# Effect of Running Exercise on Brain Functional Magnetic Resonance Characteristics of College Students with Depression

Authors: Wangda Li; Jun Yang
Journal: Scanning
 (2022)

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## Abstract

In order to effectively reduce the incidence of depression in college students, the author proposes a method to influence brain functional magnetic resonance through running exercise. Aiming at the effect of running exercise on the brain functional magnetic resonance characteristics of depression in college students, through the comparison experiment between the MDD group and the HC group and the retrospective analysis of the sugar water preference experiment in rats, explore it in depth. Experimental results show that under the running exercise for six consecutive weeks, the average body weight of the rats in the depression model group was significantly lower than that in the blank control group, and the health status was significantly better than that in the blank group. Running exercise can effectively affect and reduce the incidence of depression in college students.


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## Body

## 1. Introduction

Depression (Figure1) is a common clinical mood disorder, mainly manifested as persistent sadness, anhedonia, loss of interest, lack of energy and physical strength, and decreased self-confidence. Most of the patients were also accompanied by unexplained somatization symptoms, varying degrees of cognitive impairment, and obvious retardation of thinking and action. They are always dissatisfied with the surrounding environment and quality of life, and they cannot experience the happiness they want, in severe cases, suicidal ideation and suicidal behavior occur. With the increase of life pressure, the prevalence of depression is increasing year by year, and it is getting younger. A survey in the United States showed that among 10,000 young people aged 13-18, about 15.9% of young men and 15.9% of young women had experienced a depressive episode, and most of the young people’s symptoms became chronic into adulthood or even aggravated [1]. According to the World Health Organization, about 100% of people will experience a depressive episode in their lifetime, and it is predicted that by 2020, depression may become the second most common disease after heart disease, which damages personal mental health and social function and also affects families, and society brings an unbearable burden [2]. Therefore, depression is a major problem that threatens public health and needs to be solved urgently.Figure 1
Depression.Running is defined by the American College of Sports Medicine as one of the organized and planned repetitive physical movements [3]. In recent years, it has received extensive attention as a nondrug antidepressant treatment. Studies have shown that running exercise 3 times a week for at least 8 weeks can achieve a therapeutic effect on patients with severe depression, and the intensity of the effect is about moderate to high; it was also found in animal experiments that running exercise can effectively improve the depression-like or anxiety-like behavior of experimental animals [4]. However, some people have put forward the opposite conclusion, they believe that running exercise has no antidepressant effect, and in the follow-up study of patients with depression, there is no significant improvement in the quality of life and disease severity of patients with depression [5]. If running can improve symptoms of depression or depressive-like behaviors, what is the mechanism by which running can improve depression?In order to further study the effect of running exercise on patients with depression, therefore, from the perspective of brain functional magnetic resonance characteristics, we can quickly and effectively draw conclusions and provide a therapeutic method for the treatment of depression.


## 2. Literature Review

Depression is a common mental disorder; its main clinical manifestations are low mood, decreased interest, and decreased energy; these symptoms have a high rate of disability and recurrence; in severe cases, suicidal behavior occurs. According to statistics from the World Health Organization, there are currently more than 350 million MDD patients in the world; a large epidemiological study in my country shows that the lifetime prevalence of MDD has reached, and the incidence is increasing year by year; at the same time, more people have depression, calculated in terms of disability-adjusted life years; the disability rate of depression ranks second and shows an upward trend [6]. If the incidence of MDD continues to rise and is not effectively controlled, it will become a significant contributor to the global burden of disease and disability. If MDD is not properly treated, not only is it easy to relapse, but with the increase of the number of relapses, the patient’s social function and cognitive function will gradually decline. At present, MDD has become an urgent worldwide public health problem [7].In recent years, with the gradual deepening of research on MDD, it has been found that it has a trend of younger age, so adolescent MDD has gradually received attention. Unlike adult MDD, adolescent MDD usually has a slow, long-term course. Studies have shown that after entering adolescence, the incidence of depression in adolescents increases sharply. Compared with adults, the risk of MDD in adolescence is doubled, and the detection rate of depressive symptoms in adolescents is between 60.7%; the total value is higher than the detection rate of adults and the elderly in my country; the recurrence rate of depressive symptoms is high [8]. At the same time, the depressive symptoms of adolescents also have atypical characteristics; the onset is insidious and may manifest as emotional problems such as emotional instability and irritability or behavioral problems such as truancy, substance abuse, fighting, and suicide. Adolescents not only face tremendous physical changes, but also are under enormous psychological pressure; if depression is not well regulated, it may lead to a series of long-term negative outcomes, including declining academic performance, interpersonal tension, substance abuse, dropping out of school, and health problems. Therefore, early identification of adolescents with MDD, and providing timely, evidence-based treatment, is important to reduce disability and suffering.At the same time, an fMRI study of adolescent depression found that the limbic system-pallidal-thalamic circuit has abnormal brain functional activity [9, 10]. However, it has not been found that NLE can cause abnormal brain function in adolescents with MDD [11]. Therefore, whether NLE is an influencing factor of abnormal brain activity in adolescent MDD patients, the result is unknown and needs to be further explored.According to literature records, Grońska-Pski et al. proposed in that running exercise can significantly increase the number of precursor cells in the hippocampal dentate gyrus of C57BL/6 mice and promote the survival of new neurons [12]. Botterill et al. pointed out that running exercise can significantly increase the number of new neurons in the hippocampal dentate gyrus of aged rats and reduce dentate gyrus apoptosis [13]. A large number of studies have shown that the antidepressant effect of exercise depends on the changes in the new ability of hippocampal neurons, but the fluorescent semiquantitative BRDU+ cells obtained in previous studies cannot fully reflect the changes of new neurons, precise quantitative study on the effect of running exercise on new hippocampal neurons in improving depression symptoms; related reports have not been seen [14].On the other hand, previous studies have shown that running exercise can effectively improve depression symptoms and promote the regeneration of neurons in the dentate gyrus of the hippocampus, so does the new generation of neurons mean the renewal of the neural signaling system? And are the changes in the proliferation and differentiation of oligodendrocytes and their oligodendrocyte precursor cells, which are closely related to neural signal transduction, also involved?Based on the above research, the author conducted a related study on the effect of running exercise on the brain functional magnetic resonance characteristics of college students’ depression. The authors retrospectively analyzed the relationship between NLE and brain region function in first-episode adolescent MDD patients based on fMRI. The first-episode adolescent patients with depression who were not treated with drugs were selected as the research objects, and the correlation between NLE and the functional activity of brain regions in the first-episode adolescent MDD patients was investigated based on fMRI, and the effect of running exercise on it was further explored and provides a treatment plan for depression treatment.


## 3. Methods

Experiment 1: In order to explore the correlation between NLE and brain region function in first-episode adolescent MDD patients based on functional magnetic resonance imaging.


### 3.1. Selection of Research Objects

In order to exclude related confounding factors such as drugs and disease duration, the authors selected the data of the first-episode, untreated adolescent MDD patients in a certain experiment for a retrospective analysis [15].


#### 3.1.1. First-Episode Adolescent Depression Group (MDD Group)

(1) Inclusion Criteria.
(i)
According to the diagnostic criteria of DSM-5, patients diagnosed with depression by two or more attending psychiatric clinicians have five manic episodes, which are the first depressive episodes(ii)
Age 18-22(iii)
HAMD-24≧18 points(iv)
Have never received antidepressant treatment in various ways such as psychotropic drugs, psychotherapy, and electroconvulsive therapy(v)
Han nationality, right-handed(vi)
Able to cooperate with the completion of the scale assessment(2) Exclusion Criteria.
(i)
A previous definite episode of mania or hypomania(ii)
Those with a previous diagnosis of bipolar disorder, schizophrenia or other mental disorders(iii)
Patients with a history of substance abuse and acute poisoning(iv)
Head trauma, loss of consciousness or serious physical illness(v)
Contraindications for MRI scanning, such as artificial heart valves, metal foreign bodies, etc.


#### 3.1.2. Healthy Controls (HC Group)

Inclusion criteria:(i)
Age 18-22 years old(ii)
HAMD-24≦7 points(iii)
Han nationality, right-handed(iv)
No serious physical or mental illness(v)
Have not taken sleeping, anesthesia, analgesic, and other drugs in the past month before enrollment(1)
Able to cooperate with the completion of the scale assessmentExclusion criteria:(i)
Those with a previous diagnosis of depression, bipolar disorder, schizophrenia, or other mental disorders associated with other diseases(ii)
Patients with a history of substance dependence and acute poisoning in the past(iii)
Head trauma, loss of consciousness or serious physical illness(iv)
Contraindications for MRI scanning, such as artificial heart valves and metal foreign bodies, etc.


### 3.2. Research Tools

#### 3.2.1. General Population Information Collection

A self-made questionnaire was used to collect the demographic information of all subjects, including name, age, gender, right-handedness, ethnicity, years of education, family history, past history, and personal history, as well as the time of the onset and the last MDD medical history information such as monthly drug use [16].


#### 3.2.2. Hamilton Depression Scale (HAMD-24)

Developed in 1960, this scale is one of the scales commonly used clinically to assess the severity of depression and depressive symptoms, and the assessment time range is the most recent week. The HAMD-24 has 24 items covering the following 7 categories of factors: anxiety/somatization, blockade, cognitive impairment, sense of hopelessness, weight changes, sleep disturbances, and circadian variability, of which 10 items are on a 3 scale from 0 to 2 For scoring, 14 items were scored on a 5-point scale from 0 to 4. The total score indicates that there are no depressive symptoms; the score that may have mild or moderate depression may indicate severe depression [17].


#### 3.2.3. Hamilton Anxiety Scale (HAMA)

The scale was developed in 1959; HAMA is one of the commonly used clinical scales to evaluate anxiety symptoms, and the assessment time range is the situation of the most recent week. There are 14 items in HAMA, which can be classified into two factors: mental anxiety and somatic anxiety. A 5-point scale from 0 to 4 was used. The total score of<7 points has no anxiety symptoms; ⩾7 points may have anxiety; ⩾14 points must have anxiety; ⩾21 points must have obvious anxiety; ⩾29 points may indicate severe anxiety [18].


#### 3.2.4. Adolescent Life Events Self-Rating Scale (ASLES)

The scale is a combination of domestic and foreign literatures by many domestic experts, based on the actual situation in my country; it was compiled in 1987; the scale measures the influence of negative life events in adolescents in the past 12 months, currently widely used. ASLEC has a total of 27 items with a 5-level score [19]. It can be divided into the following six categories of factors: learning stress factor, interpersonal relationship factor, loss factor, punishment factor, health adaptation factor, and others (including school fatigue, relationship dissatisfaction or breakdown, quarrel with others, parental beating, and scolding 4 items); the higher the score, the more negative sexual events have a greater impact. The scale has good reliability and validity. It applies to adolescents to assess stress intensity and frequency of life events.


### 3.3. Research Methods

#### 3.3.1. Clinical Data and Scale Data Collection

According to the inclusion criteria, the demographic data collection was completed on the same day as outpatient visits or hospitalizations by trained researchers in the adolescent MDD group; at the same time, all subjects were asked to complete the scale assessment in a mental health center psychological testing center. The HC group was under the guidance of trained researchers to collect general demographic data and evaluate the scale; after completing the above steps, the resting state brain function MRI data of the research subjects were collected.


#### 3.3.2. Resting-State Functional Brain MRI Data Acquisition

Magnetic resonance data acquisition of study subjects was completed in a mental health center. The data of three modalities of structural image, BOLD, and diffusion tensor imaging were collected for all subjects. During the acquisition process, the head position of the research subject was fixed, and active and passive movements of the head and other parts were avoided, and the subjects were in a quiet supine position; during the scanning process, anti-irritability headphones were worn to reduce the interference caused by noise. The patient was asked to stay awake, still, eyes closed, and try to avoid moving and thinking during the entire MRI scan. Echo-planar imaging (EPI) sequence was used for scanning, and the parameters were scanned by resting state functional image: Repetition Time = 2000ms, acquisition matrix = 64×64, flip angle = 90°, Rield of View = 240 × 240mm, Echo Time = 30ms, depth of stratum: 4.0mm, no layer spacing, a total of 35 layers [20].


#### 3.3.3. Image Processing

(1) Preprocessing. Firstly, the MRI conversion software was used to convert the DICOM format images into NIfTI format for data processing. The images were then preprocessed using DPARSF software. Specific steps are as follows:
(1)
Remove time points: considering that the uneven magnetic field may affect the image, the first 10 time points of the image are removed, in order to stabilize the MRI signal, and the research subjects need to adapt to the scanning environment noise(2)
Time series correction: correct the image acquisition time, in order to eliminate the influence of the time difference of the brain due to the different scanning time on the image time series of each layer(3)
Correction of head movement: the rotation on thex, y, and z axes is greater than 3∘ or culling images with a maximum head movement translation exceeding 3 mm; head movement parameters, cerebrospinal fluid, and white matter were used as covariates(4)
Normalization: the authors registered the T1 structural and functional images, and then matched them with the Montreal Neurological Institute template for3×3×3mm voxel resampling(5)
Smoothing: convolve and smooth the normalized image using an isotropic Gaussian kernel (maximumwidthathalfmaximum=8mm) to reduce spatial noise(6)
Delinear drift and filter processing: in order to reduce low-frequency drift and eliminate physiological noise, the filter signal with frequency in the range of 0.01-0.08 Hz is extracted(2) ALFF, fALFF analysis. ALFF is the Fourier transform of the time series for each voxel throughout the brain, and convert to domain power spectrum. The area under the power spectrum can be regarded as the signal energy intensity, and then the area under the peak is squared, and the result is the change intensity of the BOLD signal, which represents the amplitude of the signal oscillation. The ALFF value for each voxel was divided by the whole-brain average ALFF value as the normalized ALFF value for each voxel. ALFF can be used to reflect the strength of spontaneous activity of voxels in the resting state, thereby reflecting the strength of local neuronal activity. ALFF is a modified ALFF that can effectively suppress nonspecific hyperintensity from the cisternal region and improve the sensitivity and specificity of spontaneous neuron detection.(3) REHO Analysis. REHO reflects the synchronization of local neuronal activity in brain regions. Perform local consistency analysis on the unsmoothed data, calculate and compare the time series synchronization of each voxel in the whole brain with its adjacent 26 voxels, obtain the Kendall harmony coefficient, that is, the REHO value, and then divide by the whole brain REHO mean, and then smoothed with an 8-mm FWHM Gaussian kernel.


### 3.4. Statistical Analysis

Data entry and statistical analysis were performed in SPSS software. On SPSS 24.0 software, the general data of the two groups were compared byx2 test and t-test. The t-test and nonparametric test were used to compare the scores of HAMD-24, HAMA, and ASLEC between the two groups. The measurement data were expressed with mean±standarddeviationx‾±s. Inspection level α=0.05. Using SPM software, t-test was performed on the ALFF value, fALFF value, and REHO value of the two groups. The xjview plug-in and BrainNet software were used to calculate and display brain areas with statistically significant differences (Alphasim correction, the areas of P<0.01 and voxel >20 are defined as statistically significant differences). Pearson correlation analysis was used to analyze the correlation between ASLEC and HAMD-24 score in MDD group. The correlation between the different brain regions in MDD group and HAMD-24 was analyzed. Partial correlation analysis was performed between different brain regions in MDD group and ASLEC.


### 3.5. Quality Control

(1)
When the research subjects were enrolled, two or more attending physicians conducted structured interviews with the patients, in order to ensure the accuracy of diagnosis(2)
The other scale assessments (HAMD-24, HAMA) were completed by two uniformly trained researchers, respectively, in order to ensure the authenticity of the test results(3)
For Self-Assessment Scale Filling (ASLEC), before filling in, the researcher will introduce the purpose and filling method of the scale and inform that if you have any questions, please raise your hand, and the researcher will give a neutral explanationExperiment 2: Establishment of depression model rats and research on the behavioral effect of running exercise.


#### 3.5.1. Experimental Animals and Groups

Sprague-Dawley rats in a certain experimental experiment were selected as the research objects for retrospective analysis; about one rat was in a cage (room temperature, with a day-night cycle between 7 : 00 and 19 : 00); food and water supplies are adequate. One week later, SD rats were randomly divided into blank control group (UCG) and depression model group (DMG). The sugar water preference test and open field test were used to evaluate the sugar water preference and autonomous activity ability of experimental rats, so as to avoid the influence of individual rat individual differences on the establishment of chronic unpredictable stress model. During the subsequent establishment of the depression model, a sugar water preference experiment was conducted every weekend to evaluate the establishment of the depression model; after the depression model was established, the rats in the depression model group were further divided into the depression model control group (MCG) and the depression running model group (RMG).


#### 3.5.2. Establishment of a Chronic Unpredictable Stress-Depression Model

Rats were randomly divided into blank control group and depression model group. Rats in the blank control group were given one cage per cage and were normally provided with food and water (room temperature, with a day-night cycle between 7 : 00 and 19 : 00), and the cleaning bedding was changed regularly every week. The depression model group established a rat model of chronic unpredictable stress-induced depression according to the method, as follows: All the rats in the depression model group were kept in single cages, randomly arranged stimuli each day; the various stressful stimuli required for model establishment include food deprivation, water deprivation, continuous noise (80 dB), continuous horizontal vibration, damp litter, 3 confinement, continuous tilted cage (45 degrees tilt), cold and hot bath day and night reversed, continuous clamping tail, overnight lighting, and foot shock (current intensity). The above stimuli lasted for 7 weeks, and each stress appeared several times during the modeling process, and the reappearance of the same stimuli required an interval of 5 days or more. After the stress, according to the behavioral test results, the successfully modeled depression model rats were randomly divided into a model control group and a depression running exercise group. During the modeling period, the rats in the blank control group did not receive any intervention.


#### 3.5.3. Running Workouts

After the model was established, the rats in the depression running exercise group were given a 6-week running exercise intervention; in the experiment, a horizontal treadmill was selected as the exercise equipment for the rats; in order to ensure that the rats in the depression running exercise group can receive regular running exercise, the initial speed of running exercise was 10 m/min in the first week and then accelerated to 20 m/min every day. In the second week, the running exercise continued at the speed of 20 m/min. Run 5 days a week with 2 days off. The blank control group and the model control group were given running intervention at the end.


### 3.6. Weight

The body weight of the experimental rats was recorded every week during the whole experiment.


### 3.7. Behavioral Tests

#### 3.7.1. Sugar Preference Experiment (SPT)

The authors conducted a retrospective analysis of the sugar water preference experiment; in the experiment, the sugar water preference laboratory was the gold index for evaluating the anhedonia characteristics of depressed animal models. In the training stage before the experiment, rats were given 200 ml/bottle of 1% sucrose water and pure water, respectively; it is used to avoid the fear response of new things in experimental rats and affect the later formal test. In the formal experiment of sugar water preference, experimental rats can freely ingest 1% sucrose water or pure water for 24 hours and record the weight of sucrose water and pure water before and after the test, respectively, so as to obtain the respective consumption of sucrose water and pure water; the percentage of preference for sugar water for each rat was then calculated according to the formula (% sugar water preference = sugar water consumption/total fluid consumption × 100%); during the period, all the experimental rats were kept in single cages and fed normally, and the sugar water preference experiment was conducted once a week.


## 3.1. Selection of Research Objects

In order to exclude related confounding factors such as drugs and disease duration, the authors selected the data of the first-episode, untreated adolescent MDD patients in a certain experiment for a retrospective analysis [15].


### 3.1.1. First-Episode Adolescent Depression Group (MDD Group)

(1) Inclusion Criteria.
(i)
According to the diagnostic criteria of DSM-5, patients diagnosed with depression by two or more attending psychiatric clinicians have five manic episodes, which are the first depressive episodes(ii)
Age 18-22(iii)
HAMD-24≧18 points(iv)
Have never received antidepressant treatment in various ways such as psychotropic drugs, psychotherapy, and electroconvulsive therapy(v)
Han nationality, right-handed(vi)
Able to cooperate with the completion of the scale assessment(2) Exclusion Criteria.
(i)
A previous definite episode of mania or hypomania(ii)
Those with a previous diagnosis of bipolar disorder, schizophrenia or other mental disorders(iii)
Patients with a history of substance abuse and acute poisoning(iv)
Head trauma, loss of consciousness or serious physical illness(v)
Contraindications for MRI scanning, such as artificial heart valves, metal foreign bodies, etc.


### 3.1.2. Healthy Controls (HC Group)

Inclusion criteria:(i)
Age 18-22 years old(ii)
HAMD-24≦7 points(iii)
Han nationality, right-handed(iv)
No serious physical or mental illness(v)
Have not taken sleeping, anesthesia, analgesic, and other drugs in the past month before enrollment(1)
Able to cooperate with the completion of the scale assessmentExclusion criteria:(i)
Those with a previous diagnosis of depression, bipolar disorder, schizophrenia, or other mental disorders associated with other diseases(ii)
Patients with a history of substance dependence and acute poisoning in the past(iii)
Head trauma, loss of consciousness or serious physical illness(iv)
Contraindications for MRI scanning, such as artificial heart valves and metal foreign bodies, etc.


## 3.1.1. First-Episode Adolescent Depression Group (MDD Group)

(1) Inclusion Criteria.
(i)
According to the diagnostic criteria of DSM-5, patients diagnosed with depression by two or more attending psychiatric clinicians have five manic episodes, which are the first depressive episodes(ii)
Age 18-22(iii)
HAMD-24≧18 points(iv)
Have never received antidepressant treatment in various ways such as psychotropic drugs, psychotherapy, and electroconvulsive therapy(v)
Han nationality, right-handed(vi)
Able to cooperate with the completion of the scale assessment(2) Exclusion Criteria.
(i)
A previous definite episode of mania or hypomania(ii)
Those with a previous diagnosis of bipolar disorder, schizophrenia or other mental disorders(iii)
Patients with a history of substance abuse and acute poisoning(iv)
Head trauma, loss of consciousness or serious physical illness(v)
Contraindications for MRI scanning, such as artificial heart valves, metal foreign bodies, etc.


## 3.1.2. Healthy Controls (HC Group)

Inclusion criteria:(i)
Age 18-22 years old(ii)
HAMD-24≦7 points(iii)
Han nationality, right-handed(iv)
No serious physical or mental illness(v)
Have not taken sleeping, anesthesia, analgesic, and other drugs in the past month before enrollment(1)
Able to cooperate with the completion of the scale assessmentExclusion criteria:(i)
Those with a previous diagnosis of depression, bipolar disorder, schizophrenia, or other mental disorders associated with other diseases(ii)
Patients with a history of substance dependence and acute poisoning in the past(iii)
Head trauma, loss of consciousness or serious physical illness(iv)
Contraindications for MRI scanning, such as artificial heart valves and metal foreign bodies, etc.


## 3.2. Research Tools

### 3.2.1. General Population Information Collection

A self-made questionnaire was used to collect the demographic information of all subjects, including name, age, gender, right-handedness, ethnicity, years of education, family history, past history, and personal history, as well as the time of the onset and the last MDD medical history information such as monthly drug use [16].


### 3.2.2. Hamilton Depression Scale (HAMD-24)

Developed in 1960, this scale is one of the scales commonly used clinically to assess the severity of depression and depressive symptoms, and the assessment time range is the most recent week. The HAMD-24 has 24 items covering the following 7 categories of factors: anxiety/somatization, blockade, cognitive impairment, sense of hopelessness, weight changes, sleep disturbances, and circadian variability, of which 10 items are on a 3 scale from 0 to 2 For scoring, 14 items were scored on a 5-point scale from 0 to 4. The total score indicates that there are no depressive symptoms; the score that may have mild or moderate depression may indicate severe depression [17].


### 3.2.3. Hamilton Anxiety Scale (HAMA)

The scale was developed in 1959; HAMA is one of the commonly used clinical scales to evaluate anxiety symptoms, and the assessment time range is the situation of the most recent week. There are 14 items in HAMA, which can be classified into two factors: mental anxiety and somatic anxiety. A 5-point scale from 0 to 4 was used. The total score of<7 points has no anxiety symptoms; ⩾7 points may have anxiety; ⩾14 points must have anxiety; ⩾21 points must have obvious anxiety; ⩾29 points may indicate severe anxiety [18].


### 3.2.4. Adolescent Life Events Self-Rating Scale (ASLES)

The scale is a combination of domestic and foreign literatures by many domestic experts, based on the actual situation in my country; it was compiled in 1987; the scale measures the influence of negative life events in adolescents in the past 12 months, currently widely used. ASLEC has a total of 27 items with a 5-level score [19]. It can be divided into the following six categories of factors: learning stress factor, interpersonal relationship factor, loss factor, punishment factor, health adaptation factor, and others (including school fatigue, relationship dissatisfaction or breakdown, quarrel with others, parental beating, and scolding 4 items); the higher the score, the more negative sexual events have a greater impact. The scale has good reliability and validity. It applies to adolescents to assess stress intensity and frequency of life events.


## 3.2.1. General Population Information Collection

A self-made questionnaire was used to collect the demographic information of all subjects, including name, age, gender, right-handedness, ethnicity, years of education, family history, past history, and personal history, as well as the time of the onset and the last MDD medical history information such as monthly drug use [16].


## 3.2.2. Hamilton Depression Scale (HAMD-24)

Developed in 1960, this scale is one of the scales commonly used clinically to assess the severity of depression and depressive symptoms, and the assessment time range is the most recent week. The HAMD-24 has 24 items covering the following 7 categories of factors: anxiety/somatization, blockade, cognitive impairment, sense of hopelessness, weight changes, sleep disturbances, and circadian variability, of which 10 items are on a 3 scale from 0 to 2 For scoring, 14 items were scored on a 5-point scale from 0 to 4. The total score indicates that there are no depressive symptoms; the score that may have mild or moderate depression may indicate severe depression [17].


## 3.2.3. Hamilton Anxiety Scale (HAMA)

The scale was developed in 1959; HAMA is one of the commonly used clinical scales to evaluate anxiety symptoms, and the assessment time range is the situation of the most recent week. There are 14 items in HAMA, which can be classified into two factors: mental anxiety and somatic anxiety. A 5-point scale from 0 to 4 was used. The total score of<7 points has no anxiety symptoms; ⩾7 points may have anxiety; ⩾14 points must have anxiety; ⩾21 points must have obvious anxiety; ⩾29 points may indicate severe anxiety [18].


## 3.2.4. Adolescent Life Events Self-Rating Scale (ASLES)

The scale is a combination of domestic and foreign literatures by many domestic experts, based on the actual situation in my country; it was compiled in 1987; the scale measures the influence of negative life events in adolescents in the past 12 months, currently widely used. ASLEC has a total of 27 items with a 5-level score [19]. It can be divided into the following six categories of factors: learning stress factor, interpersonal relationship factor, loss factor, punishment factor, health adaptation factor, and others (including school fatigue, relationship dissatisfaction or breakdown, quarrel with others, parental beating, and scolding 4 items); the higher the score, the more negative sexual events have a greater impact. The scale has good reliability and validity. It applies to adolescents to assess stress intensity and frequency of life events.


## 3.3. Research Methods

### 3.3.1. Clinical Data and Scale Data Collection

According to the inclusion criteria, the demographic data collection was completed on the same day as outpatient visits or hospitalizations by trained researchers in the adolescent MDD group; at the same time, all subjects were asked to complete the scale assessment in a mental health center psychological testing center. The HC group was under the guidance of trained researchers to collect general demographic data and evaluate the scale; after completing the above steps, the resting state brain function MRI data of the research subjects were collected.


### 3.3.2. Resting-State Functional Brain MRI Data Acquisition

Magnetic resonance data acquisition of study subjects was completed in a mental health center. The data of three modalities of structural image, BOLD, and diffusion tensor imaging were collected for all subjects. During the acquisition process, the head position of the research subject was fixed, and active and passive movements of the head and other parts were avoided, and the subjects were in a quiet supine position; during the scanning process, anti-irritability headphones were worn to reduce the interference caused by noise. The patient was asked to stay awake, still, eyes closed, and try to avoid moving and thinking during the entire MRI scan. Echo-planar imaging (EPI) sequence was used for scanning, and the parameters were scanned by resting state functional image: Repetition Time = 2000ms, acquisition matrix = 64×64, flip angle = 90°, Rield of View = 240 × 240mm, Echo Time = 30ms, depth of stratum: 4.0mm, no layer spacing, a total of 35 layers [20].


### 3.3.3. Image Processing

(1) Preprocessing. Firstly, the MRI conversion software was used to convert the DICOM format images into NIfTI format for data processing. The images were then preprocessed using DPARSF software. Specific steps are as follows:
(1)
Remove time points: considering that the uneven magnetic field may affect the image, the first 10 time points of the image are removed, in order to stabilize the MRI signal, and the research subjects need to adapt to the scanning environment noise(2)
Time series correction: correct the image acquisition time, in order to eliminate the influence of the time difference of the brain due to the different scanning time on the image time series of each layer(3)
Correction of head movement: the rotation on thex, y, and z axes is greater than 3∘ or culling images with a maximum head movement translation exceeding 3 mm; head movement parameters, cerebrospinal fluid, and white matter were used as covariates(4)
Normalization: the authors registered the T1 structural and functional images, and then matched them with the Montreal Neurological Institute template for3×3×3mm voxel resampling(5)
Smoothing: convolve and smooth the normalized image using an isotropic Gaussian kernel (maximumwidthathalfmaximum=8mm) to reduce spatial noise(6)
Delinear drift and filter processing: in order to reduce low-frequency drift and eliminate physiological noise, the filter signal with frequency in the range of 0.01-0.08 Hz is extracted(2) ALFF, fALFF analysis. ALFF is the Fourier transform of the time series for each voxel throughout the brain, and convert to domain power spectrum. The area under the power spectrum can be regarded as the signal energy intensity, and then the area under the peak is squared, and the result is the change intensity of the BOLD signal, which represents the amplitude of the signal oscillation. The ALFF value for each voxel was divided by the whole-brain average ALFF value as the normalized ALFF value for each voxel. ALFF can be used to reflect the strength of spontaneous activity of voxels in the resting state, thereby reflecting the strength of local neuronal activity. ALFF is a modified ALFF that can effectively suppress nonspecific hyperintensity from the cisternal region and improve the sensitivity and specificity of spontaneous neuron detection.(3) REHO Analysis. REHO reflects the synchronization of local neuronal activity in brain regions. Perform local consistency analysis on the unsmoothed data, calculate and compare the time series synchronization of each voxel in the whole brain with its adjacent 26 voxels, obtain the Kendall harmony coefficient, that is, the REHO value, and then divide by the whole brain REHO mean, and then smoothed with an 8-mm FWHM Gaussian kernel.


## 3.3.1. Clinical Data and Scale Data Collection

According to the inclusion criteria, the demographic data collection was completed on the same day as outpatient visits or hospitalizations by trained researchers in the adolescent MDD group; at the same time, all subjects were asked to complete the scale assessment in a mental health center psychological testing center. The HC group was under the guidance of trained researchers to collect general demographic data and evaluate the scale; after completing the above steps, the resting state brain function MRI data of the research subjects were collected.


## 3.3.2. Resting-State Functional Brain MRI Data Acquisition

Magnetic resonance data acquisition of study subjects was completed in a mental health center. The data of three modalities of structural image, BOLD, and diffusion tensor imaging were collected for all subjects. During the acquisition process, the head position of the research subject was fixed, and active and passive movements of the head and other parts were avoided, and the subjects were in a quiet supine position; during the scanning process, anti-irritability headphones were worn to reduce the interference caused by noise. The patient was asked to stay awake, still, eyes closed, and try to avoid moving and thinking during the entire MRI scan. Echo-planar imaging (EPI) sequence was used for scanning, and the parameters were scanned by resting state functional image: Repetition Time = 2000ms, acquisition matrix = 64×64, flip angle = 90°, Rield of View = 240 × 240mm, Echo Time = 30ms, depth of stratum: 4.0mm, no layer spacing, a total of 35 layers [20].


## 3.3.3. Image Processing

(1) Preprocessing. Firstly, the MRI conversion software was used to convert the DICOM format images into NIfTI format for data processing. The images were then preprocessed using DPARSF software. Specific steps are as follows:
(1)
Remove time points: considering that the uneven magnetic field may affect the image, the first 10 time points of the image are removed, in order to stabilize the MRI signal, and the research subjects need to adapt to the scanning environment noise(2)
Time series correction: correct the image acquisition time, in order to eliminate the influence of the time difference of the brain due to the different scanning time on the image time series of each layer(3)
Correction of head movement: the rotation on thex, y, and z axes is greater than 3∘ or culling images with a maximum head movement translation exceeding 3 mm; head movement parameters, cerebrospinal fluid, and white matter were used as covariates(4)
Normalization: the authors registered the T1 structural and functional images, and then matched them with the Montreal Neurological Institute template for3×3×3mm voxel resampling(5)
Smoothing: convolve and smooth the normalized image using an isotropic Gaussian kernel (maximumwidthathalfmaximum=8mm) to reduce spatial noise(6)
Delinear drift and filter processing: in order to reduce low-frequency drift and eliminate physiological noise, the filter signal with frequency in the range of 0.01-0.08 Hz is extracted(2) ALFF, fALFF analysis. ALFF is the Fourier transform of the time series for each voxel throughout the brain, and convert to domain power spectrum. The area under the power spectrum can be regarded as the signal energy intensity, and then the area under the peak is squared, and the result is the change intensity of the BOLD signal, which represents the amplitude of the signal oscillation. The ALFF value for each voxel was divided by the whole-brain average ALFF value as the normalized ALFF value for each voxel. ALFF can be used to reflect the strength of spontaneous activity of voxels in the resting state, thereby reflecting the strength of local neuronal activity. ALFF is a modified ALFF that can effectively suppress nonspecific hyperintensity from the cisternal region and improve the sensitivity and specificity of spontaneous neuron detection.(3) REHO Analysis. REHO reflects the synchronization of local neuronal activity in brain regions. Perform local consistency analysis on the unsmoothed data, calculate and compare the time series synchronization of each voxel in the whole brain with its adjacent 26 voxels, obtain the Kendall harmony coefficient, that is, the REHO value, and then divide by the whole brain REHO mean, and then smoothed with an 8-mm FWHM Gaussian kernel.


## 3.4. Statistical Analysis

Data entry and statistical analysis were performed in SPSS software. On SPSS 24.0 software, the general data of the two groups were compared byx2 test and t-test. The t-test and nonparametric test were used to compare the scores of HAMD-24, HAMA, and ASLEC between the two groups. The measurement data were expressed with mean±standarddeviationx‾±s. Inspection level α=0.05. Using SPM software, t-test was performed on the ALFF value, fALFF value, and REHO value of the two groups. The xjview plug-in and BrainNet software were used to calculate and display brain areas with statistically significant differences (Alphasim correction, the areas of P<0.01 and voxel >20 are defined as statistically significant differences). Pearson correlation analysis was used to analyze the correlation between ASLEC and HAMD-24 score in MDD group. The correlation between the different brain regions in MDD group and HAMD-24 was analyzed. Partial correlation analysis was performed between different brain regions in MDD group and ASLEC.


## 3.5. Quality Control

(1)
When the research subjects were enrolled, two or more attending physicians conducted structured interviews with the patients, in order to ensure the accuracy of diagnosis(2)
The other scale assessments (HAMD-24, HAMA) were completed by two uniformly trained researchers, respectively, in order to ensure the authenticity of the test results(3)
For Self-Assessment Scale Filling (ASLEC), before filling in, the researcher will introduce the purpose and filling method of the scale and inform that if you have any questions, please raise your hand, and the researcher will give a neutral explanationExperiment 2: Establishment of depression model rats and research on the behavioral effect of running exercise.


### 3.5.1. Experimental Animals and Groups

Sprague-Dawley rats in a certain experimental experiment were selected as the research objects for retrospective analysis; about one rat was in a cage (room temperature, with a day-night cycle between 7 : 00 and 19 : 00); food and water supplies are adequate. One week later, SD rats were randomly divided into blank control group (UCG) and depression model group (DMG). The sugar water preference test and open field test were used to evaluate the sugar water preference and autonomous activity ability of experimental rats, so as to avoid the influence of individual rat individual differences on the establishment of chronic unpredictable stress model. During the subsequent establishment of the depression model, a sugar water preference experiment was conducted every weekend to evaluate the establishment of the depression model; after the depression model was established, the rats in the depression model group were further divided into the depression model control group (MCG) and the depression running model group (RMG).


### 3.5.2. Establishment of a Chronic Unpredictable Stress-Depression Model

Rats were randomly divided into blank control group and depression model group. Rats in the blank control group were given one cage per cage and were normally provided with food and water (room temperature, with a day-night cycle between 7 : 00 and 19 : 00), and the cleaning bedding was changed regularly every week. The depression model group established a rat model of chronic unpredictable stress-induced depression according to the method, as follows: All the rats in the depression model group were kept in single cages, randomly arranged stimuli each day; the various stressful stimuli required for model establishment include food deprivation, water deprivation, continuous noise (80 dB), continuous horizontal vibration, damp litter, 3 confinement, continuous tilted cage (45 degrees tilt), cold and hot bath day and night reversed, continuous clamping tail, overnight lighting, and foot shock (current intensity). The above stimuli lasted for 7 weeks, and each stress appeared several times during the modeling process, and the reappearance of the same stimuli required an interval of 5 days or more. After the stress, according to the behavioral test results, the successfully modeled depression model rats were randomly divided into a model control group and a depression running exercise group. During the modeling period, the rats in the blank control group did not receive any intervention.


### 3.5.3. Running Workouts

After the model was established, the rats in the depression running exercise group were given a 6-week running exercise intervention; in the experiment, a horizontal treadmill was selected as the exercise equipment for the rats; in order to ensure that the rats in the depression running exercise group can receive regular running exercise, the initial speed of running exercise was 10 m/min in the first week and then accelerated to 20 m/min every day. In the second week, the running exercise continued at the speed of 20 m/min. Run 5 days a week with 2 days off. The blank control group and the model control group were given running intervention at the end.


## 3.5.1. Experimental Animals and Groups

Sprague-Dawley rats in a certain experimental experiment were selected as the research objects for retrospective analysis; about one rat was in a cage (room temperature, with a day-night cycle between 7 : 00 and 19 : 00); food and water supplies are adequate. One week later, SD rats were randomly divided into blank control group (UCG) and depression model group (DMG). The sugar water preference test and open field test were used to evaluate the sugar water preference and autonomous activity ability of experimental rats, so as to avoid the influence of individual rat individual differences on the establishment of chronic unpredictable stress model. During the subsequent establishment of the depression model, a sugar water preference experiment was conducted every weekend to evaluate the establishment of the depression model; after the depression model was established, the rats in the depression model group were further divided into the depression model control group (MCG) and the depression running model group (RMG).


## 3.5.2. Establishment of a Chronic Unpredictable Stress-Depression Model

Rats were randomly divided into blank control group and depression model group. Rats in the blank control group were given one cage per cage and were normally provided with food and water (room temperature, with a day-night cycle between 7 : 00 and 19 : 00), and the cleaning bedding was changed regularly every week. The depression model group established a rat model of chronic unpredictable stress-induced depression according to the method, as follows: All the rats in the depression model group were kept in single cages, randomly arranged stimuli each day; the various stressful stimuli required for model establishment include food deprivation, water deprivation, continuous noise (80 dB), continuous horizontal vibration, damp litter, 3 confinement, continuous tilted cage (45 degrees tilt), cold and hot bath day and night reversed, continuous clamping tail, overnight lighting, and foot shock (current intensity). The above stimuli lasted for 7 weeks, and each stress appeared several times during the modeling process, and the reappearance of the same stimuli required an interval of 5 days or more. After the stress, according to the behavioral test results, the successfully modeled depression model rats were randomly divided into a model control group and a depression running exercise group. During the modeling period, the rats in the blank control group did not receive any intervention.


## 3.5.3. Running Workouts

After the model was established, the rats in the depression running exercise group were given a 6-week running exercise intervention; in the experiment, a horizontal treadmill was selected as the exercise equipment for the rats; in order to ensure that the rats in the depression running exercise group can receive regular running exercise, the initial speed of running exercise was 10 m/min in the first week and then accelerated to 20 m/min every day. In the second week, the running exercise continued at the speed of 20 m/min. Run 5 days a week with 2 days off. The blank control group and the model control group were given running intervention at the end.


## 3.6. Weight

The body weight of the experimental rats was recorded every week during the whole experiment.


## 3.7. Behavioral Tests

### 3.7.1. Sugar Preference Experiment (SPT)

The authors conducted a retrospective analysis of the sugar water preference experiment; in the experiment, the sugar water preference laboratory was the gold index for evaluating the anhedonia characteristics of depressed animal models. In the training stage before the experiment, rats were given 200 ml/bottle of 1% sucrose water and pure water, respectively; it is used to avoid the fear response of new things in experimental rats and affect the later formal test. In the formal experiment of sugar water preference, experimental rats can freely ingest 1% sucrose water or pure water for 24 hours and record the weight of sucrose water and pure water before and after the test, respectively, so as to obtain the respective consumption of sucrose water and pure water; the percentage of preference for sugar water for each rat was then calculated according to the formula (% sugar water preference = sugar water consumption/total fluid consumption × 100%); during the period, all the experimental rats were kept in single cages and fed normally, and the sugar water preference experiment was conducted once a week.


## 3.7.1. Sugar Preference Experiment (SPT)

The authors conducted a retrospective analysis of the sugar water preference experiment; in the experiment, the sugar water preference laboratory was the gold index for evaluating the anhedonia characteristics of depressed animal models. In the training stage before the experiment, rats were given 200 ml/bottle of 1% sucrose water and pure water, respectively; it is used to avoid the fear response of new things in experimental rats and affect the later formal test. In the formal experiment of sugar water preference, experimental rats can freely ingest 1% sucrose water or pure water for 24 hours and record the weight of sucrose water and pure water before and after the test, respectively, so as to obtain the respective consumption of sucrose water and pure water; the percentage of preference for sugar water for each rat was then calculated according to the formula (% sugar water preference = sugar water consumption/total fluid consumption × 100%); during the period, all the experimental rats were kept in single cages and fed normally, and the sugar water preference experiment was conducted once a week.


## 4. Results and Discussion

Experiment 1: In order to explore the correlation between NLE and brain region function in first-episode adolescent MDD patients based on functional magnetic resonance imaging.


### 4.1. Comparison of Brain Function Activity between the Two Groups

#### 4.1.1. Comparison of ALFF Values between MDD Group and HC Group

Compared with the HC group, the ALFF values of the bilateral thalamus, right fusiform gyrus, and bilateral parahippocampal gyrus increased in the MDD group, and the difference was statistically significant (see Table1); there were no brain regions with lower ALFF values in the MDD group than in the HC group, and the difference was not statistically significant (P>0.005).Table 1
The areas where the ALFF value increased in the MDD group compared with the HC group.
Brain areaMNI coordinatest valueBulk voxelsxyzBilateral thalamus15-1234.11285Left parahippocampal gyrus-24-33-183.79253Right fusiform gyrus, parahippocampal gyrus36-51-124.05338


#### 4.1.2. Comparison of fALFF Values between MDD Group and HC Group

Compared with the HC group, the fALFF values in the cuneiform, medial prefrontal cortex, and cerebellum regions of the MDD group were increased, and the difference was statistically significant (see Table2).Table 2
The areas where the fALFF value of the MDD group increased compared with the HC group.
Brain areaMNI coordinatest valueBulk voxelsxyzWedge leaf15-69243.82242Medial prefrontal lobe-1563-34.26191Cerebellum-39-72-305.44110


#### 4.1.3. Comparison of REHO Values between MDD Group and HC Group

Compared with the HC group, the MDD group had higher REHO values in the talar gyrus and right cerebellum, and the difference was statistically significant (see Table3); no brain regions with lower REHO values were found in the MDD group than in the HC group. There was no statistical difference (P>0.005).Table 3
Areas of increased REHO value in MDD group compared with HC group.
Brain areaMNI coordinatest valueBulk voxelsxyzCalcaroid gyrus0-87-33.9543Right cerebellum18-57-393.8346Experiment 2: Establishment of depression model rats and research on the behavioral effect of running exercise.


### 4.2. Screening before Modeling

Before the establishment of the chronic unpredictable stress depression model, the sugar water preference test was used to screen the initial sugar water preference of the rats; the results showed that in the sugar water test [21], there was no significant difference in the sugar water preference between the blank control group and the depression model group (Figure 2).Figure 2
Comparison of sugar water preference between blank control group and depression model group.


### 4.3. Weight

Before the establishment of the chronic unpredictable stress depression model, the body weight of the blank control group and the depression model group showed a steady upward trend, and there was no significant difference in body weight between the two groups in Figure3.Figure 3
Statistics of body weight of rats in depression model group and blank control group.


## 4.1. Comparison of Brain Function Activity between the Two Groups

### 4.1.1. Comparison of ALFF Values between MDD Group and HC Group

Compared with the HC group, the ALFF values of the bilateral thalamus, right fusiform gyrus, and bilateral parahippocampal gyrus increased in the MDD group, and the difference was statistically significant (see Table1); there were no brain regions with lower ALFF values in the MDD group than in the HC group, and the difference was not statistically significant (P>0.005).Table 1
The areas where the ALFF value increased in the MDD group compared with the HC group.
Brain areaMNI coordinatest valueBulk voxelsxyzBilateral thalamus15-1234.11285Left parahippocampal gyrus-24-33-183.79253Right fusiform gyrus, parahippocampal gyrus36-51-124.05338


### 4.1.2. Comparison of fALFF Values between MDD Group and HC Group

Compared with the HC group, the fALFF values in the cuneiform, medial prefrontal cortex, and cerebellum regions of the MDD group were increased, and the difference was statistically significant (see Table2).Table 2
The areas where the fALFF value of the MDD group increased compared with the HC group.
Brain areaMNI coordinatest valueBulk voxelsxyzWedge leaf15-69243.82242Medial prefrontal lobe-1563-34.26191Cerebellum-39-72-305.44110


### 4.1.3. Comparison of REHO Values between MDD Group and HC Group

Compared with the HC group, the MDD group had higher REHO values in the talar gyrus and right cerebellum, and the difference was statistically significant (see Table3); no brain regions with lower REHO values were found in the MDD group than in the HC group. There was no statistical difference (P>0.005).Table 3
Areas of increased REHO value in MDD group compared with HC group.
Brain areaMNI coordinatest valueBulk voxelsxyzCalcaroid gyrus0-87-33.9543Right cerebellum18-57-393.8346Experiment 2: Establishment of depression model rats and research on the behavioral effect of running exercise.


## 4.1.1. Comparison of ALFF Values between MDD Group and HC Group

Compared with the HC group, the ALFF values of the bilateral thalamus, right fusiform gyrus, and bilateral parahippocampal gyrus increased in the MDD group, and the difference was statistically significant (see Table1); there were no brain regions with lower ALFF values in the MDD group than in the HC group, and the difference was not statistically significant (P>0.005).Table 1
The areas where the ALFF value increased in the MDD group compared with the HC group.
Brain areaMNI coordinatest valueBulk voxelsxyzBilateral thalamus15-1234.11285Left parahippocampal gyrus-24-33-183.79253Right fusiform gyrus, parahippocampal gyrus36-51-124.05338


## 4.1.2. Comparison of fALFF Values between MDD Group and HC Group

Compared with the HC group, the fALFF values in the cuneiform, medial prefrontal cortex, and cerebellum regions of the MDD group were increased, and the difference was statistically significant (see Table2).Table 2
The areas where the fALFF value of the MDD group increased compared with the HC group.
Brain areaMNI coordinatest valueBulk voxelsxyzWedge leaf15-69243.82242Medial prefrontal lobe-1563-34.26191Cerebellum-39-72-305.44110


## 4.1.3. Comparison of REHO Values between MDD Group and HC Group

Compared with the HC group, the MDD group had higher REHO values in the talar gyrus and right cerebellum, and the difference was statistically significant (see Table3); no brain regions with lower REHO values were found in the MDD group than in the HC group. There was no statistical difference (P>0.005).Table 3
Areas of increased REHO value in MDD group compared with HC group.
Brain areaMNI coordinatest valueBulk voxelsxyzCalcaroid gyrus0-87-33.9543Right cerebellum18-57-393.8346Experiment 2: Establishment of depression model rats and research on the behavioral effect of running exercise.


## 4.2. Screening before Modeling

Before the establishment of the chronic unpredictable stress depression model, the sugar water preference test was used to screen the initial sugar water preference of the rats; the results showed that in the sugar water test [21], there was no significant difference in the sugar water preference between the blank control group and the depression model group (Figure 2).Figure 2
Comparison of sugar water preference between blank control group and depression model group.


## 4.3. Weight

Before the establishment of the chronic unpredictable stress depression model, the body weight of the blank control group and the depression model group showed a steady upward trend, and there was no significant difference in body weight between the two groups in Figure3.Figure 3
Statistics of body weight of rats in depression model group and blank control group.


## 5. Conclusion

The author studies the effect of running exercise on the brain functional magnetic resonance characteristics of college students’ depression; through the comparison experiment between MDD group and HC group and the retrospective analysis of the rats’ sugar water preference experiment, the in-depth discussion was carried out. The results showed that under the running exercise for six consecutive weeks, the average body weight of the rats in the depression model group was significantly lower than that in the blank control group 22.5%; it shows that running exercise has a relieving effect on college students’ depression.



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*Source: 7558807-2022-08-05.xml*