Neuropsychiatric risk in children with intellectual disability of genetic origin: IMAGINE - The UK National Cohort Study

Background: Children with intellectual disability (ID) frequently have multiple co-morbid neuropsychiatric conditions and poor physical health. Genomic testing is increasingly recommended as a first-line investigation for these children. We aimed to determine the impact of genomics, inheritance and socioeconomic deprivation on neuropsychiatric risk in children with intellectual disability of genetic origin as compared to the general population. Methods: IMAGINE is a prospective study using online mental health and medical assessments in a cohort of 2770 children with ID and pathogenic genomic variants, identified by the UK’s National Health Service. Outcomes: Assessments completed on 2397 young people with ID (4-19 years, M 9·2, SD 3·9) with a rare pathogenic genomic variant. 1339 (55·9%) were male. 1771 (73·9%) of participants had a pathogenic copy number variant (CNV), 626 (26·1%) a pathogenic single nucleotide variant (SNV). Participants were representative of the socioeconomic spectrum of the UK general population. The relative risk of co-occurring neuropsychiatric diagnoses, compared with the UK national population, was high: Autism Spectrum Disorder 29·2 (95% CI 23·9 to 36·5), Attention Deficit Hyperactivity Disorder 13·5 (95% CI 11·1 to 16·3). In children with a CNV, those with a familial variant tended to live in more socioeconomically deprived areas. Both inheritance and socioeconomic deprivation contributed to neuropsychiatric risk in those with a CNV. Interpretation: Children with genomic variants and ID are at a greatly enhanced risk of neuropsychiatric difficulties. CNV variant inheritance and socioeconomic deprivation also contribute to the risk

Neuropsychiatric risk in children with intellectual disability of genetic origin: IMAGINE, a UK national cohort study

Background Children with intellectual disability frequently have multiple co-morbid neuropsychiatric conditions and poor physical health. Genomic testing is increasingly recommended as a first-line investigation for these children. We aim to determine the effect of genomics, inheritance, and socioeconomic deprivation on neuropsychiatric risk in children with intellectual disability of genetic origin as compared with the general population. Methods IMAGINE is a prospective cohort study using online mental health and medical assessments in a cohort of 3407 UK participants with intellectual disability and pathogenic genomic variants as identified by the UK's National Health Service (NHS). Our study is on a subset of these participants, including all children aged 4–19 years. We collected diagnostic genomic reports from NHS records and asked primary caregivers to provide an assessment of their child using the Development and Well-Being Assessment (DAWBA), the Strengths and Difficulties Questionnaire (SDQ), the Adaptive Behaviour Assessment System 3 (ABAS-3), and a medical history questionnaire. Each child was assigned a rank based on their postcode using the index of multiple deprivation (IMD). We compared the IMAGINE cohort with the 2017 National Survey of Children's Mental Health in England. The main outcomes of interest were mental health and neurodevelopment according to the DAWBA and SDQ. Findings We recruited 2770 children from the IMAGINE study between Oct 1, 2014 and June 30, 2019, of whom 2397 (86·5%) had a basic assessment of their mental health completed by their families and 1277 (46·1%) completed a medical history questionnaire. The mean age of participants was 9·2 years (SD 3·9); 1339 (55·9%) were boys and 1058 (44·1%) were girls. 355 (27·8%) of 1277 reported a seizure disorder and 814 (63·7%) reported movement or co-ordination problems. 1771 (73·9%) of 2397 participants had a pathogenic copy number variant (CNV) and 626 (26·1%) had a pathogenic single nucleotide variant (SNV). Participants were representative of the socioeconomic spectrum of the UK general population. The relative risk (RR) of co-occurring neuropsychiatric diagnoses, compared with the English national population, was high: autism spectrum disorder RR 29·2 (95% CI 23·9–36·5), ADHD RR 13·5 (95% CI 11·1–16·3). In children with a CNV, those with a familial variant tended to live in more socioeconomically deprived areas than those with a de novo variant. Both inheritance and socioeconomic deprivation contributed to neuropsychiatric risk in those with a CNV. Interpretation Children with genomic variants and intellectual disability are at an increased risk of neuropsychiatric difficulties. CNV variant inheritance and socioeconomic deprivation also contribute to the risk. Early genomic investigations of children with intellectual disability could facilitate the identification of the most vulnerable children. Additionally, harnessing parental expertise using online DAWBA assessments could rapidly identify children with exceptional needs to child mental health services

Prospective task knowledge improves working memory-guided behaviour

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How is information in working memory selected and prioritised for action?

Flexible cognition necessary for everyday behaviour depends on working memory (WM)–the ability to keep information in mind for a later use. Not all items in WM are represented equally. Attention can be allocated to select and prioritise task-relevant content for a forthcoming action. Chapter 2-3 used behaviour, eye-tracking and electroencephalography (EEG) to investigate the consequences of selecting a single feature in WM for the representation of other features belonging to the same item. Orientation judgements were faster and more precise when another feature of the same object was cued for an orthogonal task during the delay. Colour selection in WM engaged spatial attention, indexed by contralateral alpha suppression and gaze bias, and was associated with a boost in the representation of the cued object’s memorised location (Chapter 2) and orientation (Chapter 3) as decoded from EEG voltages. The results provide evidence for obligatory attentional spread between an item’s features in WM and support a special status of location in selecting and binding features. Finally, EEG decoding revealed that the cued item was automatically compared with the probe at recall, suggesting selected WM content may be in a prioritised state for interacting with new sensory input and guiding decision-making. WM is more than a passive store of recent experiences and is fundamentally future-oriented. Chapter 4 tested whether WM contents are configured as prospective task-sets for guiding behaviour. In one experiment, a prioritised item drove responses in a task-specific manner even when irrelevant in the context of a nested task. In a second experiment, task-foreknowledge improved WM-guided behaviour and enhanced retro-cued prioritisation on reaction times. Together, the results indicate that prioritised WM items are configured as prospective templates optimised for context-dependent action. Neuroimaging studies are needed to elucidate the precise mechanisms of task-specific coding in WM. Chapter 5 proposes an EEG experiment, in the form of a Registered Report, to test the hypothesis that prioritised content is stored in a functional state that is intrinsically linked to its anticipated use. I predict that patterns of neural activity coding for remembered items will be task-specific. The suitability of the analysis pipeline was demonstrated on simulated neural data. The results of this thesis highlight a key role of attentional selection in preparing WM representations for future action and motivate further research into the ways information in WM may serve as functional states for decision-making

Neural reinstatement tracks spread of attention between object features in working memory

Attention can be allocated in working memory (WM) to select and privilege relevant content. It is unclear whether attention selects individual features or whole objects in WM. Here, we used behavioral measures, eye-tracking and EEG to test the hypothesis that attention spreads between an object's features in WM. Twenty-six participants completed a WM task that asked them to recall the angle of one of two oriented, colored bars after a delay while EEG and eye-tracking data were collected. During the delay, an orthogonal "incidental task" cued the color of one item for a match/mismatch judgment. On congruent trials (50%), the cued item was probed for subsequent orientation recall; on incongruent trials (50%), the other memory item was probed. As predicted, selecting the color of an object in WM brought other features of the cued object into an attended state as revealed by EEG decoding, oscillatory α-power, gaze bias, and improved orientation recall performance. Together, the results show that attentional selection spreads between an object's features in WM, consistent with object-based attentional selection. Analyses of neural processing at recall revealed that the selected object was automatically compared with the probe, whether it was the target for recall or not. This provides a potential mechanism for the observed benefits of nonpredictive cueing in WM, where a selected item is prioritized for subsequent decision-making

Prospective task knowledge improves working memory-guided behaviour

Working memory (WM) is the ability to keep information online for a forthcoming task. WM theories have tended to focus on how sensory information is maintained, and less on how WM content is used for guiding behaviour. Here we ask if WM is supported by a transformation of sensory memoranda into task-sets that are optimised for task-dependent responses. Thirty participants performed two different WM tasks; they remembered the tilt of oriented bars for either a rotation-discrimination task or a change-detection task. Task context was instructed either in advance (fixed task blocks) or at probe onset (mixed task blocks). If WM content is configured in a task-dependent format, performance should benefit from foreknowledge of the upcoming task. In line with this prediction, we found that WM accuracy was higher when participants had advance knowledge of the task context. Even if WM content can be configured as a task-set, perhaps only one item is optimised for guiding behaviour. If so, retro-cued prioritization may be supported by a transformation of the selected item from a sensory to a task-oriented code. We included a retro-cue on half of the trials to test the second hypothesis that task-foreknowledge enhances retro-cued prioritization. Interestingly, the benefits of task foreknowledge were independent of the benefits incurred by retro-cueing, indicating that attentional selection is sufficient for prioritization of WM content. Together, these results provide preliminary evidence that WM coding may be task-dependent, but neuroimaging studies are needed to elucidate the precise mechanisms by which task foreknowledge facilitates WM-guided behaviour

Subclinical anxiety and depression are associated with deficits in attentional target facilitation, not distractor inhibition

Mood and anxiety disorders are associated with deficits in attentional control involving emotive and non-emotive stimuli. Current theories focus on impaired attentional inhibition of distracting stimuli in producing these deficits. However, standard attention tasks struggle to separate distractor inhibition from target facilitation. Here, we investigate whether distractor inhibition underlies these deficits using neutral stimuli in a behavioural task specifically designed to tease apart these two attentional processes. Healthy participants performed a validated four-location Posner cueing paradigm and completed self-report questionnaires measuring depressive symptoms and trait anxiety. Using regression analyses, we found no relationship between distractor inhibition and mood or anxiety symptoms. However, we find a relationship between target facilitation and both depression and anxiety. Specifically, higher depressive symptoms were associated with reduced target facilitation, and higher anxiety symptoms were associated with enhanced target facilitation in a task-version in which the target location repeated over a block of trials. By contrast, we find the opposite direction of relationships in a task-version in which the location of the forthcoming target was cued on a trial-wise basis. This dissociation may point to separate mechanisms underlying the relationships between depressive and anxiety symptoms and attention and warrants further investigation in clinical populations

Attentional Control in Subclinical Anxiety and Depression : Depression Symptoms Are Associated With Deficits in Target Facilitation, Not Distractor Inhibition

Mood and anxiety disorders are associated with deficits in attentional control involving emotive and non-emotive stimuli. Current theories focus on impaired attentional inhibition of distracting stimuli in producing these deficits. However, standard attention tasks struggle to separate distractor inhibition from target facilitation. Here, we investigate whether distractor inhibition underlies these deficits using neutral stimuli in a behavioral task specifically designed to tease apart these two attentional processes. Healthy participants performed a four-location Posner cueing paradigm and completed self-report questionnaires measuring depressive symptoms and trait anxiety. Using regression analyses, we found no relationship between distractor inhibition and mood symptoms or trait anxiety. However, we find a relationship between target facilitation and depression. Specifically, higher depressive symptoms were associated with reduced target facilitation in a task-version in which the target location repeated over a block of trials. We suggest this may relate to findings previously linking depression with deficits in predictive coding in clinical populations

10 Simple Rules for a Supportive Laboratory Environment

The transition to principal investigator (PI), or lab leader, can be challenging, partially due to the need to fulfil new managerial and leadership responsibilities. One key aspect of this role, which is often not explicitly discussed, is creating a supportive lab environment. Here, we present ten simple rules to guide the new PI in the development of their own positive and thriving lab atmosphere. These rules were written and voted on collaboratively, by the students and mentees of Professor Mark Stokes, who inspired this piece