Functional connectivity abnormalities during processing of predictive stimuli in patients with major depressive disorder.

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.

A quantitative physical model of the TMS-induced discharge artifacts in EEG.

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.

Schizophrenia detection and classification by advanced analysis of EEG recordings using a single electrode approach.

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.

The functional anatomy of schizophrenia: A dynamic causal modeling study of predictive coding.

This paper tests the hypothesis that patients with schizophrenia have a deficit in selectively attending to predictable events. We used dynamic causal modeling (DCM) of electrophysiological responses - to predictable and unpredictable visual targets - to quantify the effective connectivity within and between cortical sources in the visual hierarchy in 25 schizophrenia patients and 25 age-matched controls. We found evidence for marked differences between normal subjects and schizophrenia patients in the strength of extrinsic backward connections from higher hierarchical levels to lower levels within the visual system. In addition, we show that not only do schizophrenia subjects have abnormal connectivity but also that they fail to adjust or optimize this connectivity when events can be predicted. Thus, the differential intrinsic recurrent connectivity observed during processing of predictable versus unpredictable targets was markedly attenuated in schizophrenia patients compared with controls, suggesting a failure to modulate the sensitivity of neurons responsible for passing sensory information of prediction errors up the visual cortical hierarchy. The findings support the proposed role of abnormal connectivity in the neuropathology and pathophysiology of schizophrenia.

Local contextual processing in major depressive disorder.

OBJECTIVE: The study investigated local contextual processing in patients with major depressive disorder (MDD). This was defined as the ability to utilize predictive contextual information to facilitate detection of predictable versus random targets. METHOD: We recorded EEG in 15 MDD patients and 14 age-matched controls. Recording blocks consisted of targets preceded by randomized sequences of standards and by sequences of standards that included a predictive sequence signaling the occurrence of a subsequent target event. RESULTS: Both MDD patients and age-matched controls demonstrated a significant reaction time (RT) and P3b latency differences between predicted and random targets. However, patients demonstrated a specific prolongation of these measures during processing of predicted targets, as well as an attenuation of P3b amplitudes for the predictive sequence. In addition, patients target N1 amplitudes were attenuated compared with controls. CONCLUSION: MDD patients were able to utilize predictive context in order to facilitate processing of deterministic targets, however, this ability was limited compared to controls, as demonstrated by context-dependent P3b deficits. SIGNIFICANCE: These findings suggest that patients with major depression have altered processing of local contextual processing.

Functional connectivity abnormalities during contextual processing in schizophrenia and in Parkinson's disease.

Functional connectivity was evaluated in patients with schizophrenia (SC) and in patients with Parkinson's disease (PD) during the performance of a local contextual processing paradigm, to investigate the proposition that functional disconnection is involved with contextual processing deficits in these populations. To this end, we utilized event-related EEG signals, synchronization likelihood and graph theoretical analysis. Local context was defined as the occurrence of a predictive sequence of stimuli before the presentation of a target event. In the SC patients, we observed a decrease in path length (L) in the beta band, for the predictive sequence and for predicted and random targets, compared with controls. These abnormalities were associated with weaker frontal-temporal-parietal connections. In the PD patients we found longer L (theta band) for predicted targets, and higher cluster coefficients for both the predictive sequence (theta band) and predicted targets (alpha and theta bands), compared with controls. Detection of predicted targets was associated with weaker frontal-parietal connections in PD. No group differences were found for randomized standard stimuli in both SC and PD patients. These findings provide evidence of task-specific functional connectivity abnormalities within frontal networks during local contextual processing.

Personality disorders disturbances of the physical brain.

How can physical systems of the brain, explain a psychological phenomenon such as personality? Personality is an emergent property of the brain as such it requires interacting elements that generate a whole. Per definition a physical system is a compound whole made of interacting interdependent elements. The brain is composed of multiple levels of elements ranging from single neurons interconnected by axons dendrites and synapses, up to brain regions and neural network ensembles connected by multiple modalities, from direct physical pathways to synchronized functional connectivity. Today we know that the brain develops and wires according to the influences of its environment, this is called "experience dependent plasticity" and follows Hebbian-like algorithms. Such process "embeds" into the brain internal representations in the form of physical attractor configurations distributed within the brain neural-networks. Development entails formation of personal individual-specific network configurations found recently as resting-state networks or "default-mode networks." These internal configurations represent the outer world to us and determine the way we perceive it and react to it. In other words these internal configurations determine our personality styles. The internal representations continuously adapt to the changing worlds offering good adaptability and effective functionality in our changing environments. Personality disorders are reconceptualized in terms of altered disturbed mal-developed default-mode-networks, such that the internal representations are biased, limited, fixated and non-adaptive. In this context therapy of personality disorders can be reconceptualized as experience-depended plasticity therapy.

Neuroanalysis: a method for brain-related neuroscientific diagnosis of mental disorders.

BACKGROUND: As an Ancient Chinese proverb says "The beginning of wisdom is to call things by their right names" thus we must start calling mental disorders by the names of their underlying brain disturbances. Without knowledge of the causes of mental disorders, their cures will remain elusive. METHODS: Neuroanalysis is a literature-based re-conceptualization of mental disorders as disturbances of brain organization. Psychosis and schizophrenia can be re-conceptualized as disturbances to connectivity and hierarchical dynamics in the brain; mood disorders can be re-conceptualized as disturbances to optimization dynamics and free energy in the brain, and finally personality disorders can be re-conceptualized as disordered default-mode networks in the brain. RESULTS AND CONCLUSIONS: Knowledge and awareness of the disease algorithms of mental disorders will become critical because powerful technologies for controlling brain activity are developing and becoming available. The time will soon come when psychiatrists will be asked to define the exact 'algorithms' of disturbances in their psychiatric patients. Neuroanalysis can be a starting point for the response to that challenge.

Optogenetic neuronal control in schizophrenia.

Schizophrenia is a serious mental disorder characterized by a heterogeneous spectrum of clinical manifestations. Schizophrenia is basically incurable. The discovery of antipsychotic medications in the late 1940s has helped control some of the symptoms but has not reversed the course of the disorder and has had limited effect on the debilitating symptoms of the illness. In recent years brain stimulation technologies have emerged in the bio-scientific scenery. Deep brain stimulation now plays an important role in the treatment of many neurological disorders, and seems promising in treating depression. Optogenetics is a new technology that offers control over neuronal activity by turning on and off distinct neuronal populations. It has a great advantage over previous brain stimulation technologies in that it is accurate and specific to the neurons intended for activation and control. There is no evidence that brain stimulation has been investigated in schizophrenia patients. This possibility was discussed in a single commentary that proposed the hippocampus and nucleus accumbence as targets for DBS in schizophrenia, however it was emphasized that the neurophysiology and neuroanatomy of schizophrenia have not been elucidated to the extent that brain stimulation can be planned. In light of new optogenetic technology time is ripe to seriously consider optional targets of intervention in the brain of schizophrenia patients. Any such target should involve neuronal circuits (1) known to be relevant for schizophrenia, (2) involved in cognitive and brain functions that are disturbed in schizophrenia, and (3) relevant to alleged neuronal network mechanisms that are presumably damaged or malfunctioning in schizophrenia. This paper reviews the relevant literature and proposes that optogenetic interventions in schizophrenia should begin in the prefrontal cortex and the Globus-Pallidus Subthalamic nuclei systems. In the protocol for the prefrontal cortex, wide-arbore and chandelier inhibitory interneurons should be targets for optogenetic intervention and in the Globus-Pallidus Subthalamic nuclei the fast spiking neurons should be targets for optogenetic intervention. These subsystems are critical modulators of neural complexity which is directly relevant to connectivity organization in the brain. Schizophrenia is described as a disturbance of connectivity organization in the brain treatable by the relevant optogenetic interventions promoted in this paper.

Neural correlates of local contextual processing deficits in schizophrenic patients.

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.

The neurophysics of psychiatric diagnosis: clinical brain profiling.

As early as the end of the 19th century Ernest Bruck declared that the brain is a physical entity and should be studied using the science of mathematics and physics. The brain is an extremely intricate physical entity and we have only recently begun to develop the conceptual tools to decipher this complexity. We can begin to comprehend many of the mental functions and dysfunctions by using insights about brain organization as a developing physical entity of connectivity structures. A comprehensive theoretical framework for the re-conceptualization of mental disorders as real brain-disorders, called "Clinical brain profiling" can be generated to make testable predictions about the etiopathology of psychiatric disorders. If validated, this framework has groundbreaking relevance for psychiatry, not only by providing an etiological diagnostic system, in itself revolutionary, but in its potential to develop effective curative interventions. According to the proposed brain profiling all mental disturbances can be defined in a 3 dimensional space of brain disturbances (1) neural-complexity organization, (2) to neural resilience optimization dynamics and (3) to connectivity constructs for context and internal representations. Neural complexity relates to the ability of the brain to balance connectivity dynamics, neural resilience relates to brain plasticity and changeability for optimizing overall brain dynamics and contextual configurations shape the internal representations of outer world that pattern out reaction and personality styles. Each of these organizational brain functions is predicted to involve a relatively specific neuronal circuitry system in the brain. The circuitry of the nigra-striautum-cortex, are a component of the connectivity balance stabilizers and regulators, a type of neural complexity pacemaker. Thus a patient that rates high on phenomenology related to functional psychosis indicating a disturbance to connectivity balance will have disturbances that will show up in appropriate signal processing imaging of the nigra-striautum-cortex circuitry. The circuitry of thalamus-amygdala-cortex and related pathways are relevant for neuronal matching and constraint frustration. In this respect the patients scoring high on mood and anxiety disorders are predicted to suffer from perturbation shown on appropriate imaging involving the thalamus-amygdala-cortex circuitries. The hippocampus is related to the formation of internal configurations thus those patients rating highest on parameters related to personality organization and maturation will show alterations in the hippocampal organization and activation indicating deficient organizations of internal configurations.

Differences in TMS-evoked responses between schizophrenia patients and healthy controls can be observed without a dedicated EEG system.

OBJECTIVE: The combination of transcranial magnetic stimulation (TMS) and electroencephalography (EEG) has been hampered by the large artifact that the TMS generates in the EEG. Using TMS with EEG necessitates a sophisticated artifact-resistant EEG system that can acquire reliable signals in the crucial several tens of milliseconds immediately following the TMS pulse. Here, we demonstrate the use of a novel artifact removal algorithm together with a 24-bit EEG system to achieve similar recordings as those obtained with the dedicated TMS-compatible EEG system. METHODS: This setup was used to compare TMS-evoked responses between a group of healthy controls and a group of patients with schizophrenia, a condition in which effective neural connectivity is thought to be compromised. RESULTS: We observe differences in TMS-evoked responses between the two groups, similar to those recently reported in a study that used a dedicated TMS-compatible EEG system. CONCLUSIONS: The standard 24-bit EEG system combined with an artifact removal algorithm produces results similar to the dedicated TMS-compatible system. SIGNIFICANCE: This paves the way for more researchers and clinicians to use TMS-evoked responses for research and diagnosis of a wide spectrum of disorders.

Neuroscientific psychiatric diagnosis.

The DSM is not brain-related and is thus unable to relate clinical assessments to putative brain disturbances. 'Clinical brain profiling' (CBP) involves the rearrangement of clinical findings to assess the relevant disturbances in brain dynamics. CBP has three major pathological dimensions, (1) disorders of basic brain organization and development (2) disorders of connectivity dynamics and balance and (3) disorders of plasticity dynamics and neural resilience. CBP is a useful platform for the development of a brain-related neuroscientific diagnosis for psychiatry. Once the underlying pathology of a mental disorder is known an effective intervention can be designed to cure the disorder.

The distortion of reality perception in schizophrenia patients, as measured in Virtual Reality.

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.

Transcranial magnetic stimulation in a finger-tapping task separates motor from timing mechanisms and induces frequency doubling.

We study the interplay between motor programs and their timing in the brain by using precise pulses of transcranial magnetic stimulation (TMS) applied to the primary motor cortex. The movement of the finger performing a tapping task is periodically perturbed in synchronization with a metronome. TMS perturbation can profoundly affect both the finger trajectory and its kinematics, but the tapping accuracy itself is surprisingly not affected. The motion of the finger during the TMS perturbation can be categorized into two abnormal behaviors that subjects were unaware of: a doubling of the frequency of the tap and a stalling of the finger for half the period. More stalls occurred as the tapping frequency increased. In addition, an enhancement of the velocity of the finger on its way up was observed. We conclude that the timing process involved in controlling the tapping movement is separate from the motor processes in charge of execution of the motor commands. We speculate that the TMS is causing a release of the motor plan ahead of time into activation mode. The observed doubles and stalls are then the result of an indirect interaction in the brain, making use of an existing motor plan to correct the preactivation and obtain the temporal goal of keeping the beat.

Transcranial Magnetic Stimulation at M1 disrupts cognitive networks in schizophrenia.

Transcranial Magnetic Stimulation (TMS) is rapidly gaining acceptance as a non-invasive probe into brain functionality. We utilize TMS to study the connectivity of a simple motor network in patients of schizophrenia (N=19), and in healthy control subjects (N=9). TMS was used in an externally paced finger tapping task, perturbing the internal network oscillations invoked by the finger motion as it keeps pace with a metronome. TMS perturbations were synchronized to the metronome and applied to the network at the level of the primary motor cortex (M1). Contrary to initial expectations, TMS did not affect the sensorimotor synchronization of subjects with schizophrenia or their tapping accuracy. TMS did cause extreme deviations in the finger's trajectory, and altered the timing perceptions of subjects with schizophrenia. Additionally, it invoked high-level deficiencies related to attention and volition in the form of lapses, implying that the connectivity between modules in the brain that underlie motor control, sensorimotor synchronization, timing perception and awareness of action, can be disrupted by TMS in subjects with schizophrenia, but not in healthy subjects. The ability to disrupt high level network functions with perturbations to the lower level of M1 supports models describing deficits in connectivity of distributed networks in the brains of schizophrenia patients. It also demonstrates the use of TMS to probe connectivity between components of such networks.

Brain profiling and clinical-neuroscience.

The current psychiatric diagnostic system, the diagnostic statistic manual, has recently come under increasing criticism. The major reason for the shortcomings of the current psychiatric diagnosis is the lack of a scientific brain-related etiological knowledge about mental disorders. The advancement toward such knowledge is further hampered by the lack of a theoretical framework or "language" that translates clinical findings of mental disorders to brain disturbances and insufficiencies. Here such a theoretical construct is proposed based on insights from neuroscience and neural-computation models. Correlates between clinical manifestations and presumed neuronal network disturbances are proposed in the form of a practical diagnostic system titled "Brain Profiling". Three dimensions make-up brain profiling, "neural complexity disorders", "neuronal resilience insufficiency", and "context-sensitive processing decline". The first dimension relates to disturbances occurring to fast neuronal activations in the millisecond range, it incorporates connectivity and hierarchical imbalances appertaining typically to psychotic and schizophrenic clinical manifestations. The second dimension relates to disturbances that alter slower changes namely long-term synaptic modulations, and incorporates disturbances to optimization and constraint satisfactions within relevant neuronal circuitry. Finally, the level of internal representations related to personality disorders is presented by a "context-sensitive process decline" as the third dimension. For practical use of brain profiling diagnosis a consensual list of psychiatric clinical manifestations provides a "diagnostic input vector", clinical findings are coded 1 for "detection" and 0 for "non-detection", 0.5 is coded for "questionable". The entries are clustered according to their presumed neuronal dynamic relationships and coefficients determine their relevance to the specific related brain disturbance. Relevant equations calculate and normalize the different values attributed to relevant brain disturbances culminating in a three-digit estimation representing the three diagnostic dimensions. brain profiling has the promise for a future brain-related diagnosis. It offers testable predictions about the etiology of mental disorders because being brain-related it lends readily to brain imaging investigations. Being presented also as a one-point representation in a three-dimensional space, multiple follow-up diagnoses trace a trajectory representing an easy-to-see clinical history of the patient. Additional, more immediate, advantages involve reduced stigma because it relaters the disorder to the brain not the person, in addition the three-digit diagnostic code is clinically informative unlike the DSM codes that have no clinical relevance. To conclude, brain profiling diagnosis of mental disorders could be a bold new step toward a "clinical-neuroscience" substituting "psychiatry".

Serotonin transporter characteristics in lymphocytes and platelets of male aggressive schizophrenia patients compared to non-aggressive schizophrenia patients.

A large body of literature indicates that disturbances of central serotonin (5-HT) function play an important role in aggressive behavior. Results from open-label and placebo-controlled trials as well as the reported inverse relationship between 5-HT function and aggression in human subjects, suggest that reduced 5-HT activity is associated with aggressive behavior. The activity of the 5-HT transporter (5-HTT), as determined by [(3)H]5-HT uptake to blood lymphocytes, was measured in 20 currently aggressive and 20 non-aggressive male schizophrenia patients. In addition, the pharmacodynamic characteristics of platelet 5-HTT were assessed by [(3)H]citalopram binding. There were no significant differences in the density (B(max)) of platelet [(3)H]citalopram binding sites between the two groups. Similarly, the dissociation constant (K(d)) values were indistinguishable. The maximum uptake velocity (V(max)) of [(3)H]5-HT to fresh lymphocytes and the K(m) values of the 5-HT to the transporter were significantly higher in currently aggressive compared to the non-aggressive schizophrenia patients. The association of high V(max) values with current aggressive behavior provides further support to the involvement of the 5-HTT in aggressive behavior as well as to the efficacy of 5-HTT blockers in the control of aggression. The role of the various components of the serotonergic system in the pathophysiology and treatment of aggressive behavior in schizophrenia needs to be further evaluated.

Improving the accuracy of the diagnosis of schizophrenia by means of virtual reality.

OBJECTIVE: The authors' goal was to improve the diagnosis of schizophrenia by using virtual reality technology to build a complex, multimodal environment in which cognitive functions can be studied (and measured) in parallel. METHOD: The authors studied sensory integration within working memory by means of computer navigation through a virtual maze. The simulated journey consisted of a series of rooms, each of which included three doors. Each door was characterized by three features (color, shape, and sound), and a single combination of features--the door-opening rule--was correct. Subjects had to learn the rule and use it. The participants were 39 schizophrenic patients and 21 healthy comparison subjects. RESULTS: Upon completion, each subject was assigned a performance profile, including various error scores, response time, navigation ability, and strategy. A classification procedure based on the subjects' performance profile correctly predicted 85% of the schizophrenic patients (and all of the comparison subjects). Several performance variables showed significant correlations with scores on a standard diagnostic measure (Positive and Negative Syndrome Scale), suggesting potential use of these measurements for the diagnosis of schizophrenia. On the other hand, the patients did not show unusual repetition of response despite stimulus cessation (called "perseveration" in classical studies of schizophrenia), which is a common symptom of the disease. This deficit appeared only when the subjects did not receive proper explanation of the task. CONCLUSIONS: The ability to study multimodal performance simultaneously by using virtual reality technology opens new possibilities for the diagnosis of schizophrenia with objective procedures.