Going Back to Kahlbaum’s Psychomotor (and GABAergic) Origins: Is Catatonia More Than Just a Motor and Dopaminergic Syndrome?
Bibliographic record
Abstract
In 1874, Karl Kahlbaum described catatonia as an independent syndrome characterized by motor, affective, and behavioral anomalies. In the following years, various catatonia concepts were established with all sharing the prime focus on motor and behavioral symptoms while largely neglecting affective changes. In 21st century, catatonia is a well-characterized clinical syndrome. Yet, its neurobiological origin is still not clear because methodological shortcomings of hitherto studies had hampered this challenging effort. To fully capture the clinical picture of catatonia as emphasized by Karl Kahlbaum, 2 decades ago a new catatonia scale was developed (Northoff Catatonia Rating Scale [NCRS]). Since then, studies have used NCRS to allow for a more mechanistic insight of catatonia. Here, we undertook a systematic review searching for neuroimaging studies using motor/behavioral catatonia rating scales/criteria and NCRS published up to March 31, 2019. We included 19 neuroimaging studies. Studies using motor/behavioral catatonia rating scales/criteria depict cortical and subcortical motor regions mediated by dopamine as neuronal and biochemical substrates of catatonia. In contrast, studies relying on NCRS found rather aberrant higher-order frontoparietal networks which, biochemically, are insufficiently modulated by gamma-aminobutyric acid (GABA)-ergic and glutamatergic transmission. This is further supported by the high therapeutic efficacy of GABAergic agents in acute catatonia. In sum, this systematic review points out the difference between motor/behavioral and NCRS-based classification of catatonia on both neuronal and biochemical grounds. That highlights the importance of Kahlbaum's original truly psychomotor concept of catatonia for guiding both research and clinical diagnosis and therapy.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.003 | 0.006 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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 source (direct Gemma or distilled Codex), 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".