To examine neurocognitive correlates of oculomotor performance among U.S. military personnel with history of mild traumatic brain injury (mTBI).

A series of studies (total n=356) were conducted to examine saccadic eye movements and manual button presses collected in response to attention stimuli, and to compare these findings to the results of standardized neuropsychological tests. Study 1 included n=27 with remote mTBI and n=54 controls who completed the Bethesda Eye and Attention Measure (BEAM), an eye tracking task that was designed to measure visual attention and executive function. In Study 2, n=51 with chronic mTBI and n=33 controls completed the Fusion n-Back task, an eye tracking task that was designed to assess the impact of working memory load on visual attention performance. Study 3 examined psychometric characteristics of BEAM among n=191 military personnel with remote mTBI. In all studies, participants completed eye tracking tasks, a structured TBI diagnostic interview, and a brief battery of standardized neuropsychological tests.

In Study 1, BEAM saccadic and manual metrics demonstrated strong reliability and high sensitivity to multiple cognitive cues designed to elicit spatial orienting, temporal alerting, executive interference, perceptual release (gap) and inhibition (n2p=.76, p<.001). However, corresponding saccadic and manual measurements were weakly related to each other, and only manual (not saccadic) measurements were related to estimated verbal intelligence or years of education. Standardized neuropsychological measures did not differ between groups, but mTBI participants were more likely to be impaired on saccadic metrics than controls.

In Study 2, Standardized cognitive measures and estimated premorbid intelligence were positively associated with all manual metrics from the Fusion n-Back test, but were not associated with mTBI history or with saccadic metrics. Fusion n-Back saccadic and manual metrics had strong reliability and complementary sensitivity to chronic mTBI, with combined predictive power of PPV=.78, NPV=.72, r2=.44 for classification of remote mild TBI vs. controls on the more cognitively-challenging 1-back task condition.

In Study 3, BEAM metrics including manual RT latency and consistency, saccadic RT consistency, and saccadic inhibition errors showed consistent correlations with standardized measures of visual attention, processing speed, task switching, working memory, and executive functions. Hierarchical regressions showed that BEAM saccadic and manual metrics were independently predictive of cognitive test performance, above and beyond effects of demographic factors and clinical characteristics.

Results demonstrated some surprising findings related to neurocognitive influences on oculomotor performance. While both saccadic and manual performance were strongly and similarly influenced by attention cues, these two modalities were only weakly correlated to one another. Additionally, manual metrics were more strongly and consistently related to standardized cognitive test performance and premorbid intelligence than saccadic metrics. However, saccadic metrics demonstrated superior sensitivity to remote/chronic mTBI relative to manual metrics and standardized neuropsychological measures. Overall, these results suggest that saccadic eye tracking measures may provide unique value in assessment of mTBI and neurocognitive functions that is complementary with more common forms of assessment relying upon somatomotor response modalities.

In December 2019, the first reports came from China about cases of pneumonia caused by a previously unknown coronavirus, SARS-CoV-2 (Severe Acute Respiratory Syndrome Coronavirus 2), responsible for a disease called COVID-19. Since then, the pandemic has spread worldwide, affecting people’s physical and mental health and as well as quality of life. Currently, many people are experiencing the health consequences of contracting COVID-19, also due to the impact this disease has on the central nervous system. As a result, in addition to well-known ailments, such as headaches, chronic fatigue or smell and taste disorders, COVID-19 survivors may develop neuropsychological problems such as executive-attentional deficits. However, the specificity of these executive-attentional problems has not been determined. Thus, the purpose of this study was to learn if survivors of COVID-19 may present with more generalized or rather specific dysfunction(s) of the anterior attentional-executive system.

The study group consisted of 37 individuals who underwent COVID-19 (age M=44, education M=17). The comparison group consisted of 25 matched controls tested before the COVID-19 pandemia. The experimental procedures included (1) a clinical interview, (2) an assessment of selected cognitive functions (3) and attentionalexecutive functioning, which was assessed using the ROtman-Baycrest Battery to Investigate Attention (ROBBIA); a battery was designed to measure three attentional processes (i.e., energizing, task setting, and monitoring). Overall, four reaction time (RT) subtests from ROBBIA were administered: (1) Simple RT, (2) Choice RT, (3), Prepare RT, and (4) Concentrate. For each subtest, the instruction was to press an appropriate button on a response pad as quickly as possible when a target stimulus (one of the following capital letters: A, B, C, or D) is detected, but also (in Choice RT, Prepare RT and Concentrate) to make as few errors as possible.

Overall, the analyses revealed that individuals who survived COVID-19 exhibited a different effect of the warning stimulus compared to controls. Specifically, COVID19 survivors presented an increase in reaction time from 1s warning condition to 3s warning condition being significantly greater than the control group’s increase (p < .05). Also, only in the COVID-19 group, reaction time in the Concentrate task tended to be longer (p = 0.01). No group differences in monitoring (e.g., number of errors) or task setting emerged.

The patients’ problems appear analogous to those observed in other chronic somatic diseases, likely due to the impact of COVID-19 on the frontal lobe’s medial regions. However, due to a small sample size, future neuroimaging research, including computerized studies of attentional-execution networks, is needed to confirm that COVID-19 may predominantly affect the energization system that contributes to these patient’s cognitive slowing and defective ability to sustain attention.

Sensitive and non-invasive methods of screening for early-stage Alzheimer’s disease (AD) are urgently needed. The digital clock drawing test (DCTclockTM) is an established and well-researched neuropsychological tool that can aid in early detection of dementia. Other simple, yet sensitive, neuropsychological measures able to detect early stages of AD include Trail Making Tests (TMT). We investigated the psychometric properties of DCTclockTM with TMT-A and TMT-B. We then sought to understand the degree to which neuropsychological tools (i.e., DCTclockTM, TMT-A, and B) versus the Montreal Cognitive Assessment (MoCA) predict beta-amyloid (Aß) positron emission tomography (PET) status (positive or negative) in cognitively normal individuals.

Participants included a sample of cognitively normal older adults (n= 59, M age = 69.2, F = 64%) recruited from the Butler Memory and Aging Program. The Linus Health DCTclockTM uses a digital pen to capture traditional clock drawing test performance and advanced analytics to evaluate the drawing process for indicators of cognitive difficulty. DCTclockTM may have overlapping cognitive properties with TMT measures, like efficiency, processing speed, and spatial reasoning. We compared latency measures (i.e., process efficiency, clock face speed, average latency, and processing speed) and spatial reasoning of the DCTclockTM to z-scores of TMT-A and TMT-B to detect any overlapping psychometric properties. Verbal fluency was included for discriminant validity. We then ran logistic regressions on a subset of the sample to compare neuropsychological tests (DCTclockTM total score [score that captures overall performance], TMT-A/B, and verbal fluency) to the MoCA, a commonly used cognitive screening tool, in determining PET status.

Highly correlated (r > .7) DCTclockTM variables were excluded. We found statistically significant correlations between some DCTclockTM measures and TMT-A/B, like DCTclockTM drawing process efficiency and TMT-A and TMT-B (r= .45, p< .001, r=.29, p< .026, respectively), and DCTclockTM average latency and TMT-A and TMT-B (r=.3, p< .024, r= .26, p< .044, respectively). No statistically significant associations were found between any DCTclockTM measures and verbal fluency, or between DCTclockTM spatial reasoning and TMT-A/B. We then investigated the effect of these neuropsychological tests (DCTclockTM total score, TMT-A/B, verbal fluency) and age on the likelihood of PET positivity (subset of sample, total PET, n=31). The model was statistically significant (x2 (5) = 15.35, p< .01). The model explained 53% (Nagelkerke R2) of the variance in PET status and correctly classified 74.2% of cases. DCTclockTM was the only significant predictor (p< .02), after controlling for TMT-A, TMT-B, verbal fluency, and age. Comparatively, there was no effect of MoCA and age (total PET, n= 29) on the likelihood of PET positivity.

Overall, these results suggest psychometric convergence on elements of DCTclockTM and TMT-A/B, while there was no association in spatial operations between DCTclockTM and TMT measures. Further, when compared to the MoCA, DCTclockTM and these commonly used neuropsychological tests (verbal fluency and TMT-A/B) were better predictors of PET status, primarily driven by the DCTclockTM. Digitized neuropsychological tools may provide additional metrics not captured by pen-and-paper tests that can detect AD-associated pathology.

Prospective memory (PM) is the ability to execute a planned action in the future (e.g., remembering to take medication before going to bed). Prior work has suggested that PM failure can account for 50-80% of reported memory problems. Research has also shown that PM becomes increasingly impaired in the Alzheimer's disease (AD) process. To our knowledge, most PM studies use PM accuracy as a measure of PM performance. However, examining the speed of the response as it relates to the AD process remains relatively unexplored. In this study, we examined both PM accuracy and speed in healthy aging, mild cognitive impairment (MCI), and AD.

Participants included healthy older controls (N=65), persons with MCI (N=70), and persons with AD (N=11). The PM task was embedded within a working memory task as PM demands often occur during an ongoing activity in everyday life. For the working memory component of the PM task, participants were shown a series of words and asked to continuously monitor the words while maintaining the last 3 in memory. All words were displayed within 1 of 6 background patterns. For the PM component, participants were asked to press "1" on the keyboard whenever they were shown a particular background pattern on the screen. PM abilities were measured using the median response time and total accuracy.

Age was correlated with PM accuracy. An ANCOVA, controlling for age, and examining the impact of diagnosis on PM accuracy, was significant. Post-hoc tests revealed a trend toward the AD and MCI groups being less accurate than healthy controls. In contrast to accuracy, age was not related to PM speed. An ANOVA examining the impact of diagnosis on PM accuracy found that the AD group responded faster than healthy controls. The MCI group did not show differences in speed from the healthy control and AD groups.

Overall, the pattern of results differed in accuracy and speed of PM performance. There was a trend for the MCI and AD groups being less accurate than the controls, with no difference in performance between the MCI and AD groups. However, the AD group responded more quickly than the controls, which may have impacted their accuracy. These findings indicate that PM performance differences among groups can be detected by examining speed and not just accuracy. As speed appears to be an essential aspect involved in PM performance, future research should consider incorporating speed as a measure of PM performance when examining PM differences in populations.

Increased intraindividual variability (IIV) of cognitive performance is a marker of cognitive decline in older adults. Whether computerized cognitive training (CCT) and aerobic exercise counteracts cognitive decline by reducing IIV is unknown. We investigated the effects of CCT with or without aerobic exercise on IIV in older adults.

This was a secondary analysis of an 8-week randomized controlled trial. Older adults (aged 65–85 years) were randomized to CCT alone (n = 41), CCT with aerobic exercise (n = 41), or an active control group (n = 42). The CCT group trained using the Fit Brains® platform 3×/week for 1 hr (plus 3×/week of home-based training). The CCT with aerobic exercise group received 15 min of walking plus 45 min of Fit Brains® 3×/week (plus 3×/week of home-based training). The control group received sham exercise and cognitive training (3×/week for 1 hr). We computed reaction time IIV from the Dimensional Change Card Sort Test, Flanker Inhibitory Control and Attention Test (Flanker), and Pattern Comparison Processing Speed Test (PACPS).

Compared with the control group, IIV reduced in a processing speed task (PACPS) following CCT alone (mean difference [95% confidence interval]: −0.144 [−0.255 to −0.034], p < 0.01) and CCT with aerobic exercise (−0.113 [−0.225 to −0.001], p < 0.05). Attention (Flanker congruent) IIV was reduced only after CCT with aerobic exercise (−0.130 [−0.242 to −0.017], p < 0.05).

A CCT program promoted cognitive health via reductions in IIV of cognitive performance and combining it with aerobic exercise may result in broader benefits.

Reaction time variability (RTV) has been estimated using Gaussian, ex-Gaussian, and diffusion model (DM) indices. Rarely have studies examined interrelationships among these performance indices in childhood, and the use of reaction time (RT) computational models has been slow to take hold in the developmental psychopathology literature. Here, we extend prior work in adults by examining the interrelationships among different model parameters in the ABCD sample and demonstrate how computational models of RT can clarify mechanisms of time-on-task effects and sex differences in RTs.

This study utilized trial-level data from the stop signal task from 8916 children (9–10 years old) to examine Gaussian, ex-Gaussian, and DM indicators of RTV. In addition to describing RTV patterns, we examined interrelations among these indicators, temporal patterns, and sex differences.

There was no one-to-one correspondence between DM and ex-Gaussian parameters. Nonetheless, drift rate was most strongly associated with standard deviation of RT and tau, while nondecisional processes were most strongly associated with RT, mu, and sigma. Performance worsened across time with changes driven primarily by decreasing drift rate. Boys were faster and less variable than girls, likely attributable to girls’ wide boundary separation.

Intercorrelations among model parameters are similar in children as has been observed in adults. Computational approaches play a crucial role in understanding performance changes over time and can also clarify mechanisms of group differences. For example, standard RT models may incorrectly suggest slowed processing speed in girls that is actually attributable to other factors.

Performance on executive function (EF) tasks is only modestly predictive of a diagnosis of Attention Deficit Hyperactivity Disorder (ADHD), despite the common assumption that EF deficits are ubiquitous to the disorder. The current study sought to determine whether ex-Gaussian parameters of simple reaction time are better able to discriminate between children and adults with and without ADHD, compared with traditional measures of inhibitory control.

Receiver Operating Characteristic (ROC) analyses and the area under the curve (AUC) were used to examine the ability of performance on two commonly used tasks of inhibitory control (i.e. stop signal reaction time (SSRT) and go-no-go tasks) to predict ADHD status in preschool (N = 108), middle childhood (N = 309), and young adulthood (N = 133).

Across all samples, SSRT, go-no-go percentage of failed inhibits, and standard deviation of reaction (SDRT) time to “go” trials, all successfully discriminated between individuals with and without ADHD. Ex-Gaussian decomposition of the RT distribution indicated that both larger tau and larger sigma drove findings for SDRT. Contrary to predictions, traditional measures of inhibitory control were equal if not better predictors of ADHD status than ex-Gaussian parameters.

Findings support ongoing work to quantify the separate contributions of cognitive subprocesses that drive task performance, which in turn is critical to developing and improving process-based approaches in clinical assessment.

Incidental learning and memory, as well as processing speed, were examined in human immunodeficiency virus (HIV)-positive adults and a seronegative control group.

Participants completed a computerized Symbol-Digit Modalities Test (cSDMT) with two blocked conditions: a set of trials with the standard symbol–digit pairings and the second set with a rearranged symbol–digit pairings.

HIV-positive adults showed slower overall reaction time compared to the HIV-negative group. More importantly, the most cognitively impaired HIV-positive group showed no interference in the rearranged set of symbol–digit pairings from the standard pairings on the cSDMT.

The relative slowing, or interference, in the HIV-negative group and two HIV-positive groups (unimpaired and impaired) was quite large (between 122 and 131 ms). We argue that the lack of such relative slowing in the most cognitively impaired HIV-positive group indicates a deficit in incidental learning and memory.

We investigated whether adults with attention-deficit/hyperactivity disorder (ADHD) show pseudoneglect—preferential allocation of attention to the left visual field (LVF) and a resulting slowing of mean reaction times (MRTs) in the right visual field (RVF), characteristic of neurotypical (NT) individuals —and whether lateralization of attention is modulated by presentation speed and incentives.

Fast Task, a four-choice reaction-time task where stimuli were presented in LVF or RVF, was used to investigate differences in MRT and reaction time variability (RTV) in adults with ADHD (n = 43) and NT adults (n = 46) between a slow/no-incentive and fast/incentive condition. In the lateralization analyses, pseudoneglect was assessed based on MRT, which was calculated separately for the LVF and RVF for each condition and each study participant.

Adults with ADHD had overall slower MRT and increased RTV relative to NT. MRT and RTV improved under the fast/incentive condition. Both groups showed RVF-slowing with no between-group or between-conditions differences in RVF-slowing.

Adults with ADHD exhibited pseudoneglect, a NT pattern of lateralization of attention, which was not attenuated by presentation speed and incentives.