No abstract

Chronic communication impairment is common after stroke, and conventional speech and language therapy (SLT) strategies have limited effectiveness in post-stroke aphasia. Neurorehabilitation with non-invasive brain stimulation techniques (NIBS)—particularly repetitive transcranial magnetic stimulation (rTMS) or transcranial direct current stimulation (tDCS)—may enhance the effects of SLT in selected patients. Applying inhibitory NIBS to specific homologous language regions may induce neural reorganization and reduce interhemispheric competition. This mini review highlights randomized controlled trials (RCTs) and randomized cross-over trials using low-frequency rTMS or cathodal tDCS over the non-lesioned non-language dominant hemisphere and performs an exploratory meta-analysis of those trials considered combinable. Using a random-effects model, a meta-analysis of nine eligible trials involving 215 participants showed a significant mean effect size of 0.51 (95% CI = 0.24–0.79) for the main outcome “accuracy of naming” in language assessment. No heterogeneity was observed (I2 = 0%). More multicenter RCTs with larger populations and homogenous intervention protocols are required to confirm these and the longer-term effects.

Stroke is a leading cause of serious long-term disability worldwide. Functional outcome depends on stroke location, severity, and early intervention. Conventional rehabilitation strategies have limited effectiveness, and new treatments still fail to keep pace, in part due to a lack of understanding of the different stages in brain recovery and the vast heterogeneity in the poststroke population. Innovative methodologies for restorative neurorehabilitation are required to reduce long-term disability and socioeconomic burden. Neuroplasticity is involved in poststroke functional disturbances and also during rehabilitation. Tackling poststroke neuroplasticity by non-invasive brain stimulation is regarded as promising, but efficacy might be limited because of rather uniform application across patients despite individual heterogeneity of lesions, symptoms, and other factors. Transcranial direct current stimulation (tDCS) induces and modulates neuroplasticity, and has been shown to be able to improve motor and cognitive functions. tDCS is suited to improve poststroke rehabilitation outcomes, but effect sizes are often moderate and suffer from variability. Indeed, the location, extent, and pattern of functional network connectivity disruption should be considered when determining the optimal location sites for tDCS therapies. Here, we present potential opportunities for neuroimaging-guided tDCS-based rehabilitation strategies after stroke that could be personalized. We introduce innovative multimodal intervention protocols based on multichannel tDCS montages, neuroimaging methods, and real-time closed-loop systems to guide therapy. This might help to overcome current treatment limitations in poststroke rehabilitation and increase our general understanding of adaptive neuroplasticity leading to neural reorganization after stroke.

The fact that the IEEE 802.15.4 MAC does not fully satisfy the strict wireless body sensor network (BSN) requirements in healthcare systems highlights the need for the design and analysis of new scalable MAC solutions, which guarantee low power consumption to all specific sorts of body sensors and traffic loads. While taking the challenging healthcare requirements into account, this paper aims for the study of energy consumption in BSN scenarios. For that purpose, the IEEE 802.15.4 MAC limitations are first examined, and other potential MAC layer alternatives are further explored. Our intent is to introduce energy-aware radio activation polices into a high-performance distributed queuing medium access control (DQ-MAC) protocol and evaluate its energy-saving achievements, as a function of the network load and the packet length. To do so, a fundamental energy-efficiency theoretical analysis for DQ-MAC protocols is hereby for the first time provided. By means of computer simulations, its performance is validated using IEEE 802.15.4 MAC system parameters.

The regulation of cognitive and emotional processes is critical for proper executive functions and social behavior, but its specific mechanisms remain unknown. Here, we addressed this issue by studying with functional magnetic resonance imaging the changes in network topology that underlie competitive interactions between emotional and cognitive networks in healthy participants. Our behavioral paradigm contrasted periods with high emotional and cognitive demands by including a sadness provocation task followed by a spatial working memory task. We hypothesized that this paradigm would enhance the modularity of emotional and cognitive networks and reveal the hub areas that regulate the flow of information between them. By applying graph analysis methods on functional connectivity between 20 regions of interest in 22 participants we identified two main brain network modules, one cognitive and one emotional, and their hub areas: the left dorsolateral prefrontal cortex (dlPFC) and the left medial frontal pole (mFP). These hub areas did not modulate their mutual functional connectivity following sadness but they did so through an interposed area, the subgenual anterior cingulate cortex (sACC). Our results identify dlPFC and mFP as areas regulating interactions between emotional and cognitive networks, and suggest that their modulation by sadness experience is mediated by sACC.

-The fact that the IEEE 802.15.4 MAC does not fully satisfy the strict wireless body sensor network (BSN) requirements in healthcare systems highlights the need for the design of new scalable MAC solutions, which guarantee low-power consumption to all specific sorts of body sensors and traffic loads. While taking the challenging healthcare requirements into account, this article aims at the study of energy consumption in BSN scenarios. For that purpose, the IEEE 802.15.4 MAC limitations are first examined and other potential MAC layer alternatives further explored. Our intent is to introduce energy-aware radio activation polices into a highperformance distributed queuing medium access control (DQ MAC) protocol and evaluate its energy-saving achievements, as a function of the network load. To do so, a fundamental energy-efficiency theoretical analysis for DQ MAC protocols is hereby for the first time provided. By means of computer simulations, its performance is validated using IEEE 802.15.4 MAC system parameters. The achieved outcome shows that the proposed DQ MAC scheme outperforms IEEE 802.15.4 MAC energy efficiency in all possible BSN scenarios.

Wireless body sensor networks operate under the conflicting requirements of maintaining the desired reliability and message latency of data transmissions, while simultaneously maximizing battery-life of individual body sensors. In doing so, the characteristics of the operating environment, including physical, MAC and application layers have to be considered. The aim of this paper is the study of a novel quality-of-service fuzzy-rule based cross-layer scheduling algorithm under certain selected medical scenarios for body sensor networks optimization. To fulfill the above-mentioned requirements, not only are data packet transmissions scheduled taking the channel quality state among sensors into account, but also their packet waiting time in the accessing system and the specific body sensor applicability. Hereby we utilize an adapted distributed queuing MAC protocol that has recently been proved to be far more energy-efficient than the IEEE 802.15.4 standard for wireless sensor networks.

The regulation of cognitive and emotional processes is critical for proper executive functions and social behavior, but its specific mechanisms remain unknown. Here, we addressed this issue by studying with functional magnetic resonance imaging the changes in network topology that underlie competitive interactions between emotional and cognitive networks in healthy participants. Our behavioral paradigm contrasted periods with high emotional and cognitive demands by including a sadness provocation task followed by a spatial working memory task. The sharp contrast between successive tasks was designed to enhance the separability of emotional and cognitive networks and reveal areas that regulate the flow of information between them (hubs). By applying graph analysis methods on functional connectivity between 20 regions of interest in 22 participants we identified two main brain network modules, one dorsal and one ventral, and their hub areas: the left dorsolateral prefrontal cortex (dlPFC) and the left medial frontal pole (mFP). These hub areas did not modulate their mutual functional connectivity following sadness but they did so through an interposed area, the subgenual anterior cingulate cortex (sACC). Our results identify dlPFC and mFP as areas regulating interactions between emotional and cognitive networks, and suggest that their modulation by sadness experience is mediated by sACC.