Using real-time fMRI neurofeedback to restore right occipital cortex activity in patients with left visuo-spatial neglect: proof-of-principle and preliminary results

Targeted neurorehabilitation strategies in post-stroke aphasia

BACKGROUND

Aphasia is a debilitating language impairment, affecting millions of people worldwide. About 40% of stroke survivors develop chronic aphasia, resulting in life-long disability.

OBJECTIVE

This review examines extrinsic and intrinsic neuromodulation techniques, aimed at enhancing the effects of speech and language therapies in stroke survivors with aphasia.

METHODS

We discuss the available evidence supporting the use of transcranial direct current stimulation (tDCS), repetitive transcranial magnetic stimulation, and functional MRI (fMRI) real-time neurofeedback in aphasia rehabilitation.

RESULTS

This review systematically evaluates studies focusing on efficacy and implementation of specialized methods for post-treatment outcome optimization and transfer to functional skills. It considers stimulation target determination and various targeting approaches. The translation of neuromodulation interventions to clinical practice is explored, emphasizing generalization and functional communication. The review also covers real-time fMRI neurofeedback, discussing current evidence for efficacy and essential implementation parameters. Finally, we address future directions for neuromodulation research in aphasia.

CONCLUSIONS

This comprehensive review aims to serve as a resource for a broad audience of researchers and clinicians interested in incorporating neuromodulation for advancing aphasia care.

Virtual reality-based sensorimotor adaptation shapes subsequent spontaneous and naturalistic stimulus-driven brain activity

Our everyday life summons numerous novel sensorimotor experiences, to which our brain needs to adapt in order to function properly. However, tracking plasticity of naturalistic behavior and associated brain modulations is challenging. Here, we tackled this question implementing a prism adaptation-like training in virtual reality (VRPA) in combination with functional neuroimaging. Three groups of healthy participants (N = 45) underwent VRPA (with a shift either to the left/right side, or with no shift), and performed functional magnetic resonance imaging (fMRI) sessions before and after training. To capture modulations in free-flowing, task-free brain activity, the fMRI sessions included resting-state and free-viewing of naturalistic videos. We found significant decreases in spontaneous functional connectivity between attentional and default mode (DMN)/fronto-parietal networks, only for the adaptation groups, more pronouncedly in the hemisphere contralateral to the induced shift. In addition, VRPA was found to bias visual responses to naturalistic videos: Following rightward adaptation, we found upregulation of visual response in an area in the parieto-occipital sulcus (POS) only in the right hemisphere. Notably, the extent of POS upregulation correlated with the size of the VRPA-induced after-effect measured in behavioral tests. This study demonstrates that a brief VRPA exposure can change large-scale cortical connectivity and correspondingly bias visual responses to naturalistic sensory inputs.

Poststroke Cognitive Impairment Research Progress on Application of Brain-Computer Interface

Brain-computer interfaces (BCIs), a new type of rehabilitation technology, pick up nerve cell signals, identify and classify their activities, and convert them into computer-recognized instructions. This technique has been widely used in the rehabilitation of stroke patients in recent years and appears to promote motor function recovery after stroke. At present, the application of BCI in poststroke cognitive impairment is increasing, which is a common complication that also affects the rehabilitation process. This paper reviews the promise and potential drawbacks of using BCI to treat poststroke cognitive impairment, providing a solid theoretical basis for the application of BCI in this area.

Real-time fMRI and EEG neurofeedback: A perspective on applications for the rehabilitation of spatial neglect

Spatial neglect is a neuropsychological syndrome characterized by a failure to orient, perceive, and act toward the contralesional side of the space after brain injury. Neglect is one of the most frequent and disabling neuropsychological syndromes following right-hemisphere damage, often persisting in the chronic phase and responsible for a poor functional outcome at hospital discharge. Different rehabilitation approaches have been proposed over the past 60 years, with a variable degree of effectiveness. In this point-of-view article, we describe a new rehabilitation technique for spatial neglect that directly targets brain activity and pathological physiological processes: namely, neurofeedback (NFB) with real-time brain imaging methodologies. In recent proof-of-principle studies, we have demonstrated the potential of this rehabilitation technique. Using real-time functional MRI (rt-fMRI) NFB in chronic neglect, we demonstrated that patients are able to upregulate their right visual cortex activity, a response that is otherwise reduced due to losses in top-down attentional signals. Using real-time electroencephalography NFB in patients with acute or chronic condition, we showed successful regulation with partial restoration of brain rhythm dynamics over the damaged hemisphere. Both approaches were followed by mild, but encouraging, improvement in neglect symptoms. NFB techniques, by training endogenous top-down modulation of attentional control on sensory processing, might induce sustained changes at both the neural and behavioral levels, while being non-invasive and safe. However, more properly powered clinical studies with control groups and longer follow-up are needed to fully establish the effectiveness of the techniques, identify the most suitable candidates, and determine how the techniques can be optimized or combined in the context of rehabilitation.

Predictors of real-time fMRI neurofeedback performance and improvement - A machine learning mega-analysis

Real-time fMRI neurofeedback is an increasingly popular neuroimaging technique that allows an individual to gain control over his/her own brain signals, which can lead to improvements in behavior in healthy participants as well as to improvements of clinical symptoms in patient populations. However, a considerably large ratio of participants undergoing neurofeedback training do not learn to control their own brain signals and, consequently, do not benefit from neurofeedback interventions, which limits clinical efficacy of neurofeedback interventions. As neurofeedback success varies between studies and participants, it is important to identify factors that might influence neurofeedback success. Here, for the first time, we employed a big data machine learning approach to investigate the influence of 20 different design-specific (e.g. activity vs. connectivity feedback), region of interest-specific (e.g. cortical vs. subcortical) and subject-specific factors (e.g. age) on neurofeedback performance and improvement in 608 participants from 28 independent experiments. With a classification accuracy of 60% (considerably different from chance level), we identified two factors that significantly influenced neurofeedback performance: Both the inclusion of a pre-training no-feedback run before neurofeedback training and neurofeedback training of patients as compared to healthy participants were associated with better neurofeedback performance. The positive effect of pre-training no-feedback runs on neurofeedback performance might be due to the familiarization of participants with the neurofeedback setup and the mental imagery task before neurofeedback training runs. Better performance of patients as compared to healthy participants might be driven by higher motivation of patients, higher ranges for the regulation of dysfunctional brain signals, or a more extensive piloting of clinical experimental paradigms. Due to the large heterogeneity of our dataset, these findings likely generalize across neurofeedback studies, thus providing guidance for designing more efficient neurofeedback studies specifically for improving clinical neurofeedback-based interventions. To facilitate the development of data-driven recommendations for specific design details and subpopulations the field would benefit from stronger engagement in open science research practices and data sharing.

Modulating the interhemispheric activity balance in the intraparietal sulcus using real-time fMRI neurofeedback: Development and proof-of-concept

The intraparietal sulcus (IPS) plays a key role in the distribution of attention across the visual field. In stroke patients, an imbalance between left and right IPS activity has been related to a spatial bias in visual attention characteristic of hemispatial neglect. In this study, we describe the development and implementation of a real-time functional magnetic resonance imaging neurofeedback protocol to noninvasively and volitionally control the interhemispheric IPS activity balance in neurologically healthy participants. Six participants performed three neurofeedback training sessions across three weeks. Half of them trained to voluntarily increase brain activity in left relative to right IPS, while the other half trained to regulate the IPS activity balance in the opposite direction. Before and after the training, we estimated the distribution of attention across the visual field using a whole and partial report task. Over the course of the training, two of the three participants in the left-IPS group increased the activity in the left relative to the right IPS, while the participants in the right-IPS group were not able to regulate the interhemispheric IPS activity balance. We found no evidence for a decrease in resting-state functional connectivity between left and right IPS, and the spatial distribution of attention did not change over the course of the experiment. This study indicates the possibility to voluntarily modulate the interhemispheric IPS activity balance. Further research is warranted to examine the effectiveness of this technique in the rehabilitation of post-stroke hemispatial neglect.

Visuo-spatial attention to the blind hemifield of hemianopic patients: Can it survive the impairment of visual awareness?

The general aim of this study was to assess the effect produced by visuo-spatial attention on both behavioural performance and brain activation in hemianopic patients following visual stimulus presentation to the blind hemifield. To do that, we tested five hemianopic patients and six age-matched healthy controls in an MRI scanner during the execution of a Posner-like paradigm using a predictive central cue. Participants were instructed to covertly orient attention toward the blind or sighted hemifield in different blocks while discriminating the orientation of a visual grating. In patients, we found significantly faster reaction times (RT) in valid and neutral than invalid trials not only in the sighted but also in the blind hemifield, despite the impairment of consciousness and performance at chance. As to the fMRI signal, in valid trials we observed the activation of ipsilesional visual areas (mainly lingual gyrus - area 19) during the orientation of attention toward the blind hemifield. Importantly, this activation was similar in patients and controls. In order to assess the related functional network, we performed a psychophysiological interactions (PPI) analysis that revealed an increased functional connectivity (FC) in patients with respect to controls between the ipsilesional lingual gyrus and ipsilateral fronto-parietal as well as contralesional parietal regions. Moreover, the shift of attention from the blind to the sighted hemifield revealed stronger FC between the contralesional visual areas V3/V4 and ipsilateral parietal regions in patients than controls. These results indicate a higher cognitive effort in patients when paying attention to the blind hemifiled or when shifting attention from the blind to the sighted hemfield, possibly as an attempt to compensate for the visual loss. Taken together, these results show that hemianopic patients can covertly orient attention toward the blind hemifield with a top-down mechanism by activating a functional network mainly including fronto-parietal regions belonging to the dorsal attentional network.

A systematic review of fMRI neurofeedback reporting and effects in clinical populations

Real-time fMRI-based neurofeedback is a relatively young field with a potential to impact the currently available treatments of various disorders. In order to evaluate the evidence of clinical benefits and investigate how consistently studies report their methods and results, an exhaustive search of fMRI neurofeedback studies in clinical populations was performed. Reporting was evaluated using a limited number of Consensus on the reporting and experimental design of clinical and cognitive-behavioral neurofeedback studies (CRED-NF checklist) items, which was, together with a statistical power and sensitivity calculation, used to also evaluate the existing evidence of the neurofeedback benefits on clinical measures. The 62 found studies investigated regulation abilities and/or clinical benefits in a wide range of disorders, but with small sample sizes and were therefore unable to detect small effects. Most points from the CRED-NF checklist were adequately reported by the majority of the studies, but some improvements are suggested for the reporting of group comparisons and relations between regulation success and clinical benefits. To establish fMRI neurofeedback as a clinical tool, more emphasis should be placed in the future on using larger sample sizes determined through a priori power calculations and standardization of procedures and reporting.

The effects of psychiatric history and age on self-regulation of the default mode network

Real-time neurofeedback enables human subjects to learn to regulate their brain activity, effecting behavioral changes and improvements of psychiatric symptomatology. Neurofeedback up-regulation and down-regulation have been assumed to share common neural correlates. Neuropsychiatric pathology and aging incur suboptimal functioning of the default mode network. Despite the exponential increase in real-time neuroimaging studies, the effects of aging, pathology and the direction of regulation on neurofeedback performance remain largely unknown. Using real-time fMRI data shared through the Rockland Sample Real-Time Neurofeedback project (N = 136) and open-access analyses, we first modeled neurofeedback performance and learning in a group of subjects with psychiatric history (n_a = 74) and a healthy control group (n_b = 62). Subsequently, we examined the relationship between up-regulation and down-regulation learning, the relationship between age and neurofeedback performance in each group and differences in neurofeedback performance between the two groups. For interpretative purposes, we also investigated functional connectomics prior to neurofeedback. Results show that in an initial session of default mode network neurofeedback with real-time fMRI, up-regulation and down-regulation learning scores are negatively correlated. This finding is related to resting state differences in the eigenvector centrality of the posterior cingulate cortex. Moreover, age correlates negatively with default mode network neurofeedback performance, only in absence of psychiatric history. Finally, adults with psychiatric history outperform healthy controls in default mode network up-regulation. Interestingly, the performance difference is related to no up-regulation learning in controls. This finding is supported by marginally higher default mode network centrality during resting state, in the presence of psychiatric history.

Neurofeedback: Principles, appraisal, and outstanding issues

Neurofeedback is a form of brain training in which subjects are fed back information about some measure of their brain activity which they are instructed to modify in a way thought to be functionally advantageous. Over the last 20 years, neurofeedback has been used to treat various neurological and psychiatric conditions, and to improve cognitive function in various contexts. However, in spite of a growing popularity, neurofeedback protocols typically make (often covert) assumptions on what aspects of brain activity to target, where in the brain to act and how, which have far-reaching implications for the assessment of its potential and efficacy. Here we critically examine some conceptual and methodological issues associated with the way neurofeedback's general objectives and neural targets are defined. The neural mechanisms through which neurofeedback may act at various spatial and temporal scales, and the way its efficacy is appraised are reviewed, and the extent to which neurofeedback may be used to control functional brain activity discussed. Finally, it is proposed that gauging neurofeedback's potential, as well as assessing and improving its efficacy will require better understanding of various fundamental aspects of brain dynamics and a more precise definition of functional brain activity and brain-behaviour relationships.

EEG-based neglect assessment: A feasibility study

BACKGROUND

Spatial neglect (SN) is a neuropsychological syndrome that impairs automatic attention orienting to stimuli in the contralesional visual space of stroke patients. SN is commonly assessed using paper and pencil tests. Recently, computerized tests have been proposed to provide a dynamic assessment of SN. However, both paper- and computer-based methods have limitations.

NEW METHOD

Electroencephalography (EEG) shows promise for overcoming the limitations of current assessment methods. The aim of this work is to introduce an objective passive BCI system that records EEG signals in response to visual stimuli appearing in random locations on a screen with a dynamically changing background. Our preliminary experimental studies focused on validating the system using healthy participants with intact brains rather than employing it initially in more complex environments with patients having cortical lesions. Therefore, we designed a version of the test in which we simulated SN by hiding target stimuli appearing on the left side of the screen so that the subject's attention is shifted to the right side.

RESULTS

Results showed that there are statistically significant differences between EEG responses due to right and left side stimuli reflecting different processing and attention levels towards both sides of the screen. The system achieved average accuracy, sensitivity and specificity of 74.24%, 75.17% and 71.36% respectively.

COMPARISON WITH EXISTING METHODS

The proposed test can examine both presence and severity of SN, unlike traditional paper and pencil tests and computer-based methods.

CONCLUSIONS

The proposed test is a promising objective SN evaluation method.

The potential of real-time fMRI neurofeedback for stroke rehabilitation: A systematic review

Real-time functional magnetic resonance imaging (rt-fMRI) neurofeedback aids the modulation of neural functions by training self-regulation of brain activity through operant conditioning. This technique has been applied to treat several neurodevelopmental and neuropsychiatric disorders, but its effectiveness for stroke rehabilitation has not been examined yet. Here, we systematically review the effectiveness of rt-fMRI neurofeedback training in modulating motor and cognitive processes that are often impaired after stroke. Based on predefined search criteria, we selected and examined 33 rt-fMRI neurofeedback studies, including 651 healthy individuals and 15 stroke patients in total. The results of our systematic review suggest that rt-fMRI neurofeedback training can lead to a learned modulation of brain signals, with associated changes at both the neural and the behavioural level. However, more research is needed to establish how its use can be optimized in the context of stroke rehabilitation.