Reduction of Pavlovian Bias in Schizophrenia: Enhanced Effects in Clozapine-Administered Patients

The negative symptoms of schizophrenia (SZ) are associated with a pattern of reinforcement learning (RL) deficits likely related to degraded representations of reward values. However, the RL tasks used to date have required active responses to both reward and punishing stimuli. Pavlovian biases have been shown to affect performance on these tasks through invigoration of action to reward and inhibition of action to punishment, and may be partially responsible for the effects found in patients. Forty-five patients with schizophrenia and 30 demographically-matched controls completed a four-stimulus reinforcement learning task that crossed action (“Go” or “NoGo”) and the valence of the optimal outcome (reward or punishment-avoidance), such that all combinations of action and outcome valence were tested. Behaviour was modelled using a six-parameter RL model and EEG was simultaneously recorded. Patients demonstrated a reduction in Pavlovian performance bias that was evident in a reduced Go bias across the full group. In a subset of patients administered clozapine, the reduction in Pavlovian bias was enhanced. The reduction in Pavlovian bias in SZ patients was accompanied by feedback processing differences at the time of the P3a component. The reduced Pavlovian bias in patients is suggested to be due to reduced fidelity in the communication between striatal regions and frontal cortex. It may also partially account for previous findings of poorer “Go-learning” in schizophrenia where “Go” responses or Pavlovian consistent responses are required for optimal performance. An attenuated P3a component dynamic in patients is consistent with a view that deficits in operant learning are due to impairments in adaptively using feedback to update representations of stimulus value.     

Evidence for Anomalous Network Connectivity during Working Memory Encoding in Schizophrenia: An ICA Based Analysis

Background

Numerous neuroimaging studies report abnormal regional brain activity during working memory performance in schizophrenia, but few have examined brain network integration as determined by “functional connectivity” analyses.

Methodology/Principal Findings

We used independent component analysis (ICA) to identify and characterize dysfunctional spatiotemporal networks in schizophrenia engaged during the different stages (encoding and recognition) of a Sternberg working memory fMRI paradigm. 37 chronic schizophrenia and 54 healthy age/gender-matched participants performed a modified Sternberg Item Recognition fMRI task. Time series images preprocessed with SPM2 were analyzed using ICA. Schizophrenia patients showed relatively less engagement of several distinct “normal” encoding-related working memory networks compared to controls. These encoding networks comprised 1) left posterior parietal-left dorsal/ventrolateral prefrontal cortex, cingulate, basal ganglia, 2) right posterior parietal, right dorsolateral prefrontal cortex and 3) default mode network. In addition, the left fronto-parietal network demonstrated a load-dependent functional response during encoding. Network engagement that differed between groups during recognition comprised the posterior cingulate, cuneus and hippocampus/parahippocampus. As expected, working memory task accuracy differed between groups (p<0.0001) and was associated with degree of network engagement. Functional connectivity within all three encoding-associated functional networks correlated significantly with task accuracy, which further underscores the relevance of abnormal network integration to well-described schizophrenia working memory impairment. No network was significantly associated with task accuracy during the recognition phase.

Conclusions/Significance

This study extends the results of numerous previous schizophrenia studies that identified isolated dysfunctional brain regions by providing evidence of disrupted schizophrenia functional connectivity using ICA within widely-distributed neural networks engaged for working memory cognition.     

INITIAL CARE OF ACUTE BACK INJURIES

The mechanism of injury to the back should be obtained with the utmost accuracy and set down in the history as a separate paragraph under that heading. This is usually best obtained by questioning and requestioning the patient during the course of the examination. A history of any previous back affections should also be obtained at the first visit.The detailed examination of the back is not complete without a general physical examination.X-ray studies should be done immediately in all cases in which the injury has been caused by direct violence or forceful indirect violence (as in “jackknife” injury).Terms such as “disc disease,” “ruptured intervertebral disc” and various others that convey a similar meaning should not be used as the initial diagnosis and should be withheld until such a diagnosis is definitely established.The plan of treatment may include a period in hospital or of rest at home, or it may be carried out with the patient ambulatory. Corsets and braces should be prescribed only when they are to serve a definite function and the same can be said of physiotherapy.     

A Sensitive and Specific Neural Signature for Picture-Induced Negative Affect

Neuroimaging has identified many correlates of emotion but has not yet yielded brain representations predictive of the intensity of emotional experiences in individuals. We used machine learning to identify a sensitive and specific signature of emotional responses to aversive images. This signature predicted the intensity of negative emotion in individual participants in cross validation (n =121) and test (n = 61) samples (high–low emotion = 93.5% accuracy). It was unresponsive to physical pain (emotion–pain = 92% discriminative accuracy), demonstrating that it is not a representation of generalized arousal or salience. The signature was comprised of mesoscale patterns spanning multiple cortical and subcortical systems, with no single system necessary or sufficient for predicting experience. Furthermore, it was not reducible to activity in traditional “emotion-related” regions (e.g., amygdala, insula) or resting-state networks (e.g., “salience,” “default mode”). Overall, this work identifies differentiable neural components of negative emotion and pain, providing a basis for new, brain-based taxonomies of affective processes.     

Auditory Stimuli Mimicking Ambient Sounds Drive Temporal “Delta-Brushes” in Premature Infants

In the premature infant, somatosensory and visual stimuli trigger an immature electroencephalographic (EEG) pattern, “delta-brushes,” in the corresponding sensory cortical areas. Whether auditory stimuli evoke delta-brushes in the premature auditory cortex has not been reported. Here, responses to auditory stimuli were studied in 46 premature infants without neurologic risk aged 31 to 38 postmenstrual weeks (PMW) during routine EEG recording. Stimuli consisted of either low-volume technogenic “clicks” near the background noise level of the neonatal care unit, or a human voice at conversational sound level. Stimuli were administrated pseudo-randomly during quiet and active sleep. In another protocol, the cortical response to a composite stimulus (“click” and voice) was manually triggered during EEG hypoactive periods of quiet sleep. Cortical responses were analyzed by event detection, power frequency analysis and stimulus locked averaging. Before 34 PMW, both voice and “click” stimuli evoked cortical responses with similar frequency-power topographic characteristics, namely a temporal negative slow-wave and rapid oscillations similar to spontaneous delta-brushes. Responses to composite stimuli also showed a maximal frequency-power increase in temporal areas before 35 PMW. From 34 PMW the topography of responses in quiet sleep was different for “click” and voice stimuli: responses to “clicks” became diffuse but responses to voice remained limited to temporal areas. After the age of 35 PMW auditory evoked delta-brushes progressively disappeared and were replaced by a low amplitude response in the same location. Our data show that auditory stimuli mimicking ambient sounds efficiently evoke delta-brushes in temporal areas in the premature infant before 35 PMW. Along with findings in other sensory modalities (visual and somatosensory), these findings suggest that sensory driven delta-brushes represent a ubiquitous feature of the human sensory cortex during fetal stages and provide a potential test of functional cortical maturation during fetal development.     

WANTED: A BIOCHEMICAL TEST FOR SCHIZOPHRENIA

Recent discoveries and refinements in technique in the field of biochemistry have led to renewed interest in the idea that a test can be developed for the diagnosis of schizophrenia. Studies directed toward that goal have included investigations of biological amines, carbohydrate metabolism, epinephrine metabolism, serotonin, taraxein and ceruloplasmin. No conclusive evidence of any biochemical abnormality in schizophrenia has been found. Although careful studies in adults have failed to confirm a theory that ceruloplasmin levels are abnormally high in schizophrenia, the surmise that it might be true in schizophrenic children was investigated, since constitutional factors seem to be very important in this condition. Thirty-four schizophrenic children and a control group of 13 “behavior problem” children were investigated. No difference was found between the two groups in serum content of copper, ceruloplasmin or ascorbic acid.     

Reappraising the variability of effects of antipsychotic medication in schizophrenia: a meta‐analysis

It is common experience for practising psychiatrists that individuals with schizophrenia vary markedly in their symptomatic response to antipsychotic medication. What is not clear, however, is whether this variation reflects variability of medication‐specific effects (also called “treatment effect heterogeneity”), as opposed to variability of non‐specific effects such as natural symptom fluctuation or placebo response. Previous meta‐analyses found no evidence of treatment effect heterogeneity, suggesting that a “one size fits all” approach may be appropriate and that efforts at developing personalized treatment strategies for schizophrenia are unlikely to succeed. Recent advances indicate, however, that earlier approaches may have been unable to accurately quantify treatment effect heterogeneity due to their neglect of a key parameter: the correlation between placebo response and medication‐specific effects. In the present paper, we address this shortcoming by using individual patient data and study‐level data to estimate that correlation and quantitatively characterize antipsychotic treatment effect heterogeneity in schizophrenia. Individual patient data (on 384 individuals who were administered antipsychotic treatment and 88 who received placebo) were obtained from the Yale University Open Data Access (YODA) database. Study‐level data were obtained from a meta‐analysis of 66 clinical trials including 17,202 patients. Both individual patient and study‐level analyses yielded a negative correlation between placebo response and treatment effect for the total score on the Positive and Negative Syndrome Scale (PANSS) (ρ=–0.32, p=0.002 and ρ=–0.39, p<0.001, respectively). Using the most conservative of these estimates, a meta‐analysis of treatment effect heterogeneity provided evidence of a marked variability in antipsychotic‐specific effects between individuals with schizophrenia, with the top quartile of patients experiencing beneficial treatment effects of 17.7 points or more on the PANSS total score, while the bottom quartile presented a detrimental effect of treatment relative to placebo. This evidence of clinically meaningful treatment effect heterogeneity suggests that efforts to personalize antipsychotic treatment of schizophrenia have potential for success.     

Schizophrenia as a Network Disease: Disruption of Emergent Brain Function in Patients with Auditory Hallucinations

Schizophrenia is a psychiatric disorder that has eluded characterization in terms of local abnormalities of brain activity, and is hypothesized to affect the collective, “emergent” working of the brain. Indeed, several recent publications have demonstrated that functional networks in the schizophrenic brain display disrupted topological properties. However, is it possible to explain such abnormalities just by alteration of local activation patterns? This work suggests a negative answer to this question, demonstrating that significant disruption of the topological and spatial structure of functional MRI networks in schizophrenia (a) cannot be explained by a disruption to area-based task-dependent responses, i.e. indeed relates to the emergent properties, (b) is global in nature, affecting most dramatically long-distance correlations, and (c) can be leveraged to achieve high classification accuracy (93%) when discriminating between schizophrenic vs control subjects based just on a single fMRI experiment using a simple auditory task. While the prior work on schizophrenia networks has been primarily focused on discovering statistically significant differences in network properties, this work extends the prior art by exploring the generalization (prediction) ability of network models for schizophrenia, which is not necessarily captured by such significance tests.     

Clinical Presentation of Acute Abdomen: Study of 600 Patients

This paper presents the clinical features of 600 patients suffering from abdominal pain of acute onset and admitted to either the General Infirmary or St. James''s Hospital, Leeds. The survey was initially retrospective, but later put on a prospective basis. Roughly two-thirds of these 600 patients presented a “typical” picture of the disease with which they presented, while the remaining third presented one or more atypical features. Since other prospective studies have indicated that the diagnostic accuracy of a group of clinicians in respect of the acute abdomen is roughly 65% it is tentatively suggested (a) that clinical diagnosis contains a large element of “pattern-matching,” and (b) that such a policy can be expected to be ineffective in roughly one-third of all cases of acute abdominal pain.     

Cortical Source Analysis of High-Density EEG Recordings in Children

EEG is traditionally described as a neuroimaging technique with high temporal and low spatial resolution. Recent advances in biophysical modelling and signal processing make it possible to exploit information from other imaging modalities like structural MRI that provide high spatial resolution to overcome this constraint¹. This is especially useful for investigations that require high resolution in the temporal as well as spatial domain. In addition, due to the easy application and low cost of EEG recordings, EEG is often the method of choice when working with populations, such as young children, that do not tolerate functional MRI scans well. However, in order to investigate which neural substrates are involved, anatomical information from structural MRI is still needed. Most EEG analysis packages work with standard head models that are based on adult anatomy. The accuracy of these models when used for children is limited², because the composition and spatial configuration of head tissues changes dramatically over development³. In the present paper, we provide an overview of our recent work in utilizing head models based on individual structural MRI scans or age specific head models to reconstruct the cortical generators of high density EEG. This article describes how EEG recordings are acquired, processed, and analyzed with pediatric populations at the London Baby Lab, including laboratory setup, task design, EEG preprocessing, MRI processing, and EEG channel level and source analysis.      

Increased Intra-Individual Variability of Cognitive Processing in Subjects at Risk Mental State and Schizophrenia Patients

Intra-individual variability (IIV) has received recent attention as an indicator of the stability of cognitive functioning that may outperform mean performance in reflecting putative neurobiological abnormalities. Increased IIV is regarded as a core deficit in schizophrenia patients; however, whether this deficit is present in the prodromal phase before the onset of schizophrenia has not been well established. In the present study, we investigated IIV using the stop-signal paradigm in at-risk mental state (ARMS) individuals and in schizophrenia patients. The study included 27 ARMS subjects, 37 schizophrenia patients, and 38 normal controls. The stop-signal task was administered to assess IIV and response inhibition. IIV was estimated by calculating the standard deviation across sub-blocks for the three groups. We observed increased IIV in ARMS subjects and schizophrenia patients compared with normal controls in both the “stop” and the “go” processes even though the mean response inhibition performances were not impaired in the ARMS group. Schizophrenia patients showed impaired response inhibition that was associated with the severity of negative symptoms. Our findings suggest that the analysis of IIV may identify cognitive and clinical features of ARMS that are not detectable by conventional mean performance analysis. The unstable response patterns associated with ARMS may originate from abnormal processing in neural systems caused by alterations in the integrity of functional brain networks and dopamine neuromodulation.     

Reliability of Resting-State Microstate Features in Electroencephalography

Background

Electroencephalographic (EEG) microstate analysis is a method of identifying quasi-stable functional brain states (“microstates”) that are altered in a number of neuropsychiatric disorders, suggesting their potential use as biomarkers of neurophysiological health and disease. However, use of EEG microstates as neurophysiological biomarkers requires assessment of the test-retest reliability of microstate analysis.

Methods

We analyzed resting-state, eyes-closed, 30-channel EEG from 10 healthy subjects over 3 sessions spaced approximately 48 hours apart. We identified four microstate classes and calculated the average duration, frequency, and coverage fraction of these microstates. Using Cronbach''s α and the standard error of measurement (SEM) as indicators of reliability, we examined: (1) the test-retest reliability of microstate features using a variety of different approaches; (2) the consistency between TAAHC and k-means clustering algorithms; and (3) whether microstate analysis can be reliably conducted with 19 and 8 electrodes.

Results

The approach of identifying a single set of “global” microstate maps showed the highest reliability (mean Cronbach''s α>0.8, SEM ≈10% of mean values) compared to microstates derived by each session or each recording. There was notably low reliability in features calculated from maps extracted individually for each recording, suggesting that the analysis is most reliable when maps are held constant. Features were highly consistent across clustering methods (Cronbach''s α>0.9). All features had high test-retest reliability with 19 and 8 electrodes.

Conclusions

High test-retest reliability and cross-method consistency of microstate features suggests their potential as biomarkers for assessment of the brain''s neurophysiological health.     

Computer-Assisted Diagnosis of Abdominal Pain using “Estimates” Provided by Clinicians

This paper reports a comparison between two modes of computer-aided diagnosis in a real-time prospective trial involving 472 patients with acute abdominal pain. In the first mode the computer-aided system analysed each of the 472 patients by referring to data previously collated from a large series of 600 real-life patients. In the second mode the system used as a basis for its analysis “estimates” of probability provided by a group of six clinicians. The accuracy and reliability of both modes were compared with the performance of unaided clinicians.Using “real-life” data the computer system was significantly more effective than the unaided clinician. By contrast, when using the clinicians'' own estimates the computer-aided system was often less effective than the unaided clinician—especially when diagnosing less common disorders. It seems, firstly, that future systems for computer-aided diagnosis should employ data from real-life and not clinicians'' estimates, and, secondly, that clinicians themselves cannot analyse cases in a probabilistic fashion, since often they have little idea of what the “true” probabilities are.     

Kamin Blocking Is Associated with Reduced Medial-Frontal Gyrus Activation: Implications for Prediction Error Abnormality in Schizophrenia

The following study used 3-T functional magnetic resonance imaging (fMRI) to investigate the neural signature of Kamin blocking. Kamin blocking is an associative learning phenomenon seen where prior association of a stimulus (A) with an outcome blocks subsequent learning to an added stimulus (B) when both stimuli are later presented together (AB) with the same outcome. While there are a number of theoretical explanations of Kamin blocking, it is widely considered to exemplify the use of prediction error in learning, where learning occurs in proportion to the difference between expectation and outcome. In Kamin blocking as stimulus A fully predicts the outcome no prediction error is generated by the addition of stimulus B to form the compound stimulus AB, hence learning about it is “blocked”. Kamin blocking is disrupted in people with schizophrenia, their relatives and healthy individuals with high psychometrically-defined schizotypy. This disruption supports suggestions that abnormal prediction error is a core deficit that can help to explain the symptoms of schizophrenia. The present study tested 9 healthy volunteers on an f-MRI adaptation of Oades'' “mouse in the house task”, the only task measuring Kamin blocking that shows disruption in schizophrenia patients that has been independently replicated. Participant''s Kamin blocking scores were found to inversely correlate with Kamin-blocking-related activation within the prefrontal cortex, specifically the medial frontal gyrus. The medial frontal gyrus has been associated with the psychological construct of uncertainty, which we suggest is consistent with disrupted Kamin blocking and demonstrated in people with schizophrenia. These data suggest that the medial frontal gyrus merits further investigation as a potential locus of reduced Kamin blocking and abnormal prediction error in schizophrenia.     

Production of Artificial “Case Histories” by using a Small Computer

This paper describes a method of producing artificial “case histories” by using probability theory and clinical data from a series of 600 patients with acute abdominal pain. A series of 12 such cases were distributed to clinicians, medical students, medical secretaries and technicians, and members of the general public. For each “case” most clinicians concurred with the intended diagnosis. So did the medical secretaries and technicians; indeed this group were more confident of their chosen diagnoses than were the clinicians.It is suggested that clinicians are concerned to a large extent with the consequences of a diagnosis as well as its accuracy, and are motivated to some degree by a fear of the consequences of failure. They may be justified in adopting this policy, for when “errors” in diagnosis are harshly penalized the clinicians were infinitely more effective than any of the other groups.     

On the validation of crystallographic symmetry and the quality of structures

In 2008, Zwart and colleagues observed that the fraction of the structures deposited in the PDB alleged to have “pseudosymmetry” or “special noncrystallographic symmetry” (NCS) was about 6%, and that this percentage was rising annually. A few years later, Poon and colleagues found that 2% of all the crystal structures in the PDB belonged to higher symmetry space groups than those assigned to them. Here, I report an analysis of the X-ray diffraction data deposited for this class of structures, which shows that most of the “pseudosymmetry” and “special NCS” that has been reported is in fact true crystallographic symmetry (CS). This distinction is important because the credibility of crystal structures depends heavily on quality control statistics such as R_free that are unreliable when they are computed incorrectly, which they often are when CS is misidentified as “special NCS” or “pseudosymmetry”. When mistakes of this kind are made, artificially low values of R_free can give unjustified confidence in the accuracy of the reported structures.     

Never Resting Brain: Simultaneous Representation of Two Alpha Related Processes in Humans

Brain activity is continuously modulated, even at “rest”. The alpha rhythm (8–12 Hz) has been known as the hallmark of the brain''s idle-state. However, it is still debated if the alpha rhythm reflects synchronization in a distributed network or focal generator and whether it occurs spontaneously or is driven by a stimulus. This EEG/fMRI study aimed to explore the source of alpha modulations and their distribution in the resting brain. By serendipity, while computing the individually defined power modulations of the alpha-band, two simultaneously occurring components of these modulations were found. An ‘induced alpha’ that was correlated with the paradigm (eyes open/ eyes closed), and a ‘spontaneous alpha’ that was on-going and unrelated to the paradigm. These alpha components when used as regressors for BOLD activation revealed two segregated activation maps: the ‘induced map’ included left lateral temporal cortical regions and the hippocampus; the ‘spontaneous map’ included prefrontal cortical regions and the thalamus. Our combined fMRI/EEG approach allowed to computationally untangle two parallel patterns of alpha modulations and underpin their anatomical basis in the human brain. These findings suggest that the human alpha rhythm represents at least two simultaneously occurring processes which characterize the ‘resting brain’; one is related to expected change in sensory information, while the other is endogenous and independent of stimulus change.