Species-Specific Flight Styles of Flies are Reflected in the Response Dynamics of a Homolog Motion-Sensitive Neuron.

Abstract

Hoverflies and blowflies have distinctly different flight styles. Yet, both species have been shown to structure their flight behavior in a way that facilitates extraction of 3D information from the image flow on the retina (optic flow). Neuronal candidates to analyze the optic flow are the tangential cells in the third optical ganglion - the lobula complex. These neurons are directionally selective and integrate the optic flow over large parts of the visual field. Homolog tangential cells in hoverflies and blowflies have a similar morphology. Because blowflies and hoverflies have similar neuronal layout but distinctly different flight behaviors, they are an ideal substrate to pinpoint potential neuronal adaptations to the different flight styles. In this article we describe the relationship between locomotion behavior and motion vision on three different levels: (1) We compare the different flight styles based on the categorization of flight behavior into prototypical movements. (2) We measure the species-specific dynamics of the optic flow under naturalistic flight conditions. We found the translational optic flow of both species to be very different. (3) We describe possible adaptations of a homolog motion-sensitive neuron. We stimulate this cell in blowflies (Calliphora) and hoverflies (Eristalis) with naturalistic optic flow generated by both species during free flight. The characterized hoverfly tangential cell responds faster to transient changes in the optic flow than its blowfly homolog. It is discussed whether and how the different dynamical response properties aid optic flow analysis.

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INTEGRATIVE NEUROSCIENCE
ORIGINAL RESEARCH ARTICLE
published: 19 March 2012
doi: 10.3389/fnint.2012.00011
Species-specific flight styles of flies are reflected in the
response dynamics of a homolog motion-sensitive neuron
Bart R. H. Geurten1,2,3*, Roland Kern1,2and Martin Egelhaaf1,2
1Department of Neurobiology, Bielefeld University, Bielefeld, North Rhine-Westphalia, Germany
2Centre of Excellence ‘Cognitive InteractionTechnology’, Bielefeld, North Rhine-Westphalia, Germany
3Department of Cellular Neurobiology, Johann-Friedrich-Blumenbach Institute for Zoology and Anthropology, Georg-August-University Göttingen, Göttingen, Lower
Saxony, Germany
Edited by:
John J. Foxe, Albert Einstein College
of Medicine, USA
Reviewed by:
Jamie C.Theobald, Florida
International University, USA
Karin Nordstrom, Uppsala University,
Sweden
*Correspondence:
Bart R. H. Geurten, Department of
Neurobiology, Bielefeld University,
Postbox 100131, 33501 Bielefeld,
North Rhine-Westphalia, Germany.
e-mail: bart.geurten@
biologie.uni-goettingen.de
Hoverflies and blowflies have distinctly different flight styles.Yet, both species have been
shown to structure their flight behavior in a way that facilitates extraction of 3D information
fromtheimageflowontheretina(opticflow).Neuronalcandidatestoanalyzetheopticflow
are the tangential cells in the third optical ganglion – the lobula complex. These neurons
are directionally selective and integrate the optic flow over large parts of the visual field.
Homolog tangential cells in hoverflies and blowflies have a similar morphology. Because
blowflies and hoverflies have similar neuronal layout but distinctly different flight behav-
iors, they are an ideal substrate to pinpoint potential neuronal adaptations to the different
flight styles. In this article we describe the relationship between locomotion behavior and
motion vision on three different levels: (1) We compare the different flight styles based
on the categorization of flight behavior into prototypical movements. (2) We measure the
species-specific dynamics of the optic flow under naturalistic flight conditions. We found
the translational optic flow of both species to be very different. (3) We describe possi-
ble adaptations of a homolog motion-sensitive neuron. We stimulate this cell in blowflies
(Calliphora) and hoverflies (Eristalis) with naturalistic optic flow generated by both species
during free flight. The characterized hoverfly tangential cell responds faster to transient
changes in the optic flow than its blowfly homolog. It is discussed whether and how the
different dynamical response properties aid optic flow analysis.
Keywords:motion vision,lobula tangential cells,prototypical movements,optic flow,ventral centrifugal horizontal
cell, eristalis tenax, calliphora vicina
INTRODUCTION
Flies perform complex aerobatic maneuvers with a brain com-
posedoflessthanamillionneurons.Thesemaneuversarethought
tobeundervisualcontrol.Giventheextremespeedof manyflight
maneuvers,the neural processing of the retinal image shifts (optic
flow) has to be performed at a timescale of a few milliseconds.
Not only does the nervous system seem to be adapted to the spe-
cific demands of fly locomotion, but also their manner of flying
seems to be tailored to facilitate motion information processing
(Egelhaaf et al.,2009).
Two of the most basic tasks during flight are flight stabiliza-
tion and collision avoidance. Flight stabilization might be under
multimodal control, employing information from the visual sen-
sory systems (Stange, 1981) as well as mechanosensory input, for
instance from the antennae (Mamiya et al.,2011) and the halteres
(Nalbach,1993;Dickinson,1999). In contrast,collision avoidance
is mostly discussed in the context of vision (Tammero and Dick-
inson,2002a). Our study concentrates on the latter and compares
the very different flight styles of two fly species, Calliphora vicina
(blowfly) and Eristalis tenax (hoverfly). Furthermore we analyze
theconsequencesof thesedifferencesfortheneuralrepresentation
of opticflowinthevisualsystem.Althoughbothanimalssegregate
their flight trajectories into short fast rotations, called saccades,
they differ much with respect to translational motion between
these saccades (Schilstra and van Hateren, 1999; van Hateren and
Schilstra,1999;Braunetal.,2010;Geurtenetal.,2010).Thisflight
style has been interpreted, despite the differences in the transla-
tional sections, to facilitate the acquisition of spatial information
(Land, 1999; Schilstra and van Hateren, 1999; Boeddeker et al.,
2005; Kern et al.,2006; Braun et al.,2010; Geurten et al.,2010).
To be able to analyze the differences in flight style of the two
species,we reduced the complexity of flight trajectories by catego-
rizing the behavior into prototypical movements (PMs; Egelhaaf
etal.,2009;Braunetal.,2010;Geurtenetal.,2010).Thetrajectory
can then be conceived as a series of PMs, instead of a continuous
sequence of positions, orientations, and velocities of the fly. This
kindof descriptionisespeciallyusefulif theresponsesof aneuron
to optic flow evoked by particular PMs are to be investigated.
The set of nine Eristalis PMs can be divided into three sub-
groups (Figure 1A; Geurten et al., 2010). The first subgroup
contains saccadic PMs, covering fast yaw rotations (PMs 1 and
2, see numbers in Figure 1A). The second subgroup consists of
forward–sideways movements (PMs 3 and 4). The third subgroup
contains all other movements, for example upward movements
(PM5),backwardmovement(PM6),orhovering(PM9).Theset
of Calliphora’s PMs (see Figure 1B) differs from that of Eristalis
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Geurten et al.Species-specificity in response dynamics
FIGURE 1 | Prototypical movements. Prototypical movements (PMs) of
blowflies and hoverflies in confined arenas. Each translational velocity
(forward, upward, sideways) is normalized to the absolute maximum of all
translational velocities.The rotational velocities (yaw, pitch, roll) were
normalized accordingly.The velocities are plotted as length of the arrows
around a position.The gray arrows show the normalized maximum velocity.
The colored arrows show the velocity combination for that PM (for color code
see inset).The PMs are numbered. Below the PM number are its percentage
in the data and its mean duration±SD. (A) Eristalis PMs derived from body
trajectories omitting roll velocities, which we could not track for a larger
dataset (see Materials and Methods). (B) Calliphora PMs derived from head
trajectories (Braun et al., 2010).
in many respects, but contains nine PMs as well (Braun et al.,
2010). Four rotational PMs (PMs 1–4) correspond to saccades.
Four forward–sideways movements (PMs 5–8) form the second
subgroup. The last PM is directed purely forward (PM 9). All
CalliphoraPMscontainastrongtranslationalforwardcomponent,
whichisabsentinseveralEristalis PMs(PMs2,5,and9).Backward
PMsoccuronlyinEristalis (PM6).Inanycase,althoughbothflies
have in common that their PMs can be segregated into rotational
and translational ones, their translational PMs differ much.
Eristalis and Calliphora are believed to have homolog visual
systems, which include a number of similar cell types and only
few differences (Buschbeck and Strausfeld, 1996, 1997; O’Carroll
et al., 1997; Harris et al., 1999; Strausfeld, 2009). Approximately
50 tangential cells reside in their third optic ganglion called the
lobula complex. These cells react to movement in large parts of
the visual field (Nordström et al.,2008;Egelhaaf et al.,2009;Borst
etal.,2011).Inthisstudyweconcentrateontheventralcentrifugal
horizontal (vCH) cell (Hausen, 1976; Eckert and Dvorak, 1983).
It integrates the signals of several identified motion-sensitive
neurons.Therebyitreflectsthepropertiesof manytangentialcells,
ofbothbrainhemispheres.ThusthevCHcellmightbeparticularly
useful to assess potential species-specific differences in motion
vision.
In Calliphora the vCH cell has already been analyzed in par-
ticular detail (Hausen, 1976; Eckert and Dvorak, 1983; Egelhaaf
et al., 1993; Warzecha et al., 1993). Its preferred motion direction
isback-to-frontinthecontralateralhemisphereandfront-to-back
inthehemisphereofthevisualfieldipsilateraltoitsmainarboriza-
tion (Krapp et al., 2001). The vCH cell gets its ipsilateral input
from two members of the horizontal system (HS), HSE and HSS
(Farrow et al., 2003, 2006). The contralateral input is provided
by the H1, H2, V1-neuron, and the element U (Haag and Borst,
2001, 2003; Spalthoff et al., 2010). The vCH cell has been shown
to provide inhibitory input to the figure detection cell 1 (FD1)
and is responsible for its sensitivity to object motion (Egelhaaf
et al., 1993; Warzecha et al., 1993). The vCH neuron is thought
to suppress activation of the FD1-cell during preferred direction
saccades (van Hateren et al., 2005; Hennig et al., 2011).
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Geurten et al.Species-specificity in response dynamics
In this study we address the following two questions: (1) In
whichwayarethedifferencesintheflightstylesofEristalis andCal-
liphora reflectedintheiropticflow?(2)Arethereanycharacteristic
differences between the responses of vCH cells in both species
that indicate adaptations in the motion vision pathway to process
species-specific optic flow?
MATERIALS AND METHODS
All calculations presented in this article were done with MATLAB
R2008b (The MathWorks Inc., Natick, MA, USA).
ANIMALS AND TRAJECTORY DATA
The behavioral data on Eristalis tenax were collected in a previous
study (Geurten et al., 2010). The trajectory data were obtained
with a pair of high-speed cameras running at 500fps with a res-
olution of 1024×1024pixels and analyzed as described in detail
in Geurten et al. (2010). For electrophysiological experiments, we
collected Eristalis pupae from cow dung. This method was devel-
oped by Prof. Dr. K. Lunau (University of Düsseldorf). Calliphora
vicina andEristalistenax werebread25˚Cin12:12light–darkcycle
in the lab stock.
The trajectory data of Calliphora were obtained from C.
Schilstra and J. H. van Hateren (Schilstra and van Hateren, 1999;
van Hateren and Schilstra, 1999). Calliphora semi-free flight
behavior was recorded in a 40cm×40cm×40cm arena sur-
rounded by a Helmholtz coil. Head orientation was recorded via
small magnetic coils positioned on the fly’s head (for details see
Schilstra and van Hateren, 1998).
CLUSTERING ANALYSIS
Clustering algorithms find density clouds in high dimensional
data spaces. We used the translational and rotational velocities
corresponding to subsequent recorded video frames (Eristalis) or
trajectory positions (Calliphora) as the data on which our algo-
rithms operated. In our case this was a 5D data space for Eristalis
with the following velocities: forward,sideways,upward,yaw,and
pitch. In the case of Calliphora it was a 6D data space including
roll-velocity as well. The k-means algorithm (MacQueen, 1967),
which was employed for the final segregation of the data,searches
foraccumulationsofdatapointsthatliecloselytogether(“group”).
When all groups were found by clustering we derived the center
of each group,which we called the PM (for more detail see Braun
et al., 2010; Geurten et al., 2010). Finally, every frame of a given
trajectory was assigned to one of the PMs.
Please note that the PMs shown in Figure 1 are from two
different data sources. The Calliphora PMs are based on head tra-
jectories,whiletheEristalis PMsarebasedonbodytrajectories.We
werenotabletoobtainalargeenoughdata-basetoclusterEristalis
head trajectories, because these trajectories had to be acquired
manually from the video data (see Geurten et al., 2010 for more
details). We tested thoroughly, if the important but subtle differ-
ences between head and body trajectories have an influence on
the resulting PMs of the clustering (data not shown). Because
clustering is a rather coarse classification and thus cannot pick
up the subtle differences between head and body movements, the
resulting PMs are very similar.
OPTIC FLOW ANALYSIS
FortheopticflowanalysisweusedheadtrajectoriesforCalliphora
and Eristalis. Eristalis head trajectories were calculated from posi-
tion and orientation data obtained by manual video analysis. The
video material was a subset of the footage used during cluster-
ing analysis (see Geurten et al., 2010). The optic flow analysis is
based on the calculation of the distances between fly and flight
arena for every viewing direction (“sampling points”) and the
corresponding change in the position of the fly along the tra-
jectory (Koenderink and Doorn, 1987). For this, we used custom
software written at our department. We rebuilt the flight arenas’
walls in virtual reality and set a sample point matrix at the posi-
tion and in the orientation of the fly’s head. The sample point
matrix consists of 36 sample point positions in azimuth times
the 12 sample point positions in elevation, covering a field of
view from −60˚ to 60˚ in elevation and the complete azimuth.
The sample points were evenly spaced. For all sample points, we
calculated the intersection between a line drawn from the fly’s
head through the respective sample point and a wall of the flight
arena. The calculations were done for all entries of a given tra-
jectory. By comparing the intersection positions of each sample
point through time we calculated the time course of image shifts
on the retina. This calculation is independent of contrast, illumi-
nation and texture of the walls. An optic flow field was calculated
for every single location along a given trajectory. This was done
for all trajectories. Since every trajectory entry had been assigned
to a given PM (see above), the prototype-specific optic flow was
calculated as the mean of all optic flow fields corresponding to the
respective PM. Note that in case of Eristalis PM assignment, in
contrasttoprototype-specificopticflowcalculation,wasbasedon
body data.
ELECTROPHYSIOLOGY/MORPHOLOGY
We used two different preparations for the two species.
Eristalis was dissected according to Nordström et al. (2008).
Theheadwasopenedabovethelobulaplateandtrachealtissuewas
removed. In contrast to Nordström et al. (2008) the head orienta-
tion was aligned with the stimulus setup using the deep pseudop-
upil. Without any Ringer solution or removal of the neuronal
sheath, the target tissue was approached with aluminum silicate
(AlSi) electrodes. The electrodes were pulled in a two-step heat-
ingprogramonaP-97SutterInstrumentsPuller.Whenfilledwith
1MKClrecordingelectrodeshadatypicaltipresistanceof85MΩ.
Thereferenceelectrodewasplacedinthecontralateralheadhemi-
sphere. For morphological identification we filled the electrode
tips with 15mM Oregon Green 4888 (BAPTA)-1 hexapotassium
salt (Molecular Probes, OR, USA) in 1.7mM KOH/33mM (4-
(2-hydroxyethyl)-1-piperazineethanesulfonic) acid/3.3mM KCL.
The dye was iontophoretically injected (0.5–1nA) for 5–30min.
During dye injection no electrophysiological experiments were
done. Dye-filled neurons were visualized with a fluorescence
microscope in the living animal without further histological pro-
cessing. We assembled a depth projection which was then copied
by hand into a vector graphic.
Calliphora was dissected differently. The animal was fixed with
wax ventral side up to a glass holder and its head tilted forward
in order to give access to the head capsule’s back plate. The legs
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Geurten et al.Species-specificity in response dynamics
andantennaewereremovedandtheamputationholesclosedwith
beeswax. The proboscis was immobilized with wax. In this case
we used a Ringer solution, as described in Kurtz et al. (2006). We
usedborosilicateelectrodes,pulledonaP1000SutterInstruments
puller.Theseelectrodeshadatypicaltipresistanceof 35MΩwhen
filled 1M KCl.
Forbothspeciesthepre-amplifiedsignalwasfedintoacustom-
designed amplifier (TK 88, Max-Planck-Institute for Biological
Cybernetics,Tübingen,Germany).Thesignalwaslowpassfiltered
withacut-off frequencyof 2.4kHzandthensampledat8.192kHz
by a DT3001 I/O-card (Data Translation,Marlboro,MA,USA). A
thermometerrecordedthetemperaturenexttotheanimalforeach
single trial. The data was stored via the MATLAB data acquisition
toolbox (The MathWorks Inc., Natick, MA, USA) for offline data
analysis.
STIMULATION
As stimulus device we used an updated version of the high-speed
panoramic LED stimulus device FliMax described in Lindemann
et al. (2003). The FliMax2 has the same icosahedric shape as its
precursor model, covering more than 200˚ in azimuth and more
than150˚inelevation.It’s7168ultrabrightLEDs(WU-14-752GC,
525nm, 5mm diameter, Vossloh-Wustlich Opto, Kamp-Lintfort,
Germany;∼12,000cd·m−2maximumbrightness)arearrangedin
rhomboidscontaining32×32LEDseach.AllLEDsarebenttothe
center of the icosahedron, which results in a spatial resolution of
2.3˚. The number of brightness steps was increased in comparison
totheFliMax1(eightsteps)to256.Presentationrateof FliMax2is
354fps,i.e.,sufficientlyhightoaccountforthetemporalresolution
of the fly’s visual system.
Thedatapresentedinthisarticlewasrecordedwithfourdiffer-
entstimuli.Eachstimulustrialstartswithacontrastrampbringing
each LED from 50% intensity to the first pixel value of the first
stimulusimage.Afterthestimulustrialagainacontrastrampfades
the pixels from the last stimuli image to 50% intensity (500ms
duration). This is done to avoid transient on- and offset response.
Between stimuli trials the LEDs were left at 50% intensity for at
least 7s.
Spinning drum
We used a spinning drum stimulus that showed a vertical sinu-
soidalstripepattern(wavelength20˚)movinghorizontallyat2Hz
temporalfrequency.Movementdirectionswitchedfromclockwise
to counter clockwise and back again every 1080ms. In azimuth,
the spinning drum extended from −120˚ to 120˚. In the vertical,
the pattern ranged from −74˚ to 70˚.
Naturalistic stimuli based on blowfly and hoverfly trajectories
Togeneratemotionstimuliasencounteredduringflightwerecon-
structed the view of the fly cruising through its arena. For Cal-
liphora and Eristalis we used head trajectories. We took three
sample trajectories flown by three different flies of each species.
From these samples, we reconstructed the view during each tra-
jectory position. These movies were then played back repeatedly
to the experimental animals. Note that the Eristalis movies could
not be reconstructed with all walls intact, because in the experi-
mentalsetupwehadtouseanacrylicglasswallandceilingtolook
high speed videotrajectory
1st-person-perspective
so on-
optic flow
replay
replay
neuronal response
prototypical
movements
1
4
7
2
5
8
3
6
9
cluster
reconstruct
segregate
record
see Geurten et al. 2010 / Braun et al. 2010
FIGURE 2 | Experimental overview. Overview of the experimental
procedures used to obtain the data presented in this article. We recorded
Eristalis tenax with a set of high-speed cameras (upper left corner) to
obtain 3D trajectories of their flights (first row, middle). In case of Calliphora
vicina Dr. van Hateren (University of Groningen, Netherlands) provided us
with 3D head trajectories. We used these trajectories as data for clustering
analysis that rendered nine prototypical movements (PMs; upper right
corner).The first row is enclosed by a frame, which indicates that these
results were already published.We used these PMs as categories and each
position in the trajectories is assigned to a PM. Bearing this in mind, we
reconstructed the optic flow seen while moving on a given trajectory
(central picture). Now we could use the nine PMs to segregate the optic
flow we calculated directly from head trajectories (second row, right).
Hence we were able to calculate the optic flow from all the positions that
were assigned to the same PM. Furthermore we reconstructed first person
perspective movies (second row, left) from the same trajectories. We used
these movies as stimuli for electrophysiological experiments (third row left).
The neuronal responses from these experiments (third row, middle) could
be again segregated with the PMs (third row, right).
into the arena (Geurten et al., 2010). These walls are white in the
reconstruction. The vCH cell, analyzed in the present study, has a
receptive field mostly in the ventral half of the visual hemisphere
and,therefore,isstimulatedbythese“undefined”dorsalwallsonly
marginally.Furthermore,wechosetrajectoriesinwhichtheanimal
infrequently looked at the transparent walls.
ANALYSIS OF ELECTROPHYSIOLOGICAL DATA
The vCH neuron responds with a change in its graded membrane
potentialtostimuli.Inallcaseswesubtractedtherestingpotential
from the vCH response. The responses of each cell were averaged
over repetitive presentations of the same stimulus. Then the mean
and standard deviation (SD) of the responses across cells were
calculated.
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Geurten et al. Species-specificity in response dynamics
For calculation of PM-triggered response averages we used the
changeof PMsortheoccurrenceof aPMasatriggerfortheanaly-
sis. First,every data point in the trajectories was assigned to a PM.
Next, we defined a time window of 50ms symmetrically around
transitions between certain PMs. Finally, we calculated the trig-
gered response averages within the time window. In a similar way,
we calculated the saccade-triggered averages in a time window of
200ms located symmetrically around the peak velocity of each
saccade.
RESULTS
FLIGHT STYLES AND THEIR IMPACT ON OPTIC FLOW
In Figure2 we describe how we collected data and categorized the
resulting measurements.We used the PMs to reduce the complex-
ity of naturalistic time-dependent flight patterns. In this way, we
reducedthetrajectories’complexityoriginallygivenbytheirtime-
dependent rotational and translational velocity values to a series
of just nine states, i.e., the PMs. The PMs are plotted in Figure 1
to allow for easy comparison and are discussed in detail in Braun
et al. (2010) and Geurten et al. (2010).
The different flight styles of hoverflies and blowflies manifest
themselves in partly large differences of the optic flow evoked
by the different PMs (Figure 3). These PM-triggered flow fields
were obtained by the following procedure: The optic flow for all
positions and trajectories was acquired by using the Koenderink
algorithm(Koenderink,1986).TheKoenderinkalgorithmusesthe
3D structure of the world and calculates geometrically the optic
flow vectors. We projected these vectors onto a cylindrical coor-
dinate system, as can be seen in Figure 3. We then used the PM
assignmentforeachtrajectorypositiontocalculatethemeanoptic
flow over all flow fields elicited by one PM (see Figure 3).
ThesaccadicPMsleadtothestrongestopticflow(seeFigure3,
dark shading). Optic flow vectors evoked by the saccadic PMs are
pointing uniformly against the direction of rotation. The saccadic
optic flow is quite similar for both species,which is due to the fact
that both animals show similar fast rotations of short duration.
Likewise, there is also translational optic flow which is similar
for Eristalis and Calliphora. These similar flow fields (Figure 3,
intermediate shading) belong to combined forward and sideways
movements (Eristalis PMs 3 and 4 | Calliphora PMs 5–8). Not all
flow fields attributed to translational PMs of Eristalis and Cal-
liphora are similar though (Figure 3, light shading). Rather, they
may differ strongly from each other. For further information,e.g.,
the focus of expansion, see Appendix.
CHARACTERIZATION OF A HOMOLOGOUS VISUAL INTERNEURON – vCH
To assess whether these different PM-driven inputs are reflected
by the properties of neurons that are sensitive to optic flow, we
focused on the vCH neuron from which we recorded repeatedly
in both animals (Calliphora N =8;Eristalis N =8). Evidence that
the presumed vCH cell of Eristalis is homolog to its Calliphora
counterpart is based on the cell’s receptive field properties and
preferred direction of motion (see Figure A2 in Appendix) as
well as its anatomy. Since the anatomy of vCH of Eristalis was
FIGURE 3 | Mean optic flow induced by prototypical movements.
Optic flow calculated geometrical from head trajectories of both species.
The red arrows are scaled differently than the blue ones (they code for
four times the velocity of the blue arrows). A field of view of 120˚
elevation is depicted.The mean optic flow for each prototypical
movement was calculated (numeration as in Figure 1). In the lower left
corner of each flow field the corresponding PM is shown. (A) Eristalis
optic flow calculated with head trajectories and segregated after body
PMs. (B) Calliphora optic flow calculated from head trajectories and
segregated after head PMs.
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Geurten et al. Species-specificity in response dynamics
Lobula plate
Medulla
vCH neuron
Oesophagus
Lobula plate
Medulla
Oesophagus
HSN
HSNE
HSE
HSS
vCH
Retina
Medulla
Lamina
Lobula plate
Lobula
FIGURE 4 | Morphology of the Eristalis ventral centrifugal horizontal
(vCH) neuron in relation to the four HS-cells.The top row insets show
the location of the lobula plate inside the hoverfly’s head.The
ventral–dorsal projection of the lobula plate with superimposed tangential
cells is drawn below.The reconstructions of depth projections
(z-projections) of the cells’ main arborizations were copied by hand into
vector graphics.The horizontal system (green, yellow, orange, red) was
plotted to give relative position of the vCH (blue). In the bottom row a
z-projection of the vCH cell is superimposed on a wide-field image of the
fly’s brain.
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Geurten et al. Species-specificity in response dynamics
not known before, we dye-injected it as well as other tangential
cells with Oregon green (see Materials and Methods for details).
We used a dorso-ventral projection of the fill to draw a recon-
struction of the cell’s main arborizations (see Figure4). The main
arborization of the Eristalis vCH does branch in a similar fashion
to that of Calliphora (Hausen, 1993), and its position relative to
the HS-cells, another type of identified tangential cells (Hausen,
1982a,b), is similar.
In a preceding study Eristalis tangential cells were shown to
be more sensitive to slower temporal frequencies under steady-
state conditions than blowfly tangential cells (O’Carroll et al.,
1996). Therefore and because of the differences in flight dynamics
between blowflies and hoverflies we asked whether vCH cells in
both species are differently tuned to motion transients. To assess
the cells’ dynamical response properties, they were exposed to
instantaneous velocity changes. We presented a spinning drum
covered with a stripe-pattern, which drives the cell to very large
gradedmembranepotentialchanges.Thepatternmovedhorizon-
tally at a temporal frequency of 2Hz, instantaneously switching
direction after 1080ms. Although both species’ vCH cells (Cal-
liphora N =5,n =3–7|Eristalis N =8,n =2–10)signalsaresim-
ilar with respect to amplitude and shape (see Figure5),they differ
in the timing. The Eristalis vCH responds faster to the direction
changethandoestheCalliphora vCH.Forachangefrompreferred
to anti-preferred direction, the time shift between the responses
of the two species – determined at half-maximal response – is
6.8ms, and for the opposite directional change the time shift is
4.3ms. Our further analysis concentrates on the properties of this
difference.
To ensure that these large time shifts are not artifacts of the
data analysis,we conducted several controls. Since response laten-
cieshavebeenfoundtobetemperaturesensitive(Tatleretal.,2000;
Warzecha and Egelhaaf,2000; Egelhaaf et al.,2001),we controlled
thetemperatureinallexperiments.Themeantemperatureduring
the Eristalis experiments was 29.7±1.8˚C, the mean temperature
during all Calliphora experiments was 28.9±1.8˚C. In all tests,
only one Calliphora vCH was faster than the three slowest Eristalis
vCH cells. All other Calliphora vCH were slower than any of the
eight Eristalis cells. We only used female freshly emerged flies (1–
3days old) to ensure that the time shift was not biased by gender
or age differences.
COMPARISON OF RESPONSES ELICITED BY NATURALISTIC
STIMULATION
We reconstructed the image sequences seen by both fly species
during real flight trajectories and analyzed the responses of each
vCH (see Figure 6) cell to the image sequences induced by the
flight of its own and the other species (Calliphora N =5, n =3–
23 | Eristalis N =8, n =3–11). The complete response to a 3.5-s
flight sequence (see Figure6) is extremely complex because of the
many factors that influence the visual input perceived by the ani-
mal. The responses of vCH cells are influenced by the motion of
the fly, the distance to the walls and the apparent texture of the
walls,aswellasthehistoryof stimulation.Thismakesdeciphering
which of the parameters elicited which component of the cellular
response a very complex task. The PMs aid our analysis by reduc-
ingthiscomplexity,astheydidwhenweanalyzeddifferencesinthe
FIGURE 5 | vCH responses to instantaneous velocity changes during
spinning drum stimulation.The vCH cells of blowflies and hoverflies were
stimulated with a sinusoidal vertical stripe pattern moving in horizontal
direction at 2Hz temporal frequency for 1080ms in each direction. Onset to
null-direction motion (A) and to direction changes of either polarity (B,C).
Resting potential is marked by the dashed black line.The blue line denotes
the Calliphora responses (N =5, n=3–7) and the red line the Eristalis
responses (N =8, n=2–10).The gray areas around the lines mark the
standard deviations. Light green horizontal lines correspond to time shifts
(green numbers) between responses at half-maximal response.The
stimulus apparatus is depicted next to the figure legend. Below the time
axis the movement direction of the stripe pattern is given.
overall optic flow experienced by the two species as a consequence
of their different flight styles.
As is known from previous studies, the vCH cell of blowflies
reacts to yaw saccades with strong depolarizations and hyper-
polarizations, depending on the turning direction (van Hateren
et al., 2005). When stimulated with the optic flow generated by
Calliphora flights (Figure 6B) the saccadic turns and the peak
depolarizationsof themembranepotentialarestronglycorrelated
with the vCH cell responses of both species. Note that response
amplitude is not linearly related to saccade peak velocity. This
can be observed in Figure 8B for the saccades between 1.75 and
2.5s. Saccades in this part of the stimulus have very different
peak velocities, but the vCH cells respond with similar depolar-
ization levels. In intersaccadic intervals that are dominated by
translations, the vCH cells are much less activated. The cells from
both fly species respond differently to the optic flow generated
during Eristalis flights (Figure 6A). Here, not all depolarizing
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Geurten et al.Species-specificity in response dynamics
response peaks correlate with yaw saccades but instead correlate
with translational PMs, for example the depolarizations marked
with an asterisk in Figure 6A. Hence, the response profiles of
vCH cells in Calliphora and Eristalis seem to mainly depend on
the characteristics of the flight used for stimulus reconstruction.
The translational movements of Eristalis (in our arena) are slower
than those of Calliphora, which leads to a different stimulation
history.
The average responses of Calliphora and Eristalis vCH cells
(Calliphora N =5,n =3–23 | Eristalis N =8,n =3–11) triggered
by yaw saccades are shifted in time with respect to each other
(Figure 7). Again, we calculated the time shift at half-maximal
response. The Eristalis vCH is always faster than its blowfly
counterpart. The time shift between responses of both species’
vCH amounts to 12ms for blowfly preferred-direction saccades
(Calliphora; Figure 7B) and to ∼10ms for hoverfly preferred-
direction saccades (Eristalis, Figure 7A). For the anti-preferred
direction, the values seem to differ considerably but cannot be
quantified, because the responses have no distinct peaks, which
are necessary to accurately assess time-shifts.
Hoverflies and blowflies do not only change rotational veloci-
tiesratherabruptly,butalsotranslationalones,forexampleduring
zig-zagging. In this case forward flight is superimposed by alter-
natingsidewayscomponents(SchilstraandvanHateren,1999;van
Hateren and Schilstra, 1999; Geurten et al., 2010). Components
of the zig-zagging can also be found in the PMs of both species
FIGURE 6 | vCH responses to flight reconstructions. (A) Mean response
(±SD) of Eristalis (red) and Calliphora (blue) vCH cells, respectively, to the
reconstruction of the optic flow experienced during an Eristalis flight. Dashed
black line marks the resting potential. vCH responds best to horizontal
motion.Therefore, the corresponding yaw velocity trace is plotted below the
responses in black. In A strong depolarizations not accompanying fast yaw
velocities were marked with an asterisk.The prototype assigned to the
trajectory at each such instance is plotted above. (B)The responses of the
same neurons to a Calliphora flight. Eristalis vCH N =8, n=3–11 | Calliphora
vCH N =5, n=3–23.
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Geurten et al.Species-specificity in response dynamics
FIGURE 7 | Saccade-triggered vCH response. Mean response (±SD) of
Eristalis and Calliphora vCH cells, respectively, in a 200-ms time window
centered about the peak velocity of yaw saccades (0ms). Eristalis response
(N =8, n=3–11) is plotted in red and the Calliphora response (N =5,
n=3–23) is plotted in blue. Light green numbers and line denote the time
shift between mean responses at half-maximal response. Resting potential
is marked by the dashed black line. (A) Eristalis, (B) Calliphora saccades.
(see Figure 1, blowfly: PMs 5–8, hoverfly: PMs 3 and 4). There-
fore we analyzed the responses of blowfly and hoverfly vCH cells
(Calliphora N =5,n =3–23 | Eristalis N =8,n =3–11) to transi-
tions from forward-left PMs to forward-right PMs and vice versa
(Figure 8). The translational direction changes lead to smaller
changes in optic flow than do saccades. The corresponding time
shiftsintheneuralresponses(Figure8)arealsosmallerthanthose
corresponding to saccades (Figure 7).
We hypothesized that the values of time shift depend on the
transienceof changeintheopticflow.Althoughthefastestchange
in optic flow is elicited by the instantaneous direction reversal
in the spinning drum experiment (Figure 9, left column, and
Figure 5), it does not produce the largest time shift. The second
fastest change as evoked by saccades led to the largest time shifts
(Figures7 and 9). Eristalis yaw saccades in our setup have a mean
peak at ∼1000˚·s−1and have a slightly broader shape than their
Calliphora counterparts (∼2000˚·s−1; Schilstra and van Hateren,
1999;vanHaterenandSchilstra,1999;Geurtenetal.,2010).Hence,
the change in the corresponding optic flow is less transient in
Eristalis than in Calliphora. This difference in optic flow dynam-
ics might be reflected in the somewhat larger response time shift
duration for blowfly than hoverfly saccades. We stress here that
the gradual change in the magnitude of the time shift duration is
not merely due to the amplitude of the cell’s membrane potential
change.Inallthreesituations(spinningdrum,Calliphora saccade,
Eristalis saccade) the cell membrane potentials peak in the satu-
ration region of the cells’response range. The smallest time shifts
were observed for the side-to-side PM combinations (Figure 8).
Again, within this subgroup of stimuli, the stimulus correspond-
ing to the largest sideways component (the largest change in optic
flow) elicits the largest time shift.
Insummary,Eristalis vCHcellsrespondthefastertoopticflow,
the more transient the change in optic flow is. This holds true
for naturalistic situations, but not for the instantaneous direction
reversal.
DISCUSSION
In this study we analyzed how the different flight styles of
two fly species, Eristalis tenax (hoverflies) and Calliphora vicina
(blowflies) affect the optic flow the animals perceive during flight.
Furthermore we analyzed the dynamics of the corresponding
neural responses of an identified motion-sensitive neuron, the
vCH cell. This cell integrates complex binocular optic flow infor-
mation. The optic flow perceived by Eristalis varies more than
the flow perceived by the blowfly. We recorded and compared the
responses of a visual interneuron to image sequences experienced
by both fly species during free flight to assess potential adapta-
tions to each specific flight style. We found the neural responses
to temporal changes in optic flow to be faster in hoverflies than
in blowflies, with the time shift between the responses of both fly
species depending on the transience of changes in the optic flow
pattern.
For our analysis we used reconstructions of what flies saw dur-
ing free flights in confined arenas. The hoverfly flight arena has
obvious limitations. On the one hand, the size of the arena does
not allow for high velocity flights and thereby only allows us to
observe a part of the animals’ flight repertoires. On the other
hand, in many circumstances the flies also fly in confined areas
in nature. The relatively small size of the flight arena used in our
Eristalis experimentsisduetothenecessitytoresolvethefly’shead
with camera lenses (for a discussion of the blowfly setup limita-
tions,seeSchilstraandvanHateren,1999,p.1488).Thedifferently
sizedarenasusedintheCalliphora andEristalis experimentsprob-
ably had minimal impact on flight behavior. Previously (Geurten
et al., 2010) we showed that even a large change in arena size did
not much affect the flight behavior of Eristalis.
One should not mix up the limited depth structure in the used
flight arenas with the lack of a physical 3D environment. Even
though the distance distribution might be more complex in most
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Geurten et al.Species-specificity in response dynamics
FIGURE 8 | Responses to sideways direction inversion during forward
flight.This figure shows the vCH responses to translational direction
changes.The color code is as in Figure 5 (Eristalis vCH n=8 | Calliphora
vCH n=5). Plots show mean responses (±SD) of Eristalis and Calliphora
vCH cells, respectively, in a 44-ms time window centered about the
movement direction switch from forward-right to forward-left (A,B) or
vice versa (C,D) (see insets). At 0ms the direction switches. Responses in
(A,C) were elicited by Eristalis flights.The stimuli in (B,D) were from
Calliphora.The time shift denotes the time difference between reaching
the half-maximal response in Eristalis and Calliphora vCH, respectively.
Resting potential is marked by the dashed black line. Note the differently
scaled y-axis in (D).
free-flight situations,both species were cruising successfully – i.e.,
withoutwallcollisions–intheconfinedflightarenas.Thusbothfly
species had access to information about the three-dimensionality
of their actual environment.
Various fly species (Collett and Land, 1975a; Wagner, 1986;
Schilstra and van Hateren, 1999; van Hateren and Schilstra, 1999;
TammeroandDickinson,2002b;Braunetal.,2010;Geurtenetal.,
2010) as well as honeybees (Boeddeker et al., 2010), and finches
(Eckmeier et al., 2008) divide their flight trajectories into rota-
tional and translational segments (Figure 1). We used clustering
algorithmstoreducethecomplexityofthebehaviorandtocatego-
rize trajectories of both species into PMs. The rotational PMs are
of shorter and less variable duration than the translational PMs,
which have a more flexible duration (Figure 1). The separation
between rotational and translational movements is believed to aid
theperceptionofthe3Dstructureoftheflies’surroundings(Land,
1999). Only translational optic flow contains 3D information, so
reducing the rotation duration reduces the animals’3D blindness.
It was shown for Calliphora that membrane potential changes of
tangential cells contain 3D information during the intersaccadic
interval (Kern et al., 2005; Liang et al., 2008).
As a first approach to quantify the impact of the two species’
differentflightstylesontheirvisualinput,wedeterminedtheoptic
flow geometrically. For both species, the yaw saccades led to the
strongest optic flow. At least under our experimental conditions,
Calliphora’s translational movements create stronger optic flow
than those of Eristalis (see Figure3). However,the patterns of the
image shift are vastly different between species. These differences
manifest themselves in the distributions of the focus of expansion
(FOE) across the visual field for both species. The blowfly always
keeps the FOE between −30˚ and 30˚ in azimuth (see Figure 3
and FigureA1 in Appendix). Eristalis’FOEs are distributed much
more homogeneously across the visual field. We are not aware
of any study where the distribution of the FOE across the visual
field during naturalistic flight has been determined. By definition,
the FOE centers an expansion flow field. Tammero and Dickinson
(2002b) suggested that the difference in image expansion about
two hypothetical FOEs, located at 45˚ in the left and right frontal
visualfield,respectively,intheintersaccadicintervalcanbeusedas
a trigger for subsequent saccades in Drosophila. Since in contrast
to Calliphora and Drosophila regions with image expansion are
distributed across almost the entire visual field in Eristalis, a sac-
cadetriggeringmechanismbasedonimageexpansionwouldhave
to exist in parallel at many locations across the entire visual field.
Originally we hypothesized that Eristalis tangential cells might
beadaptedtosloweropticflowvelocitiesthanthoseof Calliphora,
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Geurten et al.Species-specificity in response dynamics
because in a previous study (O’Carroll et al., 1996) blowfly
tangentialcellswerefoundtobemostsensitivetovelocitiesaround
100˚·s−1(10Hztemporalfrequency),whereasEristalis wasshown
to prefer somewhat lower velocities around 70˚·s−1. Furthermore,
Eristalis responds much stronger at lower temporal frequencies
than Calliphora (0–1˚·s−1),whereas Calliphora responds stronger
at high temporal frequencies (more than 10˚·s−1). Nonetheless,
we did not find a clear difference in the responses to natu-
ralistic flight stimuli. One reason for this apparent discrepancy
might be that the velocity tuning curves were measured under
steady-state conditions (O’Carroll et al., 1996), whereas in our
experiments we stimulated the cells with highly transient natural-
istic optic flow. It is well known that steady-state and transient
velocity optima may differ tremendously (Warzecha and Egel-
haaf, 1999). Moreover, Eristalis is able to fly as fast as Calliphora
(Collett and Land, 1975b; Schilstra and van Hateren, 1999). We
found similar response amplitudes of Eristalis and Calliphora
vCH cells to Eristalis-specific optic flow. This might be due to
adaptive properties of the motion perception of both animals
(Harris et al., 1999, 2000; Warzecha and Egelhaaf, 2000; Egel-
haaf et al., 2001; Kurtz, 2007; Liang et al., 2008; Barnett et al.,
2010).Otherlobulaplatetangentialcellsbeinghomologsbetween
both species might behave differently. Nonetheless, single experi-
mentsdoneonHScells(Hausen,1982a,b)thatareoutputneurons
of the visual system, did not hint in that direction (data not
shown).
Wefoundaconsistenttrendof differencesinthetimingof both
species’response changes. The fastest acceleration we tested is the
instantaneous direction inversion of the spinning drum, which
results in a ∼7ms earlier response peak in Eristalis vCH than
in Calliphora vCH for a change from anti-preferred to preferred
directionmotion(∼4msforachangeof oppositepolarity).Inter-
estingly, preferred direction saccades, on average, elicit a larger
mean time shift of ∼12ms, although the change in optic flow
is less steep. Side-to-side movement switches (Figure 8) create a
mean time shift of ∼6ms. These side-to-side movement switches
are characteristic of the so-called zig-zagging (Schilstra and van
Hateren, 1999; Geurten et al., 2010), which could aid gathering
of 3D information in a similar fashion as peering behavior in
locusts and mantids (Wallace,1959;Sobel,1990;Kral and Poteser,
1997;Land,1999).DuringPMchangesfromhoveringtoforward–
sideward movement we did not find a clear time shift (data not
shown). It is likely that the time shift depends on the transience of
the change in the optic flow.
Onemightthinkof thetimeshiftasanimmediateconsequence
of the change in membrane potential evoked in the vCH cell. A
strong stimulus would elicit a large membrane potential change
andthereforealargetimeshift.Aweakstimuluswouldonlyelicita
smallchangeinmembranepotentialandrenderasmalltimeshift.
This is not true, because both saccades and the spinning drum
experiment drive the vCH cell into the saturation response region
and still the responses show different time shifts (Figure 9). The
time shift is less dependent on the actual membrane potential,but
rather on the transience of the stimulus.
The visual stimuli employed in most of our experiments were
aimed at approximating natural stimulation during free flight.
However, due to methodological limitations the animal had to
FIGURE 9 |Time shift overview.Time shift between the responses of
Calliphora and Eristalis. In all cases Eristalis vCH reacted faster to the
change in optic flow as determined by the time difference between reaching
the half-maximal response. Below each bar the stimulus is depicted that
corresponds to the time shift. Stimuli always built from changes to
preferred direction motion.Time shifts corresponding to the following
stimuli (from left to right): (1) Instantaneous direction inversion in a spinning
drum experiment; (2) Calliphora saccade; (3) Eristalis saccade; (4) Switch
from a forward-right to a forward-left movement in Eristalis; (5) Switch from
a forward-right to a forward-left movement in Calliphora; Note that the
sideways component preceding the switch is much smaller in Calliphora
than in Eristalis, therefore the change in optic flow is larger in (4) than in (5).
be tethered during the intracellular recording experiments and,
therefore,wasnotinaclosedloopsituation.Asaconsequence,sen-
sory input from mechanosensory systems as halteres and anten-
nae were missing, as well as a possible efference copy from the
motor system. Recent studies have shown that if the fly is in an
active locomotion state (Rosner et al., 2009, 2010; Maimon et al.,
2010) tangential cells respond with larger amplitudes than with-
outmotoractivityandthatthevelocitytuningisshiftedtoslightly
higher values (blowfly: Jung et al., 2011; fruit fly: Chiappe et al.,
2010). Pharmacological studies rendered octopamine as a candi-
dateforthismodulationofneuronalactivity(LongdenandKrapp,
2010; Jung et al., 2011). Since in our electrophysiological exper-
iments both Eristalis and Calliphora were tethered and not in a
behaviorally active state the responses evoked by the same stimuli
can be compared across these experiments,even though they may
slightly change during motor activity.
The functional significance of the faster Eristalis responses,
compared to Calliphora, to behavioral relevant changes in optic
flow will be the subject of further studies. For now we can only
speculate. Eristalis may fly in close proximity to flowers within
cluttered surroundings. The vCH cell is a wide-field interneuron
that, based on its preferred direction and receptive field charac-
teristics, might reduce the response of FD cells during saccades
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Geurten et al.Species-specificity in response dynamics
(Egelhaaf, 1985a,b,c; Egelhaaf et al., 1993; Warzecha et al., 1993;
Hennig et al., 2011). FD cells might be of use in collision avoid-
ance tasks, for example while approaching or hovering within
flower butts. Being able to suppress and reactivate the colli-
sion avoidance system very fast might be of great importance
when navigating in very cluttered and close proximities. It has
to be subject to further studies whether the specific tuning of
Eristalis’ vCH cells facilitates its flight in close proximities to
flowers.
CONCLUSIONS
During cruising flight hoverflies and blowflies compress
rotational movements into fast and short saccades. Consequently,
translational phases in-between saccades virtually lack any rota-
tion. The optic flow induced by the idiosyncratic flight behavior
of thetwoflyspeciesisrathersimilarduringsaccadesbutverydif-
ferent during translatory phases. Nonetheless,a binocular neuron
thatcouldbeidentifiedashomologousinbothspeciesandextracts
optic flow information is not attuned to these species-specific dif-
ferences. Still, there is one major species-specific difference: The
neuron responds much faster to transient optic flow changes in
the hoverfly than in the blowfly, with the time shift depending on
the transience of the optic flow change.
AUTHOR CONTRIBUTIONS
BartR.H.Geurtenperformedtheexperiments(physiologicaland
behavioral), analyzed the data, and wrote the first draft of the
manuscript. Bart R. H. Geurten, Roland Kern, and Martin Egel-
haaf conceived the concept of the study. Roland Kern and Martin
Egelhaafcontributedtotheinterpretationofthedataandthewrit-
ing of the manuscript.All authors have approved the final version
of the manuscript.
ACKNOWLEDGMENTS
We thank J. H. van Hateren (University of Groningen, Nether-
lands) for providing us the head trajectory data of Calliphora
vicina. Many thanks to J. P. Lindemann for his help with the Fli-
Maxstimulusdevice,C.Spalthoff foradviceonfigurepreparation,
and N. Carey for improving the language of the manuscript. We
alsothankK.LunauforshowingBartR.H.Geurtenhowtocollect
Eristalis in the most efficient way and D. O’Carroll for his advice
on AlSi-electrodes.
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latency ofa
Conflict of Interest Statement: The
authors declare that the research was
conducted in the absence of any com-
mercial or financial relationships that
could be construed as a potential con-
flict of interest.
Received: 17 May 2011; accepted: 28 Feb-
ruary 2012; published online: 19 March
2012.
Citation: Geurten BRH, Kern R and
Egelhaaf M (2012) Species-specific flight
styles of flies are reflected in the response
dynamics of a homolog motion-sensitive
neuron.Front.Integr.Neurosci.6:11.doi:
10.3389/fnint.2012.00011
Copyright © 2012 Geurten, Kern and
Egelhaaf. This is an open-access article
distributed under the terms of the Cre-
ative Commons Attribution Non Com-
mercial License, which permits non-
commercial use, distribution, and repro-
duction in other forums, provided the
original authors and source are credited.
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Geurten et al. Species-specificity in response dynamics
APPENDIX
DISTRIBUTION OF THE FOCUS OF EXPANSION OF ERISTALIS AND
CALLIPHORA vCH CELLS
Wequantifiedthedifferencesintheopticflowofthetwoflyspecies.
Thereforewecharacterizedtheopticflowwithrespecttotheposi-
tion of the focus of expansion (FOE). The spatial distribution of
the FOE positions is plotted in Figure A1. Blowflies fly for most
of the time nearly straight forward and make only small sideways
movements. Consequently most of the blowfly FOEs are centered
in front of them (azimuth). This finding reflects the similarity of
theflowfieldsevokedbytranslationalPMsinCalliphora.Vertically,
thelociareshifteddownwardbyabout10˚,onaverage.Incontrast,
the foci of expansion are distributed more evenly across the visual
field for Eristalis. This reflects Eristalis ability to fly in virtually
anydirectionrelativetoitsbodylongaxisorientation(Collettand
Land,1975a,1978; Geurten et al.,2010). Thus,the data illustrated
in Figure A1 mirror the differing flight styles of the two animals
and highlight the preponderance of largely different inputs into
their visual systems.
The FOE was determined from the flow fields,characterized as
anareawhereallflowarrowspointawayfrom(e.g.,Figure3B,bot-
tom left,0˚ azimuth,0˚ elevation). To find these foci we calculated
the divergence of the optic flow vectors (Korn and Korn, 2000).
The divergence sources (FOE) and sinks (foci of contraction) in
anidealcontinuousvectorfieldareeitherpositive(source)orneg-
ative (sink) infinite. In our case we have a discrete sample point
pattern. Hence, the foci are often between sample points result-
ing in smaller divergences. Therefore we have to use a threshold,
which was set to 10% of the number of the vector field’s sample
points. For instance, in case of expansional optic flow 10% of the
vectorshavetopointawayfromtheFOE.Weusedthisratherhigh
threshold, because we presumed Eristalis to have more variable
FOE positions than Calliphora.Also a high threshold ensured that
the positions of the detected FOEs reflect real FOEs and not noise
from the digitization or the discrete sampling grid. Optic flow
fields corresponding to pure rotations do not contain a FOE (e.g.,
Figure 3B, PMs 1–4). Note that the FOE can only be calculated
inside the field of view,i.e.,the sampling grid. Hence,FOEs above
and below −60˚ to 60˚ in elevation were missed. The MATLAB
toolbox to do these calculations was programed by C. Strub,Dr. J.
Lindemann, Dr. W. Stürzl, and Dr. B. Geurten.
RECEPTIVE FIELD OF vCH IN ERISTALIS AND CALLIPHORA
For a subpopulation of the recorded vCH cells, we compared the
local preferred directions of motion between Calliphora (N =4)
and Eristalis vCH (N =3). We used a stimulus similar to Nord-
ström et al. (2008) to characterize the receptive field properties
of the cells. A vertical bar of 2˚×10˚ (width×height), centered
about seven different elevations (−85˚, −57˚, −28˚, 0˚, 26˚, 47˚,
68˚),scanned the receptive field horizontally in both directions. A
horizontal bar of 10˚×2˚ (width×height), centered about seven
different azimuths (−90˚, −60˚, −30˚, 0˚, 30˚, 60˚, 90˚), traversed
the field of view vertically.
010.25
normalised distribution density
0.50.75
azimuth [deg]
0-180
0
60
-60
elevation [deg]
180
blowfly focus of expansion
hoverfly focus of expansion
FIGUREA1 | Distribution of the focus of expansion.The location of the
focus of expansion within the visual field was calculated from the optic flow
corresponding to the head trajectories and plotted as color coded density
distribution; top: hoverfly, bottom: blowfly.The data were interpolated to
avoid hard edges of the sample point grid (grid as in Figure 3).The density
was normalized to the highest count inside the sample point grid separately
for each plot.
We plotted the mean local preferred directions, i.e., the recep-
tivefieldofthevCHcellofbothspeciesinFigureA2.Theresponse
vectorsareunderlayedwiththecolorcodedmeanresponseofvCH
to preferred direction motion in front of either eye. In both cases
the most sensitive part of the receptive field is located frontally.
The overall direction preference is similar in both species. How-
ever, there are also differences: The hoverfly’s vCH cell (N =3)
has a larger receptive field with different vertical components
than its Calliphora (N =4) counterpart. The characteristics of
the response field of the Calliphora vCH differ slightly to the vCH
response field published by Krapp et al. (2001) which might be
duetodifferentstimulationandanalysismethods.Forexample,we
usedasmalltargetcrossingthefieldof viewratherthanamechan-
ical disk spinning at different locations of the receptive field as
in Krapp et al. (2001). Moreover, we applied a vector method
rather than a sinusoidal fit to approximate a neuron’s preferred
direction. Nonetheless, the most sensitive region of the receptive
field and the preferred direction within this region are similar.
Most importantly, the extended responsiveness with respect to
elevation of the Eristalis vCH as compared to its Calliphora coun-
terpart is obvious from our data and the data of Krapp et al.
(2001).
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Geurten et al. Species-specificity in response dynamics
FIGUREA2 | Receptive field of vCH in Eristalis and Calliphora. Each
plot shows the receptive field of vCH in a window of >140˚ elevation
and >160˚ azimuth.The false color map behind the local preferred
directions codes for the mean response amplitude of the cells to
movement from the left to the right at seven different elevations.The
false color map was interpolated to avoid hard edges of binning the
data.The superimposed arrows show the local preferred directions
(length codes for local sensitivity). Black arrows are samples. Gray
arrows are linearly interpolated.To determine the receptive fields a
narrow but high (2˚×10˚) target was presented to vCH neurons which
traversed the complete field of view horizontally at seven different
elevations in both directions. In addition, the same target, rotated by
90˚, was presented on a vertical trajectory at seven different azimuths.
The local direction preference of the vCH cell (FigureA2) was calculated
as follows: At first we corrected for the latencies of the cells. We
calculated the latency from the replay experiments (see Materials and
Methods), by calculating the mean time difference between the
saccade velocity peak and the response amplitude peak. For each
movement direction adopted by our bar stimulus (left to right, right to
left, top to bottom, bottom to top) we calculated the mean response
across cells. We treated the membrane potential change as the length
of a vector pointing in the direction of target motion. Summation of all
four vectors yielded the preferred direction vector.The length of this
vector was set to represent the local direction sensitivity.This was done
at all locations within the sampling grid.The color map behind the local
preferences shows the mean interpolated reaction of the cells to
left-to-right motion. (A) Receptive field of Eristalis vCH (n=3), (B)
receptive field of Calliphora vCH (n=4).
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