Minor neurological signs and behavioural function at age 2 years in neonatal hypoxic ischaemic encephalopathy (HIE)

Background: Neurodevelopmental follow-up in Neonatal Hypoxic Ischaemic Encephalopathy (HIE) typically focusses on major neuromotor (cerebral palsy, CP) and severe cognitive impairment. Outcomes in those without major neuromotor impairment are less well explored. Objectives: To examine behavioural, cognitive and neurological outcomes after neonatal HIE, in a clinical cohort of children without CP, at age 2 years. Methods: Clinical routine outcome data from children admitted to a tertiary centre with neonatal HIE for hypothermia treatment between 05/08/09 - 30/05/2016. Children were assessed for neuromotor status – particularly minor neurological signs (MNS), with Bayley Scales of Infant and Toddler Development III (Bayley III) or Ages and Stages Questionnaire-3 (ASQ), Child Behavior Checklist 1.5-5 (CBCL), Quantitative Checklist for Autism in Toddlers (Q-CHAT). Results: Of 107 children, 75.5% had normal neurology, 12.1% CP, 12.1% MNS. Children with CP were excluded from analyses. For those without CP, Bayley-III scores were in the average range for the majority; mild cognitive delay observed in 5%, 4.2% language, 1.3% motor development; severe delay in 1.3% for cognitive, 4.2% for language. More than in the normative population scored in clinical ranges for CBCL externalising, sleep, and other problems. No significant difference was seen for Q-CHAT. Children with MNS were significantly more likely to have impaired Bayley-III scores, parent-reported internalising, sleep, and other problems. Conclusions: In this clinical cohort, the majority of children had favourable outcome at 2 years. However, children with MNS were at risk for cognitive and behavioural difficulties and will benefit from enhanced clinical follow-up and support

Attention-induced deactivations in very low frequency EEG oscillations: differential localisation according to ADHD symptom status

Background: the default-mode network (DMN) is characterised by coherent very low frequency (VLF) brain oscillations. The cognitive significance of this VLF profile remains unclear, partly because of the temporally constrained nature of the blood oxygen-level dependent (BOLD) signal. Previously we have identified a VLF EEG network of scalp locations that shares many features of the DMN. Here we explore the intracranial sources of VLF EEG and examine their overlap with the DMN in adults with high and low ADHD ratings.Methodology/Principal Findings: DC-EEG was recorded using an equidistant 66 channel electrode montage in 25 adult participants with high- and 25 participants with low-ratings of ADHD symptoms during a rest condition and an attention demanding Eriksen task. VLF EEG power was calculated in the VLF band (0.02 to 0.2 Hz) for the rest and task condition and compared for high and low ADHD participants. sLORETA was used to identify brain sources associated with the attention-induced deactivation of VLF EEG power, and to examine these sources in relation to ADHD symptoms. There was significant deactivation of VLF EEG power between the rest and task condition for the whole sample. Using s-LORETA the sources of this deactivation were localised to medial prefrontal regions, posterior cingulate cortex/precuneus and temporal regions. However, deactivation sources were different for high and low ADHD groups: In the low ADHD group attention-induced VLF EEG deactivation was most significant in medial prefrontal regions while for the high ADHD group this deactivation was predominantly localised to the temporal lobes.Conclusions/Significance: attention-induced VLF EEG deactivations have intracranial sources that appear to overlap with those of the DMN. Furthermore, these seem to be related to ADHD symptom status, with high ADHD adults failing to significantly deactivate medial prefrontal regions while at the same time showing significant attenuation of VLF EEG power in temporal lobe

Identifying a distinctive familial frequency band in reaction time fluctuations in ADHD

Objective: Patients with ADHD are typically more variable in their reaction times (RT) than control children. Signal processing analyses have shown that time series RT data of children with ADHD have a distinctive low frequency periodic structure suggestive of a pattern of occasional spontaneous performance lapses. Here we use a fine-grained analysis of spectral power across a broader frequency range to differentiate the periodic qualities of ADHD time series RT data from (a) 1/frequency noise, and (b) control performance. We also assess the familiality of these frequencies by using a proband-sibling design. Method: Seventy-one children with ADHD, one of their siblings, and 50 control participants completed a simple RT task. Power across the RT frequency spectrum was calculated. The frequencies significantly differentiating the two groups were identified. Familiality was assessed in two ways: first, by comparing probands with their unaffected siblings and controls, and, second, by investigating the siblings of neuropsychologically impaired and unimpaired children with ADHD. Results: Analyses converged to highlight the potential importance of the .20–.26 Hz band in differentiating the periodic structure of ADHD RT time series data from both 1/frequency noise and control performance. This frequency band also showed the strongest evidence of familiality. Conclusions: RT performance of children with ADHD had a distinctive periodic structure. The band identified as most differentiating and familial was at a higher frequency than in most previous reports. This highlights the importance of employing tasks with faster interstimulus intervals that will allow a larger portion of the frequency spectrum to be examined

The attenuation of very low frequency brain oscillations in transitions from a rest state to active attention

Background: The default mode interference hypothesis (Sonuga-Barke & Castellanos, 2007) predicts (1) the attenuation of very low frequency oscillations (VLFO; e.g., .05 Hz) in brain activity within the default mode network during the transition from rest to task, and (2) that failures to attenuate in this way will lead to an increased likelihood of periodic attention lapses that are synchronized to the VLFO pattern. Here, we tested these predictions using DC-EEG recordings within and outside of a previously identified network of electrode locations hypothesized to reflect DMN activity (i.e., S3 network; Helps et al., 2008). Method: 24 young adults (mean age 22.3 years; 8 male), sampled to include a wide range of ADHD symptoms, took part in a study of rest to task transitions. Two conditions were compared: 5 min of rest (eyes open) and a 10-min simple 2-choice RT task with a relatively high sampling rate (ISI 1 s). DC-EEG was recorded during both conditions, and the low-frequency spectrum was decomposed and measures of the power within specific bands extracted. Results: Shift from rest to task led to an attenuation of VLFO activity within the S3 network which was inversely associated with ADHD symptoms. RT during task also showed a VLFO signature. During task there was a small but significant degree of synchronization between EEG and RT in the VLFO band. Attenuators showed a lower degree of synchrony than nonattenuators. Discussion: The results provide some initial EEG-based support for the default mode interference hypothesis and suggest that failure to attenuate VLFO in the S3 network is associated with higher synchrony between low-frequency brain activity and RT fluctuations during a simple RT task. Although significant, the effects were small and future research should employ tasks with a higher sampling rate to increase the possibility of extracting robust and stable signals

“Can waiting awaken the resting brain?” a comparison of waiting- and cognitive task-induced attenuation of very low frequency neural oscillations

The default mode network (DMN) is characterised by coherent very low frequency (VLF) neural oscillations in the resting brain. The attenuation of this activity has been demonstrated following the transition from rest to performance of a broad range of cognitive goal-directed tasks. Whether the activity of resting state VLF oscillations is attenuated during non-cognitive goal-directed tasks such as waiting for rewarding outcomes is not known. This study examined the VLF EEG power from resting to performance of attention demanding task and two types of goal-directed waiting tasks. The association between the attenuation of VLF EEG power and Attention-Deficit/Hyperactivity Disorder (ADHD) symptoms was examined.Direct current EEG (DC-EEG) data was collected from 32 healthy young adults (half high and half low ADHD symptom scorers) during (i) a rest state, (ii) while performing a cognitive demanding reaction time task (2CRT), and (iii) while undertaking each of two different goal-directed waiting conditions: “forced-to-wait (FW)” and “choose-to-wait (CW)” tasks. The spatial distribution of VLF EEG power across scalp was similar to that seen in previous resting VLF EEG studies. Significant rest-to-task attenuation of VLF EEG power occurred during the 2CRT and the CW task, but not during the FW task. The association between self-ratings of ADHD symptoms and waiting-induced attenuation was not significant.This study suggests VLF EEG power attenuation that occurs following rest to task transition is not simply determined by changes in cognitive load. The goal-directed nature of a task, its motivated nature and/or the involvement of effortful attention may also contribute. Future studies should explore the attenuation of resting state VLF oscillations during waiting and impulsive choice

VLF frequency EEG scalp distribution.

<p>Spatial distribution of (a) VLF power (0.02–0.2 Hz) at rest and (b) attention-induced deactivation of VLF power for the whole sample. For reference, the electrode montage is shown on the left and topographic maps on right.</p

Localisation of attention-induced deactivation of VLF EEG (0.02–0.2 Hz).

<p>Localisation of VLF EEG shown for the (a) low ADHD group and (b) high ADHD group. Significant voxels are shown in yellow (<i>p</i><.05).</p

Attention-induced deactivation of very low frequency (0.02–0.2 Hz) EEG in low and high ADHD groups.

<p>Attention-induced deactivation of very low frequency (0.02–0.2 Hz) EEG in low and high ADHD groups.</p