Understanding and enhancing executive networks in childhood
The ability to control our cognitive processes is critical to achieving most tasks. Even when we look around the busy visual scene we need to use attention – a particular type of control mechanism – to bias the bits of the scene that are most relevant to the task at hand. Failure of these control mechanisms results in disorganised behaviour, reduces the efficiency of our cognitive processes, and impairs learning. This research programme explores these top-down control mechanisms in the human brain, using non-invasive neuroscience techniques with real-time resolution (electroencephalographyn (EEG) and magnetoencephalography (MEG)). We are particularly interested in how these mechanisms develop in childhood, both in typically and atypically developing children. Indeed, these control biases are implicated in a wide variety of developmental disorders, and yet the mechanisms that underpin them remain poorly understood.
In summary, the key goals of this programme are to: i) explore the neural dynamics of the functional connections that underpin top-down control in childhood; ii) examine how these networks differ between children, depending upon the child’s WM capacity, degree of inattention, and genetic background; iii) develop and test the efficacy of cognitive training programmes for enhancing these control processes; and iv) explore the brain mechanisms via which these interventions are effective.
Astle, D. E., Barnes, J. J., Baker, K., Colclough, G. L., & Woolrich, M. W. (2015). Cognitive training enhances intrinsic brain connectivity in childhood. The Journal of Neuroscience, 35(16), 6277-6283
Astle, D. E., Luckhoo, H., Woolrich, M., Kuo, B. C., Nobre, A. C., & Scerif, G. (2015). The neural dynamics of fronto-parietal networks in childhood revealed using magnetoencephalography. Cerebral Cortex, 25(10), 3868-3876.
Barnes, J. J., Woolrich, M. W., Baker, K., Colclough, G. L., & Astle, D. E.(2016). Electrophysiological measures of resting state functional connectivity and their relationship with working memory capacity in childhood. Developmental science, 19(1), 19-31.
Kuo, B. C., Nobre, A. C., Scerif, G., & Astle, D. E. (2016). Top–Down Activation of Spatiotopic Sensory Codes in Perceptual and Working Memory Search. Journal of cognitive neuroscience.
Projects
[toggle title_open=”The electrophysiological basis of functional brain connectivity in childhood” title_closed=”The electrophysiological basis of functional brain connectivity in childhood” hide=”yes” border=”yes” style=”default” excerpt_length=”0″ read_more_text=”Read More” read_less_text=”Read Less” include_excerpt_html=”no”]Dynamic functional connectivity (FC) is fundamental to understanding typical top-down control mechanisms in adulthood, with disparate brain regions working together within networks. We have taken a similar approach to their study in childhood. These networks are constituted through the spontaneous synchronisation of neural oscillations across spatially distinct neuronal populations. MEG provides data directly driven by the electrophysiological nature of the networks, and we have been using the MEG to identify networks on the basis their temporal structure, affording far greater precision as to when a network is recruited for a particular cognitive process.In collaboration with researchers in Oxford (Mark Woolrich, Gaia Scerif, Kia Nobre and Henry Luckhoo), we have been exploring synchronised power relationships across different populations of neurons, using low frequency signals (4-20 Hz). We found a number of networks including lateral frontal, inferior frontal and pre-motor areas, all recruited as participants encode memory items; the former two in both children and adults and the latter in just the children. Because of the high temporal resolution of MEG, we were able to identify when these networks were critical. Interestingly, in the children we found that anticipatory activity in some networks was predictive of whether children would remember the memoranda that they were about to see.
In subsequent studies we have explored the existence of these networks at rest and the extent to which they can be altered by cognitive training.
Relevant publications
Astle, D. E., Barnes, J. J., Baker, K., Colclough, G. L., & Woolrich, M. W. (2015). Cognitive training enhances intrinsic brain connectivity in childhood. The Journal of Neuroscience, 35(16), 6277-6283
Astle, D. E., Luckhoo, H., Woolrich, M., Kuo, B. C., Nobre, A. C., & Scerif, G. (2015). The neural dynamics of fronto-parietal networks in childhood revealed using magnetoencephalography. Cerebral Cortex, 25(10), 3868-3876.
Barnes, J. J., Woolrich, M. W., Baker, K., Colclough, G. L., & Astle, D. E. (2016). Electrophysiological measures of resting state functional connectivity and their relationship with working memory capacity in childhood. Developmental science, 19(1), 19-31.
Kuo, B. C., Nobre, A. C., Scerif, G., & Astle, D. E. (2016). Top–Down Activation of Spatiotopic Sensory Codes in Perceptual and Working Memory Search. Journal of cognitive neuroscience.
[/toggle] [toggle title_open=”Why memory fails: Understanding the reasons for poor working memory in childhood” title_closed=”Why memory fails: Understanding the reasons for poor working memory in childhood” hide=”yes” border=”yes” style=”default” excerpt_length=”0″ read_more_text=”Read More” read_less_text=”Read Less” include_excerpt_html=”no”]Working memory is used for many demanding cognitive activities, and is best characterized as a ‘mental workspace’, in which information can be held and processed for brief periods of time. For instance, we might use our working memory to hold in mind a new route to school whilst stopping to tie our shoelaces. The amount of information that can be held in working memory differs greatly from person to person. These individual differences in capacity are important, particularly in childhood: over 80% of children with low working-memory capacity (those in the bottom 10th percentile for their age group) have substantial problems with either reading or mathematics, or usually both. The aim of this project is to understand why some children and adults have poor working-memory skills. In particular it focuses on the role that top-down attention plays in controlling what gains access to storage, which basic mechanisms are implicated in this control, and the extent to which this control can be trained in order to boost working-memory capacity. As part of this study we are currently engaged in a longitudinal study (collaborating with Gaia Scerif, Oxford), looking at how memory skills and attention predict educational progress. The next phase of the study will look at whether we can improve these skills.Relevant publications
Astle, D.E., Nobre, A.C. and Scerif, G (2012) Attentional control constrains visual short-term memory: Insights from developmental and individual differences. Quarterly Journal of Experimental Psychology, 65, 2, 277-294
Astle, D.E., and Scerif, G (2010) Interactions between attention and visual short-term memory (VSTM): What can be learnt from individual and developmental differences? Neuropsychologia, 49, 6, 1435-1445.
Astle, D.E. and Scerif, G. (2009) Using developmental cognitive neuroscience to study behavioural and attentional control Developmental Psychobiology, 57, 107-118[/toggle] [toggle title_open=”Modifying attentional biases following stroke ” title_closed=”Modifying attentional biases following stroke ” hide=”yes” border=”yes” style=”default” excerpt_length=”0″ read_more_text=”Read More” read_less_text=”Read Less” include_excerpt_html=”no”]This project is a collaboration with Tom Manly (MRC CBSU) and John Duncan (MRC CBSU), and is funded by the Director’s Strategic Fund.
Unilateral stroke damage often results in both spatial and non-spatial attention deficits, which are well documented, but for which there are currently few therapeutic options (and little evidence of their efficacy). We are interested in the extent to which these attentional mechanisms can be modified with targeted cognitive training. Working with Adam Hampshire (Western Ontario University, Canada) we are developing a training programme which we hope will stretch participants’ attentional capabilities. We would also like to know whether and how this training will transfer to other non-trained tasks, and even to everyday activities that might be difficult following a stroke.
Work is just getting under way, so watch this space!
[/toggle]
[toggle title_open=”The neural mechanisms of attentional-memory interactions” title_closed=”The neural mechanisms of attentional-memory interactions” hide=”yes” border=”yes” style=”default” excerpt_length=”0″ read_more_text=”Read More” read_less_text=”Read Less” include_excerpt_html=”no”]This project involved collaborations with Gaia Scerif (Oxford), Kia Nobre (Oxford), Mark Stokes (Oxford) and Kuo Bo-Cheng (National Chengchi University, Taipei). EEG provides a real-time measure ideal for capturing the rapid neural mechanisms of attention, and because they are often spatially-specific, lateralised effects can provide a good index of top-down attentional biases. We use evoked and time-frequency analyses (particularly in the alpha and gamma bands, and lateralised cross-frequency coupling) to explore the neural mechanisms by which we apply top-down attentional biases to perceptual and remembered input. Our results suggest that subjects recruit similar spatially organised attentional biases when they access the content of visual memories as when they access perceptual input. These biases differ, depending upon whether the memory system is at or within capacity, and on what type of memory system subjects attempt to access. Furthermore, the relationship between attention and memory is bidirectional: in some cases items that subjects have seen previously can capture subjects’ attention, even without their explicit awareness. We are currently developing non-lateralised tasks to explore the relationship between attention and memory.
Relevant publications
Murray, A.M., Nobre, A.C., Astle, D.E., and Stokes, M.G. (2012) Lacking control over the trade-off between between quality and quantity in visual short-term memory PLoS One, 7(8):e41223
Astle, D.E., Summerfield, J., Griffin, I., and Nobre, A.C. (2012) Orienting attention to locations in mental representations Attention, Perception and Psychophysics, 74, 1, 146-162
Astle, D.E., Nobre, A.C. and Scerif, G (2010) Subliminally presented and stored objects capture spatial attention Journal of Neuroscience, 30(10), 3567-3571
Astle, D.E., Nobre, A.C. & Scerif, G (2009) Applying an attentional set to perceived and remembered features PLoS One, 4(10)
Astle, D.E., Scerif, G., Kuo, B.-C., & Nobre, A.C. (2009) Spatial selection of features within perceived and remembered objects Frontiers in Human Neurosci, 3, 6
[/toggle] [toggle title_open=”The control mechanisms used when subjects switch cognitive tasks” title_closed=”The control mechanisms used when subjects switch cognitive tasks” hide=”yes” border=”yes” style=”default” excerpt_length=”0″ read_more_text=”Read More” read_less_text=”Read Less” include_excerpt_html=”no”]This project is a collaboration with Georgina Jackson (Nottingham).The ability to act flexibly within a constantly fluctuating environment characterises human behaviour. For instance, a bilingual speaker can switch seamlessly between using alternative languages depending upon the context. Alternatively, one might need to maintain one’s attention on a specific task, object or representation, despite the presence of salient distractions. There is now an established and growing literature exploring the way in which the human brain exerts this ‘executive’ or ‘cognitive’ control over thought, attention and action. This control is essential, as evidenced by the devastating consequences of damage to the brain regions that subserve it. EEG and MEG are particularly well suited to distinguishing rapid neural events, such as those involved in task-set control. Combining carefully controlled experimental designs with these recordings has enabled us to relate specific neural processes to specific, and robust, behavioural phenomena. For instance by combining task-switching and go/no-go paradigms it is possible to demonstrate that distinct mechanisms govern the control associated with abandoning a previously performed task from those associated with preparing a to-be-performed task. That is, we can distinguish the control processes (both in terms of their behavioural consequences and neural correlates) that enable us to change our current intention from those that enable us to overcome our previous action. Similarly, we have demonstrated that a switch between purely covert actions, such as attending to what we see versus what we hear, may not involve the same mechanisms as a switch between overt actions, such as making a written note of what we see versus what we hear.
Relevant publications
Astle, D.E., Geogiadi M., Jackson, S.R. and Jackson, G.M. (2012) Neural correlates of changing intention and the human FEF and IPS Journal of Neurophysiology, 107, 3, 859-867
Astle, D.E., Jackson, G.M. and Swainson, R. (2012) Two measures of task-specific inhibition Quarterly Journal of Experimental Psychology, 65, 2, 233-251
Astle, D.E., Jackson, G.M. and Swainson, R. (2008) Fractionating the cognitive control required to bring about a change in task-set: A dense-sensor ERP study Journal of Cognitive Neuroscience, 20, 2, 255-267
Astle, D.E., Jackson, G.M. and Swainson, R. (2008) The role of spatial information on advance task-set control: A dense-sensor ERP study European Journal of Neuroscience, 28, 1404-1418
Astle, D.E., Jackson, G.M. and Swainson, R. (2006) Dissociating neural indices of dynamic cognitive control in advance task-set preparation: An ERP study of task-switching Brain Research, 1125(1), 94-103
[/toggle][toggle title_open=”Collaborators” title_closed=”Collaborators” hide=”yes” border=”yes” style=”default” excerpt_length=”0″ read_more_text=”Read More” read_less_text=”Read Less” include_excerpt_html=”no”]My research is only made possible by on-going fruitful collaborations with a number of researchers: John Duncan (MRC CBSU); Tom Manly (MRC CBSU); Sue Gathercole (MRC CBSU); Gaia Scerif (Experimental Psychology, Oxford); Kia Nobre (Oxford Centre for Human Brain Activity, Oxford); Georgina Jackson (Division of Psychiatry, Queen’s Medical Centre, Nottingham); Mark Stokes (Oxford Centre for Human Brain Activity, Oxford); Mark Woolrich (Oxford Centre for Human Brain Activity, Oxford); and Bo-Cheng Kuo (National Chengchi University, Taipei, Taiwan).[/toggle] [toggle title_open=”Team Members” title_closed=”Team Members” hide=”yes” border=”yes” style=”default” excerpt_length=”0″ read_more_text=”Read More” read_less_text=”Read Less” include_excerpt_html=”no”]Duncan Astle (Programme Leader Track), Andria Shimi (Research Assistant), Polly Peers (Investigator Scientist), Jessica Barnes (Career Development Fellow, from 01/01/2013)[/toggle]