Patrick McClure

This paper validates the neural representations of Deep RL agents against animal neural data, showing similar geometry in latent spaces and the role of temporal information.

The paper evaluates how insufficient eye tracking data affects fixation preference reliability and between-group differences in typically developing and ASD participants.

This paper discusses how deep neural networks can model neural responses and cognitive functions, highlighting their accuracy and potential in computational neuroscience.

This paper compares recurrent convolutional neural networks with feedforward models for object recognition, finding recurrent networks more accurate and robust, especially under occlusion and noise.