Trajectories through semantic spaces in schizophrenia and the relationship to ripple bursts

Edited by György Buzsáki, New York University Grossman School of Medicine, New York, NY; received March 31, 2023; accepted July 31, 2023
October 10, 2023
120 (42) e2305290120

Significance

Schizophrenia is a debilitating neuropsychiatric disorder whose core clinical features are thought to reflect abnormalities in internal conceptual representations (“cognitive maps”). The current work provides a language-based computational assay of conceptual disorganization in schizophrenia and relates this to neural signatures of cognitive map representation measured using magnetoencephalography (MEG). At a behavioral level, patients with schizophrenia showed reduced semantically guided word sampling during a verbal fluency task (a marker of “looser” conceptual organization). At a neural level, between-participant variance in this effect correlated with the strength of an MEG signature of hippocampal ripple power (measured in a separate task), known to be involved in cognitive map stabilization. These findings shed light on the neural basis of semantic representation in schizophrenia.

Abstract

Human cognition is underpinned by structured internal representations that encode relationships between entities in the world (cognitive maps). Clinical features of schizophrenia—from thought disorder to delusions—are proposed to reflect disorganization in such conceptual representations. Schizophrenia is also linked to abnormalities in neural processes that support cognitive map representations, including hippocampal replay and high-frequency ripple oscillations. Here, we report a computational assay of semantically guided conceptual sampling and exploit this to test a hypothesis that people with schizophrenia (PScz) exhibit abnormalities in semantically guided cognition that relate to hippocampal replay and ripples. Fifty-two participants [26 PScz (13 unmedicated) and 26 age-, gender-, and intelligence quotient (IQ)-matched nonclinical controls] completed a category- and letter-verbal fluency task, followed by a magnetoencephalography (MEG) scan involving a separate sequence-learning task. We used a pretrained word embedding model of semantic similarity, coupled to a computational model of word selection, to quantify the degree to which each participant’s verbal behavior was guided by semantic similarity. Using MEG, we indexed neural replay and ripple power in a post-task rest session. Across all participants, word selection was strongly influenced by semantic similarity. The strength of this influence showed sensitivity to task demands (category > letter fluency) and predicted performance. In line with our hypothesis, the influence of semantic similarity on behavior was reduced in schizophrenia relative to controls, predicted negative psychotic symptoms, and correlated with an MEG signature of hippocampal ripple power (but not replay). The findings bridge a gap between phenomenological and neurocomputational accounts of schizophrenia.

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Data, Materials, and Software Availability

Analysis code and data to reproduce the results in the paper will be made available at github.com/matthewnour/verbal_fluency_trajectories and github.com/YunzheLiu/TDLM. The manuscript additionally relates behavioral measures to MEG data originally presented in a previous study: (11).

Acknowledgments

We thank Dr. Atheeshaan Arumuham (King’s College London) for help with patient recruitment, and Professor Zeb Kurth-Nelson (DeepMind) for discussions on task design and analysis methods.

Author contributions

M.M.N. and R.J.D. designed research; M.M.N. performed research; M.M.N., D.C.M., and Y.L. contributed new reagents/analytic tools; M.M.N. analyzed data; and M.M.N. and R.J.D. wrote the paper.

Competing interests

The authors declare no competing interest.

Supporting Information

Appendix 01 (PDF)

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Information & Authors

Information

Published in

The cover image for PNAS Vol.120; No.42
Proceedings of the National Academy of Sciences
Vol. 120 | No. 42
October 17, 2023
PubMed: 37816054

Classifications

Data, Materials, and Software Availability

Analysis code and data to reproduce the results in the paper will be made available at github.com/matthewnour/verbal_fluency_trajectories and github.com/YunzheLiu/TDLM. The manuscript additionally relates behavioral measures to MEG data originally presented in a previous study: (11).

Submission history

Received: March 31, 2023
Accepted: July 31, 2023
Published online: October 10, 2023
Published in issue: October 17, 2023

Keywords

  1. cognitive map
  2. psychosis
  3. hippocampal replay
  4. sharp wave ripple
  5. natural language processing

Acknowledgments

We thank Dr. Atheeshaan Arumuham (King’s College London) for help with patient recruitment, and Professor Zeb Kurth-Nelson (DeepMind) for discussions on task design and analysis methods.
Author contributions
M.M.N. and R.J.D. designed research; M.M.N. performed research; M.M.N., D.C.M., and Y.L. contributed new reagents/analytic tools; M.M.N. analyzed data; and M.M.N. and R.J.D. wrote the paper.
Competing interests
The authors declare no competing interest.

Notes

This article is a PNAS Direct Submission.

Authors

Affiliations

Department of Psychiatry, University of Oxford, Oxford OX3 7JX, United Kingdom
Max Planck University College London Centre for Computational Psychiatry and Ageing Research, London WC1B 5EH, United Kingdom
Daniel C. McNamee
Champalimaud Research, Centre for the Unknown, 1400-038 Lisbon, Portugal
State Key Laboratory of Cognitive Neuroscience and Learning, IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing 100875, China
Chinese Institute for Brain Research, Beijing 102206, China
Max Planck University College London Centre for Computational Psychiatry and Ageing Research, London WC1B 5EH, United Kingdom
State Key Laboratory of Cognitive Neuroscience and Learning, IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing 100875, China
Wellcome Centre for Human Neuroimaging, University College London, London WC1N 3AR, United Kingdom

Notes

1
To whom correspondence may be addressed. Email: [email protected].

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    Trajectories through semantic spaces in schizophrenia and the relationship to ripple bursts
    Proceedings of the National Academy of Sciences
    • Vol. 120
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