22 citations · 25 across the 4 of their papers we have counts for
4 papers
Modeling the Sequence of Brain Volumes by Local Mesh Models for Brain Decoding
Itir Onal, Mete Ozay, Eda Mizrak +2
We represent the sequence of fMRI (Functional Magnetic Resonance Imaging) brain volumes recorded during a cognitive stimulus by a graph which consists of a set of local meshes. The…
Learning Deep Temporal Representations for Brain Decoding
Orhan Firat, Emre Aksan, Ilke Oztekin +1
Functional magnetic resonance imaging produces high dimensional data, with a less then ideal number of labelled samples for brain decoding tasks (predicting brain states). In this…
Discriminative Functional Connectivity Measures for Brain Decoding
Orhan Firat, Mete Ozay, Ilke Oztekin +1
We propose a statistical learning model for classifying cognitive processes based on distributed patterns of neural activation in the brain, acquired via functional magnetic resona…
Mesh Learning for Classifying Cognitive Processes
Mete Ozay, Ilke Öztekin, Uygar Öztekin +1
A relatively recent advance in cognitive neuroscience has been multi-voxel pattern analysis (MVPA), which enables researchers to decode brain states and/or the type of information…