Psychiatry Investig Search


Psychiatry Investig > Volume 20(2); 2023 > Article
Lee, Cha, and Hong: Increased Right Dorsolateral Prefrontal Cortex Connectivity During Emotion Recognition Task in Adolescents With Self-Injurious Behavior: A Functional Near-Infrared Spectroscopy Study



Research on neural correlates in the prefrontal cortex (PFC) associated with self-injurious behavior has mainly been performed in adults. However, studies on adolescents are scarce. We aimed to investigate the activation and connectivity of the PFC between adolescents with self-injurious behavior (ASI) and psychiatric controls (PC) using functional near-infrared spectroscopy (fNIRS).


We used an emotion recognition task during fNIRS to assess 37 adolescents (23 with self-injurious behavior and 14 PC) between June 2020 and October 2021 and compared connectivity and activation between the two groups. We also measured adverse childhood events (ACE, Adverse Childhood Experiences) and performed a correlation analysis of channel activation according to ACE total scores.


The difference in activation between the groups was not statistically significant. The connectivity of channel 6 was statistically significant. The interaction between channel 6 and the ACE total score showed statistical significance between the two groups(t[33] -2.61; p=0.014). The ASI group showed a negative correlation with the total ACE score.


This is the first study to investigate PFC connectivity using fNIRS in ASI. It has the implication of a novel attempt with a practically useful tool to uncover neurobiological differences among Korean adolescents.


Self-injurious behavior, which one in six adolescents has done at least once in their lifetime, is a major social concern worldwide [1] because it substantially impacts families and communities and causes social costs [2,3].
Despite the seriousness of the impact of self-injurious behaviors, studies to elucidate the neurobiological mechanisms underlying these behaviors are sparse, especially in adolescents. Among neuroimaging studies of adolescents with self-injurious behavior (ASI), studies have reported structural alterations using the prefrontal cortex (PFC) [4,5], anterior cingulate cortex [4,6], insula [2,7], amygdala [4,5], and hippocampus [4,5] as regions of interest, and studies using functional tasks such as interpersonal self-processing [8], social reward processing (Cyberball task [9,10], card guessing task [11], monetary incentive delay task [12]), emotional processing (emotional and self-injuring images task [13], emotional face matching task [14], masked emotional face task [15]), and pain processing (electrical stimulation task [16] and cold stimulus task [17]).
Although extensive research has been conducted, there are no definite findings. These studies mainly used magnetic resonance imaging (MRI) or functional MRI (fMRI), which is highly infeasible for use in clinical practice, and there is also a limitation that the studies were mainly performed on the Western population. In Korea, studies that examine clinical characteristics and psychosocial correlates have been published sporadically, but there are no studies on the neurobiology of self-injurious behavior [18,19].
Self-injurious behavior (regardless of suicidal intent) was the focus of this study. Based on the results of recent studies, Huber et al. [20] reported that the clinical group (bipolar disorder and suicide attempters) showed reduced left orbitofrontal cortex volume and bilateral orbitofrontal cortex thickness than the healthy control group. Brunner et al. [21] reported that female adolescents with borderline personality disorder had reduced gray matter in the dorsolateral PFC bilaterally and in the left orbitofrontal cortex compared to healthy controls. Therefore, it is plausible to assume that the PFC is the recent focus of the brain region for both non-suicidal self-injury (NSSI) [4,5], suicidal thoughts and behavior [20,22], and makes a difference in this region. In studies using functional techniques, significant results have been reported in areas related to the PFC, especially in studies using emotion processing tasks [23]. Therefore, we hypothesized that the comparison of the activity and connectivity of the PFC between adolescents with and without self-injurious behaviors, especially using tasks related to emotion processing, might show the differences and add somewhat uncover the neurobiology of self-injurious behavior.
It is well known that not only biological factors, but also various environmental factors, such as child abuse and peer victimization, are involved in self-injurious behaviors [24,25]. Considering that the unique developmental period of adolescence is related to neural diathesis and stressors [26,27]. childhood adversity was included as a mediating factor in this study.
The near-infrared spectroscopy (NIRS) device applied in this study to measure the activation and connectivity of the PFC is superior in several respects compared to existing devices such as MRI, fMRI, diffusion tensor imaging, single-photon emission computerized tomography, positron emission tomography, and electroencephalogram. It is non-invasive, has a high spatial and temporal resolution, is free of radiation exposure, and can be performed in a comfortable position and in a short amount of time without a preparation process. It is one of neuroimaging modality that can measure the hemodynamic and metabolic responses associated with neuronal activity as well as measure neuronal activity directly. Once meaningful outcomes are derived through this tool, it is expected to be used practically in the clinical field because of the many advantages mentioned above.
This study aimed to investigate the difference in prefrontal activation and connectivity with a clinically feasible instrument, functional NIRS (fNIRS), during an emotion recognition task (ERT) between ASI and psychiatric controls (PC). Furthermore, we investigated the difference in activation between groups according to childhood adversity.



Participants were recruited from the outpatient clinic of the Child and Adolescent Psychiatry Department of Myongji Hospital. The study was approved by the Ethical Committee of Myongji Hospital (no MJH. 2020-04-010-002). Written informed consent obtained from all participants and their caregivers before participating in this study. The recruitment period began in June 2020 and ended in October 2021. An experienced child and adolescent psychiatrist conducted clinical interviews and a trained assessor performed the assessments. The inclusion criteria for the clinical group were the following: 1) aged 12-19 years and 2) any self-injurious behavior (e.g., cutting, biting, burning, carving, pinching, pulling hair, severe scratching, etc.) within a month regardless of suicide intent. The exclusion criteria for the study participants were as follows: 1) any unstable comorbidities (e.g., uncontrolled diabetes), neurological (e.g., active seizures), or mental disorder (e.g., active psychosis) and 2) serious medical conditions that require continuous treatment. The psychiatric control group was defined as who had never engaged in any self-injurious behavior with aged 12-19 years. They were recruited from the same sources and from the local community through advertisements. All participants received monetary compensation of 20,000 won (approximately $15).

Psychological assessment

Korean version of the Beck Scale for Suicide Ideation

It is a self-report scale that measures the presence and severity of suicide intent and is evaluated on a 0-2-point Likert scale. The score range for the 19 items was 0-38 [28,29].

Adverse Childhood Experiences

Adverse Childhood Experiences (ACE) is a self-report questionnaire that asks about emotional abuse, physical abuse, sexual abuse, emotional neglect, physical neglect, separation or divorce of parents, being treated violently, substance abuse in the household, mental illness in the household, and incarcerated household members [30,31]. The score range of the 10 items was 0-10.


The ERT was adopted to measure participants’ sensitivity to facial expressions of emotion. In this task, participants were asked to identify the emotion category experienced by the person in the picture. Each picture with an emotion facial expression was presented on the screen one at a time and participants were given six options to choose from (“disgusted,” “sad,” “happy,” “angry,” “surprised,” and finally, “afraid”). In each trial, with a mouse click, the participants chose one of the six categories of emotion that they believed best corresponded to the one that the person in the picture was experiencing. Each picture was presented for approximately 6 s, and if no response was made within the 6-s response window, it automatically proceeded to the next trial. The task consisted of a total of 48 trials, lasting approximately 6 min for each participant, including a 30-s baseline measurement period before the task. Three practice trials were conducted before the baseline measurement to familiarize the participants with the task requirements. The accuracy and reaction time for each trial were recorded.
Forty-eight images from the Korea University Facial Expression Collection (KUFEC) [32] were selected for this task. The “correct answer” for the ERT was determined by the emotional expression instruction that was given to the amateur actors during the photoshoot. Eight images (four male and four female faces each) were chosen from the six emotion categories, and the order of image presentation was randomized for each participant. Stimulus presentation and response collection were conducted using an experiment program written in Python with the PsychoPy3 [33] toolbox (

fNIRS measurement

We used a portable fNIRS device (NIRSIT LITE; OBELAB Inc., Seoul, Korea) to collect hemodynamic responses from the PFC of each participant during the ERT. The device is equipped with five dual-wavelength (780 and 850 nm) laser diodes and seven photodetectors comprising 15 channels, where each source and detector composing a channel are approximately 30 mm apart [34]. The sampling rate of the device is 8.138 Hz. The device collects signals mainly from the frontopolar cortex and roughly covers the adjacent prefrontal regions, including the dorsolateral and ventrolateral PFC and orbitofrontal cortex (Figure 1).

fNIRS data preprocessing and analysis

The preprocessing steps for the data collected during ERT are as follows: first, the raw signal was filtered through bandpass filters with a discrete cosine transform with a low-pass cut-off frequency of 0.1 Hz and a high-pass cut-off frequency of 0.005 Hz to filter out physiological noise and slow drift. After the signal was log-transformed to yield the delta optical density, it was converted to the HbO and HbR concentration values using the modified Beer-Lambert law [35,36]. Subsequent analyses were performed to determine the HbO concentration signal.
Hemodynamic responses during emotional recognition were captured via a general linear model using the onsets of each trial as an event-related regressor. Within the model, in addition to the task regressor, an additional regressor capturing the onset of the baseline period, temporal derivatives of each regressor, three motion regressors to account for the head movement (gyroscope and accelerometer signals converted to movement angles), and a constant regressor were included. For the contrast vector, 1 was assigned to the task regressor and 0 to every other regressor, rendering them regressors of no interest. Therefore, channels with positive beta values that differed significantly from 0 would be considered active during the task trials.
In addition to task activation, the connectivity between channels during the entire experimental duration was also calculated to capture any task-related coordination between regions. Although activation can summarize the overall level of taskrelated responses in amplitude, the correlation, which is statistically independent of the calculation of activation, is expected to indicate whether one or more regions of the PFC showed more or less active communication with other regions in the presence of the cognitive task. The correlation between the responses of a channel pair was initially calculated using the Pearson’s correlation, and then Fisher transformation before any statistical tests.

Statistical analysis

Statistical analysis was conducted using R [37] and RStudio [38]. Statistical significance was set at p<0.05. First, inclusion criteria were primarily based on the presence of self-injurious behavior within a month, and participants in the clinical group were recruited. Participants were divided into two groups: ASI group and adolescents without any psychiatric disorder (PC group). The χ2 test or independent t-test was performed to explore differences in demographic and psychiatric characteristics of participants.


Demographic and psychiatric characteristics

A total of 37 adolescents participated (PC=14, ASI=23), and the demographic characteristics of the groups and psychiatric test results are presented in Table 1 and Supplementary Figure 1 (in the online-only Data Supplement) .

PFC activation

The overall changes in oxy-Hb concentration in the PFC during the ERT in both groups are presented in Figure 2. There was no statistically significant difference between the ASI and PC groups (all n.s) before outlier removal, but after within-group outlier removal based on interquartile range, channel 6 (p=0.047) and channel 13 (p=0.02) reached significant differences, and channel 5 (p=0.089) and channel 9 (p=0.06) were marginally significant. However, none of the comparisons were found to be significant after family-wise correction. Overall, although not statistically significant, the activation patterns shown in Figure 2 suggest that the ASI group showed greater prefrontal activation than the PC group during the ERT.

fNIRS connectivity

Channel-wise connectivity analyses were performed within the PFC. In the ASI group, channel 6, located in the right dorsolateral PFC, showed significantly higher connectivity with other channels than the PC group during the ERT (Figure 3 and Supplementary Figure 2 in the online-only Data Supplement).
The greater correlations between channel 6 and every other channel in the PFC were significant only before the multiple comparison correction. However, correction performed on pairwise connectivity is rare, and the singularity of channel 6, if any, would be penalized, resulting in null results. Therefore, we report the non-corrected statistics here, which require caution when interpreting the results.

Relationship between channel 6 and ACE total score by groups

The interaction between channel 6 and the ACE total score showed statistical significance between the two groups(t[33] -2.61; p=0.014). The PC group showed no correlation with channel 6. The ASI group showed a negative correlation with activation, according to the ACE total score (Pearson’s r=-0.48; p=0.021) (Figure 4).


This is the first study to investigate PFC connectivity, showing the extent of hemodynamic responses between channels during ERTs in ASIs. In terms of activation, showing the extent of the hemodynamic response of each channel, some channels reached statistical significance after removing outliers, but in terms of connectivity, only a single channel (channel 6) showed a greater correlation with other channels. Despite being a null finding considering multiple comparisons, it is meaningful to report it because a challenging study was conducted in ASI.
Consistently reported research results indicated that areas involved in facial expression recognition were the anterior medial PFC, posterior cingulate cortex, and adjacent temporoparietal junction [39,40]. The lateral PFC and anterior cingulate cortex are known to modulate the activity of the above-mentioned region [41]. Although the tasks used were different, a study of female adults with self-injurious behavior showed increased activity of the dorsolateral PFC [42]. Nakamura et al. [43] suggested that the right lateral PFC is involved in the processing of emotional facial expressions. Although there was a gap in the areas identified in our findings, a study showed cortical alterations in female adolescents with NSSI using emotional stimulation [13]. Due to the limitations of NIRS, it was not possible to accurately identify the interplay with the area within the deep brain but considering that it is involved in emotional processing and is the target of neuromodulation, it seems to be a plausible finding. It is believed that the interplay with deep brain structures, such as the amygdala and insula, should be seen to interpret the connectivity relationship in a more detailed manner. To explain this at a hypothetical level, it appears that the ASI group uses more brain by increasing connectivity in processing emotional recognition compared to the control group.
Interestingly, there was a significant negative correlation between ACE and channel 6 activation among the ASI group. That is, ASI showed decreased channel 6 activities as the number of ACE increased, apart from the control group. This is consistent with previous findings that have shown differential frontal brain activity in vulnerable trauma-exposed, nontrauma-exposed, and resilient trauma-exposed patients [44,45].
There are several limitations to this study. First, the sample size is small. Therefore, a larger design should be considered in future research. Second, consideration of psychiatric comorbidities and structured interviews of participants was absent. Sex discrepancy in the sample is another limiting factor of this study.
Despite these limitations, there is a clinical implication that a novel attempt to reveal neurobiological differences among ASI using fNIRS, a tool that can be practically used in the clinical field after its validity is confirmed. Regarding fNIRS, only one study has examined resting-state activation in youths with NSSI [46]. In addition, cultural differences are believed to be reduced by applying ERT developed and standardized in Korea. This study is expected to contribute to future self-injurious behavior research as the first to investigate the differences in the connectivity of the PFC in Korean adolescents.

Supplementary Materials

The online-only Data Supplement is available with this article at
Supplementary Figure 1.
Distribution plots showing non-normality. SSI, severity of suicide intent; ACE, Adverse Childhood Experiences.
Supplementary Figure 2.
Channel-wise connectivity between the PC (A) and ASI (B) groups. PC, psychiatric controls; ASI, adolescents with self-injurious behavior.


Availability of Data and Material

The datasets generated or analyzed during the study are available from the corresponding author upon reasonable request.

Conflicts of Interest

The authors have no potential conflicts of interest to disclose.

Author Contributions

Conceptualization: Sang Min Lee, Minha Hong. Data curation: Minha Hong. Formal analysis: Jihyun Cha. Funding acquisition: Minha Hong. Investigation: Minha Hong. Methodology: Minha Hong. Project administration: Minha Hong. Resources: Minha Hong. Software: Jihyun Cha. Supervision: Sang Min Lee. Validation: Minha Hong. Visualization: Minha Hong. Writing—original draft: Sang Min Lee. Writing—review & editing: all authors.

Funding Statement

This work was supported by the Bumsuk Academic Research Fund (2019).


The authors thank Ms. Yoon Jae Lee and Ms. Min Seon Jung for their assistance with this research. We appreciate the patience of all participants in the study.

Figure 1.
fNIRS measurement coverage and configuration of 15 channels within the prefrontal cortex (reproduced from OBELAB. NIRSIT Channel Information, with permission of OBELAB Inc.) [34].
Figure 2.
Regions showing activation during the emotion recognition task in the PC (A) and ASI groups (B). PC, psychiatric controls; ASI, adolescents with self-injurious behavior.
Figure 3.
Channel-wise connectivity between PC and ASI (PC-ASI). The negative value indicates the higher connectivity of the ASI group than that of PC. PC, psychiatric controls; ASI, adolescents with self-injurious behavior.
Figure 4.
Correlation between channel 6 activation and the total ACE score between PC and ASI. ACE: Adverse Childhood Experiences; PC, psychiatric controls; ASI, adolescents with self-injurious behavior.
Table 1.
Demographic characteristics of the participants (N=37)
Characteristics PC (N=14) ASI (N=23) t/χ2 p
Age (yr), mean (SD) 15.86 (2.41) 16.13 (1.87) t (22.43)=0.036 0.720
Female sex, N (%) 6 (42.8) 20 (86.9) χ2(1, N=37)=8.1 0.004
K-BSS, mean (SD) 1.5 (6.13) 26 (7.39) χ2(1)=23.28 <0.001
ACE, median (SD) 0 (2.79) 4.0 (2.46) χ2(1)=7.91 0.005

PC, psychiatric control; ASI, adolescents with self-injurious behavior; ACE, Adverse Childhood Experiences; K-BSS, Korean version of the Beck Scale for Suicidal Ideation


1. Swannell SV, Martin GE, Page A, Hasking P, St John NJ. Prevalence of nonsuicidal self-injury in nonclinical samples: systematic review, meta-analysis and meta-regression. Suicide Life Threat Behav 2014;44:273-303.
crossref pmid
2. Jarvi S, Jackson B, Swenson L, Crawford H. The impact of social contagion on non-suicidal self-injury: a review of the literature. Arch Suicide Res 2013;17:1-19.
crossref pmid
3. Algorta GP, Youngstrom EA, Frazier TW, Freeman AJ, Youngstrom JK, Findling RL. Suicidality in pediatric bipolar disorder: predictor or outcome of family processes and mixed mood presentation? Bipolar Disord 2011;13:76-86.
crossref pmid pmc
4. Ando A, Reichl C, Scheu F, Bykova A, Parzer P, Resch F, et al. Regional grey matter volume reduction in adolescents engaging in non-suicidal self-injury. Psychiatry Res Neuroimaging 2018;280:48-55.
crossref pmid
5. Chanen AM, Velakoulis D, Carison K, Gaunson K, Wood SJ, Yuen HP, et al. Orbitofrontal, amygdala and hippocampal volumes in teenagers with first-presentation borderline personality disorder. Psychiatry Res 2008;163:116-125.
crossref pmid
6. Whittle S, Chanen AM, Fornito A, McGorry PD, Pantelis C, Yücel M. Anterior cingulate volume in adolescents with first-presentation borderline personality disorder. Psychiatry Res 2009;172:155-160.
crossref pmid
7. Takahashi T, Chanen AM, Wood SJ, Yücel M, Tanino R, Suzuki M, et al. Insular cortex volume and impulsivity in teenagers with first-presentation borderline personality disorder. Prog Neuropsychopharmacol Biol Psychiatry 2009;33:1395-1400.
crossref pmid
8. Quevedo K, Martin J, Scott H, Smyda G, Pfeifer JH. The neurobiology of self-knowledge in depressed and self-injurious youth. Psychiatry Res Neuroimaging 2016;254:145-155.
crossref pmid pmc
9. Groschwitz RC, Plener PL, Groen G, Bonenberger M, Abler B. Differential neural processing of social exclusion in adolescents with non-suicidal self-injury: an fMRI study. Psychiatry Res Neuroimaging 2016;255:43-49.
crossref pmid
10. Brown RC, Plener PL, Groen G, Neff D, Bonenberger M, Abler B. Differential neural processing of social exclusion and inclusion in adolescents with non-suicidal self-injury and young adults with borderline personality disorder. Front Psychiatry 2017;8:267
crossref pmid pmc
11. Poon JA, Thompson JC, Forbes EE, Chaplin TM. Adolescents’ reward-related neural activation: links to thoughts of nonsuicidal self-injury. Suicide Life Threat Behav 2019;49:76-89.
crossref pmid pmc pdf
12. Sauder CL, Derbidge CM, Beauchaine TP. Neural responses to monetary incentives among self-injuring adolescent girls. Dev Psychopathol 2016;28:277-291.
crossref pmid
13. Plener PL, Bubalo N, Fladung AK, Ludolph AG, Lulé D. Prone to excitement: adolescent females with non-suicidal self-injury (NSSI) show altered cortical pattern to emotional and NSS-related material. Psychiatry Res 2012;203:146-152.
crossref pmid
14. Westlund Schreiner M, Klimes-Dougan B, Mueller BA, Eberly LE, Reigstad KM, Carstedt PA, et al. Multi-modal neuroimaging of adolescents with non-suicidal self-injury: amygdala functional connectivity. J Affect Disord 2017;221:47-55.
crossref pmid pmc
15. Demers LA, Schreiner MW, Hunt RH, Mueller BA, Klimes-Dougan B, Thomas KM, et al. Alexithymia is associated with neural reactivity to masked emotional faces in adolescents who self-harm. J Affect Disord 2019;249:253-261.
crossref pmid pmc
16. Bonenberger M, Plener PL, Groschwitz RC, Grön G, Abler B. Differential neural processing of unpleasant haptic sensations in somatic and affective partitions of the insula in non-suicidal self-injury (NSSI). Psychiatry Res 2015;234:298-304.
crossref pmid
17. Osuch E, Ford K, Wrath A, Bartha R, Neufeld R. Functional MRI of pain application in youth who engaged in repetitive non-suicidal self-injury vs. psychiatric controls. Psychiatry Res 2014;223:104-112.
crossref pmid
18. Lee HS, Park KJ, Kwon Y, Shon SH, Youngstrom EA, Kim HW. Clinical characteristics associated with suicidal attempt and non-suicidal selfinjury in Korean adolescents. Psychiatry Investig 2021;18:561-569.
crossref pmid pmc pdf
19. Kim H, Ryu JM, Kim HW. Characteristics and trends of suicide attempt or non-suicidal self-injury in children and adolescents visiting emergency department. J Korean Med Sci 2020;35:e276.
crossref pmid pmc pdf
20. Huber RS, Subramaniam P, Kondo DG, Shi X, Renshaw PF, Yurgelun-Todd DA. Reduced lateral orbitofrontal cortex volume and suicide behavior in youth with bipolar disorder. Bipolar Disord 2019;21:321-329.
crossref pmid pdf
21. Brunner R, Henze R, Parzer P, Kramer J, Feigl N, Lutz K, et al. Reduced prefrontal and orbitofrontal gray matter in female adolescents with borderline personality disorder: is it disorder specific? Neuroimage 2010;49:114-120.
crossref pmid
22. Goodman M, Hazlett EA, Avedon JB, Siever DR, Chu KW, New AS. Anterior cingulate volume reduction in adolescents with borderline personality disorder and co-morbid major depression. J Psychiatr Res 2011;45:803-807.
crossref pmid
23. Seymour KE, Jones RN, Cushman GK, Galvan T, Puzia ME, Kim KL, et al. Emotional face recognition in adolescent suicide attempters and adolescents engaging in non-suicidal self-injury. Eur Child Adolesc Psychiatry 2016;25:247-259.
crossref pmid pmc pdf
24. Nock M. The oxford handbook of suicide and self-injury. New York: Oxford University Press; 2014.

25. Franklin JC, Ribeiro JD, Fox KR, Bentley KH, Kleiman EM, Huang X, et al. Risk factors for suicidal thoughts and behaviors: a meta-analysis of 50 years of research. Psychol Bull 2017;143:187-232.
crossref pmid
26. Spear LP. The adolescent brain and age-related behavioral manifestations. Neurosci Biobehav Rev 2000;24:417-463.
crossref pmid
27. van Heeringen K. Stress-diathesis model of suicidal behavior. In: Dwivedi Y, editor. The neurobiological basis of suicide. Boca Raton: CRC Press/Taylor & Francis, 2012, p. 113-124.

28. Beck AT, Kovacs M, Weissman A. Assessment of suicidal intention: the Scale for Suicide Ideation. J Consult Clin Psychol 1979;47:343-352.
crossref pmid
29. Shin MS, Park KB, Oh KJ, Kim ZS. A study of suicidal ideation among high school students: the structural relation among depression, hopelessness, and suicidal ideation. Kor J Clin Psychol 1990;9:1-19.

30. Felitti VJ, Anda RF, Nordenberg D, Williamson DF, Spitz AM, Edwards V, et al. Relationship of childhood abuse and household dysfunction to many of the leading causes of death in adults: the Adverse Childhood Experiences (ACE) study. Am J Prev Med 1998;14:245-258.
31. Achenbach TM, Edelbrock C. Manual for the child behavior checklist and revised child behavior profile. Burlington: University of Vermont; 1983.

32. Lee TH, Lee KY, Lee K, Choi JS, Kim HT. The Korea University Facial Expression Collection: KUFEC. Lab. Seoul, Korea: Dept. of Psychology; 2006.

33. Peirce J, Gray JR, Simpson S, MacAskill M, Höchenberger R, Sogo H, et al. PsychoPy2: experiments in behavior made easy. Behav Res Methods 2019;51:195-203.
crossref pmid pmc pdf
34. OBELAB. NIRSIT Channel Information [Internet]. Available at: Accessed September 8, 2022.

35. Delpy DT, Cope M, van der Zee P, Arridge S, Wray S, Wyatt J. Estimation of optical pathlength through tissue from direct time of flight measurement. Phys Med Biol 1988;33:1433-1442.
crossref pmid
36. Cope M. The development of a near infrared spectroscopy system and its application for non invasive monitoring of cerebral blood and tissue oxygenation in the newborn infants [dissertation] London, UK, University of London, University College London. 1991.

37. R Core Team. R: A language and environment for statistical computing [Internet]. Vienna, Austria, R Foundation for Statistical Computing. 2012;Available at: Accessed October 1, 2021.

38. Rstudio Team. RStudio: Integrated development for R. (Version 1.2. 5033) [Internet]. Boston, MA, RStudio, Inc.. 2019;Available at: .Accessed October 1, 2021.

39. Frith CD, Frith U. The neural basis of mentalizing. Neuron 2006;50:531-534.
crossref pmid
40. Zaki J, Ochsner K. The need for a cognitive neuroscience of naturalistic social cognition. Ann N Y Acad Sci 2009;1167:16-30.
crossref pmid pmc
41. Weissman DH, Perkins AS, Woldorff MG. Cognitive control in social situations: a role for the dorsolateral prefrontal cortex. Neuroimage 2008;40:955-962.
crossref pmid pmc
42. Schmahl C, Bohus M, Esposito F, Treede RD, Di Salle F, Greffrath W, et al. Neural correlates of antinociception in borderline personality disorder. Arch Gen Psychiatry 2006;63:659-667.
crossref pmid
43. Nakamura A, Maess B, Knösche TR, Friederici AD. Different hemispheric roles in recognition of happy expressions. PLoS One 2014;9:e88628.
crossref pmid pmc
44. New AS, Fan J, Murrough JW, Liu X, Liebman RE, Guise KG, et al. A functional magnetic resonance imaging study of deliberate emotion regulation in resilience and posttraumatic stress disorder. Biol Psychiatry 2009;66:656-664.
crossref pmid
45. van der Werff SJ, Pannekoek JN, Veer IM, van Tol MJ, Aleman A, Veltman DJ, et al. Resilience to childhood maltreatment is associated with increased resting-state functional connectivity of the salience network with the lingual gyrus. Child Abuse Negl 2013;37:1021-1029.
crossref pmid
46. Koenig J, Höper S, van der Venne P, Mürner-Lavanchy I, Resch F, Kaess M. Resting state prefrontal cortex oxygenation in adolescent non-suicidal self-injury - a near-infrared spectroscopy study. Neuroimage Clin 2021;31:102704
crossref pmid pmc


Browse all articles >

Editorial Office
#522, 27, Seochojungang-ro 24-gil, Seocho-gu, Seoul 06601, Korea
Tel: +82-2-717-0892    E-mail:                

Copyright © 2024 by Korean Neuropsychiatric Association.

Developed in M2PI

Close layer
prev next