Cerebral Cortex Advance Access originally published online on November 10, 2006
Cerebral Cortex 2007 17(9):2060-2071; doi:10.1093/cercor/bhl114
| ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
The Distribution of Chandelier Cell Axon Terminals that Express the GABA Plasma Membrane Transporter GAT-1 in the Human Neocortex
1 Instituto Cajal, CSIC, 28002 Madrid, Spain, 2 Department of Cell Biology, Universidad Complutense, 28040 Madrid, Spain
Address correspondence to A. Muñoz, Instituto Cajal, CSIC, Av. Dr Arce 37, 28002 Madrid, Spain. Email: amunoz{at}cajal.csic.es.
 |
Abstract |
|---|
 Top Abstract IntroductionMaterials and MethodsResultsDiscussionReferences |
|---|
Chandelier cells represent a unique type of cortical GABAergic interneuron whose axon terminals (Ch-terminals) form synapses exclusively with the axon initial segments of pyramidal cells. In this study, we have used immunocytochemistry for the high-affinity plasma membrane transporter-1 (GAT-1) to analyze the distribution and density of Ch-terminals in various cytoarchitectonic and functional areas of the human neocortex. The lowest density of GAT-1–immuoreactive (-ir) Ch-terminals was detected in the primary and secondary visual (areas 17 and 18) and in the somatosensory areas (areas 3b and 1). In contrast, an intermediate density was observed in the motor area 4 and the associative frontolateral areas 45 and 46, whereas the associative frontolateral areas 9 and 10, frontal orbitary areas 11, 12, 13, 14, and 47, associative temporal areas 20, 21, 22, and 38, and cingulate areas 24 and 32 displayed the highest density of GAT-1-ir Ch-terminals. Despite these differences, the laminar distribution of GAT-1-ir Ch-terminals was similar in most cortical areas. Hence, the highest density of this transporter was observed in layer II, followed by layers III, V, VI, and IV. In most cortical areas, the density of GAT-1-ir Ch-terminals was positively correlated with the neuronal density, although a negative correlation was detected in layer III across all cortical areas. These results indicate that there are substantial differences in the distribution and density of GAT-1-ir Ch-terminals between areas and layers of the human neocortex. These differences might be related to the different functional attributes of the cortical regions examined.
Key Words: axon initial segment • cerebral cortex • GABA • inhibition • interneurons
|
Introduction |
|---|
|
TopAbstractIntroductionMaterials and MethodsResultsDiscussionReferences |
|---|
A large variety of gamma-amino butyric acid (GABA)-ergic neurons with different morphological, molecular, and physiological characteristics has been described in the mammalian cerebral cortex. Chandelier cells are one of the best characterized cortical GABAergic interneurons because they are readily distinguished by their vertical rows of boutons in the terminal portion of their axons (Ch-terminals), which resemble candlesticks (Szentagothai and Arbib 1974
; Jones 1975). Many interneurons establish synapses at different postsynaptic regions, both with pyramidal cells and interneurons. However, chandelier cells are unique because Ch-terminals only establish synapses with the axon initial segments (AIS) of pyramidal cells. Indeed, these cells represent the main source of the AIS synapses (Somogyi 1977; Fairen and Valverde 1980; Peters et al. 1982; Somogyi et al. 1982, 1985; Freund et al. 1983; DeFelipe et al. 1985, 1989; Williams and Lacaille 1992; Buhl et al. 1994; DeFelipe 1999). The AIS is a critical region in controlling cell excitability and the generation of axon potentials, thereby determining the axonal output of principal cells (Stuart and Sakmann 1994; Colbert and Johnston 1996). Thus, in contrast to interneurons that target membrane compartments of dendrites and somata, chandelier cells have traditionally been presumed to exert a strong influence on the output of pyramidal cells (Miles et al. 1996; DeFelipe 1999). Ch-terminals are found in different cortical areas and species, including rats (Somogyi 1977; Minelli et al. 1995; Tamas and Szabadics 2004), guinea pigs (Gulyas et al. 1993), cats (Fairen and Valverde 1980; Fariñas and DeFelipe 1991), rabbits (Muller-Paschinger et al. 1983), mice (Chiu et al. 2002), ferrets (Krimer and Goldman-Rakic 2001), monkeys (Somogyi et al. 1982, 1983; DeFelipe et al. 1985), and humans (Kisvarday et al. 1986; DeFelipe 1999; Lewis et al. 2005). However, it has become increasingly clear that inhibitory inputs to the AIS of pyramidal cells are not homogeneous across species, cortical regions, layers, or neuronal populations. In addition to occasional synapses from other types of interneurons (e.g., Gonchar et al. 2002), the single AIS of pyramidal cells may be innervated by one or a few chandelier cells (reviewed in DeFelipe 1999). Moreover, the number of synaptic inputs to the AIS differs as a function of age, location, and the projection target of the pyramidal cells (DeFelipe et al. 1985; Fariñas and DeFelipe 1991; Cruz et al. 2003). Chandelier cells are chemically heterogeneous and it has been shown that they express different combinations of substances in distinct layers and species, including the GABA transporter GAT-1; the calcium-binding proteins parvalbumin (PV) and calbindin D-28k; the peptide corticotrophin releasing factor; and the polysialylated form of the neural cell adhesion molecule (DeFelipe et al. 1989; Lewis et al. 1989; Lewis and Lund 1990; Schmidt et al. 1993; Conde et al. 1994; del Rio and DeFelipe 1994; Woo et al. 1998; DeFelipe 1999; Melchitzky et al. 1999; Arellano et al. 2004). Nevertheless, no systematic studies on the distribution and the density of Ch-terminals in the various cortical areas of the human neocortex have been performed.
In the present study, we have used GAT-1 immunocytochemistry to quantify the density of Ch-terminals because GAT-1–immuoreactive (-ir) Ch-terminals are easy to distinguish from other punctate terminal-like labeled structures in the neuropil (DeFelipe and Gonzalez-Albo 1998). We have examined the distribution of Ch-terminals as well as the density of GAT-1-ir Ch-terminals with respect to the total neuron density in each layer. The results reveal that there are significant differences in the distribution and density of GAT-1-ir Ch-terminals between the different areas and layers of the human neocortex.
|
Materials and Methods |
|---|
|
TopAbstractIntroductionMaterials and MethodsResultsDiscussionReferences |
|---|
In this study, we have used human autopsy brain tissue obtained 2–3 h post-mortem (kindly supplied by Dr R. Alcaraz, Forensic Pathology Service, Basque Institute of Legal Medicine, Bilbao, Spain), from 3 normal males who died in traffic accidents (M1, M7, and M8 aged 23, 49, and 69 years, respectively). The brain tissue was cut into 1.5-cm-thick coronal slices and initially fixed by immersion for 24 h in 4% paraformaldehyde diluted in 0.1 M pH 7.4 phosphate buffer (PB). Thereafter, small blocks of neocortical tissue were selected and postfixed for 1–2 days in the same fixative. The tissue was obtained from the somatosensory (areas 1 and 3b), visual (areas 17 and 18), motor (area 4), associative frontal (dorsolateral [areas 9, 10, 45, 46] and orbitary [areas 11, 12, 13, 14, 47]), associative temporal (areas 20, 21, 22, and 38), and limbic cingulate (areas 24, 32) neocortical areas. Blocks from the different Brodmann's areas of the cortex were selected from each brain according to their surface anatomy, using the patterns of the gyri and sulci. The identification of each cortical area was later confirmed by analyzing the distinctive cytoarchitectonic features of Nissl-stained sections.
After fixation, all the specimens were immersed in graded sucrose solutions and they were stored in a cryoprotectant solution at –20 °C. Serial sections (100 µm) of the cortical tissue were obtained using a vibratome, and the sections from each region and case were batch processed for immunocytochemical staining. The sections immediately adjacent to those stained immunocytochemically were Nissl stained in order to identify the cortical areas and the laminar boundaries.
Immunostaining
Sections were first treated for 30 min with a solution of 0.5% hydrogen peroxide and 50% ethanol in PB to inactivate the endogenous peroxidase activity. Subsequently, the sections were rinsed in PB and preincubated for 1 h at room temperature in a stock solution containing 3% normal goat or horse serum (Vector Laboratories, Burlingame, CA) in PB with Triton X-100 0.25%. Thereafter, the sections were incubated for 48 h at 4 °C in the same stock solution containing rabbit-anti-GAT-1 antiserum (1:500; Chemicon, Temecula, CA) or mouse-anti-neuron–specific nuclear protein (Neu-N) antibodies (1:4000; Chemicon). The sections were washed in PB, incubated in horse-anti-mouse or goat-anti-rabbit biotinylated secondary antibodies (1:200; Vector), and processed using the Vectastain ABC immunoperoxidase kit (Vector). Antibody labeling was visualized with 0.05% 3,3'-diaminobenzidine tetrahydrochloride (Sigma, St Louis, MO) and 0.01% hydrogen peroxide. The sections were rinsed in PB, mounted on glass slides, dehydrated, cleared with xylene, and coverslipped. Controls were included in all the immunocytochemical procedures, either by replacing the primary antibody with preimmune goat or horse serum in some sections, omitting the secondary antibody, or replacing the secondary antibody with an inappropriate secondary antibody (i.e., an antibody directed against another species). No significant immunolabeling was detected under these control conditions.
Quantification and Statistical Analysis
A BX51 Olympus microscope equipped with a motorized stage and a DP70 digital camera, and the Neurolucida package (MicroBrightField, Williston, VT) were used to plot all GAT-1-ir Ch-terminals visualized at a final magnification of x400, in 3 randomly selected radial strips. Adjacent Neu-N–immunostained sections were used to trace the contour lines corresponding to the individual cortical layers within each strip. The density of GAT-1-ir Ch-terminals in each cortical layer was estimated by dividing the number of GAT-1-ir Ch-terminals by the surface area of each layer in the cortical strip.
With the aid of the Neurolucida software (MicroBrightField Inc., Version 6.0, Williston) and a x4 objective, we first defined a 1-mm-wide strip across the cortex in Neu-N–immunostained sections from each cortical area and case, each of which extended from the pial surface to the white matter. We divided each strip into 1-mm-wide rectangles (counting fields), which corresponded to the radial extent of each cortical layer. The contours of these fields were then superimposed onto video images from adjacent GAT-1–immunostained sections in order to count Ch-terminals on the computer screen. The Neurolucida package permits the complete surface of the previously defined counting fields to be scanned (x40 objective), with successive and nonoverlapping frames (17 250 µm2). All Ch-terminals throughout the entire thickness of the section were counted within an unbiased counting frame (Gundersen 1977). Ch-terminals touching the exclusion lines were not counted.
The neuronal density was estimated stereologically in each cortical area and layer by counting the nuclei in 30-µm-thick randomly selected optical dissectors of Neu-N–immunostained sections using a x100 oil-immersion objective (West and Gundersen 1990). A minimum of 30 optical dissectors per layer and cortical area were studied using a motorized stage and the Olympus Cast grid system (Denmark).
We applied a statistical factorial model that was designed with nested multiple comparisons of 4 factors, 2 fixed (layer and area) and 2 random (human and pseudorepliques), each measurement made in every layer, cortical area, and case. In this model we excluded either layer IV when examining differences between the areas or areas 4 and 24 (agranular areas) to detect differences between the layers. The SAS system 8v (SAS Institute Inc. Cary, NC) was used in this analysis. One-way analysis of variance with T3 Dunnet post hoc comparison was then performed with the SPSS statistical package software (SPSS Inc., Chicago, IL) in order to study the differences between the layers and areas. Spearman's tests were used to study the possible correlations.
To generate the figures, light microscopic images were captured using a digital camera (Olympus DP50) attached to an Olympus light microscope, and Adobe Photoshop 7.0 software was used to generate the figure plates (Adobe Systems Inc., San Jose, CA).
|
Results |
|---|
|
TopAbstractIntroductionMaterials and MethodsResultsDiscussionReferences |
|---|
In the human cerebral cortex, GAT-1 immunocytochemistry labels numerous terminal-like puncta in the neuropil and around unstained cell bodies throughout cortical layers I–VI (Figs 1 and 2). However, as described previously the elements that are most intensely labeled are the Ch-terminals (DeFelipe and González-Albo 1998). GAT-1-ir Ch-terminals were found in all cortical areas but by plotting their distribution it became apparent that there were dramatic differences between each cortical area and layer (Figs 3 and 4).
|
|
|
|
Density of GAT-1-ir Ch-Terminals
The global density of GAT-1-ir Ch-terminals was compared between each individual and it was seen to be highest in the tissue from M1 followed by that from M7. The lowest density of GAT-1-ir Ch-terminals was observed in the cortical tissue from the individual M8 (Fig. 5). However, the differences in the density of GAT-1-ir Ch-terminals were not statistically significant either between subjects or between replicates (the different measurements made in each layer, cortical area, and case). Nevertheless, there were clear differences in the mean density of GAT-1-ir Ch-terminals between different cortical areas and layers (P < 0.0001, see below). For this reason, we will present the data from both each individual case and the averages of the values obtained in the 3 cases.
|
When the densities observed in the 3 cases were averaged, there were clear differences in the mean density of GAT-1-ir Ch-terminals between different cortical areas (P < 0.0001, Fig. 6A). In general, the different cortical areas analyzed could be divided into 3 main groups according to the density of GAT-1-ir Ch-terminals. Group I contained the lowest density of GAT-1-ir Ch-terminals (mean ± standard error [SE]: 39.23 ± 2.84), and included the primary and secondary sensory areas, both visual areas 17 and 18 and somatosensory areas 3b and 1. In group II, the motor area 4 and associative frontolateral areas 45 and 46 displayed intermediate densities (80.15 ± 5.80). In contrast, group III displayed the highest mean density (124.66 ± 3.43) and it comprised the associative frontolateral areas 9 and 10, the frontal orbitary areas 11, 12, 13, 14, and 47, the associative temporal areas 20, 21, 22, and 38, and cingulate areas 24 and 32. No significant differences were found in the density of the GAT-1-ir Ch-terminals between individual layers or in the mean values of cortical areas within each group (Table 1). However, all the cortical areas of group I showed significant differences in the density of these terminals when compared with cortical areas in group III (Table 1). Only certain areas of group II showed significant differences in the density of GAT-1-ir Ch-terminals with the areas included in group I or III (Table 1).
|
|
Laminar Distribution of GAT-1-ir Ch-Terminals
When the data from all the cortical areas were averaged, each of the 3 brains showed a similar laminar distribution of GAT-1-ir Ch-terminals (Fig. 6B). The highest density of GAT-1-ir Ch-terminals corresponded to layer II (mean ± SE; 188.08 ± 7.34), which was significantly greater than that in the other layers (P < 0.0001). Layer III displayed an intermediate density of Ch-terminals (119.28 ± 5.28), significantly different to all layers except layer VI (P < 0.01). Finally, the lowest density of Ch-terminals was found in layers IV and V (80.43 ± 4.86 and 94.80 ± 4.66, respectively). Significant differences were found between the mean density of GAT-1-ir Ch-terminals in layers IV (P < 0.001) and V (P < 0.05) with that in other layers except layers V and IV, respectively. Finally, in layer VI the density of Ch-terminals (117.89 ± 5.03) was significantly different from that in all the other layers except that in layer III (P < 0.05).
The laminar distribution of GAT-1-ir Ch-terminals in sensory, motor, frontolateral associative, temporal associative, and cingulate areas is shown in Figures 3, 4, 7, and 8. Note that the distribution of these terminals is fairly similar in the 3 brains analyzed (Figs 7 and 8). The significance of the comparisons between the different layers across the different areas analyzed is illustrated in Table 1. In general, when significant differences were observed in the density of GAT-ir Ch-terminals between areas, they were mostly due to significant differences in layers III and VI. Layer II presented a homogeneously high density of GAT-1-ir Ch-terminals with no significant differences between most cortical areas. In contrast, the density of terminals in layer II of areas 1 and 18 was significantly lower when compared with most cortical areas of group III. In most areas other than the temporal lobe, a tendency toward a lower density of GAT-1-ir Ch-terminals was observed in layers IV and V, although the differences between areas did not generally reach statistical significance.
|
|
Correlation between the Density of GAT-1-ir Ch-Terminals and that of Neu-N-ir Neurons
In an attempt to detect possible correlations between the density of Neu-N-ir neurons and the number of GAT-ir Ch-terminals, we compared these parameters in 6 representative cortical areas: the sensory areas 17 and 18, motor area 4, associative areas 9 and 21, and cingulate area 24 (Figs 7–9). When these variables were analyzed in individual cortical layers from distinct cytoarchitectonic areas, an inverse correlation was found in layer III (Spearman's rho –0.664, P = 0.03). Thus, in areas with a higher neuronal density in layer III (i.e., areas 17 and 18) there was a lower density of GAT-1-ir Ch-terminals (Figs 7–9). Likewise, a similar trend was found in layers II and IV but this did not reach statistical significance (Spearman's rho –0.457 P = 0.56 and Spearman's rho –0.493 P = 0.62, respectively). In contrast, the number of GAT-ir Ch-terminals was not correlated with neuronal density in layers V and VI.
|
When neuronal density and the density of GAT-ir Ch-terminals were analyzed in the cortical layers of each individual cytoarchitectonic area, a direct correlation was found in areas 4, 9, 17, and 24. As such, the higher density of GAT-1-ir Ch-terminals was associated with a higher density of neurons in the layers of these areas (Spearman's rho for areas 4, 9, 17, 24 = 0.83**, 0.65**, 0.68**, 0.53*; *P < 0.05, **P < 0.01).
|
Discussion |
|---|
|
TopAbstractIntroductionMaterials and MethodsResultsDiscussionReferences |
|---|
Through studying GAT-1 immunohistochemistry, we have been able to quantify the density and distribution of Ch-terminals in different areas and layers of the human neocortex. This analysis has revealed both similarities and differences between distinct cytoarchitectonic areas and cortical layers. Thus, we found that the distribution of Ch-terminals is not homogeneous in the cortex and we consider that these differences are probably related to the different functional attributes of the cortical region or layer examined.
Variation in the Density of Ch-Terminals between Individuals
In this study, we found that the global density of GAT-1-ir Ch-terminals decreased with age. Indeed, there was a 15% decrease in the 69-year-old individual when compared with the tissue obtained from the 23 year old. However, this difference was not statistically significant and because we only analyzed one individual of each age, the differences could merely be due to interindividual variability. Thus, it is clear that further studies on tissue from more subjects will be necessary to verify the age-related decline in the density of GAT-1-ir Ch-terminals in the human neocortex. Nevertheless, these results are consistent with the age-related decline in GAT-1-ir Ch-terminals reported in layer III of the monkey cortex (Cruz et al. 2003). Such a decline does not seem to represent an age-dependent decrease in the number of neurons. Neither neuronal density (Pakkenberg et al. 2003) nor the density of PV-ir cell somata (including chandelier cells; Bu et al. 2003) have been seen to change as a function of age in the human neocortex. Thus, age-related axonal retraction by chandelier cells and/or a decrease of GAT-1 expression or antigenicity at Ch-terminals with age may well account for the current observations. However, because there are relatively few chandelier cells a loss of some these may pass unnoticed when the whole population of neurons is considered in stereological studies. It will be necessary to examine the pyramidal cell AISs by electron microscopy to better define the processes involved in this loss of GAT-1–labeled terminals.
Variation in the Density of GAT-1-ir Ch-Terminals between Areas
There were significant differences in the density of GAT-ir Ch-terminals between the distinct areas of the human neocortex analyzed, suggesting a regional specialization of the inhibitory circuits in which they are involved. In the 3 brains analyzed, the primary and secondary sensory areas (areas 17, 18, 3b, and 1) displayed the lowest density of GAT-1-ir Ch-terminals, the motor (area 4) and associative frontolateral areas 45 and 46 displayed intermediate values, whereas the frontolateral areas 9 and 10, the frontal orbitary areas 11, 12, 13, 14, and 47, the temporal areas 20, 21, 22, and 38, and the cingulate areas 24 and 32 contained the highest mean density of GAT-1-ir Ch-terminals. Although detailed studies of the density and distribution of Ch-terminals have not been performed previously in the human neocortex, these results are consistent with observations that there is generally a higher density of Ch-terminals in high-order association areas than in primary sensory areas in the monkey (Lewis et al. 1989; Akil and Lewis 1992; Conde et al. 1996; Elston and Gonzalez-Albo 2003). Furthermore, the results are consistent with those showing that double bouquet cells, another important component of cortical GABAergic circuits, are not homogeneously distributed throughout the neocortex but that they also display rather dramatic differences in their density between areas (Yáñez et al. 2005). Previous electron microscopy and tract tracing studies (Fariñas and DeFelipe 1991), as well as the analysis of Golgi-stained material (Lewis and Lund 1990) have shown that Ch-terminals are present in the cat and monkey visual cortex. However, it is difficult to obtain an idea about the distribution of Ch-terminals in electron microscope studies or in Golgi studies due to the inconsistency of the Golgi method and the relatively few AIS examined by electron microscopy. Therefore, the scarcity of GAT-1-ir Ch-terminals in the primary visual cortex observed here, as in other sensory areas, is best compared with other cortical areas examined using the same methodology. There are several possible explanations for the differences in the density of GAT-1-ir Ch-terminals between areas. Because not all pyramidal cells are necessarily innervated by Ch-terminals (e.g., see Fariñas and DeFelipe 1991), a smaller proportion of the pyramidal cells in sensory areas could be innervated by Ch-terminals than in associative areas. Alternatively, there may be less GAT-1 protein in Ch-terminals in sensory areas implying that many terminals in these regions contain quantities of protein that are below the levels of detection for the immunocytochemical methods used. Furthermore, it is possible that at least some Ch-terminals in sensory cortical areas could use other types of GABA transporters.
Laminar Distribution of GAT-ir Ch-Terminals in the Cerebral Cortex
The present results also indicate that there are differences in the density of GAT-1-ir Ch-terminals between the distinct cortical layers. The highest density of GAT-1-ir Ch-terminals was observed in layer II followed by layers III, V, VI, and IV. Previous studies have shown that there are differences in the density of synaptic terminals that contact the AIS of pyramidal cells located in different layers. For instance, in the monkey temporal and sensory-motor cortex, and in the cat visual cortex, the AIS of pyramidal neurons in layers II–III are more densely innervated by chandelier cell synapses than those in layers V and VI (Sloper and Powell 1979; DeFelipe et al. 1985; Fariñas and DeFelipe 1991; DeFelipe 1999). Because the pyramidal cells located in different layers project to different sites (Jones 1984; White 1989), the changes in the density of GAT-1-ir Ch-terminals observed between layers might be related to the laminar distribution of pyramidal cell populations projecting to particular sites.
In addition, it has been shown in the rat neocortex that postsynaptic GABAA receptors at the AIS of supragranular pyramidal cells are enriched with the 
2 subunit, whereas in infragranular layers the 3 subunit predominates (Fritschy et al. 1998). Thus, it is possible that chandelier cells exert their activity through different types of postsynaptic GABAA receptors depending on the cortical layer in which they are found. Finally, a direct correlation was observed between the density of GAT-1-ir Ch-terminals and neuronal density in areas 4, 9, 17, and 24. This was not the case in areas 18 and 21 where there was no correlation between GAT-1-ir Ch-terminals and neuronal density. Hence, there is a remarkable heterogeneity in the density and distribution of GAT-1-ir Ch-terminals, suggesting that chandelier cells contribute differentially to cortical circuits (anatomically and physiologically) according to the cortical area or layer in which they are situated.
|
Acknowledgments |
|---|
This work was supported by the Ministerio de Ciencia y Tecnología grants BFI 2003-01018 and BFU2006-03855 to A.M. and BFI 2003-02745 and BFU2006-13395 to J.F. We thank Laura Barrios (Department of Statistics, CTI, CSIC, Madrid, Spain) for her assistance in the statistical analysis). Conflict of Interest: None declared.
|
References |
|---|
|
TopAbstractIntroductionMaterials and MethodsResultsDiscussionReferences |
|---|
Akil M, Lewis DA. Postnatal development of parvalbumin immunoreactivity in axon terminals of basket and chandelier neurons in monkey neocortex. Prog Neuropsychopharmacol Biol Psychiatry (1992) 16:329–337.[CrossRef][Medline]
Arellano JI, Munoz A, Ballesteros-Yanez I, Sola RG, DeFelipe J. Histopathology and reorganization of chandelier cells in the human epileptic sclerotic hippocampus. Brain (2004) 127:45–64.
Bu J, Sathyendra V, Nagykery N, Geula C. Age-related changes in calbindin-D28k, calretinin, and parvalbumin-immunoreactive neurons in the human cerebral cortex. Exp Neurol (2003) 182:220–231.[CrossRef][Web of Science][Medline]
Buhl EH, Halasy K, Somogyi P. Diverse sources of hippocampal unitary inhibitory postsynaptic potentials and the number of synaptic release sites. Nature (1994) 368:823–828.[CrossRef][Medline]
Chiu CS, Jensen K, Sokolova I, Wang D, Li M, Deshpande P, Davidson N, Mody I, Quick MW, Quake SR, et al. Number, density, and surface/cytoplasmic distribution of GABA transporters at presynaptic structures of knock-in mice carrying GABA transporter subtype 1-green fluorescent protein fusions. J Neurosci (2002) 22:10251–10266.
Colbert CM, Johnston D. Axonal action-potential initiation and Na+ channel densities in the soma and axon initial segment of subicular pyramidal neurons. J Neurosci (1996) 16:6676–6686.
Conde F, Lund JS, Jacobowitz DM, Baimbridge KG, Lewis DA. Local circuit neurons immunoreactive for calretinin, calbindin D-28k or parvalbumin in monkey prefrontal cortex: distribution and morphology. J Comp Neurol (1994) 341:95–116.[CrossRef][Web of Science][Medline]
Conde F, Lund JS, Lewis DA. The hierarchical development of monkey visual cortical regions as revealed by the maturation of parvalbumin-immunoreactive neurons. Brain Res Dev Brain Res (1996) 96:261–276.[Medline]
Cruz DA, Eggan SM, Lewis DA. Postnatal development of pre- and postsynaptic GABA markers at chandelier cell connections with pyramidal neurons in monkey prefrontal cortex. J Comp Neurol (2003) 465:385–400.[CrossRef][Web of Science][Medline]
DeFelipe J. Chandelier cells and epilepsy. Brain (1999) 122. (Pt 10):1807–1822.
DeFelipe J, Gonzalez-Albo MC. Chandelier cell axons are immunoreactive for GAT-1 in the human neocortex. Neuroreport (1998) 9:467–470.[Web of Science][Medline]
DeFelipe J, Hendry SH, Jones EG. Visualization of chandelier cell axons by parvalbumin immunoreactivity in monkey cerebral cortex. Proc Natl Acad Sci USA (1989) 86:2093–2097.
DeFelipe J, Hendry SH, Jones EG, Schmechel D. Variability in the terminations of GABAergic chandelier cell axons on initial segments of pyramidal cell axons in the monkey sensory-motor cortex. J Comp Neurol (1985) 231:364–384.[CrossRef][Web of Science][Medline]
del Rio MR, DeFelipe J. A study of SMI 32-stained pyramidal cells, parvalbumin-immunoreactive chandelier cells, and presumptive thalamocortical axons in the human temporal neocortex. J Comp Neurol (1994) 342:389–408.[CrossRef][Web of Science][Medline]
Elston GN, Gonzalez-Albo MC. Parvalbumin-, calbindin-, and calretinin-immunoreactive neurons in the prefrontal cortex of the owl monkey (Aotus trivirgatus): a standardized quantitative comparison with sensory and motor areas. Brain Behav Evol (2003) 62:19–30.[CrossRef][Web of Science][Medline]
Fairen A, Valverde F. A specialized type of neuron in the visual cortex of cat: a Golgi and electron microscope study of chandelier cells. J Comp Neurol (1980) 194:761–779.[CrossRef][Web of Science][Medline]
Fariñas I, DeFelipe J. Patterns of synaptic input on corticocortical and corticothalamic cells in the cat visual cortex. II. The axon initial segment. J Comp Neurol (1991) 304:70–77.[CrossRef][Web of Science][Medline]
Freund TF, Martin KA, Smith AD, Somogyi P. Glutamate decarboxylase-immunoreactive terminals of Golgi-impregnated axoaxonic cells and of presumed basket cells in synaptic contact with pyramidal neurons of the cat's visual cortex. J Comp Neurol (1983) 221:263–278.[CrossRef][Web of Science][Medline]
Fritschy JM, Weinmann O, Wenzel A, Benke D. Synapse-specific localization of NMDA and GABA(A) receptor subunits revealed by antigen-retrieval immunohistochemistry. J Comp Neurol (1998) 390:194–210.[CrossRef][Web of Science][Medline]
Gonchar Y, Turney S, Price JL, Burkhalter A. Axo-axonic synapses formed by somatostatin-expressing GABAergic neurons in rat and monkey visual cortex. J Comp Neurol (2002) 443:1–14.[CrossRef][Web of Science][Medline]
Gulyas AI, Miles R, Hajos N, Freund TF. Precision and variability in postsynaptic target selection of inhibitory cells in the hippocampal CA3 region. Eur J Neurosci (1993) 5:1729–1751.[CrossRef][Web of Science][Medline]
Gundersen HJG. Notes on the estimation of the numerical density of arbitrary profiles: the edge effect. J Microsc (1977) 111:219–223.[Web of Science]
Jones EG. Varieties and distribution of non-pyramidal cells in the somatic sensory cortex of the squirrel monkey. J Comp Neurol (1975) 160:205–267.[CrossRef][Web of Science][Medline]
Jones EG. Laminar distribution of cortical efferent cells. In: Cellular components of the cerebral cortex—Peters A, Jones EG, eds. (1984) New York: Plenum Press.
Kisvarday ZF, Adams CB, Smith AD. Synaptic connections of axo-axonic (chandelier) cells in human epileptic temporal cortex. Neuroscience (1986) 19:1179–1186.[CrossRef][Web of Science][Medline]
Krimer LS, Goldman-Rakic PS. Prefrontal microcircuits: membrane properties and excitatory input of local, medium, and wide arbor interneurons. J Neurosci (2001) 21:3788–3796.
Lewis DA, Foote SL, Cha CI. Corticotropin-releasing factor immunoreactivity in monkey neocortex: an immunohistochemical analysis. J Comp Neurol (1989) 290:599–613.[CrossRef][Web of Science][Medline]
Lewis DA, Hashimoto T, Volk DW. Cortical inhibitory neurons and schizophrenia. Nat Rev Neurosci (2005) 6:312–324.[CrossRef][Web of Science][Medline]
Lewis DA, Lund JS. Heterogeneity of chandelier neurons in monkey neocortex: corticotropin-releasing factor- and parvalbumin-immunoreactive populations. J Comp Neurol (1990) 293:599–615.[CrossRef][Web of Science][Medline]
Melchitzky DS, Sesack SR, Lewis DA. Parvalbumin-immunoreactive axon terminals in macaque monkey and human prefrontal cortex: laminar, regional, and target specificity of type I and type II synapses. J Comp Neurol (1999) 408:11–22.[CrossRef][Web of Science][Medline]
Miles R, Toth K, Gulyas AI, Hajos N, Freund TF. Differences between somatic and dendritic inhibition in the hippocampus. Neuron (1996) 16:815–823.[CrossRef][Web of Science][Medline]
Minelli A, Brecha NC, Karschin C, DeBiasi S, Conti F. GAT-1, a high-affinity GABA plasma membrane transporter, is localized to neurons and astroglia in the cerebral cortex. J Neurosci (1995) 15:7734–7746.[Abstract]
Muller-Paschinger IB, Tombol T, Petsche H. Chandelier neurons within the rabbits' cerebral cortex. A Golgi study. Anat Embryol (Berl) (1983) 166:149–154.[CrossRef][Medline]
Pakkenberg B, Pelvig D, Marner L, Bundgaard MJ, Gundersen HJ, Nyengaard JR, Regeur L. Aging and the human neocortex. Exp Gerontol (2003) 38:95–99.[CrossRef][Web of Science][Medline]
Peters A, Proskauer CC, Ribak CE. Chandelier cells in rat visual cortex. J Comp Neurol (1982) 206:397–416.[CrossRef][Web of Science][Medline]
Schmidt S, Braak E, Braak H. Parvalbumin-immunoreactive structures of the adult human entorhinal and transentorhinal region. Hippocampus (1993) 3:459–470.[CrossRef][Web of Science][Medline]
Sloper JJ, Powell TP. A study of the axon initial segment and proximal axon of neurons in the primate motor and somatic sensory cortices. Philos Trans R Soc Lond B Biol Sci (1979) 285:173–197.
Somogyi P. A specific ‘axo-axonal’ interneuron in the visual cortex of the rat. Brain Res (1977) 136:345–350.[CrossRef][Web of Science][Medline]
Somogyi P, Freund TF, Cowey A. The axo-axonic interneuron in the cerebral cortex of the rat, cat and monkey. Neuroscience (1982) 7:2577–2607.[CrossRef][Web of Science][Medline]
Somogyi P, Freund TF, Hodgson AJ, Somogyi J, Beroukas D, Chubb IW. Identified axo-axonic cells are immunoreactive for GABA in the hippocampus and visual cortex of the cat. Brain Res (1985) 332:143–149.[CrossRef][Web of Science][Medline]
Somogyi P, Nunzi MG, Gorio A, Smith AD. A new type of specific interneuron in the monkey hippocampus forming synapses exclusively with the axon initial segments of pyramidal cells. Brain Res (1983) 259:137–142.[CrossRef][Web of Science][Medline]
Stuart GJ, Sakmann B. Active propagation of somatic action potentials into neocortical pyramidal cell dendrites. Nature (1994) 367:69–72.[CrossRef][Medline]
Szentagothai J, Arbib MA. Conceptual models of neural organization. Neurosci Res Program Bull (1974) 12:305–510.[Medline]
Tamas G, Szabadics J. Summation of unitary IPSPs elicited by identified axo-axonic interneurons. Cereb Cortex (2004) 14:823–826.
West MJ, Gundersen HJ. Unbiased stereological estimation of the number of neurons in the human hippocampus. J Comp Neurol (1990) 296:1–22.[CrossRef][Web of Science][Medline]
White EL. Cortical Circuits: aynaptic organization of the cerebral cortex Structure, function and theory. (1989) Boston: Birkhäuser.
Williams S, Lacaille JC. GABAB receptor-mediated inhibitory postsynaptic potentials evoked by electrical stimulation and by glutamate stimulation of interneurons in stratum lacunosum-moleculare in hippocampal CA1 pyramidal cells in vitro. Synapse (1992) 11:249–258.[CrossRef][Web of Science][Medline]
Woo TU, Whitehead RE, Melchitzky DS, Lewis DA. A subclass of prefrontal gamma-aminobutyric acid axon terminals are selectively altered in schizophrenia. Proc Natl Acad Sci USA (1998) 95:5341–5346.
Yáñez IB, Muñoz A, Contreras J, González J, Rodríguez-Veiga E, DeFelipe J. Double bouquet cell in the human cerebral cortex and a comparison with other mammals. J Comp Neurol (2005) 486:344–360.[CrossRef][Web of Science][Medline]
CiteULike 
Connotea 
Del.icio.us What's this?
This article has been cited by other articles:
|
|
 |
|
  M.C. Inda, J. DeFelipe, and A. Munoz Morphology and Distribution of Chandelier Cell Axon Terminals in the Mouse Cerebral Cortex and Claustroamygdaloid Complex Cereb Cortex, January 1, 2009; 19(1): 41 - 54. [Abstract] [Full Text] [PDF]
|
|
| ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||