Probing Prefrontal Cortex Hemodynamic Alterations for Major Depression Disorder

NCT ID: NCT03595020

Last Updated: 2018-07-23

Basic Information

• Recruitment Status: UNKNOWN
• Total Enrollment: 200 participants
• Study Classification: OBSERVATIONAL
• Study Start Date: 2017-02-16
• Study Completion Date: 2018-12-31

Brief Summary

Major depression disorder (MDD) has high estimated lifetime prevalence rates of 16.6%. Currently, the diagnosis for the MDD mainly depends on patients' reports of symptoms, observed behaviors and disease course. Establishment of clinically useful biomarkers for the MDD diagnosis would enhance patient management and treatment effect, and lead to the therapies adjusted to the individual. However, no such biomarkers have been established up to now. Therefore, the development of objective and feasible biomarkers is of special significance and a great challenge for accurate and early diagnosis and treatment of depression, in order to overcome the limitations of relying on clinical interviews alone.The ability to correctly recognize emotional states from faces is instrumental for interpersonal engagement and social functioning. Impairments processing of facial emotional expressions and biased facial emotion detection are frequently found in the MDD patients. To date, the studies on neural mechanism of the facial emotion recognition of the MDD patients were mainly based on the functional magnetic resonance imaging (fMRI). Functional near-infrared spectroscopy (fNIRS) has not been applied for the facial emotion recognition for the depression patients up to now. To bridge the important gap in the literature, we used the fNIRS methodology to investigate the neural mechanisms of facial emotion recognition for the patients with depression. We hypothesize the physiological feature of the hemodynamic responses in prefrontal cortex measured by fNIRS under the task of face emotion recognition, including the difference of the median, the Mayer wave power, the mean cross wavelet coefficient, and the mean wavelet coherence coefficient, combined with the behavior measurement (behavior accuracy and response time), could provide a reliable and feasible diagnosis approach to differentiate patients with the MDD from healthy control (HC) subjects with acceptable sensitivity and specificity.

Detailed Description

The fMRI technique for functional imaging were limited by the fact that the individuals need to be placed in an uncomfortable or unnatural setting and foreign, noisy, dark, or claustrophobic environment (e.g., lying in a supine position in a narrow gantry with the head restrained during the entire examination), for accurate measurement during the procedure, with relatively lower temporal resolution. In contrast, a multi-channel fNIRS machine provides a completely non-invasive, quiet and mobile measurement of brain function in ordinary clinical settings and allows patients to be comfortably seated in a normal posture in a well-lit room, with higher temporal resolution making it possible to obtain a recording of the actual time course of a hemodynamic epoch in response to a specific cognitive task (e.g., facial emotion recognition task in our study) in a single trial. Additionally, due to the small operating and maintenance costs associated with NIRS, it is possible to run fNIRS study with a large sample of participants.

Conditions

Depressive Disorder, Major

Study Design

• Observational Model Type: CASE_CONTROL
• Study Time Perspective: PROSPECTIVE

Study Groups

MDD group

The major depression group (MDD group) received antidepressant treatment but did not interfere with drug selection.

No interventions assigned to this group

HC group

The healthy control group (HC group) don't accept intervention and treatment.

No interventions assigned to this group

Eligibility Criteria

Inclusion Criteria

• MDD group:

All subjects were free of psychotropic medication for a minimum of 4 weeks; Psychiatric diagnosis was determined by DSM-IV criteria; Depressed subjects were included with 17-item Hamilton Rating Scale for Depression (HRSD) scores ≥ 18; Mini-mental State Examination(MMSE) ≥ 24; All subjects had normal or corrected-to-normal vision.

• HC group:

All subjects were free of psychotropic medication for a minimum of 4 weeks; All subjects did not have any mental, neurological or physical diseases；HRSD scores ≤ 7; MMSE ≥ 28; All subjects had normal or corrected-to-normal vision.

• Minimum Eligible Age: 18 Years
• Maximum Eligible Age: 35 Years
• Eligible Sex: ALL
• Accepts Healthy Volunteers: Yes

Sponsors

Xi'an Jiaotong University

OTHER

Sponsor Role: collaborator

Xijing Hospital

OTHER

Sponsor Role: lead

Responsible Party

Responsibility Role: SPONSOR

Principal Investigators

Huaning Wang, doctorate

Role: STUDY_CHAIR

Department of psychiatry, Xijing Hospital

Locations

Department of psychiatry, Xijing Hospital; Research Institute of Biomedical Engineering, Xi'an Jiaotong University

Xi'an, Shaanxi, China

Countries

China

References

Zwick JC, Wolkenstein L. Facial emotion recognition, theory of mind and the role of facial mimicry in depression. J Affect Disord. 2017 Mar 1;210:90-99. doi: 10.1016/j.jad.2016.12.022. Epub 2016 Dec 19.

Reference Type: BACKGROUND

PMID: 28024224 (View on PubMed)

Tsuchida A, Fellows LK. Are you upset? Distinct roles for orbitofrontal and lateral prefrontal cortex in detecting and distinguishing facial expressions of emotion. Cereb Cortex. 2012 Dec;22(12):2904-12. doi: 10.1093/cercor/bhr370. Epub 2012 Jan 5.

Reference Type: BACKGROUND

PMID: 22223852 (View on PubMed)

Takizawa R, Fukuda M, Kawasaki S, Kasai K, Mimura M, Pu S, Noda T, Niwa S, Okazaki Y; Joint Project for Psychiatric Application of Near-Infrared Spectroscopy (JPSY-NIRS) Group. Neuroimaging-aided differential diagnosis of the depressive state. Neuroimage. 2014 Jan 15;85 Pt 1:498-507. doi: 10.1016/j.neuroimage.2013.05.126. Epub 2013 Jun 10.

Reference Type: BACKGROUND

PMID: 23764293 (View on PubMed)

Other Identifiers

KY20172012-1

Identifier Type: -

Identifier Source: org_study_id