日程：2012年7月26日
会場： |
仙台国際センター
|
|---|---|
| 仙台市青葉区青葉山無番地 | |
| http://www.sira.or.jp/icenter/index.html |
スケジュール:
| 2012年7月26日 | |
| 「神経回路網の動的組織化 –研究の最前線–」 "Dynamic organization of neural networks -Frontline researches-" |
|
| 7/26(木） | |
| 9:00-9:05 | Introduction |
| 9:05-9:55 | |
| 9:55-10:45 | Neuronal circuits and computations in the olfactory system Rainer Friedrich (Friedrich Miescher Institute for Biomedical Research) |
| 10:45-11:00 | Break |
| 11:00-11:50 | How neurons code the world: insights from signal processing Dmitri “Mitya” Chklovskii (Janelia Farm Howard Hughes Medical Institute) |
| 11:50-12:10 | General Discussion |
Abstracts and References：
John O'Keefe
University College London
The role of firing rate and spike timing in hippocampal spatial computations
The rodent hippocampal formation constructs a spatial representation of the local environment which can be used to identify the animal' s current location, to remember events that happened there in the past, and to navigate to desirable locations in that environment. Spatial cells found in hippocampal formation represent the animal' s location (place cells), its current heading direction (head direction cells), the metric of the environment (grid cells), and the animal' s distance from boundaries of the environment (boundary vector cells). All of the cells use firing rate as the code for spatial representation. In addition, however place and, perhaps also, grid cells use a timing code. This timing code takes the form of the phase of spike firing relative to the ongoing theta - local field potential (LFP) wave. The sinusoidal theta rhythm is a prominent feature of the hippocampal LFP which ranges between 6 – 11 Hz in the rat, the rate varying as a function of the animal' s running speed. We have suggested that theta-LFP is an integral part of one of the mechanisms by which the hippocampus carries out spatial computations. A key idea here is that there is not one but several theta -like oscillations of differing frequencies which interact within cells and produce oscillatory interference patterns which can account for many of the properties of place and grid cell firing. I will describe these ideas and provide evidence in support of them.
Rainer Friedrich
Neuronal circuits and computations in the olfactory system
Friedrich Miescher Institute for Biomedical Research
Neuronal circuits and computations in the olfactory system
Rigorous quantitative insights into the structure and function of neuronal
cirucits are key to understand how higher brain functions arise from interactions
between large numbers of neurons. We use a small animal model, the zebrafish,
to analyze neuronal computations in the olfactory bulb and cortex by a
combination of optical, physiological, molecular and theoretical approaches.
I will focus on three or four recent findings. First, computational modelling
and mathematical analyses revealed that pattern decorrelation emerges naturally
from generic properties of recurrent neuronal circuits. The underlying
mechanisms do not require adaptation to statistical properties of inputs
and are enhanced by olfactory bulb-like network architecture. Second, we
found that odor representations across olfactory bulb output neurons are
largely invariant to changes in odor concentration but switch abruptly
when one odor is morphed into another. The olfactory bulb therefore classifies
sensory inputs into a large number of discrete outputs. This computation
creates defined, noise-limited stimulus representations and acts as a sensory
filter. Third, we found that telencephalic area Dp, the main target of
the olfactory bulb in zebrafish and the homolog of olfactory cortex, uses
multiple synaptic pathways to integrate sensory information across processing
channels in the olfactory bulb. This integration is thought to establish
synthetic representations of olfactory objects. Fourth, using optogenetic
manipulations of activity patterns in the olfactory bulb and odor stimulation,
we found that neuronal circuits in area Dp perform at least two temporal
filtering operations that tune Dp neurons to those features of input activity
patterns that are particulary informative about precise odor identity.
These results provide insights into olfactory computations and illustrate
general computational principles by which neuronal circuits represent and
process information.
Dmitri “Mitya” Chklovskii
Group Leader, Janelia Farm Howard Hughes Medical Institute
How neurons code the world: insights from signal processing
Our sensory organs face the challenge of communicating information about
the world to the rest of the brain through a limited bandwidth channel.
Because natural stimuli are highly correlated such compression may be accomplished
by predictive coding, a strategy developed by engineers about fifty years
ago. Indeed, many known neurobiological observations, such as center-surround
receptive fields, can be explained in the predictive coding framework.
We demonstrate that a negative feedback circuit commonly found in the brain
may implement both linear and non-linear predictive coding allowing us
to make non-trivial, testable predictions. Therefore, predictive coding
may help formulate a much needed unified theory of sensory processing.