44 citations · 59 across the 5 of their papers we have counts for
5 papers
Embedding of Low-Dimensional Sensory Dynamics in Recurrent Networks: Implications for the Geometry of Neural Representation
Vikas N. O'Reilly-Shah, Alessandro Maria Selvitella
Neural population activity in sensory cortex is organized on low-dimensional manifolds, but why such manifolds arise and what determines their geometry remain unclear. We model cor…
Shared Space Transfer Learning for analyzing multi-site fMRI data
Muhammad Yousefnezhad, Alessandro Selvitella, Daoqiang Zhang +2
Multi-voxel pattern analysis (MVPA) learns predictive models from task-based functional magnetic resonance imaging (fMRI) data, for distinguishing when subjects are performing diff…
Deep Representational Similarity Learning for analyzing neural signatures in task-based fMRI dataset
Muhammad Yousefnezhad, Jeffrey Sawalha, Alessandro Selvitella +1
Similarity analysis is one of the crucial steps in most fMRI studies. Representational Similarity Analysis (RSA) can measure similarities of neural signatures generated by differen…
Supervised Hyperalignment for multi-subject fMRI data alignment
Muhammad Yousefnezhad, Alessandro Selvitella, Liangxiu Han +1
Hyperalignment has been widely employed in Multivariate Pattern (MVP) analysis to discover the cognitive states in the human brains based on multi-subject functional Magnetic Reson…
Statistical Inference, Learning and Models in Big Data
Beate Franke, Jean-François Plante, Ribana Roscher +11
The need for new methods to deal with big data is a common theme in most scientific fields, although its definition tends to vary with the context. Statistical ideas are an essenti…