Characterizing cognitive performance in a large longitudinal study of aging with computerized semantic indices of verbal fluency

Exploration versus exploitation decisions in the human brain: A systematic review of functional neuroimaging and neuropsychological studies

Thoughts and actions are often driven by a decision to either explore new avenues with unknown outcomes, or to exploit known options with predictable outcomes. Yet, the neural mechanisms underlying this exploration-exploitation trade-off in humans remain poorly understood. This is attributable to variability in the operationalization of exploration and exploitation as psychological constructs, as well as the heterogeneity of experimental protocols and paradigms used to study these choice behaviours. To address this gap, here we present a comprehensive review of the literature to investigate the neural basis of explore-exploit decision-making in humans. We first conducted a systematic review of functional magnetic resonance imaging (fMRI) studies of exploration-versus exploitation-based decision-making in healthy adult humans during foraging, reinforcement learning, and information search. Eleven fMRI studies met inclusion criterion for this review. Adopting a network neuroscience framework, synthesis of the findings across these studies revealed that exploration-based choice was associated with the engagement of attentional, control, and salience networks. In contrast, exploitation-based choice was associated with engagement of default network brain regions. We interpret these results in the context of a network architecture that supports the flexible switching between externally and internally directed cognitive processes, necessary for adaptive, goal-directed behaviour. To further investigate potential neural mechanisms underlying the exploration-exploitation trade-off we next surveyed studies involving neurodevelopmental, neuropsychological, and neuropsychiatric disorders, as well as lifespan development, and neurodegenerative diseases. We observed striking differences in patterns of explore-exploit decision-making across these populations, again suggesting that these two decision-making modes are supported by independent neural circuits. Taken together, our review highlights the need for precision-mapping of the neural circuitry and behavioural correlates associated with exploration and exploitation in humans. Characterizing exploration versus exploitation decision-making biases may offer a novel, trans-diagnostic approach to assessment, surveillance, and intervention for cognitive decline and dysfunction in normal development and clinical populations.

Neuropsychological differential diagnosis of Alzheimer's disease and vascular dementia: a systematic review with meta-regressions

Introduction

Diagnostic classification systems and guidelines posit distinguishing patterns of impairment in Alzheimer's (AD) and vascular dementia (VaD). In our study, we aim to identify which diagnostic instruments distinguish them.

Methods

We searched PubMed and PsychInfo for empirical studies published until December 2020, which investigated differences in cognitive, behavioral, psychiatric, and functional measures in patients older than 64 years and reported information on VaD subtype, age, education, dementia severity, and proportion of women. We systematically reviewed these studies and conducted Bayesian hierarchical meta-regressions to quantify the evidence for differences using the Bayes factor (BF). The risk of bias was assessed using the Newcastle-Ottawa-Scale and funnel plots.

Results

We identified 122 studies with 17,850 AD and 5,247 VaD patients. Methodological limitations of the included studies are low comparability of patient groups and an untransparent patient selection process. In the digit span backward task, AD patients were nine times more probable (BF = 9.38) to outperform VaD patients (β g = 0.33, 95% ETI = 0.12, 0.52). In the phonemic fluency task, AD patients outperformed subcortical VaD (sVaD) patients (β g = 0.51, 95% ETI = 0.22, 0.77, BF = 42.36). VaD patients, in contrast, outperformed AD patients in verbal (β g = -0.61, 95% ETI = -0.97, -0.26, BF = 22.71) and visual (β g = -0.85, 95% ETI = -1.29, -0.32, BF = 13.67) delayed recall. We found the greatest difference in verbal memory, showing that sVaD patients outperform AD patients (β g = -0.64, 95% ETI = -0.88, -0.36, BF = 72.97). Finally, AD patients performed worse than sVaD patients in recognition memory tasks (β g = -0.76, 95% ETI = -1.26, -0.26, BF = 11.50).

Conclusion

Our findings show inferior performance of AD in episodic memory and superior performance in working memory. We found little support for other differences proposed by diagnostic systems and diagnostic guidelines. The utility of cognitive, behavioral, psychiatric, and functional measures in differential diagnosis is limited and should be complemented by other information. Finally, we identify research areas and avenues, which could significantly improve the diagnostic value of cognitive measures.

How well does the discrepancy between semantic and letter verbal fluency performance distinguish Alzheimer's dementia from typical aging?

In Alzheimer's dementia (AD), greater declines in semantic fluency (SF) relative to letter fluency (LF) have been assumed to reflect semantic disintegration. However, the same pattern is observed in typical aging and neurodegenerative disorders besides AD. We examined this assumption by comparing different aspects of SF and LF performance in older adults with and without dementia, and identifying which verbal fluency measures most clearly distinguish AD from typical aging. Verbal fluency data were compared from 109 individuals with AD and 66 typically aging adults. Correct items, clusters, and errors were analyzed using both raw counts and proportions. Regression analyses examined Task-by-Group interactions and the impact of demographic variables on verbal fluency measures. ROC analyses examined the sensitivity and specificity of the different outcome measures. In regressions, interactions were found for raw but not proportional data, indicating that different group patterns were driven largely by the number of correct items produced. Similarly, in ROC analyses, raw SF totals showed stronger discriminability between groups than either raw discrepancy scores (SF-LF) or discrepancy ratios (SF/LF). Age and cognitive status (MMSE) were the strongest individual predictors of performance. Findings suggest that AD entails quantitative declines in verbal fluency, but qualitatively similar patterns of performance relative to typically aging adults. Thus, SF declines in AD seem to be at least partially attributable to an exaggeration of the underlying mechanisms common to typical aging, and do not necessarily implicate semantic disintegration.

The Accuracy of Speech and Linguistic Analysis in Early Diagnostics of Neurocognitive Disorders in a Memory Clinic Setting

OBJECTIVE

To investigate whether automatic analysis of the Semantic Verbal Fluency test (SVF) is reliable and can extract additional information that is of value for identifying neurocognitive disorders. In addition, the associations between the automatically derived speech and linguistic features and other cognitive domains were explored.

METHOD

We included 135 participants from the memory clinic of the Maastricht University Medical Center+ (with Subjective Cognitive Decline [SCD; N = 69] and Mild Cognitive Impairment [MCI]/dementia [N = 66]). The SVF task (one minute, category animals) was recorded and processed via a mobile application, and speech and linguistic features were automatically extracted. The diagnostic performance of the automatically derived features was investigated by training machine learning classifiers to differentiate SCD and MCI/dementia participants.

RESULTS

The intraclass correlation for interrater reliability between the clinical total score (golden standard) and automatically derived total word count was 0.84. The full model including the total word count and the automatically derived speech and linguistic features had an Area Under the Curve (AUC) of 0.85 for differentiating between people with SCD and MCI/dementia. The model with total word count only and the model with total word count corrected for age showed an AUC of 0.75 and 0.81, respectively. Semantic switching correlated moderately with memory as well as executive functioning.

CONCLUSION

The one-minute SVF task with automatically derived speech and linguistic features was as reliable as the manual scoring and differentiated well between SCD and MCI/dementia. This can be considered as a valuable addition in the screening of neurocognitive disorders and in clinical practice.

Phonological and Semantic Fluency in Alzheimer's Disease: A Systematic Review and Meta-Analysis

BACKGROUND

Semantic and Phonological fluency (SF and PF) are routinely evaluated in patients with Alzheimer's disease (AD). There are disagreements in the literature regarding which fluency task is more affected while developing AD. Most studies focus on SF assessment, given its connection with the temporoparietal amnesic system. PF is less reported, it is related to working memory, which is also impaired in probable and diagnosed AD. Differentiating between performance on these tasks might be informative in early AD diagnosis, providing an accurate linguistic profile.

OBJECTIVE

Compare SF and PF performance in healthy volunteers, volunteers with probable AD, and patients with AD diagnosis, considering the heterogeneity of age, gender, and educational level variables.

METHODS

A total of 8 studies were included for meta-analysis, reaching a sample size of 1,270 individuals (568 patients diagnosed with AD, 340 with probable AD diagnosis, and 362 healthy volunteers).

RESULTS

The three groups consistently performed better on SF than PF. When progressing to a diagnosis of AD, we observed a significant difference in SF and PF performance across our 3 groups of interest (p = 0.04). The age variable explained a proportion of this difference in task performance across the groups, and as age increases, both tasks equally worsen.

CONCLUSION

The performance of SF and PF might play a differential role in early AD diagnosis. These tasks rely on partially different neural bases of language processing. They are thus worth exploring independently in diagnosing normal aging and its transition to pathological stages, including probable and diagnosed AD.

A comparison of techniques for deriving clustering and switching scores from verbal fluency word lists

Objective

To compare techniques for computing clustering and switching scores in terms of agreement, correlation, and empirical value as predictors of incident cognitive impairment (ICI).

Methods

We transcribed animal and letter F fluency recordings on 640 cases of ICI and matched controls from a national epidemiological study, amending each transcription with word timings. We then calculated clustering and switching scores, as well as scores indexing speed of responses, using techniques described in the literature. We evaluated agreement among the techniques with Cohen’s κ and calculated correlations among the scores. After fitting a base model with raw scores, repetitions, and intrusions, we fit a series of Bayesian logistic regression models adding either clustering and switching scores or speed scores, comparing the models in terms of several metrics. We partitioned the ICI cases into acute and progressive cases and repeated the regression analysis for each group.

Results

For animal fluency, we found that models with speed scores derived using the slope difference algorithm achieved the best values of the Watanabe–Akaike Information Criterion (WAIC), but with good net reclassification improvement (NRI) only for the progressive group (8.2%). For letter fluency, different models excelled for prediction of acute and progressive cases. For acute cases, NRI was best for speed scores derived from a network model (3.4%), while for progressive cases, the best model used clustering and switching scores derived from the same network model (5.1%). Combining variables from the best animal and letter F models led to marginal improvements in model fit and NRI only for the all-cases and acute-cases analyses.

Conclusion

Speed scores improve a base model for predicting progressive cognitive impairment from animal fluency. Letter fluency scores may provide complementary information.

Automated assessment of speech production and prediction of MCI in older adults

The population of older adults is growing dramatically and, with it comes increased prevalence of neurological disorders, including Alzheimer's disease (AD). Though existing cognitive screening tests can aid early detection of cognitive decline, these methods are limited in their sensitivity and require trained administrators. The current study sought to determine whether it is possible to identify persons with mild cognitive impairment (MCI) using automated analysis of spontaneous speech. Participants completed a brief neuropsychological test battery and a spontaneous speech task. MCI was classified using established research criteria, and lexical-semantic features were calculated from spontaneous speech. Logistic regression analyses compared the predictive ability of a commonly-used cognitive screening instrument (the Modified Mini Mental Status Exam, 3MS) and speech indices for MCI classification. Testing against constant-only logistic regression models showed that both the 3MS [χ2(1) = 6.18, p = .013; AIC = 41.46] and speech indices [χ2(16) = 32.42, p = .009; AIC = 108.41] were able to predict MCI status. Follow-up testing revealed the full speech model better predicted MCI status than did 3MS (p = .049). In combination, the current findings suggest that spontaneous speech may have value as a potential screening measure for the identification of cognitive deficits, though confirmation is needed in larger, prospective studies.

Visualizing and Quantifying Longitudinal Changes in Verbal Fluency Using Recurrence Plots

The verbal fluency task, where participants name as many instances of a specific semantic or phonemic category as possible in a certain time limit, is widely used to probe language and memory retrieval functions in research and clinical settings. More recently, interests in using longitudinal observations in verbal fluency to examine changes over the lifespan have grown, in part due to the increasing availability of such datasets, yet quantitative methods for comparing repeated measures of verbal fluency responses remain scarce. As a result, existing studies tend to focus only on the number of unique words produced and how this metric changes over time, overlooking changes in other important features in the data, such as the identity of the words and the order in which they are produced. Here, we provide an example of how the literature of recurrence analysis, which aims to visualize and analyze non-linear time series, may present useful visualization and analytical approaches for this problem. Drawing on this literature, we introduce a novel metric (the "distance from diagonal," or DfD) to quantify semantic fluency data that incorporates analysis of the sequence order and changes between two lists. As a demonstration, we apply these methods to a longitudinal dataset of semantic fluency in people with Alzheimer's disease and age-matched controls. We show that DfD differs significantly between healthy controls and Alzheimer's disease patients, and that it complements common existing metrics in diagnostic prediction. Our visualization method also allows incorporation of other less common metrics-including the order that words are recalled, repetitions of words within a list, and out-of-category intrusions. Additionally, we show that these plots can be used to visualize and compare aggregate recall data at the group level. These methods can improve understanding of verbal fluency deficits observed in various neuropsychiatric and neurological disorders.

Patients with amnestic MCI Fail to Adapt Executive Control When Repeatedly Tested with Semantic Verbal Fluency Tasks

OBJECTIVE

Semantic verbal fluency (SVF) tasks require individuals to name items from a specified category within a fixed time. An impaired SVF performance is well documented in patients with amnestic Mild Cognitive Impairment (aMCI). The two leading theoretical views suggest either loss of semantic knowledge or impaired executive control to be responsible.

METHOD

We assessed SVF 3 times on 2 consecutive days in 29 healthy controls (HC) and 29 patients with aMCI with the aim to answer the question which of the two views holds true.

RESULTS

When doing the task for the first time, patients with aMCI produced fewer and more common words with a shorter mean response latency. When tested repeatedly, only healthy volunteers increased performance. Likewise, only the performance of HC indicated two distinct retrieval processes: a prompt retrieval of readily available items at the beginning of the task and an active search through semantic space towards the end. With repeated assessment, the pool of readily available items became larger in HC, but not patients with aMCI.

CONCLUSION

The production of fewer and more common words in aMCI points to a smaller search set and supports the loss of semantic knowledge view. The failure to improve performance as well as the lack of distinct retrieval processes point to an additional impairment in executive control. Our data did not clearly favour one theoretical view over the other, but rather indicates that the impairment of patients with aMCI in SVF is due to a combination of both.

Comprehensive verbal fluency features predict executive function performance

Semantic verbal fluency (sVF) tasks are commonly used in clinical diagnostic batteries as well as in a research context. When performing sVF tasks to assess executive functions (EFs) the sum of correctly produced words is the main measure. Although previous research indicates potentially better insights into EF performance by the use of finer grained sVF information, this has not yet been objectively evaluated. To investigate the potential of employing a finer grained sVF feature set to predict EF performance, healthy monolingual German speaking participants (n = 230) were tested with a comprehensive EF test battery and sVF tasks, from which features including sum scores, error types, speech breaks and semantic relatedness were extracted. A machine learning method was applied to predict EF scores from sVF features in previously unseen subjects. To investigate the predictive power of the advanced sVF feature set, we compared it to the commonly used sum score analysis. Results revealed that 8 / 14 EF tests were predicted significantly using the comprehensive sVF feature set, which outperformed sum scores particularly in predicting cognitive flexibility and inhibitory processes. These findings highlight the predictive potential of a comprehensive evaluation of sVF tasks which might be used as diagnostic screening of EFs.

Longitudinal Patterns of the Tip-of-the-Tongue Phenomenon in People With Subjective Cognitive Complaints and Mild Cognitive Impairment

Background

The Tip-of-the-Tongue (ToTs) state is considered a universal phenomenon and is a frequent cognitive complaint in old age. Previous cross-sectional studies have found that ToT measures successfully discriminate between cognitively unimpaired adults and adults with Mild Cognitive Impairment (MCI). The aim of this study was to identify longitudinal patterns of ToTs in individuals with subjective complaints and with MCI regarding progress of their cognitive status.

Method

The study included 193 participants with subjective cognitive complaints (SCC) and 56 participants with MCI who completed a baseline and two follow-up assessments, with an interval of about 18 months between each assessment. Participants were classified into three groups by considering cognitive stability or deterioration from the baseline diagnosis: SCC-stable, MCI-stable and MCI-worsened. Participants performed a ToT task involving recognition and naming of famous people depicted in 50 photographs. Generalized Linear Mixed Models (GLMM) were used to model longitudinal changes in familiarity, feeling of knowing, semantic access, phonological access and verbal fluency.

Results

Phonological access differentiated MCI patients, stable and worsened, from adults with SCCs at all evaluation times. Phonological access declined over time in the three groups, without significant interactions between groups and time.

Discussion

This study provides the first longitudinal evidence of differences in ToT measures for adults with MCI. The findings indicate that phonological access measures successfully differentiated between the diagnostic groups. However, slopes remain irrespective of the diagnostic group and progression toward more advance stages of cognitive impairment.

Word retrieval across the biomarker-confirmed Alzheimer's disease syndromic spectrum

Alzheimer's disease (AD) is now conceptualized as a biological entity defined by amyloid and tau deposition and neurodegeneration, with heterogeneous clinical presentations. With the aid of in vivo biomarkers, clinicians are better poised to examine clinical syndromic variability arising from a common pathology. Word retrieval deficits, measured using verbal fluency and confrontation naming tests, are hallmark features of the early clinical stages of the amnestic presentations of AD, specifically in category fluency and naming with relatively spared letter fluency. As yet, there is no consensus regarding performance on these tests in atypical clinical phenotypes of AD, including posterior cortical atrophy (PCA) and logopenic primary progressive aphasia (lvPPA), in individuals who are amyloid-positive (Aβ+) but present with different clinical profiles and patterns of neurodegeneration compared to amnestic AD. The goal of the current study is to determine how Aβ+ individuals across the syndromic spectrum of AD perform on three different word retrieval tasks. A secondary goal is to determine the neuroanatomical substrates underlying word retrieval performance in these Aβ+ individuals. Thirty-two Aβ+ participants with the amnestic presentation, 16 with Aβ+ PCA, 22 with Aβ+ lvPPA, and 99 amyloid-negative (Aβ-) control participants were evaluated with verbal fluency and visual confrontation naming tests as well as high-resolution MRI. The Aβ+ patient groups were rated at very mild or mild levels of severity (CDR 0.5 or 1) and had comparable levels of global cognitive impairment (average MMSE = 23.7 ± 3.9). Behaviorally, we found that the word retrieval profile of PCA patients is comparable to that of amnestic patients, characterized by intact letter fluency but impaired category fluency and visual confrontation naming, while lvPPA patients demonstrated impairment across all tests of word retrieval. Across all AD variants, we observed that letter fluency was associated with cortical thickness in prefrontal, central precuneus, lateral parietal and temporal cortex, while category fluency and naming were associated with cortical thickness in left middle frontal gyrus, posterior middle temporal gyrus, and lateral parietal cortex. Visual confrontation naming was uniquely associated with atrophy in inferior temporal and visual association cortex. We conclude that a better understanding of the word retrieval profiles and underlying neurodegeneration across the AD syndromic spectrum will help improve interpretation of neuropsychological profiles with regard to the localization of neurodegeneration, particularly in the atypical AD variants.

Altered verbal fluency processes in older adults with age-related hearing loss

Epidemiological studies have linked age-related hearing loss (ARHL) with an increased risk of neurocognitive decline. Difficulties in speech perception with subsequent changes in brain morphometry, including regions important for lexical-semantic memory, are thought to be a possible mechanism for this relationship. This study investigated differences in automatic and executive lexical-semantic processes on verbal fluency tasks in individuals with acquired hearing loss. The primary outcomes were indices of automatic (clustering/word retrieval at start of task) and executive (switching/word retrieval after start of the task) processes from semantic and phonemic fluency tasks. To extract indices of clustering and switching, we used both manual and computerised methods. There were no differences between groups on indices of executive fluency processes or on any indices from the semantic fluency task. The hearing loss group demonstrated weaker automatic processes on the phonemic fluency task. Further research into differences in lexical-semantic processes with ARHL is warranted.

Automatic Scoring of Semantic Fluency

In neuropsychological assessment, semantic fluency is a widely accepted measure of executive function and access to semantic memory. While fluency scores are typically reported as the number of unique words produced, several alternative manual scoring methods have been proposed that provide additional insights into performance, such as clusters of semantically related items. Many automatic scoring methods yield metrics that are difficult to relate to the theories behind manual scoring methods, and most require manually-curated linguistic ontologies or large corpus infrastructure. In this paper, we propose a novel automatic scoring method based on Wikipedia, Backlink-VSM, which is easily adaptable to any of the 61 languages with more than 100k Wikipedia entries, can account for cultural differences in semantic relatedness, and covers a wide range of item categories. Our Backlink-VSM method combines relational knowledge as represented by links between Wikipedia entries (Backlink model) with a semantic proximity metric derived from distributional representations (vector space model; VSM). Backlink-VSM yields measures that approximate manual clustering and switching analyses, providing a straightforward link to the substantial literature that uses these metrics. We illustrate our approach with examples from two languages (English and Korean), and two commonly used categories of items (animals and fruits). For both Korean and English, we show that the measures generated by our automatic scoring procedure correlate well with manual annotations. We also successfully replicate findings that older adults produce significantly fewer switches compared to younger adults. Furthermore, our automatic scoring procedure outperforms the manual scoring method and a WordNet-based model in separating younger and older participants measured by binary classification accuracy for both English and Korean datasets. Our method also generalizes to a different category (fruit), demonstrating its adaptability.

Fully Automatic Speech-Based Analysis of the Semantic Verbal Fluency Task

BACKGROUND

Semantic verbal fluency (SVF) tests are routinely used in screening for mild cognitive impairment (MCI). In this task, participants name as many items as possible of a semantic category under a time constraint. Clinicians measure task performance manually by summing the number of correct words and errors. More fine-grained variables add valuable information to clinical assessment, but are time-consuming. Therefore, the aim of this study is to investigate whether automatic analysis of the SVF could provide these as accurate as manual and thus, support qualitative screening of neurocognitive impairment.

METHODS

SVF data were collected from 95 older people with MCI (n = 47), Alzheimer's or related dementias (ADRD; n = 24), and healthy controls (HC; n = 24). All data were annotated manually and automatically with clusters and switches. The obtained metrics were validated using a classifier to distinguish HC, MCI, and ADRD.

RESULTS

Automatically extracted clusters and switches were highly correlated (r = 0.9) with manually established values, and performed as well on the classification task separating HC from persons with ADRD (area under curve [AUC] = 0.939) and MCI (AUC = 0.758).

CONCLUSION

The results show that it is possible to automate fine-grained analyses of SVF data for the assessment of cognitive decline.

Automated Indices of Clustering and Switching of Semantic Verbal Fluency in Parkinson's Disease

OBJECTIVES

Deficits in semantic verbal fluency (SVF) can stem from dysfunction of an executive control system and/or of semantic knowledge. Previous analyses of SVF responses were devised to characterize these two components including switching and mean cluster size (MCS) indices, but these rely on subjective experimenter-based assessment of the words' relatedness. To address this limitation, computational data-driven SVF indices have been developed. Our aim is to assess the validity and usefulness of these automated indices in the context of cognitive decline in Parkinson's disease (PD).

METHODS

This is a retrospective study including 50 advanced PD patients with (n=28) or without (n=22) mild cognitive impairment (PD-MCI). We analyzed animal SVF outputs using an automated computational approach yielding switching, MCS, and cumulative relatedness (CuRel) indices. We compared these indices to the classic experimenter-based switching and MCS indices to assess concurrent validity, and against neuropsychological measures of executive functioning and semantic knowledge to assess construct validity. We also examined whether these indices were impaired and predicted PD-MCI.

RESULTS

Automated switching indices, but not MCS or CuRel, showed evidence of concurrent and construct validity, and characterized individual difference in advanced PD. Automated switching indices also outperformed the experimenter-dependent index in predicting the presence of PD-MCI.

CONCLUSION

Computational methods hold promise as fine-grained, unbiased indices reflecting the executive component of SVF, but none of the methods provided valid measures of semantic knowledge in PD. Our data also confirm that SVF are not adequate tests of semantic memory in patients with executive dysfunction such as PD. (JINS, 2018, 24, 1047-1056).

Thought probes during prospective memory encoding: Evidence for perfunctory processes

For nearly 50 years, psychologists have studied prospective memory, or the ability to execute delayed intentions. Yet, there remains a gap in understanding as to whether initial encoding of the intention must be elaborative and strategic, or whether some components of successful encoding can occur in a perfunctory, transient manner. In eight studies (N = 680), we instructed participants to remember to press the Q key if they saw words representing fruits (cue) during an ongoing lexical decision task. They then typed what they were thinking and responded whether they encoded fruits as a general category, as specific exemplars, or hardly thought about it at all. Consistent with the perfunctory view, participants often reported mind wandering (42.9%) and hardly thinking about the prospective memory task (22.5%). Even though participants were given a general category cue, many participants generated specific category exemplars (34.5%). Bayesian analyses of encoding durations indicated that specific exemplars came to mind in a perfunctory manner rather than via strategic, elaborative mechanisms. Few participants correctly guessed the research hypotheses and changing from fruit category cues to initial-letter cues eliminated reports of specific exemplar generation, thereby arguing against demand characteristics in the thought probe procedure. In a final experiment, encoding duration was unrelated to prospective memory performance; however, specific-exemplar encoders outperformed general-category encoders with no ongoing task monitoring costs. Our findings reveal substantial variability in intention encoding, and demonstrate that some components of prospective memory encoding can be done "in passing."

Computerized Analysis of Verbal Fluency: Normative Data and the Effects of Repeated Testing, Simulated Malingering, and Traumatic Brain Injury

In verbal fluency (VF) tests, subjects articulate words in a specified category during a short test period (typically 60 s). Verbal fluency tests are widely used to study language development and to evaluate memory retrieval in neuropsychiatric disorders. Performance is usually measured as the total number of correct words retrieved. Here, we describe the properties of a computerized VF (C-VF) test that tallies correct words and repetitions while providing additional lexical measures of word frequency, syllable count, and typicality. In addition, the C-VF permits (1) the analysis of the rate of responding over time, and (2) the analysis of the semantic relationships between words using a new method, Explicit Semantic Analysis (ESA), as well as the established semantic clustering and switching measures developed by Troyer et al. (1997). In Experiment 1, we gathered normative data from 180 subjects ranging in age from 18 to 82 years in semantic ("animals") and phonemic (letter "F") conditions. The number of words retrieved in 90 s correlated with education and daily hours of computer-use. The rate of word production declined sharply over time during both tests. In semantic conditions, correct-word scores correlated strongly with the number of ESA and Troyer-defined semantic switches as well as with an ESA-defined semantic organization index (SOI). In phonemic conditions, ESA revealed significant semantic influences in the sequence of words retrieved. In Experiment 2, we examined the test-retest reliability of different measures across three weekly tests in 40 young subjects. Different categories were used for each semantic ("animals", "parts of the body", and "foods") and phonemic (letters "F", "A", and "S") condition. After regressing out the influences of education and computer-use, we found that correct-word z-scores in the first session did not differ from those of the subjects in Experiment 1. Word production was uniformly greater in semantic than phonemic conditions. Intraclass correlation coefficients (ICCs) of correct-word z-scores were higher for phonemic (0.91) than semantic (0.77) tests. In semantic conditions, good reliability was also seen for the SOI (ICC = 0.68) and ESA-defined switches in semantic categories (ICC = 0.62). In Experiment 3, we examined the performance of subjects from Experiment 2 when instructed to malinger: 38% showed abnormal (p< 0.05) performance in semantic conditions. Simulated malingerers with abnormal scores could be distinguished with 80% sensitivity and 89% specificity from subjects with abnormal scores in Experiment 1 using lexical, temporal, and semantic measures. In Experiment 4, we tested patients with mild and severe traumatic brain injury (mTBI and sTBI). Patients with mTBI performed within the normal range, while patients with sTBI showed significant impairments in correct-word z-scores and category shifts. The lexical, temporal, and semantic measures of the C-VF provide an automated and comprehensive description of verbal fluency performance.