scholarly journals Dynamic brain network reconfiguration as a potential schizophrenia genetic risk mechanism modulated by NMDA receptor function

2016 ◽  
Vol 113 (44) ◽  
pp. 12568-12573 ◽  
Author(s):  
Urs Braun ◽  
Axel Schäfer ◽  
Danielle S. Bassett ◽  
Franziska Rausch ◽  
Janina I. Schweiger ◽  
...  

Schizophrenia is increasingly recognized as a disorder of distributed neural dynamics, but the molecular and genetic contributions are poorly understood. Recent work highlights a role for altered N-methyl-d-aspartate (NMDA) receptor signaling and related impairments in the excitation–inhibitory balance and synchrony of large-scale neural networks. Here, we combined a pharmacological intervention with novel techniques from dynamic network neuroscience applied to functional magnetic resonance imaging (fMRI) to identify alterations in the dynamic reconfiguration of brain networks related to schizophrenia genetic risk and NMDA receptor hypofunction. We quantified “network flexibility,” a measure of the dynamic reconfiguration of the community structure of time-variant brain networks during working memory performance. Comparing 28 patients with schizophrenia, 37 unaffected first-degree relatives, and 139 healthy controls, we detected significant differences in network flexibility [F(2,196) = 6.541, P = 0.002] in a pattern consistent with the assumed genetic risk load of the groups (highest for patients, intermediate for relatives, and lowest for controls). In an observer-blinded, placebo-controlled, randomized, cross-over pharmacological challenge study in 37 healthy controls, we further detected a significant increase in network flexibility as a result of NMDA receptor antagonism with 120 mg dextromethorphan [F(1,34) = 5.291, P = 0.028]. Our results identify a potential dynamic network intermediate phenotype related to the genetic liability for schizophrenia that manifests as altered reconfiguration of brain networks during working memory. The phenotype appears to be influenced by NMDA receptor antagonism, consistent with a critical role for glutamate in the temporal coordination of neural networks and the pathophysiology of schizophrenia.

2015 ◽  
Vol 112 (37) ◽  
pp. 11678-11683 ◽  
Author(s):  
Urs Braun ◽  
Axel Schäfer ◽  
Henrik Walter ◽  
Susanne Erk ◽  
Nina Romanczuk-Seiferth ◽  
...  

The brain is an inherently dynamic system, and executive cognition requires dynamically reconfiguring, highly evolving networks of brain regions that interact in complex and transient communication patterns. However, a precise characterization of these reconfiguration processes during cognitive function in humans remains elusive. Here, we use a series of techniques developed in the field of “dynamic network neuroscience” to investigate the dynamics of functional brain networks in 344 healthy subjects during a working-memory challenge (the “n-back” task). In contrast to a control condition, in which dynamic changes in cortical networks were spread evenly across systems, the effortful working-memory condition was characterized by a reconfiguration of frontoparietal and frontotemporal networks. This reconfiguration, which characterizes “network flexibility,” employs transient and heterogeneous connectivity between frontal systems, which we refer to as “integration.” Frontal integration predicted neuropsychological measures requiring working memory and executive cognition, suggesting that dynamic network reconfiguration between frontal systems supports those functions. Our results characterize dynamic reconfiguration of large-scale distributed neural circuits during executive cognition in humans and have implications for understanding impaired cognitive function in disorders affecting connectivity, such as schizophrenia or dementia.


1999 ◽  
Vol 381 (2-3) ◽  
pp. 93-99 ◽  
Author(s):  
Iain A Wilson ◽  
Jukka Puoliväli ◽  
Taneli Heikkinen ◽  
Paavo Riekkinen

2020 ◽  
Vol 11 (1) ◽  
Author(s):  
Karolina Finc ◽  
Kamil Bonna ◽  
Xiaosong He ◽  
David M. Lydon-Staley ◽  
Simone Kühn ◽  
...  

2014 ◽  
Vol 204 (4) ◽  
pp. 290-298 ◽  
Author(s):  
Christine Lycke Brandt ◽  
Tom Eichele ◽  
Ingrid Melle ◽  
Kjetil Sundet ◽  
Andrés Server ◽  
...  

BackgroundSchizophrenia and bipolar disorder are severe mental disorders with overlapping genetic and clinical characteristics, including cognitive impairments. An important question is whether these disorders also have overlapping neuronal deficits.AimsTo determine whether large-scale brain networks associated with working memory, as measured with functional magnetic resonance imaging (fMRI), are the same in both schizophrenia and bipolar disorder, and how they differ from those in healthy individuals.MethodPatients with schizophrenia (n = 100) and bipolar disorder (n = 100) and a healthy control group (n = 100) performed a 2-back working memory task while fMRI data were acquired. The imaging data were analysed using independent component analysis to extract large-scale networks of task-related activations.ResultsSimilar working memory networks were activated in all groups. However, in three out of nine networks related to the experimental task there was a graded response difference in fMRI signal amplitudes, where patients with schizophrenia showed greater activation than those with bipolar disorder, who in turn showed more activation than healthy controls. Secondary analysis of the patient groups showed that these activation patterns were associated with history of psychosis and current elevated mood in bipolar disorder.ConclusionsThe same brain networks were related to working memory in schizophrenia, bipolar disorder and controls. However, some key networks showed a graded hyperactivation in the two patient groups, in line with a continuum of neuronal abnormalities across psychotic disorders.


2019 ◽  
Author(s):  
Wessel Woldman ◽  
Helmut Schmidt ◽  
Eugenio Abela ◽  
Fahmida A. Chowdhury ◽  
Adam D. Pawley ◽  
...  

AbstractObjectiveCurrent explanatory concepts suggest seizures emerge from ongoing dynamics of brain networks. It is unclear how brain network properties determine focal or generalised seizure onset, or how network properties can be described in a clinically-useful manner. Understanding network properties would cast light on seizure-generating mechanisms and allow to quantify in the clinic the extent to which a seizure is focal or generalised.Methods68 people with epilepsy and 38 healthy controls underwent 19 channel scalp EEG recording. Functional brain networks were estimated in each subject using phase-locking between EEG channels in the 6-9Hz band from segments of 20s without interictal discharges. Simplified brain dynamics were simulated using a computer model. We introduce three concepts: Critical Coupling (Cc), the ability of a network to generate seizures; Onset Index (OI), the tendency of a region to generate seizures; and Participation Index (PI), the tendency of a region to become involved in seizures.ResultsCc was lower in both patient groups compared with controls. OI and PI were more variable in focal-onset than generalised-onset cases. No regions showed higher OI and PI in generalised-onset cases than in healthy controls; in focal cases, the regions with highest OI and PI corresponded to the side of seizure onset.ConclusionsProperties of interictal functional networks from scalp EEG can be estimated using a computer model and used to predict seizure likelihood and onset patterns. Our framework, consisting of three clinically-meaningful measures, could be implemented in the clinic to quantify the diagnosis and seizure onset pattern.


2020 ◽  
Vol 11 (1) ◽  
Author(s):  
Karolina Finc ◽  
Kamil Bonna ◽  
Xiaosong He ◽  
David M. Lydon-Staley ◽  
Simone Kühn ◽  
...  

2019 ◽  
Vol 85 (10) ◽  
pp. S358
Author(s):  
Flora Moujaes ◽  
Katrin Preller ◽  
Franz Vollenweider ◽  
Charles Schleifer ◽  
Jie Lisa Ji ◽  
...  

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Junchao Huang ◽  
Jinghui Tong ◽  
Ping Zhang ◽  
Yanfang Zhou ◽  
Yimin Cui ◽  
...  

AbstractA number of tryptophan metabolites known to be neuroactive have been examined for their potential associations with cognitive deficits in schizophrenia. Among these metabolites, kynurenic acid (KYNA), 5-hydroxyindole (5-HI), and quinolinic acid (QUIN) are documented in their diverse effects on α-7 nicotinic acetylcholine receptor (α7nAChR) and/or N-methyl-D-aspartate receptor (NMDAR), two of the receptor types thought to contribute to cognitive impairment in schizophrenia. In this study, serum levels of KYNA, 5-HI, and QUIN were measured in 195 patients with schizophrenia and in 70 healthy controls using liquid chromatography-tandem mass spectrometry; cognitive performance in MATRICS Consensus Cognitive Battery and cortical thickness measured by magnetic resonance imaging were obtained. Patients with schizophrenia had significantly lower serum KYNA (p < 0.001) and QUIN (p = 0.02) levels, and increased 5-HI/KYNA (p < 0.001) and QUIN/KYNA ratios (p < 0.001) compared with healthy controls. Multiple linear regression showed that working memory was positively correlated with serum 5-HI levels (t = 2.10, p = 0.04), but inversely correlated with KYNA concentrations (t = −2.01, p = 0.05) in patients. Patients with high 5-HI and low KYNA had better working memory than other subgroups (p = 0.01). Higher 5-HI levels were associated with thicker left lateral orbitofrontal cortex (t = 3.71, p = 2.94 × 10−4) in patients. The different effects of 5-HI and KYNA on working memory may appear consistent with their opposite receptor level mechanisms. Our findings appear to provide a new insight into the dynamic roles of tryptophan pathway metabolites on cognition, which may benefit novel therapeutic development that targets cognitive impairment in schizophrenia.


2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Abhishek Uday Patil ◽  
Sejal Ghate ◽  
Deepa Madathil ◽  
Ovid J. L. Tzeng ◽  
Hsu-Wen Huang ◽  
...  

AbstractCreative cognition is recognized to involve the integration of multiple spontaneous cognitive processes and is manifested as complex networks within and between the distributed brain regions. We propose that the processing of creative cognition involves the static and dynamic re-configuration of brain networks associated with complex cognitive processes. We applied the sliding-window approach followed by a community detection algorithm and novel measures of network flexibility on the blood-oxygen level dependent (BOLD) signal of 8 major functional brain networks to reveal static and dynamic alterations in the network reconfiguration during creative cognition using functional magnetic resonance imaging (fMRI). Our results demonstrate the temporal connectivity of the dynamic large-scale creative networks between default mode network (DMN), salience network, and cerebellar network during creative cognition, and advance our understanding of the network neuroscience of creative cognition.


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