RAPID COMMUNICATION Scalp-Recorded Optical Signals Make Sound Processing in the Auditory Cortex Visible

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1 NeuroImage 10, (1999) Article ID nimg , available online at on RAPID COMMUNICATION Scalp-Recorded Optical Signals Make Sound Processing in the Auditory Cortex Visible Teemu Rinne,* Gabriele Gratton, Monica Fabiani, Nelson Cowan, Edward Maclin, Alex Stinard, Janne Sinkkonen,* Kimmo Alho,* and Risto Näätänen* *Cognitive Brain Research Unit, Department of Psychology, University of Helsinki, FIN-00014, Helsinki, Finland; and Department of Psychology, University of Missouri Columbia, Columbia, Missouri Received April 20, 1999 The functioning human auditory cortex can be studied in detail with modern brain-imaging methods. For example, positron emission tomography (PET; Lauter et al., 1985), functional magnetic resonance imaging (fmri; Wessinger et al., 1997), and magnetoencephalography (MEG; Romani et al., 1982) have demonstrated tonotopic organization in the auditory cortex. Thus, these methods, especially fmri, are able to map brain areas involved in auditory processing on a millimeter scale. However, fmri is not able to track the finegrained temporal dynamics of the central auditory system in encoding and analyzing sound information because its time resolution is limited by the properties of the hemodynamic changes, lagging neural activity at least by several hundred milliseconds. In contrast, MEG provides temporally detailed information on central auditory processing (Lütkenhöner and Steinsträter, 1998) but has severe problems in separating simultaneously activated adjacent sources from each other and cannot indicate the extent and pattern of the activated area. The present paper reports the first event-related optical signals (EROS; Gratton and Fabiani, 1998) from the functioning human auditory cortex. Using this novel noninvasive measure of cortical activation, we were able to locate, in both time and space, neuronal generators for two of the most important auditory functions, sound detection and change detection (Näätänen, 1992). The EROS method combines both high spatial and high temporal resolution in a single measure (Gratton and Fabiani, 1998). In an EROS recording, a source of intensity-modulated near-infrared light and a detector are placed on the scalp a few centimeters apart from each other. The low-intensity light emitted by the source diffuses through the skin, bone, and brain, and some photons exit the head, reaching the detector. A spatially high-resolution signal is achieved by selecting the photons on the basis of their time of flight; those photons that take similar amounts of time to migrate through the medium are likely to follow relatively similar paths. EROS is a measure of phase-shifts in the modulation envelope of the light as the photons migrate through the brain tissue, which is optically modified by neural activation. Some of the optical changes in the brain tissue are related to various hemodynamic phenomena lasting relatively long times compared with neural electric activity (Cannestra et al., 1996). In addition, there are also rapid changes in light scattering associated with neuronal activation (Cohen, 1972; Frostig et al., 1990; Malonek and Grinvald, 1996) that are reflected in EROS. At the cellular level, the physical cause of the scattering changes is not entirely clear but factors such as ion currents across the cell membrane (Cohen, 1972; Stepnowski et al., 1991) and the swelling of the neural and glial cells have been suggested (Andrew and MacVicar, 1994). Previously it has been shown that the time courses of the electric and optic responses evoked by the same visual stimulation are similar and, further, that the loci of activation indicated by EROS correspond to those indicated by fmri (Gratton et al., 1997). So far no EROS to auditory stimulation has been reported, however. In the present study, we measured EROS from the auditory cortex when subjects were presented with tone pips. We also obtained results clarifying how the auditory cortex detects sound change when these repetitive tones are occasionally shortened in duration. We recorded EROS from six healthy subjects (ages 21 41, 3 females) with normal hearing. Subjects were presented with harmonically enriched tones (5-ms rise and fall times) at constant 400-ms onset-to-onset intervals. Stimuli consisted of frequencies of 500, 1000, and 1500 Hz, with the second and third components being 3 and 6 db lower in intensity, respectively, than the first component (Tervaniemi et al., 1999). Stimuli were delivered in sequences of 50 tones, with an interse /99 $30.00 Copyright 1999 by Academic Press All rights of reproduction in any form reserved. 620

2 RAPID COMMUNICATION 621 quence interval of about 10 s. In each stimulus sequence, two tones of different durations were presented in a random order: a frequent tone (P 0.8) of 75 ms in duration and an infrequent tone (P 0.2) of 25 ms in duration. A total of 2000 stimuli were delivered for each source detector configuration. Stimuli were binaurally presented via headphones at a comfortable hearing level (approximately 70 db above the subjective hearing threshold) while subjects were reading text of their own choice under the instruction to ignore tones, as in previous electrophysiological studies (Tervaniemi et al., 1993). EROS was recorded by 32 scalp-attached source detector pairs centered approximately 2 cm behind T4. Thus, on average, the locations covered the scalp projection of the posterior half of the supratemporal gyrus near the temporo-parietal junction of the right hemisphere (Homan et al., 1987). This recording site was chosen on the basis of previous EEG and MEG studies that have shown that the brain response evoked by infrequent changes in repetitive tones, i.e., the mismatch negativity (MMN; Näätänen, 1992), is stronger in the right than in the left hemisphere (Levänen et al., 1996; Rinne et al., 1999). Two detectors and four sources (eight source and detector pairs) were used at a time; thus the stimulus sequences were repeated four times with different sensor configurations. A 750-nm LED (power 1 mw) modulated at 112 MHz (crosscorrelation frequency 5 khz) was used as a light source. The detector was a 3-mm fiber optic bundle connected to a photomultiplier tube. Estimates of the phase delay (EROS) were obtained at 50 Hz. The arterial pulsation artifact was compensated off-line (Gratton and Corballis, 1995). Trials with artifacts (subject movement) and the first five trials of every stimulus sequence were discarded. The phase-delay data were averaged (epochs starting 40 ms before and ending 340 ms after each stimulus) separately for each subject, location, and stimulus type. After averaging, the data were filtered using a 3-point moving average. For control purposes, EEG (sampling rate 200 Hz, bandpass Hz) was recorded simultaneously with the EROS from the frontal midline location (Fz, referenced to an electrode on the tip of the nose). Because of the location and orientation of the bilateral MMN sources in the auditory cortices (Scherg et al., 1989; Giard et al., 1995), this frontal midline location typically shows the maximal MMN amplitude. The EEG was averaged (epochs starting 50 ms before and ending 250 ms after each stimulus) on-line separately for the frequent and infrequent sounds. The baseline level for the waveforms was defined as the mean voltage of the 50-ms period preceding stimulus onset. Separate EOG channels were used for off-line correction of the ocular artifact (Gratton et al., 1983). The EROS data analysis was restricted to the eight source detector pairs with the shortest source detector distances, which showed relatively low levels of noise. First, the baseline was corrected by subtracting the average of the 40-ms period preceding stimulus onset. Then, signals were separately standardized for each location and subject by dividing the phase value of each time point by the standard deviation computed over each average epoch. Two distinct EROS responses were found: one associated with stimulus detection and the other with change detection. The stimulus-detection effect was measured as the average response at ms from stimulus onset (the peak of grand-averaged response 20 ms; Fig. 1a, left). To extract the change-detection effect, the raw (i.e., baseline corrected but not standardized) waveforms in response to frequent tones were subtracted from those to infrequent tones. The difference waveforms were then standardized as described above but using a 120- to 200-ms time window (the peak of grand-averaged infrequent frequent tone subtraction waveform 40 ms; Fig. 1a, right). For both types of analyses, the channel with the largest effect was selected to account for individual differences in brain anatomy. As selecting the channel with the largest signal may bias the results, we ran a Monte Carlo simulation to determine whether the observed signal was larger than what could be obtained on the basis of random data. The present results may be summarized as follows: (1) A stimulus-detection effect peaking at about 100 ms from stimulus onset was elicited by the 75-ms repeating sound (Figs. 1a and 1b, left, solid line; n 5, t(4) 6.79, P 0.05 with Bonferroni correction; z 3.01, P 0.05 by Monte Carlo). This signal could be detected in five of six subjects (Fig. 1b, left); the sensors for one subject were probably not optimally placed because of the individual variation in cortical anatomy. No significant signal at this latency range was found in response to the 25-ms tones (Fig. 1a, left, dotted red line), however. (2) Instead, the infrequent 25-ms tones elicited a later response, peaking at ms, which can be associated with change detection (Figs. 1a and 1b, right; n 6, t(5) 5.87, P 0.05 with Bonferroni correction; z 2.24, P 0.05 by Monte Carlo). (3) These two signals were recorded from different sensors, indicating different brain generators. The sensors disclosing the maximal change-detection effect were located on the average 10.4 mm (standard deviation: 2.3 mm) inferior to the sensors showing the strongest stimulus effect (Fig. 1c; two-tailed t test, t(4) 8.92, P ), indicating that these two signals originated from different neural populations in the auditory cortex. The EROS stimulus- and change-detection effects correspond, presumably, to the N1 and MMN components of the auditory event-related potential (ERP),

3 622 RINNE ET AL. FIG. 1. EROS to auditory stimulation. The illustrated responses are standardized and baseline corrected as described in the text. The EROS effects were typically on the order of 0.2. (a, left). Grand-averaged (n 5) EROS to the frequent 75-ms sounds (solid line) shows a significant signal at 100 ms on upper sensor locations. This stimulus-detection effect was not observed in response to the infrequent 25-ms tones (dotted line). The gray area illustrates the time window (peak 20 ms) used to define the effect. (a, right) Grand-averaged (n 6) EROS from lower sensor locations reveals a change-detection effect in response to infrequent 25-ms tones (dotted line). The time window (gray) used to define the effect was determined on the basis of the grand-averaged infrequent frequent stimulus subtraction waveform (peak 40 ms). (b, left), EROS to the frequent 75-ms sound for individual subjects. The effect at ms from stimulus onset, possibly an EROS correlate of P2 or N2 of the ERP, was not statistically significant. (b, right) The individual infrequent frequent stimulus subtractions of EROS waveforms. (c) The relative loci of grand-averaged stimulus-detection (left) and change-detection (right; infrequent frequent subtraction) effects. The color-coded maps projected to the cortical sheet show t scores computed across subjects. Statistically significant positive EROS effects are indicated in red. The maximal change-detection (right) effect was measured with sensor locations 10 mm lower than those showing the strongest stimulus effect (left). The negative EROS effect (blue, right) is obtained by subtracting responses to frequent tones from those to infrequent tones. The average locations of these two activation maxima in the sensor grid (with a coordinate system fixed to preauricular points and nasion, origin in the middle of the head; in mm) were as follows: x (front back) 22, y (left right) 67, z (top bottom) 65 and x 25, y 67, z 56 for stimulus-detection and change-detection, respectively. respectively. The electric N1 is known to reflect physical aspects of auditory stimulation (Näätänen, 1992). For example, the N1 amplitude is diminished when stimulus energy is reduced by decreasing the sound duration. Consistently with this, the EROS stimulus effect was found for the longer (75-ms) tones but not for the shorter (25-ms) tones. The electric MMN, in turn, is elicited by a discriminable change in a repetitive sound (Näätänen et al., 1989; Näätänen, 1992). Similarly, the present EROS change-detection effect was elicited by the occasional shortening of the 75-ms tones. It might be argued that this EROS effect was, at least partially, due to the detection of the length of the stimuli itself. However, previously it has been shown that the electric MMN elicited by infrequent changes in the duration of the stimuli does not change when the probabilities of the shorter and longer tones are reversed (Näätänen et al., 1989). In addition, when the frequent stimuli are

4 RAPID COMMUNICATION 623 omitted from the sound sequence, i.e., the infrequent tones were presented alone, no MMN is elicited (Näätänen et al., 1989). The difference in the loci of the stimulus and stimuluschange effects, indicated by the 10-mm difference between the two activation maxima in the sensor grid, corresponds to that between the dipole-modeled N1 and MMN sources (Levänen et al., 1996; Huotilainen et al., 1998). In the present study, EROS was recorded with source-to-detector distances of 2 4 cm, suggesting that the signal probably originates from 1- to 2-cm depth (Gratton et al., 1994), which is in the range of the estimated depth of the sources of the MEG equivalents of the electric N1 and MMN (Levänen et al., 1996). An approximate Talairach transformation (Talairach and Tournoux, 1988), which was done on the basis of digitized source and detector scalp locations and an estimation of the depth of the source based on source-todetector distances, suggested that the stimulus detection effect was possibly generated in the auditory association cortex (area 41/42) and the change detection effect in or in the vicinity of the primary auditory cortex (area 22), which is in line with previous ERP and MEG studies (Scherg et al., 1989; Levänen et al., 1996; Alho et al., 1998). Taken together, the optic and electromagnetic evoked signals seem to reflect corresponding brain processes and probably originate, at least partially, from the same generators. However, there was a very interesting difference between EROS and simultaneously recorded electric ERPs: the 75-ms tones elicited no detectable response in ERPs at 100 ms (Fig. 2), whereas the EROS showed a pronounced response to these stimuli (Figs. 1a and 1b, left, solid line). This may be due to the facts that in this study the stimulus rate was very high, leading to small ERPs in response to the frequent tones, and that the ERP activity was recorded FIG. 2. Electric ERPs from a midline frontal electrode (Fz) recorded simultaneously with EROS. Grand-averaged (n 5) responses to frequent (solid line) and infrequent (dotted line) stimuli are shown. The infrequent stimuli elicited a negative response (mismatch negativity) peaking at about 150 ms from stimulus onset. The main MMN sources are located in the auditory cortex, so that the strongest signal can be recorded over frontocentral scalp areas. Note the lack of the N1 response at 100 ms from stimulus onset. from only one frontal channel that may not optimally pick up the N1 response due to the orientation of the N1 source in the auditory cortex (Näätänen and Picton, 1987). In conclusion, the EROS method proved to be capable of telling apart temporally and spatially very close functional units. A comparable temporal resolution can be achieved only with electromagnetic methods. Furthermore, the present spatial resolution was achieved directly from the scalp-recorded signals; no dipole modeling or similar source-estimation methods generally used in electromagnetic studies were needed. Thus, it appears that EROS is able to make stimulus analysis occurring in the auditory cortex visible in a way not possible with any other existing technique. 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