Associative reinstatement memory measures hippocampal function in Parkinson's Disease.

In Parkinson's Disease (PD), hippocampal atrophy is associated with rapid cognitive decline. Hippocampal function is typically assessed using memory tests but current clinical tools (e.g., free recall) also rely on executive functions or use material that is not optimally engaging hippocampal memory networks. Because of the ubiquity of executive dysfunction in PD, our ability to detect true memory deficits is suboptimal. Our previous behavioural and neuroimaging work in other populations suggests that an experimental memory task - Associative Reinstatement Memory (ARM) - may prove useful in investigating hippocampal function in PD. In this study, we investigated whether ARM is compromised in PD and we assessed its convergent and divergent validity by comparing it to standardized measures of memory and of attention and executive functioning in PD, respectively. Using fMRI, we also investigated whether performance in PD relates to degree of hippocampal engagement. Fifteen participants with PD and 13 age-matched healthy controls completed neuropsychological testing as well as an ARM fMRI recognition paradigm in which they were instructed to identify word pairs comprised of two studied words (intact or rearranged pairs) and those containing at least one new word (new or half new pairs). ARM is measured by the differences in hit rates between intact and rearranged pairs. Behaviourally, ARM was poorer in PD relative to controls and was correlated with verbal memory measures, but not with attention or executive functioning in the PD group. Hippocampal activation associated with ARM was reduced in PD relative to controls and covaried with ARM scores in both groups. To conclude, ARM is a sensitive measure of hippocampal memory function that is unaffected by attention or executive dysfunction in PD. Our study highlights the benefit of integrating cognitive neuroscience frameworks and novel experimental tasks to improve the practice of clinical neuropsychology in PD.

Using multivariate data reduction to predict postsurgery memory decline in patients with mesial temporal lobe epilepsy.

Predicting postsurgery memory decline is crucial to clinical decision-making for individuals with mesial temporal lobe epilepsy (mTLE) who are candidates for temporal lobe excisions. Extensive neuropsychological testing is critical to assess risk, but the numerous test scores it produces can make deriving a formal prediction of cognitive change quite complex. In order to benefit from the information contained in comprehensive memory assessment, we used principal component analysis (PCA) to simplify neuropsychological test scores (presurgical and pre- to postsurgical change) obtained from a cohort of 56 patients with mTLE into a few easily interpretable latent components. We next performed discriminant analyses using presurgery latent components to categorize seizure laterality and then regression analyses to assess how well presurgery latent components could predict postsurgery memory decline. Finally, we validated the predictive power of these regression models in an independent sample of 18 patients with mTLE. Principal component analysis identified three significant latent components that reflected IQ, verbal memory, and visuospatial memory, respectively. Together, the presurgery verbal and visuospatial memory components classified 80% of patients with mTLE correctly according to their seizure laterality. Furthermore, the presurgery verbal memory component predicted postsurgery verbal memory decline, while the presurgery visuospatial memory component predicted visuospatial memory decline. These regression models also predicted postsurgery memory decline successfully in the independent cohort of patients with mTLE. Our results demonstrate the value of data reduction techniques in identifying cognitive metrics that can characterize laterality of damage and risk of postoperative decline.