18 Harris-Warrick 
MECHANISMS FOR NEUROMODULATION 
OF BIOLOGICAL NEURAL NETWORKS 
Ronald M. Harris-Warrick 
Section of Neurobiology and Behavior 
Cornell University 
Ithaca, NY 14853 
ABSTRACT 
The pyloric Central Pattern Generator of the crustacean stomatogastric 
ganglion is a well-defined biological neural network. This 14-neuron 
network is modulated by many inputs. These inputs reconfigure the 
network to produce multiple output patterns by three simple 
mechanisms: 1) determining which cells are active; 2) modulating the 
synaptic efficacy; 3) changing the intrinsic response properties of 
individual neurons. The importance of modifiable intrinsic response 
properties of neurons for network function and modulation is discussed. 
I INTRODUCTION 
Many neural network models aim to understand how a particular process is accomplished 
by a unique network in the nervous system. Most studies have aimed at circuits for 
learning or sensory processing; unfortunately, almost no biological data are available on 
the actual anatomical structure of neural networks serving these tasks, so the accuracy of 
the theoretical models is unknown. Much more is known concerning the structure and 
function of motor circuits generating simple rhythmic movements, especially in simpler 
invertebrate nervous systems (Getting, 1988). Called Central Pattern Generators (CPGs), 
these are rather small circuits of relatively well-defined composition. The output of the 
network is easily measured by monitoring the motor patterns causing movement. 
Research on cellular interactions in CPGs has shown that simple models of fixed circuitry 
for fixed outputs are oversimplified. Instead, these neural networks have evolved with 
maximal flexibility in mind, such that modulatory inputs to the circuit can reconfigure it 
"on the fly" to generate an almost infinite variety of motor patterns. These modulatory 
inputs, using slow transmitters such as monoamines and peptides, can change every 
component of the network, thus constructing multiple functional circuits from a single 
network (Harris-Warrick, 1988). In this paper, I will describe a model biological system 
to demonstrate the types of flexibility that are built into real neural networks. 
Mechanisms for Neuromodulation of Biological Neural Networks 19 
2 THE CRUSTACEAN STOMATOGASTRIC GANGLION 
The pyloric CPG in the stomatogastric ganglion (STG) of lobsters and crabs is the best- 
understood neural circuit (Selverston and Moulins, 1987). The STG is a tiny ganglion of 
30 neurons that controls rhythmic movements of the foregut. The pyloric CPG controls 
the peristaltic pumping and filtering movements of the pylorus, or posterior part of the 
foregut. This network contains 14 neurons, each of which is unambiguously assignable 
to one of 6 cell types (Figure 1A). Since each neuron can be identified from preparation 
to preparation, detailed studies of the properties of each cell are possible. Thanks to the 
careful work of Selverston and Marder and their colleagues, the anatomical synaptic 
circuitry is completely known (Fig. lA), and consists of chemical synaptic inhibition and 
electrotonic coupling; there is no chemical excitation in the circuit (Miller, 1987). 
Despite the complete knowledge of the synaptic connections within this network, the 
major question of "how it works" is still an important topic of neurobiological research. 
Early modelling efforts (summarized in Hartline, 1987) showed that, while the pattern of 
mutual synaptic inhibition provided important insights into the phase relations of the 
neurons active in the three-phase motor pattern, pure connectionist models with simple 
threshold elements for neurons were insufficient to explain the motor pattern generaled by 
the network. It has been necessary to understand the intrinsic response properties of each 
neuron in the circuit, which differ markedly from one another in their responses to 
identical stimuli. Most importantly, as will be described below, all 14 neurons are 
conditional oscillators, capable (under the appropriate conditions) of generating rhythmic 
bursts of action potentials in the absence of synaptic input (Bal et al, 1988). This and 
other intrinsic properties of the neurons, coupled with the pattern of mutual synaptic 
inhibition within the circuitry, has generated relatively good models of the pyloric motor 
pauern under a specified set of conditions (Hartline, 1987). 
A. Pyloric circuit 
 ,.._ 
B. Combined 
PDN illIt lair 11til ] ] lilU 
LP-PY . J], ! I: ,, Illi! . I1, ,. ]1,,  
MVN 
(VD) ;; ;;"; ;;;;; ;;:; ;;': ;;; : 
C. sucrose block 
E. octopamine 
F. Serotonin 
 mv 
1$ec 
Figure 1: Multiple motor patterns from the pyloric network in the presence of different 
neurotransmitters. A. Synaptic wiring diagram of the pyloric CPG. B.-F. Motor 
patterns observed under different conditions (see text). PDN,LP-PY,MVN traces: 
extracellular recordings of action potentials from indicated neurons. AB: intracellular 
recording from the AB interneuron. From Harris-Warrick and Flamm (1987a). 
20 Harris-Warrick 
3 MULTIPLE MOTOR PATTERNS PRODUCED BY AN 
ANATOMICALLY FIXED NEURAL NETWORK 
When the STG is dissected with intact inputs from other ganglia, the pyloric CPG 
generates a stereotyped motor pattern (Miller, 1987). However, in vivo, the network gen- 
erates a widely varying motor pattern, depending on the feeding state of the animal (Rezer 
and Moulins, 1983). The motor pattern varies in the cycle frequency and regularity, 
which cells are active, the intensity of cell firing, and phase relations. 
This variability can be mimicked in vitro, where experimental control over the system is 
better. Two major experimental approaches have been used. First, transmitters and 
modulators that are present in the input nerve to the STG can be bath-applied, producing 
unique variants on the basic motor theme. Second, identified modulatory neurons can be 
selectively stimulated, activating and altering the ongoing motor pattern. 
As an example, the effects of the monoamines dopamine (DA), serotonin (SHT) and 
octopamine (OCT) on the pyloric motor pattern are shown in Figure 1. When modu- 
latory inputs from other ganglia are present, the pyloric rhythm cycles strongly, with all 
neurons active (Combined). Removal of these inputs usually causes the rhythm to cease, 
and cells are either silent or fire tonically (Sucrose Block). Bath application of some of 
the transmitters present in the input nerve can restore rhythmic cycling. However, the 
motor pattern induced is different and unique for each transmitter tested: clearly the 
pauems induced by DA, 5HT and OCr differ markedly in frequency, intensity, active cells 
and phasing (Flamm and Harris-Warrick, 1986a). The conclusion is that an anatomically 
fixed network can generate a variety of outputs in the presence of different modulatory in- 
puts: the anatomy of the network does not determine its output. 
4 MECHANISMS FOR ALTERATION OF NEURAL 
NETWORK OUTPUT BY NEUROMODULATORS 
We have studied the cellular mechanisms used by monoamines to modify the pyloric 
rhythm. To do this, we isolate a single neuron or single synaptic interaction by selective 
killing of other neurons or pharmacological blockade of synapses (Flamm and Harris- 
Warrick, 1986b). The amine is then added and its direct effects on the neuron or synapse 
determined. Nearly every neuron in the network responded directly to all three amines we 
tested. However, even in this simple 14-neuron circuit, different neurons responded differ- 
ently to a single amine. For example, DA induced rhythmic oscillations and bursting in 
one cell type, hyperpolarized and silenced two others, and depolarized the remaining cells 
to fire tonically (Fig.2). Thus, one cannot use the knowledge of the effects of a 
transmitter on one neuron to infer its actions on other neurons in the same circuit. Our 
studies of the actions of DA, 5HT and OCT on the pyloric network have demonstrated 
three simple mechanisms for altering the output from a network. 
Mechanisms for Neuromodulation of Biological Neural Networks 21 
Control 
AB 
PD Il]]jJ 
VD 
Dopamine 
IC 
Figure 2: Actions of dopamine on isolated neurons from the pyloric network. 
Control: Activity of each neuron when totally isolated from all synaptic input. 
Dopamine: Activity of isolated cell during bath application of 10'4M dopamine. 
4.1 ALTERATION OF THE NEURONS THAT ARE ACTIVE PARTICI- 
PANTS IN THE FUNCTIONAL CIRCUIT 
By simply exciting a silent cell or inhibiting an active cell, a neuromodulator can deter- 
mine which of the cells in a network will actively participate in the generation of the 
motor pattern. Some cells thus are physiologically inactive, even though they are 
anatomically present. 
However, in some cases, unaffected cells can make a significant contribution to the motor 
pattern. Hooper and Marder (1986) have shown that the peptide proctolin activates the 
pyloric rhythm and induces rhythmic oscillations in one neuron. Proctolin has no effect 
on three other neurons that are electrically coupled to the oscillating neuron; these cells 
impose an electrical drag on the oscillator neuron, causing it to cycle more slowly than it 
does when isolated from these cells. Thus, the unaffected cells cause the whole motor 
pattern to cycle more slowly. 
4.2 ALTERATION OF THE SYNAPTIC EFFICACY OF 
CONNECTIONS WITHIN THE NETWORK 
The flexibility of synaptic interactions is well-known and is used in virtually all models 
of plasticity in neural networks. By changing the amount of transmitter released from the 
pre-synaptic terminal or the post-synaptic responsiveness (either by altering the mem- 
brane resistance or the number of receptors), the strength of a synapse can be altered over 
an order of magnitude. Obviously, this will have important effects on the phase relations 
of neurons firing in the network. 
In the STG, the situation is complicated by the fact that graded synapses are the primary 
form of chemical communication: the cells release transmitter as a continuous function of 
membrane potential, and do not require action potentials to trigger release (Graubard, 
22 Harris-Warrick 
1978). Some neurons even release transmitter at rest and must be hyperpolarized to block 
release. We have shown that graded synaptic transmission is also strongly modulated by 
monoamines, which can completely eliminate some synapses while strengthening others 
(Fig.3; Johnson and Harris-Warrick, 1990). Amines can change the apparent threshold for 
transmitter release or the functional strength of the synapse. Modulation of graded trans- 
mission thus allows delicate adjustments of the phasing between cells in the 
motorpattern, which is often determined by synaptic interactions. Graded synaptic 
transmission occurs in many species, so this could turn out to be a general form of 
plasticity. 
Control 10-SM Oct 10-4M DA 
20 mV 
. mV 
Figure 3: Modulation of graded synaptic transmission from the PD neuron to the LP 
neuron by octopamine and dopamine. Experiment done in the presence of tetrodotoxin to 
abolish action potentials. Other synaptic inputs to these cells have been eliminated. 
In one case, modulation of graded transmission results in a sign reversal of the synaptic 
interaction between two cells (Johnson and Harris-Warrick, 1990). In the pyloric CPG, 
the PD neurons weakly inhibit the IC neuron by a graded chemical mechanism, but in 
addition the two cells are weakly electrically coupled. This mixed synapse is weak and 
variable. Dopamine weakens the chemical inhibition: the electdeal coupling dominates 
and the IC cell alepolarizes upon PD depolarization. Octopamine strengthens the chemical 
inhibition, and the IC cell hyperpolarizes upon PD depolarization. Combined chemical 
and electrical synaptic interactions have been detected in many other preparations, and thus 
can undedy flexibility in the strength and sign of synaptic interactions. 
4.3 ALTERATION OF THE INTRINSIC RESPONSE PROPERTIES 
OF THE NETWORK NEURONS 
The physiological response properties of neurons within a network are not fixed, but can 
be extensively altered by neuromodulators. As a consequence, the response to an identical 
synaptic input can vary radically in the presence of different neuromodulators. 
4.3.1 Induction of bistable firing properties 
Many neurons in both vertebrates and invertebrates are capable of firing in "plateau 
potentials", where a brief excitatory stimulus triggers a prolonged depolarized plateau, 
with tonic spiking for many seconds, which can be prematurely truncated by a brief 
hyperpolarizing input (Hartline et al, 1988). Thus, the neuron shows bistable properties: 
brief synaptic inputs can step it between two relatively stable resting potentials which 
differ markedly in spike frequency. This property is plastic, and can be induced or 
Mechanisms for Neuromodulation of Biological Neural Networks 23 
suppressed by neuromodulatory inputs. For example, Fig. 4 shows the DG neuron in the 
STG. Under control conditions, a brief depolarizing current injection causes a small 
depolarization that is subthreshold for spike initiation. However, after stimulating a 
serotonergic/cholinergic modulatory neuron (called GPR), the same brief current injection 
induces a prolonged burst of spikes on a depolarized plateau potential (Katz and Harris- 
Warrick, 1989). Similar results have been obtained in turtle and cat spinal motor neurons 
after application of monoamines such as serotonin or its biochemical precursor 
(Hounsgard et al,1988; Hounsgaard and Kiehn,1989). Stimulation of a modulatory 
neuron can also disable the plateau potentials that are normally present in a neuron (Nagy 
et al, 1988). 
DG 
   I1nA 
GPR stim. 5sec 
Figure 4: Induction of plateau potential capability in DG neuron by stimulation of a 
serotonergic/cholinergic sensory neuron, GPR. 
4.3.2 Induction of endogenous rhythmic bursting 
A more extreme form of modulation can occur where the modulatory stimulus induces 
endogenous rhythmic oscillations in membrane potential underlying rhythmic bursts of 
action potentials. For example, in Figure 4, the pyloric AB neuron shows no intrinsic 
oscillatory capabilities when it is isolated from all synaptic input. Bath application of 
monoamines such as DA, 5HT and OCT induce rhythmic bursting in this isolated cell 
(Flamm and Harris-Warrick, 1986b). Brief stimulation of the serotonergic/cholinergic 
GPR neuron can also induce or enhance rhythmic bursting that outlasts the stimulus by 
Control 
Dopamine  / 
Figure 5: Induction of rhythmic bursting in a synaptically isolated AB neuron by bath 
application of dopamine (10-4M). 
several minutes. The quantitative details of the bursting (cycle frequency, oscillation 
amplitude, spike frequency, etc.) are different with each amine, due to different ionic 
mechanisms for burst generation (Harris-Warrick and Flamm, 1987b). Since the AB 
neuron is the major pacemaker in the pyloric CPG, these differences underly the marked 
differences in pyloric rhythm frequency seen with the amines in Fig. 1. Induction of 
rhythmic bursting by neuromodulators has been observed in vertebrates (for example, 
Dekin et al,1985), and this is likely to be a general mechanism. 
24 Harris-Warrick 
4.3.3 Modulation of post-inhibitory rebound 
Most neurons show post-inhibitory rebound, a period of increased excitability following 
strong inhibition. This is probably due in part to the activation of prolonged inward 
currents during hyperpolarization (Angstadt and Calabrese, 1989). This property can be 
modified by biochemical second messengers used by neuromodulators. For example, 
elevation of cAMP by forskolin enhances post-inhibitory rebound in the pyloric LP 
neuron (Figure 5; Flamm et al, 1987). As a consequence of this modulation, the cell's 
response to a simple inhibitory input is radically changed to a biphasic response, with an 
initial inhibition followed by delayed excitation. 
Control 
50 !.dVl Forskolin 
.-71.. 
'U .......... U 
Figure 6: Induction of post-inhibitory rebound by forskolin, which elevates cAMP 
levels, in the LP neuron. Control: Hyperpolarizing current injection does not induce 
post-inhibitory rebound, measured at two different resting potentials. Forskolin: 
Elevation of cAMP depolarizes LP and induces tonic spiking (left). At all membrane 
potentials, a hyperpolarizing pulse is followed by an enhanced burst of action potentials. 
5 ENDOGENOUS RELEASE OF NEUROMODULATORS 
FROM IDENTIFIED NEURONS 
Most of the results I have described were obtained with bath application of amines or pep- 
tides, a method that can be criticized as being non-physiological. To test this, a number 
of neurons containing identified neuromodulators have been found, and the action of the 
naturally released and bath-applied modulator directly compared. An immediate 
complication arose from these studies: the majority of the known modulatory neurons 
contain more than one transmitter. All possible combinations have been observed, 
including a slow transmitter with a fast transmitter, two or more slow transmiuers, and 
multiple fast transmitters. To fully understand the complex changes in network function 
induced by activity in these neurons, it is necessary to study the actions of all the co- 
transmitters on all the neurons in the network. This has been recently accomplished in 
the STG. Here, serotonin is released by a set of sensory cells responding to muscle 
stretch (Katz et al, 1989). These cells also contain and release acetylcholine (Katz et 
a1,1989). In studying the actions of the two transmitters, remarkable flexibility was 
uncovered (Katz and Harris-Warrick, 1989,1990). First, not all target neurons responded 
Mechanisms for Neuromodulation of Biological Neural Networks 25 
to both released transmitters: some responded only to 5HT, while one cell responded only 
to ACh. Second, the responses to released 5HT were all modulatory, but varied markedly 
in different cells, mimicking the bath application studies described earlier. Finally, the 
two transmitters acted over entirely different time scales. ACh induced rapid EPSPs last- 
ing tens to hundreds of msec via nicotinic receptors, while 5HT induced slow prolonged 
responses lasting many seconds to minutes (for example, Fig.4). 
It is now clear that neural networks are targets for multiple neuronal inputs using many 
different transmitters and modulators. For example, the STG contains only 30 neurons, 
but is innervated by over 100 axons from other ganglia. Twelve neurotransmitters have 
thus far been identified in these axons (Marder and Nusbaum,1989), and these are probably 
a minority of the total that are present. In recordings from the input nerve to the gan- 
glion, many axons are spontaneously active. Thus, the pyloric network is continuously 
bathed with a varying mixture of transmitters and modulators, allowing for very subtle 
changes in the firing pattern. In vivo, we expect that each modulator plays a small role 
in the overall mixture that determines the final motor pattern. 
6 CONCLUSION 
The work described here shows conclusively that an anatomically fixed neural network can 
be modulated to produce a large variety of output pattems. The anatomical connections in 
the network are necessary but not sufficient to understand the output of the network. 
Indeed, it is best to think of these networks as libraries of potential components, which 
are then selected and activated by the modulatory inputs. In addition to altering which 
neurons are active and altering the synaptic strength in the circuits, I have emphasized the 
important role of modulation of the intrinsic response properties of the network neurons 
in determining the final pattern of output. Indeed, if this aspect of modulation is ignored, 
predictions of the actions of modulators on the final motor pattern are grossly in error. 
Many modellets claim that this emphasis on the intrinsic computational properties of 
single neurons is unique to the invertebrates, which have few cells to work with. In the 
vertebrates, they argue, the enormous increase in numbers of cells changes the computa- 
tional rules such that each cell is a simple threshold element, and complex transforma- 
tions only take place with changes in synaptic efficacy in the circuits. There are 
absolutely no data to support this hypothesis of "simple cells" in vertebrates. In fact, a 
great deal of careful work has shown that vertebrate neurons are dynamic elements that 
show all the complex intrinsic response properties of invertebrate neurons (Llin,1988). 
These properties can be changed by neuromodulators, just as in the crustacean STG, such 
that vertebrate cells can have radically different physiological "personalities" in the 
presence of different modulators. Network models which ignore the complex 
computational properties of single neurons thus do not reflect the richness and variability 
of biological neural networks of both invertebrates and vertebrates alike. 
Acknowledgments: Supported by NIH Grant NS 17323 and Hatch Act NYC-191410. 
7 BIBLIOGRAPHY 
Angstadt, J.D., Calabrese, R.L. (1989) A hyperpolarization-activated inward current in 
heart interneurons of the medicinal leech. J. Neurosci. 9: 2846-2857. 
26 Harris-Warrick 
Bal, T., Nagy, F., Moulins, M. (1988) The pyloric central pattern generator in Crustacea: 
a set of conditional neuronal oscillators. J. Comp. Physiol. A 163: 715-727. 
Dekin, M.S., Richerson, G.B., Getting, P.A. (1985) Thyrotropin-releasing hormone in- 
duces rhythmic bursting in neurons of the nucleus tractus solitarius. Science 229:67- 
69. 
Flamm, R.E., Harris-Warrick, R.M. (1986a) Aminergic modulation in lobster stomato- 
gastric ganglion. I. The effects on motor pattern and activity of neurons within the 
pyloric circuit. J. Neurophysiol. 55: 847-865. 
Flarere, R.E., Harris-Warrick, R.M. (1986b) Aminergic modulation in lobster stomato- 
gastric ganglion. II. Target neurons of dopamine, octopamine, and serotonin within 
the pyloric circuit. J. Neurophysiol. 55:866-881. 
Flamm, R.E., Fickbohm, D., Harris-Warrick, R.M. (1987) cAMP elevation modulates 
physiological activity of pyloric neurons in the lobster stomatogastric ganglion. J. 
Neurophysiol. 58: 1370-1386. 
Getting, P.A. (1988). Comparative analysis of invertebrate central pattern generators. in: 
Cohen, A.H., Rossignol, S., Grillnet, S. (eds.), Neural Control of Rhythmic 
Movements in Vertebrates, John Wiley and Sons, New York, pp. 101-127. 
Graubard, K. (1978) Synaptic transmission without action potentials: input-output prop- 
erties of a non-spiking presynaptic neuron. J. Neurophysiol. 41: 1014-1025. 
Harris-Warrick, R. M. (1988) Chemical modulation of central pattern generators. in: Co- 
hen, A.H., Rossignol, S., Grillnet, S.(eds.) Neural Control of Rhythmic Movements 
in Vertebrates, John Wiley & Sons, New York. pp 285-331. 
Harris-Warrick, R.M., Flarere, R.E. (1987a) Chemical modulation of a small central 
pattern generator circuit. Trends in Neurosci. 9: 432-437. 
Harris-Warrick, R.M., Flarere, R. E. (1987b) Multiple mechanisms of bursting in a 
conditional bursting neuron. J. Neurosci. 7: 2113-2128. 
Hartline, D.K. (1987) Modeling stomatogastric ganglion. in: Selverston, A.I., Moulins, 
M. (eds.), The Crustacean Stomatogastric System, Springer-Verlag, Berlin, pp. 181- 
197. 
Hartline, D.K., Russell, D.K., Raper, J.A., Graubard, K. (1988) Special cellular and sy- 
naptic mechanisms in motor pattern generation. Comp. Biochem. Physiol. 
91C:115-131. 
Hooper, S.L., Marder, E (1987) Modulation of the lobster pyloric rhythm by the peptide 
proctolin. J. Neurosci. 7:2097-2112. 
Hounsgard, J., Kiehn, O. (1989) Serotonin-induced bistability of turtle motoneurones 
caused by a nifedipine-sensitive calcium plateau potential. J. Physiol. 414:265-282. 
Hounsgaard, J., Hultborn, H., Jespersen, B., Kiehn, O. (1988) Bistability of alpha-mo- 
toneurones in the decerebrate cat and in the acute spinal cat after intravenous 5- 
hydroxytryptophan. J. Physiol. 405:345-367. 
Jan, L.Y., Jan, Y.N. (1982) Peptidergic transmission in sympathetic ganglia of the frog. 
J. Physiol. 327: 219-246. 
Johnson, B. R., Harris-Warrick, R.M. (1990) Aminergic modulation of graded synaptic 
transmission in the lobster stomatogastric ganglion. J. Neurosci., in press. 
Katz, P.S., Eigg, M.H., Harris-Warrick, R.M. (1989) Serotonergic/cholinergic muscle 
receptor cells in the crab stomatogastric nervous system. I. Identification and 
characterization of the gastropyloric receptor cells. J. Neurophysiol. 62: 558-570. 
Mechanisms for Neuromodulation of Biological Neural Networks 27 
Katz, P.S., Harris-Warrick, R.M. (1989) Serotonergic/cholinergic muscle receptor cells 
in the crab stomatogastric nervous system. II. Rapid nicotinic and prolonged 
modulatory effects on neurons in the stomatogastric ganglion. J. Neurophysiol. 62: 
571-581. 
Katz, P.S., Harris-Warrick, R. M. (1990) Neuromodulation of the crab pyloric central 
pattern generator by serotonergic/cholinergic proprioceptive afferents. J. Neurosci., 
in press. 
Llinfis, R.R. (1988) The intrinsic electrophysiological properties of mammalian neurons: 
insights into central nervous function. Science 242: 1654-1664. 
Marder, E., Nusbaum, M.P. (1989) Peptidergic modulation of the motor pattern genera- 
tors in the stomatogastric ganglion. in: Carew, T.J., Kelley, D.B. (eds.), Perspec- 
tives in Neural Systems and Bhvi0r, Alan R. Liss, Inc., New York. pp 73-91. 
Miller, J.P. (1987) Pyloric mechanisms. in: Selverston, A.I., Moulins, M. (eds.) Th 
Crustacean Stomatogastric Sy$lem, Springer-Verlag, Berlin, pp. 109-136. 
Nagy, F., Dickinson, P.S., Moulins, M. (1988) Control by an identified modulatory 
neuron of the sequential expression of plateau properties of, and synaptic inputs to, a 
neuron in a central pattern generator. J. Neurosci. 8:2875-2886. 
Rezer, E., Moulins, M. (1983) Expression of the crustacean pyloric pattern generator in 
the intact animal. J. Comp. Physiol. 153:17-28. 
Selverston, A.I., Moulins, M. (eds.) (1987) The Crustacean Stomatogastric $ysgm 
Springer-Verlag, Berlin, 338 pp. 
