Functional neuroimaging of odor imagery

Functional neuroimaging of odor imagery NeuroImage 24 (2005) 791 – 801 Functional neuroimaging of odor imagery J. Djordjevic,* R.J. Zatorre, M. Petrides, J.A. ...

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Functional neuroimaging of odor imagery J. Djordjevic,* R.J. Zatorre, M. Petrides, J.A. Boyle, and M. Jones-Gotman Montreal Neurological Institute, McGill University, Montreal, Que´bec, Canada Received 24 May 2004; revised 11 September 2004; accepted 22 September 2004 Available online 21 November 2004 We used positron emission tomography (PET) to investigate brain regions associated with odor imagery. Changes in regional cerebral blood flow (CBF) during odor imagery were compared with changes during nonspecific expectation of olfactory stimuli and with those during odor perception. Sixty-seven healthy volunteers were screened for their odor imagery (with a paradigm developed in a previous study), and 12 of them, assessed to be bgood odor imagers,Q participated in the neuroimaging part of the study. Imagination of odors was associated with increased activation in several olfactory regions in the brain: the left primary olfactory cortical (POC) region including piriform cortex, the left secondary olfactory cortex or posterior orbitofrontal cortex (OFC), and the rostral insula bilaterally. Furthermore, blood flow in two regions within the right orbitofrontal cortex correlated significantly with the behavioral measure of odor imagery during scanning. Overall, the findings indicated that neural networks engaged during odor perception and imagery overlap partially. D 2004 Elsevier Inc. All rights reserved. Keywords: Positron emission tomography; Olfaction; Odor imagery

Introduction Daydreaming is a common mental activity, and it often involves generation of mental images in several different sensory modalities. We seem to be very good at imagining sounds, scenes, faces, and movements of our bodies as well as of objects in space, but it remains unclear how good we are at imagining odors. Although olfactory imagery is more elusive in comparison to imagery in other sensory modalities, there has been some experimental evidence supporting its existence (Algom and Cain, 1991; Algom et al., 1993; Bensafi et al., 2003; Carrasco and Ridout, 1993; Djordjevic et al., 2004a,b; Gilbert et al., 1998; Levy et al., 1999; Lyman and McDaniel, 1990).

* Corresponding author. Montreal Neurological Institute, McGill University, 3801 University Street, Montreal, Que´bec, Canada H3A 2B4. Fax: +1 514 398 1338. E-mail address: [email protected] (J. Djordjevic). Available online on ScienceDirect ( 1053-8119/$ - see front matter D 2004 Elsevier Inc. All rights reserved. doi:10.1016/j.neuroimage.2004.09.035

Brain activity during mental imagery has been studied in the visual, auditory, tactile, and motor modalities. In general, brain regions associated with mental imagery have been found to be a subset of regions associated with perception in the same sensory modality (Halpern, 2001; Kosslyn et al., 2001a; Mellet et al., 1998). If this applies to the sense of smell, one would expect participation of the piriform and orbitofrontal cortex (OFC), insula, and amygdala, given that these regions participate in olfactory perception (Sobel et al., 2003; Zald and Pardo, 2000; Zatorre and Jones-Gotman, 2000). One research group has studied neural correlates of odor imagery (Henkin and Levy, 2002; Levy et al., 1999), but owing to several limitations of these studies, associated with experimental design, lack of anatomical detail, and, in particular, the failure to provide any evidence that participants imagined odors as requested during scanning, these findings remain inconclusive. In the present study, we sought to provide behavioral evidence of odor imagery during scanning, in order to validate the claim that participants were imagining odors as requested. The paradigm was based on an objective behavioral approach to measuring odor imagery developed in a previous study (Djordjevic et al., 2004a). In that study, we showed that people are better at detecting weak odors while simultaneously imagining the odor being detected (matched condition) than while imagining other odors (mismatched condition). This effect was specific for odor imagery; visual imagery did not influence odor detection in any way. In our previous studies (Djordjevic et al., 2004a,b), we also demonstrated large individual variation in odor imagery ability: only approximately one third of an unselected sample of subjects could be qualified as bhigh odor imagers.Q For the present neuroimaging study, we therefore screened potential participants and selected those who showed a good ability to imagine odors. Our main aim was to examine the brain regions showing changes in activity during odor imagery. We used the subtraction method to reveal areas of increased activation during odor imagery and odor perception, and a conjunction analysis to uncover regions common to imaginal and perceptual olfactory processing. We also regressed the behavioral measure of odor imagery during scanning against regional cerebral blood flow (rCBF) measures during odor imagery to determine which brain regions show changes in rCBF as a function of odor imagery. Importantly, we provided


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independent measurement of both the process of experimental interest (odor imagery) and the main possible confound (breathing); we presented evidence that the participants imagined odors as requested during scanning and that differences in brain activity were not induced by differences in breathing/sniffing patterns between conditions.

Method This investigation consisted of two main parts: behavioral screening and neuroimaging. The behavioral screening comprised one testing session in which participants completed a series of odor detection tasks to establish their odor imagery ability. Among those classified as good odor imagers, 12 proceeded to the neuroimaging part of the study, which consisted of a positron emission tomography (PET) experiment and an anatomical magnetic resonance imaging (MRI) scan. Both parts of the present study were based on the procedure reported in Djordjevic et al. (2004a), with two modifications implemented in order to adjust the paradigm to the PET scanning conditions. These modifications were the format of detection tasks (a simple yes–no detection task replaced forced choice during simultaneous imagery and detection trials) and the method for determining detection thresholds (ascending method of limits replaced a staircase procedure). Subjects Sixty-seven healthy volunteers (32 women and 35 men, mean age = 20.9 years, range 18–32) completed the odor imagery screening session. All subjects reported normal ability to smell. Exclusion criteria were respiratory infections, allergies leading to nasal congestion, history of neurological or psychiatric disease, or other conditions associated with impaired sense of smell. Twelve of these participants were selected for the neuroimaging part of the study based on having the best odor imagery ability (highest matched–mismatched difference). This group consisted of six women and six men (mean age = 21.0 years, range 19–25). Eleven participants were right-handed, and one had mixed handedness. The single mixed-handed subject had no family history of left- or mixed-handedness and showed a normal right-ear superiority on the Wexler-Halwes dichotic fused words test (Wexler and Halwes, 1983; Zatorre, 1989), suggesting that this participant’s cerebral dominance for language was most likely typical, that is, in the left hemisphere. Stimuli We used four odorants: phenyl ethyl alcohol (PEA) which smells like a rose, Siberian pine needle oil which smells like pine, and scents of lemon and strawberry. Double distilled water was used as the odorless (blank) stimulus and as the diluent for different concentrations in the threshold series (range from 8.5 to 1.0 log steps, differing by half-log steps). Because PEA and pine needle oil are only slightly soluble in water, the first two steps of the concentration series were diluted in ethyl alcohol, and all the following concentrations were obtained by diluting these in double distilled water. All stimuli were presented birhinally, in 60-ml amber bottles containing 9 ml of either the odorant or the diluent. Two odorants were used for each participant during odor imagery

and detection tasks (rose and lemon, or strawberry and pine), and odor selection was counterbalanced across subjects. During scanning, either weak or strong odorants were used, depending on the condition. During the Odor Imagery (OI) and Odor Detection (OD) conditions, weak perithreshold odorants were used, that is, concentrations were individually established for each subject to be at her/his detection threshold level. During the two Odor Perception conditions, strong suprathreshold odorants (10% dilutions) were presented. Double-distilled water was presented as a blank (odorless) stimulus throughout the Baseline condition and, occasionally, during all other conditions. Procedure Behavioral screening All participants underwent a behavioral session in which they were screened for their odor imagery ability. The procedure consisted of three parts: odor detection threshold, familiarization with the odorants and odor imagery practice, and odor detection tasks with simultaneous odor imagery. First, odor detection thresholds were established for two odorants (lemon/rose or pine/strawberry) using an ascending method of limits. In each trial, one odorant and one blank stimulus were presented one after the other; their order was randomized across trials, and the task was to indicate which one smelled stronger (two-alternative forced choice). The concentration was increased until participants made five consecutive correct responses: this was taken as the detection threshold level. Second, participants were familiarized with two odorants that they would be requested to imagine in the third part. Familiarization with odors consisted of two steps: odor ratings and practice of odor imagery. The first step involved rating suprathreshold concentrations (10% dilutions) of two odorants on four properties: intensity, familiarity, pleasantness, and typicality (for the latter rating, participants were asked to rate how typical the presented odor was of what they know as the named smell). Visual analog scales were used to make these ratings: participants made a mark on a 100-mm line, with which they expressed their subjective experience of the presented odors for each property. In the second step, participants were told that they would be asked to imagine these two smells in the last part of the session and were asked to practice imagining them. The odorants were named, presented, and removed, and participants were asked to imagine these smells in their bmind’s noses.Q This was repeated at least three times with each odorant, or until participants asserted that they were able to imagine each smell. The third part consisted of odor detection tasks associated with odor imagery. Immediately before each odor detection trial, participants were instructed to imagine one of the two odors (one half of trials each). After indicating that they had imagined the smell, they were given a yes–no detection task: a stimulus was presented and the task was to indicate whether they smelled an odor or not. Each participant completed 108 odor detection trials. Three different types of trials were administered. On 36 trials, the participants were presented with the same odor as the one they were asked to imagine (matched condition, half with each odorant); on 36 trials, they were given a different odor from the one they were asked to imagine (mismatched condition), and on 36 trials, a blank, odorless stimulus was presented. The difference in detection accuracy between matched and mismatched trials was taken as a measure of odor imagery. The two odorants were always

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presented at each individual’s threshold level, and the subjects were never informed as to which stimuli were being presented. Neuroimaging Protocol during scanning. The main experimental condition in this study was Odor Imagery with Odor Detection, which will be referred to as Odor Imagery (OI) in the rest of the article, and the control condition was Odor Detection alone, which will be referred to as Odor Detection (OD). The order and timing of events during these conditions are shown in Fig. 1. On each trial in the OI condition, the prerecorded name of the odor to be imagined was played through a speaker, whereas the instruction bGet readyQ was played in the OD condition, and both lasted 1 s. This was followed by a silent period of 5 s during which participants imagined smells in the OI or simply waited for the stimulus presentation in the OD. In both conditions, the silent period was followed by stimulus presentation, which was announced by a sound (beep, 2 s long), and the task was to respond with a choice on a two-button mouse whether an odorant was smelled or not (additional 3 s was given for response). Therefore, each trial lasted 11 s, and each condition consisted of nine trials, for a total duration of 99 s. Task presentation started before the scanning time and continued well after it, resulting in 5.45 trials over each 60-s scan. During each OI condition, three matched and three mismatched trials (adding up to six trials with presented odors) were given together with three blank trials, whereas during the OD condition, six trials with odors and three with blanks were given. The different types of trials (matched, mismatched, and blank trials in OI conditions, and odor and blank trials in OD conditions) were presented in the same pseudorandomized order to all participants, with the restriction that the same odor name (in OI) and the same odor (in OI and OD) would not be presented more than twice consecutively. The odor names and odors presented in the OI conditions and the odors in OD conditions differed among participants and were given according to one of four possible combinations/orders, which included pine–strawberry, strawberry– pine, lemon–rose, and rose–lemon. These were counterbalanced


across the 12 subjects. Another crucial aspect of the design was that, for each subject, the presented olfactory stimuli were identical in the OI and OD conditions; that is, the same two odors at identical concentrations (the predetermined threshold level) were presented in both conditions to each participant. Furthermore, the two odors and blanks were given in exactly the same order in the OI and OD. In this way, the sensory (auditory and olfactory) input, the motor output (key press), and the timing of events were equivalent across the OI and OD conditions. The main critical difference between them was what occurred during the silent period, that is, active imagination of odorants in the OI condition versus the passive expectation of odorant presentation in the OD condition. Thus, subtraction of Odor Detection from Odor Imagery (OI minus OD) will reveal changes in rCBF specific to odor imagery. Moreover, detection accuracy provided a behavioral measure of olfactory imagery during scanning (the difference between matched and mismatched detection during odor imagery). In addition, participants completed two conditions in which strong, suprathreshold stimuli were presented: Odor Perception: four odors (OP4), and Odor Perception: one odor (OP1), as well as a Baseline (B) condition during which bottles with water (that is, odorless stimuli) were presented. During OP4 and OP1, participants were instructed to indicate with a mouse press whether they smelled something or not; in both conditions, odorous stimuli were presented on six and blanks on three trials. In the B condition, subjects were informed that odorless bottles would be presented, and they were requested to press the left or right mouse key randomly after each sound signal indicating stimulus presentation. For the purposes of this study, we were interested in determining regions showing increased activation during the perception of presented odors and comparing them with regions showing increased activation during imagery of odors. Eventual differences between perceiving one versus four odors were of no interest for this comparison, and therefore, we collapsed together the regions of activation obtained during OP1 and OP4, both compared with the B condition, resulting in the Odor Perception minus Baseline (OP minus B) comparison. Each condition was repeated twice for a total of 10 scans. During all conditions, participants kept their eyes closed, and their

Fig. 1. Schematic representation of protocol during scanning. One trial (11 s) across five conditions is shown; each trial was presented nine times in each condition. Differences between conditions contrasted in the PET analyses are printed in bold. OI indicates Odor Imagery condition; OD, Odor Detection condition; OP4, Odor Perception: four-odor condition; OP1, Odor Perception: one-odor condition; B, Baseline condition.


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behavioral responses (yes–no mouse key presses) were recorded. Besides accuracy of detection, breathing of each subject was monitored during all conditions, since sniffing without any presented odorants has been shown to induce activation in olfactory regions of the brain (Sobel et al., 1998). Image acquisition and analysis. PET scans were obtained using a CTI Siemens Exact ECAT HR+ scanner operating in a threedimensional mode. The distribution of rCBF was measured during each 60-s scan using the 15O-labeled water bolus method. MRI scans (1-mm slices) were obtained with a 1.5-T Phillips MRI scanner. Each participant’s PET and MRI scans were coregistered and transformed into the Montreal Neurological Institute standardized proportional stereotaxic space that is based on the Talairach and Tournoux’s (1988) atlas. For all PET analyses (except conjunction), we used Dot, an in-house (Montreal Neurological Institute) software designed for analysis of PET data. PET images were blurred using a 14-mm Hanning filter and normalized for differences in global blood flow. PET data were averaged across subjects for each scanning condition; subtractions of interest yielded mean change image volumes and were converted to t statistic maps. In calculation of t statistics for each voxel, a standard deviation pooled across all voxels was used, yielding a very high (practically infinite) value of degrees of freedom (Worsley et al., 1996). To localize the observed peaks, these statistical maps were superimposed on the average MRI image of the 12 participants. For the two subtractions of interest (OI minus OD, and OP minus B), the statistical significance of rCBF changes was assessed using three-dimensional Gaussian random-field theory (Worsley et al., 1996). Significant changes were established using two threshold values: for the exploratory search of the gray matter volume of approximately 500 cc (182 resolution elements), the threshold was set at t = 3.52, corresponding to an uncorrected probability of P b 0.0002 and yielding a false-positive expectancy rate of 0.60. For the directed search within regions previously activated by odor perception (piriform cortex, posterior orbitofrontal cortex, and insula), the threshold was lowered to t = 3.00. We also examined what regions were activated during both odor perception and odor imagery by conducting a conjunction analysis. In functional neuroimaging, conjunction refers to the occurrence of an activity change at the same location in two or more independent three-dimensional brain images (Worsley and Friston, 2000). The question of interest in the present study was to find common regional activations during odor perception and odor imagery. We therefore conducted a conjunction of two subtractions: OI minus OD, and OP minus B. Conjunction analysis was performed using a command from the fMRIstat program (Worsley et al., 2002), a set of Matlab tools designed to analyze functional neuroimaging data including PET. In this application, conjunction analysis yields minimum activations that are consistently found in all included images (in our case, two subtraction images), whereas subtraction analysis relies on the average (Friston et al., 1999). The probability that two t statistics at the same locations coming from two different subtractions (which is the case with the conjunction analysis) exceed a threshold is smaller than the probability that one t statistic does (subtraction analysis). Therefore, the threshold for the conjunction analysis was set at t = 3.00, P b 0.05 (for the search region of 500 cc, df = 48, conjunction of two subtractions) and lowered to t = 2.50 for the predicted regions of common activation in the piriform, insular, and posterior orbitofrontal cortex.

Finally, we conducted a regression analysis in which the behavioral measure of odor imagery (difference in detection accuracy between matched and mismatched trials) was entered as a regressor against cerebral blood flow. The sum of this measure over the two odor imagery scans of each participant was taken as an index of odor imagery efficiency (OIE); although we selected good odor imagers to participate in this study, they showed some variability in odor imagery performance during scanning. We were therefore able to determine whether this behavioral measure predicts changes in rCBF during odor imagery (i.e., in the OI minus OD subtraction) in any of the regions relevant for olfaction. Respiration measurement. Subjects were instructed to breathe regularly across all conditions and especially to avoid taking excessively deep breaths regardless of the specific task and/or stimulus intensity; they were informed that stimuli would be either weak or strong odorants or blanks (depending on condition), but that they would be presented for a sufficient time so that they could be sampled while breathing normally. The intention of such instruction was to reduce possible differences in breathing patterns among conditions that were directly contrasted in PET analyses. In addition to the instruction to keep breathing constant, we measured breathing patterns during scanning, using a polygraph instrumentation system (F1000), manufactured by Focused Technology, Ridgecrest, CA. Respiratory movements (expansion and contraction, reflecting inhalation and exhalation) were recorded with two stretchable elastic belts, attached around the chest and the abdomen, which were connected to transducers. Mean amplitude and frequency of quasi-sinusoid waves were extracted for each subject for all conditions and expressed as the proportion of change in depth (amplitude) and rate (frequency) in relation to Baseline. This normalization to Baseline was conducted in order to make comparisons among subjects and across conditions.

Results Behavioral screening We first analyzed the effect of odor imagery and its content (that is, imagery of specific odor qualities) on odor detection in all 67 participants. A paired-samples t test revealed a significant difference between the matched and mismatched condition, t(66) = 5.43, P b 0.0001: odor detection was better during matched than during mismatched imagery (Fig. 2A), and the mean difference between them was 9.8% (36 matched versus 36 mismatched trials). Mean percentage of false-alarm responses (i.e., byesQ responses on the blank trials) was 27.6% (out of 36 trials). The matched–mismatched effect appears enhanced (i.e., mean difference was 27.3%) in the group of participants selected for neuroimaging, t(11) = 7.92, P b 0.0001, as shown in Fig. 2B. Mean percentage of false-alarm responses in this group during screening was 23.1%. Neuroimaging Behavioral results Detection. During all PET conditions, the participants’ detection responses (yes–no) were recorded. Detection responses for our main experimental comparison, Odor Imagery minus Odor

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during the OI conditions were also at the threshold level, since exactly the same odors at the same concentrations were used as in the OD condition; deviation of performance on matched and mismatched trials from 70% reflects an effect of imagery on detection. Breathing. Overall, results obtained from the chest belt were comparable to those obtained from the abdominal belt. However, due to more artifacts associated with the chest measures, we shall restrict our reports of breathing to abdominal measurements. Breathing results did not reveal significant differences between the experimental (OI) and control (OD) conditions, as measured with the mean abdominal breathing amplitude, t(11) = 1.07, P = 0.31, or with the mean breathing frequency, t(11) = 1.05, P = 0.32. In addition, breathing during Baseline (B) was compared with the two odor perception conditions (OP4 and OP1) collapsed together, as this was one of the contrasts in the PET analyses. A t test revealed no significant difference between Baseline and Odor Perception in the abdominal breathing amplitude, t(11) = 1.46, P = 0.17, nor in breathing frequency t(11) = 0.83, P = 0.43. PET results

Fig. 2. Results from behavioral screening. Detection of perithreshold odorants is expressed as a percentage of correct byesQ responses or hits, and error bars show standard errors. Fifty percent is chance performance. (A) Odor detection as a function of matched versus mismatched odor images in all participants (N = 67). (B) Odor detection as a function of matched versus mismatched odor images in participants selected for scanning (N = 12).

Detection, are presented in Fig. 3. Results over repeated scans were added together and expressed as percentages: three matched and three mismatched trials from each of the two OI scans were added together for a total of six matched and six mismatched trials. For the OD condition, six trials in which odors were presented were added up for both scans for a total of 12 trials. The pattern of detection responses during scanning was strikingly similar to the one obtained during screening: detection of weak odorants was significantly different as a function of whether participants imagined a same (matched) or a different (mismatched) odorant immediately preceding the detection task, t(11) = 4.47, P b 0.01, yielding a mean difference of 29.2%. The mean percentage of false-alarm responses during OI was 31.9% and 36.1% during OD conditions (in both cases, out of six blank trials, three from each scan), and there were no differences between these means, t(11) = 0.51, P = 0.62. Performance during the Odor Detection condition was significantly different from chance, t(11) = 4.90, P b 0.0001, and it approximated 70% accuracy, indicating that weak odorants presented during OD were given at the level of detection threshold. Furthermore, this finding also indicates that stimuli presented

Subtractions. In order to examine what regions showed increased activity due to odor imagery, we conducted the subtraction Odor Imagery minus Odor Detection (OI–OD). This subtraction revealed increased rCBF in some areas traditionally considered to be olfactory regions: left primary olfactory cortex (POC) including piriform cortex, left periinsular region (one of two peaks was in the rostral insula), and a subthreshold increase in the left posterior orbitofrontal cortex and the right rostral insula (Table 1, Fig. 4). In addition, increased rCBF was observed in some nonolfactory regions, such as the left parietal and left frontal (rostral supplementary motor area or pre-SMA and dorsolateral) cortex (Table 1, Fig. 5). In order to examine regions of activation during odor perception, the Baseline condition was subtracted from the two

Fig. 3. Detection of weak odors during scanning: Odor Imagery (OI) and Odor Detection (OD). Detection is expressed as a percentage of correct byesQ responses or hits, and error bars show standard errors.


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Table 1 Significant peaks of increased rCBF in the subtraction involving odor imagery (OI minus OD) Area




t value

Primary olfactory cortical region L piriform cortex and surrounding olfactory structures





Secondary olfactory cortical region L posterior orbitofrontal cortex (OFC) (area 13)*





46 36 29

1 24 13

5 2 16

3.55 3.38 2.98













Periinsular region L opercular cortex L rostral insula R rostral insula* Frontal cortex L medial frontal gyrus: presupplementary motor area (pre-SMA) L mid-dorsolateral prefrontal cortex (area 9/46) Parietal cortex L parietal cortex around the intraparietal sulcus

L, left; R, right. x, y, and z denote coordinates of functional activity changes in the right (positive) versus left (negative) direction, anterior (positive) versus posterior (negative) direction, and superior (positive) versus inferior (negative) direction, respectively, expressed as distance in millimeters from the anterior commissure. * Denotes peaks that just missed significance.

conditions collapsed together in which strong odorants were presented (OP1 and OP4), Table 2. This subtraction revealed increased rCBF in several olfactory areas: the primary olfactory and insular cortex, bilaterally, and in the right orbitofrontal cortex (Fig. 6). In addition, other cortical areas including right frontal, left occipital, and bilateral parietal cortex showed rCBF changes in this subtraction (Table 2). Conjunction. A conjunction analysis was conducted in order to investigate regions of activation common to odor imagery (OI minus OD) and odor perception (OP minus B). Peaks detected in the conjunction analysis are listed in Table 3, together with the corresponding peaks observed in the two subtraction analyses.

Fig. 5. Areas of rCBF increase in nonolfactory regions demonstrated by the Odor Imagery minus Odor Detection subtraction: left presupplementary motor area (pre-SMA) is shown on the sagittal section at x = 1, and left parietal and dorsolateral prefrontal cortices activations are shown on the sagittal section at x = 38.

The conjunction analysis revealed increased activity in the left and right rostral insulae during both odor perception and odor imagery (Fig. 7). In addition, two peaks of increased activity within the left POC were also found, although their t values missed the accepted threshold level for the directed search (Table 3 and Fig. 7). Their close proximity to each other (5-mm vector distance) suggests that they belong to the same overlapping region. Regression. In the regression analysis of odor imagery efficiency against the blood flow in the OI minus OD subtraction, we identified two regions in the right orbitofrontal cortex in which increases in activation were predicted by performance on the odor imagery task (Fig. 8). In order to illustrate this relationship, we also show correlations between the Odor Imagery Efficiency index (difference between matched and mismatched trials) and blood flow changes due to odor imagery in anterior (r = 0.70, P b 0.05) and posterior (r = 0.58, P b 0.05) orbitofrontal cortex on the right side (Fig. 8). It could be argued that this correlation between OIE and rCBF might have been related to a better overall detection in those who had better OIE and that therefore the observed rCBF increases in the right orbitofrontal cortex were associated with better odor detection rather than better odor imagery. In order to examine this possibility, we calculated the correlation between the OIE and odor detection efficiency (i.e., the total number of detected odors regardless of whether they were matched or mismatched). This correlation was not significant (r = 0.37, P = 0.23). Interestingly, the peak in the posterior orbitofrontal cortex seen in the regression analysis was in approximately the same location as the peak in the right orbitofrontal cortex associated with odor perception (in the OP minus B subtraction): the vector

Fig. 4. Increases of rCBF are shown as statistical parametric maps (t statistic as represented by the color scale) superimposed on anatomical MRI averaged over study participants. Blood flow changes in the olfactory regions observed in the Odor Imagery minus Odor Detection subtraction are shown. Left primary olfactory cortex including piriform cortex and left secondary olfactory cortex (posterior orbitofrontal gyrus) is shown on the horizontal sections at z = 13 and at z = 11, and rostral insula at z = 2 (left) and z = 16 (right).

J. Djordjevic et al. / NeuroImage 24 (2005) 791–801 Table 2 Significant peaks of increased rCBF in the subtraction involving odor perception (OP minus B) Area












Secondary olfactory cortical region R posterior orbitofrontal 23 cortex (OFC) (area 13)




31 28 32

15 17 6

6 9 9

3.61 3.53 3.57

9 12

4 11

45 65

4.03 3.95





Occipital cortex L striate cortex





Parietal cortex R rostral parietal cortex L rostral parietal cortex

24 25

38 50

50 51

3.81 3.60

Cerebellum L cerebellum





5 8 7

19 1 19

12 9 6

4.29 3.61 3.53

Primary olfactory cortical region R piriform cortex and surrounding olfactory structures L piriform cortex and surrounding olfactory structures

Insula L rostral insula R rostral insula R middle insula Frontal cortex R cingulate gyrus (area 24c) R medial frontal cortex: supplementary motor area SMA (area 6) R mid-dorsolateral prefrontal cortex (area 46)

Subcortical structures L substantia nigra region L hypothalamic region R thalamus, dorsomedial nucleus

t value


subthreshold increase in the left primary olfactory cortex. Finally, a regression analysis revealed a significant covariation of blood flow with odor imagery efficiency in two regions of the right orbitofrontal cortex. Behavioral correlates of odor imagery Although the experimental paradigm from our previous study was modified, the behavioral results reported here correspond strikingly to what we found before (Djordjevic et al., 2004a). The effect of odor imagery on odor detection was content-specific: odor detection was better when people imagined the same odor as the one they were detecting than when they imagined a different odor. In both studies, the difference between odor detection with matched and mismatched odor imagery approximated 10% in a group of unselected participants. We selected 12 participants with a large difference between matched and mismatched trials to proceed to neuroimaging, and their responses during scanning provided a further replication (with a smaller number of trials) of the results observed during screening. We previously showed that the imagery effect on detection is most consistent with an interference mechanism. We note that the results during scanning from the present study seem to suggest that the effect may go in both directions (i.e., facilitation and interference) as compared with detection with no imagery. However, the latter result was obtained with a small number of trials (six matched and six mismatched, compared with 12 odor detection trials) during scanning. We therefore consider our previous findings on interference to be more stable given that they were observed with a larger number of trials and in two separate studies using different experimental manipulations (Djordjevic et al., 2004a,b). Regardless of the direction of the effect, the behavioral findings in the present study are consistent with the notion that odor imagery is a sensory-specific type of mental imagery. Neural correlates of odor imagery In the subtraction revealing regional activations specific to odor imagery (OI minus OD), increased blood flow was demonstrated in several cortical regions. Importantly, increased activation was

L, left; R, right. x, y, and z denote coordinates of functional activity as defined in the brain atlas of Talairach and Tournoux (1988).

distance between the two peaks revealed by these two analyses was 9.8 mm.

Discussion We used PET neuroimaging and the subtraction method to examine cerebral blood flow changes associated with odor imagery and odor perception. Increased activity in specific olfactory regions—the left primary olfactory cortex, the left secondary olfactory cortex, and the rostral insula bilaterally—were associated with odor imagery. Changes in blood flow associated with odor perception were found in the primary olfactory cortex bilaterally, the right secondary olfactory cortex, and the rostral insula bilaterally. We followed this with a conjunction analysis that revealed regions of common activation between odor imagery and odor perception: these were the rostral insula bilaterally, and a

Fig. 6. Areas of rCBF increases in olfactory regions demonstrated by the Odor Perception minus Baseline subtraction. Areas of rCBF increase in the left and right primary olfactory cortex including piriform cortex and the right secondary olfactory cortex (posterior orbitofrontal gyrus) are shown on the horizontal section at z = 14; left and right rostral insula activations are shown on the horizontal section at z = 8.


J. Djordjevic et al. / NeuroImage 24 (2005) 791–801

Table 3 Location of common peaks of increased rCBF revealed by the conjunction analysis and corresponding peaks revealed by the two subtraction analyses Area

Conjunction analysis

Odor Perception minus Baseline




28 33

15 20

15 4

Primary olfactory cortical region L piriform cortex and 24 surrounding structures 24

3 7

14 17

Anterior insula R rostral insula L rostral insula



Odor Imagery minus Odor Detection








2.87 2.66

28 31

17 15

9 6

3.53 3.61

29 36

13 24

16 2

2.98 3.38

2.30* 2.26*









L, left; R, right. x, y, and z denote coordinates of functional activity as defined in the brain atlas of Talairach and Tournoux (1988). * Denotes peaks that just missed significance.

found in the following regions essential for olfaction: the left primary and secondary olfactory cortex, and the rostral insula bilaterally. This finding that olfactory cortical regions participate in the generation of olfactory mental images is a further confirmation that odor imagery is a sensory-specific type of imagery. Primary olfactory cortex The activation observed in the left primary olfactory cortical (POC) region included only its rostral or frontal part and did not extend to its medial temporal portion. The peak of this activation was in the ventral part of the basal forebrain region that includes the anterior olfactory nucleus, the olfactory tubercle, and extends to the frontal piriform cortex. However, structures constituting the POC are small in extent and are difficult to distinguish with current neuroimaging resolution. Understanding the role of the primary olfactory cortex and, more specifically, of the piriform cortex in olfaction continues to be a challenge. A series of investigations has made substantial progress in demonstrating that the role of the piriform cortex is not restricted to sensory but includes contribution to cognitive (Dade et al., 2002; Gottfried et al., 2002a) and emotional processing of odorants (Gottfried et al., 2002b; Rolls et al., 2003). Furthermore, piriform cortex seems to be involved in sniffing without smelling (Sobel et al., 1998), as well as in smelling without sniffing (Cerf-Ducastel and Murphy, 2001). Importantly, changes in the POC associated with odor imagery in the present study cannot be explained by deeper or faster breathing during odor imagery, as breathing patterns recorded during scanning showed no difference between the experimental (Odor Imagery) and the control (Odor Detection) conditions. Explicit instruction to

breathe consistently across all conditions regardless of presented stimuli or requested task probably removed some differences among conditions that might have been noted had our subjects not been instructed to keep their breathing equal and regular at all times during scanning. Notably, the involvement of primary sensory or motor cortex in corresponding imagery domains has been a major controversy in the field of mental imagery. Although many studies have shown that mental imagery is possible without the involvement of the primary sensory cortical areas (Mellet et al., 1996), activation of these regions has been elicited in all explored types of imagery including visual (for a review, see Thompson and Kosslyn, 2000), tactile (Yoo et al., 2003), and motor (Kosslyn et al., 2001b; Leonardo et al., 1995) imagery. Only auditory imagery is an exception (Halpern and Zatorre, 1999; Halpern et al., 2004; Zatorre et al., 1996). Taken together, findings from different mental imagery modalities seem to suggest that involvement of the primary sensory or motor cortical areas may not be necessary for generation of mental images, but that these brain regions can and do participate in certain mental imagery tasks. Whether there is a difference between mental images generated with and without primary cortical regions remains unknown, but this continues to be a topic of heated debate. Thus, the role of the POC in olfactory imagery remains to be defined, but the present findings are consistent with involvement of primary sensory and motor areas in other modalities during mental imagery. Secondary olfactory cortex Another peak of increased activation in association with odor imagery was located in the left orbitofrontal cortex (OFC). A

Fig. 7. Regions of common activation in two subtractions: Odor Imagery minus Odor Detection and Odor Perception minus Baseline, demonstrated by the conjunction analysis. Areas of rCBF increase in the left and right rostral insulae are shown on the horizontal section at z = 4 and 15, respectively, and CBF changes in the left primary olfactory cortex including piriform cortex are shown on the horizontal section at z = 14.

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Fig. 8. The two regions within the right orbitofrontal cortex (OFC) that showed significant covariation between CBF changes in the Odor Imagery minus Odor Detection subtraction and the behavioral measure of odor imagery: anterior (x = 24, y = 54, z = 15, t = 3.5) and posterior (x = 23, y = 32, z = 21, t = 3.47) OFC peaks are shown on the horizontal section at z = 18. Correlation plots illustrate the relationship between Odor Imagery Efficiency (OIE) and rCBF at these two locations.

probabilistic atlas of the human orbitofrontal sulci and gyri (Chiavaras et al., 2001) indicates that the present peak was located in the posterior orbitofrontal gyrus, behind the transverse orbital sulcus, and is therefore falling in area 13 according to the nomenclature of Petrides and Pandya (1994). This activation had a medial location within area 13 (area 13a), which is a region often thought to be the secondary olfactory cortex in humans. An overwhelming majority of studies has reported an activation of secondary or associative cortical regions to be involved in mental imagery, and our findings clearly show that this is also the case with imagery for scents. Furthermore, we found that our behavioral measure of odor imagery (i.e., difference in detection between matched and mismatched trials) predicted blood flow changes in two regions of the right orbitofrontal cortex, one within the right anterior and the other within the right posterior orbitofrontal cortex. Interestingly, the location of the latter peak (Fig. 8) corresponded to the location of the right OFC peak observed in association with the perception of physically presented odors (Fig. 6). The fact that this perceptual area is activated as a function of the efficiency of an individual’s odor imagery is in keeping with the idea of sensory quality associated with olfactory imagery. The degree of activation within the right orbitofrontal cortex during odor imagery may play a role in the experienced vividness or brealnessQ of an olfactory image, since this region participates in the perception of physically presented odors, as shown in this and many other (albeit not all) studies of olfactory processing (for a review, see Zald and Pardo, 2000; Zatorre and Jones-Gotman, 2000). We excluded an alternative explanation that this correlation between odor imagery efficiency and blood flow in the orbitofrontal cortex might have been due to better odor perception/detection, by showing that there was no correlation between odor imagery and odor detection efficiency. Rather, this positive correlation suggests that more successful odor imagery occurs when the brain treats odor images more like odor percepts. In summary, activity in the left OFC was observed when subjects, selected as good odor imagers, imagined smells and it was not related to efficiency of odor imagery; in contrast, activity in the right anterior and posterior OFC increased with better odor imagery efficiency. Our findings therefore suggest a somewhat different role of the left versus right secondary olfactory cortex in imaginal processing of odors: whereas the left OFC activity may be related to an effort to imagine an odor, the right OFC may be related to the successful outcome of this effort.

Insula Interestingly, we also observed increases of blood flow due to odor imagery in the rostral insula bilaterally, although stronger on the left side. It is known that several parts of this anatomically and functionally heterogeneous cortical region receive projections from the POC in rodents (Clugnet and Price, 1987; Price, 1987) and primates (Carmichael et al., 1994). In humans, involvement of the insula in olfactory processing has been demonstrated in numerous brain imaging studies, but activations have been reported across all parts of the insula (Sobel et al., 2003; Zald and Pardo, 2000). An anatomical definition of the bolfactory portionQ of the insula thus remains obscure in humans, although the agranular and dysgranular rostral insula is a likely candidate (Petrides and Pandya, 1994). The bilateral activation in rostral insula elicited by odor imagery may also be interpreted as participation of another olfaction-related brain region in this type of mental imagery. Nonolfactory regions In addition to the olfactory regions, increased activity was noted in the left parietal and left dorsolateral prefrontal cortex, and in the left presupplementary motor area (pre-SMA). These three regions were reported previously as cortical areas that participate in imagery across modalities, including visual, auditory, and tactile mental imagery (Pratt et al., 2003). Some suggestions about the role of these regions in mental imagery included their known functions in monitoring and working memory (dorsolateral prefrontal cortex), attention (parietal cortex), and initiation of internally generated programs (preSMA). However, a precise definition of their contribution to the generation, maintenance, and manipulation of mental images remains unknown. In conclusion, contrasting the OI and OD conditions revealed rCBF increases in several regions associated with olfaction and several nonolfactory regions likely to play an important role in mental imagery. Although the odor names presented during OI were likely to elicit some other forms of mental imagery, such as visual, and probably some semantic processing, there were no significant blood flow increases noted in visual or language regions in the OI minus OD subtraction. Neural correlates of odor perception Another subtraction of interest (OP minus B) revealed regions of increased activation in known olfactory regions.


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We found bilateral activation in the POC in association with odor perception. Interestingly, we observed a unilateral blood flow increase in the posterior orbitofrontal cortex on the right side in association with smelling odorants. This peak, similarly to the left-sided peak observed in association with odor imagery, fell within the posterior orbitofrontal gyrus. Our finding is consistent with others’, suggesting an important role of the right OFC in human olfactory perception (Zatorre and Jones-Gotman, 2000). Another region associated with smelling odors in the present study was the rostral insula (bilateral increase in activation), in keeping with the known role of the insula in olfactory processing (Carmichael et al., 1994; Sobel et al., 2003; Zald and Pardo, 2000). Neural systems shared by odor imagery and odor perception One of the questions addressed in the present study was whether regions of increased activation during odor imagery overlap or are just adjacent to regions of activation during odor perception. In order to address this question, we conducted a conjunction analysis of the two relevant subtractions, one revealing increased blood flow associated with imagined and the other with perceived smells. The conjunction analysis confirmed that some regions that participate in olfactory perception also participate in olfactory imagery, and these were the left and right rostral insula. In addition, we found a common area of activation for these two processes in the left primary olfactory cortical region. Although two POC peaks fell below the predetermined significance level, we hold that this activation is not a false-positive finding, given that it was predicted a priori. In addition, two adjacent peaks were found, and the observed location closely corresponds to the piriform cortex, which is a very small cortical region. Furthermore, a left POC activation was observed in both subtractions of the conjunction analysis. One possible reason that it missed the significance threshold is that close but not entirely overlapping sections of the left POC were activated during odor imagery (Fig. 4) and odor perception (Fig. 6), as confirmed by both visual inspection and the comparison of coordinates of these two peaks (Table 3). This finding is consistent with the hypothesis that cortical networks engaged in perception and imagery within the same modality do not fully overlap and that certain parts of the primary and secondary cortical areas are activated only during actual perception (Gerardin et al., 2000; Gulyas, 2001; Halpern et al., 2004; Yoo et al., 2003).

Concluding comments To the best of our knowledge, this is the first study in which independent behavioral measurement of olfactory imagery during scanning was provided. Although the importance of measuring the behavior of interest during scanning has been emphasized before and it is particularly pertinent in the study of mental imagery (Thompson and Kosslyn, 2000), this standard has not been met in previous studies of odor imagery. We were able to demonstrate that participants in our study did imagine smells during scanning. We reported increased activation in sensory regions specific to olfaction (left primary olfactory cortex, left secondary olfactory cortex, and left and right insula) and in regions involved in mental imagery across different sensory

modalities (left parietal, and medial and mid-dorsolateral frontal cortex). We also demonstrated a positive relationship between activation of the right secondary olfactory cortex and odor imagery efficiency. As such, our findings show that odor imagery can be studied experimentally and that neural substrates of olfactory imagery and perception are partially overlapping, consistent with findings in other modalities including vision, audition, touch, and motion.

Acknowledgments We thank Marc Bouffard, Philippe Chouinard, and Sylvain Milot for assistance with data analyses, Jason Golan for help with the analysis of breathing files, Keith Worsley for answering our questions about statistical analyses, and Hadiya Roderique, Dylan David Wagner, and Sinziana Tugulea for technical assistance. This work was supported by grant MOP 57846 from the Canadian Institutes of Health Research awarded to M.J.G. and R.J.Z.

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