Course Schedule The following is a tentative schedule for the Fall 2018 semester. Date Speaker Title Readings 9/7 Tomaso Poggio (CBMM Module 1) Aspects of a Computational Theory of Intelligence 1) Computational role of eccentricity dependent cortical magnification 2) "Neuroscience-Inspired AI" - Hassabis et al. - Neuron (2017) 3) CBMM Grant Proposal 9/14 Shimon Ullman (CBMM Module 2, 3 and 4) Digital baby: innate structures and knowledge 1) Atoms of recognition in human and computer vision - Ullman et al. - PNAS (2016) 2) From simple innate biases to complex visual concepts - Ullman et al. - PNAS (2012) 9/21 Student holiday 9/28 Matt Wilson (CBMM Module 2) Hippocampal mechanisms of memory and cognition 1) Hippocampal Replay of Extended Experience - Davidson et al. - Neuron (2009) 2) Oscillations, neural computations and learning during wake and sleep - Penagos et al. - Current Opinion in Neurobiology (2017) 3) Enhancement of encoding and retrieval functions through theta phase specific manipulation of hippocampus - Siegle et al. - eLife (2014) 10/05 Gabriel Kreiman (CBMM Module 2) The Brain's Operating System 1) Finding any Waldo with zero-shot invariant and efficient visual search - Zhang et al. - Nature communications (2018) 2) Recurrent computations for visual pattern completion - Tang et al. - Proceedings of the National Academy of Sciences (2018) 10/12 Josh McDermott Sound, Ears, Brains, and World 1) Adaptive and selective time averaging of auditory scenes - McWalter et al. - Current Biology (2018) 2) Summary statistics in auditory perception - McDermott et al. - Nature neuroscience (2013) 3) Sound texture perception via statistics of the auditory periphery: evidence from sound synthesis - McDermott et al. - Neuron (2011) 10/19 Margaret Livingstone (CBMM Module 1) Functional Modules: what good are they and how do we get them? 1) Genealogy of the “grandmother cell” - Gross, C. G. - The Neuroscientist (2002) 2) Why have multiple cortical areas? - Barlow, H. B. - Vision research (1986) 10/26 Andrei Barbu (CBMM Module 4) Language and Vision 1) Deep sequential models for sampling-based planning - Kuo et al. - IROS (2018) 2) Temporal Grounding Graphs for Language Understanding with Accrued Visual-Linguistic Context - Paul et al. - IJCAI (2017) 11/02 Jim DiCarlo Reverse Engineering Human Visual Intelligence 1) How Does the Brain Solve Visual Object Recognition? - DiCarlo et al. - Neuron (2012) 2) Using goal-driven deep learning models to understand sensory cortex -Yamins et al. - Nature Neuroscience (2016) 3) Brain-Score: Which Artificial Neural Network for Object Recognition is most Brain-Like? - Schrimpf et al. - bioRxiv (2018) 11/09 Josh Tenenbaum (CBMM Module 3) Computational Models of Cognition 1) Building Machines That Learn and Think Like People - Lake et al. - Behavioral and Brain Sciences (2016) 2) Galileo: Perceiving physical object properties by integrating a physics engine with deep learning - Wu et al. - NIPS (2015) 3) Marrnet: 3d shape reconstruction via 2.5 d sketches - Wu et al. - NIPS (2017) 4) Efficient inverse graphics in biological face processing - Yildirim et al. - bioRxiv (2018) 11/09 Deadline: Project registration 11/16 Bob Desimone (CBMM Module 2) Attention 1) A Soruce for Feature-based Attention in the Prefrontal Cortex - Bichot et al. - Neuron (2015) 2) Pulvinar-cortex interactions in vision and attention - Zhou et al. - Neuron (2016) 11/21 Deadline: Submission of the draft of the report 11/23 THANKSGIVING - No Class 11/30 Nancy Kanwisher (CBMM Module 3) The Functional Architecture of Human Intelligence 1) Functional neuroanatomy of intuitive physical inference - Fischer et al. - PNAS (2016) 2) Perceiving social interactions in the posterior superior temporal sulcus - Isik et al. - PNAS (2017) 11/30 Deadline: Submission of the final report Or Communication Lab appointment 12/07 Presentations And Extended report deadline if there was an appointment with the Communication Lab
