Publication
] NeuroDecodeR: a package for neural decoding in RData_Sheet_1.docx. Frontiers in Neuroinformatics 17, (2024).
Brain-Observatory-Toolbox. (2018).
Dynamic population coding and its relationship to working memory. Journal of Neurophysiology 120, 2260 - 2268 (2018).
A Data Science approach to analyzing neural data. Joint Statistical Meetings (2017).
Differences in dynamic and static coding within different subdivision of the prefrontal cortex. Society for Neuroscience's Annual Meeting - SfN 2017 (2017). at <http://www.abstractsonline.com/pp8/#!/4376/presentation/4782>
Differential Processing of Isolated Object and Multi-item Pop-Out Displays in LIP and PFC. Cerebral Cortex (2017). doi:10.1093/cercor/bhx243
New Data Science tools for analyzing neural data and computational models. Society for Neuroscience (2016).
Review of the CBMM workshop on the Turing++ Question: 'who is there?'. (2016).
Review of the CBMM workshop on the Turing++ Question- 'who is there?' .pdf (555.71 KB)
Review of the CBMM workshop on the Turing++ Question- 'who is there?' .pdf (555.71 KB) Turing++ Questions: A Test for the Science of (Human) Intelligence. AI Magazine 37 , 73-77 (2016). Turing_Plus_Questions.pdf (424.91 KB)
Turing_Plus_Questions.pdf (424.91 KB) How PFC and LIP process single and multiple-object ‘pop-out’ displays. Society for Neuroscience (2015). at <https://www.sfn.org/~/media/SfN/Documents/Annual%20Meeting/FinalProgram/NS2015/Full%20Abstract%20PDFs%202015/SfN15_Abstracts_PDF_Nanos.ashx>
Intelligent Information Loss: The Coding of Facial Identity, Head Pose, and Non-Face Information in the Macaque Face Patch System. The Journal of Neuroscience 35, (2015).
The dynamics of invariant object recognition in the human visual system. J Neurophysiol 111, 91-102 (2014).
The dynamics of invariant object recognition in the human visual system. (2014). doi:http://dx.doi.org/10.7910/DVN/KRUPXZ
The Neural Decoding Toolbox. (2013). at <http://www.readout.info/>