The Functional Consequences of Cortical Circuit Abnormalities on Gamma Oscillations in Schizophrenia: Insights from Computational Modeling

Schizophrenia is characterized by cortical circuit abnormalities, which might be reflected in γ-frequency (30–100 Hz) oscillations in the electroencephalogram. Here we used a computational model of cortical circuitry to examine the effects that neural circuit abnormalities might have on γ generation and network excitability. The model network consisted of 1000 leaky integrate-and-fire neurons with realistic connectivity patterns and proportions of neuron types [pyramidal cells (PCs), regular-spiking inhibitory interneurons, and fast-spiking interneurons (FSIs)]. The network produced a γ oscillation when driven by noise input. We simulated reductions in: (1) recurrent excitatory inputs to PCs; (2) both excitatory and inhibitory inputs to PCs; (3) all possible connections between cells; (4) reduced inhibitory output from FSIs; and (5) reduced NMDA input to FSIs. Reducing all types of synaptic connectivity sharply reduced γ power and phase synchrony. Network excitability was reduced when recurrent excitatory connections were deleted, but the network showed disinhibition effects when inhibitory connections were deleted. Reducing FSI output impaired γ generation to a lesser degree than reducing synaptic connectivity, and increased network excitability. Reducing FSI NMDA input also increased network excitability, but increased γ power. The results of this study suggest that a multimodal approach, combining non-invasive neurophysiological and structural measures, might be able to distinguish between different neural circuit abnormalities in schizophrenia patients. Computational modeling may help to bridge the gaps between post-mortem studies, animal models, and experimental data in humans, and facilitate the development of new therapies for schizophrenia and neuropsychiatric disorders in general

Baseline gamma power during auditory steady-state stimulation in schizophrenia

Several studies have reported deficits in γ oscillatory activity elicited by sensory stimulation or cognitive processes in schizophrenia patients (SZ) compared to healthy control subjects (HC). However, the evidence for cortical hyperexcitability and reduced function of N-methyl-D-aspartate receptors (NMDARs) on parvalbumin-expressing inhibitory interneurons in schizophrenia leads to the prediction that γ activity should rather be increased in SZ, but data supporting this hypothesis have been lacking. One possibility is that baseline induced γ power is increased, an effect that might have gone unnoticed in studies of stimulus-locked oscillations. Here we addressed this question by re-analyzing the data from a previously published study on the 40 Hz auditory steady-state response (ASSR) in schizophrenia in which dipole source localization was used to examine γ responses in the left and right auditory cortices. Subjects were 16 HC and 18 chronic SZ, who listened to trains of clicks presented at 40 Hz during electroencephalogram recording. Independent component analysis was used to remove ocular artifacts. Power spectra were computed for the pre-stimulus baseline period. We found that baseline power was higher in SZ than HC at 40 Hz in the left auditory cortex. Baseline 40 Hz power in the left auditory cortex was also correlated with ASSR evoked power in SZ. Thus, γ oscillation abnormalities in schizophrenia may include abnormal increases in baseline power as well as deficits in evoked oscillations. These baseline increases could be the sign of NMDAR hypofunction on parvalbumin-expressing inhibitory interneurons, which would be consistent with acute NMDAR antagonism and genetic ablation models of schizophrenia

Oscillatory dynamics of Gestalt perception in schizophrenia revisited

Background: Abnormalities in γ oscillations (30–100 Hz) in the scalp-recorded electroencephalogram (EEG) have been proposed to reflect neural circuitry abnormalities in schizophrenia. Oscillations in the γ band are thought to play an important role in visual perception, mediating the binding of visual features into coherent objects. However, there is relatively little evidence to date of deficits in γ-mediated processes associated with Gestalt perception in schizophrenia. Methods: Fourteen healthy control subjects (HC) and 17 chronic schizophrenia patients (SZ) discriminated between illusory Kanisza Squares and No-Square control stimuli, indicating their judgment with a manual button press. Time-frequency decomposition of the EEG was computed with the Morlet wavelet transform. Time-frequency maps of phase locking factor (PLF) values were calculated for stimulus- and response-locked oscillations. Results: HC and SZ did not differ in reaction time, error rate, an early ERP effect associated with Gestalt processing, nor an early visual-evoked γ oscillation. Two response-locked high γ effects had greater PLF for Square than No-Square stimuli in HC, and the reverse pattern in SZ. One of these effects was correlated with thought disorder symptom ratings in SZ. Conclusions: SZ demonstrated abnormalities in γ oscillations associated with the perception of Gestalt objects, while their early visual-evoked γ activity was mostly normal, contrary to previous results. This study supports the hypothesis that high-frequency oscillations are sensitive to aspects of psychosis

Hemispheric biases and the control of visuospatial attention: an ERP study

BACKGROUND: We examined whether individual differences in hemispheric utilization can interact with the intrinsic attentional biases of the cerebral hemispheres. Evidence suggests that the hemispheres have competing biases to direct attention contralaterally, with the left hemisphere (LH) having a stronger bias than the right hemisphere. There is also evidence that individuals have characteristic biases to utilize one hemisphere more than the other for processing information, which can induce a bias to direct attention to contralateral space. We predicted that LH-biased individuals would display a strong rightward attentional bias, which would create difficulty in selectively attending to target stimuli in the left visual field (LVF) as compared to right in the performance of a bilateral flanker task. RESULTS: Consistent with our hypothesis, flanker interference effects were found on the N2c event-related brain potential and error rate for LH-biased individuals in the Attend-LVF condition. The error rate effect was correlated with the degree of hemispheric utilization bias for the LH-Bias group. CONCLUSION: We conclude that hemispheric utilization bias can enhance a hemisphere's contralateral attentional bias, at least for individuals with a LH utilization bias. Hemispheric utilization bias may play an important and largely unrecognized role in visuospatial attention

Left auditory cortex gamma synchronization and auditory hallucination symptoms in schizophrenia

<p>Abstract</p> <p>Background</p> <p>Oscillatory electroencephalogram (EEG) abnormalities may reflect neural circuit dysfunction in neuropsychiatric disorders. Previously we have found positive correlations between the phase synchronization of beta and gamma oscillations and hallucination symptoms in schizophrenia patients. These findings suggest that the propensity for hallucinations is associated with an increased tendency for neural circuits in sensory cortex to enter states of oscillatory synchrony. Here we tested this hypothesis by examining whether the 40 Hz auditory steady-state response (ASSR) generated in the left primary auditory cortex is positively correlated with auditory hallucination symptoms in schizophrenia. We also examined whether the 40 Hz ASSR deficit in schizophrenia was associated with cross-frequency interactions.</p> <p>Sixteen healthy control subjects (HC) and 18 chronic schizophrenia patients (SZ) listened to 40 Hz binaural click trains. The EEG was recorded from 60 electrodes and average-referenced offline. A 5-dipole model was fit from the HC grand average ASSR, with 2 pairs of superior temporal dipoles and a deep midline dipole. Time-frequency decomposition was performed on the scalp EEG and source data.</p> <p>Results</p> <p>Phase locking factor (PLF) and evoked power were reduced in SZ at fronto-central electrodes, replicating prior findings. PLF was reduced in SZ for non-homologous right and left hemisphere sources. Left hemisphere source PLF in SZ was positively correlated with auditory hallucination symptoms, and was modulated by delta phase. Furthermore, the correlations between source evoked power and PLF found in HC was reduced in SZ for the LH sources.</p> <p>Conclusion</p> <p>These findings suggest that differential neural circuit abnormalities may be present in the left and right auditory cortices in schizophrenia. In addition, they provide further support for the hypothesis that hallucinations are related to cortical hyperexcitability, which is manifested by an increased propensity for high-frequency synchronization in modality-specific cortical areas.</p

Evaluating motion processing algorithms for use with functional near-infrared spectroscopy data from young children

Motion artifacts are often a significant component of the measured signal in functional near-infrared spectroscopy (fNIRS) experiments. A variety of methods have been proposed to address this issue, including principal components analysis (PCA), correlation-based signal improvement (CBSI), wavelet filtering, and spline interpolation. The efficacy of these techniques has been compared using simulated data; however, our understanding of how these techniques fare when dealing with task-based cognitive data is limited. Brigadoi et al. compared motion correction techniques in a sample of adult data measured during a simple cognitive task. Wavelet filtering showed the most promise as an optimal technique for motion correction. Given that fNIRS is often used with infants and young children, it is critical to evaluate the effectiveness of motion correction techniques directly with data from these age groups. This study addresses that problem by evaluating motion correction algorithms implemented in HomER2. The efficacy of each technique was compared quantitatively using objective metrics related to the physiological properties of the hemodynamic response. Results showed that targeted PCA (tPCA), spline, and CBSI retained a higher number of trials. These techniques also performed well in direct head-to-head comparisons with the other approaches using quantitative metrics. The CBSI method corrected many of the artifacts present in our data; however, this approach produced sometimes unstable HRFs. The targeted PCA and spline methods proved to be the most robust, performing well across all comparison metrics. When compared head to head, tPCA consistently outperformed spline. We conclude, therefore, that tPCA is an effective technique for correcting motion artifacts in fNIRS data from young children

Revealing ensemble state transition patterns in multi-electrode neuronal recordings using hidden Markov models

In order to harness the computational capacity of dissociated cultured neuronal networks, it is necessary to understand neuronal dynamics and connectivity on a mesoscopic scale. To this end, this paper uncovers dynamic spatiotemporal patterns emerging from electrically stimulated neuronal cultures using hidden Markov models (HMMs) to characterize multi-channel spike trains as a progression of patterns of underlying states of neuronal activity. However, experimentation aimed at optimal choice of parameters for such models is essential and results are reported in detail. Results derived from ensemble neuronal data revealed highly repeatable patterns of state transitions in the order of milliseconds in response to probing stimuli

Attentional Load Effects on Beta Oscillations in Healthy and Schizophrenic Individuals

Attentional deficits are prominent among the cognitive disturbances found in schizophrenia. Given that schizophrenia is also characterized by abnormalities in high-frequency oscillations, we investigated whether attentional function in schizophrenia is related to abnormalities in high-frequency oscillations in a visual discrimination task in which attentional load was manipulated. Sixteen healthy control subjects (HC) and 23 chronic schizophrenia patients (SZ) discriminated between target discs (p = 0.2) and standard discs (p = 0.8). Attentional load was manipulated by varying the size difference between the target and standard discs across blocks: large (Easy condition), medium (Medium), and small (Difficult). The electroencephalogram was recorded and the oscillations evoked by the standard stimuli were analyzed using the Morlet wavelet transform. Subjects’ performance decreased as attentional load increased, but HC and SZ did not differ. Attentional load increased β phase-locking factor at frontal, parietal, and occipital electrode sites in HC but not SZ. In SZ, however, there was a correlation between the β attentional load effect and overall d′, indicating that high-performing SZ had relatively normal β attentional load effects. These results show that variations in attentional load are associated with β oscillations and provide a link between attentional dysfunction and β-generating neural circuitry in schizophrenia

Molecular characterization of Trichomonas gallinae isolates recovered from the Canadian Maritime provinces’ wild avifauna reveals the presence of the genotype responsible for the European finch trichomonosis epidemic and additional strains

Finch trichomonosis, caused by Trichomonas gallinae, emerged in the Canadian Maritime provinces in 2007 and has since caused ongoing mortality in regional purple finch (Carpodacus purpureus) and American goldfinch (Carduelis tristis) populations. Trichomonas gallinae was isolated from (1) finches and rock pigeons (Columbia livia) submitted for post-mortem or live-captured at bird feeding sites experiencing trichomonosis mortality; (2) bird seed at these same sites; and (3) rock pigeons live-captured at known roosts or humanely killed. Isolates were characterized using internal transcribed spacer (ITS) region and iron hydrogenase (Fe-hyd) gene sequences. Two distinct ITS types were found. Type A was identical to the UK finch epidemic strain and was isolated from finches and a rock pigeon with trichomonosis; apparently healthy rock pigeons and finches; and bird seed at an outbreak site. Type B was obtained from apparently healthy rock pigeons. Fe-hyd sequencing revealed six distinct subtypes. The predominant subtype in both finches and the rock pigeon with trichomonosis was identical to the UK finch epidemic strain A1. Single nucleotide polymorphisms in Fe-hyd sequences suggest there is fine-scale variation amongst isolates and that finch trichomonosis emergence in this region may not have been caused by a single spill-over event

A Differentially Private Weighted Empirical Risk Minimization Procedure and its Application to Outcome Weighted Learning

It is commonplace to use data containing personal information to build predictive models in the framework of empirical risk minimization (ERM). While these models can be highly accurate in prediction, results obtained from these models with the use of sensitive data may be susceptible to privacy attacks. Differential privacy (DP) is an appealing framework for addressing such data privacy issues by providing mathematically provable bounds on the privacy loss incurred when releasing information from sensitive data. Previous work has primarily concentrated on applying DP to unweighted ERM. We consider an important generalization to weighted ERM (wERM). In wERM, each individual's contribution to the objective function can be assigned varying weights. In this context, we propose the first differentially private wERM algorithm, backed by a rigorous theoretical proof of its DP guarantees under mild regularity conditions. Extending the existing DP-ERM procedures to wERM paves a path to deriving privacy-preserving learning methods for individualized treatment rules, including the popular outcome weighted learning (OWL). We evaluate the performance of the DP-wERM application to OWL in a simulation study and in a real clinical trial of melatonin for sleep health. All empirical results demonstrate the viability of training OWL models via wERM with DP guarantees while maintaining sufficiently useful model performance. Therefore, we recommend practitioners consider implementing the proposed privacy-preserving OWL procedure in real-world scenarios involving sensitive data.Comment: 24 pages and 2 figures for the main manuscript, 5 pages and 2 figures for the supplementary material