The Influence of Fluid Intelligence, Executive Functions and Premorbid Intelligence on Memory in Frontal Patients

TENSOR QUANTILE REGRESSION WITH LOW-RANK TENSOR TRAIN ESTIMATION

Neuroimaging studies often involve predicting a scalar outcome from an array of images collectively called tensor. The use of magnetic resonance imaging (MRI) provides a unique opportunity to investigate the structures of the brain. To learn the association between MRI images and human intelligence, we formulate a scalar-on-image quantile regression framework. However, the high dimensionality of the tensor makes estimating the coefficients for all elements computationally challenging. To address this, we propose a low-rank coefficient array estimation algorithm based on tensor train (TT) decomposition which we demonstrate can effectively reduce the dimensionality of the coefficient tensor to a feasible level while ensuring adequacy to the data. Our method is more stable and efficient compared to the commonly used, Canonic Polyadic rank approximation-based method. We also propose a generalized Lasso penalty on the coefficient tensor to take advantage of the spatial structure of the tensor, further reduce the dimensionality of the coefficient tensor, and improve the interpretability of the model. The consistency and asymptotic normality of the TT estimator are established under some mild conditions on the covariates and random errors in quantile regression models. The rate of convergence is obtained with regularization under the total variation penalty. Extensive numerical studies, including both synthetic and real MRI imaging data, are conducted to examine the empirical performance of the proposed method and its competitors.

A Potential Measure of Premorbid Functioning: Evaluating the Construct Validity of the Author and Magazine Recognition Tests

OBJECTIVE

To establish convergent and discriminant validity for a combined measure of print exposure (i.e., Author Recognition Test and Magazine Recognition Test [ART/MRT]) and assess its potential utility for estimating premorbid cognitive functioning.

METHOD

Community-dwelling older adults (N = 84; 95% non-Hispanic White) completed the ART/MRT, Test of Premorbid Functioning (ToPF), Dementia Rating Scale - 2nd Edition (DRS-2), Hopkins Verbal Learning Test - Revised (HVLT-R-DR), and select subtests from the Delis-Kaplan Executive Functioning System (D-KEFS) as measures of executive functioning (i.e., D-KEFS-EF) and processing speed (i.e., D-KEFS-PS). Pearson correlations and linear regressions were used to examine the relationships between the ART/MRT, cognition, and demographics.

RESULTS

Cognitive scores, with the exception of HVLT-R-DR, were positively correlated with ART/MRT score such that better cognitive performance was associated with greater print exposure (range r = 0.39-0.49). ART/MRT score was positively correlated with years of education and negatively correlated with age. ToPF and DRS-2 differentially and uniquely predicted ART/MRT score beyond the other cognitive and demographic variables and beyond each other.

CONCLUSIONS

Findings indicate that measures of print exposure reflect crystallized knowledge but may also capture fluid abilities that may be more vulnerable to age-related decline or neurodegeneration. Assessment of print exposure may offer an alternative to word reading measures that may be inappropriate for translation into other languages and for use with individuals with certain language difficulties.

Long-term study of the cognitive profile of Moyamoya Disease in adults

Moyamoya Disease (MMD) is a rare cerebrovascular disorder which can have significant cognitive consequences. The aim of the current study was to describe comprehensively the domain-specific cognitive profile of adult patients with MMD and to assess whether this changes in the absence of recurrent stroke over long-term follow-up. Comprehensive neuropsychological assessment covering seven cognitive domains was conducted on 61 adult patients with MMD at baseline and then at up to 3 further time points during follow up (median=2.31, 4.87 and 7.12 years). Although 27 patients had had prior surgical revasculariation, none had surgery between neuropsychological assessments. Cognitive impairment was common. At baseline, impairment in executive functions was most frequent (57%), followed by performance IQ (36%), speed of information processing (31%) and visual memory (30%). We found that the neuropsychological profile remains broadly stable over long-term follow-up with no clear indication of improvement or significant decline. The pattern of impairment also did not differ depending on age of onset or whether there was a history of either prior stroke at presentation or revascularisation surgery at presentation.

Lifespan normative data (18-89 years) for Raven's Advanced Progressive Matrices Set I

Raven's Advanced Progressive Matrices (APM) Set I is a validated and brief test of fluid intelligence, ideal for use in busy clinical settings. However, there is a dearth of normative data allowing an accurate interpretation of APM scores. To address this, we present normative data from across the adult lifespan (18-89 years) for the APM Set I. Data are presented in five age cohorts (total N = 352), including two older adult cohorts (65-79 years and 80-89 years), which allows age-standardized assessment. We also present data from a validated measure of premorbid intellectual ability, which was absent from previous standardizations of longer forms of the APM. In line with previous findings, a striking age-related decline was noted, beginning relatively early in adulthood and most marked amongst lower-scoring individuals. Older adults did not demonstrate difficulty with specific test items or make an increased proportion of specific errors. Sex was not a significant predictor of performance. The data set is of particular use in the neuropsychological assessment of older adults, given the known susceptibility of fluid intelligence to both the effects of normal ageing and acquired brain injury in older age. The results are discussed in light of theories of neurological ageing.

Graph lesion-deficit mapping of fluid intelligence

Fluid intelligence is arguably the defining feature of human cognition. Yet the nature of its relationship with the brain remains a contentious topic. Influential proposals drawing primarily on functional imaging data have implicated 'multiple demand' frontoparietal and more widely distributed cortical networks, but extant lesion-deficit studies with greater causal power are almost all small, methodologically constrained, and inconclusive. The task demands large samples of patients, comprehensive investigation of performance, fine-grained anatomical mapping, and robust lesion-deficit inference, yet to be brought to bear on it. We assessed 165 healthy controls and 227 frontal or non-frontal patients with unilateral brain lesions on the best-established test of fluid intelligence, Raven's Advanced Progressive Matrices, employing an array of lesion-deficit inferential models responsive to the potentially distributed nature of fluid intelligence. Non-parametric Bayesian stochastic block models were used to reveal the community structure of lesion deficit networks, disentangling functional from confounding pathological distributed effects. Impaired performance was confined to patients with frontal lesions [F(2,387) = 18.491; P < 0.001; frontal worse than non-frontal and healthy participants P < 0.01, P <0.001], more marked on the right than left [F(4,385) = 12.237; P < 0.001; right worse than left and healthy participants P < 0.01, P < 0.001]. Patients with non-frontal lesions were indistinguishable from controls and showed no modulation by laterality. Neither the presence nor the extent of multiple demand network involvement affected performance. Both conventional network-based statistics and non-parametric Bayesian stochastic block modelling heavily implicated the right frontal lobe. Crucially, this localization was confirmed on explicitly disentangling functional from pathology-driven effects within a layered stochastic block model, prominently highlighting a right frontal network involving middle and inferior frontal gyrus, pre- and post-central gyri, with a weak contribution from right superior parietal lobule. Similar results were obtained with standard lesion-deficit analyses. Our study represents the first large-scale investigation of the distributed neural substrates of fluid intelligence in the focally injured brain. Combining novel graph-based lesion-deficit mapping with detailed investigation of cognitive performance in a large sample of patients provides crucial information about the neural basis of intelligence. Our findings indicate that a set of predominantly right frontal regions, rather than a more widely distributed network, is critical to the high-level functions involved in fluid intelligence. Further they suggest that Raven's Advanced Progressive Matrices is a useful clinical index of fluid intelligence and a sensitive marker of right frontal lobe dysfunction.

TENSOR QUANTILE REGRESSION WITH APPLICATION TO ASSOCIATION BETWEEN NEUROIMAGES AND HUMAN INTELLIGENCE

Human intelligence is usually measured by well-established psychometric tests through a series of problem solving. The recorded cognitive scores are continuous but usually heavy-tailed with potential outliers and violating the normality assumption. Meanwhile, magnetic resonance imaging (MRI) provides an unparalleled opportunity to study brain structures and cognitive ability. Motivated by association studies between MRI images and human intelligence, we propose a tensor quantile regression model, which is a general and robust alternative to the commonly used scalar-on-image linear regression. Moreover, we take into account rich spatial information of brain structures, incorporating low-rankness and piece-wise smoothness of imaging coefficients into a regularized regression framework. We formulate the optimization problem as a sequence of penalized quantile regressions with a generalized Lasso penalty based on tensor decomposition, and develop a computationally efficient alternating direction method of multipliers algorithm (ADMM) to estimate the model components. Extensive numerical studies are conducted to examine the empirical performance of the proposed method and its competitors. Finally, we apply the proposed method to a large-scale important dataset: the Human Connectome Project. We find that the tensor quantile regression can serve as a prognostic tool to assess future risk of cognitive impairment progression. More importantly, with the proposed method, we are able to identify the most activated brain subregions associated with quantiles of human intelligence. The prefrontal and anterior cingulate cortex are found to be mostly associated with lower and upper quantile of fluid intelligence. The insular cortex associated with median of fluid intelligence is a rarely reported region.

The relationship between neuropsychological dispersion, processing speed and memory after electrical injury

Introduction: Previous studies of neuropsychological performance in electrical injury (EI) patients have produced evidence of deficits in various cognitive domains, but studies have yet to investigate relationships among performance in cognitive domains post-EI. This study examined whether dispersion among neuropsychological test scores was associated with injury parameters and neuropsychological performance in EI patients. Additionally, we examined whether dispersion, processing speed and/or executive abilities explain variance in episodic verbal and visual memory performance among EI patients.Method: Data from 52 post-acute EI patients undergoing outpatient evaluation with objectively-verified valid neuropsychological test performance were examined. Tests included measures of verbal and visual memory, processing speed, and executive functioning. Dispersion was calculated from executive functioning and processing speed scores.Results: Dispersion was not related to mean performance or injury characteristics, but was significantly negatively correlated with performance on a test of processing speed, suggesting that increased dispersion is associated with reduced cognitive efficiency post-EI. Delayed visual memory was related to both dispersion scores and processing speed. Stepwise regression equations predicting delayed memory determined that processing speed most significantly predicted delayed visual memory, even after controlling for immediate visual memory. No significant relationships emerged between verbal memory and non-memory neuropsychological scores.Conclusions: This is the first study to examine neuropsychological dispersion and relationships among domains of cognitive functioning in EI. Current results suggested that neuropsychological dispersion is not a marker of general functioning or severity of injury in EI patients, but may represent more specific processing speed abilities. Processing speed predicts delayed visual memory performance in EI patients, which should be considered in interpreting test scores during evaluations.

Examination of the reliability and validity of the NAB Naming Test in a diverse clinical sample

Objective: The Boston Naming Test, Second Edition (BNT-2) and the Neuropsychological Assessment Battery (NAB) Naming Test are common measures to assess visual confrontation naming ability. The comparably newer NAB Naming Test is a potential alternative to the BNT-2, given the latter's history of criticism. A recent psychometric investigation of the NAB Naming Test demonstrated sufficient reliability and validity in a large clinical sample; however, their study was limited by a lack of ethnic, racial, and language diversity, all of which can impact scores on naming tests.Method: The present study examined convergent and discriminant validity and internal consistency of the NAB Naming Test in a diverse clinical sample comprised of 225 veterans (87.6% men, 51.1% White/Caucasian, 29.3% bilingual, 64.0% with cognitive impairment). All but three participants identified as White/Caucasian, Hispanic/Latino or Black/African American. These psychometric properties were examined for the overall sample and for monolingual (English) and bilingual (English/Spanish) participants separately.Results: As expected, the NAB Naming Test demonstrated sufficient internal consistency and a negatively skewed distribution for the overall sample and monolingual and bilingual participants. Evidence for adequate convergent and discriminative validity was also established for monolingual and bilingual participants separately.Conclusion: In a diverse clinical sample with differing levels of self-reported language status, the NAB Naming Test demonstrated adequate psychometric properties. Although it represents a viable option in neuropsychological practice, continued awareness of patient-specific factors that could impact performance is recommended.