Temporal lobe thickness and verbal memory in first-degree relatives of individuals with schizophrenia

Deep learning, data ramping, and uncertainty estimation for detecting artifacts in large, imbalanced databases of MRI images

Magnetic resonance imaging (MRI) is increasingly being used to delineate morphological changes underlying neurological disorders. Successfully detecting these changes depends on the MRI data quality. Unfortunately, image artifacts frequently compromise the MRI utility, making it critical to screen the data. Currently, quality assessment requires visual inspection, a time-consuming process that suffers from inter-rater variability. Automated methods to detect MRI artifacts could improve the efficiency of the process. Such automated methods have achieved high accuracy using small datasets, with balanced proportions of MRI data with and without artifacts. With the current trend towards big data in neuroimaging, there is a need for automated methods that achieve accurate detection in large and imbalanced datasets. Deep learning (DL) is the ideal MRI artifact detection algorithm for large neuroimaging databases. However, the inference generated by DL does not commonly include a measure of uncertainty. Here, we present the first stochastic DL algorithm to generate automated, high-performing MRI artifact detection implemented on a large and imbalanced neuroimaging database. We implemented Monte Carlo dropout in a 3D AlexNet to generate probabilities and epistemic uncertainties. We then developed a method to handle class imbalance, namely data-ramping to transfer the learning by extending the dataset size and the proportion of the artifact-free data instances. We used a 34,800 scans (98% clean) dataset. At baseline, we obtained 89.3% testing accuracy (F1 = 0.230). Following the transfer learning (with data-ramping), we obtained 94.9% testing accuracy (F1 = 0.357) outperforming focal cross-entropy (92.9% testing accuracy, F1 = 0.304) incorporated for comparison at handling class imbalance. By implementing epistemic uncertainties, we improved the testing accuracy to 99.5% (F1 = 0.834), outperforming the results obtained in previous comparable studies. In addition, we estimated aleatoric uncertainties by incorporating random flips to the MRI volumes, and demonstrated that aleatoric uncertainty can be implemented as part of the pipeline. The methods we introduce enhance the efficiency of managing large databases and the exclusion of artifact images from big data analyses.

Subjective memory complaints are associated with decreased cortical thickness in Veterans with histories of mild traumatic brain injury

Objective: Memory problems are frequently endorsed in Veterans following mild traumatic brain injury (mTBI), but subjective complaints are poorly associated with objective memory performance. Few studies have examined associations between subjective memory complaints and brain morphometry. We investigated whether self-reported memory problems were associated with objective memory performance and cortical thickness in Veterans with a history of mTBI. Methods: 40 Veterans with a history of remote mTBI and 29 Veterans with no history of TBI completed the Prospective-Retrospective Memory Questionnaire (PRMQ), PTSD Checklist (PCL), California Verbal Learning Test-2nd edition (CVLT-II), and 3 T T1 structural magnetic resonance imaging. Cortical thickness was estimated in 14 a priori frontal and temporal regions. Multiple regressions adjusting for age and PCL scores examined associations between PRMQ, CVLT-II scores, and cortical thickness within each Veteran group. Results: Greater subjective memory complaints on the PRMQ were associated with lower cortical thickness in the right middle temporal gyrus (β = 0.64, q = .004), right inferior temporal gyrus (β = 0.56, q = .014), right rostral middle frontal gyrus (β = 0.45, q = .046), and right rostral anterior cingulate gyrus (β = 0.58, q = .014) in the mTBI group but not the control group (q's > .05). These associations remained significant after adjusting for CVLT-II learning. CVLT-II performance was not associated with PRMQ score or cortical thickness in either group. Conclusions: Subjective memory complaints were associated with lower cortical thickness in right frontal and temporal regions, but not with objective memory performance, in Veterans with histories of mTBI. Subjective complaints post-mTBI may indicate underlying brain morphometry independently of objective cognitive testing.

Altered functional connectivity is related to impaired cognition in left unilateral asymptomatic carotid artery stenosis patients

Background

Asymptomatic carotid artery stenosis (aCAS) impairs haemodynamic and cognitive functions; however, the relationship between these changes and brain network connectivity remains largely unknown. This study aimed to determine the relationship between functional connectivity and neurocognition in patients with aCAS.

Methods

We compared functional status in 14 patients with aCAS and 15 healthy controls using resting state functional magnetic resonance imaging sequences. The subjects underwent a full range of neuropsychological tests and a graphical theoretical analysis of their brain networks.

Results

Compared with controls, patients with aCAS showed significant decline in neuropsychological functions, particularly short-term memory (word-memory, p = .046 and picture-memory, p = .014). Brain network connectivity was lower in patients with aCAS than in the controls, and the decline of functional connectivity in aCAS patients was mainly concentrated in the left and right inferior frontal gyri, temporal lobe, left cingulate gyrus, and hippocampus. Decreased connectivity between various brain regions was significantly correlated with impaired short-term memory. Patients with aCAS showed cognitive impairment independent of known vascular risk factors for vascular cognitive impairment. The cognitive defects were mainly manifested in the short-term memory of words and pictures.

Conclusions

This study is the first of its kind to identify an association between disruption of functional connections in left carotid stenosis and impairment of short-term memory. The findings suggest that alterations in network connectivity may be an essential mechanism underlying cognitive decline in aCAS patients.

Clinical trial registration-URL

Unique identifier: 04/06/2019, ChiCTR1900023610.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12883-021-02385-4.

Genetic copy number variants, cognition and psychosis: a meta-analysis and a family study

The burden of large and rare copy number genetic variants (CNVs) as well as certain specific CNVs increase the risk of developing schizophrenia. Several cognitive measures are purported schizophrenia endophenotypes and may represent an intermediate point between genetics and the illness. This paper investigates the influence of CNVs on cognition. We conducted a systematic review and meta-analysis of the literature exploring the effect of CNV burden on general intelligence. We included ten primary studies with a total of 18,847 participants and found no evidence of association. In a new psychosis family study, we investigated the effects of CNVs on specific cognitive abilities. We examined the burden of large and rare CNVs (>200 kb, <1% MAF) as well as known schizophrenia-associated CNVs in patients with psychotic disorders, their unaffected relatives and controls (N = 3428) from the Psychosis Endophenotypes International Consortium (PEIC). The carriers of specific schizophrenia-associated CNVs showed poorer performance than non-carriers in immediate (P = 0.0036) and delayed (P = 0.0115) verbal recall. We found suggestive evidence that carriers of schizophrenia-associated CNVs had poorer block design performance (P = 0.0307). We do not find any association between CNV burden and cognition. Our findings show that the known high-risk CNVs are not only associated with schizophrenia and other neurodevelopmental disorders, but are also a contributing factor to impairment in cognitive domains such as memory and perceptual reasoning, and act as intermediate biomarkers of disease risk.

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

Schizophrenia is a severe chronic mental illness leading to social and occupational dysfunction. Our primary focus in this review article was to analyze further the structural and functional alterations of the temporal lobe in patients with schizophrenia, which might contribute to the associated manifestations we often see in this illness. Our goal was to see if there was any correlation between temporal lobe abnormalities, more specifically, alterations in brain volume and specific symptoms such as auditory and language processing, etc. There is a positive correlation between volume alterations and thoughts disorders in the temporal lobe in the majority of studies. However, superior temporal gyrus volume has also been correlated negatively with the severity of hallucinations and thought disorders in some studies. We utilized Medical Subject Heading (MeSH) search strategy via PubMed database in our articles search yielding 241 papers. After the application of specific inclusion and exclusion criteria, a final number of 30 was reviewed. The involvement of the temporal lobe and its gray and white matter volume alterations in schizophrenia is quite apparent from our research; however, the exact mechanism of the underlying biological process is not thoroughly studied yet. Therefore, further research on larger cohorts combining different imaging modalities including volumetry, diffusion tensor, and functional imaging is required to explain how the progressive brain changes affect the various structural, functional, and metabolic activities of the temporal lobe in schizophrenia.

Characteristics of cognitive impairment in adult asymptomatic moyamoya disease

Background

Cognitive impairment in adult moyamoya disease (MMD) is thought to be the result of ischemic stroke; however, the presence and extent of cognitive decline in asymptomatic patients is unclear.

Methods

After classification using T2-weighted fluid attenuated inversion recovery (FLAIR) magnetic resonance imaging (MRI), a total of 19 MMD patients with a history of cerebral infarction, 21 asymptomatic MMD patients, and 20 healthy controls matched for age, sex, and years of education were prospectively included in this study. A detailed neuropsychological evaluation of two moyamoya subgroups and normal controls was conducted.

Results

Asymptomatic patients showed varying degrees of decline in intelligence (Raven’s Standard Progressive Matrices, P = 0.001), spatial imagination (mental rotation, P = 0.014), working memory (verbal working memory-backward digit span, P = 0.011), and computational ability (simple subtraction, P = 0.014; complex subtraction, P < 0.001) compared with normal controls. MMD patients with cerebral infarction had more severe impairment in complex arithmetic (P = 0.027) and word short-term memory (P = 0.01) than those without symptoms.

Conclusion

In asymptomatic MMD patients, a variety of cognitive impairment precedes the onset of clinical symptoms such as cerebral infarction, which may be a long-term complication of conservative treatment.

Neural correlates of cognitive deficits across developmental phases of schizophrenia

Schizophrenia is associated with cognitive deficits across all stages of the illness (i.e., high risk, first episode, early and chronic phases). Identifying the underlying neurobiological mechanisms of these deficits is an important area of scientific inquiry. Here, we selectively review evidence regarding the pattern of deficits across the developmental trajectory of schizophrenia using the five cognitive domains identified by the Research Domain Criteria (RDoC) initiative. We also report associated findings from neuroimaging studies. We suggest that most cognitive domains are affected across the developmental trajectory, with corresponding brain structural and/or functional differences. The idea of a common mechanism driving these deficits is discussed, along with implications for cognitive treatment in schizophrenia.