Venue: NeurIPS 2019 Workshop Neuro_AI

Reviews:

final_score: rating: null
review_content: importance_comment: Neural decoding is an important problem with applications throughout neuroscience.
rigor_comment: The methods appear to be correct and are well explained.
clarity_comment: The paper is well written but is well over the limit for this workshop. Its clear that the authors didn't try to shorten their paper for this workshop.

Figure 2 says "Sates" instead of "States"
intersection_comment: Interesting use of ML methods to analyze neural datasets.
comment: The contribution is relevant to the workshop and is well written.
review_title: Interesting paper on decoding cognitive states from fMRI data with graph convolutional NNs

final_score: rating: null
review_content: importance_comment: This paper convincingly shows how graph convolutional networks can provide very robust and interpretable predictions of cognitive states from brain activity.
rigor_comment: This is simply a solid paper which includes various control analyses.
clarity_comment: Clear and well-written
intersection_comment: Nice application of GCNs for cognitive state decoding.
comment: Thorough theoretically rigorous application of a new approach for rapid decoding of cognitive states.
review_title: Well-written and solid paper providing biologically meaningful results about neural grounding of cognitive states

Decision: Accept (Oral)