Closed-loop perception: gaps between artificial intelligence and biology

Ehud Ahissar; Eldad Assa; Neomi Mizrachi; Guy Nelinger; Tchiya Ben-Joseph; Inbar Saraf-Sinik; Shachar Geiger; Alexander Rivkind

doi:10.1016/j.cobeha.2025.101572

Closed-loop perception: gaps between artificial intelligence and biology

Ehud Ahissar, Eldad Assa, Neomi Mizrachi, Guy Nelinger, Tchiya Ben-Joseph, Inbar Saraf-Sinik, Shachar Geiger, Alexander Rivkind

Department of Brain Sciences

Research output: Contribution to journal › Review article › peer-review

Abstract

Biological perception is achieved via brain–world interactions, predominantly implemented within closed-loop systems that integrate sensory inputs and the motor actions used to acquire them. In contrast, current developments of artificial perception primarily exploit open-loop configurations. Lacking this dynamic interplay, artificial intelligence (AI) remains limited in interpreting real-world data. Here, we review the fundamental gaps between biological perception, as revealed through neuroscience research, and artificial perception, as currently implemented in AI systems. We conclude with two major recommendations for advancing AI: adopting event-based processing and integrating closed-loop architectures.

Original language	English
Article number	101572
Number of pages	7
Journal	Current Opinion in Behavioral Sciences
Volume	65
DOIs	https://doi.org/10.1016/j.cobeha.2025.101572
Publication status	Published - Oct 2025

Funding

This project has received funding from the European Research Council (ERC) under the EU Horizon 2020 Research and Innovation Programme (grant No. 786949 ), the United States-Israel Binational Science Foundation (BSF, grant No. 2021327 ), the Israel Science Foundation (ISF, grant No. 2237/20 ), the Weizmann-UK Collaboration Grant, the USA Air Force Office of Scientific Research (AFOSR, grant No. FA9550-22-1-0346 ), the MBZUAI-WIS Joint Program for AI Research, and a research grant from the Estate of Thomas Gruen .

All Science Journal Classification (ASJC) codes

Cognitive Neuroscience
Psychiatry and Mental health
Behavioral Neuroscience

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10.1016/j.cobeha.2025.101572Licence: CC BY

Cite this

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title = "Closed-loop perception: gaps between artificial intelligence and biology",

abstract = "Biological perception is achieved via brain–world interactions, predominantly implemented within closed-loop systems that integrate sensory inputs and the motor actions used to acquire them. In contrast, current developments of artificial perception primarily exploit open-loop configurations. Lacking this dynamic interplay, artificial intelligence (AI) remains limited in interpreting real-world data. Here, we review the fundamental gaps between biological perception, as revealed through neuroscience research, and artificial perception, as currently implemented in AI systems. We conclude with two major recommendations for advancing AI: adopting event-based processing and integrating closed-loop architectures.",

author = "Ehud Ahissar and Eldad Assa and Neomi Mizrachi and Guy Nelinger and Tchiya Ben-Joseph and Inbar Saraf-Sinik and Shachar Geiger and Alexander Rivkind",

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T2 - gaps between artificial intelligence and biology

AU - Ahissar, Ehud

AU - Assa, Eldad

AU - Mizrachi, Neomi

AU - Nelinger, Guy

AU - Ben-Joseph, Tchiya

AU - Saraf-Sinik, Inbar

AU - Geiger, Shachar

AU - Rivkind, Alexander

PY - 2025/10

Y1 - 2025/10

N2 - Biological perception is achieved via brain–world interactions, predominantly implemented within closed-loop systems that integrate sensory inputs and the motor actions used to acquire them. In contrast, current developments of artificial perception primarily exploit open-loop configurations. Lacking this dynamic interplay, artificial intelligence (AI) remains limited in interpreting real-world data. Here, we review the fundamental gaps between biological perception, as revealed through neuroscience research, and artificial perception, as currently implemented in AI systems. We conclude with two major recommendations for advancing AI: adopting event-based processing and integrating closed-loop architectures.

AB - Biological perception is achieved via brain–world interactions, predominantly implemented within closed-loop systems that integrate sensory inputs and the motor actions used to acquire them. In contrast, current developments of artificial perception primarily exploit open-loop configurations. Lacking this dynamic interplay, artificial intelligence (AI) remains limited in interpreting real-world data. Here, we review the fundamental gaps between biological perception, as revealed through neuroscience research, and artificial perception, as currently implemented in AI systems. We conclude with two major recommendations for advancing AI: adopting event-based processing and integrating closed-loop architectures.

UR - https://www.scopus.com/pages/publications/105010458538

U2 - 10.1016/j.cobeha.2025.101572

DO - 10.1016/j.cobeha.2025.101572

M3 - Review article

AN - SCOPUS:105010458538

SN - 2352-1546

VL - 65

JO - Current Opinion in Behavioral Sciences

JF - Current Opinion in Behavioral Sciences

M1 - 101572

ER -

Closed-loop perception: gaps between artificial intelligence and biology

Abstract

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