Abstract
Neurofeedback training (NFT) could support cognitive symptom management in neurodegenerative diseases such as Huntington’s disease (HD) by targeting brain regions whose function is disrupted by the disease. Identifying the most appropriate target for NFT is not straightforward. The aim of our study was to test whether HD patients can learn to regulate their brain activity using NFT and to compare two different NFT targets, activity NFT using as target the activity from the Supplementary Motor Area (SMA) and connectivity NFT using the correlation between SMA and left striatum signal. To evaluate each approach we measured learning by testing for an increase in NFT target levels across training visits, and near transfer by examining upregulation of the target levels in the absence of feedback after training. The activity NFT treatment group was the only group that showed both successful learning and near transfer, suggesting that it’s a more promising approach in HD than connectivity NFT.