Evidence map›Paper›PMID 40579583›Full record

ReviewBiological cybernetics2025

Artificial intelligence meets brain theory (again).

Michael A Arbib

Abstract readReview
In one paragraph

Review in Biological cybernetics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

1 author.

Michael A ArbibUniversity of California at San Diego, La Jolla, CA, USA. arbib@usc.edu.ORCID 0000-0002-6902-3580

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

After noting the cybernetic origins of Kybernetik/ Biological Cybernetics, we respond to the Editorial by Fellous et al. (2025) and then analyze talks from the NIH BRAIN NeuroAI 2024 Workshop to get one "snapshot" of the state of the conversation between Artificial intelligence (AI) and brain theory (BT). Key recommendations going beyond the earlier Editorial are that: (i) Successes in fitting ANNs to increasingly large neuroscience datasets must not distract us from the quixotic but demanding quest to understand "how the brain works" and discover underlying brain (and AI) operating principles. (ii) We must integrate functional and structural analyses in exploring systems of systems, integrating structures (e.g., brain regions, cortical modules) and functions (e.g., schemas for perception, action and cognition) that bridge between neural circuitry and patterns of behavior. (iii) We must study the diversity of intelligences exhibited by animals in their strategies for survival and not only the disembodied employment of language and reasoning. Finally and briefly, we note the urgency of assessing the societal implications of an age of increasingly pervasive human-machine symbiosis.

Indexed as

Artificial IntelligenceBrainAnimalsHumansArtificial intelligenceBrain theoryCyberneticsHuman-machine symbiosisNeuroAINeuromorphic computing

Identifiers

PMID40579583
PMCPMC12204934

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.