Chatbot Intervention Effects on Resting-State Brain Function in Anhedonia

Effects of a Chatbot-Based Intervention on Resting-State Functional Connectivity and Spontaneous Neural Activity in Individuals With Anhedonia

The main aim of the present study is to investigate the effects of a Motivational Interviewing-based artificial intelligence chatbot on resting-state brain function in college students with elevated anhedonia and depressive symptoms. The study will use a randomized active-control intervention design with pre- and post-intervention resting-state functional magnetic resonance imaging assessments.

Study Overview

• Status: Recruiting
• Conditions: Healthy
• Intervention / Treatment: Behavioral: MI Chatbot Interaction; Behavioral: Active Control Chatbot Interaction

Detailed Description

Anhedonia represents a core characteristic of depression and is characterized by reduced experience of pleasure. It is closely related to decreased motivation, altered reward processing, and alterations in intrinsic brain network function. Resting-state fMRI provides a way to examine intrinsic brain activity and functional connectivity without requiring participants to perform a specific task. This is important because changes associated with anhedonia may not only appear during reward-related tasks, but may also be reflected in spontaneous brain network organization.

• Study Type: Interventional
• Enrollment (Estimated): 80
• Phase: Not Applicable

Contacts and Locations

• Study Contact: Name: Benjamin Becker; Phone Number: (852) 3917-5097; Email: bbecker@hku.hk

Study Locations

• China
  • Sichuan
    • Chengdu, Sichuan, China
      • Recruiting
      • University of Electronic Science and Technology of China
      • Contact: Benjamin Becker, Dr; Phone Number: (852) 3917-5097; Email: bbecker@hku.hk

Participation Criteria

Eligibility Criteria

• Ages Eligible for Study: Adult
• Accepts Healthy Volunteers: Yes

Description

Inclusion Criteria:

• 18-40 years
• Right-handed
• Normal or corrected normal visual acuity
• Participants must show elevated anhedonia and depressive symptoms at screening, defined as a total score of 23.5 or higher on the Snaith-Hamilton Pleasure Scale and a score of 14 or higher on the Beck Depression Inventory

Exclusion Criteria:

• History of major central nervous system disorders, such as epilepsy, traumatic brain injury, stroke, or brain tumors.
• History of severe mental illness, including schizophrenia spectrum disorders, bipolar disorder, or other psychotic disorders.
• History of substance or alcohol use disorder or substance or alcohol misuse within the past 12 months that may affect study participation or outcome assessment.
• Individuals currently at high risk of suicide, severe self-harm, or experiencing an acute psychiatric crisis.
• Individuals who are currently using psychiatric medications or have undergone psychotherapy within the past 4 weeks that may significantly affect mood, motivation, or reward processing.
• Severe vision or hearing impairments that cannot be corrected and would interfere with task performance.
• Contraindications to MRI scanning, including metallic implants, pacemakers, severe claustrophobia, or other conditions incompatible with MRI.
• Pregnancy or breastfeeding.

Study Plan

How is the study designed?

Design Details

• Primary Purpose: Basic Science
• Allocation: Randomized
• Interventional Model: Parallel Assignment
• Masking: Double

Number of Arms

2

Arms and Interventions

Participant Group / Arm	Intervention / Treatment
Experimental: Motivational Interviewing-based AI chatbot group; Motivational Interviewing-based AI chatbot intervention	Behavioral: MI Chatbot Interaction; The experimental chatbot is designed to use principles of Motivational Interviewing to support participants in exploring their personal values, motivation for change, and daily behavioral goals related to pleasure, engagement, and reward-seeking. During the intervention period, participants will interact with the chatbot regularly through brief text-based conversations. The chatbot will provide empathic, non-judgmental responses, encourage reflection on current difficulties, and help participants identify small, feasible actions that may increase daily engagement and positive experiences. It will not provide diagnosis, crisis counseling, or medical treatment.
Active Comparator: Active control chatbot group; Active control nature-story chatbot intervention	Behavioral: Active Control Chatbot Interaction; Participants will interact with a chatbot matched in format and frequency of use. This chatbot will provide neutral nature-related stories or general natural history content. It will be designed to maintain participant engagement while avoiding therapeutic techniques, motivational interviewing strategies, behavioral activation guidance, or personalized mental health advice. This active control condition will help control for nonspecific effects of chatbot interaction, attention, expectancy, and digital engagement.

What is the study measuring?

Primary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Intervention-Related Changes in Resting-State Functional Connectivity After the Intervention	Resting-state fMRI will be used to examine functional connectivity among predefined regions involved in reward, social, and self-referential processing. Connectivity will be estimated from Pearson correlations between regional BOLD time series and then converted using the Fisher z transformation. Changes from baseline to post-intervention will be reported as dimensionless Fisher z values.	Baseline before the first chatbot interaction and Week 1 after completion of the chatbot intervention.

Secondary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Intervention-Related Changes in Spontaneous Activity After the Intervention	Indices of spontaneous neural activity in regions involved in motivation, social and self-referential processing, will be extracted from resting-state fMRI scans collected at the two assessment points. These indices will include amplitude of low-frequency fluctuations or fractional amplitude of low-frequency fluctuations, as well as regional homogeneity. Baseline and post-intervention values will then be compared to characterize pre-to-post changes.	Baseline before the first chatbot interaction and Week 1 after completion of the chatbot intervention.

Collaborators and Investigators

• Sponsor: University of Electronic Science and Technology of China

Study record dates

Study Major Dates

• Study Start (Estimated): June 20, 2026
• Primary Completion (Estimated): June 30, 2028
• Study Completion (Estimated): December 31, 2028

Study Registration Dates

• First Submitted: June 17, 2026
• First Submitted That Met QC Criteria: June 22, 2026
• First Posted (Actual): June 24, 2026

Study Record Updates

• Last Update Posted (Actual): June 24, 2026
• Last Update Submitted That Met QC Criteria: June 22, 2026
• Last Verified: June 1, 2026

More Information

Terms related to this study

• Keywords: fMRI; reward processing; AI interaction
• Other Study ID Numbers: BAM_lab_MI_01

Plan for Individual participant data (IPD)

• Plan to Share Individual Participant Data (IPD)?: NO
• IPD Plan Description: Corresponding individual level data will be made available upon request.

Drug and device information, study documents

• Studies a U.S. FDA-regulated drug product: No
• Studies a U.S. FDA-regulated device product: No