Seminars

Instructions

1. Check the internal calendar (here) for a free seminar slot. If a seminar is not already booked at the regular time of noon on Wednesday, you can reserve it.
2. Make a note on this page in the Tentative Speakers section that you are going to invite a speaker. Please include your name and email as host in case somebody wants to contact you.
3. Invite a speaker.
4. As soon as the speaker confirms, move the information to the Confirmed Speakers section.
5. Put the date into the internal calendar
6. Notify Jimmy [1] that we have a confirmed speaker so that he can update the public web page. Please include a title and abstract.
7. Notify Sharyn mailto:climons@berkeley.edu about the seminar date so she knows to send out an announcement.

Tentative Speakers

24-28 March 2008 - spring break

9 Apr 2008 or 30 Apr 2008

• Speaker: Thanos Siapas
• Affiliation: Caltech
• Host: Amir
• Title: TBD
• Abstract: TBD

Confirmed Speakers

6 Feb 2008

• Speaker: Pam Reinagel
• Affiliation: UCSD
• Host: Fritz
• Title: How context influences representation of visual information in the LGN
• Abstract:

13 Feb 2008

• Speaker: Marcelo Magnasco
• Affiliation: Rockefeller University
• Host: Kilian
• Title: Sparse time-frequency representations and the neural coding of sound
• Abstract:

20 Feb 2008

• Speaker: Costa Colbert
• Affiliation: Evolved Machines
• Host: Bruno
• Title:
• Abstract:

26/27 Feb 2008

• Speaker: Jean-Philippe Lachaux
• Affiliation: INSERM, Lyon
• Host: Tim
• Title:
• Abstract:

6 Mar 2008

• Speaker: Peter Robinson
• Affiliation: University of Sydney
• Host: Tim
• Title:
• Abstract:

12 Mar 2008

• Speaker: Ilana Witten
• Affiliation: Stanford University
• Host: Mike
• Title: Spatial Processing in a Complex Auditory Environment
• Abstract: A single, stationary object in the auditory environment activates space-selective neurons in the brain, which in turn direct orienting movements towards the object. However, the natural auditory environment is typically complex, containing auditory objects that move through space, as well as multiple simultaneous objects. Moreover, auditory objects need to be integrated with the corresponding visual objects. This complexity provides challenges that the brain most overcome in order to localize sounds appropriately. For instance, when a sound moves through space, neural activity must predict the sound's future location in order to compensate for sensorimotor delays involved in sound orienting behavior. When there are multiple sounds in the environment, the animal must decide whether or not to group them perceptually, and if they are grouped, the animal must decide where to localize them. Finally, when the animal is faced with conflicting localization information from auditory and visual systems, it must employ learning rules that can appropriately reinstate crossmodal alignment. I will describe how the auditory system mediates localization behavior and represents the auditory environment in the face of each of these complexities.

19 March 2008

• Speaker: Dana Ballard
• Affiliation: University of Texas, Austin
• Host: Fritz
• Title:
• Abstract:

26 March 2008

• Speaker: Nick Priebe
• Affiliation: University of Texas at Austin
• Host: Mike
• Title: TBA
• Abstract:

2 Apr 2008

• Speaker: Marty Usrey
• Affiliation: UC Davis
• Host: Bruno
• Title:
• Abstract:

16 Apr 2008

• Speaker: Ueli Rutishauser
• Affiliation: Caltech
• Host: Will
• Title: State dependent computation using coupled recurrent networks
• Abstract: Although procedural information processing composed of conditional

decisions is a hallmark of intelligent behavior, its neuronal implementation remains an open question. Physiological experiments have reported behavioral-state encoding neurons in the frontal cortices, but the organization of the neuronal circuits that could support such state-dependent processing is very poorly understood. In recent years, neuroanatomical studies have demonstrated rich inter-connections between neurons in the superficial layers of the cortex, and theoretical models have explained how recurrent connections within small populations of neurons can support co-operative competitive dynamics. We show by theoretical analysis and simulations how these circuits can embed reliable robust neuronal finite state-machines, which could support generic conditional processing in the neocortex. We demonstrate how a multi-stable neuronal network that embeds a number of states can be created very simply, by coupling two recurrent networks whose synaptic weights have been set within a range that offers soft winner-take-all (sWTA) performance. The two sWTAs have simple, homogenous locally recurrent connectivity except for a small fraction of recurrent cross-connections between them that are used to embed the required states. This coupling between the maps allows them to retain their current state after the input that elicted that state is withdrawn. A small number of 'transition neurons' implement the necessary input-driven transitions between the embedded states. We provide simple rules to systematically design and construct an arbitrary neuronal state machine composed of nearly identical recurrent maps. The significance of our finding is that it offers a method whereby the cortex could achieve a broad range of sophisticated processing by only limited specialization of the same generic neuronal circuit.

joint work by Ueli Rutishauser (Caltech) and Rodney J. Douglas (INI/ETH Zurich)

23 Apr 2008

• Speaker: Mark Goldman
• Affiliation: UC Davis
• Host: Bruno
• Title: Modeling the mechanisms underlying memory-related neural activity
• Abstract:

Previous Seminars

2007/2008 academic year

30 Jan 2008

• Speaker: Kai Miller
• Affiliation: University of Washington
• Host: Kilian
• Title: Changes in local cortical activity are revealed by a power law in the cortical potential spectrum
• Abstract: I will begin by demonstrating how careful experimental technique

reveals a power law of the form P~Af^-chi in the electrocortical potential spectrum with exponent \chi=4.0 \pm 0.1 above ~70Hz, and evidence for a power law with \chi_{low}=2.0 \pm 0.4 below this. During a simple finger flexion task, the potential spectrum is effectively decoupled into this power law and the \alpha and \beta rhythms. I will demonstrate that increases in the coefficient, A, of this power law (not the exponent) correspond to local cortical function and reveal discrete finger somatotopy. Finally, I will discuss some possible interpretations for the source and nature of these changes.

Nov. 27

• Speaker: Geoff Hinton
• Affiliation: Dept. of Computer Science, University of Toronto
• Host: Bruno
• Title: How are error derivatives represented in the brain
• Abstract: Neurons need to represent both the presence of a feature in the

sensory input and the derivative of an error function with repect to the neural activity. I will describe a simple way in which they can represent both of these very different quantities at the same time and show that this representational scheme would make it easy for real neurons to backpropagate error derivatives so that higher level feature detectors can fine-tune the receptive fields of lower level ones.

Nov. 13

• Speaker: Sonja Gruen
• Affiliation: Riken
• Host: Fritz
• Title: Spike synchrony and spike-LFP relation in freely viewing monkeys
• Abstract:

Oct. 31

• Speaker: Jason Kerr
• Affiliation: Max Planck Institute for Biological Cybernetics
• Host: Tim
• Title: TBA

Oct. 29

• Speaker: Laurenz Wiskott
• Affiliation: Bernstein Center for Computational Neuroscience and Institute for Theoretical Biology, Humboldt-University Berlin
• Host: Bruno
• Title: Slow feature analysis for modeling place cells in the hippocampus and its relationship to spike timing dependent plasticity
• Abstract: Slow Feature Analysis (SFA) is an algorithm for extracting slowly varying

features from a quickly varying signal. We have applied SFA to the learning of complex cell receptive fields, visual invariances for whole objects, and place cells in the hippocampus. Here I will report about our results on modeling place cells in the hippocampus. If slowness is indeed an important learning principle in visual cortex and beyond, the question arises, how it could be implemented in a biologically plausible learning rule. In the second part of the talk I will show analytically that for linear Poisson units, SFA can be implemented with STDP with the standard learning window as measured by, e.g., Bi and Poo (1998).

Oct. 23

• Speaker: Liam Paninski
• Affiliation: Columbia Univesrity
• Host: Amir
• Title: Combining biophysical and statistical methods for understanding neural codes
• Abstract:

The neural coding problem --- deciding which stimuli will cause a given neuron to spike, and with what probability --- is a fundamental question in systems neuroscience. The high dimensionality of both stimuli and spike trains has spurred the development of a number of sophisticated statistical techniques for learning the neural code from finite experimental data. In particular, modeling approaches based on maximum likelihood have proven to be flexible and powerful.

We present three such applications here. One common thread is that the models we have chosen for these data each have concave loglikelihood surfaces, permitting tractable fitting (by maximizing the loglikelihood) even in high dimensional parameter spaces, since no local maxima can exist for the optimizer to get `stuck' in.

First we describe neural encoding models in which a linear stimulus filtering stage is followed by a noisy integrate-and-fire spike generation mechanism incorporating after-spike currents and spike-dependent conductance modulations. This model provides a biophysically more realistic alternative to models based on Poisson (memoryless) spike generation, and can effectively reproduce a variety of spiking behaviors. We use this model to analyze extracellular data from populations of retinal ganglion cells, simultaneously recorded during stimulation with dynamic light stimuli. Here the model provides insight into the biophysical factors underlying the reliability of these neurons' spiking responses, and provides a framework for analyzing the cross-correlations observed between these cells. (Joint work with E.J. Chichilnisky, J. Pillow, J. Shlens, E. Simoncelli, and V. Uzzell, at NYU and Salk.)

Next we describe how to use this model to ``decode the underlying subthreshold somatic voltage dynamics, given only the superthreshold spike train. We also point out some connections to spike-triggered averaging techniques.

We close by discussing recent extensions to highly biophysically-detailed, conductance-based models, which have the potential to allow us to estimate the density of active channels in a cell's membrane and also to decode the synaptic input to the cell as a function of time. (With M. Ahrens, Q. Huys, and J. Vogelstein, at Gatsby and Johns Hopkins.)

Oct. 3

• Speaker: Flip Sabes
• Affiliation: Keck Center/UCSF
• Host: Bruno
• Title: TBA
• Abstract:

2007 summer seminars

August 21, 2007

• Speaker: Jeremy Lewi
• Affiliation: Georgia Tech
• Host: Amir
• Title: Adaptively optimizing neurophysiology experiments for estimating encoding models

2006/2007 academic year

May 15, 2007

• Speaker: Ray Guillery
• Affiliation: University of Madisson, WI/Marmara University
• Host: Fritz
• Title: Thalamus and Sensorimotor Aspects of Perception

May 8

• Speaker: Lokendra Shastri
• Affiliation: ICSI
• Host: Bruno
• Title: Micro-circuits of Episodic Memory: Structure Matches Function in the Hippocampal System

April 24

• Speaker: Jeff Johnson
• Affiliation: UC Davis
• Host: Bruno
• Title: What does EEG tell us about the timecourse of object recognition?

April 17, 2007

• Speaker: Steve Waydo
• Affiliation: Control & Dynamical Systems, California Institute of Technology
• Host: Bruno
• Title: Explicit Object Representation by Sparse Neural Codes

April 10

• Speaker: Andrew Ng
• Affiliation: Stanford University
• Host: Bruno
• Title: Unsupervised discovery of structure for transfer learning

April 3

• Speaker: Robert Miller
• Affiliation: Department of Anatomy and Structural Biology, Otago University
• Host: Fritz
• Title: Axonal conduction time and human cerebral laterality

March 20, 2007

• Speaker: Jeff Hawkins
• Affiliation: Numenta
• Host: Bruno
• Title: Hierarchical Temporal Memory

March 13, 2007

• Speaker: Chris Wiggins
• Affiliation: Columbia University, NY
• Host: Tony
• Title: Optimal signal processing in small stochastic biochemical networks

March 6

• Speaker: Pietro Perona
• Affiliation: Caltech
• Host: Bruno
• Title: An exploration of visual recognition

March 1

• Speaker: Hiroki Asari
• Affiliation: CSL
• Host: Fritz
• Title: Sparse Representations for the Cocktail Party Problem
• Abstract: A striking feature of many sensory processing problems is that there appear to be many more neurons engaged in the internal representations of the signal than in its transduction. For example, humans have about 30,000 cochlear neurons, but at least a thousand times as many neurons in the auditory cortex. Such apparently redundant internal representations have sometimes been proposed as necessary to overcome neuronal noise. We instead posit that they directly subserve computations of interest. Here we provide an example of how sparse overcomplete linear representations can directly solve difficult acoustic signal processing problems, using as an example monaural source separation using solely the cues provided by the differential filtering imposed on a source by its path from its origin to the cochlea (the head-related transfer function, or HRTF). In contrast to much previous work, the HRTF is used here to separate auditory streams rather than to localize them in space. The experimentally testable predictions that arise from this model--- including a novel method for estimating a neuron's optimal stimulus using data from a multi-neuron recording experiment---are generic, and apply to a wide range of sensory computations.

February 20, 2007

• Speaker: Yair Weiss
• Affiliation: Hebrew University, Jerusalem
• Host: Tony
• Title: What makes a good model of natural images?

February 13, 2007

• Speaker: Tobi Delbruck
• Affiliation: Inst of Neuroinformatics, UNI-ETH Zurich
• Host: Bruno
• Title: Building a high-performance event-based silicon retina leads to new ways to compute vision
• URL: http://siliconretina.ini.uzh.ch

Jan 23, 2007

• Speaker: Giuseppe Vitiello
• Affiliation: Department of Physics “E.R.Caianiello”, Salerno University
• Host: Fritz
• Title: Relations between many-body physics and nonlinear brain dynamics

Jan 9, 2007

• Speaker: Boris Gutkin
• Affiliation: University of Paris
• Host: Fritz
• Title: TBA

Dec 5

• Speaker: Tanya Baker
• Affiliation: U Chicago
• Host: Kilian
• Title: What Forest Fires Tell Us About the Brain

December 1, 2006 1.30pm

• Informal visit: Nancy Kopell
• Affiliation: Boston University
• Host: Fritz
• Title: No talk: Informal visit in the afternoon

Nov 28

• Speaker: Thomas Dean
• Host: Bruno
• Affiliation: Brown University/Google
• Title: TBA

Nov 21

• Speaker: Urs Koster
• Host: Bruno
• Affiliation: University of Helsinki
• Title: Towards Multi-Layer Processing of Natural Images

Nov 14

• Speaker: Andrew D. Straw
• Affiliation: Bioengineering, California Institute of Technology
• Host: Kilian
• Title: Closed-Loop, Visually-Based Flight Regulation in a Model Fruit Fly

Nov 7

• Speaker: Mitya Chklovskii
• Host: Bruno
• Title: What determines the shape of neuronal arbors?

Oct 31

• Speaker: Matthias Kaschube
• Host: Kilian
• Title: A mathematical constant in the design of the visual cortex

Oct 3

• Speaker: Jay McClelland
• Affiliation: Mind, Brain & Computation/MBC, Psychology Department, Stanford
• Host: Evan
• Title: Graded Constraints in English Word Forms (video)

Sept 25

• Speaker: Peter Latham
• Affiliation: Gatsby Unit, UCL
• Host: Bruno
• Title: Requiem for the spike (video)

Sept 19

• Speaker: Jerry Feldman
• Affiliation: ICSI/UC Berkeley
• Host: Bruno
• Title: From Molecule to Metaphor: Towards a Unified Cognitive Science (video)

Sept 5

• Speaker: Tom Griffiths
• Affiliation: Cogsci/UC Berkeley
• Host: Bruno
• Title: Natural Statistics and Human Cognition (video)

Aug 1

• Speaker: Carol Whitney
• Affiliation: U Maryland
• Host: Bruno
• Title: What can Visual Word Recognition Tell us about Visual Object Recognition? (video)

July 18

• Speaker: Evan Smith
• Affiliation: Redwood Center/Stanford
• Host: Bruno
• Title: Efficient auditory coding

2005/2006 academic year

June 20

• Speaker: Vincent Bonin
• Affiliation: Smith Kettlewell Institute
• Host: Thomas
• Title:

June 15

• Speaker: Philip Low
• Affiliation: Salk Institute
• Host: Tony
• Title: A New Way To Look At Sleep

May 2

• Speaker: Dileep George
• Affiliation: Numenta
• Host: Bruno
• Title: Hierarchical, cortical memory architecture for pattern recognition

April 18

• Speaker: Risto Miikkulainen
• Affiliation: The University of Texas at Austin
• Host: Bruno
• Title: Computational maps in the visual cortex (video)

April 11

• Speaker: Charles Anderson
• Affiliation: Washington University School of Medicine
• Host: Bruno
• Title: Population Coding in V1 (video)

April 10

• Speaker: Charles Anderson
• Affiliation: Washington University School of Medicine
• Host: Bruno
• Title: A Comparison of Neurobiological and Digital Computation (video)

April 4

• Speaker: Odelia Schwartz
• Affiliation: The Salk Institute
• Host: Bruno
• Title: Natural images and cortical representation

March 21

• Speaker: Mark Schnitzer
• Affiliation: Stanford University
• Host: Amir
• Title: In vivo microendoscopy and computational modeling studies of mammalian brain circuits

March 15

• Speaker: Mate Lengyel
• Affiliation: Gatsby Unit/UCL London
• Host: fritz
• Title: Bayesian model learning in human visual perception (video)

March 14

• Speaker: Mate Lengyel
• Affiliation: Gatsby Unit/UCL London
• Host: fritz
• Title: Firing rates and phases in the hippocampus: what are they good for? (video)

March 7

• Speaker: Michael Wu
• Affiliation: Gallant lab/UC Berkeley
• Host: Bruno
• Title: A Unified Framework for Receptive Field Estimation

February 28

• Speaker: Dario Ringach
• Affiliation: UCLA
• Host: thomas
• Title: Population dynamics in primary visual cortex

February 21

• Speaker: Gerard Rinkus
• Affiliation: Brandeis University
• Host: Bruno
• Title: Hierarchical Sparse Distributed Representations of Sequence Recall and Recognition (video)

February 14

• Speaker: Jack Cowan
• Affiliation: U Chicago
• Host: Bruno
• Title: Spontaneous pattern formation in large scale brain activity: what visual migraines and hallucinations tell us about the brain (video)

February 7

• Speaker: Christian Wehrhahn
• Affiliation: Max Planck Institute for Biological Cybernetics, Tuebingen, Germany
• Host: Tony
• Title: Seeing blindsight: motion at isoluminance?

January 23 (Monday)

• Speaker: Read Montague
• Affiliation: Baylor College of Medicine
• Host: Bruno
• Title: Abstract plans and reward signals in a multi-round trust game

January 17

• Speaker: Erhardt Barth
• Affiliation: Institute for Neuro- and Bioinformatics, Luebeck, Germany
• Host: Bruno
• Title: Guiding eye movements for better communication (video)

January 3

• Speaker: Dan Butts
• Affiliation: Harvard University
• Host: Thomas
• Title: "Temporal hyperacuity": visual neuron function at millisecond time resolution

December 13, 2005

• Speaker: Paul Rhodes
• Affiliation: Stanford University
• Title: Simulations of a thalamocortical column with compartment model cells and dynamic synapses (video)

December 6, 2005

• Speaker: Special debate between Walter J. Freeman and Robert Hecht-Nielsen
• Affiliation: University of California at Berkeley (Walter). University of California at San Diego (Robert)
• Title: Waves or words in neocortex
• Video: Walter, Robert

November 29, 2005

• Speaker: Stanley Klein
• Affiliation: School of Optometry, UC Berkeley
• Title: Limits of Vision and psychophysical methods (video)

November 22, 2005

• Speaker: Scott Makeig
• Affiliation: Swartz Center for Computational Neuroscience, Institute for Neural Computation, UCSD
• Title: Viewing event-related brain dynamics from the top down