Evidence map›Paper›PMID 40044672›Full record

ArticleSchizophrenia (Heidelberg, Germany)2025

Weaker top-down cognitive control and stronger bottom-up signaling transmission as a pathogenesis of schizophrenia.

Xiaodan Lyu, Tiantian Liu, Yunxiao Ma, Li Wang, Jinglong Wu, Tianyi Yan, Miaomiao Liu, Jiajia Yang

Abstract read
In one paragraph

Article in Schizophrenia (Heidelberg, Germany), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed, 1 pooled it
–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

5 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Region- and Layer-Specific Glutamatergic Synapse Development in the Nascent Cortical Hierarchy.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2026
    Article
  3. Article
  4. Article
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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

8 authors.

Xiaodan LyuCognitive Neuroscience Lab, Graduate School of Interdisciplinary Science and Engineering in Health Systems, Okayama University, Okayama, Japan.ORCID http://orcid.org/0000-0003-3102-1528
Tiantian LiuSchool of Medical Technology, Beijing Institute of Technology, Beijing, China.ORCID http://orcid.org/0000-0001-5384-0642
Yunxiao MaSchool of Medical Technology, Beijing Institute of Technology, Beijing, China.ORCID http://orcid.org/0009-0006-2874-9410
Li WangSchool of Medical Technology, Beijing Institute of Technology, Beijing, China.
Jinglong WuCognitive Neuroscience Lab, Graduate School of Interdisciplinary Science and Engineering in Health Systems, Okayama University, Okayama, Japan.ORCID http://orcid.org/0000-0002-6330-8235
Tianyi YanSchool of Medical Technology, Beijing Institute of Technology, Beijing, China. yantianyi@bit.edu.cn.ORCID http://orcid.org/0000-0002-2674-4134
Miaomiao LiuSchool of Psychology, Shenzhen University, Shenzhen, China. liumm@szu.edu.cn.
Jiajia YangCognitive Neuroscience Lab, Graduate School of Interdisciplinary Science and Engineering in Health Systems, Okayama University, Okayama, Japan. yang@okayama-u.ac.jp.ORCID http://orcid.org/0000-0001-7521-9814

Funding

China Postdoctoral Science Foundation 2023TQ0027, 2024M754099National Natural Science Foundation of China (National Science Foundation of China) 62206181National Natural Science Foundation of China (National Science Foundation of China) 62373056National Natural Science Foundation of China (National Science Foundation of China) U20A20191, 62336002
6 · The paper itself

Abstract

The clinical symptoms of schizophrenia are highly heterogeneous, with the most striking symptoms being cognitive deficits and perceptual disturbances. Cognitive deficits are typically linked to abnormalities in top-down mechanisms, whereas perceptual disturbances stem from dysfunctions in bottom-up processing. However, it remains unclear whether schizophrenia is primarily driven by top-down control mechanisms, bottom-up perceptual processes, or their interaction. We hypothesized that abnormal top-down and bottom-up interactions constitute the neural mechanisms of schizophrenia. Considering that autoencoders can identify hidden data features and support vector machines are capable of automatically locating the classification hyperplane, we developed an improved stacked autoencoder-support vector machine (ISAE-SVM) model for diagnosing schizophrenia based on resting-state functional magnetic resonance imaging data. A permutation test was used to identify the 213 most discriminative functional connections from the model's output features. Functional connections linking regions of higher cognitive functions and lower perceptual tasks were extracted to further examine their relevance to clinical symptoms. Finally, spectral dynamic causal modeling (sDCM) was used to analyze the dynamic causal interaction between brain regions corresponding to these functional connections. Our results showed that the ISAE-SVM model achieved an average classification accuracy of 82%. Notably, five resting-state functional connections spanning both cognitive and sensory brain areas were significantly correlated with Positive and Negative Syndrome Scale scores. Furthermore, sDCM analysis revealed weakened top-down regulation and enhanced bottom-up signaling in schizophrenia. These findings support our hypothesis that impaired top-down regulation and enhanced bottom-up signaling contribute to the neural mechanisms of schizophrenia.

Identifiers

PMID40044672
PMCPMC11883009

What Socratic holds

Textmetadata
LicenceCC BY-NC-ND
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 Socratic graph.