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Individualised Diagnostics and Rehabilitation of Attention

Final Report Summary - INDIREA (Individualised Diagnostics and Rehabilitation of Attention)

Impairments in attention affect a variety of groups, from children with ADHD to elderly patients suffering from dementia or recovering from stroke. The INDIREA project (Individualised Diagnostics and Rehabilitation of Attention) aimed to enhance our understanding of the neural basis of these disorders of attention, and to improve the way they can be diagnosed and treated. Our approach was to use individual attentional characteristics as predictors of treatment and rehabilitation outcome opens up possibilities for more efficient, personalised treatment, which can ultimately lower both the high personal and socio-economic costs related to attentional disorders. INDIREA has funded thirteen Early Stage Researchers at seven different institutes across Europe (in Copenhagen, Oxford, Munich, Magdeburg, Dublin, and Barcelona), forming a highly collaborative international network including both universities and partners in industry.

Our first objective was to develop new attentional screening tools, which can inform new neurorehabilitation strategies and tailor these better to the needs of individual patients. We have created several computer-based tasks which can be used in a wide range of disorders, for instance in stroke survivors as well as in patients with dementia, Parkinson’s disease, and traumatic brain injury. These tests were specially designed to be easy to use and short enough to administer at the bedside. For example, we developed a software package to administer and analyse so-called cancellation tasks, a type of test that is used to diagnose the one-sided inattention that often occurs after stroke. Until now, cancellation tasks relied on pen-and-paper testing, which is slower and more complicated for both patient and researcher than our digital version. We have used our new test battery to study multiple aspects of attentional disorders, and showed for instance that different subtypes of attention differ in severity and recovery rate after stroke. Many of our materials are freely available to researchers and clinicians (e.g.

Our second objective was to identify ‘biomarkers’ of attentional problems: features of the activity or structure of the brain that predict differences in attentional functioning. For instance, we found that changes in the connections within the cingulo-opercular network were related to the decline of visual processing speed that occurs with ageing. Using the mathematical Theory of Visual Attention (TVA) model, we could also detect subtle changes in visual processing speed that occur in the early stages of Alzheimer’s disease. This knowledge will help clinicians to diagnose Alzheimer’s earlier and monitor the progression of the disease better. It also has important implications for development of potential new treatments, for instance attentional training paradigms.

Another line of research focused on characterising individual parameters of attention in ADHD. Temporal attention, specifically the use of prior knowledge to guide attention, can be compromised in ADHD, and this may be one explanation for the variability in attention that we observe in ADHD patients. We therefore designed new experimental paradigms for testing these traits within the TVA framework. We also developed new methods to combine TVA-based tests with EEG, which allowed us to identify several brain signals that can serve as markers of attentional processes. Our investigations show that we can indeed identify deficits in specific attentional components in children and adults with ADHD, as well as the effect of medication on these problems. The next step will be to use our characterisation of attentional problems to outline the developmental trajectories from preadolescent to adult ADHD, opening up possibilities for more efficient, personalised treatment.

Our third objective was to develop new analysis methods to link brain imaging data to mathematical and computational modelling of attention. We developed a method that looks at the patterns of correlated activity between different brain regions, and divides the brain up into ‘functional clusters’ of similar patterns. With this method we were able to investigate the interplay between brain regions during attentional tasks at an unprecedented level of detail, and we found that there is surprising consistency between individual brains. Our results with healthy brains suggest that in the future we could use this method to compare the correlational structure of brain activity between patient groups, or before and after treatment. We have developed software to extract large-scale brain networks from fMRI data, and used this to build computational models. This method can be applied to investigate how differences in functional networks due to attention or a brain lesion can be modelled.

Finally, we investigated three different methods for the rehabilitation of attentional disorders. Using a technique called transcranial direct current stimulation (tDCS), we showed that stimulating the right prefrontal cortex improved performance on specific components of attention in older adults. Furthermore tDCS disrupted attention in patients with damage to their right hemisphere after a stroke, which suggests that natural compensatory processes of the unaffected hemisphere could be transiently disrupted. Our work suggests that the right prefrontal cortex plays a critical role in attention, and that non-invasive brain stimulation of this area may be a way to treat attentional impairments in ageing. It is particularly promising that we observed these effects in older adults with lower levels of cognitive reserve, as this suggests that potential treatment may not be restricted to those who have engaged in cognitively stimulating activities throughout their life.

The second potential treatment method we investigated was training people by using their own brain activity, a procedure called neurofeedback. We developed a computer algorithm that distinguishes between brain activity during two types of mind-wandering; deliberate and spontaneous. Deliberate mind-wandering helps creative processes and planning, whereas spontaneous mind-wandering can be a sign of depression and other mental health issues. Our computer algorithm could detect the difference between these two states based on EEG data, which means that we can now track mind-wandering continuously and objectively. This is a crucial step towards our eventual goal of developing a brain-computer interface; a program that analyses and presents brain signals in real-time, such that the patient can use this feedback to adapt and train their mind-wandering behaviour.

Thirdly we examined the effects of the drug guanfacine (a drug that acts to stimulate a specific brain receptor for noradrenaline, a chemical neurotransmitter) in patients who suffered a right-hemisphere stroke. These patients had developed problems attending to information in the left side of their field of vision, a condition called left-sided neglect. Neglect is associated with slower and more limited recovery after stroke, but there is currently no established treatment for it. Our study showed that guanfacine has a beneficial effect on the number of items that neglect patients find in visual search (cancellation) tasks, but it does not improve sustained attention, spatial working memory, or search organisation. These results suggest that guanfacine can modulate some aspects of attention following stroke, opening the way for further more long-term trials.

In addition to our scientific contributions, INDIREA has provided a unique training opportunity for the thirteen Early Stage Researchers that were funded through the project. The students came together during six training camps, one in each of the cities of the INDIREA network. They regularly visited each other’s institutes to exchange skills, materials and ideas, resulting in a strong personal network that spans multiple countries, sectors and scientific disciplines. This sense of international mobility and collaboration is fundamental to scientific progress, and will be a life-long asset in the students’ careers. Because of our strong links with partners in industry, the students also developed strong transferrable skills and a good sense of the commercial potential of their research, preparing them to make the leap from basic research to real-world solutions. In conclusion, INDIREA not only produced a wealth of knowledge and practical tools to improve the diagnosis and treatment of attentional disorders, but also an exceptionally well-trained and well-connected next generation of scientists who are ready to make a lasting contribution in and outside of academia.