Brain plasticity can be conceptualized as nature’s invention to overcome limitations of the genome and adapt to a rapidly changing environment. As such, plasticity is an intrinsic property of the ...brain across the lifespan. However, mechanisms of plasticity may vary with age. The combination of transcranial magnetic stimulation (TMS) with electroencephalography (EEG) or functional magnetic resonance imaging (fMRI) enables clinicians and researchers to directly study local and network cortical plasticity, in humans in vivo, and characterize their changes across the age-span. Parallel, translational studies in animals can provide mechanistic insights. Here, we argue that, for each individual, the efficiency of neuronal plasticity declines throughout the age-span and may do so more or less prominently depending on variable ‘starting-points’ and different ‘slopes of change’ defined by genetic, biological, and environmental factors. Furthermore, aberrant, excessive, insufficient, or mistimed plasticity may represent the proximal pathogenic cause of neurodevelopmental and neurodegenerative disorders such as autism spectrum disorders or Alzheimer’s disease.
Objectives: Exploring the modulatory effects of different frequencies of repetitive transcranial magnetic stimulation (rTMS) on the excitability of the motor cortex as measured by the input–output ...curve technique (I–O curve).
Methods: Sixteen healthy subjects participated in this experiment. On two different sessions, conducted 1 week apart, rTMS was applied either at a frequency of 20 or 1
Hz at 90% of individual motor threshold (MT) for a total of 1600 pulses each. Before and after rTMS, the cortical excitability was assessed by measuring MT and the size of motor evoked potentials (MEPs) collected at different intensities of stimulation.
Results: The analysis on the whole population showed a significant decrease of cortical excitability after 1
Hz rTMS and an increase after 20
Hz rTMS. A subsequent cluster analysis pointed out the presence of two distinct groups of subjects with opposite responses at the same frequency of stimulation. Significant variations on MT were found for both groups only for the facilitatory effect irrespective of the frequency of stimulation.
Conclusions: The results provide further insight into interindividual differences in the effects of rTMS and suggest the existence of subpopulations with specific patterns of response to rTMS.
We systematically appraised randomized controlled trials proposing exercise to influence cognition in older adults to (1) assess the methodologic quality using Cochrane criteria; (2) describe various ...exercise dose measures and assess their relationship with improved cognitive performance; and (3) identify consistent patterns of reported effects on cognition.
There was overall good methodologic quality in all 98 included studies. The assessment of the relationship between improved cognition and various measures of exercise dose (session duration, weekly minutes, frequency, total weeks, and total hours) revealed a significant correlation with total hours. Improvements in global cognition, processing speed/attention, and executive function were most stable and consistent.
We found that exercising for at least 52 hours is associated with improved cognitive performance in older adults with and without cognitive impairment. Exercise modes supported by evidence are aerobic, resistance (strength) training, mind-body exercises, or combinations of these interventions.
Recent studies have synchronized transcranial magnetic stimulation (TMS) application with pre-defined brain oscillatory phases showing how the effect of a perturbation depends on the brain state. ...However, none have investigated if phase-dependent TMS can possibly modulate connectivity with homologous distant brain regions belonging to the same network. In the framework of network-targeted TMS, we investigated whether stimulation delivered at a specific phase of ongoing brain oscillations might favor stronger cortico-cortical (c-c) synchronization of distant network nodes connected to the stimulation target. Neuronavigated TMS pulses were delivered over the primary motor cortex (M1) during ongoing electroencephalography recording in twenty-four healthy individuals over two repeated sessions 1-month apart. Stimulation effects were analyzed considering whether the TMS pulse was delivered at the time of a positive (peak) or negative (trough) phase of μ-frequency oscillation, which determines c-c synchrony within homologous areas of the sensorimotor network. Diffusion Weighted Imaging was used to study c-c connectivity within the sensorimotor network and identify contralateral regions connected with the stimulation spot. Depending on when during the μ-activity the TMS-pulse was applied (peak or trough), its impact on inter-hemispheric network synchrony varied significantly. Higher M1-M1 phase-lock synchronization with after the TMS-pulse (0-200ms) in the μ-frequency band was found for trough compared to peak stimulation trials in both study visits. Phase-dependent TMS delivery might be crucial not only to amplify local effects but also to increase magnitude and the reliability of the response to the external perturbation, with implications for interventions aimed at engaging more distributed functional brain networks.
Background
Alzheimer’s disease (AD) is associated with increased cortical excitability, including an elevated risk of seizures. Transcranial magnetic stimulation with electromyography (TMS‐EMG‐EEG) ...can be used to index intracortical excitability. Prior work has shown that TMS‐based excitability measures are altered in AD and are related to disease severity. However, it is not yet known how TMS‐EMG measures are related to neurodegeneration within brain regions affected by AD.
Method
TMS‐EMG was applied to left motor cortex (M1) in 22 participants with biomarker‐confirmed mild cognitive impairment due to AD (early AD, aged 70.5±8.4, 11 females). Single pulse TMS was preformed to measure resting motor threshold (RMT) and motor evoked potential amplitude (MEP Amplitude). Paired‐pulse TMS was preformed to measure short interval intracortical inhibition (SICI, GABA‐ergic) and intracortical facilitation (ICF, glutamatergic). In 5 participants, TMS‐evoked responses on EEG were also obtained during single‐pulse stimulation to M1 and the inferior parietal lobe (IPL), and the local mean field amplitude (LMFA) was computed from 15 to 40 msec after the TMS pulse. Structural MRI scans for each participant were processed using Freesurfer to obtain cortical thickness measurements within the distributed Alzheimer‐signature brain regions (AD‐signature atrophy). The primary analyses tested the relationship between each TMS measure and AD‐signature atrophy using separate linear models, controlling for age. For TMS‐EEG analysis, effect sizes were reported in lieu of p‐values given the small sample sizes.
Result
In early AD, SICI was related to AD‐signature atrophy (R2
adj = 0.40, B = ‐0.13, p = 0.018; Fig1), with less intracortical inhibition related to greater atrophy. RMT, MEP Amplitude, and ICF were not related to AD‐signature atrophy (p‐values>0.105). There was a large effect size of IPL LMFA on AD‐signature atrophy (R2
adj = 0.70), while the effect size of M1 was small (R2
adj = ‐0.19).
Conclusion
Decreased intracortical inhibition is related to increased AD‐signature atrophy in early AD. Decreased function of GABA‐A circuitry related to cortical atrophy may play a role in the development of cortical hyperexcitability in AD. Our preliminary results further suggests that TEPs from stimulation of IPL, a node of the default mode network and an area commonly showing AD pathology, may also be related to AD‐signature atrophy.
Background
It is essential both drug and lifestyle‐based interventions aimed to delay the onset of advanced cognitive decline deliver a meaningful outcome for the patient. In the early stages of ...Alzheimer’s disease and related dementias (ADRDs), patient‐reported outcome (PRO) measures should be used in parallel with biological investigations of ADRDs to provide a complementary endpoint offering further proof of intervention’s effectiveness from the patients’ point of view. The aim of the electronic Person‐Specific Outcome Measure (ePSOM) programme is to develop a scalable, easily accessible and efficient PRO tool for monitoring personally meaningful outcomes in early ADRD.
Method
We designed and ran an online nation‐wide study to understand what matters to people about their brain health in the US. The ePSOM US survey started in Jan 2023 and collects primarily free‐text responses along with sociodemographic information and self‐reported neurodegenerative disease diagnosis. Respondents are presented with five domains and asked to describe in their own words their brain‐health priorities. Free‐text data will be analysed using Natural Language Processing (NLP) techniques to identify the most common brain‐health priorities by key sociodemographic groups. We will also compare these results with previously published UK results to look for any notable differences between the US and UK respondents’ priorities.
Result
The survey aims to recruit n = 6,000 respondents. Data collection started early 2023 and is planned to be complete by Spring/Summer 2023. The previously published ePSOM UK study (Saunders et al., 2021) with n = 5,808 respondents resulted in over 80,000 free‐text responses and 184 unique priority themes about brain health. We will present the preliminary results of the US study at AAIC and contextualising the results in light of new pharmacological treatments approved for AD.
Conclusion
This large‐scale population‐based study will offer an evidence base for what outcomes constitute a meaningful impact of new treatments. Previous work from our group suggests that brain health priorities shift along the preclinical, prodromal and dementia continuum. The ultimate aim of the ePSOM programme is to design an electronic outcomes app which would allow an individual to define the most important outcomes against which we should measure treatment success across a range of severities.
Abstract
Background
DCTclock™ is an AI‐enabled digital cognitive assessment (DCA) that strongly discriminates between cognitively impaired and unimpaired individuals (receiver operating area ...under‐the‐curve AUC = 0.89). Among cognitively unimpaired individuals, DCTclock predicts greater PET Aβ burden and shows stronger discrimination (Cohen’s
d
= 0.76) between Aβ± individuals than the Preclinical Alzheimer’s Cognitive Composite (
d
= 0.30) (Rentz et al., 2021). The Digital Clock and Recall (DCR™) was recently created by adding 3‐word delayed recall to DCTclock to assess verbal memory impairment – an early hallmark of Alzheimer’s disease. We assessed whether recreating the DCR with the 3‐word delayed recall from the Mini‐Mental State Examination (MMSE) and DCTclock would improve classification of Aβ PET biomarker status among cognitively unimpaired older adults.
Method
DCTclock, MMSE (including delayed recall), and Aβ PET imaging data were collected from 159 cognitively unimpaired older adults in the Harvard Aging Brain Study (age = 78.6±5.9; 98 females; MMSE = 28.9±1.4). Logistic regression classifiers were trained to classify Aβ biomarker status and were assessed with standard metrics and AUC as compared to age‐ and MMSE‐only models.
Result
The best‐performing model classified biomarker status among cognitively unimpaired individuals with an AUC of 0.76 (sensitivity = 0.65, specificity = 0.73, accuracy = 0.71)‐outperforming age‐only and total MMSE‐only models (AUCs = 0.61). Recursive feature elimination identified spatial reasoning, average speed, maximum speed on Copy Clock, oscillatory motion on Command Clock, and delayed recall score as key features. DCTclock or recreated DCR summary scores alone classified biomarker status with AUCs of 0.72 and 0.74, respectively.
Conclusion
The DCR, which combines DCTclock with delayed verbal recall, may offer a means to classify Aβ biomarker status among cognitively unimpaired individuals in as little as 3 minutes. Classification models trained on a subset of DCR features performed better than all other models, including traditional neuropsychological testing. These results reinforce the potential for DCR solutions to streamline cognitive testing in the clinic and accelerate diagnosis for individuals with early‐stage Alzheimer’s and other dementias. Future work will examine the best possible combination of additional tests to further increase classification accuracy.
Abstract
Background
Early detection of Mild Cognitive Impairment (MCI) and Alzheimer’s Disease and Related Dementias (ADRD) is key to optimal management. Digital tests allow for the reliable capture ...of meaningful, process‐based neuropsychological test parameters that traditional paper/pencil measures fail to detect, thus enabling earlier detection. We assessed how subtle functional decline relates to process features extracted from the digital Clock Drawing Test (dCDT) and the digital Trail Making Test‐Part B (dTrB).
Methods
629 community dwelling participants (58.5% female) were assessed with the Functional Assessment Questionnaire (FAQ), the MMSE, the digital clock drawing test (dCDT) and the digital Trail Making Test‐Part B (dTrB). Three FAQ groups were constructed: FAQ = 0‐2 (minimal functional disability, n = 490); FAQ = 3‐5 (subtle functional disability, n = 90); FAQ = 6‐8 (mild functional disability, n = 49).
Results
Participants with minimal functional disability were younger (p = 0.027) and scored better on the MMSE (p = 0.001) than other groups. Groups were equated for education. dCDT command/copy component placement was more accurate among participants with minimal functional disability compared to other groups (command dCDT p = 0.001 versus mild functional disability; copy dCDT p = 0.006 versus both subtle and mild functional disability). On the dTrB, participants with minimal disability drew faster than those with subtle or mild disability (mean stroke velocity, p = 0.001). Analyses for percent pen lift time found no difference between participants with minimal versus subtle disability; however, both groups differed from participants with mild disability (p = 0.001). Optimal group classification using stepwise nominal regression with the minimal functional disability group as the reference was achieved using dCDT copy component placement and dTrB mean stroke velocity (
X
2
= 28.37, p = 0.001), where dTrB mean velocity entered first (
X
2
= 17.73, p = 0.001) followed by dCDT copy component placement (
X
2
= 11.19, p = 0.004). Both variables contributed comparably to group classification (Wald statistic range 5.82‐8.88, p = 0.012, respectively).
Conclusions
The digital assessment described above, targeting executive, scanning, visuoconstructional and motor domains, captures highly nuanced, discrete behaviors with precision/ operationalism heretofore unattainable. Consequently, it is reasonable to posit that digital cognitive assessments leveraging the Boston Process Approach can both objectively detect emergent cognitive impairment and infer its likely impact on functional activities, critical for practical assessment in clinical care.
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