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The determinants and driving forces of communication abilities in the locked-in state are poorly understood so far. Results from an experimental-clinical study on a completely paralyzed person involved in communication sessions after the implantation of a microelectrode array were retrospectively analyzed. The aim was to focus on the prerequisites and determinants for learning to control a brain-computer interface for communication in paralysis. A comparative examination of the communication results with the current literature was carried out in light of an ideomotor theory of thinking. We speculate that novel skill learning took place and that several aspects of the wording of sentences during the communication sessions reflect preserved cognitive and conscious processing. We also present some speculations on the operant learning procedure used for communication, which argues for the reformulation of the previously postulated hypothesis of the extinction of response planning and goal-directed ideas in the completely locked-in state. We highlight the importance of feedback and reinforcement in the thought-action-consequence associative chain necessary to maintain purposeful communication. Finally, we underline the necessity to consider the psychosocial context of patients and the duration of complete immobilization as determinants of the 'extinction of thinking' theory and to identify the actual barriers preventing communication in these patients.

Background: Sensory impairment has been related to age-associated cognitive decline. While these associations were investigated primarily in the auditory and visual domain, other senses such as touch have rarely been studied. Thus, it remains open whether these results are specific for particular sensory domains, or rather point to a fundamental role of sensory deficits in cognitive decline., Methods: Data from 31 participants with mild cognitive impairment (MCI), 46 participants with frailty, and 23 non-clinical control participants (NCCs) were included. We assessed sensory function using visual acuity and contrast sensitivity, hearing threshold, and mechanical detection threshold. Cognitive function in participants with MCI was assessed using associative memory performance. Group differences on sensory thresholds were tested using analyses of covariance with age, sex, and years of education as covariates. Associations between measures within participants with MCI were evaluated using Spearman correlations., Findings: We found a significant difference in mechanical detection threshold between the groups (p < 0.001, η 2  = 0.18). Participants with MCI showed significantly reduced tactile sensitivity compared to participants with frailty and NCCs. In participants with MCI, lower associative memory performance was significantly related to reduced tactile sensitivity (r s  = 0.39, p = 0.031) and auditory acuity (r s  = 0.41, p = 0.022)., Interpretation: Our results indicate that reduced tactile sensitivity is related to cognitive decline. Prospective studies should investigate the age-related alterations of multimodal sensory processes and their contribution to dementia-related processes., Funding: Deutsche Forschungsgemeinschaft (FL 156/41-1) and a grant of the Hector-Stiftung II, Weinheim, Germany., Competing Interests: Declaration of interest We declare no competing interests., (Copyright © 2023 The Authors. Published by Elsevier B.V. All rights reserved.)

Background: Loss of sensorimotor stimulation and maladaptive plastic changes of the brain may play a major role in problematic aging phenomena such as frailty. However, it is not clear if interventions specifically targeting neuroplasticity can reverse or slow the development of frailty., Objectives: We compared the effect of a tablet-based neuroplasticity-oriented sensorimotor training (experimental group, EG) and a tablet-based relaxation training (control group, CG) on frailty and sensorimotor brain function., Methods: Interventions consisted of daily 30 min sessions distributed over 90 days. Assessments took place at baseline, after 60 days, and after 90 days. A total of N = 48 frail older adults (EG: n = 24; CG: n = 24) were assigned to the two groups and reassessed after 60 days. Primary outcomes included frailty phenotype (FP) and frailty index (FI). Sensorimotor brain activity was evaluated using functional magnetic resonance imaging and single-pulse transcranial magnetic stimulation., Results: After 60 days of training, both groups showed a reduction in the number of FP criteria (p < 0.001) with a trend towards a significant time-by-group interaction (p = 0.058) indicating a stronger reduction of frailty in the EG (p < 0.001) compared to the CG (p = 0.039). In addition, pain was significantly reduced in the EG but not the CG. No significant effects were found for measures of brain function., Discussion: We provided initial evidence that a neuroplasticity-oriented sensorimotor training could be beneficial in counteracting frailty as well as chronic pain. Further studies are needed to determine the potentially underlying neuroplastic mechanisms and the influence of plasticity-related biomarkers as well as their clinical significance., Trial Registration: ClinicalTrials.gov NCT03666039 (registered 11 September 2018)., Competing Interests: Declaration of Competing Interest 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., (Copyright © 2023 Elsevier B.V. All rights reserved.)

Although investigation of the brains of criminals began quite early in the history of psychophysiological research, little is known about brain plasticity of offenders with psychopathy. Building on our preliminary study reporting successful brain self-regulation using slow cortical potential (SCP) neurofeedback in offenders with psychopathy, we investigated the central nervous and autonomic peripheral changes occurring after brain self-regulation in a group of severe male offenders with psychopathy. Regarding the central nervous system, an overall suppression of the psychopathic overrepresentation of slow frequency bands was found, such as delta and theta band activity, after EEG neurofeedback. In addition, an increase in alpha band activity could be observed after the SCP self-regulation training. Electrodermal activity adaptively changed according to the regulation task, and this flexibility improved over training time. The results of this study point towards a constructive learning process and plasticity in neural and peripheral measures of offenders with psychopathy., Competing Interests: The authors have declared that no competing interests exist.

Introduction: Dementia (particularly Alzheimer's disease, AD) is a major cause of impaired cognitive functions in the elderly. Amnestic mild cognitive impairment (aMCI) is a prodromal stage of AD, if substantiated by Alzheimer biomarkers. A neuroscientific model of pathological ageing emphasises the loss of brain plasticity, sensorimotor capacities and subsequent cognitive decline. A mechanistic treatment targeting dysfunctional plastic changes associated with ageing should be efficacious in delaying AD. In this trial, we aim to evaluate the effectiveness of a newly developed sensorimotor training, delivered at home, combined with personalised reinforcement, on the progression of aMCI-related cognitive impairments., Methods and Analysis: In a randomised trial, we will compare two aMCI groups (30 subjects each), randomly allocated to a sensorimotor or a cognitive control training. Both trainings consist of an adaptive algorithm, and will last 3 months each. We hypothesise that both trainings will have positive effects on cognitive function with the sensorimotor training being superior compared with the control training based on its improvement in basic perceptual skills underlying memory encoding and retrieval. The primary outcome is episodic memory function, improved hippocampal function during memory tasks will be a secondary outcome. As further exploratory outcomes, we expect improved segregation in sensory and motor maps, better sensory discrimination only in the sensorimotor training and reduced transition to dementia (examined after completion of this study). We expect the experimental training to be evaluated more positively by the users compared with the cognitive training, resulting in reduced rates of discontinuation., Ethics and Dissemination: The Ethics Committee of the Medical Faculty Mannheim, Heidelberg University, approved the study (2015-543N-MA), which adheres to the Declaration of Helsinki. The results will be published in a peer-reviewed journal. Access to raw data is available on request., Trial Registration Number: DRKS00012748., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2019. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)

[This corrects the article DOI: 10.1371/journal.pbio.1002593.].

Dopamine systems mediate key aspects of reward learning. Parkinson's disease (PD) represents a valuable model to study reward mechanisms because both the disease process and the anti-Parkinson medications influence dopamine neurotransmission. The aim of this pilot study was to investigate whether the level of levodopa differently modulates learning from positive and negative feedback and its electrophysiological correlate, the error related negativity (ERN), in PD. Ten PD patients and ten healthy participants performed a two-stage reinforcement learning task. In the Learning Phase, they had to learn the correct stimulus within a stimulus pair on the basis of a probabilistic positive or negative feedback. Three sets of stimulus pairs were used. In the Testing Phase, the participants were tested with novel combinations of the stimuli previously experienced to evaluate whether they learned more from positive or negative feedback. PD patients performed the task both ON- and OFF-levodopa in two separate sessions while they remained on stable therapy with dopamine agonists. The electroencephalogram (EEG) was recorded during the task. PD patients were less accurate in negative than positive learning both OFF- and ON-levodopa. In the OFF-levodopa state they were less accurate than controls in negative learning. PD patients had a smaller ERN amplitude OFF- than ON-levodopa only in negative learning. In the OFF-levodopa state they had a smaller ERN amplitude than controls in negative learning. We hypothesize that high tonic dopaminergic stimulation due to the dopamine agonist medication, combined to the low level of phasic dopamine due to the OFF-levodopa state, could prevent phasic "dopamine dips" indicated by the ERN needed for learning from negative feedback.

Objective of this study was to evaluate attentional control mechanisms in amyotrophic lateral sclerosis (ALS) using an auditory event-related potentials (ERPs) paradigm. Fifteen mild to moderate ALS patients and 15 healthy controls were administered a brief neuropsychological test battery and an ERPs paradigm assessing selective attention. Four types of auditory stimuli were presented in random order: short standard (200 Hz, 200 ms), long standard (200 Hz, 500 ms), short deviant (1000 Hz, 200 ms) and long deviant (1000 Hz, 500 ms). Participants had to respond to the long deviant stimuli only. During the task the electroencephalogram (EEG) was recorded. The N200, P300 and re-orienting negativity (RON) ERP components were analysed. Compared to controls ALS patients showed reduced amplitudes and delayed latencies of N200, P300 and RON. These results could be attributable to both an alteration in change detection resulting in a reduction of the allocation and re-orientation of attentional resources or a general slowing or reduction of neural processing efficiency in the same system. The ERPs results support the hypothesis that ALS involves extramotor cognitive functions including auditory attentional processing at all processing stages, early (200 ms) and late (300-600 ms). These data prove the usefulness and sensitivity of the auditory ERPs in detection of cognitive functions in ALS patients.

Early detection of movement intention could possibly minimize the delays in the activation of neuroprosthetic devices. As yet, single trial analysis using non-invasive approaches for understanding such movement preparation remains a challenging task. We studied the feasibility of predicting movement directions in self-paced upper limb center-out reaching tasks, i.e., spontaneous movements executed without an external cue that can better reflect natural motor behavior in humans. We reported results of non-invasive electroencephalography (EEG) recorded from mild stroke patients and able-bodied participants. Previous studies have shown that low frequency EEG oscillations are modulated by the intent to move and therefore, can be decoded prior to the movement execution. Motivated by these results, we investigated whether slow cortical potentials (SCPs) preceding movement onset can be used to classify reaching directions and evaluated the performance using 5-fold cross-validation. For able-bodied subjects, we obtained an average decoding accuracy of 76% (chance level of 25%) at 62.5 ms before onset using the amplitude of on-going SCPs with above chance level performances between 875 to 437.5 ms prior to onset. The decoding accuracy for the stroke patients was on average 47% with their paretic arms. Comparison of the decoding accuracy across different frequency ranges (i.e., SCPs, delta, theta, alpha, and gamma) yielded the best accuracy using SCPs filtered between 0.1 to 1 Hz. Across all the subjects, including stroke subjects, the best selected features were obtained mostly from the fronto-parietal regions, hence consistent with previous neurophysiological studies on arm reaching tasks. In summary, we concluded that SCPs allow the possibility of single trial decoding of reaching directions at least 312.5 ms before onset of reach.

Despite considerable growth in the field of brain-computer or brain-machine interface (BCI/BMI) research reflected in several hundred publications each year, little progress was made to enable patients in complete locked-in state (CLIS) to reliably communicate using their brain activity. Independent of the invasiveness of the BCI systems tested, no sustained direct brain control and communication was demonstrated in a patient in CLIS so far. This suggested a more fundamental theoretical problem of learning and attention in brain communication with BCI/BMI, formulated in the extinction-of-thought hypothesis. While operant conditioning and goal-directed thinking seems impaired in complete paralysis, classical conditioning of brain responses might represent the only alternative. First experimental studies in CLIS using semantic conditioning support this assumption. Evidence that quality-of-life in locked-in-state is not as limited and poor as generally believed draise doubts that "patient wills" or "advanced directives"signed long-before the locked-in-state are useful. On the contrary, they might be used as an excuse to shorten anticipated long periods of care for these patients avoiding associated financial and social burdens. Current state and availability of BCI/BMI systems urge a broader societal discourse on the pressing ethical challenges associated with the advancements in neurotechnology and BCI/BMI research.

A major clinical goal of brain-computer interfaces (BCIs) is to allow severely paralyzed patients to communicate their needs and thoughts during their everyday lives. Among others, P300-based BCIs, which resort to EEG measurements, have been successfully operated by people with severe neuromuscular disabilities. Besides reducing the number of stimuli repetitions needed to detect the P300, a current challenge in P300-based BCI research is the simplification of system's setup and maintenance by lowering the number N of recording channels. By using offline data collected in 30 subjects (21 amyotrophic lateral sclerosis patients and 9 controls) through a clinical BCI with N = 5 channels, in the present paper we show that a preprocessing approach based on a Bayesian single-trial ERP estimation technique allows reducing N to 1 without affecting the system's accuracy. The potentially great benefit for the practical usability of BCI devices (including patient acceptance) that would be given by the reduction of the number N of channels encourages further development of the present study, for example, in an online setting.

In a proof-of-principle prototypical demonstration we describe a new type of brain-machine interface (BMI) paradigm for upper limb motor-training. The proposed technique allows a fast contingent and proportionally modulated stimulation of afferent proprioceptive and motor output neural pathways using operant learning. Continuous and immediate assisted-feedback of force proportional to rolandic rhythm oscillations during actual movements was employed and illustrated with a single case experiment. One hemiplegic patient was trained for 2 weeks coupling somatosensory brain oscillations with force-field control during a robot-mediated center-out motor-task whose execution approaches movements of everyday life. The robot facilitated actual movements adding a modulated force directed to the target, thus providing a non-delayed proprioceptive feedback. Neuro-electric, kinematic, and motor-behavioral measures were recorded in pre- and post-assessments without force assistance. Patient's healthy arm was used as control since neither a placebo control was possible nor other control conditions. We observed a generalized and significant kinematic improvement in the affected arm and a spatial accuracy improvement in both arms, together with an increase and focalization of the somatosensory rhythm changes used to provide assisted-force-feedback. The interpretation of the neurophysiological and kinematic evidences reported here is strictly related to the repetition of the motor-task and the presence of the assisted-force-feedback. Results are described as systematic observations only, without firm conclusions about the effectiveness of the methodology. In this prototypical view, the design of appropriate control conditions is discussed. This study presents a novel operant-learning-based BMI-application for motor-training coupling brain oscillations and force feedback during an actual movement.

Our objective was to investigate the relationship between brain-computer interface (BCI) communication skill and disease progression in amyotrophic lateral sclerosis (ALS). We sought also to assess stability of BCI communication performance over time and whether it is related to the progression of neurological impairment before entering the locked-in state. A three years follow-up, BCI evaluation in a group of ALS patients (n = 24) was conducted. For a variety of reasons only three patients completed the three years follow-up. BCI communication skill and disability level, using the Amyotrophic Lateral Sclerosis Functional Rating Scale-Revised, were assessed at admission and at each of the three follow-ups. Multiple non-parametric statistical methods were used to ensure reliability of the dependent variables: correlations, paired test and factor analysis of variance. Results demonstrated no significant relationship between BCI communication skill (BCI-CS) and disease evolution. The patients who performed the follow-up evaluations preserved their BCI-CS over time. Patients' age at admission correlated positively with the ability to achieve control over a BCI. In conclusion, disease evolution in ALS does not affect the ability to control a BCI for communication. BCI performance can be maintained in the different stages of the illness.

Background: Brain-computer interfaces (BCIs) allow people to control devices by translating brain signals into commands. BCIs represent a concrete solution with regard to communication and motor control disabilities of patients with amyotrophic lateral sclerosis (ALS). Most of the BCIs rely on visual interfaces in which patients must move their eyes to achieve efficient BCI control. This fact represents a limitation of BCI use in ALS patients who are in the final stages of the disease., Objective: We aimed to improve visual interfaces for ALS patients to control the movement of a cursor on a monitor by orienting their covert visuospatial attention (i.e., orienting without eye movements)., Methods: A total of 10 ALS patients with different levels of impairment used 2 new visual interfaces in an event-related potential (ERP)-based BCI. In the first interface, they were required to use exogenous visuospatial attention orienting (VAO), whereas in the second interface, they were required to use endogenous VAO., Results: . ALS patients were able to use the 2 interfaces for controlling the ERP-based BCI system in real time. Nevertheless, better target classification and information transfer rate were associated with the interface that was based on endogenous VAO., Conclusions: ALS patients can exploit their covert VAO to control a BCI that does not require eye movements. The implementation of endogenous VAO in the design of covert visuospatial attention-based interfaces seems to be suitable for designing more ergonomic and efficient BCIs for ALS patients with impaired eye movements.

Patients in the completely locked-in state have no means of communication and they represent the target population for brain-computer interface research in the last 15 years. Although different paradigms have been tested and different physiological signals used, to date no sufficiently documented completely locked-in state patient was able to control a brain-computer interface over an extended time period. We introduce Pavlovian semantic conditioning to enable basic communication in completely locked-in state. This novel paradigm is based on semantic conditioning for online classification of neuroelectric or any other physiological signals to discriminate between covert (cognitive) 'yes' and 'no' responses. The paradigm comprised the presentation of affirmative and negative statements used as conditioned stimuli, while the unconditioned stimulus consisted of electrical stimulation of the skin paired with affirmative statements. Three patients with advanced amyotrophic lateral sclerosis participated over an extended time period, one of which was in a completely locked-in state, the other two in the locked-in state. The patients' level of vigilance was assessed through auditory oddball procedures to study the correlation between vigilance level and the classifier's performance. The average online classification accuracies of slow cortical components of electroencephalographic signals were around chance level for all the patients. The use of a non-linear classifier in the offline classification procedure resulted in a substantial improvement of the accuracy in one locked-in state patient achieving 70% correct classification. A reliable level of performance in the completely locked-in state patient was not achieved uniformly throughout the 37 sessions despite intact cognitive processing capacity, but in some sessions communication accuracies up to 70% were achieved. Paradigm modifications are proposed. Rapid drop of vigilance was detected suggesting attentional variations or variations of circadian period as important factors in brain-computer interface communication with locked-in state and completely locked-in state.

We investigated whether the covert orienting of visuospatial attention can be effectively used in a brain-computer interface guided by event-related potentials. Three visual interfaces were tested: one interface that activated voluntary orienting of visuospatial attention and two interfaces that elicited automatic orienting of visuospatial attention. We used two epoch classification procedures. The online epoch classification was performed via Independent Component Analysis, and then it was followed by fixed features extraction and support vector machines classification. The offline epoch classification was performed by means of a genetic algorithm that permitted us to retrieve the relevant features of the signal, and then to categorise the features with a logistic classifier. The offline classification, but not the online one, allowed us to differentiate between the performances of the interface that required voluntary orienting of visuospatial attention and those that required automatic orienting of visuospatial attention. The offline classification revealed an advantage of the participants in using the "voluntary" interface. This advantage was further supported, for the first time, by neurophysiological data. Moreover, epoch analysis was performed better with the "genetic algorithm classifier" than with the "independent component analysis classifier". We suggest that the combined use of voluntary orienting of visuospatial attention and of a classifier that permits feature extraction ad personam (i.e., genetic algorithm classifier) can lead to a more efficient control of visual BCIs.

The experimental findings herein reported are aimed at gaining a perspective on the complex neural events that follow lesions of the motor cortical areas. Cortical damage, whether by trauma or stroke, interferes with the flow of descending signals to the modular interneuronal structures of the spinal cord. These spinal modules subserve normal motor behaviors by activating groups of muscles as individual units (muscle synergies). Damage to the motor cortical areas disrupts the orchestration of the modules, resulting in abnormal movements. To gain insights into this complex process, we recorded myoelectric signals from multiple upper-limb muscles in subjects with cortical lesions. We used a factorization algorithm to identify the muscle synergies. Our factorization analysis revealed, in a quantitative way, three distinct patterns of muscle coordination-including preservation, merging, and fractionation of muscle synergies-that reflect the multiple neural responses that occur after cortical damage. These patterns varied as a function of both the severity of functional impairment and the temporal distance from stroke onset. We think these muscle-synergy patterns can be used as physiological markers of the status of any patient with stroke or trauma, thereby guiding the development of different rehabilitation approaches, as well as future physiological experiments for a further understanding of postinjury mechanisms of motor control and recovery.

Future neuroprosthetic devices, in particular upper limb, will require decoding and executing not only the user's intended movement type, but also when the user intends to execute the movement. This work investigates the potential use of brain signals recorded non-invasively for detecting the time before a self-paced reaching movement is initiated which could contribute to the design of practical upper limb neuroprosthetics. In particular, we show the detection of self-paced reaching movement intention in single trials using the readiness potential, an electroencephalography (EEG) slow cortical potential (SCP) computed in a narrow frequency range (0.1-1 Hz). Our experiments with 12 human volunteers, two of them stroke subjects, yield high detection rates prior to the movement onset and low detection rates during the non-movement intention period. With the proposed approach, movement intention was detected around 500 ms before actual onset, which clearly matches previous literature on readiness potentials. Interestingly, the result obtained with one of the stroke subjects is coherent with those achieved in healthy subjects, with single-trial performance of up to 92% for the paretic arm. These results suggest that, apart from contributing to our understanding of voluntary motor control for designing more advanced neuroprostheses, our work could also have a direct impact on advancing robot-assisted neurorehabilitation.

The paper presents some speculations on the loss of voluntary responses and operant learning in long-term paralysis in human patients and curarized rats. Based on a reformulation of the ideomotor thinking hypothesis already described in the 19th century, we present evidence that instrumentally learned responses and intentional cognitive processes extinguish as a consequence of long-term complete paralysis in patients with amyotrophic lateral sclerosis (ALS). Preliminary data collected with ALS patients during extended and complete paralysis suggest semantic classical conditioning of brain activity as the only remaining communication possibility in those states.

Brain-computer interface (BCI) technology has been used for rehabilitation after stroke and there are a number of reports involving stroke patients in BCI-feedback training. Most publications have demonstrated the efficacy of BCI technology in post-stroke rehabilitation using output devices such as Functional Electrical Stimulation, robot, and orthosis. The aim of this review is to focus on the progress of BCI-based rehabilitation strategies and to underline future challenges. A brief history of clinical BCI-approaches is presented focusing on stroke motor rehabilitation. A context for three approaches of a BCI-based motor rehabilitation program is outlined: the substitutive strategy, classical conditioning and operant conditioning. Furthermore, we include an overview of a pilot study concerning a new neuro-forcefeedback strategy. This pilot study involved healthy participants. Finally we address some challenges for future BCI-based rehabilitation.

Production of voluntary movements relies critically on the functional integration of several motor cortical areas, such as the primary motor cortex, and the spinal circuitries. Surprisingly, after almost 40 years of research, how the motor cortices specify descending neural signals destined for the downstream interneurons and motoneurons has remained elusive. In light of the many recent experimental demonstrations that the motor system may coordinate muscle activations through a linear combination of muscle synergies, we hypothesize that the motor cortices may function to select and activate fixed muscle synergies specified by the spinal or brainstem networks. To test this hypothesis, we recorded electromyograms (EMGs) from 12-16 upper arm and shoulder muscles from both the unaffected and the stroke-affected arms of stroke patients having moderate-to-severe unilateral ischemic lesions in the frontal motor cortical areas. Analyses of EMGs using a nonnegative matrix factorization algorithm revealed that in seven of eight patients the muscular compositions of the synergies for both the unaffected and the affected arms were strikingly similar to each other despite differences in motor performance between the arms, and differences in cerebral lesion sizes and locations between patients. This robustness of muscle synergies that we observed supports the notion that descending cortical signals represent neuronal drives that select, activate, and flexibly combine muscle synergies specified by networks in the spinal cord and/or brainstem. Our conclusion also suggests an approach to stroke rehabilitation by focusing on those synergies with altered activations after stroke.