1Lehrstuhl für Neurobiologie, Fakultät für Biologie, Universität Bielefeld, D-33501 Bielefeld; and 2Max-Planck-Institut für Biologische Kybernetik, D-72076 Tubingen, Germany
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ABSTRACT |
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Krapp, Holger G., Roland Hengstenberg, and Martin Egelhaaf. Binocular Contributions to Optic Flow Processing in the Fly Visual System. J. Neurophysiol. 85: 724-734, 2001. Integrating binocular motion information tunes wide-field direction-selective neurons in the fly optic lobe to respond preferentially to specific optic flow fields. This is shown by measuring the local preferred directions (LPDs) and local motion sensitivities (LMSs) at many positions within the receptive fields of three types of anatomically identifiable lobula plate tangential neurons: the three horizontal system (HS) neurons, the two centrifugal horizontal (CH) neurons, and three heterolateral connecting elements. The latter impart to two of the HS and to both CH neurons a sensitivity to motion from the contralateral visual field. Thus in two HS neurons and both CH neurons, the response field comprises part of the ipsi- and contralateral visual hemispheres. The distributions of LPDs within the binocular response fields of each neuron show marked similarities to the optic flow fields created by particular types of self-movements of the fly. Based on the characteristic distributions of local preferred directions and motion sensitivities within the response fields, the functional role of the respective neurons in the context of behaviorally relevant processing of visual wide-field motion is discussed.
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INTRODUCTION |
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Visual motion is due to relative
movements between the eyes of an observer and the visual structures of
the environment. The resulting motion pattern over the observer's eyes
is commonly referred to as "optic flow" (Gibson
1950), which is a description of retinal image movements in
terms of local velocity vectors. The global structure of optic flow
fields reflects the observer's mode of self-motion, i.e., rotation,
translation, or a combination of both (Koenderink and van Doorn
1987
, reviews: Lappe 2000
; Lappe et al.
1999
). During translation, nearby objects induce larger flow
vectors than more distant objects. Thus translation induced optic flow
contains relative distance information about the three-dimensional environment.
In the nervous system, optic flow is initially analyzed by arrays of
retinotopically arranged local direction-selective elements (review:
e.g., Borst and Egelhaaf 1989). Local motion analysis on
its own, however, does not allow the system to decide whether self-translation or -rotation induced the respective retinal image shift. A common strategy to disambiguate the situation is to spatially integrate motion information. The specificity of such integrating elements to sense rotatory or translatory self-movement can be further enhanced if motion information from both visual hemispheres is
combined. In vertebrates with laterally positioned eyes, such as
rabbits and birds, as well as in arthropods equipped with panoramic vision, extensive spatial pooling of motion information and
interactions between both eyes were shown to increase the sensitivity
to particular optic flow fields (rabbits e.g., Leonard et al.
1988
; birds e.g., Wylie and Frost 1999
;
crustaceans: Kern et al. 1993
; Nalbach and Nalbach 1987
; insects e.g., Hausen and Egelhaaf
1989
; Ibbotson 1991
; Kern 1998
;
Kern and Varjú 1998
).
In the fly lobula plate, which is the final neuropile in the
optic lobe, approximately 50-60 individually identifiable tangential neurons have been found (Hausen 1984). Tangential
neurons receive ipsilateral visual input from many retinotopically
arranged elementary movement detectors (EMDs) (review: Egelhaaf
and Borst 1993
). This is leading to receptive field sizes,
which, in some cases, comprise almost the whole visual hemisphere. Many
tangential neurons are thought to be concerned with optic flow
processing in the context of course and gaze stabilization
(Bausenwein et al. 1986
; Geiger and Nässel
1981
; Götz 1983
; Hausen and
Wehrhahn 1990
; Heisenberg et al. 1978
;
Hengstenberg 1995
). Recently it was shown for a class of
tangential neurons that their ipsilateral receptive field organization matches the global structure of optic-flow fields induced by
self-rotations around horizontally aligned body axes (Franz and
Krapp 2000
; Krapp 2000
; Krapp and
Hengstenberg 1996
).
To what degree does binocular vision increase the specificity
of tangential neurons to sense particular self-movements? To answer
this question, we investigated the receptive field organization of the
horizontal system (HS) and centrifugal horizontal (CH) wide-field
tangential neurons (Dvorak et al. 1975; Hausen
1976b
, 1982a
,b
), which are thought to be involved in optomotor
course control (HS neurons) and figure-ground discrimination (CH
neurons) (Hausen and Wehrhahn 1989
; review:
Egelhaaf and Borst 1993
; Hausen and Egelhaaf
1989
). Besides their ipsilateral retinotopic inputs, most of
these neurons receive contralateral motion information (Egelhaaf
et al. 1993
; Hausen 1976a
, 1981
;
Horstmann et al. 2000
). Here we determine the local
preferred directions (LPDs) and local motion sensitivities (LMSs) at
many positions within the ipsi- and contralateral visual hemispheres.
Furthermore we present the receptive field organization of
heterolateral connecting elements, which are thought to mediate the
contralateral input to the binocular HS and CH neurons. Based on the HS
and CH neurons' local response properties, it is quantitatively
estimated how their monocular specificity to particular self-movements
is influenced by their binocular input.
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METHODS |
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Preparation
Experiments were performed with 1- to 2-day-old female blowflies
of the genus Calliphora. Before dissection for
electrophysiology, the animals were briefly anesthetized with
CO2. Legs and wings were removed and the head was
tilted forward and fixed to a holder. Alignment with the visual
stimulus device was achieved by adjusting the head according to the
symmetrical deep pseudopupil (Franceschini 1975) in the
frontal region of both eyes. For intracellular recordings, the gut and
muscles of the mouth parts were removed to reduce brain movements.
After opening the head capsule from behind to get access to the lobula
plate, fat tissue, air sacs, and tracheae were removed. Wounds, except
the opening in the head capsule, were closed with wax to prevent the
animal from desiccation. By adding saline solution, the nervous tissue
was kept moist (Hausen 1982a
).
Electrophysiology
Extracellular tungsten electrodes with an impedance of about 2 M were used to record action potentials from the heterolateral connecting elements H1, H2, and V1. For intracellular
recording, we pulled glass capillaries (Clark, GC 100F-10) on a Brown
Flamming puller (Sutter Instruments, P87). The tips were either filled with a solution of 3% Lucifer yellow CH (Sigma) in 1 M LiCl, and the
shaft with 1 M LiCl or the entire electrode was filled with 1 M KCl.
The resistance of the electrodes was 40-60 M
. In all recordings, a
tip-broken glass capillary was used as a ground electrode and to supply
the brain with saline solution. We used electrophysiological standard
equipment for the recordings (see Krapp et al. 1998
).
Extracellularly recorded spikes were converted into unit-pulses and
sampled at a rate of 0.72 kHz. Intracellularly recorded signals were
sampled at the same rate. Programs for data acquisition and evaluation,
as well as for controlling visual stimulation, were written in ASYST
4.0 (Macmillan Software).
Identification of investigated neurons
Most of the intracellularly recorded neurons were injected with
Lucifer yellow and identified in situ immediately after the experiments
by fluorescence microscopy (Zeiss, Axiophot, fluorescein isothiocyanate
filter combination). Due to their anatomical characteristic, the HS
neurons could be easily distinguished from each other as well as from
the two CH neurons (Hausen 1981). The response fields of
individual tangential neurons are remarkably reproducible from animal
to animal and can thus be considered a characteristic fingerprint (Krapp et al. 1998
). Therefore in later experiments,
Lucifer yellow was no longer applied, and the identification was
achieved according to the response fields.
The heterolateral H1 neuron can be identified unambiguously by
recording from its output region in the left lobula plate and stimulating the contralateral eye from which it receives its input (Hausen 1976b). H2, like H1, is sensitive to horizontal
back-to-front motion over the right eye and conveys its spikes to the
contralateral part of the brain. The H2 recording reported here took
place within its dendritic input region. H2 was distinguished from H1
by means of physiological differences between the neurons. First, the
spontaneous activity of H2 is almost zero, whereas H1 spontaneously
generates spikes at rates between 10 and 40 Hz. Second, the maximum
firing rate of H2 is much lower compared with H1 firing rates
(Warzecha et al. 1998
). Third, the sensitivity
distribution within the response field of H1 is much broader than that
of H2 (cf. Fig. 4, A and B). The V1 spikes were
recorded within the neuron's output ramifications contralateral to the
side of its input region in the ventrolateral protocerebrum. V1 is as
yet the only known spiking heterolateral element that is sensitive to
vertical downward motion in the frontal to frontolateral visual field
(Hausen 1976b
; Krapp and Hengstenberg 1997
).
Determining the local response properties
The LPDs and LMSs were determined according to a procedure that
was described in detail by Krapp and Hengstenberg
(1997). A black dot (
= 7.6°) is moved along a
circular path (
= 10.4°) at 2 cycles/s for several cycles in
a clockwise (cw) and subsequently in a counterclockwise (ccw) direction
(Fig. 1A). During
intracellular recordings, three cycles in each direction were enough to
reliably determine the LPD (Fig. 1B); during extracellular
recordings, 10 cycles per direction were presented. When the
instantaneous direction of dot motion and the preferred direction of
the small field elements converging on the recorded neuron coincide,
the measured response becomes maximum. An unknown phase-shift caused by
response delays can be estimated and corrected by comparing the
responses to cw and ccw motion (Krapp and Hengstenberg
1997
). The phase-locked average of the responses to cw and ccw
motion, respectively, were pooled in 5° bins of successive dot motion directions (Fig. 1C). The mean LPD was determined by
calculating the direction of the mean vector of the resulting circular
response histogram (Batschelet 1981
). To keep from
loosing information about the neurons' absolute response range induced
by our local stimulus, we used a linear measure to define the LMS. It
is defined as the difference between the response averaged within the
interval of ±45° centered on the LPD and the response within an
equally sized interval obtained during motion in the opposite direction (Fig. 1C).
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Mapping the local response properties
In this report, we present results derived from different sets
of experiments. Data gathered from the neurons H1 and H2 were obtained
in animals whose left eye was occluded with nontoxic black acrylic
paint to avoid binocular cross-talk. In these experiments, local motion
stimuli were presented at 54 positions in the right visual hemisphere.
In experiments that aimed to investigate the binocular input to HS and
CH neurons and to V1, the number of measuring positions was 46 in the
right and 30 positions in the left visual hemisphere. LPDs and LMSs are
plotted as arrows in a Mercator map of the visual space where positions
are defined by two angles: the azimuth and the elevation
.
Positive values of
indicate positions in the right visual
hemisphere. Positive values of
denote positions above the eye
equator. The orientation of each arrow gives the LPD and its length
denotes the LMS, normalized to the respective maximum response of the
recorded neuron. In the following, such maps of the neurons' local
response properties are referred to as "response fields." The
Mercator map inherently distorts the dorsal and the ventral part of the
spherical visual field by the factor 1/cos
. To mediate a better
impression of the global appearance of the response fields, we
interpolated values between the actually measured data by applying a
Matlab routine (Vers. 5.3). The LPDs measured at the given positions (
,
) were decomposed into their x and y
components. This resulted
together with the respective LMS
distribution
in three two-dimensional scalar fields. The interpolation
algorithm used fits a smooth surface through two-dimensional scalar
fields and is based on Delauny-Triangulation (Watson
1994
). The interpolated arrows in the response fields were than
reconstructed from the interpolated x and y
components, scaled by the interpolated LMSs. Within the response fields
shown in RESULTS, all measured data are plotted in black;
interpolated values are shown in gray.
In most of our experiments, we did not carry out the time-consuming
histology and reconstruction but identified the stained neurons in
situ. To nevertheless show the morphology of the investigated neurons,
in the insets of Figs. 2-4, reconstructions are shown that were prepared, and kindly provided, by Hausen during his earlier studies (Hausen 1981, 1982a
, 1993
).
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RESULTS |
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HS neurons
The horizontal system (HS) consists of three neurons: the HSN,
HSE, and HSS (N, north; E, equatorial; S, south) (Hausen
1982a). Since HSS integrates only monocular motion information,
data obtained from this neuron are not included in our present report.
HSN dendrites occupy the dorsal part of the neuropil, whereas HSE
dendrites ramify in the medial part of the lobula plate (Hausen
1982a
) (cf. Fig. 2,
inset). Horizontal
front-to-back wide-field motion within the ipsilateral visual
hemispheres leads in HSN and HSE to depolarizing membrane potential
changes (Hausen 1982b
). These graded membrane potential
changes may be superimposed by sodium spikes of variable amplitude
(Haag et al. 1997
). Wide-field motion in the opposite direction results in hyperpolarizing membrane potential changes (Hausen 1982b
). In addition to the ipsilateral input,
HSN and HSE receive contralateral motion signals via heterolateral
connecting elements that are sensitive to back-to-front motion
(Hausen 1976a
, 1981
, 1982b
; Horstmann et al.
2000
). Although the overall response properties are well
investigated in the HS neurons (Hausen 1982a
,b
), information about their binocular receptive field organization with
respect to the distribution of local preferred directions and motion
sensitivities was not known.
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Figure 2 shows the binocular response fields of HSN and HSE. According
to its dendritic branching pattern, HSN is more sensitive to motion in
equatorial to dorsal parts of the ipsilateral visual field. The maximum
motion sensitivity of this neuron was found slightly above the eye
equator at an azimuth of about 0-15° (Fig. 2A) (cf.
Hausen 1982b). From this region, the LMSs decrease
toward the dorsal, caudal, and contralateral parts of the response
field. Within the ventral ipsilateral visual field HSN does not respond to motion. The ipsilateral response field of HSE comprises extended parts of the equatorial visual hemisphere that corresponds to its
dendritic arborizations within the medial part of the lobula plate. HSE
shows a sensitivity maximum around an azimuth between 0 and 15° at an
elevation of about
15° (Fig. 2B) (cf. Hausen 1982b
). The motion sensitivity levels off toward the dorsal and ventral visual field. The LPDs deviate from the exact horizontal in
most of the HSN and HSE response fields. In the frontal response field,
LPDs determined above and below the eye equator are tilted upward and
downward, respectively (cf. Hausen 1982b
). Deviations in
the opposite directions can be found in caudal parts of the response
fields. LPDs oriented about horizontally are confined to the equatorial
and lateral parts of the response fields (Fig. 2, A and
B).
The contralateral input to HSN and HSE has only a small impact on the
averaged membrane potential of these neurons (Hausen 1982a). Therefore applying our evaluation procedure (see
METHODS) results in relatively small local motion
sensitivities. To visualize the LPDs determined on contralateral
stimulation in Fig. 2, the length of the arrows within the framed areas
were scaled up by a factor of three (HSN) and two (HSE), respectively.
In this part of the response fields, both neurons respond preferably to
horizontal back-to-front motion along the eye equator. Only in the
frontolateral region around an azimuth of
45° within the HSE
response field the LPDs are slightly tilted downward. This deviation
from the horizontal is most likely caused by the LPD distributions of
the heterolateral elements that mediate the sensitivity of HSE to contralateral motion stimuli.
CH neurons
There are two CH neurons in each lobula plate, the VCH and the DCH
(V, ventral; D, dorsal) (Eckert and Dvorak 1983;
Hausen 1976a
, 1984
). The somata of the CH neurons are
connected via the primary neurite to their respective main arborization
in the contralateral part of the brain (see Fig.
3, inset) (cf. Hausen
1993
). CH neurons pick up inhibitory and excitatory inputs from
the contralateral visual field in the lateral protocerebrum (see Fig.
3, inset) (cf. Gauck et al. 1997
; Hausen 1976a
, 1984
,
1993
). In addition, the CH neurons receive retinotopic input to
their extended arborizations within the lobula plate (Dürr
and Egelhaaf 1999
; Egelhaaf et al. 1993
). CH
neurons whose main arborization is located within the right half of the
brain are predominantly excited by front-to-back motion in front of the
right eye and by back-to-front motion within the contralateral visual
hemisphere (Egelhaaf et al. 1993
; Hausen 1981
). VCH was identified to be a wide-field inhibitor
responsible for the small-field tuning of the figure detection neuron
FD1 (Egelhaaf 1985
; Warzecha et al.
1993
).
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The response fields of DCH and VCH extend over almost the entire visual field (Fig. 3, A and B). Compared to the HS neurons, CH neurons respond more strongly to contralateral motion stimuli. The right part of the DCH response field shows a broad sensitivity distribution with high LMSs slightly above the eye equator in the frontal and caudal visual field (Fig. 3A). The DCH responds predominantly to horizontal motion along the equatorial regions of the left eye up to the lateral part of the right eye. Only in the caudal parts of the right visual hemisphere do the LPDs tilt downward. The sensitivity maximum of VCH lies in the frontal visual field slightly below the equator (Fig. 3B). Unlike in DCH, the sensitivity decreases more steeply in all directions. A high sensitivity is maintained along the equatorial region within the right visual field where VCH is excited by horizontal front-to-back-motion. In the frontal to lateral region of the left visual field, the LPDs are tilted downward. Toward the caudolateral part along the left eye equator, the LPDs continuously change their orientation and finally become aligned almost horizontally.
Heterolateral elements H1, H2, and V1
H1 receives retinotopic input and conveys action potentials to its
output regions in the contralateral lobula plate (Hausen 1976b). The dendritic arborization of H1 covers almost the
whole lobula plate (see Fig. 4,
inset) (cf. Hausen 1976b
, 1993
). Its output
region covers wide parts of the contralateral lobula plate where it is
thought to form input to HSE, DCH, and VCH (see Fig. 4,
inset) (cf. Hausen 1976b
; Horstmann et
al. 2000
). H2 has a similar input organization but propagates
its spikes to the contralateral lateral protocerebrum where it is
thought to contact HSN and HSE as well as the CH neurons (see Fig. 4,
inset) (cf. Hausen 1981
). Its dendrites are
less extended than those of H1. V1 picks up information in the terminal
region of part of the VS neurons of the ipsilateral lobula plate and
propagates spikes to its own output arborizations in the contralateral
lobula (see Fig. 4, inset) (cf. Hausen 1984
,
1993
). To allow for an easier comparison with the input
organization of their putative target neurons, the response fields of
the heterolateral elements of the right part of the brain are plotted
as if they were obtained from their respective counterparts originating
in the left half of the brain.
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The H1 response field comprises almost the entire ipsilateral visual
hemisphere. Due to the region of binocular overlap, it includes a small
portion of the contralateral hemisphere (Fig. 4A). H1
responds preferentially to horizontal back-to-front motion (cf.
Hausen 1976b). Its sensitivity maximum is found in the
equatorial region at an azimuth of about
15°. The sensitivity
slightly decreases from frontal to caudal. In the most dorsal and
ventral parts of the visual field, H1 is insensitive to motion. In the
frontal part of the response field, the LPDs above the equator are
tilted downward, whereas the LPDs below the equator point slightly
upward. The LPD distribution of the H2 is very similar to that of H1
(cf. Fig. 4, A and B). Moreover, H2 is also
sensitive to horizontal back-to-front motion. The H2 response field,
however, is less extended because in the caudal direction, its motion
sensitivity decreases more rapidly than that of H1. The V1 response
field comprises wide parts of the visual field (Fig. 4C).
Its maximum sensitivity can be found in the azimuth range of 0-30°
around the eye's equator. The LPDs of V1 continuously change from
vertical downward in the frontolateral, to horizontal in the
dorsolateral, to obliquely vertical upward in the dorsocaudal visual
field. At an azimuth of about 120°, V1 is slightly sensitive to
vertical upward motion; this indicates that VS neurons converging on V1 have
at least partly
binocular receptive fields (Hengstenberg, personal observation).
Preferred self-motion parameters of HS and CH neurons
Given the binocular response field organization of HS and CH
neurons, what rotatory and translatory self-motions can be particularly well analyzed by these tangential neurons? To provide an answer to this
question, we first determined the optimal combination of self-rotation
and -translation, resulting in an optic flow field the local velocity
vector distribution of which most closely approximate the neuronal
response field. At any given location within the optic flow field each
velocity vector is defined by the vectors R and
T, describing the rotatory and translatory component of
self-motion, respectively. To determine R and
T, we interpreted the response fields as "noisy" optic flow fields and applied an iterative least-square algorithm developed by Koenderink and van Doorn (1987) (KvD).
Since the KvD is based on averaged sums of local velocity vectors, we
need to make two assumptions. First, the local motion signals of the elementary movement detectors (EMDs) converging on the tangential neurons are proportional to the velocity of the local retinal image
shifts, and second, the tangential neurons linearly integrate the local
motion signals. The EMD responses, however, represent the velocity of a
given motion stimulus only within a limited dynamic range. In addition,
EMD responses depend on the spatial frequency content and the contrast
of the stimulus pattern (review: Egelhaaf and Borst
1993
). Furthermore tangential neurons linearly integrate only a
small number of local motion signals, but for an increasing number of
activated local inputs, they show a kind of saturation characteristic
(Borst et al. 1995
; Hausen 1982b
; review:
Egelhaaf and Warzecha 1999
). Nevertheless, we used the KvD to obtain a first approximation of the neuron's preferred self-rotation and -translation. For the same reason, we assumed in our
calculation an isotropic distribution of distances between the eyes and
the visual structures of the surroundings. The latter assumption
allowed us to determine not only the direction of R and
T but also to assess their relative magnitude. The results
for the HS and CH neurons are listed in Table
1.
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The preferred rotation axes of HSN and HSE are oriented about vertically, resulting in the high specificity for sensing the flow components induced during yaw-rotations of the animal to the left. The preferred translations of the HS neurons slightly deviate from the straight-ahead direction. They point to the frontolateral left visual hemisphere slightly above the horizontal. Thus HS neurons appear to be specialized to sense yaw rotation, which may be superimposed by a translations in the horizontal plane, slightly to the left.
The preferred rotation axes of the CH neurons deviate by about 35° from the vertical body axis of the fly. In case of DCH, the axis is tilted toward the caudolateral aspect of the left visual hemisphere, whereas the preferred rotation axis of VCH is tilted toward the frontolateral part of the right visual hemisphere. Both CH neurons prefer a translation to the dorso-equatorial region of the frontolateral left visual hemisphere. From their preferred self-motion parameters, CH neurons are particularly sensitive to upward banked turns of the fly to the left. For both the HS and the CH neurons, the relative magnitude of R was on average about 2-2.5 times higher than the magnitude of T (cf. Table 1). This indicates that the respective distributions of LPDs within the response fields of these neurons more closely approximate optic flow fields induced during particular self-rotations of the fly than during translations.
Significance of binocular input for optic flow processing
To what degree does binocular input increase the neurons'
specificity to particular self-movements? To answer this question, we
estimate the neurons' responses to an optic flow field induced by
their preferred combination of self-rotation and -translation (FF(R+T)) as well as for optic flow fields
induced by self-rotation (FF(R)) and
self-translation (FF(R+T)) alone. The
estimations were carried out under two conditions: First, the neurons
integrate monocular local motion information only, which is basically
motion information sampled by retinotopically arranged movement
detectors within the right visual hemisphere including the first
meridian of the left visual hemisphere (15°
165°).
Second, the neurons integrate binocular local motion information; the
left and right visual hemispheres are considered (
150°
165°). In both cases, the preferred self-motions for each neuron,
i.e., R, T, and their respective relative
magnitudes, were taken from Table 1.
To estimate the neurons' responses to the optic flow fields
FF(R+T), FF(R),
and FF(T), we calculated, as a first
approximation, the geometrical projection of the respective optic flow
fields into the response fields RF according to
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The response increments r(T) on
binocular input has inconsistent effects on the estimated responses to
the preferred translation; it is either zero (HSN, HSE), increases
(VCH), or slightly decreases (DCH). The response increments are
positive for both the combination of preferred rotation and translation
(
r(R+T)) and for the preferred
rotation (
r(R); see Table 2). For
all neurons, however, the response increment
r(R) is higher than
r(R+T) (see Table 2). Thus HS and
CH neurons seem to be adapted to indicate the rotatory self-motion
component from the flies momentary self-movement.
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DISCUSSION |
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The binocular input organization of fly HS and CH neurons was determined from measurements of the local preferred directions and motion sensitivities within their receptive fields and of their potential contralateral input elements (H1, H2, and V1). Based on the local response properties, we estimated the significance of binocular inputs for the specificity of the neurons for their preferred self-movements.
Experimental evidence for the identity of heterolateral elements transmitting motion information to the HS and CH neurons
The origin of the contralateral input to the HS and CH neurons was
established by combined extra- and intracellular double recordings
(Haag 1994; Hausen 1976a
;
Horstmann 2000
). HSN was shown to receive contralateral
input from H2 in its terminal region (Haag 1994
). Since
only one class of excitatory postsynaptic potentials (EPSPs) has been
noticed in the HSN, an additional excitatory input mediated by another
heterolateral element is unlikely. Although the time-averaged responses
of HSN to local stimulation in the contralateral visual field are weak,
the LPDs determined in the frontolateral part of the contralateral
response field are compatible with the LPDs found in the corresponding
region of the H2 response field (cf. Figs. 2A and
4B). The tentative binocular input organization of HSN is
schematized in Fig. 5A.
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In accordance with earlier evidences obtained by Hausen
(1981), recent experiments have shown HSE to be postsysnaptic
to both H1 and H2 (Horstmann et al. 2000
). In all double
recordings, two classes of EPSPs could be assigned either to H1 or H2
spikes, and it seems unlikely that HSE receives additional
contralateral input from a third element (Horstmann et al.
2000
). Because we could record sizable responses to local
contralateral stimulation, we can compare the contralateral response
field of HSE with the H1 and H2 response fields (cf. Figs.
2B and 4, A and B). Although there is
a small tendency of the LPDs within the contralateral HSE response
field to point downward, the general trend is directed roughly
horizontally from back to front. Despite the minor discrepancies in the
frontolateral region below the eye equator, H1 and H2 seem to mainly
contribute to the organization of the HSE response field (cf. Figs.
2B and 4, A and B). The wiring that
most likely accounts for the observed binocular input organization of
HSE is illustrated in Fig. 5B.
DCH was shown to receive contralateral input from H1 and H2 and, in
addition, from an inhibitory wide-field neuron (element U) that has not
yet been anatomically identified (Hausen 1976a). A
comparison of the respective response fields supports this conclusion (cf. Figs. 3A and 4, A and B). The
influence of element U that is sensitive to horizontal front-to-back
motion in the contralateral visual field cannot be judged from the
response field. However, because DCH generates inhibitory postsynaptic
potentials (IPSPs) when stimulated along the preferred direction of
element U, the local motion sensitivity of DCH to contralateral
back-to-front motion may be slightly enhanced. A schematic of the DCH
input organization is shown in Fig. 5C.
VCH was thought to receive its contralateral motion sensitivity from H1 as well as from H2, although unambiguous double recording experiments are still lacking that might prove this notion. A comparison of the contralateral VCH response field with the H1 and H2 response fields supports this hypothesis only partly. In the frontolateral region of the contralateral visual field, the predominant LPDs point downward instead of being horizontally aligned. The contralateral distribution is more reminiscent of a blend of inputs including H1 and H2 signals but also of an element sensitive to downward motion in the frontolateral visual field. One candidate neuron that may supply the sensitivity to vertical downward motion is V1 (cf. Fig. 4C). In Fig. 5D, the hypothetical binocular input organization of this neuron is illustrated.
Functional significance of extended receptive fields and the binocular input organization of HS and CH neurons for estimating self-motion from optic flow
From a theoretical point of view, improving the performance in
estimating self-motion parameterslike the rotation vector R and the direction of translation T
from the
current optic flow can be achieved by two strategies: the first one
concerns the receptive field size and the number of sampling points. By applying a modified least-square algorithm (Koenderink and van Doorn 1987
), numerical simulations showed that self-motion
parameters can be reliably estimated from noisy optic flow fields if
local motion vectors were analyzed at about 100 sampling points
homogeneously distributed within about one visual hemisphere
(Dahmen et al. 2000
). Indeed, visual interneurons
sensitive to optic flow have frequently very large receptive fields
(see INTRODUCTION). The second strategy to gain reliable
information about the self-motion is to extend the visual field in a
way as to include both visual hemispheres. For instance, if a rotation
around the vertical axis is to be detected, it is an eminent advantage
to analyze motion at positions that are 180° apart on a connecting
meridian (Dahmen et al. 1997
, 2000
). In case of
rotation, the two velocity vectors point in opposite directions,
whereas during translation, they point in the same direction. Thus a
neuron integrating the signals of EMDs whose preferred directions point
front-to back in the lateral right visual hemisphere and back-to-front
in the lateral left visual hemisphere can be expected to respond
stronger to rotation than to translation. The local rotation responses
are added up by the neuron, whereas if the sensitivity is about equal within the two visual hemispheres, the local translation responses cancel out each other.
The receptive field organization of DCH, VCH, HSN, and HSE are well
suited for the task of self-motion estimation. These neurons receive
signals from thousands of local motion detectors together sensing
visual motion within almost the entire visual field. Such a dense
sampling may partly compensate for uncertainties inherent to local
motion analysis due to, for instance, neuronal noise and the pattern
dependence of elementary motion detection. Furthermore densely sampling
local motion information has been discussed as an adaptation to cope
with sparse distributions of contrasts in some natural scenes
(Dahmen et al. 2000). Most important, however, is the
fact that HSN and HSE and the CH neurons process binocular motion
information at opposite positions within the visual field.
The sensitivity of HS and CH neurons, in particular to their preferred
self-rotation, is increased by taking into account motion within the
visual field of both eyes. This is reflected by the result that the
response increment r(R) is in all
cases higher than the response increments
r(R+T) and
r(T), respectively. Recent
experiments on HSE suggest that the signal structure of this neuron may
play a decisive role in encoding self-motion. Response transients, such
as spikes and large-amplitude EPSPs, seem to be more specific
indicators of self-rotations than the mean membrane potential
(Horstmann et al. 2000
). Since we time-averaged the
responses of the HS neurons, we did not explicitly consider the
transient membrane potential fluctuations. Therefore our calculations most likely underestimate the binocular response of HSE to its preferred rotation and the resulting response increment
r(R).
It should be emphasized, however, that the way we estimated the
tangential neurons' responses to optic flow fields induced by
particular self-motions need to be considered only a first approximation. Beside the simplifications we outlined in
RESULTS, we mentioned in the INTRODUCTION that
the magnitude of translatory optic flow depends not only on the
animal's speed but also on its distance to environmental objects. In
our calculations, we assumed the same distances in all directions of
the visual field, what is certainly a surrounding the fly will never
encounter in nature. In this context, it is important to note
that the results obtained under the described assumptions are
relatively stable against changes of the distance distribution. For
instance, introducing closer distances of the fly to its surroundings
in the ventral visual field than in the dorsal visual field (cf.
Franz and Krapp 2000), leads to greater differences
between the binocular response increments to the preferred rotation and
translation,
r(R) and
r(T), respectively. In
electrophysiological experiments, we are currently investigating to
what extent predictions on the specificity of HS and CH neurons to
particular self-rotations that were based on local motion measurements
hold true for the neurons' responses on visual wide field stimulation.
With respect to the magnitude of the nonretinotopic input imparting the
neurons with binocular vision, we found that the response increment
r(R) to the rotatory optic flow in
HS neurons was, on average, only about half as high than in CH neurons
(cf. Table 2). With our stimulus procedure, we measured only very small response amplitudes under contralateral stimulation (cf. Fig. 2). This
is in accordance with a study by Hausen (1982b)
where he
reported only a subtle increase of the averaged membrane potential in
HSN and HSE on binocular compared with monocular stimulation. He
simulated rotational optic flow by back-to-front motion in the
frontolateral area of the contralateral and front-to-back motion in the
corresponding part of the ipsilateral visual hemisphere. In similar
experiments on CH neurons, however, the response to binocular motion
was shown to be almost twice as large compared with the response to
ipsilateral stimulation alone (Egelhaaf et al. 1993
).
These findings are in good accordance with our result estimating higher
response increments for the preferred rotation
r(R) in CH neurons than in HS neurons.
In summary, the detailed investigation of the local response properties
supports the idea that HSN and HSE may be well suited to encode
information about self-rotations around the vertical body axis (about
yaw-rotation), which may be superimposed by a translation in the
horizontal plane to the left. Since the HS neurons are output elements
of the visual system, signals originating from both halves of the
visual system could further interact in different ways at subsequent
processing stages to lead to more specific representations of different
types of self-motion. This information could then be utilized for
solving a variety of tasks in flight steering, walking, and gaze
stabilization. Such an elaboration of the specificity for optic flow is
not possible for the CH cells that are intrinsic elements of the third
visual neuropile and seem to indicate banked turns of the animal.
Because of their extended binocular response field organization, CH
cells are ideally suited wide-field inhibitors, for instance, in the
context of figure-ground discrimination (Egelhaaf 1985).
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ACKNOWLEDGMENTS |
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The authors are grateful to K. Hausen for kindly supplying the reconstructions of the tangential neurons and for critically reading and commenting on the manuscript. We also thank R. Kern, R. Kurtz, and A.-K. Warzecha for critically reading and discussing the manuscript. In addition, we thank two anonymous referees for constructive criticism and language corrections that helped to improve the manuscript.
This work was supported by the Max-Planck Gesellschaft and the Deutsche Forschungsgemeinschaft.
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FOOTNOTES |
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Present address and address for reprint requests: H. G. Krapp, Dept. Zoology, Cambridge University, Downing Street, Cambridge CB2 3EJ, UK (E-mail: hgk23{at}hermes.cam.ac.uk).
Received 22 February 2000; accepted in final form 24 October 2000.
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REFERENCES |
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