Invited Talks

Participants:

Speaker: Ed Boyden, Massachusetts Institute of Technology
Date: May 2
Title: Optogenetics and Other Tools For Analyzing and Engineering Neural Circuits
Video: Invited talk at the Keck School of Medicine, USC (VIDEO), Invited talk at Case Western (VIDEO)
Paper: Overview of optogenetic techniques: Bernstein and Boyden [3]
Supplements: Mathematical modeling: Börgers et al [4] (PubMed), Boyden Lab
Keywords: optogenetics, cell assemblies, diffuse coordination, gamma oscillation
News: Science Daily story on Silencing Brain Cells With Yellow and Blue light — see also this MIT News story

Speaker: David Cox, Roland Institute, Harvard University
Date: May 16
Title: Large-scale face recognition
Video: Cox and Pinto GTC 2010 (VIDEO)
Paper: Pinto and Cox [19]
Supplements: DiCarlo and Cox [9], Pinto et al [18, 20, 21], Cox Lab
Keywords: verification versus identification, representational invariants, high-throughput screening

Speaker: Tom Dean, Google
Date: April 4
Title: Three Controversial Hypotheses Concerning Computation in the Primate Cortex
Video: Invited talk at the Stanford Center for Mind, Brain and Computation (MCB)) (VIDEO) (SLIDES)
Paper: Dean et al [8] (HTML)
Keywords: computational neuroscience, combinatorial circuits, modularity of mind, scalable computing architectures

Speaker: Dileep George, Vicarious Systems
Date: May 30
Title: Towards a Mathematical Theory of Cortical Micro-circuits
Paper: George and Hawkins [11] (HTML)
Video: George and Brown 2011 Singularity Summit (VIDEO)
Keywords: Bayesian belief propagation, hierarchical temporal memory, cortical neural circuits

Speaker: Dick Lyon, Google
Date: May 9
Title: Does the brain process sound in the time domain?
Video: TBD
Paper: (PAPER), (PAPER)
Supplements: (HTML)
Keywords: auditory images, sparse coding, primary auditory cortex

Speaker: Jim Mutch, Massachusetts Institute of Technology
Date: April 11
Title: Cortical Network Simulator (CNS)
Video: Invited talk at GTC 2010 (VIDEO) (SLIDES)
Paper: Mutch et al [17]
Supplements: Poggio Lab
Keywords: cortical simulation, graphics processing unit, single-instruction multiple-data

Speaker: Bruno Olshausen, University of California, Berkeley
Date: May 23
Title: Finding spatiotemporal patterns of activity in large-scale neural recording data
Video: Invited talk at Center for Information Technology Research in the Interest of Society (VIDEO)
Paper: Cadieu and Oshausen [6]
Supplements: Cadieu and Olshausen [5], Canolty et al [7], Redwood Institute
Keywords: cell assemblies, oscillatory phase coupling, multi-cell recording

Speaker: Sebastian Seung, Massachusetts Institute of Technology
Date: April 18
Title: I am my connectome
Video: Invited talk at Technology Education and Design (TED) (VIDEO)
Paper: Seung [22] and Jain et al [13] (PubMed)
Supplements: Connectome: How the Brain’s Wiring Makes Us Who We Are — Seung [23], MIT 9.691, Seung Lab
Keywords: connectomics, cell-body segmentation, electron microscopy
News: The Human Connectome Project funded by the National Institutes of Health (NIH) — see also this MIT News story

Speaker: Steven Smith, Stanford, University
Date: April 25
Title: The synaptome meets the connectome: fathoming the deep diversity of CNS synapses
Video: Invited talk at Scientific Computing and Imaging Institute at the University of Utah (VIDEO)
Paper: (PAPER)
Supplements: Li et al [15], Micheva et al [16], Smith Lab
Keywords: proteomics, gene expression, array tomography, synaptome
News: Mouse synapses imaged with array tomography — see also the YouTube video and this Stanford News story

Supplements:

Speaker: Michael Gazzaniga, University of California, Santa Barbara
Title: Gifford Lectures at Edinburgh University in 2009
Video: Available from Edinburgh here or the University’s YouTube channel.

Speaker: Eugene Izhikevich, Brain Corporation — formerly at The Neurosciences Institute, San Diego, CA
Papers: Izhikevich and Edelman [12]
Supplements: Supporting material for the PNAS paper including PDF is available here

Speaker: Eric Kandel, Columbia University
Video: Charlie Rose’s Brain Series (VIDEO)

Speaker: Henry Markram, Brain Mind Institute at EPFL
Title: Simulating the Brain: The Next Decisive Years
Video: Invited talk at the 2011 International Supercomputing Conference (ISC) (VIDEO)

Speaker: Dharmendra S. Modha, IBM, Almaden
Title: Towards Engineering the Mind by Reverse Engineering the Brain
Paper: Ananthanarayanan et al [1] (PDF) Video: Invited talk at the Krasnow Institute’s Decade of the Mind Symposium (VIDEO)

Speaker: Paul Rhodes, Evolved Machines
Title: Synthetic Neural Arrays That Wire Themselves
Video: Nvidia High Performance Computing (VIDEO)

Speaker: Robert Sapolsky, Stanford University
Title: Are Humans Just Another Primate?
Video: Invited lecture at the California Academy of Sciences (VIDEO)

Textbooks:

There are no required textbooks for this course but you are expected to do a lot of reading on your own and these three texts are good to have around for reference. I’ve yet to meet anyone who has read them cover to cover but over the years, I’ve probably read most of the chapters in one edition or the other and found them consistently useful. A copy of each book will be put on the reference desk should you want to read a selection, and, in the case of the latter two, you can also often find preprint versions of individual chapters on the web pages of the contributing authors:

References

[1]   Rajagopal Ananthanarayanan, Steven K. Esser, Horst D. Simon, and Dharmendra S. Modha. The cat is out of the bag: cortical simulations with 109 neurons, 1013 synapses. In Proceedings of the Conference on High Performance Computing Networking, Storage and Analysis, pages 63:1–63:12, 2009.

[2]   Mark F. Bear, Barry Connors, and Michael Paradiso. Neuroscience: Exploring the Brain (Third Edition). Lippincott Williams & Wilkins, Baltimore, Maryland, 2006.

[3]   Jacob G. Bernstein and Edward S. Boyden. Optogenetic tools for analyzing the neural circuits of behavior. Trends in Cognitive Sciences, 15:592–600, 2011.

[4]   Christoph Börgers, Giovanni Talei Franzesi, Fiona E. N. LeBeau, Edward S. Boyden, and Nancy J. Kopell. Minimal size of cell assemblies coordinated by gamma oscillations. PLoS Biology, 8(2):e1002362, 2012.

[5]   Charles F. Cadieu and Bruno A. Olshausen. Learning transformational invariants from time-varying natural images. In Dale Schuurmans and Yoshua Bengio, editors, Advances in Neural Information Processing Systems 21. MIT Press, Cambridge, MA, 2008.

[6]   Charles F. Cadieu and Bruno A. Olshausen. Learning intermediate-level representations of form and motion from natural movies. Neural Computation, 24(4):827–866, 2012.

[7]   Ryan T. Canolty, Karunesh Ganguly, Steven W. Kennerley, Charles F. Cadieu, Kilian Koepsell, Jonathan D. Wallis, and Jose M. Carmena. Oscillatory phase coupling coordinates anatomically dispersed functional cell assemblies. Proceedings of the National Academy of Sciences, 107(40):17356–17361, 2010.

[8]   Thomas Dean, Greg S. Corrado, and Jonathon Shlens. Three controversial hypotheses concerning computation in the primate cortex. In Proceedings of the Twenty-Sixth AAAI Conference on Artificial Intelligence, 2012.

[9]   James J. DiCarlo and David D. Cox. Untangling invariant object recognition. Trends in Cognitive Sciences, 11(8):333–341, 2007.

[10]   Michael S. Gazzaniga. The Cognitive Neurosciences (Third Edition). Bradford Books. MIT Press, Cambridge, MA, 2009.

[11]   Dileep George and Jeff Hawkins. Towards a mathematical theory of cortical micro-circuits. PLoS Computational Biology, 5(10), 2009.

[12]   Eugene M. Izhikevich and Gerald M. Edelman. Large-scale model of mammalian thalamo-cortical systems. Proceedings of the National Academy of Science, 105(9):3593–3598, 2008.

[13]   Viren Jain, H. Sebastian Seung, and Srinivas C. Turag. Machines that learn to segment images: a crucial technology for connectomics. Current Opinion in Neurobiology, 20(5):1–14, 2010.

[14]   E.R. Kandel, J.H. Schwartz, and T.M. Jessell. Principles of neural science (Fourth Edition). McGraw-Hill, Health Professions Division, 2000.

[15]   L. Li, B. Tasic, K.D. Micheva, V.M. Ivanov, M.L. Spletter, S.J. Smith, and L. Luo. Visualizing the distribution of synapses from individual neurons in the mouse brain. PLoS Biology, 5(7):e11503, 2010.

[16]   K.D. Micheva, B.L. Busse, N.C. Weiler, N. O’Rourke, and S.J. Smith. Single-synapse analysis of a diverse synapse population: Proteomic imaging methods and markers. Neuron, 68(4):639–653, 2010.

[17]   Jim Mutch, Ulf Knoblich, and Tomaso Poggio. CNS: a GPU-based framework for simulating cortically-organized networks. Technical Report MIT-CSAIL-TR-2010-013 / CBCL-286, Massachusetts Institute of Technology, Cambridge, MA, February 2010.

[18]   N. Pinto, J.J. DiCarlo, and D.D. Cox. How far can you get with a modern face recognition test set using only simple features? In IEEE Computer Society Conference on Computer Vision and Pattern Recognition, pages 2591–2598. IEEE Computer Society, 2009.

[19]   Nicolas Pinto and David D. Cox. Beyond Simple Features: A Large-Scale Feature Search Approach to Unconstrained Face Recognition. In IEEE Automatic Face and Gesture Recognition, pages 8–15, 2011.

[20]   Nicolas Pinto, David Doukhan, James DiCarlo, and David Cox. A high-throughput screening approach to discovering good forms of biologically inspired visual representation. PLoS Computational Biology, 5(11):e1000579, November 2009.

[21]   Nicolas Pinto, Zac Stone, Todd Zickler, and David D. Cox. Scaling-up Biologically-Inspired Computer Vision: A Case-Study on Facebook. In IEEE Computer Vision and Pattern Recognition, Workshop on Biologically Consistent Vision, pages 35–42, 2011.

[22]   H. Sebastian Seung. Reading the book of memory: Sparse sampling versus dense mapping of connectomes. Neuron, 62(1):17–29, 2009.

[23]   Sebastian Seung. Connectome: How the Brain’s Wiring Makes Us Who We Are. Houghton Mifflin Harcourt, Boston, 2012.