Kármán vortex street detection by the lateral line

The incomparable fascination of comparative physiology: 40 years with animals in the field and laboratory

This paper is not meant to be a review article. Instead, it gives an overview of the major research projects that the author, together with his students, colleagues and collaborators, has worked on. Although the main focus of the author's work has always been the fish lateral line, this paper is mainly about all the other research projects he did or that were done in his laboratory. These include studies on fishing spiders, weakly electric fish, seals, water rats, bottom dwelling sharks, freshwater rays, venomous snakes, birds of prey, fire loving beetles and backswimmers. The reasons for this diversity of research projects? Simple. The authors's lifelong enthusiasm for animals, and nature's ingenuity in inventing new biological solutions. Indeed, this most certainly was a principal reason why Karl von Frisch and Alfred Kühn founded the Zeitschrift für vergleichende Physiologie (now Journal of Comparative Physiology A) 100 years ago.

A multisensory perspective on near-field detection and localization of hydroacoustic sourcesa)

This paper gives a brief synopsis of the research career of S.C. in fish bioacoustics with an emphasis on dipole near fields. The hydroacoustic nature of the dipole near field and the effective stimuli to lateral line and auditory systems combine to produce a multisensory, range-fractionated region that is critically important to many fish behaviors. The mottled sculpin and goldfish lateral lines encode the spatial complexities of the near field as spatial excitation patterns along the body surface to provide instantaneous snapshots of various source features such as distance, orientation, and direction of movement. In contrast, the pressure-sensitive channel of the goldfish auditory system [the anterior swim bladder (SB)-saccule complex] encodes the spatial complexities in a temporal fashion whenever the position or orientation of the source changes with respect to the anterior SB. A full appreciation for how these somatotopic and egocentric representations guide fish behavior requires an understanding of how multisensory information, including vision, is combined in sensorimotor regions of the brain to effect behavior. A brief overview of vertebrate brain organization indicates that behaviors directed to or away from hydroacoustic sources likely involve a variety of mechanisms, behavioral strategies, and brain regions.

Fish swimming efficiency

Every spring a 600 lb Atlantic bluefin tuna travels over 3000 miles from Newfoundland to its spawning grounds in the Gulf of Mexico. That it does so on a meal of a couple of bluefish is nothing short of remarkable. Humans will likely never engineer such an efficient swimming machine. Of course, that has not stopped us from trying. We have achieved remarkable progress by following a strategy of inspiration by nature. At the same time, our fish-like robots often fall short of matching fish performance by a considerable margin. Despite our advances, we are still left asking the question: How do fish swim so well?

Corollary discharge enables proprioception from lateral line sensory feedback

Animals modulate sensory processing in concert with motor actions. Parallel copies of motor signals, called corollary discharge (CD), prepare the nervous system to process the mixture of externally and self-generated (reafferent) feedback that arises during locomotion. Commonly, CD in the peripheral nervous system cancels reafference to protect sensors and the central nervous system from being fatigued and overwhelmed by self-generated feedback. However, cancellation also limits the feedback that contributes to an animal's awareness of its body position and motion within the environment, the sense of proprioception. We propose that, rather than cancellation, CD to the fish lateral line organ restructures reafference to maximize proprioceptive information content. Fishes' undulatory body motions induce reafferent feedback that can encode the body's instantaneous configuration with respect to fluid flows. We combined experimental and computational analyses of swimming biomechanics and hair cell physiology to develop a neuromechanical model of how fish can track peak body curvature, a key signature of axial undulatory locomotion. Without CD, this computation would be challenged by sensory adaptation, typified by decaying sensitivity and phase distortions with respect to an input stimulus. We find that CD interacts synergistically with sensor polarization to sharpen sensitivity along sensors' preferred axes. The sharpening of sensitivity regulates spiking to a narrow interval coinciding with peak reafferent stimulation, which prevents adaptation and homogenizes the otherwise variable sensor output. Our integrative model reveals a vital role of CD for ensuring precise proprioceptive feedback during undulatory locomotion, which we term external proprioception.

Sensory ecology of the fish lateral-line system: Morphological and physiological adaptations for the perception of hydrodynamic stimuli

Fishes are able to detect and perceive the hydrodynamic and physical environment they inhabit and process this sensory information to guide the resultant behaviour through their mechanosensory lateral-line system. This sensory system consists of up to several thousand neuromasts distributed across the entire body of the animal. Using the lateral-line system, fishes perceive water movements of both biotic and abiotic origin. The anatomy of the lateral-line system varies greatly between and within species. It is still a matter of debate as to how different lateral-line anatomies reflect adaptations to the hydrodynamic conditions to which fishes are exposed. While there are many accounts of lateral-line system adaptations for the detection of hydrodynamic signals in distinct behavioural contexts and environments for specific fish species, there is only limited knowledge on how the environment influences intra and interspecific variations in lateral-line morphology. Fishes live in a wide range of habitats with highly diverse hydrodynamic conditions, from pools and lakes and slowly moving deep-sea currents to turbulent and fast running rivers and rough coastal surf regions. Perhaps surprisingly, detailed characterisations of the hydrodynamic properties of natural water bodies are rare. In particular, little is known about the spatio-temporal patterns of the small-scale water motions that are most relevant for many fish behaviours, making it difficult to relate environmental stimuli to sensory system morphology and function. Humans use bodies of water extensively for recreational, industrial and domestic purposes and in doing so often alter the aquatic environment, such as through the release of toxicants, the blocking of rivers by dams and acoustic noise emerging from boats and construction sites. Although the effects of anthropogenic interferences are often not well understood or quantified, it seems obvious that they change not only water quality and appearance but also, they alter hydrodynamic conditions and thus the types of hydrodynamic stimuli acting on fishes. To date, little is known about how anthropogenic influences on the aquatic environment affect the morphology and function of sensory systems in general and the lateral-line system in particular. This review starts out by briefly describing naturally occurring hydrodynamic stimuli and the morphology and neurobiology of the fish lateral-line system. In the main part, adaptations of the fish lateral-line system for the detection and analysis of water movements during various behaviours are presented. Finally, anthropogenic influences on the aquatic environment and potential effects on the fish lateral-line system are discussed.

Form-function relationship in artificial lateral lines

We examined the form-function relationship of laboratory-constructed artificial lateral line canals. These biomimetic flow sensors consisted of a transparent silicone bar located inside a fluid filled canal equipped with canal pores. The silicone bar guided the light from a LED towards a position- sensitive photodiode. Fluid motion inside the canal deflected the silicone bar which was detected by the photodiode. We found that the resonance frequency of the silicone bar determined the resonance frequency of the artificial lateral line (frequency at which the sensor was most sensitive). The thickness and length of the silicone bar influenced both, the resonance frequency and the sensitivity (across all tested frequencies) of the artificial lateral line sensor. Sensitivity was also influenced by the length and diameter of the artificial lateral line canals. The distance between canal pores determined the spatial resolution of the sensor. The functionality of the sensor in detecting oscillatory fluid motions remained when the canal pores were covered with flexible membranes. Tension, diameter and thickness of the membranes altered the temporal filter properties of the artificial lateral line neuromast. The density and viscosity of the fluid inside the artificial lateral line canals also influenced the sensitivity and temporal filter properties of the artificial lateral line. The acquired knowledge will allow us to optimize artificial lateral line systems for specific technical applications.

Bidirectional biomimetic flow sensing with antiparallel and curved artificial hair sensors

Background: Flow stimuli in the natural world are varied and contain a wide variety of directional information. Nature has developed morphological polarity and bidirectional arrangements for flow sensing to filter the incoming stimuli. Inspired by the neuromasts found in the lateral line of fish, we present a novel flow sensor design based on two curved cantilevers with bending orientation antiparallel to each other. Antiparallel cantilever pairs were designed, fabricated and compared to a single cantilever based hair sensor in terms of sensitivity to temperature changes and their response to changes in relative air flow direction. Results: In bidirectional air flow, antiparallel cantilever pairs exhibit an axially symmetrical sensitivity between 40 μV/(m s^-1) for the lower air flow velocity range (between ±10-20 m s^-1) and 80 μV/(m s^-1) for a higher air flow velocity range (between ±20-32 m s^-1). The antiparallel cantilever design improves directional sensitivity and provides a sinusoidal response to flow angle. In forward flow, the single sensor reaches its saturation limitation, flattening at 67% of the ideal sinusoidal curve which is earlier than the antiparallel cantilevers at 75%. The antiparallel artificial hair sensor better compensates for temperature changes than the single sensor. Conclusion: This work demonstrated the successive improvement of the bidirectional sensitivity, that is, improved temperature compensation, decreased noise generation and symmetrical response behaviour. In the antiparallel configuration, one of the two cantilevers always extends out into the free stream flow, remaining sensitive to directional flow and preserving a sensitivity to further flow stimuli.

A time-stamp mechanism may provide temporal information necessary for egocentric to allocentric spatial transformations

Learning the spatial organization of the environment is essential for most animals’ survival. This requires the animal to derive allocentric spatial information from egocentric sensory and motor experience. The neural mechanisms underlying this transformation are mostly unknown. We addressed this problem in electric fish, which can precisely navigate in complete darkness and whose brain circuitry is relatively simple. We conducted the first neural recordings in the preglomerular complex, the thalamic region exclusively connecting the optic tectum with the spatial learning circuits in the dorsolateral pallium. While tectal topographic information was mostly eliminated in preglomerular neurons, the time-intervals between object encounters were precisely encoded. We show that this reliable temporal information, combined with a speed signal, can permit accurate estimation of the distance between encounters, a necessary component of path-integration that enables computing allocentric spatial relations. Our results suggest that similar mechanisms are involved in sequential spatial learning in all vertebrates.

Finding their way around is an essential part of survival for many animals and helps them to locate food, mates and shelter. Animals have evolved the ability to form a 'map' or representation of their surroundings. For example, the electric fish Apteronotus leptorhynchus, is able to precisely learn the location of food and navigate there. It can do this in complete darkness by generating a weak electric field. As it swims, every object it encounters generates an ‘electric image’ that is detected on the skin and processed in the brain.

However, all the cues the fish comes across are from its own point of view – the information about its environment is processed with respect to its location. And yet, the map that it generates needs to be independent of the fish’s position – it has to work regardless of where the animal is. The way animals translate ‘self-centered’ experiences to form a general representation of their surroundings is not yet fully understood.

Now, Wallach et al. studied how internal brain maps are generated in A. leptorhynchus. Information about the fish's environment passes through a structure in the brain called the preglomerular complex. Measuring the activity of this region revealed that the preglomerular complex does not process much self-centered information. Instead, whenever the fish passed any object – regardless of where it was in relation to the fish – the event triggered a brief burst of preglomerular activity. The intensity of the activity depended on how recently the fish had encountered another object. This information, combined with the dynamics of the fish's movement, could be what allows the fish to convert a sequence of encounters into a general spatial map.

These findings could help to inform research on learning and navigation. Further research could also reveal whether other species, including humans, generate their mental maps in a similar way. This may be relevant for people suffering from diseases such as Alzheimer’s, in which a sense of orientation has become impaired.

Head width influences flow sensing by the lateral line canal system in fishes

The architecture of the cephalic lateral line canal system, with distinct lines for the supraorbital, infraorbital and mandibular canals, is highly conserved among fish species. Because these canals lie on a cranial platform, the sensory input they receive is expected to change based on how flow interacts with the head and how the canal pores are spatially distributed. In this study, we explored how head width, a trait that can vary greatly between species and across ontogeny, affects flow sensing. We inserted pressure sensors into physical fish head models of varying widths (narrow, intermediate and wide) and placed these models in steady and vortical flows. We measured sensory performance in terms of detecting flow parameters (flow speed, vortex shedding frequency and cylinder diameter), sensitivity (change in pressure gradient as a function of flow speed) and signal-to-noise ratio (SNR; strength of vortex shedding frequency with respect to background). Our results show that in all model heads the amount of hydrodynamic information was maximized at the anterior region regardless of what metric we used to evaluate the sensory performance. In addition, we discovered that all model heads had the highest SNR for vortices at the intermediate flow speeds but that each head width passively optimized the SNR for different sized vortices, which may have implications for refuge and prey seeking. Our results provide insight into the sensory ecology of fishes and have implications for the design of autonomous underwater vehicles.

Model-based observer and feedback control design for a rigid Joukowski foil in a Kármán vortex street

Obstacles and swimming fish in flow create a wake with an alternating left/right vortex pattern known as a Kármán vortex street and reverse Kármán vortex street, respectively. An energy-efficient fish behavior resembling slaloming through the vortex street is called Kármán gaiting. This paper describes the use of a bioinspired array of pressure sensors on a Joukowski foil to estimate and control flow-relative position in a Kármán vortex street using potential flow theory, recursive Bayesian filtering, and trajectory-tracking feedback control. The Joukowski foil is fixed in downstream position in a flowing water channel and free to move on air bearings in the cross-stream direction by controlling its angle of attack to generate lift. Inspired by the lateral-line neuromasts found in fish, the sensing and control scheme is validated using off-the-shelf pressure sensors in an experimental testbed that includes a flapping device to create vortices. We derive a potential flow model that describes the flow over a Joukowski foil in a Kármán vortex street and identify an optimal path through a Kármán vortex street using empirical observability. The optimally observable trajectory is one that passes through each vortex in the street. The estimated vorticity and location of the Kármán vortex street are used in a closed-loop control to track either the optimally observable path or the energetically efficient gait exhibited by fish. Results from the closed-loop control experiments in the flow tank show that the artificial lateral line in conjunction with a potential flow model and Bayesian estimator allow the robot to perform fish-like slaloming behavior in a Kármán vortex street. This work is a precursor to an autonomous robotic fish sensing the wake of another fish and/or performing pursuit and schooling behavior.

μ-Biomimetic flow-sensors--introducing light-guiding PDMS structures into MEMS

In the area of biomimetics, engineers use inspiration from natural systems to develop technical devices, such as sensors. One example is the lateral line system of fish. It is a mechanoreceptive system consisting of up to several thousand individual sensors called neuromasts, which enable fish to sense prey, predators, or conspecifics. So far, the small size and high sensitivity of the lateral line is unmatched by man-made sensor devices. Here, we describe an artificial lateral line system based on an optical detection principle. We developed artificial canal neuromasts using MEMS technology including thick film techniques. In this work, we describe the MEMS fabrication and characterize a sensor prototype. Our sensor consists of a silicon chip, a housing, and an electronic circuit. We demonstrate the functionality of our μ-biomimetic flow sensor by analyzing its response to constant water flow and flow fluctuations. Furthermore, we discuss the sensor robustness and sensitivity of our sensor and its suitability for industrial and medical applications. In sum, our sensor can be used for many tasks, e.g. for monitoring fluid flow in medical applications, for detecting leakages in tap water systems or for air and gas flow measurements. Finally, our flow sensor can even be used to improve current knowledge about the functional significance of the fish lateral line.

A fish perspective: detecting flow features while moving using an artificial lateral line in steady and unsteady flow

For underwater vehicles to successfully detect and navigate turbulent flows, sensing the fluid interactions that occur is required. Fish possess a unique sensory organ called the lateral line. Sensory units called neuromasts are distributed over their body, and provide fish with flow-related information. In this study, a three-dimensional fish-shaped head, instrumented with pressure sensors, was used to investigate the pressure signals for relevant hydrodynamic stimuli to an artificial lateral line system. Unsteady wakes were sensed with the objective to detect the edges of the hydrodynamic trail and then explore and characterize the periodicity of the vorticity. The investigated wakes (Kármán vortex streets) were formed behind a range of cylinder diameter sizes (2.5, 4.5 and 10 cm) and flow velocities (9.9, 19.6 and 26.1 cm s(-1)). Results highlight that moving in the flow is advantageous to characterize the flow environment when compared with static analysis. The pressure difference from foremost to side sensors in the frontal plane provides us a useful measure of transition from steady to unsteady flow. The vortex shedding frequency (VSF) and its magnitude can be used to differentiate the source size and flow speed. Moreover, the distribution of the sensing array vertically as well as the laterally allows the Kármán vortex paired vortices to be detected in the pressure signal as twice the VSF.

Organization of the gymnotiform fish pallium in relation to learning and memory: II. Extrinsic connections

This study describes the extrinsic connections of the dorsal telencephalon (pallium) of gymnotiform fish. We show that the afferents to the dorsolateral and dorsomedial pallial subdivisions of gymnotiform fish arise from the preglomerular complex. The preglomerular complex receives input from four clearly distinct regions: (1) descending input from the pallium itself (dorsomedial and dorsocentral subdivisions and nucleus taenia); (2) other diencephalic nuclei (centroposterior, glomerular, and anterior tuberal nuclei and nucleus of the posterior tuberculum); (3) mesencephalic sensory structures (optic tectum, dorsal and ventral torus semicircularis); and (4) basal forebrain, preoptic area, and hypothalamic nuclei. Previous studies have implicated the majority of the diencephalic and mesencephalic nuclei in electrosensory, visual, and acousticolateral functions. Here we discuss the implications of preglomerular/pallial electrosensory-associated afferents with respect to a major functional dichotomy of the electric sense. The results allow us to hypothesize that a functional distinction between electrocommunication vs. electrolocation is maintained within the input and output pathways of the gymnotiform pallium. Electrocommunication information is conveyed to the pallium through complex indirect pathways that originate in the nucleus electrosensorius, whereas electrolocation processing follows a conservative pathway inherent to all vertebrates, through the optic tectum. We hypothesize that cells responsive to communication signals do not converge onto the same targets in the preglomerular complex as cells responsive to moving objects. We also hypothesize that efferents from the dorsocentral (DC) telencephalon project to the dorsal torus semicircularis to regulate processing of electrocommunication signals, whereas DC efferents to the tectum modulate sensory control of movement.

A model of the lateral line of fish for vortex sensing

In this paper, the lateral line trunk canal (LLTC) of a fish is modeled to investigate how it is affected by an external flow field. Potential flow theory is adopted to model the flow field around a fish's body in the presence of a Karman vortex street. Karman and reverse Karman streets represent the flow patterns behind a bluff body and a traveling fish, respectively. An analytical solution is obtained for a flat body, while a fish-like body is modeled using a Joukowski transformation and the corresponding equations are solved numerically. The pressure distribution on the body surface is then computed employing Bernoulli's equation. For a known external flow, the flow inside the LLTC is driven by the pressure gradient between a pair of consecutive pores, which can be solved analytically. Governing dimensionless parameters are obtained from this analytical solution, and the effects of these numbers on the amplitude or features of the velocity distribution inside the canal are studied. The results show that the main characteristics of a vortex street including the magnitude of vortices, their translational speed, their spacing, their distance from the fish's body and the angle of the vortex street axis can all be recovered by measuring the velocity distribution along the canal and its changes with time. To this end, the proposed LLTC model could explain how a fish identifies the characteristics of a Karman vortex street shed by a nearby object or a traveling fish. It is also demonstrated that while this model captures the ac (alternating current) component of the external velocity signal, the dc (direct current) component of the signal is filtered out. Based on the results of our model, the role of the LLTC in a fish's schooling and its evolutionary impact on fish sensing are discussed.

Hydrodynamic pressure sensing with an artificial lateral line in steady and unsteady flows

With the overall goal being a better understanding of the sensing environment from the local perspective of a situated agent, we studied uniform flows and Kármán vortex streets in a frame of reference relevant to a fish or swimming robot. We visualized each flow regime with digital particle image velocimetry and then took local measurements using a rigid body with laterally distributed parallel pressure sensor arrays. Time and frequency domain methods were used to characterize hydrodynamically relevant scenarios in steady and unsteady flows for control applications. Here we report that a distributed pressure sensing mechanism has the capability to discriminate Kármán vortex streets from uniform flows, and determine the orientation and position of the platform with respect to the incoming flow and the centre axis of the Kármán vortex street. It also enables the computation of hydrodynamic features which may be relevant for a robot while interacting with the flow, such as vortex shedding frequency, vortex travelling speed and downstream distance between vortices. A Kármán vortex street was distinguished in this study from uniform flows by analysing the magnitude of fluctuations present in the sensor measurements and the number of sensors detecting the same dominant frequency. In the Kármán vortex street the turbulence intensity was 30% higher than that in the uniform flow and the sensors collectively sensed the vortex shedding frequency as the dominant frequency. The position and orientation of the sensor platform were determined via a comparative analysis between laterally distributed sensor arrays; the vortex travelling speed was estimated via a cross-correlation analysis among the sensors.

Temporal precision and reliability in the velocity regime of a hair-cell sensory system: the mechanosensory lateral line of goldfish, Carassius auratus

Fish and aquatic frogs detect minute water motion by means of a specialized mechanosensory system, the lateral line. Ubiquitous in fish, the lateral-line system is characterized by hair-cell based sensory structures across the fish's surface called neuromasts. These neuromasts occur free-standing on the skin as superficial neuromasts (SN) or are recessed into canals as canal neuromasts. SNs respond to rapid changes of water velocity in a small layer of fluid around the fish, including the so-called boundary layer. Although omnipresent, the boundary layer's impact on the SN response is still a matter of debate. For the first time using an information-theoretic approach to this sensory system, we have investigated the SN afferents encoding capabilities. Combining covariance analysis, phase analysis, and modeling of recorded neuronal responses of primary lateral line afferents, we show that encoding by the SNs is adequately described as a linear, velocity-responsive mechanism. Afferent responses display a bimodal distribution of opposite Wiener kernels that likely reflected the two hair-cell populations within a given neuromast. Using frozen noise stimuli, we further demonstrate that SN afferents respond in an extremely precise manner and with high reproducibility across a broad frequency band (10-150 Hz), revealing that an optimal decoder would need to rely extensively on a temporal code. This was further substantiated by means of signal reconstruction of spike trains that were time shifted with respect to their original. On average, a time shift of 3.5 ms was enough to diminish the encoding capabilities of primary afferents by 70%. Our results further demonstrate that the SNs' encoding capability is linearly related to the stimulus outside the boundary layer, and that the boundary layer can, therefore, be neglected while interpreting lateral line response of SN afferents to hydrodynamic stimuli.

Determination of object position, vortex shedding frequency and flow velocity using artificial lateral line canals

The lateral line system of fish consists of superficial neuromasts, and neuromasts embedded in lateral line canals. Lateral line neuromasts allow fish to sense both minute water motions and pressure gradients, thereby enabling them to detect predators and prey or to recognize and discriminate stationary objects while passing them. With the aid of the lateral line, fish can also sense vortices caused by an upstream object or by undulatory swimming movements of fish. We show here that artificial lateral line canals equipped with optical flow sensors can be used to detect the water motions generated by a stationary vibrating sphere, the vortices caused by an upstream cylinder or the water (air) movements caused by a passing object. The hydrodynamic information retrieved from optical flow sensors can be used to calculate bulk flow velocity and thus the size of the cylinder that shed the vortices. Even a bilateral sensor platform equipped with only one artificial lateral line canal on each side is sufficient to determine the position of an upstream cylinder.

Wake tracking and the detection of vortex rings by the canal lateral line of fish

Research on the lateral line of fish has mainly focused on the detection of oscillating objects. Yet many fish are able to track vortex wakes that arise from other fish. It is not yet known what the sensory input from a wake looks like and how fish can extract relevant information from it. We present a mathematical model to determine how vortices stimulate the canal lateral line and verify it by neuronal recordings. We also show how the information about the orientation of a vortex ring is captured by the lateral-line sensors so as to enable fish to follow a vortex street.

Afferent neurons of the zebrafish lateral line are strict selectors of hair-cell orientation

Hair cells in the inner ear display a characteristic polarization of their apical stereocilia across the plane of the sensory epithelium. This planar orientation allows coherent transduction of mechanical stimuli because the axis of morphological polarity of the stereocilia corresponds to the direction of excitability of the hair cells. Neuromasts of the lateral line in fishes and amphibians form two intermingled populations of hair cells oriented at 180° relative to each other, however, creating a stimulus-polarity ambiguity. Therefore, it is unknown how these animals resolve the vectorial component of a mechanical stimulus. Using genetic mosaics and live imaging in transgenic zebrafish to visualize hair cells and neurons at single-cell resolution, we show that lateral-line afferents can recognize the planar polarization of hair cells. Each neuron forms synapses with hair cells of identical orientation to divide the neuromast into functional planar-polarity compartments. We also show that afferent neurons are strict selectors of polarity that can re-establish synapses with identically oriented targets during hair-cell regeneration. Our results provide the anatomical bases for the physiological models of signal-polarity resolution by the lateral line.

Drag force acting on a neuromast in the fish lateral line trunk canal. I. Numerical modelling of external-internal flow coupling

Fishes use a complex, multi-branched, mechanoreceptive organ called the lateral line to detect the motion of water in their immediate surroundings. This study is concerned with a subset of that organ referred to as the lateral line trunk canal (LLTC). The LLTC consists of a long tube no more than a few millimetres in diameter embedded immediately under the skin of the fish on each side of its body. In most fishes, pore-like openings are regularly distributed along the LLTC, and a minute sensor enveloped in a gelatinous cupula, referred to as a neuromast, is located between each pair of pores. Drag forces resulting from fluid motions induced inside the LLTC by pressure fluctuations in the external flow stimulate the neuromasts. This study, Part I of a two-part sequence, investigates the motion-sensing characteristics of the LLTC and how it may be used by fishes to detect wakes. To this end, an idealized geometrical/dynamical situation is examined that retains the essential problem physics. A two-level numerical model is developed that couples the vortical flow outside the LLTC to the flow stimulating the neuromasts within it. First, using a Navier-Stokes solver, we calculate the unsteady flow past an elongated rectangular prism and a fish downstream of it, with both objects moving at the same speed. By construction, the prism generates a clean, periodic vortex street in its wake. Then, also using the Navier-Stokes solver, the pressure field associated with this external flow is used to calculate the unsteady flow inside the LLTC of the fish, which creates the drag forces acting on the neuromast cupula. Although idealized, this external-internal coupled flow model allows an investigation of the filtering properties and performance characteristics of the LLTC for a range of frequencies of biological interest. The results obtained here and in Part II show that the LLTC acts as a low-pass filter, preferentially damping high-frequency pressure gradient oscillations, and hence high-frequency accelerations, associated with the external flow.