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Imaging study provides new information on how the brain processes sounds of different tones

  [ 16 votes ]   [ Discuss This Article ] • November 13, 2002

(November 12, 2002) - Bethesda, MD – In 1968, country music singer Johnny Cash recorded the fictional lament of a convict in Folsom prison. The lyrics, "I hear the train a comin'; it's rollin' 'round the bend, And I ain't seen the sunshine since I don't know when, ©" contain an acoustic anomaly, the sound of a train. Despite its insight into human nature, it's unlikely Cash knew that the sound of a train would be the catalyst for new research findings into how the brain processes auditory repetition rates.


We encounter differing rates of sound each day that are important in the perception of the more complex acoustic conditions. Since repetition rate plays a fundamental role in determining how sounds are heard, it is not surprising that there have been numerous neurophysiological studies of rate in animals. Broad trends concerning the coding of rate in the auditory pathway have emerged from this work. For instance, the highest repetition rates at which neurons respond faithfully to each successive sound in a train (or each successive cycle of amplitude modulated stimuli) tends to decrease from brain stem to thalamus to cortex.

While animal studies have shed light on the neural representations of repetition rate, the degree to which the animal findings are related to humans' remains uncertain because of interspecies differences, anesthesia differences, and a paucity of data in humans that can serve as a link to the animal work. In the end, direct neurophysiological data in human listeners is important to understand how repetition rate is represented in the activity patterns of the human brain.

Most previous neurophysiological studies of repetition rate in humans have used noninvasive techniques for probing brain function, such as evoked potential and evoked magnetic field measurements. A limitation of this line of research is that the sites of response generation cannot always be reliably localized. Evoked magnetic field examinations of repetition rate are further limited in that they provide information mainly concerning cortical areas because of inherent limitations in probing subcortical function.

Now, a team of researchers have used Functional Magnetic Resonance Imaging (fMRI) study to compare compared the representation of repetition rate across cortical and subcortical structures of the human auditory pathway using a wide range of rates. Stimuli were trains of repeated noise bursts with repetition rates ranging from low (where each burst could be resolved individually) to high (where individual bursts were not distinguishable and the train was perceived as a continuous, but modulated, sound). Noise bursts were chosen as the elemental stimulus based on the assumption that broadband sound would elicit robust responses by activating neurons across a wide range of characteristic frequencies. fMRI was selected for its high spatial resolution, its localizing capabilities, and its higher temporal resolution.

The authors of "Sound Repetition Rate in the Human Auditory Pathway: Representations in the Waveshape and Amplitude of fMRI Activation," are Michael P. Harms Ph.D. and Jennifer R. Melcher, Ph.D, both from the Eaton-Peabody Laboratory, Massachusetts Eye and Ear Infirmary, Boston, and the Harvard–Massachusetts Institute of Technology Division of Health Sciences and Technology, Speech and Hearing Bioscience and Technology Program, Cambridge, MA. Dr. Melcher is also a member of the Department of Otology and Laryngology, Harvard Medical School, Boston, MA. Their findings appear in the Journal of Neurophysiology, a publication of the American Physiological Society (APS).


A series of four experiments were conducted. The first two examined the effect of repetition rate on the response to a noise burst train in the inferior colliculus (IC), Heschl's gyrus (HG), and the superior temporal gyrus (STG) (experiment I); or the IC and medial geniculate body (MGB) (experiment II). The remaining experiments (experiments III and IV) were aimed at understanding one of the findings from experiment I, namely an unusual form of temporal response in the cortex to trains with a high repetition rate.

A total of 12 subjects participated in these experiments. They ranged in age from 19 to 35. Ten of the subjects were male. Nine were right-handed. Subjects had no known audiological or neurological disorders. The experiments consisted of the following elements:

Experiments I and II (Noise burst trains with different repetition rates): Nine subjects participated in a total of 11 imaging sessions for experiments I and II. The stimuli were bursts of uniformly distributed white noise. Individual noise bursts in all four experiments were 25 minutes (ms) in duration (full-width half-maximum), with a rise/fall time of 2.5 ms. The bursts were presented at repetition rates of 1, 2, 10, and 35/s (experiment I) or 2, 10, 20, and 35/s (experiment II). The 1/s rate was used in only three of the five sessions of experiment I. The spectrum of the noise stimulus at the subjects' ears was low-pass, reflecting the frequency response of the acoustic system. Noise bursts were presented in 30-s trains alternated with 30-s "off" periods, during which no auditory stimulus was presented.

Experiment III (Small numbers of noise bursts): To investigate how the initial bursts of a train contribute to cortical responses to the onset of a train, the researchers examined the responses to a single noise burst and short clusters of noise bursts. Responses were collected in three imaging sessions with three subjects. Either one noise burst or a cluster of noise bursts was presented once every 18 s, constituting a single "trial".

Experiment IV (Noise burst trains with different durations): The effect of train duration was examined in two imaging sessions with two subjects. Trains of four different durations were presented with an "off" period of 40 s following each train. Noise burst repetition rate within each train was always 35/s. Each train duration was presented once per run (8–9 runs; 310 s per run) with the order of durations randomized across runs. Supplementary information concerning the effects of train duration was obtained in two additional experiments that used a single, long-train duration (60 s) and 35/s noise bursts.

Additional elements: Separately for each ear, the subject's threshold of hearing to 10/s noise bursts was determined in the scanner room. For all experiments, the stimuli were presented binaurally at 55 dB above this threshold. Subjects were instructed to listen to the noise burst stimuli. At the end of each scanning run, subjects reported their alertness on a qualitative scale ranging from 1 (fell asleep during run) to 5 (highly alert). Subjects were imaged using a whole-body scanner and a head coil. The scanners were retrofitted for high-speed imaging. Experiments I and II were conducted at 1.5 T. experiments III and IV were conducted at 3 T, except for one of the supplementary sessions of experiment IV.


There was a systematic change in the form of fMRI response rate-dependencies from midbrain to thalamus to cortex.

In the inferior colliculus, response amplitude increased with increasing rate while response waveshape remained unchanged and sustained.

In the medial geniculate body, increasing rate produced an increase in amplitude and a moderate change in waveshape at higher rates (from sustained to one showing a moderate peak just after train onset).

In auditory cortex, amplitude changed somewhat with rate, but a far more striking change occurred in response waveshape--low rates elicited a sustained response, whereas high rates elicited an unusual phasic response that included prominent peaks just after train onset and offset.

The shift in cortical response waveshape from sustained to phasic with increasing rate corresponds to a perceptual shift from individually resolved bursts to fused bursts forming a continuous (but modulated) percept.


At high rates, a train forms a single perceptual "event," the onset and offset of which are delimited by the on and off peaks of phasic cortical responses. While auditory cortex showed a clear, qualitative correlation between perception and response waveshape, the medial geniculate body showed less correlation (since there was less change in waveshape with rate), and the inferior colliculus showed no correlation at all.

Overall, these results suggest a population neural representation of the beginning and the end of distinct perceptual events that is weak or absent in the inferior colliculus, begins to emerge in the medial geniculate body, and is robust in auditory cortex.

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