Modeling Insect Olfactory Neuron Signaling by a Network Utilizing Disinhibition

7/30/2019 Modeling Insect Olfactory Neuron Signaling by a Network Utilizing Disinhibition

http://slidepdf.com/reader/full/modeling-insect-olfactory-neuron-signaling-by-a-network-utilizing-disinhibition 1/8

BioSystems 36 (1995) 101-108

M odeling insect olfactory neuron signaling by a network

utilizing disinhibition

Evyatar Av-Ron*a9b, Jean-Pierre RosparsC

‘ B3E, INSERM I J263, I SARS, Facultk de Mdecine Saint-Antoine. 27 rue Chaligny. 7S571 Paris Cedex 12. Fr ance

bGroupe de Bioin formatique. URA 686, Ecole Normol e SupCri eure, 46 rue d’ lll m, 75230, Pari s Cedex 05, Fr ance

=L .uboratoire de Biomktr ie, lnstitut National de la Recherche Agronomique, 78026 Versailles Cedex, F rance

Received 24 February 1995; accepted 27 March 1995

Ah&met

A male moth locates a conspecific female by detecting her sexual-pheromone blend. This detection is carried out

in the antenna1 lobe, the first stage of olfactory information processing , wh ere local inhibitory neurons and projection

(relay) neurons interact. A ntennal-lobe neurons exhibit low-frequency (C 10 Hz) backgrou nd activity and bursting

(> 100 Hz ) activity in respons e to pherom one stimulation. We describe this behavior by a realistic biophysical neuron

mod el. The bursting behavior of the mode l is the result of both intrinsic cellular pro pertieS and n etwork interaction.A slowly activating and inactivating calcium channel provid es a depolarizing current for bursting and disinhibition

is show n to be. a feasible network mechanism for triggering this calcium chan nel. Small neural n etwork s utilizing

disinhibition are presented w ith local neurons intercalated between recept or and projection neurons. The tiring

behavio rs of projection neurons in respons e to stimulation by the pherom one blend or its compo nents are in accor-

dance with experimental results. This network architecture offers an alternative view of olfactory processing from the

classical architecture derived from vertebrate studies.

Keyw ords: Insect olfaction; Ion conductance neuron mo del; Netw ork disinhibition

1. Introduction

The first stage of insect olfaction processing

resides in the brain antenna1 lobes (ALs). Receptor

neurons (RNs ) of the antennae send afferent in-

puts into well-organized structures of the AL, call-

??Corresponding author, Tel.: +33 1 44738433;Fax: +33 I

43738462;E-mail: [email protected].

ed glomeruli, in which they make synapse with ALneurons. Two main types of AL neurons are found

in glomeruli, local neurons (LNs) with arboriza-

tions confined to the AL and projection neurons

(PNs) with axons that relay information to higher

brain centers in the protocerebrum (for reviews see

Christensen and Hildebrand 1987a, Rospars 1988,

Homberg et al. 1989, Masson and M ustaparta

1990, Boeckh et al. 199 0, Hildebrand et al. 1992 ).

As a case study we examined olfaction process-

0303-264 7/95609.50 0 1995 Elsevier Science Ireland Ltd. All rights reservedSSDI 0303-2647(95)01531-O



10 2 E. Av -Ron, .-P. Rospars Bi oSystems 6 f T99.5) 101-108

ing in a specific glomerular AL neuropil, the so-

called macroglomerular complex (MGC ) of male

moths (which is also present in other insects, e.g.

cockroaches and honey bees (Rospars 1988,

Masson and M ustaparta 1990, Boeckh et al. 1990,Hildebrand et al. 1992). This complex processes

sex-pheromone inputs coded by specialized RNs.

Sex pheromones released by female moths attract

their conspecific males. This system p lays a crucial

role for the survival a nd evolution of the species.

The sex pheromone blend is composed of a num-

ber of different compound s. For example, in the

moth M unducu sex& (Kaissling et al. 1989,

Tumlinson et al. 1989), twelve aldehydes have been

identified. Of these, two 16carbon compoun ds

have been found ‘major’ from quantitative and be-havioral points of view, a dienal (bombykal, Bal)

and a trienal mimicked by a 15carbon aldehyde

(Cl 5). In wind tunnel experiments, a blend of these

two components is sufficient to induce up wind

flight of males towards the odor source (Tumlin-

son et al., 1 989). This blend was also found to elicit

neuronal response similar to extract from the fe-

male sex-pheromone gland (see Fig. 12 in

(Christensen a nd Hildebrand, 1987b)). Similar

neuronal responses were found in other moth spe-

cies (Christensen et al. 1989 ).Intracellular recordings from PNs in the MG C

show various types of responses to the two major

components and sex-pheromone gland extract (see

Fig. 9 in (Christensen et al. 1989)). Some neurons

are found to be generalists, i.e. they exhibit either

excitatory response to Bal, Cl5 and blend or in-

hibitory response to all three. Other neu rons are

specialists. One type of specialist respond s with ex-

citation to Bal and blend, bu t exhibits no response

to C15, or vice-versa, respond s with excitation to

Cl5 and blend, but not to Bal. A second type ofspecialist exhibits excitation to one major compo-

nent and inhibition to the other (e.g. see Figs. la,

b). The response to blend is a mixture of the two

(Fig. lc).

The connections between neurons in the

glomeruli in general and the MGC in particular

can be summ arized as follows. The RN s send ex-

citatory input to LNs, which are intercalated be-

tween RNs and PNs. Most (or all) LNs are

GAB Aergic and probably inhibitory (Hoskins et

al. 1986 , W aldrop et al. 1987). The delay in PN ex-

citation suggests that there are no direct synapses

from RN s to PNs (Christensen et al. 1993).

Our goal is to study neuronal signaling

mechanisms in the MGC . This small network(there are 86 000 RNs and 30 PNs in the M GC of

M& UCU (Homberg et al. 1989)), with its well

defined biological function, is attractive for a theo-

retical study. In this article we examine disinhibi-

tion as a possible mec hanism for neural processing

and signal recognition. W e use a realistic biophysi-

cal model to describe the PN s of the network. In

this manner the biophysical features of the basic

neural comp onents can be related to the overall

computational properties of the network.

2. Neuron model

PNs respond to an odorant stimulation with a

burst followed by a period of inactivation (Fig.

la). We have chosen to describe four properties of

this response: duration and spiking frequency of

the burst, duration of the inactivation period and

spiking frequency of the background activity.

---

c-15. 50ng L

Fig. 1. Response of a neuron to odor stimulation. (a) Bal. (b)

Cl5 (c) Pheromone-gland wash. Early inhibition is indicated

by open arrow. Bars indicate stimuli. Scale markers: 50 mV,

625 ms. Taken w ith permission from Christensen and

Hildebrand (1987b).



E. Av -Ron , J.-P. Rospars/ B ioSystems 36 (1995) 101-108 103

The biophysical model (Av-Ro n 1994, see Ap

per&x) consists of two inward currents (sodium

INo and calcium Z cJ and three ou tward potassium

currents (delayed ZK, transient IA and calcium-

dependent ZK(,-~J) nd a leak current IL. An ioncurrent Zi is described by the product of three

MI NIS; the maxim al conductance gig the activation

and inactivation variables or functions, and the

driving force (V - Vi). The steady-state functions

are modeled as sigmoid curves, determined by two

parameters, the half maxim um voltage Vi,2 (in-

flection point), and the slope a of the curve at this

point. This model wa s developed in a stepwise

manne r. For a single action potential the currents

Z,, and ZK are required (Hodgkin and Huxley

1952, FitzHugh 1961, Av-Ron et al. 1991). Forbursting behavior the currents Ia and ZKccalwere

incorporated (Plant 1981, Rinzel and Lee 1987,

Av-Ron et al. 1993). Finally, to exhibit both low

0

-6 0

1 ----__ _ _ ‘_

0 50 0 1000 1500 2(

Time (msec)

Fig. 2. Low-frequency activity and bu rsting behavior of neuron

model. Depicted are membrane potential V (solid line), intra-

cellular calcium concentration C (dashed tine), calcium channel

activation X (solid line marked X) and transient potassium

channel inactivation B (solid line marked B). Burst initiated by

an input current Li, = 5 @cm2 from t = 300 to 320 ms.

Mod el parameters: C, = 1 pFlcm2, gNU= 120 mS/cm2,

&= I5 mW m2, zr. = 0.3 m Wm2, &ca, = 0.5 rnWcm2,

&. = I mS/cm2, & = 12.5 m!Ycm2, V,, = 55 mV, V,, = 12 4

mV, V,= -72 mV, V, = -50 mV, P)rn = -31 m V atrn)

0.065, Vc”), = -35 mV a@+= 0.055, K = 0.08, s = I, Wr,2 =

-70 mV, a$) = -0.1, r6 = IO ms, W)tj2 = -45 mV acx) = 2,

rx = 25 ms, v(l)ro) = -20 mV, a@ = 0.02, K, = 2, KP= 0.0002,

R = 0.006, Kd = 0.5.

and high firing frequencies the current IA was in-

troduced (Connor et al. 1977, Rose an d Hind-

marsh 1989, Av-Ron 1994).

A typical behavior of the model is shown in Fig.

2. W ith no stimulation, the model exhibits slowoscillations (6 Hz with the specific values chosen

for the parameters). For a short excitatory stimu-

lation, a burst respon se is displayed. The stimula-

tion activates (variable x) the current Zca which

remains active for the duration of the burst due to

the slow time constant rX (see curve x). During

the burst, calcium enters the cell, activating the

current ZKlcol (see (10)) and inactivating the cur-

rent I,, (see (7)); eventually bringing about the

quiescence (inactive) period. C alcium w as assum ed

to reside in a thin shell under the membrane. Forsimplicity a single process is used for calcium dif-

fusion, buffering and sequestration. As well the re-

versal potential for calcium is assum ed to be

constant. During quiescence, intracellular calcium

is removed (see curve C ). Upon returning to

resting levels, low-frequency oscillations com-

mence. This is mainly determ ined by the current

IA, which has a slow time constant rb for inactiva-

tion (see curve Z?).

In this paper, a single neuron model was used,

i.e. the values of the parameters that define the ki-netics of the different currents were kept constant.

Only two parameters were varied to achieve the

different behaviors, the maxim al potassium con-

ductance g’Aand the rate of calcium removal (R).

The ordinary differential equations were solved

numerically using the fourth-order Runge-K utta

method with a time step of 0.01 ms.

3. Results

3.1. Serial networkA basic network utilizing disinhibition consists

of four neurons in series (Fig. 3a). In the absence

of stimulation, we assum e the projection neuron

(PN) has an oscillatory behavior (ca. 20 Hz, see

right-hand side of Fig. 4a). Wh en connected to a

local neuron (LN2) the low frequency spontaneous

activity of LN2 is sufficient to inhibit the PN a nd

keep it below the bursting threshold. For the PN

to exhibit a bursting response to odor stimulation,

another local neuron (LNl) connected to LN2 is



10 4 E. Av-Ron. J.-P. Rospars/BioSyslems 36 (1995) 101-108

a

b

c

Fig. 3. Neural networks of receptor (RN), local (LN) and pro-

jection (PN) neurons with excitatory (+) and inhibitory (-)

connections. (a) Generalist network utilising disinhibition. PN

exhibits an excitatory response (see Fig. 4a) w hen R Ns a~

stimulated with odors A and/or B. (b) Specialist network

uti!ising disinhibition. PN exhibits an excitatory resp onse (see

Fig. 4a) to stimulation with odor B and an inhibitory esponse

(see Fig. 4a) to stimulation with odor A. Stimulation with both

odors A and B elicits a ‘mixed’ response (see Fig. 4c). (c) Sp e-

cialist network b ased on the ‘classical’ architecture of the

vertebrate olfactory bulb with lateral inhibition. Responses to

odor A or B is as (b). For odors A and B, a short excitatory

response is elicited.

required. W hen stimulated by the excitatory RN s,

LNl inhibits LN2, which leads to the disinhibition

of the PN, allowing it to fire a burst.

Fig. 4a shows the behavior of a PN resulting

from this serial network. During the first second

the neuron receives inhibition (Z,im = -0.5

@U cm’, mimick ing tonic inhibition by LN2) and

exhibits slow spontaneous oscillations (3 Hz for

the chosen param eters). At time 0.5 s the in-

hibitory current is suppressed (mimicking inhibi-tion of LN2 by LNl during odor stimulation) and

the neuron exhibits its bursting response. The

duration of the burst depends on the intracellular

calcium concentration which activates the current

IKfcoJ and inactivates the current Zca The burst is

followed by a period of inactivation during which

intracellular calcium is removed. At time 2.2 s in-

tracellular calcium concentration has reached its

base level and the model begins to oscillate at 20

Hz. Wh en the inhibitory current is re-established

the neuron returns to its spontaneous 3 Hzoscillations.

This simulation describes the experimentally

observed behavior shown in Fig. la, excluding the

20-Hz oscillation after time 2.2 s shown in Fig. 4a.

In the experimental recordings the duration of the

burst coincides with the duration of stimulation

(0.5 s). However, for the model, a shorter period

(120 ms) of disinhibition is sticient to obtain a

bursting response. T his can be compared with

observed experimental results where short odor

stimulations (about 50 ms) triggered b urstingresponses (see Fig. 1 in Christensen and

Hildebrand 1988).

3.2. Para l le l network

A network based on inhibition and disinhibition

is shown in Figure 3b. The PN has the sam e pro-

perties as above. For stimulation with odorant B

(e.g. Bal) it behaves as shown in Fig. 4a. For stim-

ulation with odorant A (e.g. C15) it is strongly in-

hibited by LN2 for the duration of the odorantstimulation and responds as shown in Fig. 4b.

Wh en the stimulation ceases the PN returns to its

slow background activity (3 Hz). For stimulation

with a mixture of odorants A and B the PN

responds as shown in Fig. 4c. An initial inhibition

is followed by a burst. Both LN l and LN2 are ex-

cited simultaneously by their respective RN s.

Therefore, LN2 inhibits the PN. After a synaptic

delay LN2 receives inhibition from LNl. This

input inhibits LN2 and consequently releases the



E. Av-Ron. J.-P. Rospars/ BioSystems 36 (1995) 101-108 105

PN which fires a burst of activity. Following the

burst the PN is inactive and eventually returns to

its low-frequency spontaneous background ac-

tivity.

. . . . . . . .

--.- /

1. . I,

- . _ _ _ _

_ _ _ _ _ _ - -

500 1000 1500 2000

60 -

-60 -

r

I”0 ,500 1000 1500 2000

- 0.5

n

7

;

4. Discussion

In this paper we have studied disinhibition, first-

ly as a biophysical mechan ism for explaining intra-

cellular recordings (individual neuron properties)

and secondly, as an information-processing mech-

anism (local network properties).

4.1. Disinhibition of neuron membrane potential

Cell culture work suggests that the channel

types used in the biophysical model are present in

receptor (Zufall et al. 1991, Stengl 1994) and A L

neurons (Hayashi and Hildebrand 1990,

Hildebrand et al. 1992, Mercer et al. 1995, Klop

penburg and Hildebrand 1995). This model ex-

hibits intrinsic low-frequency background activity(6 Hz in Fig. 2 and 20 Hz in Fig. 4a on the right,

due to different values of g” a nd R ) and shows a

burst in response to a short excitatory stimulation.

This behavior results from the existence of two

thresholds, a threshold for action potentials (acti-

vation of the sodium current) and a threshold for

burst discharge (activation of the calcium current).

Applying inhibition reduces the background ac-

tivity further (Fig. 4a, from 20 Hz on the right to

3 Hz on the left). When inhibition is stopped

(disinhibition) a bursting response occurs, calledpostinhibitory rebound (Selverston and Mo ulins

1985). The mecha nism of this response is as

follows. Inhibition hyperpolarixes the mem brane

potential which in turn increases the threshold for

tiring. A decrease of the firing rate follows which

brings about the lower intracellular calcium con-

Fig. 4. Beh avior of projection-neuron model. Depicted are

membrane potential V (solid line), intracellular calcium con -centration (dashed line) and stimulating current (dotted line).

(a) Low frequency background activity resulting from constant

inhibition (&,, = -0.5 nNcm*) until r = 0.5 s. Respo nse to

disinhibition (ISrim 0 for t>0.5 s) includes a burst followed

by a period of inactivation. Without inhibition (I,, = 0) the

model exhibits 20-Hz background activity (I > 2.2 s). (b) Cons-

tant inhibition IStim -0.5 @cm * for the entire duration (0 to

2 s), except inhibition IS,i,,, -5 fiA/cm* from r = 0.5 to I s. (c)

Constant inhibition Isrh = -0.5 pA/cm* for the entire duration

except inhibition I,,h = -5 @/cm* from 0.50 to 0.52 s and

disinhibition (Istim 0) from t = 0.52 to 1 s.Model parameters:

as Fig. 2 except fA = IO mS/crn*, R = 0.0025.



106 E. Av-Ron. .-P . Rospars/Bi oSysrems 6 (1995) 101-108

centration C. W hen inhibition is removed the

mem brane depolarizes rapidly. If C would also

increase rapidly the system would reach a stable

oscillation as seen on the right-hand side of Fig.

4a. However this is not the case, the slow increasein C results in a relatively weak current IK(c+

This allows the firing frequency and consequently

the depolarizing calcium current to increase, in-

stigating a positive feedback which results in the

burst discharge.

Presented here is a simple biophysical model

which can describe the qualitative behavior

observed in PNs. The next step would be to choose

parameters based on patch clamp experiments. As

well, the sensitivity of the model to parameter

changes should be studied. This may be examinedin relation to both neuronal development (Lockery

and Spitzer 1992) and neuromodulation (Mercer et

al. 1995, Kloppenburg and Hildebrand 1995).

4.2. D & i n h i b i t i o n i n l o c al - c i r cu i t p r o cessi n g

The local circuit network is derived from experi-

mental evidence.

(a) The latency in response of PNs in comparison

with LNs suggests that PNs do not receive direct

excitatory inputs from receptor cells (Christensen

and Hildebrand 1987, Christensen et al. 1993).(b) In some PNs (Fig. lc) the burst response

is preceded by a short hyperpolarization

(Christensen and Hildebrand 1988). (c) M ost (or

all) of the LNs are probably inhibitory in-

temeurons (Hildebrand et al. 1992). (d) Correla-

tion between activities in LN and PN pairs was

found both in the MG C an d regular glomeruli.

The depolarization of the LN brought about the

inactivation of the PN. Conversely, hyperpolariz-

ing the LN caused an increase in activity of the

PN. This shows that at least some PN excitation is

the result of disinhibition (Christensen et al. 1993).

The disinhibition model proposed offers an alter-

native to the ‘classical’ model (Fig. 3c) of the

vertebrate olfactory bulb in term of information

processing. However, d isinhibition may also apply

to the vertebrate olfactory bulb because serial

synapses between dendrites of presumed inhibitory

LNs within the glomeruli have been documented

(Pinching and Pow ell 1 971; W hite 1972). These ar-

rangemen ts are in addition to the direct connec-

tions from RN terminals onto LN and PN

dendrites, an d the reciprocal contacts between

these dendrites (cf. Shepherd and Greer 1990).

However, it is not evident w hether the disinhibi-

tion model is capable of coding the quantitativefeatures of the olfactory message, e .g. concentra-

tions of A and B for specialist P Ns (parallel net-

work), ratio of concentrations A:B for generalist

PNs (serial network). More generally, the differ-

ences in terms of information processing between

the ‘classical model’ (e.g. L&rsky and Rospars

1993, Rospa rs and Fort 1994, Rospars et al., 1994)

and the model of disinhibition remain to be further

investigated.

The mecha nisms of disinhibition observed in the

insect glomerulus and in the vertebrate reticularthalamic nucleus seem analogous. I&inhibition of

thalamocortical neurons reduces the inactivation

of the low-threshold calcium current bringing

about a rebound calcium plateau which causes a

burst of action potentials (Jahnsen and Llinas

1984, Steriade, et al. 199 3). This m echanism is

similar to that of Fig. 4a, where the inactivation

component is the current IKIca,.

In conclusion, disinhibition provides an altema-

tive to lateral inhibition’as a functional role for in-

hibitory LNs in a network. One possibleadvantage of disinhibition over excitation is that

the PNs spontaneously return to the resting (inac-

tive) state, whereas excitatory mecha nisms may

lead to propagating waves of activity (W ilson and

Bower 1989).

Acknowledgements

E. Av-Ron was supported by program ‘Poste

Vert’, INSERM , France.

AppediX

C ,d V l d t = I , ,- I N ,- I I C ,- Z I K - I A - I K ( C o l - I L (1 )

dW l d t = [ W , ( I ’ ) - W J/ r ,( V ) , (2)

dX l d t = [X ,( J’ ) - X J/ r ,, (3)

dB l d t = [B ,( V ) - B ] l q , (4 )

d Cl d t = K & - I & - R . C (5)



E. Av-Ron, J.-P. Rospars / BioSystems 36 (1995) 101-108 107

P, (v) = (1 + exp[-2dp)(V - v@)1,2)])-1for = [ W,m,X, A, B]

r,(v) = (Xexp[a(W)V -V(W),,2)]+ xkxp[-dw)( V - P)&])-l

(12)

(13)

References

Av-Ron, E., Pamas, H. and Segel, L.A. 1991 , A minimal bio-

physical model for an excitable and oscillatory neuron.

Biol. Cybem. 65,487-500.

Av-Ron, E., Pamas, H. and Segel, L.A. 1993 , A basic

biophyscial model for bursting neurons. Biol. Cybern. 6 9,

87-94.

Av-Ron, E, 1994 , The role of a transient potassium current ina bursting neuron model. J. Math. Biol. 33, 71-87 .

Boeckh, J., Distler, P., Ernst, K.D., H&l, M. and Malun, D.,

1990 , Olfactory bulb and antenna1 lobe, in: Chemosensory

information processing, D . Schild (ed.), (Springer Verlag,

Berlin) pp. 201-227.

Christensen, T.A . and Hildebrand J.G. 1987 a, Functions,

organization, and physiology of the olfactory pathw ays in

the Lepidoteran brain, in: Arthropod Brain: its evolution,

development, structure and functions, A.P. Gupta (ed.),

(John Wiley and Sons) pp. 457-484.

Christensen, T.A. and Hildebrand J.G. 1987 b, Male-specific,

sex pheromone-selective projection neurons in the antenna1

lobes of the moth Man&a sexta. J. Comp. Physiol. A 160,

553-569.

Christensen, T.A . and Hildebrand J.G. 1988 , Frequency coding

by central olfactory neurons in the sphinx m oth Manduca

sexta. Chemical Senses 13, 123-130.

Christensen, T.A., Mustap arta, H. and Hildebrand, J.G. 1989 ,

Discrimination of sex pheromone blends in the olfactory

system of the moth. C hemical Senses 14 , 463-4 77.

Christensen, T.A., Hildebrand J.G., Tumhnson J,H. and

Doolittle, R.E . 1989 , Sex pheromone blend of Manduca

sexta: Responses of central olfactory intemeurons to anten-

nal stimulation in male moths. Arch. Insect Biochem.

Physiol. IO, 281-291.

Christensen, T.A., Waldrop, B.R., Harrow, I.D. and

Hildebrand, J.G. 1 993, Local interneurons and information

processing in the olfactory glomeruli in the moth Manduca

sexta. J. Comp. Physiol. A 173, 385-399.

Connor, J.A., Walter, D. and McKnown, R. 1977, Neural re-

petitive Bring - modifications of the Hodgkin-Huxley axon

suggested by experimental results from crustacean axons.

Biophys. J. 18, 81-102.

FitxHugh, R. 1 961, Impulses and physiological states in theo-

retical models of nerve membrane. Biophys. J. I, 445-466.

Hayashi, J.H. and Hildebrand, J.G. 1990 , Insect olfactory

neurons in vitro: Morphological and physiological

characterization of cells from the developing antenna1 lobes

of Manduca sexta. J. Neurosci. IO, 848-859.

Hildebrand, J.G., Christensen, T.A., Arbas, E.A., Hayashi,

J.H., Homberg, U., Kanxaki, R. and Stengl, M. 1992,

Olfaction in Manduca sexta: Cellular mechanisms of

responses to sex pheromone, in: Neurotox 199 1 Molecular

basis of drug and pesticide action, 1.R. Duce (ed.), (ElsevierApplied Science, London and New York) pp. 323-338.

Hodgkin, A.L. and Huxley, A.F. 1952 , A quantitative descrip-

tion of membrane current and its application to conduction

and excitation in nerve. J. Physiol. 117, 500-5 44.

Homberg, U., Christensen, T .A. and Hildebrand, J.G . 198 9,

Structure and function of the deutocerebrum in insects.

Ann. Rev. Entomol. 34, 477-501.

Hoskins, S.G., Homb urg, U., Kingan, T.G., Christensen, T.A.

and Hildebrand, J .G. 198 6, Immunocytochemistry of

GABA in the antenna1 lobes of the sphinx moth Manduca

sexta. Cell Tissue Res. 244, 243-252.

Jahnsen, H . and Llinh, R. 19 84, Electrophysiological proper-

ties of guinea-pig thalamic neurones: An in vitro study. J.Physiol. 349, 205-226.

Kaissling, K.-E., Hildebrand, J.G. and Tumlinson, J.H. 1989,

Pheromone receptor cells in the male moth Manduca sexta.

Arch. Insect Biochem. Physiol. IO, 273-2 79.

Kloppenburg P. and Hildebrand, J.G. 1995 , Neurom odulation

by 5-hydroxytryptamine in the antenna1 lobe of the sphinx

moth Manduca sexta. J. Exp. Bio. 198 , 603-611.

Ldnsky, P. and R ospars, J.P. 1993 , Coding of odor intensity.

BioSystems 3 1, 15-38.

Lockery, S.R. and Spitzer, N.C. 1992 , Reconstruction of action

potential development from whole-ceil currents of differen-

tiating spinal neurons. J. Neurosci. 12, 2268 -2287 .

Masson, C . and Mustaparta, H. 1990 , Chemical information

processing in the olfactory system of insects. Physiol. Rev.

70, 199-245.

Mercer, A.R., Hayashi, J.H. and Hildebrand, J.G. 1995,

Modu latory effects of 5-hydroxytryptamine on voltage-

activated currents in cultured antenna1 lobe neurones of the

sphinx moth Manduca sexta. J. Exp. Bio. 19 8, 613-627.

Pinching, A.L. and Powell, T.P.S. 1971 , The neuropil of the

glomeruli of the olfactory bulb. J. Cell Sci. 9, 347-377.

Plant, R.E . 1981 , Bifurcation and resonance in a model for

bursting nerve cells. J. Math. Biol. 11,15-32.

Rinzel, J. and Lee, Y.S. 1987 , Dissection of a model for neuro-

nal parabolic bursting. J . Math. B iol. 25, 653-6 75.



10 8 E. Av- Ron, J.-P. Rospars / Bi oSystems 36 (199s) 101-108

Rospars, J.P. 1988 , Structure and development of the insect

antennodeutocerebral system. Int. J. Insect Morphol. Em-

bryol. 17, 243-294.

Rospars, J.-P. and Hildebrand, J.G. 1992 , Anatomical identili-

cation of glomeruli in the antenna1 lobes of the male sphinx

moth Mumfncu sexra. Cell Tissue R es. 270, 205-227.

Rospars, J.P., Lrlnsky, P., Vaillant, J., Duchamp-V iret, P. and

Ducham p, A. 19 94, Spontaneous activity of first- and

second-order neurons in the frog olfactory system. Brain

Res. 662, 3 l-44.

Rospars, J.P. and Fort, J.C . 1994 , Coding of odor quality: role

of convergence and inhibition. Network 5, 121-1 45.

Rose, R.M . and Hindm arsh, J.L. 198 9, The assembly of ionic

currents in a thalamic neuron I. The threedimensional

model. Proc. R. Sot. Lond. B 237, 267-288.

Selverston, AI. and Moulins, M. 19 85, Oscillatory neural net-

works. Ann. R ev. Physiol. 47, 29-48.

Shepherd, G.M . and Greer, 1990 , Olfactory bulb, in: The

Synaptic Organization of the Brain G.M. S hepherd (rd.),(Oxford Univ. Press, Oxford) pp. 133-169.

Steriade, M., McCormick, D.A. and Sejnowski, T.J. 1993,

Stengl, M. 199 4, Inositol-triphosphatedependent calcium cur-

rents precede cation currents in insect olfactory receptor

neurons i n vi t ro . J. Comp. Physiol. 174, 187- 194.

Tumlinson, J.H., Brennan, M.M., Doolittle, R.E., Mitchell,

E.R., Brabham. A., Maxomenos, B.E., Baumhover, A.H.

and Jackson, D.M . 1989 , Identification of a pheromone

blend attractive to Mun ducu sexta (L.) males in a wind tun-

nel. Arch. Insect B&hem . Physiol. 10, 255-2 71.

Waldrop, B ., Christensen, T.A . and Hildebrand, J.G . 19 87,

GABA -mediated synaptic inhibition of projection neurons

in the antennal lobes of the sphinx moth, Mon ducu sexfu. J.

Comp. Physiol. A 161, 23-32.

Wilson, M .A. and Bower, J.M. 1989 , The simulation of large-

scale neural networks, in: Methods in neuronal modeling:

from synapses to networks, C. Koch and I. Segev (eds.)

(MI T Press, Cambridge, Massachusetts) pp. 291-3 33.

White, E.L. 1972 , Synaptic organ ization in the olfactory

glomerulus of the mouse. B rain Res. 37, 69-80.

Zufall, F., Stengl, M., Franke, C., Hildebrand, J.G. and Hatt,H. 1 991, Ionic currents of cultured olfactory receptor neu-

rons from antennae of male Munduca sextu. J. Neurosci. 11,

Thalamo cortical oscillations in the sleeping and aroused

brain. Science 262, 679-6 85.

956-965.

Documents

Modeling Insect Olfactory Neuron Signaling by a Network Utilizing Disinhibition