Computational Neuroscience (invited mini-workshop)

Members: Anirban Dutta, Alan Stocker, Andreas Andreou, Bernhard Englitz, Jorg Conradt, Christopher Rozell, Chang-Woo Shin, Clara Suied, Daniel Pressnitzer, David Lester, Daniel Lofaro, frederic broccard, Paco Gomez-Rodriguez, Chuck Higgins, Hynek Hermansky, Ivo Georgiev, Jonathan Tapson, janet wiles, Kazuki Nakada, Matthew Cook, Mounya Elhilali, Michele Rucci, Odelia Schwartz, Patrick Kanold, Piotr Dudek, Ryad Benjamin Benosman, Ravi Shekhar, Shih-Chii Liu, Steve Kalik, Spencer Kellis, Timmer Horiuchi, Tobi Delbruck, Viviane Ghaderi, Andre van Schaik, Xutao Kuang

Organized by Terrence Sejnowski

See wiki:2010/results/cns for results of this topic area.

See the 2009 Computational Neuroscience workshop for format and last year's outcome - an interesting discussion on "what is cognition?". This year, at least half the talks will be on the chalkboard. This year's speakers are:

Speakers

John Allman (Caltech) - Learning/Cognition -

Studies social cognition in primates, particularly in humans. Analyzes neurons in the prefrontal cortex that are involved in regulating self monitoring during learning.

Gert Cauwenberghs (UCSD) - Learning/Engineering

Builds neuromorphic learning chips and systems of chips for large-scale visual processing

Javier Movellan (UCSD) - !Learning / Machine Vision / Developmental Robotics

Builds robots that learn their behaviors, advanced methods for computer vision.

Simon Haykin (McMaster) - Cognition/Engineering

Applies cognitive architectures to engineering problems, including cognitive radio and cognitive radar.

Christof Koch (Caltech) - Cognition/Engineering

Studies consciousness in humans and rats and a founder of the neuromorphic engineering workshop.

Yann LeCun (NYU) - Learning / Engineering

Applies machine learning algorithms to deep belief networks, especially for hierarchical visual processing.

Barry Richmond (NIH) - Learning/Cognition?

Studies learning and vision in monkeys, particularly in areas of the monkey brain that are involved in visual learning and reinforcement learning.

Michael Stryker (UCSF) - Cognition / Learning

Studies synaptic plasticity in the visual systems of cats and mice

Steven Zucker (Yale) - Cognition/Engineering

Develops algorithms for analyzing visual images based on the architecture of the visual cortex for high-level object recognition.

Schedule for second week

Mon PM

Steven Zucker (Yale)

"Distance Images: a new role for LFP's"

Tuesday AM

Yann LeCun (NYU)

"Training Hierarchical Visual Systems" - chalk

Simon Haykin (McMaster)

"Cognitive Radar" - chalk

Tuesday PM

Barry Richmond (NIH)

"Working for what you want: the roles of prefrontal cortex in learning about predicted value."

Wed AM

Christof Koch (Caltech)

"Grandmother like representation in the human medial lobe"? - chalk

Wed PM

John Allman (Caltech)

"The Evolving Brain"

Th AM

Gert Cauwenberghs (UCSD)

"Humans, machines, spikes, and dopamine in sequential games" - chalk

Th PM

Michael Stryker (UCSF)

"Wiring up the brain--how to make the right connections between areas?" - slide

Friday AM

Javier Movellan (UCSD)

"Infomax Approaches to Learning and Control" - chalk

Avis Cohen - (UM)

"The Power and the the Glory of Highly Interdisciplinary Research" - chalk

Friday PM

Terry Sejnowski

"How does the Motor Cortex Control Movement?" - chalk