Normative perceptual estimates for 91 healthy subjects age 60-75: impact of age, education, employment, physical exercise, alcohol, and video gaming

Why am I overwhelmed by bright lights? The behavioural mechanisms of post-stroke visual hypersensitivity

After stroke, patients can experience visual hypersensitivity, an increase in their sensitivity for visual stimuli as compared to their state prior to the stroke. Candidate behavioural mechanisms for these subjective symptoms are atypical bottom-up sensory processing and impaired selective attention, but empirical evidence is currently lacking. In the current study, we aimed to investigate the relationship between post-stroke visual hypersensitivity and sensory thresholds, sensory processing speed, and selective attention using computational modelling of behavioural data. During a whole/partial report task, participants (51 stroke patients, 76 orthopedic patients, and 77 neurotypical adults) had to correctly identify a single target letter that was presented alone (for 17-100 ms) or along a distractor (for 83ms). Performance on this task was used to estimate the sensory threshold, sensory processing speed, and selective attention abilities of each participant. In the stroke population, both on a group and individual level, there was evidence for impaired selective attention and -to a lesser extent- lower sensory thresholds in patients with post-stroke visual hypersensitivity as compared to neurotypical adults, orthopedic patients, or stroke patients without post-stroke sensory hypersensitivity. These results provide a significant advancement in our comprehension of post-stroke visual hypersensitivity and can serve as a catalyst for further investigations into the underlying mechanisms of sensory hypersensitivity after other types of acquired brain injury as well as post-injury hypersensitivity for other sensory modalities.

In vivo biomarkers of structural and functional brain development and aging in humans

Brain aging is a major determinant of aging. Along with the aging population, prevalence of neurodegenerative diseases is increasing, therewith placing economic and social burden on individuals and society. Individual rates of brain aging are shaped by genetics, epigenetics, and prenatal environmental. Biomarkers of biological brain aging are needed to predict individual trajectories of aging and the risk for age-associated neurological impairments for developing early preventive and interventional measures. We review current advances of in vivo biomarkers predicting individual brain age. Telomere length and epigenetic clock, two important biomarkers that are closely related to the mechanistic aging process, have only poor deterministic and predictive accuracy regarding individual brain aging due to their high intra- and interindividual variability. Phenotype-related biomarkers of global cognitive function and brain structure provide a much closer correlation to age at the individual level. During fetal and perinatal life, autonomic activity is a unique functional marker of brain development. The cognitive and structural biomarkers also boast high diagnostic specificity for determining individual risks for neurodegenerative diseases.

Ten Years of BrainAGE as a Neuroimaging Biomarker of Brain Aging: What Insights Have We Gained?

With the aging population, prevalence of neurodegenerative diseases is increasing, thus placing a growing burden on individuals and the whole society. However, individual rates of aging are shaped by a great variety of and the interactions between environmental, genetic, and epigenetic factors. Establishing biomarkers of the neuroanatomical aging processes exemplifies a new trend in neuroscience in order to provide risk-assessments and predictions for age-associated neurodegenerative and neuropsychiatric diseases at a single-subject level. The "Brain Age Gap Estimation (BrainAGE)" method constitutes the first and actually most widely applied concept for predicting and evaluating individual brain age based on structural MRI. This review summarizes all studies published within the last 10 years that have established and utilized the BrainAGE method to evaluate the effects of interaction of genes, environment, life burden, diseases, or life time on individual neuroanatomical aging. In future, BrainAGE and other brain age prediction approaches based on structural or functional markers may improve the assessment of individual risks for neurological, neuropsychiatric and neurodegenerative diseases as well as aid in developing personalized neuroprotective treatments and interventions.

Age-Related Changes in the Ability to Switch between Temporal and Spatial Attention

Background: Identifying age-related changes in cognition that contribute towards reduced driving performance is important for the development of interventions to improve older adults' driving and prolong the time that they can continue to drive. While driving, one is often required to switch from attending to events changing in time, to distribute attention spatially. Although there is extensive research into both spatial attention and temporal attention and how these change with age, the literature on switching between these modalities of attention is limited within any age group. Methods: Age groups (21-30, 40-49, 50-59, 60-69 and 70+ years) were compared on their ability to switch between detecting a target in a rapid serial visual presentation (RSVP) stream and detecting a target in a visual search display. To manipulate the cost of switching, the target in the RSVP stream was either the first item in the stream (Target 1st), towards the end of the stream (Target Mid), or absent from the stream (Distractor Only). Visual search response times and accuracy were recorded. Target 1st trials behaved as no-switch trials, as attending to the remaining stream was not necessary. Target Mid and Distractor Only trials behaved as switch trials, as attending to the stream to the end was required. Results: Visual search response times (RTs) were longer on "Target Mid" and "Distractor Only" trials in comparison to "Target 1st" trials, reflecting switch-costs. Larger switch-costs were found in both the 40-49 and 60-69 years group in comparison to the 21-30 years group when switching from the Target Mid condition. Discussion: Findings warrant further exploration as to whether there are age-related changes in the ability to switch between these modalities of attention while driving. If older adults display poor performance when switching between temporal and spatial attention while driving, then the development of an intervention to preserve and improve this ability would be beneficial.

Clinical TVA-based studies: a general review

In combination with whole report and partial report tasks, the theory of visual attention (TVA) can be used to estimate individual differences in five basic attentional parameters: the visual processing speed, the storage capacity of visual short-term memory, the perceptual threshold, the efficiency of top-down selectivity, and the spatial bias of attentional weighting. TVA-based assessment has been used in about 30 studies to investigate attentional deficits in a range of neurological and psychiatric conditions: (a) neglect and simultanagnosia, (b) reading disturbances, (c) aging and neurodegenerative diseases, and most recently (d) neurodevelopmental disorders. The article introduces TVA based assessment, discusses its methodology and psychometric properties, and reviews the progress made in each of the four research fields. The empirical results demonstrate the general usefulness of TVA-based assessment for many types of clinical neuropsychological research. The method's most important qualities are cognitive specificity and theoretical grounding, but it is also characterized by good reliability and sensitivity to minor deficits. The review concludes by pointing to promising new areas for clinical TVA-based research.

Cognitive aging on latent constructs for visual processing capacity: a novel structural equation modeling framework with causal assumptions based on a theory of visual attention

We examined the effects of normal aging on visual cognition in a sample of 112 healthy adults aged 60–75. A testbattery was designed to capture high-level measures of visual working memory and low-level measures of visuospatial attention and memory. To answer questions of how cognitive aging affects specific aspects of visual processing capacity, we used confirmatory factor analyses in Structural Equation Modeling (SEM; Model 2), informed by functional structures that were modeled with path analyses in SEM (Model 1). The results show that aging effects were selective to measures of visual processing speed compared to visual short-term memory (VSTM) capacity (Model 2). These results are consistent with some studies reporting selective aging effects on processing speed, and inconsistent with other studies reporting aging effects on both processing speed and VSTM capacity. In the discussion we argue that this discrepancy may be mediated by differences in age ranges, and variables of demography. The study demonstrates that SEM is a sensitive method to detect cognitive aging effects even within a narrow age-range, and a useful approach to structure the relationships between measured variables, and the cognitive functional foundation they supposedly represent.