Corpus Callosum Abnormalities at Term-Equivalent Age Are Associated with Language Development at 2 Years' Corrected Age in Infants Born Very Preterm.

We studied the effect of microstructural abnormalities in the corpus callosum on language development in 348 infants born very prematurely. We discovered that the fractional anisotropy of the corpus callosum anterior midbody was a significant predictor of standardized language scores at 2 years, independent of clinical and social risk factors.

Structural connectivity at term equivalent age and language in preterm children at 2 years corrected.

We previously reported interhemispheric structural hyperconnectivity bypassing the corpus callosum in children born extremely preterm (<28 weeks) versus term children. This increased connectivity was positively associated with language performance at 4-6 years of age in our prior work. In the present study, we aim to investigate whether this extracallosal connectivity develops in extremely preterm infants at term equivalent age by leveraging a prospective cohort study of 350 very and extremely preterm infants followed longitudinally in the Cincinnati Infant Neurodevelopment Early Prediction Study. For this secondary analysis, we included only children born extremely preterm and without significant brain injury (n = 95). We use higher-order diffusion modelling to assess the degree to which extracallosal pathways are present in extremely preterm infants and predictive of later language scores at 22-26 months corrected age. We compare results obtained from two higher-order diffusion models: generalized q-sampling imaging and constrained spherical deconvolution. Advanced MRI was obtained at term equivalent age (39-44 weeks post-menstrual age). For structural connectometry analysis, we assessed the level of correlation between white matter connectivity at the whole-brain level at term equivalent age and language scores at 2 years corrected age, controlling for post-menstrual age, sex, brain abnormality score and social risk. For our constrained spherical deconvolution analyses, we performed connectivity-based fixel enhancement, using probabilistic tractography to inform statistical testing of the hypothesis that fibre metrics at term equivalent age relate to language scores at 2 years corrected age after adjusting for covariates. Ninety-five infants were extremely preterm with no significant brain injury. Of these, 53 had complete neurodevelopmental and imaging data sets that passed quality control. In the connectometry analyses adjusted for covariates and multiple comparisons (P < 0.05), the following tracks were inversely correlated with language: bilateral cerebellar white matter and middle cerebellar peduncles, bilateral corticospinal tracks, posterior commissure and the posterior inferior fronto-occipital fasciculus. No tracks from the constrained spherical deconvolution/connectivity-based fixel enhancement analyses remained significant after correction for multiple comparisons. Our findings provide critical information about the ontogeny of structural brain networks supporting language in extremely preterm children. Greater connectivity in more posterior tracks that include the cerebellum and connections to the regions of the temporal lobes at term equivalent age appears to be disadvantageous for language development.

Corpus callosum abnormalities at term-equivalent age are associated with language development at two years corrected age in infants born very preterm.

We studied the impact of microstructural abnormalities in the corpus callosum on language development in 348 infants born very prematurely. We discovered that the fractional anisotropy of the corpus callosum anterior midbody was a significant predictor of standardized language scores at two years, independent of clinical and social risk factors.

Diffuse excessive high signal intensity in the preterm brain on advanced MRI represents widespread neuropathology.

Preterm brains commonly exhibit elevated signal intensity in the white matter on T2-weighted MRI at term-equivalent age. This signal, known as diffuse excessive high signal intensity (DEHSI) or diffuse white matter abnormality (DWMA) when quantitatively assessed, is associated with abnormal microstructure on diffusion tensor imaging. However, postmortem data are largely lacking and difficult to obtain, and the pathological significance of DEHSI remains in question. In a cohort of 202 infants born preterm at ≤32 weeks gestational age, we leveraged two newer diffusion MRI models - Constrained Spherical Deconvolution (CSD) and neurite orientation dispersion and density index (NODDI) - to better characterize the macro and microstructural properties of DWMA and inform the ongoing debate around the clinical significance of DWMA. With increasing DWMA volume, fiber density broadly decreased throughout the white matter and fiber cross-section decreased in the major sensorimotor tracts. Neurite orientation dispersion decreased in the centrum semiovale, corona radiata, and temporal lobe. These findings provide insight into DWMA's biological underpinnings and demonstrate that it is a serious pathology.

Acute histologic chorioamnionitis independently and directly increases the risk for brain abnormalities seen on magnetic resonance imaging in very preterm infants.

BACKGROUND: The independent risk for neurodevelopmental impairments attributed to chorioamnionitis in premature infants remains controversial. Delayed brain maturation or injury identified on magnetic resonance imaging at term-equivalent age can be used as a surrogate measure of neurodevelopmental impairments that is less confounded by postdelivery neonatal intensive care unit environmental factors to investigate this relationship more clearly. OBJECTIVE: This study aimed to determine whether preterm infants born with moderate to severe acute histologic chorioamnionitis would have a higher magnetic resonance imaging-determined global brain abnormality score, independent of early premature birth, when compared with preterm infants with no or mild chorioamnionitis. STUDY DESIGN: This was a prospective, multicenter cohort study involving infants born very prematurely ≤32 weeks' gestational age with acute moderate to severe histologic chorioamnionitis, graded using standard histologic criteria. Brain abnormalities were diagnosed and scored using a well-characterized, standardized scoring system captured using a high-resolution 3 Tesla magnetic resonance imaging research magnet. In secondary analyses, total brain volume and 4 magnetic resonance imaging metrics of cortical maturation (cortical surface area, sulcal depth, gyral index, and inner cortical curvature) were calculated using an automated algorithm and correlated with chorioamnionitis. The association of funisitis (any grade) with brain abnormalities was also explored. We investigated if premature birth mediated the relationship between histologic chorioamnionitis and brain abnormality score using mediation analysis. RESULTS: Of 353 very preterm infants, 297 infants had mild or no chorioamnionitis (controls), and 56 were diagnosed with moderate to severe acute histologic chorioamnionitis. The primary outcome brain abnormality score was significantly higher in histologic chorioamnionitis-exposed infants than in the controls (median, 4 vs 7; P<.001). Infants with acute histologic chorioamnionitis had significantly lower brain tissue volume (P=.03) and sulcal depth (P=.04), whereas other morphometric indices did not differ statistically. In the multiple regression analysis, we observed persistent significant relationships between moderate to severe acute histologic chorioamnionitis and brain abnormality scores (ß=2.84; 1.51-4.16; P<.001), total brain volume (P=.03), and sulcal depth (P=.02). Funisitis was also significantly associated with brain abnormality score after adjustment for clinical confounders (P=.005). Mediation analyses demonstrated that 50% of brain abnormalities was an indirect consequence of premature birth, and the remaining 50% was a direct effect of moderate to severe acute histologic chorioamnionitis when compared with preterm infants with no or mild chorioamnionitis exposure. Examining gestational age as a mediator, funisitis did not exert a significant direct effect on brain abnormalities after the significant indirect effects of preterm birth were accounted for. CONCLUSION: Acute histologic chorioamnionitis increases the risk for brain injury and delayed maturation, both directly and indirectly, by inducing premature birth.

Brain microstructural antecedents of visual difficulties in infants born very preterm.

Infants born very preterm (VPT) are at risk of later visual problems. Although neonatal screening can identify ophthalmologic abnormalities, subtle perinatal brain injury and/or delayed brain maturation may be significant contributors to complex visual-behavioral problems. Our aim was to assess the micro and macrostructural antecedents of early visual-behavioral difficulties in VPT infants by using diffusion MRI (dMRI) at term-equivalent age. We prospectively recruited a cohort of 262 VPT infants (≤32 weeks gestational age [GA]) from five neonatal intensive care units. We obtained structural and diffusion MRI at term-equivalent age and administered the Preverbal Visual Assessment (PreViAs) questionnaire to parents at 3-4 months corrected age. We used constrained spherical deconvolution to reconstruct nine white matter tracts of the visual pathways with high reliability and performed fixel-based analysis to derive fiber density (FD), fiber-bundle cross-section (FC), and combined fiber density and cross-section (FDC). In multiple logistic regression analyses, we related these tract metrics to visual-behavioral function. Of 262 infants, 191 had both high-quality dMRI and completed PreViAs, constituting the final cohort: mean (SD) GA was 29.3 (2.4) weeks, 90 (47.1%) were males, and postmenstrual age (PMA) at MRI was 42.8 (1.3) weeks. FD and FC of several tracts were altered in infants with (N = 59) versus those without retinopathy of prematurity (N = 132). FDC of the left posterior thalamic radiations (PTR), left inferior longitudinal fasciculus (ILF), right superior longitudinal fasciculus (SLF), and left inferior fronto-occipital fasciculus (IFOF) were significantly associated with visual attention scores, prior to adjusting for confounders. After adjustment for PMA at MRI, GA, severe retinopathy of prematurity, and total brain volume, FDC of the left PTR, left ILF, and left IFOF remained significantly associated with visual attention. Early visual-behavioral difficulties in VPT infants are preceded by micro and macrostructural abnormalities in several major visual pathways at term-equivalent age.

Association between brain structural network efficiency at term-equivalent age and early development of cerebral palsy in very preterm infants.

Very preterm infants (born at less than 32 weeks gestational age) are at high risk for serious motor impairments, including cerebral palsy (CP). The brain network changes that antecede the early development of CP in infants are not well characterized, and a better understanding may suggest new strategies for risk-stratification at term, which could lead to earlier access to therapies. Graph theoretical methods applied to diffusion MRI-derived brain connectomes may help quantify the organization and information transfer capacity of the preterm brain with greater nuance than overt structural or regional microstructural changes. Our aim was to shed light on the pathophysiology of early CP development, before the occurrence of early intervention therapies and other environmental confounders, to help identify the best early biomarkers of CP risk in VPT infants. In a cohort of 395 very preterm infants, we extracted cortical morphometrics and brain volumes from structural MRI and also applied graph theoretical methods to diffusion MRI connectomes, both acquired at term-equivalent age. Metrics from graph network analysis, especially global efficiency, strength values of the major sensorimotor tracts, and local efficiency of the motor nodes and novel non-motor regions were strongly inversely related to early CP diagnosis. These measures remained significantly associated with CP after correction for common risk factors of motor development, suggesting that metrics of brain network efficiency at term may be sensitive biomarkers for early CP detection. We demonstrate for the first time that in VPT infants, early CP diagnosis is anteceded by decreased brain network segregation in numerous nodes, including motor regions commonly-associated with CP and also novel regions that may partially explain the high rate of cognitive impairments concomitant with CP diagnosis. These advanced MRI biomarkers may help identify the highest risk infants by term-equivalent age, facilitating earlier interventions that are informed by early pathophysiological changes.

Diffuse white matter abnormality in very preterm infants at term reflects reduced brain network efficiency.

Between 50 and 80% of very preterm infants (<32 weeks gestational age) exhibit increased white matter signal intensity on T2-weighted MRI at term-equivalent age, known as diffuse white matter abnormality (DWMA). A few studies have linked DWMA with microstructural abnormalities, but the exact relationship remains poorly understood. We related DWMA extent to graph theory measures of network efficiency at term in a representative cohort of 343 very preterm infants. We performed anatomic and diffusion MRI at term and quantified DWMA volume with our novel, semi-automated algorithm. From diffusion-weighted structural connectomes, we calculated the graph theory metrics local efficiency and clustering coefficient, which measure the ability of groups of nodes to perform specialized processing, and global efficiency, which assesses the ability of brain regions to efficiently combine information. We computed partial correlations between these measures and DWMA volume, adjusted for confounders. Increasing DWMA volume was associated with decreased global efficiency of the entire very preterm brain and decreased local efficiency and clustering coefficient in a variety of regions supporting cognitive, linguistic, and motor function. We show that DWMA is associated with widespread decreased brain network efficiency, suggesting that it is pathologic and likely has adverse developmental consequences.

Early micro- and macrostructure of sensorimotor tracts and development of cerebral palsy in high risk infants.

Infants born very preterm (VPT) are at high risk of motor impairments such as cerebral palsy (CP), and diagnosis can take 2 years. Identifying in vivo determinants of CP could facilitate presymptomatic detection and targeted intervention. Our objectives were to derive micro- and macrostructural measures of sensorimotor white matter tract integrity from diffusion MRI at term-equivalent age, and determine their association with early diagnosis of CP. We enrolled 263 VPT infants (≤32 weeks gestational age) as part of a large prospective cohort study. Diffusion and structural MRI were acquired at term. Following consensus guidelines, we defined early diagnosis of CP based on abnormal structural MRI at term and abnormal neuromotor exam at 3-4 months corrected age. Using Constrained Spherical Deconvolution, we derived a white matter fiber orientation distribution (fOD) for subjects, performed probabilistic whole-brain tractography, and segmented nine sensorimotor tracts of interest. We used the recently developed fixel-based (FB) analysis to compute fiber density (FD), fiber-bundle cross-section (FC), and combined fiber density and cross-section (FDC) for each tract. Of 223 VPT infants with high-quality diffusion MRI data, 14 (6.3%) received an early diagnosis of CP. The cohort's mean (SD) gestational age was 29.4 (2.4) weeks and postmenstrual age at MRI scan was 42.8 (1.3) weeks. FD, FC, and FDC for each sensorimotor tract were significantly associated with early CP diagnosis, with and without adjustment for confounders. Measures of sensorimotor tract integrity enhance our understanding of white matter changes that antecede and potentially contribute to the development of CP in VPT infants.

Microstructural Measures of the Inferior Longitudinal Fasciculus Predict Later Cognitive and Language Development in Infants Born With Extremely Low Birth Weight.

OBJECTIVE: Extremely preterm children are at high risk for adverse neurodevelopmental outcomes. Identifying predictors of discrete developmental outcomes early in life would allow for targeted neuroprotective therapies when neuroplasticity is at its peak. Our goal was to examine whether diffusion magnetic resonance imaging (MRI) metrics of the inferior longitudinal and uncinate fasciculi early in life could predict later cognitive and language outcomes. STUDY DESIGN: In this pilot study, 43 extremely low-birth-weight preterm infants were scanned using diffusion MRI at term-equivalent age. White matter tracts were assessed via diffusion tensor imaging metrics of fractional anisotropy and mean diffusivity. The Language and Cognitive subscale scores of the Bayley Scales of Infant & Toddler Development-III at 18-22 months corrected age were our outcomes of interest. Multiple linear regression models were created to assess diffusion metrics of the inferior longitudinal and uncinate fasciculi as predictors of Bayley scores. We controlled for brain injury score on structural MRI, maternal education, birth weight, and age at MRI scan. RESULTS: Of the 43 infants, 36 infants had high-quality diffusion tensor imaging and returned for developmental testing. The fractional anisotropy of the inferior longitudinal fasciculus was associated with Bayley-III scores in univariate analyses and was an independent predictor of Bayley-III cognitive and language development over and above known predictors in multivariable analyses. CONCLUSIONS: Incorporating new biomarkers such as the fractional anisotropy of the inferior longitudinal fasciculus with structural MRI findings could enhance accuracy of neurodevelopment predictive models. Additional research is needed to validate our findings in a larger cohort.

Prenatal opioid exposure is associated with smaller brain volumes in multiple regions.

BACKGROUND: The impact of prenatal opioid exposure on brain development remains poorly understood. METHODS: We conducted a prospective study of term-born infants with and without prenatal opioid exposure. Structural brain MRI was performed between 40 and 48 weeks postmenstrual age. T2-weighted images were processed using the Developing Human Connectome Project structural pipeline. We compared 63 relative regional brain volumes between groups. RESULTS: Twenty-nine infants with prenatal opioid exposure and 42 unexposed controls were included. The groups had similar demographics, except exposed infants had lower birth weights, more maternal smoking and maternal Hepatitis C, fewer mothers with a college degree, and were more likely non-Hispanic White. After controlling for sex, postmenstrual age at scan, birth weight, and maternal education, exposed infants had significantly smaller relative volumes of the deep gray matter, bilateral thalamic ventrolateral nuclei, bilateral insular white matter, bilateral subthalamic nuclei, brainstem, and cerebrospinal fluid. Exposed infants had larger relative volumes of the right cingulate gyrus white matter and left occipital lobe white matter. CONCLUSIONS: Infants with prenatal opioid exposure had smaller brain volumes in multiple regions compared to controls, with two regions larger in the opioid-exposed group. Further research should focus on the relative contributions of maternal opioids and other exposures. IMPACT: Prenatal opioid exposure is associated with developmental and behavioral consequences, but the direct effects of opioids on the developing human brain are poorly understood. Prior small studies using MRI have shown smaller regional brain volumes in opioid-exposed infants and children. After controlling for covariates, infants with prenatal opioid exposure scanned at 40-48 weeks postmenstrual age had smaller brain volumes in multiple regions compared to controls, with two regions larger in the opioid-exposed group. This adds to the literature showing potential impact of prenatal opioid exposure on the developing brain.

Automated brain morphometric biomarkers from MRI at term predict motor development in very preterm infants.

Very preterm infants are at high risk for motor impairments. Early interventions can improve outcomes in this cohort, but they would be most effective if clinicians could accurately identify the highest-risk infants early. A number of biomarkers for motor development exist, but currently none are sufficiently accurate for early risk-stratification. We prospectively enrolled very preterm (gestational age ≤31 weeks) infants from four level-III NICUs. Structural brain MRI was performed at term-equivalent age. We used a established pipeline to automatically derive brain volumetrics and cortical morphometrics - cortical surface area, sulcal depth, gyrification index, and inner cortical curvature - from structural MRI. We related these objective measures to Bayley-III motor scores (overall, gross, and fine) at two-years corrected age. Lasso regression identified the three best predictive biomarkers for each motor scale from our initial feature set. In multivariable regression, we assessed the independent value of these brain biomarkers, over-and-above known predictors of motor development, to predict motor scores. 75 very preterm infants had high-quality T2-weighted MRI and completed Bayley-III motor testing. All three motor scores were positively associated with regional cortical surface area and subcortical volumes and negatively associated with cortical curvature throughout the majority of brain regions. In multivariable regression modeling, thalamic volume, curvature of the temporal lobe, and curvature of the insula were significant predictors of overall motor development on the Bayley-III, independent of known predictors. Objective brain morphometric biomarkers at term show promise in predicting motor development in very preterm infants.

Early cortical maturation predicts neurodevelopment in very preterm infants.

OBJECTIVE: To evaluate the ability of four objectively defined, cortical maturation features-surface area, gyrification index, sulcal depth and curvature-from structural MRI at term-equivalent age (TEA) to independently predict cognitive and language development at 2 years corrected age in very preterm (VPT) infants. DESIGN: Population-based, prospective cohort study. Structural brain MRI was performed at term, between 40 and 44 weeks postmenstrual age and processed using the developing Human Connectome Project pipeline. SETTING: Multicentre study comprising four regional level III neonatal intensive care units in the Columbus, Ohio region. PATIENTS: 110 VPT infants (gestational age (GA) ≤ 31 weeks). MAIN OUTCOME MEASURES: Cognitive and language scores at 2 years corrected age on the Bayley Scales of Infant and Toddler Development, Third Edition. RESULTS: Of the 94 VPT infants with high-quality T2-weighted MRI scans, 75 infants (80%) returned for Bayley-III testing. Cortical surface area was positively correlated with cognitive and language scores in nearly every brain region. Curvature of the inner cortex was negatively correlated with Bayley scores in the frontal, parietal and temporal lobes. In multivariable regression models, adjusting for GA, sex, socioeconomic status, and injury score on MRI, regional measures of surface area and curvature independently explained more than one-third of the variance in cognitive and language scores at 2 years corrected age in our cohort. CONCLUSIONS: We identified increased cortical curvature at TEA as a new prognostic biomarker of adverse neurodevelopment in very premature infants. When combined with cortical surface area, it enhanced prediction of cognitive and language development. Larger studies are needed to externally validate our findings.

Retinopathy of Prematurity and Bronchopulmonary Dysplasia are Independent Antecedents of Cortical Maturational Abnormalities in Very Preterm Infants.

Very preterm (VPT) infants are at high-risk for neurodevelopmental impairments, however there are few validated biomarkers at term-equivalent age that accurately measure abnormal brain development and predict future impairments. Our objectives were to quantify and contrast cortical features between full-term and VPT infants at term and to associate two key antecedent risk factors, bronchopulmonary dysplasia (BPD) and retinopathy of prematurity (ROP), with cortical maturational changes in VPT infants. We prospectively enrolled a population-based cohort of 110 VPT infants (gestational age ≤31 weeks) and 51 healthy full-term infants (gestational age 38-42 weeks). Structural brain MRI was performed at term. 94 VPT infants and 46 full-term infants with high-quality T2-weighted MRI were analyzed. As compared to full-term infants, VPT infants exhibited significant global cortical maturational abnormalities, including reduced surface area (-5.9%) and gyrification (-6.7%) and increased curvature (5.9%). In multivariable regression controlled for important covariates, BPD was significantly negatively correlated with lobar and global cortical surface area and ROP was significantly negatively correlated with lobar and global sulcal depth in VPT infants. Our cohort of VPT infants exhibited widespread cortical maturation abnormalities by term-equivalent age that were in part anteceded by two of the most potent neonatal diseases, BPD and ROP.

Cortical Spectral Activity and Connectivity during Active and Viewed Arm and Leg Movement.

Active and viewed limb movement activate many similar neural pathways, however, to date most comparison studies have focused on subjects making small, discrete movements of the hands and feet. The purpose of this study was to determine if high-density electroencephalography (EEG) could detect differences in cortical activity and connectivity during active and viewed rhythmic arm and leg movements in humans. Our primary hypothesis was that we would detect similar but weaker electrocortical spectral fluctuations and effective connectivity fluctuations during viewed limb exercise compared to active limb exercise due to the similarities in neural recruitment. A secondary hypothesis was that we would record stronger cortical spectral fluctuations for arm exercise compared to leg exercise, because rhythmic arm exercise would be more dependent on supraspinal control than rhythmic leg exercise. We recorded EEG data while ten young healthy subjects exercised on a recumbent stepper with: (1) both arms and legs, (2) just legs, and (3) just arms. Subjects also viewed video playback of themselves or another individual performing the same exercises. We performed independent component analysis, dipole fitting, spectral analysis, and effective connectivity analysis on the data. Cortical areas comprising the premotor and supplementary motor cortex, the anterior cingulate, the posterior cingulate, and the parietal cortex exhibited significant spectral fluctuations during rhythmic limb exercise. These fluctuations tended to be greater for the arms exercise conditions than for the legs only exercise condition, which suggests that human rhythmic arm movements are under stronger cortical control than rhythmic leg movements. We did not find consistent spectral fluctuations in these areas during the viewed conditions, but effective connectivity fluctuated at harmonics of the exercise frequency during both active and viewed rhythmic limb exercise. The right premotor and supplementary motor cortex drove the network. These results suggest that a similarly interconnected neural network is in operation during active and viewed human rhythmic limb movement.

Independent Component Analysis of Gait-Related Movement Artifact Recorded using EEG Electrodes during Treadmill Walking.

There has been a recent surge in the use of electroencephalography (EEG) as a tool for mobile brain imaging due to its portability and fine time resolution. When EEG is combined with independent component analysis (ICA) and source localization techniques, it can model electrocortical activity as arising from temporally independent signals located in spatially distinct cortical areas. However, for mobile tasks, it is not clear how movement artifacts influence ICA and source localization. We devised a novel method to collect pure movement artifact data (devoid of any electrophysiological signals) with a 256-channel EEG system. We first blocked true electrocortical activity using a silicone swim cap. Over the silicone layer, we placed a simulated scalp with electrical properties similar to real human scalp. We collected EEG movement artifact signals from ten healthy, young subjects wearing this setup as they walked on a treadmill at speeds from 0.4-1.6 m/s. We performed ICA and dipole fitting on the EEG movement artifact data to quantify how accurately these methods would identify the artifact signals as non-neural. ICA and dipole fitting accurately localized 99% of the independent components in non-neural locations or lacked dipolar characteristics. The remaining 1% of sources had locations within the brain volume and low residual variances, but had topographical maps, power spectra, time courses, and event related spectral perturbations typical of non-neural sources. Caution should be exercised when interpreting ICA for data that includes semi-periodic artifacts including artifact arising from human walking. Alternative methods are needed for the identification and separation of movement artifact in mobile EEG signals, especially methods that can be performed in real time. Separating true brain signals from motion artifact could clear the way for EEG brain computer interfaces for assistance during mobile activities, such as walking.

Isolating gait-related movement artifacts in electroencephalography during human walking.

OBJECTIVE: High-density electroencephelography (EEG) can provide an insight into human brain function during real-world activities with walking. Some recent studies have used EEG to characterize brain activity during walking, but the relative contributions of movement artifact and electrocortical activity have been difficult to quantify. We aimed to characterize movement artifact recorded by EEG electrodes at a range of walking speeds and to test the efficacy of artifact removal methods. We also quantified the similarity between movement artifact recorded by EEG electrodes and a head-mounted accelerometer. APPROACH: We used a novel experimental method to isolate and record movement artifact with EEG electrodes during walking. We blocked electrophysiological signals using a nonconductive layer (silicone swim cap) and simulated an electrically conductive scalp on top of the swim cap using a wig coated with conductive gel. We recorded motion artifact EEG data from nine young human subjects walking on a treadmill at speeds from 0.4 to 1.6 m s(-1). We then tested artifact removal methods including moving average and wavelet-based techniques. MAIN RESULTS: Movement artifact recorded with EEG electrodes varied considerably, across speed, subject, and electrode location. The movement artifact measured with EEG electrodes did not correlate well with head acceleration. All of the tested artifact removal methods attenuated low-frequency noise but did not completely remove movement artifact. The spectral power fluctuations in the movement artifact data resembled data from some previously published studies of EEG during walking. SIGNIFICANCE: Our results suggest that EEG data recorded during walking likely contains substantial movement artifact that: cannot be explained by head accelerations; varies across speed, subject, and channel; and cannot be removed using traditional signal processing methods. Future studies should focus on more sophisticated methods for removal of EEG movement artifact to advance the field.

Your brain on speed: cognitive performance of a spatial working memory task is not affected by walking speed.

When humans walk in everyday life, they typically perform a range of cognitive tasks while they are on the move. Past studies examining performance changes in dual cognitive-motor tasks during walking have produced a variety of results. These discrepancies may be related to the type of cognitive task chosen, differences in the walking speeds studied, or lack of controlling for walking speed. The goal of this study was to determine how young, healthy subjects performed a spatial working memory task over a range of walking speeds. We used high-density electroencephalography to determine if electrocortical activity mirrored changes in cognitive performance across speeds. Subjects stood (0.0 m/s) and walked (0.4, 0.8, 1.2, and 1.6 m/s) with and without performing a Brooks spatial working memory task. We hypothesized that performance of the spatial working memory task and the associated electrocortical activity would decrease significantly with walking speed. Across speeds, the spatial working memory task caused subjects to step more widely compared with walking without the task. This is typically a sign that humans are adapting their gait dynamics to increase gait stability. Several cortical areas exhibited power fluctuations time-locked to memory encoding during the cognitive task. In the somatosensory association cortex, alpha power increased prior to stimulus presentation and decreased during memory encoding. There were small significant reductions in theta power in the right superior parietal lobule and the posterior cingulate cortex around memory encoding. However, the subjects did not show a significant change in cognitive task performance or electrocortical activity with walking speed. These findings indicate that in young, healthy subjects walking speed does not affect performance of a spatial working memory task. These subjects can devote adequate cortical resources to spatial cognition when needed, regardless of walking speed.