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The Journal of Neuroscience, June 1, 1999, 19(11):4472-4483
Dendritic Dynamics In Vivo Change during Neuronal
Maturation
Gang Yi
Wu,
Dong Jing
Zou,
Indrani
Rajan, and
Hollis
Cline
Cold Spring Harbor Laboratory, Cold Spring Harbor, New York 11724
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ABSTRACT |
In vivo imaging of optic tectal neurons in the intact
Xenopus tadpole permits direct observation of the
structural dynamics that occur during dendritic arbor formation. Based
on images of single DiI-labeled neurons collected at daily intervals
over a period of 6 d, we divided tectal cell development into
three phases according to the total length of the dendritic arbor.
During phase 1, the cell differentiates from a neuroepithelial cell
type and extends an axon out of the tectum. The total dendritic branch length (TDBL) is <100 µm. During phase 2, when TDBL is 100-400 µm, the dendritic arbor grows rapidly. During phase 3, when TDBL is
>400 µm, the dendritic arbor grows slowly and appears stable. Neurons at different positions along the rostrocaudal developmental axis of the tectum were imaged at 2 hr intervals over 6 hr and at 24 hr
intervals over several days. Images collected at 2 hr intervals were
analyzed to determine rates of branch additions and retractions.
Morphologically complex, phase 3 neurons show half the rate of branch
additions and retractions as phase 2 neurons. Therefore, rapidly
growing neurons have dynamic dendritic arbors, and slower-growing
neurons are structurally stable. The change in growth rate and
dendritic arbor dynamics from phase 2 to phase 3 correlates with the
developmental increase in synaptic strength in neurons located along
the rostrocaudal tectal axis. The data are consistent with the idea
that strong synaptic inputs stabilize dendritic arbor structures and
that weaker synaptic inputs are permissive for a greater degree of
dynamic rearrangements and a faster growth rate in the dendritic arbor.
Key words:
activity-dependent; Xenopus; dendrite; retinotectal; glutamate receptor; plasticity
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INTRODUCTION |
The process of dendritic arbor
development and the mechanisms that control it are not fully
understood. Several studies have suggested that synaptic inputs promote
dendritic arbor development and stability. The dendritic fields of
neurons in many sensory systems are oriented with respect to their
afferent inputs (Greenough and Chang, 1988
; Katz and Constantine-Paton,
1988
; Katz et al., 1989
; Schweitzer, 1991
; Kossel et al., 1995
), likely
because of either directed growth or stabilization of local
dendrites by afferents. In dissociated cell cultures, afferents appear
to operate locally to sculpt the dendritic arbor (Mattson et al., 1988
;
Kossel et al., 1997
). Time-lapse images of developing axons and
dendrites in cultured hippocampal slices suggest that contacts between
presynaptic and postsynaptic elements stabilized dendritic
branches (Dailey and Smith, 1996
; Ziv and Smith, 1996
). Manipulations
of excitatory or inhibitory transmitter systems in brain slice
preparations and in vivo lead to changes in dendritic arbor
development (Kalb, 1994
; Vogel and Prittie, 1995
; McAllister et al.,
1996
; Sanes and Hafidi, 1996
; Rajan and Cline, 1998
), suggesting that
the influence of afferents is not based solely on physical contact. Information on the time course of development of the dendritic arbor in
intact tissue has for the most part been generated from static images
of neurons collected at different stages of development, which do not
permit one to determine dynamic structural changes that contribute to
neuronal development. In vivo time-lapse observations of
dendritic growth during synaptogenesis would provide valuable information on the potential mechanisms controlling dendritic arbor development.
The optic tectum of Xenopus laevis is organized along
a rostrocaudal maturational gradient, such that neurons in rostral and lateral tectum are chronologically older and morphologically more complex than those located in the younger caudomedial pole of the
tectum (Straznicky and Gaze, 1972
; Lázár, 1973
). The
synaptic physiology of tectal neurons also follows a maturational
program that follows the rostrocaudal developmental gradient (Wu et
al., 1996
). Young neurons in caudal tectum receive glutamatergic
retinal synapses that are mediated principally by the NMDA type
glutamate receptor (NMDA R). As the neurons mature, their somata are
displaced rostrolaterally by newly generated cells in the caudomedial
germinal zone (Straznicky and Gaze, 1972
), and their retinotectal
synapses strengthen as a result of the addition of AMPA R-mediated
currents (Wu et al., 1996
). Therefore, both synaptic strength and
morphological complexity increase along the rostrocaudal development
axis in the tectum, and these two aspects of neuronal maturation are
concurrent (Wu et al., 1996
; Rajan and Cline, 1998
; Wu and Cline,
1998
). In experiments correlating the strength of synaptic inputs with the sensitivity of the dendritic arbor development to glutamate receptor blockade, dendritic arbor growth was most severely impaired early during development of the arbor when glutamatergic synapses were
mediated principally by NMDA R. More mature neurons were less sensitive
to glutamate receptor blockade (Rajan and Cline, 1998
). These data
suggest that more mature neurons with strong synaptic inputs have more
stable dendritic arbors than younger neurons, which receive weaker inputs.
To determine whether dendritic arbor stability correlates with the
strength of synaptic inputs, we collected in vivo time-lapse images of single optic tectal neurons at different locations along the
rostrocaudal axis of the tectum over periods of 3-6 d. We find that
the dynamic rearrangements of the developing tectal cell dendritic
arbors change as the neurons mature; younger neurons with simple
dendritic arbors are in a rapid growth phase and exhibit rapid
dendritic arbor dynamics. More mature neurons with complex dendritic
arbors grow more slowly and are significantly less dynamic. These
observations indicate that in vivo dendritic arbor dynamics in individual neurons change in a manner that is correlated with the
strength of their synaptic inputs. The data support the idea that
strong synaptic inputs stabilize dendritic arbor structure.
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MATERIALS AND METHODS |
Image acquisition. Albino Xenopus
laevis tadpoles were obtained by matings induced by human
chorionic gonadotropin injections. Single optic tectal neurons in stage
39-48 tadpoles (Nieuwkoop and Faber, 1956
) were fluorescently labeled
by 1,1'-dioctadecyl-3,3,3',3'-tetramethylindocarbocyanine perchlorate
(DiI) iontophoresis (0.02% in absolute ethanol; Molecular Probes, Eugene, OR), as described in detail previously
(Cline et al., 1999
). Briefly, 1-10 nA of positive current were
applied in 3-10 pulses of 200 msec duration. This results in a tiny
crystal deposit of DiI near the cell body. The dye intercalates into
the plasma membrane and rapidly labels the entire plasma membrane, based on observations that fine filopodia at distal tips of dendrites and axons are dye-labeled. Two hours after dye labeling, animals were
screened for those with single DiI-labeled neurons. Confocal images
were collected through the entire Z dimension of single dye-labeled
neurons using a Noran Instruments (Middleton, WI) XL laser scanning
confocal attachment mounted on an upright Nikon (Tokyo, Japan) Optiphot
equipped with a 40× Nikon lens (0.8 NA). Each optical section is an
average of 8-16 frames and is separated from the next optical section
in the Z dimension by 1-4 µm. Dye injection, screening, and imaging
were done in animals anesthetized with 0.02% 3-aminobenzoic acid ethyl
ester (MS222) (Sigma, St. Louis, MO) in Steinberg's rearing solution.
Animals recovered from anesthetic between imaging sessions, except when
images were collected at 10 min intervals. For these experiments,
animals remained anesthetized throughout the imaging session.
Image analysis. Line drawings of the images were produced by
tracing each optical section in series onto an acetate sheet until the
entire arbor was completed. This type of three-dimensional reconstruction provides a more detailed representation of the morphology than the computer generated three-dimensional image, because
finer processes visible in the individual optical sections are lost in
the computer-generated reconstructions. The number of branch tips was
manually counted. To measure total dendritic branch length
(TDBL), the line drawings were scanned into a Macintosh personal
computer, and the NIH Image program 1.61 was used to skeletonize the
image and measure the total dendritic branch length. Branch dynamics
were assessed by superimposing drawings from sequential time points.
Additions and retractions of branches for each time point were
tabulated. Statistical significance was estimated using the two-tailed
t test.
BrdU labeling. BrdU labeling reagent (Zymed, San Francisco,
CA) was diluted 1:10 in PBS with 0.1% fast green, and ~200 nl was
injected into the tectal ventricle. Animals were fixed in 4%
paraformaldehyde either 2 hr or 6 d later, and horizontal cryostat sections through the brains were processed for BrdU
immunohistochemistry according to the manufacturer's protocol.
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RESULTS |
Morphogenesis of the tectum
Retinal ganglion cells first innervate the optic tectum at stage
39/40, when the tectum consists of narrow bilateral lobes on the roof
of the midbrain (Holt, 1989
). Tectal cells are generated in a
crescent-shaped proliferative zone extending through the caudal and
medial borders of the optic tectum (Fig.
1). The continuous production of new
cells in the proliferative zone results in extension of the tectum
caudally and medially. By stage 46, the lobes of the tectum have grown
medially to meet at the midline so the dorsal midbrain obtains a
distinct hourglass appearance. At the same time, the tectum thickens
dorsoventrally as a result of cell addition and the growth of the
existing cells. The majority of DiI-labeled cells that we observed in
stage 39/40 tecta were extremely simple in structure. The cell bodies
extend a single process oriented laterally and rostrally (Fig. 1).
Animals of these stages are still feeding off their yolk and exhibit no
detectable visually guided behaviors.

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Figure 1.
Gross morphogenesis of the tectum.
A, Superimposition of images of a single optic lobe from
an animal injected with BrdU at stage 40, 6 d before being killed,
and an animal injected with BrdU, 2 hr before being killed at stage 48. The cells that incorporated BrdU at stage 40 (green) were displaced rostrally and laterally
over the 6 d period by more recently added cells in the
caudomedial proliferative zone. Cells that incorporated BrdU 2 hr
before being killed and that therefore mark the proliferative zone are
shown in red. The border of the tectum is outlined in
blue. B-D, Summary drawings showing
morphological complexities of optic tectum cells labeled by DiI
iontophoresis and imaged by confocal microscopy in vivo
in stage 39, stage 44, and stage 48 tadpoles, respectively. Cells shown
are representative of the range of complexities of cells imaged at each
stage. For simplicity, axons of complex cells were omitted.
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Albino tadpoles progress from stage 40 to 42 in ~14 hr at room
temperature. Behaviorally, stage 42 tadpoles are mostly immobile. Touch
and vibration result in escape behaviors: frantic short bouts of
swimming, after which the animal is again immobile. Neurons with
slightly more complex morphologies could be dye-labeled in the rostral
tectum at stage 42 compared with those seen at stage 40. Cells in the
caudal tectum of these animals were morphologically simple, consistent
with their recent differentiation (Fig. 1C). Retinal
innervation has increased by this stage; however, the majority of
retinal axons are still extremely simple in their morphology (Sakaguchi
and Murphey, 1985
). Retinal stimulation results in glutamatergic
synaptic responses mediated by both NMDA and AMPA type glutamate
receptors (Zhang et al., 1998
).
Approximately 2 d later, when animals reach stage 46, they are
behaviorally more active and exhibit visually responsive behaviors. At
this stage, the rostrocaudal gradient of morphological development of
tectal neurons is more pronounced than in younger stages; in rostral
tectum, neurons of different morphological classes, such as
interneurons, and efferent neurons with rostrally or caudally projecting axons can be identified by DiI labeling, whereas cells in
caudal tectal include undifferentiated neuroepithelial cells and
recently differentiated neurons and glia.
Animals reach stage 47 the following day. They begin to swim
continuously as they feed and are visually responsive. Whole-cell recordings from tectal neurons in animals of stage 46 and older reveal
a clear rostrocaudal gradient of glutamatergic responses in which
rostral neurons have stronger synapses, with a relatively large
proportion of synaptic current mediated by the AMPA R, with neurons in
progressively more caudal locations in the tectum having lower
AMPA/NMDA ratios in their glutamatergic retinal synaptic currents (Wu
et al., 1996
). At this time, the tectum has become laminated, and many
of the morphological cell types identified by Lázár (1973)
in Golgi stained stage 49 tadpole tectum can be identified in
DiI-labeled material.
Overall pattern of dendrite arbor elaboration
To determine the time course of dendritic arbor development,
single DiI-labeled neurons were imaged at daily intervals over a period
of 5-6 d (Fig. 2). For this series of
experiments, cells were labeled and imaged in animals starting at stage
46 and followed through the imaging period to stage 48; however, the
general pattern of morphological development that we describe occurs
for newly generated neurons in animals at least through stage 49 and
likely throughout the later tadpole stages of development.

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Figure 2.
Dendritic arbor development. A,
Drawings of a neuron imaged at daily intervals over a period of 6 d. The arrowhead marks the efferent axon.
B, Change in TDBL for neurons imaged over 5-6 d
(n = 8). Scale bar, 25 µm.
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This paper includes an analysis of projection neurons, which extend an
axon either rostrally or caudally out of the optic tectum. The efferent
axon of the neurons is marked by an arrowhead in the
figures. Cells located at the caudomedial pole of the tectum were
selected for imaging. In general, these neurons have extremely simple
morphologies on the first day and typically do not increase their
dendritic arbor branch length significantly over the first day of
imaging. Over the next few days, the dendritic arbor rapidly elaborates, after which it appears to grow more slowly (Fig.
2B). Based on these observations, we divided
development of the dendritic arbor into three distinct phases according
to their growth rates. Phase 1 is the initial period of development
during which the neuron differentiates from a neuroepithelial cell type
and extends an efferent axon toward lateral tectum. During this period,
there is little significant increase in dendritic branch length. Phase 2 is a period of rapid dendritic arbor growth, and phase 3 is a later
period of slower branch growth. Furthermore, neurons could be
categorized as phase 1, phase 2, or phase 3 based on measurements of
their TDBL. In general, phase 1 neurons have TDBL of less than ~100
µm, phase 2 neurons have TDBL ranging from ~100-400 µm, and phase 3 neurons have TDBL >400 µm. Shorter interval observations indicate that the transition between phases 2 and 3 is gradual (Rajan
et al., 1999
). Synaptic physiology also matures during these phases: in
phase 1 neurons, no retinotectal evoked synaptic responses are
recorded; phase 2 neurons have retinal glutamatergic responses with low
AMPA/NMDA ratios; and phase 3 neurons have higher AMPA/NMDA responses
(Wu et al., 1996
; Rajan and Cline, 1998
). Because the magnitude of the
AMPA R-mediated current recorded near the resting potential of the
neuron is a measure of the strength of synaptic transmission (Hestrin
et al., 1990
), these data suggest that dendritic arbor growth rate
might correlate with the strength of glutamatergic synaptic inputs to
the neuron.
We analyzed a total of 96 neurons imaged at different locations along
the rostrocaudal gradient of development in the optic tectum to test
whether growth rate correlates with dendritic branch length. Many of
these neurons passed through two phases of development (i.e., phase 1 to 2 or phase 2 to 3) over the time course of the observations.
Approximately half of the neurons were also imaged at 2 hr intervals
within the first day of the experiment to test whether the dynamic
rearrangements in dendritic arbors correlate with growth rates and
whether dendritic dynamics change with the strength of synaptic inputs.
Three-dimensional reconstructions of the in vivo images are
shown, as well as drawings of the neuron generated from each of the
optical sections. The drawings show more detail and were used for
quantification of dendritic growth. Further details of phase 1 of
development are not included in this paper, because this phase does not
include significant dendritic arbor elaboration.
Phase 2 of dendritic arbor development
Three examples of phase 2 tectal neurons are shown in Figures
3-5
to demonstrate the range of dynamic behaviors and growth rates observed. The neuron in Figure 3 was among the simplest phase 2 neurons
imaged, with the dendritic branch length measuring 125 µm at the
first image. The dendritic arbor develops as a profusion of fine
branches extending from a major apical process. Fine branches are added
and retracted from these initial branches, as seen in the observations
collected at 2 hr intervals. In this neuron, there is little net
increase in dendritic arbor branch length over the first 24 hr
period, but growth rate increases rapidly over the next 24 hr and is
maintained for the next several days.

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Figure 3.
Initial dendritic arbor development. Time-lapse
confocal images (A) and drawings
(B) of an early phase 2 neuron collected at time
points specified. Dendritic branch length at the first image was 125 µm. The axon is distinguishable as a thin unbranched process
extending toward lateral tectum. The dendritic arbor starts as a
profusion of fine filopodial branches extending from an apical process.
The dendritic branches rearrange considerably over the first 6 hr of
imaging. There is little net growth of the arbor, even over 24 hr (TDBL
at 6 hr, 170 µm; TDBL at 24 hr, 200 µm), but the arbor does enlarge
by the 48 hr time point. At the 48 hr time point, a branch emerges from
the axon, which exits the tectum rostrally at the 72 hr time
point.
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Figure 4.
Early stages of dendritic arbor development.
Time-lapse confocal images (A) and drawings
(B) of a phase 2 neuron collected at time points
specified. Dendritic branch length at the first image was 140 µm, 170 µm at 6 hr, and 400 µm at 24 hr. Note the large dendritic growth
cone at the first image and the dramatic rearrangements revealed by the
short interval observations for 0-6 hr. A second efferent axon exits
the tectum rostrally at the 48 hr time point.
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Figure 5.
Dendritic arbors are dynamic in rapidly growing
neurons. Images (A) and drawings
(B) of a phase 2 neuron collected at time points
specified. Dendritic branch length at the first image was 240 µm.
Note the dendritic dynamics at short observation intervals and the
rapid increase in branch length over each day of imaging. The cell body
was not included in the reconstruction of the 48 hr image. Scale bar:
A, B, 25 µm; inset in
B, 50 µm.
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The neuron shown in Figure 4 illustrates several types of dynamic
rearrangements in the dendrites of these young neurons. Images
collected at 2 hr intervals reveal that dendritic branches extend and
retract repeatedly. A large growth cone tips one of the major dendritic
branches; however, this growth cone is not the site of a branch point
seen at the following observation. Indeed, that branch does extend over
the next 4 hr but is almost completely retracted at the 6 hr
observation and does not reappear at later time points. The arbor
transiently increases in branch tip number and branch length at the 4 hr time point, but many branches are retracted by the following
observation, so this growth spurt did not contribute to net growth of
the arbor. These rapid rearrangements are comparable with those
described in tectal neurons of zebrafish (Kaethner and Stuermer,
1997
).
The dendritic arbor significantly increases in TDBL from 140 µm at 0 hr to 400 µm at 24 hr. Despite the increased dendritic branch length,
the arbor does not appear to cover significantly more tangential area
in the tectum than it did at the earlier 4 hr time point, because the
dendritic arbor became more densely branched. The arbor continues to
increase in branch length and branch number over the next 2 d of
imaging. By the 24 hr time point, this neuron has extended a second
axonal branch tipped with a lamellar growth cone. Both axons
subsequently exited the tectum. The additional relatively unbranched
processes toward the rostral tectum in this neuron may be a local axon
arbor, as seen in a minority of neurons imaged. The local axon arbor
elaboration is typically delayed until after the dendritic arbor has
already become complex.
When neurons whose cell bodies were positioned rostrally and laterally
from the proliferative zone were labeled, the first images revealed
neurons with dendritic arbors somewhat more complex than the simple
neurons located close to the caudal pole of the tectum (Fig. 5),
consistent with the rostrocaudal gradient of morphological development
in the optic tectum (Lázár, 1973
; Wu and Cline, 1998
).
Figure 5 shows such a phase 2 neuron, measuring 240 µm at the first
observation. The dendritic arbor of this neuron included many branch
tips with growth cones and fine filopodia. Note the high degree of
rearrangements in the dendritic branches from one 2 hr observation to
the next in this neuron and the other phase 2 neurons in Figures 3 and
4. The dendritic rearrangements include addition of new branches,
complete retraction of branches, as well as both extension or
shortening of branches that were present in the previous observation.
The dendritic arbors of these phase 2 neurons grew rapidly over the
next 48 hr. The axon of the neuron shown in Figure 5 sent projections
both rostrally to the contralateral tegmentum via the posterior
commissure and caudally to the spinal cord.
Phase 3 of dendritic arbor development
Neurons with cell bodies located further rostrally and laterally
within the optic tectum have more complex dendritic arbors at the first
day of imaging (Figs. 6,
7). Compared with the rapid increases in
dendritic arbor elaboration seen in the neurons in Figures 3-5, the
arbors of these more complex neurons are remarkably similar from one
observation to the next, indicating that slower-growing neurons also
have more stable dendritic arbors. Despite the overall structural
similarity in the dendritic arbors over days of imaging, the 2 hr
observations do show branch additions and retractions at each 2 hr
interval, indicating that complex neurons are capable of modest
structural rearrangements. As the neurons elaborate their dendritic
arbor, continual cell proliferation in the caudomedial proliferative
zone of the tectum adds cells so the cell bodies of the differentiated
neurons occupy positions more rostrally and laterally within the tectum
(Fig. 7, insets).

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Figure 6.
Later stages of dendritic arbor development.
Images (A) and drawings (B)
of a phase 3 neuron collected at time points specified. Dendritic
branch length at the first image was 580 µm. Note the structural
stability of the dendritic arbor over the 3 d of
imaging.
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Figure 7.
Dendritic arbors are stable in morphologically
complex neurons. Images (A, C) and
drawings (B, D) of two phase 3 neurons
collected at the time points specified. Dendritic branch lengths at the
first image were 580 and 450 µm for the cells in A and
C, respectively. Insets in
B and D show rostrolateral shift in cell
body location as the cells mature. Dendritic arbor structures are very
similar from the first to last observations. Fine dendritic
rearrangements do occur, even in complex neurons.
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Localized dendritic arbor growth
Neurons can display clear regionalized elaboration (Figs. 4,
8). For the neuron shown in Figure
8A, a burst of short branches is added to the neurons
at the arrow between the 1 and 2 hr time points. Over the
following 2 hr, longer branches emerge at the same site. Other regions
of the arbor also become more elaborate. In particular, one branch,
marked by the arrowhead, adds many side branches, which
rearrange again before the 6 hr time point. For the neuron in Figure
8B, the part of the arbor on the left shows localized branch retraction followed by branch additions, whereas
the portion of the arbor on right of the figure shows less
net growth over the 6 hr observation period. It is not clear whether
the localized growth in these latter 2 neurons will result in
longer-lasting regional bias in dendritic elaboration or whether the
local elaboration is transient as in the neuron in Figure 4.

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Figure 8.
Regionalized dendritic elaboration. Images
collected at the designated intervals for either phase 2 (A) or phase 3 (B) neurons
show regionalized dendritic arbor growth (arrows and
arrowhead).
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Quantification of dendritic arbor growth parameters
Neurons showed different growth rates that correlated with their
TDBL on the first day of imaging (Fig.
9), supporting the idea that dendritic
development can be divided into phases that correlate with the
dendritic arbor size and growth rate of the arbor. Phase 2 neurons are
characterized by a rapid growth rate of the neurons, in terms of
increases in dendritic branch length, branch tip numbers, and arbor
density (data not shown). The increases in numbers of dendritic
branch tips change in a parallel manner to the branch length during
phase 2 (Fig. 9B), indicating that dendritic arbor
development involves a coordination of mechanisms controlling new
branch additions and extension of branches. For phase 3 neurons, TDBL
continues to increase, although branch tip numbers remain constant.
This suggests that more complex neurons continue to elaborate by
increasing segmental branch lengths rather than adding new
branches,

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Figure 9.
Coordinate changes in multiple features of the
dendritic arbor with phases of dendritic arbor development.
A, Total dendritic branch length. B,
Dendritic branch tip number, graphed for each day of imaging. Neurons
were divided into phases 1, 2, or 3 based on TDBL measurements on the
first day of imaging. Because phase 1 lasts ~24 hr, neurons that
start as phase 1 transition into phase 2 during the 3 d
observation period. C, Growth rates for phases 1, 2, and
3 neurons. D, Sholl analysis of dendritic arbors from
phase 2 (black squares) and phase 3 neurons
(gray circles).
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Sholl analysis was used to quantify complexity and tangential extent of
dendritic arbors from neurons at different phases of development (Fig.
9D). Phase 2 neurons were significantly less complex than
phase 3 neurons and covered less tectal area than phase 3 neurons.
Phase 2 neurons had a maximum of 3.75 ± 0.3 branches crossing the
concentric rings, whereas phase 3 neurons had a maximum of 7.25 ± 0.4 branches crossing. Furthermore, phase 3 neurons extended as far as
140 µm from the cell body, whereas phase 2 neurons extended
only 100 µm from the cell body.
Quantification of dendritic dynamics in phase 2 and phase
3 neurons
To test whether dynamic rearrangements of rapidly growing phase 2 neurons are greater than the slower-growing phase 3 neurons, we
analyzed the images of neurons collected at 2 hr intervals over a
period of 6 hr. This protocol allows us to identify every branch in the
dendritic arbor at each time point and to compare changes in dendritic
branches by superimposing drawings of the neurons from sequential
observations. A 2 hr imaging protocol is sufficiently frequent to
permit accurate superimposition of drawings from each time point while
also being sufficiently long to permit significant changes in branch
tip numbers and branch length during the observation period. We
determined the rates of branch additions and retractions at each 2 hr
time point and over the 6 hr observation period (Fig.
10). We analyzed two additional parameters indicative of arbor stability: the skeleton of the arbor, or
the fraction of branches that persist throughout the 6 hr observation
period, and the average relative lifetime of branches.

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Figure 10.
Dendritic arbor stability increases with neuronal
maturity. A, Branch dynamics. Initial and final branch
numbers and cumulative branch additions and retractions in phase 2 (black bars; n = 19) and phase 3 (gray bars; n = 10) neurons
over the 6 hr observation, graphed relative to initial branch tip
number. B, The skeleton, or the fraction of branches
that persists through the observation period, for phase 2 and phase 3 neurons. C, The average relative lifetime of branches in
phase 2 and phase 3 neurons. **p < 0.001.
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Phase 2 neurons average ~14.4 ± 1.3 (n = 19)
branch tips at the initial observation and add ~10 branches at each
of the 2 hr intervals. Slightly fewer branch tips are retracted at each of the time points than are added over the same interval. These constant rates of branch additions and retractions over the observation period, as well as the continuous elaboration of the dendritic arbor
after the 6 hr period, indicates that the imaging protocol is not
detrimental to the neuronal growth rate. Summed over the 6 hr period,
phase 2 neurons add approximately twice as many branches (28.3 ± 1.9) as are initially present. Again, fewer branches are retracted
(25.4 ± 2.3), such that the branch tip number at the final
observation (18.6 ± 1.7) is significantly greater
(p < .05) than the initial branch tip number.
Phase 3 neurons have approximately twice as many branch tips at the
initial observation as phase 2 neurons (34.7 ± 4.8;
n = 10). At each 2 hr time point, the more complex
neurons add and retract an average of ~10 branches, so that the final
branch tip number (32.5 ± 3.5) is not significantly different
from the initial value.
We observed two principle differences in the dynamics of phase 2 and
phase 3 neurons. (1) The phase 3 neurons are structurally more stable
that phase 2 neurons. The relative rates of branch additions and
retractions of phase 3 neurons is half that in phase 2 neurons (Fig.
10A). The fraction of the branches that persist throughout the 6 hr observation period, or the skeleton, is
significantly greater in phase 3 neurons than phase 2 neurons. In
addition, an analysis of the lifetimes of new branches added during the 6 hr observation period indicates that branches in phase 3 neurons have
a longer lifetime than those in phase 2 neurons. (2) The second
principle difference between phase 2 and 3 neurons is that rearrangements in phase 3 neurons are confined to short branch tips
within the complex arbor (Figs. 6, 7), whereas phase 2 neurons show
larger structural changes over the same 2 hr periods (Figs. 3-5).
Short-term dendritic dynamics
To illustrate the difference in dynamics between phase 2 and phase
3 neurons, we collected images of neurons at 10 min intervals and
superimposed three of these images. Portions of the dendritic arbor are
color coded according to the degree to which the branches were
superimposable (Fig. 11). White
branches were completely superimposable for all the time
points, and colored branches do not superimpose during
the different time points. The complex phase 3 neuron in Figure
11B is mostly white with a little color at some
branch tips. This indicates that the structure of this neuron is very
stable over the imaging period. In contrast, the phase 2 neuron is very colorful in all the dendritic branches. Only the soma and proximal dendritic regions are white, indicating that they are the only stable
portions of the neuron during this imaging period.

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Figure 11.
Colorized dendritic arbors show sites of branch
dynamics. Composite images of a phase 2 (A) and
phase 3 (B) neuron, each imaged three times at 10 min intervals and pseudocolored to show dynamics of dendritic branches
in superimposed images. The first image is red, the
second is green, and the third is blue.
White portions of the arbor are stable, and
colored branches are dynamic over the imaging
period.
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DISCUSSION |
High-resolution confocal time-lapse images of single neurons in
the Xenopus optic tectum were collected over periods of
days. Our data demonstrate that neurons have different dendritic arbor growth rates and branch dynamics. Because electrophysiological recordings cannot be taken from the same neurons from which we collected time-lapse images, we compared the dynamics of the dendritic arbors from the imaging experiments with the properties of retinotectal synaptic physiology from neurons occupying similar locations along the
rostrocaudal axis of the tectum (Wu et al., 1996
). Our previous experiments have shown that, during this time, synaptic responses mature from relatively weak, low AMPA/NMDA synapses to stronger, high
AMPA/NMDA synapses. Therefore, the data further suggest that growth
rates and branch dynamics correlate with synaptic maturation; neurons
with relatively simple dendritic arbors have low AMPA/NMDA ratios (Wu
et al., 1996
), rapid dendritic growth rates, and rapid arbor dynamics.
Neurons with more complex dendritic arbors and higher AMPA/NMDA ratios
have slower growth rates and fewer dendritic branch rearrangements.
In vivo imaging of dendritic dynamics
We categorized tectal cell development into three phases. During
phase 1, neurons differentiate from neuroepithelial progenitors, and
projection neurons extend their efferent axon. Further details of phase
1 of development are not included in this paper. Phase 2 neurons are
characterized by dendritic arbors within ~100-400 µm TDBL, a rapid
dendritic growth rate, and rapid arbor dynamics. Phase 3 neurons have
dendritic arbors with >400 µm TDBL, slower growth rates, and fewer
dendritic branch rearrangements.
Phase 2 neurons grow rapidly and show dramatic rearrangements in the
dendritic arbor over 2 hr intervals and even over 10 min intervals
(Fig. 11). The rearrangements include addition of new branches,
complete retraction of branches, as well as both extension or
shortening of branches that were present in the previous observation.
Slightly more branch additions than retractions occur over 6 hr, which
accounts for the net increase in arbor elaboration over longer periods.
Branches are added at any point along a parent dendrite, indicating
that backbranching is a means of dendritic arbor growth in
vivo, as has been shown previously for axon arbor elaboration
(Harris et al., 1987
; O'Rourke et al., 1994
). Growth cones are often
seen with active lamellopodial and filopodial rearrangements,
characteristic of exploratory behaviors. Arbors show a coordinated
increase in branch length and branch tips, indicating that dendritic
arbors do not develop first by extending long branches that
subsequently add side branches.
Time-lapse imaging of morphologically complex phase 3 neurons indicates
that they continue to exhibit modest dynamic rearrangements in their
branch tips, consistent with their continued elaboration during later
phases of development (Lázár, 1973
). Dendritic stabilization is caused by a decreased rate of branch retractions, consistent with the stabilization of synaptic contacts and their supporting branches. Stabilization is also caused by a decreased rate
of branch additions. This decreased rate of branch additions is not
necessarily predicted from the hypothesis that strong synapses stabilize dendritic structure and suggests that a stop-growing signal
exists, which decreases rates of branch additions in response to
increased synaptic strength.
Structural dynamics and synaptic strength
The higher growth rate and rapid structural dynamics of phase 2 neurons correlate with the presence of relatively weak retinotectal inputs, mediated principally by NMDA R, in this group of neurons. The
slower growth rate and stable dendritic structure of phase 3 neurons
correlate with the stronger synaptic inputs, with high AMPA/NMDA
ratios, which these more mature neurons receive. Because the amplitude
of the NMDA currents do not change significantly over the developmental
window we have examined (Wu et al., 1996
), the increased AMPA/NMDA
ratio represents an increased amplitude of the AMPA R-mediated synaptic
currents during neuronal maturation. The data support the model that
strong synaptic inputs stabilize dendritic arbors; however, we suggest
a modification of the model in two respects. First, we suggest that
silent or pure NMDA R-mediated synapses provide a means by which
synapses can form, which will have no impact on the activity of the
postsynaptic neuron unless that input is coactive with the tectal cell.
In a visual projection that is actively establishing and maintaining a
retinotopic projection, the ability to form such trial synapses to test
for coactivity without degrading information transfer would seem to be
a distinct advantage (Cline et al., 1997
). We suggest that the pure
NMDA trial synapses would retract if they were not coactive with tectal cell activity, and the presynaptic and postsynaptic branches may also
retract. This might account for a large degree of structural dynamics
in young neurons that have a large fraction of their synapses mediated
solely by NMDA R. Second, we suggest that the addition of AMPA R and
the stronger synaptic transmission that comes with the addition of AMPA
R-mediated responses stabilize the dendritic arbor. Arbor stability can
then be dynamically regulated as synaptic strength can be dynamically
regulated. Weaker inputs, with lower amplitude AMPA responses, permit
the dendritic arbor to undergo greater structural rearrangements.
Greater dendritic dynamics correlate with a faster arbor growth rate,
suggesting some relationship between high rates of branch additions and
retractions and net growth of the arbor.
Inherent in this model is the idea that branches supporting weaker
synaptic inputs remain dynamic, even in mature neurons. Indeed,
recordings from mature neurons in rostral tectum show that they
continue to have some synapses mediated principally by NMDA R (Wu et
al., 1996
), and we do observe fine branch dynamics in phase 3 neurons
imaged at 2 hr intervals (Figs. 6, 7). Furthermore, the model predicts
that modifying synaptic strength will lead to corresponding changes in
branch dynamics. In support of this idea, we found that blocking AMPA
receptors led to modest increases in rates of branch retractions and a
decrease in TDBL in complex neurons with high AMPA/NMDA ratios (Rajan
and Cline, 1998
) and that increasing synaptic strength by expressing
CaM kinase II (CaMKII) in tectal neurons decreased dendritic
dynamics (Wu et al., 1996
; Wu and Cline, 1998
). It would be interesting
to see whether experimental conditions that result in reorganization of
sensory projections and a recapitulation of the developmental program
of synaptic maturation, as seen in the prism-shifted visual projection
of the barn owl (Feldman et al., 1996
; Feldman and Knudsen, 1997
,
1998
), also result in an increase in structural dynamics of those
neurons with increased NMDA receptor-mediated responses.
As mentioned above, we reported previously that increased CaMKII
activity in tectal neurons increases the amplitude of AMPA R-mediated
synaptic currents (Wu et al., 1996
) and stabilizes dendritic arbor
structure (Wu and Cline, 1998
). These experiments suggest that an
interaction between strong synaptic inputs and CaMKII activity may
stabilize dendrites. Indeed, the developmental decrease in arbor
dynamics from phase 2 to phase 3 neurons (Fig. 10) is comparable with
the decreased dynamics seen in phase 2 neurons when CaMKII is expressed
by viral gene transfer (Wu and Cline, 1998
). This supports our previous
conclusion that the developmental increase in tectal cell CaMKII
expression provides them with a mechanism to translate strong synaptic
input into stable dendritic structure. The interplay between glutamate
receptor activity, CaMKII, and as yet undefined downstream effectors
that control cytoskeletal assembly and disassembly remain an area of
active research effort. Glutamate receptor activity and CaMKII can
activate a RasGTPase (SynGap) (Chen et al., 1998
; Kim et al., 1998
).
Although the ras signaling pathway is known to activate gene
transcription via mitogen-activated protein kinase, recent
evidence also indicate that ras may regulate actin cytoskeletal
dynamics (Leblanc et al., 1998
; Sharma, 1998
; Harden et al., 1999
),
suggesting a mechanism by which dendrite dynamics can be locally
controlled by synaptic activity.
A developmental decrease in dendritic branch dynamics has been observed
previously in hippocampal slice cultures (Dailey and Smith, 1996
) and
dissociated hippocampal neuronal cultures (Ziv and Smith, 1996
). Using
dissociated hippocampal neuronal cultures in which the presence of
synapses was assessed by uptake of FM 4-64 into presynaptic sites, Ziv
and Smith (1996)
demonstrated that FM 4-64-labeled presynaptic sites
were associated with persistent dendritic branches compared with the
dynamic dendritic branches, which were apparently without presynaptic
contact. Although Ziv and Smith (1996)
concluded that synaptogenesis
stabilizes dendritic branches, our data indicate that it is more likely
the addition of AMPA R and the increased synaptic strength that comes
about with the addition of these receptors that specifically promotes dendritic arbor stability rather than synaptogenesis per se.
Many factors contribute to the regulation of dendritic arbor
development. These may be as diverse in mechanisms of action as
developmental expression of adhesion molecules and their receptors (Lander et al., 1997
), metabotropic glutamate receptors (Zirpel and
Rubel, 1996
; Reid et al., 1997
; Liu et al., 1998
), neurotrophins (McAllister et al., 1995
), activity-induced genes (Nedivi et al., 1998
), or the developmental changes in responses to transmitters (Cherubini et al., 1991
; Hestrin, 1992
). In addition, many of these
regulatory factors develop concurrently and are interdependent in their
actions on the development of neuronal structure and function.
Therefore, our observations that a developmental decrease in dendritic
arbor stability correlates with increased synaptic strength represents
a first step in determining the mechanisms through which synaptic
inputs can regulate dendritic structure.
Afferents inputs and dendritic arbor orientation
The dendritic arbors of tectal neurons we imaged are highly
polarized, with the arbor extending rostrally and laterally toward the
retinal afferents. In some cases, such as the neurons shown in Figures
4 and 8, we observed clear regionalized arbor elaboration and
regionalized retractions. Such localized branch elaboration may reflect
the trophic effect of inputs on dendritic arbor growth and over time
would be expected to result in a polarized dendritic arbor. A trophic
effect of afferents has been convincingly demonstrated in the auditory
system in which different afferents terminate on different portions of
the dendritic arbor in neurons in nucleus laminaris, which
exhibit an increase in dendritic arbor complexity that correlates with
afferent ingrowth (Smith and Rubel, 1979
). Deafferentation of specific
afferents leads to selective atrophy of the corresponding part of the
dendritic arbor (Gray et al., 1982
; Smith et al., 1983
; Deitch and
Rubel, 1984
). Katz and Constantine-Paton (1988)
noted previously a
rostral bias in dendritic arbor elaboration in tectal neurons from
postmetamorphic Rana pipiens and suggested that it might be caused by a
trophic influence of retinal afferents. We subsequently reported that
NMDA R activity promotes dendritic arbor development by increasing
rates of branch additions and branch length extensions (Rajan and
Cline, 1998
), supporting the idea that glutamate released from retinal
afferents acts trophically to increase dendritic growth in phase 2 neurons. The data in the present study provide evidence for a distinct
effect of glutamatergic inputs in stabilizing dendritic arbor structure
in more mature phase 3 neurons. It appears that, during phase 2 of
dendritic arbor elaboration when AMPA/NMDA ratios are low, glutamate,
acting through NMDA R, may have a trophic effect on tectal neuronal
dendrites, promoting branch additions and branch lengthening. Such a
trophic effect could be mediated through tyrosine kinases, which form a
complex that may be activated by NMDA R (Tezuka et al., 1999
). In more mature phase 3 neurons that already receive strong synapses, glutamatergic inputs now shape the dendritic arbor in a distinct manner
by stabilizing those branches with the strong synaptic inputs.
Conclusion
Here, we use in vivo imaging techniques with vital dyes
to observe the development and structural dynamics of optic tectal cells. By taking images of DiI-labeled cells at short intervals, we
have been able to directly observe rapid morphological dynamics in
neurons. Images collected at longer intervals reveal larger scale
structural rearrangements in these cells. Neuronal development can be
divided into three phases according to the dendritic arbor size and
growth rate. Phase 2 neurons are in a rapid growth phase, and growth
rate slows down when the dendritic arbor reaches a mature size,
measured as TDBL. One of the striking findings that we report here is
the great degree to which neurons modify their dendritic structure.
Furthermore, we find that dendritic arbor dynamics change in a
consistent manner during the development of the arbor, such that
rapidly growing phase 2 neurons are twice as dynamic as phase 3 neurons. As neurons mature, the increased structural stability is
concurrent with an increase in the strength of retinotectal synaptic
inputs. These data are consistent with the idea that strong synaptic
inputs stabilize the dendritic arbor.
 |
FOOTNOTES |
Received Dec. 21, 1998; revised March 19, 1999; accepted March 22, 1999.
This work was supported by the Hoffritz Trust, the National Science
Foundation, and National Institutes of Health. We thank Kim Bronson for
excellent technical assistance and David Baek, Dominik Rosa, and Julia
Jay for help with the data analysis.
Correspondence should be addressed to Hollis Cline, Cold Spring Harbor
Laboratory, Beckman Building, 1 Bungtown Road, Cold Spring Harbor, NY 11724.
 |
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