Reproducible Quantitative Stimulation Allows New Analysis of Crayfish Muscle Receptor Organ Responses

Abstract

The crustacean muscle receptor organ (MRO) has provided a particularly accessible preparation for the study of sensory coding, which has been widely used in introductory laboratory courses incorporating extracellular recording from sensory nerves in living preparations. We describe three innovations to the standard laboratory exercise using the MRO: (1) a new form of suction electrode to facilitate extracellular recording; (2) a new, Arduino-driven actuator to allow reproducible and quantifiable mechanical stimulation of the MRO; and (3) a new approach to the crayfish abdomen preparation that allows linear extension of the MRO muscles. These novel approaches allow the collection of data sets comprised of sensory cell spike trains under software control as important mechanical stimulus parameters are varied systematically through software. This additional level of user control facilitates a more robust quantitative approach to the analysis of MRO sensory neuron spike trains, which is facilitated by training in data analysis using python.

The muscle receptor organs (MROs) of decapod crustacea were introduced to neuroscience in 1951 (Alexandrowicz, 1951) and rapidly became favored material for a variety of types of analysis, including biophysical analysis of membrane currents (Eyzaguirre and Kuffler, 1955; Terzuolo and Bullock, 1956; Edwards and Ottoson, 1958; Terzuolo and Washizu, 1962; Loewenstein et al., 1963; Nakajima and Onodera, 1969; Sokolove and Cooke, 1971; Brown et al., 1978; Rydqvist, 2007; Purali, 2011, 2017), cellular analysis of synaptic inputs (Kuffler and Eyzaguirre, 1955; Burgen and Kuffler, 1957) and outputs (Macmillan and Vescovi, 1997; Nakagawa and Mulloney, 2001; Drummond and Macmillan, 2004) of the MRO sensory neurons, and circuit level analysis of reflex function during crayfish postural movements (Eckert, 1961b, 1961a; Fields and Kennedy, 1965; Fields, 1966; Fields et al., 1967; Page and Sokolove, 1972, 1973; Patullo et al., 2001; Faulkes and Macmillan, 2002; McCarthy et al., 2004). The anatomy and physiology of the crayfish MROs are in several regards analogous to mammalian muscle spindles (Knellwolf et al., 2019), which added to their popularity (Kuffler, 1954). The sensory neurons of the crayfish MRO were also central to the analysis of gamma-aminobutyric acid (GABA) and other neurotransmitters at the synapses onto the soma and dendrites of the MRO sensory neurons from efferent modulatory neurons (Wiersma et al., 1953; Florey, 1954; Kuffler and Edwards, 1958; Edwards and Kuffler, 1959; Hagiwara et al., 1960; Sokolove and Roth, 1978; Craelius and Fricke, 1981; Elekes and Florey, 1987). In addition, a variety of quantitative modeling and simulation studies provided insights into MRO functions at several levels of analysis, from biophysical to network (Brown and Stein, 1966; Sokolove, 1972; Hartline, 1976; Macmillan, 1990; Swerup and Rydqvist, 1996). Appreciation of the structure and function of the crayfish MROs was greatly aided by the elegant studies of Purali (2005). The crayfish stretch receptor preparation has been described for student use (Welsh et al., 1968b; Leksrisawat et al., 2010; Wyttenbach et al., 2014). Variations of this classic preparation (e.g., Khaitin et al., 2015) present opportunities for extending the student exercise.

Practice in the use of modern methods of data analysis requires the generation of data sets containing reproducible neural responses produced by systematic and quantitative variation of relevant stimulus parameters. For the crayfish MRO, this means manipulation of stretch speed and the extent of either transient or maintained stretch, preferably under software control. This stimulation method allows the clearest differentiation of the tonic (slowly adapting) MRO and the phasic (rapidly adapting) MRO. A readily constructed flexible suction electrode also is required to maintain good contact with the MRO sensory nerve during vigorous abdominal movements. A device to impose reproducible and quantitative translational movements on the crayfish abdomen during recordings is also required. These two items will be described in the first two sections of this paper. Finally, a new version of the crayfish abdominal preparation is described which allows linear extensions rather than curling movements to be imposed on the isolated abdomen. Sensory nerve recordings generated by our students will be presented to show typical results of the novel methods we describe.

Our learning goals and objectives for this laboratory exercise are 3-fold: 1. To introduce students to the basic functions of a proprioceptor, including its stimulus/response and adaptation properties; 2. To introduce students to reproducible methods of obtaining a stimulus/response function from a single sensory neuron; 3. To introduce students to the concept of quantitative analysis of neuronal responses for application to multiple identical stimuli.

MATERIALS AND METHODS

Novel suction electrode design

To record from the MRO sensory nerve, we use a visually controlled fracture of a glass microelectrode that is directly coupled to a 1 mL syringe and suction tubing with a Tuohy adapter. The syringe body allows the electrode to be mounted on a coarse micromanipulator (Sutter MM-33 or equivalent). We prepare the glass suction electrode tips, silver wires, and suction apparatus, and the students assemble the working suction electrode from these components. Production of the suction electrode tips and apparatus is described detail in Appendices B and C.

The glass suction electrode tip is broken from a long glass microelectrode (pulled from capillaries of OD 1.2 mm, Sutter B120-69-15), using a serrated ceramic tile, at a diameter appropriate to hold the cut end or a loop of the MRO nerve (generally 150–300 μm). A chlorided silver wire is inserted into the lumen of the glass microelectrode and a second chlorided silver wire is affixed to the outside of the electrode near the tip (Figure 1A). The glass microelectrode is coupled to a 1mL syringe with a Tuohy adapter (1510, S4J Manufacturing Services, Inc., Cape Coral, FL), and the syringe is connected via silastic tubing to a suction apparatus (Figure 1B, 1C). Suction is imposed with a 10mL syringe and a 4-way Luer stopcock.

Figure 1.

A. Diagram to show the layout of the two silver wires, one inside and one outside the tip of the suction electrode. The outer silver wire (red arrow) is shown stabilized to the outside of the suction electrode tip with a small piece of dental wax. B. Magnified view of assembled suction electrode tip. Note that the inside wire does not extend to the electrode tip; it needs only a fluid column in contact with the saline bath to function. C. Example of a fully assembled suction electrode.

Arduino controlled MRO stimulator

To achieve quantitative and reproducible activation of the MRO sensory cells, we have developed an Arduino-controlled rotary actuator which at maximum speed and translation distance can reliably activate both the phasic and tonic MRO neurons during imposed curls of the abdomen (Figure 2). Slow speeds and short distances are sufficient to activate the tonic MRO neurons alone, while the phasic MRO neuron can be recruited at higher speeds and longer distances. The rotary actuator design was chosen after an initial design with a linear actuator was unable to generate the displacement speed necessary to activate the phasic MRO neuron. The maximum speed achieved by the rotary actuator is >1000 mm/sec.

Figure 2.

Interior view of the Arduino-controlled micro-rotary actuator shows the Arduino board mounted next to the rotary actuator, connections to the input and output ports, and the flexible wire attached to the actuator arm that exits the device housing. Device schematics are available in (Appendix VII).

The apparatus is designed such that a rotary actuator in the form of a servo motor (DaViga DS213, Aloft Hobbies, Novato, CA) gives approximately linear displacement to an attached flexible wire when moving over a 90° sweep of its arc. The technical specifications for the DaViga DS213 are given in Appendix VIII. The rotary position of the servo is controlled by an Arduino (Arduino Uno R3, Sparkfun: https://www.sparkfun.com). The Arduino board and servo motor are mounted in a compact plastic housing (LH43-200 kit, PacTec, Concordville, PA), which is securely connected to a 7 mm diameter aluminum rod to simplify mounting the device on a coarse micromanipulator. The device also has a BNC connector which outputs a position signal to be recorded simultaneously with the electrode recording. A loop in the end of the flexible wire that emerges from the device housing is connected to a strong thread that is tied to the telson of the crayfish abdomen. The apparatus housing is mounted in a coarse micromanipulator and positioned so that the baseline level of tension applied to the MRO is set by the X-axis control of the coarse micromanipulator. The puller is supplied to the students preassembled in an enclosed case. The interior of the apparatus is shown in Figure 2, and device schematics are shown in Appendix VII.

The Arduino board is flashed with a script using the standard servo library. The Arduino takes serial commands over a USB connection, generated from a graphical user interface (GUI) on the student’s computer. This GUI, written in python, allows the student to control the linear extent and speed of retraction, and allows for repeated trials with a given set of stimulus parameters. These controls are sufficient for precise and reproducible stimulation as presented in this manuscript, and students seeking more intricate stimulus timing or parameters can edit or create new code to direct the action of the puller (e.g., sinusoidal patterns of stretch, to simulate patterns of activation during rhythmic swimming or tail flips). Code for the Arduino and GUI are available in Appendices I and J.

Preparation of the crayfish abdomen for activation of MRO by imposed movements

Tail curl

Preparation of a crayfish tail for stimulation of MROs by tail curling is as described by Wyttenbach et al. (2014), which includes movies illustrating the various steps of the dissection. Immerse a crayfish in crushed ice for at least 20 minutes. Remove the crayfish from the ice when it is unresponsive and quickly separate the abdomen from the cephalothorax. Immediately place the cephalothorax in a freezer. Isolate the dorsal surface of the abdominal carapace by making two longitudinal cuts along the margins of the dorsal carapace, then peel the dorsal carapace away from the ventral surface. Remove the fast flexor and extensor muscles to reveal the ends of the MRO sensory nerves on each side of each abdominal segment. Near the end of the MRO sensory nerve it is comprised of three branches. The central branch contains the MRO sensory axons, as shown in Figure 8.

Figure 8.

A. Semi-diagrammatic figure showing the three nerve branches that converge to form the main trunk of the MRO nerve. NPM = nerve to the profundis (deep extensor) muscles, NRM = nerve to the MROs, NCS = nerve to sensory hairs on the exoskeleton. RM1, RM2 = receptor muscle 1 and 2. Anterior is to the top of the panel. See Wiersma (1953) for further details. B. MRO recording from a tail curl experiment separating the tactile hair response (purple dots) from the tonic MRO response (yellow dots). Students may misidentify the tactile hair response as an MRO unit if they fail to pay attention to (or record) the release of tail stretch.

Make a hole in the telson, insert a coarse thread through the hole and tie it in place. The other end of this string will be connected to the loop in the end of the flexible wire emerging from the Arduino-controlled stimulator box. Finally, pin the crayfish abdomen dorsal side down in a sylgard-lined preparation dish by pinning only the most anterior segment of the abdomen. This will allow tension on the string tied to the telson to impose abdominal flexion. Cover the preparation with crayfish saline (205 mM NaCl, 5.4 mM KCl, 10 mM CaCl2, 2.6 mM MgCl2, 2 mM glucose, 2.3 mM NaHCO3, pH 7.4). To avoid collisions between the tail fan and the suction electrode, the lateral components of the tail fan can be removed.

Linear stretch

In the standard laboratory preparation, the phasic MRO nerve tends to respond only to very fast tail curl stimuli, with the result that it can be hard to recruit. When the phasic MRO nerve is stimulated, the necessarily brief stimulus tends to evoke only a very small number of spikes, making quantitative analysis (e.g., of adaptation) very difficult. The prior section details methods aimed at increasing the reproducibility of recruiting the phasic MRO with a fast pull. Here we describe an additional dissection step that allows MROs in a given segment to be stretched linearly, allowing both a simpler measurement of the muscle stretch and an investigation of the behavior of the phasic MRO outside its normal physiological constraints. This added step can be challenging for students new to dissection, so we present it to our undergraduates as an alternate approach. Thus some of our students who opt to implement this technique do so on the second day of lab designated for the MRO experiment, after successfully obtaining an MRO recording with the standard method on day 1.

This alternative approach follows the normal dissection protocol of Wyttenbach et al. (2014) up to and including the removal of fast flexor muscles to expose the MRO nerves. Students then identify the segment with the best candidate (i.e., visibly intact and accessible) MRO nerves. This segment is separated from the one posterior to it by using a #10 scalpel blade to cut through the tergite joints and the arthroidal membrane between segments (Figure 3). The remaining muscles including the MROs can now be stretched by applying a pull to the tail fan in a posterior direction, reliably recruiting both the phasic and tonic MROs.

Figure 3.

Dissection to separate two tail segments of the crayfish abdomen to allow excitation of MRO sensory neurons by linear extension of the abdomen. The segments are separated by cutting through the two hinge joints and the arthroidal membrane holding the segments together. A. Intersegmental hinge joints on either side are cut with the tail placed ventral side down on a firm surface. B. The arthroidal membrane should then be cut with the segment bent to 90 degrees, with the scalpel kept shallow and parallel to the more anterior segment, to prevent cutting the MRO or deep extensor muscles.

A diagram showing the complete setup of the crayfish abdomen, Arduino-controlled stimulator, suction electrode and input probe of the extracellular amplifier is shown in Appendix VI. Commercial sources for living crayfish are listed in Appendix V.

RESULTS

Using the protocol modifications outlined above, our students are able to generate recordings from the MRO nerve with reproducible, user-varied stimuli, which offers the adapts from an initial firing rate to a steady state firing rate opportunity for more robust quantitative measurements and analysis. Sample student recordings of MRO sensory neuron activity in response to imposed abdominal curling or stretch according to these protocols are shown in Figures 4 and 5. Figure 4A shows the most typical response profile of the MRO nerve: after a tail curl, the tonic MRO over 10 seconds, and can be modeled with an exponential decay function (Figure 4B; Appendix I). The phasic MRO (generally a much larger unit) responds during the fast pull with a burst that is too abrupt to fit to an exponential. Figure 4C captures a rare, sustained phasic MRO response at maximum tail curl, a feature we were aiming to capture reliably in the development of the linear stretch approach to dissection. Data from the linear stretch preparation are shown in Figure 5, in an exploration of responses at successive stretch distance, including a phasic MRO response despite the slow stimulus speed.

Figure 4.

Example student recordings and analysis from the crayfish MRO nerve using the tail curl protocol described herein. A. A sample recording from the MRO sensory nerve showing responses from both the phasic MRO (larger, unlabeled spikes) and tonic MRO (smaller spikes with peaks labeled in green). B. An exponential model (magenta) (Wyttenbach et al., 2014; see Appendix I) fits the observed tonic MRO data (red) very well (R^2 = 0.994). C. A second example showing sustained responses from both the phasic and tonic MROs. In this example a 30 mm stretch at a speed of 25 mm/sec sequentially recruits the phasic and tonic MROs. Phasic MRO spikes are denoted with yellow markers; tonic MRO spikes are denoted with purple markers; and the puller position signal is plotted in red.

Figure 5.

Student data demonstrating the tonic response to successive linear stretch stimuli and the stretch threshold of both tonic and phasic MRO units. The crayfish tail was prepared according to the protocol for linear stretch, and the tail was stretched in 2mm steps at minimum speed (5.25mm/s) while recording from the MRO nerve. A. The stretch applied revealed linear stretch thresholds for the tonic and phasic MROs. The initial threshold stimulus of the tonic MRO (cyan trace; tonic unit spikes labeled with black dots) happens near 18mm of linear stretch, and the unit ceases firing as it adapts to the first suprathreshold stimulus. The phasic MRO is recruited at a stretch distance of 26–28 mm. Position signal shown in purple. B. Instantaneous firing rate of the tonic MRO (orange traces) together with position signal (purple trace). Successive stretches show increasingly high initial and adapted firing rates. C. Magnified view of the recording shown in panel A, highlighting the recruitment of phasic MRO spikes at 27 mm of linear stretch.

The utility of reproducible stimulation of the MRO is shown in Figures 6 and 7, in which a sequence of thirteen consecutive extensions is imposed in an investigation of the relationship between MRO adaptation and recovery time between stimuli. The rapidly delivered stimuli at maximal pull speed elicit short bursts from the phasic MRO neuron, and activity from the tonic MRO neuron that is sustained for the duration of the imposed flexion. In contrast to the tonic MRO, the phasic MRO does not recover to full responsiveness at the shortest rest intervals, most likely due to the dramatic differences in adaptation kinetics between the fast and slow MROs. This difference in adaptation of the two MRO units is quantified by fitting each stimulus response to an exponential decay curve (Figure 7 and Appendix I). The adaptation rate tau varies as a function of recovery time for the phasic MRO (Figure 7D), but initial and adapted firing rates do not vary as a function of rest time for either MRO. The ability to gather extensive data sets with reliable and reproducible mechanical stimuli applied to the MRO sensory neurons while maintaining high quality recordings from the sensory nerve is the major advantage of using the Arduino-controlled device.

Figure 6.

Student recording showing a sequence of Arduino-commanded MRO flexions delivered while both MRO sensory nerve activity and rotary actuator position signal are recorded, in an investigation of the relationship between adaptation rates and recovery time between trials. Upward deflections in the servo position trace indicate puller retraction (tail curl) and downward deflections indicate relaxation. The change in spike height is likely due to a change in suction electrode contact with the nerve.

Figure 7.

A. Binned spike rates and exponential model fits for the phasic and tonic MRO neurons during an extended stimulation period shown in Figure 6. Spike rate was modeled in python as an exponential function of time with form R_t = R_∞ + R₀e^−t/τ (Wyttenbach et al., 2014; Appendix I). As expected, the phasic MRO ceased firing while the tonic MRO had a sustained response following adaptation. B–D. Plots of the fit parameters as a function of recovery time between stimuli. One interesting observation was that the firing rate decay (τ) was found to vary with the recovery time between trials for the phasic MRO but not the tonic MRO, with phasic MRO adapting more quickly at short recovery times.

DISCUSSION

Course context

The MRO exercise is deployed in two neuroscience laboratory courses: a core lab for undergraduate neuroscience majors who generally take it in the spring semester of their junior year, and a core lab for first year neuroscience graduate students. Our teaching lab has a capacity for 16 students working in pairs; we generally run one section of the graduate course in the fall and two to three sections of the undergraduate lab in the spring. Both courses are open to students from other concentrations, and in recent years we have had visiting molecular biology, physics, and engineering students. The courses meet twice per week for laboratory sessions: 3 hours per session for the undergraduate course and 4 hours per session for the graduate course.

In both courses, students submit figures each week, demonstrating a quantitative analysis of the data recorded in that week’s module, as well as two lab reports over the course of the semester, which explore the experiments in greater depth. The second lab report is based on an independent project, designed and completed by students in the final two weeks of the semester. The student data presented in this paper are from these figure and lab report assignments. To alleviate the pressure to generate good data from challenging experiments on a weekly basis, we have an explicit data sharing policy, allowing free use of classmates’ data with their permission and proper attribution.

Our feedback to the students on their assignments is spread between the quality of quantitative analyses and clarity in explaining those analyses (both visually and textually). We aim to structure each module so that students learn a laboratory technique, and then use that technique to ask a question of the system under study. To facilitate this we provide tutorial materials in the form of jupyter notebooks illustrating analysis of sample data using python. We frame this exercise in terms of sensory coding, and introduce (1) plotting of binned or instantaneous firing rate (IFR) and (2) curve fitting to the analysis ‘toolbox’, which includes data handling, plotting, peak detection, and amplitude-based spike sorting from earlier weeks. The student analyses for this exercise tend to focus either on comparing responses between different stimulus parameters they manipulated during data collection (speed, distance, recovery time) or a quantitative exploration of adaptation under a single stimulus mode. Students who don’t wish to fit a decay curve can still compare initial and adapted firing rates and relative adaptation rates by manually inspecting their IFR plots.

This lab is the third module in our course and the first time our students are prompted to develop a question to ask about their data by choosing the conditions under which they wish to make their recordings. (The preceding two weeks of recording from the crayfish neuromuscular junction are more prescriptive in terms of experimental design.) The focus on framing a question at this stage firmly establishes that expectation going forward, and dispenses with questions about how to frame the empirical question after an experiment has been performed. The students have done well with this freedom, with some venturing outside the manipulations we suggest: we only added recovery time to our list of parameters to explore after a student submitted the analysis shown in Figures 6 and 7.

Some students struggle with the details involved in generating the figures at this stage. For example, occasionally students will fail to look closely enough at their data to exclude the tactile hair response in the analysis of the tonic MRO. (This arises from the fact that the MRO nerve includes a branch that receives sensory input from the exoskeleton, which can introduce movement-based artifacts; see Figure 8). We view these mistakes as the opportunity for the most learning to happen in the course, which we encourage with a robust feedback cycle, and reduce the sting of by making each figure a small part of the final grade (figures collectively being worth as much as one lab report). We find that our students’ ability to generate effective figures improves over the course of the semester, and they report that this was the most generalizable skill they acquired from their experience in the course.

When we first developed this course, we presented parallel tutorial materials using either Matlab or, for students who did not wish to learn to code, Excel and the analysis suite packaged with our acquisition software (Clampfit). Since that time the ubiquity of coding in neuroscience has made it inescapable in the context of our teaching lab. We have settled on python as the language of choice for our tutorial materials, but since programming literacy is generalizable, we require programming experience in any language as a prerequisite for the course, and students can perform their analysis using any language they choose. In the earliest phase of the course we hold supplementary office hours to help with the practical use of python for analysis of electrophysiology data. For students without a strong computational background, two useful references are (Cohen, 2017; Nylen and Wallisch, 2017).

MRO system

The sensory neurons of the crayfish MROs provide readily accessible preparations for the quantitative study and modeling of sensory transduction (Brown and Stein, 1966; Sokolove, 1972; Hartline, 1976; Macmillan, 1990; Swerup and Rydqvist, 1996) and neuromodulation, particularly the inhibitory input from GABAergic interneurons making synapses directly on the dendrites and somata of the MRO sensory neurons (Kuffler and Edwards, 1958; Edwards and Kuffler, 1959; Sokolove and Roth, 1978; Craelius and Fricke, 1981). The properties of the crustacean MROs have been extensively reviewed (Alexandrowicz, 1967; Swerup and Rydqvist, 1992; Rydqvist, 2007; Rydqvist et al., 2007); however, many essential aspects of their biophysical properties and behavioral control functions remain to be elucidated, presenting a rich variety of opportunities to use this preparation in extending basic student exercises and formulating student research projects..

Stimulation of the isolated MRO sensory nerve while recording from the tonic MRO neuron intracellularly reveals antidromic stimulus-locked IPSPs for some stimulus strengths at some stimulating electrode positions (Sokolove and Cooke, 1971). The peripheral axons of the GABAergic efferent neurons presumably maintained their viability in these experiments (Bittner, 1991). These stimulus-evoked IPSPs are likely to be due to the GABAergic efferent synapses onto the MRO sensory neurons. The study of the reflex activity patterns in efferent neurons making synapses on the MRO sensory neurons will be facilitated by a recently-described version of the crayfish abdominal MRO preparation which maintains its central connections to the chain of abdominal ganglia (Khaitin et al., 2015).

The biophysical understanding of the ionic events underlying adaptation in the crayfish MROs has focused on the ability of stretch-sensitive channels in the MRO membranes. The stretch-activated channels mediate adaptation of the receptor current by admitting calcium ions which act internally to activate a potassium current responsible for the fast phase of receptor current adaptation (Erxleben, 1989, 1993; Rydqvist et al., 2007). Presumably the fast and slow MROs differ in the number and sensitivity of the stretch-activated channels and the kinetics of activation of the calcium-sensitive potassium channels.

A leading candidate for the deformation-sensitive MRO sensory neuron membrane channels is one or more of the newly described mechanosensitive piezo family of ion channels (Woo et al., 2015; Haselwandter and MacKinnon, 2018; Zhao et al., 2018). Piezo channels have been shown to be essential for stretch-activated mechanical transduction in the larval Drosophila dorsal bipolar dendritic sensory neurons (Suslak et al., 2015). Also, some progress has been made in understanding the substructure of the piezo channels and the molecular features important for stretch activation (Lacroix et al., 2018). This molecular information may allow creation of a more selective piezo channel blocker than gadolinium (Swerup et al., 1991) or tarantula toxin GsMTx4 (Bowman et al., 2007; Bae et al., 2011; Lee et al., 2014) which can then be applied to the crayfish MRO sensory neurons to confirm or refute the hypothesis that piezo channels are required for MRO sensory neuron responses to stretch (McCubbin et al., 2020).

The crayfish abdominal posture control system, of which the MRO sensory neurons are presumably an integral part, mediates both slow adjustments of abdominal extension and flexion, and fast movements during repetitive tail flips that mediate escape swimming. It has been remarkably difficult to demonstrate robust effects on either of these two motor outputs due to ablation of the MROs or correlate MRO activity during behavior by recording their activity during spontaneous or stimulus-evoked abdominal movements (Patullo et al., 2001; Faulkes and Macmillan, 2002; McCarthy et al., 2004). It may require dual site recording with implanted cuff electrodes on the MRO sensory nerve to distinguish afferent and efferent axon activity during both fast and slow abdominal postural changes. Another important aspect of these studies of the MRO activity in situ is whether or not abdominal movements are working against an opposing force (Page, 1978; Sukhdeo and Page, 1992). Also, it is important to realize that there is a second set of stretch sensitive sensory neurons in the crayfish abdomen, mediated by stretch receptors in the ventral nerve cord itself (Grobstein, 1973a; 1973b; Savati and Macmillan, 1993; Drummond and Macmillan, 2002). These crayfish nerve cord stretch receptors are analogous to stretch receptors described in abdominal nerves of Phormia that play a critical role in the regulation of food intake (Gelperin, 1971). The role of the crayfish nerve cord stretch receptors in postural control of the abdomen is unknown, although description of the ultrastructure of the phasic nerve cord stretch receptor (Cobb and Heitler, 1985) may offer some guidance as to its function.

Previous work using an electrically activated stretch stimulus to the MRO spanning the cephalothorax-abdomen junction allowed application of periodic stimulus variations such as sine waves or ramp variations in stretch to be applied during tonic firing of the slow adapting MRO sensory cell (Vibert et al., 1979). This MRO preparation also allowed intercalation of inhibitory input to the tonic sensory cell by electrical stimulation applied in the vicinity of the rapidly adapting phasic sensory cell. The electrical stimulus activated the fibers of an inhibitory neuron, resulting in inhibitory input to the tonic sensory cell by axon reflex (Nja and Walloe, 1975). In preparations retaining the connections of the MROs and the central ganglia, activation of two efferent inhibitory fibers to the MRO sensory cells can be evoked by imposed activity in the MRO sensory cells themselves (Eckert, 1961b; Jansen et al., 1970a, 1970b; Jansen et al., 1971). The two MRO sensory cells on each side of each abdominal segment receive a total of four efferent inhibitory neurons (Wine and Hagiwara, 1977; Drummond and Macmillan, 1998a, 1998b). Understanding the reflex activation and dynamics of this population of efferent inhibitory neurons is critical to a complete description of MRO function in vivo.

Suction electrode design

The fabrication and use of a variety of suction electrodes have been described (Easton, 1960, 1965; Kanno, 1963; Florey and Kriebel, 1966; Welsh et al., 1968a; Brown et al., 2006) including versions particularly suited to use in a teaching laboratory (Easton, 1993; Land et al., 2001; Johnson et al., 2007). A very useful feature of the suction electrode design described here is the ability to quickly and easily change electrode tips to optimize the snug fit of a nerve end or nerve loop in the electrode tip. Theoretical studies of suction electrode recording configurations (Stys et al., 1991; Easton, 1993) emphasize the importance of reducing leakage of action currents around the exterior of the nerve in the electrode tip to achieve optimum signal to noise ratios in the recorded signals. The suction electrode configuration we describe here can work with very small tip openings (5 – 10 μm ID) which proved critical for recording from a very small insect nerve, the recurrent nerve of the blowfly Phormia regina (Gelperin, 1967).

Learning to assemble their own suction electrodes is an important component of this laboratory exercise, as the students learn that they are recording the potential difference between points (the inner and outer wires of the suction electrode); and that when a length of active nerve is lodged in the suction electrode’s tip, the recording pathway includes the extracellular space around the axons in the nerve, which is where local currents flow during the passage of an action potential. They also learn the importance of the nerve in the electrode tip making a snug fit and have the ability to easily change the glass electrode tip to find a tip of optimal size for the nerve from which they are aiming to record.

A recent innovation in techniques for in vivo recording involves application of microfabrication methods to the design and construction of implanted microelectrodes. This fabrication method has allowed significant progress in the ability to make in vivo recordings from crayfish nerve fibers (Lott and Hoy, 2008; Chen et al., 2009). Silicone encapsulated pairs of hook electrodes have also been used to record afferent and efferent activity in vivo from the dorsal branch of nerve 2 in the crayfish abdomen during both postural adjustment, walking and tail flips (Gruhn and Rathmayer, 2002).

Arduino Mechanostimulator

Arduino microcontrollers are increasingly popular for controlling and sensing applications in the neuroscience laboratory, as they are inexpensive open-source devices supported by an extensive user community (Teikari et al., 2012; Sheinin et al., 2015; Artoni et al., 2016; Landa-Jimenez et al., 2016). Arduinos incorporate communication via a USB port that serves both to provide power to the board and for uploading control programs, either custom written or from a standard library. Arduino boards are equipped with analog and digital input/output pins facilitating creation of control signals for external devices, such as an LED (Titlow et al., 2015) or the rotary actuator used in the MRO stimulation device described here. Free tutorials on the use of Arduino devices are readily available (www.arduino.cc/en/Tutorial).

CONCLUSIONS

The muscle receptor organs of the crayfish, Procambarus clarkii, provide a widely used and readily accessible preparation for the study of general principles of sensory coding, particularly for mechanoreceptive stimuli. The pedagogical value of studies of this preparation is greatly enhanced by the ability to apply reproducible, quantitative stretch stimuli to the receptor muscles while recording the spike trains from the MRO sensory neurons elicited by these stimuli. The data sets generated by application of the mechanostimulator described here allow quantitative analysis of response reproducibility and the kinetics of response evolution with time after stimulus application, using readily available software tools. The combination of these factors greatly enhances the utility and effectiveness of student studies of the crayfish MRO preparation.

APPENDIX I. FITTING AN MRO FIRING RATE CURVE TO AN EXPONENTIAL DECAY EQUATION

The adaptation curve of MRO activity can be fit to an exponential of the form:

$$R_t=R_{\mathit{0}}•e^{-t/\tau }+R_{\mathit{\infty }}$$

In this equation, R_t is the firing rate at time t, R_∞ is the steady state firing rate; R₀ + R_∞ is initial firing rate; and 1/τ (tau) is the decay constant. Students should fit the binned or instantaneous firing rate curves beginning from the peak firing rate, using a utility like the curve_fit method from python’s scipy package. The output will be the values for the three parameters (R₀, R_∞, and τ) that best fit the supplied data to the above equation. Fitting time-binned data can produce a more “visually satisfying” fit than IFR data when the decay is relatively fast, because the curve fitting is biased toward the part of the curve with a higher density of data points. Time binning reduces this bias, but in doing so loses resolution at the peak firing rate.

Students can make meaningful comparisons of initial and adapted firing rates and adaptation rates without curve fitting by comparing IFR curves plotted on the same axis. Initial and adapted firing rates can be estimated by eye, while the decay rate can be described as the time the curve takes to decay halfway to R_∞.

Having students fit the MRO response to this equation was described in Wyttenbach et al, 2014.

APPENDIX II. PREPARATION OF SUCTION ELECTRODE TIP

1. Pull a microelectrode blank as for a crayfish muscle intracellular recording electrode (Wyttenbach et al., 2014). We use 15 cm glass capillaries (Sutter B120-69-15) to create tips that are long enough to minimize complications caused by the crayfish telson hitting the electrode.

2. Under the low power of a dissecting microscope, score the tip of the microelectrode using a ceramic tile (CTS, Sutter Instruments, Novato, CA) so that when the tip is broken at the score, the inner diameter of the electrode tip makes a snug fit with the nerve end or with the nerve loop selected for recording. For recording from the end of the MRO sensory nerve the inner diameter of the tip of the suction recording electrode should be in the range 150 – 300 μm, depending on the size and species of the crayfish being used.

3. Two silver wires, 0.008" diameter and ~10cm length are soldered to connectors appropriate for the inputs to the head stage of the extracellular amplifier being used.

4. For most extracellular amplifiers, it will be useful to chloride the silver wires to avoid baseline drift. We use a 30 sec immersion of the ends of the silver wires in a ferric chloride PCB etchant solution (CAS No: 7705-08-0) to produce a sturdy layer of silver chloride. Use of this plating solution requires care to avoid skin contact and thorough rinsing of the plated silver wires to remove residual plating solution.

5. Fine stainless steel wires can be used in place of silver wires as a high pass filter on the amplifier input will block the offset potentials of the stainless steel wires. Note that in either case the bath ground wire must be a chlorided silver wire.

APPENDIX III. PREPARATION OF SUCTION ELECTRODE

The suction apparatus described here has a shelf life of several years, so long as they are stored without any residual crayfish saline. Saline left in the tubing will cause mold growth. An example of the completed suction electrode is shown in Figure 1B.

1. Drill out the back end of a 1 mL slip-tip BD disposable syringe (Cole Parmer UX-07944-00) using a drill size #3 or 7/32"

2. Use a ¼-28 tap to tap threads into the back end of the disposable syringe

3. Obtain a package of Loctite Plastics Bonding System with 4g Activator and 2g Adhesive

4. Obtain a PTFE adapter ¼-28 thread to 1/8" barb (DWK 953918-2313)

5. Apply the Loctite activator to the threads in both the syringe and on the adapter

6. Wait at least 1 minute for the activator solvent to evaporate

7. Apply Plastic Bonder Glue only to the threads on the adapter

8. Screw the adapter by hand firmly into the syringe and let dry for at least 1 day

9. Put a 32" length of Tygon tubing size 1/8" ID by ¼" OD (Cole Parmer EW-06407-76) onto the barbed fitting on the back end of the 1 mL syringe

10. Insert a 1/8" barb to female Luer (Cole Parmer EW-30800-08) adapter into the free end of the Tygon tubing

11. Mate the female Luer connection from the tubing to a male Luer-lock connection on a three-way stopcock (Mainlinemedical 9-5311-01)

12. Attach a 10 mL disposable BD slip-tip syringe (Cole Parmer UX-07944-14) to the female Luer connection on the stopcock opposite the tubing connection

Figure A1.

Assembled suction electrode. Refer also to Figure 1 in the text.

APPENDIX IV. EQUIPMENT AND SOFTWARE DEPLOYED IN OUR TEACHING LAB

Equipment	Model	Manufacturer
extracellular amplifier	AM-3000	AM Systems (Everett, WA)
digitizer	Digidata 1440A	Molecular Devices (San Jose, CA)
acquisition software	pClamp/Clampex 10	Molecular Devices

APPENDIX V. COMMERCIAL SOURCES FOR LIVING CRAYFISH FOR BIOLOGICAL RESEARCH

1. Carolina Biological Supply, Burlington, NC	www.carolina.com
2. Ward’s Science, Rochester, NY	www.wardsci.com
3. Nasco, Fort Atkinson, WI	www.enasco.com
4. Connecticut Valley Biological Supply, Southampton, MA	www.connecticutvalleybiological.com
5. Niles Biological, Sacramento, CA	www.nilesbio.com/

A very useful guide to identifying the species of crayfish that has been supplied is (DiStefano et al., 2008).

APPENDIX VI.

Diagram showing the arrangement and electrode connections of the crayfish abdominal preparation, Arduino control box, suction electrode and amplifier input probe.

Figure A2.

Diagram to show the arrangement and connections of the crayfish abdomen preparation, the suction electrode, extracellular amplifier and input probe and the Arduino control box. This particular orientation is for the linear stretch of the tail. For the tail curl, the tail is rotated 180° with respect to the Arduino puller box. Any extracellular amplifier that can provide differential recording between the two suction electrode wires and accept a bath ground input would suffice for recording (see Land et al., 2001).

APPENDIX VII. SCHEMATIC DIAGRAM SHOWING CIRCUIT CONNECTIONS FOR ARDUINO CONTROL BOX

Figure A3.

Circuit diagram to show input and output connections and device wiring of the Arduino control box. The small numbers (3, 9) indicate the socket numbers on the Arduino board used to plug in the respective connection wires.

APPENDIX VIII. TECHNICAL SPECIFICATIONS FOR THE DAVIGA DS213 ROTARY ACTUATOR

Servo Type	Digital
Gear Type	Metal
Stall Torque	2.5Kg.cm@4.8V, 3Kg.cm@6.0V
Speed	0.08sec/60°@4.8V, 0.07sec/60°@6.0V
Dimensions	23.1 x 12 x 24.5 mm
Weight	16 g
Operating Voltage	4.5V to 6V
Potentiometer	Direct Drive
Ball Bearings	2
Device Shell	Aluminum Alloy

The rotary actuator specified above was chosen after testing several other models to determine which rotary actuator could produce the torque and speed adequate to activate both the phasic and tonic MROs, while also remaining relatively still at a particular command voltage. We found that the best servos by these criteria were in the $25–30 price range. The MRO pull speed is measured from the readout of the position sensor build into the actuator.

APPENDIX IX. SOURCE CODE FOR ARDUINO-CONTROLLED STIMULATOR

A downloadable .ino file is accessible at https://github.com/neu350/MRO.

Figure 13.

APPENDIX X. PYTHON 3.X SOURCE CODE FOR GRAPHICAL USER INTERFACE

A downloadable .py file is accessible at https://github.com/neu350/MRO.

Figure J1.

Screenshot of python GUI for Arduino puller.

Figure 14.