Sex significantly predicts medial temporal volume when controlling for the influence of ApoE4 biomarker and demographic variables: A cross-ethnic comparison.

OBJECTIVE: To explore the relationship between age, education, sex, and ApoE4 (+) status to brain volume among a cohort with amnestic mild cognitive impairment (aMCI). METHOD: One hundred and twenty-three participants were stratified into Hispanic (n = 75) and White non-Hispanic (WNH, N = 48). Multiple linear regression analyses were conducted with age, education, sex, and ApoE4 status as predictor variables and left and right combined MRI volumes of the hippocampus, parahippocampus, and entorhinal cortex as dependent variables. Variations in head sizes were corrected by normalization with a total intracranial volume measurement. RESULTS: Bonferroni-corrected results indicated that when controlling for ApoE4 status, education, and age, sex was a significant predictor of hippocampal volume among the Hispanic group (ß = .000464, R2 = .196, p < .01) and the WNH group (ß = .000455, R2 = .195, p < .05). Education (ß = .000028, R2 = .168, p < .01) and sex (ß = .000261, R2 = .168, p < .01) were significant predictors of parahippocampal volume among the Hispanic MCI group when controlling for the effects of ApoE4 status and age. One-way ANCOVAs comparing hippocampal and parahippocampal volume between males and females within groups revealed that females had significantly larger hippocampal volumes (p < .05). Hispanic females had significantly larger hippocampal (p < .001) and parahippocampal (p < .05) volume compared to males. No sex differences in parahippocampal volume were noted among WNHs. CONCLUSIONS: Biological sex, rather than ApoE4 status, was a greater predictor of hippocampal volume among Hispanic and WNH females. These findings add to the mixed literature on sex differences in dementia research and highlight continued emphasis on ethnic populations to elucidate on neurodegenerative disparities.

A distributed multitask multimodal approach for the prediction of Alzheimer's disease in a longitudinal study.

Predicting the progression of Alzheimer's Disease (AD) has been held back for decades due to the lack of sufficient longitudinal data required for the development of novel machine learning algorithms. This study proposes a novel machine learning algorithm for predicting the progression of Alzheimer's disease using a distributed multimodal, multitask learning method. More specifically, each individual task is defined as a regression model, which predicts cognitive scores at a single time point. Since the prediction tasks for multiple intervals are related to each other in chronological order, multitask regression models have been developed to track the relationship between subsequent tasks. Furthermore, since subjects have various combinations of recording modalities together with other genetic, neuropsychological and demographic risk factors, special attention is given to the fact that each modality may experience a specific sparsity pattern. The model is hence generalized by exploiting multiple individual multitask regression coefficient matrices for each modality. The outcome for each independent modality-specific learner is then integrated with complementary information, known as risk factor parameters, revealing the most prevalent trends of the multimodal data. This new feature space is then used as input to the gradient boosting kernel in search for a more accurate prediction. This proposed model not only captures the complex relationships between the different feature representations, but it also ignores any unrelated information which might skew the regression coefficients. Comparative assessments are made between the performance of the proposed method with several other well-established methods using different multimodal platforms. The results indicate that by capturing the interrelatedness between the different modalities and extracting only relevant information in the data, even in an incomplete longitudinal dataset, will yield minimized prediction errors.

Effects of Bilingualism on Verbal and Nonverbal Memory Measures in Mild Cognitive Impairment.

OBJECTIVES: Maintaining two active languages may increase cognitive and brain reserve among bilingual individuals. We explored whether such a neuroprotective effect was manifested in the performance of memory tests for participants with amnestic mild cognitive impairment (aMCI). METHODS: We compared 42 bilinguals to 25 monolinguals on verbal and nonverbal memory tests. We used: (a) the Loewenstein-Acevedo Scales for Semantic Interference and Learning (LASSI-L), a sensitive test that taps into proactive, retroactive, and recovery from proactive semantic interference (verbal memory), and (b) the Benson Figure delayed recall (nonverbal memory). A subsample had volumetric MRI scans. RESULTS: The bilingual group significantly outperformed the monolingual group on two LASSI-L cued recall measures (Cued A2 and Cued B2). A measure of maximum learning (Cued A2) showed a correlation with the volume of the left hippocampus in the bilingual group only. Cued B2 recall (sensitive to recovery from proactive semantic interference) was correlated with the volume of the hippocampus and the entorhinal cortex of both cerebral hemispheres in the bilingual group, as well as with the left and right hippocampus in the monolingual group. The memory advantage in bilinguals on these measures was associated with higher inhibitory control as measured by the Stroop Color-Word test. CONCLUSIONS: Our results demonstrated a superior performance of aMCI bilinguals over aMCI monolinguals on selected verbal memory tasks. This advantage was not observed in nonverbal memory. Superior memory performance of bilinguals over monolinguals suggests that bilinguals develop a different and perhaps more efficient semantic association system that influences verbal recall. (JINS, 2019, 25, 15-28).

A Novel Cognitive Stress Test for the Detection of Preclinical Alzheimer Disease: Discriminative Properties and Relation to Amyloid Load.

OBJECTIVE: To examine the utility of a novel "cognitive stress test" to detect subtle cognitive impairments and amyloid load within the brains of neuropsychologically normal community-dwelling elders. METHODS: Participants diagnosed as cognitively normal (CN), subjective memory impairment (SMI), mild cognitive impairment (MCI), and preclinical mild cognitive impairment (PreMCI) were administered the Loewenstein-Acevedo Scale for Semantic Interference and Learning (LASSI-L), a sensitive test of proactive semantic interference (PSI), retroactive semantic interference, and, uniquely, the ability to recover from the effects of PSI. Ninety-three subjects (31 men and 62 women) were recruited from three academic institutions in a research consortium. A subset of these individuals underwent 18F florbetapir positron emission tomography scanning. Relative percentages of impairment for each diagnostic group on the LASSI-L were calculated by χ(2) and Fisher's exact tests. Spearman's rho was used to examine associations between amyloid load and different cognitive measures. RESULTS: LASSI-L deficits were identified among 89% of those with MCI, 47% with PreMCI, 33% with SMI, and 13% classified as CN. CN subjects had no difficulties with recovery from PSI, whereas SMI, preMCI, and MCI participants evidenced deficits in recovery from PSI effects. Among a subgroup of participants with normal scores on traditional neuropsychological tests, the strong associations were between the failure to recover from the effects of PSI and amyloid load in the brain. CONCLUSION: Failure to recover or compensate for the effects of PSI on the LASSI-L distinguishes the LASSI-L from other widely used neuropsychological tests and appears to be sensitive to subtle cognitive impairments and increasing amyloid load.

Proactive Semantic Interference is Associated with Total and Regional Abnormal Amyloid Load in Non-Demented Community-Dwelling Elders: A Preliminary Study.

OBJECTIVE: To evaluate the relationship between susceptibility to proactive semantic interference (PSI) and retroactive semantic interference (RSI) and brain amyloid load in non-demented elders. METHODS: 27 participants (11 cognitively normal [CN] with subjective memory complaints, 8 CN without memory complaints, and 8 with mild cognitive impairment [MCI]) underwent complete neurological and neuropsychological evaluations. Participants also received the Semantic Interference Test (SIT) and AV-45 amyloid PET imaging. RESULTS: High levels of association were present between total amyloid load, regional amyloid levels, and the PSI measure (in the entire sample and a subsample excluding MCI subjects). RSI and other memory measures showed much weaker associations or no associations with total and regional amyloid load. No associations between amyloid levels and non-memory performance were observed. CONCLUSIONS: In non-demented individuals, vulnerability to PSI was highly associated with total and regional beta-amyloid load and may be an early cognitive marker of brain pathology.

An evaluation of deficits in semantic cueing and proactive and retroactive interference as early features of Alzheimer's disease.

OBJECTIVES: To determine the degree to which susceptibility to different types of semantic interference may reflect the initial manifestations of early Alzheimer's disease (AD) beyond the effects of global memory impairment. METHODS: Normal elderly (NE) subjects (n = 47), subjects with amnestic mild cognitive impairment (aMCI; n = 34), and subjects with probable AD (n = 40) were evaluated by using a unique cued recall paradigm that allowed for evaluation of both proactive and retroactive interference effects while controlling for global memory impairment (i.e., Loewenstein-Acevedo Scales of Semantic Interference and Learning [LASSI-L] procedure). RESULTS: Controlling for overall memory impairment, aMCI subjects had much greater proactive and retroactive interference effects than NE subjects. LASSI-L indices of learning by using cued recall revealed high levels of sensitivity and specificity, with an overall correct classification rate of 90%. These measures provided better discrimination than traditional neuropsychological measures of memory function. CONCLUSIONS: The LASSI-L paradigm is unique and unlike other assessments of memory in that items posed for cued recall are explicitly presented, and semantic interference and cueing effects can be assessed while controlling for initial level of memory impairment. This is a powerful procedure that allows the participant to serve as his or her own control. The high levels of discrimination between subjects with aMCI and normal cognition that exceeded traditional neuropsychological measures makes the LASSI-L worthy of further research in the detection of early AD.

Case study: a patient with agenesis of the corpus callosum with minimal associated neuropsychological impairment.

This is a case study of an 88-year-old man who presented with agenesis of the corpus callosum and colpocephaly. Symptomatically, he reported a sudden onset of mild, intermittent left hand apraxia, but denied any previous manifestations consistent with this type of brain malformation. The patient underwent neuroimaging, evaluation by neurology, and comprehensive neuropsychological testing to determine the nature of any other associated impairments. Test results indicated that he was, with a few exceptions, neuropsychologically normal. He performed well on tests that are highly sensitive to acquired brain dysfunction. His most notable deficit was failed performance in the simultaneous and coordinated use of both hands in using tactile and proprioceptive feedback on the Tactual Performance Test. This case is discussed in terms of plasticity of the developing brain, including compensatory mechanisms, highlighting the variability in clinical outcome in the context of congenital brain malformation. This case study illustrates the strong influence of cerebral plasticity as well as a possible circumscribed manifestation of interhemispheric disconnection.

Cross-cultural Diagnostic Validity of the Multilingual Naming Test (MINT) in a Sample of Older Adults.

OBJECTIVE: We aimed to evaluate the psychometric properties and diagnostic accuracy of the 32-item version of the Multilingual Naming Test (MINT) in participants from 2 ethnic groups (European Americans [EA; n = 106] and Hispanic Americans [HA; n = 175]) with 3 diagnostic groups (cognitively normal [CN], n = 94, mild cognitive impairment [MCI], n = 148, and dementia, n = 39). METHOD: An Item Response Theory model was used to evaluate items across ethnicity and language groups (Spanish and English), resulting in a 24-item version. We analyzed the MINT discriminant and predictive validity across diagnostic groups. RESULTS: A total of 8 items were differentially difficult between languages in the 32-item version of the MINT. EA scored significantly higher than HA, but the difference was not significant when removing those 8 items (controlling for Education). The Receiver Operating Characteristics showed that the MINT had poor accuracy when identifying CN participants and was acceptable in identifying dementia participants but unacceptable in classifying MCI participants. Finally, we tested the association between MINT scores and magnetic resonance imaging volumetric measures of language-related areas in the temporal and frontal lobes. The 32-item MINT in English and Spanish and the 24-item MINT in Spanish were significantly correlated with the bilateral middle temporal gyrus. The left fusiform gyrus correlated with MINT scores regardless of language and MINT version. We also found differential correlations depending on the language of administration. CONCLUSIONS: Our results highlight the importance of analyzing cross-cultural samples when implementing clinical neuropsychological tests such as the MINT.

Stability in cognitive classification as a function of severity of impairment and ethnicity: A longitudinal analysis.

OBJECTIVE: The interaction of ethnicity, progression of cognitive impairment, and neuroimaging biomarkers of Alzheimer's Disease remains unclear. We investigated the stability in cognitive status classification (cognitively normal [CN] and mild cognitive impairment [MCI]) of 209 participants (124 Hispanics/Latinos and 85 European Americans). METHODS: Biomarkers (structural MRI and amyloid PET scans) were compared between Hispanic/Latino and European American individuals who presented a change in cognitive diagnosis during the second or third follow-up and those who remained stable over time. RESULTS: There were no significant differences in biomarkers between ethnic groups in any of the diagnostic categories. The frequency of CN and MCI participants who were progressors (progressed to a more severe cognitive diagnosis at follow-up) and non-progressors (either stable through follow-ups or unstable [progressed but later reverted to a diagnosis of CN]) did not significantly differ across ethnic groups. Progressors had greater atrophy in the hippocampus (HP) and entorhinal cortex (ERC) at baseline compared to unstable non-progressors (reverters) for both ethnic groups, and more significant ERC atrophy was observed among progressors of the Hispanic/Latino group. For European Americans diagnosed with MCI, there were 60% more progressors than reverters (reverted from MCI to CN), while among Hispanics/Latinos with MCI, there were 7% more reverters than progressors. Binomial logistic regressions predicting progression, including brain biomarkers, MMSE, and ethnicity, demonstrated that only MMSE was a predictor for CN participants at baseline. However, for MCI participants at baseline, HP atrophy, ERC atrophy, and MMSE predicted progression.

Patient values in healthcare decision making among diverse older adults.

OBJECTIVE: To provide high-quality healthcare, it is essential to understand values that guide the healthcare decisions of older adults. We investigated the types of values that culturally diverse older adults incorporate in medical decision making. METHODS: Focus groups were held with older adults who varied in cognitive status (mildly impaired versus those with normal cognition) and ethnicity (Hispanic and non-Hispanic). Investigators used a qualitative descriptive approach to analyze transcripts and identify themes. RESULTS: Forty-nine individuals (49% with cognitive impairment; 51% Hispanic) participated. Participants expressed a wide range of values relating to individual factors, familial/cultural beliefs and expectations, balancing risks and benefits, receiving decisional support, and considering values other than their own. Participants emphasized that values are individual-specific, influenced by aging, and change throughout life course. Participants described barriers and facilitators that interfere with or promote value solicitation and incorporation during medical encounters. CONCLUSION: Study findings highlight that in older adults with various health experiences, cognitive and physical health status, and sociocultural backgrounds, medical decisions are influenced by a variety of values. PRACTICAL IMPLICATIONS: Clinicians should take time to elicit, understand, and reassess the different types of values of older adults.

A Tensorized Multitask Deep Learning Network for Progression Prediction of Alzheimer's Disease.

With the advances in machine learning for the diagnosis of Alzheimer's disease (AD), most studies have focused on either identifying the subject's status through classification algorithms or on predicting their cognitive scores through regression methods, neglecting the potential association between these two tasks. Motivated by the need to enhance the prospects for early diagnosis along with the ability to predict future disease states, this study proposes a deep neural network based on modality fusion, kernelization, and tensorization that perform multiclass classification and longitudinal regression simultaneously within a unified multitask framework. This relationship between multiclass classification and longitudinal regression is found to boost the efficacy of the final model in dealing with both tasks. Different multimodality scenarios are investigated, and complementary aspects of the multimodal features are exploited to simultaneously delineate the subject's label and predict related cognitive scores at future timepoints using baseline data. The main intent in this multitask framework is to consolidate the highest accuracy possible in terms of precision, sensitivity, F1 score, and area under the curve (AUC) in the multiclass classification task while maintaining the highest similarity in the MMSE score as measured through the correlation coefficient and the RMSE for all time points under the prediction task, with both tasks, run simultaneously under the same set of hyperparameters. The overall accuracy for multiclass classification of the proposed KTMnet method is 66.85 ± 3.77. The prediction results show an average RMSE of 2.32 ± 0.52 and a correlation of 0.71 ± 5.98 for predicting MMSE throughout the time points. These results are compared to state-of-the-art techniques reported in the literature. A discovery from the multitasking of this consolidated machine learning framework is that a set of hyperparameters that optimize the prediction results may not necessarily be the same as those that would optimize the multiclass classification. In other words, there is a breakpoint beyond which enhancing further the results of one process could lead to the downgrading in accuracy for the other.

The association of depression and apathy with Alzheimer's disease biomarkers in a cross-cultural sample.

Cross-cultural differences in the association between neuropsychiatric symptoms and Alzheimer's disease (AD) biomarkers are not well understood. This study aimed to (1) compare depressive symptoms and frequency of reported apathy across diagnostic groups of participants with normal cognition (CN), mild cognitive impairment (MCI), and dementia, as well as ethnic groups of Hispanic Americans (HA) and European Americans (EA); (2) evaluate the relationship between depression and apathy with Aß deposition and brain atrophy. Statistical analyses included ANCOVAs, chi-squared, nonparametric tests, correlations, and logistic regressions. Higher scores on the Geriatric Depression Scale (GDS-15) were reported in the MCI and dementia cohorts, while older age corresponded with lower GDS-15 scores. The frequency of apathy differed across diagnoses within each ethnicity, but not when comparing ethnic groups. Reduced volume in the rostral anterior cingulate cortex (ACC) significantly correlated with and predicted apathy for the total sample after applying false discovery rate corrections (FDR), controlling for covariates. The EA group separately demonstrated a significant negative relationship between apathy and superior frontal volume, while for HA, there was a relationship between rostral ACC volume and apathy. Apathy corresponded with higher Aß levels for the total sample and for the CN and HA groups.

Phase 1 Safety Trial of Autologous Human Schwann Cell Transplantation in Chronic Spinal Cord Injury.

A phase 1 open-label, non-randomized clinical trial was conducted to determine feasibility and safety of autologous human Schwann cell (ahSC) transplantation accompanied by rehabilitation in participants with chronic spinal cord injury (SCI). Magnetic resonance imaging (MRI) was used to screen eligible participants to estimate an individualized volume of cell suspension to be implanted. The trial incorporated standardized multi-modal rehabilitation before and after cell delivery. Participants underwent sural nerve harvest, and ahSCs were isolated and propagated in culture. The dose of culture-expanded ahSCs injected into the chronic spinal cord lesion of each individual followed a cavity-filling volume approach. Primary outcome measures for safety and trend-toward efficacy were assessed. Two participants with American Spinal Injury Association Impairment Scale (AIS) A and two participants with incomplete chronic SCI (AIS B, C) were each enrolled in cervical and thoracic SCI cohorts (n = 8 total). All participants completed the study per protocol, and no serious adverse events related to sural nerve harvest or ahSC transplantation were reported. Urinary tract infections and skin abrasions were the most common adverse events reported. One participant experienced a 4-point improvement in motor function, a 6-point improvement in sensory function, and a 1-level improvement in neurological level of injury. Follow-up MRI in the cervical (6 months) and thoracic (24 months) cohorts revealed a reduction in cyst volume after transplantation with reduced effect over time. This phase 1 trial demonstrated the feasibility and safety of ahSC transplantation combined with a multi-modal rehabilitation protocol for participants with chronic SCI.

Depression and the Diagnosis of MCI in a Culturally Diverse Sample in the United States.

OBJECTIVE: To analyze (1) whether there are ethnic differences in the severity of depressive symptoms between groups of elders classified as cognitively normal (CN) or amnestic mild cognitive impairment (aMCI) and (2) the influence of depressive symptoms on specific cognitive performance by ethnicity across diagnoses, controlling for covariates. METHODS: 164 Hispanics residing in the United States (HAs) and European Americans (EAs) (100 women; Mage = 72.1, SD = 8.0) were diagnosed as either CN or aMCI. Depressive symptoms were measured with the Geriatric Depression Scale (GDS-15). Cognition was assessed using the Loewenstein-Acevedo Scales for Semantic Interference and Learning (semantic memory), Multilingual Naming Test (confrontation naming), and the Stroop Test (Color-Word condition; executive function). A 2 × 2 univariate ANCOVA as well as linear and logistic regressions explored differences in depressive symptoms among diagnostic and ethnic groups. RESULTS: Higher depression was seen in aMCI compared to the CN group for both ethnicities, after controlling for age, education, gender, and Mini-Mental State Examination score. Greater levels of depression also predicted lower scores in confrontation naming and semantic memory for only the EA group and marginally in scores of executive function for HA participants. GDS-15 scores of ≤ 4 also predicted less likelihood of aMCI diagnosis. CONCLUSIONS: Severity of depressive symptoms was associated with greater cognitive impairment, independent of ethnicity. Significant results suggest detrimental effects of depression on clinical diagnoses most evidently for subjects from the EA group.

The Association Between Functional Assessment and Structural Brain Biomarkers in an Ethnically Diverse Sample With Normal Cognition, Mild Cognitive Impairment, or Dementia.

OBJECTIVE: To investigate the association between the functional activities questionnaire (FAQ) and brain biomarkers (bilateral hippocampal volume [HV], bilateral entorhinal volume [ERV], and entorhinal cortical thickness [ERT]) in cognitively normal (CN) individuals, mild cognitive impairment (MCI), or dementia. METHOD: In total, 226 participants (137 females; mean age = 71.76, SD = 7.93; Hispanic Americans = 137; European Americans = 89) were assessed with a comprehensive clinical examination, a neuropsychological battery, a structural magnetic resonance imaging, and were classified as CN or diagnosed with MCI or dementia. Linear regression analyses examined the association between functional activities as measured by the FAQ on brain biomarkers, including HV, ERV, and ERT, controlling for age, education, global cognition, gender, and ethnicity. RESULTS: The FAQ significantly predicted HV, ERV, and ERT for the entire sample. However, this association was not significant for ERV and ERT when excluding the dementia group. The FAQ score remained a significant predictor of HV for the non-dementia group. Age, education, gender, ethnicity, Montreal Cognitive Assessment score, and FAQ were also significant predictors of HV for the overall sample, suggesting that younger Hispanic females with fewer years of education, higher global mental status, and better functioning, were more likely to have larger HV. CONCLUSION: FAQ scores were related to HV in older adults across clinical groups (CN, MCI, and dementia), but its association with the entorhinal cortex was driven by individuals with dementia. Demographic variables, including ethnicity, additionally influenced these associations.

Gaussian discriminative component analysis for early detection of Alzheimer's disease: A supervised dimensionality reduction algorithm.

BACKGROUND: Using multiple modalities of biomarkers, several machine leaning-based approaches have been proposed to characterize patterns of structural, functional and metabolic differences discernible from multimodal neuroimaging data for Alzheimer's disease (AD). Current investigations report several studies using binary classification often augmented with local feature selection methods, while fewer other studies address the challenging problem of multiclass classification. NEW METHOD: To assess the merits of each of these research directions, this study introduces a supervised Gaussian discriminative component analysis (GDCA) algorithm, which can effectively delineate subtle changes of early mild cognitive impairment (EMCI) group in relation to the cognitively normal control (CN) group. Using 251 CN, 297 EMCI, 196 late MCI (LMCI), and 162 AD subjects from the Alzheimer's Disease Neuroimaging Initiative (ADNI) and considering both structural and functional (metabolic) information from magnetic resonance imaging (MRI) and positron emission tomography (PET) modalities as input, the proposed method conducts a dimensionality reduction algorithm taking into consideration the interclass information to define an optimal eigenspace that maximizes the discriminability of selected eigenvectors. RESULTS: The proposed algorithm achieves an accuracy of 79.25 % for delineating EMCI from CN using 38.97 % of Gaussian discriminative components (i.e., dimensionality reduction). Moreover, for detecting the different stages of AD, a multiclass classification experiment attained an overall accuracy of 67.69 %, and more notably, discriminates MCI and AD groups from the CN group with an accuracy of 75.28 % using 48.90 % of the Gaussian discriminative components. COMPARISON WITH EXISTING METHOD(S): The classification results of the proposed GDCA method outperform the more recently published state-of-the-art methods in AD-related multiclass classification tasks, and seems to be the most stable and reliable in terms of relating the most relevant features to the optimal classification performance. CONCLUSION: The proposed GDCA model with its high prospects for multiclass classification has a high potential for deployment as a computer aided clinical diagnosis system for AD.

Memory Impairment in Relapsing-Remitting Multiple Sclerosis Using a Challenging Semantic Interference Task.

Objective: Episodic memory is frequently impaired in Multiple Sclerosis (MS), but the cognitive characteristics and neuropsychological processes involved remain controversial. Our aim was to study episodic memory dysfunction in MS, using the LASSI-L, a novel memory-based cognitive stress test that uses a new paradigm that capitalizes on semantic interference. Methods: Cross-sectional study in which 93 patients with MS (relapsing-remitting) and 124 healthy controls were included. The LASSI-L test was administered to all participants, as well as a comprehensive neuropsychological battery including a selective reminding test. MS patients were divided into two groups, with cognitive impairment (CI-MS) and cognitively preserved (CP-MS). Results: Reliability of the LASSI-L test was high (Cronbach's alpha 0.892) and there were less ceiling effects. MS patients scored lower than controls on all LASSI-L subtests, except for maximum storage of the initial target items (CRA2). Effect sizes were moderate-large. A delay in learning, difficulties in retroactive semantic interference, failure to recover from proactive semantic interference, and delayed recall were the most frequent findings in MS patients. Scores associated with maximum storage capacity, and retroactive semantic interference were the most strongly associated with cognitive impairment and employment status. Conclusion: We found that deficits in maximum learning, difficulties in recovery from the effects of proactive semantic interference and retroactive semantic interference are three important breakdowns in episodic memory deficits among patients with MS. The LASSI-L showed good psychometric and diagnostic properties. Overall, our study supports the utility of the LASSI-L, as a new cognitive test, useful for neuropsychological assessment in MS in clinical and research settings.

A Gaussian-based model for early detection of mild cognitive impairment using multimodal neuroimaging.

BACKGROUND: Diagnosis of early mild cognitive impairment (EMCI) as a prodromal stage of Alzheimer's disease (AD) with its delineation from the cognitively normal (CN) group remains a challenging but essential step for the planning of early treatment. Although several studies have focused on the MCI diagnosis, this study introduces the early stage of MCI to assess more thoroughly the earliest signs of disease manifestation and progression. NEW METHOD: We used random forest feature selection model with a Gaussian-based algorithm to perform method evaluation. This integrated method serves to define multivariate normal distributions in order to classify different stages of AD, with the focus placed on detecting EMCI subjects in the most challenging classification of CN vs. EMCI. RESULTS: Using 896 participants classified into the four categories of CN, EMCI, late mild cognitive impairment (LMCI) and AD, the results show that the EMCI group can be delineated from the CN group with a relatively high accuracy of 78.8% and sensitivity of 81.3%. COMPARISON WITH EXISTING METHOD(S): The feature selection model and classifier are compared with some other prominent algorithms. Although higher accuracy has been achieved using the Gaussian process (GP) model (78.8%) over the SVM classifier (75.6%) for CN vs. EMCI classification, with 0.05 being the cutoff for significance, and based on student's t-test, it was determined that the differences for accuracy, sensitivity, specificity between the GP method and support vector machine (SVM) are not statistically significant. CONCLUSION: Addressing the challenging classification of CN vs. EMCI provides useful information to help clinicians and researchers determine essential measures that can help in the early detection of AD.

Types of errors on a semantic interference task in mild cognitive impairment and dementia.

OBJECTIVE: This research aimed to determine whether qualitative analysis of different types of intrusion errors on a verbal cognitive task was useful in detecting subtle cognitive impairment in preclinical stages prior to the progression to dementia. METHOD: Different types of semantic intrusions on the Loewenstein-Acevedo Scales of Semantic Interference and Learning (LASSI-L) were compared across 160 individuals diagnosed as cognitively normal (CN), amnestic Mild Cognitive Impairment (aMCI), and dementia. The sample included Hispanics and non-Hispanic European Americans. RESULTS: Across diagnostic groups, the most common type of intrusion error was actual targets presented from a competing word list under conditions eliciting proactive semantic interference (PSI), and retroactive semantic interference (RSI), followed by intrusions that represented one of three overlapping semantic categories but none of the targets from List A or B. Nonsemantic intrusions rarely occurred. These competing list intrusions (CLI) and semantically related intrusions (SRI) differentiated between aMCI and CN participants. Further, these intrusion error were related to brain amyloid load, indicating their importance as potential primary markers of AD-related neurodegeneration. Ethnicity effects were not seen across the types of intrusion errors. CONCLUSIONS: Two types of intrusion errors (CLI and SRI) showed differences between the CN and aMCI group, with the aMCI group evidencing a higher rate of these intrusion errors compared with the CN group. These results support previous literature about the LASSI-L's sensitivity at the earliest stages of abnormal aging. (PsycINFO Database Record (c) 2019 APA, all rights reserved).

Novel Cognitive Paradigms for the Detection of Memory Impairment in Preclinical Alzheimer's Disease.

In spite of advances in neuroimaging and other brain biomarkers to assess preclinical Alzheimer's disease (AD), cognitive assessment has relied on traditional memory paradigms developed well over six decades ago. This has led to a growing concern about their effectiveness in the early diagnosis of AD which is essential to develop preventive and early targeted interventions before the occurrence of multisystem brain degeneration. We describe the development of novel tests that are more cognitively challenging, minimize variability in learning strategies, enhance initial acquisition and retrieval using cues, and exploit vulnerabilities in persons with incipient AD such as the susceptibility to proactive semantic interference, and failure to recover from proactive semantic interference. The advantages of various novel memory assessment paradigms are examined as well as how they compare with traditional neuropsychological assessments of memory. Finally, future directions for the development of more effective assessment paradigms are suggested.