect of game elements and gameplay on the amount of the performed motion in several planes and percentage of failure by using the data from 33 unimpaired subjects who played 53 games within two consecutive days. In order to provide a more generic adaptation strategy in the future, we discretize the game area to circular zones. We then show the effect of changing these zones during gameplay on the activation of different muscles through EMG data in a pilot study.The study shows that it is possible to increase the challenge level by adding more active agents chasing the player and increasing the speed of these agents. However, only the increase in number of agents significantly increases the users' motion on both planes. Analysis of player behaviors leads us to suggest that by adapting the behaviour of these active agents in specific zones, it is possible to change the trajectory of the user, and to provide a focus on the activation of specific muscles.

In hemiparetic stroke, functional recovery of paretic limb may occur with the reorganization of neural networks in the brain. Neuroimaging techniques, such as magnetic resonance imaging (MRI), have a high spatial resolution which can be used to reveal anatomical changes in the brain following a stroke. However, low temporal resolution of MRI provides less insight of dynamic changes of brain activity. In contrast, electro-neurophysiological techniques, such as electroencephalography (EEG), have an excellent temporal resolution to measure such transient events, however are hindered by its low spatial resolution. This proof-of-principle study assessed a novel multimodal brain imaging technique namely Variational Bayesian Multimodal Encephalography (VBMEG), which aims to improve the spatial resolution of EEG for tracking the information flow inside the brain and its changes following a stroke. The limitations of EEG are complemented by constraints derived from anatomical MRI and diffusion weighted imaging (DWI). EEG data were acquired from individuals suffering from a stroke as well as able-bodied participants while electrical stimuli were delivered sequentially at their index finger in the left and right hand, respectively. The locations of active sources related to this stimulus were precisely identified, resulting in high Variance Accounted For (VAF above 80%). An accurate estimation of dynamic information flow between sources was achieved in this study, showing a high VAF (above 90%) in the cross-validation test. The estimated dynamic information flow was compared between chronic hemiparetic stroke and able-bodied individuals. The results demonstrate the feasibility of VBMEG method in revealing the changes of information flow in the brain after stroke. This study verified the VBMEG method as an advanced computational approach to track the dynamic information flow in the brain following a stroke. This may lead to the development of a quantitative tool for monitoring functional changes of the cortical neural networks after a unilateral brain injury and therefore facilitate the research into, and the practice of stroke rehabilitation.