In: Changing Views of Cajal’s Neuron
Molecular and Behavioral Neuroscience,
Abstract: Computational anatomical studies suggest that specific clusters of projection neurons in the basal forebrain together with specific prefrontal and posterior cortical associational regions constitute distributed parts of functional parallel circuits. The predictable sequence of cell clusters consisting of various types of non-cholinergic cell populations in the basal forebrain suggests further subdivisions within these circuits. It is possible that similar to the parallel basal ganglia circuits (Alexander and Crutcher, 1990), large number of specialized channels and sub-channels exist within this triangular circuitry that permit parallel, multilevel processing concurrently. The location and size of the active modules may temporarily vary according to the prevalence of state-related diffuse ascending brain stem and specific telencephalic inputs. From this latter group of afferents, the prefrontal input may function as an external threshold control which allocates attentional resources via the basal forebrain to distributed cortical processes in a selective, self-regulatory fashion.
Ramon y Cajal is widely acclaimed as the major player in establishing the neuron doctrine, however, Cajal’s studies also were fundamental to the subsequent development of the concept of the modular organizational design of the brain. Although the first explicit statement about the modular arrangement of the neuropil, including some discussion on its possible functional significance, was made by Scheibel and Scheibel in 1958 in their description of the brainstem reticular formation, it is not difficult to see in Cajal’s superb illustrations the forerunners of modern concepts about integrative units. In his final summary (Cajal, 1935), he listed various types of systematic synaptic arrangements, like the glomeruli of the olfactory bulb and the cerebellum, which essentially correspond to modular substructures.
Ironically, Camillo Golgi’s idea of a nerve network appears as a valid attempt to deal with some of the holistic aspect of brain function (Shepherd, 1991). However, he could not conceive how behavior could be the product of the individual actions of nerve cells acting independently. Rather he envisioned the nervous system as a diffuse network with extensive interaction of its elements (Golgi, Nobel Lecture, 1967). In contrast to the diffuse net of axon collaterals of Purkinje cells according to Golgi, Cajal demonstrated that terminals of recurrent collaterals of Purkinje cells end on the dendritic trunks of neighboring Purkinje cells: “This fact showed therefore, as we had admitted formerly, that the recurrent collaterals serve to associate in a dynamic ensemble the neurons of the same kind from the same area of the gray matter” (Cajal, Nobel Lecture, p. 229, 1967). He also states in the Histology (pp. 93-127, vol. 1, 1995): “Therefore, we should not concern ourselves with the disposition of a single neuron, but rather with chains of neurons, which may be quite long and act in concert as a functional whole. Thus, no reflex chain of neurons is entirely linear; each chain shares at least some neurons in common with its neighbors, and even with more remote chains in the various neural centers”.
Modular organization at various levels of the neuraxis
Numerous elements of the module principle were implicit in Cajal’s work on the architecture of the spinal cord by showing the systemic orientation of terminal axon arborizations in the dorsal horn. He emphasized that collaterals from the ascending and descending main branches of the primary afferents, after their bifurcation in the dorsal funiculus, are issued to the gray matter not at random but at determined distances (see Figs. 209-211, Cajal, 1995).
Certain regularities in the architecture of the thalamic sensory relay nuclei are well known both in terms of axonal arborizations or cellular layering. Cajal observed and illustrated (Fig. 257, Cajal, 1995) the fact that the bushy terminal arborizations of the specific sensory (lemniscal) afferents give rise to a quasi-concentric lamination in the VPL of the thalamus. Figure 1A is a reproduction of his drawing from the Histology (Fig. 548, Cajal, 1995). An explanation for the systematic discontinuity in the architectural organization of the ventrobasal complex is given some seventy years later in the findings of Woolsey and van der Loos (1970) by showing the faithful reproduction of the whisker pad in the thalamus (Figs. 1B and 1C).
The idea of columnar organization of the neocortex (A more detailed discussion of the columnar-modular organization of the cortex is beyond the scope of this manuscript and the reader is referred to a recent review by Rockland (1998)) is part of the more general hypothesis of the modular organization of the nervous system, a widely documented principle of design for both vertebrate and invertebrate brains. Some of the main characteristics of the modular principle are summarized in a recent review by Liese (1990) and in the superb book on the anatomy and functions of cerebral cortex by Mountcastle (1998). The following features can be enlisted: 1) modules are local networks of cells in any regions of the CNS containing one or more electrically compact circuits active in a particular behavioral function; 2) modules are dynamic entities: modules, repeated iteratively within each larger structure, function independently, or they may act together when combined in groups whose composition may vary from time to time; 3) modules may differ in cell type and number in internal and external connectivity and in the mode of neuronal processing between different large entities; but within any single entity, like the neocortex, they have a basic similarity of internal design and operation, ranging in diameter from about 150-1000 μm; 4) the neighborhood relations between connected subsets of modules in different entities result in nested systems that serve distributed functions. A cortical area defined in classical cytoarchitectural terms may belong to more than one and sometimes to several such systems; 5) modules may develop through ontogenesis and phylogenesis by duplication of homebox genes (Almann and Kaas, 1998); 6) modules can be anatomically differentiable from the surrounding tissue. For example, in the striatum the striosome-matrix compartments can be defined using AChE histochemical reaction (Graybiel and Ragsdale, 1978) or application of immunocytochemical and autoradiographic methods for the presence of various transmitters and receptors (Gerfen, 1985). AChE–staining also delineates patches in the superior colliculus that represent special sites where information from various sensory modalities can be integrated (Chevalier and Mana, 2000). In certain brain stem regions, computational anatomical methods helped to reveal a clustered, putatively modular organization, defined by patterns of connectivity (Malmierca et al., 1998; Leergaard et al, 2000).
When multiple cell types are considered, the spatial variation of the relative density of different cell types is suggestive of the sites of integrative operations in the brain because these are areas where neurons would most likely share input and interact via local axonal connections. Utilizing novel computational methods (Nadasdy and Zaborszky, 2001), we investigated whether or not the imposition of numerical and spatial constraints may help to define hidden organizational patterns in the basal forebrain. Clustered structures can be revealed in a distributed population of a single cell type or can represent the topological association pattern of different chemically or hodologically defined cell populations. Careful reading of the structure of cellular segregation and association could contribute to a better understanding of how architectural features determine information processing.
In summary, based upon neuronal connectivity, dendritic and axonal arborization pattern, or cellular density distributions, networks can be disassembled into distinct pieces (units) of characteristic internal connectivity that are arranged into larger structures by repetition of similar architectural units. Modules are building blocks of the neural tissue that contain the necessary minimal pool of neurons to perform serial and parallel operations in the brain.
In a brief account, Cajal (1995) compared the large neurons, deep to the anterior perforate substance, to motor cells, based upon their size, abundant Nissl substance as well as rather large amounts of yellowish pigment (p. 598, vol II, Histology, 1995). Cajal, however, did not include these scattered large cells into a single system and did not realize their continuity with dispersed large neurons within the diagonal band of Broca as depicted in his Golgi specimens (Fig. 505, Cajal, 1995). Cajal thought that the large neurons underneath the globus pallidus are a special part of the corpus striatum. Interestingly, he understood that the scattered cells in the septum are associated with the hippocampus and cingulate cortex. Cajal also noted the overwhelming dorso-ventral orientation of the dendrites in the medial septum. However, the use of sophisticated computer reconstruction methods revealed hundred years later that dendrites of basal forebrain neurons show a systematic, regionally selective orientation (Zaborszky et al., 2002).
It was Brockhaus in the early forties (1942), who rediscovered what Kolliker (1896) had already suggested half a century earlier that the aggregate, large neurons from the septal pole rostrally to the subthalamic nucleus caudally, embedded in the ill-defined regions of the substantia innominata, belonged to one system. This concept was confirmed later by histo-, immunocytochemical and connectional studies of the late seventies and early eighties by Butcher, Mesulam, Saper Sofroniew and their colleagues (Sofroniew et al., 1982; Armstrong et al., 1983; Mesulam et al., 1983; Saper, 1984; Butcher, 1995). Recent interest in basal forebrain research was prompted by discoveries showing that a specific population of neurons in this region, namely those that use acetylcholine (ACh) as their transmitter and project to the cerebral cortex, are seriously compromised in Alzheimer's disease (Price et al., 1986). However, cholinergic corticopetal neurons represent only a fraction of the total cell population in these forebrain areas, which also contain various non-cholinergic neurons, including GABAergic and possibly glutamatergic corticopetal cells (Jones and Muhlethaler, 1999; Zaborszky et al., 1999).
Calbindin (CB), calretinin (CR) and parvalbumin (PV) are different calcium-binding proteins that are colocalized in different, non-overlapping populations of non-cholinergic neurons in the basal forebrain of rodents. When cholinergic and these three chemically identified neuronal populations are studied separately, each cell population shows a characteristic distribution pattern. Due to the lack of adequate multiple labeling techniques and the fact that differences between cases and different cell types are difficult to grasp in individual 2D histological sections, previous studies dealt only with the organization of basal forebrain subregions and failed to recognize that a systematic spatial relationship might exist among these cell populations along the entire extent of the basal forebrain (Zaborszky et al., 1986; Jakab and Leranth, 1995; Kiss et al., 1997).
We have shown in a recent publication (Zaborszky et al., 1999, Fig. 5 and Zaborszky, Buhl, Pobalashingham, Somogyi, Bjaalie and Nadasdy, in preparation) that cholinergic (CH) and the three calcium-binding containing neuronal populations construct large-scale cell sheets or bands that seem to be twisted and attached to each other in a complicated fashion. However, a closer observation suggests that the four cell sheets display a pattern of association in the entire basal forebrain. By constructing volumetric databases of local cell counts for the four major cell populations in the basal forebrain, it is apparent that the density of cells in each cell populations shows regional variation. One can delineate subspaces where cell densities are significantly higher from an average cell density. Figure 4A shows a scatter-plot distribution of CH and PV cells (red and green dots) including high density locations of either cell populations (large red and green symbols). Although using a relatively low threshold of high pass filtering on the density data (³ 5 cells per 250 x 250 x 50 μm voxel size) these clusters seem to be diffusely distributed. When using a relatively high thresholding (d³15 cells/unit space) as in Figure 4A, the clustering of CH and PV cell populations deviate from randomness. As can be seen, high density CH and PV clusters often share a narrow space. For further analyzing the spatial relationships among the four cell populations, we first determined locations where pairs of the four cell populations overlap and then combined these separate renderings into one scheme. The model in Figure 4B displays a combined rendering of voxels where CH/PV (green) CH/CR (yellow) and CH/CB (dark blue) cell populations show overlapping distributions at a given threshold density. Since often more than two cell populations occupy the same space, to avoid misinterpreting topological relationships among multiple cell populations, several independent methods had to be used. Disregarding local details, Figure 4B suggests that the large-scale relationships among the four cell populations arise from a twisted banded pattern along the entire basal forebrain. The similarity of the large-scale arrangement of the three non-cholinergic projection bands of Figure 3I and the systematic twisted banded pattern of the three calcium-binding neuronal populations relative to cholinergic neurons shown in Figure 4B is striking. The model in Figure 4C applies another algorithm on the same database. This so-called iso-relational surface rendering technique imposes a combination of density and spatial relational constraints (Nadasdy and Zaborszky, 2001). In Figure 4C each differently colored surfaces rendered around regions where the density of both the cholinergic and one from the other three cell populations met two criteria: (1) density is at least five for each cell type within the voxel dimension (250 x 250 x 50 μm) and (2) the ratio of cholinergic to the other cell type counts is 0.5 or higher. For example, the voxels covered by green surfaces contain at least twice as many parvalbumin as cholinergic neurons. Similarly, yellow surfaces cover voxels where the density of both calretinin and cholinergic cells are >5 in each voxel and the ratio of calretinin/cholinergic cells is at least 0.5. Finally blue surfaces highlight the iso-relational distributions of cholinergic and calbindin cells. Merging the three pairwise iso-relational surfaces into one scheme suggests that the gross cholinergic cell band can be parcelled into several smaller clusters or larger amalgamations, where cholinergic cells are mixed with the other three cell types in a specific fashion. Since, CR, CB and PV have been found at least in a subpopulation of corticopetal neurons (Zaborszky et al., 1999; Gritti et al., 2001) it is likely that each non-cholinergic projection band from Figure 3I may consist of several transmitter-specific ‘sub-bands’. A similar global pattern emerges when comparing similar types of renderings from different brains, suggesting that the configuration of the iso-relational surfaces is not by chance and that the high density clusters in the individual cell populations may correspond to the zones where the different cell bands overlap with each other resulting in mixed clusters (Zaborszkyet al., in preparation). The location of these mixed clusters can be predicted based upon the twisted pattern of ‘macro’ (topographically organized projection neurons) and ‘micro’ bands (the various chemically specified cell groups within a projection channel). Figure 5 shows the possible arrangement of the three projection bands from Figure 3I. It is also indicated in this scheme that each projection band may contain several transmitter-specific sub-bands.
A systematic analysis of all voxels from a volumetric database that contain all four cell markers suggests that cholinergic neurons are admixed with the three other non-cholinergic cell populations in a large number of combinations. However, the composition of these mixed clusters is predictable and characteristic of the location (Zaborszky et al., 2002; Zaborszky, Buhl, Pobalashingham, Somogyi, Bjaalie and Nadasdy, in preparation). In spite of the high percentage of mixed high-density voxels, a substantial proportion (23-45%) of the high-density voxels for each cell types remains ‘lonely’; i.e., contain only one marker above the set threshold density level. The consequence of this arrangement is that for each cell type and structure a characteristic ‘signature’ combination of overlapping and lonely voxels exists. Unfortunately, at present, it is unknown how signaling factors along the longitudinal and transverse domains of the forebrain proliferative ‘protomap’ regulate gene expression and migration pattern (Rakic, 1995; and this volume; Rubinstein et al., 1998) as to establish the observed sequence of mixed clusters. It is also unknown how these specific clusters may establish connection during ontogenesis with specified cortical locations as proposed below.
It is interesting to note in this context that stimulations in spatially different locations in the basal forebrain result in different modulation of ongoing cortical activity (Jimenez-Capdeville et al., 1997). For example, activation of some basal forebrain sites provoked an intense discharge of many neurons in the vicinity of the cortical recording electrode and the same stimulus site provoked release of large amount of ACh in the cortex. Stimulation of other sites produced strong inhibition and no increase in cortical ACh release. Jimenez-Capdeville suggested that the immediate excitatory response was due to a disinhibition of the pyramidal cells by activation of the basalo-cortical GABAergic projection terminating on cortical interneurons as suggested earlier by Freund and his colleagues (Freund and Meskenaite, 1992). The excitation was then maintained by the slower onset excitatory ACh action. On the other hand, according to this study, the silencing of the cortical activity at the end of the basal forebrain stimulation is due to the activation of putative glutamatergic basalo-cortical neurons that may preferentially contact certain classes of cortical neurons, leading to intracortical inhibition. The authors also suggested without any experimental proof that basal forebrain sites generating inhibition of cortical neuronal activity are surrounded by basal forebrain regions that activated the cortex and provoked release of ACh. We hypothesize that these different responses could relate to the differential composition of clusters in the basal forebrain. For example, one can expect that stimulation electrodes located in predominantly PV/CH mixed regions would result in different cortical responses from that caused by stimulating locations in regions populated primarily with CB and CR cells that may contain glutamate (Gritti et al., 2001). This postulated organization could ensure that a combination of a relatively few types of basal forebrain neurons may generate a large spectra of differential tuning in various cortical areas.
Input-output relations of cholinergic clusters
Using a double strategy of recording the location of putative contact sites between identified axons and cholinergic profiles as well as identifying the presence of synapses in representative cases under the electron microscope, one can get a fairly good idea about the extent of potential transmitter interactions in the basal forebrain. Although ascending brainstem noradrenergic and dopaminergic axons contact cholinergic neurons in extensive portions of the basal forebrain, the majority of telencephalic afferents (cortical, amygdaloid, striatal) appear to have a preferential distribution in subregions of the basal forebrain (Zaborszky et al., 1991; Zaborszky and Duque, 2000). The prefrontal cortex innervates exclusively non-cholinergic neurons in the basal forebrain, including parvalbumin-containing cell populations (Zaborszky et al., 1997), suggesting some selectivity in the innervation pattern of various neurons. A partial 3D reconstruction of the dendrites of several hundred cholinergic neurons suggests a tendency of iso-orientation of dendrites within a given cholinergic cell cluster (Zaborszky et al., 2002). Since many of the afferent axons also show regionally specific orientation, it is likely that cholinergic cell clusters in each major subdivision of the basal forebrain can sample a unique combination of afferents.
Cortical release of ACh from the basal forebrain appears to be essential for the enhancement of sensory evoked responses and cortical reorganization of the body surface representations (Juliano et al., 1991; Metherate and Ashe, 1991; Killgard and Mersenich, 1998; Rasmusson, 2000). Experiments with basal forebrain stimulations and measuring in vivo cortical release of ACh are somewhat equivocal in determining whether the basal forebrain contributes selectively to sensory processing or if the released ACh in the cortex is only part of a general cortical arousal mechanism as suggested by Sarter and Bruno (1997). Our anatomical and preliminary electrophysiological studies (Golmayo et al., 1999), however, raises the possibility that the basal forebrain may participate in selective sensory processing via its input from the prefrontal cortex and its output to distributed, functionally-related cortical areas. This notion is diagrammatically visualized in Figure 6 by showing several specific cortico-prefrontal-basal forebrain-cortical circuits. This hypothesis is based upon a) the strict topography in cortico-prefrontal (Zaborszky and Csordas, in preparation), b) prefrontal-basal forebrain (Sesack et al, 1989; Zaborszky et al., 1997) c) basal forebrain-sensory projections (Zaborszky and Raza, in preparation), and d) the close spatial relationship among basal forebrain cells that project to both prefrontal and posterior association cortex (Csordas and Zaborszky, 2001).
Many neurobehavioral studies have indicated the involvement of the prefrontal cortex in higher cognitive functions such as working memory and attention (Goldman-Rakic, 1987; Fuster, 1989; Miller and Cohen, 2001). PET imaging studies in humans (Paus et al., 1997) and orientation deficits in rats and monkeys after lesions of the basal forebrain (Whisaw et al., 1985; Voytko et al., 1994), together with our preliminary electrophysiological results (Golmayo et al., 1999), suggest that the role played by the prefrontal cortex in these cognitive operations could be due in part to its close relation with the basal forebrain in modulating specific sensory responses.
Imaging studies revealed that combinations of multiple activated cortical fields in prefrontal and associational cortical areas are reproducible associated with specific cognitive components of mental operations (Roland, 1994; Raichle and Posner, 1997; Cabeza and Nyberg, 1997; Duncan and Owen, 2000). It seems to be that for each type of brain operation there is a working memory in the dorsolateral prefrontal-anterior cingulate regions that is responsible for the recruitment and maintenace of specific cortical fields via controlling selective attention (Roland, 1994; Desimone and Duncan, 1995; de Fockert et al., 2001). While the cortical network of attention is partially known (Posner and Dehaene, 1994; Raichle and Posner, 1997), the subcortical structures responsible for the necessary cortical coactivation and tuning are less well understood. From various physiological and limited imaging studies, it is likely that, the pulvinar (LaBerge, 1995), the intralaminar nuclei, the mesopontine tegmentum (Kinomura et al., 1996) and the basal forebrain (Voytko, 1994) participate in this function. The proposed re-entrant circuitry of Figure 6 could explain the timeline of attention-related evoked potentials in prefrontal and sensory cortical areas after sensory stimulations (see discussion of this issue on p. 360 in Zaborszky et al., 1999) and fits with the idea that selective attention, recruitment of processors, tuning, working memory, vigilance, strategy selection and planning represent an interrelated multicomponent system (Baddeley, 1995).
In light of the possible significance of fast cortical oscillations in attention, perception and consciousness (Crick and Koch, 1990; Singer and Gray, 1995; Singer, 1999; Steinmetz et al., 2000; Gray, 2000; Fries et al., 2001; Lumer et al., 1997), the 20-40 Hz membrane potential fluctuations elicited by basal forebrain stimulation in cortical pyramidal neurons (Metherate et al., 1992) are of particular interest. We hypothesize that pyramidal cells in selected cortical regions could start to oscillate at high frequency when specifically located basal forebrain cell clusters receive signals from the prefrontal cortex about the significance of the sensory stimulus within 100 msec after sensory stimulation. Due to the possibility that the basal forebrain receives topographically organized input from the prefrontal cortex and its output preferentially targets associational cortical routes, the basal forebrain is well positioned anatomically to coordinate cortical oscillations among widely separated cortical regions and capable of binding these regions into larger functional networks. This proposed triangular circuitry for synchronized oscillations in large-scale networks may work concurrently with other proposed mechanisms, including cortico-thalamo-cortical (Ribari et al., 1991; Lumer et al., 1997; Steriade, 1999; Jones, 2001) or brain stem-thalamic oscillators (Munk et al., 1996; Steriade, 1996, 1999).
Alexander, G. E. and Crutcher, M. D. (1990) Functional architecture of basal ganglia circuits: neural substrates of parallel processing. Trends Neurosci.,13: 266-271.
Allman, J.M. (1998) Evolving Brains. Scientific American Library, W.H. Freeman
Amaral, D.G. and Kurz, J. (1985) An analysis of the origins of the cholinergic and non-cholinergic septal projections to the hippocampal formation in the rat. J. Comp. Neurol., 240: 37-59.
Armstrong, D.M., Saper, C.B., Levey, A.I., Wainer, B.H. and Terry, R.D. (1983) Distribution of cholinergic neurons in the rat brain demonstrated by immunohistochemical localization of choline acetyltransferase. J. Comp. Neurol., 216: 53-68.
Baddeley, A. (1995) Working memory. In: M.S. Gazzaniga (Ed.), The Cognitive
Neurosciences., MIT Press,
Barbas, H. and Rempel-Clower, N. (1997) Cortical structure predicts the pattern
of cortico-cortical connections. Cerebral Cortex. 7: 635-646.
Baskerville, K.A., Chang, H.T. and Herron, P. (1993) Topography of cholinergic afferents from the nucleus basalis of Meynert to representational areas of sensorimotor cortices in the rat. J. Comp. Neurol., 335: 552-562.
Basalkern Komplex. J. Psychol. Neurol.,
Butcher, L.L. The cholinergic system. In: G. Paxinos (Ed.), The Rat Nervous
Cabezza, R. and Nyberg, L. (1997) Imaging cognition: An empirical review of
PET studies with normal subjects. J. Cogn. Neurosci., 9: 1-26.
Cajal, S. Ramon y (1995) Histology of the Nervous System. Vol I-II. Translated
by N. Sawnson and L. Swanson,
Cajal, S. Ramon y (1935) Die Neuronlehre. In: Bumke O., Foester, O. (Eds.),
Handbuch der Neurologie I. Anatomie. Springer,
Cajal, S. Ramon y (1967) The structure and connexions of neurons. Nobel
Cajal, S. Ramon y (1892) El nuevo concepto de la histologia de los centros
nerviosos. Rev. Ciencias Med., 18: 457-476.
Chevalier G. and Mana, S. (2000) Honeycomb-like structure of the intermediate
layers of the rat superior colliculus, with additional observations in several
other mammals: AChE patterning. J. Comp. Neurol., 419: 137-153.
Coogan, T.A. and Burkhalter, A. (1990) Conserved patterns of cortico-cortical
connections define areal hierarchy in rat visual cortex. Exp. Brain Res.,
Coogan, T.A. and Burkhalter, A. (1993) Hierarchical organization of areas in rat
visual cortex. J. Neuroscience., 13: 3749-3772.
Crick, F. and Koch, C. (1990) Some reflections on visual awareness. Cold Spring
Harbor Symposia on Quantitative Biology. 55: 953-962.
Csordas, A. and Zaborszky. L. (2001) Organization of the basal forebrain
corticopetal system: A computational anatomical study. Cajal Club/Cajal
Institute Int. Conference May 2001,
DeFelipe, J., Jones, E.G. (1988) Cajal on the Cerebral Cortex. An Annotated
Translation of the Complete
DeFockert, J.W., Rees, G., Frith, C.D. and Lavie, N. (2001) The role of working
memory in visual selective attention. Science, 291: 1803-1806.
Desimone, R. and Duncan, J. (1995) Neural mechanisms of selective attention.
Annu. Rev. Neurosci., 18: 193-222.
Duncan, J. and Owen, A.M. (2000) Common regions of the human frontal lobe
recruited by diverse cognitive demands. Trends Neurosci. 23: 475-483.
Felleman, D.J. and
the primate cerebral cortex. Cerebral Cortex. 1: 1-47.
Freund, T.F. and Meskenaite, V. (1992) Gamma-aminobutyric acid-containing
basal forebrain neurons innervate inhibitory interneurons in the neocortex.
Proc. Nat. Acad. Sci. USA., 89: 738-742.
Fries, P., Reynolds, J.H., Rorie, A.E., Desimone, R, (2001) Modulation of
oscillatory neuronal synchronization by selective visual attention.
Science. 291: 1561-1563
Fuster, J.M. (1989) The Prefrontal Cortex: Anatomy, Physiology and
Neuropsychology of the Frontal Lobe, 2nd edition, Raven Press, New
Gallyas, F., Wolff, J.R., Bottcher, H. and Zaborszky, L. (1980) A reliable and sensitive method to localize terminal degeneration and lysosomes in the central nervous system. Stain Technol., 55: 299‑305.
Goldman, P.S. and Nauta, W.J.H. (1977) Columnar distribution of cortico-cortical
fibres in the frontal association, limbic and motor cortex of the developing
rhesus monkey. Brain Res., 122: 393-413.
Goldman-Rakic, P.S. (1987) Circuitry of primate prefrontal cortex and regulation
of behavior by
representational memory. In:
Physiology, The Nervous System, Higher Functions of the Brain, Am.
Physiol. Soc. Bethesda, pp. 373-417.
Goldman-Rakic, P.S. (1984) Modular organization of prefrontal cortex. Trends
Neurosci., 7: 419-429.
Golgi, C. (1967) The neuron doctrine –theory and facts. Nobel Lecture December
11, 1906. In: Nobel Lectures. Physiology or Medicine, 1901-1921.
Gray, C.M. (1999) The temporal correlation hypothesis of visual feature
integration: still alive and well. Neuron. 24: 31-47.
Graybiel, A.M. and Ragsdale, C.W. Jr. (1978) Histochemically distinct
compartments in the striatum of human, moneky, and cat demonstrated by
acetylthiocholinesterase staining. Proc. Natl. Acad. Sci. USA.,75: 5723-
Gerfen, C.R., Baimbridge, K.G. and Miller, J.J. (1985) The neostriatal mosaic:
Compartmental distribution of calcium-binding protein and parvalbumin in
the basal ganglia of rat and monkey. Proc. Natl. Acad. Sci. USA., 82: 8780-784.
Golmayo, L., Zaborszky, L. and Nunez, A. (1999) Somatosensory cortical inputs to the
basal forebrain contribute to somatosensory cortical processing. Soc. Neurosci. Abst., 25: 1167.
proteins reveal a distinct subgroup of cortically projecting basal forebrain
neurons that may synthesize glutamate as a neurotransmitter. Soc. Neurosci. Abstr., 27: 675.
Hubel, D.H. and Wiesel, T.N. (1959) Receptive fields of single neurons in the
cat’s striate cortex. J. Physiol. (Lond). 148: 574-591.
Hubel, D.H. and Wiesel, T.N. (1972) Laminar and columnar distribution of
geniculo-cortical fibers in the macaque monkey. J. Comp. Neurol.,
Jakab, R.L and Lernath, C. (1995) Septum. In: The Rat Nervous System. 2nd ed.
Paxinos, G. (Ed.), Academic Press,
control of cortical activity by the basal forebrain in rats: a role for both
cholinergic and inhibitory influences. J. Comp. Neurol., 381: 53-67.
Johnson, R.R. and Burkhalter, A. (1997) A polysynaptic feedback circuit in rat
visual cortex. J. Neurosci., 17: 7129-7140.
Jones, E.G. (2001) The thalamic matrix and thalamocortical synchrony. Trends
Neurosci., 24: 595-601.
Jones, B.E. and Muhlethaler, M. (1999)
Cholinergic and GABAergic neurons of the basal
forebrain: role in cortical activation In: Lydic, R.
and Baghdoyan, H.A., (Eds.), Handbook of Behavioral State Control - Cellular and Molecular
Mechanisms, CRC Press,
Kiss , J., Magloczky, Z., Somogyi, J. and Freund, T.F. (1997) Distribution of
calretinin-containing neurons relative to other neurochemically identified
cell types in the medial septum of the rat. Neuroscience. 78: 399-410.
Koelliker, A. (1896) Handbuch der Gewebelehre des Menschen. Vol 2.
Nervensystem des Menschen und der Thiere. Verlag von Wilhelm
Koralek, K.A., Olavarria, J. and Killackey, H. (1990) Areal and laminar
organization of corticocortical projections in the rat somatosensory cortex.
J. Comp Neurol., 299: 133-150.
Leergaard, B.T., Alloway, K.D., Mutic, J.J., Bjaalie, J.G. (2000) Three-dimensional topography of corticopontine projections from rat barrel cortex: correlations with corticostriatal organization. J. Neurosci., 20, 8474-8484.
Leise, E.M. (1990) Modular construction of nervous system: a basic principle of design for invertebrates and vertebrates. Brain Res Reviews 15:1-23.
Lubke, J., Egger, V., Sakmann, B. and Feldmeyer, D. (2000) Columnar organization of dendrites and axons of single and synaptically coupled excitatory spiny neurons in layer 4 of the rat barrel cortex, J Neurosci., 20: 5300-5311.
Luiten, P.G., Gaykema, R.P., Traber, J. and Spencer, D.G., Jr. (1987) Cortical projection patterns of magnocellular basal nucleus subdivisions as revealed by anterogradely transported Phaseolus vulgaris leucoagglutinin. Brain Res., 413: 229-250.
Malach, R. (1994) Cortical columns as devices for maximizing neuronal diversity. Trends Neurosci., 17: 101-104.
Malmierca, M.S., Leergard, T.B., Bajo, V.M., Bjaalie, J.G., and Merchan, M.A. (1998) Anatomic evidence of a three-dimensional mosaic pattern of tonotopic organization in the ventral complex of the lateral lemniscus in cat. J. Neurosci., 18: 10603-10618.
Mesulam, M.M., Mufson, E.J., Wainer, B.H., and Levey, A.I. (1983) Central cholinergic pathways in the rat: an overview based on an alternative nomenclature (Ch1-Ch6). Neurosci., 10: 1185-1201.
Metherate, R. and Ashe, J.H. (1991) Basal forebrain stimulation modifies auditory
cortex responsiveness by an action at muscarinic receptors. Brain Res.,
Metherate, R., Cox, C.L. and Ashe, J.H. (1992) Cellular bases of neocortical
activation – modulation of neural oscillations by the nucleus basalis and
endogenous acetylcholine. J. Neurosci ., 12: 4701-4711.
Miller, E.K. and Cohen, J.D. (2001) An integrative theory of prefrontal cortex
function. Annu. Rev. Neurosci., 24: 167-202.
Mountcastle, V. B. (1957) Modalities and topographic properties of single
neurons of cat’s sensory cortex. J. Neurophysiol., 20: 408-434.
Mountcastle, V.B. (1998) Perceptual Neuroscience. The
Munk, M.H.J., Roelfsema, P.R. Konig, P. Engel, A.K. and Singer, W. (1996) Role
of reticular activation in the modulation of intracortical synchronization.
Science. 272: 271-274.
Nadasdy, Z. and Zaborszky, L. (2001) Visualization of density relations in large scale
neural networks. Anatomy and Embryology. 204: 303-318.
Paperna, T. and Malach R. (1991) Patterns of sensory intermodality relationships in
the cerebral cortex of the rat. J. Comp. Neurol., 308: 432-456.
Paus, T., Zatorre, R.J. Hofle, N., Caramanos, Z., Gotman, J., Petrides, M. and Evans, A.C. (1997) Time-related changes in neural systems underlying attention and arousal during the performance of an auditory vigilance task. J. Cogn. Neurosci., 9: 392-408.
Paxinos, G. and Watson, C. (1998) The Rat Brain in Stereotaxic Coordinates.
Price, D.L., Whitehouse, P.J. and Struble, R.G. (1986) Cellular pathology in Alzheimer's and Parkinson's diseases. Trends Neurosci., 9: 29-33.
Rasmusson, D.D. (2000) The role of acetylcholine in cortical synaptic plasticity.
Behav. Brain Res., 115: 205-218.
Rubenstein, J.L., Shimamura,
Regionalization of the prosencephalic neural plate. Annu. Rev. Neurosci.,
Saper, C.B. (1984) Organization of cerebral cortical afferent systems in the rat, I.
Magnocellular basal nucleus. J. Comp. Neurol., 222: 313-342.
Sarter, M. and Bruno, J.P. (1997) Cognitive functions of cortical acetylcholine: toward a
unifying hypothesis. Brain Res. Rev., 23: 28-46.
Sesack,S.R., Deutch, Y., Roth, R.H. and Bunney, B.S. (1989) Topographical
organization of the efferent projections of the medial prefrontal cortex in
the rat: An anterograde tract-tracing study with Phaseolus vulgaris
leucoagglutinin. J. Comp. Neurol., 290: 213-242.
Shepherd, G.M. (1991) Foundations of the Neuron Doctrine.
Singer, W. (1999) Neuronal synchrony: a versatile code for the definition of
relations? Neuron. 24: 49-65.
Singer, W. and Gray, C.M. (1995) Visual feature integration and the temporal
correlation hypothesis. Annu. Rev. Neurosci., 18: 555-586.
Sofroniew, M.V., Eckenstein, F., Thoenen, H. and Cuello, A.C. (1982) Topography of choline acetyltransferase-containing neurons in the
forebrain of the rat. Neurosci. Lett., 33: 7-12.
E. (2000) Attention modulates synchronized neuronal firing in primate
somatosensory cortex. Nature. 404: 187-190.
Steriade, M. (1996) Arousal: revisiting the reticular activating system. Science.
Steriade, M. (1999) Coherent oscillations and short-term plasticity in
corticothalamic networks. Trends in Neurosci., 22: 337-345.
Sugitani, M, Yano, J., Sugai, T. and H ooyama (1990) Somatotopic organization
and columnar structure of vibrissae representation in the rat ventrobasal
complex. Exp. Brain Res., 81: 346-352.
Swanson, L.W. (1992) Brain Maps: Structure of the Rat Brain. Elsevier,
Szentagothai, J, (1978) The Ferrier Lecture 1997. The neuron network of the cerebral cortex: a functional interpretation. Proc. R. Soc. (Lond). 201: 219-248.
D.L. (1994) Basal forebrain lesions in monkeys disrupt attention but not learning and memory. J. Neurosci., 14: 167-186.
Whisaw, I.Q., O'Connor, W.T. and Dunnett, S.B. (1985) Disruption of central
cholinergic systems in the rat by basal forebrain lesions or atropine:
Effects on feeding, sensorimotor behavior, locomotor activity and spatial
navigation. Behav. Brain Res., 17: 103-115.
Wolff, J.R. and
Zaborszky, L. (1979) On the normal arrangement of fibres
and terminals and limits of plasticity in the callosal
system of the rat. In: Russel,
Woolsey, T.A. and Van der Loos, H. (1970) The structural organization of layer
IV in the somatosensory region (SI) of mouse cerebral cortex. Brain Res.,
Zaborszky, L., Buhl, D.L., Pobalashingham, S., Somogyi, J. Bjaalie, J.G. and
Nadasdy, Z. (in preparation) Three-dimensional chemoarchitecture of the basal forebrain: spatially specific clusters of cholinergic and calcium binding protein-containing neurons.
Zaborszky, L., Carlsen, J., Brashear, H.R. and Heimer, L. (1986) Cholinergic and GABAergic afferents to the olfactory bulb in the rat with special emphasis on the projection neurons in the nucleus of the horizontal limb of the diagonal band. J. Comp. Neurol., 243: 488‑509.
Zaborszky, L., Csordas, A., Buhl, D., Duque, A., Somogyi, J. and Nadasdy, Z. (2002) Computational anatomical analysis of the basal forebrain corticopetal system. In: A. Ascoli (Ed.), Computational Neuroanatomy: Principles and Methods. Humana Press (in press).
Zaborszky, L., Cullinan, W.E. and Braun, A. (1991) Afferents to basal
forebrain cholinergic projection neurons: An update. In:
Napier, T.C., Kaliwas, P.W. and Hanin,
Zaborszky, L. and Duque, A. (2000) Local synaptic connections of basal forebrain neurons. Behav. Brain Res., 15: 143-158.
Zaborszky, L., Gaykema, R.P., Swanson, D.J. and Cullinan, W.E. (1997) Cortical input to the basal forebrain. Neuroscience. 79: 1051-1078.
Pang, K., Somogyi,J., Nadasdy,
Z. and Kallo,
Zaborszky, L. and Wolff, J.R. (1982) Distribution patterns and individual variations of callosal connections in albino rat. Anat. Embryol., 165:213‑232.
Fig 3. Figure 3A-H depict a series of rostro-caudal coronal maps compiled from three cases showing basal forebrain location where non-cholinergic neurons projecting to different medio-laterally located frontal/prefrontal and posterior association areas occupy overlapping zones. Injection sites are marked with red, yellow and green colors and basal forebrain locations that contain projection neurons are marked with appropriately colored boxes. The different colored voxels (500 x 500 x 50 μm) in this figure represent spaces where non-cholinergic neurons in each individual animal, project to both a posterior association area and a corresponding frontal region are represented by at least 3 neurons from both cell populations. Figure 3I shows the 3D distribution of these different voxels using the Micro3D program on a Silicon Graphics Octane computer. As can be seen only one voxel (panel D) is shared among the three animals.
Fig 4. A: Differential density scatter plot to show the spatial distribution of cholinergic (red dots) and parvalbumin (green dots) containing neurons in the basal forebrain. Filled circles mark the high-density locations where the density of cholinergic or parvalbumin cells is higher than 15 in the unit space (250 x 250 x 50 μm). Data from this and subsequent panels are derived from a brain alternately stained for choline acetyltransferase, parvalbumin, calretinin and calbindin. Cells were plotted using a computerized microscope and the Neurolucida® software. Axis scaling is in μm corresponding to the x, y and z coordinates according to the Neurolucida database. B: Combined rendering to show locations where cholinergic/parvalbumin (green), cholinergic /calretinin (yellow) and cholinergic /calbindin (dark blue) cells overlap in the basal forebrain from the same dataset as (A). Voxel size is the same as in (A), density≥5 per voxels. Medial view, rostral is right, caudal is left. The wire frames are the outlines of the corpus callosum. C: Iso-relational maps. The spatial relationship of cholinergic neurons to the other three cell types was determined by mapping the change in their density ratios. The ratios between the cholinergic and other markers were calculated considering only those unit spaces where both cell types have a density ³ 5 cells. These surfaces cover the space where the relationship of cholinergic cells to parvalbumin (green), calretinin (yellow) and calbindin (blue) neurons is at least 0.5:1. The numbers along the x and y-axis indicate the voxel indices. Numbers along the z-axis indicate layers (sections). Note that the orientation of both models in panel (A) and (C) is the same. GP, globus pallidus; S, septum. Figure C is from Zaborszky et al. (2002).
Fig. 6 Schematic model to show that specific cell groups in the basal forebrain together with specific prefrontal and associational cell groups constitute parts of distributed functional modules. The different colors represent three segregated parallel circuits. The background template is based from Swanson: Brain Maps. Structure of the Rat Brain. Elsevier, 1992.