Dementia due to Alzheimer?s disease (AD) is a leading public health concern in the US with tremendous care costs and no effective pharmacotherapy despite multiple clinical trials. Numerous studies have shown mild cognitive impairment (MCI) to be a precursor to AD and potentially amenable to nonpharmacological intervention. Transcranial magnetic stimulation (TMS) is a promising non-invasive therapeutic approach that has been shown to increase brain plasticity and enhance cognitive functions that are impaired across the AD spectrum. Yet, while TMS has shown benefits in normative populations, there is still a need to show efficacy in AD-related populations. Most previous neurostimulation research on AD and MCI has focused on effects of stimulation at one brain region, however the cognitive processes underlying successful memory are mediated by a complex whole-brain network. Neurostimulation affects multiple sites within a cortical network, but these more global effects have not been used as targets for stimulation because of limited knowledge about what influence of a single site on more widespread cortical changes. The novelty of the current proposal is that we use information about the network control structure of the affected brain areas by considering the influence of neuromodulation on global changes in brain state or connectivity and the underlying vascular changes mediating long-term consequences for behavior. This network-based TMS is informed by functional connectivity and neurovascular as mediators of the behavioral response as a means to specifically tailor the TMS treatment to the neuropathology of each MCI patient, thus individualizing the treatment to achieve better therapeutic effects. To address this problem, we will use multimodal neuroimaging and network modeling during a titrated memory task to demonstrate how focal neurostimulation evokes changes in neural function and behavior in MCI. These goals will be addressed in two specific aims. First, we will use network-based TMS to optimize the activation of a memory success network (MSN) in a group of MCI patients, targeting a TMS site that focused on the controllability of a stimulation site to provide the maximum benefit to memory performance. Second, we will assess longitudinal change in structural and neurovascular factors affecting the efficacy of individualized network-based TMS across multiple sessions of concurrent TMS-fMRI. By creating a multimodal model of these neurovascular deficits related to MCI, we will systematically adjust network-based TMS to demonstrate how the MCI brain might compensate for these neural deficits. The proposed work will be the first of its kind to estimate the utility of network controllability as a TMS target for memory enhancement in AD-related syndromes, and the first to assess the short-term neuroplastic effects of neuromodulation in such rich detail. The knowledge gained by this project may therefore lead to novel and innovative biometrics for gauging pharmacological and nonpharmacological treatment response or for targeted and enriched clinical trials in AD and related disorders.
The proposed research will test a novel network-based neurostimulation approach using MRI-derived measures of brain connectivity to establish target sites for neurostimulation and test for the enhancement of memory function beyond a sham stimulation condition. This will be tested in cohort of MCI adults using network-based transcranial magnetic stimulation (TMS) to assess for behavioral improvement due to the controlled intervention. This study will provide important evidence towards the efficacy of neuromodulatory treatments for memory decline and will accelerate the discovery of potent non-invasive treatments to remediate cognitive decline in cognitively impaired older adults.
