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Introduction: We are developing the California Cognitive Assessment Battery (CCAB) to provide neuropsychological assessments to patients who lack test access due to cost, capacity, mobility, and transportation barriers. Methods: The CCAB consists of 15 non-verbal and 17 verbal subtests normed for telemedical assessment. The CCAB runs on calibrated tablet computers over cellular or Wi-Fi connections either in a laboratory or in participants' homes. Spoken instructions and verbal stimuli are delivered through headphones using naturalistic text-to-speech voices. Verbal responses are scored in real time and recorded and transcribed offline using consensus automatic speech recognition which combines the transcripts from seven commercial ASR engines to produce timestamped transcripts more accurate than those of any single ASR engine. The CCAB is designed for supervised self-administration using a webbrowser application, the Examiner. The Examiner permits examiners to record observations, view subtest performance in real time, initiate video chats, and correct potential error conditions (e.g., training and performance failures, etc.,) for multiple participants concurrently. Results: Here we describe (1) CCAB usability with older (ages 50 to 89) participants; (2) CCAB psychometric properties based on normative data from 415 older participants; (3) Comparisons of the results of at-home vs. in-lab CCAB testing; (4) We also present preliminary analyses of the effects of COVID-19 infection on performance. Mean z-scores averaged over CCAB subtests showed impaired performance of COVID+ compared to COVID-participants after factoring out the contributions of Age, Education, and Gender (AEG). However, inter-cohort differences were no longer significant when performance was analyzed with a comprehensive model that factored out the influences of additional pre-existing demographic factors that distinguished COVID+ and COVID-cohorts (e.g., vocabulary, depression, race, etc.,). In contrast, unlike AEG scores, comprehensive scores correlated significantly with the severity of COVID infection. (5) Finally, we found that scoring models influenced the classification of individual participants with Mild Cognitive Impairment (MCI, z-scores < -1.50) where the comprehensive model accounted for more than twice as much variance as the AEG model and reduced racial bias in MCI classification. Discussion: The CCAB holds the promise of providing scalable laboratoryquality neurodiagnostic assessments to underserved urban, exurban, and rural populations. [ABSTRACT FROM AUTHOR]

Objective: Processing Speed (PS), the ability to perceive and react fast to stimuli in the environment, has been shown to be impaired in children with attention deficit hyperactivity disorder (ADHD). However, it is unclear whether PS can be improved following targeted treatments for ADHD. Here we examined potential changes in PS following application of transcranial electric stimulation (tES) combined with cognitive training (CT) in children with ADHD. Specifically, we examined changes in PS in the presence of different conditions of mental fatigue. Methods: We used a randomized double-blind active-controlled crossover study of 19 unmedicated children with ADHD. Participants received either anodal transcranial direct current stimulation (tDCS) over the left dorsolateral prefrontal cortex (dlPFC) or transcranial random noise stimulation (tRNS), while completing CT, and the administration order was counterbalanced. PS was assessed before and after treatment using the MOXO-CPT, which measures PS in the presence of various conditions of mental fatigue and cognitive load. Results: tRNS combined with CT yielded larger improvements in PS compared to tDCS combined with CT, mainly under condition of increased mental fatigue. Further improvements in PS were also seen in a 1-week follow up testing. Conclusion: This study provides initial support for the efficacy of tRNS combined with CT in improving PS in the presence of mental fatigue in pediatric ADHD. [ABSTRACT FROM AUTHOR]

ObjectiveProcessing Speed (PS), the ability to perceive and react fast to stimuli in the environment, has been shown to be impaired in children with attention deficit hyperactivity disorder (ADHD). However, it is unclear whether PS can be improved following targeted treatments for ADHD. Here we examined potential changes in PS following application of transcranial electric stimulation (tES) combined with cognitive training (CT) in children with ADHD. Specifically, we examined changes in PS in the presence of different conditions of mental fatigue.MethodsWe used a randomized double-blind active-controlled crossover study of 19 unmedicated children with ADHD. Participants received either anodal transcranial direct current stimulation (tDCS) over the left dorsolateral prefrontal cortex (dlPFC) or transcranial random noise stimulation (tRNS), while completing CT, and the administration order was counterbalanced. PS was assessed before and after treatment using the MOXO-CPT, which measures PS in the presence of various conditions of mental fatigue and cognitive load.ResultstRNS combined with CT yielded larger improvements in PS compared to tDCS combined with CT, mainly under condition of increased mental fatigue. Further improvements in PS were also seen in a 1-week follow up testing.ConclusionThis study provides initial support for the efficacy of tRNS combined with CT in improving PS in the presence of mental fatigue in pediatric ADHD.

Pathological mental fatigue after mild traumatic brain injury (TBI-MF) is characterized by pronounced mental fatigue after cognitive activity. The neurological origin is unknown, and we aimed in the present study to investigate how prolonged mental activity affects cognitive performance and its neural correlates in individuals with TBI-MF. We recruited individuals with TBI-MF (n = 20) at least 5 months after injury, and age-matched healthy controls (n = 20). We used functional near-infrared spectroscopy (fNIRS) to assess hemodynamic changes in the frontal cortex. The self-assessed mental energy level was measured with a visual analog scale (VAS) before and after the experimental procedure. A battery of six neuropsychological tests including Stroop–Simon, Symbol Search, Digit Span, Parallel Serial Mental Operation (PaSMO), Sustained Attention and Working Memory test, and Digit Symbol Coding (DSC) were used. The sequence was repeated once after an 8 min sustained-attention test. The test procedure lasted 2½ h. The experimental procedure resulted in a decrease in mental energy in the TBI-MF group, compared to controls (interaction, p < 0.001, ηp2 = 0.331). The TBI-MF group performed at a similar level on both DSC tests, whereas the controls improved their performance in the second session (interaction, p < 0.01, ηp2 = 0.268). During the Stroop–Simon test, the fNIRS event-related response showed no time effect. However, the TBI-MF group exhibited lower oxygenated hemoglobin (oxy-Hb) concentrations in the frontal polar area (FPA), ventrolateral motor cortex, and dorsolateral prefrontal cortex (DLPFC) from the beginning of the test session. A Stroop and Group interaction was found in the left ventrolateral prefrontal cortex showing that the TBI-MF group did have the same oxy-Hb concentration for both congruent and incongruent trials, whereas the controls had more oxy-Hb in the incongruent trial compared to the congruent trial (interaction, p < 0.01, ηp2 = 0.227). In sum these results indicate that individuals with TBI-MF have a reduced ability to recruit the frontal cortex, which is correlated with self-reported mental fatigue. This may result both in deterioration of cognitive function and the experience of a mental fatigue after extended mental activity.

Pathological mental fatigue after mild traumatic brain injury (TBI-MF) is characterized by pronounced mental fatigue after cognitive activity. The neurological origin is unknown, and we aimed in the present study to investigate how prolonged mental activity affects cognitive performance and its neural correlates in individuals with TBI-MF. We recruited individuals with TBI-MF (n = 20) at least 5 months after injury, and age-matched healthy controls (n = 20). We used functional near-infrared spectroscopy (fNIRS) to assess hemodynamic changes in the frontal cortex. The self-assessed mental energy level was measured with a visual analog scale (VAS) before and after the experimental procedure. A battery of six neuropsychological tests including Stroop–Simon, Symbol Search, Digit Span, Parallel Serial Mental Operation (PaSMO), Sustained Attention and Working Memory test, and Digit Symbol Coding (DSC) were used. The sequence was repeated once after an 8 min sustained-attention test. The test procedure lasted 2½ h. The experimental procedure resulted in a decrease in mental energy in the TBI-MF group, compared to controls (interaction, p < 0.001, ηp2 = 0.331). The TBI-MF group performed at a similar level on both DSC tests, whereas the controls improved their performance in the second session (interaction, p < 0.01, ηp2 = 0.268). During the Stroop–Simon test, the fNIRS event-related response showed no time effect. However, the TBI-MF group exhibited lower oxygenated hemoglobin (oxy-Hb) concentrations in the frontal polar area (FPA), ventrolateral motor cortex, and dorsolateral prefrontal cortex (DLPFC) from the beginning of the test session. A Stroop and Group interaction was found in the left ventrolateral prefrontal cortex showing that the TBI-MF group did have the same oxy-Hb concentration for both congruent and incongruent trials, whereas the controls had more oxy-Hb in the incongruent trial compared to the congruent trial (interaction, p < 0.01, ηp2 = 0.227). In sum these results indicate that individuals with TBI-MF have a reduced ability to recruit the frontal cortex, which is correlated with self-reported mental fatigue. This may result both in deterioration of cognitive function and the experience of a mental fatigue after extended mental activity. [ABSTRACT FROM AUTHOR]

This study compared magnetoencephalographic (MEG) imaging-derived indices of auditory and somatosensory cortical processing in children aged 8–12 years with autism spectrum disorder (ASD; N = 18), those with sensory processing dysfunction (SPD; N = 13) who do not meet ASD criteria, and typically developing control (TDC; N = 19) participants. The magnitude of responses to both auditory and tactile stimulation was comparable across all three groups; however, the M200 latency response from the left auditory cortex was significantly delayed in the ASD group relative to both the TDC and SPD groups, whereas the somatosensory response of the ASD group was only delayed relative to TDC participants. The SPD group did not significantly differ from either group in terms of somatosensory latency, suggesting that participants with SPD may have an intermediate phenotype between ASD and TDC with regard to somatosensory processing. For the ASD group, correlation analyses indicated that the left M200 latency delay was significantly associated with performance on the WISC-IV Verbal Comprehension Index as well as the DSTP Acoustic-Linguistic index. Further, these cortical auditory response delays were not associated with somatosensory cortical response delays or cognitive processing speed in the ASD group, suggesting that auditory delays in ASD are domain specific rather than associated with generalized processing delays. The specificity of these auditory delays to the ASD group, in addition to their correlation with verbal abilities, suggests that auditory sensory dysfunction may be implicated in communication symptoms in ASD, motivating further research aimed at understanding the impact of sensory dysfunction on the developing brain.

This study compared magnetoencephalographic (MEG) imaging-derived indices of auditory and somatosensory cortical processing in children aged 8-12 years with autism spectrum disorder (ASD; N = 18), those with sensory processing dysfunction (SPD; N = 13) who do not meet ASD criteria, and typically developing control (TDC; N = 19) participants. The magnitude of responses to both auditory and tactile stimulation was comparable across all three groups; however, the M200 latency response from the left auditory cortex was significantly delayed in the ASD group relative to both the TDC and SPD groups, whereas the somatosensory response of the ASD group was only delayed relative to TDC participants. The SPD group did not significantly differ from either group in terms of somatosensory latency, suggesting that participants with SPD may have an intermediate phenotype between ASD and TDC with regard to somatosensory processing. For the ASD group, correlation analyses indicated that the left M200 latency delay was significantly associated with performance on the WISC-IV Verbal Comprehension Index as well as the DSTP Acoustic-Linguistic index. Further, these cortical auditory response delays were not associated with somatosensory cortical response delays or cognitive processing speed in the ASD group, suggesting that auditory delays in ASD are domain specific rather than associated with generalized processing delays. The specificity of these auditory delays to the ASD group, in addition to their correlation with verbal abilities, suggests that auditory sensory dysfunction may be implicated in communication symptoms in ASD, motivating further research aimed at understanding the impact of sensory dysfunction on the developing brain. [ABSTRACT FROM AUTHOR]

Aging is associated with delayed processing in choice reaction time (CRT) tasks, but the processing stages most impacted by aging have not been clearly identified. Here, we analyzed CRT latencies in a computerized serial visual feature-conjunction task. Participants responded to a target letter (probability 40%) by pressing one mouse button, and responded to distractor letters differing either in color, shape, or both features from the target (probabilities 20% each), by pressing the other mouse button. Stimuli were presented randomly to the left and right visual fields and stimulus onset asynchronies (SOAs) were adaptively reduced following correct responses using a staircase procedure. In Experiment 1, we tested 1466 participants who ranged in age from 18 to 65 years. CRT latencies increased significantly with age (r = 0.47, 2.80 ms/year). Central processing time (CPT), isolated by subtracting simple reaction times (obtained in a companion experiment performed on the same day) from CRT latencies, accounted for more than 80% of age-related CRT slowing, with most of the remaining increase in latency due to slowed motor responses. Participants were faster and more accurate when the stimulus location was spatially compatible with the mouse button used for responding, and this effect increased slightly with age. Participants took longer to respond to distractors with target color or shape than to distractors with no target features. However, the additional time needed to discriminate the more target-like distractors did not increase with age. In Experiment 2, we replicated the findings of Experiment 1 in a second population of 178 participants (ages 18-82 years). CRT latencies did not differ significantly in the two experiments, and similar effects of age, distractor similarity, and stimulus-response spatial compatibility were found. The results suggest that the age-related slowing in visual CRT latencies is largely due to delays in response selection and production.

Some studies highlight similarities between Autism Spectrum Disorder (ASD) and healthy aging. Indeed, the decline in older individuals’ ability to create a unified representation of the individual features of an event is thought to arise from a disruption of integration within the episodic buffer of working memory as the same way as observed in ASD. In both cases, this deficit may result from an abnormal engagement of a frontohippocampal network. The objective of the present study is to identify both cognitive processes and neural substrates associated to the deficit of integration in healthy aging. We studied the capacity of integration and the cognitive processes that might mediate its decline in 72 healthy participants aged 18-84 years. We confronted the behavioral data to the changes in brain metabolism associated with the age-related decline in a subgroup of 34 healthy participants aged 20-77 years using the resting-state [18F] fluorodeoxyglucose positron emission tomography (18F-FDG PET). Forward stepwise regression analyses showed that the age-related decline in binding was partially explained by a decline in inhibition and processing speed. PET correlation analyses indicated that metabolism of the medial frontal regions, anterior and middle cingulate cortices is implicated in this phenomenon. These data suggest that executive functions and processing speed may play a crucial rule in the capacity to integrate unified representations in memory in aging. Possible implications are discussed in ASD.

Simple reaction time (SRT), the minimal time needed to respond to a stimulus, is a basic measure of processing speed. SRTs were first measured by Francis Galton in the 19th century who reported visual SRT latencies below 190 ms in young subjects. However, recent large-scale studies have reported substantially increased SRT latencies that differ markedly in different laboratories, in part due to timing delays introduced by computer hardware and software used for SRT measurement. We developed a calibrated and temporally-precise SRT paradigm to analyze the factors that influence SRT latencies in a paradigm where visual stimuli were presented to the left or right hemifield at varying stimulus onset asynchronies (SOAs). Experiment 1 examined a community sample of 1469 subjects ranging in age from 18 to 65. Mean SRT latencies were short (231 ms, 213 ms when corrected for hardware delays) and increased significantly with age (0.55 ms/year), but were unaffected by sex or education. As in previous studies, SRTs were prolonged at shorter SOAs and were slightly faster for stimuli presented in the visual field contralateral to the responding hand. Stimulus detection time (SDT) was estimated by subtracting movement-initiation time, measured in a speeded finger-tapping test, from SRTs. SDT latencies averaged 131 ms and were unaffected by age. Experiment 2 tested 189 subjects ranging in age from 18 to 82 years in a different laboratory using a larger range of SOAs. Both SRTs and SDTs were slightly prolonged (by 7 ms). SRT latencies increased with age while SDT latencies did not. Precise computer-based measurements of SRT latencies show that processing speed is as fast in contemporary populations as in those from the Victorian era and that age-related increases in SRT latencies are due primarily to slowed motor output.

Sleep spindles are waxing and waning thalamocortical oscillations with accepted frequencies of between 11 and 16 Hz and a minimum duration of 0.5 seconds. Our research has suggested that there is spindle activity in all of the sleep stages, and thus for the present analysis we examined the link between spindle activity (Stage 2, REM and SWS) and waking cognitive abilities in 32 healthy adolescents. After software was used to filter frequencies outside the desired range, slow spindles (11.00-13.50 Hz), fast spindles (13.51-16.00 Hz) and spindle-like activity (16.01-18.50 Hz) were observed in Stage 2, SWS and REM sleep. Our analysis suggests that these specific EEG frequencies were significantly related to processing speed, which is one of the subscales of the intelligence score, in adolescents. The relationship was prominent in SWS and REM sleep. Further, the spindle-like activity (16.01-18.50 Hz) that occurred during SWS was strongly related to processing speed. Results suggest that the ability of adolescents to respond to tasks in an accurate, efficient and timely manner is related to their sleep quality. These findings support earlier research reporting relationships between learning, learning potential and sleep spindle activity in adults and adolescents.

Several fMRI studies have examined brain regions mediating inter-subject variability in cognitive efficiency, but none have examined regions mediating intra-subject variability in efficiency. Thus, the present study was designed to identify brain regions involved in intra-subject variability in cognitive efficiency via participant-level correlations between trial-level reaction time (RT) and trial-level fMRI BOLD percent signal change on a processing speed task. On each trial, participants indicated whether a digit-symbol probe-pair was present or absent in an array of nine digit-symbol probe-pairs while fMRI data were collected. Deconvolution analyses, using RT time-series models (derived from the proportional scaling of an event-related hemodynamic response function model by trial-level RT), were used to evaluate relationships between trial-level RTs and BOLD percent signal change. Although task-related patterns of activation and deactivation were observed in regions including bilateral occipital, bilateral parietal, portions of the medial wall such as the precuneus, default mode network regions including anterior cingulate, posterior cingulate, bilateral temporal, right cerebellum, and right cuneus, RT-BOLD correlations were observed in a more circumscribed set of regions. Positive RT-related patterns, or RT-BOLD correlations where fast RTs were associated with lower BOLD percent signal change, were observed in regions including bilateral occipital, bilateral parietal, and the precuneus. RT-BOLD correlations were not observed in the default mode network indicating a smaller set of regions associated with intra-subject variability in cognitive efficiency. The results are discussed in terms of a distributed area of regions that mediate variability in the cognitive efficiency that might underlie processing speed differences between individuals.

When facing age-related cerebral decline, older adults are unequally affected by cognitive impairment without us knowing why. To explore underlying mechanisms and find possible solutions to maintain life-space mobility, there is a need for a standardized behavioral test that relates to behaviors in natural environments. The aim of the project described in this paper was therefore to provide a free, reliable, transparent, computer-based instrument capable of detecting age-related changes on visual processing and cortical functions for the purposes of research into human behavior in computational transportation science. After obtaining content validity, exploring psychometric properties of the developed tasks, we derived (Study1) the scoring method for measuring cerebral decline on 106 older drivers aged ≥70 years attending a driving refresher course organized by the Swiss Automobile Association to test the instrument’s validity against on-road driving performance (106 older drivers). We then validated the derived method on a new sample of 182 drivers (Study2). We then measured the instrument’s reliability having 17 healthy, young volunteers repeat all tests included in the instrument five times (Study3) and explored the instrument’s psychophysical underlying functions on 47 older drivers (Study4). Finally, we tested the instrument’s responsiveness to alcohol and effects on performance on a driving simulator in a randomized, double-blinded, placebo, crossover, dose-response, validation trial including 20 healthy, young volunteers (Study5). The developed instrument revealed good psychometric properties related to processing speed. It was reliable (ICC=0.853) and showed reasonable association to driving performance (R2=0.053), and responded to blood alcohol concentrations of 0.5 g/L (p=0.008). Our results suggest that MedDrive is capable of detecting age-related changes that affect processing speed. These changes nevertheless do not necessarily affect driving behavior.

Within a few sentences, listeners learn to understand severely degraded speech such as noise-vocoded speech. However, individuals vary in the amount of such perceptual learning and it is unclear what underlies these differences. The present study investigates whether perceptual learning in speech relates to statistical learning, as sensitivity to probabilistic information may aid identification of relevant cues in novel speech input. If statistical learning and perceptual learning (partly) draw on the same general mechanisms, then statistical learning in a non-auditory modality using non-linguistic sequences should predict adaptation to degraded speech.In the present study, 73 older adults (aged over 60 years) and 60 younger adults (aged between 18 and 30 years) performed a visual artificial grammar learning task and were presented with sixty meaningful noise-vocoded sentences in an auditory recall task. Within age groups, sentence recognition performance over exposure was analyzed as a function of statistical learning performance, and other variables that may predict learning (i.e., hearing, vocabulary, attention switching control, working memory and processing speed). Younger and older adults showed similar amounts of perceptual learning, but only younger adults showed significant statistical learning. In older adults, improvement in understanding noise-vocoded speech was constrained by age. In younger adults, amount of adaptation was associated with lexical knowledge and with statistical learning ability. Thus, individual differences in general cognitive abilities explain listeners' variability in adapting to noise-vocoded speech. Results suggest that perceptual and statistical learning share mechanisms of implicit regularity detection, but that the ability to detect statistical regularities is impaired in older adults if visual sequences are presented quickly.

Background. Proton Magnetic Resonance Spectroscopy (1H-MRS) is a non-invasive imaging technique that enables quantification of neurochemistry in vivo and thereby facilitates investigation of the biochemical underpinnings of human cognitive variability. Studies in the field of cognitive spectroscopy have commonly focused on relationships between measures of N-acetyl aspartate (NAA), a surrogate marker of neuronal health and function, and broad measures of cognitive performance, such as IQ.Methodology/Principal Findings. In this study, we used 1H-MRS to interrogate single-voxels in occipitoparietal and frontal cortex, in parallel with assessments of psychometric intelligence, in a sample of 40 healthy adult participants. We found correlations between NAA and IQ that were within the range reported in previous studies. However, the magnitude of these effects was significantly modulated by the stringency of data screening and the extent to which outlying values contributed to statistical analyses.Conclusions/Significance. 1H-MRS offers a sensitive tool for assessing neurochemistry non-invasively, yet the relationships between brain metabolites and broad aspects of human behaviour such as IQ are subtle. We highlight the need to develop an increasingly rigorous analytical and interpretive framework for collecting and reporting data obtained from cognitive spectroscopy studies of this kind.

Simple reaction time (SRT), the minimal time needed to respond to a stimulus, is a basic measure of processing speed. SRTs were first measured by Francis Galton in the 19th century, who reported visual SRT latencies below 190 ms in young subjects. However, recent large-scale studies have reported substantially increased SRT latencies that differ markedly in different laboratories, in part due to timing delays introduced by the computer hardware and software used for SRT measurement. We developed a calibrated and temporally precise SRT test to analyze the factors that influence SRT latencies in a paradigm where visual stimuli were presented to the left or right hemifield at varying stimulus onset asynchronies (SOAs). Experiment 1 examined a community sample of 1469 subjects ranging in age from 18 to 65. Mean SRT latencies were short (231, 213 ms when corrected for hardware delays) and increased significantly with age (0.55 ms/year), but were unaffected by sex or education. As in previous studies, SRTs were prolonged at shorter SOAs and were slightly faster for stimuli presented in the visual field contralateral to the responding hand. Stimulus detection time (SDT) was estimated by subtracting movement initiation time, measured in a speeded finger tapping test, from SRTs. SDT latencies averaged 131 ms and were unaffected by age. Experiment 2 tested 189 subjects ranging in age from 18 to 82 years in a different laboratory using a larger range of SOAs. Both SRTs and SDTs were slightly prolonged (by 7 ms). SRT latencies increased with age while SDT latencies remained stable. Precise computer-based measurements of SRT latencies show that processing speed is as fast in contemporary populations as in the Victorian era, and that age-related increases in SRT latencies are due primarily to slowed motor output. [ABSTRACT FROM AUTHOR]

Sleep spindles are waxing and waning thalamocortical oscillations with accepted frequencies of between 11 and 16 Hz and a minimum duration of 0.5 s. Our research has suggested that there is spindle activity in all of the sleep stages, and thus for the present analysis we examined the link between spindle activity (Stage 2, rapid eye movement (REM) and slow wave sleep (SWS)) and waking cognitive abilities in 32 healthy adolescents. After software was used to filter frequencies outside the desired range, slow spindles (11.00-13.50 Hz), fast spindles (13.51-16.00 Hz) and spindle-like activity (16.01-18.50 Hz) were observed in Stage 2, SWS and REM sleep. Our analysis suggests that these specific EEG frequencies were significantly related to processing speed, which is one of the subscales of the intelligence score, in adolescents. The relationship was prominent in SWS and REM sleep. Further, the spindle-like activity (16.01-18.50 Hz) that occurred during SWS was strongly related to processing speed. Results suggest that the ability of adolescents to respond to tasks in an accurate, efficient and timely manner is related to their sleep quality. These findings support earlier research reporting relationships between learning, learning potential and sleep spindle activity in adults and adolescents. [ABSTRACT FROM AUTHOR]

Within a few sentences, listeners learn to understand severely degraded speech such as noise-vocoded speech. However, individuals vary in the amount of such perceptual learning and it is unclear what underlies these differences. The present study investigates whether perceptual learning in speech relates to statistical learning, as sensitivity to probabilistic information may aid identification of relevant cues in novel speech input. If statistical learning and perceptual learning (partly) draw on the same general mechanisms, then statistical learning in a non-auditory modality using non-linguistic sequences should predict adaptation to degraded speech. In the present study, 73 older adults (aged over 60 years) and 60 younger adults (aged between 18 and 30 years) performed a visual artificial grammar learning task and were presented with 60 meaningful noise-vocoded sentences in an auditory recall task. Within age groups, sentence recognition performance over exposure was analyzed as a function of statistical learning performance, and other variables that may predict learning (i.e., hearing, vocabulary, attention switching control, working memory, and processing speed). Younger and older adults showed similar amounts of perceptual learning, but only younger adults showed significant statistical learning. In older adults, improvement in understanding noise-vocoded speech was constrained by age. In younger adults, amount of adaptation was associated with lexical knowledge and with statistical learning ability. Thus, individual differences in general cognitive abilities explain listeners' variability in adapting to noise-vocoded speech. Results suggest that perceptual and statistical learning share mechanisms of implicit regularity detection, but that the ability to detect statistical regularities is impaired in older adults if visual sequences are presented quickly. [ABSTRACT FROM AUTHOR]

Background: Proton Magnetic Resonance Spectroscopy (1H-MRS) is a non-invasive imaging technique that enables quantification of neurochemistry in vivo and thereby facilitates investigation of the biochemical underpinnings of human cognitive variability. Studies in the field of cognitive spectroscopy have commonly focused on relationships between measures of N-acetyl aspartate (NAA), a surrogate marker of neuronal health and function, and broad measures of cognitive performance, such as IQ. Methodology/Principal Findings: In this study, we used 1H-MRS to interrogate single-voxels in occipitoparietal and frontal cortex, in parallel with assessments of psychometric intelligence, in a sample of 40 healthy adult participants. We found correlations between NAA and IQ that were within the range reported in previous studies. However, the magnitude of these effects was significantly modulated by the stringency of data screening and the extent to which outlying values contributed to statistical analyses. Conclusions/Significance: 1H-MRS offers a sensitive tool for assessing neurochemistry non-invasively, yet the relationships between brain metabolites and broad aspects of human behavior such as IQ are subtle. We highlight the need to develop an increasingly rigorous analytical and interpretive framework for collecting and reporting data obtained from cognitive spectroscopy studies of this kind. [ABSTRACT FROM AUTHOR]

Age-related declines in processing speed are hypothesized to underlie the widespread changes in cognition experienced by older adults. We used a structural covariance approach to identify putative neural networks that underlie age-related structural changes associated with processing speed for 42 adults ranging in age from 19-79 years. To characterize a mechanism by which age-related gray matter changes lead to slower processing speed, we examined the extent to which cerebral small vessel disease influenced the association between age-related gray matter changes and processing speed. A frontal pattern of gray matter and white matter variation that was related to cerebral small vessel disease, as well as a cerebellar pattern of gray matter and white matter variation were uniquely related to age-related declines in processing speed. These results demonstrate that at least 2 distinct factors affect age-related changes in processing speed, which might be slowed by mitigating cerebral small vessel disease and factors affecting declines in cerebellar morphology.

The article comments on the article "Factors influencing the latency of simple reaction time" by by D. L. Woods, J. M Wyma and E. W. Yund. Topics discussed include disappearance of Simple Reaction Time (SRT) slowing once modern studies are corrected for software and hardware lag, recording of SRTs on magnetic tape with electronic chronoscope and study on SRT slowing by researcher P. Verhaeghen.

Aging is associated with delayed processing in choice reaction time (CRT) tasks, but the processing stages most impacted by aging have not been clearly identified. Here, we analyzed CRT latencies in a computerized serial visual feature-conjunction task. Participants responded to a target letter (probability 40%) by pressing one mouse button, and responded to distractor letters differing either in color, shape, or both features from the target (probabilities 20% each) by pressing the other mouse button. Stimuli were presented randomly to the left and right visual fields and stimulus onset asynchronies (SOAs) were adaptively reduced following correct responses using a staircase procedure. In Experiment 1, we tested 1466 participants who ranged in age from 18 to 65 years. CRT latencies increased significantly with age (r = 0.47, 2.80 ms/year). Central processing time (CPT), isolated by subtracting simple reaction times (SRT) (obtained in a companion experiment performed on the same day) from CRT latencies, accounted for more than 80% of age-related CRT slowing, with most of the remaining increase in latency due to slowed motor responses. Participants were faster and more accurate when the stimulus location was spatially compatible with the mouse button used for responding, and this effect increased slightly with age. Participants took longer to respond to distractors with target color or shape than to distractors with no target features. However, the additional time needed to discriminate the more target-like distractors did not increase with age. In Experiment 2, we replicated the findings of Experiment 1 in a second population of 178 participants (ages 18-82 years). CRT latencies did not differ significantly in the two experiments, and similar effects of age, distractor similarity, and stimulus-response spatial compatibility were found. The results suggest that the age-related slowing in visual CRT latencies is largely due to delays in response selection and production.

Some studies highlight similarities between Autism Spectrum Disorder (ASD) and healthy aging. Indeed, the decline in older individuals' ability to create a unified representation of the individual features of an event is thought to arise from a disruption of binding within the episodic buffer of working memory (WM) as the same way as observed in ASD. In both cases, this deficit may result from an abnormal engagement of a frontohippocampal network. The objective of the present study is to identify both cognitive processes and neural substrates associated with the deficit of binding in WM in healthy aging. We studied the capacity of binding and the cognitive processes that might subtend its decline in 72 healthy participants aged 18-84 years. We examined the behavioral data in relation to the changes in brain metabolism associated with the age-related decline in a subgroup of 34 healthy participants aged 20-77 years using the resting-state [(18)F] fluorodeoxyglucose positron emission tomography ((18)F-FDG PET). Forward stepwise regression analyses showed that the age-related decline in binding was partially explained by a decline in inhibition and processing speed. PET correlation analyses indicated that metabolism of the frontal regions, anterior and middle cingulate cortices is implicated in this phenomenon. These data suggest that executive functions and processing speed may play a crucial role in the capacity to integrate unified representations in memory in aging. Possible implications are discussed in ASD.

Several fMRI studies have examined brain regions mediating inter-subject variability in cognitive efficiency, but none have examined regions mediating intra-subject variability in efficiency. Thus, the present study was designed to identify brain regions involved in intra-subject variability in cognitive efficiency via participant-level correlations between trial-level reaction time (RT) and trial-level fMRI BOLD percent signal change on a processing speed task. On each trial, participants indicated whether a digit-symbol probe-pair was present or absent in an array of nine digit-symbol probe-pairs while fMRI data were collected. Deconvolution analyses, using RT time-series models (derived from the proportional scaling of an event-related hemodynamic response function model by trial-level RT), were used to evaluate relationships between trial-level RTs and BOLD percent signal change. Although task-related patterns of activation and deactivation were observed in regions including bilateral occipital, bilateral parietal, portions of the medial wall such as the precuneus, default mode network regions including anterior cingulate, posterior cingulate, bilateral temporal, right cerebellum, and right cuneus, RT-BOLD correlations were observed in a more circumscribed set of regions. Positive RT-BOLD correlations, where fast RTs were associated with lower BOLD percent signal change, were observed in regions including bilateral occipital, bilateral parietal, and the precuneus. RT-BOLD correlations were not observed in the default mode network indicating a smaller set of regions associated with intra-subject variability in cognitive efficiency. The results are discussed in terms of a distributed area of regions that mediate variability in the cognitive efficiency that might underlie processing speed differences between individuals.

When facing age-related cerebral decline, older adults are unequally affected by cognitive impairment without us knowing why. To explore underlying mechanisms and find possible solutions to maintain life-space mobility, there is a need for a standardized behavioral test that relates to behaviors in natural environments. The aim of the project described in this paper was therefore to provide a free, reliable, transparent, computer-based instrument capable of detecting age-related changes on visual processing and cortical functions for the purposes of research into human behavior in computational transportation science. After obtaining content validity, exploring psychometric properties of the developed tasks, we derived (Study 1) the scoring method for measuring cerebral decline on 106 older drivers aged ≥70 years attending a driving refresher course organized by the Swiss Automobile Association to test the instrument's validity against on-road driving performance (106 older drivers). We then validated the derived method on a new sample of 182 drivers (Study 2). We then measured the instrument's reliability having 17 healthy, young volunteers repeat all tests included in the instrument five times (Study 3) and explored the instrument's psychophysical underlying functions on 47 older drivers (Study 4). Finally, we tested the instrument's responsiveness to alcohol and effects on performance on a driving simulator in a randomized, double-blinded, placebo, crossover, dose-response, validation trial including 20 healthy, young volunteers (Study 5). The developed instrument revealed good psychometric properties related to processing speed. It was reliable (ICC = 0.853) and showed reasonable association to driving performance (R (2) = 0.053), and responded to blood alcohol concentrations of 0.5 g/L (p = 0.008). Our results suggest that MedDrive is capable of detecting age-related changes that affect processing speed. These changes nevertheless do not necessarily affect driving behavior.

Age-related declines in processing speed are hypothesized to underlie the widespread changes in cognition experienced by older adults. We used a structural covariance approach to identify putative neural networks that underlie age-related structural changes associated with processing speed for 42 adults ranging in age from 19 to 79 years. To characterize a potential mechanism by which age-related gray matter changes lead to slower processing speed, we examined the extent to which cerebral small vessel disease influenced the association between age-related gray matter changes and processing speed. A frontal pattern of gray matter and white matter variation that was related to cerebral small vessel disease, as well as a cerebellar pattern of gray matter and white matter variation were uniquely related to age-related declines in processing speed. These results demonstrate that at least two distinct factors affect age-related changes in processing speed, which might be slowed by mitigating cerebral small vessel disease and factors affecting declines in cerebellar morphology.