In: Changing Views of Cajal’s Neuron
Center for
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.
Introduction
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.
Basal Forebrain
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).
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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. 5. Schematic illustration to show the relationship of the three
projection bands from Fig. 3I and the notion that each of these bands contains
several transmitter-specific sub-channels.
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.