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The combination of Transcranial Magnetic Stimulation (TMS) with Electroencephalography (EEG) exposes the brain’s global response to localized and abrupt stimulations. However, large electric artifacts are induced in the EEG by the TMS, obscuring crucial stages of the brain’s response. Artifact removal is commonly performed by data processing techniques. However, an experimentally verified physical model for the origin and structure of the TMS-induced discharge artifacts, by which these methods can be justified or evaluated, is still lacking. We re-examine the known contribution of the skin in creating the artifacts, and outline a detailed model for the relaxation of the charge accumulated at the electrode-gel-skin interface due to the TMS pulse. We then experimentally validate implications set forth by the model. We find that the artifacts decay like a power law in time rather than the commonly assumed exponential. In fact, the skin creates a power-law decay of order 1 at each electrode, which is turned into a power law of order 2 by the reference electrode. We suggest an artifact removal method based on the model which can be applied from times after the pulse as short as 2 milliseconds onwards to expose the full EEG from the brain. The method can separate the capacitive discharge artifacts from those resulting from cranial muscle activation, demonstrating that the capacitive effect dominates at short times. Overall, our insight into the physical process allows us to accurately access TMS-evoked EEG responses that directly follow the TMS pulse, possibly opening new opportunities in TMS-EEG research. [ABSTRACT FROM AUTHOR]

Electroencephalographic (EEG) analysis has emerged as a powerful tool for brain state interpretation and diagnosis, but not for the diagnosis of mental disorders; this may be explained by its low spatial resolution or depth sensitivity. This paper concerns the diagnosis of schizophrenia using EEG, which currently suffers from several cardinal problems: it heavily depends on assumptions, conditions and prior knowledge regarding the patient. Additionally, the diagnostic experiments take hours, and the accuracy of the analysis is low or unreliable. This article presents the “TFFO” (Time-Frequency transformation followed by Feature-Optimization), a novel approach for schizophrenia detection showing great success in classification accuracy with no false positives. The methodology is designed for single electrode recording, and it attempts to make the data acquisition process feasible and quick for most patients. [ABSTRACT FROM AUTHOR]

Highlights: [•] Reaction times and P3b latencies of predicted targets were prolonged in depression. [•] P3b amplitudes were attenuated in major depressive disorder during processing of predictive contextual information, as well as target N1 amplitudes. [•] Processing of local contextual processing is altered in major depressive disorder. [ABSTRACT FROM AUTHOR]

Deficits in processing contextual information are one of the main features of cognitive dysfunction in schizophrenia, but the neurophysiologic substrate underlying this dysfunction is poorly understood. We used ERPs to investigate local contextual processing in schizophrenic patients. Local context was defined as the occurrence of a short predictive series of stimuli occurring before delivery of a target event. Response times of predicted targets were faster in controls compared to patients. Schizophrenia patients failed to generate the P3b latency shift between predicted and random targets that was observed in controls and demonstrated a prominent reduction of the peak of an early latency context dependent positivity. The current study provides evidence of contextual processing deficits in schizophrenia patients by demonstrating alteration in the behavioral and neural correlates of local contextual processing. [ABSTRACT FROM AUTHOR]

Background: Virtual Reality is an interactive three-dimensional computer generated environment. Providing a complex and multi-modal environment, VR can be particularly useful for the study of complex cognitive functions and brain disorders. Here we used a VR world to measure the distortion in reality perception in schizophrenia patients. Methods: 43 schizophrenia patients and 29 healthy controls navigated in a VR environment and were asked to detect incoherencies, such as a cat barking or a tree with red leaves. Results: Whereas the healthy participants reliably detected incoherencies in the virtual experience, 88% of the patients failed in this task. The patients group had specific difficulty in the detection of audio-visual incoherencies; this was significantly correlated with the hallucinations score of the PANSS. Conclusions: By measuring the distortion in reality perception in schizophrenia patients, we demonstrated that Virtual Reality can serve as a powerful experimental tool to study complex cognitive processes. [ABSTRACT FROM AUTHOR]

Summary: In 1895 Freud tried to explain mental disorders using the neurophysiological knowledge of his time. He soon abandoned this attempt realizing it was immature considering the neuroscientific knowledge available to him. For the rest of his career he limited himself to psychological formulations. Along the same lines, lacking etiology for mental disorders, the diagnostic system of psychiatry is exclusively descriptive. The need for a brain related diagnosis of mental disorders is important for developing better treatments and more reliable diagnosis. Today with the development of neuroscience it is time to go back to Freud’s initial attempts and explain mental disorders as altered neuronal organizations in the brain. The neural network level is chosen as the relevant description level for mental functions. Plasticity is chosen as a general concept for neuronal dynamics explaining neuropathology of psychiatric disorders. Plasticity is divided according to timescales into “fast plasticity,” “slow plasticity” and “stable plasticity”. It is proposed that normal mental functions require optimal balance among all the plasticity timescales. Mental disorders arise when such balance is disturbed, thus mental disorders could be reformulated as deficiencies of the different plasticity processes. Changes in coherence synchrony and phase-locking membrane potentials in cortically spread neuronal ensembles are all expressions of fast plasticity. Synaptogenic and neurogenic processes, such as brain derived neurotrophic factor-dependent processes, are defined as slow plasticity. Finally those synaptic and neuronal pathways that consolidated into long lasting circuits are referred to as stable plasticity. With the aid of a neural network model simulating the plasticity imbalance, a mathematical formulation could be realized for mental disorders. Once achieved this mathematical formulation could form a guiding framework for interpreting brain-imaging data collected from psychiatric patients. Such a model is realized using interconnected “modules” each simulating the relevant plasticity dynamics relevant for the model. Diagnosing plasticity imbalance has some advantages over current descriptive psychiatric diagnosis. It is brain-related thus less stigmatising in the sense that mental disorders are brain disorders and not “person” disorders. The diagnostic system is much more flexible allowing for a high degree of variations and combinations in the description of the disorders thus naturally accounting for comorbidities. Most importantly, this diagnostic model is brain-related offering research targets for intervention and a theoretical framework guiding such interventions. [Copyright &y& Elsevier]

Our goal is to develop a new family of automatic tools for the diagnosis of schizophrenia, using Virtual Reality Technology (VRT). VRT is specifically suitable for this purpose, because it allows for multi‐modal stimulation in a complex setup, and the simultaneous measurement of multiple parameters. In this work we studied sensory integration within working memory, in a navigation task through a VR maze. Along the way subjects pass through multiple rooms that include three doors each, only one of which can be used to legally exit the room. Specifically, each door is characterized by three features (color, shape and sound), and only one combination of features – as determined by a transient opening rule – is legal. The opening rule changes over time. Subjects must learn the rule and use it for successful navigation throughout the maze. 39 schizophrenic patients and 21 healthy controls participated in this study. Upon completion, each subject was assigned a performance profile, including various error scores, response time, navigation ability and strategy. We developed a classification procedure based on the subjects' performance profile, which correctly predicted 85% of the schizophrenic patients (and all the controls). We observed that a number of parameters showed significant correlation with standard diagnosis scores (PANSS), suggesting the potential use of our measurements for future diagnosis of schizophrenia. On the other hand, our patients did not show unusual repetition of response despite stimulus cessation (called perseveration in classical studies of schizophrenia), which is usually considered a robust marker of the disease. Interestingly, this deficit only appeared in our study when subjects did not receive proper explanation of the task. [ABSTRACT FROM AUTHOR]

Patients with schizophrenia have thinking disorders such as delusions or hallucinations because they have a deficit in the ability to systematize and integrate information. Therefore, they cannot integrate or systematize visual, auditory, and tactile stimuli. The multimodal integration model of the brain can provide a theoretical background from which one can approach multimodal stimulus integration. In this study, we suggest a virtual reality system for the multi-modal assessment of cognitive ability of schizophrenia patients. The virtual reality system can provide multimodal stimuli, such as visual and auditory stimuli, to the patient and can evaluate the patient's multimodal integration and working memory integration abilities by making the patient interpret and react to multimodal stimuli, which must be remembered for a given period of time. The clinical study showed that the virtual reality program developed is comparable to those of the Wisconsin Card Sorting Test (WCST) and the Standard Progressive Matrices (SPM), and it provides some information related to the schizophrenic patients' behavior in 3D virtual environment. [ABSTRACT FROM AUTHOR]

Presents an electroencephalograph study of functional connectivity and working memory in schizophrenia. Importance of connectivity for simulation of working memory; Failure of schizophrenics to activate the neural networks of the fronto-temporal regions; Findings supporting a 'disconnection syndrome' for schizophrenia.

• Increased functional connectivity during processing of predictive stimuli in MDD. • Functional connectivity changes in beta band and within frontal networks in MDD. • Findings may indicate compensatory mechanisms for neural insufficiency in MDD. The study investigated the underlying mechanisms associated with the ability of patients with major depressive disorder (MDD) to utilize predictive contextual information in order to facilitate detection of predictable versus random targets. To this end we evaluated EEG event-related functional connectivity during the processing of predictive stimuli in MDD and control subjects. A target detection task was used where targets were either preceded by randomized sequences of standards, or by sequences that included a predictive sequence. Functional connectivity was evaluated using synchronization likelihood and graph theory. The cluster coefficient and local efficiency values were greater in MDD compared to controls, during the processing of the three stimuli consisting of the predictive sequence, in the beta frequency band, suggesting an increased structured network organization. These changes were associated with increased functional connectivity within frontal networks in MDD patients compared to controls. However, no significant functional connectivity group-changes were observed for target conditions or randomized standards. These findings suggest that MDD is associated with context-specific functional connectivity abnormalities during the processing of predictive stimuli. [ABSTRACT FROM AUTHOR]

Background: Virtual Reality is an interactive three-dimensional computer generated environment. Providing a complex and multi-modal environment, VR can be particularly useful for the study of complex cognitive functions and brain disorders. Here we used a VR world to measure the distortion in reality perception in schizophrenia patients., Methods: 43 schizophrenia patients and 29 healthy controls navigated in a VR environment and were asked to detect incoherencies, such as a cat barking or a tree with red leaves., Results: Whereas the healthy participants reliably detected incoherencies in the virtual experience, 88% of the patients failed in this task. The patients group had specific difficulty in the detection of audio-visual incoherencies; this was significantly correlated with the hallucinations score of the PANSS., Conclusions: By measuring the distortion in reality perception in schizophrenia patients, we demonstrated that Virtual Reality can serve as a powerful experimental tool to study complex cognitive processes.

There is growing dissatisfaction regarding the available diagnostic systems for psychiatric disorders (DSM, ICD). Psychiatrists acknowledge that though mental disease reflects brain disorders, the descriptive and symptom based nature of psychiatric diagnosis bears no relation to brain functions. According to Helmut's article published in the October 2003 issue of Science, in the coming decade researchers and psychiatrists will be called upon to propose a basis for the psychiatric diagnostic system of the future. I propose a new etiology-oriented diagnostic system for psychiatry by integrating two recently emerging bodies of knowledge, one regarding plasticity and the other involving complex systems. Plasticity refers to all brain processes involved in dynamic alterations within communicating neuronal ensembles or networks, in the brain. Complexity refers to certain formulations from system theories relevant to brain dynamics and plasticity. It is proposed to divide plasticity processes into three types based on time domains: (1) "developmental plasticity", (2) "tuning plasticity" and (3) "fast stabilizing plasticity". Each type of plasticity is related to different complexity models achieved by the brain, developmental plasticity is life-long brain organization, it is related to state-space configurations molded into brain representations internalized via processes such as Hebbian learning. Tuning plasticity is related to "matching complexity" a measure of adaptability between internal configurations in the brain-system and externally originating event stimuli. Fast stabilizing plasticity is related to "neural complexity" a measure of neural network integration in the brain. Neural complexity meets the mental requirement to extract important features from different sensory inputs and to simultaneously generate coherent perceptual and cognitive states, thus balancing specialized segregated brain processes with coherent globally integrated whole brain activity. Mental disorders can be reconceptualized as disorders of plasticity resulting in disturbances of state-space brain configurations, matching and neural complexities. Personality disorders result from altered internal representations of the psychosocial environment. Depression and anxiety have been recently linked to alterations of adaptive neuronal plasticity thus reconceptualized as disorders of matching complexity. Finally, psychoses, including schizophrenia spectrum disorders, are reconceptualized as disturbances of neural complexity resulting in altered fast stabilizing plasticity. The new diagnostic system generates testable predictions regarding diagnosis and treatments of mental disorders which may be the future of psychiatry.

Patients with schizophrenia have thinking disorders such as delusions or hallucinations because they have a deficit in the ability to systematize and integrate information. Therefore, they cannot integrate or systematize visual, auditory, and tactile stimuli. The multimodal integration model of the brain can provide a theoretical background from which one can approach multimodal stimulus integration. In this study, we suggest a virtual reality system for the multi-modal assessment of cognitive ability of schizophrenia patients. The virtual reality system can provide multimodal stimuli, such as visual and auditory stimuli, to the patient and can evaluate the patient's multimodal integration and working memory integration abilities by making the patient interpret and react to multimodal stimuli, which must be remembered for a given period of time. The clinical study showed that the virtual reality program developed is comparable to those of the Wisconsin Card Sorting Test (WCST) and the Standard Progressive Matrices (SPM), and it provides some information related to the schizophrenic patients' behavior in 3D virtual environment.