Work Packages

work package diagram 070614 v2
Schematic overview of INDIREA indicating the multi-level analyses of the cognitive and neutral basis of attention, and emergent goals for improved diagnostics 

 WP1 : Clinical screening of attention (ESRs 1,2)

The objectives of WP1 are: (i) to develop clinically applicable and commercially viable means of screening acquired and developmental dysfunctions in attention linked to parameters modelled through TVA, and (ii) to assess the neural substrates of behaviour measured with the clinical screen, to enable lesion-symptom predictions to be formed. We start from the BCoS test developed by the applicants (UOXF) which provides a sensitive and validated cognitive profile for patients (measuring attention, language, memory, number skills and praxis), advancing prior screening tools by being designed to be maximally inclusive (e.g., so data collection can include aphasic patients and patients with visual neglect) and time efficient (single tests measuring multiple factors).


WP2 : Mathematical modelling of attention (ESRs 5,6,7,8)

WP2 aims to evaluate the use of mathematical modelling of visual attention, using TVA, to characterise (i) attentional changes in MCI patients (longitudinal study) and in healthy aging (cross-sectional study), (ii) attentional dysfunctions in ADHD (in adults and children) and (iii) the relations between parameters of TVA and a variety of neural biomarkers including structural and functional MR and EEG. In Munich a group of 50 patients with MCI, classified on the basis of both behavioural and imaging data, will be assessed along with cross-sectional groups of age-matched controls with no symptoms of cognitive decline. Behavioural tests using whole and partial report of briefly presented displays will be used to derive
15 attentional parameters based on TVA at annual intervals. In addition, the patients will be tested using matching MR and EEG protocols to those used in WP1, in order to derive neural correlates of the changes in attentional parameters that predict whether MCI cases progress into Alzheimer’s Disease.


WP3 : Neurocomputational modelling of attention (ESRs 9,10)

WP3 will link the cognitive and mathematical accounts of attention (WPs 1 and 2) to neuroimaging data within WP by simulating the results using neurocomputational models. Specifically, WP3 will ( i) develop theoretical tools to analyze large-scale neurodynamical models, and (ii) explore differences in neural dynamics found in individuals with attentional dysfunction and evaluate possible diagnostic applications and predictions concerning intervention.


WP4 : Rehabilitation of attention (ESRs 3,4,11,12,13)

WP4 will link the clinical diagnostic tests and the emerging neuroscientific data (WPs 1-3) to the rehabilitation of attentional disorders, with work focused at TCD and UOXF. The studies will use common outcome measures from our clinical screen (WP1) and the parameters of TVA (WP2), going beyond prior studies by assessing multiple (rather than single) attentional processes through our novel diagnostic tests. Measuring multiple processes is critical when changes in one parameter might influence others. Behavioural changes will be linked to measures of neural activity (fMRI and EEG, using procedures from WP 1-3 in conjunction with SIEMENS and BraProd) recorded before and after intervention. In WP4a tDCS will be used in two trials examining excitatory stimulation over sections of the fronto-parietal attentional network linked to working memory: dorso-lateral pre-frontal cortex and posterior parietal cortex (ESR11: “Enhancing brain plasticity in MCI via tDCS”), as MCI patients perform attention-demanding tasks. A randomly selected patient control group will receive sham excitatory stimulation over the vertex. Effects of on-line EEG feedback in WP4b will focus on feedback in memory-related theta band power disrupted in Alzheimer’s patients, comparing randomised groups given correct theta band feedback vs. performance-unrelated feedback.