Modelling electrosensory systems in sharks - uni-potsdam.demwinkler/cms/data/...Abstract An existing model describing the voltage generation in the ampullae of Lorenzini based on induction

Modelling electrosensory systems in sharks

Michael Winkler

October 5, 2007

Abstract

An existing model describing the voltage generation in the ampullae of Lorenzini based on

induction has been examined and advanced to achieve better approximation to the real

electrosensory system in elasmobranches. Particularly the frequency and phase behaviour

of the assumed input signals has been carefully studied. The functional analysis is based on

the assumed utilization of the electric sense to navigate.

To investigate the actual electric properties specifically of the canal connecting the receptor

cavity to the sea water a measurement setup has been developed. Due to the high

sensitivity of the electrosensory system in sharks and the aim of achieving a setup that

allows measurements as close to the real life situation as possible several aspects of low

level measurement had to be taken into account.

Especially the ability to measure the conductivity of ampullary canals dissected from dogfish

in AC and DC environment was demanded to examine any eventual electrical active

behaviour of the gel the canals are filled with.

Acknowledgement

I would like to thank Dr. Mike Paulin (Zoology Dept., University of Otago) for his

illuminating input in several discussions and clarifying explanations about the complex

mechanisms in electrosensitive receptor cells. Furthermore I would like thank my supervisor

Tim Molteno for his inspiring ideas regarding this project. I’d also like to dedicate my

appreciation to the mechanics workshop team, namely Peter Stroud and Richard Sparrow

did an amazingly accurate job on manufacturing the sample holder.

Contents

1 Introduction 1

1.1 Glossary 4

2 Research Background

2.1 Anatomic Details 6

2.1.1 Receptor Cell 6

2.1.2 Gel Canal Anatomy 7

2.1.3 Geometric Distribution of Ampullae of Lorenzini in Dogfish 8

2.1.4 Comparison of Different Ampullae Types 9

2.2 Characterisation of the gel 10

2.1.1 Chemical Composition of the Gel 10

2.2.2 Electrical Properties of the Gel 11

2.3 Navigation based on induction 12

2.3.1 Induction based Electroreception regarding Navigation 12

2.3.2 Variation in Swimming Direction 13

2.3.3 Considering Environmental Fields 15

3 Technical Background

3.1 Preface 17

3.2 Technical Aspects Using the Electrometer “Keithley 2010” 18

3.2.1 Accuracy 18

3.2.2 Noise 18

3.3 Low Level Current Measurements 19

3.3.1 Leakage Current and Guarding 19

3.3.2 Zero Drift and Offset Currents 21

3.3.3 Voltage Burden 21

3.3.4 Electrostatic Interference and Shielding 22

3.3.5 Temperature Effects 22

4 Modifications to Inductive Perception Model

4.1 Trajectory Analysis 23

4.2 Modelling Perturbations by Ocean Flows 25

4.3 Frequency Spectrum Analysis 27

4.4 Phase Spectrum Analysis 29

4.5 Influence of Electric Perturbation on Phase and Frequency 30

5 Dipole Model Approach

5.1 General Hypothesis 32

5.2 Opposing Mechanism 33

5.3 Considering Molecular Dipoles of Water 33

6 Software Interface for digital electrometer

6.1. Aspects about used program language 34

6.2 Implementing a Measurement Strategy 35

6.3 Graphical User Interface 35

6.4 Programming Remarks 36

7 Measurement Setup

7.1 Sample Holder Design Considerations 37

7.1.1 General Design 37

7.1.2 Geometry Constraints 38

7.1.3 Solidworks Model 38

7.2 Measurement Schematics 40

7.2.1 Voltage Source 40

7.2.2 Setup Diagram 41

7.3 Fabricating Electrodes 42

8 Experimental Realization

8.1 Zero Level Evaluation 43

8.2 Conductivity Estimate 45

8.3 Alternating Current Measurements 47

9 Discussion 49

10 Perspective on Future Research 51

11 Bibliography 52

Appendix A VB. Net subroutine handling file output of received characters 55

Appendix B VB.Net measurement routine 56

Appendix C Photo of Sample Holder 62

Appendix D EAGLE Schematics of Voltage Divider 63

Appendix E Photo of Measurement Setup 64

________________________________________________________________________________________ Michael Winkler University of Otago Postgraduate Diploma in Science Thesis 1 Department of Physics – Electronics Program

Chapter I

Introduction

This research project is placed in the interdisciplinary field of biophysics dealing with the

characterization of the electrosensitive perception in Elasmobranches (sharks, rays and

skates). Electrosensitivity in general means that electric fields with an amplitude above the

sensitivity limit of the animal are perceived with a network of directional sensors and

mapped to known field patterns to identify its environment.

Considering the nerve infrastructure in sharks, their ability to perceive electromagnetic fields

is at least as important as visual and acoustic senses [Murray(1974)], which makes the

understanding of this ability even more important. As humans lack the ability of detecting

EM-waves outside of the optical range the intuitive comprehension of this sense is very

limited.

It is known that the electric sense is used for near field detection of the electric signals in

the muscles of prey, but it is also argued [Kalmijn(1973),Kalmijn(2000),Paulin(1997)] that the

same sensory system is used for navigational purpose. There is evidence that migrational

species of Elasmobranches use the earth’s magnetic field to navigate in the ocean

[Klimley(1993)]. Yet orienting over long distances and taking disturbances like ocean

currents or field perturbations into account is a much more complex task than approaching

a local dipole field. The sensory system in sharks is only sensitive to slow changing AC

signals but not to constant fields [Paulin(1995)]. Therefore the detection of constant fields

can only be performed by movement of the shark changing its orientation with respect to

the field vector.

The majority of published research in the field of electrosensory systems is focussed on the

characterization of anatomy and cell function. Whereas the scientific research dealing with

the functional analysis is usually constrained to feeding behaviour and prey approaching

mechanisms.


The organs used to measure electric fields are named after Stephano Lorenzini who first

described these jelly filled canals distributed over shark heads in detail: The ampullae of

Lorenzini.

They were first thought to be temperature [Sand(1938)] or mechanically [Murray(1957)]

sensitive as the impulse response of the afferent neurons also varies with these factors. In

1960 the first evidence about their true electrosensitive function was published by R.W.

Murray [Murray(1960)]. Since then only a few research groups have dedicated their work to

the characterization and understanding of the ampullae of Lorenzini.

A. J. Kalmijn was the first to quantify the sensitivity of these organs and has shown that rays

orient in electric fields as weak as those that are induced when swimming in the earth

magnetic field [Kalmijn(1971)]. Although till now no accurate model for sensing induced

voltages has been verified. The Ampullae of Lorenzini consist of a small cavity lined with

receptor cells which is connected to the sea water through small canals. It is known that the

receptor cells initiate a nerve impulse when the potential on their surface is different to the

reference potential on the inside [Lu and Fishman(1994), [Bromm et al.(1976)], but the

function of the connecting canal and its influence on the generated voltage gradient is not

known. Assumptions have been proposed by B. Waltmann who proposed that the

substance inside the canal behaves like sea water considering electrical properties and can

be treated as a wire like structure protecting the receptor cells from outside influences

[Waltmann(1966)]. He suggested a model incorporating the canal as an antenna amplifying

signals with a certain frequency depending on the length of the canal. This model was

recently questioned by B.R. Brown who reports that the frequency dependency is far lower

than expected and that simply conveying a signal from the pore to the ampulla seems

irrelevant to the electric sense [Brown(2005)].

The research carried out by Brown characterises the electrical properties of the gel as a bulk

material in a measuring cell with substantially different geometry. Considering the actual

composition of the gel it is therefore questionable if the measured impedance spectra

match the real life situation.


Based on these two opposing statements my research project aimed at the verification of

Browns impedance measurements taking the actual biologic environment and geometry

into account. A measurement setup to yield the low noise requirements was designed which

in addition can also be used to characterize capacitive effects in the ampullae of Lorenzini.

Elasmobranches show the highest sensitivity when exposed to fields in the frequency range

from 0.1 to 10 Hz and are sensitive to a field strength down to 5 nV/cm [Murray(1962),

Kalmijn(1966)]. Although it is not certain if one single ampullae can achieve this resolution

or if it is an accumulated effect measured over hundreds of ampullae.

It is relatively difficult to reach the sensitivity floor in the experiment as it would require the

accurate measuring of currents in the range of picoamperes. Since the available

Electrometer can resolve about 10nA I am aiming at the characterization with fields in the

range of 1 to 100 µV/cm. This is still reasonable as it was shown that the electric properties

of shark gel do not vary with the magnitude of the electric field in a reasonably large range

[Brown(2002)].

The phase lag of the ampullary system was examined by J.A. Sisneros and T.C. Tricas

[Sisneros and Tricas(2000)] but with focus on hormone influence and actual phase lag of the

neuron response. In this regard the present work is dedicated to enable the analysis of

phase changes just across the canal which may influence the voltage at the actual receptor

cell.

Furthermore based on the conductive behaviour and considering the chemical structure

and geometry of the canal it will be attempted to implement an electronic physical model.

This might allow characterisation of the system to predict the behaviour in its environment.

The functional characterisation is established upon the navigational model established by

M. Paulin which is based on the sinusoidal movement of the shark’s head in the earth

magnetic field. This movement induces voltage signals with the phase depending on the

angle of the velocity vector and the magnetic field vector thereby allowing the shark to

determine its swimming direction.


Glossary

Acoustico lateralis system – aural events detected by ears and pressure changes detected by

the lateral line organ are linked in the sharks brain. Effectively creating a detector for low

the low frequency range of longitudinal waves. This combination is known as the Acoustico

lateralis system.

Elasmobranch – subclass of cartilaginous fish including rays, skates and sharks.

Epithelium – tissue that is made up of cell layers. This type of tissue usually lines the skin

and inside of cavities like the ampullae of Lorenzini

Kinocilium – A change in distance between the kinocilium and the microvilli alters the

neuron firing rate. This is achieved by modifying the polarization of the underlying

membrane

Microvilli – small structures increasing the surface area of cells. Functionally related to the

Alveoli – Latin for “small cavity”

Afferent nerve – sensory neurons conveying the nerve impulse train to brain

Teleost – subclass of ray-finned fishes (Actinopterygii)

Apical membrane – outer part of the sensory lining

Basal membrane – inside part of the sensory lining / part of ion channelling mechanisms

Gel Electrophoresis – separation of molecules by applying a charge. The polymer

compounds are filtered by size via a porous gel acting as a molecular sieve.

CAD – abbreviation for Computer Aided Design


Aperture – refers to the time the signal is measured by the device

Lateral – refers to the movement away from the midline of the body. In terms of canal

movement translating to a sideway movement when viewed from the top.

Medial – refers to the movement towards the midline of the body. Describes the forward

and backward movement in a top view perspective along the general heading direction.

Hydrogel – a network of hydrophobic polymer chains that contains a very high amount of

water.

Ophthalmic – related to the eye


Chapter 2

Research Background

2.1 Anatomic details

The first substantial research going beyond the phenomenological features of the Ampullae

of Lorenzini concerning electroreception was published in 1960 by Murray [Murray(1960)].

The amount of innervation of the ampullary system is similar to other members of the

acoustico lateralis system and consequently the electric sense is equally as important as

visual or aural perception [Murray(1974)]. Electro perception is a feature that all

Elasmobranches have in common whereas the actual distribution of the ampullae of

Lorenzini varies from species to species.

2.1.1 Receptor cell

The sensory epithelium consists of a single layer of supporting cells in which the receptor

cells are embedded. The actual cavity containing the receptor cells is divided in several

alveoli thereby maximizing the surface area and number of available receptor cells.

Connecting nerve and receptor cell the synapse reaches the lumen of the ampullae where a

kinocilium is located. As not the whole epithelium surface is covered with receptor cells

flattened tops of supporting cells functioning as a separator are situated in between. A

cluster of microvilli projects around each kinocilium. At the surface away from the centre

point of attachment all cells are closely joined together by narrow connections. These

junctions form coherent bands around the receptor cell blocking off extracellular space.

The receptor cell is connected to the nerve via synaptic junctions at the distal side of the

receptor cell. At this junction a rod like presynaptic bar surrounded by ordered vesicles

extends into the receptor cell. Lining of presynaptic material on the inside and postsynaptic

material on the outside of the receptor cell form the actual connection to the nerve fibre.

[Murray(1974)]

Figure 2.0: bm: basal membrane, kc: kinocillium, mv: microvilli, n: nucleus, nb: nerve bundle, ne: nerve ending, presynaptic structure, pm: postsynaptic material, g: gutter, r: ribbon-shaped presynaptic bar, rec: receptor cell, sc: supporting cell, se: sensory epithelium, syn: synapse, t: tight junction, v: vesicle [FIG1. Bottom (DFH),p. 126, Murray (1974)]

2.1.2 gel canal anatomy

The ampullae are divided into three separate sections: The alveolar as described above, the

canal epithelium and the transition area, called marginal zone. The canal epithelium is only

about 1 – 2 µm thick and is supported by thin layers of connective tissue. The marginal zone

forms the transition region to the alveolar epithelium which is noticeable thicker (15µm).

Moreover axons can only enter through this region to innervate the receptor cells.

Consisting of two cell layers positioned approximately 10 nm apart from each other the

canal epithelium does not form an effective insulation as extracellular fluid forms a

conducting path. Subsequently one of the present cell layers must have a high resistivity

due to its cell structure. The basement layer is the same as the one encapsulating the

receptor cells in the alveoli and therefore cannot exhibit a high resistance as it would cause

a voltage drop across this layer rather than the receptor cells. Following the inner superficial

cell layer is the base of the present high voltage insulation. The measured resistivity of

about 23 M cmΩ is based on a cell structure which is impassable for ions.

As the receptor and supporting cells in the alveoli are linked via the same mechanism as the

epithelial layer in the canal it can be assumed that the receptor cells are placed across the

voltage gradient in the ampulla.

[Waltmann(1974)]


2.1.3 Geometric distribution of ampullae of Lorenzini in dogfish

The Network of ampullae of Lorenzini is grouped into several dense regions concentrated in

the forehead. Most interestingly there is a group of receptors placed distinctively separate

from the main clusters in the superficial ophthalmic regions. This hyoid group of ampullae

has primarily a vertical orientation whereas most of the ampullae in the forehead are

positioned horizontally. Based on the ampullae distribution it is argued that the front part is

used for near field prey detection and that the hyoid group may have a navigational

purpose [Paulin(1997)]. This argument is reinforced by various examples of Elasmobranches

that show only show either the ophthalmic or hyoid group. The availability of the front

group is thereby congruent with the feeding behaviour: Herbivorous Elasmobranches

appear to always lack the fine distribution of ampullae in the forehead whereas carnivorous

species always seem to rely on this sensor array. Another aspect is migration: Species that

do not migrate lack the hyoid group whereas for example migrating herbivores still exhibit

this specific ampullae group.

Figure 2.1: 3D model of a dogfish showing the distribution of ampullae of Lorenzini

(turquoise) and the nervous system (yellow) (picture kindly provided by M. Paulin)


2.1.4 Comparison of different ampullae types

Two different types of ampullae of Lorenzini have been found in different types of marine

animals. Whereas Teleosts respectively freshwater animals exhibit receptor cavities that are

placed only 50 to 200 µm below the surface [Collin and Whitehead(2004)], the ampullary

canals in Elasmobranches which connect the receptor cells to the skin surface can reach a

length of up to 20cm [Murray1974].

Comparing Browns work to other publications from Waltmann or New [New(1997)] it is

arguable if evolution actually tuned the sensitivity of the ampullae to different frequencies

comparable to the structure of the human aural sense or if different ampullae length just

account for varying sensitivity. In addition canal length and properties might not be the

only factor influencing sensitivity as the number of afferent nerve fibers inervating the

ampullae is much bigger in Elasmobranches than in Teleosts [Zakon(1986)]. This also applies

for the actual number of ampullae as in sharks they are organized in clusters of up to 400

that are distributed over the head region [Collin(2004)].

receptor cell

nerve

supporting cell

supporting cell

canal

epidermis

Figure 2.2: Cell schematic of two types of ampullae of Lorenzini. Left: Teleost / freshwater type Right: Elasmobranch / salt water type (schematic adapted from [Collin2004])


The form of the ampullae may also be highly dependent on the salinity level of the

environment. As the skin of sea water fish is permeable to ions [Murray(1974)] the canal

could just provide a basic insulating tube from currents in the fish’s body or on its surface.

This argument is deduced from recent findings which conclude that the sensitivity is

increased with distance from the skin surface. This was proven by a comparison of sensitivity

between puppet and juvenile scalloped hammerhead sharks [Sisneros et al.(1998),

Kajiura(2001)].

2.2 Characterisation of the gel

2.2.1 Chemical composition of the gel

The gel inside the ampullary canal is made up of a polymer with high ion content

[Brown(2005)]. Namely a sulphated polysaccharide (i-Carrageenan) forming a double helix

polymer structure that inhibits the movement of monovalent ions. This is mainly due to

interactions with the two bounded negatively charged sulphate ion groups [Ciszkowska and

Guillaume(1999)]. It is also worth mentioning that the macroscopic viscosity of the gel has

no influence on the ion movability as only the molecular properties of the gel network are

responsible for this effect [Ciszkowska and Guillaume(1999). As i-Carrageenan is a hydrogel

another effect described by G.H. Pollack must be taken into account: The charged

functional groups in the polymer order water molecules around them thereby impeding the

mass migration of ions [Brown(2005)]. Ion species found in shark gels are sodium, calcium,

chloride and potassium ions [Brown(2005)].


Figure 2.3: chemical structure of iota – Carrageenan. Figure adapted from [Ciszkowska and Guillaume(1999)]


2.2.2 Electrical properties of the gel

The first results quantifying the electrical properties of the gel inside the ampullary canals

where published by Waltmann in 1966. He concluded seawater like properties and assumed

a wire like function transferring surface potentials to the ampullae [Waltmann(1966)]. As

stated by Brown the resistance in bulk sea water and therefore between pores of the

ampullae is far lower than the resistance across the canal [Brown(2005)]. He concludes that

this particular resistance relation sets all ampullae pores to the same value whereas the

receptor cells remain at a different potential at the apical membrane. Correspondingly

conveying a surface potential to the receptor cell is not favoured.

Furthermore he presumes that the reference potential of each ampulla at the basal

membrane in a cluster is the same. This is congruent with Waltmann’s results indicating a

low resistivity for the basement membrane surrounding a single ampulla. Eliminating the

forwarding of a surface potential as a cause for a potential difference at the receptor cell, it

remains unclear at this stage how the perceived voltage gradient is actually generated. A

possible explanation is included in the theory about navigation with use of the electric

sense by M. Paulin involving basic induction mechanisms that will be discussed later on

[Paulin(1997)].

Brown proved his hypothesis by impedance measurements of gel that was squeezed out of

the ampullae and measured in a sample holder of significantly different geometry than the

actual canal. This is reasonable to obtain basic properties of the actual compound, but does

not allow conclusions about the perception of periodic voltage signals that might involve an

active influence of the gel depending on the geometry. It is assumed that the sample

preparation does not affect the physical nor chemical composition of the gel. Examining the

gel composition via gel electrophoresis exhibits a good match of mass composition before

and after his experiments. Although considering that the examined substance has gel

properties and high ion content the presumed match to certain molecular weight may be

questionable but it still remains a qualitative clue about changes in the shark gel; The gel

structure could act as a molecular sieve inhibiting molecule movement more than expected

just from macroscopic viscosity and the properties of the carrier gel.

In Contrast Waltmann used a setup measuring the time response of voltage pulses through

dissected canals. His main argument is that compared to a system with the receptor cavity

still attached the canal with two open ends shows a less significant response delay till the

peak value of the applied voltage is reached. The response time drops from 100ms to an

average between 5 to 10 ms for a canal length of 10 cm [Waltmann(1966)]. As the voltage

pulse with the ampullae still attached to the canal passes through the high resistivity

epithelium lining a resulting higher response time is logical.

Putting it into scale a response delay of several milliseconds is qualitatively different from an

instant direct conduction and may have a crucial role in the perception of periodic signals.

2.3 Navigation based on induction

2.3.1 Induction based electroreception regarding navigation

The basic idea of the following model is that the sinusoidal head movement of the shark in

the earth magnetic field induces a periodically varying voltage that can be measured via the

receptor cells.

The simplified model treats the canal as a projection vertical to the field.

Applying the basic concept of induction in a conducting rod the generated voltage signal

can be calculated:

Assuming a right angle between the magnetic field B and velocity v the arising potential

across a canal with an effective vertical length l is given by:

( )indV v B J dl vρ= × − ≅∫ Bl

This results in a linear proportionality between amplitude of induced voltage and canal

length. Furthermore the voltage is equivalently dependent on the relative velocity of the

canal with respect to the magnetic field.


As the insulation of the system is not perfect and current through the ampullae, the fish’s

body and sea water can lower the voltage gradient, the voltage amplitude is also

dependent on the current density and resistivity. However in this case we assume a perfect

insulation where leakage currents are negligible.

If the shark is heading on a different angle ϑ relative to the magnetic field the effective

velocity is reduced as only the perpendicular vector component causes induction:

( )sinindV vBl ϑ=

2.3.2 Variation in swimming direction

Sharks perform a sinusoidal movement along their actual swimming direction. Considering

the simple case of heading perpendicular to the magnetic field and parallel to the earth

surface a pure sinusoidal lateral variation of the canal position would not have any effect on

the induced voltage: The canal is just shifted along the magnetic field lines. It needs to be

taken into account that the canal actual moves on a fixed trajectory that is constricted by

the skeletal structure effectively moving the canal on a semicircle like pathway. Accounting

for that only the relative movement back and forth of the canal has a change on the

induced voltage.

H

ϑΔ B

α

Figure 2.4: Top view of the circular trajectory of the canal during swimming movements. The

shark’s heading direction is given by H . ϑΔ represents the current deviation of the

velocity vector with respect to the heading direction. The vertical canal is symbolized by the

grey circle.


Following M. Paulins model the induced voltage is then given by:

( )sin sin( )indV vB tλ α ω ϑ= +

The parameter λ relates to the relative vertical extent and resistivity properties of the canal.

The frequency ω is related to the actual turning frequency of the sharks head and accounts

for the back and forward movement with a maximum amplitude of α .

Examining this correlation for 0ϑ = to 2ϑ π= yields in a receptor voltage pattern that

shows unique phase configurations for each swimming direction displayed in figure 2.5 and

2.6. As stated by M. Paulin this is easily proven by the rotational anti symmetric manner of

the phase surface. The previous result allows the animal to determine its direction of

heading just by measuring the induced voltage and correlating the signal with its current

swimming speed.

Figure 2.5: normalized 3D surface plot of the generated voltage signal. The time is

normalized over the period, so that one full cycle is displayed. Each path from the centre to

the outer limit accounts for the voltage pattern generated for this specific direction relative

to the magnetic field.


Figure 2.6: This plot shows the top view of the 3D surface plot in figure 2.5. The plotted

angle is the relative angle between the heading direction and the magnetic field. An angle

of 0° accounts for parallel heading with respect to the magnetic field

2.3.3 Considering environmental fields

One of the major influences to such a sensitive system is the perturbation by electric fields

induced by ocean flows. Following M. Paulins theory vertical electric fields can be neglected

as the angle between the electric field vector and the canal does not change and therefore

vertical fields only create a constant offset. Unfortunately fields in oceans are mostly

oriented in the horizontal plane at the ocean surface. This is due to their mainly horizontal

spatial dimension and flow boundary conditions that inhibit vertical currents of horizontal

flows [Paulin(1997)].



At any given point in the flow the electric field is a function of the actual flow velocity, but

this function is not necessarily the same through out the flow [Paulin(1997)].

Furthermore it has been shown that the influence of electric flows varies between 16 – 90 %

of the magnetically induced signal [Kalmijn(1974)].

Since it is likely that the ampullary canals are not oriented perfectly perpendicular to the

electric field these modulations must be taken into account. Additionally sharks also change

their pitch while swimming therefore changing the effective horizontal canal length that is

susceptible to horizontal electric fields [Paulin(1997)]

Considering a large array of sensors that range from mainly horizontal to mainly vertical

orientation it might be possible for the shark to determine the electric flow influence due to

turning movements and variation of its swimming speed [Paulin(1997)].


Chapter 3

Technical Background

3.1 Preface

In the following practical considerations when measuring low DC currents, high resistances

and low DC voltages will be discussed. The expected currents lie within the nanoampere

range and the expected voltages will have an amplitude in the order of microvolts. it is

therefore significant to design a measurement setup that reaches an extremely low noise

threshold.

Since the sensitivity floor of an elasmobranch reaches down to 5nV/cm with a presumed

resistance in the order of several kilo-ohms across a typical canal length of less than 10cm

the expected current would lie in the range of picoamperes. Unfortunately this is beyond

the capabilities of the available electrometer. Therefore only fields that are about 3 to 4

orders of magnitude larger resulting in voltages in the microvolt to millivolt range allow a

convincing measurement. This increase in field strength should be negligible as Brown

stated, that the electrical properties of the gel do not substantially vary over seven orders of

magnitude [Brown(2005)].


3.2 Technical aspects using the Electrometer “KEITHLEY 2010”

3.2.1 Accuracy

When used with a range setting of 10mA the electrometer is able to resolve 10nA when a

voltage of less than 0.15V is applied, which is certainly the case. The accuracy is given in

ppm (part per million) and is calculated by adding the range accuracy plus a reading

accuracy that is dependent on the actual measured value.

Measurement type Range Resolution Accuracy of

reading [ppm]

Accuracy of

range [ppm]

Burden

Voltage

Current 10mA 10nA 55 7 < 0.15V

Voltage 100mV 10nV 50 10

Table 3.1: accuracy specifications [Keithley(1996)]

To enable low voltage measurements the cables must be shielded and a 4 wire setup

involving the SENSE terminals is required. This makes it possible to account for voltage

offsets and generally yields in a higher accuracy (as discussed in the measurement setup

section). However this type of setup reduces the actual precision as the accuracy for both

the normal and sense terminal must be summed up.

3.2.2 Noise

The examined frequency range is 0.1 to 10 Hz as the elasmobranch is most sensitive at

these frequencies and the periodic movement which provides important information

regarding navigation, also lies in this range. Measuring at low frequencies makes it

necessary to undertake measurements in the direct current mode of the Electrometer hence

the low frequency bandwidth limit cuts off at 3 Hz.

To avoid coupling of the 50Hz power line signal the electrometer averages over a selectable

number of powerline cycles (NPLC). Considering the maximum frequency of 10 Hz and

chosen minimum desired number of 50 measured values per wavelength yields in a setting

of 0.1 PLC (=0.2µs) integration time for frequencies above 1 Hz. At 0.2 Hz it is possible to


choose an aperture of 5 PLC and only the lowest frequency limit of 0.1 Hz would make it

possible to achieve the lowest noise with 10 PLC. Unfortunately Keithley does not provide

noise values for the setting of 10 PLC.

Rate [PLC] RMS Noise – 100mV range Usable Digits

5 100 nV 7 ½

1 120 nV 6 ½

0.1 1,5 µV 5 ½

0.01 3 µV 4 ½

Table 3.2: noise specifications [Keithley(1996)]

It is also worth noting that the electrometer has a delay of 26ms when switching the

measuring function. Since a alternating mode where consecutively current and voltage

measurements are taken this effectively doubles the needed measurement time at the

setting of 1 PLC.

Since in the presented case the DC current accuracy limits the measurement accuracy the

voltage noise is well in the manageably range. A root mean square read error of 1.5 or 3

microvolt is sufficient for applied minimum voltages 10 – 100 µV whereas 10µV already

accounts for the DC current measurement limit of 10nA.

3.3 Low level current measurements

3.3.1 Leakage current and guarding

Leakage currents can be generated by stray resistance paths between the measurement

circuit and nearby voltage sources. It is therefore crucial to maximise the distance between

the electrometer and the used voltage generator. It is also vital to use good insulators to

avoid charge transfer from the low to the high impedance lead. Another important factor is

the reduction of humidity thus certain insulators absorb water which leads to a higher

conductivity [Keithley et al.(1984)].

One common technique to reduce leakage currents is the utilization of guarding which as a

side effect also reduces the shunt capacitance of the measurement circuit. A guard is a low

impedance point in the circuit that has almost the same potential as the high impedance

lead being guarded [Keithley(1996)]. The Keithley 2010 guard terminal is the low input

terminal.

Figure 3.1: left: An additional guard conductor is used to split the leakage resistance

right: Standard configuration without guard setup

adapted from Keithley – Low Level Measurements [Keithley et al.(1984)]

In the unguarded circuit the full bias voltage appears across the leakage resistance along

the shielded path, resulting in a leakage current along that path that adds to the measured

signal. This parasitic current is mainly due to the insulator between the two measuring wires.

Using a guard connection splits the leakage resistance into two parts resulting in a

considerably lower current. The voltage across the HI and LO terminals of the electrometer

is the voltage burden. The full bias voltage appears across the measurement chamber (here

simplified shown as a resistor) but the leakage current flowing around this loop will not

affect the measurement.


3.3.2 Zero drift and offset currents

Zero drift is a gradual change of the measured signal when no circuitry is attached to the

electrometer. Internal current offsets are caused by bias currents of active devices and

leakage currents through insulators inside the instrument. Fortunately the used

electrometer does provide a compensation for internal zero shifts or offsets (auto zero).

Any constant internal and external zero offset can be nulled by taking a reference

measurement at the beginning and subtracting this value from future measured quantities.

External offset currents can be generated by ionic contamination in the insulators

connected to the electrometer. Another source of unwelcome currents is the triboelectric

effect, where currents can occur due to friction in the cable [Keithley et al.(1984)]. If the

cable is bend and the insulator grinds along the conducting leads, charge imbalances can

be generated and result in a current flowing through the insulator. In standard cables this

effect can reach magnitudes of 1 – 10 nA. The triboelectric effect is thus an error source to

be considered in the present case. It is therefore necessary to fixate the cables mechanically

and control the temperature as an increase in temperature would create thermal expansion

forces.

Error currents also arise from electrochemical effects when ionic chemicals create weak

batteries between two conductors. This effect can occur when the insulating material used

to stabilize the ampullae of Lorenzini in the measurement setup is contaminated with the

surrounding seawater ion content. In combination with a high humidity respectively water

content this can form a conducting path resulting in a decrease of the insulating resistance

or even a conducting path.

3.3.3 Voltage Burden

An electrometer used as ammeter can be represented as an ideal ammeter with no internal

resistance in serial connection with a resistance iR . This resistance causes an additional


voltage drop called the voltage burden. The voltage burden is specified for a full scale input

which is in the case of the Keithley 2010 100fsI mA= (for the 100mA range).

The actual voltage burden can therefore be calculated as follows:

( ) inB in B

fs

IV I VI

⎛ ⎞= ⎜ ⎟⎜ ⎟

⎝ ⎠

Taking this into account the actual measurement error resulting from the voltage burden

can be calculated:

originally corrected currentmeasured value

inin B

fs in

in in

IV VI VI

R Rδ

⎛ ⎞− ⎜ ⎟⎜ ⎟

⎝ ⎠= −

3.3.4 Electrostatic interference and shielding

Electrostatic coupling or interference occurs when an electrically charged object approaches

the measurement setup. To avoid these changes the setup can be shielded using a box or

mesh made of conducting material fully enclosing the sample holder can be used.

The shield is thereby connected to the LO input of the electrometer. The noise present in

cables connecting the voltage source, sample and electrometer can also be reduced by

using shielded cables which are earthed at the LO input of the electrometer.

3.3.5 Temperature effects

The conductivity of ionic compounds like the elasmobranch gel or sea water is highly

dependent on the temperature which makes it essential to measure at thermal equilibrium

where the whole setup is at constant temperature.

Another effect that can arise from different temperatures are thermoelectric EM-fields. If in

a circuit conductors are made up of dissimilar materials that are joined together and

temperature variations are present it is possible that thermoelectric voltages are generated

[Keithley et al.(1984)]. ________________________________________________________________________________________ Michael Winkler University of Otago Postgraduate Diploma in Science Thesis 22 Department of Physics – Electronics Program

Chapter 4

Modifications to inductive perception model

4.1 trajectory analysis

As stated in chapter 2.3.2 M. Paulin assumes that the ampullae of Lorenzini move on a semi

circle like trajectory during the animal’s standard swimming movements. Therefore the

actual amplitude the canal is shifted with respect to the field lines is independent of the

angle between the heading vector and the magnetic field. Thus when the shark heads

parallel to the magnetic field the actual shift sideways is important and not the back and

forth movement which is in this case parallel to the magnetic field.

Due to skeletal restrictions it can be assumed that the shifting amplitude to the sides is

about ten times larger than the back and forth shifting. This results in an elliptically shaped

trajectory for the canal (Figure 4.1).

ϑΔ

2α H

B

1α

Figure 4.1: Top view of the elliptical trajectory of the canal during swimming movements.

The shark’s heading direction is given by H . ϑΔ represents the current deviation of the

velocity vector with respect to the heading direction. The vertical canal is symbolized by the

grey disc.


t

( )v t⊥

B

t ( )v t

Figure 4.2: impact of the velocity oscillation of the canal on voltage induction. Red depicts

the lateral velocity change. Blue refers to the medial velocity oscillation.

At any angle ϑ in the range of 0 to 90° between the heading vector and the magnetic field

both oscillations contribute.

It is also essential to note that the frequency of the medial movement is twice as high as the

actual turning frequency, which can be easily concluded from the trajectory scheme. A turn

from left to right which accounts for half a period of one full turn results in the canal

moving back and forth for a full cycle. Figure 4.2 displays the superposition of the two canal

velocities for an arbitrary heading direction.

These effects can be easily modelled by splitting the term which depends on the velocity

modulation into its sine and cosine part:

Original form by M. Paulin: ( )sin sin( )indV vB tλ α ω ϑ= +

⇒ ( ) ( )( )2 21 2sin sin( )sin sin(2 ) cosindV vB t tλ α ω ϑ α ω ϑ ϑ= + ⋅ +

1α - amplitude of lateral turning movement

2α - amplitude of medial turning movement ( 2 110α α≈ )


To analyze the effect of a ten to one amplitude difference, surface plots with varying

proportions between 1α and 2α are compared:

Figure 4.3: surface plots with different of the generated voltage pattern for each heading

direction relative to the magnetic field.

From the surface plots in figure 4.3 can be deduced that a higher ratio produces a higher

torsion of sine waves into each other. This consecutively results in patterns that contain

increased frequency components when viewed along one heading angle. Considering that

the shark’s movement is rather slow compared to the sensitivity range of its electrosensory

system this may result in a more accurate perception of the geomagnetic input generated

by the swimming movements.

The symmetry of the voltage pattern is not affected thereby conserving its rotational

unambiguous nature. Although the amplitude alignments clearly gain similarity with larger

ratios a slight angular offset of enclosed circular local maxima or minima allows them to be

clearly distinguished from the pattern related to its anti parallel heading direction.

4.2 Modelling perturbations by ocean flows

As stated before it is very unlikely that the elasmobranch is navigating in completely still

standing water. Flows present in the ocean create two major perturbations influencing the

navigational system. Most obviously they generate a constant offset to the shark’s velocity

relative to the earth magnetic field. This generally creates an offset to the amplitude of the

induced voltage, but has negligible effect on navigation as till now it is not known that the

actual measured amplitude of the magnetic field needs to be considered. ________________________________________________________________________________________ Michael Winkler University of Otago Postgraduate Diploma in Science Thesis 25 Department of Physics – Electronics Program

The second more crucial influence of ocean flows is that the moving ion content of sea

water creates an electric field that can impair the navigational sense as stated in chapter

2.3.3.

The perturbation by electric fields only acts on parts of the canal that are aligned parallel to

the electric field. Therefore it is maximal when the angle between the horizontal projection

of the canal and the electric field vector approaches zero and minimal at an angle of 2π .

Following this it is possible to model the generated voltage inside a canal with the following

simple proportionality:

( )0 coselV Eλ ϑ=

Adding the same time dependent oscillation of the canal orientation:

( )( )0 cos sinel eV E tλ α ω ϑ ϕ= + +

As usual eα accounts for the turning amplitude and ω accounts for the turning frequency.

To allow a convenient analysis of the combination of electric and magnetic influences on

the receptor system the angle of the electric field is given relative to the magnetic field

vector whereas ϕ represents the difference between the E and B vector.

The relation between V and V varies in the range of 16 to 90 % [Kalmijn(1974)]. To

qualitatively determine the distortion of electric fields a ratio of 0.9 between the two

voltages is chosen and two cases with

ind el

2πϕ = − and ϕ π= will be reviewed.

Fig 4.4: generated voltage amplitude with electric field influence. Left: 2π− shift of E-vector

relative to magnetic field. Right: π shift of E-vector relative to magnetic field


Even with a high amount of electric field influence the pattern of maxima and minima

remains almost unchanged. Although at a relative angle of 2π− the phase distortion is so

substantial that two peaks are flattened without showing a zero in the gradient.

Nevertheless there are quite significant changes in the absolute amplitude of the generated

voltages. The amplitude pattern is subject to partial inversions.

4.3 Frequency spectrum analysis

The sensitivity of the receptor system is frequency dependent so that it is reasonable to

assume that the elasmobranch can distinguish signals with different frequencies. In the

presented model the frequency pattern is also dependent on the magnitude ratio between

the lateral and medial movement because these two components are enclosed in a sine

function. Taking the Fourier transform of the above voltage patterns reveals the contained

frequencies for each heading direction.


B

Figure 4.5: This plot displays the frequency power spectrum for each heading direction

relative to the magnetic field. The axes are scaled with multiples of the turning frequency.

Amplitude

Figure 4.6: Surface plot of the frequency power spectrum for each heading direction

relative to the magnetic field. It shows essentially the same information given by figure 4.5,

but due to plotting limitations the angular axis is shown separately from the accurate

frequency scaling.

The frequency power spectrum is point symmetric and therefore shows the same pattern

for two heading directions lying oppositely to each other. As the signal is composed of

encapsulated sine functions the frequencies pattern shows a range of harmonics. The

dominant frequency is dependent on which head movement with respect to the magnetic

field has the larger influence on voltage generation. Movement parallel to the field involves

a larger contribution of the signal oscillating with the native velocity oscillation whereas the

perpendicular heading with respect to the magnetic field yields in a larger influence of the

signal generated at twice the velocity oscillation.

It would be expected that the signal frequency pattern behaves similar to the modulation

pattern of the velocity therefore just doubling the frequency. However the dominant

frequency when moving at a 90 degree angle with respect to the magnetic fields yields

amplitude maxima at a fourfold larger frequency. This occurs due to the substantially

different amplitude of the primary canal oscillations. It is also worth noting that at angles of


3π± and ( )3

π π± + a substantial amount of the signal is mapped to a frequency well below

the initial turning frequency.

4.4 Phase spectrum analysis

The absolute value of the Fourier transform discards any phase information present in the

signal. It is therefore significant to also analyze the phase behaviour. Since sudden shifts in

the signal phase can result in a relatively abrupt voltage change which may provide the

elasmobranch with an additional clue to determine its position.

The phase is evaluated taking the absolute signal magnitude into account to set the priority

to the phase signals of the major frequencies. The phase information therefore resolves the

ambiguity of the absolute frequency analysis with respect to the north and south heading.

Figure 4.7: magnitude weighted phase shift. The phase amplitude is normalized by π .

The phase diagram shows a distinct differentiation between a parallel and anti parallel

heading with respect to the magnetic field. This can be clearly concluded by comparing the

phase of two oppositely placed frequencies. While the signal for heading south shows for

example no phase shift, the signal at the same frequency when heading north reveals a

maximum in phase shift. The frequency symmetry for east – west heading directions is ________________________________________________________________________________________ Michael Winkler University of Otago Postgraduate Diploma in Science Thesis 29 Department of Physics – Electronics Program

theoretically also voided by a inverting the phase shift when crossing the magnetic field

axis. However considering that the maximum of phase shift is at π an inversion to a phase

shift of π− in a continuous signal can not be distinguished. Although the ripple happening

at the actual change might provide a clue about the switch from east to west. Nevertheless

a quantitative analysis of the actual phase shift values shows that the absolute value of the

phase is similar, but not identical.

4.5 Influence of electric perturbation on phase and frequency

To analyze the consequences of electric fields a perturbation with the relative magnitude of

90% in reference to the inductive voltage was added to the original signal. Since the electric

field influence is proportional to the cosine of the turning frequency an impact on the

frequency scheme is expected.


E E

B

Figure 4.8: This plot displays the power spectrum weighted phase distribution for each

heading direction relative to the magnetic field.. The angle between B and E is 2π (left

plot) respectively 23π (right plot). A phase ambiguity is marked with red circles in the right

graph.

The general phase pattern is conserved, but phase inversions occur no longer

predominantly at the 2π axis but are observed at a number of angles. The ideal situation

where north can be easily distinguished from a south heading just by the phase of the

signal is no longer valid as paths mirrored at the north-south equator don’t necessarily have

a inversed phase when a electric field is present (Figure 4.8,right).

B

E

Figure 4.9: This plot displays the frequency power spectrum for each heading direction

relative to the magnetic field. The axes are scaled with multiples of the turning frequency.

The interfering electric field is at an angle of 2π .

Secondarily it also changes the amplitude relations between the different frequencies

(Figure 4.9). Surprisingly the perturbation also creates an anti symmetric pattern

perpendicular to the magnetic field at very low frequencies. It especially focuses a

significant amount on the low frequency which may be the result of constructive

interference.


Chapter 5

Dipole Model Approach

5.1 general hypothesis

As reviewed in chapter 2.2.1 the shark gel contains localized anion and cation pairs

surrounded by ordered water. Fundamentally a pair of two counter ions forms an electric

dipole creating a static electric field. The macroscopic movement of ions is inhibited even in

the presence of large electric fields [Hyk and Ciszkowska(1999)]. Nevertheless to change the

influence of the electric field of a dipole it is not necessary to move the ion across large

molecular distances. It is only needed to reverse the position of the ions relative to each

other to achieve a polarity inversion of the generated electric field. Considering the

dimensions of the molecule and ions the change in position is only in the order of

nanometres.

Since the shark is operating in a very low frequency regime and the moving ions therefore

can be treated as a system of slowly varying static dipole moments. The electric field of a

static dipole is given by:

( ) ( )30

14

r pr

φπε

r= ⋅

The canal has a much smaller diameter then length which permits to discard the cross

sectional distribution of dipoles. The point of reception is also always aligned with the canal

making the characterization of the dipole field at other points than the canal end

redundant.

Considering these geometry constraints this equation can be reduced to the one

dimensional case.

With no induced fields the ion pairs have a random distribution and do not contribute. This

changes when an electric field is induced due to the movement in the magnetic field. The


field imposes a directional preference to the orientation of the ion pairs generating a

macroscopic dipole field.

Since the voltage across the canal is not constant in time the dipole field needs to vary in

time as well. Similar to modelling the velocity oscillation a sinusoidal variation can be

applied to the static dipole field:

( ) (20

1 sin4 zz p t

z)φ ω ϕ

πε= + ( ),

1

N

z i zi

p r=

iq= ⋅∑

This potential is dependent on the distance between two ions in the z direction , the

total number of ion pairs in one canal N, the amount of charge carried by the ions and

the overall distance z from the receptor cell. The model is also only accounting for the

dipole field component along the canal.

,i zr

iq

It is likely that an offset ϕ to the actual induced signal due to viscosity may occur

5.2 Opposing mechanism

Like any ordered effect the dipole alignment is influenced by relaxation processes. As in this

case the dipole generation is dependent on the reposition of particles which is influenced

by viscosity and temperature resulting in Brownian motion. Overall this can be described

simplified by a time dependent decay of orientation:

( ) 0

t

p t p e τ−

=

5.3 Considering molecular dipoles of water

The structured water might add a dipole related field since water has a very high molecular

dipole moment. However it is not known how the ordered water is affected by induced

electric fields and the resulting ion movement and therefore possibly just contributes a

static offset.



Chapter 6

Software Interface for digital electrometer

The Keithley 2010 electrometer provides two types of connections to allow for digital read

out of measurement values. It is possible to connect via GPIB the standard interface for

scientific instruments or via the serial port. Since no GPIB terminal was available the read

out had to be realized using the serial port.

6.1 Aspects about used program language

Keithley makes a basic program available to send commands to the device and displays the

output of the electrometer if there is any. This program is coded in Microsoft Visual Basic

6.0 using the mscomm32.ocx library to communicate with the serial port. Unfortunately for

the time planned to interface the electrometer only a version of Microsoft Visual Basic .NET

2002 has been available which does not support the use of this library directly.

Therefore a sample program whose original purpose was to test a modem connected to the

serial port for MS VB.NET has been modified to initialize the COM-port and send

commands to the serial port. One of the major difficulties in the transition from MS VB 6.0

to MS VB.NET where timing issues. The electrometer does not respond instantaneously to

send commands since taking a measurement may need several seconds to finish depending

on the settings.

The internal timer used in the program to clock commands sent to the serial port stopped

checking the serial port after a certain time of inactivity was the common error.

This problem was solved rather inelegant in terms of efficiency and code structure as global

status variables to keep the timer routine alive where used in combination with a

periodically delayed check on the serial port. The delay was implemented as checking for

the serial port as often as possible continuously would lead to a high CPU utilization.

6.2 Implementing a measurement strategy

Since voltage and current need to be measured by the same device an automated switching

algorithm must be implemented. Two different modes were implemented to allow either

the continuous measurement of current followed by a continuous measurement of voltage

(“serial” mode) or an alternating read mode which measures pairs of voltage and current at

the cost of reduced speed (“alternating ” mode). The buffer in electrometer can store a

maximum of 1024 continuously measured samples in its memory. Hence the data transfer

rate of the serial port is limited to 9600 bauds there occurs a substantial delay between two

burst read measurements.

6.3 Graphical user interface

To make changes of the most important settings for the measuring process more

convenient a graphical user interface was designed. It mainly offers control over range and

accuracy settings.

Figure 6.1: Screenshot of the graphical user interface while measuring.



The number of power line cycles determines the aperture of the electrometer and therefore

primarily speed and accuracy. To average over a certain number of samples the filter

function of the electrometer can be enabled. By default a repeat filter is used whose stack

of measurement values is cleared after each averaging cycle.

The program allows either a two or four wire setup whereas the extra cables can be used for

connected to a shield or guard resulting in lower noise. The four wire mode can be used by

enabling the SENSE-terminals so that the shield can be connected to the ground terminal of

the normal inputs.

To account for external voltage offsets it is possible to set a reference value that is

subtracted from all future voltage readings. It is necessary to mention that the reference

value is taken with a direct read command without applying any other changes made

through the program interface beforehand.

The read data is saved in to separate files accompanied by a status file which contains

information about measurement mode, start time and the NPLC setting to reconstruct the

time base and additionally outputs the voltage offset value.

6.4 Programming remarks

The program code produced to interface the electrometer is very linear and not optimized.

Each measurement mode contains a certain number of initialising commands that are just

repeated for each measuring mode (current or voltage, serial or alternating). It was built

with the aim of maximum simplicity to minimize the risk of errors in the line of commands

sent to the electrometer.


Chapter 7

Measurement Setup

7.1 Sample holder design considerations

7.1.1 General design

To allow the measurement of currents and voltages through the canal an electrical connection on

both canal ends which are isolated from each other must be established. While performing

measurements the canal must be fully suspended in a solution that inhibits cell decay and

simulates the regular biological environment of the tissue. This might not be critical as

experiments examining membrane interaction in the receptor cells by J. Lu and H. Fishman where

carried out with an air gap between the two suspended ends [Lu and Fishman(1994)]. Besides that

they also measured at room temperature which would certainly affect the electrical properties of

the canal.

As it is not possible to contact the filigree ends of the canal directly with a wire only an indirect

conduction mechanism can be applied. It is a very well established method to use sea water

electrodes as the electrical properties of sea water are well known and easy to control.

Furthermore it also simulates the natural conditions for one end of the canal.

This design approach basically leads to a three chamber design. The outer two chambers are filled

with seawater and allow for the electrical conduction of the canal that is mounted through holes

in the two barriers.

7.1.2 Geometry constraints

The measurements shall be performed on ampullary canals dissected from dogfish (Squalus

Acanthias) that are held at the Portobello Research Station of the University of Otago, New

Zealand. The average length was expected to be in the range of 2 to 5 cm. The sample holder was

designed to be as adaptable as possible to allow measurements of all samples without

misspending material due to the adjustment to a fixed sample holder length. Therefore both

canal mountings are shiftable: One end with a fixed ratio of 1 cm per step and the second one

allowing for continuous adjustments in a smaller range.

Aiming for a maximum of flexibility for future measurements the sample holder was designed to

allow measurements of Ampullae of Lorenzini with a maximum length of 10cm which should be

ample for a wide range of shark and ray species.

The mounting of the canal in the sample holder is the most critical part as the canal is rather

flexible and easy to compress altering the geometry of the canal which must be preserved.

With an average diameter of only 1mm direct clamping is impossible. Following design ideas of B.

Waltmann the canal is embedded in a viscous isolating medium at both ends. In the current setup

Vaseline was used. Vaseline is a petroleum jelly made up of semi solid saturated hydrocarbons

with mainly paraffinic nature ( 2 2n nC H + ).

The cylindrical cavity in the sample mounts has a diameter of 3mm to minimize the influence of

the Vaseline and a length of 5mm to provide enough friction to preserve vertical orientation.

7.1.3 Solidworks model

The final model of the sample holder was modelled in the 3D CAD program SolidWorks™ and

manufactured by the mechanics workshop in the Physics Department at University of Otago.

As a compromise between high resistivity and good manufacturability acrylic glass has been

chosen to build the sample holder. The sample holder offers a range of sequence of M3 threads

on each side to mount electrodes on them.


Figure 7.1: isometric perspective of the designed sample holder

The assembly consists of five parts in total whereas the four components forming the two

boundaries are fitted tightly into the vessel. Complete insulation at the crevices is again achieved

by using Vaseline. Due to the ability to be continuously shifted the second boundary components

are less stable in their position. This is countered with two threads which make it possible to

combine the upper and lower part of the canal mount.


7.2 Measurement schematics

7.2.1 Voltage source

The necessary voltage ranges between 1µV and 100 µV. To achieve a low noise voltage signal the

output of a function generator is supplied to a voltage divider consisting of a six decade resistor

network which is wired up with shielded BNC connectors. The voltage is transformed down to

either times the input value at output 1 or to 510− 410− times the input value at output 2. Whereas

output 1 refers to a connection between pin 1 and pin 2 and output 2 refers to a connection

between pin 1 and pin 3 of the schematic show in figure 7.2. A voltmeter and loading to either of

the outputs can be connected simultaneously.

Figure 7.2.: schematic of resistor network used to downgrade the input voltage.

Considering the specifications of the resistor network thermal EMFs are negligibly low with only

0.1µVC° . The shift with temperature is about 10m± Ω for the 100Ω step and about for the

considering a measurement at room temperature which results in only minor voltage

variations. In general the shift of resistance during the measurement should not cause any

noticeable voltage drifts. All numbers are obtained from the corresponding data sheet

[Vishay(2001)].

0.1± Ω

1000Ω


7.2.2 Setup diagram

Figure 7.3: measurement setup and schematic wiring.

All cables are shielded with a common ground conductor and connected via coax connectors to

the signal source and voltage divider terminal. Hence the electrometer offers only banana plug

type connectors, cables were manufactured to establish a contact. The common shield for the

ammeter cables was soldered together in vicinity of the banana plugs.


7.3 Fabricating electrodes

It is essential to establish a low resistance interface between the sea water and the electrodes.

To create a proper conducting junction between the copper lead and the seawater in which the

canal end is submerged silver wire is used. Silver chloride electrodes convert ionic currents in

solutions to an electric current within a wire [WarnerInstruments()]. The provided silver wire had

an insulating Teflon coating which had to be removed prior to the use. Following the silver wire

was chlorided through bathing in sodium hypochlorid ( ) for about 20 minutes. NaClO

Ag Cl AgCl e+ − −+ ← −−→ +

redox reaction creating silver chloride

A drawback of silver chloride electrodes is the development of a potential at the electrode surface

due to the electrochemical potential of AgCl and Cl − ions. A voltage bias dependent on the

chloride ion concentration at the electrode will occur which may lead to a shift of the present

voltage over time during the measurement [WarnerInstruments()].


Chapter 8

Experimental Realization

8.1 Zero level evaluation The first Step to allow a quantitative estimate of the electrical properties is to determine the

actual resolution of the setup. As we are limited by the accuracy of the ammeter function of

the electrometer the maximum accuracy is at about 10nA. Resolving the necessary voltage

values to achieve that magnitude of currents is no issue as they range at several microvolts.

The Auto-zero function the electrometer was always turned on so that internally generated

currents are negligible. A null measurement was performed with all cables connected and

the function generator turned on, but with disabled output. The Electrodes were emerged

in salt water but no piece of conducting media was connecting them.

0 100 200 300 400 500 600

-10

-8

-6

-4

-2

0

2

4

6

8

10

0

1

2

3

4

5

6

7

8

9

10 current variation

Cur

rent

[nA

]

t im e [s]

voltage

Vol

tage

[µV

]

Figure 8.1: null measurement of current variation and voltage. No conductive link between

electrodes.


The measured signal shown in figure 8.1 is cleared from a constant offset at approximately

-30nA. The signal itself exhibits quite significant noise, but the mean value over time is

acceptably constant. Since the voltage signal is not critical concerning accuracy it is only

plotted in a low vertical resolution.

Error estimation:

The simplest way of expressing the average variance of the measurement signal is the mean

standard deviation:

( )2

1

1 2.9N

I ii

I I nN

σ=

= − =∑ A

Based on this expression the standard error of the mean value is given by the following

equation:

, 0.14IE Is n

NAσ

= =

These values are remarkably small and would make it theoretically possible to well

differentiate signals that are more than 5nA apart from each other. Although considering

that the exponential fit may vary with magnitude of the measured signal it is advisable to

only consider differences of 10nA or more as measurable. The preceding is also based on

the fact that Keithley states an accuracy of only 10nA.


8.2 Conductivity estimate

To calibrate the setup for measuring properties of unknown substances a measurement of a

Teflon tubed seawater sample was used. Teflon is highly insulating and the used tubed

approximated the dimensions of the canal reasonably accurate with 1mm wall thickness.

Hence the conductivity of seawater is reasonably well known for different values of salinity

and temperatures the expected resistance taking the tube geometry into account can be

calculated in a very simple manner:

1 lR A

σρ

= =⋅

⇒U lRI Aσ

= =

σ - conductivity ρ - resisitivity A - cross-sectional area of the tube

l - canal length - measured voltage respectively current /U I

Temperature [°C] Salinity [ g / kg ]

20 25 30 35 40

Conductivity [S / m]

5 2.015 2.466 2.523 3.346 3.778

10 2.300 2.811 2.909 3.808 4.297

15 2.595 3.170 3.313 4.290 4.837

20 2.901 3.542 3.735 4.788 5.397

25 3.217 3.926 4.171 5.302 5.974

Chart 8.1: sea water conductivity in dependence of temperature and salinity [Bullard(2007)]

The average conductivity of the ocean is approximately 3.27 S/m [Bullard(2007)]. To reach

that level with a artificially prepared sodium chloride solution at a temperature of 20°C a

salinity of 22.5 g/kg was chosen resulting in a conductivity of 3.22 S/m. Using the given

equation for the expected resistance consequential delivers . At a typical

voltage of 80µV for the current setup this would yield in a current of approximately 5nA.

15.5R k= Ω



Figure 8.2: current and voltage values for different input voltages. (Note: DC input value is

the signal fed into the voltage divider. The actual voltage across the canal can be obtained

from the graph)

As shown in figure 8.2 the current measurement shows an initial exponential decay that was

reproducible throughout various setups. The slope of the decay was relatively constant

throughout a series of measurements so that it is possible to remove this systematic current

drift. The original data has been fitted with a first order exponential decay.

0 100 200 300 400 500 600

-35-30-25-20-15-10-505

101520253035

40

45

50

55

60

65

70

75

80

85 current @ 0V DC Input current @ 2V DC Input current @ 4V DC Input exponential fits linear fit

Cur

rent

[nA

]

time [s]

applied voltage @ 4V DC Input applied voltage @ 2V DC Input

Vol

tage

[µV

]

The difference between the zero signal and the calculated offset of the exponential fit at

infinity for the measurement with 4V yields in an absolute current value of 14.4nA. With an

applied voltage value of 41µV and measured canal length of 72mm the conductivity can be

calculated to approximately 13.6 S/m. Following the same method for the 2V input signal

yields in a value of 17.5 S/m (effective current value: 9.2nA).

8.3 Alternating Current measurements

Since measurements in direct current mode are likely to produce electrode or sample

polarisation it is recommendable to also conduct measurements with a sinusoidally varying

input. Normally it is also possible to record the phase shift and therefore acquire

information about the capacitive or inductive behaviour of the sample. However this would

require recording the input signal of the frequency generator which was not implemented.


0 100 200 300 400 500 600

-6.0x10-8

-5.5x10-8

-5.0x10-8

-4.5x10-8

-4.0x10-8

-3.5x10-8

-3.0x10-8

-1.0x103

-5.0x102

0.0

5.0x102

1.0x103

current peak fit

Cur

rent

[A]

time [s/2]

voltage

Vol

tage

[µV

]

Figure 8.3: Recorded current and voltage signal for an input frequency of 100mHz,

recorded with 5 PLC setting. Input voltage: 10Vpp

The most noticeable fact obtained from the diagram above is the inconsistent phase

behaviour of the current signal. Unfortunately this is due to different internal delays of the

electrometer when measuring current respectively voltage. As a result the two signals occur

at different frequencies. To bring both signals in phase the time base of the voltage signal

was modified (Figure 8.4). The difference in period is about 25% and may occur due to the

SENSE – terminal use as this phenomenon could not be observed using the normal voltage

input terminals

-

60

55

50

45

40

35

30

______________________ ____________________ Michael Winkler University of Otago Postgraduate Diploma in Science Thesis 48 Department of Physics – Electronics Program

______________________________________________

0 50 100 150 200 250 300

-

-

-

-

-

-

-1.0

-0.8

-0.6

-0.4

-0.2

0.0

0.2

0.4

0.6

0.8

1.0

Cur

rent

[nA

]

time [s]

Vol

tage

[mV

] Figure 8.4: Recorded current and voltage signal for an input frequency of 100mHz; time

base of voltage signal has been uniformly extended. The linear plot shows the varying

offset.

Since both signals were measured in succession a constant phase shift is expected. The

conductivity can be calculated taking current and voltage values that have the same phase.

As readings with higher amplitude show less noise the peak current values were extracted

and averaged.

Current [nA] Current [nA] Current [nA] Time

[s] Offset

Time [s]

Offset

Time [s]

Offset 12.75 -34.7 -44.02 129.75 -38,4 -45.76 249 -39.2 -47.54

36 -34.9 -44.36 153 -39,5 -46.15 272 -41.1 -47.89 59.25 -37.5 -44.71 177 -38.4 -46.49 297 -44 -48.27 83.25 -36.3 -45.09 201.5 -39.5 -46.48 106.5 -38.7 -45.44 223.5 -35.7 -47.19

Chart 8.2: peak current values and according offset. Using the current values stated in chart 8.2 and setting the voltage to 1mV as its variation is

negligible the average conductivity can be calculated.

( )

13

1

1 0.608 0.1313

Smi Offset

i

l I IAU

σ=

= ⋅ − = ±∑


Chapter 9

Discussion

The presented analysis of a navigational model gives an insight on which systematic

clues are available to the shark through its electrosensory system that could aid the

animal in navigation. Despite the existence of heading ambiguities due to symmetry

in the individual components (amplitude, frequency and phase) an elasmobranch

might very well be in the position to accurately estimate by combining these clues

with a variation in speed or swimming direction. This process may be similar to the

visual equivalent of looking into several directions, recognising patterns, comparing

these with stored memories and from that determining the position.

Most of the presented symmetries and ambiguities occur due to the simplicity of the

involved model which is merely based on linear trigonometric relations. Non linear

field perturbations resulting from turbulences along the shark’s surface as well as the

spatial extent of the body alter the surrounding electric field.

Till now no behavioural experiments about directional phase differentiation or specific

frequency pattern sensitivity have been conducted. Therefore the estimate of a

navigational aid due to the presented features is still to be proven. Furthermore the

fact that sharks approach a local dipole field on trajectories that follow a constant

gradient in field strength [Kalmijn(2000)] is not accounted for in the modelling

approach.

The brief analysis of the electric perturbation to the magnetic signal seems to obscure

the determination the position to a kind of reference frame. However constant major

ocean flows provide an invariant electric field so that the cognitive map used for

navigation may just be based on both influences.

The accuracy of the developed setup is high enough to allow measurements close to

biologic environments. Although to get reasonable good noise ratios it is still

necessary to increase the applied fields by at least 3 orders of magnitude compared

to the sensitivity floor of the animals ( µVcm versus nV

cm ).

Furthermore the measured conductivity value at the desired current and voltage

values deviates from the expected values by a factor of 5 for direct current

measurements. It is likely that the interface between the electrodes and seawater

causes the problem as the involved soldering or chloriding may exhibit defects or

other abnormalities. It may therefore be necessary for future measurements to clamp

the electrodes or solder with a grease free type of soldering tin.

It is also worth mentioning that the chlorided silver electrodes degrade relatively fast

and return to their original unchlorided state resulting in reduced conductivity.

Apparently the silver – silver chloride junction seems to develop a potential distorting

the measured signal.

The measurement of conductivity with a slowly varying input signal at considerably

higher amplitude should be less affected by current shifts or effects of surface

polarisation. Due to the higher input amplitude the signal noise ratio is also better.

Consequently the calculated conductivity should be more reliable and accurate.

Nonetheless the resulting conductivity is smaller by a factor of approximately five.



Chapter 10

Perspective on future research

The provided frequency schematic can be utilized to determine the actual frequencies

perceived by any kind of elasmobranch performing sinusoidal movements along its

swimming path. To achieve an accurate quantitative estimate only the swimming velocity

and turning frequency must be recorded. Nonetheless both the canal geometry as well as

the real trajectory of the canal have a large influence on the actual generated amplitude.

In cooperation with the Zoology Department of the University of Otago measurements on

complete intact specimen of ampullae dissected from dogfish head might be performed

using the presented setup. Although the current and voltage recordings might be carried

out using equipment provided by the Zoology Department in favour for higher resolution.

Transferring the setup would then also allow measuring in a temperature controlled

environment which is crucial as Waltmann states the irreversible alteration of properties

when the canal is heated above critical temperature [Waltmann(1966)].

To simulate the interaction of a cluster of ampullae the orientation for each canal can be

slightly varied and added to a superimposed voltage pattern. As the frequency pattern

should not differ the analytic effort for the elasmobranch does not change.

Taking the spatial distribution of vertically oriented ampullae into account may however

result in a frequency shift as the turning amplitude ratio changes due to the shape of the

trajectory.

To further differentiate the generated voltage pattern it may also be necessary to account

for vertical head movements as elasmobranches are also known to vary their pitch. This may

cause a variation in the frequency pattern.


Chapter II

Bibliography [Bromm et al.(1976)] Bromm, Hensel, and Tagmat] B. Bromm, H. Hensel, and A. Tagmat, “The Electrosensitivity of the isolated ampulla of lorenzini in the dogfish”, Journal of Comparative Physiology A: Sensory, Neural, and Behavioural Physiology, vol. 111, no. 2, pp. 127–136, 1976. [Brown(2002)] B. Brown, “Modeling an electrosensory landscape behavioral and morphological optimization in elasmobranch prey capture”, Journal of Experimental Biology, vol. 205, no. 7, pp. 999–1007, 2002. [Brown et al.(2002)] B. Brown, J. Hutchison, M. Hughes, D. Kellogg, and R. Murray, “Electrical characterization of gel collected from shark electrosensors”, Physical Review E, vol. 65, no. 6, p. 61903, 2002. [Brown(2005)] B. Brown, M. Hughes, and C. Russo, “Infrastructure in the electric sense: admittance data from shark hydrogels”, Journal of Comparative Physiology A: Sensory, Neural, and Behavioral Physiology, vol. 191, no. 2, pp. 115–123, 2005. [Bullard(2007)] S. E. Bullard, “2.7.9 Physical properties of sea water, http://www.kayelaby.npl.co.uk/general physics/2 7/2 7 9.html”, National Physical Laboratory - Kaye and Laby, 2007. [Ciszkowska and Guillaume(1999)] M. Ciszkowska and M. Guillaume, “Transport of Ions and Molecules in Biopolymeric Gels: Electroanalytical Studies”, Journal of Physical Chemistry A, vol. 103, no. 5, pp. 607–613, 1999. [Collin and Whitehead(2004)] S. Collin and D. Whitehead, “The functional roles of passive electroreception in non-electric fishes”, Animal Biology (formerly Netherlands Journal of Zoology), vol. 54, no. 1, pp. 1–25, 2004. [Hyk and Ciszkowska(1999)] W. Hyk and M. Ciszkowska, “Studies of Transport Phenomena and Electrostatic Interactions in Polyacrylate Gels,” Journal of Physical Chemistry B, vol. 103, no. 31, pp. 6466–6474, 1999. [Kajiura(2001)] S. Kajiura, “Head Morphology and Electrosensory Pore Distribution of Carcharhinid and Sphyrnid Sharks”, Environmental Biology of Fishes, vol. 61, no. 2, pp. 125–133, 2001.


[Kalmijn(1971)] A. KALMIJN, “The Electric Sense of Sharks and Rays”, Journal of Experimental Biology, vol. 55, no. 2, pp. 371–383, 1971. [Kalmijn (1973)] A. Kalmijn, “Electro-orientation in sharks and rays: theory and experimental evidence”, Scripps Institution of Oceanography Reference Series, Contribution, pp. 73–39, 1973 [Kalmijn(1974)] A. Kalmijn, “The detection of electric fields from inanimate and animate sources other than electric organs”, Handbook of Sensory Physiology, vol. 3, p. 3, 1974. [Kalmijn(2000)] A. Kalmijn, “Detection and processing of electromagnetic and nearfield acoustic signals in elasmobranch fishes,” Philosophical Transactions: Biological Sciences, vol. 355, no. 1401, pp. 1135–1141, 2000. [Keithley(1996)] Keithley, “2010 Multimeter User’s Manual, Rev. D”, Keithley Instruments, 1996. [Keithley et al.(1984)] J. Keithley, J. Yeager, and R. Erdman, “Low Level Measurements: For Effective Low Current, Low Voltage, and High Impedance Measurements”, Keithley Instruments, 1984. [Klimley(1993)] A. Klimley, “Highly directional swimming by scalloped hammerhead sharks, Sphyrna lewini, and subsurface irradiance, temperature, bathymetry, and geomagnetic field,” Marine Biology, vol. 117, no. 1, pp. 1–22, 1993. [Lu and Fishman(1994)] J. Lu and H. Fishman, “Interaction of apical and basal membrane ion channels underlies electroreception in ampullary epithelia of skates,” Biophysical Journal, vol. 67, no. 4, pp. 1525–1533, 1994. [Murray(1957)] R. Murray, “Evidence for a Mechanoreceptive Function of the Ampullæ of Lorenzini”, Nature, vol. 179, no. 4550, pp. 106–107, 1957. [Murray(1960)] R. Murray, “Electrical sensitivity of the ampullae of Lorenzini,” Nature, vol. 187, no. 4741, p. 957, 1960. [MURRAY(1962)] R. MURRAY, “The Response of the Ampullae of Lorenzini of Elasmobranchs to Electrical Stimulation,” Journal of Experimental Biology, vol. 39, no. 1, pp. 119–128, 1962. [Murray(1974)] R. Murray, “The ampullae of Lorenzini”, Handbook of Sensory Physiology, vol. 3, p. 3, 1974. [New(1997)] J. New, “The evolution of vertebrate electrosensory systems”, Brain Behaviour Evolution, vol. 50, no. 4, pp. 244–52, 1997. [Paulin(1995)] M. Paulin, “Electroreception and the compass sense of sharks”, Journal of Theoretical Biology, vol. 174, no. 3, pp. 325–339, 1995.


[Sand(1938)] A. Sand, “The Function of the Ampullae of Lorenzini, with some Observations on the Effect of Temperature on Sensory Rhythms,” Proceedings of the Royal Society of London. Series B, Biological Sciences, vol. 125, no. 841, pp. 524–553, 1938. [Sisneros and Tricas(2000)] J. Sisneros and T. Tricas, “Androgen-Induced Changes in the Response Dynamics of Ampullary Electrosensory Primary Afferent Neurons”, Journal of Neuroscience, vol. 20, no. 22, p. 8586, 2000. [Sisneros et al.(1998)] J. Sisneros, T. Tricas, and C. Luer, “Response properties and biological function of the skate electrosensory system during ontogeny”, Journal of Comparative Physiology A: Sensory, Neural, and Behavioral Physiology, vol. 183, no. 1, pp. 87–99, 1998. [Vishay(2001)] Vishay, “CNS471 - Decade Divider, Single-In-Line Thin Film Resistor Networks (Standard),” 2001. [Waltmann(1966)] B. Waltmann, “Electricalproperties and fine structure of the ampullary canals of lorenzini”, Acta Physiologica Scandinavica, vol. 66, no. 264, 1966. [WarnerInstruments()] WarnerInstruments, “Bilayer Clamp Amplifier – Model BC-535”, BC-535 Preliminary, Rev. 060126. [Zakon(1986)] H. Zakon, “The electroreceptive periphery,” Electroreception (Bullock TH, Heiligenberg W, eds), pp. 103–156, 1986.


Appendix A

VB. Net subroutine handling file outputof received characters ' This subroutine is fired when the timer event is raised. It writes whatever ' is in the Comm Port buffer to the output window. Private Sub tmrReadCommPort_Tick(ByVal sender As System.Object, ByVal e As System.EventArgs) Handles tmrReadCommPort.Tick Try ' As long as there is information, read one byte at a time and ' output it. Dim stream As Byte While (m_CommPort.Read(1) <> -1) 'Write the output to the screen. stream = m_CommPort.InputStream(0) 'WriteMessage(Chr(stream), False) ' can be enabled for debug output 'handling non numerical characters If Me.Measurement_status = 1 Then Select Case stream Case 44 Me.current_write.Write(Chr(13)) Case 19, 17 Case 13 Me.Measurement_status = 0 Me.pnlMeasurementInProgress.Text = "measurement finished" Me.pnlMeasurementInProgress.ForeColor = ForeColor.Gray Case Else Me.current_write.Write(Chr(stream)) End Select Else If Me.Measurement_status = 2 Then Select Case stream Case 44 Me.voltage_write.Write(Chr(13)) Case 19, 17 Case 13 Me.Measurement_status = 0 Me.pnlMeasurementInProgress.Text = "measurement finished" Me.pnlMeasurementInProgress.ForeColor = ForeColor.Gray Case Else Me.voltage_write.Write(Chr(stream)) End Select ElseIf Me.Measurement_status = 3 Then Select Case stream Case 19, 17 Case 13, 44 Me.Measurement_status = 0 Case Else Me.offset = Me.offset + Chr(stream) End Select End If End If End While Catch exc As Exception ' An exception is raised when there is no information to read. ' Don't do anything here, just let the exception go. End Try End Sub


Appendix B

VB. Net measurement routine 'measurement routine Private Sub btnStartMeasurement_Click(ByVal sender As System.Object, ByVal e As System.EventArgs) Handles btnStartMeasurement.Click ' write status information into file Me.status_write = Me.status_file.CreateText(Me.StatusDataFile.Text) Me.status_write.WriteLine("time: " + "{0,8:HH:mm:ss}", Now()) Me.status_write.WriteLine("date: " + "{0,10:dd.MM.yyyy}", Now()) Me.status_write.WriteLine("measuring mode: " + MeasuringMode.SelectedItem.ToString()) Me.status_write.WriteLine("NPLC setting: " + Me.txtNPLC.Text) Me.status_write.WriteLine("Voltage Offset: " + Me.offset) Me.status_write.Close() If Me.MeasuringMode.SelectedIndex = 1 Then 'measuring in serial mode 'CURRENT MEASUREMENT Me.Measurement_status = 1 Try ' Enable the timer. Me.tmrReadCommPort.Enabled = True ' Attempt to open the port. m_CommPort.Open(m_ModemPort, 9600, 8, Rs232.DataParity.Parity_None, Rs232.DataStopBit.StopBit_1, 4096) m_CommPort.Write(Encoding.ASCII.GetBytes("*RST" & Chr(13))) m_CommPort.Write(Encoding.ASCII.GetBytes("*CLS" & Chr(13))) m_CommPort.Write(Encoding.ASCII.GetBytes(":INIT:CONT OFF" & Chr(13))) ' disable continous trigger m_CommPort.Write(Encoding.ASCII.GetBytes(":ABORT" & Chr(13))) ' reset trigger system m_CommPort.Write(Encoding.ASCII.GetBytes(":SENS:FUNC 'CURR:DC'" & Chr(13))) ' set function m_CommPort.Write(Encoding.ASCII.GetBytes(":SYST:AZER:STAT ON" & Chr(13))) ' control autozero ' control filter If Me.chkEnableFilter.Checked = True Then m_CommPort.Write(Encoding.ASCII.GetBytes(":SENS:CURR:DC:AVER:STAT ON" & Chr(13))) m_CommPort.Write(Encoding.ASCII.GetBytes(":SENS:CURR:DC:AVER:COUN " + Me.txtFilterCount.Text & Chr(13))) Else m_CommPort.Write(Encoding.ASCII.GetBytes(":SENS:CURR:DC:AVER:STAT OFF" & Chr(13))) End If m_CommPort.Write(Encoding.ASCII.GetBytes(":SENS:CURR:DC:NPLC " + Me.txtNPLC.Text & Chr(13))) ' control range If Me.chkEnableAutoCurrent.Checked = True Then m_CommPort.Write(Encoding.ASCII.GetBytes(":SENS:CURR:DC:RANG:AUTO ON" & Chr(13))) Else m_CommPort.Write(Encoding.ASCII.GetBytes(":SENS:CURR:DC:RANG:AUTO OFF" & Chr(13))) m_CommPort.Write(Encoding.ASCII.GetBytes(":SENS:CURR:DC:RANG " + Me.txtCurrentRange.Text & Chr(13))) End If m_CommPort.Write(Encoding.ASCII.GetBytes(":SENS:CURR:DC:DIG 8" & Chr(13))) ' control accuracy


m_CommPort.Write(Encoding.ASCII.GetBytes(":FORM:ELEM READ" & Chr(13))) ' format elements m_CommPort.Write(Encoding.ASCII.GetBytes(":TRIG:COUN 1" & Chr(13))) ' control trigger m_CommPort.Write(Encoding.ASCII.GetBytes(":SAMP:COUN " + Me.txtReadValues.Text & Chr(13))) 'burst read m_CommPort.Write(Encoding.ASCII.GetBytes(":TRIG:DEL 0" & Chr(13))) ' control trigger delay m_CommPort.Write(Encoding.ASCII.GetBytes(":TRIG:SOUR IMM" & Chr(13))) ' control trigger source ' Sleep long enough for the electrometer to respond and the timer to fire. System.Threading.Thread.Sleep(1000) m_CommPort.Write(Encoding.ASCII.GetBytes(":READ?" & Chr(13))) System.Threading.Thread.Sleep(200) ' File Setup Me.current_write = Me.current_file.CreateText(Me.CurrentDataFile.Text) Me.pnlMeasurementInProgress.ForeColor = ForeColor.Red Me.pnlMeasurementInProgress.Text = "measurement in progress" While Me.Measurement_status = 1 System.Threading.Thread.Sleep(500) Application.DoEvents() End While 'VOLTAGE MEASUREMENT Me.Measurement_status = 2 m_CommPort.Write(Encoding.ASCII.GetBytes("*RST" & Chr(13))) m_CommPort.Write(Encoding.ASCII.GetBytes("*CLS" & Chr(13))) m_CommPort.Write(Encoding.ASCII.GetBytes(":INIT:CONT OFF" & Chr(13))) ' disable continous trigger m_CommPort.Write(Encoding.ASCII.GetBytes(":ABORT" & Chr(13))) ' reset trigger system m_CommPort.Write(Encoding.ASCII.GetBytes(":SENS:FUNC 'VOLT:DC'" & Chr(13))) ' set function m_CommPort.Write(Encoding.ASCII.GetBytes(":SYST:AZER:STAT ON" & Chr(13))) ' control autozero ' control filter If Me.chkEnableFilter.Checked = True Then m_CommPort.Write(Encoding.ASCII.GetBytes(":SENS:VOLT:DC:AVER:STAT ON" & Chr(13))) m_CommPort.Write(Encoding.ASCII.GetBytes(":SENS:VOLT:DC:AVER:COUN " + Me.txtFilterCount.Text & Chr(13))) Else m_CommPort.Write(Encoding.ASCII.GetBytes(":SENS:VOLT:DC:AVER:STAT OFF" & Chr(13))) End If m_CommPort.Write(Encoding.ASCII.GetBytes(":SENS:VOLT:DC:NPLC " + Me.txtNPLC.Text & Chr(13))) ' control range If Me.chkEnableAutoVolt.Checked = True Then If Me.chkSENSEterminals.Checked = True Then m_CommPort.Write(Encoding.ASCII.GetBytes(":SENS:VOLT:DC:TERM SENS" & Chr(13))) m_CommPort.Write(Encoding.ASCII.GetBytes(":SENS:VOLT:DC:STER:RANG:AUTO ON" & Chr(13))) Else m_CommPort.Write(Encoding.ASCII.GetBytes(":SENS:VOLT:DC:RANG:AUTO ON" & Chr(13))) End If Else If Me.chkSENSEterminals.Checked = True Then m_CommPort.Write(Encoding.ASCII.GetBytes(":SENS:VOLT:DC:TERM SENS" & Chr(13)))


m_CommPort.Write(Encoding.ASCII.GetBytes(":SENS:VOLT:DC:STER:RANG:AUTO OFF" & Chr(13))) m_CommPort.Write(Encoding.ASCII.GetBytes(":SENS:VOLT:DC:STER:RANG " + Me.txtVoltageRange.Text & Chr(13))) Else m_CommPort.Write(Encoding.ASCII.GetBytes(":SENS:VOLT:DC:RANG:AUTO OFF" & Chr(13))) m_CommPort.Write(Encoding.ASCII.GetBytes(":SENS:VOLT:DC:RANG " + Me.txtVoltageRange.Text & Chr(13))) End If End If 'control offset If Me.chkVoltRef.Checked = True Then If Me.chkSENSEterminals.Checked = True Then m_CommPort.Write(Encoding.ASCII.GetBytes(":SENS:VOLT:DC:STER:REF " + Me.offset & Chr(13))) m_CommPort.Write(Encoding.ASCII.GetBytes(":SENS:VOLT:DC:STER:REF:STAT ON" & Chr(13))) Else m_CommPort.Write(Encoding.ASCII.GetBytes(":SENS:VOLT:DC:REF " + Me.offset & Chr(13))) m_CommPort.Write(Encoding.ASCII.GetBytes(":SENS:VOLT:DC:REF:STAT ON" & Chr(13))) End If Else If Me.chkSENSEterminals.Checked = True Then m_CommPort.Write(Encoding.ASCII.GetBytes(":SENS:VOLT:DC:TERM SENS" & Chr(13))) m_CommPort.Write(Encoding.ASCII.GetBytes(":SENS:VOLT:DC:STER:REF:STAT OFF" & Chr(13))) Else m_CommPort.Write(Encoding.ASCII.GetBytes(":SENS:VOLT:DC:REF:STAT OFF" & Chr(13))) End If End If m_CommPort.Write(Encoding.ASCII.GetBytes(":SENS:VOLT:DC:DIG 8" & Chr(13))) ' control accuracy m_CommPort.Write(Encoding.ASCII.GetBytes(":FORM:ELEM READ" & Chr(13))) ' format elements m_CommPort.Write(Encoding.ASCII.GetBytes(":TRIG:COUN 1" & Chr(13))) ' control trigger m_CommPort.Write(Encoding.ASCII.GetBytes(":SAMP:COUN " + Me.txtReadValues.Text & Chr(13))) 'burst read m_CommPort.Write(Encoding.ASCII.GetBytes(":TRIG:DEL 0" & Chr(13))) ' control trigger delay m_CommPort.Write(Encoding.ASCII.GetBytes(":TRIG:SOUR IMM" & Chr(13))) ' control trigger source ' Sleep long enough for the electrometer to respond and the timer to fire. System.Threading.Thread.Sleep(1000) m_CommPort.Write(Encoding.ASCII.GetBytes(":READ?" & Chr(13))) System.Threading.Thread.Sleep(200) Me.voltage_write = Me.voltage_file.CreateText(Me.VoltageDataFile.Text) Me.pnlMeasurementInProgress.ForeColor = ForeColor.Red Me.pnlMeasurementInProgress.Text = "measurement in progress" While Me.Measurement_status = 2 System.Threading.Thread.Sleep(500) Application.DoEvents() End While Application.DoEvents()


m_CommPort.Write(Encoding.ASCII.GetBytes(":SYST:LOC" & Chr(13))) m_CommPort.Close() Catch ex As Exception ' Warn the user. MessageBox.Show("Unable to communicate with device") Finally ' Disable the timer + close files Me.tmrReadCommPort.Enabled = False Me.current_write.Close() Me.voltage_write.Close() End Try Else Try ' Enable the timer. Me.tmrReadCommPort.Enabled = True m_CommPort.Open(m_ModemPort, 9600, 8, Rs232.DataParity.Parity_None, Rs232.DataStopBit.StopBit_1, 4096) m_CommPort.Write(Encoding.ASCII.GetBytes("*RST" & Chr(13))) m_CommPort.Write(Encoding.ASCII.GetBytes("*CLS" & Chr(13))) m_CommPort.Write(Encoding.ASCII.GetBytes(":INIT:CONT OFF" & Chr(13))) ' disable continous trigger m_CommPort.Write(Encoding.ASCII.GetBytes(":ABORT" & Chr(13))) ' reset trigger system m_CommPort.Write(Encoding.ASCII.GetBytes(":SENS:FUNC 'CURR:DC'" & Chr(13))) ' set function m_CommPort.Write(Encoding.ASCII.GetBytes(":SYST:AZER:STAT ON" & Chr(13))) ' control autozero ' control filter If Me.chkEnableFilter.Checked = True Then m_CommPort.Write(Encoding.ASCII.GetBytes(":SENS:CURR:DC:AVER:STAT ON" & Chr(13))) m_CommPort.Write(Encoding.ASCII.GetBytes(":SENS:CURR:DC:AVER:COUN " + Me.txtFilterCount.Text & Chr(13))) Else m_CommPort.Write(Encoding.ASCII.GetBytes(":SENS:CURR:DC:AVER:STAT OFF" & Chr(13))) End If m_CommPort.Write(Encoding.ASCII.GetBytes(":SENS:CURR:DC:NPLC " + Me.txtNPLC.Text & Chr(13))) ' control range If Me.chkEnableAutoCurrent.Checked = True Then m_CommPort.Write(Encoding.ASCII.GetBytes(":SENS:CURR:DC:RANG:AUTO ON" & Chr(13))) Else m_CommPort.Write(Encoding.ASCII.GetBytes(":SENS:CURR:DC:RANG:AUTO OFF" & Chr(13))) m_CommPort.Write(Encoding.ASCII.GetBytes(":SENS:CURR:DC:RANG " + Me.txtCurrentRange.Text & Chr(13))) End If m_CommPort.Write(Encoding.ASCII.GetBytes(":SENS:CURR:DC:DIG 8" & Chr(13))) ' control accuracy m_CommPort.Write(Encoding.ASCII.GetBytes(":SENS:FUNC 'VOLT:DC'" & Chr(13))) ' set function m_CommPort.Write(Encoding.ASCII.GetBytes(":SYST:AZER:STAT ON" & Chr(13))) ' control autozero ' control filter If Me.chkEnableFilter.Checked = True Then m_CommPort.Write(Encoding.ASCII.GetBytes(":SENS:VOLT:DC:AVER:STAT ON" & Chr(13))) m_CommPort.Write(Encoding.ASCII.GetBytes(":SENS:VOLT:DC:AVER:COUN " + Me.txtFilterCount.Text & Chr(13))) Else m_CommPort.Write(Encoding.ASCII.GetBytes(":SENS:VOLT:DC:AVER:STAT OFF" & Chr(13))) End If ' control Offset


If Me.chkVoltRef.Checked = True Then If Me.chkSENSEterminals.Checked = True Then m_CommPort.Write(Encoding.ASCII.GetBytes(":SENS:VOLT:DC:STER:REF " + Me.offset & Chr(13))) m_CommPort.Write(Encoding.ASCII.GetBytes(":SENS:VOLT:DC:STER:REF:STAT ON" & Chr(13))) Else m_CommPort.Write(Encoding.ASCII.GetBytes(":SENS:VOLT:DC:REF " + Me.offset & Chr(13))) m_CommPort.Write(Encoding.ASCII.GetBytes(":SENS:VOLT:DC:REF:STAT ON" & Chr(13))) End If Else If Me.chkSENSEterminals.Checked = True Then m_CommPort.Write(Encoding.ASCII.GetBytes(":SENS:VOLT:DC:TERM SENS" & Chr(13))) m_CommPort.Write(Encoding.ASCII.GetBytes(":SENS:VOLT:DC:STER:REF:STAT OFF" & Chr(13))) Else m_CommPort.Write(Encoding.ASCII.GetBytes(":SENS:VOLT:DC:REF:STAT OFF" & Chr(13))) End If End If m_CommPort.Write(Encoding.ASCII.GetBytes(":SENS:VOLT:DC:NPLC " + Me.txtNPLC.Text & Chr(13))) ' ' control range If Me.chkEnableAutoVolt.Checked = True Then If Me.chkSENSEterminals.Checked = True Then m_CommPort.Write(Encoding.ASCII.GetBytes(":SENS:VOLT:DC:TERM SENS" & Chr(13))) m_CommPort.Write(Encoding.ASCII.GetBytes(":SENS:VOLT:DC:STER:RANG:AUTO ON" & Chr(13))) Else m_CommPort.Write(Encoding.ASCII.GetBytes(":SENS:VOLT:DC:RANG:AUTO ON" & Chr(13))) End If Else If Me.chkSENSEterminals.Checked = True Then m_CommPort.Write(Encoding.ASCII.GetBytes(":SENS:VOLT:DC:TERM SENS" & Chr(13))) m_CommPort.Write(Encoding.ASCII.GetBytes(":SENS:VOLT:DC:STER:RANG:AUTO OFF" & Chr(13))) m_CommPort.Write(Encoding.ASCII.GetBytes(":SENS:VOLT:DC:STER:RANG " + Me.txtVoltageRange.Text & Chr(13))) Else m_CommPort.Write(Encoding.ASCII.GetBytes(":SENS:VOLT:DC:RANG:AUTO OFF" & Chr(13))) m_CommPort.Write(Encoding.ASCII.GetBytes(":SENS:VOLT:DC:RANG " + Me.txtVoltageRange.Text & Chr(13))) End If End If m_CommPort.Write(Encoding.ASCII.GetBytes(":SENS:VOLT:DC:DIG 8" & Chr(13))) ' control accuracy m_CommPort.Write(Encoding.ASCII.GetBytes(":FORM:ELEM READ" & Chr(13))) ' format elements m_CommPort.Write(Encoding.ASCII.GetBytes(":SAMP:COUN 1" & Chr(13))) 'burst read m_CommPort.Write(Encoding.ASCII.GetBytes(":TRIG:DEL 0" & Chr(13))) ' control trigger delay m_CommPort.Write(Encoding.ASCII.GetBytes(":TRIG:SOUR IMM" & Chr(13))) ' control trigger source


' File Setup Me.current_write = Me.current_file.CreateText(Me.CurrentDataFile.Text) Me.voltage_write = Me.voltage_file.CreateText(Me.VoltageDataFile.Text) Dim i As Integer For i = 1 To CInt(Me.txtReadValues.Text) Me.Measurement_status = 2 Me.pnlMeasurementInProgress.ForeColor = ForeColor.Red Me.pnlMeasurementInProgress.Text = "measurement in progress" m_CommPort.Write(Encoding.ASCII.GetBytes(":SENS:FUNC 'VOLT:DC'" & Chr(13))) ' set function m_CommPort.Write(Encoding.ASCII.GetBytes(":READ?" & Chr(13))) While Me.Measurement_status = 2 System.Threading.Thread.Sleep(50) Application.DoEvents() End While System.Threading.Thread.Sleep(CInt(Me.txt_timedelay.Text)) Me.Measurement_status = 1 Me.pnlMeasurementInProgress.ForeColor = ForeColor.Red Me.pnlMeasurementInProgress.Text = "measurement in progress" m_CommPort.Write(Encoding.ASCII.GetBytes(":SENS:FUNC 'CURR:DC'" & Chr(13))) ' set function m_CommPort.Write(Encoding.ASCII.GetBytes(":READ?" & Chr(13))) While Me.Measurement_status = 1 System.Threading.Thread.Sleep(50) Application.DoEvents() End While Me.current_write.Write(Chr(13)) Me.voltage_write.Write(Chr(13)) Next i Application.DoEvents() m_CommPort.Write(Encoding.ASCII.GetBytes(":SYST:LOC" & Chr(13))) m_CommPort.Close() Catch ex As Exception ' Warn the user. MessageBox.Show("Unable to communicate with device") Finally ' Disable the timer. Me.tmrReadCommPort.Enabled = False Me.current_write.Close() Me.voltage_write.Close() End Try End If End Sub

Appendix C

Photo of sample holder


Appendix D

EAGLE schematics of voltage divider


Appendix E

Photo of Measurement setup


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