Abstract

Cortical spreading depression (SD) is a self-propagating wave of depolarization accompanied by a substantial disturbance of the ionic distribution between the intra- and extracellular compartments. Glial cells, including astrocytes, play critical roles in maintenance of the extracellular environment, including ionic distribution. Therefore, SD propagation in the cerebral cortex may depend on the density of astrocytes. The present study aimed to examine the profile of SD propagation in the insular cortex (IC), which is located between the neocortex and paleocortex and is where the density of astrocytes gradually changes. The velocity of SD propagation in the neocortex, including the somatosensory, motor, and granular insular cortices (5.7 mm/min), was higher than that (2.8 mm/min) in the paleocortex (agranular insular and piriform cortices). Around thick vessels, including the middle cerebral artery, SD propagation was frequently delayed and sometimes disappeared. Immunohistological analysis of glial fibrillary acidic protein (GFAP) demonstrated the sparse distribution of astrocytes in the somatosensory cortex and the IC dorsal to the rhinal fissure, whereas the ventral IC showed a higher density of astrocytes. These results suggest that cortical cytoarchitectonic features, which possibly involve the distribution of astrocytes, are crucial for regulating the velocity of SD propagation in the cerebral cortex.

Introduction

Spreading depression (SD) is an electrophysiological phenomenon characterized by a self-propagating wave of transient neuronal depolarization spreading throughout the cerebral hemisphere. SD is followed by a long-lasting suppression of neuronal activity (Leão 1944) and has been implicated in various neurological disorders such as migraine, stroke, epilepsy, and trauma (Gorji 2001; Cui et al. 2009; Zhang et al. 2010). The principal structures where SD develops are the gray matter of the central nervous system, for example, the cerebral cortex, hippocampus, and cerebellum. SD appears first in a restricted region and spreads out in all directions at a velocity of 3–5 mm/min (Hadjikhani et al. 2001; Cui et al. 2003; Tfelt-Hansen 2010). SD propagation in the cerebral cortex is likely induced by release and diffusion of certain excitatory substances, most likely potassium and glutamate, into the interstitial space (Hansen et al. 1980; Holland et al. 2010; Dreier 2011; Grafstein 2011). Glial cells, including astrocytes, buffer extracellular K+ (Gardner-Medwin 1981) and take up glutamate (John et al. 2012). Several neurological reports have demonstrated that SD propagation ends at the border of the gray and white matter, and at the edge of glial-fibrous scars left by injury or infarction (van Harreveld et al. 1956; Hull and van Harreveld 1964; Somjen 2001). Therefore, the distribution pattern of astrocytes could be involved in the regulation of SD propagation.

The cerebral cortex is evolutionarily divided into 2 categories: the neocortex, which basically represents 6 layers, and the paleocortex, which shows a heterogeneous laminar structure (Sarma et al. 2011). The insular cortex (IC) is located between the somatosensory cortex, a part of the neocortex with 6 distinct layers, and the piriform cortex, a part of the paleocortex consisting of 3 layers (Reep and Winans 1982; Chen et al. 2007; Kobayashi 2011; Sarma et al. 2011). The dorsal IC, the granular part of the IC (GI), shows a similar laminar structure to the somatosensory cortex, whereas the ventral IC, the agranular part of the IC (AI), lacks the granule cell layer (layer IV). The dysgranular part of the IC (DI), between the GI and AI, shows an incomplete layer IV. The IC also has, as another anatomical feature, graduation, the density of astrocytes. The GI and AI exhibit low and high densities of glial fibrillary acidic protein (GFAP)-immunoreactive astrocytes, respectively (Zilles et al. 1991). Given these findings, the IC is considered to be a suitable cortical area to examine the structural features that are critical for propagation of cortical SD.

The present study investigated how cortical cytoarchitecture affects the velocity of SD propagation. To address the issue, we developed an in vivo optical imaging system with a voltage-sensitive dye to visualize cortical neural activity. This enabled us to observe the propagation of cortical SD intuitively with high spatio-temporal resolution. In addition, GFAP-immunohistological analysis was performed to examine the distribution pattern of astrocytes in the IC and surrounding areas.

Materials and Methods

The experiments were approved by the Animal Experimentation Committee of Nihon University and were performed in accordance with the institutional guidelines for the care and use of experimental animals described in the National Institutes of Health Guide for the care and use of laboratory animals. All efforts were made to minimize animal suffering and reduce the number of animals used.

Optical Imaging

Five- to six-week-old male Sprague-Dawley rats (Sankyo Labo, Tokyo, Japan) weighing 164.3 ± 3.1 g (n = 21) received atropine methyl bromide (5 mg/kg, intraperitoneal injection, Sigma-Aldrich, St Louis, MO, USA) and were anesthetized with urethane (1.5 g/kg, intraperitoneal injection, Sigma-Aldrich). The adequacy of anesthesia was gauged by the absence of the toe pinch reflex and heart rate changes to pinching the toe. Anesthesia was maintained throughout the experiments by injecting additional urethane. The heart rate was maintained at physiological levels (350–460 beats/min). Body temperature was monitored using a rectal probe (BWT-100, Bio Research Center, Tokyo, Japan) and was maintained at approximately 37°C using a heating pad. Animals received a tracheotomy and intubation, with lidocaine (2% gel) applied to the incisions to ensure complete analgesia. The anesthetized animal was mounted on a custom-made stereotaxic snout frame (Narishige, Tokyo, Japan), which was then tilted 60° laterally to make the left IC accessible to the CCD camera system and electrodes. The left temporal muscle and zygomatic arch were carefully removed, and a craniotomy was performed to expose the IC and surrounding cortices.

The method of optical imaging with a voltage-sensitive dye has been described previously (Chen et al. 2010; Fujita et al. 2010, 2011, 2012; Kobayashi et al. 2010; Mizoguchi et al. 2011; Adachi et al. 2013), and only a brief account of the methods employed will be given here. The voltage-sensitive dye, RH1691 (1 mg/mL, Optical Imaging, NY, USA), in 0.9% saline was applied to the cortical surface for approximately 1 h, residual dye was rinsed with saline for approximately 30 min, and fluorescent changes in RH1691 were measured by a CCD camera system (MiCAM02, Brainvision, Tokyo, Japan) mounted on a stereomicroscope (Leica Microsystems, Wetzler, Germany). The cortical surface was illuminated through a 632-nm excitation filter and a dichroic mirror by a tungsten halogen lamp (CLS150XD, Leica Microsystems), and the fluorescent emission was captured through an absorption filter (λ > 650 nm long-pass, Andover, Salem, NH, USA). The IC and surrounding cortices were imaged (Fig. 1). The CCD-based camera had a 6.4 × 4.8 mm2 imaging area consisting of 184 × 124 pixels. The sampling interval was 200 ms. Acquisition time was set at 8 min.

Figure 1.

A schematic drawing of the preparation for optical imaging of the insular cortex (IC). To induce cortical spreading depression (SD), a cotton ball soaked with 1 M KCl was applied at the edge of the caudal side in the imaging area in the caudal–rostral experiments (black arrowhead) or in an opening of another craniotomy on the parietal part of skull in the dorso-ventral experiments (white arrowhead; modified from Fujita et al. 2010).

Figure 1.

A schematic drawing of the preparation for optical imaging of the insular cortex (IC). To induce cortical spreading depression (SD), a cotton ball soaked with 1 M KCl was applied at the edge of the caudal side in the imaging area in the caudal–rostral experiments (black arrowhead) or in an opening of another craniotomy on the parietal part of skull in the dorso-ventral experiments (white arrowhead; modified from Fujita et al. 2010).

Induction of Cortical Spreading Depression

To evoke cortical SD, a cotton ball (1 mm diameter) soaked with 1 M KCl (Wako Pure Chemical, Tokyo, Japan) in distillated water was placed on the pial surface for approximately 2 s. The stimulation point was set at the caudal end of the imaged area (Fig. 1, black arrowhead) or the dorsal part of the somatosensory area (Fig. 1, white arrowhead). In the latter experiments, another small craniotomy (2 mm diameter) was performed on the parietal part of skull. Some rats were used in both experiments. The stimulation was applied every 20 min. Between acquisitions, 0.9% saline was applied to moisten the cortical surface and wash away excess KCl.

Local Field Potentials

In some imaging experiments, local field potentials (LFPs) were simultaneously recorded to confirm that optical signals were correlated with electrical activity. A monopolar tungsten electrode (impedance = 0.25 MΩ; FHC, Bowdoin, ME, USA) was inserted 0.3 mm from the cortical surface, and LFPs were amplified (band pass: 0–100 Hz; ER-1, Cygnus Technology, Delaware Water Gap, PA, USA), digitized, and stored on a computer hard disk (Micro 1401 MK2, Cambridge Electronic Design, Cambridge, UK).

Data Analysis for Optical Imaging

The change in the intensity of fluorescence (ΔF) in each pixel relative to the initial fluorescence intensity (F) was calculated (ΔF/F). A digital bleaching filter (Brain Vision Analyzer, Brainvision, Tokyo, Japan) was used to compensate for dye bleaching (Fig. 2A,C). The methods regarding velocity calculation and activation map analysis were described previously (Efimov et al. 2004). Briefly, images were processed with a derivative (DERIV) filter (±3 frames) to detect the frontline of the SD propagation, that is, the rising portion of the depolarization, from the slow depolarization traces of SDs. A spatial filter (9 × 9 pixels) and a low-pass filter (0.390 Hz) were applied to obtain the apparent frontline of SDs and reduce the noise (Fig. 2B,C; Brain Vision Analyzer). An activation map was constructed by superimposition of the frontlines of an SD (Fig. 2D). The velocity of SD propagation was calculated by line analysis (Fig. 2E; Brain Vision Analyzer). To calculate velocities, 3 SDs from a rat were averaged. In the rostral part of piriform cortex, the velocity of SD propagation was calculated only from the cases in which an SD was observed in that area. Data are expressed as means ± SEM. Velocities of SD propagations were compared using one-way ANOVA followed by Tukey's post hoc test (SPSS version 15, Chicago, IL, USA). A level of P < 0.05 was considered statistically significant.

Figure 2.

The detection of the frontline of cortical SD. (A) Color-coded optical signals of cortical SD are shown. A template of cortical subdivisions around the IC is shown in the left upper panel. A blue circle in the agranular part of the IC (AI) indicates the location of the region of interest (ROI). The asterisk indicates the site of the recording electrode. The red star indicates the stimulation site. In this figure, long-term bleaching was corrected by a beaching filter. Note that in the SD, biphasic waves of potent depolarization and hyperpolarization can be observed. (B) The frontline of the SD is clearly visible due to the use of derivative (DERIV), spatial, and low-pass filters. (C) The frontline corresponded to the rising phase of depolarization of the SD. Note that traces of local field potential (LFP; black line) from the recording electrode and optical signals (blue line; digital bleaching filtered) from an ROI in (A) are very similar. A DERIV filter revealed the rise phasing of the SD (red line). The vertical lines in upper part correspond to timings of panels in (A) and (B). (D) Example of activation map analysis. The red lines indicate a frontline traveling from 10 to 180 s at 10 s intervals after 1 M KCl stimulation. The area filled by black indicates the shadow of the LFP recording electrode. (E) A spatio-temporal map of the movement of a frontline of an SD wave along the arrow in (D) is shown. AI, agranular IC; DI, dysgranular IC; DLO, dorsolateral orbital cortex; Fr3, frontal cortex (area 3); GI, granular IC; Pir, piriform cortex; MC, motor cortex; SI, primary somatosensory cortex; SII, secondary somatosensory cortex.

Figure 2.

The detection of the frontline of cortical SD. (A) Color-coded optical signals of cortical SD are shown. A template of cortical subdivisions around the IC is shown in the left upper panel. A blue circle in the agranular part of the IC (AI) indicates the location of the region of interest (ROI). The asterisk indicates the site of the recording electrode. The red star indicates the stimulation site. In this figure, long-term bleaching was corrected by a beaching filter. Note that in the SD, biphasic waves of potent depolarization and hyperpolarization can be observed. (B) The frontline of the SD is clearly visible due to the use of derivative (DERIV), spatial, and low-pass filters. (C) The frontline corresponded to the rising phase of depolarization of the SD. Note that traces of local field potential (LFP; black line) from the recording electrode and optical signals (blue line; digital bleaching filtered) from an ROI in (A) are very similar. A DERIV filter revealed the rise phasing of the SD (red line). The vertical lines in upper part correspond to timings of panels in (A) and (B). (D) Example of activation map analysis. The red lines indicate a frontline traveling from 10 to 180 s at 10 s intervals after 1 M KCl stimulation. The area filled by black indicates the shadow of the LFP recording electrode. (E) A spatio-temporal map of the movement of a frontline of an SD wave along the arrow in (D) is shown. AI, agranular IC; DI, dysgranular IC; DLO, dorsolateral orbital cortex; Fr3, frontal cortex (area 3); GI, granular IC; Pir, piriform cortex; MC, motor cortex; SI, primary somatosensory cortex; SII, secondary somatosensory cortex.

Immunohistochemistry

Male Sprague-Dawley rats (6 weeks old, n = 5) were deeply anesthetized with pentobarbital (100 mg/kg) and perfused transcardially with 0.9% saline (50 mL) followed by 4% paraformaldehyde in 0.1 M phosphate buffer (PB, pH7.4, 200 mL). The brain was removed and postfixed in 4% paraformaldehyde at 4°C. After an overnight fixation, tissues were transferred to 15–30% sucrose in phosphate-buffered saline (PBS) for several days for cryoprotection. Thirty-micrometer-thick coronal (n = 3) or horizontal (n = 2) sections were cut with a cryostat and collected in PBS.

The protocols for immunohistochemistry were described previously (Li et al. 2004). Briefly, the sections were rinsed with 0.3% Triton X-100 in 10 mM phosphate-buffered saline (PBST) and then treated with 0.3% H2O2 for 1.5 h at room temperature to suppress endogenous peroxidase activity. After rinsing in 10 mM PBST, the sections were incubated with Goat anti-Glial Fibrillary Acidic Protein serum (GFAP, 1:1000; Santa Cruz Biotechnology, Santa Cruz, CA, USA) overnight at 4°C. After primary antibody incubation, sections were washed in 10 mM PBST. For light microscopic visualization with diaminobenzidine (DAB) as the chromagen, sections were incubated with an anti-Goat biotinylated secondary antibody (1:200; Vector, Burlingame, CA, USA) for 1 h at room temperature. After further rinsing in 10 mM PBST, the sections were then incubated in avidin-biotinylated enzyme complex solution (ABC reagent; 1:100, Vector, Burlingame, CA, USA) for 1 h. After rinsing in 10 mM PBST, the reaction product was detected using 0.03% 3-3′-DAB (Sigma-Aldrich) and 0.01% H2O2 in 50 mM Tris–HCl at room temperature. The sections were mounted on gelatin-coated slides and coverslipped. Control sections that were processed without primary antiserum displayed no specific staining.

Quantitative Analysis for GFAP

A microscope (Eclipse E600, Nikon, Tokyo, Japan) equipped with a motorized stage (Lucivid, MicroBrightField, Colchester, VT, USA) and Stereo Investigator software (Neurolucida, ver. 10.40, MicroBrightField) was used to count immunocytochemically labeled astrocytes (Chen et al. 2010; Kobayashi et al. 2010). In this study, multipolar-shaped structures with a densely stained cell body and 3 ≥processes (Fig. 8C, black arrowheads) were counted with a ×20–40 objective.

We chose coronal sections located near the intersection of the middle cerebral artery (MCA) and rhinal fissure (RF) to compare the density of astrocytes between dorsal and ventral regions. We generated contour plots (Origin 8, OriginLab, MA, USA) in horizontal sections to visualize the distribution of astrocytes. The contour lines were smoothed using a software function (Smooth Matrix values = 0.01).

Results

Frontlines of Cortical Spreading Depression

Topical application of 1 M KCl (Ayata et al. 2006; Chen et al. 2006; Zhang et al. 2010) to the pial surface of the caudal end of the imaged area increased the amplitude of the optical signal (ΔF/F), which was followed by a long-lasting signal decrease as shown in Figure 2. An increase or decrease in optical signals is considered to reflect neuronal depolarization or hyperpolarization, respectively (Farkas et al. 2008).

Simultaneous recording of the field potential demonstrated that an approximately −20-mV negative DC potential shift was observed being synchronously accompanied by a depolarization phase of optical signals, as is characteristic of the cortical SD (Fig. 2C; Herreras and Somjen 1993; Cui et al. 2013). In agreement with a previous study comparing the signals of LFP and voltage-sensitive dye in SD propagation (Farkas et al. 2008), the signals consistently showed good concordance in the depolarization phase but not in the hyperpolarization phase following depolarization. Application of a DERIV filter allowed clear visualization of the sharp frontlines of SD propagations (Fig. 2B). The frontlines of SD propagated in a concentric manner (Supplementary Movie 1). A line perpendicular to the frontline of the SD was drawn to measure the velocity of SD propagation (Arrow in Fig. 2D). By applying the stripe map function (see Materials and Methods; Brain Vision Analyzer), a spatio-temporal map along the perpendicular line was generated (Fig. 2E). Movement of the frontline of the SD was represented as a color-coded signal in the map (Dotted line in Fig. 2E). The calculated velocity of SD was 4.8 mm/min. Similar to a previous study (Farkas et al. 2008), LFP in the AI showed a similar temporal excitation curve to optical signals obtained from the voltage-sensitive dye (Fig. 2C); this indicated that the frontlines of optical signals represented the onset to peak of the depolarization phase of SD.

Propagation Velocity of SD in the IC Area

We evoked cortical SD by stimulating the caudal edge of the imaging area to investigate the propagation characteristics of SD in the IC in a caudal-to-rostral direction, which involves a representative transition of cytoarchitectonic laminar structures (stars in Figs 2A and 3A,B). The activation map showed distinct characteristics of SD between the dorsal and ventral part of the IC (Fig. 3A,B; also see Supplementary Movie 1). Fast SD propagation was observed in dorsal part of the imaging area, including the motor cortex (MC), primary sensory cortex (SI) and GI (Fig. 3A,B). No significant difference in propagation velocity was observed among the MC, SI, and GI (Fig. 4). A lower velocity of SD propagation was observed in the AI and piriform cortex, which are characterized by typical paleocortical cytoarchitecture, that is, <6 cell layers and a high density of glial cells. In DI, which is located between GI and AI, SD propagated with medium velocity (Fig. 4B; F5,66 = 19.83, P < 0.001, one-way ANOVA).

Figure 3.

Two examples of cortical SDs in the caudal–rostral experiments. The frontline travels (thin lines) from 18 to 50 s at 2 s intervals (A) and from 26 to 74 s at 2 s intervals (B) after 1 M KCl stimulation. A template of cortical subdivisions around the IC is shown in the panels. Thick dotted and solid lines indicate the middle cerebral artery (MCA) and the rhinal fissure (RF). Note that the distance between thin lines is large on dorsal side, whereas it is narrow on the ventral side. The frontlines on the rostral side of the MCA become orthogonal to the MCA at the arrowhead.

Figure 3.

Two examples of cortical SDs in the caudal–rostral experiments. The frontline travels (thin lines) from 18 to 50 s at 2 s intervals (A) and from 26 to 74 s at 2 s intervals (B) after 1 M KCl stimulation. A template of cortical subdivisions around the IC is shown in the panels. Thick dotted and solid lines indicate the middle cerebral artery (MCA) and the rhinal fissure (RF). Note that the distance between thin lines is large on dorsal side, whereas it is narrow on the ventral side. The frontlines on the rostral side of the MCA become orthogonal to the MCA at the arrowhead.

Figure 4.

The velocity of cortical SD propagation varied depending on the area. (A) Velocities were measured from the MC, SI, GI, DI, AI, and Pir. Arrows indicate examples of actual measurement sites. Black thin lines indicate the frontline traveling from 5 to 140 s at 5 s intervals after 1 M KCl stimulation. (B) The velocities were lower in the DI, AI, and Pir compared with the SI, GI, and MC. (*P < 0.05, **P < 0.01, ***P < 0.001, Tukey's test).

Figure 4.

The velocity of cortical SD propagation varied depending on the area. (A) Velocities were measured from the MC, SI, GI, DI, AI, and Pir. Arrows indicate examples of actual measurement sites. Black thin lines indicate the frontline traveling from 5 to 140 s at 5 s intervals after 1 M KCl stimulation. (B) The velocities were lower in the DI, AI, and Pir compared with the SI, GI, and MC. (*P < 0.05, **P < 0.01, ***P < 0.001, Tukey's test).

To confirm the characteristic profile of SD propagation, that is, that AI and piriform cortex show a lower velocity relative to the dorsal part of IC and somatosensory cortex, the pial surface of the parietal cortex was stimulated with a cotton ball soaked with 1 M KCl, and SD propagation velocity was evaluated in a dorsal-to-ventral direction (Fig. 5). Consistent with the above hypothesis, the propagation velocity gradually decreased from SI/SII and GI to the ventral IC. A significant decrease of propagation velocity was observed in DI and AI relative to SI (Fig. 5B; F3,48 = 22.42, P < 0.001, one-way ANOVA).

Figure 5.

The observation of cortical SD induced by parietal cortex stimulation revealed a gradual decrement from dorsal areas to the ventral areas. (A) An example of movement of frontlines in the dorso-ventral SD experiment is shown. Thin lines indicate the frontline traveling from 140 to 285 s at 5 s intervals after 1 M KCl stimulation. (B) An example of a spatio-temporal map based on the travel of the frontline (thick black band) of the SD wave along the arrow in (A) is shown. The dotted white line indicates the frontline. In this case, the vessels delayed the propagation of the SD for a moment, and this part was removed from velocity measurements (arrowhead). (C) The velocity of the cortical SD decreased gradually from the GI to the AI (*P < 0.05, **P < 0.01, ***P < 0.001, Tukey's test).

Figure 5.

The observation of cortical SD induced by parietal cortex stimulation revealed a gradual decrement from dorsal areas to the ventral areas. (A) An example of movement of frontlines in the dorso-ventral SD experiment is shown. Thin lines indicate the frontline traveling from 140 to 285 s at 5 s intervals after 1 M KCl stimulation. (B) An example of a spatio-temporal map based on the travel of the frontline (thick black band) of the SD wave along the arrow in (A) is shown. The dotted white line indicates the frontline. In this case, the vessels delayed the propagation of the SD for a moment, and this part was removed from velocity measurements (arrowhead). (C) The velocity of the cortical SD decreased gradually from the GI to the AI (*P < 0.05, **P < 0.01, ***P < 0.001, Tukey's test).

Disturbance of SD Propagation by the MCA and Rhinal Fissure

Interestingly, SD propagation seems to be disturbed by the MCA and RF. As shown in Figures 3 and 4, SD passed across the dorsal MCA but not across the ventral MCA (see Supplementary Movie 1). Therefore, the direction of SD propagation changed near the MCA in the ventral part of IC (Figs 3 and 4A). On the other hand, regardless of the thickness of the MCA, such a strong disturbance of SD propagation was not found in the dorsal area, including DI and SI (Fig. 3A,B); SD sometimes traveled with a short time delay onto the MCA (solid arrowhead in Figs 5B and 6, but not outline arrowhead). In addition to the MCA, SD propagation was sometimes disturbed by the caudal part of the RF. In the dorso-ventral experiments, 29 of 39 SDs propagated through the RF (Fig. 7A), whereas 10 of 39 SDs did not traverse the RF directly (Fig. 7B). Seven of the latter 10 SDs detoured caudally outside of the imaging area and propagated recurrently in the caudal to rostral direction. Each of these 7 SDs stopped at the ventral MCA (Fig. 7B). Only 1 SD detoured around the intersection of the MCA and RF and reached the ventral area. In the remaining 2 cases, SDs terminated completely at the RF.

Figure 6.

The MCA sometimes briefly delayed the propagation of the SD. The left panels show a frontline traveling from the caudal to rostral direction. A red star indicates the stimulation site. The right panel shows a spatio-temporal map of the movement of a frontline along the arrow in the first left panel. Note that there is a slight shift shown by the two dotted lines because the propagation was temporally delayed at the solid arrowhead, but not at the outlined arrowhead.

Figure 6.

The MCA sometimes briefly delayed the propagation of the SD. The left panels show a frontline traveling from the caudal to rostral direction. A red star indicates the stimulation site. The right panel shows a spatio-temporal map of the movement of a frontline along the arrow in the first left panel. Note that there is a slight shift shown by the two dotted lines because the propagation was temporally delayed at the solid arrowhead, but not at the outlined arrowhead.

Figure 7.

The RF sometimes prevented the propagation of the SD into the ventral area. (A) The SDs (29/39 cases of the dorso-ventral experiments) usually propagated through the caudal part of the RF (arrowheads). Directions of arrowheads correspond to directions of SD propagation. Note that the blue-colored zone (asterisk) is due to transition (repolarization) from depolarization phase to hyperpolarization phase (see Fig. 2). (B) The SD (7/39 cases) propagations detoured caudally outside the imaging area and spread to the area below the RF from the caudal to rostral direction (black arrowheads). Note that the cortical SD stopped at the MCA in all cases (white arrowheads).

Figure 7.

The RF sometimes prevented the propagation of the SD into the ventral area. (A) The SDs (29/39 cases of the dorso-ventral experiments) usually propagated through the caudal part of the RF (arrowheads). Directions of arrowheads correspond to directions of SD propagation. Note that the blue-colored zone (asterisk) is due to transition (repolarization) from depolarization phase to hyperpolarization phase (see Fig. 2). (B) The SD (7/39 cases) propagations detoured caudally outside the imaging area and spread to the area below the RF from the caudal to rostral direction (black arrowheads). Note that the cortical SD stopped at the MCA in all cases (white arrowheads).

Distribution Profile of Astrocytes

In agreement with previous studies using computer-assisted image analysis of GFAP-immunoreactive astrocytes (Zilles et al. 1991), our immunohistological analysis showed sparse astrocytes in SI/SII and IC dorsal to the RF, whereas ventral IC and piriform cortex showed a higher density of astrocytes (Fig. 8AE). In SI/GI, distribution patterns were heterogeneous; superficial and deeper layers generally showed higher densities of astrocytes (Fig. 8AD; Zilles et al. 1991). Density of astrocytes in the middle layers gradually increased from SI/SII and GI to RF (Fig. 8E). Density of astrocytes in the ventral region 1–2 mm from RF was 2.3-fold higher relative to the dorsal region 4–5 mm from the RF (n = 3, P < 0.05, ANOVA with Tukey's test, Fig. 8E). In addition, the distribution pattern of astrocytes was affected by thick vessels. A dense distribution of astrocytes was observed around RF (Fig. 8F). The MCA effected a hollow in the cortical surface, which exhibited a higher density of astrocytes (Fig. 8IK). On the other hand, thin vessels had little effect on morphology of the cortical surface, though the density of astrocytes was slightly higher than in adjacent regions (Fig. 8G,H).

Figure 8.

The characteristics of astrocyte distributions. (A) An example of glial fibrillary acidic protein (GFAP)-immunoreactive astrocytes in a coronal section. An arrowhead indicates the RF. (B) An example of the transition area where astrocytes density changes, which is boxed with red-dotted lines in (A). Note that the dorsal part shows a lighter reaction, whereas the ventral part is darkened. (C) An example of astrocyte counting (arrowheads). (D) An example of plots of astrocytes and compartments where density was quantified. (E) A summary of the distribution of astrocytes (n = 3). (F) A contour plot from blue-dotted area in (D). Note that astrocytes were dense around the RF (arrowhead). (G) An example of plots of astrocytes around thin arteries (arrowheads) in a coronal section. (H) A contour plot from (G). (I) An example of GFAP-immunoreactive astrocytes around a thick MCA in the horizontal section. “r” and “c” indicate rostral and caudal, respectively. (J) The plots from (I). (K) A contour plot on from (J). Note that the sparse astrocyte area was narrow around the MCA, as if it was being compressed by the MCA.

Figure 8.

The characteristics of astrocyte distributions. (A) An example of glial fibrillary acidic protein (GFAP)-immunoreactive astrocytes in a coronal section. An arrowhead indicates the RF. (B) An example of the transition area where astrocytes density changes, which is boxed with red-dotted lines in (A). Note that the dorsal part shows a lighter reaction, whereas the ventral part is darkened. (C) An example of astrocyte counting (arrowheads). (D) An example of plots of astrocytes and compartments where density was quantified. (E) A summary of the distribution of astrocytes (n = 3). (F) A contour plot from blue-dotted area in (D). Note that astrocytes were dense around the RF (arrowhead). (G) An example of plots of astrocytes around thin arteries (arrowheads) in a coronal section. (H) A contour plot from (G). (I) An example of GFAP-immunoreactive astrocytes around a thick MCA in the horizontal section. “r” and “c” indicate rostral and caudal, respectively. (J) The plots from (I). (K) A contour plot on from (J). Note that the sparse astrocyte area was narrow around the MCA, as if it was being compressed by the MCA.

Discussion

The present study investigated whether SD propagation patterns are dependent on cortical cytoarchitecture, using an in vivo voltage-sensitive dye imaging technique. We demonstrated that AI and piriform cortex exhibited a lower SD propagation velocity relative to SI/SII and GI. The velocity change likely relates to cytoarchitectonic differences between SI/SII/GI (neocortex) and AI/piriform cortex (paleocortex). We also demonstrated that AI/piriform exhibited a higher density of astrocytes than SI/SII/GI (Fig. 8; Zilles et al. 1991). In addition, we found that propagation of SD was disturbed at thick vessels, such as the MCA and RF, where the density of astrocytes was higher than in surrounding regions. Therefore, it is likely that the buffering mechanism in astrocytes may play a critical role in propagation of cortical SD.

Anisotropic Propagation Patterns of SD in IC and Surrounding Cortices

The main finding of the present study is that different velocities of SD propagation in the temporal cortex depend on the different cytoarchitectonic laminar patterns. Since the discovery of cortical SD as a self-propagating wave of depolarization, cortical SD has been considered to spread in a concentric manner (Tomita et al. 2002). To the best of our knowledge, propagation of SD has been studied in tissue of uniform cytoarchitecture. In this study, we demonstrate anisotropic propagation of SD in IC, which consists of cytoarchitectonically heterogeneous laminar structures, that is, the neocortex (GI) and paleocortex (AI; Cechetto and Saper 1987; Shi and Cassell 1998; Kobayashi 2011; Maffei et al. 2012). The piriform cortex is the most ventral area imaged in this study, and it consists of 3 layers (Chen et al. 2007; Sarma et al. 2011). We found a gradual decrement in SD propagation velocity from SI and GI to AI (Fig. 5B). Several studies have demonstrated variation in SD propagation velocity. Bowyer et al. (1999) showed faster SD propagation in gyri than that in sulci in the pig brain in vivo. In vitro, hippocampal, and entorhinal cortical slice preparations exhibited the highest velocity (5.4 mm/min) in CA3 region and the slowest velocity (2.7 mm/min) in cortical regions (Buchheim et al. 2002). These observations suggest that cytoarchitectonic features contribute to the propagation of SD velocity.

Astrocytes Possibly Regulate SD Propagation Velocity

It has been proposed that SD propagation is caused by the release and diffusion of excitatory chemical mediators, including potassium and glutamate, into the extracellular space. Therefore, it has been hypothesized that glia, especially astrocytes in the brain, contribute to SD propagation by buffering extracellular potassium and excitatory amino acids (Gardner-Medwin 1981; Somjen 2001). Astrocytes remove potassium ions from the extracellular space by several mechanisms: 1) inwardly rectifying K+ channels; 2) Na+/K+-ATPase; 3) Na+-K+-Cl co-transporters; and 4) gap junctions (Kofuji and Newman 2004; Olsen and Sontheimer 2008; Larsen et al. 2014). Astrocyte-dependent buffering of extracellular glutamate is mediated by membrane transporters, such as excitatory amino acid transporter 1 and excitatory amino acid transporter 2. In agreement with the above hypothesis, ventral IC, which has a higher density of astrocytes, showed slower SD propagation relative to dorsal IC, where astrocytes are sparse (Fig. 8; Zilles et al. 1991).

Relative to the decrease in velocity of SD propagation, the density of astrocytes abruptly decreased from dorsal to ventral IC. A possible explanation is that the density map was made by plotting cell bodies, rather than their abundant branches. Therefore, the functional region of an astrocyte is likely to be much larger than its plot, which may cause gradual alternation of velocity. Interestingly, SD propagation from caudal IC was slowed or stopped near the MCA at the ventral part of IC (Fig. 7). In addition, dorso-ventral propagation of SD showed a delayed frontline near the MCA, indicating a decrease in propagation velocity (Fig. 5A). Astrocytes are densely localized around brain blood vessels (Fig. 8FH; Maddahi et al. 2009), where abundant expression of inwardly rectifying K+ channels is observed (Newman 1984; Hibino et al. 2004; Hibino and Kurachi 2007). Taking into account the role of inward rectifying K+ channels, that is, removing extracellular K+, astrocytes near blood vessels in the brain may disturb SD propagation by buffering extracellular K+ and glutamate. Previous studies using optical imaging techniques have reported that such disturbances by blood vessels are not found in the rat neocortex (Tomita et al. 2002; Chen et al. 2006; Brennan et al. 2007). The reason for the discrepancy between our findings and these reports may be differences in cortical areas examined. The present study demonstrated that SD propagation was stopped or slowed at the MCA only in IC or piriform cortex, but not in SI. Recently, Santos et al. (2014) demonstrated that morphology critically affects SD propagation in pig gyrencephalic brain; the pial vessels acted as physical barriers that blocked SD propagation. Our findings in rat cerebral cortex are in line with their observation. We propose that the density of astrocytes in the region surrounding the MCA and RF in the paleocortex is higher than in the neocortex and, therefore, the buffering effect is larger in IC than in SI.

The astrocyte-induced buffering of extracellular K+ is considered to suppress SD propagation, and our present results support this hypothesis. In addition to the functional contribution of astrocytes, other components, including neurons and microglia, may also play a role in regulating SD propagation. Indeed, Ca2+ influx causes K+ efflux to the extracellular space via Ca2+-dependent K+ channels, and the increase in [K+]o is considered to trigger cortical SD and increase velocity of SD propagation (Torrente et al. 2014), suggesting that high neural activity facilitates SD. In addition, a recent study reported that SD requires microglia (Pusic et al. 2014). Depletion of microglia in slice cultures inhibits initiation of SD, and microglial polarization state modulates SD threshold both in vitro and in vivo.

SD is considered to cause migraine aura symptoms. Our results suggest that the paleocortex, such as AI and piriform cortex, is resistive to SD propagation. Taking into account that IC and piriform cortex process gustatory, visceral, and olfactory information, such senses are less likely to be affected by SD. Indeed, in contrast to visual and somatosensory aura, gustatory and olfactory aura are minor symptoms of migraine in humans (Ferrari 1998).

Technical Advantage

Cortical SD is characterized by a self-propagating wave of intense depolarization. Optical imaging techniques with a voltage-sensitive dye are potent tools for investigating the kinetics of a direct current potential with high temporal and spatial resolution (Farkas et al. 2008; see also Fig. 2). Although the SD signal was intense and showed a high signal/noise ratio, cortical SD exhibited very slow and wide development, which makes for difficulty in detecting its onset. To resolve this problem, we differentiated between signal intensity and time. As a result, onset of SD propagation, that is, the rising component of depolarization, is clearly detected as a frontline. This derivation process has been widely used in investigation of cardiac physiology. For optical imaging of the heart, fluorescence derivatives are used to detect time points of myocardial activation and repolarization (Efimov et al. 2004).

Inhomogeneous SD propagation due to the MCA results in inaccurate velocity measurements. Therefore, the short time delay (solid arrowhead, but not the outlined arrowhead in Fig. 6) in the dorsal part of the MCA was excluded from velocity measurements (Fig. 5B). In addition to change in SD propagation velocity, a diffraction-like phenomenon (i.e., direction of change of SD propagation by the MCA in the ventral part of IC) also makes the accurate measurement of SD velocity difficult (Figs 3 and 4A; see Supplementary Movie 1). A line perpendicular to the wave of SD was required to calculate the accurate velocity of SD propagation. Therefore, as part of caudal-to-rostral experiments, in the ventral part of the MCA, we divided SD propagation measurement in IC into segments caudal and rostral to the MCA.

Conclusions

In the present study, we demonstrated for the first time that the propagation velocity of cortical SD gradually decreased from dorsal to ventral cortical areas of the IC. In this area, the laminar cytoarchitecture and the volume distribution of glial cells are known to change gradually from neocortex to paleocortex. These results suggest that these cytoarchitectonic features, especially the density of glial cells, are crucial for regulating SD propagation among cortical areas.

Supplementary Material

Supplementary material can be found at http://www.cercor.oxfordjournals.org/ online.

Funding

This work was supported by Japan Society for the Promotion of Science KAKENHI (22791802 to S.F., 25293379 to M.K., 26463192 to N.M.); the Ministry of Education, Culture, Sports, Science and Technology—supported Program for the Strategic Research Foundation at Private Universities, 2013–2017, to M.K.; the Sato Fund, Nihon University School of Dentistry to S.F.

Notes

We thank Prof. John L. Waddington for critical comments on the manuscript. We also thank Drs Kenji Tsubokura and Kiyo Murano for developing the software for optical imaging analysis. Conflict of Interest: None declared.

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