Evidence for mutual allocation of social attentionthrough interactive signaling in a mormyridweakly electric fishMartin Worma,1, Tim Landgrafb, Julia Prumea, Hai Nguyenb, Frank Kirschbaumc, and Gerhard von der Emdea

aInstitut für Zoologie, Neuroethologie/Sensorische Ökologie, Universität Bonn, 53115 Bonn, Germany; bInstitut für Informatik, Fachbereich Informatikund Mathematik, Freie Universität Berlin, 14195 Berlin, Germany; and cBiologie und Ökologie der Fische, Lebenswissenschaftliche Fakultät,Humboldt-Universität-zu Berlin, 10115 Berlin, Germany

Edited by John G. Hildebrand, University of Arizona, Tucson, AZ, and approved May 16, 2018 (received for review January 26, 2018)

Mormyrid weakly electric fish produce electric organ discharges(EODs) for active electrolocation and electrocommunication. Thesepulses are emitted with variable interdischarge intervals (IDIs)resulting in temporal discharge patterns and interactive signalingepisodes with nearby conspecifics. However, unequivocal assign-ment of interactive signaling to a specific behavioral context hasproven to be challenging. Using an ethorobotical approach, weconfronted single individuals of weakly electric Mormyrus rumeproboscirostris with a mobile fish robot capable of interactingboth physically, on arbitrary trajectories, as well as electrically,by generating echo responses through playback of species-specific EODs, thus synchronizing signals with the fish. Interactivesignaling by the fish was more pronounced in response to a dy-namic echo playback generated by the robot than in response toplayback of static random IDI sequences. Such synchronizationswere particularly strong at a distance corresponding to the outerlimit of active electrolocation, and when fish oriented toward thefish replica. We therefore argue that interactive signaling throughechoing of a conspecific’s EODs provides a simple mechanism bywhich weakly electric fish can specifically address nearby individ-uals during electrocommunication. Echoing may thus enable mor-myrids to mutually allocate social attention and constitute afoundation for complex social behavior and relatively advancedcognitive abilities in a basal vertebrate lineage.

electrocommunication | ethorobotics | interactive signaling | social attention

Mormyrid weakly electric fish produce series of electric organdischarges (EODs) for active electrolocation of their envi-

ronment (1) and electrocommunication with nearby conspecifics(2). Interdischarge intervals (IDIs) between EODs are variable andcan be modified to spontaneously improve the temporal resolutionduring active sensing (3) and to encode signaling patterns intodischarge sequences that are associated with characteristic behav-ior patterns serving in intraspecific communication (4).Apart from spontaneous changes in discharge frequency and

temporal patterning, mormyrids can also produce interactive IDIsequences. By responding to a conspecific’s EOD with a preferredlatency of only a few milliseconds, they generate so-called echoresponses, which, if mutually engaged in by two individuals over acoherent time period, lead to episodes of time-locked signalingsequences that constitute electrical discharge synchronization be-tween individuals (5–7). Although echoing is a behavior consis-tently observed across mormyrid species, the underlying neuralpathways are unresolved, and its behavioral significance remainsspeculative. Echo responses have been interpreted as jammingavoidance behavior during active electrolocation (8, 9) and as acommunication strategy (5, 10, 11), possibly by enhancing groupintegration and affirmative interactions.Systematic investigation of the implications of echoing for

communication is impeded by the difficulty to assign EODs tothe respective sender in experiments involving more than a singlefreely moving fish (but see refs. 12 and 13), as well as by the lackof control over the behavior of the fish that invokes echo

responses from a conspecific. We solved both problems by usinga freely moving robotic fish capable of emitting either predefinedor dynamic sequences of playback EODs in an interactive be-havioral experiment with single individuals of the weakly electricfish Mormyrus rume proboscirostris.Robotic fish have been successfully employed to investigate the

features determining attraction between individual fish (14–16), aswell as collective decision making and internal dynamics in groupsof fish in shoals (17–22). Similar experiments have demonstratedthat mormyrids are attracted to a mobile fish replica playing backelectric signals (23, 24). Electrical playback signals are a convenientway to experimentally control signaling properties for waveform,IDI sequence, and latency relationships. This allows assigningsignaling attributes to behavioral contexts and to uncover theirsignificance for communication (9, 25, 26).Here, we investigate the effect of interactive electric signaling

on attraction and social interactions with a mobile robot that canrespond to EODs of live fish and propose a social function ofechoing based on two observations: Firstly, fish responded with anincrease of interactive signaling to artificial echo responses, in-dicating that interactivity has some intrinsic communicative valueas a signal. Secondly, discharge synchronizations were associatedwith following-behavior and approach configurations, suggestingthat echoing represents a way to address another individual elec-trically. Our results suggest that discharge synchronizations be-tween mormyrid weakly electric fish constitute a strategy for

Significance

Interactive electric signaling between mormyrid weakly electricfish by means of echoing a conspecific’s signals has been dis-cussed both in the context of jamming avoidance during activeelectrolocation and as a strategy for electrocommunication. Byconfronting individuals of the weakly electric fish Mormyrusrume proboscirostris with a mobile robot that responds dy-namically to the signaling activity of the fish, we show thatinteractive signaling, in turn, leads to increased synchroniza-tion of communication signals by the receiving animals. Syn-chronization of electric signaling occurred most frequently inapproach configurations, suggesting that echoing may beemployed specifically to address conspecific individuals andto initiate mutual allocation of social attention duringelectrocommunication.

Author contributions: M.W., T.L., J.P., and G.v.d.E. designed research; M.W. performedresearch; T.L., H.N., and F.K. contributed new reagents/analytic tools; M.W. analyzed data;and M.W., T.L., and G.v.d.E. wrote the paper.

The authors declare no conflict of interest.

This article is a PNAS Direct Submission.

Published under the PNAS license.1To whom correspondence should be addressed. Email: mworm@uni-bonn.de.

This article contains supporting information online at www.pnas.org/lookup/suppl/doi:10.1073/pnas.1801283115/-/DCSupplemental.

Published online June 11, 2018.

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mutual allocation of social attention, thus providing a relativelysimple electromotor basis for the development of complex be-havioral interactions and social coordination not frequently ob-served at the taxonomic level of fish.

ResultsAll animals were highly attracted by the robotic fish and showedinteractions both by following its trajectories, as well as by syn-chronizing their EODs to the playback sequences through echoresponses to the playback EODs. Attraction was strong when therobot emitted EODs either as a static random playback (SRP) oras a dynamic echo playback (DEP), but not in response to anelectrically silent control condition (ESC). The attractiveness ofthe moving robot was quantified by the fish’s distance to therobot (Fig. 1A), the accuracy with which it followed the robot’sswimming trajectory (Fig. 1B), and its propensity to give up wall-following behavior (SI Appendix, Figs. S1 and S2). Electricalplayback led to a significant decrease in distance between robotand fish compared with ESC [repeated-measures ANOVA:F(2,44) = 144.44; P < 0.001], indicating that electric signaling wasthe main feature of attraction. The relative amount of the robot’sturns that were followed by the fish confirmed this pattern[Friedman test: χ2(2) = 34.80; P < 0.001]. While electrical play-back was crucial to attract individual fish to the moving robot,playback type did not influence spatial interactions. However,with regard to electric signaling, different playback types had asignificant effect on the fish.Echo responses represent an interactive signaling strategy and

occur when a fish responds with an EOD at a preferred latency tothe EOD of another fish more often than would be expected bychance. All fish produced echo responses with preferred latenciesranging from 15 to 19 ms both to SRP and DEP. Exemplary re-sults of an individual fish are shown in Fig. 2A. The relativeamount of echo responses produced by each fish in response toSRP and DEP was quantified by calculating an echoing quotient,which allows assessing how many times more often than expecteda preferred latency occurs during echoing (6). DEP evoked moreechoing responses than SRP [paired-samples t test: t(22) = −5.38;P < 0.001], suggesting that echo responses induce echoing by fishwho receive echoes to their EODs (Fig. 2B).Electric signaling responses were additionally analyzed as time

series to characterize temporal aspects of their interactions withthe different playbacks. Fig. 3 depicts sections from trials withSRP (A) and DEP (B). The Upper panels show plots of overlaidIDI sequences of the respective playback and the respondingfish. Adaptive cross-correlations calculated between each of thetwo sequences are shown in the Lower panels.

The cross-correlation analysis in Fig. 3A reveals consistentdischarge synchronization to SRP, with response times corre-sponding to the preferred latency of the echoing fish. Maximumcorrelations frequently exceed the 0.3 correlation threshold, in-dicative of relatively strong synchronization (see SI Appendix,Figs. S3 and S4 for illustrations). IDI sequences during interac-tions with DEP were more regular, and the cross-correlationanalysis shows synchronization at response times correspondingto the echo latency. DEP was designed to respond to EODs oflive fish with an echo latency of 21 ms. Hence, high correlationcoefficients at these (negative) response times are visible in thecross-correlation diagram (Fig. 3B).To quantify discharge synchronizations between fish and robot,

the maximum correlation coefficient was averaged over time forboth positive and negative response times separately (Fig. 4A). Wecalled this metric average synchronization coefficient (ASC). Forcomparison, we computed two ASC baselines for randomly oc-curring correlations, representing no synchronization, by calcu-lating the same metric for cross-correlations of EOD sequences ofthe fish during the ESC condition with SRP, and DEP, re-spectively. The ASC of live fish differed statistically highly signif-icantly between the conditions [repeated-measures ANOVA withGreenhouse–Geisser correction: F(2.152, 47.349) = 192.00; P < 0.001;e = 0.31]. Interactive playback triggered more interactive signalingresponses by the fish. Synchronization of M. rume with SRPresulted in ASC values of 0.31 ± 0.011 (mean ± SEM). The ASCof SRP with live fish was significantly lower (0.16 ± 0.002), butstatistically indifferent to both baselines (baseline 1: 0.16 ± 0.002,baseline 2: 0.16 ± 0.002). Responses of M. rume to DEP resultedin significantly higher discharge synchronizations (ASC: 0.37 ±0.012; mean ± SEM) than during SRP, confirming our results forthe echo quotient. The respective synchronization response ofDEP to the signals of M. rume was with 0.29 ± 0.009 (mean ±SEM) statistically indifferent to the fish’s response to SRP, thusconfirming the comparability of DEP with the interactive signalingbehavior of live fish. The independent control responses of fish toDEP were statistically indifferent to those obtained for SRPcontrols (ASCs: 0.17 ± 0.002). Statistical differences in synchro-nization responses to the playbacks were therefore not caused bygeneral differences between the two playback types.We further analyzed temporal aspects of synchronization by

quantifying the duration of sequences with correlation coeffi-cients ≥0.3. Median sequence lengths of episodes with highcorrelation at a relative cumulative sum of 0.75 were longer inresponse to DEP compared with SRP (Wilcoxon signed-ranktest: Z = 2.42; P = 0.016; Fig. 4B).

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Fig. 1. Influence of the robotic fish on following behavior during differenttypes of electrical playback. (A) Mean distance (±SEM) between the snout ofthe fish and the closest point of the robot. (B) Relative amount of robotturns that were followed by the fish. Categories not sharing a common su-perscript letter differ significantly based on Bonferroni adjusted P values, n =23. DEP, dynamic echo playback; ESC, electrically silent control; SRP, staticrandom playback; rel., relative.

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Fig. 2. Echo responses to static and interactive electrical playback. (A) Ex-emplary depiction of the relative occurrence of EOD-response latencies offish 9 during SRP. The horizontal line represents the expected distribution ofresponse latencies. The observed latencies at the mode of the distributionexceed the expected distribution. Bin size: 1 ms. (B) Echoing quotient, i.e.,the ratio of observed to expected latencies at the mode of the latency dis-tribution (mean ± SEM). This proportion was higher in response to DEP foralmost all of the n = 23 fish compared with SRP. ***P < 0.001.

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Simultaneous recording of electric signaling and motor re-sponses of the fish allowed associating both behaviors at anygiven time of the experiments. Tracking data were used to ana-lyze linear distances as well as directional relationships betweenrobot and fish with regard to discharge synchronization of M.rume with SRP and to establish the constellations they mostfrequently occurred in. Averaging maximal correlation valuesacross the distances observed during all trials with SRP revealedthat fish synchronized most strongly at distances of around100 mm (Fig. 5A). This corresponds to the range of activeelectrolocation, i.e., the maximum distance up to which fish candetect objects by using their active electric sense (1).The intensity of electrical discharge synchronization was also

affected by directional interrelations between the moving robotand the fish. When made independent of the total frequency byaveraging correlation coefficients into bins of 1° (Fig. 5B), themagnitude of synchronization engaged in by M. rume correlatedwith the replica’s position relative to the perspective of the fish(ρp = 0.64; P < 0.001; Fig. 5B). Additionally, correlations werehighest when the fish was positioned behind the replica, at about180° relative to its coordinates (ρp = 0.43; P < 0.001; SI Appendix,Fig. S5A) and when the difference in orientation between replicaand fish was smallest (ρp = 0.68; P < 0.001; SI Appendix, Fig.S5B). This shows that animals synchronized their discharge ac-tivity most intensely when they swam toward the replica andapproached it from behind with similar orientation. These ob-servations are consistent with a situation where two fish followeach other swimming in the same direction and engage in syn-chronization of their electric discharges.

DiscussionDetermining the key stimuli triggering the release of social be-haviors lies at the heart of behavioral biology (27) and is a crucialprerequisite for using robots to investigate animal behavior (28).Ethorobotical experiments with various fish species have shownthat mainly visual and hydrodynamic cues mediate interactionsbetween live fish and robotic replicas (14–16, 20, 29). In mor-myrids, the importance of electric signaling for mediating socialbehaviors is well established (30–32), and playback studies suggestthat electric signals are key stimuli, which allow using mobile fishdummies as proxies for conspecifics when investigating electro-communication (23, 24). We investigated locomotor and electro-motor responses of individual M. rume to a mobile robot, whichemitted playback EODs either as a static random IDI sequence(SRP) or in a dynamically interacting echo paradigm (DEP).Electric playback reliably induced social interactions and followingbehavior in all fish. However, in contrast to the fish’s electromotorresponses, attraction was not influenced by playback type. At thelevel of electric signaling interactions, however, the fish’s responsedepended on whether the playback sequence was static or dy-namic, i.e., whether the robot responded to the electromotor be-havior of the fish. Both playback types elicited echo responses, butthe relative amount of echoing was higher in response to DEP,which resulted in a higher degree of discharge synchronizationsustained over longer periods of time. Differences in interactivesignaling by the fish did not depend on general differences be-tween the playback types, which was demonstrated using in-dependently recorded sequences as a control. The higher amountof interactive signaling by M. rume seems therefore to result fromthe interactivity of DEP, meaning that an animal that receives

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Fig. 3. Synchronization of electrical discharge activity. Discharge synchronization of M. rume with SRP (A) and DEP (B). (A1 and B1) IDI sequences of playback(black) and fish (blue) over time (see SI Appendix, Figs. S3 and S4 for complete sequences). (A2 and B2) Cross-correlation diagrams calculated for each pair ofIDI sequences displayed in A1 and B1. Correlation coefficients of the fish’s signals with the playback signals are color coded for response times of ±100 ms. Highcorrelation coefficients at positive response times represent synchronization of the animal’s signaling behavior to the playback, whereas high correlation atnegative response times represents synchronization of the playback with the signaling behavior of the fish. This can occur only randomly with SRP. Highcorrelation coefficients at negative response times in B2 reflect the consistent synchronization of DEP with the signaling behavior of the fish.

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echoes reacts by responding with more echoes of its own. This inturn leads to more intense discharge synchronization betweenindividuals, supporting the notion that echoing serves an impor-tant function during electrocommunication in mormyrids.Echoing has been proposed to serve a jamming avoidance

function during active electrolocation (8, 9), a notion contestedby the observation that object discrimination in Gnathonemuspetersii was not impaired during jamming (33). However, jam-ming avoidance also occurs in other active sensory systems suchas active electrolocation in gymnotiform weakly electric fish (34,35) and echolocation in bats (36). The necessity for a jammingavoidance strategy is apparent in gymnotiforms because they lacka reafferent neuronal pathway, which enables mormyrids todistinguish between self- and nonself-generated EODs (37).Nevertheless, jamming avoidance has been linked also in gym-notiforms to social communication (34, 38), and the two func-tions need not be mutually exclusive in mormyrids either.Effective communication may even require jamming avoidancemechanisms because they can provide senders with a strategy toemphasize their signals. Such strategic signaling adjustmentshave for instance been described in calling insects (39), frogs(40), and songbirds (41).Gymnotiform Gymnotus carapo exhibit a strongly reduced

sensitivity for electric signals directly after they generate an EOD(42). In an interactive electrical playback protocol, G. carapopreferentially discharged within the time window during whichthe receptors of the conspecific represented by the playbackwould have been more sensitive to the signals of the fish, whichmay enable these animals to adjust their EODs with respect tothose of a conspecific, depending on an intent to communicate(43). Similarly, the corollary discharge, generated in the mor-myrid brain each time an EOD is initiated, results in inhibitorypostsynaptic potentials of up to 10 ms that are measurable in thenucleus of the electrosensory lateral line lobe (nELL) (37). ThenELL receives afferent input from knollenorgans, which areelectroreceptor organs specialized for communication (44). Theecho response might thereby assure that a sender places its EODat the end of this refractory period, but before the next EOD ofthe receiver is initiated. The EOD will thus be detected by thereceiver and may signal social intentions of the sender. If the

receiver responds by echoing the sender’s signals, this mayeventually lead to mutual allocation of social attention throughdischarge synchronization in a variety of behavioral contexts.The sensory perception of mormyrids also benefits from

echoing because it ensures compatibility of active and passivesensing during social interactions. Mormyrids were shown to usethe information provided by knollenorgans to approach a dipolesource representing a conspecific from outside the range of ac-tive electrolocation (45). Thus, a conspecific’s EODs also pro-vide spatial information during social interactions (46). Sinceafferent information from knollenorgans is inhibited in the nELLduring EOD production (37), echoing ensures that active elec-trolocation does not impair passive sensing performance in socialcontexts. Echoing will consequently be perceived by the indi-vidual that is approached and could have ritualized into a sig-naling display during which the approached individual echoes aswell and thereby acknowledges its detection. In the currentstudy, synchronization was strongest at the outer range of activeelectrolocation at around 10 cm (1), a distance where passivesensing may be the most reliable source of information aboutconspecifics during nocturnal activity.The echo response has been described in several mormyrid

species and in behavioral contexts as diverse as agonistic en-counters, foraging, and resting (5, 6, 11, 13, 47). This suggests thatit may serve a more general signaling purpose, which is not nec-essarily linked to an activity-dependent behavioral context. Fieldreports from predatoryMormyrops anguilloides have demonstratedthat these mormyrids gather in relatively stable groups and hunt inpacks for small cichlids. Based on these observations, Arnegardand Carlson (10) hypothesized that mutual synchronization ofdischarge bursts through echoing allows “mutual acknowledge-ment of recognition” between individuals of the group.Collective, coordinated, and collaborative hunting strategies

of varying complexity have been documented for several fishspecies, and it becomes increasingly evident that such abilitiesare not unique features of mammalian predators (48). The in-volvement of echoing in the nocturnal hunting behavior of M.anguilloides has interesting implications, because it may enable

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Fig. 5. Electrical discharge synchronization and spatial interactions. (A) Cross-correlation coefficients of the IDI sequences of M. rume with SRP for n = 23animals plotted against the distance between robot and fish observed at therespective time (gray dots). Average values per distance (black dots) show thatsynchronization was strongest at ∼100 mm. Bin size: 1 mm. (B) Polar plot of theaverage cross-correlation coefficients per 1° of the angle representing therobot’s bearings in the fish’s egocentric coordinate system. The distance fromthe center of the plot represents the correlation coefficient.

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Fig. 4. Synchronization of electrical discharge sequences. (A) Bars representthe mean (±SEM) of the averaged maximum cross-correlation values (ASC)for experiments with n = 23 fish during the presentation of SRP (black) andDEP (red). Comparisons were made for synchronizations of the electricaldischarges of M. rume with the playback and synchronization of the play-back with the signals of the fish. Categories without a common superscriptletter differ significantly based on Bonferroni-adjusted P values. (B) Durationof episodes with relatively strong synchronization. Box plots comparing se-quences where n = 23 fish synchronized their discharges to the IDI sequencesof SRP (black) and DEP (red) with cross-correlation coefficients ≥0.3. DEP led toa significantly longer duration of synchronization events than SRP. *P < 0.05.

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mormyrids to perform social behaviors otherwise restricted toanimals with more advanced cognitive abilities. One such abilityis the capacity for vocal imitation, which is rare among non-human animals (49). It is, however, used by parrots and dolphins,which were shown to use learned vocal labels to address specificindividuals by imitating their calls (50, 51). The mormyrid echoresponse allows spontaneous matching of signaling sequenceswith high temporal precision and may thus enable mormyrids toaddress other individuals of a group without the need for a ca-pacity of imitation or learning. Jamming avoidance in the knol-lenorgan pathway could in these situations facilitate undisturbedmutual identification of individuals based on differences in EODwaveform (25), or the exchange of dominance-related waveforminformation between unfamiliar individuals to determine hier-archy ranks without fighting (52, 53). The echo response, as asimple mechanism providing the capability to synchronize elec-tric signals with conspecifics, combined with the ability of mor-myrids to recognize individuals based on the waveform of theirEOD, may have served as a foundation for the evolution ofcomplex social interactions and cognitive capacities not fre-quently observed at the taxonomic level of fish (54).

Materials and MethodsAnimals. A total of 23M. rume proboscirostris were kept in 50- to 200-L tanksat temperatures of ∼25 °C, water conductivity of ∼100 μS·cm−1 and a light/dark cycle of 12/12 h. Animals were bred in captivity and measured 6.4–11.4 cm in standard length. In each tank, two or more fish were confined tosingle compartments providing a shelter. Compartments were separated bywater permeable barriers that prevented physical contact but allowedelectrocommunication. Food was provided in the form of defrosted chi-ronomid larvae. All experiments were carried out in accordance with theguidelines of German law, with the animal welfare regulations of the Uni-versity of Bonn, and with the Guidelines for the treatment of animals inbehavioural research and teaching (55).

Setup. Experiments were performed in a 120 × 100 × 20 cm3 tank, which wasmounted on a support frame leaving the base area accessible from below (SIAppendix, Fig. S6). The water in the tank was of 26 ± 1 °C and had a con-ductivity of 100 ± 5 μS·cm−1 during experiments. The water level was kept at15 cm. The frame supported a second plane below the tank, on which awheeled robot (56) (SI Appendix, Fig. S7A) could be manually controlled by apersonal computer to move on arbitrary trajectories via a wireless connec-tion. A fish replica (SI Appendix, Fig. S7B) was made from an 8-cm fishinglure mounted on a base plate with a magnet underneath. With this magnet,the replica inside the tank was coupled to the mobile robot underneath thetank and could thus reproduce its trajectories.

The replica was fitted with a pair of carbon electrodes inserted at the frontand the rear end, andwith a pair of silver electrodes along the longitudinal axis.A multielectrode array consisting of five pairs of carbon electrodes recorded allelectrical activity in the tank. Signals were recorded differentially (BrownleePrecisionModel 440), digitized (CED Power 1401; Cambridge Electronic Design),and recorded to disc using Spike2 software (version 5.21; Cambridge ElectronicDesign). All behavior in the tank was simultaneously video recorded at 15 fpsusing an infrared sensitive camera (DMK 23FM021 FireWire camera with VariFocal T4Z2813CS-IR CCTV lens; The Imaging Source) and Spike2 video recorder.Illumination was provided indirectly using a LED floodlight resulting in 1.5 lx ofvisible light intensity (Light ProbeMeter, 403 125; Extech Instruments). Cameravision was enhanced by additional illumination with infrared spotlights(850 nm, IR Illuminator Model SA1-60-C-IR; Itakka).

The silver electrodes of the robot were used to record signals of the fishwhen it came into close range. These signals were amplified differentiallyusing a custom-built trigger box (University of Regensburg, Regensburg,Germany) which generated a transistor–transistor logic (TTL) pulse for eachsignal exceeding a threshold. The TTL output of the trigger box was used togenerate DEP in real-time via the Spike2 sequencer (see below). The robot’scarbon electrodes were used for playback generation and were connectedto a stimulus isolator (model 2200; A-M Systems, Inc.) as a power supply.Playback signals were output via the Spike2 sequencer, converted digital toanalog using the CED 1401 and attenuated (dB-attenuator; University ofRegensburg) to match the signal characteristics of a medium-sized fish (23).The key components of the setup are illustrated in SI Appendix, Fig. S6.

Playbacks. Two types of electrical playback sequences were generated using aprerecorded template EOD that was averaged from 50 EODs of an M. rumerecorded head to tail (high pass: 1 Hz) and digitized at a sampling rate of 50 kHz.SRP was generated using a custom-written Matlab script (version R2013b; TheMathWorks, Inc.), which concatenated template EODs to 15-s sequences. IDIswere randomly selected within two SDs around the mean (67 ms) of a distri-bution with a mode of 60 ms that was obtained from a similar experiment (24)and contained a total of 17,644 IDIs. SRP sequences were repeated three timesto obtain a 45-s stimulus protocol and a new sequence was designed for everytrial. DEP was generated by programming the Spike2 sequencer to produceplayback signals at intervals greater than 60 ms in the absence of a triggersignal, but respond with a latency of 21 ms to the detection of a fish’s EOD. Arefractory period prevented the program from echoing to its own signals. DEPgeneration is illustrated in SI Appendix, Fig. S8.

Procedures. Individual fish were taken from the holding tanks and placed intoa 22 × 14 cm2 opaque start box inside the experimental tank. The robot wasthen moved on random trajectories for 3 min to habituate the fish to anydisturbances associated with the robot’s movements. Fish were then re-leased from the start box and confronted with the robot in three consecu-tive trials featuring either SRP, DEP, or no playback as a control (ESC). Theorder of these conditions was pseudorandomized. The robot was moved bythe experimenter on arbitrary trajectories designed to approach the fish andentice it to follow into the open area of the tank. Each presentation startedwith a 10-s period without playback, followed by three 15-s episodes duringwhich the respective condition was repeated. This resulted in a total of 55 sof recorded data. In additional control experiments, the robot was removedafter the habituation period, and the behavior of the fish was recordedaccording to the time points defined for playback presentation. This controlwas performed with all fish in a separate session on a nonconsecutive day.Half of the animals were subjected to this control in the first session, whilethe other half were first confronted with the robot.

Video Analysis. Videos were rectified to compensate for radial distortion, andtracking was performed using Ctrax (Caltech Multiple Walking Fly Tracker,version 5.0, ref. 57) and the FixErrors graphical user interface provided forMatlab. The center distance between test fish and replica, their difference inorientation, as well as the relative position of the fish, which was defined bythe angular difference of the robot’s orientation and the connecting linebetween the centers of the robot and the fish, were calculated using theBehavioralMicroarray toolbox provided with Ctrax. Distances from the snoutof the fish to the closest wall of the tank, as well as the closest distance to therobot, were manually assessed every 3 s using ImageJ (version 1.46r, NIH). Theresulting 15 values were averaged to obtain 1 value per fish for statisticalanalysis. The number of turns performed by the robot was counted manuallyfrom video recordings, and the proportion of turns that were followed by thefish was calculated for each condition. Videos were renamed and randomizedto leave the experimenter blind to the test condition.

Signal Analysis. Waveform data were transformed into time series markingthe occurrence of all EODs, which were then assigned to either the playbackor the fish (24). Echo responses displayed by the fish were analyzed by usingthe EOD sequence of the playback as a reference and calculating the la-tencies with which the fish generated EODs in response to the stimulus untilthe occurrence of the following playback EOD. The latency distribution thatwould be expected if both IDI sequences were independent time series wasobtained by inverting the relative cumulative histogram of the stimulus IDIdistribution. To check for echo responses of the playback to the fish’s signals,the sequences used as stimulus and response signals were reversed. Echoresponses were quantified according to ref. 6 by calculating the ratio ofobserved latencies at the mode of the latency distribution to the amountexpected at that latency, if assuming no dependency between the IDI se-quences of playback and the tested fish.

Adaptive cross-correlations for a response window of ±100 ms were cal-culated between two IDI sequences each, using the playback signals as ref-erence values (see ref. 7 for details). The IDI sequences of playback and fishwere thereby transformed into high-resolution time series comprising onevalue per millisecond. The time course of temporal synchronization betweenthe IDI sequences of M. rume and the playback could thus be quantified viacorrelation coefficients. For each of the high-resolution time points, themaximum correlation value within the 100-ms response frame was extractedfrom the matrix of correlation coefficients (see SI Appendix, Figs. S3 and S4for an illustration). This was done separately for correlations of the fish’ssignals with the playback, as well as for correlations of the playback with theIDI sequence of the fish. The average of these maximum values over the 45-s

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period (ASC) was calculated for each trial and used for statistical analysis. Tocontrol for randomly occurring correlations, cross-correlation analysis wasperformed for both playbacks by using the IDI sequence the fish had emittedindependently of the playback during ESC in the same session.

Values of maximum correlation from the high-resolution time series wereaveraged to obtain single values matched to the corresponding video frames(24). For both SRP and DEP, sequences of successive frames during which theassigned value of correlation of the fish’s signaling response was ≥0.3 werequantified to calculate the duration of synchronization episodes. Relativecumulative histograms were used to determine the duration of synchroni-zation sequences at a proportion on 0.75 for statistical comparison of theeffects of SRP and DEP on the duration the fish synchronized their signals tothe respective playback. Simultaneous tracking and waveform data wereused to associate the linear and directional relationships between fish and

replica to the amount of discharge synchronizations at a given time definedby the frame rate of video recording. This analysis was only performedfor SRP.

Statistics. Statistical analyses were performed using IBM SPSS (version 22.0;IBM Corp.). Normality of data were assessed by Shapiro–Wilk’s test andparametric or nonparametric tests for repeated measurements were usedaccordingly. Circular–linear correlations between the magnitude of EODsynchronization and the angular relationships of fish and replica were cal-culated using the CircStat toolbox for Matlab (58).

ACKNOWLEDGMENTS. This study was supported by the German ResearchFoundation (DFG Graduiertenkolleg Bionik GR1572).

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