I am a Senior Lecturer in the Computational, Cognitive and Clinical Neuroimaging Laboratory, which is part of the Department of Medicine's Division of Brain Sciences.
The overarching aim of my research is to derive a better understanding of how task active networks in the human brain support key aspects of cognition such as attention, motor response inhibition, working memory, planning and reasoning, and how these aspects of cognition are affected in the pathological brain. I apply a wide range of techniques in pursuit of this aim including functional and structural brain imaging, genotyping, machine learning and computational modelling.
I also have a particular interest in the potential applications of technologies that can be used to apply cognitive testing and training in the home. For example, Apps and websites that can assess large-scale cohorts, track clinical populations longitudinally, or deliver cognitive training regimes.
If you are a student who is interested in undertaking PhD or postdoctoral research in my lab then please feel free to email me directly at a.hampshire_at_imperial.ac.uk.
Lorenz R, Hampshire A, Leech R, 2017, Neuroadaptive Bayesian Optimization and Hypothesis Testing., Trends Cogn Sci, Vol:21, Pages:155-167
Matthews PM, Hampshire A, 2016, Clinical Concepts Emerging from fMRI Functional Connectomics, Neuron, Vol:91, ISSN:0896-6273, Pages:511-528
et al., 2015, The Effect of an Online Cognitive Training Package in Healthy Older Adults: An Online Randomized Controlled Trial, Journal of the American Medical Directors Association, Vol:16, ISSN:1525-8610, Pages:990-997
et al., 2016, Network mechanisms of intentional learning, Neuroimage, Vol:127, ISSN:1053-8119, Pages:123-134
Hampshire A, Sharp DJ, 2015, Contrasting network and modular perspectives on inhibitory control, Trends in Cognitive Sciences, Vol:19, ISSN:1364-6613, Pages:445-452
et al., 2015, Dynamic Network Mechanisms of Relational Integration, Journal of Neuroscience, Vol:35, ISSN:0270-6474, Pages:7660-7673
Hampshire A, 2015, Putting the brakes on inhibitory models of frontal lobe function, Neuroimage, Vol:113, ISSN:1053-8119, Pages:340-355
et al., 2015, Association between MAPT haplotype and memory function in patients with Parkinson's disease and healthy aging individuals., Neurobiol Aging, Vol:36, Pages:1519-1528
et al., 2015, Exploring Spatiotemporal Network Transitions in Task Functional MRI, Human Brain Mapping, Vol:36, ISSN:1065-9471, Pages:1348-1364
et al., 2014, Genetic impact on cognition and brain function in newly diagnosed Parkinson's disease: ICICLE-PD study, Brain, Vol:137, ISSN:0006-8950, Pages:2743-2758
Erika-Florence M, Leech R, Hampshire A, 2014, A functional network perspective on response inhibition and attentional control, Nature Communications, Vol:5, ISSN:2041-1723
Hampshire A, MacDonald A, Owen AM, 2013, Hypoconnectivity and hyperfrontality in retired American football players., Sci Rep, Vol:3
et al., 2013, Assessing residual reasoning ability in overtly non-communicative patients using fMRI, Neuroimage: Clinical, Vol:2, Pages:174-183
et al., 2012, Fractionating human intelligence., Neuron, Vol:76, Pages:1225-1237
et al., 2011, Lateral prefrontal cortex subregions make dissociable contributions during fluid reasoning., Cereb Cortex, Vol:21, Pages:1-10
et al., 2010, Putting brain training to the test, Nature, Vol:465, ISSN:0028-0836, Pages:775-U6
et al., 2010, The role of the right inferior frontal gyrus: inhibition and attentional control., Neuroimage, Vol:50, Pages:1313-1319
et al., 2008, Orbitofrontal dysfunction in patients with obsessive-compulsive disorder and their unaffected relatives., Science, Vol:321, Pages:421-422
et al., 2008, Attentional control in Parkinson's disease is dependent on COMT val 158 met genotype., Brain, Vol:131, Pages:397-408
Hampshire A, Owen AM, 2006, Fractionating attentional control using event-related fMRI., Cerebral Cortex, Vol:16, ISSN:1047-3211, Pages:1679-1689