ACC Neuro-over-Connectivity Is Associated with Mathematically Modeled Additional Encoding Operations of Schizophrenia Stroop-Task Performance

Formal Innovations in Clinical Cognitive Science and Assessment

Mathematical modeling is increasingly driving progress in clinical cognitive science and assessment. Mathematical modeling is essential for detecting certain effects of psychopathology through comprehensive understanding of telltale cognitive variables, such as workload capacity and efficiency in using capacity, as well as for quantitatively stipulating the subtle but important differences among these variables. The research paradigm guiding this formal clinical science is outlined. A distinctive cognitive abnormality in schizophrenia—taking longer to cognitively represent encountered stimulation—is used as a specific example to illustrate a general quantitative framework for studying intricate phenomena that impair mental health. Developments in mathematical modeling will also benefit symptom description and prediction; provide grounding in cognitive and statistical science for new methods of clinical assessment over time, both for individuals and for treatment regimens; and contribute to refining the cognitive-function side of clinical functional neurophysiology.

Cortical and subcortical contributions to interference resolution and inhibition - An fMRI ALE meta-analysis

Interacting with our environment requires the selection of appropriate responses and the inhibition of others. Such effortful inhibition is achieved by a number of interference resolution and global inhibition processes. This meta-analysis including 57 studies and 73 contrasts revisits the overlap and differences in brain areas supporting interference resolution and global inhibition in cortical and subcortical brain areas. Activation likelihood estimation was used to discern the brain regions subserving each type of cognitive control. Individual contrast analysis revealed a common activation of the bilateral insula and supplementary motor areas. Subtraction analyses demonstrated the voxel-wise differences in recruitment in a number of areas including the precuneus in the interference tasks and the frontal pole and dorsal striatum in the inhibition tasks. Our results display a surprising lack of subcortical involvement within these types of cognitive control, a finding that is likely to reflect a systematic gap in the field of functional neuroimaging.

Ultra-high field imaging in Major Depressive Disorder: a review of structural and functional studies

BACKGROUND

Major depressive disorder (MDD) is a severe and pervasive psychiatric condition with a lifetime prevalence of 15-25%. Numerous Magnetic Resonance Imaging (MRI) studies employing scans at field strengths of 1.5T or 3T have been carried out in the last decades, providing an unprecedented insight into the neural correlates of MDD. However, in recent years, MRI technology has largely progressed and the use of scans at ultra-high field (≥ 7T) has improved the sensitivity and the resolution of MR images. In this context, with this review we aim to summarize evidence of structural and functional brain mechanisms underlying MDD obtained with ultra-high field MRI.

METHODS

We conducted a search on PubMed, Scopus and Web of Science of neuroimaging studies on MDD patients, which employed ultra-high field MRI. We detected six structural MRI studies, two Diffusion Tensor Imaging (DTI) studies and five functional MRI (fMRI) studies.

RESULTS

Overall, the MRI and DTI studies showed volumetric and structural connectivity alterations in the hippocampus and, to a lesser extent, in the amygdala. In contrast, more heterogeneous results were reported by fMRI studies, which, though, described functional abnormalities in the cingulate cortex, thalamus and several other brain areas.

LIMITATIONS

The small sample size and the heterogeneity in patients' samples, processing and study design limit the conclusion of the present review.

CONCLUSIONS

Studies employing scans at ultra-high magnetic field may provide a useful contribution to the mixed body of literature on MDD. This preliminary but promising evidence confirms the importance of performing ultra-high field MRI investigations in order to detect and better characterize subtle brain abnormalities in MDD.

Glutamate and Dysconnection in the Salience Network: Neurochemical, Effective Connectivity, and Computational Evidence in Schizophrenia

BACKGROUND

Functional dysconnection in schizophrenia is underwritten by a pathophysiology of the glutamate neurotransmission that affects the excitation-inhibition balance in key nodes of the salience network. Physiologically, this manifests as aberrant effective connectivity in intrinsic connections involving inhibitory interneurons. In computational terms, this produces a pathology of evidence accumulation and ensuing inference in the brain. Finally, the pathophysiology and aberrant inference would partially account for the psychopathology of schizophrenia as measured in terms of symptoms and signs. We refer to this formulation as the 3-level hypothesis.

METHODS

We tested the hypothesis in core nodes of the salience network (the dorsal anterior cingulate cortex [dACC] and the anterior insula) of 20 patients with first-episode psychosis and 20 healthy control subjects. We established 3-way correlations between the magnetic resonance spectroscopy measures of glutamate, effective connectivity of resting-state functional magnetic resonance imaging, and correlations between measures of this connectivity and estimates of precision (inherent in evidence accumulation in the Stroop task) and psychopathology.

RESULTS

Glutamate concentration in the dACC was associated with higher and lower inhibitory connectivity in the dACC and in the anterior insula, respectively. Crucially, glutamate concentration correlated negatively with the inhibitory influence on the excitatory neuronal population in the dACC of subjects with first-episode psychosis. Furthermore, aberrant computational parameters of the Stroop task performance were associated with aberrant inhibitory connections. Finally, the strength of connections from the dACC to the anterior insula correlated negatively with severity of social withdrawal.

CONCLUSIONS

These findings support a link between glutamate-mediated cortical disinhibition, effective-connectivity deficits, and computational performance in psychosis.

Cortical morphometry and structural connectivity relate to executive function and estradiol level in healthy adolescents

INTRODUCTION

Emotional and behavioral control is necessary self-regulatory processes to maintain stable goal-driven behavior. Studies indicate that variance in these executive function (EF) processes is related to morphological features of the brain and white matter (WM) differences. Furthermore, sex hormone level may modulate circuits in the brain important for cognitive function.

METHODS

We aimed to investigate the structural neural correlates of EF behavior in gray matter (GM) and WM while taking into account estradiol level, in an adolescent population. The present study obtained neuroimaging behavioral and physiological data from the National Institute of Health's Pediatric Database (NIHPD). We analyzed the relationship between cortical morphometry and structural connectivity (N = 55), using a parent-administered behavioral monitoring instrument (Behavior Rating Inventory of Executive Function-BRIEF), estradiol level, as well as their interaction.

RESULTS

Executive function behavior and estradiol level related to bidirectional associations with cortical morphometry in the right posterior dorsolateral prefrontal cortex (pDLPFC) and primary motor cortex (PMC), as well as fractional anisotropy (FA) in the forceps major and minor. Lastly, the interaction of EF behavior and estradiol level related to decreased volume in the right PMC and was linked to altered FA in the right inferior fronto-occipital fasciculus (iFOF).

CONCLUSIONS

The study provides evidence that the relationship between EF behavior and estradiol level related to bidirectional GM and WM differences, implying estradiol level has an influence on the putative structural regions underlying EF behavior. The findings represent a crucial link between EF behavior and hormonal influence on brain structure in adolescence.

Neuronal underpinnings of cognitive impairment and - improvement in mood disorders

Neuropsychiatric illnesses including mood disorders are accompanied by cognitive impairment, which impairs work capacity and quality of life. However, there is a lack of treatment options that would lead to solid and lasting improvement of cognition. This is partially due to the absence of valid and reliable neurocircuitry-based biomarkers for pro-cognitive effects. This systematic review therefore examined the most consistent neural underpinnings of cognitive impairment and cognitive improvement in unipolar and bipolar disorders. We identified 100 studies of the neuronal underpinnings of working memory and executive skills, learning and memory, attention, and implicit learning and 9 studies of the neuronal basis for cognitive improvements. Impairments across several cognitive domains were consistently accompanied by abnormal activity in dorsal prefrontal (PFC) cognitive control regions-with the direction of this activity depending on patients' performance levels-and failure to suppress default mode network (DMN) activity. Candidate cognition treatments seemed to enhance task-related dorsal PFC and temporo-parietal activity when performance increases were observed, and to reduce their activity when performance levels were unchanged. These treatments also attenuated DMN hyper-activity. In contrast, nonspecific cognitive improvement following symptom reduction was typically accompanied by decreased limbic reactivity and reversal of pre-treatment fronto-parietal hyper-activity. Together, the findings highlight some common neural correlates of cognitive impairments and cognitive improvements. Based on this evidence, studies are warranted to examine the reliability and predictive validity of target engagement in the identified neurocircuitries as a biomarker model of pro-cognitive effects.

Temporoparietal Junction Functional Connectivity in Early Schizophrenia and Major Depressive Disorder

Background

The temporoparietal junction (TPJ) has been linked to lower-level attentional and higher-level social processing, both of which are affected in schizophrenia (SZ) and major depressive disorder (MDD). We examined resting functional connectivity of bilateral anterior and posterior TPJ in SZ and MDD to evaluate potential anomalies in each disorder and differences between disorders.

Methods

Resting-state functional magnetic resonance imaging data were acquired from 24 patients with SZ, 24 patients with MDD, and 24 age-matched healthy controls. We performed seed-based functional connectivity analyses with seed regions in bilateral anterior and posterior TPJ, covarying for gender and smoking.

Results

SZ had reduced connectivity versus controls between left anterior TPJ and dorsolateral prefrontal cortex (dlPFC) and posterior cingulate cortex (PCC); between left posterior TPJ and middle cingulate cortex, left dorsal PFC, and right lateral PFC; between right anterior TPJ and bilateral PCC; and between right posterior TPJ and middle cingulate cortex, left posterior insula, and right insula. MDD had reduced connectivity versus controls between left posterior TPJ and right dlPFC and between right posterior TPJ and PCC and dlPFC. SZ had reduced connectivity versus MDD between right posterior TPJ and left fusiform gyrus and right superior-posterior temporal cortex.

Conclusion

Functional connectivity to the TPJ was demonstrated to be disrupted in both SZ and MDD. However, TPJ connectivity may differ in these disorders with reduced connectivity in SZ versus MDD between TPJ and posterior brain regions.

Theoretical Modeling of Cognitive Dysfunction in Schizophrenia by Means of Errors and Corresponding Brain Networks

The current evidence of cognitive disturbances and brain alterations in schizophrenia does not provide the plausible explanation of the underlying mechanisms. Neuropsychological studies outlined the cognitive profile of patients with schizophrenia, that embodied the substantial disturbances in perceptual and motor processes, spatial functions, verbal and non-verbal memory, processing speed and executive functioning. Standardized scoring in the majority of the neurocognitive tests renders the index scores or the achievement indicating the severity of the cognitive impairment rather than the actual performance by means of errors. At the same time, the quantitative evaluation may lead to the situation when two patients with the same index score of the particular cognitive test, demonstrate qualitatively different performances. This may support the view why test paradigms that habitually incorporate different cognitive variables associate weakly, reflecting an ambiguity in the interpretation of noted cognitive constructs. With minor exceptions, cognitive functions are not attributed to the localized activity but eventuate from the coordinated activity in the generally dispersed brain networks. Functional neuroimaging has progressively explored the connectivity in the brain networks in the absence of the specific task and during the task processing. The spatio-temporal fluctuations of the activity of the brain areas detected in the resting state and being highly reproducible in numerous studies, resemble the activation and communication patterns during the task performance. Relatedly, the activation in the specific brain regions oftentimes is attributed to a number of cognitive processes. Given the complex organization of the cognitive functions, it becomes crucial to designate the roles of the brain networks in relation to the specific cognitive functions. One possible approach is to identify the commonalities of the deficits across the number of cognitive tests or, common errors in the various tests and identify their common "denominators" in the brain networks. The qualitative characterization of cognitive performance might be beneficial in addressing diffuse cognitive alterations presumably caused by the dysconnectivity of the distributed brain networks. Therefore, in the review, we use this approach in the description of standardized tests in the scope of potential errors in patients with schizophrenia with a subsequent reference to the brain networks.

Failures of cognitive control or attention? The case of stop-signal deficits in schizophrenia

We used Bayesian cognitive modelling to identify the underlying causes of apparent inhibitory deficits in the stop-signal paradigm. The analysis was applied to stop-signal data reported by Badcock et al. (Psychological Medicine 32: 87-297, 2002) and Hughes et al. (Biological Psychology 89: 220-231, 2012), where schizophrenia patients and control participants made rapid choice responses, but on some trials were signalled to stop their ongoing response. Previous research has assumed an inhibitory deficit in schizophrenia, because estimates of the mean time taken to react to the stop signal are longer in patients than controls. We showed that these longer estimates are partly due to failing to react to the stop signal ("trigger failures") and partly due to a slower initiation of inhibition, implicating a failure of attention rather than a deficit in the inhibitory process itself. Correlations between the probability of trigger failures and event-related potentials reported by Hughes et al. are interpreted as supporting the attentional account of inhibitory deficits. Our results, and those of Matzke et al. (2016), who report that controls also display a substantial although lower trigger-failure rate, indicate that attentional factors need to be taken into account when interpreting results from the stop-signal paradigm.