Re: Pitch neurons (was "Autocorrelation-like ...")

[Peter Cariani <peter@xxxxxxxxxxxxxxxxxxxx>]

On Thursday, March 6, 2003, at 08:27  AM, Martin Braun wrote:

> Peter Cariani wrote:
>
> > Martin: "No problem. F0 periods that arise in the frequency laminae of
> > the partials are forwarded to the frequency laminae of F0."
> > if this were the case then there should be true pitch detectors that
> > respond both to a pure tone and a complex with a missing F0 at the
> > same
> > frequency. Schwarz & Tomlinson (1990) looked hard in the awake monkey
> > cortex without success.
> F0 pitch and pure-tone pitch are detected by the same neurons in the
> low-frequency laminae of the midbrain. After that they are not
> represented
> by the same neurons in the cortex. This is no surprise at all. An F0
> comes
> together with spectral information (timbre), a pure-tone doesn't. We
> have
> completely different inhibitory response chains for the two stimuli.
> Remember that pure-tones do not occur in nature, and that our hearing
> is in
> no way adapted to them.
Yes I agree that pure tones are highly artificial, and if anything our
hearing is adapted to complex, broadband sounds.

It would solve the problem if IC units with 300 Hz BFs also responded
to AM tones with Fm's of 300 Hz and carriers at 1 kHz. Unfortunately, I
know of no evidence for such responses (if you have seen such things or
know of a suitable reference, I would be more than happy to disabuse
myself of my mistaken belief that none have been seen. It would relieve
me of a good deal of irritating cognitive dissonance I experience
whenever I think about the central coding of pitch).

I am very confident, however, that one would see interspike interval
correlates of the 300 Hz periodicity in both cases (even) at the level
of the IC (they are visible in Langner's beautiful spike raster plots).
The problem with the interval representation at that level is that
units respond with much lower discharge rates that in earlier stations,
so that intervals at 1/F0 are not in huge abundance. This problem might
be overcome by looking at patterns of longer intervals (n/F0) or by a
volley principle in which across-neuron intervals are used. Chow(1951)
estimated that there are 400,000 neurons in the macaque midbrain, as
opposed to 30,000 in its auditory nerve -- perhaps what is going on is
that the timing information is being more sparsely distributed across
many more neurons as you go up the pathway. Why this should be, or what
this says about the basic signal processing principles that are operant
in the system is anyone's guess. We tend to think reflexively in terms
of signal reductions (sequential hierarchies of feature detectors)
rather than signal expansions and statistical mass-action schemes. Some
of this is a holdover from AI machine vision processing strategies from
the 1960's.

> > Martin: "We only hear two pitches, if there are strong timbre labels
> > attached to them. These are decoded in the cortex, which then feeds
> > back to the pitch neurons in the midbrain."
> > Simultaneously play two notes a whole step (or more) apart on the
> > piano. Do you hear one or two notes?
> No note at all. Only a chord.
I've never been accused of being an overly analytical listener.
Yes I can hear the chord, but I can also tell that there are two notes
and I can match the pitches of the notes. For chords, one can often
hear out the pitches of the constituent notes
(see Parncutt's book, which has pitch matches for chords in it,  or the
paper on tonal fusion by De Witt and Crowder  "Oomph in Stumpf".) I
agree that for some simple intervals (4ths, 5ths, octaves) the tones
are more likely to fuse than others, but if you pick a major 2nd or a
minor 3rd, I'll wager that most people will tell you that more than one
note is being played.

> > On what basis can you say that the notes MUST be separated in the
> > cortex? How "anatomically and physiologically realistic" is this
> > assertion?
> Timbre detection is based on memory reference. This is not possible
> below the cortex.
I think it's difficult to rule out subcortical timbre discrimination at
this point. Why do you think it's not possible?

The cortex does seem to be involved in fine grained hearing (see Tramo
et al and Phillip's paper on word deafness) although it is far from
clear to me whether there are fine representations of pitch and timbre
there at the cortical level proper or whether these would exist in
cortico-thalamic loops, or whether the cortico-thalamic system sets up
the lower level stations to make fine-grained comparisons. In any of
these cases cortical damage would impede fine grained pitch and timbre
perception.

My impression is that people and animals with extensive bilateral
cortical lesions can still make coarse pitch and timbral judgements,
although one never knows whether some primary auditory regions are
spared or have reorganized over time (many are completely deaf for some
period immediately after the precipitating event -- which argues that
you need some functioning cortex to hear sounds in the first place.
Question: is there an auditory analogue of Blindsight in which people
with cortical lesions can localize and discriminate sounds in the
absence of consciously hearing them?).

Are there any fMRI studies out there that look at both subcortical and
cortical activation during echoic and working memory fine pitch-related
auditory  tasks? These might shed some light on the problem of where
fine-grained representations are stored.

> > But it still seems to me that even at the level of the IC,
> > interval representations for low pitches still have more plausibility
> > than those based on modulation-tuned pitch detectors
> Interval representations are the matter that must be detected by
> SOMETHING.
> This something are tuned pitch neurons.
This is exactly what I meant about our fixation on single neurons and
tuned feature detectors.

There are other possible ways that neural networks can handle
information through distributed representations and processings that do
not require highly tuned units.
The connectionists have various demonstration models of how this could
conceivably be realized with Hopfield nets (rate-based codes), although
the story gets very complicated if units are very coarsely tuned and
have level-dependent and nonmonotonic  responses. It's not clear to me
whether anyone has demonstrated how these mechanisms  would work in
practice, using the messy kinds of responses that the physiologists
actually see. I have found that feedforward timing nets in principle
can be used to beat interval distributions against each other in a
coincidence-delay network to compare interval distributions in a manner
that could operate on sparse-distributed temporal patterns, but this is
also still only a demonstration of functional principle rather than a
concrete model of the behavior of a particular set of neurons.

So, there are many possible ways to skin a cat as they say, and the
limits largely reside in our own imaginations.
This is why it is so dangerous and destructive to rule out a whole
class of possible neural explanations (interval representations)
because we don't yet know how they are processed.
Even though I am highly, highly critical of central rate codes and am
critical of these modulation-based representations, we still cannot
rule them out of hand -- maybe there are ways that we/I haven't thought
of in which they operate.

Similar kinds of dismissive thinking set back the theory of continental
drift by half a century -- the reigning geologists at the time could
not imagine a motor mechanism which would propel the continents, and
the hypothesis was ridiculed for decades until World War II and the
discovery of sea floor spreading forced that community to re-evaluate
it. My father was a geologist and as a young boy I remember the
controversy, even after a great deal of supporting evidence had been
amassed. Continents that move is a hard thing to get used to if you've
always thought of them in other terms. Preposterous!


> > Martin: "Level stability is provided by lamina-based lateral
> > inhibition in the midbrain."
> > Show me the neural data. I want to see MTFs and pitch representations
> > that are every bit as good at 90 dB SPL as they are at 40 or 50 dB.
> MTFs [modulation transfer functions] do not occur with a piano tone.
> With a piano tone you have beats between the partials in the
> middle-frequency laminae of the midbrain, which are then detected by
> tuned pitch neurons. Sound level does not affect either the partial
> frequencies or the beat frequencies. It only affects the mutual
> inhibition of partial frequencies, and thus strength of pitch, but not
> pitch height.
Schouten and de Boer's experiments on inharmonic complex tones pretty
much destroyed theories of F0-pitch based on neighboring harmonics that
beat. This is one of the strong demonstrations that argues that low
(F0) pitch (of resolved harmonics) does not depend on envelope
periodicity per se, and that the fine structure of the waveform must be
analyzed in a manner that is similar to autocorrelation. Spectrally, it
means that you can't simply infer F0 from harmonic spacings -- a
harmonic pattern analysis must be carried out. I know of no good
physiological evidence for any central harmonic spectral pattern
analysis (excluding bats and combination-sensitive units with BFs > 5
kHz).

> > Martin: "Period detectors register these pitch shifts, as calculated
> > many years ago."
> > Only if they are based on autocorrelation or something roughly
> > equivalent. Modulation detectors won't work ...
> See last answer. Also see what I wrote on beats in the midbrain
> (Braun, 1999). You will then see that pitch neurons that function as
> tuned resonators can do all what autocorrelators can. Subcellular time
> constants are solutions of biology, whereas autocorrelation circuits
> are solutions of man-made electronics.
I will try to look again at your 1999 paper.

Maybe our quibble is semantic. If you see pitch neurons that "do all
what autocorrelators can", then functionally they are autocorrelators,
and they will have properties that are associated with those (e.g. comb
filter characteristics). Autocorrelations differ from renewal processes
in that they don't reset, and this in turn means that they handle
competing and interleaved temporal patterns without much destructive
interference. Autocorrelators are not tied to any particular man-made
electronic circuits -- they do require delay operations but there are
many ways besides delay lines to realize those, although tapped delay
lines and axons with collaterals are obvious analogues.

A decade ago, I initially thought that "intrinsic oscillations" in CN
choppers might be able to implement a Licklider architecture using
cellular autocorrelators, but when I looked at chopper responses to
periodic complex stimuli, yes there was some very coarse F0 tuning, but
the interval information was still much, much better and as in the
auditory nerve, it follows the psychophysics.

More power to you if you can figure out a way to make a cellular
autocorrelator it that is compatible with the observed neural responses
and the neuroanatomy. I would not even rule out the possibility of
sub-cellular tuned resonances in particular axons and dendrites (see
the Waxman book). It's possible that we may be able to get something
like an autocorrelation out of the bandpass MTF neural elements in the
pathway or from combinations of elements, and I think you should keep
trying -- it would be a huge step forward if you could do it. Just
don't be so blindly dismissive of other possibilities in the meantime.

--Peter Cariani


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