The effect of repetitive transcranial magnetic stimulation of the cerebellum on cognitive control

doi:10.21203/rs.3.rs-5317310/v1

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The effect of repetitive transcranial magnetic stimulation of the cerebellum on cognitive control

https://doi.org/10.21203/rs.3.rs-5317310/v1

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Background

Research on brain interventions utilizing transcranial magnetic stimulation (TMS) technology has advanced significantly, however, studies focusing on the transcranial magnetic stimulation of the cerebellum remain in their preliminary phase. Research in neuroscience has established the cerebellum as a critical component in cognitive control, decision-making, and response regulation.;

Methods

The present study focused on the Curs II subregion of the cerebellum and involved 125 participants, who were categorized into five distinct groups. Each group received repetitive transcranial magnetic stimulation (rTMS) at frequencies of 1 Hz, 5 Hz, 10 Hz, 20 Hz, as well as a sham stimulation. Participants were evaluated through a go/no-go task both prior to and following the stimulation, while their electroencephalogram (EEG) were concurrently recorded for subsequent analysis.;

Results

The results indicate that cerebellar transcranial magnetic stimulation has a significant impact on cognitive task performance throughout the brain. High-frequency stimulation at 5 Hz, 10 Hz, and 20 Hz appears to activate neurons in brain regions linked to cognitive functions, leading to an increase in event-related potential (ERP) peaks and enhancements in the global efficiency and clustering coefficient of the overall brain network. Among the high-frequency conditions, stimulation at 10 Hz produced the most pronounced improvement in cognitive task performance and significantly enhanced the global efficiency of brain networks In contrast, low-frequency stimulation at 1 Hz was found to suppress cognitive task performance..;

Conclusions

TMS of the cerebellum can either enhance or inhibit cognitive control functions, suggesting that the cerebellum plays a significant role in the participation and regulation of cognitive control.

TMS

cerebellum

cognitive control

EEG

Cognitive control represents a fundamental cognitive capacity that involves the brain's processes of receiving, interpreting, and making decisions based on information[1]. This ability is integral to the management and regulation of thought and behavior in everyday life, encompassing aspects such as attention regulation, emotional management, and action control. A decline in cognitive control serves as a significant marker of cognitive decline associated with aging and various medical conditions. Therefore, the enhancement of cognitive control holds considerable potential for improving individual capabilities and addressing clinical issues. Presently, strategies for augmenting cognitive control include non-invasive stimulation techniques, such as TMS and ultrasound stimulation, as well as invasive methods like deep brain electrical stimulation. In comparison to invasive interventions, non-invasive transcranial magnetic stimulation is generally more acceptable, although certain patient populations, including those with epilepsy and Parkinson's disease, may present exceptions. This technique offers several advantages, including being painless, low-risk, and cost-effective, which contributes to its widespread application in diverse areas of neuroscience research.

TMS is a non-invasive technique that modulates activity in the human brain to improve specific cognitive functions. It is presently employed in clinical settings for the treatment of various conditions, including Alzheimer's disease, stroke, and depression, among others[2–4]. As a method of localized stimulation, the identification of appropriate stimulation targets is a crucial determinant of the efficacy of TMS interventions. This selection is typically based on the goal of enhancing brain regions within circuits that are related to the targeted brain function. Previous research has predominantly identified the prefrontal cortex (PFC) as the primary target for enhancing cognitive control capabilities[5], establishing it as a significant focus for TMS therapy aimed at clinical cognitive enhancement. Additionally, the leading areas of investigation in cognitive and memory research continue to emphasize PFC-associated cognitive brain circuits, which encompass regions such as the dorsolateral prefrontal cortex, inferior frontal gyrus, superior temporal gyrus, and anterior cingulate cortex[6, 7]. However, recent research has indicated that the cerebellum also plays a significant role in regulating complex tasks such as cognition, memory, and decision-making.

The function of the cerebellum in cognitive processing has recently sparked considerable interest in cognitive neuroscience [8–10]. It was revealed that the surface of the cerebellum is folded more tightly than the cerebral cortex, with almost 80% of the neocortex connected to the cognitive network of the brain [11]. Studies have suggested that the role of the cerebellum in the processing of the various cognitive functions such as working memory [12], emotion [13], language [14], and other executive functions [15] can be attributed to its extensive connections to the cortical and subcortical areas (particularly between the Crus I and Crus II, known as the lateral “limbic” cerebellar circuit) [16]. The cerebellum acts as a key part of the adaptive regulator in cognitive processing, supervising the working brain areas, detecting cognitive patterns, changes and errors, and generating responses anddistributing feedback to numerous cerebral areas, to increase the effectiveness of brain activity [17]. The previous study showed that the cognitive impairment after cerebellar injury was involved in multiple cognitive domains. The connection efficiency and information integration ability of the brain network were disrupted, indicating that the cerebellum could participate in the integration and regulation of the cognitive network [18]. Additionally, in another work, it was observed that the cerebellum Crus II exhibited increased activity in the preclinical stage of AD, reflecting a compensatory function that could mitigate early AD symptoms [19].

TMS produces varying neural regulatory effects depending on the stimulation frequency [20]. Repetitive transcranial magnetic stimulation (rTMS) has been widely utilized in clinical practice. Research indicates that high-frequency stimulation enhances cortical excitability, whereas low-frequency stimulation exerts inhibitory effects on neural circuits. Specifically, high-frequency rTMS (≥ 5 Hz) induces long-term potentiation and generates excitatory effects on neural tissue, while low-frequency rTMS (≤ 1 Hz) applies inhibitory effects on neural tissue through long-term inhibitory mechanisms [21]. TMS interventions targeting the cerebellum can modulate neural circuits associated with cognitive functions, including the default mode network, attention network, and frontoparietal network [23–25]. Additionally, TMS can influence the primary motor cortex and motor-evoked potentials [26]. In studies related to cognition, TMS interventions in the cerebellum have been shown to significantly enhance the semantic memory function of participants [27, 28].

The Go/No-Go task is a widely utilized psychological paradigm for assessing individual cognitive control and decision-making. It aims to measure an individual's capacity to regulate and inhibit responses to various stimuli [29]. When integrated with EEG experiments, ERPs serve as significant observational indicators of evoked potentials and are extensively employed in neuroscience research [30]. The P300 component is a cognitive-related ERP that is frequently recorded during EEG data analysis of Go/No-Go experiments [31] and is a crucial indicator for evaluating the cognitive abilities of participants.

Although the cerebellum has been shown to play a role in cognitive behavior, particularly in cerebellar Crus II, research on the effects of TMS interventions in the cerebellum on cognitive control abilities remains limited. Therefore, this study aims to target cerebellar Crus II with TMS, using a go/no-go task as the cognitive ability assessment. Multiple stimulation frequencies will be employed. During the experiment, EEG data will be collected synchronously, and ERP and brain network analyses will be conducted to evaluate the enhancement of cognitive control abilities resulting from TMS cerebellar intervention at different frequencies.

2.1. Participants

The study was conducted according to the guidelines of the Declaration of Helsinki and approved by the Ethics Committee of the Affiliated Brain Hospital of Nanjing Medical University (2022-KY026-01, approved date: 24 February 2022). A total of 125 graduate students, aged between 18 and 30 years, will be recruited for participation in the study. Participants must have Mini-Mental State Examination (MMSE) and Montreal Cognitive Assessment (MoCA) scores within the normal range. Additionally, Hamilton Anxiety Rating Scale (HAM-A) and Hamilton Depression Rating Scale (HAM-D) scores must be less than 7 points. Magnetic resonance imaging (MRI) of the head will be conducted, and no organic diseases should be present.

Exclusion criteria: Patients with a history of neurological disorders that impair cog-nitive function, including but not limited to traumatic brain injury, stroke, and epilepsy. Patients with a history of mental illness, as well as those with related family histories or other contributing factors. Patients with severe primary diseases affecting the cardio-vascular, liver, kidney, or hematopoietic systems. Patients who have been implanted with medical devices. Patients who are unable to cooperate in completing examinations or follow-up procedures.

2.2. Process of Experiment

Before participating in the experiment, participants must understand the Go/No-Go task, complete two training sessions to achieve a basic level of proficiency, and have the entire process explained to them, excluding key factors such as stimulus grouping and experimental objectives. Prior to the formal experiment, participants should wear EEG caps, set up the data collection devices, and adjust to a comfortable sitting position to minimize any electromyographic interference caused by physical discomfort during the experiment. We utilized a 69 + 2 channel EEG cap (Neuracle Technology (Changzhou) Co, Ltd. China), The EEG signal acquisition equipment was also sourced from the same company [33], and the experimental data acquisition frequency was set at 1000 Hz. This task requires participants to use a computer screen and keyboard. The screen displays stimuli, while the keyboard is used to confirm Go stimuli. When participants confirm that they have received the Go stimuli, they must press the keys themselves. Once the participants have demonstrated their understanding of the Go/No-Go task, the experiment officially begins.

The participant ts were required to undergo a Go/No-Go experiment both before and after transcranial magnetic stimulation, as shown in Fig. 1. During the stimulation phase, the Crus II region of the cerebellum was targeted for rTMS at a consistent frequency, location, and intensity, as shown in Fig. 2. The selection of stimulation sites utilized whole-brain precise navigation devices, and the specific stimulation points for each participant were determined based on the structural localization of MRI data [34]. The stimulus intensity was set at 80% of the resting motor threshold. Throughout the experiment, all participants demonstrated a high tolerance to the stimuli, and none reported any adverse reactions, such as headaches, dizziness, or nausea.

In the experiment, we employed five types of stimuli: 1 Hz, 5 Hz, 10 Hz, 20 Hz, and sham stimulation (Sham). The 1 Hz stimulus is classified as a low-frequency stimulus, whereas the other true stimulus frequencies are categorized as high-frequency stimuli. The sham stimulus serves as the control group to assess the effectiveness of TMS intervention in the experiment. Without taking into account the participants' age, education level, or other factors, each participant will be randomly assigned to receive only the corresponding frequency of stimulation. However, they will remain unaware of which stimulation they have received until the completion of the experiment.

Due to safety concerns and the tolerance levels of the subjects, we established a maximum stimulation frequency of 20 Hz. Additionally, varying intensities of rTMS can yield different regulatory effects [22]; however, this factor is beyond the scope of the current study. We ensured a consistent stimulation intensity across all experiments.

Considering that the elderly population will experience varying degrees of cognitive decline as they age, and acknowledging the individual differences among them [32], varying cognitive levels will introduce additional baseline differences. Consequently, we recruited 125 graduate students from Nanjing Brain Hospital to participate in the experiment.

2.3. Design of Go/No-Go Experiments

The process of the gongo paradigm used to evaluate the cognitive control abilities of participants is shown in Fig. 3, where the gray circles represent and the blue circles represent go and nogo stimuli, respectively. Participants are required to press a button when the go stimulus image appears and refrain from any button actions when the nogo stimulus image appears. Trigger recording occurs each time a stimulus appears. Two stimuli were randomly presented in a 3:1 ratio, with each stimulus images presented for 500ms and a 1500ms interval between stimuli. The images were centered on the screen in the form of a white cross. Each experimental session, conducted before and after the TMS intervention, consisted of two sessions, with 6 trials per session and a total of 100 stimulus images presented in each trial.

The process of the gongo paradigm used to evaluate the cognitive control abilities of participants is shown in Fig. 1, where the gray circles represent and the blue circles represent go and nogo stimuli, respectively. Participants are required to press a button when the go stimulus image appears and refrain from any button actions when the nogo stimulus image appears. Trigger recording occurs each time a stimulus appears. Two stimuli were randomly presented in a 3:1 ratio, with each stimulus images presented for 500ms and a 1500ms interval between stimuli. The images were centered on the screen in the form of a white cross. Each experimental session, conducted before and after the TMS intervention, consisted of two sessions, with 6 trials per session and a total of 100 stimulus images presented in each trial.

2.4. Data Analysis

Our data processing utilizes the MATLAB toolkit, EEGLAB. First, it is essential to perform channel localization and incorporate the electrode distribution map for the cerebellar leads, as shown in Fig. 4. Secondly, we used low-pass filtering to eliminate interference below 0.1 Hz in the data, and band-pass filtering to remove 50 Hz power frequency interference caused by the device. Thirdly, use the Nima principle [35] to identify and exclude any bad channels in the EEG data. Fourth, we performed whole-brain average referencing on the data to eliminate baseline interference. Finally, the data underwent source component analysis, during which interference components such as electrooculography, electromyography, and circuit noise were removed using the built-in IC Label plugin in EEGLAB.

2.5. ERP and Brain network Analysis

After completing the data preprocessing, the data was segmented with a window width of -200 to 500 ms based on the nogo trigger in the stimulation experiment. The segmented data was then subjected to a 2–8 Hz bandpass filter for ERP observation. Subsequently, the data was overlaid and averaged to analyze the ERP induced by nogo stimulation in the participants. This study focuses on three ERP potentials: P100, N200, and P300.To examine the effects of TMS on different brain regions, we selected specific channels from various areas, including the frontal lobe (FP1, FP2, F3, F4), parietal lobe (C1, C2, C3, C4), and occipital lobe (P3, P4, O1, O2), for data analysis both before and after stimulation. Given the variability of ERP responses among individuals, we utilized the ratio of ERP induction amplitude before and after the transcranial magnetic intervention as the observation indicator, as shown in formula (2 − 1):

\(\:{\text{y}}_{i-P300}=\:{x}_{i2-P300}/{x}_{i1-P300}\)

(2 − 1)

Assuming\(\:{\text{x}}_{\text{i}1-\text{P}300}\) is the absolute values of the P300 waveform peaks and valleys induced by No-Go stimulation in i-channel participants prior to transcranial magnetic stimulation, \(\:{\text{x}}_{\text{i}2-\text{P}300}\) is the absolute values of the P300 waveform peaks and valleys induced by No-Go stimulation in i-channel participants following transcranial magnetic stimulation, \(\:{\text{y}}_{\text{i}-\text{P}300}\) is the efficacy of transcranial magnetic cerebellar stimulation on the P300 potential response in i-channel-covered brain regions of the participants. \(\:{\text{y}}_{\text{i}-\text{P}300}\)> 1 suggests that the stimulation has an enhancing effect on P300-related functions in that brain region; conversely, otherwise it has an inhibitory effect.

TMS intervention enhances the overall improvement of brain regions in the cerebellum. This includes the improvement effect index\(\:{\text{y}}_{\text{f}\text{r}\text{o}\text{n}\text{t}\text{a}\text{l}-\text{P}300}\) related to frontal lobe P300 functions, which represents the average value of all electrode elevation results in frontal lobe-associated brain regions, as shown in Eq. (2–2):

\(\:{\text{y}}_{frontal-P300}=({\text{y}}_{FP1-P300}+{\text{y}}_{FP2-P300}+{\text{y}}_{F3-P300}+{\text{y}}_{F4-P300})/4\)

(2–2)

We also conducted a variance analysis to assess the effects of different stimulus groups on improvement. Subsequently, we employed post hoc multiple comparisons to evaluate the results between paired groups. A p-value of less than 0.05 is considered statistically significant in data analysis, while a p-value of less than 0.001 indicates a higher level of statistical significance.

The phase-locked brain network was analyzed using EEG data with a window width of 700 ms, as described in Section 2.4. The clustering coefficients and global efficiency of the brain network were calculated using the MATLAB toolkit, Brain Connectivity Toolbox version 2019.03.03. Additionally, pairwise t-tests were conducted on the two indicators for each group of participants following transcranial magnetic stimulation. A p-value of less than 0.05 was considered statistically significant, while a p-value of less than 0.001 indicated a more substantial level of significance. Furthermore, to facilitate data comparison, the results of both indicators were normalized.

3.1. Participants Results

The means of general information and group analysis results for the five participant groups are presented in Table 1.Gender was tested using the chi-square test, while the remaining variables were analyzed using analysis of variance (ANOVA). No significant differences were found across multiple tests between the groups. Due to the large number of groups involved—totaling ten—the table does not provide a detailed breakdown but instead reports only the p-values for variance. A significance level of p < 0.05 was used to determine statistical significance. From the table, it is evident that there were no significant differences in age, gender, or cognitive level among the participants across the groups. There was no significant difference between the two groups in the multiple checks as well.

Tabel 1 Participants testing information

	Sham	1hz	5hz	10hz	20hz	p
Age(years)	24.85\(\:\pm\:\)1.85	24.61\(\:\pm\:\)1.39	24.10\(\:\pm\:\)1.32	24.77\(\:\pm\:\)1.66	24.52\(\:\pm\:\)1.02	0.257
Education(years)	17.74\(\:\pm\:\)0.94	17.61\(\:\pm\:\)0.79	17.53\(\:\pm\:\)0.90	17.65\(\:\pm\:\)1.32	17.69\(\:\pm\:\)0.85	0.943
Sex(male)	52.00%	56.00%	44.00%	40.00%	56.00%	0.320
MMSE(scores)	29.74\(\:\pm\:\)0.59	29.96\(\:\pm\:\)0.19	29.83\(\:\pm\:\)0.38	29.88\(\:\pm\:\)0.43	29.93\(\:\pm\:\)0.26	0.243
MOCA(scores)	28.44\(\:\pm\:\)1.15	28.89\(\:\pm\:\)1.10	28.17\(\:\pm\:\)1.44	28.73\(\:\pm\:\)1.31	28.59\(\:\pm\:\)1.24	0.236
HAMA(scores)	1.33\(\:\pm\:\)1.44	2.14\(\:\pm\:\)1.78	1.77\(\:\pm\:\)1.65	1.54\(\:\pm\:\)1.61	1.97\(\:\pm\:\)1.66	0.369
MAMD(scores)	1.19\(\:\pm\:\)1.44	1.36\(\:\pm\:\)0.99	1.37\(\:\pm\:\)1.27	1.35\(\:\pm\:\)1.44	1.62\(\:\pm\:\)1.35	0.806

3.2. ERP Results

The comparison of ERP induced by No-Go stimulation before and after TMS intervention in the experiment yielded three results: enhancement, inhibition, and slight change. These results are shown in Fig. 5, where the blue curve represents the ERP potential induced by No-Go stimulation prior to the TMS intervention, and the red curve represents the ERP potential induced by No-Go stimulation after TMS intervention. The ERP potentials highlighted in yellow include P100, N200, and P300, which are of particular interest in this research.

Figure 5. (a) shows that the ERP response of the participants to No Go stimuli was inhibited after TMS intervention, Fig. 5. (b) shows that the ERP response of the participants to No Go stimuli was enhanced after TMS intervention, and Fig. 5. (c) shows that there was almost no change in the ERP response of the participants to No Go stimuli after TMS intervention.

In the experiment, there may be instances where a specific electrode channel displays only one ERP both before and after the TMS interven. For instance, in one participant's experiment, if the FP1 channel demonstrated P300 induction in response to No-Go stimulation before TMS intervention, but no P300 induction after intervention, then \(\:{\text{y}}_{\text{F}\text{P}1-\text{P}300}\) is recorded as 0. Conversely, if there was no P300 induction before the intervention and a P300 potential appeared after intervention, \(\:{\text{y}}_{\text{F}\text{P}1-\text{P}300}\) is recorded as 2.

The results of the comparative analysis of ERP before and after five different frequency TMS interventions in the participant groups are shown in the heatmap presented in Fig. 6–8. The p-values corresponding to the ERPs of the five groups were calculated using Eq. (2–2), as indicated above the figure. The numbers adjacent to each stimulus frequency on the x-axis represent the average ERP values for the participants in that group. For instance, 1Hz-0.898 represents the mean of the results calculated by Eq. (2–2) in the experiment for all participants in the 1Hz group, which is 0.898. Each grid represents the p-value of multiple checks between different frequencies. In the figure, 9.089\(\:{\text{e}}^{-8}\) represents 9.089 × \(\:{10}^{-8}\), fr represents the frontal lobe, pa represents the parietal lobe, and oc represents the occipital lobe.

3.2.1 P100 analysis

After the TMS intervention, all participants in the low-frequency stimulation group exhibited inhibition of the P100 potential peak induced by No-Go stimulation, with the most significant inhibition observed in the occipital lobe. In contrast, the peak P100 potential of participants in the high-frequency stimulation group was enhanced, with the strongest enhancement noted in the 10 Hz stimulation group. In the parietal and occipital regions, the enhancement effect was more pronounced in the 20 Hz group compared to the 5 Hz group. The P100 amplitude of participants in the sham stimulation group showed almost no difference compared to measurements taken before the TMS intervention.

The analysis of variance revealed extremely significant differences among the various groups. In multiple validations, a highly significant difference was observed between the 1 Hz group and the high-frequency stimulation group, as well as between the sham stimulation group and the 1 Hz group in the frontal and parietal regions. A significant difference was noted in the occipital region with a p-value < 0.05. Additionally, a p < 0.05 difference between the 5 Hz group and the other two high-frequency stimuli in the parietal and occipital lobes of the 20 Hz group, along with a p-value < 0.05 in all brain regions compared to the sham stimulation group. No significant difference was found between the 10 Hz group and the 20 Hz group; however, a highly significant difference was observed in the frontal and parietal lobes when compared to the sham stimulation group. Furthermore, a p-value < 0.05 indicated a difference in the occipital lobe, as well as in all brain regions between the 20 Hz group and the sham stimulation group.

3.2.2 N200 analysis

After the TMS intervention, the participants in the low-frequency stimulation group exhibited similar inhibition of the N200 potential peak induced by No-Go stimulation in all three brain regions, with less inhibition observed in the occipital lobe compared to the P100. In contrast, the peak N200 potential of participants in the high-frequency stimulation group was enhanced, with the N200 enhancement effect of participants in the 10hz group was also the strongest, but the effect was comparable to that of the 20 Hz group in the parietal lobe region. No significant differences in N200 amplitude changes were found between the sham stimulation group and the measurements taken prior to the TMS intervention.

The analysis of variance revealed highly significant differences among the various test groups. In multiple validations, there were highly significant differences between the 1 Hz group and the other true stimulus groups, with a p-value < 0.05 difference between the 1 Hz group to the sham stimulus group. In the high-frequency stimulation group, a significant difference (p < 0.05) was observed between the 5 Hz group and the 20 Hz group in the parietal lobe region, as well as between the 5 Hz group and the sham stimulation group. No significant difference was found between the 10 Hz group and the 20 Hz group; however, both groups exhibited significant differences (p < 0.05) when compared to the sham stimulation group.

3.2.3 P300 analysis

After the TMS intervention, the low-frequency stimulation group exhibited inhibition of the P300 potential peak induced by No-Go stimulation in three brain regions. The levels of inhibition were greater in the frontal and parietal lobes compared to the P100 and N200 components. In contrast, the peak P300 potential of participants in the high-frequency stimulation group was enhanced, with the most pronounced effects observed in the 5 Hz and 10 Hz groups within the frontal and occipital regions. Notably, the strongest enhancement effect was recorded in the 10 Hz group in the parietal region. The amplitude changes of P300 in the sham stimulation group showed no significant differences compared to measurements taken prior to the TMS intervention.

Specifically, there was a highly significant difference between the 1 Hz group and the other true stimulus groups in multiple validations, with a p-value < 0.05 when comparing the 1 Hz group to the false stimulus group. Additionally, no significant differences were observed among the high-frequency stimulation groups across the different brain regions; however, a p-value < 0.05 was noted when comparing the high-frequency stimulation group to the sham stimulation group.

3.2. Brain network Results

The clustering coefficients and global efficiency of the brain networks for five groups of participants, both before and after the TMS intervention, are shown in Table 2. The clustering coefficients are denoted as CC, while global efficiency is represented as E_glob. Specifically, CC_pre refers to the mean clustering coefficient of the brain networks for all participants in the group before the TMS intervention, CC_post indicates the mean clustering coefficient of the brain networks for all participants in the group after the TMS intervention, and CC_p represents the p-value obtained from a t-test comparing the data before and after the intervention. The method for recording global efficiency remains consistent.

As shown in Table 2, consistent with the results shown in Section 3.2, the TMS intervention led to a significant decrease in the clustering coefficient of the brain network in the 1 Hz group of participants. In contrast, the high-frequency stimulation groups 5 Hz and 10 Hz patient groups, exhibited a significant enhancement in their brain network connectivity. Notably, the 5 Hz group demonstrated the most substantial increase in the clustering coefficient, accompanied by a smaller p-value. Although the changes in brain network clustering coefficients before and after the TMS intervention were not statistically significant in the 20 Hz and sham groups, the average improvement observed in the 20 Hz group was considerably greater than that in the sham group.

Table 2

Brain network analysis results cefore and after TMS intervention
1hz	CC_pre	CC_post	CC_p	Eglob_pre	Eglob_post	Eglob_p
	0.558	0.461	0.039	0.459	0.368	0.004
5hz	CC_pre	CC_post	CC_p	Eglob_pre	Eglob_post	Eglob_p
	0.364	0.545	0.002	0.445	0.553	9.734\(\:{e}^{-4}\)
10hz	CC_pre	CC_post	CC_p	Eglob_pre	Eglob_post	Eglob_p
	0.319	0.458	0.041	0.305	0.488	1.237\(\:{e}^{-4}\)
20hz	CC_pre	CC_post	CC_p	Eglob_pre	Eglob_post	Eglob_p
	0.492	0.594	0.053	0.463	0.551	0.002
sham	CC_pre	CC_post	CC_p	Eglob_pre	Eglob_post	Eglob_p
	0.491	0.521	0.079	0.488	0.503	0.067

After the low-frequency TMS intervention, the global efficiency of the brain network in the participants exhibited a significant decrease. In contrast, the three groups receiving high-frequency stimulation demonstrated a notable improvement in global efficiency. Specifically, the 5 Hz and 10 Hz groups showed highly significant enhancements, with the 10 Hz group displaying a greater average improvement in global efficiency compared to the other groups. No statistically significant changes in global efficiency were observed among the participants in the sham group.

TMS is a non-invasive technique that employs a magnetic field to stimulate the cerebral cortex, generating induced currents that modify the action potentials of cortical neurons. This modulation affects both metabolism and neural electrical activity in the brain. The induced currents can either activate or inhibit neuronal activity in specific brain regions, thereby influencing overall brain function. Recent studies have demonstrated that the cerebellum plays a crucial role in various cognitive behaviors in humans [36]. TMS intervention has the potential to enhance cognitive function by targeting cerebellar neurons. Furthermore, the intensity of the induced currents varies with different stimulation frequencies, leading to differential effects on neuronal activity. In this study, we established four true stimulation groups targeting the cerebellum: 1 Hz, 5 Hz, 10 Hz, and 20 Hz, with a sham stimulation group serving as the control. ERP and brain network parameters were utilized as observational indicators to assess the effect of TMS cerebellar intervention on cognitive function across different frequencies.

ERP, which represent the cumulative postsynaptic potentials in neurons, indicate the level of excitation or inhibition of the neural response to external stimuli. In this study, after cerebellar TMS at varying frequencies, the ERP of subjects in the low-frequency stimulation group exhibited inhibition, whereas the ERP of subjects in the high-frequency stimulation group demonstrated enhancement. No significant changes in ERP were observed in the control group that received sham stimulation. These findings suggest that low-frequency TMS can lead to long-term inhibition of synaptic transmission, resulting in reduced neuronal activity, while high-frequency stimulation can induce long-term enhancement of synaptic transmission, thereby increasing cortical excitability. This alteration is reflected in the peak ERP potential. Furthermore, the results from the control group indicate that the psychological effects of repetitive tasks or TMS interventions on ERP enhancement are minimal.

The peak value of P100 is regarded as an indicator of early perceptual processing and exhibits sensitivity to variations in color, brightness, attention, and spatial frequency. Observations of P100 before and after TMS intervention revealed that 10 Hz stimulation produced the most significant enhancement in the frontal, parietal, and occipital regions. Additionally, 20 Hz stimulation in the parieto-occipital region was more effective than 5 Hz stimulation, suggesting that the excitability response of P100 related neurons in the cerebellum was most pronounced under 10 Hz stimulation. Furthermore, the strongest inhibition observed in the occipital lobe during low-frequency stimulation indirectly supports this conclusion. As the most stable visual evoked potential, P100 reflects responses to external visual stimuli. TMS intervention in the cerebellum induces changes in the amplitude of P100, indicating that the cerebellum plays a role in modulating visual responses in the frontal, parietal, and occipital regions. Notably, 10 Hz stimulation is particularly effective in regulating visual responses in the cerebellum, with a stronger regulatory effect on the frontal and parietal lobes compared to the occipital lobes. The excitability of neurons triggered by visual stimuli may facilitate the activation of neurons associated with perceptual processing in the frontal and parietal lobes, suggesting that cerebellar excitation enhances visual and perceptual processing functions.

The N200 peak is considered sensitive to tasks involving attention and working memory. Observations of the N200 after TMS intervention revealed that 10 Hz stimulation produced the most significant enhancement in the frontal, parietal, and occipital regions. However, the enhancement effect in the parietal lobe was comparable to that observed in the 20 Hz group. The top-down information flow in the parietal lobe during attention processing can enhance sensory control. Previous studies have indicated that the frontal and parietal lobes are involved in a similar "selection" mechanism that governs the representations "stored" in working memory. Visual-spatial templates and central executive systems play a role in related tasks [37], and the N200 may represent one of the resultant potentials associated with neuronal activity in these tasks. Additionally, the N200 response linked to the posterior frontal and parietal lobes of the cerebellum was enhanced by TMS, suggesting that the cerebellum is involved in or regulates tasks related to working memory. After high-frequency stimulation, the excitation of neurons in the corresponding brain regions can positively influence participants' engagement in attention and working memory tasks.

P300 is closely associated with cognitive and psychological processes, including recognition, difficulty, task engagement, attention, and memory of stimulus signals. It can objectively reflect advanced cognitive activities, such as the brain's cognitive and judgment functions. The intensity of its peak serves as an observational indicator of cognitive ability, and some researchers have utilized the peak of P300 as a basis for assessing patients with cognitive disorders [38]. In the experiment, after TMS intervention, the 5 Hz group exhibited the most significant enhancement of P300 in the frontal and occipital regions, while the 10 Hz group demonstrated the most notable enhancement of P300 in the parietal region. P300 is categorized into P300a and P300b, with peaks occurring in the frontal and parietal lobes, respectively. Notably, the P300b component is more closely linked to cognitive control, originating not only from the parietal lobe but also being regulated by temporal regions, such as the hippocampus [39]. A study that combined visual search and cognitive tasks revealed that P300 in the frontal lobe was associated with search tasks, while P300 in the parietal lobe was linked to cognitive tasks [40]. Additionally, P300 in the occipital lobe is primarily related to the induction of cognitively relevant visual stimuli. Research findings indicate that the cerebellum has a more effective regulatory role in the search and discovery functions of cognitively related visual stimuli during 5 Hz stimulation. Conversely, in the processing of specific cognitive tasks, 10 Hz stimulation appears to be more effective in regulating the corresponding functions of the cerebellum. The enhancement of cognitive function through TMS intervention in the cerebellum may require multi-frequency coordination to achieve optimal results.

The brain network refers to the collective functioning state of neurons across various regions of the brain.Recent whole-brain imaging studies utilizing fMRI data have revealed significant interdependence among brain regions, which collaborate to process information and generate responses [41, 42]. After TMS intervention in the cerebellum, the brain regions that collaborate with it during cognitive tasks are also synchronously affected within the brain network. This change is transmitted throughout the entire brain, reflecting an alteration in the global efficiency of the network. After TMS intervention in the cerebellum, the global efficiency of the brain network in the high-frequency stimulation group improved, indicating that the excitation of cerebellar neurons facilitated the activation of cognitive-related brain neurons, thereby enhancing the overall information processing efficiency of the brain. The most significant improvement was consistent with the ERP group in the 10 Hz stimulation group, while the 5 Hz group exhibited a stronger effect than the 20 Hz group. This suggests that excessively high-frequency stimulation may lead to over-excitation of neurons, potentially diminishing some aspects of improvement in efficiency. Reason: Improved clarity, vocabulary, and technical accuracy while correcting grammatical and punctuation errors.

The clustering coefficient of brain networks is utilized to measure the efficiency of information transmission among local brain regions and to characterize the clustering efficiency of information processing in these areas during various tasks. After TMS intervention in the cerebellum, the clustering coefficient of the brain network in the high-frequency stimulation group showed significant improvement, with the 5 Hz group exhibiting the most pronounced enhancement. This suggests that the neurons engaged in cognitive tasks within the brain may not remain consistent throughout the process. In certain clusters, 5 Hz stimulation appears to more effectively enhance the excitability of the associated neurons. The cerebellum's neural regulation of cognitive functions in the brain operates through a multi-frequency collaborative mechanism.

This article presents a study on the enhancement of cognitive control through TMS targeting the cerebellum. Four experimental groups were established, each subjected to different stimulation frequencies, alongside a sham stimulation group serving as a control. All participants engaged in a go/no-go task, during which their EEG signals were collected synchronously. Following the experiment, ERP and brain network analyses were conducted on the EEG data. The findings indicated that TMS intervention in the cerebellum could either excite or inhibit neuronal activity in subjects during cognitive tasks, thereby affecting their cognitive abilities. Specifically, the research revealed that stimulation at 10 Hz significantly enhances subjects' cognitive comprehension and information processing capabilities, while stimulation at 5 Hz is more effective in improving functions related to visual cognitive task search. Furthermore, stimulation at 10 Hz was found to enhance the overall efficiency of brain information processing during cognitive tasks, whereas 5 Hz was more effective in improving the information processing efficiency of localized neuronal networks.

Author Contributions: Conceptualization, L.Q., J.S. and K.Y.; methodology, L.Q.; software, L.Q.; validation, L.Q. and B.S.; formal analysis, L.Q.; investigation, L.Q. and B.S.; resources, J.S. and K.Y..; data curation, B.S.; writing—original draft preparation, L.Q.; writing—review and editing, L.Q.; visualization, L.Q.; supervision, J.S. and K.Y; project administration, K.Y..; funding acquisition, K.Y. All authors will be informed about each step of manuscript processing includingsubmission, revision, revision reminder, etc. via emails from our system or assigned Assistant Editor.All authors have read and agreed to the published version of the manuscript

Funding: This research was funded by: 1)the National Natural Science Foundation of China, grant
number U19B2018; 2)Jiangsu Multidimensional Perception Laboratory,project number BM2022017.

Institutional Review Board Statement: The study was conducted according to the guidelines of theDeclaration of Helsinki, and approved by the Ethics Committee of the Affiliated Brain Hospital ofNanjing Medical University (2022-KY026-01, approved date: 24 February 2022).

Informed Consent Statement:. Informed consent was obtained from subjects involved in the study.

Data Availability Statement: The data are available upon reasonable request.

Acknowledgments: We would like to thank Bo Mu for their help in collecting data, Wendu Tao and Chao Yu for their suggestions on data processing.

Conflicts of Interest: The authors declare that there are no conflict of interest regarding the publication of this paper.

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The effect of repetitive transcranial magnetic stimulation of the cerebellum on cognitive control

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Abstract

Figures

1. Introduction

2. Materials and Methods

2.1. Participants

2.2. Process of Experiment

2.3. Design of Go/No-Go Experiments

2.4. Data Analysis

2.5. ERP and Brain network Analysis

3. Results

3.1. Participants Results

3.2. ERP Results

3.2.1 P100 analysis

3.2.2 N200 analysis

3.2.3 P300 analysis

3.2. Brain network Results

4. Discussion

5. Conclusions

Declarations

References

Additional Declarations

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Version 1