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The Journal of Neuroscience, November 1, 1998, 18(21):8580-8589
Computational Properties of Peri-Dendritic Calcium
Fluctuations
David M.
Egelman and
P. Read
Montague
Division of Neuroscience, Center for Theoretical Neuroscience,
Baylor College of Medicine, Houston, Texas 77030
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ABSTRACT |
Using a model of the extracellular space, we show how external
calcium fluctuations, engendered during normal neural activity, can act
as a rapid information-bearing signal in nervous systems. We
demonstrate that action potentials propagating along a dendrite can
induce large peri-dendritic calcium fluctuations, lowering significantly the external calcium available to overlying presynaptic terminals. The geometrical distribution of active calcium sinks critically influences the time and spatial extent of fluctuations in
external calcium. In particular, clusters of coactive dendrites can
prolong and amplify an external calcium fluctuation. This latter effect
provides a natural substrate for a computational mechanism that locates
specific volumes of neural tissue on rapid time scales. Such an
interpretation suggests that the detailed structure of the
extracellular space, in combination with the three-dimensional
distribution of active calcium sinks, may play a role in neural
information processing.
Key words:
resource consumption principle; back-propagating action
potential; self-organized computing; dendrites; content-addressable
memory; external calcium
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INTRODUCTION |
The calcium ion is involved in many
signaling pathways and is necessary for synaptic transmission and
plasticity (Dodge and Rahamimoff, 1967 ; Katz and Miledi, 1970 ; Bootman
and Berridge, 1995 ; Mintz et al., 1995 ; Qian et al., 1997 ). To date,
intracellular signaling pathways involving calcium have received the
most detailed experimental examination, leaving virtually unexplored
the potential roles played by fluctuations in extracellular calcium. It
has long been known from electrode measurements that synaptic
activation can cause large (on the order of millimolar) changes in
external calcium (Nicholson et al., 1978 ). Only recently has it been
appreciated that these fluctuations may represent an
information-bearing signal to nearby neural elements (Smith, 1992 ;
Montague, 1996 ; Egelman et al., 1998 ).
We focus here on the fact that neurons produce action potentials that
propagate into their axons and dendrites (Stuart and Sakmann, 1994 ).
Action potentials that invade the dendrites of a cell cause large
fluxes of calcium into the dendrite through a variety of voltage-gated
calcium channels (Magee and Johnston, 1995 ; Yuste and Tank, 1996 ). This
influx of calcium is mirrored by an efflux of calcium from the
extracellular space just outside the dendrite. Hence, the timing of the
back-propagating spike (BP-spike) can be encoded briefly in a
fluctuation in external calcium in the peri-dendritic region (Fig.
1).

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Figure 1.
Back-propagating spikes are encoded as brief
fluctuations in external calcium. Calcium
(circles) in the synaptic cleft is shared. Experimental
data suggest that a back-propagating spike travels relatively
unattenuated along dendritic branches where A-type potassium currents
have been inactivated. The occurrence of the back-propagating dendritic
spike is associated with large influxes of calcium through
voltage-gated channels. This influx is mirrored by a peri-dendritic
efflux of calcium from the extracellular space. An overlying
terminal would feel a decrement in the available calcium when a
BP-spike (arrow) passes by.
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As we will demonstrate below, external calcium levels and the geometry
of the extracellular space are arranged so that neural activity can
cause significant fluctuations in external calcium. The potential
significance of such fluctuations derives from the many roles that
calcium plays in synaptic transmission, long-term synaptic modulation,
cell adhesion, growth cone motility, and a vast number of intracellular
signaling pathways. External calcium fluctuations can be studied from
two basic perspectives: biophysical and computational. At the
biophysical level, one can appeal to the physical mechanisms used by
neural elements to construct, detect, and respond to external calcium
fluctuations. Using a simplification of the biophysical problem, we
focus instead on the potential computational roles of these
fluctuations. We pursue the hypothesis that external calcium
fluctuations engendered by normal neural activity represent an
information-bearing signal. In particular, we show how patterns of
synaptic activation in a broad region of neural tissue could use
external calcium fluctuations in a mechanism that rapidly locates small
volumes of neural tissue.
To calculate external calcium fluctuations, we have developed a
finite-difference model of the extracellular space and calibrated it
using a combination of analytic and Monte Carlo methods (see Materials
and Methods). Our results are presented in three parts. (1) We
demonstrate that back-propagating action potentials can induce large
peri-dendritic calcium fluctuations, thereby lowering the calcium
available to overlying presynaptic terminals; (2) we show how different
geometrical arrangements of dendrites, dendritic spines, and calcium
sinks can act to change the amplitude and time course of external
calcium fluctuations; and (3) we describe how these calcium
fluctuations could be part of a mechanism that rapidly indexes specific
volumes of neural tissue.
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MATERIALS AND METHODS |
Strategy. Monte Carlo calculations and the
finite-difference model of the extracellular space were programmed in C
and run on Silicon Graphics workstations. To calibrate the
finite-difference model, we calibrated the Monte Carlo simulator first
against free diffusion and then introduced the reflecting boundaries.
The Monte Carlo model was then used to calibrate the finite-difference
model of the extracellular space, which runs three to four orders of magnitude faster. In both models, the membranes of synapses, spines, and dendrites were implemented explicitly as reflecting boundaries.
Monte Carlo calculations. In the Monte Carlo simulator,
external calcium was implemented as random walkers moving within the interstices of the extracellular space. The assumption of isotropic diffusion dictated a symmetrical probability distribution function for
moving right or left along each axis (x, y, and
z). The Monte Carlo simulator (see Fig.
3A) is compared against the analytical result for
three-dimensional free diffusion from an instantaneous point
source:
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(1)
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where C(r,t) is the expected
concentration at radial distance r at time t,
N is the number of molecules that started at the point
source, and D is the diffusion coefficient. Further tests covered a range of diffusion coefficients, as well as reflections from
boundaries (data not shown). The Monte Carlo time step ( = 50 nsec)
translates to a fixed step length (along each axis) of = 5.5 nm for
D = 300 µm2/sec and = 7.7 nm
for D = 600 µm2/sec (where = 2D ). The number of walkers released was between 5000 and 106. With these parameters,
the Monte Carlo calculations match the analytic results to within
<1%. There are error bars in Figure 3A, but they are
obscured by the size of the symbols.
After calibration against the analytic equations, we introduced cubic
reflecting boundaries 0.806 µm on a side. This side length yields the
same volume as a sphere 1 µm in diameter that approximates a synaptic
bouton or spine head volume. Extended lengths of dendrites were made by
concatenating multiple cubes into an elongated segment. Boundary
elements were separated by small clefts of the same height as real
synaptic clefts (20 nm). Typically, the total volume examined was a
cube 7 µm on a side. A minimum of 6 × 105
random walkers was placed at random in the interstices, the positions of all walkers were updated in parallel, and the walkers reflected off
the boundaries after collision except when they collided with active
calcium sinks on the boundary. After collision with an active calcium
sink, the probability of a walker being consumed is defined by
Pc: Pc = 0 for inactive units and 0 < Pc 1.0 for consuming units.
Calcium extrusion is a first-order function of intracellular
concentration, calibrated for a half-life between 35 and 500 msec
(Helmchen et al., 1996 ). For a half-life t*, the probability of extrusion per walker per time step was:
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(2)
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where k = ln(1/2). Because sequestered molecules
are extruded from their point of entry, this is equivalent to ignoring
slow intracellular diffusion.
The finite-difference model. The model is illustrated in
Figure 2. The basic cubic unit is called
an intracellular unit (IU). IUs can be combined to represent spines, as
well as longer segments that represent dendrites. These structures are
modeled as reflecting boundaries except for the regions that
represented active calcium sinks. The units are packed together tightly
with an extracellular space (ECS) width of 20 nm.

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Figure 2.
The finite-difference model. Elementary
IUs are cubes 0.806 µm on a side (same volume as a
sphere 1 µm in diameter). IUs can be connected to form
larger structures, such as dendrites and cell bodies. Shown in this
figure are a presynaptic terminal (shaded cube) and a
segment of dendrite (shaded rectangle). The
clefts between the IUs are subdivided into smaller
ECS units with side lengths of 115 nm. Each ECS
unit holds the average calcium concentration in that region. At
each time step, each ECS subunit updates its
concentration as a function of the concentration of its contiguous
neighbors and as a function of the activity of the intracellular units
with which it is in contact. The time step used is 2 µsec, which
simulates diffusion with very little error at the specified spatial
scales (see Fig. 3). In all studies (see Figs. 4-8), the dendritic
segments are couched within a larger volume of simulated tissue, as
indicated by the dotted cubes in this figure. The total
volume is 5.8 µm on a side, or ~195 µm3, which
is sufficient to avoid border effects. The extracellular calcium
concentration is initialized to 1.6 mM throughout the
volume.
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The extracellular space is subdivided into small parallelograms called
ECS units. Each ECS unit holds a single-state variable that represents
the average concentration in that volume. At each time step, an ECS
unit updates its concentration as a function of its adjacent ECS
neighbors and the calcium extruded by adjacent IUs. The IUs consume and
extrude. For consumption of external calcium, an IU can either be in an
active or inactive state. Consumption takes place through some fraction
of the surface of the IU that we generically call the consumption zone
or calcium sink. The sinks can be spread evenly over the surface of an
IU, or they can be clumped arbitrarily to represent uneven spatial
distribution of calcium sinks. Consumption by an active calcium sink is
described by a single parameter Pc [0,1], which is engineered to correspond to the homologous parameter
in the Monte Carlo calculations, above.
Although Pc is a complicated function of
channel distribution and open probabilities, we have made a simplifying
approximation to represent calcium consumption during a dendritic
action potential; a section of dendrite becomes active for a fixed
amount of time and consumes a fixed number of external calcium atoms.
In the studies presented below, we have used the fact that dendritic calcium channel densities are estimated between 1 and 15 channels/µm2 (Magee and Johnston, 1995 ). If we
estimate each channel to have a 10 pS calcium conductance and a mean
open time of ~1 msec, then for a typical action potential, a density
of 10 channels/µm2 translates into a consumption
of ~21,500 atoms/µm2. Thus, for each cubic face
of the model (0.65 µm2), we have adjusted
Pc for an integrated consumption of 14,000 atoms/msec. Although the above calculation makes the rough assumption of a square-pulse 70 mV depolarization, lasting for 1 msec, and further
assumes that all the current is carried by Ca2+
atoms, the result is nonetheless consonant with other numbers from the
literature. For example, 14,000 calcium atoms per active zone per spike
has been estimated at a CNS terminal (the calyx of Held) (Helmchen et
al., 1997 ); we have used this same value for total consumption at
presynaptic terminals (see Figs. 4, 8). At a presynaptic terminal,
14,000 atoms/msec consumption would only require ~13 channels, which
may seem surprising because ~200 calcium channels are thought to
exist on a typical terminal (Smith, 1992 ). The apparent discrepancy is
most likely explained by the possibility that most of the channels are
not activatible when a spike arrives. To display explicitly the
dependence of our results on the total integrated current, we have
explored consumption over a range of calcium channel density estimates
(see Fig. 5). As will be shown, adjusting the density over a wide range
will temper, but not eliminate, the computational ideas presented in this paper. That is, we are proposing that back-propagating action potentials can modulate the transmission probabilities of overlying presynaptic terminals; we will attempt to show that the modulation will
hold true, even as the channel densities vary over a liberal range.
As part of our control, we compared our finite-difference model against
Monte Carlo simulations in a number of conditions. Two examples are
presented in Figure 3. In Figure
3B, the cleft is "sealed off" by prohibiting lateral
diffusion outside the borders of the cleft, and consumption is then
assayed at two different consumption probabilities
(Pc). In Figure 3C, a single
cleft is filled with 1.6 mM calcium, whereas the
neighboring extracellular space is set to zero concentration; the
concentration is then measured in contiguous clefts as the calcium
diffuses. In Figure 3, B and C, results from the
two simulators match to within 1%.

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Figure 3.
Comparison of the two models. A,
Monte Carlo calibration to free diffusion. Five thousand random walkers
were released in the middle of a volume with no barriers. The
filled squares indicate the concentration of walkers in
successive concentric spherical shells at t = 100 µsec and D = 600 µm2/sec,
averaged over five runs. The solid line compares the
analytically expected concentrations by the use of the
three-dimensional free-diffusion equation (Eq. 1). B,
Comparison of the function of the two models. Lateral diffusion is
turned off so consumption can be assayed alone (i.e., the walkers are
confined to a single cleft). Solid lines show the
finite-difference model calculation for concentration in the cleft
using two different values of Pc: 0.00052 (upper trace) and 0.00135 (lower trace).
Dotted lines show Monte Carlo simulation under the same
conditions with 5000 walkers. C, Measurement of
diffusion without consumption. A single cleft is filled to resting
levels (1.6 mM), whereas the rest of the ECS remains empty.
The concentration is then measured as the walkers diffuse from the
original cleft into the neighboring extracellular space. Solid
lines show the finite-difference model calculation for
concentration in the cleft (upper trace), a neighboring
cleft 0.8 µm away (center-to-center distance; middle
trace), and 1.6 µm away (bottom trace).
D = 600 µm2/sec. Dotted
lines show the analogous Monte Carlo simulation with 10,000 walkers. As in all of our simulations, the basic IUs are 806 nm on a
side, and the interstitial space between the IUs is 20 nm.
D, A 1 msec square-pulse conductance change used to
represent the effect of an action potential on voltage-gated calcium
channels (solid line; inset) in
simulations in this paper. For comparison, we show a conductance change
represented by an function, f(x) = x·exp( x) (dashed line;
inset). Under both profiles, the calcium fluctuations
measured at a single 115 × 115 nm active zone have approximately
the same amplitude, whereas the concentration decrement is held longer
when the function is used. Thus, our use of square pulses here is
conservative, because we are suggesting that time to recovery is an
important functional variable.
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In the examples presented below (see Figs. 4-8), we modeled the
conductance change in calcium channels as a square pulse (Fig. 3D, inset). The use of a potentially more
realistic conductance change (Fig. 3D, inset, function) yields results that are similar with respect to amplitude but
that have a prolonged recovery time (Fig. 3D). Because we
make statements in this paper about recovery time, we err on the
conservative side by using square pulses.
The discrete dynamics for consumption are derived from a simple
statistical argument; of a concentration of C molecules in an ECS unit, the fraction of atoms within striking distance of the cell
surface in the next time step is described by the ratio of the step
length = 2D (where is the time step) to the cleft height
Z. Of this fraction, half the atoms within reach will step
toward the surface, whereas the other half will step away. Those that
collide with the surface are absorbed with probability Pc yielding:
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(3)
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Extrusion takes place as a first-order function of intracellular
concentration with a half-life t*:
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(4)
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where k = ln(1/2) and Cint is
the intracellular concentration underlying each ECS unit. Calcium is
extruded back into the ECS unit from which it was consumed. Putting
everything together, the concentration change in the ith ECS
unit Ci is:
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(5)
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= 2 µsec is the time step of the finite-difference
simulation, is the distance between the centers of the ECS units
(115 nm), D is the local diffusion coefficient, and
j sums over contiguous ECS neighbors (up to 12 in three
dimensions). The second term represents depletion attributable to ion
channels. Z is the cleft height (20 nm), and
P1c and
P2c are
the consumption probabilities (per Monte Carlo time step, = 50 nsec) of the two IUs touching each ECS unit. = 2D is the
average step length (along each Cartesian axis) of a random walker in
time . The choices for and were carefully calibrated against
the Monte Carlo model.
A quick inspection shows that needs to be on the order of 50 nsec;
otherwise, the step length of each walker would be close to or greater
than the cleft height. In the finite-difference simulations, the time
step = 2 µsec = 40 × 50 nsec; therefore, the
second term is raised to an exponent ( / ) or in this case the 40th
power. This latter maneuver allows us to account for the depletion that
takes place in / instances of -size ticks. An example will
illustrate. According to Equation 3, after a = 50 nsec time step,
the new concentration in the cleft will be C(t + ) = [1 ( /2Z)Pc]C(t).
To represent the passage of = 2 µsec (finite-difference time
step), we iterate the consumption ( / ) times (in this case, 40 times), which yields a new cleft concentration of
C(t + ) = [1 ( /2Z)Pc] / C(t).
The total change in cleft concentration after = 2 µsec is
C(t + ) = [1 [1 ( /2Z)Pc] / ]C(t).
The above representation of consumption compares within 1% error to
Monte Carlo simulations (Fig. 3) and reduces computational time by four
orders of magnitude.
Finally, the third term in Equation 5 represents first-order extrusion
from the two IUs adjacent to the ECS unit.
As mentioned, all simulations were assayed between an upper bound
(D = 600 µm2/sec) and a lower
bound (D = 300 µm2/sec) for the
diffusion coefficient. The diffusion of Ca2+ atoms
in the networks of neural ECS will be slower than free diffusion,
attributable at least to geometrical boundaries and buffering. The
character and extent of extracellular calcium buffering are primarily
unknown, but presumably the effect of ECS buffers will be absorbed in
the local diffusion coefficient. There are currently no measures of
"local" diffusion coefficients, but the past two decades have given
us several studies of "long-distance" diffusion parameters in the
mammalian brain. Experiments were pioneered in the early 1980s in which
a current of test ion was injected in one location in the brain and the
building concentration profile was measured at a distant site (30-200
µm away) (Nicholson, 1980 ; Nicholson and Phillips, 1981 ; Sykova,
1997 ). The results yield a dimensionless, empirical parameter called
tortuosity, . Tortuosity relates the free-diffusion coefficient
Dfree to the effective diffusion constant
Deff:
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(6)
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Under nonpathological conditions, is within a narrow range
of 1.5 1.7. This range encompasses measurements in
different species, over different parts of the brain, and made with
cations (calcium, tetramethylammonium, and tetraethylammonium) or
anions ( -naphthalene sulfonate and hexafluoroarsenate) (Nicholson,
1980 ; Nicholson and Phillips, 1981 ; Sykova, 1997 ). A value of = 1.6 reduces Deff from 600 µm2/sec in free solution to 234 µm2/sec in the brain.
Such studies do not specify the diffusion coefficient locally. Because
tortuosity involves paths through the bulk geometry, such a measurement
is mute on the speed with which a molecule can move in an individual
synaptic cleft. In separate studies, we have determined that the value
of inherent in our choice of geometry yields = 1.23, which
would reduce D = 600 µm2/sec to
Deff = 395 µm2/sec (D. M. Egelman and P. R. Montague, unpublished observations). Two possibilities, or a combination of the two, will account for the
remaining slowing of diffusion measured in real tissue; (1) Dlocal is <600 µm2/sec,
reflecting local extracellular binding, and/or (2) the extracellular space can be made more tortuous, by the combination of elementary units
into larger units (such as somas), or equivalently some of the clefts
can be clogged, acting as barriers to diffusion. Because there is no
way to estimate accurately the contribution of these two possibilities,
we run all our simulations over a wide parameter range, using
Dlocal values of 300 and 600 µm2/sec as lower and upper bounds,
respectively.
In summary, simulations used the following parameter values: diffusion
coefficient D = 300-600 µm2/sec,
side length of intracellular unit (cube) = 0.806 µm, size of smallest
active zone = 115 × 115 nm, time step = 50 nsec (Monte Carlo simulator) or 2 µsec (finite-difference model), cleft
height = 20 nm, and the consumption parameter
Pc = 0.0005-1.0.
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RESULTS |
Back-propagating spikes can be encoded in peri-dendritic
calcium fluctuations
Back-propagating action potentials cause large fluxes of calcium
into the dendrite; that influx is mirrored by an efflux of calcium from
the peri-dendritic extracellular space. Figure
4A shows a model
presynaptic terminal directly contacting a dendritic shaft. During a
back-propagating spike in the dendrite, the overlying terminal feels a
large (38%) drop in available external calcium. The known sensitivity
of neurotransmitter release to external calcium (Dodge and Rahamimoff,
1967 ; Katz and Miledi, 1970 ; Mintz et al., 1995 ; Qian et al., 1997 )
suggests that such a decrement may influence the probability of
synaptic transmission. If the presynaptic terminal were invaded by an
action potential just after the passage of the back-propagating spike,
the presynaptic release probabilities could be diminished. This effect
highlights one of the important properties of external calcium
signaling: the rapid bidirectional transfer of information at synaptic
junctions. External calcium fluctuations encode information about
postsynaptic activity (such as BP-spikes) as effectively as presynaptic
activity (see Discussion).

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Figure 4.
Large peri-dendritic calcium fluctuations may be
reduced by moving the overlying terminal away. To examine the calcium
fluctuations resulting from a dendritic action potential, we activated
a 4.1 µm dendritic segment by a back-propagating spike. The plots
show the external calcium concentration in a synaptic cleft (806 × 806 nm) shared between a presynaptic terminal and the dendrite (with
or without a spine). Diffusion coefficients (D values)
are between 300 and 600 µm2/sec, as shown in the
middle and bottom rows. Calcium sinks are
spread evenly along the dendrite. Three conditions are presented in
each plot; (1) the terminal is activated by an invading action
potential, (2) the dendrite is activated by a back-propagating action
potential, or (3) the terminal and dendrite are activated
simultaneously. The dendritic segments diagrammed in the top
row are couched within a larger volume of simulated neural
tissue, as in Figure 2. A, No spine. When the
presynaptic terminal (open cube) directly contacts the
dendritic shaft, the calcium in the cleft transiently drops between 27 and 34.5% (D, 600 and 300 µm2/sec,
respectively) because of a back-propagating spike alone (solid
trace). B, Addition of a spine. If the spine
head and neck contain voltage-gated calcium conductances (VGCCs), the
addition of a spine does little to change the external calcium
fluctuation felt at the overlying terminal. The model spine here is an
attached shaded cube 0.8 µm on a side. Here the
calcium in the cleft transiently drops between 22 and 32%
(D, 600 and 300 µm2/sec,
respectively) because of a back-propagating spike (solid
trace); this is only slightly different from the result in
A. C, Inhibition of a spine
(attached open cube). If VGCCs on the spine do
not become activated by a BP-spike (e.g., because of inhibition,
inactivation, or absence), the geometry of the spine insulates the
overlying bouton from the peri-dendritic calcium fluctuation. In
C, a back-propagating spike causes a calcium decrement
in the cleft of between only 5.4 and 6.1% (D, 600 and
300 µm2/sec, respectively), approximately fivefold
smaller than in A and B above.
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Addition of a dendritic spine with calcium sinks
The geometry of the active dendritic elements influences the
character of external calcium fluctuations. Figure 4B
shows a model presynaptic terminal contacting a dendritic spine. The
spine consumes the same total calcium per unit area as the parent
dendrite (see Materials and Methods). In this case, moving the synaptic junction away from the dendritic shaft (via a short spine) does little
to change the calcium fluctuation experienced by the synaptic cleft.
The situation changes significantly if the spine does not contain
voltage-gated calcium channels or has them inhibited.
Addition of a dendritic spine with inactive calcium sinks
In Figure 4C, we consider the case in which
voltage-gated calcium sinks on the dendritic spine are not active
during the back-propagating spike, e.g., because of inhibition,
inactivation, or absence. In this case, an ~1 µm inactive spine
insulates the synaptic cleft from the large peri-dendritic calcium
fluctuation demonstrated above. Thus, spine synapses could be
distinguished from shaft synapses via fluctuations in external calcium
felt by an overlying synaptic cleft.
Density of calcium channels
Extracellular signal
As a control over the total integrated current, we have explored
consumption over a range of calcium channel density estimates, changing
the consumption parameter from 10 to 200% of our baseline estimate of
~10 channels/µm2 (Fig.
5A). Even at one-tenth of our
baseline density, the concentration drops to 95.5-96.8%; a decrement
of this magnitude will presumably translate into an ~10% decrease in
the probability of neurotransmitter release at an overlying terminal.
At double the channel density, the concentration drops to 46.7-57.8%,
which represents an almost total depression of the release probability
(Mintz et al., 1995 ; Qian et al., 1997 ). One of the central ideas in
this paper is that back-propagating action potentials can modify the
transmission probabilities of overlying presynaptic terminals. The
details of this theme will become increasingly focused as more exact
details about calcium channel kinetics, positions, and densities are
discovered experimentally. However, we predict this idea will weather
the test of new data, for calcium consumption will have effects even at
one-tenth of our original estimate (corresponding to ~1
channel/µm2).

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Figure 5.
Changing the channel density affects extracellular
and intracellular signals. A, Extracellular signal. The
channel density covering the dendrite is changed from 10 to 200% of
the values used in Figure 4. External calcium is measured in the cleft
between the shaft and the overlying presynaptic terminal
(inset). As always, the dendritic segment is couched
within a larger volume of simulated neural tissue, as in Figure 2. Each
calculation is bracketed by a diffusion coefficient D of
300-600 µm2/sec (lower and
upper trace in each pair, respectively).
B, Intracellular signal. Over a 806 × 806 nm patch
of membrane, the total calcium influx is a function of the channel
density (modeled as consumption probability, see Materials and
Methods). Doubling the density does not quite double the influx. The
calcium depletion in the cleft does not fill in as rapidly in the
D = 300 µm2/sec case; thus at
higher channel densities, the influx is lesser at 300 than at 600 µm2/sec. The difference at lower densities is
artifactual.
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Intracellular signal
One of the most important signals known in biology is calcium
influx. To understand the relationship between the density of calcium
channels and the resulting influx, we measure the total intracellular
signal in our model. Figure 5B shows that doubling the
number of calcium channels on a surface will not suffice to double the
influx. This is because taking more calcium from a cleft requires the
sinks to wait for replenishment from diffusion from neighboring
extracellular space. At a baseline density, total influx is between
12,243 and 12,581 atoms, which corresponds to a current of ~4 pA
through a unit patch of membrane (0.64 µm2). We
will return to the issue of the intracellular signals below.
Small-scale changes in calcium sink distribution have significant
effects on calcium fluctuations
In Figures 4 and 5, the calcium sinks were spread evenly over the
dendrite. Figure 6 illustrates some of
the consequences of putting calcium sinks in small clumps along the
dendrite. To allow a comparison with the cases in Figure 4, we adjusted
the parameters of the model so that the integrated calcium current per
square micrometer was constant (see Materials and Methods). With
increasing clustering, local calcium fluctuations grow increasingly large. In the three cases examined, the time course of the
average calcium concentration in the synaptic cleft was
the same (Fig. 6D); however, the calcium immediately
available to the consuming zones differs substantially (Fig.
6E).

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Figure 6.
Time course and duration of external calcium
fluctuations are sensitive to the geometrical arrangement of calcium
sinks. A-C, Calcium sinks are placed
randomly along the dendrite. Twenty-two (A), 7 (B), or 1 (C) calcium
sink(s) is placed on each unit patch of dendrite (0.64 µm). In all
cases, the total consumption is engineered to consume 14,000 calcium
atoms per unit patch during a 1 msec BP-spike. The surface
plots show a snapshot of the calcium in the cleft between the
dendrite and the overlying presynaptic terminal at the end of the
BP-spike. Increasing the clustering of the consuming zones heightens
the maximum decrement and the signal to noise. A single 115 × 115 nm clumping of channels (C) causes a rather
dramatic fluctuation. D, External calcium measured in
the cleft between the dendrite and the overlying terminal is shown. The
average calcium in the 0.8 × 0.8 µm cleft does not differ for
the 22, 7, and 1 clump cases. E, Measuring the amount
immediately available to the clump (because clumps represent the
pathways for internalizing calcium from the extracellular space) shows
a dramatic difference.
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Coincident activation of neighboring dendrites extends calcium
fluctuations in time and tissue space
During development of the cerebral cortex, glial cells extend
radial processes along which neuroblasts migrate. As a result, columnar
regions of neuropil develop with vertical bundles of apical dendrites
of pyramidal cells (Schmolke, 1987 ). It is unknown whether the
dendritic bundles are leftovers of development or whether their
existence is necessary for some computation. When viewed from the point
of view of external calcium fluctuations, the bundle structure yields
interesting possibilities.
In our previous examples, we examined the influence of one dendritic
branch on calcium availability to synaptic clefts shared by overlying
presynaptic terminals. In those examples, large decrements in local
calcium levels recover quickly (within milliseconds) to baseline. This
fact is easily understood, because in diffusion systems, replenishing
fluxes are proportional to the concentration gradient and the
concentration gradient is extremely large next to point sinks
(presynaptic terminals) or even elongated line-like sinks (isolated
active dendrite). However, a bundle of coactive neighboring dendrites
will consume calcium from a spatially extended region, the gradients
near the bundle center are small. Such synchronously active bundles
cause a slower recovery of calcium near the center of the bundle (Fig.
7A). The recovery time has
increased six- to eightfold, from 1 msec for an isolated dendrite (Fig.
4) to 6-8 msec (Fig. 7). The amplitude is also much larger than that in the comparable single dendrite case (Fig. 4).

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Figure 7.
Synchronous spikes in a dendritic bundle scale the
recovery time for external calcium. A, Peri-dendritic
calcium fluctuations remain fairly local; i.e., their magnitude
diminishes rapidly with distance through the tissue. However, different
geometrical arrangements of these extended calcium sinks can
dramatically change the time for external calcium to replenish by
diffusion. Nine dendritic segments (each 4.03 µm in length) are
synchronously activated. The plot shows the external
calcium measured in different locations relative to the bundle. The
recovery time in the interior of the bundle has increased from 1 msec
in the single dendrite case to just under 10 msec. The large calcium
decrement could block synaptic transmission for variable lengths of
time. B, Synchronicity is not required for large calcium
signaling. In this example, the activation time for each dendritic
segment was drawn from a Gaussian distribution (mean = 12 msec;
of 1, 5, and 10 msec). The external calcium measured in a cleft on
the inner face of the bundle is shown. C, The same
jitter in the activation times seen in B is shown for
external calcium measured in a cleft 0.8 µm away from the
bundle.
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The large fluctuations shown in Figure 7A do not require
precisely synchronous activity in the dendrites. Figure 7, B
and C, shows the calcium fluctuations in the center of the
bundle and one unit away (0.8 µm) from the bundle, respectively. In
B and C, each dendrite in the bundle makes a
single spike but with Gaussian jitter in the exact time of the spike
(mean time of spike production = 12 msec; SDs of 1, 5, and
10 msec). Even with large jitter, the bundle structure serves to
increase the amplitude of the fluctuations in the center of the bundle
(Fig. 7B). Interestingly, a reader measuring the calcium
fluctuation from one unit away may have a hard time determining how
synchronous the dendrites were; even with widely varying jitter, the
calcium profiles look approximately the same from a short distance away
(Fig. 7C).
Magnitude of calcium influx may carry information about local
geometry and activity
Because intracellular enzymes carry different affinities for
calcium, the exact size of a calcium influx signal can lead to diverse
intracellular results (Bootman and Berridge, 1995 ). In Figure
8, we demonstrate how the local
spatiotemporal surroundings can lead to different intracellular calcium
signals, even given the same channels on a patch of membrane. In Figure
8A, we adjust the consumption parameter
Pc to yield an total influx of 14,000 at a
presynaptic terminal, in keeping with results from Helmchen et al.
(1997) . This same Pc is then used to
define the consumption over an entire dendritic segment. The
extracellular fluctuation is larger in the dendritic case, and the
intracellular signal is correspondingly smaller. In this way the same
patch of membrane can pass different signals to its intracellular
signal depending on its local surroundings. Figure 8B
extends the studies of Figure 7 in which we examined the extracellular
signals generated by asynchronous firing in a dendritic bundle. In
Figure 8B, the magnitude of total calcium influx is
assayed with different amounts of jitter in the firing times of the
dendritic segments (SDs, 1-10 msec). When all nine dendritic segments
fire simultaneously, the influx across a given patch of membrane is
approximately one-half of its value at SDs > 10 msec. Thus, the
magnitude of calcium influx carries information about the synchronicity
of the bundle; as the bundle fires more synchronously, the total
calcium influx is reduced.

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Figure 8.
Magnitude of calcium influx can carry
information about local geometry and synchronicity. Depending on the
local spatiotemporal surroundings, a given set of calcium channels on a
patch of membrane can lead to different extra- and intracellular
calcium signals. A, Left, At a single
presynaptic terminal, we adjust the consumption parameter
Pc to consume 14,000 ions during a 1 msec
square-pulse action potential (Helmchen et al., 1997 ). This corresponds
to a maximal change in the external calcium of 9-15%.
Middle, If that same value of
Pc (representing a certain concentration
of calcium channels) is now used on the surface of a dendritic segment,
the external calcium outside a unit patch of membrane (0.64 µm2) now drops to 65.6-73.8%. This larger change
in external calcium is easily understood, because the calcium sinks now
cover the surface of an entire dendritic segment, not simply a terminal
face, and thus there is more total consumption. Right,
The corresponding intracellular signal is ~12% smaller in the case
of the dendritic segment, because there is less external calcium
available. B, A bundle of nine dendritic segments
is asynchronously activated as shown in Figure 7, with SDs of 1, 2, 3, 5, and 10 msec. The same consumption parameter
Pc is used as in A. Calcium
consumption at the outside surfaces of the bundle is
approximately the same in all cases. However, on the inside
surfaces, the magnitude of calcium influx carries information
about synchronicity of the bundle; as the bundle fires more
synchronously, the total calcium influx is reduced. For simplicity of
illustration, we only show the results for D = 300 µm2/sec.
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Dendritic activity convergence as an indexing mechanism
The branched structure of dendrites in hippocampus and cortex
creates an opportunity for dendrites from different (and distant) somas
to come into contact as neighbors. In this way, a dendritic bundle or meshwork is achieved, in which back-propagating spikes may come together close in time and tissue space. Near-coincident activity in these neighboring dendrites may engender the same sort of
calcium signals as those examined in Figure 7.
We propose that external calcium fluctuations could be used in an
addressing scheme in the brain. As indicated in Figure
9, such a mechanism could locate a
specific volume of tissue by directing back-propagating spikes to that
volume and by flagging the matching volumes with a large and temporally
extended fluctuation in external calcium.

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Figure 9.
External calcium fluctuations are ideally suited
to act as a marker signal for rapidly indexing a volume of neural
tissue. A, In regions with a high density of synaptic
transmission (filled circles), the EPSPs caused by the
transmissions will deactivate A-type K+ channels
along that dendritic branch. B, Those same EPSPs
may cause the soma to generate a spike, which will back-propagate
(shaded lines) to the region of the high density
transmission. In that region, the crossing of dendrites from different
somas can lead to extended calcium decrements, of the type displayed in
Figure 7. The calcium depletion zone indexes a specific region of the
tissue.
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Recent physiological work on back-propagating spikes suggests one
realistic possibility. It is known that back-propagating spikes tend to
attenuate quickly because of the presence of A-type potassium channels
in dendrites (Hoffman et al., 1997 ). This same work has shown that
synaptic input inactivates these conductances and causes dendritic
spike propagation to proceed unattenuated into branches that have
experienced the synaptic input. We propose here that this effect could
mediate the addressing mechanism described in Figure 9: (1) coincident
synaptic transmissions inactivate A-currents in dendrites present in a
common volume of tissue; (2) back-propagating spikes are directed into
the volumes in which transmissions occurred; and (3) large, temporally
extended fluctuations in external calcium "mark" tissue volumes in
which sufficient spatiotemporal overlap of back-propagating spikes
occurs.
In short, high densities of synaptic input in a volume of neural tissue
cause a convergence of dendritic spike activity, "calling" dendritic spikes into the volume in which the transmissions occurred. As illustrated in Figure 9, this mechanism permits widely broadcast activity, encoded in patterns of action potentials, to locate and flag
specific volumes of tissue.
 |
DISCUSSION |
The implicit idea running through the examples in this paper is
best cast as a question. If synapses require calcium to transmit, then
why is all or most of the calcium pumped into the extracellular space,
set to 1.5-2 mM, and shared with neighboring neural and non-neural elements? Such an arrangement forces neighboring neural elements to share a resource that is necessary for neural transmission and general intracellular signaling but is in limited supply on short
temporal and spatial scales. As we have demonstrated, resting levels of
external calcium are not sufficiently high to protect against large
fluctuations in this important resource. Instead, it seems as though
the tissue is engineered so that external calcium levels are meant to
fluctuate dramatically; given the functional importance of external
calcium, we are led to the strong suspicion that external calcium
fluctuations represent an information-bearing signal in the nervous
system.
It is possible that some undiscovered compensatory mechanism protects
neural tissue from the consequences of rapid external calcium
fluctuations; however, many compensatory mechanisms are not plausible
based on simple physical arguments. For example, any ionic channel
permeable to calcium will cause the unidirectional movement of calcium
out of the extracellular space because of the extreme calcium gradient
established by cells; 1.5-2.0 mM outside and 50-100
nM inside translate into a 15,000-40,000:1 outside-to-inside gradient. Thus, it seems unlikely that an ionic channel that fluxes calcium could counteract the expected fluctuations in external calcium. Calcium pumps and cotransporters will be unable to
counterbalance the rapid fluctuations that we present in this paper,
because they move calcium back into the extracellular space two to four
orders of magnitude more slowly than the ionic channels steal it from
the extracellular space.
A bidirectional signal that may scale
transmission probabilities
In the synaptic cleft, one important event encoded in external
calcium fluctuations is the occurrence of an action potential in either
the dendrite or axon. As a signal, the calcium fluctuation is naturally
fast and bidirectional, informing both pre- and postsynaptic elements
of the arrival of a spike in the axon or dendrite. Moreover, for
presynaptic spikes, an external calcium fluctuation does not depend on
whether the terminal transmits. It is therefore possible that a rapid
change in cleft calcium acts as a rapid anterograde and retrograde
signal.
We have shown that even the firing of a single segment of dendrite can
lower the external calcium drastically, and the decrement lasts a few
milliseconds (Figs. 4-6). The computational function of dendritic
spines has been long debated (Koch et al., 1992 ; Koch and Zador, 1993 ;
Yuste and Tank, 1996 ); we propose here an additional role for spines.
When the channels on a spine are inactivated, inhibited, or not
present, the geometry of the spine is sufficient to protect the
overlying presynaptic terminal from the large peri-dendritic calcium
fluctuation caused by a back-propagating spike. We have also shown that
when multiple, neighboring dendrites all propagate spikes, the local
calcium fluctuation will be even larger and last longer (Fig. 7). Given
the known sensitivity of neurotransmitter release on external calcium
levels (Dodge and Rahamimoff, 1967 ; Katz and Miledi, 1970 ; Mintz et
al., 1995 ; Qian et al., 1997 ), the demonstrated fluctuations may
decrease the release probabilities of synaptic terminals nearby. This
effect may implement a scaling of transmission probabilities that
ranges from mild decrements to a full transmission failure.
Transmission failures because of calcium fluctuations
It is thought that a neuron conveys information in part through
the pattern of action potentials it generates. This viewpoint is
supported by recent experiments that demonstrate that mammalian neurons
are capable of reliably producing spikes with a precision on the order
of a millisecond. However, for the recipient neuron or tissue volume,
i.e., the decoders of the message, the incoming spike train may not be
the important variable; it may instead be the successful release
of neurotransmitter. Synapses transmit only a fraction of the spikes
that impinge on them, and recent work argues that mechanisms intrinsic
to the presynaptic terminal make important decisions about whether a
spike causes neurotransmission (Abbott et al., 1997 ). The point of view
taken in this paper suggests that the postsynaptic neuron may also get
to influence transmission at synaptic connections made on it.
By choosing when to generate a spike, a postsynaptic neuron can rapidly
modulate the release probability of its overlying synaptic terminals
via a decrement in extracellular calcium near its dendrites. In this
manner, a spike in the recipient neuron that propagates into dendrites
could block transmission at a connection that receives an axonal spike
a short time later. This would eliminate transmissions caused by
incoming spikes that the recipient neuron could, by some means,
anticipate. In this scenario, transmission events at synapses occur
when the postsynaptic neuron anticipates incorrectly the time of an
incoming spike that would have otherwise caused a transmission; i.e.,
transmissions act somewhat like error signals.
Noisy neurons and their bounded firing rates
The transmission block would also place a limit on the
maximal maintained firing rate of a recipient neuron. Cortical neurons tend to produce streams of spikes and silences at a temporal resolution of ~1 msec; i.e., firing rates above 1000 Hz are rare and not sustained for an appreciable number of spikes. With the idea of transmission blocks using external calcium fluctuations, a high spike
rate traveling up the dendrites (e.g., 250 Hz) could presumably block
most afferent transmission. This would eliminate input drive to the
recipient neuron, and spike production would decrease. As spike
production drops, the number of transmission blocks drops, making it
more likely that a transmission event will occur. Hence, the calcium
depletion mechanism provides a means to keep a neuron noisy by bounding
its spike production away from 0, yet beneath a relatively well-defined
maximal value.
 |
FOOTNOTES |
Received July 16, 1998; accepted Aug. 10, 1998.
This work was supported by the Center for Theoretical Neuroscience at
Baylor College of Medicine and by National Institute of Mental Health
Grant RO1 MH52797. We thank Drs. Francis Crick, Peter Dayan, Dan
Johnston, Thomas Bartol, and Saurabh Sinha for helpful comments before
the preparation of this manuscript. Help in many aspects is gratefully
acknowledged to Richard King.
Correspondence should be addressed to Dr. P. Read Montague, Center for
Theoretical Neuroscience, Baylor College of Medicine, One Baylor Plaza,
Houston, TX 77030.
 |
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