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

Development of the Alpha Rhythm Is Linked to Visual White Matter Pathways and Visual Detection Performance

Alpha is the strongest electrophysiological rhythm in awake humans at rest. Despite its predominance in the EEG signal, large variations can be observed in alpha properties during development, with an increase in alpha frequency over childhood and adulthood. Here, we tested the hypothesis that these changes in alpha rhythm are related to the maturation of visual white matter pathways. We capitalized on a large diffusion MRI (dMRI)-EEG dataset (dMRI n = 2,747, EEG n = 2,561) of children and adolescents of either sex (age range, 5-21 years old) and showed that maturation of the optic radiation specifically accounts for developmental changes of alpha frequency. Behavioral analyses also confirmed that variations of alpha frequency are related to maturational changes in visual perception. The present findings demonstrate the close link between developmental variations in white matter tissue properties, electrophysiological responses, and behavior.

Referential and inferential production across the lifespan: different patterns and different predictive cognitive factors

Introduction

The ability to speak is grounded in general memory and control processes and likely changes across the lifespan. However, our knowledge on how word production abilities naturally evolve from childhood to old age remains marginally investigated. Our aim was to shed further light on this issue by exploiting the contrast between two ways to elicit word production: referential picture naming and inferential naming from definition.

Methods

We collected accuracy and production latencies in a picture naming task and in a naming from definition task from 130 participants ranging from 10 to 80 years old. Measures of vocabulary size, digit span memory, semantic and phonemic fluencies and processing speed were also collected. We used multivariate adaptative regression splines and regression models to characterize lifespan patterns of the two tasks.

Results

Patterns of increase in performance were similar for picture naming and naming from definition only from childhood to young adulthood. In the second half of the lifespan, significant decrease of performance was found in older adults for picture naming (from around 60 years-old) but not for naming from definition. Clearly, word production elicited with an inferential task (naming from definition) yields different age-related patterns than usually described in the literature with a referential task (picture naming).

Discussion

We discuss how cognitive processes such as visual-conceptual processes and lexical prediction may explain the differential pattern of results in aging in referential and inferential production tasks. We argue for more lifespan studies and the need to investigate language production beyond picture naming, in particular with respect to aging.

Stability of neural representations in the auditory midbrain across the lifespan despite age-related brainstem delays

The extent to which aging of the central auditory pathway impairs auditory perception in the elderly independent of peripheral cochlear decline is debated. To cause auditory deficits in normal hearing elderly, central aging needs to degrade neural sound representations at some point along the auditory pathway. However, inaccessible to psychophysical methods, the level of the auditory pathway at which aging starts to effectively degrade neural sound representations remains poorly differentiated. Here we tested how potential age-related changes in the auditory brainstem affect the stability of spatiotemporal multiunit complex speech-like sound representations in the auditory midbrain of old normal hearing CBA/J mice. Although brainstem conduction speed slowed down in old mice, the change was limited to the sub-millisecond range and only minimally affected temporal processing in the midbrain (i.e. gaps-in-noise sensitivity). Importantly, besides the small delay, multiunit complex temporal sound representations in the auditory midbrain did not differ between young and old mice. This shows that although small age-related neural effects in simple sound parameters in the lower brainstem may be present in aging they do not effectively deteriorate complex neural population representations at the level of the auditory midbrain when peripheral hearing remains normal. This result challenges the widespread belief of 'pure' central auditory decline as an automatic consequence of aging, at least up to the inferior colliculus. However, the stability of midbrain processing in aging emphasizes the role of undetected 'hidden' peripheral damage and accumulating effects in higher cortical auditory-cognitive processing explaining perception deficits in 'normal hearing' elderly.

Disturbances in primary visual processing as a function of healthy aging

For decades, visual entrainment paradigms have been widely used to investigate basic visual processing in healthy individuals and those with neurological disorders. While healthy aging is known to be associated with alterations in visual processing, whether this extends to visual entrainment responses and the precise cortical regions involved is not fully understood. Such knowledge is imperative given the recent surge in interest surrounding the use of flicker stimulation and entrainment in the context of identifying and treating Alzheimer's disease (AD). In the current study, we examined visual entrainment in eighty healthy aging adults using magnetoencephalography (MEG) and a 15 Hz entrainment paradigm, while controlling for age-related cortical thinning. MEG data were imaged using a time-frequency resolved beamformer and peak voxel time series were extracted to quantify the oscillatory dynamics underlying the processing of the visual flicker stimuli. We found that, as age increased, the mean amplitude of entrainment responses decreased and the latency of these responses increased. However, there was no effect of age on the trial-to-trial consistency in phase (i.e., inter-trial phase locking) nor amplitude (i.e., coefficient of variation) of these visual responses. Importantly, we discovered that the relationship between age and response amplitude was fully mediated by the latency of visual processing. These results indicate that aging is associated with robust changes in the latency and amplitude of visual entrainment responses within regions surrounding the calcarine fissure, which should be considered in studies examining neurological disorders such as AD and other conditions associated with increased age.

A correlational study between microstructural, macrostructural and functional age-related changes in the human visual cortex

Age-related changes in the human brain can be investigated from either structural or functional perspectives. Analysis of structural and functional age-related changes throughout the lifespan may help to understand the normal brain development process and monitor the structural and functional pathology of the brain. This study, combining dedicated electroencephalography (EEG) and magnetic resonance imaging (MRI) approaches in adults (20-78 years), highlights the complex relationship between micro/macrostructural properties and the functional responses to visual stimuli. Here, we aimed to relate age-related changes of the latency of visual evoked potentials (VEPs) to micro/macrostructural indexes and find any correlation between micro/macrostructural features, as well. We studied age-related structural changes in the brain, by using the MRI and diffusion-weighted imaging (DWI) as preferred imaging methods for extracting brain macrostructural parameters such as the cortical thickness, surface area, folding and curvature index, gray matter volume, and microstructural parameters such as mean diffusivity (MD), radial diffusivity (RD) and axial diffusivity (AD). All the mentioned features were significantly correlated with age in V1 and V2 regions of the visual cortex. Furthermore, we highlighted, negative correlations between structural features extracted from T1-weighted images and DWI. The latency and amplitude of the three dominants peaks (C1, P1, N1) of the VEP were considered as the brain functional features to be examined for correlation with age and structural features of the corresponding age. We observed significant correlations between mean C1 latency and GM volume averaged in V1 and V2. In hierarchical regression analysis, the structural index did not contribute to significant variance in the C1 latency after regressing out the effect of age. However, the age explained significant variance in the model after regressing out the effect of structural feature.

Age-related central gain with degraded neural synchrony in the auditory brainstem of mice and humans

Aging is associated with auditory nerve (AN) functional deficits and decreased inhibition in the central auditory system, amplifying central responses in a process referred to here as central gain. Although central gain increases response amplitudes, central gain may not restore disrupted response timing. In this translational study, we measured responses putatively generated by the AN and auditory midbrain in younger and older mice and humans. We hypothesized that older mice and humans exhibit increased central gain without an improvement in inter-trial synchrony in the midbrain. Our data demonstrated greater age-related deficits in AN response amplitudes than auditory midbrain response amplitudes, as shown by significant interactions between inferred neural generator and age group, indicating increased central gain in auditory midbrain. However, synchrony decreases with age in both the AN and midbrain responses. These results reveal age-related increases in central gain without concomitant improvements in synchrony, consistent with those predictions based on decreases in inhibition. Persistent decreases in synchrony may contribute to auditory processing deficits in older mice and humans.

Neurophysiological and Brain Structural Markers of Cognitive Frailty Differ from Alzheimer's Disease

With increasing life span and prevalence of dementia, it is important to understand the mechanisms of cognitive aging. Here, we focus on a subgroup of the population we term "cognitively frail," defined by reduced cognitive function in the absence of subjective memory complaints, or a clinical diagnosis of dementia. Cognitive frailty is distinct from cognitive impairment caused by physical frailty. It has been proposed to be a precursor to Alzheimer's disease, but may alternatively represent one end of a nonpathologic spectrum of cognitive aging. We test these hypotheses in humans of both sexes, by comparing the structural and neurophysiological properties of a community-based cohort of cognitive frail adults, to people presenting clinically with diagnoses of Alzheimer's disease or mild cognitive impairment, and community-based cognitively typical older adults. Cognitive performance of the cognitively frail was similar to those with mild cognitive impairment. We used a novel cross-modal paired-associates task that presented images followed by sounds, to induce physiological responses of novelty and associative mismatch, recorded by EEG/MEG. Both controls and cognitively frail showed stronger mismatch responses and larger temporal gray matter volume, compared with people with mild cognitive impairment and Alzheimer's disease. Our results suggest that community-based cognitively frail represents a spectrum of normal aging rather than incipient Alzheimer's disease, despite similar cognitive function. Lower lifelong cognitive reserve, hearing impairment, and cardiovascular comorbidities might contribute to the etiology of the cognitive frailty. Critically, community-based cohorts of older adults with low cognitive performance should not be interpreted as representing undiagnosed Alzheimer's disease.SIGNIFICANCE STATEMENT The current study investigates the neural signatures of cognitive frailty in relation to healthy aging and Alzheimer's disease. We focus on the cognitive aspect of frailty and show that, despite performing similarly to the patients with mild cognitive impairment, a cohort of community-based adults with poor cognitive performance do not show structural atrophy or neurophysiological signatures of Alzheimer's disease. Our results call for caution before assuming that cognitive frailty represents latent Alzheimer's disease. Instead, the cognitive underperformance of cognitively frail adults could result in cumulative effects of multiple psychosocial risk factors over the lifespan, and medical comorbidities.

Development of the visual white matter pathways mediates development of electrophysiological responses in visual cortex

The latency of neural responses in the visual cortex changes systematically across the lifespan. Here, we test the hypothesis that development of visual white matter pathways mediates maturational changes in the latency of visual signals. Thirty-eight children participated in a cross-sectional study including diffusion magnetic resonance imaging (MRI) and magnetoencephalography (MEG) sessions. During the MEG acquisition, participants performed a lexical decision and a fixation task on words presented at varying levels of contrast and noise. For all stimuli and tasks, early evoked fields were observed around 100 ms after stimulus onset (M100), with slower and lower amplitude responses for low as compared to high contrast stimuli. The optic radiations and optic tracts were identified in each individual's brain based on diffusion MRI tractography. The diffusion properties of the optic radiations predicted M100 responses, especially for high contrast stimuli. Higher optic radiation fractional anisotropy (FA) values were associated with faster and larger M100 responses. Over this developmental window, the M100 responses to high contrast stimuli became faster with age and the optic radiation FA mediated this effect. These findings suggest that the maturation of the optic radiations over childhood accounts for individual variations observed in the developmental trajectory of visual cortex responses.

Early auditory cortical processing predicts auditory speech in noise identification and lipreading

Individuals typically exhibit better cross-sensory perception following unisensory loss, demonstrating improved perception of information available from the remaining senses and increased cross-sensory use of neural resources. Even individuals with no sensory loss will exhibit such changes in cross-sensory processing following temporary sensory deprivation, suggesting that the brain's capacity for recruiting cross-sensory sources to compensate for degraded unisensory input is a general characteristic of the perceptual process. Many studies have investigated how auditory and visual neural structures respond to within- and cross-sensory input. However, little attention has been given to how general auditory and visual neural processing relates to within and cross-sensory perception. The current investigation examines the extent to which individual differences in general auditory neural processing accounts for variability in auditory, visual, and audiovisual speech perception in a sample of young healthy adults. Auditory neural processing was assessed using a simple click stimulus. We found that individuals with a smaller P1 peak amplitude in their auditory-evoked potential (AEP) had more difficulty identifying speech sounds in difficult listening conditions, but were better lipreaders. The results suggest that individual differences in the auditory neural processing of healthy adults can account for variability in the perception of information available from the auditory and visual modalities, similar to the cross-sensory perceptual compensation observed in individuals with sensory loss.

Toward more robust and reproducible diffusion kurtosis imaging

PURPOSE

The general utility of diffusion kurtosis imaging (DKI) is challenged by its poor robustness to imaging artifacts and thermal noise that often lead to implausible kurtosis values.

THEORY AND METHODS

A robust scalar kurtosis index can be estimated from powder-averaged diffusion-weighted data. We introduce a novel DKI estimator that uses this scalar kurtosis index as a proxy for the mean kurtosis to regularize the fit.

RESULTS

The regularized DKI estimator improves the robustness and reproducibility of the kurtosis metrics and results in parameter maps with enhanced quality and contrast.

CONCLUSION

Our novel DKI estimator promotes the wider use of DKI in clinical research and potentially diagnostics by improving the reproducibility and precision of DKI fitting and, as such, enabling enhanced visual, quantitative, and statistical analyses of DKI parameters.

Evidence for microscopic kurtosis in neural tissue revealed by correlation tensor MRI

PURPOSE

The impact of microscopic diffusional kurtosis (µK), arising from restricted diffusion and/or structural disorder, remains a controversial issue in contemporary diffusion MRI (dMRI). Recently, correlation tensor imaging (CTI) was introduced to disentangle the sources contributing to diffusional kurtosis, without relying on a-priori multi-gaussian component (MGC) or other microstructural assumptions. Here, we investigated µK in in vivo rat brains and assessed its impact on state-of-the-art methods ignoring µK.

THEORY AND METHODS

CTI harnesses double diffusion encoding (DDE) experiments, which were here improved for speed and minimal bias using four different sets of acquisition parameters. The robustness of the improved CTI protocol was assessed via simulations. In vivo CTI acquisitions were performed in healthy rat brains using a 9.4T pre-clinical scanner equipped with a cryogenic coil, and targeted the estimation of µK, anisotropic kurtosis, and isotropic kurtosis.

RESULTS

The improved CTI acquisition scheme substantially reduces scan time and importantly, also minimizes higher-order-term biases, thus enabling robust µK estimation, alongside K_aniso and K_iso metrics. Our CTI experiments revealed positive µK both in white and gray matter of the rat brain in vivo; µK is the dominant kurtosis source in healthy gray matter tissue. The non-negligible µK substantially were found to bias prior MGC analyses of K_iso and K_aniso .

CONCLUSIONS

Correlation Tensor MRI offers a more accurate and robust characterization of kurtosis sources than its predecessors. µK is non-negligible in vivo in healthy white and gray matter tissues and could be an important biomarker for future studies. Our findings thus have both theoretical and practical implications for future dMRI research.

Diffusional Kurtosis Imaging in the Diffusion Imaging in Python Project

Diffusion-weighted magnetic resonance imaging (dMRI) measurements and models provide information about brain connectivity and are sensitive to the physical properties of tissue microstructure. Diffusional Kurtosis Imaging (DKI) quantifies the degree of non-Gaussian diffusion in biological tissue from dMRI. These estimates are of interest because they were shown to be more sensitive to microstructural alterations in health and diseases than measures based on the total anisotropy of diffusion which are highly confounded by tissue dispersion and fiber crossings. In this work, we implemented DKI in the Diffusion in Python (DIPY) project-a large collaborative open-source project which aims to provide well-tested, well-documented and comprehensive implementation of different dMRI techniques. We demonstrate the functionality of our methods in numerical simulations with known ground truth parameters and in openly available datasets. A particular strength of our DKI implementations is that it pursues several extensions of the model that connect it explicitly with microstructural models and the reconstruction of 3D white matter fiber bundles (tractography). For instance, our implementations include DKI-based microstructural models that allow the estimation of biophysical parameters, such as axonal water fraction. Moreover, we illustrate how DKI provides more general characterization of non-Gaussian diffusion compatible with complex white matter fiber architectures and gray matter, and we include a novel mean kurtosis index that is invariant to the confounding effects due to tissue dispersion. In summary, DKI in DIPY provides a well-tested, well-documented and comprehensive reference implementation for DKI. It provides a platform for wider use of DKI in research on brain disorders and in cognitive neuroscience.

Separating vascular and neuronal effects of age on fMRI BOLD signals

Accurate identification of brain function is necessary to understand the neurobiology of cognitive ageing, and thereby promote well-being across the lifespan. A common tool used to investigate neurocognitive ageing is functional magnetic resonance imaging (fMRI). However, although fMRI data are often interpreted in terms of neuronal activity, the blood oxygenation level-dependent (BOLD) signal measured by fMRI includes contributions of both vascular and neuronal factors, which change differentially with age. While some studies investigate vascular ageing factors, the results of these studies are not well known within the field of neurocognitive ageing and therefore vascular confounds in neurocognitive fMRI studies are common. Despite over 10 000 BOLD-fMRI papers on ageing, fewer than 20 have applied techniques to correct for vascular effects. However, neurovascular ageing is not only a confound in fMRI, but an important feature in its own right, to be assessed alongside measures of neuronal ageing. We review current approaches to dissociate neuronal and vascular components of BOLD-fMRI of regional activity and functional connectivity. We highlight emerging evidence that vascular mechanisms in the brain do not simply control blood flow to support the metabolic needs of neurons, but form complex neurovascular interactions that influence neuronal function in health and disease. This article is part of the theme issue 'Key relationships between non-invasive functional neuroimaging and the underlying neuronal activity'.

Neural changes in early visual processing after 6 months of mindfulness training in older adults

Mindfulness has been shown to improve attentional performance, which is known to decline in aging. Long-latency electroencephalographic (EEG) event-related potential (ERP) changes have been reported immediately after mindfulness training, however the enduring stability of these effects is unknown. Furthermore, the ability of mindfulness to impact earlier stages of information processing is unclear. We examined neural activation using high density EEG in older adults engaged in mindfulness training to examine the long-term stability of training effects. After 6 months of training, mindfulness practitioners displayed enhanced neural activation during sensory encoding and perceptual processing of a visual cue. Enhanced perceptual processing of a visual cue was associated with increased neural activation during post-perceptual processing of a subsequent target. Similar changes were not observed in a control group engaged in computer-based attention training over the same period. Neural changes following mindfulness training were accompanied by behavioural improvements in attentional performance. Our results are suggestive of increased efficiency of the neural pathways subserving bottom-up visual processing together with an enhanced ability to mobilise top-down attentional processes during perceptual and post-perceptual processing following mindfulness training. These results indicate that mindfulness may enhance neural processes known to deteriorate in normal aging and age-related neurodegenerative diseases.

The Autism Palette: Combinations of Impairments Explain the Heterogeneity in ASD

Autism spectrum disorder (ASD) is a heterogeneous neuropsychiatric condition traditionally defined by core symptoms in social behavior, speech/communication, repetitive behavior, and restricted interests. Beyond the core symptoms, autism has strong association with other disorders such as intellectual disability (ID), epilepsy, schizophrenia among many others. This paper outlines a theory of ASD with capacity to connect heterogeneous "core" symptoms, medical and psychiatric comorbidities as well as other etiological theories of autism in a unifying cognitive framework rooted in neuroscience and genetics. Cognition is embedded into an ever-developing structure modified by experiences, including the outcomes of environment influencing behaviors. The key constraint of cognition is that the brain can handle only 7±2 relevant variables at a time, whereas sensory variables, i.e., the number of sensory neurons is orders of magnitude larger. As a result, (a) the extraction, (b) the encoding, and (c) the capability for the efficient cognitive manipulation of the relevant variables, and (d) the compensatory mechanisms that counteract computational delays of the distributed components are critical. We outline our theoretical model to describe a Cartesian Factor (CF) forming, autoencoder-like cognitive mechanism which breaks combinatorial explosion and is accelerated by internal reinforcing machineries and discuss the neural processes that support CF formation. Impairments in any of these aspects may disrupt learning, cognitive manipulation, decisions on interactions, and execution of decisions. We suggest that social interactions are the most susceptible to combinations of diverse small impairments and can be spoiled in many ways that pile up. Comorbidity is experienced, if any of the many potential impairments is relatively strong. We consider component spoiling impairments as the basic colors of autism, whereas the combinations of individual impairments make the palette of autism. We put forth arguments on the possibility of dissociating the different main elements of the impairments that can appear together. For example, impairments of generalization (domain general learning) and impairments of dealing with many variable problems, such as social situations may appear independently and may mutually enhance their impacts. We also consider mechanisms that may lead to protection.

Audio-visual combination of syllables involves time-sensitive dynamics following from fusion failure

In face-to-face communication, audio-visual (AV) stimuli can be fused, combined or perceived as mismatching. While the left superior temporal sulcus (STS) is presumably the locus of AV integration, the process leading to combination is unknown. Based on previous modelling work, we hypothesize that combination results from a complex dynamic originating in a failure to integrate AV inputs, followed by a reconstruction of the most plausible AV sequence. In two different behavioural tasks and one MEG experiment, we observed that combination is more time demanding than fusion. Using time-/source-resolved human MEG analyses with linear and dynamic causal models, we show that both fusion and combination involve early detection of AV incongruence in the STS, whereas combination is further associated with enhanced activity of AV asynchrony-sensitive regions (auditory and inferior frontal cortices). Based on neural signal decoding, we finally show that only combination can be decoded from the IFG activity and that combination is decoded later than fusion in the STS. These results indicate that the AV speech integration outcome primarily depends on whether the STS converges or not onto an existing multimodal syllable representation, and that combination results from subsequent temporal processing, presumably the off-line re-ordering of incongruent AV stimuli.

Physical Activity Predicts Population-Level Age-Related Differences in Frontal White Matter

Physical activity has positive effects on brain health and cognitive function throughout the life span. Thus far, few studies have examined the effects of physical activity on white matter microstructure and psychomotor speed within the same, population-based sample (critical if conclusions are to extend to the wider population). Here, using diffusion tensor imaging and a simple reaction time task within a relatively large population-derived sample (N = 399; 18–87 years) from the Cambridge Centre for Ageing and Neuroscience (Cam-CAN), we demonstrate that physical activity mediates the effect of age on white matter integrity, measured with fractional anisotropy. Higher self-reported daily physical activity was associated with greater preservation of white matter in several frontal tracts, including the genu of corpus callosum, uncinate fasciculus, external capsule, and anterior limb of the internal capsule. We also show that the age-related slowing is mediated by white matter integrity in the genu. Our findings contribute to a growing body of work, suggesting that a physically active lifestyle may protect against age-related structural disconnection and slowing.

Functional and structural correlates of the preterm infant's brain: relating developmental changes of auditory evoked responses to structural maturation

Functional responses recorded during the last trimester of gestation reveal that human sensory activity begins before birth, allowing the brain to process the external environment. Along with the maturation of the brain, new cognitive skills emerge in the human infant's brain. The development of non-invasive techniques provides the opportunity to study the relationship between brain structural maturation and cognitive development in vivo. Here, we aimed to relate developmental changes of the latency of cortical auditory evoked potentials (CAEPs) to a structural maturation index, presumed to be representative of myelination. CAEPs to syllables were recorded in 17 preterm neonates with a mean recording age of 30.5 weeks gestational age (28.4-32.2 wGA). The latency of the first peak of the global field power (GFP) was considered the functional feature of interest to be examined for correlation with age and the structural maturation index extracted from brain atlases of the corresponding term age. GFP latency significantly decreased with age (R² = 0.311, p = 0.02). Structural maturation indices, calculated as the mean values of T1w/T2w image intensities, were extracted for various brain regions. We observed significant correlations between the maturation indices of the auditory-involved areas and the latency of the GFP first-peak, as well as age. In hierarchical models, neither the structural maturation index nor age contributed to significant additional variance in the GFP first-peak latency after accounting for the variance associated with the other parameter.

Predicting Neural Response Latency of the Human Early Visual Cortex from MRI-Based Tissue Measurements of the Optic Radiation

Although the non-invasive measurement of visually evoked responses has been extensively studied, the structural basis of variabilities in latency in healthy humans is not well understood. We investigated how tissue properties of optic radiation could predict interindividual variability in the latency of the initial visually evoked component (C1), which may originate from the primary visual cortex (V1). We collected C1 peak latency data using magnetoencephalography (MEG) and checkerboard stimuli, and multiple structural magnetic resonance imaging (MRI) data from 20 healthy subjects. While we varied the contrast and position of the stimuli, the C1 measurement was most reliable when high-contrast stimuli were presented to the lower visual field (LVF). We then attempted to predict interindividual variability in C1 peak latency in this stimulus condition with a multiple regression model using MRI parameters along the optic radiation. We found that this model could predict >20% of variance in C1 latency, when the data were averaged across the hemispheres. The model using the corticospinal tract did not predict variability in C1 latency, suggesting that there is no evidence for generalization to a non-visual tract. In conclusion, our results suggest that the variability in neural latencies in the early visual cortex in healthy subjects can be partly explained by tissue properties along the optic radiation. We discuss the challenges of predicting neural latency using current structural neuroimaging methods and other factors that may explain interindividual variance in neural latency.

Model-Predicted Balance Between Neural Excitation and Inhibition Was Maintained Despite of Age-Related Decline in Sensory Evoked Local Field Potential in Rat Barrel Cortex

The balance between neural excitation and inhibition has been shown to be crucial for normal brain function. However, it is unclear whether this balance is maintained through healthy aging. This study investigated the effect of aging on the temporal dynamics of the somatosensory evoked local field potential (LFP) in rats and tested the hypothesis that excitatory and inhibitory post-synaptic activities remain balanced during the aging process. The LFP signal was obtained from the barrel cortex of three different age groups of anesthetized rats (pre-adolescence: 4–6 weeks, young adult: 2–3 months, middle-aged adult: 10–20 months) under whisker pad stimulation. To confirm our previous finding that the initial segment of the evoked LFP was solely associated with excitatory post-synaptic activity, we micro-injected gabazine into the barrel cortex to block inhibition while LFP was collected continuously under the same stimulus condition. As expected, the initial slope of the evoked LFP in the granular layer was unaffected by gabazine injection. We subsequently estimated the excitatory and inhibitory post-synaptic activities through a balanced model of the LFP with delayed inhibition as an explicit constraint, and calculated the amplitude ratio of inhibition to excitation. We found an age-dependent slowing of the temporal dynamics in the somatosensory-evoked post-synaptic activity, as well as a significant age-related decrease in the amplitude of the excitatory component and a decreasing trend in the amplitude of the inhibitory component. Furthermore, the delay of inhibition with respect to excitation was significantly increased with age, but the amplitude ratio was maintained. Our findings suggest that aging reduces the amplitude of neural responses, but the balance between sensory evoked excitatory and inhibitory post-synaptic activities is maintained to support normal brain function during healthy aging. Further whole cell patch clamp experiments will be needed to confirm or refute these findings by measuring sensory evoked synaptic excitatory and inhibitory activities in vivo during the normal aging process.

Combining magnetoencephalography with magnetic resonance imaging enhances learning of surrogate-biomarkers

Electrophysiological methods, that is M/EEG, provide unique views into brain health. Yet, when building predictive models from brain data, it is often unclear how electrophysiology should be combined with other neuroimaging methods. Information can be redundant, useful common representations of multimodal data may not be obvious and multimodal data collection can be medically contraindicated, which reduces applicability. Here, we propose a multimodal model to robustly combine MEG, MRI and fMRI for prediction. We focus on age prediction as a surrogate biomarker in 674 subjects from the Cam-CAN dataset. Strikingly, MEG, fMRI and MRI showed additive effects supporting distinct brain-behavior associations. Moreover, the contribution of MEG was best explained by cortical power spectra between 8 and 30 Hz. Finally, we demonstrate that the model preserves benefits of stacking when some data is missing. The proposed framework, hence, enables multimodal learning for a wide range of biomarkers from diverse types of brain signals.

Central auditory processing in adults with chronic stroke without hearing loss: A magnetoencephalography study

OBJECTIVE

Stroke lesions in non-auditory areas may affect higher-order central auditory processing. We sought to characterize auditory functions in chronic stroke survivors with unilateral arm/hand impairment using auditory evoked responses (AERs) with lesion and perception metrics.

METHODS

The AERs in 29 stroke survivors and 14 controls were recorded with single tones, active and passive frequency-oddballs, and a dual-oddball with pitch-contour and time-interval deviants. Performance in speech-in-noise, mistuning detection, and moving-sound detection was assessed. Relationships between AERs, behaviour, and lesion overlap with functional networks, were examined.

RESULTS

Despite their normal hearing, eight patients showed unilateral AER in the hemisphere ipsilateral to the affected hand with reduced amplitude compared to those with bilateral AERs. Both groups showed increasing attenuation of later components. Hemispheric asymmetry of AER sources was reduced in bilateral-AER patients. The N1 wave (100 ms latency) and P2 (200 ms) were delayed in individuals with lesions in the basal-ganglia and white-matter, while lesions in the attention network reduced the frequency-MMN (mismatch negativity) responses and increased the pitch-contour P3a response. Patients' impaired speech-in-noise perception was explained by AER measures and frequency-deviant detection performance with multiple regression.

CONCLUSION

AERs reflect disruption of auditory functions due to damage outside of temporal lobe, and further explain complexity of neural mechanisms underlying higher-order auditory perception.

SIGNIFICANCE

Stroke survivors without obvious hearing problems may benefit from rehabilitation for central auditory processing.

Anatomo-functional correlates of auditory development in infancy

Infant brain development incorporates several intermingled mechanisms leading to intense and asynchronous maturation across cerebral networks and functional modalities. Combining electroencephalography (EEG) and diffusion magnetic resonance imaging (MRI), previous studies in the visual modality showed that the functional maturation of the event-related potentials (ERP) during the first postnatal semester relates to structural changes in the corresponding white matter pathways. Here investigated similar issues in the auditory modality. We measured ERPs to syllables in 1- to 6-month-old infants and related them to the maturational properties of underlying neural substrates measured with diffusion tensor imaging (DTI). We first observed a decrease in the latency of the auditory P2, and in the diffusivities in the auditory tracts and perisylvian regions with age. Secondly, we highlighted some of the early functional and structural substrates of lateralization. Contralateral responses to monoaural syllables were stronger and faster than ipsilateral responses, particularly in the left hemisphere. Besides, the acoustic radiations, arcuate fasciculus, middle temporal and angular gyri showed DTI asymmetries with a more complex and advanced microstructure in the left hemisphere, whereas the reverse was observed for the inferior frontal and superior temporal gyri. Finally, after accounting for the age-related variance, we correlated the inter-individual variability in P2 responses and in the microstructural properties of callosal fibers and inferior frontal regions. This study combining dedicated EEG and MRI approaches in infants highlights the complex relation between the functional responses to auditory stimuli and the maturational properties of the corresponding neural network.

Disentangling the Effects of Processing Speed on the Association between Age Differences and Fluid Intelligence

Several studies have demonstrated that individual differences in processing speed fully mediate the association between age and intelligence, whereas the association between processing speed and intelligence cannot be explained by age differences. Because measures of processing speed reflect a plethora of cognitive and motivational processes, it cannot be determined which specific processes give rise to this mediation effect. This makes it hard to decide whether these processes should be conceived of as a cause or an indicator of cognitive aging. In the present study, we addressed this question by using a neurocognitive psychometrics approach to decompose the association between age differences and fluid intelligence. Reanalyzing data from two previously published datasets containing 223 participants between 18 and 61 years, we investigated whether individual differences in diffusion model parameters and in ERP latencies associated with higher-order attentional processing explained the association between age differences and fluid intelligence. We demonstrate that individual differences in the speed of non-decisional processes such as encoding, response preparation, and response execution, and individual differences in latencies of ERP components associated with higher-order cognitive processes explained the negative association between age differences and fluid intelligence. Because both parameters jointly accounted for the association between age differences and fluid intelligence, age-related differences in both parameters may reflect age-related differences in anterior brain regions associated with response planning that are prone to be affected by age-related changes. Conversely, age differences did not account for the association between processing speed and fluid intelligence. Our results suggest that the relationship between age differences and fluid intelligence is multifactorially determined.

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.

Cognitive and White-Matter Compartment Models Reveal Selective Relations between Corticospinal Tract Microstructure and Simple Reaction Time

The speed of motor reaction to an external stimulus varies substantially between individuals and is slowed in aging. However, the neuroanatomical origins of interindividual variability in reaction time (RT) remain unclear. Here, we combined a cognitive model of RT and a biophysical compartment model of diffusion-weighted MRI (DWI) to characterize the relationship between RT and microstructure of the corticospinal tract (CST) and the optic radiation (OR), the primary motor output and visual input pathways associated with visual-motor responses. We fitted an accumulator model of RT to 46 female human participants' behavioral performance in a simple reaction time task. The non-decision time parameter (T _er) derived from the model was used to account for the latencies of stimulus encoding and action initiation. From multi-shell DWI data, we quantified tissue microstructure of the CST and OR with the neurite orientation dispersion and density imaging (NODDI) model as well as the conventional diffusion tensor imaging model. Using novel skeletonization and segmentation approaches, we showed that DWI-based microstructure metrics varied substantially along CST and OR. The T _er of individual participants was negatively correlated with the NODDI measure of the neurite density in the bilateral superior CST. Further, we found no significant correlation between the microstructural measures and mean RT. Thus, our findings suggest a link between interindividual differences in sensorimotor speed and selective microstructural properties in white-matter tracts.SIGNIFICANCE STATEMENT How does our brain structure contribute to our speed to react? Here, we provided anatomically specific evidence that interindividual differences in response speed is associated with white-matter microstructure. Using a cognitive model of reaction time (RT), we estimated the non-decision time, as an index of the latencies of stimulus encoding and action initiation, during a simple reaction time task. Using an advanced microstructural model for diffusion MRI, we estimated the tissue properties and their variations along the corticospinal tract and optic radiation. We found significant location-specific correlations between the microstructural measures and the model-derived parameter of non-decision time but not mean RT. These results highlight the neuroanatomical signature of interindividual variability in response speed along the sensorimotor pathways.

Age Related Decline in Cortical Multifocal Flash VEP: Latency Increases Shown to Be Predominately Magnocellular

As the visual system ages, flicker sensitivity decreases and the latencies of cortical visual evoked potentials (VEP) increase. However, the extent to which these effects reflect age-related changes in the magnocellular (M) and or parvocellular (P) pathways remain unclear. Here, we investigated the relation between flicker fusion frequencies and VEP non-linearities induced by rapid stimulation, as a function of age over 6 decades. The approach, using Wiener kernel analysis of multifocal flash (mf)VEP, allows the extraction of signatures of both M and P processing and hence establishing a neural basis of the known decline in flicker fusion threshold. We predicted that, in a sample of 86 participants, age would be associated with a latency increase in early mfVEP response components and that flicker fusion thresholds, for both low and high contrast stimuli, would relate to the temporal efficiency of the M-generated VEP component amplitudes. As expected, flicker fusion frequency reduced with age, while latencies of early second order peaks of the mfVEP increased with age, but M temporal efficiency (amplitude ratio of first to second order peaks) was not strongly age-related. The steepest increases in latency were associated with the M dominated K2.1 (second order first slice) N70 components recorded at low and high contrast (6.7 and 5.9 ms/decade, respectively). Interestingly, significant age-related latency shifts were not observed in the first order responses. Significant decreases in amplitude were found in multiple first and second order components up to 30 years of age, after which they remained relatively constant. Thus, aging and decline in visual function appears to be most closely related to the response latencies of non-linearities generated by the M pathway.

Consistent pre-stimulus influences on auditory perception across the lifespan

As we get older, perception in cluttered environments becomes increasingly difficult as a result of changes in peripheral and central neural processes. Given the aging society, it is important to understand the neural mechanisms constraining perception in the elderly. In young participants, the state of rhythmic brain activity prior to a stimulus has been shown to modulate the neural encoding and perceptual impact of this stimulus - yet it remains unclear whether, and if so, how, the perceptual relevance of pre-stimulus activity changes with age. Using the auditory system as a model, we recorded EEG activity during a frequency discrimination task from younger and older human listeners. By combining single-trial EEG decoding with linear modelling we demonstrate consistent statistical relations between pre-stimulus power and the encoding of sensory evidence in short-latency EEG components, and more variable relations between pre-stimulus phase and subjects' decisions in longer-latency components. At the same time, we observed a significant slowing of auditory evoked responses and a flattening of the overall EEG frequency spectrum in the older listeners. Our results point to mechanistically consistent relations between rhythmic brain activity and sensory encoding that emerge despite changes in neural response latencies and the relative amplitude of rhythmic brain activity with age.

BOLD hemodynamic response function changes significantly with healthy aging

Functional magnetic resonance imaging (fMRI) has been used to infer age-differences in neural activity from the hemodynamic response function (HRF) that characterizes the blood-oxygen-level-dependent (BOLD) signal over time. BOLD literature in healthy aging lacks consensus in age-related HRF changes, the nature of those changes, and their implications for measurement of age differences in brain function. Between-study discrepancies could be due to small sample sizes, analysis techniques, and/or physiologic mechanisms. We hypothesize that, with large sample sizes and minimal analysis assumptions, age-related changes in HRF parameters could reflect alterations in one or more components of the neural-vascular coupling system. To assess HRF changes in healthy aging, we analyzed the large population-derived dataset from the Cambridge Center for Aging and Neuroscience (CamCAN) study (Shafto et al., 2014). During scanning, 74 younger (18-30 years of age) and 173 older participants (54-74 years of age) viewed two checkerboards to the left and right of a central fixation point, simultaneously heard a binaural tone, and responded via right index finger button-press. To assess differences in the shape of the HRF between younger and older groups, HRFs were estimated using FMRIB's Linear Optimal Basis Sets (FLOBS) to minimize a priori shape assumptions. Group mean HRFs were different between younger and older groups in auditory, visual, and motor cortices. Specifically, we observed increased time-to-peak and decreased peak amplitude in older compared to younger adults in auditory, visual, and motor cortices. Changes in the shape and timing of the HRF in healthy aging, in the absence of performance differences, support our hypothesis of age-related changes in the neural-vascular coupling system beyond neural activity alone. More precise interpretations of HRF age-differences can be formulated once these physiologic factors are disentangled and measured separately.

Strong and specific associations between cardiovascular risk factors and white matter micro- and macrostructure in healthy aging

Cardiovascular health declines with age, increasing the risk of hypertension and elevated heart rate in middle and old age. Here, we used multivariate techniques to investigate the associations between cardiovascular health (diastolic blood pressure, systolic blood pressure, and heart rate) and white matter macrostructure (lesion volume and number) and microstructure (as measured by diffusion-weighted imaging) in the cross-sectional, population-based Cam-CAN cohort (N = 667, aged 18–88). We found that cardiovascular health and age made approximately similar contributions to white matter health and explained up to 56% of variance therein. Lower diastolic blood pressure, higher systolic blood pressure, and higher heart rate were each strongly, and independently, associated with white matter abnormalities on all indices. Body mass and exercise were associated with white matter health, both directly and indirectly via cardiovascular health. These results highlight the importance of cardiovascular risk factors for white matter health across the adult lifespan and suggest that systolic blood pressure, diastolic blood pressure, and heart rate affect white matter health via separate mechanisms.

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Cardiovascular health is related to white matter lesion burden and diffusivity.

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Low diastolic pressure, high systolic pressure, and higher heart rate contribute independently.

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Cardiovascular health and age explain up to 56% of variance in white matter health.

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The uncinate fasciculus, inferior fronto-occipital fasciculus, and forceps minor show most sensitivity.

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Lower BMI and more exercise may have protective effects.

Over-representation of speech in older adults originates from early response in higher order auditory cortex

Previous research has found that, paradoxically, while older adults have more difficulty comprehending speech in challenging circumstances than younger adults, their brain responses track the envelope of the acoustic signal more robustly. Here we investigate this puzzle by using magnetoencephalography (MEG) source localization to determine the anatomical origin of this difference. Our results indicate that this robust tracking in older adults does not arise merely from having the same responses as younger adults but with larger amplitudes; instead, they recruit additional regions, inferior to core auditory cortex, with a short latency of ~30 ms relative to the acoustic signal.

Choice of Magnetometers and Gradiometers after Signal Space Separation

BACKGROUND

Modern Elekta Neuromag MEG devices include 102 sensor triplets containing one magnetometer and two planar gradiometers. The first processing step is often a signal space separation (SSS), which provides a powerful noise reduction. A question commonly raised by researchers and reviewers relates to which data should be employed in analyses: (1) magnetometers only, (2) gradiometers only, (3) magnetometers and gradiometers together. The MEG community is currently divided with regard to the proper answer.

METHODS

First, we provide theoretical evidence that both gradiometers and magnetometers result from the backprojection of the same SSS components. Then, we compare resting state and task-related sensor and source estimations from magnetometers and gradiometers in real MEG recordings before and after SSS.

RESULTS

SSS introduced a strong increase in the similarity between source time series derived from magnetometers and gradiometers (r² = 0.3-0.8 before SSS and r² > 0.80 after SSS). After SSS, resting state power spectrum and functional connectivity, as well as visual evoked responses, derived from both magnetometers and gradiometers were highly similar (Intraclass Correlation Coefficient > 0.8, r² > 0.8).

CONCLUSIONS

After SSS, magnetometer and gradiometer data are estimated from a single set of SSS components (usually ≤ 80). Equivalent results can be obtained with both sensor types in typical MEG experiments.