Evidence map›Paper›PMID 40900765›Full record

ArticleFrontiers in neural circuits2025

Non-negative connectivity causes bow-tie architecture in neural circuits.

Zhaofan Liu, CongCong Du, KongFatt Wong-Lin, Da-Hui Wang

Abstract read
In one paragraph

Article in Frontiers in neural circuits, 2025. 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

4 authors.

Zhaofan LiuPeking University HuiLongGuan Clinical Medical School, Beijing Huilongguan Hospital, Beijing, China.
CongCong DuSchool of Systems Science, Beijing Normal University, Beijing, China.
KongFatt Wong-LinIntelligent Systems Research Centre, School of Computing, Engineering and Intelligent Systems, Ulster University, Londonderry, United Kingdom.
Da-Hui WangSchool of Systems Science, Beijing Normal University, Beijing, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Bow-tie architecture (BTA) is widely observed in biological neural systems, yet the underlying mechanism driving its spontaneous emergence remains unclear. In this study, we identify a novel formation mechanism by training multi-layer neural networks under biologically inspired non-negative connectivity constraints across diverse classification tasks. We show that non-negative weights reshape network dynamics by amplifying back-propagated error signals and suppressing hidden-layer activity, leading to the self-organization of BTA without pre-defined architecture. To our knowledge, this is the first demonstration that non-negativity alone can induce BTA formation. The resulting architecture confers distinct functional advantages, including lower wiring cost, robustness to scaling, and task generalizability, highlighting both its computational efficiency and biological relevance. Our findings offer a mechanistic account of BTA emergence and bridge biological structure with artificial learning principles.

Indexed as

Models, NeurologicalNerve NetNeural Networks, ComputerAnimalsHumansbackpropagation algorithmbow-tie architecturecomputational neurosciencediscrimination tasksefficiencyneural circuitsnon-negative connectivityrobustness

Identifiers

PMID40900765
PMCPMC12399558

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.