Characteristics of psychomotor retardation distinguishes patients with depression using multichannel near-infrared spectroscopy and finger tapping task
Bibliographic record
Abstract
BACKGROUND: Psychomotor retardation (PMR) is frequently noted as a characteristic feature of major depressive disorder (MDD). In patients with depression, it is characterized by retardation of speech, emotion, thinking, and cognition. This study explored the activation pattern of the prefrontal cortex (PFC) during the finger-tapping task (FTT) in subjects with MDD, aiming to provide additional understanding on the connection between PMR and PFC activation pattern in depression through the use of near-Infrared Spectroscopy (NIRS). We hypothesized that, through use of NIRS during the FTT, motor retardation in depression would generate a distinct PFC activation pattern, allowing for differentiation between patients with MDD and healthy controls (HCs). METHODS: Thirty-five patients with MDD and thirty-nine HCs underwent NIRS evaluation during performance of the FTT. The FTT included both left-finger tapping and right-finger tapping performed by a computer screen. Each participant was assessed using a 45-channel NIRS and various clinical scales. FINDINGS: During the left-FTT, the left orbitofrontal cortex (OFC) showed higher oxy-hemoglobin (Oxy-Hb) activation in the MDD group when compared to the HCs. During the right-FTT, the right dorsolateral prefrontal cortex (DLPFC) demonstrated lower Oxy-Hb activation, and the dorsomedial prefrontal cortex (DMPFC) showed higher Oxy-Hb activation in the MDD group versus the HC group. CONCLUSION: Our results demonstrated different activation patterns of the PFC between the MDD and HC groups, using FTT as a motor performance task. In particular, the OFC, the DLPFC and the DMPFC areas hold promise as new useful sites for such differentiation in future investigations.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".