Healthy aging delays scalp EEG sensitivity to noise in a face discrimination task

Spatiotemporal EEG Dynamics of Prospective Memory in Ageing and Mild Cognitive Impairment

Prospective memory (PM, the memory of future intentions) is one of the first complaints of those that develop dementia-related disease. Little is known about the neurophysiology of PM in ageing and those with mild cognitive impairment (MCI). By using a novel artificial neural network to investigate the spatial and temporal features of PM related brain activity, new insights can be uncovered. Young adults (n = 30), healthy older adults (n = 39) and older adults with MCI (n = 27) completed a working memory and two PM (perceptual, conceptual) tasks. Time-locked electroencephalographic potentials (ERPs) from 128-electrodes were analysed using a brain-inspired spiking neural network (SNN) architecture. Local and global connectivity from the SNNs was then evaluated. SNNs outperformed other machine learning methods in classification of brain activity between younger, older and older adults with MCI. SNNs trained using PM related brain activity had better classification accuracy than working memory related brain activity. In general, younger adults exhibited greater local cluster connectivity compared to both older adult groups. Older adults with MCI demonstrated decreased global connectivity in response to working memory and perceptual PM tasks but increased connectivity in the conceptual PM models relative to younger and healthy older adults. SNNs can provide a useful method for differentiating between those with and without MCI. Using brain activity related to PM in combination with SNNs may provide a sensitive biomarker for detecting cognitive decline. Cognitively demanding tasks may increase the amount connectivity in older adults with MCI as a means of compensation.

Healthy aging delays the neural processing of face features relevant for behavior by 40 ms

Fast and accurate face processing is critical for everyday social interactions, but it declines and becomes delayed with age, as measured by both neural and behavioral responses. Here, we addressed the critical challenge of understanding how aging changes neural information processing mechanisms to delay behavior. Young (20-36 years) and older (60-86 years) adults performed the basic social interaction task of detecting a face versus noise while we recorded their electroencephalogram (EEG). In each participant, using a new information theoretic framework we reconstructed the features supporting face detection behavior, and also where, when and how EEG activity represents them. We found that occipital-temporal pathway activity dynamically represents the eyes of the face images for behavior ~170 ms poststimulus, with a 40 ms delay in older adults that underlies their 200 ms behavioral deficit of slower reaction times. Our results therefore demonstrate how aging can change neural information processing mechanisms that underlie behavioral slow down.

Perceptual and conceptual processing of visual objects across the adult lifespan

Making sense of the external world is vital for multiple domains of cognition, and so it is crucial that object recognition is maintained across the lifespan. We investigated age differences in perceptual and conceptual processing of visual objects in a population-derived sample of 85 healthy adults (24-87 years old) by relating measures of object processing to cognition across the lifespan. Magnetoencephalography (MEG) was recorded during a picture naming task to provide a direct measure of neural activity, that is not confounded by age-related vascular changes. Multiple linear regression was used to estimate neural responsivity for each individual, namely the capacity to represent visual or semantic information relating to the pictures. We find that the capacity to represent semantic information is linked to higher naming accuracy, a measure of task-specific performance. In mature adults, the capacity to represent semantic information also correlated with higher levels of fluid intelligence, reflecting domain-general performance. In contrast, the latency of visual processing did not relate to measures of cognition. These results indicate that neural responsivity measures relate to naming accuracy and fluid intelligence. We propose that maintaining neural responsivity in older age confers benefits in task-related and domain-general cognitive processes, supporting the brain maintenance view of healthy cognitive ageing.

Asymmetric interference between cognitive task components and concurrent sensorimotor coordination

Everyday cognitive tasks are frequently performed under dual-task conditions alongside continuous sensorimotor coordinations (CSCs) such as driving, walking, or balancing. Observed interference in these dual-task settings is commonly attributed to demands on executive function or attentional resources, but the time course and reciprocity of interference are not well understood at the level of information-processing components. Here we used electrophysiology to study the detailed chronometry of dual-task interference between a visual oddball task and a continuous visuomanual tracking task. The oddball task's electrophysiological components were linked to underlying cognitive processes, and the tracking task served as a proxy for the continuous cycle of state monitoring and adjustment inherent to CSCs. Dual-tasking interfered with the oddball task's accuracy and attentional processes (attenuated P2 and P3b magnitude and parietal alpha-band event-related desynchronization), but errors in tracking due to dual-tasking accrued at a later timescale and only in trials in which the target stimulus appeared and its tally had to be incremented. Interference between cognitive tasks and CSCs can be asymmetric in terms of timing as well as affected information-processing components. NEW & NOTEWORTHY Interference between cognitive tasks and continuous sensorimotor coordination (CSC) has been widely reported, but this is the first demonstration that the cognitive operation that is impaired by concurrent CSC may not be the one that impairs the CSC. Also demonstrated is that interference between such tasks can be temporally asymmetric. The asynchronicity of this interference has significant implications for understanding and mitigating loss of mobility in old age, and for rehabilitation for neurological impairments.

The development of human visual cortex and clinical implications

The primary visual cortex (V1) is the first cortical area that processes visual information. Normal development of V1 depends on binocular vision during the critical period, and age-related losses of vision are linked with neurobiological changes in V1. Animal studies have provided important details about the neurobiological mechanisms in V1 that support normal vision or are changed by visual diseases. There is very little information, however, about those neurobiological mechanisms in human V1. That lack of information has hampered the translation of biologically inspired treatments from preclinical models to effective clinical treatments. We have studied human V1 to characterize the expression of neurobiological mechanisms that regulate visual perception and neuroplasticity. We have identified five stages of development for human V1 that start in infancy and continue across the life span. Here, we describe these stages, compare them with visual and anatomical milestones, and discuss implications for translating treatments for visual disorders that depend on neuroplasticity of V1 function.

Age-related delay in visual and auditory evoked responses is mediated by white- and grey-matter differences

Slowing is a common feature of ageing, yet a direct relationship between neural slowing and brain atrophy is yet to be established in healthy humans. We combine magnetoencephalographic (MEG) measures of neural processing speed with magnetic resonance imaging (MRI) measures of white and grey matter in a large population-derived cohort to investigate the relationship between age-related structural differences and visual evoked field (VEF) and auditory evoked field (AEF) delay across two different tasks. Here we use a novel technique to show that VEFs exhibit a constant delay, whereas AEFs exhibit delay that accumulates over time. White-matter (WM) microstructure in the optic radiation partially mediates visual delay, suggesting increased transmission time, whereas grey matter (GM) in auditory cortex partially mediates auditory delay, suggesting less efficient local processing. Our results demonstrate that age has dissociable effects on neural processing speed, and that these effects relate to different types of brain atrophy.

Effect of Aging on ERP Components of Cognitive Control

As people age, their performance on tasks requiring cognitive control often declines. Such a decline is frequently explained as either a general or specific decline in cognitive functioning with age. In the context of hypotheses suggesting a general decline, it is often proposed that processing speed generally declines with age. A further hypothesis is that an age-related compensation mechanism is associated with a specific cognitive decline. One prominent theory is the compensation hypothesis, which proposes that deteriorated functions are compensated for by higher performing functions. In this study, we used event-related potentials (ERPs) in the context of a GO/NOGO task to examine the age-related changes observed during cognitive control in a large group of healthy subjects aged between 18 and 84 years. The main question we attempted to answer was whether we could find neurophysiological support for either a general decline in processing speed or a compensation strategy. The subjects performed a relatively demanding cued GO/NOGO task with similar omissions and reaction times across the five age groups. The ERP waves of cognitive control, such as N2, P3cue and CNV, were decomposed into latent components by means of a blind source separation method. Based on this decomposition, it was possible to more precisely delineate the different neurophysiological and psychological processes involved in cognitive control. These data support the processing speed hypothesis because the latencies of all cognitive control ERP components increased with age, by 8 ms per decade for the early components (<200 ms) and by 20 ms per decade for the late components. At the same time, the compensatory hypothesis of aging was also supported, as the amplitudes of the components localized in posterior brain areas decreased with age, while those localized in the prefrontal cortical areas increased with age in order to maintain performance on this simple task at a relatively stable level.

A robust and representative lower bound on object processing speed in humans

How early does the brain decode object categories? Addressing this question is critical to constrain the type of neuronal architecture supporting object categorization. In this context, much effort has been devoted to estimating face processing speed. With onsets estimated from 50 to 150 ms, the timing of the first face-sensitive responses in humans remains controversial. This controversy is due partially to the susceptibility of dynamic brain measurements to filtering distortions and analysis issues. Here, using distributions of single-trial event-related potentials (ERPs), causal filtering, statistical analyses at all electrodes and time points, and effective correction for multiple comparisons, we present evidence that the earliest categorical differences start around 90 ms following stimulus presentation. These results were obtained from a representative group of 120 participants, aged 18-81, who categorized images of faces and noise textures. The results were reliable across testing days, as determined by test-retest assessment in 74 of the participants. Furthermore, a control experiment showed similar ERP onsets for contrasts involving images of houses or white noise. Face onsets did not change with age, suggesting that face sensitivity occurs within 100 ms across the adult lifespan. Finally, the simplicity of the face-texture contrast, and the dominant midline distribution of the effects, suggest the face responses were evoked by relatively simple image properties and are not face specific. Our results provide a new lower benchmark for the earliest neuronal responses to complex objects in the human visual system.

Selectivity of Face Perception to Horizontal Information over Lifespan (from 6 to 74 Year Old)

Face recognition in young human adults preferentially relies on the processing of horizontally-oriented visual information. We addressed whether the horizontal tuning of face perception is modulated by the extensive experience humans acquire with faces over the lifespan, or whether it reflects an invariable processing bias for this visual category. We tested 296 subjects aged from 6 to 74 years in a face matching task. Stimuli were upright and inverted faces filtered to preserve information in the horizontal or vertical orientation, or both (HV) ranges. The reliance on face-specific processing was inferred based on the face inversion effect (FIE). FIE size increased linearly until young adulthood in the horizontal but not the vertical orientation range of face information. These findings indicate that the protracted specialization of the face processing system relies on the extensive experience humans acquire at encoding the horizontal information conveyed by upright faces.

On the particular vulnerability of face recognition to aging: a review of three hypotheses

Age-related face recognition deficits are characterized by high false alarms to unfamiliar faces, are not as pronounced for other complex stimuli, and are only partially related to general age-related impairments in cognition. This paper reviews some of the underlying processes likely to be implicated in theses deficits by focusing on areas where contradictions abound as a means to highlight avenues for future research. Research pertaining to the three following hypotheses is presented: (i) perceptual deterioration, (ii) encoding of configural information, and (iii) difficulties in recollecting contextual information. The evidence surveyed provides support for the idea that all three factors are likely to contribute, under certain conditions, to the deficits in face recognition seen in older adults. We discuss how these different factors might interact in the context of a generic framework of the different stages implicated in face recognition. Several suggestions for future investigations are outlined.

Segmentation precedes face categorization under suboptimal conditions

Both categorization and segmentation processes play a crucial role in face perception. However, the functional relation between these subprocesses is currently unclear. The present study investigates the temporal relation between segmentation-related and category-selective responses in the brain, using electroencephalography (EEG). Surface segmentation and category content were both manipulated using texture-defined objects, including faces. This allowed us to study brain activity related to segmentation and to categorization. In the main experiment, participants viewed texture-defined objects for a duration of 800 ms. EEG results revealed that segmentation-related responses precede category-selective responses. Three additional experiments revealed that the presence and timing of categorization depends on stimulus properties and presentation duration. Photographic objects were presented for a long and short (92 ms) duration and evoked fast category-selective responses in both cases. On the other hand, presentation of texture-defined objects for a short duration only evoked segmentation-related but no category-selective responses. Category-selective responses were much slower when evoked by texture-defined than by photographic objects. We suggest that in case of categorization of objects under suboptimal conditions, such as when low-level stimulus properties are not sufficient for fast object categorization, segmentation facilitates the slower categorization process.

Regression-based estimation of ERP waveforms: I. The rERP framework

ERP averaging is an extraordinarily successful method, but can only be applied to a limited range of experimental designs. We introduce the regression-based rERP framework, which extends ERP averaging to handle arbitrary combinations of categorical and continuous covariates, partial confounding, nonlinear effects, and overlapping responses to distinct events, all within a single unified system. rERPs enable a richer variety of paradigms (including high-N naturalistic designs) while preserving the advantages of traditional ERPs. This article provides an accessible introduction to what rERPs are, why they are useful, how they are computed, and when we should expect them to be effective, particularly in cases of partial confounding. A companion article discusses how nonlinear effects and overlap correction can be handled within this framework, as well as practical considerations around baselining, filtering, statistical testing, and artifact rejection. Free software implementing these techniques is available.

Cluster-based computational methods for mass univariate analyses of event-related brain potentials/fields: A simulation study

BACKGROUND

In recent years, analyses of event related potentials/fields have moved from the selection of a few components and peaks to a mass-univariate approach in which the whole data space is analyzed. Such extensive testing increases the number of false positives and correction for multiple comparisons is needed.

METHOD

Here we review all cluster-based correction for multiple comparison methods (cluster-height, cluster-size, cluster-mass, and threshold free cluster enhancement - TFCE), in conjunction with two computational approaches (permutation and bootstrap).

RESULTS

Data driven Monte-Carlo simulations comparing two conditions within subjects (two sample Student's t-test) showed that, on average, all cluster-based methods using permutation or bootstrap alike control well the family-wise error rate (FWER), with a few caveats.

CONCLUSIONS

(i) A minimum of 800 iterations are necessary to obtain stable results; (ii) below 50 trials, bootstrap methods are too conservative; (iii) for low critical family-wise error rates (e.g. p=1%), permutations can be too liberal; (iv) TFCE controls best the type 1 error rate with an attenuated extent parameter (i.e. power<1).

How the visual cortex handles stimulus noise: insights from amblyopia

Adding noise to a visual image makes object recognition more effortful and has a widespread effect on human electrophysiological responses. However, visual cortical processes directly involved in handling the stimulus noise have yet to be identified and dissociated from the modulation of the neural responses due to the deteriorated structural information and increased stimulus uncertainty in the case of noisy images. Here we show that the impairment of face gender categorization performance in the case of noisy images in amblyopic patients correlates with amblyopic deficits measured in the noise-induced modulation of the P1/P2 components of single-trial event-related potentials (ERP). On the other hand, the N170 ERP component is similarly affected by the presence of noise in the two eyes and its modulation does not predict the behavioral deficit. These results have revealed that the efficient processing of noisy images depends on the engagement of additional processing resources both at the early, feature-specific as well as later, object-level stages of visual cortical processing reflected in the P1 and P2 ERP components, respectively. Our findings also suggest that noise-induced modulation of the N170 component might reflect diminished face-selective neuronal responses to face images with deteriorated structural information.

Early ERPs to faces: aging, luminance, and individual differences

Recently, Rousselet et al. reported a 1 ms/year delay in visual processing speed in a sample of healthy aged 62 subjects (Frontiers in Psychology 2010, 1:19). Here, we replicate this finding in an independent sample of 59 subjects and investigate the contribution of optical factors (pupil size and luminance) to the age-related slowdown and to individual differences in visual processing speed. We conducted two experiments. In experiment 1 we recorded EEG from subjects aged 18–79. Subjects viewed images of faces and phase scrambled noise textures under nine luminance conditions, ranging from 0.59 to 60.8 cd/m². We manipulated luminance using neutral density filters. In experiment 2, 10 young subjects (age < 35) viewed similar stimuli through pinholes ranging from 1 to 5 mm. In both experiments, subjects were tested twice. We found a 1 ms/year slowdown in visual processing that was independent of luminance. Aging effects became visible around 125 ms post-stimulus and did not affect the onsets of the face-texture ERP differences. Furthermore, luminance modulated the entire ERP time-course from 60 to 500 ms. Luminance effects peaked in the N170 time window and were independent of age. Importantly, senile miosis and individual differences in pupil size did not account for aging differences and inter-subject variability in processing speed. The pinhole manipulation also failed to match the ERPs of old subjects to those of young subjects. Overall, our results strongly suggest that early ERPs to faces (<200 ms) are delayed by aging and that these delays are of cortical, rather than optical origin. Our results also demonstrate that even late ERPs to faces are modulated by low-level factors.

Modeling Single-Trial ERP Reveals Modulation of Bottom-Up Face Visual Processing by Top-Down Task Constraints (in Some Subjects)

We studied how task constraints modulate the relationship between single-trial event-related potentials (ERPs) and image noise. Thirteen subjects performed two interleaved tasks: on different blocks, they saw the same stimuli, but they discriminated either between two faces or between two colors. Stimuli were two pictures of red or green faces that contained from 10 to 80% of phase noise, with 10% increments. Behavioral accuracy followed a noise dependent sigmoid in the identity task but was high and independent of noise level in the color task. EEG data recorded concurrently were analyzed using a single-trial ANCOVA: we assessed how changes in task constraints modulated ERP noise sensitivity while regressing out the main ERP differences due to identity, color, and task. Single-trial ERP sensitivity to image phase noise started at about 95-110 ms post-stimulus onset. Group analyses showed a significant reduction in noise sensitivity in the color task compared to the identity task from about 140 ms to 300 ms post-stimulus onset. However, statistical analyses in every subject revealed different results: significant task modulation occurred in 8/13 subjects, one showing an increase and seven showing a decrease in noise sensitivity in the color task. Onsets and durations of effects also differed between group and single-trial analyses: at any time point only a maximum of four subjects (31%) showed results consistent with group analyses. We provide detailed results for all 13 subjects, including a shift function analysis that revealed asymmetric task modulations of single-trial ERP distributions. We conclude that, during face processing, bottom-up sensitivity to phase noise can be modulated by top-down task constraints, in a broad window around the P2, at least in some subjects.

Quantifying the Time Course of Visual Object Processing Using ERPs: It's Time to Up the Game

Hundreds of studies have investigated the early ERPs to faces and objects using scalp and intracranial recordings. The vast majority of these studies have used uncontrolled stimuli, inappropriate designs, peak measurements, poor figures, and poor inferential and descriptive group statistics. These problems, together with a tendency to discuss any effect p < 0.05 rather than to report effect sizes, have led to a research field very much qualitative in nature, despite its quantitative inspirations, and in which predictions do not go beyond condition A > condition B. Here we describe the main limitations of face and object ERP research and suggest alternative strategies to move forward. The problems plague intracranial and surface ERP studies, but also studies using more advanced techniques – e.g., source space analyses and measurements of network dynamics, as well as many behavioral, fMRI, TMS, and LFP studies. In essence, it is time to stop amassing binary results and start using single-trial analyses to build models of visual perception.

LIMO EEG: a toolbox for hierarchical LInear MOdeling of ElectroEncephaloGraphic data

Magnetic- and electric-evoked brain responses have traditionally been analyzed by comparing the peaks or mean amplitudes of signals from selected channels and averaged across trials. More recently, tools have been developed to investigate single trial response variability (e.g., EEGLAB) and to test differences between averaged evoked responses over the entire scalp and time dimensions (e.g., SPM, Fieldtrip). LIMO EEG is a Matlab toolbox (EEGLAB compatible) to analyse evoked responses over all space and time dimensions, while accounting for single trial variability using a simple hierarchical linear modelling of the data. In addition, LIMO EEG provides robust parametric tests, therefore providing a new and complementary tool in the analysis of neural evoked responses.

Functional Dedifferentiation and Altered Connectivity in Older Adults: Neural Accounts of Cognitive Aging

Aging is associated with myriad changes in behavioral performance and brain structure and function. Given this complex interplay of brain and behavior, two streams of findings are reviewed here that show that aging is generally associated with dedifferentiated neural processes, and also changes in functional connectivity. This article considers an integrated view of how such age-related dedifferentiation of neural function and changes in functional connectivity are related, highlighting some recent findings on differences in small-world architecture in the functional connectivity of young and older adults. These findings suggest that both neural connectivity and the organization of these connections are important determinants of processing efficiency with aging that may be the underlying mechanisms for dedifferentiation. Thus, the evaluation of the neurocognitive effects of aging on functional connectivity provides an alternative framework that captures the behavioral and brain changes that are observed in cognitive aging.