Semantic Network Disconnection in Formal Thought Disorder

Horn, Helge; Jann, Kay; Federspiel, Andrea; Walther, Sebastian; Wiest, Roland; Müller, Thomas; Strik, Werner

doi:10.1159/000337133

Cited by 48 publications

(36 citation statements)

References 155 publications

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“…In contrast, a lower WM directionality in language tracts increases vulnerability to positive FTDs [72]. Further studies have supported the particular link of FTDs to structural [79-81] and functional [41, 82-84] disorders of the language system.…”

Section: Mapping Symptoms Onto Brain Systems: Empirical Evidence For mentioning

confidence: 99%

Systems Neuroscience of Psychosis: Mapping Schizophrenia Symptoms onto Brain Systems

et al. 2017

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Schizophrenia research has been in a deadlock for many decades. Despite important advances in clinical treatment, there are still major concerns regarding long-term psychosocial reintegration and disease management, biological heterogeneity, unsatisfactory predictors of individual course and treatment strategies, and a confusing variety of controversial theories about its etiology and pathophysiological mechanisms. In the present perspective on schizophrenia research, we first discuss a methodological pitfall in contemporary schizophrenia research inherent in the attempt to link mental phenomena with the brain: we claim that the time-honored phenomenological method of defining mental symptoms should not be contaminated with the naturalistic approach of modern neuroscience. We then describe our Systems Neuroscience of Psychosis (SyNoPsis) project, which aims to overcome this intrinsic problem of psychiatric research. Considering schizophrenia primarily as a disorder of interindividual communication, we developed a neurobiologically informed semiotics of psychotic disorders, as well as an operational clinical rating scale. The novel psychopathology allows disentangling the clinical manifestations of schizophrenia into behavioral domains matching the functions of three well-described higher-order corticobasal brain systems involved in interindividual human communication, namely, the limbic, associative, and motor loops, including their corticocortical sensorimotor connections. The results of several empirical studies support the hypothesis that the proposed three-dimensional symptom structure, segregated into the affective, the language, and the motor domain, can be specifically mapped onto structural and functional abnormalities of the respective brain systems. New pathophysiological hypotheses derived from this brain system-oriented approach have helped to develop and improve novel treatment strategies with noninvasive brain stimulation and practicable clinical parameters. In clinical practice, the novel psychopathology allows confining the communication deficits of the individual patient, shifting attention from the symptoms to the intact resources. We have studied this approach and observed important advantages for therapeutic alliances, personalized treatment, and de-escalation strategies. Future studies will further conjoin clinical definitions of psychotic symptoms with brain structures and functions, and disentangle structural and functional deficit patterns within these systems to identify neurobiologically distinct subsyndromes. Neurobiologically homogeneous patient groups may provide new momentum for treatment research. Finally, lessons learned from schizophrenia research may contribute to developing a comprehensive perspective on human experience and behavior that integrates methodologically distinct, but internally consistent, insights from humanities and neuroscience.

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Section: Mapping Symptoms Onto Brain Systems: Empirical Evidence For mentioning

confidence: 99%

Systems Neuroscience of Psychosis: Mapping Schizophrenia Symptoms onto Brain Systems

et al. 2017

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“…Accordingly, research has been interested in both normal and psychiatric patients. Specifically schizophrenia patients that show cognitive impairments in working memory [34,67,68,69] and language [67,70 ]as well as present symptoms such as hallucinations indicate that the respective networks might show pathophysiological alterations not just during task execution but also during the resting state.…”

Section: Review Of Rsnsmentioning

confidence: 99%

Integrating Different Aspects of Resting Brain Activity: A Review of Electroencephalographic Signatures in Resting State Networks Derived from Functional Magnetic Resonance Imaging

et al. 2015

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Electroencephalography (EEG) is an established measure in the field of brain resting state with a range of quantitative methods (qEEG) that yield unique information about neuronal activation and synchronization. Meanwhile, in the last decade, functional magnetic resonance imaging (fMRI) studies have revealed the existence of more than a dozen resting state networks (RSNs), and combined qEEG and fMRI have allowed us to gain understanding about the relationship of qEEG and fMRI-RSNs. However, the overall picture is less clear because there is no a priori hypothesis about which EEG features correspond well to fMRI-RSNs. We reviewed the associations of several types of qEEG features to four RSNs considered as neurocognitive systems central for higher brain processes: the default mode network, dorsal and ventral frontoparietal networks, and the salience network. We could identify 12 papers correlating qEEG and RSNs in adult human subjects and employing a simultaneous design under a no-task resting state condition. A systematic overview investigates which qEEG features replicably relate to the chosen RSNs. This review article leads to the conclusion that spatially delimited θ and whole/local α may be the most promising measures, but the time domain methods add important additional information.

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“…To identify the FCNs on a pure data driven basis, we used a temporally concatenated group level ICA approach (Calhoun et al 2001(Calhoun et al , 2004Horn et al 2012). For this purpose, the individual flow time series were normalized (scaled between 0 and 1) to reduce the inter-subject variability in the CBF data while maintaining the relative temporal signal fluctuations.…”

Section: Ica Decomposition and Identification Of Networkmentioning

confidence: 99%

“…Based on the group ICA results we calculated for each subject its specific spatial map using a back-reconstruction approach based on dual spatio-temporal regression (Calhoun et al 2004;Horn et al 2012). Therefore we used the z-transformed GC timeseries (segmented into the timeperiods corresponding to the individual subjects) as regressors in single subject GLMs (dependent variable were the original, unscaled CBF timeseries; motion parameters were not included in the GLM (Erhardt et al 2010).…”

Section: Estimation Of Subject Specific Maps (Sms)mentioning

confidence: 99%

Quantification of Network Perfusion in ASL Cerebral Blood Flow Data with Seed Based and ICA Approaches

et al. 2013

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Independent component analysis (ICA) or seed based approaches (SBA) in functional magnetic resonance imaging blood oxygenation level dependent (BOLD) data became widely applied tools to identify functionally connected, large scale brain networks. Differences between task conditions as well as specific alterations of the networks in patients as compared to healthy controls were reported. However, BOLD lacks the possibility of quantifying absolute network metabolic activity, which is of particular interest in the case of pathological alterations. In contrast, arterial spin labeling (ASL) techniques allow quantifying absolute cerebral blood flow (CBF) in rest and in task-related conditions. In this study, we explored the ability of identifying networks in ASL data using ICA and to quantify network activity in terms of absolute CBF values. Moreover, we compared the results to SBA and performed a test-retest analysis. Twelve healthy young subjects performed a fingertapping block-design experiment. During the task pseudo-continuous ASL was measured. After CBF quantification the individual datasets were concatenated and subjected to the ICA algorithm. ICA proved capable to identify the somato-motor and the default mode network. Moreover, absolute network CBF within the separate networks during either condition could be quantified. We could demonstrate that using ICA and SBA functional connectivity analysis is feasible and robust in ASL-CBF data. CBF functional connectivity is a novel approach that opens a new strategy to evaluate differences of network activity in terms of absolute network CBF and thus allows quantifying inter-individual differences in the resting state and task-related activations and deactivations.

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Semantic Network Disconnection in Formal Thought Disorder

Cited by 48 publications

References 155 publications

Systems Neuroscience of Psychosis: Mapping Schizophrenia Symptoms onto Brain Systems

Systems Neuroscience of Psychosis: Mapping Schizophrenia Symptoms onto Brain Systems

Integrating Different Aspects of Resting Brain Activity: A Review of Electroencephalographic Signatures in Resting State Networks Derived from Functional Magnetic Resonance Imaging

Quantification of Network Perfusion in ASL Cerebral Blood Flow Data with Seed Based and ICA Approaches

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