Influence of Brain-Derived Neurotrophic Factor Genotype on Short-Latency Afferent Inhibition and Motor Cortex Metabolites

Advancements in Transcranial Magnetic Stimulation Research and the Path to Precision

Transcranial magnetic stimulation (TMS) has become increasingly popular in clinical practice in recent years, and there have been significant advances in the principles and stimulation modes of TMS. With the development of multi-mode and precise stimulation technology, it is crucial to have a comprehensive understanding of TMS. The neuroregulatory effects of TMS can vary depending on the specific mode of stimulation, highlighting the importance of exploring these effects through multimodal application. Additionally, the use of precise TMS therapy can help enhance our understanding of the neural mechanisms underlying these effects, providing us with a more comprehensive perspective. This article aims to review the mechanism of action, stimulation mode, multimodal application, and precision of TMS.

Association between screen time and suspected developmental coordination disorder in preschoolers: A national population-based study in China

Introduction

Excessive screen exposure (ESE) is a growing global public health concern. This study aims to investigate the potential association between ESE and suspected developmental coordination disorder (DCD) in Chinese pre-schoolers, with or without siblings.

Method

A retrospective cohort study was conducted, involving 126,433 children from 551 cities in China. The Little Developmental Coordination Disorder Questionnaire (LDCDQ) was employed to evaluate motor impairment in children, while parents provided information on their children’s screen time in the past year. A mixed and multi-level logistic regression model was used to analyze the associations of all screen exposure measurements from the past year with LDCDQ scores and the risk of suspected DCD.

Results

The prevalence of excessive screen exposure was 67.6% (>1 h per day) and 28.9% (>2 h per day) in Chinese pre-schoolers. One hour’s increase in weekday daily screen time, weekend daily screen time, and screen time before sleep in the past year was associated with a decreased total score of the LDCDQ (β were −0.690, −0.398, and −1.587, p < 0.001) and an increased risk of suspected DCD by 15.3%, 9.1%, and 46.8% when adjusting for the child, family and maternal health characteristics. Excessive screen exposure decreased the total LDCDQ scores by 1.335 (>1 vs. ≤1 h) and 1.162 (>2 vs. ≤2 h) and increased risks of suspected DCD by 44.0% (>1 vs. ≤1 h) and 31.1% (>2 vs. ≤2 h) with statistical significance (each p < 0.05). The stratified analysis showed that the association between screen time and LDCDQ score was stronger in children without siblings than in those with siblings.

Conclusion

The risk of suspected DCD was highest for screen time exposure before bed compared with average weekday and weekend exposures. Parents should be advised to prevent their children from using electronic screens unsupervised, especially in one-child families.

Brain total creatine differs between primary progressive aphasia (PPA) subtypes and correlates with disease severity

Primary progressive aphasia (PPA) is comprised of three subtypes: logopenic (lvPPA), non-fluent (nfvPPA), and semantic (svPPA). We used magnetic resonance spectroscopy (MRS) to measure tissue-corrected metabolite levels in the left inferior frontal gyrus (IFG) and right sensorimotor cortex (SMC) from 61 PPA patients. We aimed to: (1) characterize subtype differences in metabolites; and (2) test for metabolite associations with symptom severity. tCr differed by subtype across the left IFG and right SMC. tCr levels were lowest in lvPPA and highest in svPPA. tCr levels predicted lvPPA versus svPPA diagnosis. Higher IFG tCr and lower Glx correlated with greater disease severity. As tCr is involved in brain energy metabolism, svPPA pathology might involve changes in specific cellular energy processes. Perturbations to cellular energy homeostasis in language areas may contribute to symptoms. Reduced cortical excitatory capacity (i.e. lower Glx) in language regions may also contribute to symptoms. Thus, tCr may be useful for differentiating between PPA subtypes, and both tCr and Glx might have utility in understanding PPA mechanisms and tracking progression.

The recent history of afferent stimulation modulates corticospinal excitability

BACKGROUND

Transcranial magnetic stimulation (TMS) is widely used to probe corticospinal excitability and fast sensorimotor integration in the primary motor hand area (M1-HAND). A conditioning electrical stimulus, applied to the contralateral hand, can suppress the motor evoked potential (MEP) elicited by TMS of M1-HAND when the afferent stimulus arrives in M1-HAND at the time of TMS. The magnitude of this short-latency afferent inhibition (SAI) is expressed as the ratio between the conditioned and unconditioned MEP amplitude.

OBJECTIVE/HYPOTHESIS

We hypothesized that corticospinal excitability and SAI are influenced by the recent history of peripheral electrical stimulation.

METHODS

In twenty healthy participants, we recorded MEPs from the right first dorsal interosseus muscle. MEPs were evoked by single-pulse TMS of the left M1-HAND alone (unconditioned TMS) or by TMS preceded by electrical stimulation of the right index finger ("homotopic" conditioning) or little finger ("heterotopic" conditioning). The three conditions were either pseudo-randomly intermixed or delivered in blocks in which a single condition was repeated five or ten times. MEP amplitudes and SAI magnitudes were compared using linear mixed-effect models and one-way ANOVAs.

RESULTS

All stimulation protocols consistently produced SAI, which was stronger after homotopic stimulation. Randomly intermingling the three stimulation conditions reduced the relative magnitude of homotopic and heterotopic SAI as opposed to blocked stimulation. The apparent attenuation of SAI was caused by a suppression of the unconditioned but not the conditioned MEP amplitude during the randomly intermixed pattern.

CONCLUSION(S)

The recent history of afferent stimulation modulates corticospinal excitability. This "history effect" impacts on the relative magnitude of SAI depending on how conditioned and unconditioned responses are intermixed and needs to be taken into consideration when probing afferent inhibition and corticospinal excitability.

Effect of brain-derived neurotrophic factor gene polymorphisms on motor performance and motor learning: A systematic review and meta-analysis

Brain-derived neurotrophic factor (BDNF) gene polymorphisms may modulate neurotransmitter efficiency, thereby influencing motor performance and motor learning. However, studies to date have provided no consensus regarding the genetic influence of BDNF genotypes (i.e., Val/Val, Val/Met, or Met/Met type). This study aimed to investigate the effect of BDNF genotype on motor performance and motor learning in healthy human adults via a systematic review and meta-analysis. A total of 19 relevant studies were identified using PubMed and Web of Science search for articles published between 2000 and 2021 with motor performance or motor learning as the primary outcome measures. The results of our systematic review suggest that the BDNF genotype is unlikely to contribute to motor performance and motor learning abilities because only 2/32 datasets (6.3%) from 16 studies on motor performance and 3/19 datasets (17.6%) from 13 studies on motor learning indicated a significant genetic effect. Moreover, a meta-analysis of motor learning publications involving 17 datasets from 11 studies revealed that there was no significant difference in the learning score normalized using baseline data between Val/Val and Met carriers (Val/Met + Met/Met or Val/Met; standardized mean differences = 0.08, P = 0.37) with zero heterogeneity (I² = 0) and a relatively low risk of publication bias. Taken together, the BDNF genotype may have only a minor impact on individual motor performance and motor learning abilities.

Do Brain-Derived Neurotrophic Factor Genetic Polymorphisms Modulate the Efficacy of Motor Cortex Plasticity Induced by Non-invasive Brain Stimulation? A Systematic Review

Techniques of non-invasive brain stimulation (NIBS) of the human primary motor cortex (M1) are widely used in basic and clinical research to induce neural plasticity. The induction of neural plasticity in the M1 may improve motor performance ability in healthy individuals and patients with motor deficit caused by brain disorders. However, several recent studies revealed that various NIBS techniques yield high interindividual variability in the response, and that the brain-derived neurotrophic factor (BDNF) genotype (i.e., Val/Val and Met carrier types) may be a factor contributing to this variability. Here, we conducted a systematic review of all published studies that investigated the effects of the BDNF genotype on various forms of NIBS techniques applied to the human M1. The motor-evoked potential (MEP) amplitudes elicited by single-pulse transcranial magnetic stimulation (TMS), which can evaluate M1 excitability, were investigated as the main outcome. A total of 1,827 articles were identified, of which 17 (facilitatory NIBS protocol, 27 data) and 10 (inhibitory NIBS protocol, 14 data) were included in this review. More than two-thirds of the data (70.4–78.6%) on both NIBS protocols did not show a significant genotype effect of NIBS on MEP changes. Conversely, most of the remaining data revealed that the Val/Val type is likely to yield a greater MEP response after NIBS than the Met carrier type in both NIBS protocols (21.4–25.9%). Finally, to aid future investigation, we discuss the potential effect of the BDNF genotype based on mechanisms and methodological issues.

Gray Matter Volume Variability in Young Healthy Adults: Influence of Gender Difference and Brain-Derived Neurotrophic Factor Genotype

Although brain gray matter (GM) plastically changes during short-term training, it is still unclear whether brain structures are stable for short periods (several months). Therefore, this study aimed to re-test the short-term variability of GM volumes and to clarify the effect of factors (gender and BDNF-genotype) expected to contribute to such variability. The subjects comprised 41 young healthy adults. T1-weighted images were acquired twice with an interval of approximately 4 months using a 3 T-MRI scanner. Voxel-based morphometry (VBM) was used to calculate GM volumes in 47 regions. The intraclass correlation coefficient (ICC) and Test–retest variability (%TRV) were used as indices of variability. As a result, the ICCs in 43 regions were excellent (ICC > 0.90) and those in 3 regions were good (ICC > 0.80), whereas the ICC in the thalamus was moderate (ICC = 0.694). Women had a higher %TRV than men in 5 regions, and %TRV of the Val66Val group was higher than that of the Met carrier group in 2 regions. Moreover, the Female-Val66Val group had a higher %TRV than the Male-Met carrier group in 3 regions. These results indicate that although the short-term variability of GM volumes is small, it is affected by within-subject factors.

Contribution of the brain-derived neurotrophic factor and neurometabolites to the motor performance

Individual motor performance ability is affected by various factors. Although the key factor has not yet completely been elucidated, the brain-derived neurotrophic factor (BDNF) genotype as well as neurometabolites may become contibuting factors depending on the learning stage. We investigated the effects of the Met allele of the BDNF gene and those of the neurometabolites on visuomotor learning. In total, 43 healthy participants performed a visuomotor learning task consisting of 10 blocks using the right index finger (Val66Val, n = 15; Val66Met, n = 15; and Met66Met, n = 13). Glutamate plus glutamine (Glx) concentrations in the primary motor cortex, primary somatosensory cortex (S1), and cerebellum were evaluated using 3-T magnetic resonance spectroscopy in 19 participants who participated in the visuomotor learning task. For the learning stage, the task error (i.e., learning ability) was significantly smaller in the Met66Met group compared with that observed in the remaining groups, irrespective of the learning stage (all p values < 0.003). A significant difference was observed between the Val66Val and Met66Met groups in the learning slope (i.e., learning speed) in the early learning stage (p = 0.048) but not in the late learning stage (all p values> 0.54). Moreover, positive correlations were detected between the learning slope and Glx concentrations in S1 only in the early learning stage (r = 0.579, p = 0.009). The BDNF genotype and Glx concentrations in S1 partially contribute to interindividual variability on learning speed in the early learning stage.