Structural and Functional Alterations of the Temporal lobe in Schizophrenia: A Literature Review

An ensemble approach using multidimensional convolutional neural networks in wavelet domain for schizophrenia classification from sMRI data

Schizophrenia is a complicated mental condition marked by disruptions in thought processes, perceptions, and emotional responses, which can cause severe impairment in everyday functioning. sMRI is a non-invasive neuroimaging technology that visualizes the brain's structure while providing precise information on its anatomy and potential problems. This paper investigates the role of multidimensional Convolutional Neural Network (CNN) architectures: 1D-CNN, 2D-CNN and 3D-CNN, using the DWT subbands of sMRI data. 1D-CNN involves energy features extracted from the CD subband of sMRI data. The sum of gradient magnitudes of CD subband, known as energy feature, highlights diagonal high frequency elements associated with schizophrenia. 2D-CNN uses the CH subband decomposed by DWT that enables feature extraction from horizontal high frequency coefficients of sMRI data. In the case of 3D-CNNs, the CV subband is used which leads to volumetric feature extraction from vertical high frequency coefficients. Feature extraction in DWT domain explores textural changes, edges, coarse and fine details present in sMRI data from which the multidimensional feature extraction is carried out for classification.Through maximum voting technique, the proposed model optimizes schizophrenia classification from the multidimensional CNN models. The generalization of the proposed model for the two datasets proves convincing in improving the classification accuracy. The multidimensional CNN architectures achieve an average accuracy of 93.2%, 95.8%, and 98.0%, respectively, while the proposed model achieves an average accuracy of 98.9%.

Atypical antipsychotics improve dendritic spine pathology in temporal lobe cortex neurons in a developmental rodent model of schizophrenia

"Dendritic spine pathology" refers to alterations in density and morphology of dendritic spines, crucial in corticolimbic neurons in schizophrenia. These structural neuroplasticity changes contribute to the disease's neurobiological underpinnings, alongside alterations in other brain regions, such as temporal lobe cortices like the auditory cortex (Au1) and the entorhinal cortex (Ent), involved in sensory processing, memory, and learning. The neonatal ventral hippocampus lesion (NVHL) in rats exhibits behavioral abnormalities akin to schizophrenia symptoms and corticolimbic dendritic spine pathology, mitigated by atypical antipsychotic drugs (AADs) like risperidone (RISP) and olanzapine (OLZ). This study investigated NVHL-induced dendritic spine pathology in Au1 and Ent, evaluating RISP and OLZ effects. NVHL induced dendritic spine pathology mainly by reducing the dendritic spine density in Au1 and Ent neurons; both RISP and OLZ mitigated it, increasing dendritic spine density and mushroom spine population, the ones related with synaptic strengthening, while decreasing stubby spine population. These findings underscore the role of impaired neuroplasticity in the temporal lobe cortices in schizophrenia pathophysiology and highlight the relevance of the NVHL model for studying neuroplasticity mechanisms in the disease. They also contribute to the growing understanding of targeting structural and functional neuroplasticity for novel drugs in the pharmacotherapy of the disease.

Real-time fMRI neurofeedback modulates auditory cortex activity and connectivity in schizophrenia patients with auditory hallucinations: A controlled study

Background and Hypothesis

We have reported previously a reduction in superior temporal gyrus (STG) activation and in auditory verbal hallucinations (AHs) after real-time fMRI neurofeedback (NFB) in schizophrenia patients with AHs.

Study Design

With this randomized, participant-blinded, sham-controlled trial, we expanded our previous results. Specifically, we examined neurofeedback effects from the STG, an area associated with auditory hallucinations. The effects were compared to Sham-NFB from the motor cortex, a region unrelated to hallucinations. Twenty-three adults with schizophrenia or schizoaffective disorder and frequent medication-resistant hallucinations performed mindfulness meditation to ignore pre-recorded stranger's voices while receiving neurofeedback either from the STG (n=10, Real-NFB) or motor cortex (n=13 Sham-NFB). Individuals randomized to Sham-NFB received Real-NFB in a subsequent visit, providing a within-subject 'Real-after-Sham-NFB' comparison.

Study Results

Both groups showed reduced AHs after NFB, with no group differences. Compared to the Sham-NFB group, the Real-NFB group showed more reduced activation in secondary auditory cortex (AC) and more reduced connectivity between AC and cognitive control regions including dorsolateral prefrontal cortex (DLPFC) and anterior cingulate. The connectivity reduction was also observed in the Real-after-Sham-NFB condition. Secondary AC-DLPFC connectivity reduction correlated with hallucination reduction in the Real-NFB group. Replicating prior results, both groups showed reduced primary auditory cortex activation, suggesting mindfulness meditation may regulate bottom-up processes involved in hallucinations.

Conclusions

Our findings emphasize delivering NFB from brain regions involved in medication-resistant AHs. They provide insights into auditory cortex and cognitive control network interactions, highlighting complex processing dynamics and top-down modulation of sensory information.

Case report: Recurrence of psychosis after the surgical resection and radiation of a temporal lobe astrocytoma

It is estimated that the incidence of first episode psychotic disorder is about 33 people out of 100,000 each year. Beyond primary psychotic illness (e.g., schizophrenia, schizophreniform disorder), some of these patients will develop psychotic disorder due to a complex interplay of genetics, anatomical variations, traumatic brain injury (TBI), environment, substance use, and/or other causes. A small subset of patients will develop psychotic disorder due to a structural anatomic lesion, such as a CNS tumor. Here we present a 35-year-old male with worsening auditory hallucinations after surgical resection and radiation of a right temporal lobe astrocytoma in the setting of co-morbid methamphetamine usage. This case report helps illustrate how a neuroimaging work-up is important for the first incidence of psychotic disorder and how a tumor can produce a psychotic disorder that persists after oncologic treatment. This paper adds to the literature on the presentation and treatment of post-resection tumor-induced psychotic disorder.

Brain aging patterns in a large and diverse cohort of 49,482 individuals

Brain aging process is influenced by various lifestyle, environmental and genetic factors, as well as by age-related and often coexisting pathologies. Magnetic resonance imaging and artificial intelligence methods have been instrumental in understanding neuroanatomical changes that occur during aging. Large, diverse population studies enable identifying comprehensive and representative brain change patterns resulting from distinct but overlapping pathological and biological factors, revealing intersections and heterogeneity in affected brain regions and clinical phenotypes. Herein, we leverage a state-of-the-art deep-representation learning method, Surreal-GAN, and present methodological advances and extensive experimental results elucidating brain aging heterogeneity in a cohort of 49,482 individuals from 11 studies. Five dominant patterns of brain atrophy were identified and quantified for each individual by respective measures, R-indices. Their associations with biomedical, lifestyle and genetic factors provide insights into the etiology of observed variances, suggesting their potential as brain endophenotypes for genetic and lifestyle risks. Furthermore, baseline R-indices predict disease progression and mortality, capturing early changes as supplementary prognostic markers. These R-indices establish a dimensional approach to measuring aging trajectories and related brain changes. They hold promise for precise diagnostics, especially at preclinical stages, facilitating personalized patient management and targeted clinical trial recruitment based on specific brain endophenotypic expression and prognosis.

Cross-cohort replicable resting-state functional connectivity in predicting symptoms and cognition of schizophrenia

Schizophrenia (SZ) is a debilitating mental illness characterized by adolescence or early adulthood onset of psychosis, positive and negative symptoms, as well as cognitive impairments. Despite a plethora of studies leveraging functional connectivity (FC) from functional magnetic resonance imaging (fMRI) to predict symptoms and cognitive impairments of SZ, the findings have exhibited great heterogeneity. We aimed to identify congruous and replicable connectivity patterns capable of predicting positive and negative symptoms as well as cognitive impairments in SZ. Predictable functional connections (FCs) were identified by employing an individualized prediction model, whose replicability was further evaluated across three independent cohorts (BSNIP, SZ = 174; COBRE, SZ = 100; FBIRN, SZ = 161). Across cohorts, we observed that altered FCs in frontal-temporal-cingulate-thalamic network were replicable in prediction of positive symptoms, while sensorimotor network was predictive of negative symptoms. Temporal-parahippocampal network was consistently identified to be associated with reduced cognitive function. These replicable 23 FCs effectively distinguished SZ from healthy controls (HC) across three cohorts (82.7%, 90.2%, and 86.1%). Furthermore, models built using these replicable FCs showed comparable accuracies to those built using the whole-brain features in predicting symptoms/cognition of SZ across the three cohorts (r = .17-.33, p < .05). Overall, our findings provide new insights into the neural underpinnings of SZ symptoms/cognition and offer potential targets for further research and possible clinical interventions.

The hidden link: Investigating functional connectivity of rarely explored sub-regions of thalamus and superior temporal gyrus in Schizophrenia

Functional magnetic resonance imaging (fMRI) stands as a pivotal tool in advancing our comprehension of Schizophrenia, offering insights into functional segregations and integrations. Previous investigations employing either task-based or resting-state fMRI primarily focused on large main regions of interest (ROI), revealing the thalamus and superior temporal gyrus (STG) as prominently affected areas. Recent studies, however, unveiled the cytoarchitectural intricacies within these regions, prompting a more nuanced exploration. In this study, resting-state fMRI was conducted on 72 schizophrenic patients and 74 healthy controls to discern whether distinct thalamic nuclei and STG sub-regions exhibit varied functional integrational connectivity to main networks and to identify the most affected sub-regions in Schizophrenia. Employing seed-based analysis, six sub-ROIs - four in the thalamus and two in the STG - were selected. Our findings unveiled heightened positive functional connectivity in Schizophrenic patients, particularly toward the anterior STG (aSTG) and posterior STG (pSTG). Notably, positive connectivity emerged between the medial division of mediodorsal thalamic nuclei (MDm) and the visual network, while increased functional connectivity linked the ventral lateral nucleus of the thalamus with aSTG. This accentuated functional connectivity potentially influences these sub-regions, contributing to dysfunctions and manifesting symptoms such as language and learning difficulties alongside hallucinations. This study underscores the importance of delineating sub-regional dynamics to enhance our understanding of the nuanced neural alterations in Schizophrenia, paving the way for more targeted interventions and therapeutic approaches.

Five dominant dimensions of brain aging are identified via deep learning: associations with clinical, lifestyle, and genetic measures

Brain aging is a complex process influenced by various lifestyle, environmental, and genetic factors, as well as by age-related and often co-existing pathologies. MRI and, more recently, AI methods have been instrumental in understanding the neuroanatomical changes that occur during aging in large and diverse populations. However, the multiplicity and mutual overlap of both pathologic processes and affected brain regions make it difficult to precisely characterize the underlying neurodegenerative profile of an individual from an MRI scan. Herein, we leverage a state-of-the art deep representation learning method, Surreal-GAN, and present both methodological advances and extensive experimental results that allow us to elucidate the heterogeneity of brain aging in a large and diverse cohort of 49,482 individuals from 11 studies. Five dominant patterns of neurodegeneration were identified and quantified for each individual by their respective (herein referred to as) R-indices. Significant associations between R-indices and distinct biomedical, lifestyle, and genetic factors provide insights into the etiology of observed variances. Furthermore, baseline R-indices showed predictive value for disease progression and mortality. These five R-indices contribute to MRI-based precision diagnostics, prognostication, and may inform stratification into clinical trials.

Brain-Wide Mendelian Randomization Study of Anxiety Disorders and Symptoms

Background

To gain insights into the role of brain structure and function on anxiety (ANX), we conducted a genetically informed investigation leveraging information from ANX genome-wide association studies available from UK Biobank (UKB; N=380,379), FinnGen Program (N=290,361), and Million Veteran Program (MVP; N=199,611) together with UKB genome-wide data (N=33,224) related to 3,935 brain imaging-derived phenotypes (IDP).

Methods

A genetic correlation analysis between ANX and brain IDPs was performed using linkage disequilibrium score regression. To investigate ANX-brain associations, a two-sample Mendelian randomization (MR) was performed considering multiple methods and sensitivity analyses. A subsequent multivariable MR (MVMR) was executed to distinguish between direct and indirect effects. Finally, a generalized linear model was used to explore the associations of brain IDPs with ANX symptoms.

Results

After false discovery rate correction (FDR q<0.05), we identified 41 brain IDPs genetically correlated with ANX without heterogeneity among the datasets investigated (i.e., UKB, FinnGen, and MVP). Six of these IDPs showed genetically inferred causal effects on ANX. In the subsequent MVMR analysis, reduced area of the right posterior middle-cingulate gyrus (rpMCG; beta=-0.09, P= 8.01×10 -4 ) and reduced gray-matter volume of the right anterior superior temporal gyrus (raSTG; beta=-0.09, P=1.55×10 -3 ) had direct effects on ANX. In the ANX symptom-level analysis, rpMCG was negatively associated with "tense sore oraching muscles during the worst period of anxiety" (beta=-0.13, P=8.26×10 -6 ).

Conclusions

This study identified genetically inferred effects generalizable across large cohorts, contributing to understand how changes in brain structure and function can lead to ANX.

Structural aging of human neurons is opposite of the changes in schizophrenia

Human mentality develops with age and is altered in psychiatric disorders, though their underlying mechanism is unknown. In this study, we analyzed nanometer-scale three-dimensional structures of brain tissues of the anterior cingulate cortex from eight schizophrenia and eight control cases. The distribution profiles of neurite curvature of the control cases showed a trend depending on their age, resulting in an age-correlated decrease in the standard deviation of neurite curvature (Pearson's r = -0.80, p = 0.018). In contrast to the control cases, the schizophrenia cases deviate upward from this correlation, exhibiting a 60% higher neurite curvature compared with the controls (p = 7.8 × 10-4). The neurite curvature also showed a correlation with a hallucination score (Pearson's r = 0.80, p = 1.8 × 10-4), indicating that neurite structure is relevant to brain function. This report is based on our 3D analysis of human brain tissues over a decade and is unprecedented in terms of the number of cases. We suggest that neurite curvature plays a pivotal role in brain aging and can be used as a hallmark to exploit a novel treatment of schizophrenia.

Patterns of Impaired Neurocognitive Performance on the Global Neuropsychological Assessment, and Their Brain Structural Correlates in Recent-onset and Chronic Schizophrenia

Objective

Schizophrenia is associated with impairment in multiple cognitive domains. There is a paucity of research on the effect of prolonged illness duration (≥ 15 years) on cognitive performance along multiple domains. In this pilot study, we used the Global Neuropsychological Assessment (GNA), a brief cognitive battery, to explore the patterns of cognitive impairment in recent-onset (≤ 2 years) compared to chronic schizophrenia (≥ 15 years), and correlate cognitive performance with brain morphometry in patients and healthy adults.

Methods

We assessed cognitive performance in patients with recent-onset (n = 17, illness duration ≤ 2 years) and chronic schizophrenia (n = 14, duration ≥ 15 years), and healthy adults (n = 16) using the GNA and examined correlations between cognitive scores and gray matter volumes computed from T1-weighted magnetic resonance imaging images.

Results

We observed cognitive deficits affecting multiple domains in the schizophrenia samples. Selectively greater impairment of perceptual comparison speed was found in adults with chronic schizophrenia (p = 0.009, η2partial = 0.25). In the full sample (n = 47), perceptual comparison speed correlated significantly with gray matter volumes in the anterior and medial temporal lobes (TFCE, FWE p < 0.01).

Conclusion

Along with generalized deficit across multiple cognitive domains, selectively greater impairment of perceptual comparison speed appears to characterize chronic schizophrenia. This pattern might indicate an accelerated or premature cognitive aging. Anterior-medial temporal gray matter volumes especially of the left hemisphere might underlie the impairment noted in this domain in schizophrenia.

High levels of childhood trauma associated with changes in hippocampal functional activity and connectivity in young adults during novelty salience

Childhood trauma (CT) has been linked to increased risk for psychosis. Moreover, CT has been linked to psychosis phenotypes such as impaired cognitive and sensory functions involved in the detection of novel sensory stimuli. Our objective was to investigate if CT was associated with changes in hippocampal and superior temporal gyrus functional activation and connectivity during a novelty detection task. Fifty-eight young adults were assigned to High-CT (n = 28) and Low-CT (n = 24) groups based on their scores on the childhood trauma questionnaire (CTQ) and underwent functional Magnetic Resonance Imaging during an auditory oddball task (AOT). Relative to the Low CT group, High CT participants showed reduced functional activation in the left hippocampus during the unpredictable tone condition of the AOT. Furthermore, in the High CT group, psychophysiological interaction analysis revealed hypoconnectivity between the hippocampus and temporal and medial regions. The present study indicates both altered hippocampal activation and hippocampal-temporal-prefrontal connectivity during novelty detection in individuals that experienced CT, similarly to that reported in psychosis risk populations. Early stressful experiences and environments may alter hippocampal function during salient events, mediating the relationship between childhood trauma and psychosis risk.

Brain instability in dynamic functional connectivity in schizophrenia

Schizophrenia is a severe psychiatric disorder associated with altered connectivity of brain functional networks (BFNs). Researchers have observed a profound disruption in prefrontal-temporal interactions, damage to hub regions in brain networks and modified topological organization of BFNs in schizophrenia (SCZ) individuals. Assessment of BFNs with dynamic approaches allow the characterization of new functional structures, such as topological stability patterns and temporal connectivity, which are not accessible through static methods. In this perspective, the present study investigated the physiological processes of brain connectivity in SCZ. A resting-state EEG dataset of 14 SCZ individuals and 14 healthy controls (HC) was obtained at a sampling rate of 250 Hz. Dynamic BFNs were constructed using time-varying graphs combined with the motifs' synchronization method and the indexes were evaluated in different scales: global averages, by hemispheres, by regions, and by electrodes for both groups. The SCZ group exhibited lower temporal connectivity, lesser hub probability, and fewer number of edges in right and left temporal lobes over time, besides increased temporal connectivity in the central-parietal region. Neither differences for the full synchronization time of BFNs were observed, nor for intra- and inter-hemispheric connections between groups. These results indicate that SCZ BFNs exhibit a dynamic fluctuation pattern with abrupt increases in connectivity over time for the regions studied. This elucidates an attempted interaction of the temporal area with other regions (frontal, central-parietal, and occipital) that is not sufficient to maintain a connectivity pattern in schizophrenia individuals similar to that of healthy subjects. Our results suggest that changes in interaction of dynamic BFNs connections in SCZ can be better approached by dynamic analyses that enable a thorough glance at brain changes over time.

Inefficient white matter activity in Schizophrenia evoked during intra and inter-hemispheric communication

Intensive cognitive tasks induce inefficient regional and network responses in schizophrenia (SCZ). fMRI-based studies have naturally focused on gray matter, but appropriately titrated visuo-motor integration tasks reliably activate inter- and intra-hemispheric white matter pathways. Such tasks can assess network inefficiency without demanding intensive cognitive effort. Here, we provide the first application of this framework to the study of white matter functional responses in SCZ. Event-related fMRI data were acquired from 28 patients (nine females, mean age 43.3, ±11.7) and 28 age- and gender-comparable controls (nine females, mean age 42.1 ± 10.1), using the Poffenberger paradigm, a rapid visual detection task used to induce intra- (ipsi-lateral visual and motor cortex) or inter-hemispheric (contra-lateral visual and motor cortex) transfer. fMRI data were pre- and post-processed to reliably isolate activations in white matter, using probabilistic tractography-based white matter tracts. For intra- and inter-hemispheric transfer conditions, SCZ evinced hyper-activations in longitudinal and transverse white matter tracts, with hyper-activation in sub-regions of the corpus callosum primarily observed during inter-hemispheric transfer. Evidence for the functional inefficiency of white matter was observed in conjunction with small (~50 ms) but significant increases in response times. Functional inefficiencies in SCZ are (1) observable in white matter, with the degree of inefficiency contextually related to task-conditions, and (2) are evoked by simple detection tasks without intense cognitive processing. These cumulative results while expanding our understanding of this dys-connection syndrome, also extend the search of biomarkers beyond the traditional realm of fMRI studies of gray matter.

Meta-analysis of structural and functional brain abnormalities in schizophrenia with persistent negative symptoms using activation likelihood estimation

BACKGROUND

Persistent negative symptoms (PNS) include both primary and secondary negative symptoms that persist after adequate treatment, and represent an unmet therapeutic need. Published magnetic resonance imaging (MRI) evidence of structural and resting-state functional brain abnormalities in schizophrenia with PNS has been inconsistent. Thus, the purpose of this meta-analysis is to identify abnormalities in structural and functional brain regions in patients with PNS compared to healthy controls.

METHODS

We systematically searched PubMed, Web of Science, and Embase for structural and functional imaging studies based on five research methods, including voxel-based morphometry (VBM), diffusion tensor imaging (DTI), functional connectivity (FC), the amplitude of low-frequency fluctuation or fractional amplitude of low-frequency fluctuation (ALFF/fALFF), and regional homogeneity (ReHo). Afterward, we conducted a coordinate-based meta-analysis by using the activation likelihood estimation algorithm.

RESULTS

Twenty-five structural MRI studies and thirty-two functional MRI studies were included in the meta-analyses. Our analysis revealed the presence of structural alterations in patients with PNS in some brain regions including the bilateral insula, medial frontal gyrus, anterior cingulate gyrus, left amygdala, superior temporal gyrus, inferior frontal gyrus, cingulate gyrus and middle temporal gyrus, as well as functional differences in some brain regions including the bilateral precuneus, thalamus, left lentiform nucleus, posterior cingulate gyrus, medial frontal gyrus, and superior frontal gyrus.

CONCLUSION

Our study suggests that structural brain abnormalities are consistently located in the prefrontal, temporal, limbic and subcortical regions, and functional alterations are concentrated in the thalamo-cortical circuits and the default mode network (DMN). This study provides new insights for targeted treatment and intervention to delay further progression of negative symptoms.

SYSTEMATIC REVIEW REGISTRATION

[https://www.crd.york.ac.uk/prospero/], identifier [CRD42022338669].

Brain capillary structures of schizophrenia cases and controls show a correlation with their neuron structures

Brain blood vessels constitute a micrometer-scale vascular network responsible for supply of oxygen and nutrition. In this study, we analyzed cerebral tissues of the anterior cingulate cortex and superior temporal gyrus of schizophrenia cases and age/gender-matched controls by using synchrotron radiation microtomography or micro-CT in order to examine the three-dimensional structure of cerebral vessels. Over 1 m of cerebral blood vessels was traced to build Cartesian-coordinate models, which were then used for calculating structural parameters including the diameter and curvature of the vessels. The distribution of vessel outer diameters showed a peak at 7-9 μm, corresponding to the diameter of the capillaries. Mean curvatures of the capillary vessels showed a significant correlation to the mean curvatures of neurites, while the mean capillary diameter was almost constant, independent of the cases. Our previous studies indicated that the neurites of schizophrenia cases are thin and tortuous compared to controls. The curved capillaries with a constant diameter should occupy a nearly constant volume, while neurons suffering from neurite thinning should have reduced volumes, resulting in a volumetric imbalance between the neurons and the vessels. We suggest that the observed structural correlation between neurons and blood vessels is related to neurovascular abnormalities in schizophrenia.

Detailed Postmortem Profiling of Inflammatory Mediators Expression Revealed Post-inflammatory Alternation in the Superior Temporal Gyrus of Schizophrenia

Recent studies have lent support to the possibility that inflammation is associated with the pathology of schizophrenia. In the study of measurement of inflammatory mediators, which are markers of inflammation, elevated inflammatory cytokine levels in the brain and blood have been reported in patients with schizophrenia. Several postmortem brain studies have also reported changes in the expression of inflammatory cytokines. However, it is not clear how these elevated inflammatory cytokines interact with other inflammatory mediators, and their association with the pathology of schizophrenia. We comprehensively investigated the expression of 30 inflammatory mediators in the superior temporal gyrus (STG) of 24 patients with schizophrenia and 26 controls using a multiplex method. Overall, inflammatory mediator expression in the STG was mostly unchanged. However, the expression of interleukin (IL)1-α and interferon-gamma-inducible protein (IP)-10 was decreased [IL-1α, median (IQR), 0.51 (0.37-0.70) vs. 0.87 (0.47-1.23), p = 0.01; IP-10, 13.99 (8.00-36.64) vs. 30.29 (10.23-134.73), p = 0.05], whereas that of IFN-α was increased [2.34 (1.84-4.48) vs. 1.94 (1.39-2.36), p = 0.04] in schizophrenia, although these alterations did not remain significant after multiple testing. Clustering based on inflammatory mediator expression pattern and analysis of upstream transcription factors using pathway analysis revealed that the suppression of IL-1α and IP-10 protein expression may be induced by regulation of a common upstream pathway. Neuroinflammation is important in understanding the biology of schizophrenia. While neuroimaging has been previously used, direct observation to determine the expression of inflammatory mediators is necessary. In this study, we identified protein changes, previously unreported, using comprehensive protein analysis in STG. These results provide insight into post-inflammatory alternation in chronic schizophrenia.