EEG correlates of visual short-term memory in older age vary with adult lifespan cognitive development

Exploring Network Properties Across Preclinical Stages of Alzheimer’s Disease Using a Visual Short-Term Memory and Attention Task with High-Density Electroencephalography: A Brain-Connectome Neurophysiological Study

Background: Visual short-term memory (VSTMT) and visual attention (VAT) exhibit decline in the Alzheimer’s disease (AD) continuum; however, network disruption in preclinical stages is scarcely explored. Objective: To advance our knowledge about brain networks in AD and discover connectivity alterations during VSTMT and VAT. Methods: Twelve participants with AD, 23 with mild cognitive impairment (MCI), 17 with subjective cognitive decline (SCD), and 21 healthy controls (HC) were examined using a neuropsychological battery at baseline and follow-up (three years). At baseline, the subjects were examined using high density electroencephalography while performing a VSTMT and VAT. For exploring network organization, we constructed weighted undirected networks and examined clustering coefficient, strength, and betweenness centrality from occipito-parietal regions. Results: One-way ANOVA and pair-wise t-test comparisons showed statistically significant differences in HC compared to SCD (t (36) = 2.43, p = 0.026), MCI (t (42) = 2.34, p = 0.024), and AD group (t (31) = 3.58, p = 0.001) in Clustering Coefficient. Also with regards to Strength, higher values for HC compared to SCD (t (36) = 2.45, p = 0.019), MCI (t (42) = 2.41, p = 0.020), and AD group (t (31) = 3.58, p = 0.001) were found. Follow-up neuropsychological assessment revealed converge of 65% of the SCD group to MCI. Moreover, SCD who were converted to MCI showed significant lower values in all network metrics compared to the SCD that remained stable. Conclusion: The present findings reveal that SCD exhibits network disorganization during visual encoding and retrieval with intermediate values between MCI and HC.

What Can Neural Activity Tell Us About Cognitive Resources in Aging?

A reduction in cognitive resources has been originally proposed to account for age-related decrements in several cognitive domains. According to this view, aging limits the pool of available cognitive supplies: Compared to younger adults, elderly exhaust the resources more rapidly as task difficulty increases, hence a dramatic performance drop. Neurophysiological indexes (e.g., BOLD response and EEG activity) may be instrumental to quantify the amount of such cognitive resources in the brain and to pinpoint the stage of stimulus processing where the decrement in age-related resources is evident. However, as we discuss in this mini-review, the most recent studies on the neurophysiological markers of age-related changes lack a consistent coupling between neural and behavioral effects, which casts doubt on the advantage of measuring neural indexes to study resource deployment in aging. For instance, in the working memory (WM) domain, recent cross-sectional studies found varying patterns of concurrent age-related brain activity, ranging from equivalent to reduced and increased activations of old with respect to younger adults. In an attempt to reconcile these seemingly inconsistent findings of brain-behavior coupling, we focus on the contribution of confounding sources of variability and propose ways to control for them. Finally, we suggest an alternative perspective to explain age-related effects that implies a qualitative (instead of or along with a quantitative) difference in the deployment of cognitive resources in aging.

Neural measures of working memory in a bilateral change detection task

The change detection task is a widely used paradigm to examine visual working memory processes. Participants memorize a set of items and then, try to detect changes in the set after a retention period. The negative slow wave (NSW) and contralateral delay activity (CDA) are event-related potentials in the EEG signal that are commonly used in change detection tasks to track working memory load, as both increase with the number of items maintained in working memory (set size). While the CDA was argued to more purely reflect the memory-specific neural activity than the NSW, it also requires a lateralized design and attention shifts prior to memoranda onset, imposing more restrictions on the task than the NSW. The present study proposes a novel change detection task in which both CDA and NSW can be measured at the same time. Memory items were presented bilaterally, but their distribution in the left and right hemifield varied, inducing a target imbalance or "net load." NSW increased with set size, whereas CDA increased with net load. In addition, a multivariate linear classifier was able to decode the set size and net load from the EEG signal. CDA, NSW, and decoding accuracy predicted an individual's working memory capacity. In line with the notion of a bilateral advantage in working memory, accuracy, and CDA data suggest that participants tended to encode items relatively balanced. In sum, this novel change detection task offers a basis to make use of converging neural measures of working memory in a comprehensive paradigm.

Learning by task repetition enhances object individuation and memorization in the elderly

A decline in visuospatial Working Memory (vWM) is a hallmark of cognitive aging across various tasks, and facing this decline has become the target of several studies. In the current study we tested whether older adults can benefit from task repetition in order to improve their performance in a vWM task. While learning by task repetition has been shown to improve vWM performance in young adulthood, little is known on whether a similar enhancement can be achieved also by the aging population. By combining different behavioral and electrophysiological measures, we investigated whether practicing a specific task (delayed match-to-sample judgement) over four consecutive sessions could improve vWM in healthy aging, and which are the neurophysiological and cognitive mechanisms modulated by learning. Behavioral data revealed that task repetition boosted performance in older participants, both in terms of sensitivity to change (as revealed by d' measures) as well as capacity estimate (as measured by k values). At the electrophysiological level, results indicated that only after task repetition both target individuation (as evidenced by the N2pc) and vWM maintenance (as reflected by the CDA) were modulated by target numerosity. Our results suggest that repetition learning is effective in enhancing vWM in aging and acts through modifications at different stages of stimulus processing.

TVA-based modeling of short-term memory capacity, speed of processing and perceptual threshold in chronic stroke patients undergoing cognitive training: case-control differences, reliability, and associations with cognitive performance

Attentional deficits following stroke are common and pervasive, and are important predictors for functional recovery. Attentional functions comprise a set of specific cognitive processes allowing to attend, filter and select among a continuous stream of stimuli. These mechanisms are fundamental for more complex cognitive functions such as learning, planning and cognitive control, all crucial for daily functioning. The distributed functional neuroanatomy of these processes is a likely explanation for the high prevalence of attentional impairments following stroke, and underscores the importance of a clinical implementation of computational approaches allowing for sensitive and specific modeling of attentional sub-processes. The Theory of Visual Attention (TVA) offers a theoretical, computational, neuronal and practical framework to assess the efficiency of visual selection performance and parallel processing of multiple objects. Here, in order to assess the sensitivity and reliability of TVA parameters reflecting short-term memory capacity (K), processing speed (C) and perceptual threshold (t 0), we used a whole-report paradigm in a cross-sectional case-control comparison and across six repeated assessments over the course of a three-week computerized cognitive training (CCT) intervention in chronic stroke patients (> 6 months since hospital admission, NIHSS ≤ 7 at hospital discharge). Cross-sectional group comparisons documented lower short-term memory capacity, lower processing speed and higher perceptual threshold in patients (n = 70) compared to age-matched healthy controls (n = 140). Further, longitudinal analyses in stroke patients during the course of CCT (n = 54) revealed high reliability of the TVA parameters, and higher processing speed at baseline was associated with larger cognitive improvement after the intervention. The results support the feasibility, reliability and sensitivity of TVA-based assessment of attentional functions in chronic stroke patients.

Steady-state visual evoked potential temporal dynamics reveal correlates of cognitive decline

OBJECTIVE

A central concern in aging is the preservation of cognitive skills. Tools to detect cognitive decline are sparse. The aim of this study was to ascertain whether cognitive decline is accompanied by alterations in the temporal dynamics of steady-state visual evoked potentials (SSVEPs).

METHODS

We included 162 men from the Danish Metropolit birth cohort. Their cognitive trajectory was based on their intelligence test score at youth (age ~18), middle age (age ~56), and late middle age (age ~62). Subjects underwent cognitive tests and steady-state visual stimulation. Temporal dynamics of SSVEPs were assessed in terms of amplitude and phase coherence.

RESULTS

The latency and magnitude of the amplitude modulation of the 36-Hz response correlated negatively with subjects' cognition indices. Furthermore, negative cognition index was associated with loss of SSVEPs at 36 Hz, and both 8 Hz and 36 Hz in severe cases.

CONCLUSION

Latency and magnitude of gamma frequency SSVEPs increase with cognitive decline. This suggests that the facilitation of SSVEPs first becomes problematic at gamma frequencies, then at alpha frequencies.

SIGNIFICANCE

Our data suggests that the temporal dynamics of SSVEPs can be used as an indicator of cognitive impairment. Furthermore, evoked gamma oscillations are especially vulnerable in cognitive decline.

Contralateral delay activity is not a robust marker of cognitive function in older adults at risk of mild cognitive impairment

Contralateral delay activity (CDA) has been proposed as a pre-clinical neural marker for mild cognitive impairment (MCI). However, existing evidence is limited to one study with a small sample size (n = 24). Our aim was to extend previous work by investigating the relationship between the CDA and MCI risk in a large sample of older adults (n = 76). We used a regression approach to determine whether (and when) CDA amplitude predicted MCI risk, as indexed by the Montreal Cognitive Assessment (MoCA). CDA amplitude from ~300-500 and ~800-900 ms predicted MoCA performance. However, significant effects were only observed for specific electrodes (P5/P6 and CP3/CP4, but not PO7/PO8) and the nature of the relationship between the CDA and MoCA scores differed across time and according to set size. Bayesian regression analysis indicated partial evidence in favour of the null hypothesis (BF₁₀ values = 4-1.18). Contrary to previous results, our findings suggest that the CDA may not a robust marker of MCI risk. More broadly, our results highlight the difficulty in identifying at-risk individuals, particularly as MCI is a heterogeneous, unstable condition. Future research should prioritise longitudinal approaches in order to track the progression of the CDA and its association with cognitive decline in later life.

Linking the impact of aging on visual short-term memory capacity with changes in the structural connectivity of posterior thalamus to occipital cortices

Aging impacts both visual short-term memory (vSTM) capacity and thalamo-cortical connectivity. According to the Neural Theory of Visual Attention, vSTM depends on the structural connectivity between posterior thalamus and visual occipital cortices (PT-OC). We tested whether aging modifies the association between vSTM capacity and PT-OC structural connectivity. To do so, 66 individuals aged 20-77 years were assessed by diffusion-weighted imaging used for probabilistic tractography and performed a psychophysical whole-report task of briefly presented letter arrays, from which vSTM capacity estimates were derived. We found reduced vSTM capacity, and aberrant PT-OC connection probability in aging. Critically, age modified the relationship between vSTM capacity and PT-OC connection probability: in younger adults, vSTM capacity was negatively correlated with PT-OC connection probability while in older adults, this association was positive. Furthermore, age modified the microstructure of PT-OC tracts suggesting that the inversion of the association between PT-OC connection probability and vSTM capacity with aging might reflect age-related changes in white-matter properties. Accordingly, our results demonstrate that age-related differences in vSTM capacity links with the microstructure and connectivity of PT-OC tracts.

Assessing distinct patterns of cognitive aging using tissue-specific brain age prediction based on diffusion tensor imaging and brain morphometry

Multimodal imaging enables sensitive measures of the architecture and integrity of the human brain, but the high-dimensional nature of advanced brain imaging features poses inherent challenges for the analyses and interpretations. Multivariate age prediction reduces the dimensionality to one biologically informative summary measure with potential for assessing deviations from normal lifespan trajectories. A number of studies documented remarkably accurate age prediction, but the differential age trajectories and the cognitive sensitivity of distinct brain tissue classes have yet to be adequately characterized. Exploring differential brain age models driven by tissue-specific classifiers provides a hitherto unexplored opportunity to disentangle independent sources of heterogeneity in brain biology. We trained machine-learning models to estimate brain age using various combinations of FreeSurfer based morphometry and diffusion tensor imaging based indices of white matter microstructure in 612 healthy controls aged 18-87 years. To compare the tissue-specific brain ages and their cognitive sensitivity, we applied each of the 11 models in an independent and cognitively well-characterized sample (n = 265, 20-88 years). Correlations between true and estimated age and mean absolute error (MAE) in our test sample were highest for the most comprehensive brain morphometry (r = 0.83, CI:0.78-0.86, MAE = 6.76 years) and white matter microstructure (r = 0.79, CI:0.74-0.83, MAE = 7.28 years) models, confirming sensitivity and generalizability. The deviance from the chronological age were sensitive to performance on several cognitive tests for various models, including spatial Stroop and symbol coding, indicating poorer performance in individuals with an over-estimated age. Tissue-specific brain age models provide sensitive measures of brain integrity, with implications for the study of a range of brain disorders.

Neural processing of working memory in adults with ADHD in a visuospatial change detection task with distractors

Individuals with Attention-Deficit Hyperactivity Disorder (ADHD) are often characterized by deficits in working memory (WM), which manifest in academic, professional, and mental health difficulties. To better understand the underlying mechanisms of these presumed WM deficits, we compared adults with ADHD to their peers on behavioral and neural indices of WM. We used a visuospatial change detection task with distractors which was designed to assess the brain’s ability to effectively filter out distractors from WM, in addition to testing for effects of WM load. Twenty-seven unmedicated adults with ADHD were compared to 27 matched peers on event-related potential (ERP) measures of WM, i.e., the contralateral delay activity (CDA). Despite severe impairments in everyday life functioning, findings showed no difference in deficits in behavioral tests of working memory for adults with ADHD compared to their peers. Interestingly, there were differences in neural activity between individuals with ADHD and their peers showing that the CDA of individuals with ADHD did not distinguish between high, distractor, and low memory load conditions. These data suggest, in the face of comparable behavioral performance, a difference in neural processing efficiency, wherein the brains of individuals with ADHD may not be as selective in the allocation of neural resources to perform a WM task.

Event-related Electroencephalographic Lateralizations Mark Individual Differences in Spatial and Nonspatial Visual Selection

Selective attention controls the distribution of our visual system's limited processing resources to stimuli in the visual field. Two independent parameters of visual selection can be quantified by modeling an individual's performance in a partial-report task based on the computational theory of visual attention (TVA): (i) top-down control α, the relative attentional weighting of relevant over irrelevant stimuli, and (ii) spatial bias w_λ, the relative attentional weighting of stimuli in the left versus right hemifield. In this study, we found that visual event-related electroencephalographic lateralizations marked interindividual differences in these two functions. First, individuals with better top-down control showed higher amplitudes of the posterior contralateral negativity than individuals with poorer top-down control. Second, differences in spatial bias were reflected in asymmetries in earlier visual event-related lateralizations depending on the hemifield position of targets; specifically, individuals showed a positivity contralateral to targets presented in their prioritized hemifield and a negativity contralateral to targets presented in their nonprioritized hemifield. Thus, our findings demonstrate that two functionally different aspects of attentional weighting quantified in the respective TVA parameters are reflected in two different neurophysiological measures: The observer-dependent spatial bias influences selection by a bottom-up processing advantage of stimuli appearing in the prioritized hemifield. By contrast, task-related target selection governed by top-down control involves active enhancement of target, and/or suppression of distractor, processing. These results confirm basic assumptions of the TVA framework, complement the functional interpretation of event-related lateralization components in selective attention studies, and are of relevance for the development of neurocognitive attentional assessment procedures.