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

OBJECTIVE: To establish convergent and discriminant validity for a combined measure of print exposure (i.e., Author Recognition Test and Magazine Recognition Test [ART/MRT]) and assess its potential utility for estimating premorbid cognitive functioning. METHOD: Community-dwelling older adults (N = 84; 95% non-Hispanic White) completed the ART/MRT, Test of Premorbid Functioning (ToPF), Dementia Rating Scale - 2nd Edition (DRS-2), Hopkins Verbal Learning Test - Revised (HVLT-R-DR), and select subtests from the Delis-Kaplan Executive Functioning System (D-KEFS) as measures of executive functioning (i.e., D-KEFS-EF) and processing speed (i.e., D-KEFS-PS). Pearson correlations and linear regressions were used to examine the relationships between the ART/MRT, cognition, and demographics. RESULTS: Cognitive scores, with the exception of HVLT-R-DR, were positively correlated with ART/MRT score such that better cognitive performance was associated with greater print exposure (range r = 0.39-0.49). ART/MRT score was positively correlated with years of education and negatively correlated with age. ToPF and DRS-2 differentially and uniquely predicted ART/MRT score beyond the other cognitive and demographic variables and beyond each other. CONCLUSIONS: Findings indicate that measures of print exposure reflect crystallized knowledge but may also capture fluid abilities that may be more vulnerable to age-related decline or neurodegeneration. Assessment of print exposure may offer an alternative to word reading measures that may be inappropriate for translation into other languages and for use with individuals with certain language difficulties.

A Test of the Behavioral Model of Tic Disorders Using a Dynamical Systems Framework.

Tic disorders are a class of neurodevelopmental disorders characterized by involuntary motor and/or vocal tics. It has been hypothesized that tics function to reduce aversive premonitory urges (i.e., negative reinforcement) and that suppression-based behavioral interventions such as habit reversal training (HRT) and exposure and response prevention (ERP) disrupt this process and facilitate urge reduction through habituation. However, previous findings regarding the negative reinforcement hypothesis and the effect of suppression on the urge-tic relationship have been inconsistent. The present study applied a dynamical systems framework and within-subject time-series autoregressive models to examine the temporal dynamics of urges and tics and assess whether their relationship changes over time. Eleven adults with tic disorders provided continuous urge ratings during separate conditions in which they were instructed to tic freely or to suppress tics. During the free-to-tic conditions, there was considerable heterogeneity across participants in whether and how the urge-tic relationship followed a pattern consistent with the automatic negative reinforcement hypothesis. Further, little evidence for within-session habituation was seen; tic suppression did not result in a reduction in premonitory urges for most participants. Analysis of broader urge change metrics did show significant disruption to the urge pattern during suppression, which has implications for the current biobehavioral model of tics.

Associations between the resting EEG aperiodic slope and broad domains of cognitive ability.

Recent studies suggest that the EEG aperiodic exponent (often represented as a slope in log-log space) is sensitive to individual differences in momentary cognitive skills such as selective attention and information processing speed. However, findings are mixed, and most of the studies have focused on just a narrow range of cognitive domains. This study used an archival dataset to help clarify associations between resting aperiodic features and broad domains of cognitive ability, which vary in their demands on momentary processing. Undergraduates (N = 166) of age 18-52 years completed a resting EEG session as well as a standardized, individually administered assessment of cognitive ability that included measures of processing speed, working memory, and higher-order visuospatial and verbal skills. A subsample (n = 110) also completed a computerized reaction time task with three difficulty levels. Data reduction analyses revealed strong correlations between the aperiodic offset and slope across electrodes, and a single component accounted for ~60% of variance in slopes across the scalp, in both eyes-closed and eyes-open conditions. Structural equation models did not support relations between the slope and specific domains tapping momentary processes. However, secondary analyses indicated that the eyes-open slope was related to higher overall performance, as represented by a single general ability factor. A latent reaction time variable was significantly inversely related to both eyes-closed and eyes-open resting exponents, such that faster reaction times were associated with steeper slopes. These findings support and help clarify the relation of the resting EEG exponent to individual differences in cognitive skills.

Associations between age-related differences in occipital alpha power and the broadband parameters of the EEG power spectrum: A cross-sectional cohort study.

In adulthood, neurological structure and function are often affected by aging, with negative implications for daily life as well as laboratory-based tasks. Some of these changes include decreased efficiency modulating cortical activity and lower signal-to-noise ratios in neural processing (as inferred from surface electroencephalography). To better understand mechanisms influencing age-related changes in cortical activity, we explored the effects of aging on narrow-band alpha power (7.5-12.5 Hz) and broadband/aperiodic components that span a wider range (1.5-30.5 Hz) over the occipital region during eyes-open and eyes-closed wakeful rest in 19 healthy young adults (18-35 years) and 21 community-dwelling older adults (59+ years). Older adults exhibited a smaller change in alpha power across conditions compared to younger adults. Older adults also showed flatter aperiodic slopes in both conditions. These changes in narrow-band alpha are consistent with previous work and suggest that older adults may have a reduced ability to modulate state-specific activity. Differences in the aperiodic slope suggest age-related changes in the signal-noise-ratio in cortical oscillations. However, the relationship between narrow-band alpha modulation and the aperiodic slope was unclear, warranting further investigation into how these variables relate to each other in the aging process. In summary, aging is associated with a broadband flattening of the EEG power spectrum and reduced state-specific modulation of narrow-band alpha power, but these changes appear to be (at least partially) independent of each other. The present findings suggest that separate mechanisms may underlie age-related differences in aperiodic power and narrow-band oscillations.

Diversity of electroencephalographic patterns during propofol-induced burst suppression.

Burst suppression is a brain state consisting of high-amplitude electrical activity alternating with periods of quieter suppression that can be brought about by disease or by certain anesthetics. Although burst suppression has been studied for decades, few studies have investigated the diverse manifestations of this state within and between human subjects. As part of a clinical trial examining the antidepressant effects of propofol, we gathered burst suppression electroencephalographic (EEG) data from 114 propofol infusions across 21 human subjects with treatment-resistant depression. This data was examined with the objective of describing and quantifying electrical signal diversity. We observed three types of EEG burst activity: canonical broadband bursts (as frequently described in the literature), spindles (narrow-band oscillations reminiscent of sleep spindles), and a new feature that we call low-frequency bursts (LFBs), which are brief deflections of mainly sub-3-Hz power. These three features were distinct in both the time and frequency domains and their occurrence differed significantly across subjects, with some subjects showing many LFBs or spindles and others showing very few. Spectral-power makeup of each feature was also significantly different across subjects. In a subset of nine participants with high-density EEG recordings, we noted that each feature had a unique spatial pattern of amplitude and polarity when measured across the scalp. Finally, we observed that the Bispectral Index Monitor, a commonly used clinical EEG monitor, does not account for the diversity of EEG features when processing the burst suppression state. Overall, this study describes and quantifies variation in the burst suppression EEG state across subjects and repeated infusions of propofol. These findings have implications for the understanding of brain activity under anesthesia and for individualized dosing of anesthetic drugs.

Recall and recognition subtests of the repeatable battery for the assessment of neuropsychological status and their relationship to biomarkers of Alzheimer's disease.

Recently, two new recognition subtests for the Repeatable Battery for the Assessment of Neuropsychological Status (RBANS) were developed and initially validated in a cohort of older adults who were cognitively intact or classified as amnestic Mild Cognitive Impairment (MCI) or mild Alzheimer's disease (AD). The current paper extends that validation by comparing the recall and recognition subtests of the RBANS, including the existing and recently developed scores, to three commonly used biomarkers in AD in an expanded sample from the initial validation. One hundred fifty-four older adults (65 intact, 46 MCI, 43 AD) were administered the RBANS, which included the recently developed subtests for Story Recognition and Figure Recognition (hits, false positives, total correct), as part of a study on memory and biomarkers. Participants also completed magnetic resonance imaging to obtain hippocampal volumes, positron emission tomography to obtain amyloid plaque deposition, and a blood draw to obtain APOE ε4 status. Whereas correlations between recall scores and biomarkers tended to be moderate (average r = ±0.48), these correlations were comparable across the three recognition total scores (average r = ±0.42), but tended to be lower for recognition hits (average r = ±0.28) and false positives (average r = ±0.38). These results further validate the existing and recently developed recognition scores on the RBANS as providing useful information about brain and genetic pathology in older adults with intact and impaired cognitive functioning.

Intelligence and Visual Mismatch Negativity: Is Pre-Attentive Visual Discrimination Related to General Cognitive Ability?

EEG has been used for decades to identify neurocognitive processes related to intelligence. Evidence is accumulating for associations with neural markers of higher-order cognitive processes (e.g., working memory); however, whether associations are specific to complex processes or also relate to earlier processing stages remains unclear. Addressing these issues has implications for improving our understanding of intelligence and its neural correlates. The MMN is an ERP that is elicited when, within a series of frequent standard stimuli, rare deviant stimuli are presented. As stimuli are typically presented outside the focus of attention, the MMN is suggested to capture automatic pre-attentive discrimination processes. However, the MMN and its relation to intelligence has largely only been studied in the auditory domain, thus preventing conclusions about the involvement of automatic discrimination processes in humans' dominant sensory modality-vision. EEG was recorded from 50 healthy participants during a passive visual oddball task that presented simple sequence violations and deviations within a more complex hidden pattern. Signed area amplitudes and fractional area latencies of the visual MMN were calculated with and without Laplacian transformation. Correlations between visual MMN and intelligence (Raven's Advanced Progressive Matrices) were of negligible to small effect sizes, differed critically between measurement approaches, and Bayes Factors provided anecdotal to substantial evidence for the absence of an association. We discuss differences between the auditory and visual MMN, the implications of different measurement approaches, and offer recommendations for further research in this evolving field.

Exploring the reliability and sensitivity of the EEG power spectrum as a biomarker.

INTRODUCTION: The slope of the electroencephalography (EEG) power spectrum (also referred to as 1/f noise) is an important consideration when calculating narrow-band power. However, psychophysiological data also suggest this slope is a meaningful signal itself, not merely background activity or noise. We present two different methods for quantifying the slope of the power spectrum and assess their reliability and sensitivity. METHODS: We used data from N = 60 participants who had EEG collected during rest, a videogame task, and a second period of rest. At all phases of the experiment, we calculated the "spectral slope" (a regression-based method fit to all datapoints) and the "aperiodic slope" (estimated with the fitting oscillations with 1/f algorithm FOOOF). For both methods we assessed: their reliability, their sensitivity to the transition from rest to task, their sensitivity to changes during the videogame task itself, and the agreement between the two measures. RESULTS: Across resting phases, both spectral and aperiodic slopes showed a high degree of reliability. Both methods also showed a steepening of the power spectrum on-task compared to rest. There was also a high degree of consistency between the two methods in their estimate of the underlying slope, but FOOOF explained more variance in the power spectra across regions and type of activity (rest versus task). CONCLUSION: The slope of the power spectrum is a highly reliable individual difference and sensitive to within-subject changes across two different methods of estimation. Moving forward, we generally recommend the use of the FOOOF algorithm for its ability to account for narrow-band signals, but these data show how regression-based approaches produce similar estimates of the spectral slope, which may be useful in some applications.

It's about time: The role of temporal variability in improving assessment of executive functioning.

Objective: Executive Functioning (EF) is a group of cognitive abilities related to one's capacity to engage in and maintain goal-oriented behaviours and is one of the most important constructs in neuropsychology. Although EF has been repeatedly linked to response variability and is known to be impacted by various moderators (e.g., stress, sleep, etc.), in practice, EF is typically considered a stable trait. This article seeks to extend this conventional view, by highlighting the additional role of within-subject temporal variability in manifestations of EF and the potential of emerging technologies to better incorporate these dynamics into neuropsychological assessment.Method: Narrative review. Key developmental and dynamical systems concepts for operationalizing different forms of temporal patterns are reviewed. The applicability of these concepts to neuropsychology is then illustrated via specific clinical examples. Ecological Momentary Assessment (EMA) is posited as a potentially critical methodology for capturing temporal patterns in EF, particularly in combination with advances in smartphone technology. The budding literature on cognitive assessment using EMA is reviewed, concluding with a discussion of the challenges to overcome and benefits that could be realized by adopting these methods and technology for clinical use.Conclusions: The conceptualization and assessment of EF can be improved through increased attention to within-subject patterns of temporal variability. Recent technological innovations can facilitate advances in neuropsychological assessment, particularly in our ability to understand and measure the factors that promote and impede EF in daily life.

Neural anticipatory mechanisms predict faster reaction times and higher fluid intelligence.

Higher cognitive ability is reliably linked to better performance on chronometric tasks (i.e., faster reaction times, RT), yet the neural basis of these effects remains unclear. Anticipatory processes represent compelling yet understudied potential mechanisms of these effects, which may facilitate performance through reducing the uncertainty surrounding the temporal onset of stimuli (temporal uncertainty) and/or facilitating motor readiness despite uncertainty about impending target locations (target uncertainty). Specifically, the contingent negative variation (CNV) represents a compelling candidate mechanism of anticipatory motor planning, while the alpha oscillation is thought to be sensitive to temporal contingencies in perceptual systems. The current study undertook a secondary analysis of a large data set (n = 91) containing choice RT, cognitive ability, and EEG measurements to help clarify these issues. Single-trial EEG analysis in conjunction with mixed-effects modeling revealed that higher fluid intelligence corresponded to faster RT on average. When considered together, temporal and target uncertainty moderated the RT-ability relationship, with higher ability being associated with greater resilience to both types of uncertainty. Target uncertainty attenuated the amplitude of the CNV for all participants, but higher ability individuals were more resilient to this effect. Similarly, only higher ability individuals showed increased prestimulus alpha power (at left-lateralized sites) during longer, more easily anticipated interstimulus intervals. Collectively, these findings emphasize top-down anticipatory processes as likely contributors to chronometry-ability correlations.

Intelligence and uncertainty: Implications of hierarchical predictive processing for the neuroscience of cognitive ability.

Hierarchical predictive processing (PP) has recently emerged as a candidate theoretical paradigm for neurobehavioral research. To date, PP has found support through its success in offering compelling explanations for a number of perceptual, cognitive, and psychiatric phenomena, as well as from accumulating neurophysiological evidence. However, its implications for understanding intelligence and its neural basis have received relatively little attention. The present review outlines the key tenets and evidence for PP, and assesses its implications for intelligence research. It is argued that PP suggests indeterminacy as a unifying principle from which to investigate the cognitive hierarchy and brain-ability correlations. The resulting framework not only accommodates prominent psychometric models of intelligence, but also incorporates key findings from neuroanatomical and functional activation research, and motivates new predictions via the mechanisms of prediction-error minimization. Because PP also suggests unique neural signatures of experience-dependent activity, it may also help clarify environmental contributions to intellectual development. It is concluded that PP represents a plausible, integrative framework that could enhance progress in the neuroscience of intelligence.

Changes in Dimensionality and Fractal Scaling Suggest Soft-Assembled Dynamics in Human EEG.

Humans are high-dimensional, complex systems consisting of many components that must coordinate in order to perform even the simplest of activities. Many behavioral studies, especially in the movement sciences, have advanced the notion of soft-assembly to describe how systems with many components coordinate to perform specific functions while also exhibiting the potential to re-structure and then perform other functions as task demands change. Consistent with this notion, within cognitive neuroscience it is increasingly accepted that the brain flexibly coordinates the networks needed to cope with changing task demands. However, evaluation of various indices of soft-assembly has so far been absent from neurophysiological research. To begin addressing this gap, we investigated task-related changes in two distinct indices of soft-assembly using the established phenomenon of EEG repetition suppression. In a repetition priming task, we assessed evidence for changes in the correlation dimension and fractal scaling exponents during stimulus-locked event-related potentials, as a function of stimulus onset and familiarity, and relative to spontaneous non-task-related activity. Consistent with predictions derived from soft-assembly, results indicated decreases in dimensionality and increases in fractal scaling exponents from resting to pre-stimulus states and following stimulus onset. However, contrary to predictions, familiarity tended to increase dimensionality estimates. Overall, the findings support the view from soft-assembly that neural dynamics should become increasingly ordered as external task demands increase, and support the broader application of soft-assembly logic in understanding human behavior and electrophysiology.

Working memory performance inversely predicts spontaneous delta and theta-band scaling relations.

Electrophysiological studies have strongly implicated theta-band activity in human working memory processes. Concurrently, work on spontaneous, non-task-related oscillations has revealed the presence of long-range temporal correlations (LRTCs) within sub-bands of the ongoing EEG, and has begun to demonstrate their functional significance. However, few studies have yet assessed the relation of LRTCs (also called scaling relations) to individual differences in cognitive abilities. The present study addressed the intersection of these two literatures by investigating the relation of narrow-band EEG scaling relations to individual differences in working memory ability, with a particular focus on the theta band. Fifty-four healthy adults completed standardized assessments of working memory and separate recordings of their spontaneous, non-task-related EEG. Scaling relations were quantified in each of the five classical EEG frequency bands via the estimation of the Hurst exponent obtained from detrended fluctuation analysis. A multilevel modeling framework was used to characterize the relation of working memory performance to scaling relations as a function of general scalp location in Cartesian space. Overall, results indicated an inverse relationship between both delta and theta scaling relations and working memory ability, which was most prominent at posterior sensors, and was independent of either spatial or individual variability in band-specific power. These findings add to the growing literature demonstrating the relevance of neural LRTCs for understanding brain functioning, and support a construct- and state-dependent view of their functional implications.

Neurocognitive and neurophysiological correlates of motor planning during familiar and novel contexts.

OBJECTIVE: Research suggests that behavioral indices of motor planning (i.e., latencies that precede motor output) (a) relate to processing speed (PS) and executive functioning (EF), but not working memory (WM), and (b) deteriorate in novel contexts. It is not clear whether an electrophysiological index of motor planning (i.e., movement-related cortical potentials; MRCPs) also relates to PS and EF, and whether it deteriorates in novel contexts. This study sought to clarify associations among these variables while manipulating contextual novelty. METHOD: Forty healthy adults completed standardized measures of PS, EF, and WM. Participants performed highly familiar motor sequences in familiar versus novel contexts during EEG recording, while motor planning latencies and peak MRCPs were obtained. Hierarchical regressions assessed the relative contributions of PS, EF, and WM to motor planning latencies and MRCPs. RESULTS: Novel contexts elicited longer planning latencies (gav = 1.96) and reduced MRCPs (gav = .24) compared to familiar contexts. PS predicted planning times in both familiar (R² = .12) and novel contexts (R² = .15), while EF contributed additional variance during novel contexts only (R² Change = .10). EF was the sole predictor of MRCPs in both familiar (R² = .12) and novel contexts (R² = .18). WM did not predict planning latencies or MRCPs. CONCLUSIONS: Contextual novelty alone can decrease performance and neural activation during complex sequencing. The general link between preparatory activation and EF suggests that capacity limitations drive novelty effects, and implies a common substrate underlying motor planning and higher-order behavioral control.

Reliable activation to novel stimuli predicts higher fluid intelligence.

The ability to reliably respond to stimuli could be an important biological determinant of differences in fluid intelligence (Gf). However, most electrophysiological studies of Gf employ event-related potential (ERP) measures that average brain activity over trials, and hence have limited power to quantify neural variability. Time-frequency analyses can capture cross-trial variation in the phase of neural activity, and thus can help address the importance of neural reliability to differences in Gf. This study recruited a community sample of healthy adults and measured inter-trial phase clustering (ITPC), total spectral power, and ERP amplitudes elicited by Repeated and Novel non-target stimuli during two visual oddball tasks. Condition effects, relations among the EEG measures, and relations with Gf were assessed. Early visual responses to Repeated stimuli elicited higher ITPC, yet only ITPC elicited by Novel stimuli was associated with Gf. Analyses of spectral power further highlighted the contribution of phase consistency to the findings. The link between Gf and reliable responding to changing inputs suggests an important role for flexible resource allocation in fluid intellectual skills.

Bilateral hippocampal dysfunction in schizophrenia.

The hippocampus has long been known to be important for memory, with the right hippocampus particularly implicated in nonverbal/visuo-spatial memory and the left in verbal/narrative or episodic memory. Despite this hypothesized lateralized functional difference, there has not been a single task that has been shown to activate both the right and left hippocampi differentially, dissociating the two, using neuroimaging. The transverse patterning (TP) task is a strong candidate for this purpose, as it has been shown in human and nonhuman animal studies to theoretically and empirically depend on the hippocampus. In TP, participants choose between stimuli presented in pairs, with the correct choice being a function of the specific pairing. In this project, TP was used to assess lateralized hippocampal function by varying its dependence on verbal material, with the goal of dissociating the two hippocampi. Magnetoencephalographic (MEG) data were collected while controls performed verbal and nonverbal versions of TP in order to verify and validate lateralized activation within the hippocampi. Schizophrenia patients were evaluated to determine whether they exhibited a lateralized hippocampal deficit. As hypothesized, patients' mean level of behavioral performance was poorer than controls' on both verbal and nonverbal TP. In contrast, patients had no decrement in performance on a verbal and nonverbal non-hippocampal-dependent matched control task. Also, controls but not patients showed more right hippocampal activation during nonverbal TP and more left hippocampal activation during verbal TP. These data demonstrate the capacity to assess lateralized hippocampal function and suggest a bilateral hippocampal behavioral and activation deficit in schizophrenia.