My lab's interests focus on understanding the cerebral cortex. We use theoretical and computational methods to unravel the circuitry of the cerebral cortex, the rules by which this circuitry develops or "self-organizes", and the computational functions of this circuitry. Our guiding hypothesis -- motivated by the stereotypical nature of cortical circuitry across sensory modalities and, with somewhat more variability, across motor and "higher-order" cortical areas as well -- is that there are fundamental computations done by the cortical circuit that are invariant across highly varying input signals. In some way that does not strongly depend on the specific content of the input, cortex extracts invariant structures from its input and learns to represent these structures in an associative, relational manner. We (and many others) believe the atomic element underlying these computations is likely to be found in the computations done by a roughly 1mm-square chunk of the cortical circuit. To understand this element, we have focused on one of the best-studied cortical systems, primary visual cortex, and also have interest in any cortical system in which the data gives us a foothold (such as rodent whisker barrel cortex, studied here at Columbia by Randy Bruno, and monkey area LIP, studied here by Mickey Goldberg and Jackie Gottlieb).
The function of this element depends both on its mature pattern of circuitry and on the developmental and learning rules by which this circuitry is shaped by the very inputs that it processes. Thus we focus both on understanding how the mature circuitry creates cortical response properties (see lab publications on Models of Neuronal Integration and Circuitry, below) and on how this circuitry is shaped by input activity during development and learning (see lab publications on Models of Neural Development, below).
While I was at UCSF, I also developed an experimental component to my lab, focused on the study of the simultaneous activity of many neurons in visual cortex using the "tetrode" method of recording (see lab publications on Experimental Results, below). Experiments applied these methods in cat visual cortex and LGN (the nucleus providing visual input to cortex). Additional publications from that work are still in process. I did not establish an experimental lab at Columbia. Instead, Michael Stryker took over the operation of the lab at UCSF.
Can't read postscript? Pick up ghostscript/ghostview; this
link includes pointers to Mac and PC as well as Unix versions.
How to view postscript and
gzipped files
(Note: these instructions are very old and I haven't checked to see
that the links are current. If not, google should get you there.)
To read compressed files: It's easy to install gzip/gunzip on
your system: Click here
to find Mac and Dos executables for gzip/gunzip, as well as
source code that should compile on any Unix machine. Web browsers can
be easily configured to automatically gunzip .gz files; talk to your
system manager, or see Los Alamos
faq, described below. Windows users: compressed (gzipped) files
can also be unpacked with
winzip.
Terrific general information about getting started with
postscript and gzip, including how to get your browser to
automatically uncompress and display gzipped postscript, is here at
the faq of the Los
Alamos physics
e-print archives.
Guided tour of cortical development papers:
If you wish to get started reading the papers on models of cortical
development, I recommend the following path (for postscript files, I
link here to the compressed versions; links to the uncompressed
versions are also available, above):
Read
Miller, 1996a for a more theoretically-oriented overview, but only
through the separate models of orientation and of ocular dominance.
Also, you might read the very short Miller,
1996b, which is a minireview focusing on the biological nature of
synaptic competition. The existence of this competition is assumed in
our modeling, but we do not model its mechanism.
UPDATE: see
Also read
Erwin and Miller, 1999 to see the implications of this
combined orientation/ocular dominance model for the binocular
organization and disparity selectivity of mature simple cells, and
how this compares with experimental data.
See also Wimbauer et al.,
1997a and
1997b, in which this same formal model is used to study the
development of direction selectivity in oriented simple cells through
competition of lagged and non-lagged inputs.
(i) Read Miller,
1990b to see how the framework can be derived from a more fully
nonlinear starting point.
(ii) Read Miller,
1998 to see how the framework can be used to analyze models based
on synaptic sprouting and retraction as well as on modification of
the strengths of anatomically fixed synapses.
(iii) Read the Ph.D. thesis (Miller, 1989) (text-only),
chapters 5 and 6, for the fullest available mathematical analysis of
the full (many-output-cell) model. Alternatively, Miller and Stryker,
1990 has somewhat more mathematical detail than Miller, 1990a, but
less than the thesis. The full thesis includes all the material in
both Miller, 1990a and Miller and Stryker, 1990.
See Also: