Odor Processing in the Bee: a Preliminary 
Study of the Role of Central Input to the 
Antennal Lobe. 
Christiane Linster 
David Marsan 
ESPCI, Laboratoire dlectmnique 
10, Rue Vauquelin, 75005 Paris 
linste neurones.espci.fr 
Claudine Masson 
Laboratoire de Neurobiologie Compar6e 
des Invert6r6es 
INRA/CNRS (URA 1190) 
91140 Bures sur Yvette, France 
masson@jouy.inra. fr 
Michel Kerszberg 
Institut Pasteur 
CNRS (URA 1284) 
Neurobiologie Mo16:ulaire 
25, Rue du Dr. Roux 
75015 Paris, France 
Abstract 
Based on precise anatomical data of the bee's olfactory system, we 
propose an investigation of the possible mechanisms of modulation and 
control between the two levels of olfactory information processing: the 
antennal lobe glomeruli and the mushroom bodies. We use simplified 
neurons, but realistic architecture. As a first conclusion, we postulate 
that the feature extraction performed by the antennal lobe (glomeruli and 
interneurons) necessitates central input from the mushroom bodies for 
fine tuning. The central input thus facilitates the evolution from fuzzy 
olfactory images in the glomerular layer towards more focussed images 
upon odor presentation. 
1. Introduction 
Honeybee foraging behavior is based on discrimination among complex odors which is the 
result of a memory process involving extraction and recall of "key-features" representative 
of the plant aroma (for a review see Masson et al. 1993). The study of the neural correlates 
of such mechanisms requires a determination of how the olfactory system successively 
analyses odors at each stage (namely: receptor cells, antennal lobe interneurons and 
glomeruli, mushroom bodies). Thus far, all experimental studies suggest the implication 
of both antennal lobe and mushroom bodies in these processes. The signal transmitted by 
the receptor cells is essentially unstable and fluctuating. The antennal lobe appears as the 
location of noise reduction and feature extraction. The specific associative components 
operating on the olfactory memory trace would be essentially located in the mushroom 
bodies. The results of neuroethological experiments indicate furthermore that both the 
527 
528 Linster, Marsan, Masson, and Kerszberg 
feed-forward connections from the antennal lobe projection neurons to the mushroom 
bodies and the feedback connections from the mushroom bodies to the antennal lobe 
neurons are crucial for the storage and the recall of odor signals (Masson 1977; Erber et al. 
1980; Erber 1981). 
Interestingly, the antennal lobe compares to the mammalian olfactory bulb. Computational 
models of the insect antennal lobe (Kerszberg and Masson 1993; Linster et al. 1993) and 
the mammalian olfactory bulb (Anton et al. 1991; Li and Hopfield 1989; Schild 1988) 
have demonstrated that feature extraction can be performed in the glomerular layer, but the 
possible role of central input to the glomerular layer has not been investigated (although it 
has been included, as a uniform signal, in the Li and Hopfield model). On the other hand, 
several models of the mammalian olfactory cortex (Hasselmo 1993; Wilson and Bower 
1989; Liljenstr6m 1991) have investigated its associative memory function, but have 
ignored the nature of the input from the olfactory bulb to this system. 
Based on anatomical and electrophysiological data obtained for the bee's olfactory system 
(Fonta et al. 1993; Sun et al. 1993), we propose in this paper to investigate of the 
possible mechanisms of modulation and control between the two levels of olfactory 
information processing in a formal neural model. In the model, the presentation of an 
"odor" (a mixture of several molecules) differentially activates several populations of 
glomeruli. Due to coupling by local interneurons, competition is triggered between the 
activated glomeruli, in agreement with a recent proposal (Kerszberg and Masson 1993). We 
investigate the role of the different types of neurons implicated in the circuitry, and study 
the modulation of the glomerular states by reentrant input from the upper centers in the 
brain (i.e. mushroom bodies). 
2. Olfactory circuitry in the bee's antennal lobe and mushroom 
bodies 
95% of sensory cells located on the bee's antenna are olfactory (Esslen and Kaissling 
1976), and convey signals to the antennal lobes. In the honeybee, due to some overlap of 
receptor cell responses, the peripheral representation of an odor stimulus is represented in 
an across fiber code (Fonta et al. 1993). Sensory axons project on two categories of 
antennal lobe neurons, namely local interneurons (LIN) and output neurons (ON). The 
synaptic contacts between sensory neurons and antennal lobe neurons, as well as the 
synaptic contacts between antennal lobe neurons are localized in areas of high synaptic 
density, the antennal lobe glomeruli; each glomerulus represents an identifiable 
morphological neuropilar sub-unit (of which there are 165 for the worker honeybee) 
(Arnold et al. 1985). 
Local interneurons constitute the majority of antennal lobe neurons, and there is evidence 
that a majority of the LINs are inhibitory. As receptor cells are supposed to synapse 
mainly with LINs, the high level of excitation observed in the responses of ONs suggests 
that local excitation also exists (Malun 1991), in the form of spiking or non-spiking LINs, 
or as a modulation of local excitatbility. 
All LINs are pluriglomerular, but the majority of them, heterogeneous local intemeurons 
(or HeteroLINs), have a high density of dendfite branches in one particular glomerulus, and 
sparser branches distributed across other glomemli. A second category, homogeneous local 
interneurons (or Homo LINs), distribute their branches more homogeneously over the 
whole antennal lobe. Similarly, some of the ONs have dendrites invading only one 
glomerulus (Uniglomerular, or Uni ON), whereas the others (Pluri ON) are 
pluriglomerular. The axons of both types of ON project to different areas of the 
protocerebmm, including the mushroom bodies (Fonta et al. 1993). 
Odor Processing in the Bee 529 
3. Olfactory processing in the bee's antennal lobe glomeruli 
Responses of antennal lobe neurons to various odor stimuli are characterized by complex 
temporal patterns of activation and inactivation (Sun et al. 1993). Intracellularly recorded 
responses to odor mixtures are in general very complex and difficult to interpret from the 
responses to single odor components. A tendency to select particular odor related 
information is expressed by the category of "localized" antennal lobe neurons, both Hetero 
LINs and Uni ONs. In contrast, "global" neurons, both Homo LINs and Pluri ONs are 
often more responsive to mixtures than to single components. This might indicate that the 
related localized glomeruli represent functional sub units which are particularly involved in 
the discrimination of some key features. 
An adaptation of the 2DG method to the honeybee antennal lobe has permitted to study the 
spatial distribution of odor related activity in the antennal lobe glomeruli (Nicolas et al. 
1993; Masson et al. 1993). Results obtained with several individuals indicate that a 
correspondence can be established between two different odors and the activity maps they 
induce. This suggests that in the antennal lobe, different odor qualities with different 
biological meaning might be decoded according to separate spatial maps sharing a number 
of common processing areas. 
4. Model of olfactory circuitry 
In the model, we introduce the different categories of neurons described above (Figure 1). 
Glomeruli are grouped into several regions and each receptor cell projects onto all local 
interneurons with arborizations in one region. Interneurons corresponding to heterogeneous 
LINs can be (i) excitatory, these have a dendritic arborization (input and output synapses) 
restricted to one glomerulus; they provide "local" excitation, or, (ii) inhibitory, these have 
a dense arborization (mainly input synapses) in one glomerulus and sparse arborizations 
(mainly output synapses) in all others; they provide "local inhibition" and "lateral 
inhibition" between glomeruli. Interneurons corresponding to homogeneous LINs are 
inhibitory and have sparse arborizations (input and output synapses) in all glomeruli; they 
provide "uniform inhibition" over the glomerular layer. 
Output neurons are postsynaptic only to interneurons, they do not receive direct input from 
receptor cells. Each output neuron collects information from all interneurons in one 
glomerulus: thus modeling uniglomerular ONs. 
Implementation: The different neuron populations associated with one glomerulus are 
represented in the program as one unit (each unit is governed by one differential equation); 
the output of one unit represents the average firing probability of all neurons in this 
population (assuming that on the average, all neurons in one population receive the same 
input and have the same intrinsic properties). All units have membrane constants and a 
non-linear output function. Connection delays and connection strengths between units are 
chosen randomly around an average value: this assures a "realistic spatial averaging" over 
populations. The differential equations associated with the units are translated into 
difference equations and simulated by synchronous updating (sampling step 5ms). 
530 Linster, Marsan, Masson, and Kerszberg 
M 
Molecule spectra 
Receptor cell types 
Local excitation 
Receptor input 
 Global inhibition 
Glomerulus 
Glomerular region 
 Local inhibition and lateral inhibition 
Local modulation 
Modulation of global inhibition 
 Global inhibitory intemeuron 
O Localized output neuron 
 Localized excitatory interneuron 
0 Localized inhibitory interneuron 
Figure 1: Organization of the model olfactory circuitry. 
In the model, we introduce receptor cells with overlapping molecule spectra; each 
receptor cell has its maximal spiking probability P for the presence of a particular 
molecule i. The axons of the receptor cells project into distinct regions of the 
glomerular layer. All allowed connections exist with the same probability, but with 
different connection strengths. The activity of each glomerulus is represented by its 
associated output neurons. Central input projects onto the global inhibitory 
interneurons (modulation of global inhibition) or on all interneurons in one 
glomerulus (local modulation). 
5. Olfactory processing by the model circuitry 
In the model, odors are represented as one-dimensional arrays of molecules; each molecule 
can be present in varying amounts. Due to the gaussian distributions of receptor cell 
sensitivities, an active molecule activates more than one receptor cell (with varying degrees 
of activation). As each receptor cell projects into all glomeruli belonging to its target 
region, thus, a molecular bouquet differentially activates a number of glomeruli in different 
glomerular regions. This triggers several phenomena: (i) due to the excitatory elements 
local to each glomerulus, and activated glomerulus tends to enhance the activation it 
receives from the receptor cells, (ii) the local inhibitory elements are activated (with a 
certain delay) by the receptor cell activity and by the self-activation of the local excitatory 
elements, and, (iii) trend to inhibit neighboring glomeruli. These phenomena result in a 
competition between active glomeruli: during a number of sampling steps, the output 
activity of each glomerulus (represented by the firing probability of the associated output 
neuron), oscillates from high activity to low activity. Due to the competition provided by 
Odor Processing in the Bee 531 
the lateral inhibition, the spatial oscillatory activity pattern changes over time, and a stable 
activity map is reached eventually. A number of glomemli "win" and stay active, whereas 
others "loose" and are inhibited (Figure 2). 
The activities of individual output neurons follow the general pattern described above: 
oscillation of the activity during a number of sampling steps until the activity "settles" 
down to a stable value. A stable activity can either be a constant firing probability, or a 
"stable" oscillation of the firing probability. An output neuron associated to a particular 
glomerulus may be active for a particular odor input, and silent for others. Complex 
temporal patterns of excitation and inhibition may occur after stimulus presentation, 
Thus, the model predicts that odor representation is performed through spatial maps of 
activity spanning the whole glomerular layer. Individual output neurons, representing the 
activity of their associated glomeruli may be either excited or inhibited by a particular odor 
pattern. 
Glomeruli After stabilization 
1- 15 
Figure 2: Behavior of the model after stimulation of the receptor cells with the 
molecule array indicated in the figure. For several sampling steps (of 5 ms), the 
activity (firing probability) of the ON associated to each glomerulus is shown. At 
step 1, all glomeruli are differentially activated by the receptor cell input. Lateral 
inhibition silences all glomeruli during the next sampling step. At step 3, some 
glomeruli are highly activated (due to their local excitation), whereas others are 
almost silenced. Then, t spatial activation pattern oscillates for a number of 
sampling steps (which depends on the strength of the lateral inhibitory connections 
and on the number of active molecules in the odor array), and finally stabilizes in a 
spatial activity map. 
6. Comparison of odor processing in the Bee's antennal lobe 
and in the model 
Antennal lobe neurons in the bee show various response patterns to stimulation with pure 
components and mixtures. Most LINs and ONs respond with simple excitation or 
inhibition to stimulation, often followed by a hyperpolarized (resp. depolarized) phase. 
Interestingly, most LINs respond with various degrees of excitation to stimulation with 
binary odors and mixtures, whereas ONs respond equally often by excitation than by 
inhibition (Sun et al. 1993). In the model, LINs receive direct afferent input from receptor 
cells, and are therefore differentially activated by odor stimulation; they respond with 
varying degrees of excitation to stimulation with pure components and their mixtures. 
Output neurons in the model receive indirect input from receptor cells via local 
interneurons. Output neurons in the model are either activated (if their associated 
532 Linster, Marsan, Masson, and Kerszberg 
glomerulus wins the competfion) or inhibited (if their associated glomerulus looses the 
competition) by odor stimulation. 
In the simulations, output neurons which are excited for a particular odor stimulation 
belong to an active glomerulus in the spatial activity map associated to that odor. For each 
odor, a particular activity map is established. An output neuron is either excited or 
inhibited by a particular odor stimulation, indicating that it takes part in the representation 
of an activity map across glomeruli, which might be compared to the antennal lobe 2DG 
maps. 
7. Modulation of the model dynamics 
Odor detection by modulation of spontaneous activity 
At high spontaneous activity, all glomeruli in the model oscillate spontaneously (Figure 
3). Odor stimulation tends to synchronize these oscillations, but no feature detection is 
performed. In the model, the underlying activity map which corresponds to the odor signal 
can only emerge if the spontaneous activity is decreased (Figure 3). Decreasing of the 
spontaneous activity can be achieved by 5i) activation of the global inhibitory interneurons 
by central input, or, (ii) decreasing of the spiking threshold of all antennal lobe neurons. 
These data fit well with experimental data (see Sun et al. 1993, Figures 7 and 8). 
I I I I I I I I I 
Stimulus armlication 
500 ms 
Reduction of spontaneous 
activity 
Figure 3 
Figure 3: Modulation of the spontaneous activity. We show the spiking probabilities of 
output neurons associated to different glomeruli. Arrows indicate stimulus onset. Stimulus 
presentation synchronizes the oscillations. A decreasing of the spontaneous activity results 
in the emergence of the underlying activity map: several output neurons exhibit high 
activities, whereas the others are silent. 
Contrast enhancement by modulation of lateral inhibition 
Presentation of an odor in the model differentially activates many or all glomeruli, which, 
due to the local excitation, try to enhance the activation due to the odor stimulus. Due to 
the competition between glomeruli, feature detection is performed in the glomerular layer, 
which enhances some elements of the stimulus and suppresses others. 
In the model, for a given odor stimulation, the number of winning glomeruli depends on 
the strength of the lateral inhibition between glomeruli (Figure 5). At low lateral 
inhibition, most glomeruli stay active for any odor; no feature extraction is performed. 
Odor Processing in the Bee 533 
Increasing of the lateral inhibition focuses the odor maps, which can now 
different odor inputs. 
differentiate 
oe$oocoo$ 
ooooooo$ 
Figure 5: Stabilized activity maps for different odor stimuli with increasing lateral 
inhibition strength. At low competition, all glomeruli tend to be active due to their 
local excitation. Increasing of lateral inhibition permits to enhance the important 
features of each odor, and leads to uncon'elated activity maps for the different 
stimulations. 
Increasing of the lateral inhibition permits to focus a fuzzy olfactory image in the 
glomerular layer, or to "smell closer". A fuzzy sampling of an odor may be useful at first 
approach, whereas a more precise analysis of its important components is facilitated by 
increasing the competition between glomeruli increases contrast enhancement. 
8. Discussion 
We have presented the computational abilities of the neural circuitry in the antennal lobe 
model, based on what is known of the bee's circuitry. Single cell responses and global 
activity patterns are comparable to the odor processing mechanisms proposed in the insect 
(Linster et al. 1993; Masson et al. 1993; Kerszberg and Masson 1993) and in the vertebrate 
(Kauer et al. 1991; Li and Hopfield 1989; Freeman 1991) literature. As suggested by 
Kerszberg and Masson (1993), we show that odor preprocessing is based on spontaneous 
dynamics of the antennal lobe glomeruli, and that, in addition, feature detection needs 
competition between activated glomeruli due to global and lateral inhibition. The model is 
able to predict the role of the four types of neurons morphologically identified in the bee 
antennal lobe. It also predicts how intracellular recordings and 2DG data can be explained 
by the odor processing mechanism. Furthermore, modulation of the models dynamics 
opens up a number of new ideas about the respective role of the two main categories 
("localized" and "global") of antennal lobe neurons, and the possible role of central input to 
these neurons. 
Acknowledgements 
The authors are grateful to G. Dreyfus and L. Personnaz for fruitful discussions. 
534 Linster, Marsan, Masson, and Kerszberg 
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