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Dor A, Harrison C, Irani SR, Al-Diwani A, Grogan J, Manohar S. N-Methyl-D-Aspartate Receptor-Antibody Encephalitis Impairs Maintenance of Attention to Items in Working Memory. J Neurosci 2024; 44:e1500232024. [PMID: 38830760 PMCID: PMC11236588 DOI: 10.1523/jneurosci.1500-23.2024] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/07/2023] [Revised: 04/23/2024] [Accepted: 04/28/2024] [Indexed: 06/05/2024] Open
Abstract
NMDA receptors (NMDARs) may be crucial to working memory (WM). Computational models predict that they sustain neural firing and produce associative memory, which may underpin maintaining and binding information, respectively. We test this in patients with antibodies to NMDAR (n = 10, female) and compare them with healthy control participants (n = 55, 20 male, 35 female). Patients were tested after recovery with a task that separates two aspects of WM: sustaining attention and feature binding. Participants had to remember two colored arrows. Then attention was directed to one of them. After a variable delay, they reported the direction of either the same arrow (congruent cue) or of the other arrow (incongruent cue). We asked how congruency affected recall precision and measured types of error. Patients had difficulty in both sustaining attention to an item over time and feature binding. Controls were less precise after longer delays and incongruent cues. In contrast, patients did not benefit from congruent cues at longer delays [group × congruency (long condition); p = 0.041], indicating they could not sustain attention. Additionally, patients reported the wrong item (misbinding errors) more than controls after congruent cues [group × delay (congruent condition), main effect of group; p ≤ 0.001]. Our results suggest NMDARs are critical for both maintaining attention and feature binding.
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Affiliation(s)
- Afrose Dor
- Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford OX3 9DU, United Kingdom
| | - Corin Harrison
- Department of Experimental Psychology, University of Oxford, Oxford OX2 6GG, United Kingdom
| | - Sarosh R Irani
- Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford OX3 9DU, United Kingdom
| | - Adam Al-Diwani
- Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford OX3 9DU, United Kingdom
- Department of Psychiatry, University of Oxford, Oxford OX3 7JX, United Kingdom
| | - John Grogan
- Trinity College Institute of Neuroscience, Trinity College Dublin, Dublin 2, Ireland
| | - Sanjay Manohar
- Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford OX3 9DU, United Kingdom
- Department of Experimental Psychology, University of Oxford, Oxford OX2 6GG, United Kingdom
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2
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Mana L, Schwartz-Pallejà M, Vila-Vidal M, Deco G. Overview on cognitive impairment in psychotic disorders: From impaired microcircuits to dysconnectivity. Schizophr Res 2024; 269:132-143. [PMID: 38788432 DOI: 10.1016/j.schres.2024.05.008] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/15/2024] [Revised: 05/09/2024] [Accepted: 05/13/2024] [Indexed: 05/26/2024]
Abstract
Schizophrenia's cognitive deficits, often overshadowed by positive symptoms, significantly contribute to the disorder's morbidity. Increasing attention highlights these deficits as reflections of neural circuit dysfunction across various cortical regions. Numerous connectivity alterations linked to cognitive symptoms in psychotic disorders have been reported, both at the macroscopic and microscopic level, emphasizing the potential role of plasticity and microcircuits impairment during development and later stages. However, the heterogeneous clinical presentation of cognitive impairment and diverse connectivity findings pose challenges in summarizing them into a cohesive picture. This review aims to synthesize major cognitive alterations, recent insights into network structural and functional connectivity changes and proposed mechanisms and microcircuit alterations underpinning these symptoms, particularly focusing on neurodevelopmental impairment, E/I balance, and sleep disturbances. Finally, we will also comment on some of the most recent and promising therapeutic approaches that aim to target these mechanisms to address cognitive symptoms. Through this comprehensive exploration, we strive to provide an updated and nuanced overview of the multiscale connectivity impairment underlying cognitive impairment in psychotic disorders.
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Affiliation(s)
- L Mana
- Center for Brain and Cognition, Computational Neuroscience Group, Department of Information and Communication Technologies, Universitat Pompeu Fabra, Roc Boronat 138, Barcelona 08018, Spain.
| | - M Schwartz-Pallejà
- Center for Brain and Cognition, Computational Neuroscience Group, Department of Information and Communication Technologies, Universitat Pompeu Fabra, Roc Boronat 138, Barcelona 08018, Spain; Department of Experimental and Health Science, Universitat Pompeu Fabra, Roc Boronat 138, Barcelona 08018, Spain; Eurecat, Technology Center of Catalonia, Multimedia Technologies, Barcelona, Spain.
| | - M Vila-Vidal
- Center for Brain and Cognition, Computational Neuroscience Group, Department of Information and Communication Technologies, Universitat Pompeu Fabra, Roc Boronat 138, Barcelona 08018, Spain; Computational Biology and Complex Systems Group, Department of Physics, Universitat Politècnica de Catalunya, Barcelona, Spain.
| | - G Deco
- Center for Brain and Cognition, Computational Neuroscience Group, Department of Information and Communication Technologies, Universitat Pompeu Fabra, Roc Boronat 138, Barcelona 08018, Spain; Institució Catalana de la Recerca i Estudis Avançats (ICREA), Passeig Lluís Companys 23, Barcelona 08010, Spain.
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3
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Monov G, Stein H, Klock L, Gallinat J, Kühn S, Lincoln T, Krkovic K, Murphy PR, Donner TH. Linking Cognitive Integrity to Working Memory Dynamics in the Aging Human Brain. J Neurosci 2024; 44:e1883232024. [PMID: 38760163 PMCID: PMC11211717 DOI: 10.1523/jneurosci.1883-23.2024] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/26/2023] [Revised: 04/13/2024] [Accepted: 04/18/2024] [Indexed: 05/19/2024] Open
Abstract
Aging is accompanied by a decline of working memory, an important cognitive capacity that involves stimulus-selective neural activity that persists after stimulus presentation. Here, we unraveled working memory dynamics in older human adults (male and female) including those diagnosed with mild cognitive impairment (MCI) using a combination of behavioral modeling, neuropsychological assessment, and MEG recordings of brain activity. Younger adults (male and female) were studied with behavioral modeling only. Participants performed a visuospatial delayed match-to-sample task under systematic manipulation of the delay and distance between sample and test stimuli. Their behavior (match/nonmatch decisions) was fit with a computational model permitting the dissociation of noise in the internal operations underlying the working memory performance from a strategic decision threshold. Task accuracy decreased with delay duration and sample/test proximity. When sample/test distances were small, older adults committed more false alarms than younger adults. The computational model explained the participants' behavior well. The model parameters reflecting internal noise (not decision threshold) correlated with the precision of stimulus-selective cortical activity measured with MEG during the delay interval. The model uncovered an increase specifically in working memory noise in older compared with younger participants. Furthermore, in the MCI group, but not in the older healthy controls, internal noise correlated with the participants' clinically assessed cognitive integrity. Our results are consistent with the idea that the stability of working memory contents deteriorates in aging, in a manner that is specifically linked to the overall cognitive integrity of individuals diagnosed with MCI.
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Affiliation(s)
- Gina Monov
- Section of Computational Cognitive Neuroscience, Department of Neurophysiology & Pathophysiology, University Medical Center Hamburg-Eppendorf, Hamburg 20246, Germany
| | - Henrik Stein
- Department of Psychiatry, University Medical Center Hamburg-Eppendorf, Hamburg 20246, Germany
| | - Leonie Klock
- Department of Psychiatry, University Medical Center Hamburg-Eppendorf, Hamburg 20246, Germany
| | - Juergen Gallinat
- Department of Psychiatry, University Medical Center Hamburg-Eppendorf, Hamburg 20246, Germany
| | - Simone Kühn
- Department of Psychiatry, University Medical Center Hamburg-Eppendorf, Hamburg 20246, Germany
| | - Tania Lincoln
- Department of Clinical Psychology and Psychotherapy, Institute of Psychology, University of Hamburg, Hamburg 20146, Germany
| | - Katarina Krkovic
- Department of Clinical Psychology and Psychotherapy, Institute of Psychology, University of Hamburg, Hamburg 20146, Germany
| | - Peter R Murphy
- Section of Computational Cognitive Neuroscience, Department of Neurophysiology & Pathophysiology, University Medical Center Hamburg-Eppendorf, Hamburg 20246, Germany
- Department of Psychology, Maynooth University, Co. Kildare, Ireland
| | - Tobias H Donner
- Section of Computational Cognitive Neuroscience, Department of Neurophysiology & Pathophysiology, University Medical Center Hamburg-Eppendorf, Hamburg 20246, Germany
- Bernstein Center for Computational Neuroscience, Charité Universitätsmedizin, Berlin 10115, Germany
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Yin L, Yu Y, Han F, Wang Q. Unveiling serotonergic dysfunction of obsessive-compulsive disorder on prefrontal network dynamics: a computational perspective. Cereb Cortex 2024; 34:bhae258. [PMID: 38904079 DOI: 10.1093/cercor/bhae258] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/13/2024] [Revised: 05/27/2024] [Accepted: 06/04/2024] [Indexed: 06/22/2024] Open
Abstract
Serotonin (5-HT) regulates working memory within the prefrontal cortex network, which is crucial for understanding obsessive-compulsive disorder. However, the mechanisms how network dynamics and serotonin interact in obsessive-compulsive disorder remain elusive. Here, we incorporate 5-HT receptors (5-HT1A, 5-HT2A) and dopamine receptors into a multistable prefrontal cortex network model, replicating the experimentally observed inverted U-curve phenomenon. We show how the two 5-HT receptors antagonize neuronal activity and modulate network multistability. Reduced binding of 5-HT1A receptors increases global firing, while reduced binding of 5-HT2A receptors deepens attractors. The obtained results suggest reward-dependent synaptic plasticity mechanisms may attenuate 5-HT related network impairments. Integrating serotonin-mediated dopamine release into circuit, we observe that decreased serotonin concentration triggers the network into a deep attractor state, expanding the domain of attraction of stable nodes with high firing rate, potentially causing aberrant reverse learning. This suggests a hypothesis wherein elevated dopamine concentrations in obsessive-compulsive disorder might result from primary deficits in serotonin levels. Findings of this work underscore the pivotal role of serotonergic dysregulation in modulating synaptic plasticity through dopamine pathways, potentially contributing to learned obsessions. Interestingly, serotonin reuptake inhibitors and antidopaminergic potentiators can counteract the over-stable state of high-firing stable points, providing new insights into obsessive-compulsive disorder treatment.
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Affiliation(s)
- Lining Yin
- Department of Dynamics and Control, Beihang University, No. 37 Xueyuan Road, HaiDian District, Beijing 100191, China
| | - Ying Yu
- Department of Dynamics and Control, Beihang University, No. 37 Xueyuan Road, HaiDian District, Beijing 100191, China
| | - Fang Han
- College of Information Science and Technology, Donghua University, No. 2999 Renmin North Road, Songjiang District, Shanghai 201620, China
| | - Qingyun Wang
- Department of Dynamics and Control, Beihang University, No. 37 Xueyuan Road, HaiDian District, Beijing 100191, China
- Ningxia Basic Science Research Center of Mathematics, Ningxia University, No. 217 Wencui North Street, Xixia District, Yinchuan 750021, China
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Daub J, Brandt GA, Volkmer S, Northoff G, Hirjak D. Arthur Schopenhauer: An underappreciated philosopher in psychiatry and his applied epistemology of body and self- experience. Schizophr Res 2024; 267:487-496. [PMID: 38693031 DOI: 10.1016/j.schres.2024.04.019] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/30/2024] [Revised: 04/22/2024] [Accepted: 04/23/2024] [Indexed: 05/03/2024]
Abstract
BACKGROUND Arthur Schopenhauer (1788-1860) was one of the most important thinkers of the 19th century. Although his writings have exerted great influence in many different disciplines, his epistemological concepts and analysis of the body and self-experience were rarely considered in the context of psychiatric research of schizophrenia spectrum disorders (SSD) and depression (MDD). METHODS The method applied for the study of anomalous self and body-experience first consists in the close reading and analysis of Schopenhauer's most influential writings, namely his opus magnus "The World as Will and Representation" and his dissertation "On the Fourfold Root of the Principle of Sufficient Reason". Second, psychopathological and phenomenological aspects of the anomalous body and self, as well as altered space and time experience, are discussed by means of Schopenhauer's philosophy and four patient cases. RESULTS Schopenhauer's insights contribute to contemporary psychiatry by (1) unifying materialistic (neurobiological) and idealistic (subjective) conceptions of psychiatric disorders and improving the awareness of methods in psychiatric research; (2) emphasizing the integral significance of the body as a gateway to the surrounding world and basal self-experience; (3) delineating subjective space and time-experience as crucial dimensions of the conditio humana in SSD and MDD; and (4) demonstrating the feasibility of transferring his theories directly to clinical case vignettes stemming from the daily clinical routine. CONCLUSION Close reading of Schopenhauer's texts might help bridge the gap between different scientific methods in psychiatry and overcome the translational crisis of contemporary psychiatry by unifying neurobiological and subjective approaches to SSD and MDD.
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Affiliation(s)
- Jonas Daub
- Department of Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, University of Heidelberg, Mannheim, Germany; German Centre for Mental Health (DZPG), partner site Mannheim, Germany.
| | - Geva A Brandt
- Department of Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, University of Heidelberg, Mannheim, Germany; German Centre for Mental Health (DZPG), partner site Mannheim, Germany
| | - Sebastian Volkmer
- Department of Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, University of Heidelberg, Mannheim, Germany; German Centre for Mental Health (DZPG), partner site Mannheim, Germany
| | - Georg Northoff
- Mind, Brain Imaging and Neuroethics Research Unit, The Royal's Institute of Mental Health Research, University of Ottawa, Ottawa, ON, Canada
| | - Dusan Hirjak
- Department of Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, University of Heidelberg, Mannheim, Germany; German Centre for Mental Health (DZPG), partner site Mannheim, Germany.
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Powers A, Angelos P, Bond A, Farina E, Fredericks C, Gandhi J, Greenwald M, Hernandez-Busot G, Hosein G, Kelley M, Mourgues C, Palmer W, Rodriguez-Sanchez J, Seabury R, Toribio S, Vin R, Weleff J, Benrimoh D. A computational account of the development and evolution of psychotic symptoms. ARXIV 2024:arXiv:2404.10954v1. [PMID: 38699166 PMCID: PMC11065053] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Download PDF] [Subscribe] [Scholar Register] [Indexed: 05/05/2024]
Abstract
The mechanisms of psychotic symptoms like hallucinations and delusions are often investigated in fully-formed illness, well after symptoms emerge. These investigations have yielded key insights, but are not well-positioned to reveal the dynamic forces underlying symptom formation itself. Understanding symptom development over time would allow us to identify steps in the pathophysiological process leading to psychosis, shifting the focus of psychiatric intervention from symptom alleviation to prevention. We propose a model for understanding the emergence of psychotic symptoms within the context of an adaptive, developing neural system. We will make the case for a pathophysiological process that begins with cortical hyperexcitability and bottom-up noise transmission, which engenders inappropriate belief formation via aberrant prediction error signaling. We will argue that this bottom-up noise drives learning about the (im)precision of new incoming sensory information because of diminished signal-to-noise ratio, causing an adaptive relative over-reliance on prior beliefs. This over-reliance on priors predisposes to hallucinations and covaries with hallucination severity. An over-reliance on priors may also lead to increased conviction in the beliefs generated by bottom-up noise and drive movement toward conversion to psychosis. We will identify predictions of our model at each stage, examine evidence to support or refute those predictions, and propose experiments that could falsify or help select between alternative elements of the overall model. Nesting computational abnormalities within longitudinal development allows us to account for hidden dynamics among the mechanisms driving symptom formation and to view established symptomatology as a point of equilibrium among competing biological forces.
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Affiliation(s)
- Albert Powers
- Yale University School of Medicine and the Connecticut Mental Health Center, New Haven, CT, USA
| | - Philip Angelos
- Yale University School of Medicine and the Connecticut Mental Health Center, New Haven, CT, USA
| | - Alexandria Bond
- Yale University School of Medicine and the Connecticut Mental Health Center, New Haven, CT, USA
| | - Emily Farina
- Yale University School of Medicine and the Connecticut Mental Health Center, New Haven, CT, USA
| | - Carolyn Fredericks
- Yale University School of Medicine and the Connecticut Mental Health Center, New Haven, CT, USA
| | - Jay Gandhi
- Yale University School of Medicine and the Connecticut Mental Health Center, New Haven, CT, USA
| | - Maximillian Greenwald
- Yale University School of Medicine and the Connecticut Mental Health Center, New Haven, CT, USA
| | | | - Gabriel Hosein
- Yale University School of Medicine and the Connecticut Mental Health Center, New Haven, CT, USA
| | - Megan Kelley
- Yale University School of Medicine and the Connecticut Mental Health Center, New Haven, CT, USA
| | - Catalina Mourgues
- Yale University School of Medicine and the Connecticut Mental Health Center, New Haven, CT, USA
| | - William Palmer
- Yale University Department of Psychology, New Haven, CT USA
| | | | - Rashina Seabury
- Yale University School of Medicine and the Connecticut Mental Health Center, New Haven, CT, USA
| | - Silmilly Toribio
- Yale University School of Medicine and the Connecticut Mental Health Center, New Haven, CT, USA
| | - Raina Vin
- Yale University School of Medicine and the Connecticut Mental Health Center, New Haven, CT, USA
| | - Jeremy Weleff
- Yale University School of Medicine and the Connecticut Mental Health Center, New Haven, CT, USA
| | - David Benrimoh
- Department of Psychiatry, McGill University, Montreal, Canada
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Crowe DA, Willow A, Blackman RK, DeNicola AL, Chafee MV, Amirikian B. A prefrontal network model operating near steady and oscillatory states links spike desynchronization and synaptic deficits in schizophrenia. eLife 2024; 13:e79352. [PMID: 38319151 PMCID: PMC10863986 DOI: 10.7554/elife.79352] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/08/2022] [Accepted: 11/24/2023] [Indexed: 02/07/2024] Open
Abstract
Schizophrenia results in part from a failure of prefrontal networks but we lack full understanding of how disruptions at a synaptic level cause failures at the network level. This is a crucial gap in our understanding because it prevents us from discovering how genetic mutations and environmental risks that alter synaptic function cause prefrontal network to fail in schizophrenia. To address that question, we developed a recurrent spiking network model of prefrontal local circuits that can explain the link between NMDAR synaptic and 0-lag spike synchrony deficits we recently observed in a pharmacological monkey model of prefrontal network failure in schizophrenia. We analyze how the balance between AMPA and NMDA components of recurrent excitation and GABA inhibition in the network influence oscillatory spike synchrony to inform the biological data. We show that reducing recurrent NMDAR synaptic currents prevents the network from shifting from a steady to oscillatory state in response to extrinsic inputs such as might occur during behavior. These findings strongly parallel dynamic modulation of 0-lag spike synchrony we observed between neurons in monkey prefrontal cortex during behavior, as well as the suppression of this 0-lag spiking by administration of NMDAR antagonists. As such, our cortical network model provides a plausible mechanism explaining the link between NMDAR synaptic and 0-lag spike synchrony deficits observed in a pharmacological monkey model of prefrontal network failure in schizophrenia.
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Affiliation(s)
- David A Crowe
- Department of Biology, Augsburg UniversityMinneapolisUnited States
| | - Andrew Willow
- Department of Biology, Augsburg UniversityMinneapolisUnited States
| | - Rachael K Blackman
- Department of Neuroscience, University of MinnesotaMinneapolisUnited States
- Medical Scientist Training Program (MD/PhD), University of MinnesotaMinneapolisUnited States
- Brain Sciences Center, VA Medical CenterMinneapolisUnited States
| | - Adele L DeNicola
- Department of Neuroscience, University of MinnesotaMinneapolisUnited States
- Brain Sciences Center, VA Medical CenterMinneapolisUnited States
| | - Matthew V Chafee
- Department of Neuroscience, University of MinnesotaMinneapolisUnited States
- Brain Sciences Center, VA Medical CenterMinneapolisUnited States
- Center for Cognitive Sciences, University of MinnesotaMinneapolisUnited States
| | - Bagrat Amirikian
- Department of Neuroscience, University of MinnesotaMinneapolisUnited States
- Brain Sciences Center, VA Medical CenterMinneapolisUnited States
- Center for Cognitive Sciences, University of MinnesotaMinneapolisUnited States
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Diehl GW, Redish AD. Measuring excitation-inhibition balance through spectral components of local field potentials. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.01.24.577086. [PMID: 38328057 PMCID: PMC10849740 DOI: 10.1101/2024.01.24.577086] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/09/2024]
Abstract
The balance between excitation and inhibition is critical to brain functioning, and dysregulation of this balance is a hallmark of numerous psychiatric conditions. Measuring this excitation-inhibition (E:I) balance in vivo has remained difficult, but theoretical models have proposed that characteristics of local field potentials (LFP) may provide an accurate proxy. To establish a conclusive link between LFP and E:I balance, we recorded single units and LFP from the prefrontal cortex (mPFC) of rats during decision making. Dynamic measures of synaptic coupling strength facilitated direct quantification of E:I balance and revealed a strong inverse relationship to broadband spectral power of LFP. These results provide a critical link between LFP and underlying network properties, opening the door for non-invasive recordings to measure E:I balance in clinical settings.
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Affiliation(s)
- Geoffrey W Diehl
- Department of Neuroscience, University of Minnesota, Minneapolis, MN, United States
| | - A David Redish
- Department of Neuroscience, University of Minnesota, Minneapolis, MN, United States
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Preller KH, Scholpp J, Wunder A, Rosenbrock H. Neuroimaging Biomarkers for Drug Discovery and Development in Schizophrenia. Biol Psychiatry 2024:S0006-3223(24)00036-2. [PMID: 38272287 DOI: 10.1016/j.biopsych.2024.01.009] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/04/2023] [Revised: 12/19/2023] [Accepted: 01/14/2024] [Indexed: 01/27/2024]
Abstract
Schizophrenia is a chronic mental illness that affects up to 1% of the population. While efficacious therapies are available for positive symptoms, effective treatment of cognitive and negative symptoms remains an unmet need after decades of research. New developments in the field of neuroimaging are accelerating our knowledge gain regarding the underlying pathophysiology of symptoms in schizophrenia and psychosis spectrum disorders, inspiring new targets for drug development. However, no validated and qualified biomarkers are currently available to support the development of new therapeutics. This review summarizes the current use of neuroimaging technology in clinical drug development for psychotic disorders. As exemplified by drug development programs that target NMDA receptor hypofunction, neuroimaging results play a critical role in target discovery and establishing target engagement and dose selection. Furthermore, pharmacological neuroimaging may provide response biomarkers that allow for early decision making in proof-of-concept studies that leverage pharmacological challenge models in healthy volunteers. That said, while response and predictive biomarkers are starting to be evaluated in patient populations, they continue to play a limited role. Novel approaches to neuroimaging data acquisition and analysis may aid the establishment of biomarkers that are predictive at the individual level in the future. Nevertheless, various gaps in knowledge need to be addressed and biomarkers need to be validated to establish them as "fit for purpose" in drug development.
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Affiliation(s)
- Katrin H Preller
- Boehringer Ingelheim Pharma GmbH & Co. KG, Biberach an der Riss, Germany; Boehringer Ingelheim (Schweiz) GmbH, Basel, Switzerland.
| | - Joachim Scholpp
- Boehringer Ingelheim Pharma GmbH & Co. KG, Biberach an der Riss, Germany
| | - Andreas Wunder
- Boehringer Ingelheim Pharma GmbH & Co. KG, Biberach an der Riss, Germany
| | - Holger Rosenbrock
- Boehringer Ingelheim Pharma GmbH & Co. KG, Biberach an der Riss, Germany
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10
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Parrella NF, Hill AT, Dipnall LM, Loke YJ, Enticott PG, Ford TC. Inhibitory dysfunction and social processing difficulties in autism: A comprehensive narrative review. J Psychiatr Res 2024; 169:113-125. [PMID: 38016393 DOI: 10.1016/j.jpsychires.2023.11.014] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/13/2023] [Revised: 09/04/2023] [Accepted: 11/15/2023] [Indexed: 11/30/2023]
Abstract
The primary inhibitory neurotransmitter γ-aminobutyric acid (GABA) has a prominent role in regulating neural development and function, with disruption to GABAergic signalling linked to behavioural phenotypes associated with neurodevelopmental disorders, particularly autism. Such neurochemical disruption, likely resulting from diverse genetic and molecular mechanisms, particularly during early development, can subsequently affect the cellular balance of excitation and inhibition in neuronal circuits, which may account for the social processing difficulties observed in autism and related conditions. This comprehensive narrative review integrates diverse streams of research from several disciplines, including molecular neurobiology, genetics, epigenetics, and systems neuroscience. In so doing it aims to elucidate the relevance of inhibitory dysfunction to autism, with specific focus on social processing difficulties that represent a core feature of this disorder. Many of the social processing difficulties experienced in autism have been linked to higher levels of the excitatory neurotransmitter glutamate and/or lower levels of inhibitory GABA. While current therapeutic options for social difficulties in autism are largely limited to behavioural interventions, this review highlights the psychopharmacological studies that explore the utility of GABA modulation in alleviating such difficulties.
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Affiliation(s)
| | - Aron T Hill
- Cognitive Neuroscience Unit, School of Psychology, Deakin University, Geelong, Australia; Department of Psychiatry, Central Clinical School, Monash University, Melbourne, Victoria, Australia
| | - Lillian M Dipnall
- Cognitive Neuroscience Unit, School of Psychology, Deakin University, Geelong, Australia; Early Life Epigenetics Group, Deakin University, Geelong, Australia
| | - Yuk Jing Loke
- Epigenetics Group, Murdoch Children's Research Institute, Melbourne, Victoria, Australia; Department of Paediatrics, The University of Melbourne, Melbourne, Victoria, Australia
| | - Peter G Enticott
- Cognitive Neuroscience Unit, School of Psychology, Deakin University, Geelong, Australia
| | - Talitha C Ford
- Cognitive Neuroscience Unit, School of Psychology, Deakin University, Geelong, Australia; Centre for Human Psychopharmacology, Faculty of Health, Arts and Design, Swinburne University of Technology, Melbourne, Victoria, Australia
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11
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Bansal S, Bae GY, Robinson BM, Dutterer J, Hahn B, Luck SJ, Gold JM. Qualitatively Different Delay-Dependent Working Memory Distortions in People With Schizophrenia and Healthy Control Participants. BIOLOGICAL PSYCHIATRY. COGNITIVE NEUROSCIENCE AND NEUROIMAGING 2023; 8:1218-1227. [PMID: 37459911 PMCID: PMC10792108 DOI: 10.1016/j.bpsc.2023.07.004] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/30/2023] [Revised: 06/30/2023] [Accepted: 07/08/2023] [Indexed: 07/28/2023]
Abstract
BACKGROUND Impairments in working memory (WM) have been well documented in people with schizophrenia (PSZ). However, these quantitative WM impairments can often be explained by nonspecific factors, such as impaired goal maintenance. Here, we used a spatial orientation delayed response task to explore a qualitative difference in WM dynamics between PSZ and healthy control participants (HCs). More specifically, we took advantage of the discovery that WM representations may drift either toward or away from previous trial targets (serial dependence). We tested the hypothesis that WM representations would drift toward the previous trial target in HCs but away from the previous trial target in PSZ. METHODS We assessed serial dependence in PSZ (n = 31) and HCs (n = 25) using orientation as the to-be-remembered feature and memory delays lasting from 0 to 8 seconds. Participants were asked to remember the orientation of a teardrop-shaped object and reproduce the orientation after a delay period of varying length. RESULTS Consistent with prior studies, we found that current trial memory representations were less precise in PSZ than in HCs. We also found that WM for the current trial orientation drifted toward the previous trial orientation in HCs (representational attraction) but drifted away from the previous trial orientation in PSZ (representational repulsion). CONCLUSIONS These results demonstrate a qualitative difference in WM dynamics between PSZ and HCs that cannot be easily explained by nuisance factors such as reduced effort. Most computational neuroscience models also fail to explain these results because they maintain information solely by means of sustained neural firing, which does not extend across trials. The results suggest a fundamental difference between PSZ and HCs in longer-term memory mechanisms that persist across trials, such as short-term potentiation and neuronal adaptation.
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Affiliation(s)
- Sonia Bansal
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland, School of Medicine, Baltimore, Maryland.
| | - Gi-Yeul Bae
- Department of Psychology, Arizona State University, Tempe, Arizona
| | - Benjamin M Robinson
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland, School of Medicine, Baltimore, Maryland
| | - Jenna Dutterer
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland, School of Medicine, Baltimore, Maryland
| | - Britta Hahn
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland, School of Medicine, Baltimore, Maryland
| | - Steven J Luck
- Center for Mind & Brain and Department of Psychology, University of California, Davis, Davis, California
| | - James M Gold
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland, School of Medicine, Baltimore, Maryland
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12
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Mount RA, Athif M, O’Connor M, Saligrama A, Tseng HA, Sridhar S, Zhou C, Bortz E, San Antonio E, Kramer MA, Man HY, Han X. The autism spectrum disorder risk gene NEXMIF over-synchronizes hippocampal CA1 network and alters neuronal coding. Front Neurosci 2023; 17:1277501. [PMID: 37965217 PMCID: PMC10641898 DOI: 10.3389/fnins.2023.1277501] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/14/2023] [Accepted: 10/10/2023] [Indexed: 11/16/2023] Open
Abstract
Mutations in autism spectrum disorder (ASD) risk genes disrupt neural network dynamics that ultimately lead to abnormal behavior. To understand how ASD-risk genes influence neural circuit computation during behavior, we analyzed the hippocampal network by performing large-scale cellular calcium imaging from hundreds of individual CA1 neurons simultaneously in transgenic mice with total knockout of the X-linked ASD-risk gene NEXMIF (neurite extension and migration factor). As NEXMIF knockout in mice led to profound learning and memory deficits, we examined the CA1 network during voluntary locomotion, a fundamental component of spatial memory. We found that NEXMIF knockout does not alter the overall excitability of individual neurons but exaggerates movement-related neuronal responses. To quantify network functional connectivity changes, we applied closeness centrality analysis from graph theory to our large-scale calcium imaging datasets, in addition to using the conventional pairwise correlation analysis. Closeness centrality analysis considers both the number of connections and the connection strength between neurons within a network. We found that in wild-type mice the CA1 network desynchronizes during locomotion, consistent with increased network information coding during active behavior. Upon NEXMIF knockout, CA1 network is over-synchronized regardless of behavioral state and fails to desynchronize during locomotion, highlighting how perturbations in ASD-implicated genes create abnormal network synchronization that could contribute to ASD-related behaviors.
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Affiliation(s)
- Rebecca A. Mount
- Department of Biomedical Engineering, Boston University, Boston, MA, United States
| | - Mohamed Athif
- Department of Biomedical Engineering, Boston University, Boston, MA, United States
| | | | - Amith Saligrama
- Department of Biomedical Engineering, Boston University, Boston, MA, United States
- Commonwealth School, Boston, MA, United States
| | - Hua-an Tseng
- Department of Biomedical Engineering, Boston University, Boston, MA, United States
| | - Sudiksha Sridhar
- Department of Biomedical Engineering, Boston University, Boston, MA, United States
| | - Chengqian Zhou
- Department of Biomedical Engineering, Boston University, Boston, MA, United States
| | - Emma Bortz
- Department of Biomedical Engineering, Boston University, Boston, MA, United States
| | - Erynne San Antonio
- Department of Biomedical Engineering, Boston University, Boston, MA, United States
| | - Mark A. Kramer
- Department of Mathematics, Boston University, Boston, MA, United States
| | - Heng-Ye Man
- Department of Biology, Boston University, Boston, MA, United States
| | - Xue Han
- Department of Biomedical Engineering, Boston University, Boston, MA, United States
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13
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Howell AM, Warrington S, Fonteneau C, Cho YT, Sotiropoulos SN, Murray JD, Anticevic A. The spatial extent of anatomical connections within the thalamus varies across the cortical hierarchy in humans and macaques. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.07.22.550168. [PMID: 37546767 PMCID: PMC10401924 DOI: 10.1101/2023.07.22.550168] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 08/08/2023]
Abstract
Each cortical area has a distinct pattern of anatomical connections within the thalamus, a central subcortical structure composed of functionally and structurally distinct nuclei. Previous studies have suggested that certain cortical areas may have more extensive anatomical connections that target multiple thalamic nuclei, which potentially allows them to modulate distributed information flow. However, there is a lack of quantitative investigations into anatomical connectivity patterns within the thalamus. Consequently, it remains unknown if cortical areas exhibit systematic differences in the extent of their anatomical connections within the thalamus. To address this knowledge gap, we used diffusion magnetic resonance imaging (dMRI) to perform brain-wide probabilistic tractography for 828 healthy adults from the Human Connectome Project. We then developed a framework to quantify the spatial extent of each cortical area's anatomical connections within the thalamus. Additionally, we leveraged resting-state functional MRI, cortical myelin, and human neural gene expression data to test if the extent of anatomical connections within the thalamus varied along the cortical hierarchy. Our results revealed two distinct corticothalamic tractography motifs: 1) a sensorimotor cortical motif characterized by focal thalamic connections targeting posterolateral thalamus, associated with fast, feed-forward information flow; and 2) an associative cortical motif characterized by diffuse thalamic connections targeting anteromedial thalamus, associated with slow, feed-back information flow. These findings were consistent across human subjects and were also observed in macaques, indicating cross-species generalizability. Overall, our study demonstrates that sensorimotor and association cortical areas exhibit differences in the spatial extent of their anatomical connections within the thalamus, which may support functionally-distinct cortico-thalamic information flow.
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Affiliation(s)
- Amber M Howell
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT 06511, USA
- Division of Neurocognition, Neurocomputation, & Neurogenetics (N3), Yale University School of Medicine, New Haven, Connecticut, 06511, USA
- Interdepartmental Neuroscience Program, Yale University, New Haven, Connecticut, 06511, USA
| | - Shaun Warrington
- Sir Peter Mansfield Imaging Centre, School of Medicine, University of Nottingham, Nottingham, UK
| | - Clara Fonteneau
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT 06511, USA
- Division of Neurocognition, Neurocomputation, & Neurogenetics (N3), Yale University School of Medicine, New Haven, Connecticut, 06511, USA
| | - Youngsun T Cho
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT 06511, USA
- Division of Neurocognition, Neurocomputation, & Neurogenetics (N3), Yale University School of Medicine, New Haven, Connecticut, 06511, USA
| | - Stamatios N Sotiropoulos
- Sir Peter Mansfield Imaging Centre, School of Medicine, University of Nottingham, Nottingham, UK
- Wellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford, UK
- National Institute for Health Research (NIHR) Nottingham Biomedical Research Centre, Queens Medical Centre, Nottingham, UK
| | - John D Murray
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT 06511, USA
- Division of Neurocognition, Neurocomputation, & Neurogenetics (N3), Yale University School of Medicine, New Haven, Connecticut, 06511, USA
- Interdepartmental Neuroscience Program, Yale University, New Haven, Connecticut, 06511, USA
- Physics, Yale University, New Haven, Connecticut, 06511, USA
| | - Alan Anticevic
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT 06511, USA
- Division of Neurocognition, Neurocomputation, & Neurogenetics (N3), Yale University School of Medicine, New Haven, Connecticut, 06511, USA
- Interdepartmental Neuroscience Program, Yale University, New Haven, Connecticut, 06511, USA
- Department of Psychology, Yale University, New Haven, Connecticut, 06511, USA
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14
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Abbasi S, Wolff A, Çatal Y, Northoff G. Increased noise relates to abnormal excitation-inhibition balance in schizophrenia: a combined empirical and computational study. Cereb Cortex 2023; 33:10477-10491. [PMID: 37562844 PMCID: PMC10560578 DOI: 10.1093/cercor/bhad297] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/29/2023] [Revised: 07/25/2023] [Accepted: 07/26/2023] [Indexed: 08/12/2023] Open
Abstract
Electroencephalography studies link sensory processing issues in schizophrenia to increased noise level-noise here is background spontaneous activity-as measured by the signal-to-noise ratio. The mechanism, however, of such increased noise is unknown. We investigate if this relates to changes in cortical excitation-inhibition balance, which has been observed to be atypical in schizophrenia, by combining electroencephalography and computational modeling. Our electroencephalography task results, for which the local field potentials can be used as a proxy, show lower signal-to-noise ratio due to higher noise in schizophrenia. Both electroencephalography rest and task states exhibit higher levels of excitation in the functional excitation-inhibition (as a proxy of excitation-inhibition balance). This suggests a relationship between increased noise and atypical excitation in schizophrenia, which was addressed by using computational modeling. A Leaky Integrate-and-Fire model was used to simulate the effects of varying degrees of noise on excitation-inhibition balance, local field potential, NMDA current, and . Results show a noise-related increase in the local field potential, excitation in excitation-inhibition balance, pyramidal NMDA current, and spike rate. Mutual information and mediation analysis were used to explore a cross-level relationship, showing that the cortical local field potential plays a key role in transferring the effect of noise to the cellular population level of NMDA.
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Affiliation(s)
- Samira Abbasi
- University of Ottawa, Institute of Mental Health Research, Ottawa ON K1Z 7K4, Canada
- Department of Biomedical Engineering, Hamedan University of Technology, Hamedan 65169-13733, Iran
| | - Annemarie Wolff
- University of Ottawa, Institute of Mental Health Research, Ottawa ON K1Z 7K4, Canada
| | - Yasir Çatal
- University of Ottawa, Institute of Mental Health Research, Ottawa ON K1Z 7K4, Canada
| | - Georg Northoff
- University of Ottawa, Institute of Mental Health Research, Ottawa ON K1Z 7K4, Canada
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15
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Santa C, Rodrigues D, Coelho JF, Anjo SI, Mendes VM, Bessa-Neto D, Dunn MJ, Cotter D, Baltazar G, Monteiro P, Manadas B. Chronic treatment with D2-antagonist haloperidol leads to inhibitory/excitatory imbalance in striatal D1-neurons. Transl Psychiatry 2023; 13:312. [PMID: 37803004 PMCID: PMC10558446 DOI: 10.1038/s41398-023-02609-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/18/2023] [Revised: 09/18/2023] [Accepted: 09/20/2023] [Indexed: 10/08/2023] Open
Abstract
Striatal dysfunction has been implicated in the pathophysiology of schizophrenia, a disorder characterized by positive symptoms such as hallucinations and delusions. Haloperidol is a typical antipsychotic medication used in the treatment of schizophrenia that is known to antagonize dopamine D2 receptors, which are abundantly expressed in the striatum. However, haloperidol's delayed therapeutic effect also suggests a mechanism of action that may go beyond the acute blocking of D2 receptors. Here, we performed proteomic analysis of striatum brain tissue and found more than 400 proteins significantly altered after 30 days of chronic haloperidol treatment in mice, namely proteins involved in glutamatergic and GABAergic synaptic transmission. Cell-type specific electrophysiological recordings further revealed that haloperidol not only reduces the excitability of striatal medium spiny neurons expressing dopamine D2 receptors (D2-MSNs) but also affects D1-MSNs by increasing the ratio of inhibitory/excitatory synaptic transmission (I/E ratio) specifically onto D1-MSNs but not D2-MSNs. Therefore, we propose the slow remodeling of D1-MSNs as a mechanism mediating the delayed therapeutic effect of haloperidol over striatum circuits. Understanding how haloperidol exactly contributes to treating schizophrenia symptoms may help to improve therapeutic outcomes and elucidate the molecular underpinnings of this disorder.
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Affiliation(s)
- Cátia Santa
- CNC-Center for Neuroscience and Cell Biology, University of Coimbra, 3004-504, Coimbra, Portugal
- III - Institute of Interdisciplinary Research, University of Coimbra, 3030-789, Coimbra, Portugal
| | - Diana Rodrigues
- Life and Health Sciences Research Institute (ICVS), School of Medicine, University of Minho, Braga, Portugal
- ICVS/3B's-PT Government Associate Laboratory, Braga/Guimaraes, Portugal
| | - Joana F Coelho
- CNC-Center for Neuroscience and Cell Biology, University of Coimbra, 3004-504, Coimbra, Portugal
- Faculty of Medicine, University of Coimbra, Coimbra, Portugal
| | - Sandra I Anjo
- CNC-Center for Neuroscience and Cell Biology, University of Coimbra, 3004-504, Coimbra, Portugal
| | - Vera M Mendes
- CNC-Center for Neuroscience and Cell Biology, University of Coimbra, 3004-504, Coimbra, Portugal
| | - Diogo Bessa-Neto
- CICS-UBI - Health Sciences Research Centre, University of Beira Interior, Covilhã, Portugal
| | - Michael J Dunn
- Proteome Research Centre, UCD Conway Institute of Biomolecular and Biomedical Research, School of Medicine, and Medical Sciences, University College Dublin, Dublin, Ireland
| | - David Cotter
- RCSI Psychiatry, Royal College of Surgeons in Ireland, Education and Research Centre Beaumont, Dublin, Ireland
| | - Graça Baltazar
- CICS-UBI - Health Sciences Research Centre, University of Beira Interior, Covilhã, Portugal
| | - Patrícia Monteiro
- Life and Health Sciences Research Institute (ICVS), School of Medicine, University of Minho, Braga, Portugal.
- ICVS/3B's-PT Government Associate Laboratory, Braga/Guimaraes, Portugal.
- Department of Biomedicine, Faculty of Medicine, University of Porto, 4200-319, Porto, Portugal.
| | - Bruno Manadas
- CNC-Center for Neuroscience and Cell Biology, University of Coimbra, 3004-504, Coimbra, Portugal.
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16
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Luscher B, Maguire JL, Rudolph U, Sibille E. GABA A receptors as targets for treating affective and cognitive symptoms of depression. Trends Pharmacol Sci 2023; 44:586-600. [PMID: 37543478 PMCID: PMC10511219 DOI: 10.1016/j.tips.2023.06.009] [Citation(s) in RCA: 12] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/12/2023] [Revised: 06/23/2023] [Accepted: 06/23/2023] [Indexed: 08/07/2023]
Abstract
In the past 20 years, our understanding of the pathophysiology of depression has evolved from a focus on an imbalance of monoaminergic neurotransmitters to a multifactorial picture including an improved understanding of the role of glutamatergic excitatory and GABAergic inhibitory neurotransmission. FDA-approved treatments targeting the glutamatergic [esketamine for major depressive disorder (MDD)] and GABAergic (brexanolone for peripartum depression) systems have become available. This review focuses on the GABAA receptor (GABAAR) system as a target for novel antidepressants and discusses the mechanisms by which modulation of δ-containing GABAARs with neuroactive steroids (NASs) or of α5-containing GABAARs results in antidepressant or antidepressant-like actions and discusses clinical data on NASs. Moreover, a potential mechanism by which α5-GABAAR-positive allosteric modulators (PAMs) may improve cognitive deficits in depression is presented.
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Affiliation(s)
- Bernhard Luscher
- Department of Biology, Pennsylvania State University, University Park, PA 16802, USA; Department of Biochemistry and Molecular Biology, Pennsylvania State University, University Park, PA 16802, USA; Department of Psychiatry, Pennsylvania State University, University Park, PA 16802, USA; Penn State Neuroscience Institute, Pennsylvania State University, University Park, PA 16802, USA
| | - Jamie L Maguire
- Department of Neuroscience, Tufts University School of Medicine, Boston, MA 02111, USA
| | - Uwe Rudolph
- Department of Comparative Biosciences, College of Veterinary Medicine, University of Illinois at Urbana-Champaign, Urbana, IL 61802, USA; Carl R. Woese Institute for Genomic Biology, University of Illinois at Urbana-Champaign, Urbana, IL 61802, USA.
| | - Etienne Sibille
- Campbell Family Mental Health Research Institute of the Centre for Addiction and Mental Health, University of Toronto, Toronto, ON, Canada; Department of Psychiatry, University of Toronto, Toronto, ON, Canada; Department of Pharmacology and Toxicology, University of Toronto, Toronto, ON, Canada
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17
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Vinnakota C, Hudson MR, Jones NC, Sundram S, Hill RA. Potential Roles for the GluN2D NMDA Receptor Subunit in Schizophrenia. Int J Mol Sci 2023; 24:11835. [PMID: 37511595 PMCID: PMC10380280 DOI: 10.3390/ijms241411835] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/12/2023] [Revised: 07/19/2023] [Accepted: 07/22/2023] [Indexed: 07/30/2023] Open
Abstract
Glutamate N-methyl-D-aspartate receptor (NMDAR) hypofunction has been proposed to underlie schizophrenia symptoms. This theory arose from the observation that administration of NMDAR antagonists, which are compounds that inhibit NMDAR activity, reproduces behavioural and molecular schizophrenia-like phenotypes, including hallucinations, delusions and cognitive impairments in healthy humans and animal models. However, the role of specific NMDAR subunits in these schizophrenia-relevant phenotypes is largely unknown. Mounting evidence implicates the GluN2D subunit of NMDAR in some of these symptoms and pathology. Firstly, genetic and post-mortem studies show changes in the GluN2D subunit in people with schizophrenia. Secondly, the psychosis-inducing effects of NMDAR antagonists are blunted in GluN2D-knockout mice, suggesting that the GluN2D subunit mediates NMDAR-antagonist-induced psychotomimetic effects. Thirdly, in the mature brain, the GluN2D subunit is relatively enriched in parvalbumin (PV)-containing interneurons, a cell type hypothesized to underlie the cognitive symptoms of schizophrenia. Lastly, the GluN2D subunit is widely and abundantly expressed early in development, which could be of importance considering schizophrenia is a disorder that has its origins in early neurodevelopment. The limitations of currently available therapies warrant further research into novel therapeutic targets such as the GluN2D subunit, which may help us better understand underlying disease mechanisms and develop novel and more effective treatment options.
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Affiliation(s)
- Chitra Vinnakota
- Department of Psychiatry, School of Clinical Sciences, Faculty of Medical, Nursing and Health Sciences, Monash University, Clayton, VIC 3168, Australia
| | - Matthew R Hudson
- Department of Neuroscience, Faculty of Medical, Nursing and Health Sciences, Monash University, Melbourne, VIC 3004, Australia
| | - Nigel C Jones
- Department of Neuroscience, Faculty of Medical, Nursing and Health Sciences, Monash University, Melbourne, VIC 3004, Australia
| | - Suresh Sundram
- Department of Psychiatry, School of Clinical Sciences, Faculty of Medical, Nursing and Health Sciences, Monash University, Clayton, VIC 3168, Australia
- Mental Health Program, Monash Health, Clayton, VIC 3168, Australia
| | - Rachel A Hill
- Department of Psychiatry, School of Clinical Sciences, Faculty of Medical, Nursing and Health Sciences, Monash University, Clayton, VIC 3168, Australia
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18
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Martínez‐Cañada P, Perez‐Valero E, Minguillon J, Pelayo F, López‐Gordo MA, Morillas C. Combining aperiodic 1/f slopes and brain simulation: An EEG/MEG proxy marker of excitation/inhibition imbalance in Alzheimer's disease. ALZHEIMER'S & DEMENTIA (AMSTERDAM, NETHERLANDS) 2023; 15:e12477. [PMID: 37662693 PMCID: PMC10474329 DOI: 10.1002/dad2.12477] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/30/2023] [Revised: 07/27/2023] [Accepted: 08/08/2023] [Indexed: 09/05/2023]
Abstract
INTRODUCTION Accumulation and interaction of amyloid-beta (Aβ) and tau proteins during progression of Alzheimer's disease (AD) are shown to tilt neuronal circuits away from balanced excitation/inhibition (E/I). Current available techniques for noninvasive interrogation of E/I in the intact human brain, for example, magnetic resonance spectroscopy (MRS), are highly restrictive (i.e., limited spatial extent), have low temporal and spatial resolution and suffer from the limited ability to distinguish accurately between different neurotransmitters complicating its interpretation. As such, these methods alone offer an incomplete explanation of E/I. Recently, the aperiodic component of neural power spectrum, often referred to in the literature as the '1/f slope', has been described as a promising and scalable biomarker that can track disruptions in E/I potentially underlying a spectrum of clinical conditions, such as autism, schizophrenia, or epilepsy, as well as developmental E/I changes as seen in aging. METHODS Using 1/f slopes from resting-state spectral data and computational modeling, we developed a new method for inferring E/I alterations in AD. RESULTS We tested our method on recent freely and publicly available electroencephalography (EEG) and magnetoencephalography (MEG) datasets of patients with AD or prodromal disease and demonstrated the method's potential for uncovering regional patterns of abnormal excitatory and inhibitory parameters. DISCUSSION Our results provide a general framework for investigating circuit-level disorders in AD and developing therapeutic interventions that aim to restore the balance between excitation and inhibition.
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Affiliation(s)
- Pablo Martínez‐Cañada
- Department of Computer EngineeringAutomation and RoboticsUniversity of GranadaGranadaSpain
- Research Centre for Information and Communications Technologies (CITIC)University of GranadaGranadaSpain
| | - Eduardo Perez‐Valero
- Department of Computer EngineeringAutomation and RoboticsUniversity of GranadaGranadaSpain
- Research Centre for Information and Communications Technologies (CITIC)University of GranadaGranadaSpain
| | - Jesus Minguillon
- Research Centre for Information and Communications Technologies (CITIC)University of GranadaGranadaSpain
- Department of Signal TheoryTelematics and CommunicationsUniversity of GranadaGranadaSpain
| | - Francisco Pelayo
- Department of Computer EngineeringAutomation and RoboticsUniversity of GranadaGranadaSpain
- Research Centre for Information and Communications Technologies (CITIC)University of GranadaGranadaSpain
| | - Miguel A. López‐Gordo
- Research Centre for Information and Communications Technologies (CITIC)University of GranadaGranadaSpain
- Department of Signal TheoryTelematics and CommunicationsUniversity of GranadaGranadaSpain
| | - Christian Morillas
- Department of Computer EngineeringAutomation and RoboticsUniversity of GranadaGranadaSpain
- Research Centre for Information and Communications Technologies (CITIC)University of GranadaGranadaSpain
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Langdon C, Genkin M, Engel TA. A unifying perspective on neural manifolds and circuits for cognition. Nat Rev Neurosci 2023; 24:363-377. [PMID: 37055616 PMCID: PMC11058347 DOI: 10.1038/s41583-023-00693-x] [Citation(s) in RCA: 19] [Impact Index Per Article: 19.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 03/06/2023] [Indexed: 04/15/2023]
Abstract
Two different perspectives have informed efforts to explain the link between the brain and behaviour. One approach seeks to identify neural circuit elements that carry out specific functions, emphasizing connectivity between neurons as a substrate for neural computations. Another approach centres on neural manifolds - low-dimensional representations of behavioural signals in neural population activity - and suggests that neural computations are realized by emergent dynamics. Although manifolds reveal an interpretable structure in heterogeneous neuronal activity, finding the corresponding structure in connectivity remains a challenge. We highlight examples in which establishing the correspondence between low-dimensional activity and connectivity has been possible, unifying the neural manifold and circuit perspectives. This relationship is conspicuous in systems in which the geometry of neural responses mirrors their spatial layout in the brain, such as the fly navigational system. Furthermore, we describe evidence that, in systems in which neural responses are heterogeneous, the circuit comprises interactions between activity patterns on the manifold via low-rank connectivity. We suggest that unifying the manifold and circuit approaches is important if we are to be able to causally test theories about the neural computations that underlie behaviour.
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Affiliation(s)
- Christopher Langdon
- Princeton Neuroscience Institute, Princeton University, Princeton, NJ, USA
- Cold Spring Harbor Laboratory, Cold Spring Harbor, NY, USA
| | - Mikhail Genkin
- Cold Spring Harbor Laboratory, Cold Spring Harbor, NY, USA
| | - Tatiana A Engel
- Princeton Neuroscience Institute, Princeton University, Princeton, NJ, USA.
- Cold Spring Harbor Laboratory, Cold Spring Harbor, NY, USA.
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20
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McCutcheon RA, Keefe RSE, McGuire PK. Cognitive impairment in schizophrenia: aetiology, pathophysiology, and treatment. Mol Psychiatry 2023; 28:1902-1918. [PMID: 36690793 PMCID: PMC10575791 DOI: 10.1038/s41380-023-01949-9] [Citation(s) in RCA: 50] [Impact Index Per Article: 50.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/19/2022] [Revised: 01/03/2023] [Accepted: 01/06/2023] [Indexed: 01/25/2023]
Abstract
Cognitive deficits are a core feature of schizophrenia, account for much of the impaired functioning associated with the disorder and are not responsive to existing treatments. In this review, we first describe the clinical presentation and natural history of these deficits. We then consider aetiological factors, highlighting how a range of similar genetic and environmental factors are associated with both cognitive function and schizophrenia. We then review the pathophysiological mechanisms thought to underlie cognitive symptoms, including the role of dopamine, cholinergic signalling and the balance between GABAergic interneurons and glutamatergic pyramidal cells. Finally, we review the clinical management of cognitive impairments and candidate novel treatments.
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Affiliation(s)
- Robert A McCutcheon
- Department of Psychiatry, University of Oxford, Oxford, UK.
- Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, London, UK.
- Oxford health NHS Foundation Trust, Oxford health NHS Foundation Trust, Oxford, UK.
| | - Richard S E Keefe
- Departments of Psychiatry and Behavioral Sciences, Duke University Medical Center, Durham, NC, USA
| | - Philip K McGuire
- Department of Psychiatry, University of Oxford, Oxford, UK
- Oxford health NHS Foundation Trust, Oxford health NHS Foundation Trust, Oxford, UK
- NIHR Oxford Health Biomedical Research Centre, Oxford, UK
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21
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Bansal S, Bae GY, Robinson BM, Dutterer J, Hahn B, Luck SJ, Gold JM. Qualitatively different delay-dependent working memory distortions in people with schizophrenia and healthy control subjects. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.04.04.535597. [PMID: 37066149 PMCID: PMC10104073 DOI: 10.1101/2023.04.04.535597] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/18/2023]
Abstract
Background Impairments in working memory(WM) have been well-documented in people with schizophrenia(PSZ). However, these quantitative WM impairments can often be explained by nonspecific factors, such as impaired goal maintenance. Here, we used a spatial orientation delayed-response task to explore a qualitative difference in WM dynamics between PSZ and healthy control subjects(HCS). Specifically, we took advantage of the discovery that WM representations may drift either toward or away from previous-trial targets(serial dependence). We tested the hypothesis that WM representations drift toward the previous-trial target in HCS but away from the previous-trial target in PSZ. Methods We assessed serial dependence in PSZ(N=31) and HCS(N=25), using orientation as the to-be-remembered feature and memory delays from 0 to 8s. Participants were asked to remember the orientation of a teardrop-shaped object and reproduce the orientation after a varying delay period. Results Consistent with prior studies, we found that current-trial memory representations were less precise in PSZ than in HCS. We also found that WM for the current-trial orientation drifted toward the previous-trial orientation in HCS(representational attraction) but drifted away from the previous-trial orientation in PSZ(representational repulsion). Conclusions These results demonstrate a qualitative difference in WM dynamics between PSZ and HCS that cannot easily be explained by nuisance factors such as reduced effort. Most computational neuroscience models also fail to explain these results, because they maintain information solely by means of sustained neural firing, which does not extend across trials. The results suggest a fundamental difference between PSZ and HCS in longer-term memory mechanisms that persist across trials, such as short-term potentiation and neuronal adaptation.
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Affiliation(s)
- Sonia Bansal
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, Maryland
| | - Gi-Yeul Bae
- Department of Psychology, Arizona State University, Tempe, Arizona
| | - Benjamin M Robinson
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, Maryland
| | - Jenna Dutterer
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, Maryland
| | - Britta Hahn
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, Maryland
| | - Steven J Luck
- Center for Mind & Brain and Department of Psychology, University of California, Davis, Davis, California
| | - James M Gold
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, Maryland
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22
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Santarriaga S, Gerlovin K, Layadi Y, Karmacharya R. Human stem cell-based models to study synaptic dysfunction and cognition in schizophrenia: A narrative review. Schizophr Res 2023:S0920-9964(23)00084-1. [PMID: 36925354 PMCID: PMC10500041 DOI: 10.1016/j.schres.2023.02.029] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/21/2022] [Revised: 02/27/2023] [Accepted: 02/28/2023] [Indexed: 03/18/2023]
Abstract
Cognitive impairment is the strongest predictor of functional outcomes in schizophrenia and is hypothesized to result from synaptic dysfunction. However, targeting synaptic plasticity and cognitive deficits in patients remains a significant clinical challenge. A comprehensive understanding of synaptic plasticity and the molecular basis of learning and memory in a disease context can provide specific targets for the development of novel therapeutics targeting cognitive impairments in schizophrenia. Here, we describe the role of synaptic plasticity in cognition, summarize evidence for synaptic dysfunction in schizophrenia and demonstrate the use of patient derived induced-pluripotent stem cells for studying synaptic plasticity in vitro. Lastly, we discuss current advances and future technologies for bridging basic science research of synaptic dysfunction with clinical and translational research that can be used to predict treatment response and develop novel therapeutics.
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Affiliation(s)
- Stephanie Santarriaga
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA; Chemical Biology and Therapeutic Science Program, Broad Institute of MIT and Harvard, Cambridge, MA, USA; Department of Psychiatry, Harvard Medical School, Boston, MA, USA
| | - Kaia Gerlovin
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA; Chemical Biology and Therapeutic Science Program, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Yasmine Layadi
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA; Chimie ParisTech, Université Paris Sciences et Lettres, Paris, France
| | - Rakesh Karmacharya
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA; Chemical Biology and Therapeutic Science Program, Broad Institute of MIT and Harvard, Cambridge, MA, USA; Department of Psychiatry, Harvard Medical School, Boston, MA, USA; Schizophrenia and Bipolar Disorder Program, McLean Hospital, Belmont, MA, USA.
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23
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Driesen NR, Herman P, Rowland MA, Thompson G, Qiu M, He G, Fineberg S, Barron DS, Helgeson L, Lacadie C, Chow R, Gueorguieva R, Straun TC, Krystal JH, Hyder F. Ketamine Effects on Energy Metabolism, Functional Connectivity and Working Memory in Healthy Humans. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.02.21.529425. [PMID: 36865249 PMCID: PMC9980048 DOI: 10.1101/2023.02.21.529425] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/24/2023]
Abstract
Working memory (WM) is a crucial resource for temporary memory storage and the guiding of ongoing behavior. N-methyl-D-aspartate glutamate receptors (NMDARs) are thought to support the neural underpinnings of WM. Ketamine is an NMDAR antagonist that has cognitive and behavioral effects at subanesthetic doses. To shed light on subanesthetic ketamine effects on brain function, we employed a multimodal imaging design, combining gas-free calibrated functional magnetic resonance imaging (fMRI) measurement of oxidative metabolism (CMRO 2 ), resting-state cortical functional connectivity assessed with fMRI, and WM-related fMRI. Healthy subjects participated in two scan sessions in a randomized, double-blind, placebo-controlled design. Ketamine increased CMRO 2 and cerebral blood flow (CBF) in prefrontal cortex (PFC) and other cortical regions. However, resting-state cortical functional connectivity was not affected. Ketamine did not alter CBF-CMRO 2 coupling brain-wide. Higher levels of basal CMRO 2 were associated with lower task-related PFC activation and WM accuracy impairment under both saline and ketamine conditions. These observations suggest that CMRO 2 and resting-state functional connectivity index distinct dimensions of neural activity. Ketamine’s impairment of WM-related neural activity and performance appears to be related to its ability to produce cortical metabolic activation. This work illustrates the utility of direct measurement of CMRO 2 via calibrated fMRI in studies of drugs that potentially affect neurovascular and neurometabolic coupling.
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Using Nonhuman Primate Models to Reverse-Engineer Prefrontal Circuit Failure Underlying Cognitive Deficits in Schizophrenia. Curr Top Behav Neurosci 2023; 63:315-362. [PMID: 36607528 DOI: 10.1007/7854_2022_407] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/07/2023]
Abstract
In this chapter, I review studies in nonhuman primates that emulate the circuit failure in prefrontal cortex responsible for working memory and cognitive control deficits in schizophrenia. These studies have characterized how synaptic malfunction, typically induced by blockade of NMDAR, disrupts neural function and computation in prefrontal networks to explain errors in cognitive tasks that are seen in schizophrenia. This work is finding causal relationships between pathogenic events of relevance to schizophrenia at vastly different levels of scale, from synapses, to neurons, local, circuits, distributed networks, computation, and behavior. Pharmacological manipulation, the dominant approach in primate models, has limited construct validity for schizophrenia pathogenesis, as the disease results from a complex interplay between environmental, developmental, and genetic factors. Genetic manipulation replicating schizophrenia risk is more advanced in rodent models. Nonetheless, gene manipulation in nonhuman primates is rapidly advancing, and primate developmental models have been established. Integration of large scale neural recording, genetic manipulation, and computational modeling in nonhuman primates holds considerable potential to provide a crucial schizophrenia model moving forward. Data generated by this approach is likely to fill several crucial gaps in our understanding of the causal sequence leading to schizophrenia in humans. This causal chain presents a vexing problem largely because it requires understanding how events at very different levels of scale relate to one another, from genes to circuits to cognition to social interactions. Nonhuman primate models excel here. They optimally enable discovery of causal relationships across levels of scale in the brain that are relevant to cognitive deficits in schizophrenia. The mechanistic understanding of prefrontal circuit failure they promise to provide may point the way to more effective therapeutic interventions to restore function to prefrontal networks in the disease.
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25
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Dai Z, Zhang S, Wang H, Chen Z, Zhang W, Hu X, Yao Z, Lu Q. Hampered gamma oscillations induced by sad emotion underlying suicide attempt in major depressive disorder. Psychiatry Clin Neurosci 2023; 77:20-29. [PMID: 36207792 DOI: 10.1111/pcn.13487] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/25/2022] [Revised: 09/18/2022] [Accepted: 09/30/2022] [Indexed: 01/06/2023]
Abstract
AIM Major depressive disorder (MDD) is associated with high suicidality, especially for those with suicide attempt (SA). Although impaired oscillatory activity has been previously reported in patients with SA, little is known about precise temporal-spatial variability of its neural dynamics. To solve this, the current study probed the spectral power and network interactions underlying SA in MDD. METHODS The present study recruited 104 subjects including 56 subjects with MDD (30 with SA and 26 without SA) and 48 healthy controls, who performed sad expressions recognition task during magnetoencephalography (MEG) recording. By investigating source-reconstructed MEG-data, brain states representing different task stages were estimated from a Hidden Markov model. Spectrum power and network connectivity were compared via Gaussian Mixture Models, and fractional occupancy (FO) of states were compared via an independent F-test. RESULTS Brain states were corresponding to various frequencies (theta/beta/low gamma/ high gamma). In low gamma band (35-45 Hz), the early visual state exhibited increased activation and hyper inter-network connectivity between visual regions and the limbic system, while the middle fronto-parietal state exhibited attenuated activation and decreased intra-network connectivity within fronto-parietal regions in SA group. Crucially, FO values of these two states were significantly correlated with the suicide risks. CONCLUSIONS Suicide behavior of patients with MDD was significantly associated with aberrant oscillations in low gamma band. Elevated oscillations in occipital cortices and attenuated oscillations in fronto-parietal cortices were significantly associated with SA. Manifesting sadness indulging and reckless decision-making, the hampered temporal characteristics could help explain the neural-electric basis of SA.
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Affiliation(s)
- Zhongpeng Dai
- School of Biological Sciences & Medical Engineering, Child Development and Learning Science, Key Laboratory of Child Development and Learning Science, Ministry of Education, Research Center for Learning Science, Southeast University, Nanjing, China.,Centre for Human Brain Health, School of Psychology, University of Birmingham, Birmingham, UK
| | - Siqi Zhang
- School of Biological Sciences & Medical Engineering, Child Development and Learning Science, Key Laboratory of Child Development and Learning Science, Ministry of Education, Research Center for Learning Science, Southeast University, Nanjing, China
| | - Huan Wang
- School of Biological Sciences & Medical Engineering, Child Development and Learning Science, Key Laboratory of Child Development and Learning Science, Ministry of Education, Research Center for Learning Science, Southeast University, Nanjing, China
| | - Zhilu Chen
- Nanjing Brain Hospital, Medical School of Nanjing University, Nanjing, China
| | - Wei Zhang
- School of Biological Sciences & Medical Engineering, Child Development and Learning Science, Key Laboratory of Child Development and Learning Science, Ministry of Education, Research Center for Learning Science, Southeast University, Nanjing, China
| | - Xiaowen Hu
- School of Biological Sciences & Medical Engineering, Child Development and Learning Science, Key Laboratory of Child Development and Learning Science, Ministry of Education, Research Center for Learning Science, Southeast University, Nanjing, China
| | - Zhijian Yao
- Nanjing Brain Hospital, Medical School of Nanjing University, Nanjing, China.,Department of Psychiatry, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, China
| | - Qing Lu
- School of Biological Sciences & Medical Engineering, Child Development and Learning Science, Key Laboratory of Child Development and Learning Science, Ministry of Education, Research Center for Learning Science, Southeast University, Nanjing, China
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26
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Vinogradov S, Chafee MV, Lee E, Morishita H. Psychosis spectrum illnesses as disorders of prefrontal critical period plasticity. Neuropsychopharmacology 2023; 48:168-185. [PMID: 36180784 PMCID: PMC9700720 DOI: 10.1038/s41386-022-01451-w] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/29/2022] [Revised: 08/17/2022] [Accepted: 08/21/2022] [Indexed: 01/05/2023]
Abstract
Emerging research on neuroplasticity processes in psychosis spectrum illnesses-from the synaptic to the macrocircuit levels-fill key gaps in our models of pathophysiology and open up important treatment considerations. In this selective narrative review, we focus on three themes, emphasizing alterations in spike-timing dependent and Hebbian plasticity that occur during adolescence, the critical period for prefrontal system development: (1) Experience-dependent dysplasticity in psychosis emerges from activity decorrelation within neuronal ensembles. (2) Plasticity processes operate bidirectionally: deleterious environmental and experiential inputs shape microcircuits. (3) Dysregulated plasticity processes interact across levels of scale and time and include compensatory mechanisms that have pathogenic importance. We present evidence that-given the centrality of progressive dysplastic changes, especially in prefrontal cortex-pharmacologic or neuromodulatory interventions will need to be supplemented by corrective learning experiences for the brain if we are to help people living with these illnesses to fully thrive.
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Affiliation(s)
- Sophia Vinogradov
- Department of Psychiatry & Behavioral Science, University of Minnesota Medical School, Minneapolis, MN, USA.
| | - Matthew V Chafee
- Department of Neuroscience, University of Minnesota Medical School, Minneapolis, MN, USA
| | - Erik Lee
- Masonic Institute for the Developing Brain, University of Minnesota Medical School, Minneapolis, MN, USA
- University of Minnesota Informatics Institute, University of Minnesota, Minneapolis, MN, USA
| | - Hirofumi Morishita
- Department of Psychiatry, Neuroscience, & Ophthalmology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
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27
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Test-retest reliability of prepulse inhibition (PPI) and PPI correlation with working memory. Acta Neuropsychiatr 2022; 34:344-353. [PMID: 35959694 DOI: 10.1017/neu.2022.19] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/07/2022]
Abstract
OBJECTIVE Sensorimotor gating is experimentally operationalized by the prepulse inhibition (PPI) of the startle response (SR). Previous studies suggest high test-retest reliability of PPI and potential correlation with working memory (WM). Here, we aimed to validate and extend the test-retest reliability of PPI in healthy humans and its correlation with WM performance. METHODS We applied an acoustic startle PPI paradigm with four different prepulse intensities (64, 68, 72 and 76 dB) and two different WM tasks [n-back, change detection task (CDT)] in a group of 26 healthy adults (final sample size n = 23). To assess test-retest reliability, we performed all tests on two separate days ~27 days (range: 21-32 days) apart. RESULTS We were able to confirm high test-retest reliability of the PPI with a mean intraclass correlation (ICC) of > 0.80 and significant positive correlation of PPI with n-back but not with CDT performance. Detailed analysis showed that PPI across all prepulse intensities significantly correlated with both the 2-back and 0-back conditions, suggesting regulation by cross-conditional processes (e.g. attention). However, when removing the 0-back component from the 2-back data, we found a specific and significant correlation with WM for the 76-dB PPI condition. CONCLUSION With the present study, we were able to confirm the high test-retest reliability of the PPI in humans and could validate and expand on its correlation with WM performance.
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28
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Zhang M, Sun Y, Saggar M. Cross-attractor repertoire provides new perspective on structure-function relationship in the brain. Neuroimage 2022; 259:119401. [PMID: 35732244 PMCID: PMC9503321 DOI: 10.1016/j.neuroimage.2022.119401] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/04/2022] [Revised: 05/16/2022] [Accepted: 06/17/2022] [Indexed: 11/24/2022] Open
Abstract
The brain exhibits complex intrinsic dynamics, i.e., spontaneously arising activity patterns without any external inputs or tasks. Such intrinsic dynamics and their alteration are thought to play crucial roles in typical as well as atypical cognitive functioning. Linking the ever-changing intrinsic dynamics to the rather static anatomy is a challenging endeavor. Dynamical systems models are important tools for understanding how structure and function are linked in the brain. Here, we provide a novel modeling framework to examine how functional connectivity depends on structural connectivity in the brain. Existing modeling frameworks typically focus on noise-driven (or stochastic) dynamics near a single attractor. Complementing existing approaches, we examine deterministic features of the distribution of attractors, in particular, how regional states are correlated across all attractors - cross-attractor coordination. We found that cross-attractor coordination between brain regions better predicts human functional connectivity than noise-driven single-attractor dynamics. Importantly, cross-attractor coordination better accounts for the nonlinear dependency of functional connectivity on structural connectivity. Our findings suggest that functional connectivity patterns in the brain may reflect transitions between attractors, which impose an energy cost. The framework may be used to predict transitions and energy costs associated with experimental or clinical interventions.
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Affiliation(s)
- Mengsen Zhang
- Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, CA 94304, USA; Department of Psychiatry, University of North Carolina at Chapel Hill, Chapel Hill, NC 27514, USA.
| | - Yinming Sun
- Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, CA 94304, USA
| | - Manish Saggar
- Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, CA 94304, USA.
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29
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Vinogradov S, Hamid AA, Redish AD. Etiopathogenic Models of Psychosis Spectrum Illnesses Must Resolve Four Key Features. Biol Psychiatry 2022; 92:514-522. [PMID: 35931575 PMCID: PMC9809152 DOI: 10.1016/j.biopsych.2022.06.024] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/19/2022] [Revised: 06/22/2022] [Accepted: 06/22/2022] [Indexed: 01/07/2023]
Abstract
Etiopathogenic models for psychosis spectrum illnesses are converging on a number of key processes, such as the influence of specific genes on the synthesis of proteins important in synaptic functioning, alterations in how neurons respond to synaptic inputs and engage in synaptic pruning, and microcircuit dysfunction that leads to more global cortical information processing vulnerabilities. Disruptions in prefrontal operations then accumulate and propagate over time, interacting with environmental factors, developmental processes, and homeostatic mechanisms, eventually resulting in symptoms of psychosis and disability. However, there are 4 key features of psychosis spectrum illnesses that are of primary clinical relevance but have been difficult to assimilate into a single model and have thus far received little direct attention: 1) the bidirectionality of the causal influences for the emergence of psychosis, 2) the catastrophic clinical threshold seen in first episodes of psychosis and why it is irreversible in some individuals, 3) observed biotypes that are neurophysiologically distinct but clinically both convergent and divergent, and 4) a reconciliation of the role of striatal dopaminergic dysfunction with models of prefrontal cortical state instability. In this selective review, we briefly describe these 4 hallmark features and we argue that theoretically driven computational perspectives making use of both algorithmic and neurophysiologic models are needed to reduce this complexity and variability of psychosis spectrum illnesses in a principled manner.
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Affiliation(s)
- Sophia Vinogradov
- Department of Psychiatry & Behavioral Sciences, University of Minnesota Medical School, Minneapolis, Minnesota.
| | - Arif A Hamid
- Department of Neuroscience, University of Minnesota Medical School, Minneapolis, Minnesota
| | - A David Redish
- Department of Neuroscience, University of Minnesota Medical School, Minneapolis, Minnesota
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30
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Perry A, Hughes LE, Adams N, Naessens M, Murley AG, Rouse MA, Street D, Jones PS, Cope TE, Kocagoncu E, Rowe JB. The neurophysiological effect of NMDA-R antagonism of frontotemporal lobar degeneration is conditional on individual GABA concentration. Transl Psychiatry 2022; 12:348. [PMID: 36030249 PMCID: PMC9420128 DOI: 10.1038/s41398-022-02114-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/29/2022] [Revised: 08/09/2022] [Accepted: 08/11/2022] [Indexed: 02/02/2023] Open
Abstract
There is a pressing need to accelerate therapeutic strategies against the syndromes caused by frontotemporal lobar degeneration, including symptomatic treatments. One approach is for experimental medicine, coupling neurophysiological studies of the mechanisms of disease with pharmacological interventions aimed at restoring neurochemical deficits. Here we consider the role of glutamatergic deficits and their potential as targets for treatment. We performed a double-blind placebo-controlled crossover pharmaco-magnetoencephalography study in 20 people with symptomatic frontotemporal lobar degeneration (10 behavioural variant frontotemporal dementia, 10 progressive supranuclear palsy) and 19 healthy age- and gender-matched controls. Both magnetoencephalography sessions recorded a roving auditory oddball paradigm: on placebo or following 10 mg memantine, an uncompetitive NMDA-receptor antagonist. Ultra-high-field magnetic resonance spectroscopy confirmed lower concentrations of GABA in the right inferior frontal gyrus of people with frontotemporal lobar degeneration. While memantine showed a subtle effect on early-auditory processing in patients, there was no significant main effect of memantine on the magnitude of the mismatch negativity (MMN) response in the right frontotemporal cortex in patients or controls. However, the change in the right auditory cortex MMN response to memantine (vs. placebo) in patients correlated with individuals' prefrontal GABA concentration. There was no moderating effect of glutamate concentration or cortical atrophy. This proof-of-concept study demonstrates the potential for baseline dependency in the pharmacological restoration of neurotransmitter deficits to influence cognitive neurophysiology in neurodegenerative disease. With changes to multiple neurotransmitters in frontotemporal lobar degeneration, we suggest that individuals' balance of excitation and inhibition may determine drug efficacy, with implications for drug selection and patient stratification in future clinical trials.
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Affiliation(s)
- Alistair Perry
- MRC Cognition and Brain Sciences Unit, University of Cambridge, Cambridge, CB2 7EF, UK. .,Department of Clinical Neurosciences and Cambridge University Hospitals NHS Trust, University of Cambridge, Cambridge, CB2 0QQ, UK.
| | - Laura E. Hughes
- grid.5335.00000000121885934MRC Cognition and Brain Sciences Unit, University of Cambridge, Cambridge, CB2 7EF UK ,grid.5335.00000000121885934Department of Clinical Neurosciences and Cambridge University Hospitals NHS Trust, University of Cambridge, Cambridge, CB2 0QQ UK
| | - Natalie Adams
- grid.5335.00000000121885934Department of Clinical Neurosciences and Cambridge University Hospitals NHS Trust, University of Cambridge, Cambridge, CB2 0QQ UK
| | - Michelle Naessens
- grid.5335.00000000121885934Department of Clinical Neurosciences and Cambridge University Hospitals NHS Trust, University of Cambridge, Cambridge, CB2 0QQ UK
| | - Alexander G. Murley
- grid.5335.00000000121885934Department of Clinical Neurosciences and Cambridge University Hospitals NHS Trust, University of Cambridge, Cambridge, CB2 0QQ UK
| | - Matthew A. Rouse
- grid.5335.00000000121885934MRC Cognition and Brain Sciences Unit, University of Cambridge, Cambridge, CB2 7EF UK
| | - Duncan Street
- grid.5335.00000000121885934Department of Clinical Neurosciences and Cambridge University Hospitals NHS Trust, University of Cambridge, Cambridge, CB2 0QQ UK
| | - P. Simon Jones
- grid.5335.00000000121885934Department of Clinical Neurosciences and Cambridge University Hospitals NHS Trust, University of Cambridge, Cambridge, CB2 0QQ UK
| | - Thomas E. Cope
- grid.5335.00000000121885934MRC Cognition and Brain Sciences Unit, University of Cambridge, Cambridge, CB2 7EF UK ,grid.5335.00000000121885934Department of Clinical Neurosciences and Cambridge University Hospitals NHS Trust, University of Cambridge, Cambridge, CB2 0QQ UK
| | - Ece Kocagoncu
- grid.5335.00000000121885934MRC Cognition and Brain Sciences Unit, University of Cambridge, Cambridge, CB2 7EF UK ,grid.5335.00000000121885934Department of Clinical Neurosciences and Cambridge University Hospitals NHS Trust, University of Cambridge, Cambridge, CB2 0QQ UK
| | - James B. Rowe
- grid.5335.00000000121885934MRC Cognition and Brain Sciences Unit, University of Cambridge, Cambridge, CB2 7EF UK ,grid.5335.00000000121885934Department of Clinical Neurosciences and Cambridge University Hospitals NHS Trust, University of Cambridge, Cambridge, CB2 0QQ UK
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Abstract
Working memory (WM) refers to the ability to maintain a small number of representations in an activated, easily accessible state for a short period of time in the service of ongoing cognitive processing and behavior. Because WM is a resource critical for multiple forms of complex cognition and executive control of behavior, it is of central interest in the study of disorders such as schizophrenia that involve a broad compromise of cognitive function and in the regulation of goal-directed behavior. There is now robust evidence that WM impairment is characteristic of people with schizophrenia. The impairment includes both elementary storage capacity as well as more complex forms of WM that involve the manipulation and updating of WM representations. These impairments appear to underlie a substantial portion of the generalized cognitive deficit in schizophrenia. Neuroimaging studies have implicated widespread abnormalities in the broad neural system that subserves WM performance, consistent with the evidence of broad cognitive impairment seen in PSZ.
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Affiliation(s)
- James M Gold
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, MD, USA.
| | - Steven J Luck
- Center for Mind & Brain and Department of Psychology, University of California, Davis, CA, USA
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32
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Chen-Engerer HJ, Jaeger S, Bondarenko R, Sprengel R, Hengerer B, Rosenbrock H, Mack V, Schuelert N. Increasing the Excitatory Drive Rescues Excitatory/Inhibitory Imbalance and Mismatch Negativity Deficit Caused by Parvalbumin Specific GluA1 Deletion. Neuroscience 2022; 496:190-204. [PMID: 35750109 DOI: 10.1016/j.neuroscience.2022.06.027] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/28/2022] [Revised: 05/02/2022] [Accepted: 06/15/2022] [Indexed: 11/25/2022]
Abstract
Disturbance in synaptic excitatory and inhibitory (E/I) transmission in the prefrontal cortex is considered a critical factor for cognitive dysfunction, a core symptom in schizophrenia. However, the cortical network pathophysiology induced by E/I imbalance is not well characterized, and an effective therapeutic strategy is lacking. In this study, we simulated imbalanced cortical network by using mice with parvalbumin neuron (PV) specific knockout of GluA1 (AMPA receptor subunit 1) (Gria1-PV KO) as an experimental model. Applying high-content confocal imaging and electrophysiological recordings in the medial prefrontal cortex (mPFC), we found structural and functional alterations in the local network of Gria1-PV KO mice. Additionally, we applied electroencephalography (EEG) to assess potential deficits in mismatch negativity (MMN), the standard readout in the clinic for measuring deviance detection and sensory information processing. Gria1-PV KO animals exhibited abnormal theta oscillation and MMN, which is consistent with clinical findings in cognitively impaired patients. Remarkably, we demonstrated that the glycine transporter 1 (GlyT1) inhibitor, Bitopertin, ameliorates E/I imbalance, hyperexcitability, and sensory processing malfunction in Gria1-PV KO mice. Our results suggest that PV-specific deletion of GluA1 might be an experimental approach for back translating the E/I imbalance observed in schizophrenic patients. Our work offers a systematic workflow to understand the effect of GlyT1 inhibition in restoring cortical network activity from single cells to local brain circuitry. This study highlights that selectively boosting NMDA receptor-mediated excitatory drive to enhance the network inhibitory transmission from interneurons to pyramidal neurons (PYs) is a potential therapeutic strategy for restoring E/I imbalance-associated cognitive-related abnormality.
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Affiliation(s)
- Hsing-Jung Chen-Engerer
- Central Nervous System Disease Research, Boehringer Ingelheim Pharma GmbH & Co. KG, Birkendorferstr. 65, 88397 Biberach Riß, Germany.
| | - Stefan Jaeger
- Central Nervous System Disease Research, Boehringer Ingelheim Pharma GmbH & Co. KG, Birkendorferstr. 65, 88397 Biberach Riß, Germany
| | - Rimma Bondarenko
- Central Nervous System Disease Research, Boehringer Ingelheim Pharma GmbH & Co. KG, Birkendorferstr. 65, 88397 Biberach Riß, Germany
| | - Rolf Sprengel
- Max Planck Institute for Medical Research at the Institute for Anatomy and Cell Biology at Heidelberg University, Germany
| | - Bastian Hengerer
- Central Nervous System Disease Research, Boehringer Ingelheim Pharma GmbH & Co. KG, Birkendorferstr. 65, 88397 Biberach Riß, Germany
| | - Holger Rosenbrock
- Central Nervous System Disease Research, Boehringer Ingelheim Pharma GmbH & Co. KG, Birkendorferstr. 65, 88397 Biberach Riß, Germany
| | - Volker Mack
- CardioMetabolic Disease Research, Boehringer Ingelheim Pharma GmbH & Co. KG, Birkendorferstr. 65, 88397 Biberach Riß, Germany
| | - Niklas Schuelert
- Central Nervous System Disease Research, Boehringer Ingelheim Pharma GmbH & Co. KG, Birkendorferstr. 65, 88397 Biberach Riß, Germany
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Abstract
OBJECTIVE Cognitive impairments in schizophrenia are associated with lower gamma oscillation power in the prefrontal cortex (PFC). Gamma power depends in part on excitatory drive to fast-spiking parvalbumin interneurons (PVIs). Excitatory drive to cortical neurons varies in strength, which could affect how these neurons regulate network oscillations. The authors investigated whether variability in excitatory synaptic strength across PVIs could contribute to lower prefrontal gamma power in schizophrenia. METHODS In postmortem PFC from 20 matched pairs of comparison and schizophrenia subjects, levels of vesicular glutamate transporter 1 (VGlut1) and postsynaptic density 95 (PSD95) proteins were quantified to assess variability in excitatory synaptic strength across PVIs. A computational model network was then used to simulate how variability in excitatory synaptic strength across fast-spiking (a defining feature of PVIs) interneurons (FSIs) regulates gamma power. RESULTS The variability of VGlut1 and PSD95 levels at excitatory inputs across PVIs was larger in schizophrenia relative to comparison subjects. This alteration was not influenced by schizophrenia-associated comorbid factors, was not present in monkeys chronically exposed to antipsychotic medications, and was not present in calretinin interneurons. In the model network, variability in excitatory synaptic strength across FSIs regulated gamma power by affecting network synchrony. Finally, greater synaptic variability interacted synergistically with other synaptic alterations in schizophrenia (i.e., fewer excitatory inputs to FSIs and lower inhibitory strength from FSIs) to robustly reduce gamma power. CONCLUSIONS The study findings suggest that greater variability in excitatory synaptic strength across PVIs, in combination with other modest synaptic alterations in these neurons, can markedly lower PFC gamma power in schizophrenia.
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Affiliation(s)
- Daniel W Chung
- Translational Neuroscience Program, Department of Psychiatry, University of Pittsburgh, Pittsburgh
| | - Matthew A Geramita
- Translational Neuroscience Program, Department of Psychiatry, University of Pittsburgh, Pittsburgh
| | - David A Lewis
- Translational Neuroscience Program, Department of Psychiatry, University of Pittsburgh, Pittsburgh
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34
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Khaleghi A, Mohammadi MR, Shahi K, Nasrabadi AM. Computational Neuroscience Approach to Psychiatry: A Review on Theory-driven Approaches. CLINICAL PSYCHOPHARMACOLOGY AND NEUROSCIENCE 2022; 20:26-36. [PMID: 35078946 PMCID: PMC8813324 DOI: 10.9758/cpn.2022.20.1.26] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/13/2021] [Revised: 06/09/2021] [Accepted: 06/14/2021] [Indexed: 11/21/2022]
Abstract
Translating progress in neuroscience into clinical benefits for patients with psychiatric disorders is challenging because it involves the brain as the most complex organ and its interaction with a complex environment and condition. Dealing with such complexity requires powerful techniques. Computational neuroscience approach to psychiatry integrates multiple levels and types of simulation, analysis and computation according to the different types of computational models to enhance comprehending, prediction and treatment of psychiatric disorder. This approach comprises two approaches: theory-driven and data-driven. In this review, we focus on recent advances in theory-driven approaches that mathematically and mechanistically examine the relationships between disorder-related changes and behavior at different level of brain organization. We discuss recent progresses in computational neuroscience models that relate to psychiatry and show how principles of neural computational modeling can be employed to explain psychopathology.
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Affiliation(s)
- Ali Khaleghi
- Psychiatry and Psychology Research Center, Tehran University of Medical Sciences, Tehran, Iran
| | - Mohammad Reza Mohammadi
- Psychiatry and Psychology Research Center, Tehran University of Medical Sciences, Tehran, Iran
| | - Kian Shahi
- Psychiatry and Psychology Research Center, Tehran University of Medical Sciences, Tehran, Iran
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35
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Yao HK, Guet-McCreight A, Mazza F, Moradi Chameh H, Prevot TD, Griffiths JD, Tripathy SJ, Valiante TA, Sibille E, Hay E. Reduced inhibition in depression impairs stimulus processing in human cortical microcircuits. Cell Rep 2022; 38:110232. [PMID: 35021088 DOI: 10.1016/j.celrep.2021.110232] [Citation(s) in RCA: 17] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/09/2021] [Revised: 10/07/2021] [Accepted: 12/16/2021] [Indexed: 12/01/2022] Open
Abstract
Cortical processing depends on finely tuned excitatory and inhibitory connections in neuronal microcircuits. Reduced inhibition by somatostatin-expressing interneurons is a key component of altered inhibition associated with treatment-resistant major depressive disorder (depression), which is implicated in cognitive deficits and rumination, but the link remains to be better established mechanistically in humans. Here we test the effect of reduced somatostatin interneuron-mediated inhibition on cortical processing in human neuronal microcircuits using a data-driven computational approach. We integrate human cellular, circuit, and gene expression data to generate detailed models of human cortical microcircuits in health and depression. We simulate microcircuit baseline and response activity and find a reduced signal-to-noise ratio and increased false/failed detection of stimuli due to a higher baseline activity in depression. We thus apply models of human cortical microcircuits to demonstrate mechanistically how reduced inhibition impairs cortical processing in depression, providing quantitative links between altered inhibition and cognitive deficits.
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Affiliation(s)
- Heng Kang Yao
- Krembil Centre for Neuroinformatics, Centre for Addiction and Mental Health, Toronto, ON M5T 1R7, Canada; Department of Physiology, University of Toronto, Toronto, ON M5S 1A1, Canada
| | - Alexandre Guet-McCreight
- Krembil Centre for Neuroinformatics, Centre for Addiction and Mental Health, Toronto, ON M5T 1R7, Canada
| | - Frank Mazza
- Krembil Centre for Neuroinformatics, Centre for Addiction and Mental Health, Toronto, ON M5T 1R7, Canada; Department of Physiology, University of Toronto, Toronto, ON M5S 1A1, Canada
| | | | - Thomas D Prevot
- Department of Psychiatry, University of Toronto, Toronto, ON M5S 1A1, Canada; Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, ON M5T 1R7, Canada
| | - John D Griffiths
- Krembil Centre for Neuroinformatics, Centre for Addiction and Mental Health, Toronto, ON M5T 1R7, Canada; Department of Psychiatry, University of Toronto, Toronto, ON M5S 1A1, Canada; Institute of Medical Sciences, University of Toronto, Toronto, ON M5S 1A1, Canada
| | - Shreejoy J Tripathy
- Krembil Centre for Neuroinformatics, Centre for Addiction and Mental Health, Toronto, ON M5T 1R7, Canada; Department of Physiology, University of Toronto, Toronto, ON M5S 1A1, Canada; Department of Psychiatry, University of Toronto, Toronto, ON M5S 1A1, Canada; Institute of Medical Sciences, University of Toronto, Toronto, ON M5S 1A1, Canada
| | - Taufik A Valiante
- Krembil Research Institute, University Health Network, Toronto, ON M5T 0S8, Canada; Institute of Medical Sciences, University of Toronto, Toronto, ON M5S 1A1, Canada; Department of Electrical and Computer Engineering, University of Toronto, Toronto, ON M5S 1A1; Institute of Biomaterials and Biomedical Engineering, University of Toronto, Toronto, ON M5S 1A1, Canada; Department of Surgery, University of Toronto, Toronto, ON M5S 1A1, Canada; Max Planck-University of Toronto Center for Neural Science and Technology, University of Toronto, Toronto, ON M5S 1A1, Canada; Center for Advancing Neurotechnological Innovation to Application, University of Toronto, Toronto, ON M5S 1A1, Canada
| | - Etienne Sibille
- Department of Psychiatry, University of Toronto, Toronto, ON M5S 1A1, Canada; Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, ON M5T 1R7, Canada; Department of Pharmacology & Toxicology, University of Toronto, Toronto, ON M5S 1A1, Canada
| | - Etay Hay
- Krembil Centre for Neuroinformatics, Centre for Addiction and Mental Health, Toronto, ON M5T 1R7, Canada; Department of Physiology, University of Toronto, Toronto, ON M5S 1A1, Canada; Department of Psychiatry, University of Toronto, Toronto, ON M5S 1A1, Canada.
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36
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Griffiths JD, Bastiaens SP, Kaboodvand N. Whole-Brain Modelling: Past, Present, and Future. ADVANCES IN EXPERIMENTAL MEDICINE AND BIOLOGY 2022; 1359:313-355. [DOI: 10.1007/978-3-030-89439-9_13] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/18/2022]
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37
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Fisher VL, Ortiz LS, Powers AR. A computational lens on menopause-associated psychosis. Front Psychiatry 2022; 13:906796. [PMID: 35990063 PMCID: PMC9381820 DOI: 10.3389/fpsyt.2022.906796] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/29/2022] [Accepted: 07/07/2022] [Indexed: 11/21/2022] Open
Abstract
Psychotic episodes are debilitating disease states that can cause extreme distress and impair functioning. There are sex differences that drive the onset of these episodes. One difference is that, in addition to a risk period in adolescence and early adulthood, women approaching the menopause transition experience a second period of risk for new-onset psychosis. One leading hypothesis explaining this menopause-associated psychosis (MAP) is that estrogen decline in menopause removes a protective factor against processes that contribute to psychotic symptoms. However, the neural mechanisms connecting estrogen decline to these symptoms are still not well understood. Using the tools of computational psychiatry, links have been proposed between symptom presentation and potential algorithmic and biological correlates. These models connect changes in signaling with symptom formation by evaluating changes in information processing that are not easily observable (latent states). In this manuscript, we contextualize the observed effects of estrogen (decline) on neural pathways implicated in psychosis. We then propose how estrogen could drive changes in latent states giving rise to cognitive and psychotic symptoms associated with psychosis. Using computational frameworks to inform research in MAP may provide a systematic method for identifying patient-specific pathways driving symptoms and simultaneously refine models describing the pathogenesis of psychosis across all age groups.
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Affiliation(s)
- Victoria L Fisher
- Yale University School of Medicine and the Connecticut Mental Health Center, New Haven, CT, United States
| | - Liara S Ortiz
- Yale University School of Medicine and the Connecticut Mental Health Center, New Haven, CT, United States
| | - Albert R Powers
- Yale University School of Medicine and the Connecticut Mental Health Center, New Haven, CT, United States
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Predictive Feedback, Early Sensory Representations, and Fast Responses to Predicted Stimuli Depend on NMDA Receptors. J Neurosci 2021; 41:10130-10147. [PMID: 34732525 DOI: 10.1523/jneurosci.1311-21.2021] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/24/2021] [Revised: 09/23/2021] [Accepted: 10/25/2021] [Indexed: 01/03/2023] Open
Abstract
Learned associations between stimuli allow us to model the world and make predictions, crucial for efficient behavior (e.g., hearing a siren, we expect to see an ambulance and quickly make way). While there are theoretical and computational frameworks for prediction, the circuit and receptor-level mechanisms are unclear. Using high-density EEG, Bayesian modeling, and machine learning, we show that inferred "causal" relationships between stimuli and frontal alpha activity account for reaction times (a proxy for predictions) on a trial-by-trial basis in an audiovisual delayed match-to-sample task which elicited predictions. Predictive β feedback activated sensory representations in advance of predicted stimuli. Low-dose ketamine, an NMDAR blocker, but not the control drug dexmedetomidine, perturbed behavioral indices of predictions, their representation in higher-order cortex, feedback to posterior cortex, and pre-activation of sensory templates in higher-order sensory cortex. This study suggests that predictions depend on alpha activity in higher-order cortex, β feedback, and NMDARs, and ketamine blocks access to learned predictive information.SIGNIFICANCE STATEMENT We learn the statistical regularities around us, creating associations between sensory stimuli. These associations can be exploited by generating predictions, which enable fast and efficient behavior. When predictions are perturbed, it can negatively influence perception and even contribute to psychiatric disorders, such as schizophrenia. Here we show that the frontal lobe generates predictions and sends them to posterior brain areas, to activate representations of predicted sensory stimuli before their appearance. Oscillations in neural activity (α and β waves) are vital for these predictive mechanisms. The drug ketamine blocks predictions and the underlying mechanisms. This suggests that the generation of predictions in the frontal lobe, and the feedback pre-activating sensory representations in advance of stimuli, depend on NMDARs.
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Schöbi D, Do CT, Frässle S, Tittgemeyer M, Heinzle J, Stephan KE. Technical note: A fast and robust integrator of delay differential equations in DCM for electrophysiological data. Neuroimage 2021; 244:118567. [PMID: 34530135 DOI: 10.1016/j.neuroimage.2021.118567] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/21/2021] [Revised: 07/05/2021] [Accepted: 09/07/2021] [Indexed: 10/20/2022] Open
Abstract
Dynamic causal models (DCMs) of electrophysiological data allow, in principle, for inference on hidden, bulk synaptic function in neural circuits. The directed influences between the neuronal elements of modeled circuits are subject to delays due to the finite transmission speed of axonal connections. Ordinary differential equations are therefore not adequate to capture the ensuing circuit dynamics, and delay differential equations (DDEs) are required instead. Previous work has illustrated that the integration of DDEs in DCMs benefits from sophisticated integration schemes in order to ensure rigorous parameter estimation and correct model identification. However, integration schemes that have been proposed for DCMs either emphasize speed (at the possible expense of accuracy) or robustness (but with computational costs that are problematic in practice). In this technical note, we propose an alternative integration scheme that overcomes these shortcomings and offers high computational efficiency while correctly preserving the nature of delayed effects. This integration scheme is available as open-source code in the Translational Algorithms for Psychiatry-Advancing Science (TAPAS) toolbox and can be easily integrated into existing software (SPM) for the analysis of DCMs for electrophysiological data. While this paper focuses on its application to the convolution-based formalism of DCMs, the new integration scheme can be equally applied to more advanced formulations of DCMs (e.g. conductance based models). Our method provides a new option for electrophysiological DCMs that offers the speed required for scientific projects, but also the accuracy required for rigorous translational applications, e.g. in computational psychiatry.
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Affiliation(s)
- Dario Schöbi
- Translational Neuromodeling Unit, Institute for Biomedical Engineering, University of Zurich & Swiss Institute of Technology (ETH Zurich), Wilfriedstrasse 6, Zurich 8032, Switzerland
| | - Cao-Tri Do
- Translational Neuromodeling Unit, Institute for Biomedical Engineering, University of Zurich & Swiss Institute of Technology (ETH Zurich), Wilfriedstrasse 6, Zurich 8032, Switzerland
| | - Stefan Frässle
- Translational Neuromodeling Unit, Institute for Biomedical Engineering, University of Zurich & Swiss Institute of Technology (ETH Zurich), Wilfriedstrasse 6, Zurich 8032, Switzerland
| | - Marc Tittgemeyer
- Max Planck Institute for Metabolism Research, Gleuler Strasse 50, Cologne 50931, Germany; Cluster of Excellence in Cellular Stress and Aging associated Disease (CECAD), Cologne 50931, Germany
| | - Jakob Heinzle
- Translational Neuromodeling Unit, Institute for Biomedical Engineering, University of Zurich & Swiss Institute of Technology (ETH Zurich), Wilfriedstrasse 6, Zurich 8032, Switzerland.
| | - Klaas Enno Stephan
- Translational Neuromodeling Unit, Institute for Biomedical Engineering, University of Zurich & Swiss Institute of Technology (ETH Zurich), Wilfriedstrasse 6, Zurich 8032, Switzerland; Max Planck Institute for Metabolism Research, Gleuler Strasse 50, Cologne 50931, Germany
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40
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Patel GH, Arkin SC, Ruiz-Betancourt D, DeBaun H, Strauss NE, Bartel LP, Grinband J, Martinez A, Berman RA, Leopold DA, Javitt DC. What you see is what you get: visual scanning failures of naturalistic social scenes in schizophrenia. Psychol Med 2021; 51:2923-2932. [PMID: 32498743 PMCID: PMC7751380 DOI: 10.1017/s0033291720001646] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/16/2023]
Abstract
BACKGROUND Impairments in social cognition contribute significantly to disability in schizophrenia patients (SzP). Perception of facial expressions is critical for social cognition. Intact perception requires an individual to visually scan a complex dynamic social scene for transiently moving facial expressions that may be relevant for understanding the scene. The relationship of visual scanning for these facial expressions and social cognition remains unknown. METHODS In 39 SzP and 27 healthy controls (HC), we used eye-tracking to examine the relationship between performance on The Awareness of Social Inference Test (TASIT), which tests social cognition using naturalistic video clips of social situations, and visual scanning, measuring each individual's relative to the mean of HC. We then examined the relationship of visual scanning to the specific visual features (motion, contrast, luminance, faces) within the video clips. RESULTS TASIT performance was significantly impaired in SzP for trials involving sarcasm (p < 10-5). Visual scanning was significantly more variable in SzP than HC (p < 10-6), and predicted TASIT performance in HC (p = 0.02) but not SzP (p = 0.91), differing significantly between groups (p = 0.04). During the visual scanning, SzP were less likely to be viewing faces (p = 0.0001) and less likely to saccade to facial motion in peripheral vision (p = 0.008). CONCLUSIONS SzP show highly significant deficits in the use of visual scanning of naturalistic social scenes to inform social cognition. Alterations in visual scanning patterns may originate from impaired processing of facial motion within peripheral vision. Overall, these results highlight the utility of naturalistic stimuli in the study of social cognition deficits in schizophrenia.
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Affiliation(s)
- Gaurav H. Patel
- Columbia University Medical Center
- New York State Psychiatric Institute
| | | | | | | | | | - Laura P. Bartel
- Columbia University Medical Center
- New York State Psychiatric Institute
| | - Jack Grinband
- Columbia University Medical Center
- New York State Psychiatric Institute
| | | | | | | | - Daniel C. Javitt
- Columbia University Medical Center
- New York State Psychiatric Institute
- Nathan Kline Institute
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41
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Stein H, Barbosa J, Compte A. Towards biologically constrained attractor models of schizophrenia. Curr Opin Neurobiol 2021; 70:171-181. [PMID: 34839146 DOI: 10.1016/j.conb.2021.10.013] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/25/2021] [Revised: 10/19/2021] [Accepted: 10/27/2021] [Indexed: 12/31/2022]
Abstract
Alterations in neuromodulation or synaptic transmission in biophysical attractor network models, as proposed by the dominant dopaminergic and glutamatergic theories of schizophrenia, successfully mimic working memory (WM) deficits in people with schizophrenia (PSZ). Yet, multiple, often opposing alterations in memory circuits can lead to the same behavioral patterns in these network models. Here, we critically revise the computational and experimental literature that links NMDAR hypofunction to WM precision loss in PSZ. We show in network simulations that currently available experimental evidence cannot set apart competing biophysical accounts. Critical points to resolve are the effects of increases vs. decreases in E/I ratio (e.g. through NMDAR blockade) on firing rate tuning and shared noise modulations and possible concomitant deficits in short-term plasticity. We argue that these concerted experimental and computational efforts will lead to a better understanding of the neurobiology underlying cognitive deficits in PSZ.
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Affiliation(s)
- Heike Stein
- Laboratoire de Neurosciences Cognitives et Computationnelles, Département d'Études Cognitives, École Normale Supérieure, INSERM U960, PSL University, Paris, France
| | - Joao Barbosa
- Laboratoire de Neurosciences Cognitives et Computationnelles, Département d'Études Cognitives, École Normale Supérieure, INSERM U960, PSL University, Paris, France
| | - Albert Compte
- Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain.
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42
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Liu Y, Ouyang P, Zheng Y, Mi L, Zhao J, Ning Y, Guo W. A Selective Review of the Excitatory-Inhibitory Imbalance in Schizophrenia: Underlying Biology, Genetics, Microcircuits, and Symptoms. Front Cell Dev Biol 2021; 9:664535. [PMID: 34746116 PMCID: PMC8567014 DOI: 10.3389/fcell.2021.664535] [Citation(s) in RCA: 17] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/05/2021] [Accepted: 09/27/2021] [Indexed: 12/29/2022] Open
Abstract
Schizophrenia is a chronic disorder characterized by specific positive and negative primary symptoms, social behavior disturbances and cognitive deficits (e.g., impairment in working memory and cognitive flexibility). Mounting evidence suggests that altered excitability and inhibition at the molecular, cellular, circuit and network level might be the basis for the pathophysiology of neurodevelopmental and neuropsychiatric disorders such as schizophrenia. In the past decades, human and animal studies have identified that glutamate and gamma-aminobutyric acid (GABA) neurotransmissions are critically involved in several cognitive progresses, including learning and memory. The purpose of this review is, by analyzing emerging findings relating to the balance of excitatory and inhibitory, ranging from animal models of schizophrenia to clinical studies in patients with early onset, first-episode or chronic schizophrenia, to discuss how the excitatory-inhibitory imbalance may relate to the pathophysiology of disease phenotypes such as cognitive deficits and negative symptoms, and highlight directions for appropriate therapeutic strategies.
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Affiliation(s)
- Yi Liu
- National Clinical Research Center on Mental Disorders and Department of Psychiatry, The Second Xiangya Hospital, Central South University, Changsha, China.,Department of Psychiatry, The Affiliated Brain Hospital, Guangzhou Medical University, Guangzhou, China
| | - Pan Ouyang
- National Clinical Research Center on Mental Disorders and Department of Psychiatry, The Second Xiangya Hospital, Central South University, Changsha, China
| | - Yingjun Zheng
- Department of Psychiatry, The Affiliated Brain Hospital, Guangzhou Medical University, Guangzhou, China
| | - Lin Mi
- Department of Psychiatry, The Affiliated Brain Hospital, Guangzhou Medical University, Guangzhou, China
| | - Jingping Zhao
- National Clinical Research Center on Mental Disorders and Department of Psychiatry, The Second Xiangya Hospital, Central South University, Changsha, China
| | - Yuping Ning
- Department of Psychiatry, The Affiliated Brain Hospital, Guangzhou Medical University, Guangzhou, China.,The First School of Clinical Medical University, Guangzhou, China
| | - Wenbin Guo
- National Clinical Research Center on Mental Disorders and Department of Psychiatry, The Second Xiangya Hospital, Central South University, Changsha, China
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43
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Almeida VN, Radanovic M. Semantic priming and neurobiology in schizophrenia: A theoretical review. Neuropsychologia 2021; 163:108058. [PMID: 34655651 DOI: 10.1016/j.neuropsychologia.2021.108058] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/23/2021] [Revised: 10/06/2021] [Accepted: 10/07/2021] [Indexed: 12/11/2022]
Abstract
In this theoretical review we bridge the cognitive and neurobiological sciences to shed light on the neurocognitive foundations of the semantic priming effect in schizophrenia. We review and theoretically evaluate the neurotransmitter systems (dopaminergic, GABAergic and glutamatergic) and neurobiological underpinnings of behavioural and electrophysiological (N400) semantic priming in the pathology, and the main hypotheses on their geneses: a disinhibition of the semantic spread of activation, a disorganised semantic storage or noisy lexical-semantic associations, a psychomotor artefact, an artefact of relatedness proportions, or an inability to mobilise contextual information. We further assess the literature on the endophenotype of Formal Thought Disorder from multiple standpoints, ranging from neurophysiology to cognition: considerations are weaved on neuronal (PV basket cell, SST, VIP) and receptor deficits (DRD1, NMDA), neurotransmitter imbalances (dopamine), cortical and dopaminergic lateralisation, inter alia. In conclusion, we put forth novel postulates on the underlying causes of controlled hypopriming, automatic hyperpriming, N400 reversals (larger amplitudes for close associations), indirect versus direct hyperpriming, and the endophenotype of lexical-semantic disturbances in schizophrenia.
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Affiliation(s)
- Victor N Almeida
- Faculdade de Letras, Universidade Federal de Minas Gerais (UFMG), Av. Pres. Antônio Carlos, 6627 - Pampulha, Belo Horizonte, MG, 31270-901, Brazil.
| | - Marcia Radanovic
- Laboratório de Neurociências (LIM-27), Faculdade de Medicina, Departamento e Instituto de Psiquiatria, Hospital das Clínicas HCFMUSP, Universidade de São Paulo, Brazil
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Wojtak W, Coombes S, Avitabile D, Bicho E, Erlhagen W. A dynamic neural field model of continuous input integration. BIOLOGICAL CYBERNETICS 2021; 115:451-471. [PMID: 34417880 DOI: 10.1007/s00422-021-00893-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/01/2021] [Accepted: 08/01/2021] [Indexed: 06/13/2023]
Abstract
The ability of neural systems to turn transient inputs into persistent changes in activity is thought to be a fundamental requirement for higher cognitive functions. In continuous attractor networks frequently used to model working memory or decision making tasks, the persistent activity settles to a stable pattern with the stereotyped shape of a "bump" independent of integration time or input strength. Here, we investigate a new bump attractor model in which the bump width and amplitude not only reflect qualitative and quantitative characteristics of a preceding input but also the continuous integration of evidence over longer timescales. The model is formalized by two coupled dynamic field equations of Amari-type which combine recurrent interactions mediated by a Mexican-hat connectivity with local feedback mechanisms that balance excitation and inhibition. We analyze the existence, stability and bifurcation structure of single and multi-bump solutions and discuss the relevance of their input dependence to modeling cognitive functions. We then systematically compare the pattern formation process of the two-field model with the classical Amari model. The results reveal that the balanced local feedback mechanisms facilitate the encoding and maintenance of multi-item memories. The existence of stable subthreshold bumps suggests that different to the Amari model, the suppression effect of neighboring bumps in the range of lateral competition may not lead to a complete loss of information. Moreover, bumps with larger amplitude are less vulnerable to noise-induced drifts and distance-dependent interaction effects resulting in more faithful memory representations over time.
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Affiliation(s)
- Weronika Wojtak
- Research Centre of Mathematics, University of Minho, Guimarães, Portugal.
- Research Centre Algoritmi, University of Minho, Guimarães, Portugal.
| | - Stephen Coombes
- Centre for Mathematical Medicine and Biology, School of Mathematical Sciences, University of Nottingham, Nottingham, UK
| | - Daniele Avitabile
- Department of Mathematics, Vrije Universiteit, Amsterdam, The Netherlands
- MathNeuro Team, Inria Sophia Antipolis Méditerranée Research Centre, Sophia Antipolis, France
| | - Estela Bicho
- Research Centre Algoritmi, University of Minho, Guimarães, Portugal
| | - Wolfram Erlhagen
- Research Centre of Mathematics, University of Minho, Guimarães, Portugal
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Wang X, Liao W, Han S, Li J, Wang Y, Zhang Y, Zhao J, Chen H. Frequency-specific altered global signal topography in drug-naïve first-episode patients with adolescent-onset schizophrenia. Brain Imaging Behav 2021; 15:1876-1885. [PMID: 33188473 DOI: 10.1007/s11682-020-00381-9] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/08/2023]
Abstract
Adolescent-onset schizophrenia (AOS) is a severe neuropsychiatric disease associated with frequency-specific abnormalities across distributed neural systems in a slow rhythm. Recently, functional magnetic resonance imaging (fMRI) studies have determined that the global signal. (GS) is an important source of the local neuronal activity in 0.01-0.1 Hz frequency band. However, it remains unknown whether the effects follow a specific spatially preferential pattern in different frequency bands in schizophrenia. To address this issue, resting-state fMRI data from 39 drug-naïve AOS patients and 31 healthy controls (HCs) were used to assess the changes in GS topography patterns in the slow-4 (0.027-0.073 Hz) and slow-5 bands (0.01-0.027 Hz). Results revealed that GS mainly affects the default mode network (DMN) in slow-4 and sensory regions in the slow-5 band respectively, and GS has a stronger driving effect in the slow-5 band. Moreover, significant frequency-by-group interaction was observed in the frontoparietal network. Compared with HCs, patients with AOS exhibited altered GS topography mainly located in the DMN. Our findings demonstrated that the influence of the GS on brain networks altered in a frequency-specific way in schizophrenia.
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Affiliation(s)
- Xiao Wang
- The Clinical Hospital of Chengdu Brain Science Institute, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, 610054, People's Republic of China.,MOE Key Lab for Neuroinformation, High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, University of Electronic Science and Technology of China, Chengdu, 610054, People's Republic of China
| | - Wei Liao
- The Clinical Hospital of Chengdu Brain Science Institute, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, 610054, People's Republic of China.,MOE Key Lab for Neuroinformation, High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, University of Electronic Science and Technology of China, Chengdu, 610054, People's Republic of China
| | - Shaoqiang Han
- The Clinical Hospital of Chengdu Brain Science Institute, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, 610054, People's Republic of China.,MOE Key Lab for Neuroinformation, High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, University of Electronic Science and Technology of China, Chengdu, 610054, People's Republic of China
| | - Jiao Li
- The Clinical Hospital of Chengdu Brain Science Institute, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, 610054, People's Republic of China.,MOE Key Lab for Neuroinformation, High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, University of Electronic Science and Technology of China, Chengdu, 610054, People's Republic of China
| | - Yifeng Wang
- The Clinical Hospital of Chengdu Brain Science Institute, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, 610054, People's Republic of China.,MOE Key Lab for Neuroinformation, High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, University of Electronic Science and Technology of China, Chengdu, 610054, People's Republic of China
| | - Yan Zhang
- Key Laboratory for Mental Health of Hunan Province, Mental Health Institute, the Second Xiangya Hospital of Central South University, Changsha, China
| | - Jingping Zhao
- Mental Health Institute, the Second Xiangya Hospital of Central South University, 139, Middle Renmin Road, Changsha, 410011, Hunan, China
| | - Huafu Chen
- The Clinical Hospital of Chengdu Brain Science Institute, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, 610054, People's Republic of China. .,Radiology department of the First Affiliated Hospital, the Third Military Medical University, Chongqing, 400038, China.
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Psychiatric Illnesses as Disorders of Network Dynamics. BIOLOGICAL PSYCHIATRY: COGNITIVE NEUROSCIENCE AND NEUROIMAGING 2021; 6:865-876. [DOI: 10.1016/j.bpsc.2020.01.001] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/17/2019] [Accepted: 01/06/2020] [Indexed: 01/05/2023]
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Parkin BL, Daws RE, Das-Neves I, Violante IR, Soreq E, Faisal AA, Sandrone S, Lao-Kaim NP, Martin-Bastida A, Roussakis AA, Piccini P, Hampshire A. Dissociable effects of age and Parkinson's disease on instruction-based learning. Brain Commun 2021; 3:fcab175. [PMID: 34485905 PMCID: PMC8410985 DOI: 10.1093/braincomms/fcab175] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/17/2020] [Revised: 04/06/2021] [Accepted: 05/10/2021] [Indexed: 12/02/2022] Open
Abstract
The cognitive deficits associated with Parkinson's disease vary across individuals and change across time, with implications for prognosis and treatment. Key outstanding challenges are to define the distinct behavioural characteristics of this disorder and develop diagnostic paradigms that can assess these sensitively in individuals. In a previous study, we measured different aspects of attentional control in Parkinson's disease using an established fMRI switching paradigm. We observed no deficits for the aspects of attention the task was designed to examine; instead those with Parkinson's disease learnt the operational requirements of the task more slowly. We hypothesized that a subset of people with early-to-mid stage Parkinson's might be impaired when encoding rules for performing new tasks. Here, we directly test this hypothesis and investigate whether deficits in instruction-based learning represent a characteristic of Parkinson's Disease. Seventeen participants with Parkinson's disease (8 male; mean age: 61.2 years), 18 older adults (8 male; mean age: 61.3 years) and 20 younger adults (10 males; mean age: 26.7 years) undertook a simple instruction-based learning paradigm in the MRI scanner. They sorted sequences of coloured shapes according to binary discrimination rules that were updated at two-minute intervals. Unlike common reinforcement learning tasks, the rules were unambiguous, being explicitly presented; consequently, there was no requirement to monitor feedback or estimate contingencies. Despite its simplicity, a third of the Parkinson's group, but only one older adult, showed marked increases in errors, 4 SD greater than the worst performing young adult. The pattern of errors was consistent, reflecting a tendency to misbind discrimination rules. The misbinding behaviour was coupled with reduced frontal, parietal and anterior caudate activity when rules were being encoded, but not when attention was initially oriented to the instruction slides or when discrimination trials were performed. Concomitantly, Magnetic Resonance Spectroscopy showed reduced gamma-Aminobutyric acid levels within the mid-dorsolateral prefrontal cortices of individuals who made misbinding errors. These results demonstrate, for the first time, that a subset of early-to-mid stage people with Parkinson's show substantial deficits when binding new task rules in working memory. Given the ubiquity of instruction-based learning, these deficits are likely to impede daily living. They will also confound clinical assessment of other cognitive processes. Future work should determine the value of instruction-based learning as a sensitive early marker of cognitive decline and as a measure of responsiveness to therapy in Parkinson's disease.
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Affiliation(s)
- Beth L Parkin
- Department of Psychology, School of Social Science, University of Westminster, 115 New Cavendish Street, London, W1W 6UW, UK
| | - Richard E Daws
- The Cognitive, Computational and Clinical Neuroscience Laboratory, Department of Medicine, Imperial College London, London W120NN, UK
| | - Ines Das-Neves
- The Cognitive, Computational and Clinical Neuroscience Laboratory, Department of Medicine, Imperial College London, London W120NN, UK
| | - Ines R Violante
- The Cognitive, Computational and Clinical Neuroscience Laboratory, Department of Medicine, Imperial College London, London W120NN, UK
- School of Psychology, Faculty of Health and Medical Sciences, University of Surrey, Guildford GU2 7XH, UK
| | - Eyal Soreq
- The Cognitive, Computational and Clinical Neuroscience Laboratory, Department of Medicine, Imperial College London, London W120NN, UK
| | - A Aldo Faisal
- Brain and Behaviour Laboratory, Department of Bioengineering, Imperial College London, London W12 0NN, UK
- Brain and Behaviour Laboratory, Department of Computing, Imperial College London, London W12 0NN, UK
- Behaviour Analytics Lab, Data Science Institute, Imperial College London, London W12 0NN, UK
- MRC London Institute of Medical Sciences, London W12 0NN, UK
| | - Stefano Sandrone
- The Cognitive, Computational and Clinical Neuroscience Laboratory, Department of Medicine, Imperial College London, London W120NN, UK
| | - Nicholas P Lao-Kaim
- Neurology Imaging Unit, Division of Neurology, Imperial College London, London W12 0NN, UK
| | - Antonio Martin-Bastida
- Neurology Imaging Unit, Division of Neurology, Imperial College London, London W12 0NN, UK
- Department of Neurology and Neurosciences, Clinica Universidad de Navarra, Pamplona-Madrid 28027, Spain
| | | | - Paola Piccini
- Neurology Imaging Unit, Division of Neurology, Imperial College London, London W12 0NN, UK
| | - Adam Hampshire
- The Cognitive, Computational and Clinical Neuroscience Laboratory, Department of Medicine, Imperial College London, London W120NN, UK
- UK DRI Care Research & Technology Centre, Imperial College London, London W12 0NN, UK
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Lehet M, Tso IF, Neggers SFW, Thompson IA, Yao B, Kahn RS, Thakkar KN. Altered effective connectivity within an oculomotor control network in individuals with schizophrenia. Neuroimage Clin 2021; 31:102764. [PMID: 34284336 PMCID: PMC8313596 DOI: 10.1016/j.nicl.2021.102764] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/10/2021] [Revised: 07/09/2021] [Accepted: 07/10/2021] [Indexed: 11/22/2022]
Abstract
Rapid inhibition or modification of actions is a crucial cognitive ability, which is impaired in persons with schizophrenia (SZP). Primate neurophysiology studies have identified a network of brain regions that subserves control over gaze. Here, we examine effective connectivity within this oculomotor control network in SZP and healthy controls (HC). During fMRI, participants performed a stop-signal task variant in which they were instructed to saccade to a visual target (no-step trials) unless a second target appeared (redirect trials); on redirect trials, participants were instructed to inhibit the planned saccade and redirect to the new target. We compared functional responses on redirect trials to no-step trials and used dynamic causal modelling (DCM) to examine group differences in network effective connectivity. Behaviorally, SZP were less efficient at inhibiting, which was related to their employment status. Compared to HC, they showed a smaller difference in activity between redirect trials and no-step trials in frontal eye fields (FEF), supplementary eye fields (SEF), inferior frontal cortex (IFC), thalamus, and caudate. DCM analyses revealed widespread group differences in effective connectivity across the task, including different patterns of self-inhibition in many nodes in SZP. Group differences in how effective connectivity was modulated on redirect trials revealed differences between the FEF and SEF, between the SEF and IFC, between the superior colliculus and the thalamus, and self-inhibition within the FEF and caudate. These results provide insight into the neural mechanisms of inefficient inhibitory control in individuals with schizophrenia.
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Affiliation(s)
- Matthew Lehet
- Department of Psychology, Michigan State University, East Lansing, MI, USA
| | - Ivy F Tso
- Department of Psychiatry, University of Michigan, Ann Arbor, MI, USA
| | | | - Ilse A Thompson
- Department of Psychiatry, University Medical Center Utrecht, Utrecht, the Netherlands
| | - Beier Yao
- Department of Psychology, Michigan State University, East Lansing, MI, USA
| | - René S Kahn
- Department of Psychiatry, University Medical Center Utrecht, Utrecht, the Netherlands; Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Katharine N Thakkar
- Department of Psychology, Michigan State University, East Lansing, MI, USA; Department of Psychiatry, University Medical Center Utrecht, Utrecht, the Netherlands; Department of Psychiatry and Biobehavioral Medicine, Michigan State University, Grand Rapids, MI, USA.
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49
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Atiya NAA, Huys QJM, Dolan RJ, Fleming SM. Explaining distortions in metacognition with an attractor network model of decision uncertainty. PLoS Comput Biol 2021; 17:e1009201. [PMID: 34310613 PMCID: PMC8341696 DOI: 10.1371/journal.pcbi.1009201] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/25/2020] [Revised: 08/05/2021] [Accepted: 06/18/2021] [Indexed: 11/21/2022] Open
Abstract
Metacognition is the ability to reflect on, and evaluate, our cognition and behaviour. Distortions in metacognition are common in mental health disorders, though the neural underpinnings of such dysfunction are unknown. One reason for this is that models of key components of metacognition, such as decision confidence, are generally specified at an algorithmic or process level. While such models can be used to relate brain function to psychopathology, they are difficult to map to a neurobiological mechanism. Here, we develop a biologically-plausible model of decision uncertainty in an attempt to bridge this gap. We first relate the model's uncertainty in perceptual decisions to standard metrics of metacognition, namely mean confidence level (bias) and the accuracy of metacognitive judgments (sensitivity). We show that dissociable shifts in metacognition are associated with isolated disturbances at higher-order levels of a circuit associated with self-monitoring, akin to neuropsychological findings that highlight the detrimental effect of prefrontal brain lesions on metacognitive performance. Notably, we are able to account for empirical confidence judgements by fitting the parameters of our biophysical model to first-order performance data, specifically choice and response times. Lastly, in a reanalysis of existing data we show that self-reported mental health symptoms relate to disturbances in an uncertainty-monitoring component of the network. By bridging a gap between a biologically-plausible model of confidence formation and observed disturbances of metacognition in mental health disorders we provide a first step towards mapping theoretical constructs of metacognition onto dynamical models of decision uncertainty. In doing so, we provide a computational framework for modelling metacognitive performance in settings where access to explicit confidence reports is not possible.
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Affiliation(s)
- Nadim A. A. Atiya
- Max Planck University College London Centre for Computational Psychiatry and Ageing Research, University College London, London, United Kingdom
- Wellcome Centre for Human Neuroimaging, University College London, London, United Kingdom
| | - Quentin J. M. Huys
- Max Planck University College London Centre for Computational Psychiatry and Ageing Research, University College London, London, United Kingdom
- Division of Psychiatry, University College London, London, United Kingdom
| | - Raymond J. Dolan
- Max Planck University College London Centre for Computational Psychiatry and Ageing Research, University College London, London, United Kingdom
- Wellcome Centre for Human Neuroimaging, University College London, London, United Kingdom
| | - Stephen M. Fleming
- Max Planck University College London Centre for Computational Psychiatry and Ageing Research, University College London, London, United Kingdom
- Wellcome Centre for Human Neuroimaging, University College London, London, United Kingdom
- Department of Experimental Psychology, University College London, London, United Kingdom
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Möller TJ, Georgie YK, Schillaci G, Voss M, Hafner VV, Kaltwasser L. Computational models of the "active self" and its disturbances in schizophrenia. Conscious Cogn 2021; 93:103155. [PMID: 34130210 DOI: 10.1016/j.concog.2021.103155] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/27/2021] [Revised: 05/14/2021] [Accepted: 05/20/2021] [Indexed: 11/16/2022]
Abstract
The notion that self-disorders are at the root of the emergence of schizophrenia rather than a symptom of the disease, is getting more traction in the cognitive sciences. This is in line with philosophical approaches that consider an enactive self, constituted through action and interaction with the environment. We thereby analyze different definitions of the self and evaluate various computational theories lending to these ideas. Bayesian and predictive processing are promising approaches for computational modeling of the "active self". We evaluate their implementation and challenges in computational psychiatry and cognitive developmental robotics. We describe how and why embodied robotic systems provide a valuable tool in psychiatry to assess, validate, and simulate mechanisms of self-disorders. Specifically, mechanisms involving sensorimotor learning, prediction, and self-other distinction, can be assessed with artificial agents. This link can provide essential insights to the formation of the self and new avenues in the treatment of psychiatric disorders.
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Affiliation(s)
- Tim Julian Möller
- Berlin School of Mind and Brain, Humboldt-Universität zu Berlin, Berlin, Germany; Department of Psychiatry and Psychotherapy, Charité University Medicine, Berlin, Germany.
| | - Yasmin Kim Georgie
- Department of Computer Science, Humboldt-Universität zu Berlin, Germany.
| | - Guido Schillaci
- The BioRobotics Institute and Dept. of Excellence in Robotics & AI, Scuola Superiore Sant'Anna, Pisa, Italy.
| | - Martin Voss
- Berlin School of Mind and Brain, Humboldt-Universität zu Berlin, Berlin, Germany; Department of Psychiatry and Psychotherapy, Charité University Medicine and St. Hedwig Hospital, Berlin, Germany.
| | | | - Laura Kaltwasser
- Berlin School of Mind and Brain, Humboldt-Universität zu Berlin, Berlin, Germany; Department of Psychiatry and Psychotherapy, Charité University Medicine, Berlin, Germany.
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