Systems Neuroscience of Human Memory and its Disorders
The aim of this work is to understand how our brains enable our memories. Specifically, we use the techniques of fMRI and EEG/MEG to examine brain activity as healthy volunteers try to remember things in the laboratory, and relate these findings to the memory problems following brain damage. We are interested in the neural bases of both explicit (conscious) memory and implicit (unconscious) memory, particularly the relationship between recollection, familiarity, and priming, and the relationship between memory and perception. A deeper knowledge of these different expressions of memory is important for understanding the memory impairments associated with neurological damage, with normal “healthy” ageing and with neurodegenerative diseases such as dementia.
When something happens that violates our expectations (incongruent), what exactly determines how well this event is encoded? In our PIMMS model (e.g, Henson & Gagnepain, 2010), we characterised this in terms of prediction error (PE): the divergence between a prior probability distribution and a likelihood (evidence). We have conducted a number of experiments that confirm this basic prediction for episodic memory (Greve et al., 2017). We are currently exploring how PE operates at all levels of the visual processing hierarchy, both in perception and memory, including priming and familiarity.
Henson, R.N. & Gagnepain, P. (2010). Predictive, Interactive Multiple Memory Systems. Hippocampus, 20, 1315-1326.
Van Kesteren, M.T.R., Ruiter, D.J., Fernández, G. & Henson, R.N. (2012). How schema and novelty augment memory formation. Trends in Neurosciences, 35, 211-219.
Greve, A., Cooper, E., Kaula, A., Anderson, M.C. & Henson, R.N. (2017). Does Prediction Error drive one-shot declarative learning? Journal of Memory and Language, 94, 149-165.
Greve, A., Cooper, E., Tibon, R. & Henson, R.N. (2019). Knowledge is power: prior knowledge aids memory for both congruent and incongruent events, but in different ways. Journal of Experimental Psychology: General, 148, 325-341.
Barense, M.D, Groen, I, Lee, A.C, Yeung, L-K, Brady, S.M, Gregori, M, Kapur, N, Bussey, T.J, Saksida, L.M. & Henson, R.N. (2012). Intact memory for irrelevant information impairs perception in amnesia. Neuron, 75, 157-167.
Staresina, B.P., Fell, J. Do Lam, A.T.A., Axmacher, N. & Henson, R.N. (2012). Memory signals are temporally dissociated within and across human Hippocampus and Perirhinal cortex. Nature Neuroscience, 15, 1167-1173.
Henson, R.N., Greve, A., Cooper, E., Gregori, M., Simons, J.S., Geerligs, L., Erzinçlioğlu, S., Kapur, N. & Browne, G. (2016). The effects of hippocampal lesions on MRI measures of structural and functional connectivity. Hippocampus, 26, 1447–1463.
Henson, R.N., Horner, A.J., Greve, A., Cooper, E., Gregori, M., Simons, J.S., Erzinçlioğlua, S., Browne, G. & Kapur, N. (2017). No effect of hippocampal lesions on stimulus-response bindings. Neuropsychologia, 103, 106–114.
Greve, A., Cooper, E. & Henson, R.N. (2014). No evidence that ‘fast-mapping’ benefits novel learning in healthy older adults. Neuropsychologia, 60, 52-59.
Henson, R.N., Campbell, K.L., Davis, S.W., Taylor, J.R., Emery, T., Erzinclioglu, S., Cam-CAN & Kievit, R.A. (2016). Multiple determinants of lifespan memory differences. Scientific Reports, 6:32527.
Cooper, E., Greve, A. & Henson, R.N. (2017). Assumptions behind Scoring Source versus Item Memory: Effects of Age, Hippocampal Lesions and Mild Memory Problems. Cortex, 91, 297-315.
Morcom, A.M., Cam-CAN & Henson, R.N. (2018). Increased prefrontal activity with aging reflects nonspecific neural responses rather than compensation. Journal of Neuroscience, 38, 7303–7313.
Maestu, F., Peña, J.M., Garcés, P., Gonzalez, S., Bajo, R., Bagic, A., Cuesta, P., Funke, M., Makela, J. Menasalvas, E., Nakamura, A., Parkkonen, L., Lopez, M.E., del Pozo, F., Sudre, G., Zamrini, E., Pekkonen, E., Henson, R. & Becker, J. (2015). A multicenter study of the early detection of synaptic dysfunction in mild cognitive impairment using magnetoencephalography-derived functional connectivity. Neuroimage: Clinical, 9, 103-109.
Sami, S., Hughes, L.E., Williams, N., Cope, C.E., Rittman, T., Coyle-Gilchrist, I., Henson, R.N. & Rowe, J.B. (2018). Neurophysiological signatures of Alzheimer’s disease and Frontotemporal lobar degeneration: pathology versus phenotype. Brain, 141, 2500-2510.
Dr Andrea Greve (MRC Band 4 Postdoc)
Dr Elisa Cooper (MRC Band 4 Postdoc)
Dr Roni Tibon (Newton Fellow)
Dr Aya Ben-Yakov (EU Marie Curie Fellow)
Dr Darren Price (MRC CamCAN Postdoc)
Mr Alex Kaula (Gates PhD Student)
Mr Jiri Cevora (Gates PhD Student)
Dr David Nesbitt (MD/PhD)