The Cambridge Centre for Ageing and Neuroscience (Cam-CAN) uses epidemiological, behavioral, and neuroimaging data to understand how individuals can best retain cognitive abilities into old age. The Cam-CAN Data Access Portal provides access to datasets from the Cambridge Centre for Ageing and Neuroscience, including neuroimaging and cognitive data from participants aged 18-90.
Cam-CAN is a research project at the University of Cambridge focused on understanding cognitive decline and healthy ageing. It aims to improve our understanding of how people can maintain cognitive abilities as they age. The portal offers a range of data from the Cam-CAN project, including MRI and MEG scans, cognitive assessments, and demographic information. Researchers can apply for access to these freely available datasets to study cognitive ageing.
This study surveys the attitudes and behaviors of US higher education faculty members regarding online resources, the library, and related topics. It covers a wide range of issues, including faculty dependence on electronic scholarly resources, the transition from print to electronic journals, publishing preferences, e-books, and the preservation of scholarly journals.
This project implements the conversion algorithm from the ToMi dataset to the T4D (Thinking is for Doing) dataset, as introduced in the paper https://arxiv.org/abs/2310.03051. It filters examples with Theory of Mind (ToM) questions and adapts the algorithm to account for second-order false beliefs.
This dataset contains 20,000 labelled English tweets of depressed and non-depressed users. The data is collected using the Twitter API and includes feature extraction techniques such as topic modelling and emoji sentiment analysis. It is designed for mental health classification at the tweet level.