Evidence map›Paper›PMID 42846959›Full record

ReviewFundamental research2026

Dual-brain fusion: Bidirectional empowerment between human brain and brain-inspired systems.

Ziyu Li, Qing Li, Xiuxing Li, Zhuo Wang, Xia Wu

Abstract readReview
In one paragraph

Review in Fundamental research, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

5 authors.

Ziyu LiSchool of Computer Science & Technology, Beijing Institute of Technology, Beijing 100081, China.
Qing LiSchool of Computer Science & Technology, Beijing Institute of Technology, Beijing 100081, China.
Xiuxing LiSchool of Computer Science & Technology, Beijing Institute of Technology, Beijing 100081, China.
Zhuo WangSchool of Computer Science & Technology, Beijing Institute of Technology, Beijing 100081, China.
Xia WuSchool of Computer Science & Technology, Beijing Institute of Technology, Beijing 100081, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Artificial intelligence (AI) is fundamentally reshaping societal futures, with its transformative applications driving profound, cross-sectoral change. From surgical robots that enhance medical precision and safety to autonomous vehicles that reconfigure transportation ecosystems, AI is accelerating social progress at an unprecedented pace and scale. Yet current AI technologies face persistent foundational challenges: overreliance on static, context-insensitive rules; limited capacity for dynamic, real-world simulation; and representation models that lack depth and integrative coherence. These limitations constrain adaptability in non-stationary environments, hinder the emergence of holistic intelligence, and obscure the mechanistic essence of true intelligence, constituting a critical barrier to artificial general intelligence (AGI). Dual-Brain Fusion, the deep, bidirectional synergy between the human brain and brain-inspired systems, represents the essential pathway to overcoming this barrier. As nature's most sophisticated intelligent system, the human brain offers fundamental insights for brain-inspired research through its capacities for multimodal perception, adaptive cognition, and goal-directed decision-making. Although existing research has advanced perception optimization, cognitive enhancement, and decision-making improvement, it remains constrained by a single-layer simulation paradigm of brain functions, incomplete understanding of neural functional mechanisms, and the absence of engineered bidirectional interaction between the two systems. To address these challenges, this paper proposes leveraging the human brain's perceptual, cognitive, and decision-making functional mechanisms as a unifying bridge, breaking down interdisciplinary barriers to construct a full-chain collaborative innovation paradigm centered on Dual-Brain Fusion, which enables mutual inspiration between the human brain and brain-inspired systems. Within this framework, brain-inspired systems are optimized using principles derived from human brain mechanisms, while empirical feedback from these systems informs refined analysis of brain functional mechanisms, establishing a closed loop of bidirectional empowerment. Looking ahead, the continued advancement of Dual-Brain Fusion will catalyze an intelligence leap grounded in brain functional mechanisms. This paradigm, anchored in brain mechanisms as a source of principled inspiration, drives AI breakthroughs at the level of intelligence itself, unlocks synergistic human-machine co-adaptation, and charts a developmental path toward human-machine symbiosis and co-evolution.

Indexed as

Artificial intelligenceBrain functional mechanismsBrain-inspired systemsFull-chain collaborationIntelligent leap

Identifiers

PMID42846959
PMCPMC13644476

What OpenQuestion holds

Textmetadata
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.