4, 1055 - 1056 (2001) |
Coding the temporal structure of sounds in
cortex in anesthetized animals responds poorly to rapid
stimulus trains. In awake marmosets, rapidly repeating sounds
are now shown to be represented by a rate code.
Perceiving change in sounds over time is the most
important function of human hearing. If all the fine spectral
(frequency) information is omitted from speech, leaving only a
relatively slow, amplitude modulation of 'white noise' by the
speech envelope, we still hear remarkably well, scoring well
above chance on phoneme identification1.
Temporal coding also contributes in several ways in listening
to simple, non-speech sounds, including pitch, space and
auditory system has developed several specialized mechanisms
to process rapidly time-varying stimuli. In the cochlea,
direct, mechanically coupled ion channels in the stereocilia
of hair cells are very rapidly opened and closed in synchrony
with the displacement of the basilar membrane3.
Single auditory nerve fiber discharges are able to follow
these channel openings, or 'phase-lock', to frequencies up to
4 kHz in mammals and even up to 9 kHz in certain birds. At
higher frequencies, filtering by the hair cell membrane
prevents phase locking, and a 'place code', reflecting place
of innervation along the cochlea, is thought to be responsible
for very high-frequency hearing. Nevertheless, further
specializations for time preservation are found in the
Auditory nerve fibers form giant, 'endbulb of Held' terminals
onto some cochlear nucleus neurons, and transmitter-gated
channels with extremely rapid kinetics are found
postsynaptically. In contrast to the auditory periphery,
neurons at higher levels of the auditory system seem to
process time-varying signals with much less fidelity. Although
most neurons in the auditory cortex respond precisely to the
onset of a sound, the responses are usually transient and
cannot explain the perception of connected streams of sound.
Lu, Liang and Wang5
now show in this issue that two populations of neurons, in the
primary auditory cortex of awake marmosets, process
time-varying acoustic stimuli (clicks) using independent
codes. One population shows sustained, synchronized responses
for lower- frequency click trains, whereas a second, newly
identified population shows non-synchronized increases in
spike rate for higher frequency trains (Fig.
1) Many neurons in the 'synchronized' population actually
show a decreased response rate for higher frequency
Most previous research on auditory cortex physiology
has used barbiturate anesthesia. The focus of the research has
typically been on examining the responses of single neurons to
variations in the (spectral) frequency of long-duration pure
tones. This approach enabled maps to be made of the spatial
distribution of the 'best frequency' of neurons across the
surface of the cortex (tonotopicity). Whereas the transient
responses of neurons in the anesthetized cortex are precisely
timed to the stimulus onset, the capacity to follow
repetitive, shorter duration stimuli is limited to relatively
low frequencies. A major departure of the study by Lu and
was the use of an unanesthetized preparation. Neurons in the
unanesthetized cortex were found to show much more sustained
responses to trains of rapidly presented stimuli than those
studied previously in the anesthetized cortex. Although a
smaller proportion of neurons in the awake cortex had
synchronized responses, they discharged synchronously in
response to higher rates of repetitive sounds. However, the
major impact of the Lu et al. paper5
is likely to be the discovery of the population of neurons
having a non-synchronized, rate code for stimuli presented at
high repetition rates (Fig.
1). In these neurons, increasing rates of stimulation
(above about 30 Hz) led to increasing rates of discharge, up
to a mean peak response rate of 30−40 spikes/second at 200−300
Hz, the fastest stimulus rates used. The discovery of this
rate coding depended on the sustained firing of neurons found
so much more commonly in the cortex of awake animals, but it
was also due to the analytic rigor and insight of the authors.
Overall, just under half of the click-responsive cortical
neurons tested (n = 190) in the Lu et al.
could be clearly classified as synchronized or
rate-responsive. The remainder showed a variety of
non-synchronized and rate-insensitive responses.
perceptual experiments, it is clear that the auditory system
processes and interprets fast and slow temporal fluctuations
in a fundamentally different manner. Fast, periodic
oscillations, of amplitude-modulated noise, for example, are
perceived as one continuous sound. Thus, temporal fluctuations
occurring on this fast time scale contribute to pitch. In
contrast, temporal patterns that occur on a slower time scale
(less than about 30 Hz) are perceptually resolved as
individual auditory events, and may carry most of the
information required to identify and characterize a sound
source. The study cited above1,
showing the recognition of noise modulated by the speech
envelope, is an example of this slow temporal perception. The
existence of two separate temporal codes in the auditory
cortex may help to explain these and other auditory perceptual
phenomena, such as the ability to detect temporal gaps between
noises separated by just a couple of milliseconds. As noted by
Lu and colleagues5,
it is intriguing that several qualitative changes in temporal
perception occur around the frequency (about 30 Hz) that
separates the two populations of cortical neurons. For
example, fast, periodic oscillations, such as those from a
fully revved motorcycle engine, are perceived as one
continuous sound having a clear, high-frequency pitch. Slower
oscillations (such as from an idling engine) are perceptually
resolved as individual auditory events, each having a distinct
Although it is tempting to suggest that the temporal
code and the spike rate code, each operating over a different
range of stimulus rate, underlie perception, proving that
connection is not straightforward. One way forward, as
frequently used by visual neuroscientists, is to train the
animal to make a perceptual decision while the activity of
cortical neurons is being recorded. On each perceptual trial,
the activity of the neuron is compared with the decision
reached by the animal. Significant correlations have now been
obtained in both the primary and non-primary visual cortex.
This approach has been used with great success, for example,
by Newsome, Shadlen and their colleagues in their studies of
the cortical basis of visual motion discrimination6,
In contrast, Lu and colleagues5
recorded from A1 neurons in marmosets that were trained to sit
quietly, but not to perform a behavioral task.
note of caution is signaled by some other recent studies using
alternate modes of response analysis. For example, the
presence of continuous sounds might be encoded by the
synchronization of low levels of background firing often
observed in cortical neurons8.
Thus, in the auditory cortex of anesthetized marmosets,
deCharms and Merzenich showed that the correlation between the
discharges of nearby clusters of neurons could signal stimulus
features, even though the firing rate of the neurons did not
change. It has been argued that the distinction between rate
and spike timing codes may also not be as clear as it appears
An interesting case in point is a study by Panzeri and
2). Single-neuron responses to whisker stimulation,
recorded from rat somatosensory cortex, were analyzed using
information theory, rather than more conventional approaches.
The results of this analysis led to the perhaps
counterintuitive observation that even neurons normally
described as 'rate coding' often seemed to carry more
information in spike timing than in firing rate.
The study of Lu and colleagues5
has made a highly significant contribution to our
understanding of auditory cortex function. However, its most
important legacy may be to encourage the growing trend in
auditory neuroscience away from anesthesia and thus allow
psychophysical theories of auditory perception to be tested at
a physiological level.
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