1Department of Mathematics, University of Pittsburgh, Pittsburgh, Pennsylvania 15260; and 2Biological Computation Research Department, Bell Laboratories, Lucent Technologies, Murray Hill, New Jersey 07974
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ABSTRACT |
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Ermentrout, B., Jing W. Wang, Jorge Flores, and A. Gelperin. Model for Olfactory Discrimination and Learning in Limax Procerebrum Incorporating Oscillatory Dynamics and Wave Propagation. J. Neurophysiol. 85: 1444-1452, 2001. We extend our model of the procerebral (PC) lobe of Limax, which is comprised of a layer of coupled oscillators and a layer of memory neurons, each layer 4 rows by 20 columns, corresponding to the cell body layer (burster cells) and neuropil layer (nonburster cells) of the PC lobe. A gradient of connections in the layer of model burster cells induces periodic wave propagation, as measured in the PC lobe. We study odor representations in the biological PC lobe using the technique of Kimura and coworkers. Lucifer yellow injection into intact Limax after appetitive or aversive odor learning results in a band or patch of labeled cells in the PC lobe with the band long axis normal to the axis of wave propagation. Learning two odors yields two parallel bands of labeled PC cells. We introduce olfactory input to our model PC lobe such that each odor maximally activates a unique row of four cells which produces a short-term memory trace of odor stimulation. A winner-take-all synaptic competition enabled by collapse of the phase gradient during odor presentation produces a single short-term memory band for each odor. The short-term memory is converted to long-term memory if odor stimulation is followed by activation of an input pathway for the unconditioned stimulus (US) which presumably results in release of one or more neuromodulatory amines or peptides in the PC lobe.
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INTRODUCTION |
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The computational function of
coherent oscillations and synchronous firing is under investigation at
a number of loci in the mammalian CNS, notably hippocampus
(Czurko et al. 1999; Draguhn et al.
1998
), cerebellum (Hartmann and Bower 1998
;
Mann-Metzer and Yarom 1999
), cortex (Crook et al.
1997
, 1998
; Murthy and Fetz 1996
), and
thalamocortical circuits (Buzsaki 1991
; Llinas et
al. 1998
). Oscillatory synchronization of activity in spatially
dispersed cortical modules has been invoked as critical for feature
binding during internal stimulus representation (Singer
1998
; Singer and Gray 1995
)
The olfactory bulb shows reliable and robust odor-evoked oscillatory
activity (Adrian 1942; Delaney and Hall
1996
; Dorries and Kauer 2000
; Freeman
1991
; Lam et al. 2000
). In arthropods olfactory
oscillations have been shown to result in synchronous firing of
odor-responding interneurons (Heinbockel et al. 1998
; Mellon and Wheller 1999
; Wehr and Laurent
1999
). The ubiquitous occurrence of olfactory oscillations
(Gelperin 1999
) and the extensive cellular studies of
olfactory bulb (Shepherd 1999
; Shipley and Ennis
1995
) have prompted construction of a variety of structural models of olfactory bulb function incorporating oscillatory dynamics (Hendin et al. 1998
; Li and Hopfield
1989
; Linster and Gervais 1996
; Meredith
1992
; Taylor and Keverne 1991
; White et
al. 1992
).
The procerebral (PC) lobe of the terrestrial mollusc Limax
maximus is the major central site of odor processing and displays a
number of design features in common with olfactory bulb
(Gelperin 1999; see also Hildebrand and Shepherd
1997
). These include oscillatory dynamics (Gelperin and
Tank 1990
; Kawahara et al. 1997
) modified by
behaviorally relevant odors (Gervais et al. 1996
;
Kimura et al. 1998c
), circuits based on
principal cells interacting with local inhibitory interneurons
(Kleinfeld et al. 1994
; Watanabe et al.
1998
), continuous generation and connection of newly generated receptors after birth (Chase and Rieling 1986
),
postembryonic generation of olfactory interneurons (Zakharov et
al. 1998
), and modulation of circuit dynamics by both nitric
oxide (Gelperin 1994
) and carbon monoxide
(Gelperin et al. 2000
).
We have constructed a coupled oscillator model of the Limax
PC lobe (Ermentrout et al. 1998). The model has two
layers of units, each layer comprising 20 rows of four units,
corresponding to the layers of burster cells and nonburster cells in
the PC lobe. The four units in row 1 correspond to the most
apical part of the PC lobe, while the four units in row 20 correspond to the most basal part of the PC. The model has a gradient
of connection strengths between burster units so that it propagates
activity waves, as measured in the PC lobe (Delaney et al.
1994
). Recent evidence suggests that odor learning by
Limax results in band-like regions of odor representation in
the PC lobe (Gelperin 1999
; Kimura et al.
1998a
,b
; Teyke and Gelperin 1999
).
Injection of intact Limax with Lucifer yellow (LY) after
odor learning results in a band of LY-labeled cells in the PC lobe with
the long axis of the band of labeled cells normal to the apical-basal
axis of wave propagation. Learning two odors yields two parallel bands of labeled PC cells. We introduce olfactory input to our model PC such
that each odor maximally activates a unique row of four cells which
produces a long-term memory trace if odor stimulation is followed by
activation of an input pathway for the unconditioned stimulus
(US). Dynamics inherent in wave propagation suggests that similar but
perceptually distinct odors result in closely spaced but distinct bands
in the model PC. The model also has the property that if wave
propagation is blocked, inputs from closely related odors address the
same band in the model. This accords with recent work in honeybee
showing that antennal lobe oscillations are necessary for
discriminating closely related odors (Stopfer et al.
1997
) and with electrophysiological results in Limax
in which peritentacular nerve output becomes similar for related odors
only when the PC oscillation and wave propagation are blocked
(Teyke and Gelperin 1999
).
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METHODS |
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Labeling odor memory bands
In the first experiment, each slug was given one training trial
in which it was induced to eat an agarose pellet containing starch,
sucrose, and mint, an aversive odor. The 2.5% (wt/vol) agarose
contained 4% (wt/vol) cornstarch, 10% (wt/vol) sucrose, and 0.01%
(vol/vol) mint extract (McCormick). The slug was induced to initiate
feeding movements by application of a solution containing 4% starch
and 10% sucrose. The mint-containing agarose disk was placed in
contact with the lips during ongoing feeding movements, resulting in
ingestion of a substantial amount of the agarose pellet. This
appetitive conditioning results in subsequent approach responses to
mint odor, which prior to conditioning elicited aversive responses.
Following the protocol of Kimura et al. (1998a), 20 min
after completion of the appetitive training trial the slug was injected
with 200 µl of 8% Lucifer yellow CH lithium salt (Sigma) in
Limax saline. One hour later the slug was dissected and the
PC lobes desheathed and photographed. Drawings were made as overlays
from the scanned PC lobe photographs.
In the second experiment, we starved a group of 15 slugs weighing 2 g for 10 days and then applied potato odor-quinidine aversive conditioning as follows. Each slug was placed in a dry 15-cm Petri dish. After the slug started to crawl spontaneously, 1 ml of a 5% (wt/vol) solution of potato flakes in water was placed in front of the slug's head. Before the slug touched the source of potato odor (~10 s), 100 µl of a saturated solution of quinidine sulfate was applied to the oral area of the head. After 20 s the slug was rinsed with Limax saline and transferred to a clean chamber lined with moist filter paper. Control slugs given unpaired conditioning were treated similar to conditioned slugs except that after the 10-s potato-odor exposure the slug was gently moved to a clean Petri dish for 15 min before treatment with quinidine sulfate. Twenty minutes after the conditioning or control procedure, 200 µl of 0.1% (wt/vol) LY in Limax saline was injected into the hemocoel, where it distributed throughout the slug, turning it distinctly yellow. One hour after LY injection, the animal was anesthetized with cold and the brain harvested by fine dissection, followed by fixation in 4% (wt/vol) paraformaldehyde. Photographs were taken of the fixed preparations and scored for labeled cells using the following categories; 0 = no labeled cells, few = few scattered cells, cluster = group of labeled cells.
In a third experiment we used an aversive odor conditioning procedure
previously shown to be effective (Sahley et al. 1981) and exposed the entire CNS to LY during memory consolidation as in the
previous experiment. Aversive conditioning was applied to 26 slugs
(1.0-2.2 g) selected for approach and feeding responses within 2 min
to a piece of potato tuber (Solanum tuberosum) placed 1 cm
in front of the slug. After feeding for 5 min, the slug was gently
transferred to a Petri dish lined with filter paper moistened with 1%
(wt/vol) quinidine sulfate. The slug was left in contact with quinidine
for 20 min, after which it was injected with 0.8% (wt/vol) LY, Li, or
K salt, in Limax saline, at a dosage of 100 µl/g body wt.
One hour after injection of LY, the PC lobes were harvested by
microdissection and examined with epifluorescence illumination in a
compound microscope. Drawings were made of the distribution of labeled
cells in the unfixed PC lobe and photographs taken with a CCD camera.
Modeling
Simulations of dynamical equations were made using custom software (XPP or XTC, available at http://www3.pitt.edu/~phase) running on a UNIX workstation. The output of the model was taken either as the spatial pattern of activity over the array of units or as the simulated voltage of individual units.
To account for the bilaterality of the lobe and the fact that in some
circumstances bands occur on one side or the other, we will generalize
our current model to include two distinct lobes. Experiments suggest
that there are crossed inhibitory connections between the two lobes
(Teyke and Gelperin 1999). Inhibitory connections can
play two distinct roles in coupled oscillators. If the coupling strength is not too strong, then they can serve to synchronize the two
lobes. This leads to a coherent traveling wave in which both lobes
produce traveling waves. However, if the inhibition is too strong, then
it is possible to suppress one side or the other depending on the
initial conditions and local heterogeneities (White et al.
1998
). Thus crossed inhibition plays two roles as follows:
1) in the default mode of the model, it serves to
synchronize the traveling waves between the two halves, and
2) in "learning" mode when the oscillations synchronize,
it can act to suppress one side or the other allowing asymmetric LY
band formation.
In our previous paper (Ermentrout et al. 1998), we
showed that a simple one-variable phase-model description was
sufficient to model the traveling waves and the transition to
synchrony. We continue that simplification in the present paper by
using a single layer of oscillatory (bursting) cells. In addition, we add a layer of memory cells to represent the nonbursting neurons that
take up the LY and encode the odor memory. The basic idea of the model
is that the oscillatory cells act as gates to the inputs to the memory
cells. Thus the memory cells will fire in the presence of inputs only
during certain cycles of the oscillation. The memory cells suppress
distant cells in the same layer (lateral inhibition) but only when they
are active. Thus if there is a phase gradient in the oscillation, the
suppression mechanism will not work since cells are never active at the
same time. However, when the wave collapses to a synchronous
oscillation, all the cells fire simultaneously in both lobes and the
localization of odor bands becomes possible. Li and Hertz
(2000)
have devised a model that has some similar features for
studying associative memory in the mammalian olfactory system. Their
olfactory bulb layer plays a similar role to our oscillating layer and
their olfactory cortex is like the "memory layer" in our model.
However, there is no topographic organization in their model, the
oscillations occur only during input, and there are no spatially
organized waves.
The Limax model consists of a left and right lobe coupled
with mutual inhibition. Each lobe consists of two layers of cells, the
oscillatory layer (bursters) and the memory layer (nonbursters). The
oscillatory layer consists of a two-dimensional array of coupled phase
oscillators identical in form to our previous model. Since the
oscillations produced by this system are always synchronized along the
axis perpendicular to the direction of the waves, we will collapse the
oscillatory layer to a single row of cells that either produces a wave
or is synchronized. Figure 1 shows a
schematic for the model. Since the details of how the traveling waves
are produced in the oscillatory layer are not important, we simplify the model proposed in Ermentrout et al. (1998) by both
collapsing the two-dimensional oscillatory system to a single
one-dimensional chain and imposing local frequency differences at the
two ends sufficient to give a phase-gradient. In the simplified model, changing a single parameter collapses the gradient. The equation for
the oscillator layer of the left lobe has the following form
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Now we turn to the layer that is responsible for segmenting the input
into a local spatial band. As shown in Fig. 1, we assume that this is
driven by the oscillations and the input is only apparent to the cell
at certain phases of the oscillation. The equation for the activity,
u
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We introduce a simplified model in which we look at the ability of the
network to select between two competing inputs as a function of the
phase-lag between the oscillatory gating. For this analysis, we look at
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(1) |
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(2) |
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RESULTS |
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Lucifer yellow labels odor memory bands
An example of a unilateral LY-labeled band of PC lobe neurons resulting from single trial appetitive odor conditioning is shown in Fig. 2, A and B. The band of LY-labeled cells in the right PC lobe is oriented approximately normal to the apical-basal axis of wave propagation. The unilateral nature of the LY-labeled odor memory band strongly suggests some form of bilateral interaction which results in the dominance of the right side in this animal for storing odor memories. The learning-associated LY labeling occurs in half the animals on the right side and in half the animals on the left side.
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Of the 10 slugs conditioned with potato-quinidine pairings in experiment 2, five (50%) showed a cluster of labeled cells in either the right or the left PC lobe (Table 1). The remaining five conditioned slugs had either a few scattered cells or no labeled cells in their PC lobes. Of the five control slugs, one (20%) showed a cluster in one PC lobe. The 15-min interval between potato odor and quinidine treatment may not be long enough to obviate learning in all slugs.
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We performed a third experiment in an attempt to obtain more dramatic
odor conditioning-dependent labeling of PC neurons. Of the 26 slugs
given one trial of aversive odor conditioning in experiment
2, 16 (62%) had either a band or a patch in a PC lobe (Table
2). All but one slug had labeling in only
the right PC lobe (6 of 15, 40%) or only the left PC lobe (9 of 15, 60%). Figure 3 shows examples of a band
and a patch. We identified a band as a group of LY-labeled PC neurons
with the length of the long axis of the region enclosing the labeled
cells >2 times the length of the short axis (Fig. 3D) while
a patch is a group of LY-labeled PC neurons with the long axis of the
region enclosing the labeled cells 2 times the length of the short
axis (Fig. 3B). In five of six cases (83%), the long axis
of the LY-labeled band was parallel to the wave front of the activity
wave which propagates from apex to base.
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The LY is present in the somata of the labeled cells contained in
membrane-bound vesicles, as determined by two-photon laser scanning
microscopy (Denk et al. 1994). We also determined that the LY-labeled cells are nonburster (NB) neurons, the major class of
interneurons in the PC lobe, rather than burster (B) neurons. B neurons
are responsible for the oscilla-tion of the local field potential and
the wave-like propagation of activity from apex to base of the PC lobe
(Delaney et al. 1994
; Gelperin and Tank 1990
; Kleinfeld et al. 1994
). The LY-labeled
cells have only one neurite which projects from the soma directly to
the PC neuropil, characteristic of NB cells (data not shown). B cells
have two or more neurites which project in the plane of the cell body
layer and do not invade the PC neuropil (Wang et al.
2001
). The unilateral nature of the LY labeling is a striking
and unexpected feature which may derive from crossed inhibition between
right and left odor processing streams, as recently demonstrated in the
Limax nose-brain preparation (Teyke et al.
2000
). The regional localization of LY-labeled PC neurons,
particularly in band-like clusters with the long axis of the band
parallel to the front of the propagating activity wave, prompted us to
extend our model of the PC lobe to exhibit odor learning with storage
of odor memories in bands of PC cells.
Model for odor learning
The network, as before, begins with a chain of locally coupled
oscillators with a gradient of coupling strengths so that at rest the
network propagates a periodic wave with wavelength equal to the chain
length (PC length). We obtain synchrony in response to odor input by
nulling the coupling gradient. We assume that memory bands arise from
neurons within the PC becoming more active in the presence of odor
input and turning on some long-term process to store the odor memory
due to US-triggered neuromodulation. The PC lobe contains several amine
and peptide neuromodulators among the 21 different neurotransmitters
found in the PC lobe (Gelperin 1999).
Model description
The model works as follows. During the generation of waves, if odor inputs come in, then each cell in the memory layer sees the inputs at different times due to the phase gradient. Thus no single cluster of cells can suppress all the others since it will be active at a different time in the cycle than the others. However, if the oscillatory network synchronizes, then all the active clusters are available for suppression at the same time and a "winner" emerges. It is important to point out that oscillations are not required for WTA. There are many simple networks without oscillations that can implement WTA behavior. However, if there are oscillations, then, by keeping them desynchronized (as through a phase-gradient), every point in the network is available for excitation at different points in the cycle. By transiently synchronizing the network, we enable it to select a unique spatial region to represent the input and presumably perform a useful computation. The other advantage of oscillations over a static WTA network is that it is simple to switch between behavior which selects a single most salient stimulus (during synchrony) to behavior allowing all inputs to have an effect (during waves).
As a first simulation we consider a pared down model representing the
two sides of the Limaxthat is, we collapse the right and
left lobes to two points to illustrate the competition during synchrony. We ask under which circumstances a selection between two
inputs can be made if they are not perfectly synchronized. We simulate
Eqs. 1 and 2 with the input to the right lobe
slightly larger than that to the left. If the phase separation of the
two oscillators is small enough, then the input to the left will be suppressed. We arbitrarily define suppression to mean that the response
of uL is <30% of that of
uR at their respective peaks. We choose
= 0.2 for the driving oscillations. Suppose that
= 1. Then if
< 0.4, then uR will be
selected and uL suppressed. For each
,
there is a range of
such that uL will
be suppressed. The maximum such
is called the critical
. Figure
4 shows a plot of the critical value of
as a function of the relaxation constant of the network. If the
network responds quickly, then the oscillations must be very close to
synchrony in order to make a selection. This is because if the duration of the response of the network is quite short then suppression can only
occur in a limited time window. On the other hand, if the duration of
the network response is too long lasting, then the magnitudes of
patterns are both small. Due to these factors there is an optimal
response time for the network in which suppression takes place over a
wide time window without undue reduction in response magnitude.
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The previous simulation shows how gating the inputs can enable suppression between two sides if the timing is close enough. Since the left and right lobes are closely synchronized even during wave generation, it is clear that selection of one side or the other can readily occur through this mechanism.
We now turn to the full model. We ask whether spatial localization can occur and whether there will be bands. First, we remark that in a WTA network, there is no a priori reason why there should be bands. In fact, one expects only small clusters of cells to be selected. In particular, since the oscillations are always synchronous perpendicular to the direction of the traveling wave, the competition is "fiercest" in this direction. Thus there must be constraints on the connections in the network and perhaps on the inputs. We suggest that there are relatively strong excitatory connections along the transverse direction and that the odor inputs to the lobe are similar in strength along this direction. If we make this assumption, then there is tendency for bands to occur even if the inputs are not identical. One of the consequences of tight coupling along the direction of the bands is that a band will form at a position j even if a single input to another region is larger than any of the inputs to the winning band. This is because of the cooperative effect of the coupling across the band. Figure 5 shows a sample of the times series from six spatial regions from a 20 × 4 array of cells. The wave propagates down the long axis of the array. The first four graphs show the activity of the four cells belonging to the winning pattern before (to the left of the top vertical arrow) and after the wave collapses to synchronous activity. Note the low activity in one of the units u4,2 until the wave collapses. Then, after the bands in other spatial locations are suppressed, the activity in unit u4,2 is enhanced. Two units from a suppressed region (u1,9, u4,9) are shown before and after the collapse of the wave. After the phase gradient collapses, the activity in both unit u1,9 and unit u4,9 is completely suppressed as is all activity in all spatial regions except the winning band.
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Figure 6 shows the space-time evolution of the first row of cells along the long axis of one lobe. Inputs come to cells in positions 1, 2, and 9. After the wave collapses (shown by the >>>), only cells in the second position persist in their activity.
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DISCUSSION |
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Two types of experimental results indicate that the PC lobe is
involved in storing information related to odor learning. First, LY
injection 20 min after a single odor training trial leads to bands or
patches of labeled PC neurons. The LY labeling of PC neurons does not
occur with odor and quinidine exposures timed to obviate learning
(Kimura et al. 1998c). Second, if slugs are given
aversive odor training and then responses to the trained odor measured
by imaging the PC lobe using an in vitro nose-brain preparation,
phase-specific depolarization in a band-shaped region of the PC lobe
can be observed (cf. Fig. 6 in Kimura et al. 1998c
). The
phase-specific band of depolarization is seen in response to the
conditioned odor but not to a control odor.
The learning-specific LY labeling of PC lobe neurons occurs in response
to both aversive odor conditioning (cf. Figs. 2 and 3 and
Kimura et al. 1998c) and appetitive conditioning (Fig. 1 in Gelperin 1999
). The memory trace set up by
Limax odor conditioning transforms from a short-term to
long-term form (Sekiguchi et al. 1997
, 1991
;
Yamada et al. 1992
) as found in other species
(Dubnau and Tully 1998
; Squire 1987
). The
endocytosis-like event which results in LY filled vesicles in the
somata of bands of NB neurons may be related to activation by the US
(quinidine) of the biochemical cascade which transforms a short-term
memory into a long-term form (Abel and Kandel 1998
).
Quinidine application may lead to release of a neuromodulatory
transmitter in the PC, which contains 21 different neurotransmitter
candidates (Gelperin 1999
), including serotonin (but see
Teyke 1996
). The odor-learning-specific LY labeling of
NB cells rather than B cells may derive from the fact that odor input
fibers connect with the neurites of PC neurons only in the neuropil,
which contains NB cell neurites but not B cell neurites (Wang et
al. 2001
; Watanabe et al. 1998
).
The band of units in the model which forms an odor memory trace is a
central representation of the learned odor which can be associated with
either a positive or a negative behavioral response to the learned
odor. The odor memory representation in the model PC may be coupled to
changes in premotor circuitry located elsewhere to determine the nature
of the behavioral response to the learned odor, as in the original
LIMAX model (Gelperin et al. 1985). Both
appetitive and aversive odor conditioning result in LY-labeled bands of
neurons in the PC lobe. The LY-labeled neurons take up the dye due to
membrane internalization events coupled to synaptic events which set up
the odor memory, while in the model learning directly modifies synaptic
strengths so that subsequent presentations of the learned odor produce
unique localized patterns of activity in the PC. The link between
synaptic modifications due to learning and membrane internalizations at the soma remains to be determined.
Wave propagation is blocked in the model by nulling the phase
gradient. This yields synchronous oscillation of the entire mode PC.
Only during synchronous activity can a selection of units most strongly
driven by an odor input be made and competition occur to implement the
WTA interaction resulting in a single band representing a single odor
in the model PC. Wave propagation is blocked in the biological PC by
treatments which block both wave propagation and synchronous
oscillation, such as nitric oxide synthesis inhibitors. Under these
conditions, when nitric oxide synthesis is blocked in vivo, no odor
learning occurs (Teyke 1996).
The relation between perceptual and chemical similarity of odors and
the spatial contiguity of their odor memory bands remains to be
determined. If Limax is trained sequentially first with odor
A and then with odor B, two LY-labeled bands are found in the same PC
lobe (Kimura et al. 1998c). For carrot and cucumber odors, the bands are separated by about half the apical-basal extent of
the PC lobe (cf. Fig. 13 in Kimura et al. 1998a
). Using an in vitro nose-brain preparation, two closely related odors (apple
variety A versus apple variety B) are not clearly discriminated from
each other when the PC lobe oscillation and wave propagation are
suppressed pharmacologically (Teyke and Gelperin 1999
).
We suggest that closely related odors are stored in spatially
contiguous regions of the PC lobe and further, that in the absence of
oscillatory dynamics and wave propagation, two similar odors with
minimal spatial separation of their PC representations will no longer be discriminated from each other. This has also been observed in
behavioral measurements of odor discrimination in honeybees after
pharmacological suppression of antennal lobe oscillations (Stopfer et al. 1997
). The storage of odor
representations in spatially separated bands in the Limax PC
lobe may be analogous to spatial segregation of odor representations in
groups of glomeruli (Friedrich and Korsching 1997
;
Joerges et al. 1997
; Vickers et al.
1998
), which is also modified by associative learning
(Faber et al. 1999
).
A striking feature of the LY labeling of odor memory bands is the
unilateral nature of the labeling in spite of bilateral odor exposure.
This may result from the lateralized access of olfactory afferents to
the PC lobe ipsilateral to a given nose in combination with crossed
inhibition between right and left odor processing streams. Using the
odor elicited peritentacular nerve discharge as a surrogate signal for
appetitive odor responses (Peschel et al. 1996), clear
evidence was obtained for right-left inhibition when the right superior
nose was stimulated with known attractive odor A and simultaneously the
left superior nose was stimulated with known attractive odor B
(Teyke et al. 2000
). This crossed inhibition between
left and right odor processing streams resulting in unilateral odor
memory storage could result in doubled odor memory storage capacity if
one PC lobe is used for memory storage after the other PC lobe has
stored the maximum number of odor memories consistent with accurate
discrimination and recall.
The mechanism of learning-dependent LY uptake into the somata of
procerebral NB neurons is unknown. There are demonstrations of
activity-dependent LY uptake in a variety of neural tissues (Wunderer et al. 1989; Zimmerman 1986
;
Zinkl et al. 1990
), although the nature of the activity
leading to LY uptake is not known (Page et al. 1994
;
Sarthy et al. 1982
). Uptake of LY into membrane-bound vesicles occurs at the somata of PC nonburster neurons, perhaps as a
concomitant of somatic release and recycling of synaptic vesicles.
Somatic exocytosis of transmitter vesicles has been shown for an
identified dopamine neuron in the aquatic snail Planorbis (Anderson et al. 1999
; Chen et al. 1995
)
and somatostatin-containing neurons in the terrestrial snail
Helix (Darbon et al. 1996
). The somatic
vesicles of somatostatin-containing Helix neurons
incorporated the fluorescent dye FM1-43 after producing trains of
action potentials, confirming that spike-triggered exocytosis and
vesicle recycling occurred at the soma. Learning-induced
internalization of surface proteins such as cell adhesion molecules
(Bailey et al. 1997
; Martin and Kandel
1996
) is another candidate mechanism for learning-induced internalization of LY.
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ACKNOWLEDGMENTS |
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Portions of this study were supported by National Science Foundation Grant DMS-9972913 to B. Ermentrout and National Institute of Mental Health Grants MH-47150 to B. Ermentrout and MH-56090 to A. Gelperin.
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FOOTNOTES |
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Address for reprint requests: A. Gelperin, Rm. 1C464, Bell Laboratories, 600 Mountain Ave., Murray Hill, NJ 07974 (E-mail: CNSAG{at}physics.bell-labs.com).
Received 28 April 2000; accepted in final form 5 December 2000.
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REFERENCES |
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