Pinpointing the precise stimulation targets for brain rehabilitation in early-stage Parkinson's disease.

BACKGROUND: Transcranial magnetic stimulation (TMS) is increasingly used as a promising non-pharmacological treatment for Parkinson's disease (PD). Scalp-to-cortex distance (SCD), as a key technical parameter of TMS, plays a critical role in determining the locations of treatment targets and corresponding dosage. Due to the discrepancies in TMS protocols, the optimal targets and head models have yet to be established in PD patients. OBJECTIVE: To investigate the SCDs of the most popular used targets in left dorsolateral prefrontal cortex (DLPFC) and quantify its impact on the TMS-induced electric fields (E-fields) in early-stage PD patients. METHODS: Structural magnetic resonance imaging scans from PD patients (n = 47) and normal controls (n = 36) were drawn from the NEUROCON and Tao Wu datasets. SCD of left DLPFC was measured by Euclidean Distance in TMS Navigation system. The intensity and focality of SCD-dependent E-fields were examined and quantified using Finite Element Method. RESULTS: Early-stage PD patients showed an increased SCDs, higher variances in the SCDs and SCD-dependent E-fields across the seven targets of left DLPFC than normal controls. The stimulation targets located on gyral crown had more focal and homogeneous E-fields. The SCD of left DLPFC had a better performance in differentiating early-stage PD patients than global cognition and other brain measures. CONCLUSION: SCD and SCD-dependent E-fields could determine the optimal TMS treatment targets and may also be used as a novel marker to differentiate early-stage PD patients. Our findings have important implications for developing optimal TMS protocols and personalized dosimetry in real-world clinical practice.

Clinical and radiomic features for predicting the treatment response of repetitive transcranial magnetic stimulation in major neurocognitive disorder: Results from a randomized controlled trial.

Image-guided repetitive transcranial magnetic stimulation (rTMS) has shown clinical effectiveness in senior adults with co-occurring depression and cognitive impairment, yet the imaging markers for predicting the treatment response are less investigated. In this clinical trial, we examined the efficacy and sustainability of 10 Hz rTMS for the treatment of depression and cognitive impairment in major neurocognitive disorder (NCD) patients and tested the predictive values of imaging-informed radiomic features in response to rTMS treatment. Fifty-five major NCD patients with depression were randomly assigned to receive a 3-week rTMS treatment of either active 10 Hz rTMS (n = 27) or sham rTMS (n = 28). Left dorsolateral prefrontal cortex (DLPFC) was the predefined treatment target. Based on individual structural magnetic resonance imaging scans, surface-based analysis was conducted to quantitatively measure the baseline radiomic features of left DLPFC. Severity of depression, global cognition and the serum brain-derived neurotrophic factor (BDNF) level were evaluated at baseline, 3-, 6- and 12-week follow-ups. Logistic regression analysis revealed that advanced age, higher baseline cognition and randomized group were associated with the remission of depression. Increased cortical thickness and gyrification in left DLPFC were the significant predictors of clinical remission and cognitive enhancement. A 3-week course of 10 Hz rTMS is an effective adjuvant treatment for rapid ameliorating depressive symptoms and enhancing cognitive function. Pre-treatment radiomic features of the stimulation target can predict the response to rTMS treatment in major NCD. Cortical thickness and folding of treatment target may serve as imaging markers to detect the responders. ChiCTR-IOR-16008191, registered on March 30, 2016.

Dynamic changes of region-specific cortical features and scalp-to-cortex distance: implications for transcranial current stimulation modeling.

BACKGROUND: Transcranial current stimulation in rehabilitation is a fast-growing field featured with computational and biophysical modeling. Cortical features and scalp-to-cortex distance (SCD) are key variables for determining the strength and distribution of the electric field, yet longitudinal studies able to capture these dynamic changes are missing. We sought to investigate and quantify the ageing effect on the morphometry and SCD of left primary motor cortex (M1) and dorsolateral prefrontal cortex (DLPFC) in normal ageing adults and mild cognitive impairment (MCI) converters. METHODS: Baseline, 1-year and 3-year follow-up structural magnetic resonance imaging scans from normal ageing adults (n = 32), and MCI converters (n = 22) were drawn from the Open Access Series of Imaging Studies. We quantified the changes of the cortical features and SCDs of left M1 and DLPFC, including grey matter volume, white matter volume, cortical thickness, and folding. Head model was developed to simulate the impact of SCD on the electric field induced by transcranial current stimulation. RESULTS: Pronounced ageing effect was found on the SCD of left DLPFC in MCI converters. The SCD change of left DLPFC from baseline to 3-year follow-up demonstrated better performance to discriminate MCI converters from normal ageing adults than the other morphometric measures. The strength of electric field was consequently decreased with SCD in MCI converters. CONCLUSION: Ageing has a prominent, but differential effect on the region-specific SCD and cortical features in older adults with cognitive impairments. Our findings suggest that SCD, cortical thickness, and folding of the targeted regions could be used as valuable imaging markers when conducting transcranial brain stimulation in individuals with brain atrophy.

Aberrant interhemispheric functional connectivity within default mode network and its relationships with neurocognitive features in cognitively normal APOE ε 4 elderly carriers.

BACKGROUND: Default mode network (DMN) is vulnerable to the effects of APOE genotype. Given the reduced brain volumes and APOE ε 4-related brain changes in elderly carriers, it is less known that whether these changes would influence the functional connectivity and to what extent. This study aimed to examine the functional connectivity within DMN, and its diagnostic value with age-related morphometric alterations considered. METHODS: Whole brain and seed-based resting-state functional connectivity (RSFC) analysis were conducted in cognitively normal APOE ε 4 carriers and matched non-carriers (N=38). The absolute values of mean correlation coefficients (z-values) were used as a measure of functional connectivity strength (FCS) between DMN subregions, which were also used to estimate their diagnostic value by receiver-operating characteristic (ROC) curves. RESULTS: APOE ε 4 carriers demonstrated decreased interhemispheric FCS, particularly between right hippocampal formation (R.HF) and left inferior parietal lobular (L.IPL) (t=3.487, p<0.001). ROC analysis showed that the FCS of R.HF and L.IPL could differentiate APOE ε 4 carriers from healthy counterparts (AUC value=0.734, p=0.025). Moreover, after adjusting the impact of morphometry, the differentiated value of FCS of R.HF and L.IPL was markedly improved (AUC value=0.828, p=0.002). CONCLUSIONS: Our findings suggest that APOE ε 4 allele affects the functional connectivity within posterior DMN, particularly the atrophy-corrected interhemispheric FCS before the clinical expression of neurodegenerative disease.

Efficiency of Attentional Components in Elderly with Mild Neurocognitive Disorders Shown by the Attention Network Test.

AIMS: Complex attention, serving as a main diagnostic item of mild neurocognitive disorders (NCD), has been reported to be susceptible to pathological ageing. This study aimed to evaluate the attention network functions in older adults with subtypes of NCD. METHODS: 36 adults with NCD due to Alzheimer's disease (NCD-AD), 31 adults with NCD due to vascular disease (NCD-vascular) and 137 healthy controls were recruited. Attention Network Test (ANT) was conducted to assess the efficiency of alerting, orienting and executive control. RESULTS: Significant between-group differences were found in executive control (conventional score: F = 11.472, p < 0.001; ratio score: F = 8.430, p < 0.001) and processing speed (F = 4.958, p = 0.008). NCD subgroups demonstrated poorer performance on the ANT, particularly on executive control (healthy 59.9 ± 45.9, NCD-vascular 88.9 ± 44.8, NCD-AD 97.0 ± 53.9). Moreover, the NCD-AD group showed both less efficient executive control and prominent slowing processing speed (reaction time: healthy 687.5 ± 106.0 ms, NCD-vascular 685.3 ± 97.1 ms, NCD-AD 750.6 ± 132.6 ms). CONCLUSIONS: The NCD-vascular group appeared to be less efficient in executive control, while the NCD-AD group demonstrated less effective executive control and also slower processing speed. These results suggest that the characterized performance of ANT, processing speed and executive control in particular, might help differentiate adults at risk of different forms of cognitive impairment.

The effects of apolipoprotein ε 4 on aging brain in cognitively normal Chinese elderly: a surface-based morphometry study.

BACKGROUND: Default mode network (DMN) has been reported to be susceptible to APOE ε 4 genotype. However, the APOE ε 4-related brain changes in young carriers are different from the ones in elderly carriers. The current study aimed to evaluate the cortical morphometry of DMN subregions in cognitively normal elderly with APOE ε 4. METHOD: 11 cognitively normal senior APOE ε 4 carriers and 27 matched healthy controls (HC) participated the neuropsychological tests, genotyping, and magnetic resonance imaging (MRI) scanning. Voxel-based morphometry (VBM) analysis was used to assess the global volumetric changes. Surface-based morphometry (SBM) analysis was performed to measure regional gray matter volume (GMV) and gray matter thickness (GMT). RESULTS: Advancing age was associated with decreased GMV of DMN subregions. Compared to HC, APOE ε 4 carriers presented cortical atrophy in right cingulate gyrus (R_CG) (GMV: APOE carriers: 8475.23 ± 1940.73 mm3, HC: 9727.34 ± 1311.57 mm3, t = 2.314, p = 0.026, corrected) and left insular (GMT: APOE ε 4 carriers: 3.83 ± 0.37 mm, HC: 4.05 ± 0.25 mm, t = 2.197, p = 0.033, corrected). CONCLUSIONS: Our results highlight the difference between different cortical measures and suggest that the cortical reduction of CG and insular maybe a potential neuroimaging marker for APOE 4 ε senior carriers, even in the context of relatively intact cognition.

Disturbance of attention network functions in Chinese healthy older adults: an intra-individual perspective.

BACKGROUND: Intra-individual variability (IIV) and the change of attentional functions have been reported to be susceptible to both healthy ageing and pathological ageing. The current study aimed to evaluate the IIV of attention and the age-related effect on alerting, orienting, and executive control in cognitively healthy older adults. METHOD: We evaluated 145 Chinese older adults (age range of 65-80 years, mean age of 72.41 years) with a comprehensive neuropsychological battery and the Attention network test (ANT). A two-step strategy of analytical methods was used: Firstly, the IIV of older adults was evaluated by the intraindividual coefficient of variation of reaction time (ICV-RT). The correlation between ICV-RT and age was used to evaluate the necessity of subgrouping. Further, the comparisons of ANT performance among three age groups were performed with processing speed adjusted. RESULTS: Person's correlation revealed significant positive correlations between age and IIV (r = 0.185, p = 0.032), age and executive control (r = 0.253, p = 0.003). Furthermore, one-way ANOVA comparisons among three age groups revealed a significant age-related disturbance on executive control (F = 4.55, p = 0.01), in which oldest group (group with age >75 years) showed less efficient executive control than young-old (group with age 65-70 years) (Conventional score, p = 0.012; Ratio score, p = 0.020). CONCLUSION: Advancing age has an effect on both IIV and executive attention in cognitively healthy older adults, suggesting that the disturbance of executive attention is a sensitive indicator to reflect healthy ageing. Its significance to predict further deterioration should be carefully evaluated with prospective studies.

MRI-informed machine learning-driven brain age models for classifying mild cognitive impairment converters.

BACKGROUND: Brain age model, including estimated brain age and brain-predicted age difference (brain-PAD), has shown great potentials for serving as imaging markers for monitoring normal ageing, as well as for identifying the individuals in the pre-diagnostic phase of neurodegenerative diseases. PURPOSE: This study aimed to investigate the brain age models in normal ageing and mild cognitive impairments (MCI) converters and their values in classifying MCI conversion. METHODS: Pre-trained brain age model was constructed using the structural magnetic resonance imaging (MRI) data from the Cambridge Centre for Ageing and Neuroscience (Cam-CAN) project (N = 609). The tested brain age model was built using the baseline, 1-year and 3-year follow-up MRI data from normal ageing (NA) adults (n = 32) and MCI converters (n = 22) drew from the Open Access Series of Imaging Studies (OASIS-2). The quantitative measures of morphometry included total intracranial volume (TIV), gray matter volume (GMV) and cortical thickness. Brain age models were calculated based on the individual's morphometric features using the support vector machine (SVM) algorithm. RESULTS: With comparable chronological age, MCI converters showed significant increased TIV-based (Baseline: P = 0.021; 1-year follow-up: P = 0.037; 3-year follow-up: P = 0.001) and left GMV-based brain age than NA adults at all time points. Higher brain-PAD scores were associated with worse global cognition. Acceptable classification performance of TIV-based (AUC = 0.698) and left GMV-based brain age (AUC = 0.703) was found, which could differentiate the MCI converters from NA adults at the baseline. CONCLUSIONS: This is the first demonstration that MRI-informed brain age models exhibit feature-specific patterns. The greater GMV-based brain age observed in MCI converters may provide new evidence for identifying the individuals at the early stage of neurodegeneration. Our findings added value to existing quantitative imaging markers and might help to improve disease monitoring and accelerate personalized treatments in clinical practice.

Based on individual's MRI scans, brain age model has shown great potentials for serving as imaging markers for monitoring normal ageing (NA), as well as for identifying the ones in the pre-diagnostic phase of age-related neurodegenerative diseases. In this study, we investigated the brain age models in normal ageing and mild cognitive impairments (MCI) converters and their values in classifying MCI conversion. Pre-trained brain age model was constructed using the quantitative measures of morphometry included total intracranial volume (TIV), gray matter volume (GMV) and cortical thickness. With comparable chronological age, MCI converters showed significant increased brain age than NA adults at all time points. Higher brain age were associated with worse global cognition. This is the first demonstration that MRI-informed brain age models exhibit feature-specific patterns. The greater GMV-based brain age observed in MCI converters may provide new evidence for identifying the individuals at the early stage of neurodegeneration. Our findings added value to existing quantitative imaging markers and might help to improve disease monitoring and accelerate personalized treatments in clinical practice.

Decoding MRI-informed brain age using mutual information.

OBJECTIVE: We aimed to develop a standardized method to investigate the relationship between estimated brain age and regional morphometric features, meeting the criteria for simplicity, generalization, and intuitive interpretability. METHODS: We utilized T1-weighted magnetic resonance imaging (MRI) data from the Cambridge Centre for Ageing and Neuroscience project (N = 609) and employed a support vector regression method to train a brain age model. The pre-trained brain age model was applied to the dataset of the brain development project (N = 547). Kraskov (KSG) estimator was used to compute the mutual information (MI) value between brain age and regional morphometric features, including gray matter volume (GMV), white matter volume (WMV), cerebrospinal fluid (CSF) volume, and cortical thickness (CT). RESULTS: Among four types of brain features, GMV had the highest MI value (8.71), peaking in the pre-central gyrus (0.69). CSF volume was ranked second (7.76), with the highest MI value in the cingulate (0.87). CT was ranked third (6.22), with the highest MI value in superior temporal gyrus (0.53). WMV had the lowest MI value (4.59), with the insula showing the highest MI value (0.53). For brain parenchyma, the volume of the superior frontal gyrus exhibited the highest MI value (0.80). CONCLUSION: This is the first demonstration that MI value between estimated brain age and morphometric features may serve as a benchmark for assessing the regional contributions to estimated brain age. Our findings highlighted that both GMV and CSF are the key features that determined the estimated brain age, which may add value to existing computational models of brain age. CRITICAL RELEVANCE STATEMENT: Mutual information (MI) analysis reveals gray matter volume (GMV) and cerebrospinal fluid (CSF) volume as pivotal in computing individuals' brain age. KEY POINTS: Mutual information (MI) interprets estimated brain age with morphometric features. Gray matter volume in the pre-central gyrus has the highest MI value for estimated brain age. Cerebrospinal fluid volume in the cingulate has the highest MI value. Regarding brain parenchymal volume, the superior frontal gyrus has the highest MI value. The value of mutual information underscores the key brain regions related to brain age.

Predictive values of pre-treatment brain age models to rTMS effects in neurocognitive disorder with depression: Secondary analysis of a randomised sham-controlled clinical trial.

INTRODUCTION: One major challenge in developing personalised repetitive transcranial magnetic stimulation (rTMS) is that the treatment responses exhibited high inter-individual variations. Brain morphometry might contribute to these variations. This study sought to determine whether individual's brain morphometry could predict the rTMS responders and remitters. METHODS: This was a secondary analysis of data from a randomised clinical trial that included fifty-five patients over the age of 60 with both comorbid depression and neurocognitive disorder. Based on magnetic resonance imaging scans, estimated brain age was calculated with morphometric features using a support vector machine. Brain-predicted age difference (brain-PAD) was computed as the difference between brain age and chronological age. RESULTS: The rTMS responders and remitters had younger brain age. Every additional year of brain-PAD decreased the odds of relieving depressive symptoms by ∼25.7% in responders (Odd ratio [OR] = 0.743, p = .045) and by ∼39.5% in remitters (OR = 0.605, p = .022) in active rTMS group. Using brain-PAD score as a feature, responder-nonresponder classification accuracies of 85% (3rd week) and 84% (12th week), respectively were achieved. CONCLUSION: In elderly patients, younger brain age appears to be associated with better treatment responses to active rTMS. Pre-treatment brain age models informed by morphometry might be used as an indicator to stratify suitable patients for rTMS treatment. TRIAL REGISTRATION: ClinicalTrials.gov Identifier: ChiCTR-IOR-16008191.

Non-improvement predicts subsequent non-response to repeated-dose intravenous ketamine for depression: a re-analysis of a 2-week open-label study in patients with unipolar and bipolar depression.

There is insufficient evidence to guide dose and frequency optimization with repeated-dose ketamine for depression. This study assessed the value of symptomatic non-improvement after the first few ketamine infusions as a predictor of overall non-response in depression for early decision-making to discontinue treatment. A total of 135 individuals with major depressive disorder or bipolar disorder experiencing a current major depressive episode were administered six repeated doses of intravenous ketamine. Depressive symptoms were assessed using the Montgomery-Åsberg Depression Rating Scale (MADRS) at baseline, 4 h after the first infusion, and 24 h after each infusion. Improvement, partial response, and response were defined as a reduction rate of ≥ 20%, 30%, and 50% in MADRS scores, respectively. This study examined the relationship between improvement (as opposed to non-improvement after each infusion or consecutive non-improvements after the first few infusions) and partial response and response after the sixth infusion. This analysis was summarized using sensitivity, specificity, and other diagnostic test parameters. The sensitivities of improvement at 24 h post-infusion 4 and improvement at 24 h post-infusion 3, vs. three consecutive non-improvements, as predictors for overall partial response and response exceeded 90%. No significant reduction in depressive symptoms was seen in non-improvers following the remaining infusions after the above-identified point. Our study suggests that non-improvement after four infusions, or more conservatively three consecutive non-improvements after three infusions, could serve as a signal of overall non-response to repeated-dose intravenous ketamine for depression and that subsequent treatments would not be warranted.

Association between degree centrality and neurocognitive impairments in patients with Schizophrenia: A Longitudinal rs-fMRI Study.

BACKGROUND: Evidence indicates that patients with schizophrenia (SZ) experience significant changes in their functional connectivity during antipsychotic treatment. Despite previous reports of changes in brain network degree centrality (DC) in patients with schizophrenia, the relationship between brain DC changes and neurocognitive improvement in patients with SZ after antipsychotic treatment remains elusive. METHODS: A total of 74 patients with acute episodes of chronic SZ and 53 age- and sex-matched healthy controls were recruited. The Positive and Negative Syndrome Scale (PANSS), Symbol Digit Modalities Test, digital span test (DST), and verbal fluency test were used to evaluate the clinical symptoms and cognitive performance of the patients with SZ. Patients with SZ were treated with antipsychotics for six weeks starting at baseline and underwent MRI and clinical interviews at baseline and after six weeks, respectively. We then divided the patients with SZ into responding (RS) and non-responding (NRS) groups based on the PANSS scores (reduction rate of PANSS ≥50%). DC was calculated and analyzed to determine its correlation with clinical symptoms and cognitive performance. RESULTS: After antipsychotic treatment, the patients with SZ showed significant improvements in clinical symptoms, semantic fluency performance. Correlation analysis revealed that the degree of DC increase in the left anterior inferior parietal lobe (aIPL) after treatment was negatively correlated with changes in the excitement score (r = -0.256, p = 0.048, adjusted p = 0.080), but this correlation failed the multiple test correction. Patients with SZ showed a significant negative correlation between DC values in the left aIPL and DST scores after treatment, which was not observed at the baseline (r = -0.359, p = 0.005, adjusted p = 0.047). In addition, we did not find a significant difference in DC between the RS and NRS groups, neither at baseline nor after treatment. CONCLUSIONS: The results suggested that DC changes in patients with SZ after antipsychotic treatment are correlated with neurocognitive performance. Our findings provide new insights into the neuropathological mechanisms underlying antipsychotic treatment of SZ.

Diversity in verbal fluency performance and its associations with MRI-informed brain age matrices in normal ageing and neurocognitive disorders.

INTRODUCTION: Category verbal fluency test (CVFT) has been widely used to assess and monitor the cognitive capacities in epidemiological studies and clinical trials. Pronounced discrepancy in CVFT performance has been found in individuals with different cognitive statuses. This study aimed to combine the psychometric and morphometric approaches to decode the complex verbal fluency performance in senior adults with normal ageing and neurocognitive disorders. METHODS: This study adopted a two-stage cross-sectional design involving quantitative analyses of neuropsychological and neuroimaging data. In study I, capacity- and speed-based measures of CVFT were developed to evaluate the verbal fluency performance in normal ageing seniors (n = 261), those with mild cognitive impairment (n = 204), and those with dementia (n = 23) whose age range is from 65 to 85 years. In study II, structural magnetic resonance imaging-informed gray matter volume (GMV) and brain age matrices were calculated in a subsample (n = 52) from Study I through surface-based morphometry analysis. With age and gender as covariates, Pearson's correlation analysis was used to examine the associations of CVFT measures, GMV, and brain age matrices. RESULTS: Speed-based measures showed extensive and stronger associations with other cognitive functions than capacity-based measures. The component-specific CVFT measures showed shared and unique neural underpinnings with lateralized morphometric features. Moreover, the increased CVFT capacity was significantly correlated with younger brain age in mild neurocognitive disorder (NCD) patients. CONCLUSION: We found that the diversity of verbal fluency performance in normal ageing and NCD patients could be explained by a combination of memory, language, and executive abilities. The component-specific measures and related lateralized morphometric correlates also highlight the underlying theoretical meaning of verbal fluency performance and its clinical utility in detecting and tracing the cognitive trajectory in individuals with accelerated ageing.

Decoding the radiomic features of dorsolateral prefrontal cortex in individuals with accelerated cortical changes: implications for personalized transcranial magnetic stimulation.

Purpose: Image-guided transcranial magnetic stimulation (TMS) is an emerging research field in neuroscience and rehabilitation medicine. Cortical morphometry, as a radiomic phenotype of aging, plays a vital role in developing personalized TMS model, yet few studies are afoot to examine the aging effects on region-specific morphometry and use it in the estimation of TMS-induced electric fields. Our study was aimed to investigate the radiomic features of bilateral dorsolateral prefrontal cortex (DLPFC) and quantify the TMS-induced electric fields during aging. Approach: Baseline, 1-year and 3-year structural magnetic resonance imaging (MRI) scans from normal aging (NA) adults ( n = 32 ) and mild cognitive impairment (MCI) converters ( n = 22 ) were drawn from the Open Access Series of Imaging Studies. The quantitative measures of radiomics included cortical thickness, folding, and scalp-to-cortex distance. Realistic head models were developed to simulate the impacts of radiomic features on TMS-induced E-fields using the finite-element method. Results: A pronounced aging-related decrease was found in the gyrification of left DLPFC in MCI converters ( t = 2.21 , p = 0.035 ), which could predict the decline of global cognition at 3-year follow up. Along with the decreased gyrification in left DLPFC, the magnitude of TMS-induced E-fields was rapidly decreased in MCI converters ( t = 2.56 , p = 0.018 ). Conclusions: MRI-informed radiomic features of the treatment targets have significant effects on the intensity and distribution of the stimulation-induced electric fields in prodromal dementia patients. Our findings highlight the importance of region-specific radiomics when conducting the transcranial brain stimulation in individuals with accelerated cortical changes, such as Alzheimer's disease.

Enhanced brain functional connectivity and activation after 12-week Tai Chi-based action observation training in patients with Parkinson's disease.

Introduction: Motor-cognitive interactive interventions, such as action observation training (AOT), have shown great potential in restoring cognitive function and motor behaviors. It is expected that an advanced AOT incorporating specific Tai Chi movements with continuous and spiral characteristics can facilitate the shift from automatic to intentional actions and thus enhance motor control ability for early-stage PD. Nonetheless, the underlying neural mechanisms remain unclear. The study aimed to investigate changes in brain functional connectivity (FC) and clinical improvement after 12 weeks of Tai Chi-based action observation training (TC-AOT) compared to traditional physical therapy (TPT). Methods: Thirty early-stage PD patients were recruited and randomly assigned to the TC-AOT group (N = 15) or TPT group (N = 15). All participants underwent resting-state functional magnetic resonance imaging (rs-fMRI) scans before and after 12 weeks of training and clinical assessments. The FCs were evaluated by seed-based correlation analysis based on the default mode network (DMN). The rehabilitation effects of the two training methods were compared while the correlations between significant FC changes and clinical improvement were investigated. Results: The results showed that the TC-AOT group exhibited significantly increased FCs between the dorsal medial prefrontal cortex and cerebellum crus I, between the posterior inferior parietal lobe and supramarginal gyrus, and between the temporal parietal junction and clusters of middle occipital gyrus and superior temporal. Moreover, these FC changes had a positive relationship with patients' improved motor and cognitive performance. Discussion: The finding supported that the TC-AOT promotes early-stage PD rehabilitation outcomes by promoting brain neuroplasticity where the FCs involved in the integration of sensorimotor processing and motor learning were strengthened.

Study protocol of a double-blind randomized control trial of transcranial direct current stimulation in post-stroke fatigue.

Rationale: Post-stroke fatigue (PSF) is a frequent problem in stroke survivors and often hinders their rehabilitation. PSF is difficult to treat, and pharmacological therapy is often ineffective. Transcranial direct current stimulation (tDCS) can modulate motor, sensory, cognitive and behavioral responses, as it alters neuronal activity by delivering a small amount of current via the scalp to the cortex, resulting in prolonged alterations to brain function. tDCS has been studied for the treatment of fatigue associated with other neurological diseases, namely, multiple sclerosis, Parkinson's disease and post-polio syndrome. Aims: This proposed project will examine the effect of tDCS on PSF. Sample size estimates: We will recruit 156 participants aged 18 to 80 with chronic stroke and allocate them equally to two groups (i.e., n = 78 per group). Methods and design: This proposed project will be a double-blind randomized control trial. The participants will be randomly divided into two groups. The control group will receive sham tDCS, and the treatment group will receive active tDCS. The latter treatment will involve application of a constant 2-mA current via one 5 × 5-cm anodal electrode positioned on the scalp over the C3 or C4 positions (motor cortex) of the lesioned hemisphere and one cathodal electrode positioned at the ipsilateral shoulder in two 20-min sessions per day for 5 days. The period of follow-up will be 4 weeks. Study outcomes: The primary outcome measure will be a change in fatigue severity, as measured using the modified fatigue impact scale (MFIS). The participants' scores on the MFIS (total score and physical, cognitive and psychosocial subscores) will be collected before treatment (T0), after 10 treatment sessions, i.e., 1 day after the fifth treatment day (T1), and 1 week (T2), 2 weeks (T3) and 4 weeks (T4) thereafter. Both per-protocol analysis and intention-to-treat analysis will be performed. Discussion: This proposed project will provide proof-of-concept, i.e., demonstrate the benefits of tDCS for the treatment of PSF. The beneficiaries are the subjects participated in the study. This will stimulate further research to optimize tDCS parameters for the treatment of PSF. Clinical trial registration: www.Chictr.org.cn, identifier: ChiCTR2100052515.

Using gamma-band transcranial alternating current stimulation (tACS) to improve sleep quality and cognition in patients with mild neurocognitive disorders due to Alzheimer's disease: A study protocol for a randomized controlled trial.

BACKGROUND: Sleep disturbances are highly prevalent in patients with age-related neurodegenerative diseases, which severely affect cognition and even lead to accumulated ß-amyloid. Encouraging results from recent studies on transcranial direct current stimulation (tDCS) showed moderate positive effects on sleep quality in preclinical Alzheimer's disease (AD). Compared to tDCS, transcranial alternating current stimulation (tACS) enables the entrainment of neuronal activity with optimized focality through injecting electric current with a specific frequency and has significant enhancement effects on slow wave activities. METHODS AND DESIGN: This is a randomized, double-blind, sham-controlled clinical trial comparing 40 Hz tACS with tDCS in mild neurocognitive disorders due to AD with sleep disturbances. Magnetic resonance imaging (MRI) data is used to construct personalized realistic head model. Treatment outcomes, including sleep quality, cognitive performance and saliva Aß levels will be conducted at baseline, 4th week, 8th week, 12th week and 24th week. CONCLUSIONS: It is expected that the repeated gamma-band tACS will show significant improvements in sleep quality and cognitive functions compared to tDCS and sham tDCS. The findings will provide high-level evidence and guide further advanced studies in the field of neurodegenerative diseases and sleep medicine. TRIAL REGISTRATION: ClinicalTrials.gov Identifier: NCT05544201.