8O2 
CRICKET WIND DETECTION 
John P. Miller 
Neurobiology Group, University of California, 
Berkeley, California 9 720, U.S.A. 
A great deal of interest has recently been focused on theories concerning 
parallel distributed processing in central nervous systems. In particular, 
many researchers have become very interested in the structure and function 
of "computational maps" in sensory systems. As defined in a recent review 
(Knudsen et al, 1987), a "map" is an array of nerve cells, within which there 
is a systematic variation in the "tuning" of neighboring cells for a particular 
parameter. For example, the projection from retina to visual cortex is a rel- 
atively simple topographic map; each cortical hypercolumn itself contains a 
more complex "computational" map of preferred line orientation represent- 
ing the angle of tilt of a simple line stimulus. 
The overall goal of the research in my lab is to determine how a relatively 
complex mapped sensory system extracts and encodes information from ex- 
ternal stimuli. The preparation we study is the cercal sensory system of 
the cricket, Acheta domesticus. Crickets (and many other insects) have two 
antenna-like appendages at the rear of their abdomen, covered with hundreds 
of "filiform" hairs, resembling bristles on a bottle brush. Deflection of these 
filiform hairs by wind currents activates mechanosensory receptors, which 
project into the terminal abdominal ganglion to form a topographic repre- 
sentation (or "map") of "wind space". Primary sensory interneurons having 
Cricket Wind Detection 803 
dendritic branches within this afferent map of wind space are selectively 
activated by wind stimuli with "relevant" parameters, and generate action 
potentials at frequencies that depend upon the value of those parameters. 
The "relevant" parameters are thought to be the direction, velocity, and 
acceleration of wind currents directed at the animal (Shimozawa & Kanou, 
1984a & b). There are only ten pairs of these interneurons which carry the 
system's output to higher centers. All ten of these output units are identi- 
fied, and all can be monitored individually with intracellular electrodes or 
simultaneously with extracellular electrodes. The following specific ques- 
tions are currently being addressed: What are the response properties of the 
sensory receptors, and what are the I/O properties of the receptor layer  
a whole? What are the response properties of all the units in the output 
layer? Is all of the direction, velocity and acceleration information that is 
extracted at the receptor layer also available at the output layer? How is 
that information encoded? Are any higher order "features" also encoded? 
What is the overall threshold, sensitivity and dynamic range of the system 
as a whole for detecting features of wind stimuli? 
Michael Landolfa is studying the sensory neurons which serve as the inputs 
to the cercal system. The sensory cell layer consists of about 1000 afferent 
neurons, each of which innervates a single mechanosensory hair on the cerci. 
The input/output relationships of single sensory neurons were characterized 
by recording from an afferent axon while presenting appropriate stimuli to 
the sensory hairs. The primary results were as follows: 1) Afferents are direc- 
tionally sensitive. Graphs of afferent response amplitude versus wind direc- 
tion are approximately sinusoidal, with distinct preferred and anti-preferred 
directions. 2) Afferents are velocity sensitive. Each afferent encodes wind 
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velocity over a range of approximately 1.5 log units. 3) Different afferents 
have different velocity thresholds. The overlap of these different sensitivity 
curves insures that the system as a whole can encode wind velocities that 
span several log units. 4) The nature of the afferent response to deflection 
of its sensory hair indicates that the parameter transduced by the afferent is 
not hair displacement, but change in hair displacement. Thus, a significant 
portion of the processing which occurs within the cercal sensory system is 
accomplished at the level of the sensory afferents. 
This information about the direction and velocity of wind stimuli is encoded 
by the relative firing rates of at least 10 pairs of identified sensory interneu- 
rons. A full analysis of the input/output properties of this system requires 
that the activity of these output neurons be monitored simultaneously. Shai 
Gozani has implemented a computer-based system capable of extracting the 
firing patterns of individual neurons from multi-unit recordings. For these 
experiments, extracellular electrodes were arrayed along the abdominal nerve 
cord in each preparation. Wind stimuli of varying directions, velocities and 
frequencies were presented to the animals. The responses of the cells were 
analyzed by spike descrimination software based on an algorithm originally 
developed by Roberts and Hartline (1975). The algorithm employs multiple 
linear filters, and is capable of descriminating spikes that were coincident in 
time. The number of spikes that could be descriminated was roughly equal 
to the number of independent electrodes. These programs are very pow- 
erful, and may be of much more general utility for researchers working on 
other invertebrate and vertebrate preparations. Using these programs and 
protocols, we have characterized the output of the cercal sensory system 
in terms of the simultaneous activity patterns of several pairs of identified 
Cricket Wind Detection 805 
interneurons. 
The results of these multi-unit recording studies, as well as studies using sin- 
gle intracdlular electrodes, have yielded information about the directional 
tuning and velocity sensitivity of the first order sensory interneurons. Tun- 
ing curves representing interneuron response amplitude versus wind direc- 
tion are approximately sinusoidal, as was the case for the sensory afferents. 
Sensitivity curves representing interneuron response amplitude versus wind 
velocity are sigmoidal, with "operating ranges" of about 1.5 log units. The 
interneurons are segregated into several distinct classes having different but 
overlapping operating ranges, such that the direction and velocity of any 
wind stimulus can be uniquely represented as the ratio of activity in the dif- 
ferent interneurons. Thus, the overlap of the different direction and velocity 
sensitivity curves in approximately 20 interneurons insures that the system 
as a whole can encode the characteristics of wind stimuli having directions 
that span 360 degrees and velocities that span at least 4 orders of magnitude. 
We are particularly interested in the mechanisms underlying directional sen- 
sitivity in some of the first-order sensory interneurons. Identified interneu- 
rons with different morphologies have very different directional sensitivities. 
The excitatory receptive fields of the different interneurons have been shown 
to be directly related to the position of their dendrites within the topographic 
map of wind space formed by the filiform afferents discussed above (Bacon 
& Murphey, 1984; Jacobs & Miller,1985; Jacobs, Miller & Murphey, 1986). 
The precise shapes of the directional tuning curves have been shown to be 
dependent upon two additional factors. First, local inhibitory interneurons 
can have a stong influence over a cell's response by shunting excitatory in- 
puts from particular directions, and by reducing spontaneous activity during 
806 Miller 
stimuli from a cells "null" direction. Second, the "electroanatomy" of a neu- 
ron's dendritic branches determines the relative weighting of synaptic inputs 
onto its different arborizations. 
Some specific aims of our continuing research are as follows: 1) to charac- 
terize the distribution of all synaptic inputs onto several different types of 
identified interneurons, 2) to measure the functional properties of individual 
dendrites of these cell types, 3) to locate the spike initiating zones of the 
cells, and 4) to synthesize a quantiSative explanation of signal processing by 
each cell. Steps 1, 2 & 3 are being accomplished through electrophysiological 
experiments. Step 4 is being accomplished by developing a compartmental 
model for each cell type and testing the model through further physiologi- 
cal experiments. These computer modeling studies are being carried out by 
Rocky Nevin and John Tromp. For these models, the structure of each in- 
terneuron's dendritic branches are of particular functional importance, since 
the flow of bioelectrical currents through these branches determine how sig- 
nMs received from "input" cells are "integrated" and transformed into mean- 
ingful output which is transmitted to higher centers. 
We are now at a point where we can begin to understand the operation of 
the system as a whole in terms of the structure, function and synaptic con- 
nectivity of the individual neurons. The proposed studies will also lay the 
technical and theoretical groundwork for future studies into the nature of 
signal "decoding" and higher-order processing in this preparation, mecha- 
nisms underlying the development, self-organization and regulative plasticity 
of units within this computational map, and perhaps information processing 
in more complex mapped sensory systems. 
Cricket Wind Detection 807 
REFERENCES 
Bacon, J.P. and Murphey, R.K. (1984) Receptive fields of cricket (Acheta do- 
mesticus) are determined by their dendritic structure. J. Phllsiol. (Lond) 
352:601 
Jacobs, G.A. and Miller, J.P. (1985) Functional properties of individual neu- 
tonal branches isolated in situ by laser photoinactivation. Scie.nce, 228: 
344-346 
Jacobs, G.A., Miller, J.P. and Murphey, R.K. (1986) Cellular mechanisms 
underlying directional sensitivity of an identified sensory interneuron. 
J. Neurosci. 6(8): 2298-2311 
Knudsen, E.I., S. duLac and Esterly, S.D. (1987) Computational maps in 
the brain. Annual Review of Neuroscience 10:41-66 
Roberts, W.M. and Hartline, D.K. (1975) Separation of multi-unit nerve 
impulse trains by a multi-channel linear filter algorithm. Brain Res. 
94: 141- 149. 
Shimozawa, T. and Kanou, M. (1984a) Varieties of fillform hairs: range 
fractionation by sensory afferents and cercal interneurons of a cricket. 
J. Comp. Phllsiol. A. 155:485-493 
Shimozawa, T. and Kanou, M. (1984b) The aerodynamics and sensory phys- 
iology of range fractionation in the cercal fillform sensilla of the cricket 
Gryllus bimaculatus. J. Comp. Ph!tsiol. A. 155:495-505 
