The effect of head motion on brain age prediction using deep convolutional neural networks.

Deep learning can be used effectively to predict participants' age from brain magnetic resonance imaging (MRI) data, and a growing body of evidence suggests that the difference between predicted and chronological age-referred to as brain-predicted age difference (brain-PAD)-is related to various neurological and neuropsychiatric disease states. A crucial aspect of the applicability of brain-PAD as a biomarker of individual brain health is whether and how brain-predicted age is affected by MR image artifacts commonly encountered in clinical settings. To investigate this issue, we trained and validated two different 3D convolutional neural network architectures (CNNs) from scratch and tested the models on a separate dataset consisting of motion-free and motion-corrupted T1-weighted MRI scans from the same participants, the quality of which were rated by neuroradiologists from a clinical diagnostic point of view. Our results revealed a systematic increase in brain-PAD with worsening image quality for both models. This effect was also observed for images that were deemed usable from a clinical perspective, with brains appearing older in medium than in good quality images. These findings were also supported by significant associations found between the brain-PAD and standard image quality metrics indicating larger brain-PAD for lower-quality images. Our results demonstrate a spurious effect of advanced brain aging as a result of head motion and underline the importance of controlling for image quality when using brain-predicted age based on structural neuroimaging data as a proxy measure for brain health.

Amygdala Volume is Associated with ADHD Risk and Severity Beyond Comorbidities in Adolescents: Clinical Testing of Brain Chart Reference Standards.

Understanding atypicalities in ADHD brain correlates is a step towards better understanding ADHD etiology. Efforts to map atypicalities at the level of brain structure have been hindered by the absence of normative reference standards. Recent publication of brain charts allows for assessment of individual variation relative to age- and sex-adjusted reference standards and thus estimation not only of case-control differences but also of intraindividual prediction. METHODS: Aim was to examine, whether brain charts can be applied in a sample of adolescents (N = 140, 38% female) to determine whether atypical brain subcortical and total volumes are associated with ADHD at-risk status and severity of parent-rated symptoms, accounting for self-rated anxiety and depression, and parent-rated oppositional defiant disorder (ODD) as well as motion. RESULTS: Smaller bilateral amygdala volume was associated with ADHD at-risk status, beyond effects of comorbidities and motion, and smaller bilateral amygdala volume was associated with inattention and hyperactivity/impulsivity, beyond effects of comorbidities except for ODD symptoms, and motion. CONCLUSIONS: Individual differences in amygdala volume meaningfully add to estimating ADHD risk and severity. Conceptually, amygdalar involvement is consistent with behavioral and functional imaging data on atypical reinforcement sensitivity as a marker of ADHD-related risk. Methodologically, results show that brain chart reference standards can be applied to address clinically informative, focused and specific questions.

Study protocol of the Hungarian Longitudinal Study of Healthy Brain Aging (HuBA).

Background and purpose:

Neuro­cog­nitive aging and the associated brain diseases impose a major social and economic burden. Therefore, substantial efforts have been put into revealing the lifestyle, the neurobiological and the genetic underpinnings of healthy neurocognitive aging. However, these studies take place almost exclusively in a limited number of highly-developed countries. Thus, it is an important open question to what extent their findings may generalize to neurocognitive aging in other, not yet investigated regions. The purpose of the Hungarian Longitudinal Study of Healthy Brain Aging (HuBA) is to collect multi-modal longitudinal data on healthy neurocognitive aging to address the data gap in this field in Central and Eastern Europe.

We adapted the Australian Ima­ging, Biomarkers and Lifestyle (AIBL) study of aging study protocol to local circumstances and collected demographic, lifestyle, men­tal and physical health, medication and medical history related information as well as re­cor­ded a series of magnetic resonance imaging (MRI) data. In addition, participants were al­so offered to participate in the collection of blood samples to assess circulating in­flam­matory biomarkers as well as a sleep study aimed at evaluating the general sleep quality based on multi-day collection of subjective sleep questionnaires and whole-night elec­troencephalographic (EEG) data.

Baseline data collection has al­ready been accomplished for more than a hundred participants and data collection in the se­cond
session is on the way. The collected data might reveal specific local trends or could also indicate the generalizability of previous findings. Moreover, as the HuBA protocol al­so offers a sleep study designed for tho­rough characterization of participants’ sleep quality and related factors, our extended multi-modal dataset might provide a base for incorporating these measures into healthy and clinical aging research. 

Besides its straightforward na­tional benefits in terms of health ex­pen­di­ture, we hope that this Hungarian initiative could provide results valid for the whole Cent­ral and Eastern European region and could also promote aging and Alzheimer’s disease research in these countries.

Automatic brain MRI motion artifact detection based on end-to-end deep learning is similarly effective as traditional machine learning trained on image quality metrics.

Head motion artifacts in magnetic resonance imaging (MRI) are an important confounding factor concerning brain research as well as clinical practice. For this reason, several machine learning-based methods have been developed for the automatic quality control of structural MRI scans. Deep learning offers a promising solution to this problem, however, given its data-hungry nature and the scarcity of expert-annotated datasets, its advantage over traditional machine learning methods in identifying motion-corrupted brain scans is yet to be determined. In the present study, we investigated the relative advantage of the two methods in structural MRI quality control. To this end, we collected publicly available T1-weighted images and scanned subjects in our own lab under conventional and active head motion conditions. The quality of the images was rated by a team of radiologists from the point of view of clinical diagnostic use. We present a relatively simple, lightweight 3D convolutional neural network trained in an end-to-end manner that achieved a test set (N = 411) balanced accuracy of 94.41% in classifying brain scans into clinically usable or unusable categories. A support vector machine trained on image quality metrics achieved a balanced accuracy of 88.44% on the same test set. Statistical comparison of the two models yielded no significant difference in terms of confusion matrices, error rates, or receiver operating characteristic curves. Our results suggest that these machine learning methods are similarly effective in identifying severe motion artifacts in brain MRI scans, and underline the efficacy of end-to-end deep learning-based systems in brain MRI quality control, allowing the rapid evaluation of diagnostic utility without the need for elaborate image pre-processing.

Lateralization of orthographic processing in fixed-gaze and natural reading conditions.

Lateralized processing of orthographic information is a hallmark of proficient reading. However, how this finding obtained for fixed-gaze processing of orthographic stimuli translates to ecologically valid reading conditions remained to be clarified. To address this shortcoming, here we assessed the lateralization of early orthographic processing in fixed-gaze and natural reading conditions using concurrent eye-tracking and EEG data recorded from young adults without reading difficulties. Sensor-space analyses confirmed the well-known left-lateralized negative-going deflection of fixed-gaze EEG activity throughout the period of early orthographic processing. At the same time, fixation-related EEG activity exhibited left-lateralized followed by right-lateralized processing of text stimuli during natural reading. A strong positive relationship was found between the early leftward lateralization in fixed-gaze and natural reading conditions. Using source-space analyses, early left-lateralized brain activity was obtained in lateraloccipital and posterior ventral occipito-temporal cortices reflecting letter-level processing in both conditions. In addition, in the same time interval, left-lateralized source activity was found also in premotor and parietal brain regions during natural reading. While brain activity remained left-lateralized in later stages representing word-level processing in posterior and middle ventral temporal regions in the fixed-gaze condition, fixation-related source activity became stronger in the right hemisphere in medial and more anterior ventral temporal brain regions indicating higher-level processing of orthographic information. Although our results show a strong positive relationship between the lateralization of letter-level processing in the two reading modes and suggest lateralized brain activity as a general marker for processing of orthographic information, they also clearly indicate the need for reading research in ecologically valid conditions to identify the neural basis of visuospatial attentional, oculomotor and higher-level processes specific to natural reading.

Movement-related artefacts (MR-ART) dataset of matched motion-corrupted and clean structural MRI brain scans.

Magnetic Resonance Imaging (MRI) provides a unique opportunity to investigate neural changes in healthy and clinical conditions. Its large inherent susceptibility to motion, however, often confounds the measurement. Approaches assessing, correcting, or preventing motion corruption of MRI measurements are under active development, and such efforts can greatly benefit from carefully controlled datasets. We present a unique dataset of structural brain MRI images collected from 148 healthy adults which includes both motion-free and motion-affected data acquired from the same participants. This matched dataset allows direct evaluation of motion artefacts, their impact on derived data, and testing approaches to correct for them. Our dataset further stands out by containing images with different levels of motion artefacts from the same participants, is enriched with expert scoring characterizing the image quality from a clinical point of view and is also complemented with standard image quality metrics obtained from MRIQC. The goal of the dataset is to raise awareness of the issue and provide a useful resource to assess and improve current motion correction approaches.

Lateralization of early orthographic processing during natural reading is impaired in developmental dyslexia.

Skilled reading requires specialized visual cortical processing of orthographic information and its impairment has been proposed as a potential correlate of compromised reading in dyslexia. However, which stage of orthographic information processing during natural reading is disturbed in dyslexics remains unexplored. Here we addressed this question by simultaneously measuring the eye movements and EEG of dyslexic and control young adults during natural reading. Isolated meaningful sentences were presented at five inter-letter spacing levels spanning the range from minimal to extra-large spacing, and participants were instructed to read the text silently at their own pace. Control participants read faster, performed larger saccades and shorter fixations compared to dyslexics. While reading speed peaked around the default letter spacing, saccade amplitude increased and fixation duration decreased with the increase of letter spacing in both groups. Lateralization of occipito-temporal fixation-related EEG activity (FREA) was found in three consecutive time intervals corresponding to early orthographic processing in control readers. Importantly, the lateralization in the time range of the first negative left occipito-temporal FREA peak was specific for first fixations and exhibited an interaction effect between reading ability and letter spacing. The interaction originated in the significant decrease of FREA lateralization at extra-large compared to default letter spacing in control readers and the lack of lateralization in both letter spacing conditions in the case of dyslexics. These findings suggest that expertise-driven hemispheric functional specialization for early orthographic processing thought to be responsible for letter identity extraction during natural reading is compromised in dyslexia.

Neural basis of distractor resistance during visual working memory maintenance.

Visual working memory representations must be protected from the intervening irrelevant visual input. While it is well known that interference resistance is most challenging when distractors match the prioritised mnemonic information, its neural mechanisms remain poorly understood. Here, we identify two top-down attentional control processes that have opposing effects on distractor resistance. We reveal an early selection negativity in the EEG responses to matching as compared to non-matching distractors, the magnitude of which is negatively associated with behavioural distractor resistance. Additionally, matching distractors lead to reduced post-stimulus alpha power as well as increased fMRI responses in the object-selective visual cortical areas and the inferior frontal gyrus. However, the congruency effect found on the post-stimulus periodic alpha power and the inferior frontal gyrus fMRI responses show a positive association with distractor resistance. These findings suggest that distractor interference is enhanced by proactive memory content-guided selection processes and diminished by reactive allocation of top-down attentional resources to protect memorandum representations within visual cortical areas retaining the most selective mnemonic code.

Topography of Movement-Related Delta and Theta Brain Oscillations.

The aim of this study was to analyse the high density EEG during movement execution guided by visual attention to reveal the detailed topographic distributions of delta and theta oscillations. Twenty right-handed young subjects performed a finger tapping task, paced by a continuously transited repeating visual stimuli. Baseline corrected power of scalp current density transformed EEG was statistically assessed with cluster-based permutation testing. Delta and theta activities revealed differences in their spatial properties at the time of finger tapping execution. Theta synchronization showed a contralateral double activation in the parietal and fronto-central regions, while delta activity appeared in the central contralateral channels. Differences in the spatiotemporal topography between delta and theta activity in the course of movement execution were identified on high density EEG.

Neural entrainment to the beat in multiple frequency bands in 6-7-year-old children.

Entrainment to periodic acoustic stimuli has been found to relate both to the auditory and motor cortices, and it could be influenced by the maturity of these brain regions. However, existing research in this topic provides data about different oscillatory brain activities in different age groups with different musical background. In order to obtain a more coherent picture and examine early manifestations of entrainment, we assessed brain oscillations at multiple time scales (beta: 15-25 Hz, gamma: 28-48 Hz) and in steady state evoked potentials (SS-EPs in short) in 6-7-year-old children with no musical background right at the start of primary school before they learnt to read. Our goal was to exclude the effect of music training and reading, since previous studies have shown that sensorimotor entrainment (movement synchronization to the beat) is related to musical and reading abilities. We found evidence for endogenous anticipatory processing in the gamma band related to meter perception, and stimulus-related frequency specific responses. However, we did not find evidence for an interaction between auditory and motor networks, which suggests that endogenous mechanisms related to auditory processing may mature earlier than those that underlie motor actions, such as sensorimotor synchronization.

The effect of beat frequency on eye movements during free viewing.

External periodic stimuli entrain brain oscillations and affect perception and attention. It has been shown that background music can change oculomotor behavior and facilitate detection of visual objects occurring on the musical beat. However, whether musical beats in different tempi modulate information sampling differently during natural viewing remains to be explored. Here we addressed this question by investigating how listening to naturalistic drum grooves in two different tempi affects eye movements of participants viewing natural scenes on a computer screen. We found that the beat frequency of the drum grooves modulated the rate of eye movements: fixation durations were increased at the lower beat frequency (1.7Hz) as compared to the higher beat frequency (2.4Hz) and no music conditions. Correspondingly, estimated visual sampling frequency decreased as fixation durations increased with lower beat frequency. These results imply that slow musical beats can retard sampling of visual information during natural viewing by increasing fixation durations.

The first independent study on the complex trial protocol version of the P300-based concealed information test: Corroboration of previous findings and highlights on vulnerabilities.

More than a dozen studies of the Complex Trial Protocol (CTP) version of the P300-based Concealed Information Test have been published since its introduction (Rosenfeld et al., 2008), and it has been fairly consistently proven to provide high accuracy and strong resistance to countermeasures (Rosenfeld et al., 2013). However, no independent authors have verified these findings until now. In the present, first independent study, we corroborate the accuracy and countermeasure-resistance of the CTP, when the probe item (critical presented information, e.g., crime detail; P) vs. all irrelevant items (Iall) comparison is used for classifying participants as guilty or innocent, but we also show that the CTP is severely vulnerable to countermeasures, when the P vs. the irrelevant item with the largest P300 responses (Imax) comparison is used. This latter measure can be defeated by creating "oddball" items among the irrelevant items (through targeting them with covert responses), and thereby making their P300 responses statistically indistinguishable from those of the probe item. Practical implications are discussed.

Visual processing during natural reading.

Reading is a unique human ability that plays a pivotal role in the development and functioning of our modern society. However, its neural basis remains poorly understood since previous research was focused on reading words with fixed gaze. Here we developed a methodological framework for single-trial analysis of fixation onset-related EEG activity (FOREA) that enabled us to investigate visual information processing during natural reading. To reveal the effect of reading skills on orthographic processing during natural reading, we measured how altering the configural properties of the written text by modifying inter-letter spacing affects FOREA. We found that orthographic processing is reflected in FOREA in three consecutive time windows (120-175 ms, 230-265 ms, 345-380 ms after fixation onset) and the magnitude of FOREA effects in the two later time intervals showed a close association with the participants' reading speed: FOREA effects were larger in fast than in slow readers. Furthermore, these expertise-driven configural effects were clearly dissociable from the FOREA signatures of visual perceptual processes engaged to handle the increased crowding (155-220 ms) as a result of decreasing letter spacing. Our findings revealed that with increased reading skills orthographic processing becomes more sensitive to the configural properties of the written text.

Object-based attentional selection modulates anticipatory alpha oscillations.

Visual cortical alpha oscillations are involved in attentional gating of incoming visual information. It has been shown that spatial and feature-based attentional selection result in increased alpha oscillations over the cortical regions representing sensory input originating from the unattended visual field and task-irrelevant visual features, respectively. However, whether attentional gating in the case of object based selection is also associated with alpha oscillations has not been investigated before. Here we measured anticipatory electroencephalography (EEG) alpha oscillations while participants were cued to attend to foveal face or word stimuli, the processing of which is known to have right and left hemispheric lateralization, respectively. The results revealed that in the case of simultaneously displayed, overlapping face and word stimuli, attending to the words led to increased power of parieto-occipital alpha oscillations over the right hemisphere as compared to when faces were attended. This object category-specific modulation of the hemispheric lateralization of anticipatory alpha oscillations was maintained during sustained attentional selection of sequentially presented face and word stimuli. These results imply that in the case of object-based attentional selection-similarly to spatial and feature-based attention-gating of visual information processing might involve visual cortical alpha oscillations.

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.

Increased mesiotemporal delta activity characterizes virtual navigation in humans.

Hippocampal theta or rhythmic slow activity (RSA) occurring during exploratory behaviors and rapid-eye-movement (REM) sleep is a characteristic and well-identifiable oscillatory rhythm in animals. In contrast, controversy surrounds the existence and electrophysiological correlates of this activity in humans. Some argue that the human hippocampal theta occurs in short and phasic bursts. On the contrary, our earlier studies provide evidence that REM-dependent mesiotemporal RSA is continuous like in animals but instead of the theta it falls in the delta frequency range. Here we used a virtual navigation task in 24 epilepsy patients implanted with foramen ovale electrodes. EEG was analyzed for 1-Hz wide frequency bins up to 10 Hz according to four conditions: resting, non-learning route-following, acquisition and recall. We found progressively increasing spectral power in frequency bins up the 4 Hz across these conditions. No spectral power increase relative to resting was revealed within the traditional theta band and above in any of the navigation conditions. Thus the affected frequency bins were below the theta band and were similar to those characterizing REM sleep in our previous studies providing further indication that it is delta rather than theta that should be regarded as a human analog of the animal RSA.

Amblyopic deficits in the timing and strength of visual cortical responses to faces.

Behavioral research revealed that object vision is impaired in amblyopia. Nevertheless, neurophysiological research in humans has focused on the amblyopic effects at the earliest stage of visual cortical processing, leaving the question of later, object-specific neural processing deficits unexplored. By measuring event-related potentials (ERPs) to foveal face stimuli we characterized the amblyopic effects on the N170 component, reflecting higher-level structural face processing. Single trial analysis revealed that latencies of the ERP components increased and were more variable in the amblyopic eye compared to the fellow eye both in strabismic and anisometropic patent groups. Moreover, there was an additional delay of N170 relative to the early P1 component over the right hemisphere, which was absent in the fellow eye, suggesting a slower evolution of face specific cortical responses in amblyopia. On the other hand, distribution of single trial N170 peak amplitudes differed between the amblyopic and fellow eye only in the strabismic but not in the anisometropic patients. Furthermore, the amblyopic N170 latency increment but not the amplitude reduction correlated with the interocular differences in visual acuity and fixation stability. We found no difference in the anticipatory neural oscillations between stimulation of the amblyopic and the fellow eye implying that impairment of the neural processes underlying generation of stimulus-driven visual cortical responses might be the primary reason behind the observed amblyopic effects. These findings provide evidence that amblyopic disruption of early visual experience leads to deficits in the strength and timing of higher-level, face specific visual cortical responses, reflected in the N170 component.

Comparison of fractal and power spectral EEG features: effects of topography and sleep stages.

Fractal nature of the human sleep EEG was revealed recently. In the literature there are some attempts to relate fractal features to spectral properties. However, a comprehensive assessment of the relationship between fractal and power spectral measures is still missing. Therefore, in the present study we investigated the relationship of monofractal and multifractal EEG measures (H and ΔD) with relative band powers and spectral edge frequency across different sleep stages and topographic locations. In addition we tested sleep stage classification capability of these measures according to different channels. We found that cross-correlations between fractal and spectral measures as well as between H and ΔD exhibit specific topographic and sleep stage-related characteristics. Best sleep stage classifications were achieved by estimating measure ΔD in temporal EEG channels both at group and individual levels, suggesting that assessing multifractality might be an adequate approach for compact modeling of brain activities.

Spatio-temporal analysis of monofractal and multifractal properties of the human sleep EEG.

Fractality is a common property in nature. It can also be observed in time series representing dynamics of complex processes. Therefore fractal analysis could be a useful tool to describe the dynamics of brain electrical activities in physiological and pathological conditions. In this study, we carried out a spatio-temporal analysis of monofractal and multifractal properties of whole-night sleep EEG recordings. We estimated the Hurst exponent (H) and the range of fractal spectra (dD) in 10 healthy subjects. We found higher H values during NREM4 compared to NREM2 and REM in all electrodes. Measure dD showed an opposite trend. Differences of H and dD between NREM2 and REM reached significancy at circumscribed regions only. Our results contribute to a deeper understanding of the fractal nature of brain electrical activities and may have implications for automatic classification of sleep stages.