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Simon W Davis

Publications and source records attributed to Simon W Davis.

2 recordsLinked to original sources

Causal Relationships Underlying Episodic Memory Network Dynamics in Older Adults

Lesion and functional neuroimaging evidence suggest that local network deficits can be compensated by global network over-recruitment during a cognitive task. However, the neural mechanisms linking local and global network changes remain uncertain. To investigate this issue, we manipulated local function using repetitive transcranial magnetic stimulation (rTMS) and measured structural and task-based functional network organization during memory encoding. The study yielded two main findings. First, consistent with the compensation hypothesis, 1-Hz rTMS attenuated local activity in the stimulated left prefrontal cortex (PFC) but increased the connectivity of this region with other brain areas, including contralateral PFC. Second, this 1-Hz related increase in global connectivity effects was associated with the volume of more global connections, suggesting white-matter constraints adaptive changes in functional connectivity. Taken together, these results clarify the neural mechanisms linking local and global network changes and the role of structural connectivity.

Neuroscience

A watershed model of individual differences in fluid intelligence

Fluid intelligence is a crucial cognitive ability that predicts key life outcomes across the lifespan. Strong empirical links exist between fluid intelligence and processing speed on the one hand, and white matter integrity and processing speed on the other. We propose a watershed model that integrates these three explanatory levels in a principled manner in a single statistical model, with processing speed and white matter figuring as intermediate endophenotypes. We fit this model in a large (N=555) adult lifespan cohort from the Cambridge Centre for Ageing and Neuroscience (Cam-CAN) using multiple measures of processing speed, white matter health and fluid intelligence. The model fit the data well, outperforming competing models and providing evidence for a many-to-one mapping between white matter integrity, processing speed and fluid intelligence. The model can be naturally extended to integrate other cognitive domains, endophenotypes and genotypes.

Neuroscience