pith:GAPQ5F2G
Letting the neural code speak: Automated characterization of monkey visual neurons through human language
Natural language descriptions capture the selectivity of most neurons in macaque V1 and V4.
arxiv:2605.12485 v2 · 2026-05-12 · q-bio.NC · q-bio.QM
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\usepackage{pith}
\pithnumber{GAPQ5F2GWCCQCQT2BD75JWKNGD}
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Record completeness
Claims
Across macaque V1 and V4, the selectivity of most neurons is captured by concise, verifiable semantic descriptions; in V4, images generated from activating and suppressing hypotheses drove 96.1% of neurons above the 95th and 97.6% below the 5th percentile of natural-image responses, respectively.
That the digital-twin models of V1 and V4 faithfully reproduce the response statistics of real biological neurons for the novel synthetic images generated from language hypotheses.
Natural-language descriptions generated and verified through generative models and digital twins capture the selectivity of most neurons in macaque V1 and V4.
Receipt and verification
| First computed | 2026-05-20T00:04:36.600846Z |
|---|---|
| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | Pith Ed25519
(pith-v1-2026-05) · public key |
| Schema | pith-number/v1.0 |
Canonical hash
301f0e9746b08501427a08ffd4d94d30fdb07625a82e13dbc57e73f0402eaa3b
Aliases
· · · · ·Agent API
Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/GAPQ5F2GWCCQCQT2BD75JWKNGD \
| 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: 301f0e9746b08501427a08ffd4d94d30fdb07625a82e13dbc57e73f0402eaa3b
Canonical record JSON
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