pith:OP6JBWTF
CalM: A Self-Supervised Foundation Model for Population Dynamics in Calcium Imaging Data
A self-supervised model pretrained on calcium traces forecasts neural population dynamics better than specialized baselines and adapts to decode behavior.
arxiv:2604.04958 v3 · 2026-04-03 · q-bio.QM · cs.AI · q-bio.NC
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\pithnumber{OP6JBWTFSXBOYUSP4ATGQYMSPI}
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Claims
On the neural population dynamics forecasting task, CalM outperforms strong specialized baselines after pretraining. With a task-specific head, CalM further adapts to the behavior decoding task and achieves superior results compared with supervised decoding models.
That the self-supervised pretraining framework with the proposed tokenizer and dual-axis transformer learns representations that transfer effectively to multiple downstream tasks without requiring extensive task-specific architectural changes or data curation.
CalM uses a discrete tokenizer and dual-axis autoregressive transformer pretrained self-supervised on calcium traces to outperform specialized baselines on population dynamics forecasting and adapt to superior behavior decoding.
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Receipt and verification
| First computed | 2026-06-02T02:04:52.784866Z |
|---|---|
| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | Pith Ed25519
(pith-v1-2026-05) · public key |
| Schema | pith-number/v1.0 |
Canonical hash
73fc90da6595c2ec524fe0266861927a03c8f50ff1c745b8bad5430137ab6530
Aliases
· · · · ·Agent API
Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/OP6JBWTFSXBOYUSP4ATGQYMSPI \
| jq -c '.canonical_record' \
| python3 -c "import sys,json,hashlib; b=json.dumps(json.loads(sys.stdin.read()), sort_keys=True, separators=(',',':'), ensure_ascii=False).encode(); print(hashlib.sha256(b).hexdigest())"
# expect: 73fc90da6595c2ec524fe0266861927a03c8f50ff1c745b8bad5430137ab6530
Canonical record JSON
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