Different Conceptual Frameworks of Catatonia
Bibliographic record
Abstract
Since the initial description of catatonia in 1874, three different distinct clinical and neurobiological frameworks have emerged. The first emphasizes psychomotor and affective aspects, building on Karl Ludwig Kahlbaum’s legacy. The second focuses on motor symptoms alone, influenced by the work of Emil Kraepelin and Eugen Bleuler. The third introduces the Wernicke–Kleist–Leonhard concept of psychomotor abnormalities such as catatonia as a significant neuropsychiatric framework. This chapter critically examines all three frameworks from both scientific and clinical perspectives, highlighting their advantages and disadvantages in research and treatment. The chapter will also delve into common synergies between neurobiological and clinical studies, discussing how these can inform the day-to-day management of catatonia. Furthermore, we will analyze the current classification systems of DSM-5 and ICD-11 and their relation to the described frameworks, with a focus on their strengths and weaknesses in diagnosing catatonia. Finally, this chapter will introduce a novel approach that links neural correlates and subjective experience of catatonia through their spatial (space) and temporal (time) patterns. This chapter will provide a comprehensive overview of diagnostic approaches and their clinical implications.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.013 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".