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.

Default-mode brain dysfunction in mental disorders: a systematic review.

In this review we are concerned specifically with the putative role of the default-mode network (DMN) in the pathophysiology of mental disorders. First, we define the DMN concept with regard to its neuro-anatomy, its functional organisation through low frequency neuronal oscillations, its relation to other recently discovered low frequency resting state networks, and the cognitive functions it is thought to serve. Second, we introduce methodological and analytical issues and challenges. Third, we describe putative mechanisms proposed to link DMN abnormalities and mental disorders. These include interference by network activity during task performance, altered patterns of antagonism between task specific and non-specific elements, altered connectively and integrity of the DMN, and altered psychological functions served by the network DMN. Fourth, we review the empirical literature systematically. We relate DMN dysfunction to dementia, schizophrenia, epilepsy, anxiety and depression, autism and attention deficit/hyperactivity disorder drawing out common and unique elements of the disorders. Finally, we provide an integrative overview and highlight important challenges and tasks for future research.

Different effects of adding white noise on cognitive performance of sub-, normal and super-attentive school children.

OBJECTIVES: Noise often has detrimental effects on performance. However, because of the phenomenon of stochastic resonance (SR), auditory white noise (WN) can alter the "signal to noise" ratio and improve performance. The Moderate Brain Arousal (MBA) model postulates different levels of internal "neural noise" in individuals with different attentional capacities. This in turn determines the particular WN level most beneficial in each individual case-with one level of WN facilitating poor attenders but hindering super-attentive children. The objective of the present study is to find out if added WN affects cognitive performance differently in children that differ in attention ability. METHODS: Participants were teacher-rated super- (N = 25); normal- (N = 29) and sub-attentive (N = 36) children (aged 8 to 10 years). Two non-executive function (EF) tasks (a verbal episodic recall task and a delayed verbal recognition task) and two EF tasks (a visuo-spatial working memory test and a Go-NoGo task) were performed under three WN levels. The non-WN condition was only used to control for potential differences in background noise in the group testing situations. RESULTS: There were different effects of WN on performance in the three groups-adding moderate WN worsened the performance of super-attentive children for both task types and improved EF performance in sub-attentive children. The normal-attentive children's performance was unaffected by WN exposure. The shift from moderate to high levels of WN had little further effect on performance in any group. SIGNIFICANCE: The predicted differential effect of WN on performance was confirmed. However, the failure to find evidence for an inverted U function challenges current theories. Alternative explanations are discussed. We propose that WN therapy should be further investigated as a possible non-pharmacological treatment for inattention.

"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 were 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.

An electrophysiological monetary incentive delay (e-MID) task: a way to decompose the different components of neural response to positive and negative monetary reinforcement.

BACKGROUND: The ability to anticipate and then secure future rewards and avoid future punishments by responding effectively to environmental demands is at the core of successful decision making. Disruptions to these processes have been shown to be implicated in a number of psychiatric conditions. In the current paper we use the electrophysiological monetary incentive delay task (e-MID) to decompose the neural response to (i) reinforcement anticipation, (ii) reinforcement-contingent target processing and (iii) reinforcement-related feedback. METHODS: Thirty-eight adolescents and young adults performed an ERP-based analogue of the monetary incentive delay task. ERP components previously associated with motivationally salient cue (cue-P3 and contingent negative variation, CNV), target (P3) and feedback (success vs. failure; feedback-related negativity; FRN and the late positive potential; LPP) stimuli were examined. RESULTS: Response times were shorter and less variable in the monetary gain and loss conditions. Distinctive ERP components were observed for each phase of reinforcement processing. First, cue-P3 was enhanced to monetary gain cues. Predicted alterations in cue-P3 following monetary loss cues and the CNV following cues of either monetary loss or gain were not observed. Target P3 was enhanced in both incentive conditions. The FRN was greater following monetary loss feedback. LPP amplitude was enhanced following feedback denoting monetary gain and the avoidance of monetary loss. CONCLUSION: Although behaviourally the effects of monetary loss and gain were similar, the e-MID task differentiated neural processing in terms of anticipation and feedback-related brain potentials. The e-MID task and the results of the current study provide a valuable complement to fMRI-based approaches to studying normal and abnormal brain correlates of reinforcement processing.

Electrophysiological markers of the motivational salience of delay imposition and escape.

BACKGROUND: The ubiquitous tendency to choose immediate over delayed rewards can, in extremis, lead to maladaptive preferences for smaller sooner over larger later rewards (i.e., impulsive choice) in certain pathological groups. The delay aversion hypothesis provides one possible account of impulsive choice and argues that this tendency is motivated by the avoidance of the negative affective states associated with delay imposed prior to the delivery of a large reward. This model also predicts that on non-choice tasks individuals will be motivated to work harder and more efficiently, when given the opportunity to avoid delay. In the current paper we studied the neural markers of the motivational salience of the imposition and escape from delay using a simple reaction time task under two conditions: First where fast responses were expected to lead to delay escape and second where delay was inescapable. METHODS: Forty participants performed the Escape Delay Incentive (EDI) task during which they were asked to respond as quickly as they could to a target stimulus. The EDI task included two conditions: first, a Delay Escape condition where fast responses led to the avoidance of delay and a Delay No-Escape condition in which a delay was presented on every trial irrespective of response speed. EEG was recorded from 66 equidistant electrode sites across the scalp. The neural response in these two conditions was compared in terms of contingent negative variation (CNV; preparation of motivated responses) and late positive potential, LPP; evaluation of performance feedback). RESULTS: As predicted individuals responded more quickly and showed enhanced CNV amplitude to Delay Escape compared with Delay No-Escape trials. Enhanced LPP amplitude was also observed when participants were not able to avoid the delay in the Delay Escape condition. ADHD symptoms were associated with larger CNV differences between Delay Escape and Delay No-Escape conditions. An association between ADHD symptoms and the LPP in the Delay Escape condition did not reach significance. CONCLUSION: The results of the current study suggest that delay escape is a potent reinforcer at both behavioural and neural levels. Future research should extend this analysis to clinical samples using a broader range of delays and across imaging modalities.

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.

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 lobes.

Altered spontaneous low frequency brain activity in attention deficit/hyperactivity disorder.

BACKGROUND: Resting brain activity appears altered in Attention Deficit/Hyperactivity Disorder (ADHD). The default mode interference hypothesis (Sonuga-Barke and Castellanos, 2007) postulates that patterns of spontaneous very low frequency brain activity, typical of the resting brain, cause attention lapses in ADHD when they remain unattenuated following the transition from rest to active task performance. Here we test this hypothesis using DC-EEG. METHODS: DC-EEG recordings of very low frequency brain activity (<1.5Hz) were compared for 16 male children with ADHD and 16 healthy controls during both rest and active task performance (two choice reaction time task). RESULTS: A previously identified very low frequency resting network of electrodes was replicated. At rest ADHD children showed less EEG power in very low frequency bands (i.e., .02-.2Hz). They also showed less attenuation of power at these frequency bands during rest-to-task transition. Reduced attenuation was associated with a number of measures of performance. DISCUSSION: We confirmed the existence of altered very low frequency brain activity in ADHD. ADHD children may have deficits both in maintaining a resting brain when needed and 'protecting' an active brain from the intrusion of resting state brain activity.