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Re: 40 Hz RIP

Hi DeLiang

> I wish you understood the oscillatory framework before you

In fact I have been following this for some time. I have a copy
of your paper in Cognitive Science (I refer to it in Todd
(1996) "An auditory cortical theory of primitive auditory
grouping". Network:Computation in neural systems. 7, 349-356. )
and Guy Brown's various papers. As you know I have worked with
Guy myself so I am quite familiar with the arguments. We have
been arguing about this for two years now. You may also like to
know that because I am so interested I actually teach this
stuff to our undergraduates and postgrads. We have a second
year course "Recent Papers in Perception" which includes Singer
and Gray (1995) "Visual Feature Integration and the Temporal
Correlation Hypothesis". Ann. Rev. Neurosci. 18, 555 and a MSc
Cog. Sci. module "Machine Perception" which includes an
analysis of four different models of auditory grouping (Beauvois
and Meddis, 1991; Brown and Cooke, 1995; Todd, 1996; McCabe,

> The information for binding is, of course, in the input and memory. The
> whole point of binding is HOW to extract and represent the information
> scattered around in neural signals.

Exactly! So, far we are in complete agreement.

> There is no mystery to oscillations, particularly from the modeling
> perspective. Neurons generate spikes in response to stimulation. The Hodgkin
> -Huxley equations (published in 1952) .....

It doesn't matter what kind of fancy oscillators you have, my
point was how you arrange them in relation to the signal. For
example, in Guy's chaotic oscillator the  output of the
oscillator had no temporal relationship with the signal
whatsover. This is in direct contrast to what is known about
cortical cells which phase-lock , depending on their modulation
transfer function and the period of the stimulus. (Perhaps Guy
might like to comment here? Come on, join the fun!)

> Well, natural selection seems to come up with highly
> nonlinear neuronal spikes. Any computations with such
> spikes would need to incorporate some aspects of
> oscillations.

Yes, but I don't know of any natural system whose output bore
no relation to its input!

If you had looked more carefully at my message, particularly at
the end I said that the impulse response of a modulation filter
is a damped oscillation. The essential difference between my
model and your approach is that in my case the function of the
filters is to passively transform the signal into the frequency
domain, i.e. to faithfully represent the temporal information
in the signal *spatially* in terms of its power spectrum,
including phase, rather than some more abstract relationship
such as a clocking cycle.  In order to do this you need a
population of cells/filters which sample the range of
periodicities that are found in natural signals. In the case of
speech there are two such important ranges (a) voice pitch (b)
voice rhythm. These ranges happen to coincide with the known
ranges of BMFs in two important physiological stations in the
auditory system, the ICC and the cortex (Langner, 1992.
"Periodicity coding in the auditory system". Hearing Research,
60, 115-142.).

> >
> > One important thing which many people seem to forget about the
> > visual system is that if an image is actually stabilised
> > ......

> It's better to leave the above speculations to the vision

In fact Deliang, the information about the various kinds of eye
movements required to avoid image adaptation was taken directly
 from Barlow and Mollon (1982) "The senses". CUP. The chapter
was "Eye movements and strabismus" by Mathew Alpern. The
information concerning the temporal and spatial contrast
sensitivity functions was taken from the chapter by Woodhouse
and Barlow "Spatial and temporal resolution and analysis".

If I may quote from Hawken et al (1996, "Temporal-frequency
selectivity in monkey visual cortex." Visual Neuroscience, 13,
477-492.) p. 490.

"Human and monkey observers can perceive flicker and drift
rates greater than 40 Hz under photopic conditions. Recent
experiments indicate macaque retinal ganglion cells
show flicker responses at higher temporal frequencies than the
psychophysical critical fusion frequency (CFF). Under the
assumption that CFF is dependent on cortical processing, then
there must be additional filtering in the cortex because
signals present in the retina and LGN are not available
perceptually. Therefore, it seems likely that CFF depends upon
cortical as well as subcortical temporal integration. The
temporal tuning of a number of V1 cells would give a reliable
response at the highest temporal frequencies that are required
to account for human and monkey perception".

It follows logically from this that a number of V1 cells will
respond to micronystagmus.

> >
> > Those who are advocates of the "oscillatory framework" have
> > searched in desperation for some evidence of "40 Hz
> > oscillations" in the auditory system, but to no avail.

> How many have looked in the auditory system?

Certainly, Gray and Singer have! In Ann. Rev. Neurosci. 18,  p.
567 there is a section entitled "Evidence for synchrony in
non-visual structures". There are the usual references to the
hippocampus and the olfactory system. In the case of the
auditory system there are four references to MEG and EEG evoked
potential studies which they claim show evidence for
gamma-frequency components.

> I heard such predictions by prominent neurophysiologists in
> 1991-1992 saying that neural oscillations would die in 1-2 years.
> Things have not turned out that way, ....

As I said, no doubt it may live on a little while yet, for some

> For a hypothesis as fundamental as temporal correlation, it
> is impossible to draw either a positive conclusion
> or a negative conclusion om several
> studies. ...

As I also said, in fact I have no problem with the notion of
temporal correlation. The disgreement I have is in relation the
following three points:
(a) what information is being correlated
(b) how is that information represented and
(c) by what mechanism is the correlation carried out?

The solution I have proposed is

(a) it is the temporal information of the signal, rather than
abstract properties of a fancy oscillator (chaotic, van der
pol, etc, etc)
(b) the temporal information is represented *spatially* in the
frequency domain ( a wavelet transform is one way to do this,
but note that the impulse response of the basis functions are a
damped oscillation, e.g. Gabor wavelet)
(c) the correlation is carried out by a network of
cortico-cortico connections where a basic processing unit is a
cortical column

As I also said, the general architecture of this model is not
dissimilar to some "neural oscillator" models, including your
own, but there is a fundamental difference in that it is based
on the strong evidence that the brain represents its inputs in
the form of multi-scale decompositions.

To give you another concrete example of this let us return to
the visual system. No one would now dispute that the visual
cortex does a spatial-frequency analysis. These may be
represented by a family of Gabor wavelets. The evidence seems
now extremely clear that the visual cortex also does a
temporal-frequency analysis (e.g. Hawken et al, 1996, as
above). Joint spatio-temporal analysis provides the basis for
visual motion perception. One model which uses exactly such a
basis is that proposed by Heeger (1987, "Model for the
extraction of image flow." J. Opt. Soc. Am. 4(8), 1455.).
He used a family of three-dimensional (space-time) Gabor
filters which effectively sample the power spectrum of a moving

The model has four stages
(a) center-surround filter
(b) 3-D Gabor filter
(c) motion energies
(d) velocity tuned units

This model is entirely consistent with the physiology
(a) bipolar cells (retina)
(b) simple cells (V1)
(c) complex cells (V1)
(d) MT units (V4, medial temporal lobe in the primate).

In case you hadn't already noticed from my first message, this
provides the basis for a model of audio-visual binding since
the temporal information for motion is coded in precisely the
same form as for rhythm. Well I guess I've let the cat out of
the bag. So I'd better rush this one into publication before I
get trampled by the stampede. I've burnt my fingers with
patents once too often to be bothered about prior disclosure.

> So given tremendous computational tasks ahead, let's keep
> alternatives alive before the problem is solved.

DeLiang, I would be extremely upset if you gave up on "neural
oscillators" - it would ruin my fun.

> If this debate is to continue, it would
> be more productive to focus on technical aspects

I think you will realise that I have done extactly that.

Best wishes