Evidence map›Paper›PMID 32513554›Full record

ArticleBiological psychiatry. Cognitive neuroscience and neuroimaging2020

Cognitive Control Errors in Nonhuman Primates Resembling Those in Schizophrenia Reflect Opposing Effects of NMDA Receptor Blockade on Causal Interactions Between Cells and Circuits in Prefrontal and Parietal Cortices.

Erich Kummerfeld, Sisi Ma, Rachael K Blackman, Adele L DeNicola, A David Redish, Sophia Vinogradov, David A Crowe, Matthew V Chafee

Abstract read
In one paragraph

Article in Biological psychiatry. Cognitive neuroscience and neuroimaging, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing 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

8 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Effects of Ketamine on Frontoparietal Interactions in a Rule-Based Antisaccade Task in Macaque Monkeys.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2024
    Article
  5. Power Analysis for Causal Discovery.International journal of data science and analytics · 2024
    Article
  6. Article
  7. Review
  8. Article
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.

Erich KummerfeldInstitute for Health Informatics, University of Minnesota, Minneapolis, Minnesota.
Sisi MaInstitute for Health Informatics, University of Minnesota, Minneapolis, Minnesota.
Rachael K BlackmanMedical Scientist Training Program, University of Minnesota, Minneapolis, Minnesota; Department of Neuroscience, University of Minnesota, Minneapolis, Minnesota; Brain Sciences Center, Veterans Administration Medical Center, Minneapolis, Minnesota.
Adele L DeNicolaDepartment of Neuroscience, University of Minnesota, Minneapolis, Minnesota; Brain Sciences Center, Veterans Administration Medical Center, Minneapolis, Minnesota.
A David RedishDepartment of Neuroscience, University of Minnesota, Minneapolis, Minnesota.
Sophia VinogradovDepartment of Psychiatry, University of Minnesota, Minneapolis, Minnesota.
David A CroweDepartment of Biology, Augsburg University, Minneapolis, Minnesota.
Matthew V ChafeeDepartment of Neuroscience, University of Minnesota, Minneapolis, Minnesota; Brain Sciences Center, Veterans Administration Medical Center, Minneapolis, Minnesota. Electronic address: chafe001@umn.edu.

Funding

University of Minnesota Clinical and Translational Science Institute (UMN CTSI)UL1TR002494 · NCATS · UNIVERSITY OF MINNESOTA · PI BLAZAR, BRUCE R, WEISDORF, DANIEL J · 2018 to 2022
$34.9M
Using a computational and network neuroscience framework to study pharmacological manipulations of state representation processes in early psychosisP50MH119569 · NIMH · UNIVERSITY OF MINNESOTA · PI Sophia Vinogradov · 2020 to 2026
$24.5M
MEDICAL SCIENTIST TRAINING PROGRAMT32GM008244 · NIGMS · UNIVERSITY OF MINNESOTA TWIN CITIES · PI SHIMIZU, YOJI · 1988 to 2024
$13.6M
Testing hybrid theories of action-selectionR01MH112688 · NIMH · UNIVERSITY OF MINNESOTA · PI A DAVID REDISH · 2017 to 2026
$5.0M
Interdisciplinary Training Program in Cognitive ScienceT32HD007151 · NICHD · UNIVERSITY OF MINNESOTA TWIN CITIES · PI KERSTEN, DANIEL J · 1985 to 2013
$4.4M
Relating episodic memory and episodic future thinking in hippocampusR01MH080318 · NIMH · UNIVERSITY OF MINNESOTA · PI REDISH, A DAVID · 2008 to 2020
$3.7M
Neuroscience-Guided Cognitive Remediation in Adolescents at Risk for PsychosisR01MH081051 · NIMH · NORTHERN CALIFORNIA INSTITUTE/RES/EDU · PI VINOGRADOV, SOPHIA · 2008 to 2012
$2.4M
Circuit and synaptic basis of cognitive control in monkey prefrontal cortexR01MH107491 · NIMH · UNIVERSITY OF MINNESOTA · PI CHAFEE, MATTHEW V · 2015 to 2019
$1.6M
Prefrontal network dynamics and top-down control of spatial representationR01MH077779 · NIMH · UNIVERSITY OF MINNESOTA · PI CHAFEE, MATTHEW V · 2009 to 2013
$1.4M
Is cognitive training neuroprotective in early psychosis?R21MH110208 · NIMH · UNIVERSITY OF MINNESOTA · PI NAGARAJAN, SRIKANTAN S., VINOGRADOV, SOPHIA · 2017 to 2018
$430k
Cognition Trajectories in Cognitive Training and Early Intervention Treatment Programs in SchizophreniaR03MH117254 · NIMH · UNIVERSITY OF MINNESOTA · PI VINOGRADOV, SOPHIA · 2019 to 2020
$154k
Characterizing thalamocortical prefrontal network dynamics underlying cognitive control in a model of schizophreniaF31MH109238 · NIMH · UNIVERSITY OF MINNESOTA · PI DENICOLA, ADELE LUCIA · 2015 to 2017
$85k
NCATS NIH HHS UL1 TR002494NICHD NIH HHS T32 HD007151NIGMS NIH HHS T32 GM008244NIMH NIH HHS F31 MH109238NIMH NIH HHS P50 MH119569NIMH NIH HHS R01 MH077779NIMH NIH HHS R01 MH080318NIMH NIH HHS R01 MH081051NIMH NIH HHS R01 MH107491NIMH NIH HHS R01 MH112688NIMH NIH HHS R03 MH117254NIMH NIH HHS R21 MH110208
6 · The paper itself

Abstract

backgroundThe causal biology underlying schizophrenia is not well understood, but it is likely to involve a malfunction in how neurons adjust synaptic connections in response to patterns of activity in networks. We examined statistical dependencies between neural signals at the cell, local circuit, and distributed network levels in prefrontal and parietal cortices of monkeys performing a variant of the AX continuous performance task paradigm. We then quantified changes in the pattern of neural interactions across levels of scale following NMDA receptor (NMDAR) blockade and related these changes to a pattern of cognitive control errors closely matching the performance of patients with schizophrenia.

methodsWe recorded the spiking activity of 1762 neurons along with local field potentials at multiple electrode sites in prefrontal and parietal cortices concurrently, and we generated binary time series indicating the presence or absence of spikes in single neurons or local field potential power above or below a threshold. We then applied causal discovery analysis to the time series to detect statistical dependencies between the signals (causal interactions) and compared the pattern of these interactions before and after NMDAR blockade.

resultsGlobal blockade of NMDAR produced distinctive and frequently opposite changes in neural interactions at the cell, local circuit, and network levels in prefrontal and parietal cortices. Cognitive control errors were associated with decreased interactions at the cell level and with opposite changes at the network level in prefrontal and parietal cortices.

conclusionsNMDAR synaptic deficits change causal interactions between neural signals at different levels of scale that correlate with schizophrenia-like deficits in cognitive control.

Indexed as

SchizophreniaAnimalsCognitionHumansMacaca mulattaMaleParietal LobePrefrontal CortexReceptors, N-Methyl-D-AspartateUnited StatesReceptors, N-Methyl-D-AspartateAX-CPTCausal modelingCognitive controlNeural dynamicsNMDAPrimateSchizophrenia

Identifiers

PMID32513554
PMCPMC7874848

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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.