Figure 1.
A schematic of the olfactory pathway in canines.
Arrows indicate the olfactory signal flow. Anterior olfactory cortex, piriform cortex, periamygdaloid cortex, and entorhinal cortex are contained in a green box and the green arrows extending from this green box indicate the olfactory signal from them go to frontal cortex and thalamus. The gray arrow from entorhinal cortex to hippocampal formation indicates the olfactory signal to hippocampus comes only from the entorhinal cortex. For functions of each site, please refer to [1]–[4], [6], [7].
Figure 2.
Components of the dog fMRI olfactory imaging system.
(A) dog training to insert and keep their heads as still as possible inside the human knee coil using positive reinforcement learning (a black dog can be seen inside the coil); (B) components of imaging system outside the MRI room showing odorant applicator, air tank, motion parameter recording palmtop, video monitor, laptop with VT-8 software (see explanation in “Methods and Material: olfactory stimulus device”), and the entrance port to the MRI room; (C) components of imaging system inside the MRI room, showing human knee coil, infrared camera and infrared radiator.
Figure 3.
The interlinked trigger system.
Arrows denote the triggering direction. A laptop with VT-8 software [35] provided the interface to trigger the odorant applicator. The VT-8 software is a platform that can be used to design and display sequence of odorant flow and clearance, and provides communication and control to odorant applicator to generate the expected experimental sequence. Once the odorant applicator started to give odorant stimulus, it sent a signal to the trigger synchronizer, which then triggered the scanner and sent a signal to the manual trigger. The manual trigger, as the name suggests, was manually set for switching between two states. One was waiting for signals from trigger synchronizer, and the other was waiting for signal from a hand-pressed button. In our experiment, the first state was used for data collection and the second was used only for testing. Upon receiving the signal, it triggered the infrared radiation transmitter to give off infrared rays, and the infrared camera to start recording infrared reflections from the dog's head, and the motion parameter recording palmtop to start calculating displacement parameters. When the camera was triggered, it sent the signal to the monitor for display.
Figure 4.
Diagrammatic representation of the olfactory stimulation device.
The device consists of inflow & clearance air paths and an electronic control system. The inflow air/odorant path consists of a tank, flow control Valve 1, dry-rite type air Filter 1, Manifold 1 (6 isolated channels with electronically controlled valves), an electronic valve (EV1), 6 unidirectional pressure controlled valves (VU1, VU2), 6 odor bottles, Manifold 2 (6 flow-through isolated channels), flow control Valve 2, pressure regulated valve (PR), and electronic Manometer. The clearance path includes vacuum pump (VP), charcoal Filter 2, and electronic valve (EV2). The electronic control system consists of a 6-channel valve Timer, 6-channel valve Controller; Power-supply (feeds the VP, the visual LED control pane, and the cooling fan (CF)). Power for the Timer and Controller comes from the personal computer (PC). The protocols of timing and sequencing are stored and directed by the PC connected to the Timer. The Timer is synchronized with MRI. The experimental air pressure directed to the Mask are measured by the electronic Manometer and recorded by PC.
Figure 5.
Odorant applicator sequences controlled by VT-8 Warner Timer software and fMRI experimental block design.
For the first sequence, green arrows indicate the onset time of the odorant stimulus and red arrows indicate when the stimulation ends. For the second one, green arrows indicate the onset of clearance of odorant, and red arrows indicate when it ends. The third sequence shows the fMRI block design in this work, matching the first sequence. “0” and “1” denote the odor “on” and “off” conditions.
Figure 6.
A black dog positioned with muzzle in mask for odorant delivery.
The dot reflector is mounted to dog's head for motion tracking, the knee coil encompasses the dog's head and the mask is mounted on the front frame of the knee coil.
Figure 7.
Flow chart of proposed spatial normalization procedure.
A good quality anatomical image of an anesthetized dog was chosen as the template from Session 4 (4, being just an example). Then one functional image from the same session (Session 4) was chosen and normalized to the template. Subsequently, this transformed functional image was used as a template to normalize other functional images of other sessions. (*Anes:Anesthetized)
Figure 8.
Normalization of functional images to anatomical template.
The image (A) is the chosen anatomical template, its functional counterpart acquired in the same session is normalized to this template, which is shown in (B). The image (C) is a functional image of another dog. After normalization to the functional image (B), it becomes the image (D). (A: Anterior, P: posterior, S: superior, I: inferior, L: left, R: right)
Figure 9.
Group activation maps for anesthetized dogs.
(Overall FDR = 0.05, cluster threshold = 15 voxels using AlphaSim, t-contrast) Three orthogonal views are shown for each subfigure. Hot colormap is used for activation intensity, and important areas are indicated by arrows with labels. Subfigure (A) corresponds to low concentration odorant (0.016 mM), subfigure (B) corresponds to high concentration odorant (0.16 mM). (A: Anterior, P: posterior, S: superior, I: inferior, L: left, R: right)
Figure 10.
Group activation maps for awake dogs.
(Overall FDR = 0.05, cluster threshold = 15 voxels using AlphaSim, t-contrast) Three orthogonal views are shown for each subfigure. Hot colormap is used for activation intensity, and important areas are indicated by arrows with labels. Subfigure (A) corresponds to low concentration odorant (0.016 mM), subfigure (B) corresponds to high concentration odorant (0.16 mM). The activation in olfactory bulb for low concentration is not visible in this view, please refer to Table 3 for activation statistics with regard to this region. (A: Anterior, P: posterior, S: superior, I: inferior, L: left, R: right)
Figure 11.
Group activation maps for parametric modulation in anesthetized dogs (A) and awake dogs (B).
(Overall FDR = 0.05, cluster threshold = 15 voxels using AlphaSim, t-contrast). Three orthogonal views are shown for each subfigure. Hot colormap is used for activation intensity, and important areas are indicated by arrows with labels. (A: Anterior, P: posterior, S: superior, I: inferior, L: left, R: right)
Table 1.
Cluster-level statistics of activations for anesthetized dogs, low concentration of odorant.*
Table 2.
Cluster-level statistics of activations for anesthetized dogs, high concentration of odorant.*
Table 3.
Cluster-level statistics of activations for awake dogs, low concentration of odorant.*
Table 4.
Cluster-level statistics of activations for awake dogs, high concentration of odorant.*
Table 5.
Cluster-level statistics of activations for parametric modulation of anesthetized dogs.*
Table 6.
Cluster-level statistics of activations for parametric modulation of awake dogs.*
Figure 12.
Comparisons of fitted time series obtained from the GLM for ROIs in anesthetized dogs.
The ROIs are in brain regions that were activated by low and high odor concentration, as well as parametric modulation by odor intensity in anesthetized dogs. These regions are olfactory bulb and bilateral piriform lobes, which are shown in bold face in Tables 1, 2, and 5. In each of these regions, the ROI was determined by a sphere which centers at the peak activation of parametric modulation and has a radius of 2 mm. Fitted time series for low concentration are shown in blue, and high concentration in red.
Figure 13.
Comparisons of fitted time series obtained from the GLM for ROIs in awake dogs.
The ROIs are in brain regions that were activated by low and high odor concentration, as well as parametric modulation by odor intensity in awake dogs. These regions are olfactory bulb and cerebellum, which are shown in bold face in Tables 3, 4, and 6. In each of these regions, the ROI was determined by a sphere which centers at the peak activation of parametric modulation and has a radius of 2 mm. Fitted time series for low concentration are shown in blue, and high concentration in red.
Figure 14.
Comparison of activation maps with and without camera motion tracking parameters as regressors.
(Overall FDR = 0.05, cluster threshold = 15 voxels using AlphaSim, t-contrast) The activtion maps were for low concentration (0.016 mM) in awake dogs. The activation map obtained with only SPM realignment parameters as regressors is shown in cool colormap. The activation map with camera motion tracking parameters and SPM realignment parameters as regressors is shown in hot colormap. The common areas are overlaid such that they appear as purple. We found 3 clusters, 379 voxels in cool-colored map (same as in Table 3); 3 clusters, 396 voxels in hot-colorred map, and 3 clusters, 340 voxels in the common area. (A: Anterior, P: posterior, S: superior, I: inferior, L: left, R: right)
Figure 15.
Affine parameters relative to the first functional image volume calculated by SPM realignment procedure.
(A) mean time series of 6 affine parameters for anesthetized dogs; (B) standard deviation time series of 6 affine parameters for anesthetized dogs; (C) The time series of 6 affine parameters for the worst performing dog run at anesthetized state; (D) The time series of 6 affine parameters for the best performing dog run at anesthetized state; (E) mean time series of 6 affine parameters for awake dogs; (F) standard deviation time series of 6 affine parameters for awake dogs; (G) The time series of 6 affine parameters for the worst performing dog run at awake state (not included in the analysis); (H) The time series of 6 affine parameters for the best performing dog run at awake state.