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Neuronal tissues can be excited by electrical stimulation. Two commonly encountered characteristics for electrically stimulating nerve cells is the threshold and the rheobase. My question is what the difference is between rheobase and threshold? In the definitions I've read it's described as almost the same thing. The threshold, or minimal stimulus, is defined as "the electrical stimulus whose strength (or voltage) is sufficient to excite the tissue. Rheobase is defined as "the minimum strength (voltage) of stimulus which can excite the tissue". What is the difference?
Excellent question! The difference is the fact that the rheobase is an example of a threshold measure. The threshold, as you correctly suggest, is the minimal energy (typically current level and not voltage as you suggest) to excite neural tissue. The threshold applies only under the specific experimental parameter settings used. These parameters include the type of electric stimulus (for example, a biphasic current pulse), the electrode configuration (for example, bipolar stimulation) and the stimulus duration (for example 200 microseconds).
The rheobase is the minimal current level needed to excite a tissue when an infinitely long stimulus would be applied. The rheobase is typically found by plotting the threshold level (as defined above) as a function of stimulus duration. The reason for developing this measure is the fact that excitable membranes integrate the injected current, so charge builds up in the tissue. In other words, increasing the pulse duration decreases the threshold current level needed. Hence, the rheobase is a convenient threshold measure because it incorporates the duration parameter of the stimulus. It will still depend on things like electrode configuration and stimulus shape.
The function of the strength-duration relationship can be fitted with a decaying exponential:
I = Ith / ( 1-e(-t/Tsd) )
where I= Threshold current level; Irh = rheobase t = stimulus duration Tsd = Tau = exponential
Here is a picture of a theoretical strength-duration curve copied from the wiki page on rheobase. [NB: I find the wiki page needlessly complicated].
The rheobase is the horizontal asymptote. An often used parameter to characterize the function is chronaxie, which is the pulse duration equivalent to two times the rheobase.
The explanation given here was adapted from the book "Cochlear Implants", chapter 5 "Biophysics and Physiology" by Abbas and Miller, two veterans in cochlear implant electrophysiology. Unfortunately I cannot give you a link to the pdf as I own the work in hard copy.
Whether the threshold potential is reached depends on the amount of charge transferred across the membrane. Figure 19.6 shows that the total charge transfer across the membrane required to produce excitation is approximately constant (k = xy or Q = IT). It is an approximate rectangular hyperbola (xy = k) over the sharply-bending region of the curve. The strength–duration (S-D) curve can be derived from the equation for the exponential charge of the membrane capacitance.
FIGURE 19.6 . Strength–duration curve for AP initiation in excitable membranes. The intensity of rectangular stimulating pulses is plotted against their duration for stimuli that are just sufficient to elicit an AP. The rheobase current and chronaxie (σ) are indicated.
The S-D curve deals only with the stimulus parameters (i.e. strength and duration of the applied current pulses) necessary to bring the membrane to threshold. It shows that the greater the duration of the applied pulse, the smaller the current intensity required to just excite the fiber. The asymptote parallel to the x-axis is the rheobase, which is the lowest intensity of current capable of producing excitation, even when the current is applied for infinite time (practically, >10 ms for myelinated nerve fibers). The asymptote parallel to the y-axis is the minimal stimulation time, which is the shortest duration of stimulation capable of producing excitation, even when huge currents are applied.
The usefulness of the rheobase is limited when comparing the excitability of one nerve with another because only the relative current intensity is meaningful. Furthermore, it is difficult to measure the stimulation time of a current with the intensity of the rheobase because it is an asymptote. Thus, a graphic measurement is made of the time during which a stimulus of double the rheobasic strength must act in order to reach threshold. This time is the chronaxie. Chronaxie values tend to remain constant regardless of geometry of the stimulating electrodes. The shorter the chronaxie, the more excitable the fiber. The chronaxie value for normal myelinated nerve fibers is about 0.7 ms. Some nerve pathologies in humans can be detected early by changes in their chronaxies.
Measurement of chronaxie in the laboratory is also valuable because it provides an easy method for measuring the value of the membrane time constant τm (see Chapter 18 ). In brief, the relationship between chronaxie (σ) and time constant (τm) is:
Thus, τm is 1.44 times the value of σ. Therefore, σ is analogous to a half-time for a first-order reaction, whose rate constant is the reciprocal of the τm (k=1/τm).
The S-D curve indicates that current pulses of very short duration (e.g. <0.1 ms) are less effective for stimulation. Thus, sinusoidal alternating current (AC) at frequencies above 10 000 Hz is less capable of stimulation. Another way to view this is that, because the membrane impedance decreases greatly at high frequencies (since the cell membrane is a parallel RC network), the pd that can be produced across the membrane by current flow across it (IR or IX drops) is very small. Hence, AC of very high frequency has less tendency to electrocute and the energy of such currents can be dissipated as heat in body tissues and thus may be used in diathermy for therapeutic warming of injured tissues.
As the duration of a test stimulus increases, the strength of the current required to activate a single fiber or a specified fraction of a compound action potential decreases. Strength–duration time constant (or chronaxie ) and rheobase are parameters that describe the strength–duration curve, i.e., the curve that relates the intensity of a threshold stimulus to its duration. Strength–duration time constant (SDTC) is an apparent membrane time constant inferred from the relationship between threshold current and stimulus duration, and provides a measure of the rate at which threshold current increases as the duration of the test stimulus is reduced to zero. In human peripheral nerve, the strength–duration relationship is described remarkably well by Weiss's empirical law: 13
where Q = stimulus charge I = stimulus current of duration t Irh = rheobasic current.
Weiss's formula is used widely to calculate SDTC. 14, 15 In this formulation, SDTC equates to chronaxie (the stimulus duration corresponding to a threshold current that is twice rheobase). Rheobase is the threshold current (or estimated threshold current in mA) required if the stimulus is of infinitely long duration. Because there is a linear relationship between stimulus charge and stimulus duration, rheobase and SDTC can be calculated from a charge–stimulus duration plot with four different stimulus widths (0.2, 0.4, 0.8, and 1 msec). 15, 16 SDTC is derived from the x-intercept of the straight line fitted to the points representing different stimulus widths, whereby the slope of this relationship equates to the rheobase ( Fig. 15-3 ). Rheobase and SDTC are both properties of the nodal membrane. SDTC averages 0.46 msec in human motor axons and 0.67 msec in sensory axons of peripheral nerve. 15 These values are much longer than the passive time constant of the nodes of Ranvier (approximately 50 μsec) because the effects of subthreshold current pulses are prolonged by the local response of low threshold Na + channels, particularly by persistent Na + channels. 17 These channels are also important in determining repetitive and spontaneous activity, and this is the reason that SDTC is a clinically important excitability parameter.
All three known members of the selectin family (L-, E-, and P-selectin) share a similar cassette structure: an N-terminal, calcium-dependent lectin domain, an epidermal growth factor (EGF)-like domain, a variable number of consensus repeat units (2, 6, and 9 for L-, E-, and P-selectin, respectively), a transmembrane domain (TM) and an intracellular cytoplasmic tail (cyto). The transmembrane and cytoplasmic parts are not conserved across the selectins being responsible for their targeting to different compartments.  Though they share common elements, their tissue distribution and binding kinetics are quite different, reflecting their divergent roles in various pathophysiological processes. 
There are three subsets of selectins:
L-selectin is the smallest of the vascular selectins, expressed on all granulocytes and monocytes and on most lymphocytes, can be found in most leukocytes. P-selectin, the largest selectin, is stored in α-granules of platelets and in Weibel–Palade bodies of endothelial cells, and is translocated to the cell surface of activated endothelial cells and platelets. E-selectin is not expressed under baseline conditions, except in skin microvessels, but is rapidly induced by inflammatory cytokines.
These three types share a significant degree of sequence homology among themselves (except in the transmembrane and cytoplasmic domains) and between species. Analysis of this homology has revealed that the lectin domain, which binds sugars, is most conserved, suggesting that the three selectins bind similar sugar structures. The cytoplasmic and transmembrane domains are highly conserved between species, but not conserved across the selectins. These parts of the selectin molecules are responsible for their targeting to different compartments: P-selectin to secretory granules, E-selectin to the plasma membrane, and L-selectin to the tips of microfolds on leukocytes. 
The name selectin comes from the words "selected" and "lectins," which are a type of carbohydrate-recognizing protein. 
Selectins are involved in constitutive lymphocyte homing, and in chronic and acute inflammation processes, including post-ischemic inflammation in muscle, kidney and heart, skin inflammation, atherosclerosis, glomerulonephritis and lupus erythematosus  and cancer metastasis.
During an inflammatory response, P-selectin is expressed on endothelial cells first, followed by E-selectin later. Stimuli such as histamine and thrombin cause endothelial cells to mobilize immediate release of preformed P-selectin from Weible-Palade bodies inside the cell. Cytokines such as TNF-alpha stimulate transcription and translation of E-selectin and additional P-selection, which account for the delay of several hours. 
As the leukocyte rolls along the blood vessel wall, the distal lectin-like domain of the selectin binds to certain carbohydrate groups presented on proteins (such as PSGL-1) on the leukocyte, which slows the cell and allows it to leave the blood vessel and enter the site of infection. The low-affinity nature of selectins is what allows the characteristic "rolling" action attributed to leukocytes during the leukocyte adhesion cascade. 
Each selectin has a carbohydrate recognition domain that mediates binding to specific glycans on apposing cells. They have remarkably similar protein folds and carbohydrate binding residues,  leading to overlap in the glycans to which they bind.
Selectins bind to the sialyl Lewis X (SLe x ) determinant “NeuAcα2-3Galβ1-4(Fucα1-3)GlcNAc.” However, SLe x , per se, does not constitute an effective selectin receptor. Instead, SLe x and related sialylated, fucosylated glycans are components of more extensive binding determinants. 
The best-characterized ligand for the three selectins is P-selectin glycoprotein ligand-1 (PSGL-1), which is a mucin-type glycoprotein expressed on all white blood cells.
Neutrophils and eosinophils bind to E-selectin. One of the reported ligands for E-selectin is the sialylated Lewis X antigen (SLe x ). Eosinophils, like neutrophils, use sialylated, protease-resistant structures to bind to E-selectin, although the eosinophil expresses much lower levels of these structures on its surface. 
Ligands for P-selectin on eosinophils and neutrophils are similar sialylated, protease-sensitive, endo-beta-galactosidase-resistant structures, clearly different than those reported for E-selectin, and suggest disparate roles for P-selectin and E-selectin during recruitment during inflammatory responses. 
Selectins have hinge domains, allowing them to undergo rapid conformational changes in the nanosecond range between ‘open’ and ‘closed’ conformations. Shear stress on the selectin molecule causes it to favor the ‘open’ conformation. 
In leukocyte rolling, the ‘open’ conformation of the selectin allows it to bind to inward sialyl Lewis molecules farther up along the PSGL-1 chain, increasing overall binding affinity—if the selectin-sialyl Lewis bond breaks, it can slide and form new bonds with the other sialyl Lewis molecules down the chain. In the ‘closed’ conformation, however, the selectin is only able to bind to one sialyl Lewis molecule, and thus has greatly reduced binding affinity.
The result of such is that selectins exhibit catch and slip bond behavior—under low shear stresses, their bonding affinities are actually increased by an increase in tensile force applied to the bond because of more selectins preferring the ‘open’ conformation. At high stresses, the binding affinities are still reduced because the selectin-ligand bond is still a normal slip bond. It is thought that this shear stress threshold helps select for the right diameter of blood vessels to initiate leukocyte extravasation, and may also help prevent inappropriate leukocyte aggregation during vascular stasis. 
It is becoming evident that selectin may play a role in inflammation and progression of cancer.  Tumor cells exploit the selectin-dependent mechanisms mediating cell tethering and rolling interactions through recognition of carbohydrate ligands on tumor cell to enhance distant organ metastasis,   showing ‘leukocyte mimicry’. 
A number of studies have shown increased expression of carbohydrate ligands on metastatic tumor,  enhanced E-selectin expression on the surface of endothelial vessels at the site at tumor metastasis,  and the capacity of metastatic tumor cells to roll and adhere to endothelial cells, indicating the role of selectins in metastasis.  In addition to E-selectin, the role of P-selectin (expressed on platelets) and L-selectin (on leukocytes) in cancer dissemination has been suggested in the way that they interact with circulating cancer cells at an early stage of metastasis.  
Organ selectivity Edit
The selectins and selectin ligands determine the organ selectivity of metastasis. Several factors may explain the seed and soil theory or homing of metastasis. In particular, genetic regulation and activation of specific chemokines, cytokines and proteases may direct metastasis to a preferred organ. In fact, the extravasation of circulating tumor cells in the host organ requires successive adhesive interactions between endothelial cells and their ligands or counter-receptors present on the cancer cells. Metastatic cells that show a high propensity to metastasize to certain organs adhere at higher rates to venular endothelial cells isolated from these target sites. Moreover, they invade the target tissue at higher rates and respond better to paracrine growth factors released from the target site.
Typically, the cancer cell/endothelial cell interactions imply first a selectin-mediated initial attachment and rolling of the circulating cancer cells on the endothelium. The rolling cancer cells then become activated by locally released chemokines present at the surface of endothelial cells. This triggers the activation of integrins from the cancer cells allowing their firmer adhesion to members of the Ig-CAM family such as ICAM, initiating the transendothelial migration and extravasation processes.
The appropriate set of endothelial receptors is sometimes not expressed constitutively and the cancer cells have to trigger their expression. In this context, the culture supernatants of cancer cells can trigger the expression of E- selectin by endothelial cells suggesting that cancer cells may release by themselves cytokines such as TNF-α, IL-1β or INF-γ that will directly activate endothelial cells to express E-selectin, P-selectin, ICAM-2 or VCAM. On the other hand, several studies further show that cancer cells may initiate the expression of endothelial adhesion molecules in a more indirect ways.
Since the adhesion of several cancer cells to endothelium requires the presence of endothelial selectins as well as sialyl Lewis carbohydrates on cancer cells, the degree of expression of selectins on the vascular wall and the presence of the appropriate ligand on cancer cells are determinant for their adhesion and extravasation into a specific organ. The differential selectin expression profile on endothelium and the specific interactions of selectins expressed by endothelial cells of potential target organs and their ligands expressed on cancer cells are major determinants that underlie the organ-specific distribution of metastases.
Selectins are involved in projects to treat osteoporosis, a disease that occurs when bone-creating cells called osteoblasts become too scarce. Osteoblasts develop from stem cells, and scientists hope to eventually be able to treat osteoporosis by adding stem cells to a patient’s bone marrow. Researchers have developed a way to use selectins to direct stem cells introduced into the vascular system to the bone marrow.  E-selectins are constitutively expressed in the bone marrow, and researchers have shown that tagging stem cells with a certain glycoprotein causes these cells to migrate to the bone marrow. Thus, selectins may someday be essential to a regenerative therapy for osteoporosis. 
The percentage difference formula
Before we dive deeper into more complex topics regarding the percentage difference, we should probably talk about the specific formula we use to calculate this value. The percentage difference formula is as follows:
percentage difference = 100 * |a - b| / ((a + b) / 2)
To get even more specific, you may talk about a percentage increase or percentage decrease. To simply compare two numbers, use the percentage calculator.
Now you know the percentage difference formula and how to use it. Please keep in mind that since there is an absolute value in the formula, the percentage difference calculator won&apost work in reverse. This is why you cannot enter a number into the last two fields of this calculator.
Stimulation and Excitation of Cardiac Tissues
Stimulus Charge-Duration Relationship
It should always be remembered that implantable pacemakers and ICDs are powered by a battery with a fixed quantity of available charge. Therefore minimizing the amount of charge used for stimulation of the heart is an important determinant of device longevity. For a pacing stimulus, the charge (Q) that is delivered is the product of current (I), measured in charges per second, and pulse duration (d), measured in msec, such that:
The graphical plot of charge versus pulse duration shows that the charge with each stimulus decreases rapidly as the pulse duration is shortened before approaching a minimum asymptote (Qmin) (see Fig. 3-36 ). 116 This minimum charge is related to the membrane time constant, and therefore chronaxie , by the equation:
Thus in terms of charge, and therefore battery drain, a pulse duration of less than τ does not save significant charge drained from the battery. Reducing the pulse duration to only 1/10th of chronaxie produces a charge that is only 10% above the minimum. The charge equation can also be rearranged to determine the energy at each point on the strength-duration curve. As energy (E) is equal to the product of voltage (V), current (I) and pulse duration (d):
The minimum energy on the strength-duration curve is predicted to be 1.25 τ. This is also the point where the strength-duration curve for capture and the charge versus pulse duration curve intersect (see Fig. 3-35B ). As a practical point, when programming the pulse duration of a pulse generator, chronaxie is an excellent choice to minimize energy, limit charge drained from the battery, and provide a stimulus amplitude within the limits that can be provided by the pulse generator (see Fig. 3-35 ).
There are several clinically relevant aspects to the strength-duration relationship: first, whereas true rheobase occurs at a pulse duration of approximately 10 msec, the practical value of increasing the pulse duration beyond approximately 1.5 msec is minimal because this is on the flat portion of the curve and there is very little decrease in the threshold amplitude beyond this point second, when the pulse duration is shortened below approximately 0.20 msec, the stimulus amplitude encounters the steeply rising portion of the exponential curve such that the stimulus amplitude required to capture may begin to exceed the maximum amplitude that the pulse generator can deliver. Because of these facts, the capture threshold should always be noted as the combination of amplitude and pulse duration that were used to determine myocardial capture, (e.g., 0.5 V at 0.3 msec, or 0.4 V at 0.5 msec, etc.). From a clinical standpoint, determining the voltage threshold at a pulse duration of 0.3 to 0.5 msec and programming the amplitude twice the threshold value is an effective method for managing stimulus amplitude while providing an excellent safety margin. It should also be recognized that the value of chronaxie, and therefore the strength-duration curve, depends of the homogeneity of the tissue and the proximity of the electrode to excitable tissue. 120 The chronaxie value is different for muscle and nerves as well as for complex tissues such as atrial and ventricular myocardium, the AV node, and Purkinje fibers. 121,122
What is Afferent Neuron
The neurons, which carry sensory impulses towards the CNS are referred to as afferent neurons. The afferent neurons convert external stimuli into internal electrical impulse. The nerve impulse travels along the afferent nerve fibers to the CNS. The cell body of the afferent neuron is located in the dorsal ganglia of the spinal cord.
The afferent neurons gather information from sensory perceptions such as light, smell, taste, touch, and hearing, respectively, from the eye, nose, tongue, skin, and ear. The sensory signals of light are gathered from the rod and cone cells in the retina of the eye, and those nerve impulses are carried to the brain by the afferent neurons of the eye. The afferent neurons in the nose are stimulated by different odors, and nerve impulses are sent to the brain. The taste buds in the tongue gather sensory information about different tastes and the nerve impulses are carried to the brain by the afferent nerves of the tongue. The mechanical stimuli such as touch, pressure, stretch, and temperature are detected by the skin, and the nerve signals are sent to the brain by the afferent neurons. The afferent neurons of the ear are stimulated by different wavelengths within the sensible range to each animal, and the nerve impulses are carried to the brain. All sensory signals are processed in the brain, and the brain coordinates the relevant organs for a specific response. The structure of the afferent and efferent neurons are shown in figure 1.
Figure 1: Afferent and Efferent Neurons
Sex differences in pain perception
Background: A number of studies have demonstrated a higher prevalence of chronic pain states and greater pain sensitivity among women compared with men. Pain sensitivity is thought to be mediated by sociocultural, psychological, and biological factors.
Objective: This article reviews laboratory studies that provide evidence of sex differences in pain sensitivity and the response to analgesic drugs in animals and humans. The biological basis of such differences is emphasized.
Methods: The literature from this relatively new field was surveyed, and studies that clearly illustrate the differences in pain mechanisms between the sexes are presented. Using the search terms sex, gender, and pain, a review was conducted of English-language literature published on MEDLINE between January 1980 and August 2004.
Results: Although differences in pain sensitivity between women and men are partly attributable to social conditioning and to psychosocial factors, many laboratory studies of humans have described sex differences in sensitivity to noxious stimuli, suggesting that biological mechanisms underlie such differences. In addition, sex hormones influence pain sensitivity pain threshold and pain tolerance in women vary with the stage of the menstrual cycle. Imaging studies of the brain have shown differences between men and women in the spatial pattern and intensity of response to acute pain. Among rodents, females are more sensitive than males to noxious stimuli and have lower levels of stress-induced analgesia. Male rodents generally have stronger analgesic response to mu-opioid receptor agonists than females. Research on transgenic mice suggests that normal males have a higher level of activity in the endogenous analgesic system compared with normal females, and a human study has found that mu-receptors in the healthy female brain are activated differently from those in the healthy male brain. The response to kappa-opioids, which is mediated by the melanocortin-1 receptor gene in both mice and humans, is also different for each sex.
Conclusion: Continued research at the genetic and receptor levels may support the need to develop gender-specific drug therapies.
What is the difference between rheobase and threshold? - Biology
In the branch of experimental psychology focused on sense, sensation, and perception, which is called psychophysics, a just-noticeable difference (JND) is the amount something must be changed in order for a difference to be noticeable, or detectable at least half the time (absolute threshold). This limen (another word for threshold) is also known as the difference limen, differential threshold, or least perceptible difference.
For many sensory modalities, over a wide range of stimulus magnitudes sufficiently far from the upper and lower limits of perception, the JND is a fixed proportion of the reference sensory level, and so the ratio of the JND/reference is roughly constant (that is the JND is a constant proportion/percentage of the reference level). Measured in physical units, we have:
where I is the original intensity of the particular stimulation, ΔI is the addition to it required for the change to be perceived (the JND), and k is a constant. This rule was first discovered by Ernst Heinrich Weber (1795–1878), an anatomist and physiologist, in experiments on the thresholds of perception of lifted weights. A theoretical rationale (not universally accepted) was subsequently provided by Gustav Fechner, so the rule is therefore known either as the Weber Law or as the Weber–Fechner law the constant k is called the Weber constant. It is true, at least to a good approximation, of many but not all sensory dimensions, for example the brightness of lights, and the intensity and the pitch of sounds. It is not true, however, of the wavelength of light. Stanley Smith Stevens argued that it would hold only for what he called prothetic sensory continua, where change of input takes the form of increase in intensity or something obviously analogous it would not hold for metathetic continua, where change of input produces a qualitative rather than a quantitative change of the percept. Stevens developed his own law, called Stevens’ Power Law, that raises the stimulus to a constant power while, like Weber, also multiplying it by a constant factor in order to achieve the perceived stimulus.
The JND is a statistical, rather than an exact quantity: from trial to trial, the difference that a given person notices will vary somewhat, and it is therefore necessary to conduct many trials in order to determine the threshold. The JND usually reported is the difference that a person notices on 50% of trials. If a different proportion is used, this would be included in the description—for example a study might report the value of the 75 percent JND.
Modern approaches to psychophysics, for example signal detection theory, imply that the observed JND is not an absolute quantity, but will depend on situational and motivational as well as perceptual factors. For example, when a researcher flashes a very dim light, a participant may report seeing it on some trials but not on others.
Try It Yourself
It is easy to differentiate between a one-pound bag of rice and a two-pound bag of rice. There is a one-pound difference, and one bag is twice as heavy as the other. However, would it be as easy to differentiate between a 20- and a 21-pound bag?
Question: What is the smallest detectible weight difference between a one-pound bag of rice and a larger bag? What is the smallest detectible difference between a 20-pound bag and a larger bag? In both cases, at what weights are the differences detected? This smallest detectible difference in stimuli is known as the just-noticeable difference (JND).
Background: Research background literature on JND and on Weber’s Law, a description of a proposed mathematical relationship between the overall magnitude of the stimulus and the JND. You will be testing JND of different weights of rice in bags. Choose a convenient increment that is to be stepped through while testing. For example, you could choose 10 percent increments between one and two pounds (1.1, 1.2, 1.3, 1.4, and so on) or 20 percent increments (1.2, 1.4, 1.6, and 1.8).
Hypothesis: Develop a hypothesis about JND in terms of percentage of the whole weight being tested (such as “the JND between the two small bags and between the two large bags is proportionally the same,” or “. . . is not proportionally the same.”) So, for the first hypothesis, if the JND between the one-pound bag and a larger bag is 0.2 pounds (that is, 20 percent 1.0 pound feels the same as 1.1 pounds, but 1.0 pound feels less than 1.2 pounds), then the JND between the 20-pound bag and a larger bag will also be 20 percent. (So, 20 pounds feels the same as 22 pounds or 23 pounds, but 20 pounds feels less than 24 pounds.)
Test the hypothesis: Enlist 24 participants, and split them into two groups of 12. To set up the demonstration, assuming a 10 percent increment was selected, have the first group be the one-pound group. As a counter-balancing measure against a systematic error, however, six of the first group will compare one pound to two pounds, and step down in weight (1.0 to 2.0, 1.0 to 1.9, and so on.), while the other six will step up (1.0 to 1.1, 1.0 to 1.2, and so on). Apply the same principle to the 20-pound group (20 to 40, 20 to 38, and so on, and 20 to 22, 20 to 24, and so on). Given the large difference between 20 and 40 pounds, you may wish to use 30 pounds as your larger weight. In any case, use two weights that are easily detectable as different.
Record the observations: Record the data in a table similar to the table below. For the one-pound and 20-pound groups (base weights) record a plus sign (+) for each participant that detects a difference between the base weight and the step weight. Record a minus sign (−) for each participant that finds no difference. If one-tenth steps were not used, then replace the steps in the “Step Weight” columns with the step you are using.
|Table 1. Results of JND Testing (+ = difference − = no difference)|
|Step Weight||One pound||20 pounds||Step Weight|
Analyze the data/report the results: What step weight did all participants find to be equal with one-pound base weight? What about the 20-pound group?
Draw a conclusion: Did the data support the hypothesis? Are the final weights proportionally the same? If not, why not? Do the findings adhere to Weber’s Law? Weber’s Law states that the concept that a just-noticeable difference in a stimulus is proportional to the magnitude of the original stimulus.
We are grateful to the Cardiac Electrophysiology Laboratory staff at McGuire VA Medical Center, in particular to Donna Sargent, RN (research coordinator), for her dedication to this project.
Sources of Funding
This study was supported by National Institutes of Health grant UL1RR031990 to the VCU Center for Clinical and Translational Research (Dr Thacker).
Dr Huizar received grant support from St Jude Medical and was a clinical investigator for Biotronik. Dr Kaszala is a clinical investigator for Boston Scientific, St Jude Medical, and Sorin. Dr Ellenbogen has received grants and honoraria and is a clinical investigator and consultant for Boston Scientific, Medtronic, St Jude Medical, and Biotronik. Dr Wood is a clinical investigator and speaker for Boston Scientific. Dr Kowalski is a consultant for Medtronic.