Comments: fMRI scans find abnormalities in the brains of those with Internet Addiction Disorder.
Chin Med J (Engl). 2010 Jul;123(14):1904-8.
Liu J, Gao XP, Osunde I, Li X, Zhou SK, Zheng HR, Li LJ.
Source
Institute of Mental Health, the Second Xiangya Hosipital, Central South University, Changsha, Hunan 410011, China.
Abstract:
Background:
Internet addition disorder (IAD) is currently becoming a serious mental health problem among Chinese adolescents. The pathogenesis of IAD, however, remains unclear. The purpose of this study applied regional homogeneity (ReHo) method to analyze encephalic functional characteristic of IAD college students under resting state.
Methods:
Functional magnetic resonanc image (fMRI) was performed in 19 IAD college students and 19 controls under resting state. ReHo method was used to analyze the differences between the average ReHo in two groups.
Results:
The following increased ReHo brain regions were found in IAD group compared with control group: cerebellum, brainstem, right cingulate gyrus, bilateral parahippocampus, right frontal lobe (rectal gyrus, inferior frontal gyrus and middle frontal gyrus), left superior frontal gyrus, left precuneus, right postcentral gyrus, right middle occipital gyrus, right inferior temporal gyrus, left superior temporal gyrus and middle temporal gyrus. The decreased ReHo brain regions were not found in the IAD group compared with the control group.
Conclusions:
There are abnormalities in regional homogeneity in IAD college students compared with the controls and enhancement of synchronization in most encephalic regions can be found. The results reflect the functional change of brain in IAD college students. The connections between the enhancement of synchronization among cerebellum, brainstem, limbic lobe, frontal lobe and apical lobe may be relative to reward pathways.
The use of Internet has increased considerably over the last few years. Data from the China Internet Network Information Center (as of December 31, 2008) showed that 298 million people had gone online, of which 60% were teenagers below 30 years old. With this soaring number of Internet users, the problem of Internet addiction disorder has attracted high attention from psychiatrists, educators and the public. Internet addition disorder is currently becoming a serious mental health problem among Chinese adolescents. Chou and Hsiao1 reported that the incidence rate Internet addiction among Taiwan college students was 5.9%. Wu and Zhu2 identified 10.6% of Chinese college students as Internet addicts. The pathogenesis of IAD, however, remains unclear.
Resting state fMRI, however, has attracted more attention recently because study participants are instructed simply to remain motionless and keep their eyes closed during the fMRI scan. Therefore, resting state fMRI has the practical advantage of clinical application. In the present resting state fMRI study, a newly reported regional homogeneity (ReHo) method was used to analyze the blood oxygen level-dependent (BOLD) signal of the brain.3 It is hoped that the resting state fMRI will allow new insight into the pathophysiology of IAD.
METHODS
Subjects
According to modified YDQ criteria by Beard and Wolf,3 from July 2008 to May 2009, 19 IAD (11 males and 8 females; mean age of (21.0±1.3) years with range from 18 to 25 years), and 19 sex-matched subjects (mean age of (20.0±1.8) years with range from 18 to 25 years) underwent fMRI under resting state at our hospital. The subjects were all right-handed as measured by the Edinburgh Inventory. No subjects took any medications that could affect brain excitability. All subjects had a normal neurological examination. They met the following inclusion criteria: 1) the top 5 criterias must be met in Diagnostic Questionnaire for Internet Addiction (Beard3—“5+1 criteria”), and meet any one in the remaining three criterias. 2) duration of attack was ≥6 hours per day for 3 months. 3) social function significantly impaired, including decline in academic performance, unable to maintain normal school learning. Subjects reported no history of neurological illness of schizophrenia, depression and substance dependence or psychiatric disorder. There was no statistically significant difference in age, gender or educational levels between the IAD group and the control group. The Research Committee of the Second Xiangya Hosipital affiliated to Central South University approved the study. All subjects gave their written informed consent for the study.
MRI screening
Images were acquired on a 3.0T Siemens Tesla Trio Tim scanner with high-speed gradients. The participant’s head was positioned with a standard head coil. Foam padding was provided to restrict head movement. High resolution axial T1- and T2- weighted images were obtained in every subject. During resting state fMRI, subjects were instructed to keep their eyes closed, to remain motionless orthink nothing in particular. The following parameters were used for T1 anatomical imaging axially: 3080/12 ms (TR/TE), 36 slices, 256×256 matrix, 24 cm field of view (FOV), 3 mm section thickness and 0.9 mm gap, 1 NEX, flip angle=90. At the same locations to anatomical slices, functional images were acquired by using an echoplanar imaging sequence with the following parameters: 3000/30 ms (TR/TE), 36 slices, 64×64 matrix, 24 cm field of view (FOV), 3 mm section thickness and 0.9 mm gap, 1 NEX, flip angle=90. Each fMRI scan lasted 9 minutes.
Statistical analysis
Data of each subject’s fMRI contained 180 time points. The first five time points of fMRI data were discarded because of instability of initial MRI signal and adaption of participants to the circumatance, leaving 175 volumes. The remaining 175 volumes were preprocessed using Statistical Parametric Mapping 2 (SPM2) software (London University, Britain). They were slice-time corrected, and aligned to the first image of each session for motion correction, spatially normalized to MNI and were smoothed with a Gaussian filter of 8 mm full-width at half-maximum (FWHM) to reduce noise and residual differences in gyral anatomy. All subjects had less than 0.5 mm maximum displacement in X, Y, Z and 1.0° of angylar motion during the whole fMRI scan. No subjects were excluded. A temporal filter (0.01Hz< f <0.08HZ) was applied to remove low-frequency drifts and physiological high-frequency noise.
We used Kendall’s coefficient of concordance (KCC)4 to measure regional homogeneity of the time series of a given voxel with its nearest 26 neighbor voxel in a voxel-wise way. The KCC can be computed by the following formula:
Where W is the KCC of a cluster, ranged from 0 to 1; Ri is sum rank of the ith time point, n is the number of time points of each voxel time series (here n=175); =((n+1))/2 is the mean of the Ri’s; k is the number of voxels in the cluster (here k=27). Individual W map was obtained on a voxel by voxel basis for each subject data set. The above program was coded in Matrix Laboratory (MATLAB, MathWorks Inc., Natick, USA)
For exploring the ReHo difference between the IADs and controls, a second-level random-effect two-sample t test was performed on the individual ReHo maps in a voxel-by-voxel manner. The resulting statistical map was set at a combined threshold of P <0.001 and a minimum cluster size of 270 mm3, which results in a correted the threshold of P <0.05.
RESULTS
For all subjects, no significant pathological change was found with high resolution T1- and T2-weighted MRI. The IAD group showed increased brain regions in ReHo in the resting state compared with the controls. The increased ReHo was distributed over the cerebellum, brainstem, right cingulate gyrus, bilateral parahippocampus, right frontal lobe (rectal gyrus, inferior frontal gyrus and middle frontal gyrus), left superior frontal gyrus, left precuneus, right postcentral gyrus, right middle occipital gyrus, right inferior temporal gyrus, left superior temporal gyrus and middle temporal gyrus. The decreased ReHo in IAD group was not found (Figure and Table).
Figure. Different areas in brain with increased ReHo in combined images of IADs and controls got by SPM2 software. A: cerebellum. B: brainstem. C: right cingulate gyrus. D: right parahippocampus. E: left parahippocampus. F: left superior frontal gyrus. These regions have the higher ReHo value: IADs > controls. L: left. R: right. Blue cruciform represent activity brain regions. A one-sample t test was performed on the individual ReHo maps in a voxel-by-voxel manner between the IADs and the controls. Data of the two groups were tested using two-sample t test. The final statistical map was set at a combined threshold of P <0.001 and a minimum cluster size of 270 mm3, which results in a correted threshold of P <0.05.
Table. Brain regions with abnormal regional homogeneity in IADs compared with the controls
DISCUSSION
ReHo method about fMRI
ReHo method, a new way to analyze the fMRI data under the resting state.4 The basic theory hypothesis of ReHo method is that a given voxel is temporally similar to its neighbors. It measures the ReHo of the time series of the regional BOLD signal. Therefore, ReHo reflects the temporal homogeneity of the regional BOLD signal rather than its density. ReHo may detect the activity in the different brain regions. ReHo method has already being successfully applied to the study of Parkinson, Alzheimer, depression, attention deficit hyperactivity disorder, schizophrenia and epilepsy.5-10 However, none has ever detected the brain activity of IAD by using resting state fMRI.
Characteristics and meaning of the increased ReHo brain regions in IAD compared with the controls
Compared with the controls, the experiment group found that the increased ReHo brain regions were distributed over the cerebellum, brainstem, right cingulate gyrus, bilateral parahippocampus, right frontal lobe (rectal gyrus, inferior frontal gyrus and middle frontal gyrus), left superior frontal gyrus, left precuneus, right postcentral gyrus, right middle occipital gyrus, right inferior temporal gyrus, left superior temporal gyrus and middle temporal gyrus. It represents the increase in nervous activity.
Studies have shown that the cerebellum has a high-level cognitive functions,11-12 such as language awareness and so on. There is an extensive functional connection between the cerebellum and the brain, which helps to regulate the cognitive activity, thinking and emotions to some extent. There are fibrous joint between mesencephalon and cerebellum, cerebellum and thalamus, cerebellum and cerebrum, e.g. prefrontal lobe. Researchers have discovered the correlations between cerebellar structural abnormalities and the clinical manifestation of certain mental illness.13 Studies have found in patients with schizophrenia that prefrontal lobe-cerebellum and the cerebellum-thalamus connections were weakened, but thalamus-prefrontal lobe connection was enhanced.14
The cingulate gyrus belonging the limbic system is located at the top of the corpus callosum. It, together with parahippocampal gyrus, was considered to be transition region of heterotypical cortex and neocortex, which was also known as the mesocortex. The anterior cingutate regulates reactions and serves as a sensory integrater in the congnition regulation. The anterior cingulated primary function is the monitoring of conflict. The posterior cingulate was involved in the process of visual sense and sensorimotor.15-18
Mesencephalon and subiculum hippocampi play an impotant role in the mesolimbic dopaminergic system. Ventral tegmental nucleus is an important part of reward pathway and there are extensive connections between the mesencephalon and cerebellum, and the mesencephalon and cerebrum. The enhancment of the reactiveness synchronization of the mesencephalon, cerebellum, cingulate gyrus and parahippocampal gyrus is consistent with the substance addition rewarding pathway. It indicated that, to a certain extent, the connections of rewarding pathway in IAD enhanced.
The study found increased ReHo in temporal region and occipital region, which suggesting the raised synchronization in IAD group than the control group. This may be caused by the behavior of addict, such as contacting the network picture frequently, indulging in the noisy internet bar or in the game sound. The optic and auditory center, which have been stimulated repeatedly for a long time, become easily to excited or have a raised excitability. The major function of temporal lobe is to regulate sense perception including visual and auditory processing through the primary and secondary associated cortex. The increased ReHo in cortex of temporal lobe, serves as positive intensifying factor to reveal oneself as a Internet addict. The repetitive behaviors browsing on the internet of IAD deserve further research.
By fMRI, Bartzokis et al19 found that the volume of frontal lobe and temporal lobe were significantly reduced in cocaine and amphetamine dependent persons, while the gray matter of temporal lobe in cocaine-dependent persons reduced obviousily with the increasing of age. It indicated that cocaine dependence may speed up the reduction of the gray matter of temporal lobe, and the reduction of frontal lobe and temporal lobe can be the identification marker of addiction behavior. The varation of ReHo in cortex of temporal lobe of Internet addict, can be the early sign of barin structure changing, and to some extent can signify the abnormality of the brain function. Modell et al20 discovered activation among caudate nucleus, corpora striata, thalamencephal, cortex of frontal lobe in alcohol and drug addict by fMRI. Tremblay and Schultz21 found that the function of orbital gyri of frontal lobe and reward related, and the damge to the orbital gyri of frontal lobe could lead to decreased inhibition and impulse.
Compared to the normal person, the increased ReHo in certain regions of the frontal lobe and the parietal lobe reveals an advanced synchronization than is normally seen. The cortex of frontal lobe, which is the most complex and highly evolved neocortex region, accepts the afferent nerve fibers from the parietal lobe, temporal lobe, occipital lobe, and sensory latero-association cortex near Brodman 1, 2, and 3, as well as limbic latero-association cortex, including cingulate gyrus, parahippocampal gyrus and whose efferent nerve fibers project to striatum and pons. It is the essential brain area for the impulsion control.22-24
Various studies found that parietal lobe had a concerted relationship with visuospatial task .The position change of the concerning object could lead to a strong activation of superior parietal cortex on both sides.25,26 By fMRI, Zheng et al27 discovered that the apical lobe played a dominant role when brain was dealing with short-term memory. Neuroanatomy found that the dorsal prefrontal lobe accepted the projection of association fiber from apical lobe, and the primary visual cortex transmitted the spatial characteristics (in the visual informaton transformed by visual pathway) to the associated cortex of the apical lobe, and formed spatial perception at the same time. Finally, the integrated spatial information is conveyed to the dorsal prefrontal lobe to form spatial memory. In a word, visual information completed the processing of positional and spatial relation in superior posterior cortex by dorsal pathway.28
Based on available literature and the results of this experiment, we believe that the images and sound are input by certain auditory and visual conduction pathways. Concrete senses such as color, relative spatial position and space perception are formed in the parietal lobe. In the end, signals spread to the frontal lobe to carry on further processing such as the next decision, planning and execution. The frequent activation of these encephalic regions of the Internet addicts leads to the enhancement of the synchronization in these regions. The enhancement of synchronization among the cerebellum, brainstem, limbic lobe, frontal lobe and apical lobe may be associated with reward pathways, and its concrete mechanisms need to be confirmed by further studies.
In conclusion, this research applied the resting state fMRI method to collect data and the ReHo method to analyze data. We discovered that there were abnormalities in regional homogeneity in IAD college students compared with the control group. There is enhancement of synchronization in most brain regions. The results reflect the functional change of brain in IAD college students and the enhancement of synchronization among cerebellum, brainstem, limbic lobe, frontal lobe, apical lobe may be relevant to reward pathways. This study provides a new method and idea to study the etiology of IAD, and confirms the possibility to apply ReHo to preclinical and clinical IAD studies at the same time.
REFERENCES
1. Chou C, Hsiao MC. Internet addiction, usage, gratification, and pleasure experience: the Taiwan college students’ case. Comput Educ 2000; 35: 65-80.
2. Wu HR, Zhu KJ. Path analysis on related factors causing internet addiction disorder in college students. Chin J Pub Health (Chin) 2004; 20: 1363-1364.
3. Beard KW, Wolf EM. Modification in the proposed diagnostic criteria for Internet addiction. Cyberpsychol Behav 2001; 4: 377-383.
4. Zang Y, Jiang T, Lu Y, He Y, Tian L. Regional homogeneity approach to fMRI data analysis. NeuroImage 2004; 22: 394-400.
5. Wu T, Long X, Zang Y, Wang L, Hallett M, Li K, et al. Regional homogeneity changes in patients with Parkinson’s disease. Hum Brain Mapp 2009; 30: 1502-1510.
6. Liu Y, Wang K, Yu C, He Y, Zhou Y, Liang M, et al. Regional homogeneity, functional connectivity and imaging markers of Alzheimer’s disease: a review of resting-state fMRI studies. Neuropsychologia 2008; 46: 1648-1656.
7. Tian LX, Jiang TZ, Liang M, Zang Y, He Y, Sui M, et al. Enhanced resting-state brain activities in ADHD patients: a fMRI study. Brain Dev 2008; 30: 342-348.
8. Yuan Y, Zhang Z, Bai F, Yu H, Shi Y, Qian Y, et al. Abnormal neural activity in the patients with remitted geriatric depression: a resting-state functional magnetic resonance imaging study. J Affect Disord 2008; 111: 145-152.
9. Liu H, Liu Z, Liang M, Hao Y, Tan L, Kuang F, et al. Decreased regional homogeneity in schizophrenia: a resting state functional magnetic resonance imaging study. Neuroreport 2006; 17: 19-22.
10. Yu HY, Qian ZY, Zhang ZQ, Chen ZL, Zhong Y, Tan QF, et al. Study of brain activity based on arithmetic of amplitude of low frequency fluctuation by fMRI during mental calculation task. Acta Biophysica Sinica 2008; 24: 402-407.
11. Katanoda K, Yoshikawa K, Sugishita M. A functional MRI study on the neural substrates for writing. Hum Brain Mapp 2001; 13: 34-42.
12. Preibisch C, Berg D, Hofmann E, Solymosi L, Naumann M. Cerebral activation patterns in patients with writer’s cramp: a functional magnetic resonance imaging study. J Neurol 2001; 248: 10-17.
13. Wassink TH, Andreasen NC, Nopoulos P, Flaum M. Cerebellar morphology as a predictor of symptom and psychosocial outcome in schizophrenia. Biol Psychiatry 1999; 45: 41-48.
14. Schlosser R, Gesierich T, Kaufmann B, Vucurevic G, Hunsche S, Gawehn J, et al. Altered effective connectivity during working memory performance in schizophrenia: a study with fMRI and structural equation modeling. NeuroImage 2003; 19: 751-763.
15. Badre D, Wagner AD. Selection, integration, and conflict monitoring; assessing the nature and generality of prefrontal cognitive control mechanisms. Neuron 2004; 41: 473-487.
16. Braver TS, Barch DM, Gray JR, Molfese DL, Snyder A. Anterior cingulate cortex and response conflict: effects of frequency, inhibition and errors. Cereb Cortex 2001; 11: 825-836.
17. Barch DM, Braver TS, Akbudak E, Conturo T, Ollinger J, Snyder A. Anterior cingulate cortex and response conflict: effects of response modality and processing domain. Cereb Cortex 2001; 11: 837-848.
18. Bush G, Frazier JA, Rauch SL, Seidman LJ, Whalen PJ, Jenike MA, et al. Anterior cingulate cortex dysfunction in attention-deficit/hyperactivity disorder revealed by fMRI and the Counting Stroop. Biol Psychiatry 1999; 45: 1542-1552.
19. Bartzokis G, Beckson M, Lu PH, Edwards N, Rapoport R, Wiseman E, et al. Age-related brain volume reductions in amphetamine and cocaine addicts and normal controls: implications for addiction research. Psychiatry Res 2000; 98: 93-102.
20. Modell JG, Mountz JM, Beresford TP. Basal ganglia/limbic striatal and thalamocortical involvement in craving and loss of control in alcoholism. J Neuropsychiatry Clin Neurosci 1990; 2: 123-144.
21. Tremblay A, Schultz W. Relative reward preference in primate orbitofrontal cortex. Nature 1999; 398: 704-708.
22. Robbins TW. Chemistry of the mind: neurochemical modulation of prefrontal cortical function. J Comp Neurol 2005; 493: 140-146.
23. Hester R, Garavan H. Executive dysfunction in cocaine addiction: evidence for discordant frontal, cingulate, and cerebellar activity. J Neurosci 2004; 24: 11017-11022.
24. Berlin HA, Rolls ET, Kischka U. Impulsivity, time perception, emotion and reinforcement sensitivity in patients with orbitofrontal cortex lesions. Brain 2004; 127: 1108-1126.
25. Sack AT, Hubl D, Prvulovic D, Formisano E, Jandl M, Zanella FE, et al. Brain Res Cogn Brain Res 2002; 13: 85-93.
26. Vandenberghe R, Gitelman DR, Parrish TB, Mesulam MM. Functional specificity of superior parietal mediation of spatial shifting. Neuroimage 2001; 14: 661-673.
27. Zheng JL, Wu YM, Shu SY, Liu SH, Guo ZY, Bao XM, et al. Role of the parietal lobes in cognition of the spatial memory in healthy volunteers.Tianjin Med J (Chin) 2008; 36: 81-83.
28. Rao SC, Rainer G, Miller EK. Integration of what and where in the primate prefrontal cortex. Science 1997; 276: 821-824.
;