Inter-individual Differences in Occipital Alpha Oscillations Correlate with White Matter Tissue Properties of the Optic Radiation

Tractometry of Human Visual White Matter Pathways in Health and Disease

Diffusion-weighted MRI (dMRI) provides a unique non-invasive view of human brain tissue properties. The present review article focuses on tractometry analysis methods that use dMRI to assess the properties of brain tissue within the long-range connections comprising brain networks. We focus specifically on the major white matter tracts that convey visual information. These connections are particularly important because vision provides rich information from the environment that supports a large range of daily life activities. Many of the diseases of the visual system are associated with advanced aging, and tractometry of the visual system is particularly important in the modern aging society. We provide an overview of the tractometry analysis pipeline, which includes a primer on dMRI data acquisition, voxelwise model fitting, tractography, recognition of white matter tracts, and calculation of tract tissue property profiles. We then review dMRI-based methods for analyzing visual white matter tracts: the optic nerve, optic tract, optic radiation, forceps major, and vertical occipital fasciculus. For each tract, we review background anatomical knowledge together with recent findings in tractometry studies on these tracts and their properties in relation to visual function and disease. Overall, we find that measurements of the brain's visual white matter are sensitive to a range of disorders and correlate with perceptual abilities. We highlight new and promising analysis methods, as well as some of the current barriers to progress toward integration of these methods into clinical practice. These barriers, such as variability in measurements between protocols and instruments, are targets for future development.

The relationship between alpha power and heart rate variability commonly seen in various mental states

The extensive exploration of the correlation between electroencephalogram (EEG) and heart rate variability (HRV) has yielded inconsistent outcomes, largely attributable to variations in the tasks employed in the studies. The direct relationship between EEG and HRV is further complicated by alpha power, which is susceptible to influences such as mental fatigue and sleepiness. This research endeavors to examine the brain-heart interplay typically observed during periods of music listening and rest. In an effort to mitigate the indirect effects of mental states on alpha power, subjective fatigue and sleepiness were measured during rest, while emotional valence and arousal were evaluated during music listening. Partial correlation analyses unveiled positive associations between occipital alpha2 power (10-12 Hz) and nHF, an indicator of parasympathetic activity, under both music and rest conditions. These findings underscore brain-heart interactions that persist even after the effects of other variables have been accounted for.

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.

Resting EEG power spectra across middle to late life: associations with age, cognition, APOE-ɛ4 carriage, and cardiometabolic burden

We investigated how resting electroencephalography (EEG) measures are associated with risk factors for late-life cognitive impairment and dementia, including age, apolipoprotein E ɛ4 (APOE-ɛ4) carriage, and cardiometabolic burden. Resting EEG was recorded from 86 adults (50-80 years of age). Participants additionally completed the Addenbrooke's Cognitive Examination (ACE) III and had blood drawn to assess APOE-ɛ4 carriage status and cardiometabolic burden. EEG power spectra were decomposed into sources of periodic and aperiodic activity to derive measures of aperiodic component slope and alpha (7-14 Hz) and beta (15-30 Hz) peak power and peak frequency. Alpha and beta peak power measures were corrected for aperiodic activity. The aperiodic component slope was correlated with ACE-III scores but not age. Alpha peak frequency decreased with age. Individuals with higher cardiometabolic burden had lower alpha peak frequencies and lower beta peak power. APOE-ɛ4 carriers had lower beta peak frequencies. Our findings suggest that the slope of the aperiodic component of resting EEG power spectra is more closely associated with measures of cognitive performance rather than chronological age in older adults.

Macromolecular tissue volume mapping of lateral geniculate nucleus subdivisions in living human brains

The lateral geniculate nucleus (LGN) is a key thalamic nucleus in the visual system, which has an important function in relaying retinal visual input to the visual cortex. The human LGN is composed mainly of magnocellular (M) and parvocellular (P) subdivisions, each of which has different stimulus selectivity in neural response properties. Previous studies have discussed the potential relationship between LGN subdivisions and visual disorders based on psychophysical data on specific types of visual stimuli. However, these relationships remain speculative because non-invasive measurements of these subdivisions are difficult due to the small size of the LGN. Here we propose a method to identify these subdivisions by combining two structural MR measures: high-resolution proton-density weighted images and macromolecular tissue volume (MTV) maps. We defined the M and P subdivisions based on MTV fraction data and tested the validity of the definition by (1) comparing the data with that from human histological studies, (2) comparing the data with functional magnetic resonance imaging measurements on stimulus selectivity, and (3) analyzing the test-retest reliability. The findings demonstrated that the spatial organization of the M and P subdivisions was consistent across subjects and in line with LGN subdivisions observed in human histological data. Moreover, the difference in stimulus selectivity between the subdivisions identified using MTV was consistent with previous physiology literature. The definition of the subdivisions based on MTV was shown to be robust over measurements taken on different days. These results suggest that MTV mapping is a promising approach for evaluating the tissue properties of LGN subdivisions in living humans. This method potentially will enable neuroscientific and clinical hypotheses about the human LGN subdivisions to be tested.

Decreased resting-state alpha peak frequency in children and adolescents with fetal alcohol spectrum disorders or prenatal alcohol exposure

Prenatal alcohol exposure (PAE) can result in long-lasting changes to physical, behavioral, and cognitive functioning in children. PAE might result in decreased white matter integrity, corticothalamic tract integrity, and alpha cortical oscillations. Previous investigations of alpha oscillations in PAE/fetal alcohol spectrum disorder (FASD) have focused on average spectral power at specific ages; therefore, little is known about alpha peak frequency (APF) or its developmental trajectory making this research novel. Using resting-state MEG data, APF was determined from parietal/occipital regions in participants with PAE/FASD or typically developing controls (TDC). In total, MEG data from 157 infants, children, and adolescents ranging in age from 6 months to 17 years were used, including 17 individuals with PAE, 61 individuals with an FASD and 84 TDC. In line with our hypothesis, we found that individuals with PAE/FASD had significantly reduced APF relative to TDC. Both age and group were significantly related to APF with differences between TDC and PAE/FASD persisting throughout development. We did not find evidence that sex or socioeconomic status had additional impact on APF. Reduced APF in individuals with an FASD/PAE may represent a long-term deficit and demonstrates the detrimental impact prenatal alcohol exposure can have on neurophysiological processes.

Stress effects on the top-down control of visuospatial attention: Evidence from cue-dependent alpha oscillations

Stress is assumed to inhibit the top-down control of attention and to facilitate bottom-up processing. Evidence from human experiments, however, remains scarce. Previous studies have addressed how stress affects the interplay of bottom-up and top-down mechanisms of attention. A key open question is in how far such effects can actually be attributed to a stress-induced modulation of top-down attention control. We sought to isolate top-down from bottom-up effects by assessing stress effects on anticipatory changes in alpha oscillations that precede stimulus processing. Participants performed in a cued target detection task in which a cue prompted them to covertly shift their attention to left or right screen positions, 20 min after being exposed to the bilateral feet cold pressor test or a warm water control procedure. The stressor led to a substantial increase in cortisol, peaking 20 min post stressor, along with rises in heart rate, blood pressure, and subjective ratings of stress and arousal. As expected, cued attention deployment led to higher alpha power over posterior electrodes contralateral versus ipsilateral to the attended hemifield during the cue-target interval. Importantly, this purely endogenous effect was potentiated by stress, however, significant differences were restricted to the middle of the cue-target interval and thus temporally separated from the appearance of the target. These results indicate that stress does not impair top-down attentional control per se but may introduce a qualitative change modulating the way attention is deployed to meet action goals.

Alpha power during task performance predicts individual language comprehension

Alpha power attenuation during cognitive task performing has been suggested to reflect a process of release of inhibition, increase of excitability, and thereby benefit the improvement of performance. Here, we hypothesized that changes in individual alpha power during the execution of a complex language comprehension task may correlate with the individual performance in that task. We tested this using magnetoencephalography (MEG) recorded during comprehension of German sentences of different syntactic complexity. Results showed that neither the frequency nor the power of the spontaneous oscillatory activity at rest were associated with the individual performance. However, during the execution of a sentences processing task, the individual alpha power attenuation did correlate with individual language comprehension performance. Source reconstruction localized these effects in left temporal-parietal brain regions known to be associated with language processing and their right-hemisphere homologues. Our results support the notion that in-task attenuation of individual alpha power is related to the essential mechanisms of the underlying cognitive processes, rather than merely to general phenomena like attention or vigilance.

Biophysical mechanism underlying compensatory preservation of neural synchrony over the adult lifespan

We propose that the preservation of functional integration, estimated from measures of neural synchrony, is a key objective of neurocompensatory mechanisms associated with healthy human ageing. To support this proposal, we demonstrate how phase-locking at the peak alpha frequency in Magnetoencephalography recordings remains invariant over the lifespan in a large cohort of human participants, aged 18-88 years. Using empirically derived connection topologies from diffusion tensor imaging data, we create an in-silico model of whole-brain alpha dynamics. We show that enhancing inter-areal coupling can cancel the effect of increased axonal transmission delays associated with age-related degeneration of white matter tracts, albeit at slower network frequencies. By deriving analytical solutions for simplified connection topologies, we further establish the theoretical principles underlying compensatory network re-organization. Our findings suggest that frequency slowing with age- frequently observed in the alpha band in diverse populations- may be viewed as an epiphenomenon of the underlying compensatory mechanism.

Analysis of MEG data from healthy participants and whole-brain network modeling suggests that the brain compensates for age-related disruptions in connectivity by slowing down the frequency of neural synchronization.

Theta oscillations shift towards optimal frequency for cognitive control

Cognitive control allows to flexibly guide behaviour in a complex and ever-changing environment. It is supported by theta band (4-7 Hz) neural oscillations that coordinate distant neural populations. However, little is known about the precise neural mechanisms permitting such flexible control. Most research has focused on theta amplitude, showing that it increases when control is needed, but a second essential aspect of theta oscillations, their peak frequency, has mostly been overlooked. Here, using computational modelling and behavioural and electrophysiological recordings, in three independent datasets, we show that theta oscillations adaptively shift towards optimal frequency depending on task demands. We provide evidence that theta frequency balances reliable set-up of task representation and gating of task-relevant sensory and motor information and that this frequency shift predicts behavioural performance. Our study presents a mechanism supporting flexible control and calls for a reevaluation of the mechanistic role of theta oscillations in adaptive behaviour.

Relationship between regional white matter hyperintensities and alpha oscillations in older adults

Aging is associated with increased white matter hyperintensities (WMHs) and with alterations of alpha oscillations (7-13 Hz). However, a crucial question remains, whether changes in alpha oscillations relate to aging per se or whether this relationship is mediated by age-related neuropathology like WMHs. Using a large cohort of cognitively healthy older adults (N = 907, 60-80 years), we assessed relative alpha power, alpha peak frequency, and long-range temporal correlations from resting-state EEG. We further associated these parameters with voxel-wise WMHs from 3T MRI. We found that a higher prevalence of WMHs in the superior and posterior corona radiata as well as in the thalamic radiation was related to elevated alpha power, with the strongest association in the bilateral occipital cortex. In contrast, we observed no significant relation of the WMHs probability with alpha peak frequency and long-range temporal correlations. Finally, higher age was associated with elevated alpha power via total WMH volume. We suggest that an elevated alpha power is a consequence of WMHs affecting a spatial organization of alpha sources.

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.