spontaneous and stimulus-evoked intrinsic optical signals

Spontaneous and Stimulus-Evoked Intrinsic Optical Signalsin Primary Auditory Cortex of the Cat

MATTHEW W. SPITZER, MICHAEL B. CALFORD, JANINE C. CLAREY, JOHN D. PETTIGREW,AND ANNA W. ROEVision, Touch and Hearing Research Centre, Department of Physiology and Pharmacology, The University of Queensland,St. Lucia, Queensland 4072, Australia

Received 14 June 2000; accepted in final form 3 November 2000

Spitzer, Matthew W., Michael B. Calford, Janine C. Clarey, JohnD. Pettigrew, and Anna W. Roe.Spontaneous and stimulus-evokedintrinsic optical signals in primary auditory cortex of the cat.JNeurophysiol85: 1283–1298, 2001. Spontaneous and tone-evokedchanges in light reflectance were recorded from primary auditorycortex (A1) of anesthetized cats (barbiturate induction, ketaminemaintenance). Spontaneous 0.1-Hz oscillations of reflectance of 540-and 690-nm light were recorded in quiet. Stimulation with tone pipsevoked localized reflectance decreases at 540 nm in 3/10 cats. Thedistribution of patches “activated” by tones of different frequenciesreflected the known tonotopic organization of auditory cortex. Stim-ulus-evoked reflectance changes at 690 nm were observed in 9/10 catsbut lacked stimulus-dependent topography. In two experiments, stim-ulus-evoked optical signals at 540 nm were compared with multiunitresponses to the same stimuli recorded at multiple sites. A significantcorrelation (P , 0.05) between magnitude of reflectance decrease andmultiunit response strength was evident in only one of five stimulusconditions in each experiment. There was no significant correlationwhen data were pooled across all stimulus conditions in either exper-iment. In one experiment, the spatial distribution of activated patches,evident in records of spontaneous activity at 540 nm, was similar tothat of patches activated by tonal stimuli. These results suggest thatlocal cerebral blood volume changes reflect the gross tonotopic orga-nization of A1 but are not restricted to the sites of spiking neurons.

I N T R O D U C T I O N

Aside from the systematic representation of frequency (Mer-zenich and Brugge 1973; Reale and Imig 1980), details of thefunctional organization of auditory cortex remain controver-sial. Several studies have provided evidence of compartmentalorganization within the tonotopic representation of primaryauditory cortex (A1) in the cat based on clustered or bandeddistributions of neurons with different response properties(e.g., Imig and Adrian 1977; Mendelson et al. 1993; Middle-brooks and Pettigrew 1981; Phillips et al. 1994; Schreiner andMendelson 1990). Due to limitations of conventional micro-electrode mapping techniques, however, a comprehensive viewof the functional organization of A1 has yet to emerge. In asingle mapping experiment, it is only possible to characterizeeffects of a few stimulus parameters from a large number ofrecording sites. Consequently, it is not yet clear how thevarious topographies of response properties described by dif-

ferent studies relate to one another. A second limiting factor isthe lack of anatomical markers. The discovery of histologicalmarkers for functionally distinct neuronal subpopulations,most notably cytochrome oxidase, was a considerable aid toelucidating the functional organization of visual cortex (Hortonand Hubel 1981; Humphrey and Hendrikson 1983; Wong-Riley 1979). In auditory cortex, by contrast, the same markersprovide little compelling evidence for compartmentalization(Tootell et al. 1985; Wallace et al. 1991). Resolution of thisissue in auditory cortex may have implications for our under-standing of cortical organization in general.

Optical imaging (OI) of intrinsic signals (Grinvald et al.1986; Ts’o et al. 1990) offers both vastly increased spatialsampling density and the potential to sample cortical responsesto a larger stimulus repertoire in a single experiment than ispossible with microelectrode mapping, making it a promisingalternative approach for studying the physiological organiza-tion of A1. This technique uses changes in light reflectance,associated with physiological activity, to visualize the locationof cortical tissue activated by a given stimulus. The lightreflectance signals derive from multiple sources, includingchanges in local blood volume, which dominate the signal atwavelengths below 600 nm, and changes in the oxygenationstate of hemoglobin and light scattering, which provide a majorsource of signals at longer wavelengths (Frostig et al. 1990;Malonek and Grinvald 1996; Malonek et al. 1997). Becauseneuronal responses are measured indirectly, it is essential toverify results obtained by this method with electrophysiologi-cal recording. Although most studies of visual cortex haveshown a high degree of correspondence between stimulus-evoked optical and neurophysiological responses (Crair et al.1997; Ghose and Ts’o 1997; Grinvald et al. 1986; Roe andTs’o 1995; Shmuel and Grinvald 1996; Shoham et al. 1997),under certain conditions, the areal extent of over which evokedoptical signals are recorded can be several times greater thanthat of the neuronal spiking response (Das and Gilbert 1995).

Recently, several groups have used OI of intrinsic signals tostudy the topography of stimulus evoked activity in auditorycortex of rodents (Bakin et al. 1996; Harrison et al. 1998; Hessand Scheich 1996). Results of these studies differ from those ofsingle-unit mapping studies of cat A1 (Heil et al. 1994; Phillips

Present address and address for reprint requests: M. W. Spitzer, Institute ofNeuroscience, University of Oregon, Eugene, OR 97403 (E-mail: [email protected]).

The costs of publication of this article were defrayed in part by the paymentof page charges. The article must therefore be hereby marked ‘‘advertisement’’in accordance with 18 U.S.C. Section 1734 solely to indicate this fact.

12830022-3077/01 $5.00 Copyright © 2001 The American Physiological Societywww.jn.physiology.org

et al. 1994) in several respects, including threshold and timecourse of evoked activity, spatial distribution of tone-evokedactivity, and effects of changing sound pressure level (SPL). Itis not clear, however, to what extent these apparent differencesare due to species differences or recording methodology be-cause in only one case (Bakin et al. 1996) were optical imagesverified with electrophysiological recording.

For a number of reasons, including the large exposed surfacearea of auditory cortex and the elaborate auditory corticalspecializations, most mapping studies of A1 have been per-formed on the domestic cat (Reale and Imig 1980). As a result,it is possible to formulate relatively high-order questions aboutphysiological organization in this species. On the other hand,all published intrinsic signal-based OI studies of A1 have beenconducted on rodents, about which much less is known. Thepresent study was therefore undertaken to characterize stimu-lus-evoked intrinsic optical signals at different wavelengths incat A1 and to compare optical responses to neuronal spikingresponses elicited by the same stimuli. Preliminary accounts ofthe results were published in abstract form (Spitzer and Clarey1998).

M E T H O D S

Anesthesia and surgical procedures

All surgical and experimental procedures were approved by theAnimal Experimentation Ethics Committee of the University ofQueensland and conformed to the guidelines for use of animals of theNational Health and Medical Research Council of Australia. Experi-ments were performed on cats between 8 wk and 10 mo of age.Stimulus-evoked optical signals at 540 nm, presented in the followingtext, were obtained from three cats, aged 18, 20, and 27 wk. Younganimals were used because it has been reported that the signal-to-noise ratio of optical signals is higher than in older animals (Hubeneret al. 1997). Moreover, because response properties of auditory cor-tical neurons such as latency and threshold mature to adult-like levelswithin the first three to four postnatal weeks (Brugge et al. 1988), it isunlikely that the present results are compromised by any physicalimmaturity of auditory cortex.

Animals were initially sedated with ketamine hydrochloride andinspected to ensure there were no signs of external ear blockage ormiddle ear infection. Surgical anesthesia was then induced with asingle dose of pentobarbital sodium (25 mg/kg ip). Atropine sulfate(10 mg/kg sc) was administered to minimize bronchial mucous secre-tion. Anesthesia was maintained with supplemental doses of ketaminehydrochloride (0.5–5 mgz kg21 z h21 iv, typically starting 2 h afterbarbiturate injection) throughout the subsequent surgery and record-ing session. The subject’s heart rate was monitored throughout therecording session. During the optical and electrophysiological record-ing sessions, anesthetic and supplementary fluids (lactated Ringersolution) were administered by intravenous injection and/or continu-ous intravenous infusion; anesthetic dose rate was adjusted to main-tain a constant heart rate and no signs of skeletal muscle activity(indicated by high-frequency contamination of the electrocardio-gram). Anesthetic level was sufficient to attenuate the eye-blinkreflex. Throughout all procedures, the animal’s temperature was main-tained with a homeothermic heating blanket (Harvard Instruments).

Following induction of surgical anesthesia, the trachea was cannu-lated and an intravenous line was established. A craniotomy wasperformed to expose the temporal cortical surface with the dura intact.A recording chamber was mounted over the skull opening with acryliccement. The dura was then reflected to expose the cortical surface, andthe recording chamber was filled with low-viscosity silicone oil

(Corning) and sealed with a glass cover. Following the optical record-ing session, the top of the recording chamber was removed to permitintroduction of microelectrodes. Dexamethosone was administered (1mg/kg iv) prior to reflection of the dura and opening of the recordingchamber to prevent cerebral edema. During the recording sessions,subjects were situated on a vibration isolation table (Newport Instru-ments) housed in an anechoic chamber. The cat’s head was stabilizedby attachment of the skull to a stereotaxic frame. Following experi-ments, animals were euthanized by overdose of pentobarbitone so-dium (120 mg/kg iv).

Optical data acquisition and acoustic stimulation

Intrinsic optical signals were recorded using the Imager 2001video acquisition system (Optical Imaging, Germantown, NY), thedetails of which have been described previously (Bonhoeffer andGrinvald 1996; Grinvald et al. 1986, 1988; Ts’o et al. 1990). Thecortical surface was illuminated with narrowband light, generatedby band-pass filtering (band centers, 540, 630, or 6906 10 nm;interference filters from Edmund Scientific, Barrington, NJ) theoutput of a tungsten light source, and conveyed by two fiber-opticlight guides. Video images of the illuminated cortex were acquiredat 30 frames per second with a CCD camera (Bischke, Japan). Thecamera was positioned orthogonal to the exposed surface of puta-tive primary auditory cortex (gyral surface between the tops of theanterior ectosylvian and posterior ectosylvian sulci). Data werecollected with the camera focused between 350 and 500mm belowthe cortical surface to minimize artifacts due to the presence ofsurface blood vessels. A typical imaging session began at least 4 hafter induction of anesthesia and continued for 12 h. While 12-bitcameras permit the encoding of absolute reflectance value, theImager 2001 system employs differential imaging methodology toallow the use of standard 8-bit video technology. In this method, areference image (average of 64 video frames) is obtained prior toeach block of recording trials. This reference image is subtractedfrom each subsequent recorded image within a block of trials. Thereference-subtracted images constitute the stored data files onwhich further analyses are performed. Such initial reference sub-traction allows the encoding of the differential signal within the8-bit limit and has comparable signal-to-noise resolution as thatobtained by storing the absolute reflectance values. Absolute re-flectance values can be reconstructed from the reference images. Inthis study, intrinsic optical signals were acquired by summingvideo frames captured over 0.5 s for stimulus-evoked signals, or 1 sfor spontaneous signals, followed by reference subtraction. Theresulting differential image was then amplified, digitized (8 bits),and stored on computer disk. The stored image produced by thisprocess will be referred to hereafter as adata frame.

Acoustic stimuli were generated digitally (MALab, Kaiser Instru-ments, Irvine, CA) and presented via a calibrated piezo-electric trans-ducer (Motorola KSN 1141) positioned 25 cm from the ear contralat-eral to the imaged cortex and approximately 50° in azimuth from thecat’s midline. Individual acoustic stimuli consisted of trains of five toseven identical tone pips (10-ms cosine rise and fall, 70-ms duration,730-ms inter-pip interval), as illustrated in Fig. 5. Detailed stimulusparameters are included in figure legends. Stimuli were presented insets consisting of five or six combinations of frequency and soundpressure level (SPL) and a no-stimulus condition, presented in randomorder.

Acoustically evoked optical signals were recorded by acquiringa sequence of data frames during presentation of each acousticstimulus. Acquisition of optical data was synchronized to acousticstimulus presentation, starting one frame (500 ms) prior to stimulusonset and continuing for up to 6.5 s after stimulus offset (see Figs.3 and 5). Following this data acquisition period, there was a silentinterval of 12 s. To remove periodic spontaneous variation of the

1284 SPITZER, CALFORD, CLAREY, PETTIGREW, AND ROE

optical signal (seeRESULTS), it was necessary to sum optical datarecorded during multiple repeated trials of each stimulus set.Typically, data were collected and stored on-line in blocks of fouror five repeated stimulus sets.

Acoustically evoked and spontaneous optical signals were visual-ized by off-line analysis (SumAnal program) (Ghose and Ts’o 1997).For acoustically evoked images, corresponding data frames (i.e., samestimulus and time after stimulation) from multiple blocks of storeddata were first summed. Each successive summed frame collectedafter stimulus onset was then divided by the frame collected prior tostimulus onset within the trial. (n.b. This differential analysis proce-dure should not be confused with the initial reference image subtrac-tion performed prior to saving data, on-line.) The resulting valuesindicate the change in light reflectance (DR) at each measured pixelfollowing stimulus onset. Further analyses are described inRESULTS.To displayDR data as images, images were clipped (top and bottom19% of the pixel value distribution removed) to eliminate large signalsdue to blood vessel artifact and fit to a common linear 33 color scale(shown in each figure). Spontaneous optical signals were visualizedusing a similar procedure of frame-by-frame, temporal analysis ofsignal development. However, data from individual trials (20-s dataacquisition period, no stimulus) were analyzed separately withoutsummation across blocks.

The present data were obtained in 10 experiments performed oncats maintained under ketamine anesthesia. An earlier series of ex-periments was performed on 15 cats maintained under barbiturateanesthesia (pentothal sodium). In general, results obtained using bar-biturate anesthesia were inconclusive due to excessive variability.However, a few references are made to results from these experi-ments, where appropriate.

Electrophysiological recording

Electrophysiological mapping was performed in four of the exper-iments. Following the imaging session, a dose of dexamethosone (1mg/kg iv) was administered, and the lid of the recording chamber wasremoved. A reference image of the cortical surface collected underillumination with green light (590 nm) was used to guide electrodeplacement and for later alignment of optical and electrophysiologicaldata. Glass-coated, tungsten microelectrodes (0.5–2.5 MV impedanceat 1 kHz) were introduced perpendicular to the cortical surface usinga stepping motor microdrive (Herb Adams, Caltech) controlled fromoutside the anechoic chamber. The electrode signal was amplified(31,000 gain) and filtered 0.3–5 kHz. Recordings of multi- andsingle-unit activity were obtained by level triggering (MALab).Multiunit recordings were only obtained at sites where action poten-tials of the constituent units could be clearly distinguished visuallyusing an oscilloscope. Single-unit recordings were also distinguishedby visual criteria. In each electrode penetration, an attempt was madeto record from the closest site to the cortical surface exhibitingacoustically driven unit activity. In practice, the majority of record-ings were obtained at depths between 400 and 800mm.

Neuronal responses to the stimulus set used for optical imagingwere collected at each recording site. In addition, an attempt wasalways made to determine the frequency/level combination thatgave an optimal response. The response to the “optimal” stimuluswas also recorded if it was considerably greater than responses toany of the stimuli used for optical imaging. Slight modifications tothe stimulation protocol were made for electrophysiological re-cording: stimuli were presented as 70-ms-duration tone pips(10-ms cosine rise/fall), 730-ms interstimulus interval, 20 repeti-tions. The time of occurrence of triggered action potentials andstimulus events were logged (more than 1-ms resolution) andstored in a FIFO buffer, from which they were retrieved by the hostcomputer and stored on disk.

R E S U L T S

Spontaneous optical signals

Spontaneous changes of light reflectance in auditory cortexwere observed in the absence of acoustic stimulation in 9/10cats. In most cases, the spontaneous signals were manifest asirregular variations of reflectance in the no-stimulus conditionbut were obscured by averaging signals from multiple trials. Tovisualize the spontaneous signal directly, optical signals wererecorded without averaging from one cat. An example of thespontaneous optical signal recorded under illumination with540-nm light is shown in Figs. 1 and 2. The change in corticallight reflectance (DR) during a 20-s sampling period was mea-sured by recording 21 consecutive 1-s data frames and dividingframe 2 through 21 by frame 1. During the sampling period, thereflectance of 540-nm light increased and decreased relative tothe initial frame in an oscillatory manner at a frequency of 0.1Hz (Fig. 1). The optical signal thus recorded has two compo-nents. The first component is a coherent oscillation of reflec-tance at all points on the cortical surface (Fig. 1C). A secondcomponent consists of systematic variation of the amplitude ofsignals recorded at different sites. The local variations of signalamplitude can be dissociated from the global variations bydividing the reflectance change at each site by the mean re-flectance change measured over the entire image. Such analysis(Fig. 1D) reveals that the amplitude of reflectance change ateach site oscillates relative to the image mean at a frequency of0.1 Hz and that the phase of oscillation shifts with changesof position across the cortical surface. The local variation ofoptical signals can also be visualized by displaying the reflec-tance change at each measured pixel as an image (individualframes in Fig. 2; seeMETHODS for details). In this case, theglobal reflectance changes are removed by fitting the histogramof pixel values of each frame to a common color map, a similartransformation to division by the image mean. When viewed asan image, it becomes apparent that in each frame areas ofsimilar relative reflectance change form distinct patches, sev-eral millimeters across. A similar 0.1-Hz oscillation of corticallight reflectance was also recorded using 690-nm light (notshown).

Stimulus-evoked optical signals

Stimulus-evoked intrinsic optical signals were clearly evi-dent in only 3/10 cats imaged with 540-nm light. A similarsuccess rate has been reported for imaging at 540 nm inchinchilla auditory cortex (Harrison et al. 1998). In two of theunsuccessful cases, normal multiunit responses were recordedafter the imaging sessions, indicating that our failure to recordoptical signals was not a result of a physiologically unrespon-sive auditory cortex. In successful cases, it was necessary toaverage responses to large numbers of stimulus presentationsto obtain acceptable image quality and to negate the spontane-ous signals. An example of the optical signal recorded at 540nm by averaging responses to 50 presentations of a tone piptrain is illustrated in Figs. 3 and 4. Stimulus-evoked opticalsignals were measured by recording optical data for 10.5 s,starting just prior to stimulation, and dividing data framescollected after stimulus onset by the frame collected beforestimulus onset (Fig. 3C). Within 3 s ofstimulus onset, reflec-tance begins to decrease at nearly all points on the cortical

1285OPTICAL IMAGING IN AUDITORY CORTEX

surface (Fig. 3D). Reflectance continues to decrease through-out the duration of the 4.8-s stimulus sequence and then returnsto prestimulation levels following stimulus offset. The magni-tude of the stimulus evoked reflectance changes at most sites ismuch greater than that of any fluctuations evident in the nostimulus condition (- - -). The absence of large reflectancechanges in the no-stimulus condition indicates that signal av-eraging was sufficient to negate the contribution of spontane-ous signals. Local variations of the amplitude of stimulus-evoked reflectance changes are clearly evident in Fig. 3D.Division by the image mean reveals a restricted region exhib-iting relative decrease of reflectance near the center of pre-sumptive A1 (Fig. 3E). The image representation (Fig. 4A)shows development of an “activated” area (red and orange),corresponding to the location of maximum reflectance de-crease, and, presumably, maximum blood volume increase,within 1 s ofstimulus onset. The activated area remains rela-tively stable from 2-s postonset until stimulus offset and thenquickly dissipates. Note, also, the late “activation” of postero-medial and anterolateral regions that showed relative increasesof reflectance during stimulation. In comparison to the stimu-lated condition, the unstimulated condition shows only minorand unsystematic fluctuations of reflectance (Fig. 4B).

The position of the activated region revealed by opticalsignals at 540 nm is dependent on stimulus frequency. Opticalsignals recorded from the same cortex in response to sixdifferent frequency-level combinations are shown in Fig. 5.Responses to stimuli presented at 65 dB SPL show a clearprogressive shift of the activated region from caudal to rostral

as stimulus frequency is incremented from 5 to 20 kHz, inagreement with the known tonotopic organization of cat A1(Reale and Imig 1980). In contrast to the pattern of neuronalactivation, described previously (Heil et al. 1994; Phillips et al.1994; Schreiner et al. 1992), the position of optical activationevoked by 15-kHz tones remains constant across a 30-dB rangeof stimulus level. The decaying phase of the activation se-quence follows a curious course in responses to the 15-kHz,80-dB and 20-kHz, 65-dB stimuli. In both cases, followingstimulus offset the region of decreased reflectance shifts in acaudal direction. Similar shifts of the activated region afterstimulus offset or during the later stages of the stimulationperiod were observed in all three successful 540-nm imagingexperiments. In this particular case, as a result of the shift, theimages obtained for over 2 s following offset of the 20-kHzstimulus are very similar to the stimulus-evoked images re-corded in response to the 5-kHz stimulus. Thus in this and theother two cases, a topographic relationship of reflectancechanges was apparent only for the period during stimuluspresentation.

Weak stimulus-evoked intrinsic optical signals were alsoevident in 9/10 cats imaged using 690-nm light and ketamineanesthesia, including those exhibiting stimulus-evoked signalsat 540 nm. The magnitude of evoked reflectance changes at690 nm was approximately one-tenth that observed at 540 nm.In contrast to the optical signals recorded at 540 nm, at 690 nm,reflectance changes were uniformly distributed across the cor-tical surface, and their topography was uninfluenced by stim-ulus frequency. Multiunit mapping was performed in four cats

FIG. 1. Oscillatory spontaneous optical signals recorded with 540-nm light.A: schematic illustrates the location of the imagedarea with respect to the major cortical sulci. AES, anterior ectosylvian sulcus; PES, posterior ectosylvian sulcus; SSS, suprasylviansulcus; M, medial; A, anterior.B: macroscopic view of the exposed cortical surface. Scale bar5 5 mm.C: reflectance change wasmeasured in a 1623 129 pixel region (box inA andB) by recording video data during a 21-s period as a series of 21 data framesand dividing pixel values in frames 1–20 by the corresponding pixel values in frame 0. Mean reflectance change (DR) measuredin 5 3 5 pixel regions (crosses inB) underwent coherent oscillatory change throughout the 20-s sampling period.D: dividing DRvalues measured at each site by the meanDR value of all pixels of each frame (meanDR) revealed incoherent local oscillationsof DR amplitude.


exhibiting stimulus evoked signals at 690 nm, and in all cases,revealed normal multiunit responses with stimulus-dependenttopography. Cross-condition analyses of the evoked opticalsignals (e.g., dividing responses to different frequencies andlevels, subtracting responses to a single condition from the sumof all conditions, dividing across binaural conditions in barbi-turate anesthetized animals), such as those performed in studiesof visual cortex (Bonhoeffer and Grinvald 1993; Frostig et al.1990; Ts’o et al. 1990), did not reveal any stimulus-dependenttopography at 690 nm. Finally, similarly uniform and stimulus-feature-independent topography of intrinsic optical signals wasobserved in barbiturate anesthetized cats using light band-passfiltered at 690 or at 636 nm or long-pass filtered with 650-nmcutoff.

Comparison of optical and multiunit responses

Multiunit mapping was performed in 2/3 animals that ex-hibited stimulus-evoked optical signals at 540 nm. Results ofone experiment in which optical signals and multiunit electro-physiological data were recorded from the same cortex are

shown in Fig. 6. The optical images form a tonotopic sequencewith the region of activation shifting progressively from caudalto rostral as stimulus frequency is incremented from 5 to 20kHz. Multiunit responses were classified as either clear re-sponses, no response, or near-threshold responses (details inlegend). In each image, there are a number of multiunit record-ing sites at which the optical and electrophysiological re-sponses are in apparent agreement (e.g., 5 kHz: 1, 6, 9; 10 kHz:3, 5, 8, 9; 15 kHz: 4, 5, 6; 20 kHz: 1, 3, 4, 5, 6, 8) and a numberat which they clearly disagree (e.g., all stimuli at sites 10 and11; 10 kHz: 1, 2, 4; 15 kHz: 3; 20 kHz: 7). Multiunit recordsand optical signals recorded at each site in response to the 20kHz stimulus are shown in Fig. 7 to permit detailed compari-sons. This case was chosen for illustration because it representsthe best agreement between optical and multiunit responses.While there appears to be good agreement between optical andmultiunit responses at the majority of sites (e.g., 1–6, and 8),there are also sites where the two measures clearly disagree (10and 11), and others where the relationship is questionable (7and 9).

Examination of cases where the optical and multiunit re-

FIG. 2. Temporal progression of spontaneous optical signals recorded at 540 nm from the boxed region in Fig. 1. Numberedimages correspond to data frames averaged over successive 1-s sampling periods. Crosses indicate positions sampled in Fig. 1.Regions showing minimumDR values, corresponding to maximum reflectance decrease and, presumably, maximum increase inlocal blood volume, are shown in red, and maximumDR values are shown in black.DR values were mapped, linearly, onto theindicated color table.DR values less than or greater than the clipped range are shown in red and black, respectively. Scale bar52 mm.


sponses disagreed revealed several examples of both falsepositive (decrease of reflectance relative to image mean, but nomultiunit response; e.g., Fig. 6, site 3 at 15 kHz, sites 1 and 4at 10 kHz) and false negative (clear multiunit response but noreflectance decrease relative to image mean; e.g., Figs. 6 and 7,sites 10 and 11 for all stimuli) optical signals. Inexperiment98s11, 55 comparisons of optical and multiunit responses(responses to 5 stimulus conditions compared at 11 sites)revealed 22 clear mismatches of which 9 were false positivesand 13 false negatives. Cases where the multiunit response wasclassified in the threshold category were not counted in thisanalysis. Inexperiment 98s5,95 comparisons (5 stimulus con-ditions, 19 sites) revealed 30 mismatches of which 8 were falsepositives and 22 were false negatives. Thus in both experi-ments in which multiunit data are available, the majority oferrors were false negatives.

It is not obvious from the preceding qualitative comparisonswhether the level of agreement of optical signals and multiunitresponses is higher than that expected by chance. To addressthis issue, quantitatively, the magnitude of optical and multi-unit responses was compared at each electrophysiological re-cording site in two cats. A strong association would be ex-pected to result in a significant negative correlation betweenthese two response measures. Scatter plots relating the magni-tudes of optical signals and multiunit responses, recorded at thesame sites, in response to all stimuli that elicited clear, stimu-lus-evoked optical signals, are shown in Fig. 8 (see legend for

details). To enable comparison of multiunit responses acrossrecording sites, response magnitude at each site is expressed asa percentage of the response to the optimal stimulus at that site.Sites at which an optimal stimulus could not be determinedwere excluded from analysis. The level of correlation betweenmagnitudes of optical signals and multiunit responses wasassessed separately for each stimulus condition and also for allresponses pooled across stimuli within each experiment, bycalculating Spearman’s rank order correlation coefficient (Rs; anonparametric measure was used because the multiunit re-sponse data were not normally distributed due to a strongceiling effect). Correlation values for individual stimulus con-ditions are shown in Table 1. In only 3 of the 10 cases was asignificant (P , 0.05) correlation detected between optical andmultiunit response magnitudes. Furthermore, in one of thethree cases showing significant correlation, the direction ofrelationship was reversed. Due to the small sample sizes, itremains possible that a weak association existed in the remain-ing cases but was not detected. However, analysis of datapooled across conditions in each experiment (Fig. 8) providedno evidence of a significant correlation. Thus the present dataprovide little evidence of an association between the magnitudeof stimulus-evoked optical and multiunit responses.

Relation of stimulus-evoked and spontaneous optical signal

Finally, an intriguing similarity between spatial patterns ofspontaneous and stimulus-evoked optical signals was observed

FIG. 3. Stimulus-evoked optical signals recorded at 540 nm.A: schematic illustrates location of imaged region. Abbreviationsand conventions same as Fig. 1.B: macroscopic view of the exposed cortex. Scale bar5 5 mm.C: stimulus consisted of a trainof 7 tone pips (pip duration, 70 ms; rise/fall time, 10 ms; interpip interval, 730 ms) of 10 kHz at 65 dB SPL. Data frames weresummed from 50 trials per stimulus. After summation, frames 1–20 were individually divided by frame 0 to calculateDR. D: DRdecreased at all sites during the period of stimulus presentation (n above time axis) and returned to prestimulus levels thereafter.Stimulus evoked optical signals (—) were much larger than reflectance changes measured in the unstimulated condition (- - -).E:division by the image mean revealed systematic local variations of amplitude of stimulus evoked signals.


in the single case for which both forms of data are available. Acomparison of spontaneous and stimulus-evoked images ob-tained at 540 nm from the same cortex, is shown in Fig. 9. Thetop row of images are single frames (frame 5, 2,000- to2,500-ms poststimulus onset) taken from sequences of stimu-lus-evoked activity, which form a tonotopic sequence as shownin Fig. 6. The images in themiddle row are single frames,arbitrarily selected, from sequences of spontaneous opticalactivity recorded from the same cortex. The apparent similarity

of patterns of stimulus-evoked and spontaneous optical signalswas confirmed by subtracting each image in themiddle rowfrom the image above it (results shown onbottom row). Theresulting difference images show little overall variation fromthe mean value, with most of the remaining peaks and troughscorresponding to major blood vessels. The similarity of topog-raphy of stimulus-evoked and spontaneous images might ap-pear to suggest thatall of the images resulted from spontaneousactivity. This suggestion is, however, untenable because it

FIG. 4. Optical images illustrate the rel-atively focal topography of stimulus-evokedoptical signals recorded at 540 nm. Crossesindicate locations sampled in Fig. 3. Scalebar5 3 mm.A: in the stimulated condition,a focal region of maximum reflectance de-crease develops and is maintained for theduration of stimulus presentation.DR valuesfor each image frame were mapped onto thecolor table shown such that numericallysmallest values, corresponding to maximumreflectance decrease, are red and numericallylargest values are black.B: only minor re-flectance changes are evident in the unstimu-lated condition.


cannot account for synchronization of reflectance changes toonset of acoustic stimulation, persistence of stimulus-evokedsignals despite averaging images from multiple presentations,dependence of the topography of evoked images on stimulusfrequency, nor for absence of major reflectance changes in theno-stimulus condition after extensive averaging. An alterna-tive, albeit speculative explanation is that the neuronal orvascular functional units that are activated by acoustic stimu-lation are also spontaneously active in the absence of stimula-tion.

D I S C U S S I O N

The major findings of the present study are that both spon-taneously occurring and stimulus-evoked optical signals wereobserved in auditory cortex of anesthetized cats; the spatialdistribution of stimulus-evoked optical signals recorded at 540nm was consistent with the known tonotopic organization ofA1; and despite the stimulus-dependent topography of opticalsignals, the distribution of maximum reflectance changes wasapparently not related to the distribution of extracellularlyrecorded neuronal activity.

The mismatch between the spatial distribution of opticalsignals and multiunit responses suggests that the optical signalat 540 nm corresponds to local blood volume changes withinvascular functional units, recruited in response to physiological

activation, whose fine structure is imprecisely matched to thatof the multiunit response. The following sections discuss therationale for these conclusions as well as alternative explana-tions of our results.

Differences in recording depth of optical and multiunitresponses

Due to constraints imposed by light penetration and scatter-ing, intrinsic optical signals are recorded from the superficialcortical layers (Bonhoeffer and Grinvald 1996). In these ex-periments, optical signals were recorded at a depth of 500mmbelow the cortical surface. Because the superficial corticallayers contained few electrically responsive units, multiunitresponses were recorded at depths ranging from 320 to 1,200mm, with mean recording depths of 821 and 580mm forexperiments 98s5and 98s11,respectively. The difference indepths at which optical and multiunit responses were recordedraises two issues pertinent to interpretation of the presentresults and may help to explain the low success rate of theimaging experiments. First, do neuronal response propertiesvary with depth in A1? In agreement with the general conceptof columnar organization, several studies have shown thatresponse properties, including type of response to contralateralear stimulation and frequency tuning, remain consistentthroughout the depth of A1 (Abeles and Goldstein 1970; Imig

FIG. 5. Optical images recorded at 540 nm show tonotopic organization of stimulus-evoked reflectance changes. Images werecollected in response to 6 frequency3 sound pressure level combinations (left) and a no-stimulus condition from the same cortexas in Figs. 3 and 4. The region of peak activation during the stimulation period shifts from posterior to anterior as stimulusfrequency is incremented from 5 to 20 kHz. Schematic, atbottom, illustrates timing of stimulus sequence relative to image frames.


and Adrian 1977), including the superficial layers (Reser et al.2000). A major exception is that, under binaural conditions, theinfluence of ipsilateral ear stimulation may vary with corticaldepth (Phillips and Irvine 1979; Reser et al. 2000). Despite thevariation of ipsilateral ear influences, however, Clarey et al.(1994) found that preferred azimuth remained homogenousthroughout cortical depth in 72% of electrode penetrations.Thus although it is possible that the response to the contralat-erally located speaker, used in the present study, would changewith depth at some recording sites, such effects would belimited to a minority of sites.

Furthermore it is difficult to evaluate the extent to whichsuch depth effects might confound the comparison of multiunitand optical responses because it is unknown whether the op-tical signals are generated in response to subthreshold neuronalactivity in the superficial cortical layers or suprathresholdactivity in the middle layers. The depth disparity is onlyrelevant in the latter case. A second issue is whether the540-nm optical signals could be displaced laterally from theirsite of origin due to blood flow with an orientation parallel tothe cortical surface. This would appear unlikely because thearterioles and venules that supply the cortical parenchyma areoriented orthogonal to the cortical surface (Edvinsson et al.1993). Reflecting this anatomical arrangement, numerous stud-ies have demonstrated that local blood flow within the cerebralcortex follows a course parallel to that of neuronal columns(e.g., Bryan and Duckrow 1995). Thus optical signals with ahemodynamic basis should remain aligned with their columnof origin regardless of recording depth. Finally, the paucity ofneuronal responses in the superficial layers of A1, whereoptical signals are recorded, is an obvious potential cause ofthe low success rate of the imaging experiments. Future at-tempts at intrinsic signal based imaging of A1 might benefit

from use of anesthetics, such as isofluorane, which are lessdisruptive to cortical activity patterns, or an awake preparation.

Spontaneous optical signals

In the present study we observed spontaneous oscillatorychanges of reflectance of both red and green light at frequen-cies close to 0.1 Hz. Spontaneous optical signals with similarproperties have been reported previously (Mayhew et al. 1996).Using similar optical recording methods, Mayhew and cowork-ers observed 0.1-Hz oscillations of reflected dichromatic light(570 and 660 nm) from the surfaces of diverse brain structuresin anesthetized rats and unanesthetized cats. Furthermore theydemonstrated that the change of intensity of reflected light washighly correlated with changes of local blood flow measured inthe same tissue by laser-Doppler flowmetry. Thus it is highlylikely that the spontaneous optical signal recorded by Mayhewet al., and in the present study results from vasomotion, a0.1-Hz oscillation of local cerebral and somatic blood flow thathas been widely reported (Dirnagl et al. 1989; Fagrell et al.1980; Golanov et al. 1994; Meyer et al. 1988; Morita-Tsuzukiet al. 1992).

Spontaneous optical signals are a major source of noisethat must be overcome to record stimulus-evoked signals.The spontaneous signals measured by Mayhew et al. couldbe as large as 1–2% of the total reflected light signal;whereas, the “mapping signals” used to define functionalarchitecture by intrinsic signal based optical imaging aretypically an order of magnitude smaller (Frostig et al. 1990;Grinvald et al. 1988). At least one other optical imagingstudy of auditory cortex has reported “spontaneous waves ofcortical activity” with a cycle of 5–10 s that acted as a majorsource of interference (Harrison et al. 1998). In the present

FIG. 6. Comparison of multiunit responses and optical images recorded at 540 nm in 1 animal. Multiunit responses wererecorded at numbered sites and classified qualitatively as either clear responses, threshold responses, or no response. The thresholdcategory included responses of less than 7 spikes per 20 stimulus presentations and in a few cases where it was difficult todifferentiate a putative response from spontaneous activity. Optical images of responses to tone pips at 65 dB SPL were collectedas shown in Fig. 4, using identical stimulus parameters. Image frames 4–7 were summed, and results were median filtered to reducenoise.


study, averaging data from multiple stimulus presentations(more than 16) proved sufficient to remove major contribu-tions of the spontaneous signals.

Comparison with previous studies of auditory cortex

Results of recent optical imaging studies of auditorycortex in ketamine-anesthetized chinchillas (Harrison et al.1998) and barbiturate-anesthetized cats (Dinse et al. 1996)are similar to those obtained with 540-nm light in thepresent study. Harrison et al. (1998) recorded tone-evoked

optical signals at 540 nm with similar time course andtopography to those reported here. Threshold levels forreliably eliciting optical signals were between 40 and 50 dBSPL. Both previous imaging studies reported monotonicgrowth of activated regions as stimulus SPL was increasedand tonotopic organization of activated regions at suprath-reshold SPL.

Results obtained with optical imaging at 540 nm differ inseveral respects from the previously described maps of single-unit (Phillips et al. 1994), and multiunit (Heil et al. 1994;

FIG. 7. Comparison of optical (540 nm) and multiunit responses to 20 kHz, 65 dB stimulus recorded at numbered sites in Fig.6. Optical signals recorded in a 53 5 pixel region centered on each multiunit site in the stimulated and unstimulated conditionsare shown as — and - - -, respectively. Multiunit responses are shown as poststimulus time histograms and dot rasters below eachoptical signal. Ordinate axes of histograms are scaled relative to the maximum response recorded at each site. Pip duration ()is shown on the horizontal axis of each histogram.


Schreiner et al. 1992), responses to tones in A1. First, single-unit thresholds were often lower than 10 dB SPL, and patchesof neighboring sites containing units responding to a givenfrequency were evident at 20 dB SPL, at least 20 dB belowthreshold for optical signals. Second, as SPL was increased, thelocation of patches of active neurons changed such that thelocation of neurons responding maximally at the highest SPLwas usually very different from the location of neurons activenear threshold SPL. All maps contained at least some patchesof recording sites where neuronal activity decreased as a func-tion of increasing SPL. By contrast, the area of activated cortexindicated by optical recording grows monotonically with in-creasing SPL, remaining centered on the site showing activa-tion at threshold (Dinse et al. 1996; Harrison et al. 1998).Finally, at high SPL (e.g., at least 60 dB), the distribution ofsingle-unit activity consisted of multiple, discrete, patches ofactive neurons separated by intervening areas of unresponsiveneurons. The largest continuous patches of active neurons werenot more than 3 mm across. Optical imaging, on the otherhand, typically reveals a single, large region of activation(Dinse et al. 1996; Harrison et al. 1998; present results). In ourhands the activated region could span more than 5 mm (Figs.4 and 5). Finally, the lack of correspondence between multiunitresponses and optical signals at 540 nm reported here is un-surprising, given the major discrepancies between the previ-ously reported optical and single-unit maps.

It might be argued that the maps of unit activity obtainedusing contralateral ear stimulation, are not directly comparableto the images obtained in the present study, using free-fieldstimulation. Certainly, the single-unit maps obtained with dif-ferent procedures are likely to differ, primarily as a result ofdifferences in the contribution of ipsilateral ear stimulation.However, the effects of SPL on the distribution of active

neurons primarily reflect the patchy organization of neuronswith different forms of sensitivity to SPL (Clarey et al. 1994;Heil et al. 1994; Phillips et al. 1994; Sutter and Schreiner1995), as opposed to binaural interaction, and are thereforeunlikely to be dramatically altered by the difference in stimu-lation procedures.

Two studies, thus far, have reported tone-evoked opticalsignals at wavelengths greater than 600 nm in auditory cortex.Hess and Sheich (1996) recorded at 610 nm in auditory cortexof unanesthetized gerbils, and Bakin et al. (1994) recorded at630 nm in barbiturate-anesthetized rats and guinea pigs. Inagreement with the present findings, in both studies opticalimaging indicated activation of very large, continuous regionsof A1. The contiguous and broad distribution of activatedregions revealed by optical imaging at 630 nm in rats (Bakin etal. 1996) differs from the patchy distribution of single-unitactivity reported by Phillips et al. (1994) in cats. Subsequentmultiunit mapping, however, revealed much better agreementbetween optical and neuronal responses in rats than was evi-dent in the present study. The mapping data presented by Bakinet al. (1994) permit 214 comparisons of optical and multiunitresponses (2 stimulus conditions at 107 sites) of which only 33showed clear disagreement between the two measures. Thusthe difference between imaging results in rats and single-unitmapping results in cats may indicate a fundamental differencein the topographic representation of suprathreshold tones inauditory cortex of the two species. In the gerbil, the location ofthe activated region revealed by optical imaging shifted at laterstages of the stimulation period and continued to shift aftercessation of stimulation (Hess and Scheich 1996). Similarshifts were observed in all three cats successfully imaged at540 nm in the present study. Hess and Sheich suggested thatshift of the activated area is indicative of a corresponding shiftof subthreshold electrophysiological activity. However, in theabsence of corroborating electrophysiological data, and in lightof the lack of correspondence between optical signals andneuronal responses demonstrated here, it is equally likely thatthe phenomenon reflects the spatiotemporal properties of thehemodynamic response rather than those of the neuronal re-sponse.

Comparison with previous studies of visual andsomatosensory cortex

The findings of the present study differ from those of intrin-sic signal-based optical imaging studies of visual and somato-sensory cortices in two regards. First, in the present study

FIG. 8. Peak amplitude of optical signals recorded at 540nm is plotted against multiunit response magnitude at eachrecording site for all stimuli that evoked clear optical responsesin experiments 98s11and 98s5.Stimuli are listed in Table 1.Only stimuli that evoked a clear decrease in reflectance (DR) atmultiple recording sites, initiated within the first 3 s afterstimulus onset, were included in this analysis. Spearman’s rankorder correlation coefficient (Rs) are shownatop each plot. Inneither case was the correlation significant (P , 0.05). Opticalsignals were measured by calculating the reflectance change(DR) in a 5 3 5 pixel window centered at each multiunitrecording site and determining the maximum absolute valueoccurring within 3 s of stimulus onset. Multiunit responsemagnitude is expressed as percentage of response to the opti-mum stimulus at each recording site. Stimulus parameters andoptical recording procedures are identical to those in Fig. 4.

TABLE 1. Correlations ofDR and multiunit response magnitudefor individual stimuli

Experiment n Stimulus Rs Significance

98s11 11 5 kHz, 65 dB 0.03 NS10 kHz, 50 dB 20.43 NS10 kHz, 65 dB 20.29 NS15 kHz, 65 dB 20.13 NS20 kHz, 65 dB 20.63 P , 0.05

98s5 19 5 kHz, 65 dB 0.58 P , 0.0110 kHz, 50 dB 20.35 NS10 kHz, 65 dB 20.32 NS10 kHz, 80 dB 20.52 P , 0.0515 kHz, 65 dB 0.19 NS


optical signals with stimulus-dependent topography were re-corded at 540 nm but not at longer wavelengths. By contrast,in visual cortex, similar functional maps of ocular dominanceand orientation preference can be obtained at wavelengthsranging from 480 to 940 nm (Frostig et al. 1990). In rodentsomatosensory cortex, stimulation of a single facial vibrissaalso evokes optical images with similar spatial location andextent at 550, 610, and 850 nm (Narayan et al. 1994). Thewavelength dependence of optical signals in cat auditory cortexsuggests that stimulus-evoked changes in local blood volume,oxygen saturation of hemoglobin, and light scattering, whichprovide the major sources of optical signals recorded at 540,630, and 690 nm, respectively (Frostig et al. 1990; Malonekand Grinvald 1996; Malonek et al. 1997), are not as wellcoupled in this cortex as they are other sensory cortices and,presumably, in auditory cortex in other species (Bakin et al.1996; Harrison et al. 1998; Hess and Scheich 1996). Thereason for this apparent difference is not readily apparent. Asecond difference is that, in the present study, the topographies

of optical signals and neuronal spiking responses evoked by thesame stimulus were unrelated. By contrast, several studies havedemonstrated a tight correspondence between the spatial dis-tribution of optical and spiking responses in visual cortex(Crair et al. 1997; Ghose and Ts’o 1997; Grinvald et al. 1986;Roe and Ts’o 1995; Shmuel and Grinvald 1996; Shoham et al.1997) and rodent somatosensory cortex (Masino et al. 1993;Peterson et al. 1998). In the following text, we consider threepossible explanations for the latter difference.

Visualization of subthreshold and interneuron activity

Two studies of visual cortex, using spatially restricted stim-uli, provide evidence that intrinsic optical signals reflect bothsub- and suprathreshold neuronal activity. In contrast to pre-vious imaging studies that used full-field visual stimulation,these studies demonstrated that partial field stimulation evokesoptical signals distributed over a much larger cortical area thanthe corresponding neuronal spiking responses. Using stimuli

FIG. 9. Similarity of stimulus-evoked and spontaneous optical images recorded at 540 nm.Top: optical images in response tostimuli of 5 kHz (A), 10 kHz (B), and 20 kHz (C) at 65 dB SPL. Data are the same as in Fig. 6.Middle: individual 1-s framesselected from 3 20-s epochs of spontaneous activity recorded as in Fig. 1.Bottom: results of subtracting images in the middle rowfrom images in thetop row (G 5 A–D; H 5 B–E; I 5 C–F).


designed to simulate the receptive field size of a single corticalneuron, Das and Gilbert (1995) reported that the areal extent ofevoked optical signals was approximately 20 times greater thanthat of evoked spiking activity. In a second study, using partialfield stimulation, single-unit data provided evidence of sub-threshold physiological activity within regions containingevoked optical signals but no spiking neurons (Toth et al.1996). Thus in visual cortex, stimuli that elicit spatially re-stricted patterns of spiking activity, as do tones in auditorycortex, reveal large discrepancies between the spatial distribu-tion of optical and unit responses, most likely due to visual-ization of subthreshold physiological activity. It is thereforepossible that visualization of subthreshold activity could be aprimary cause of the mismatch between patterns of opticalactivation and spiking activity observed in the present study.

Another potential source of the mismatch between opticaland unit activity is the difficulty of recording spiking activityfrom inhibitory interneurons with extracellular electrodes.Mountcastle et al. (1969) reported that the majority of extra-cellular recordings obtained with metal electrodes in somato-sensory cortex exhibited a type of waveform referred to as“regular spikes.” Only occasionally were recordings obtainedfrom neurons with “thin spikes,” characterized by a compara-tively shorter initial negative phase, smaller amplitude, andspatially restricted electrical field. A slightly higher proportionof “thin,” or “fast spiking,” neurons have been recorded instudies using glass micropipette electrodes (e.g., Simons 1978).More recently, intracellular experiments have confirmedMountcastle’s proposal that regular spiking neurons have py-ramidal morphology and thin spiking neurons have aspinystellate morphology, typical of GABAergic inhibitory inter-neurons (McCormick et al. 1985). These findings providestrong circumstantial evidence that metal extracellular elec-trodes record preferentially from pyramidal neurons. The tem-poral properties of stimulus-evoked spike bursts recorded ex-tracellularly in auditory cortex are consistent with this view(Bowman et al. 1995; Phillips et al. 1996). Consequently amismatch between multiunit and optical responses could po-tentially arise in areas where spiking activity of interneuronsgenerates a strong optical signal, while simultaneously inhib-iting nearby pyramidal neurons.

There is certainly considerable evidence that stimulationwith tones at high SPL elicits subthreshold electrophysiologi-cal activity throughout a substantial proportion of auditorycortex, including a major component due to inhibitory pro-cesses and, presumably, spiking activity in inhibitory interneu-rons. First, because many A1 neurons have frequency-domaininhibitory side bands (Calford and Semple 1995; Calford et al.1993; Phillips 1988; Phillips and Cynader 1985; Schreiner andMendelson 1990; Shamma and Symmes 1985; Shamma et al.1993), a tonal stimulus of a given frequency will inducewidespread inhibition of neurons with higher and lower bestfrequencies. Second, many A1 neurons exhibit level-dependentsuppression (Phillips and Irvine 1981), referred to as “non-monotonicity,” a substantial proportion of which is likely gen-erated by intracortical inhibitory mechanisms (Barone et al.1996; Prieto et al. 1994). Because nonmonotonic neurons aredistributed in patches (Clarey et al. 1994; Phillips et al. 1994),the spatial pattern of cortical activity induced by tones at highSPL should be expected to include patches of spiking inhibi-tory interneurons, together with inhibited pyramdial neurons.

Consistent with this contention, a recent voltage-sensitive dye-based imaging study of guinea pig auditory cortex demon-strated that tonal stimulation produces regions of activation,flanked by regions of inhibition, and that the area of excitatoryactivation could be dramatically expanded by local applicationof GABA antagonists (Horikawa et al. 1996). Finally, althoughbinaural inhibitory mechanisms would not be expected to havea major influence on the distribution of unit responses tocontralaterally presented tonal stimuli, such stimuli might in-duce subthreshold activation of “predominantly binaural” cor-tical neurons (Kitzes et al. 1980).

In addition to the difference between optical and multiunitresponseswithin A1, failure to distinguish between supra- andsubthreshold activity might also account for the difference inthe degree of correspondence of optical and unit responsesbetweenA1 and visual cortex. In visual cortex, columns ofneurons with similar orientation preference are interconnectedby a lattice-like array of axonal projections (Gilbert and Wiesel1983, 1989; Rockland and Lund 1983). As a result, stimulationof a single orientation column gives rise to subthreshold exci-tatory and inhibitory synaptic inputs preferentially directed tosurrounding columns with similar orientation preference (Grin-vald et al. 1994; Weliky et al. 1995). Consequently, the spatialpattern of subthreshold electrophysiological activation inducedby partial visual field stimulation corresponds very closely tothe pattern of suprathreshold activation induced by full-fieldstimulation. Thus for full-field stimulation, the failure to dis-tinguish between sub- and suprathreshold activation has littleeffect on the correspondence of optical and unit responses. Inauditory cortex, by contrast, it is likely that the patches ofactivated and actively inhibited pyramidal neurons are spatiallyseparated. Thus visualization of subthreshold physiologicalactivity could have a far greater effect on results in auditorycortex than in visual cortex.

The hypothesis that the discrepancy between optical and unitresponses in cat auditory cortex results entirely from visual-ization of subthreshold activity, and/or inability to record spik-ing activity of interneurons, is inconsistent, however, with thefact that the majority of mismatches that we observed werefalse-negative errors. In either case, one expects the majority oferrors to be false positives. Although our data do not allow usto rule out a contribution of visualized subthreshold activity orinterneuronal spiking activity, it is unlikely that either is themajor cause of discrepancies between optical and multiunitresponses observed here.

Timing of auditory cortical neuronal responses

The characteristic temporal response properties of neuronsin auditory cortex of anesthetized cats might account for thedifference in results of optical imaging in auditory and othercortical areas. Most neurons in A1 respond to best-frequencytonal stimulation with one or two spikes synchronized to stim-ulus onset, followed by suppression of spiking activity for theduration of the stimulus (Fig. 7). In addition, because repeatedstimulation at short interstimulus intervals results in decreasedresponsiveness, it is necessary to use a stimulation duty cyclewith a low ratio (;1:10) of stimulus-on time to stimulus-offtime to obtain maximum responsiveness to individual stimuli(Hocherman and Gilat 1981; Phillips et al. 1989). As a conse-quence, using optimal stimulus parameters, suprathreshold


neuronal responses are only elicited during a very small frac-tion of the duration of a repetitive tone-pip sequence. Bycontrast, sustained neuronal responses lasting several secondsare elicited by optimal stimuli in visual cortex of barbiturateanesthetized animals (Hubel and Wiesel 1959). Because of thisdifference in response properties, discharge rates of optimallystimulated neurons in visual cortex, recorded throughout a 5-sstimulus presentation, may exceed those of auditory corticalneurons by more than a factor of 15 (Roe and Ts’o 1995;Sengpiel and Blakemore 1994). In barrel cortex, periodicvibrissal stimulation elicits sustained spike discharges, withtwo spike bursts per stimulus period (Peterson et al. 1998). The4- to 5-Hz stimulation frequencies, typically used in opticalimaging studies, would thus elicit discharge rates several timesthose typically observed in auditory cortex.

The gross differences in amount of suprathreshold neuronalresponses throughout the period of stimulation in differentcortical areas may be reflected in the corresponding opticalsignals. Specifically, the paucity of neuronal spiking responsesmay be insufficient to generate a reliable and robust opticalsignal at 540 nm in auditory cortex. This explanation is con-sistent with the unreliability of the optical signal, which wasonly detectable in 3/10 cats tested, and then only after exten-sive averaging. This hypothesis may, at first, appear inconsis-tent with the fact that optical imaging has been shown to revealboth suprathreshold and subthreshold activity (Das and Gilbert1995; Toth et al. 1996), as the paucity of spike discharges inA1 is at least partly due to an abundance of stimulus-evokedinhibitory processes some of which may last beyond the stim-ulus duration (Volkov and Galazjuk 1991, 1992). It should benoted, however, that optical signals accompanying suprath-reshold activity are larger than those accompanying subthresh-old activity and can be distinguished on this basis using ap-propriate analysis (Toth et al. 1996). Furthermore it is not clearhow inhibitory activity is reflected by intrinsic optical signals.Thus it remains entirely plausible that the failure of opticalsignals recorded at 540 nm to reveal physiologically relevantfunctional topographies in cat auditory cortex is due in largepart to the sparseness of neuronal spiking responses. If this isthe case, one potential approach to improving the quality ofoptical signals recorded from auditory cortex would be the useof an awake, behaving preparation. Previous studies have in-dicated that tones evoke a wider range of response types in A1of unanesthetized animals, including a greater prevalence ofsustained responses (Abeles and Goldstein 1972; Brugge andMerzenich 1973; Pfingst et al. 1977). One previous opticalimaging study of auditory cortex used an awake preparation(Hess and Scheich 1996), but in the absence of corroboratingphysiological data, there is no reason to suppose that the resultswere any different to those of the present study.

Vascular organization

Finally, we consider the possibility that the success of opti-cal imaging in visual and barrel cortex depends on specializa-tions of the vascular supply that may be absent in cat auditorycortex. The primary and secondary visual cortices of primatesare distinguished by a finely structured modular organizationthat is demarcated by the pattern of cytochrome oxidase stain-ing (Horton and Hubel 1981; Livingstone and Hubel 1984a;

Murphy et al. 1995; Wong-Riley 1979). Neurons within thedifferent cytochrome oxidase defined modules have differentresponse properties (Hubel and Livingstone 1987; Livingstoneand Hubel 1984a; Silverman et al. 1989; Ts’o and Gilbert1988). Furthermore the modularity of functional organizationis reflected in the distribution of metabolic activity (Humphreyand Hendrikson 1983; Tootell et al. 1983) as well as thepatterns of intrinsic and interareal cortico-cortical connections(Hubel and Livingstone 1987; Levitt et al. 1994; Livingstoneand Hubel 1984b, 1987; Rockland and Lund 1983; Yoshioka etal. 1996), and in the distribution of a number of neurochemicalmarkers including CAT-301 (Hendry et al. 1984) and parval-bumin (Blumcke et al. 1990). At least in macaque monkeys,the modular neuronal organization within visual cortex is alsoreflected by the distribution of small diameter blood vessels(Zheng et al. 1991). The density of capillaries and radialpenetrating vessels is greater in cytochrome oxidase-rich blobsand stripes than in the intervening cortical tissue. Similarly, inbarrel cortex each histologically defined barrel is delimited bya dense capillary plexus within the barrel core (Patel 1983).There is not, however, a one-to-one relationship between in-dividual barrels and vascular supply, as individual penetratingarterioles give rise to capillaries in several adjacent barrels(Woolsey et al. 1996). Nevertheless, in both visual and barrelcortex, there is evidence that the microvasculature is organizedinto functional units that bear a close spatial relationship to theanatomically and physiologically defined neuronal functionalmodules.

Because optical imaging relies primarily on blood-bornesignals, it is possible that the organization of vascular elementssets constraints on the spatial pattern of activation that can bevisualized with this technique. Consistent with this view, theareal extent of activation in barrel cortex produced by near-threshold deflection of a single vibrissa (Peterson et al. 1998)corresponds very well with the areal extent of the minimalvascular functional unit, consisting of the capillaries suppliedby a single penetrating arteriole (Woolsey et al. 1996). If anequivalent complementarity of neuronal and vascular func-tional units does not exist in auditory cortex, the local bloodvolume changes, presumably the major source of optical sig-nals recorded at 540 nm, might be spatially decoupled from thepattern of electrophysiological activity. It is difficult to furtherevaluate this conjecture at present, however, because it is notknown whether A1 exhibits modular neuronal organization,comparable to that in visual cortex, and because the micro-scopic organization of blood supply to A1 has not been de-scribed.

We thank S. Kaiser, M. Ward, and the staff of Optical Imaging, withoutwhose technical expertise these experiments would not have been possible. Wealso thank D. Vaney for contributing the vibration isolation table, D. Ts’O foruse of the SumAnal program, and K. Keller for help with image analysis.

This work was supported by National Health and Medical Research Councilof Australia Project Grants 971147 and 96/NHMRC9002G to M. W. Spitzerand J. D. Pettigrew, respectively, and by NHMRC Project Fellowship Grant961226 to M. B. Calford.

Present addresses: M. B. Calford, Faculty of Medicine and Health Sciences,The University of Newcastle, Callaghan, NSW 2308, Australia; J. C. Clarey,Dept. of Otolaryngology, The University of Melbourne, Melbourne, VIC 3010,Australia; A. W. Roe, Dept. of Neurobiology, Yale University School ofMedicine, New Haven, CT 06520.


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