Behavioral Experiment - Science topic

I wonder if this is the kind of thing you are looking for:

Hidaya Rojoub Thank you for your eagerness to help. I will rethink this issue seriously.

Based on your description, the variable "disclosure vs non-disclosure" is what's commonly referred to as a manipulation check or a treatment condition. It's a way to ensure that participants are indeed exposed to the intended experimental conditions. In your case, it seems like it's a manipulation of whether participants are informed about the source of the content they are viewing (AI vs. human).

Here's how you can classify it:

Regarding visualization, you can indeed create a matrix including both of the independent variables. Here's how you can visualize it:

Disclosure Non-Disclosure

__________________ __________________

| | |

| AI Content | AI Content |

|__________________|__________________|

| | |

| Human-generated | Human-generated |

| Content | Content |

|__________________|__________________|

Each cell in the matrix represents a unique combination of the two independent variables. Participants are randomly assigned to one of these conditions.

For data analysis, you would conduct a two-way analysis of variance (ANOVA) to examine the main effects of content source and disclosure, as well as any interaction effects between them, on the dependent variables (content quality measures).

This will allow you to determine if there are statistically significant differences in content quality based on the content source, the disclosure condition, or their combination.

Remember to conduct appropriate post-hoc tests if you find significant effects, to further explore the nature of these effects.

Also, ensure that your experiment design and statistical analysis plan are aligned with your research questions and hypotheses. If in doubt, consulting with your professor or a research methodologist can provide further guidance.

Do you have paired data? ie same individuals's pre and post test scores.

If so work on the means and sds of the differences.

Jil Ullenboom Thank you for providing this article!

I can send you a book chapter in PDF format on your email, if you want? Just PM me your email and I will send it :) Hemangi Narvekar

I had something similar when trying to make fibre optic cannulae - the epoxy was just not setting properly. Either that or they were to viscous to get the epoxy into the cannula.

My solution was to stop trying to make them myself. Now I just buy them in pack of 20 from Thorlabs, and they cost less than £20 each. These are the ones I get:

Is there a particular reason you need to make them yourself?

You can estimate this model within the framework of path analysis / structural equation modeling. The moderated effects can be represented and tested by including interaction (product) terms as in moderated regression analysis (e.g., computing and including a product variable LUX*OKU to represent the potential interaction between the two conditions).

The interactions between the binary condition variables (LUX, OKU) and latent variables (e.g., KS*LUX) are more difficult to model if the latent variables are represented with multiple indicators (i.e., if there is a measurement model with multiple observed variables for each latent factor). In that situation, latent moderated structural equation modeling (LMS; Klein & Moosbrugger, 2000) or the so-called product-indicator approach may be used to model the latent-by-observed interactions (both would be complicated in your case though given the presence of multiple interaction effects in the model). To my knowledge, LMS is not currently available in AMOS (it is available in Mplus), but you could potentially use the product-indicator approach. See, e.g.,

Klein, A., & Moosbrugger, H. (2000). Maximum likelihood estimation of latent interaction effects with the LMS method. Psychometrika, 65(4), 457–474. https://doi.org/10.1007/BF02296338

An easier way would be to represent the KS, PS, ZSM, and BSS variables by observed (sum or mean) scores (rather than by multiple indicators). In that case, you would not have to deal with the complications of modeling latent interaction effects. When all variables are observed variables in your data set, you can simply compute and include manifest product terms to model the interaction/moderator effects.

Mac is best option.

Here's a nice paper on ways to measure oxytocin levels in humans: https://www.nature.com/articles/s41598-017-17674-7

Unfortunately, it doesn't appear as if you can image oxytocin using MRS (which has pretty poor spatial and temporal resolution anyway) or any other neuroimaging measures as far as I can tell.

Thanks!

There is a terminology issue here (and the terminology is confusing). They reviewers might have meant:

1) a mixed ANOVA with a combination of within (repeated measures) and between (independent measures factors). This is relatively easy to run via the repeated measures ANOVA commands in SPSS (e.g., see https://www.discoveringstatistics.com/repository/mixed_2020.pdf ). This is a single model that handles all the error terms etc.

2) They could have meant a linear mixed model (or multilevel model). If you have a completely balanced design with no missing cells and no time-varying covariates then this is essentially equivalent to the mixed ANOVA (assuming a single random factor for participants and a nested design). Generally this approach is useful because you have imbalance or complex random effects that you want to model (and the mixed ANOVA is a special case of this kind of model). The mixed term here is a mixture of random and mixed effects being modelled. Its a highly flexible approach. You can run this in SPSS but it isn't straightforward if you are new to these models.

The table you show appears to be from a mixed ANOVA. Your description isn't sufficient to tell what the reviewers meant.

Dear Waqas Ali,

Thank you for the link to the scientific publication on the subject: behavioral economics.

Greetings, Have a nice day,

Dariusz Prokopowicz

Cannulated rats housed together will lead to scratch, slow healing, and potentially severe injuries. Make sure your control group is housed in the same conditions and isolate them following surgery to ensure recovery.

Thx

In a similarly styled experiment, we are only manipulating the key variables of interest, not the less important ones. As long that seems reasonable in your settings (e.g., in your example, your respondents would would expect candidates to have a BA education, mid-level exam score) I think it's okay to not vary that and keep it constant.

One way I would think about it is what the experiment is asking them to do - is it making them pick at the final stages of hiring (e.g., job offer) or screening candidates at the initial stages?

At initial stages, reviewers would expect more variation in the job candidate pool (so it makes sense to vary less important attributes as well). At later stages of the hiring process, we would expect that everyone being reviewed meets certain basic minimum criteria.

Hope this helps!

I am assuming that your compound was administered with nicotine during the induction phase of the CPP study. Nonetheless, I agree with the comment above that I don’t think you can really say much about how the drugs are interacting at a cellular pharmacological level if you are administering the drugs systemically. They may be acting at very different sites, cellular targets or a whole gamut of other possibilities. This doesn’t negate what sounds like an interesting finding but detailed pharmacological studies, possibly in vitro, may be required to get to the bottom of what is going on.

Best,

Niall

I agree that I would also stick with the mixed ANOVA in this situation. However, many authors who published on multilevel models won't agree with the statement that you don't need to consider the multilevel structure when there is no significant intra-class correlation (ICC). Even if the ICC is not significant (i.e., the null model with the random intercept does not fit the data significantly better than a linear model without random intercept) you should consider the multilevel data structure, because even in the absence of a significant ICC the standard error could be biased due to the nesting leading to a significance test that is too liberal.

Thank-you for everyone's help. I found a solution to my question and have added the link in case anyone encounters the same problem in the future. This solution also changes where the output goes, into the main output page rather than the model viewer, meaning that you can edit it too.

I tested a few online survey platforms today, and most were terrible for this task. Many platforms use the language “A/B split testing” to refer to assignment of separate streams of stimuli (that detail is for Auneeb Hussain). I found two acceptable options:

https://freeonlinesurveys.com seems far better than many alternatives. You can randomize text, images, or videos, and doing so is very easy. A major weakness is that you cannot randomly display an entire question from a question bank. Nor can you randomly display a video with some text underneath (from a set of possible videos with paired text).

Soscisurvey is powerful and provides its services for free to some groups (non-profits, individuals, etc.). However, it is not a good option for casual use (for quick student projects, for instance) because the learning curve is steep and the documentation is difficult to follow. For example, to randomize showing a question, I had to set up a random variable TR01 that is either 1 or 2 and then add PHP code that would display question TC01 if TR01 took on a value of 1 and question TC02 if TR01 was not 1:

if (value('TR01') == 1) {

question('TC01');

} else {

question('TC02');

}

Paid versions of Survey Monkey will randomize images and text (and possibly videos) like freeonlinesurveys.com, but it will also (sort of) randomize questions. Strangely, I could only find an option to randomize the question stem text. This means that if you want respondents to face different multiple choice questions, both questions must have the same answer options. I have no idea why. I guess that’s just the way the monkey likes it. Pretty silly. The free version of Survey Monkey does not support this and does not even let you download survey responses as a spreadsheet, so I would avoid it.

Paid versions of Qualtrics are powerful and can certainly do what you want. However, this is nowhere near “mostly free”.

Other products I tested:

SoGoSurvey: Despite the positive words elsewhere in this thread, I could not find the option for A/B testing. Perhaps, it is completely hidden from non-pro users.

Typeform: Could not find the functionality (although the company frequently implies that the functionality exists)

Zoho Survey: Could not find the functionality

Microsoft Forms: I am almost certain the option exists, but my understanding is that implementation would require even more coding than with Soscisurvey

Google Forms: Same problem as Microsoft forms

Note that there are many other platforms that I did not test.

Dear Gerrit,

You wrote that "The multilevel approach is given due to utilising GLM with additive predictor variables (I do not use interaction terms).".

Maybe this term of "multilevel" might have different meanings, I however thought about adding individuals as random effects in a generalized mixed model.

Abdylla Parahadov

Unfortunately I don't know a highly polymorphic region that is reported specifically for the strain of mice you are working with. Specially since I have always worked with natural populations samples.

The characteristics of your samples makes challenging the DNA profiling using a single locus. Even if you find a single region that is highly polymorphic the inbreeding nature of the samples you are working with suggests that they may all inherited a single haplotype.

I would suggest you to think in a multi-locus approach to your problem. Using several loci will highly increase the probabilities of discrimination between samples due to reduced linkage disequilibrium. You could try:

+ Using gel electrophoresis based approaches (the least expensive) like RAPD (https://en.wikipedia.org/wiki/RAPD ) or RFLPs (https://en.wikipedia.org/wiki/Restriction_fragment_length_polymorphism).

+ Genotype several microsatellite loci (medium price). https://link.springer.com/chapter/10.1007/978-3-642-56207-5_3

+ Doing a Reduced-representation sequencing approach: such as RADseq and genotyping thousands of SNPs across the genome. Very expensive, however it will certainly allow you to identify your samples.

JotForm [https://www.jotform.com] is something that I have had students use in my classes over the last few years. It is a bit clunky, but still extremely useful to collect recordings with minimum effort. This is free.

Psychopy online [http://psychopy.org] is another option. I have just started working with online production experiments, and it's been pretty decent so far. You need to pay for "credits" to set up a proper online link for the experiment, but it is very reasonable. Plus, if you are willing to invest more time and collect data in "pilot" mode (which only generates a temporary link that is active for an hour), then it can effectively be free.

Yes, there is a direct connection. By engaging the talented, our processes become more creative and innovative. It is the best competitive advantage that is almost impossible to reach and copy.

I'm glad my comments were useful. You will also find that if a question is shaped primarily by analytical concerns, you will likely not be able to translate the question into everyday language that will be easily understood. If we ask a survey question in any language, and we get a puzzled look, then we have failed to do our job. A good survey question is one for which you know in advance more or less what answers people will give; you just don't know how many will give which of the 3-5 likely answers.

Possibly, if the material's magnetic susceptibility is known

You have three treatments applied to 10 subjects. These represent 30 treatments (3x10). Then you have “m” time levels. That means you have 30m treatments. If you perform at least two replicates by each treatment you can perform your experiment as a completely random design (for 30m treatments) and you can perform a 1W ANOVA with Tukey multiple comparison test. Alternatively you can fit a model for time effect for the 30 treatment.

What concentration of dextranamine are you using? I am using dextran, Alexa Fluor 488, 10000MW, anionic, fixable.

What volumes do you (try to) inject? 0.5

What injection system are you using? Simple syringe, with tubing and a glass pipette

I like the monetary game approach mentioned above. What I typically do in these types of situations (though there is certainly no single one-size-fits-all approach) is to do a small sample pre-survey to get a general notion of what people would say in terms of willingness to accept or willingness to pay. I then use that to rephrase the survey for the full distribution of the survey with a bid that the respondent can either accept or reject. If the respondent accepts, then there is a follow-up question of whether or not there is an upper bound that they would be willing to accept. Similarly, if the respondent rejects the bid, then that there is a follow-up question regarding whether or not there is any particular amount that they would be willing to accept. Depending on the situation, this can be followed up with various debriefing questions to see whether or not they understood the question in terms of proper evaluation, etc. And, you always have to ensure that you are not comparing chalk and cheese. And there always needs to be a mechanism for correcting for different valuation responses based on various factors such as income and demographics since that can obviously impact willingness to pay/accept. You may also be able to set up the survey to see if you can get statistically different groups of respondents based on revealed preferences, which may very well cross income, geographic, socioeconomic, and demographic boundaries (www.choicewaves.com).

I would also have proposed the Hayes sources. But you should keep in mind that it is not only the statistical structure that is necessary to establish mediation, but also the temporal structure of the assessement of the indvidual variables. To be sure that it is a causal chain you would need a longitudinal analysis. Cross-sectional studies cant really show causality.

If you're talking about mediation in the traditional sense, this assumes that the "attitude" variable M is influenced by X, and that M in turn has a causal effect on Y. In this case you can use mediation analysis, either with classic regression methods (eg Baron and Kenny) or structural equation modeling.

However your description sounds more like a case where M is fixed, but the effectiveness of intervention X depends on the value of M. This is a non-linear interaction, but you can easily assess it using interaction terms in a linear regression model.

Hello Andreas,

Several differences are at work when you compare dummy (1, 0) and effects (1, -1) coding for a 2x2 design. First, I presume that you did include an interaction term for the analysis (e.g., row effect = IV1, column effect = IV2, interaction = IV3). As well, for simplicity, I assume a balanced design (each of the four cells having equal number of cases).

In dummy coding, the row and column effects will correlate with the interaction term, whereas all three terms will be uncorrelated in effects coding. So, there is some collinearity among the IVs in dummy coding, but not in effects coding. That will generally cause the interaction term to have a different standard error than the row and column effect terms in dummy coding.

The effects coded regression solution should yield exactly the same statistical test results as would a 2 x 2 anova (though perhaps as t-tests rather than F-tests; remember here, t-squared for an effect = F)

Second, remember that the interpretation of the coefficients will differ between the two coding methods. In dummy coding, the standard errors tend to be larger, since there is one numeric unit separating the two levels (0 vs. 1), whereas in effects coding, there are two numeric units separating the two levels (-1 vs. 1). Recall that the usual interpretation of a regression coefficient is that it represents the estimated difference in the dependent variable (Y) per unit change in the independent variable, holding all other IVs constant.

Good luck with your work.

It sounds like are going in the right direction. Linear regression is great for a continuous DV, and it can handle both continuous and categorical IVs. It will take a little practice to interpret your regression equations, but I find this approach very useful and I use it frequently in my work.

Out of curiosity, why do you want to use a scale of 1-14? I personally am used to a scale of 0-10. If I rate my well-being with an 8, I need to do a disturbing calculation in order to rate it on a 1-14 scale.

I think a slider of some fixed length is easier to use than a jog-wheel: the scale is immediately visible!

You are welcome dear Anastasiia Popelnukha

If they no longer make that software, they might be able to point you in the proper direction.

The first step is compare with the experimental test results, after that you can decide if you can depend on the finite element results or not.

Fibonacci.

Hope this helps,

Mattt

As no one answered my question and I have already found a solution more than a year ago, I'll answer to share it.

First, maturation in cases like this can be mitigated by randomized or pseudorandomized order of the questions. It's the first possible strategy for that. If you offer all participants the order Q1, Q2, Q3, the measurement of Q3 might be distorted by maturation. But if instead you offer one participant this order, and another one the order Q1, Q3, Q2, and another Q3, Q2, Q1, and another Q3, Q1, Q2; Q2,Q1,Q3; and Q2, Q3, Q1, having an "equilibrium" (ensuring all orders are equally available with pseudorandomization) or simply being truly random (reducing effects to chance), you mitigate the effect.

Yet you can also measure the effect of maturation by collecting information about the answering order. Doing so you won't just really prevent the extraneous variable, but also measure it.

Yes. In a more general sense- the method used for measuring can bias the subject.

Dear Lewend,

One way you can combine scores is to use a principal component analysis and save the regression scores for the first component.

You cannot feel fear when you eat. Do your rats have some "favorite food"?

I agree with Russell on this. There is a difference in behaviour between exposure to pure NaCl and exposure to seawater. For example, the presence of sulphates will encourage ettringite formation, while the solubility of ettringite and gypsum are also lowered in the presence of chlorides. The presence of magnesium will also be a factor, with magnesium salts potentially attacking the C-S-H.

This is reflected in exposure classes, with seawater (XS) being recognised as being more aggressive than non-marine chlorides (XD).

Dear, you find useful information in links below:

I had tried to contact people in Spain for the colors. Because of the lack of official health certificate, I couldn't use them. As Michael Jacobson suggested, I will implant head blockers to trace the pigeons. Thank you for suggestions.

have a look at this , is for acute pain.

Dear Mr. Henry,

Here is the reference for the paper I was talking about:

Thak you so much for answer,

the exemple i cited below was juste an illustrative exemple.

My experiment was indeed a 2 by 2 by 2 full design and I want to submit a paper with only 2 factors becuse the editorial review asks for that. So i'm asking if its methodologically right to use this same experimentation with only 2 factors (2x2)

Thank you all for your useful answers! 

How large is your object arena? If it is too large (i.e. the size you may wish to use for rats, etc) it may be too big for the mice, thereby making it appear as though they are spending less time with the objects, when in fact they may be spending a proportional amount when you take into account arena size. Someone else already mentioned the possibility of analyzing overall path/distance traveled I believe - this could also help. What are you giving the mice? If you are treating with a compound that may interfere with a key behavior in this task (i.e. mobility/awakeness/etc) that could be an issue driving your experimental animals to perform more slowly. Though typically in this task, there is no completing the task 'faster', as all animals should be given the same amount of time to explore for each portion of the task. Then, you can analyze the data (typically as a ratio) and compare to chance (50%). If i knew a little more about your specific paradigm I might be able to provide more helpful information.

Hi Hassan:

You say that you  want to investigate the relationship between physicians perspective around euthanasia on the one hand and their moral judgment in medical job on the other hand. Let me say that this theme of research is timely and worthy of being investigated. Timely, because euthanasia is nowadays a heated and highly debated topic in many countries around the world. Worthy of being investigated because there are few, in any study relating physicians' ideas and practice of euthanasia and their level of moral judgment and development.

Are you acquainted with Kohlberg's theory of moral development, namely with his three levels (pre-conventional, conventional, and post-conventional) and six stages of moral (1, 2, 3, 4, 5, 6) judgment and development?

As far as I see, you can profit a lot from seeing what you want to investigate from a Kohlbergian viewpoint.  

Is should be noted that Kohlberg created a hypothetical dilemma on euthanasia [see Colby, A., Kohlberg, L. (1987). The measurement of moral judgment. Vol. 2 (p. 279). Cambridge: Cambridge University Press. This dilemma follows:

"There was a woman who had a very bad cancer, and there was no treatment known to medicine that would save her. Her doctor, Dr. Jefferson, knew that she had only about six months to live. She was in terrible pain, but she was so weak that a good dose of a painkiller like ether or morphine would make her die sooner. She was delirious and almost crazy with pain, and in her calm periods she would ask Dr. Jefferson to give her enough ether to kill her. She said she couldn't stand the pain and she was going to die in a few days anyway. Although he knows that mercy killing is against the law, the doctor thinks about granting her request".

Several questions could be raised about this dilemma. The most important is the following: "Should Dr. Jefferson to give the drug that would make her die. Why/why not?".

Consider the case of a physician who says, for example, that the doctor should not give the woman the drug because it would be murder and, if he were caught up would be put in jail. This response (and this physician) would be a stage 1- oriented physician. With all likelihood he would not give the woman the drug.

Think now of a physician who says, for instance, that the doctor should not give the woman the drug because her husband needs her and wants her to live. This response (and this physician) would be a stage 2- oriented physician. With all likelihood he would not give the woman the drug either.

Stage 1 and 2 are in Kohlberg's theory pre-conventional stages because people at these stages only take into account egocentric, individualist, and personal wants, needs, and desires.

Consider now the case  of a physician who says, for instance, that the doctor should not give the woman the drug because  doctors are supposed to help people live or salve lives, not help people die. This physician would be a stage 3- oriented physician. Probably  he would not give the woman the drug.

Think now of a physician who, for instance, says that the doctor should not give the woman the drug because respect for the law will be destroyed if citizens feel that they break the law anytime they disagree with it or because taking the law into one's hands breeds disrespect for the law. This physician would be a stage 4- oriented physician.  Probably he would not give the woman the drug either.

In Kohlberg's theory, Stages 3 and 4 are conventional stages for at these stages people go well beyond egocentric reasons and take into account others' expectations as well as legitimate social rules and widespread  moral norms such as the  golden rule.

Think now of a physician who believes, for example, that the doctor should give the woman the drug because autonomy in making life decisions ought to be respected or guaranteed  as a fundamental right, or because true appreciation of the value of human life must include respect for the right of the individual to autonomy in making life decisions. This physician would be a stage 5 or stage 6- oriented physician. I say stage 5 or 6, because  the late Kohlberg gave up his stage 6 from a factual perspective, even though he has maintained it from an ideal perspective. Stages  5 and 6 are post-conventional  stages because  individuals at these stages saw existing moral norms and social rule as relative and, hence they must be violated when they do not protect  individual, not individualist,  fundamental rights. Because  of this, post-conventional  physicians would give the woman  the drug and would be  likely to accept the legal consequences of their apparently immoral acts.

As Kohlberg's theory is  structural, this means that his stages do not depend on the content or course of action advocated (i.e., Dr. Jefferson should/should not give the woman the drug), but on the reasons invoked to justify the chosen  course of action.

I hope that I have  got your question and that this helps.

Best regards.

PS. It would  be wonderful that  you could perform the research you intend to. Kohlberg' s theory is, in my humble opinion, a theoretical  framework on which you could base  your project.

Dear Kate, if you want to take into account the initial exploration of the objects as a baseline, you can utilize the recognition index (RI), as described in:

If the RI confirms the result obtained with the discrimination index (DI), then you might really have found a neophobic phenotype. You said you have counterbalaced for both the objects and the sides, but the best way to check for possible biases is to compare the RI and the DI. If you still find a significant aversion for the new object, then it would be interesting to investigate this phenotype with a different test. As Katherine suggested, you could use the novelty-suppressed feeding test, by which you can evaluate the hyponeophagia phenomenon (https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3197427/).

It sounds like what you propose has some similarities to the Between-Subjects research methodology. This design is not technically control group/experimental group design, but tests two different "treatments" applied to two groups.

Thanks for response .I understand . I think I should use more fish than that I need in case of this situation.

Dear Julia, 

check this out: 

Although I could not envision your task and the apparatus, if you want to counterbalance, I would divide both species into two groups and use the first and the second task in a counterbalanced design. Initially, half of the rats in for each species get test A, while the other half gets B first. Is it not possible to use a completely different test for the same behavior? What is the test, what is the apparatus?

Not familiar with the psychopy stuff, but does one of these actually tell it to send the trigger?

For example in matlab you would use the following to set up the trigger

 dio=digitalio('parallel','lpt1');

Port1.Trig=addline(dio,0:7,0,'out'); %Pin 2-9

putvalue(Port1.Trig,0);

And then the something along the lines of the following to send the trigger

putvalue(Port1.Trig,3); 

 disp('trig 3'); % display trigger information

putvalue(Port1.Trig,0);

I'm sorry if I've missed the point or if this is of no use.

Hi Frederico,

apologies for the late reply. We have also considered the floating home cage but there are some issues that it is too big to fit in our sound isolation boxes. Furthermore, it would be difficult to attach anything to the home cage to present various stimuli as the cage would become to heavy and stop floating.

But thank you for the suggestion.

Has anyone worked with this air-lifted home-cage before and can share their experience ?

Hi Gordon and Diogo:

Thank you very much for your comments. I really appreciate your help.

Vijay

How about the control animals and baseline values for the biochemical markers?

I assume you also have a control group that does not receive the treatment but only vehicle administration. You should include this control group in the 3-6-9 weeks tests. The number of animals should be similar to the treatment groups.

Additionally, you should consider baseline values for the biochemical markers in naive rats without any behavioral testing and drug treatment, because behavioral testing or possible stress from the drug/vehicle administration may also impact your biochemical markers.

I agree with the answers already given, but I would like to add: ECS can be used to measure seizure threshold.  If you are for example, testing antiepileptic drugs, it might be useful to find out if the threshold rises when the mouse has been given the drug.  Good luck!

Outcomes are  related to processes.Behavior is changeable concept.For understanding outcomes (Negative-Positive) need to make a check list or questionnaire based on your selected areas.As it is not enough, to prepare interview schedule,observe and check the answer with comparing check list or questionnaire's answer.Observation and discussion are the best way.But it  is controlled by context, time and sample size.Group interview might be possible.

We just generate a matrix over the field and record how many times the animal is in each square. Then you can analyse it any way you want. External square use, internal square use, distance from object, activity levels etc. It's cheap and easy.

Usually male animals are used for behavioral studies in order to get more reproducable results for their lesser effect of hormone influence

How do you define successfully developing diabetes? 

Depending on the severity of diabetes, their life-span without some intervention will greatly diminish.

What question are you trying answer by your study? Relationship of duration of hyperglycemia with cognitive impairment? Search through the literature to find what is already known in rats and go from there.

In case of humans, a good deal of information already exists. For example:

In the implicit test, each significant trait is associated with a positive, or negative value, which gives an estimation, instead of a measure of the trait, as acceptable or disregarded. 

@ Morten Bo Søndergaard Svendsen:

Hi Morten,

Thanks for your interest I will contact you shortly. And yes, open source is the way of the future in my opinion! I intend to have a repository for the software on GitHub so that I can track changes and additions. Thanks again!

Hello,

corticosteroid administration triggers some physiological pathways. First, hyperglycemia: you can measure circulating glucose. It responds to corticosteroid administration after a short time but remains elevated even after corticosteroid clearance. Second, immune response: corticosteroid administration suppress immune function, especially when administered chronically. Thus, you can measure  circulating immune protein (complement system), lysozyme, immunoglobulins, and acute phase proteins. Also, leukocyte related immune functions could be assayed.

They are the main effects of corticosteroid administration. But, corticosteroid administration also can reduce bone formation (long term osteoporosis),

See Sabine Hölter: Assessing Cognition [in mice]

Hi Analisa,

yes, as Vittorio Porciatti wrote, there is a reliable way to do that. It's the Westheimer paradigm (no "r" in Westheimer), and the field size that is measured by it is called the "perceptive field size".Oehler (1985) has even used it with monkeys, and the seminal paper is by Lothar Spillmann. There is a chapter in my review on peripheral vision on it:

(or go to my website, ww.hans.strasburger.de)

The amplification you need is dependent on the ADC resolution. For example in the Mosers' lab we used 20000x amplification because the ADCs were only 8 bits. With a 16 bit ADC the resolution is 256 times better, which means amplification can be reduced accordingly. So when I used 3000x amplification in Johan F. Storm's lab the spike waveforms were actually measured an order of magnitude more precise than in the Moser's lab, although the amplification was reduced by an order of magnitude. An 8 bit ADC does not have sufficient resolution to measure spikes and LFP simultaneously. A 12 bit ADC is borderline. 16, 24 or 32 bit ADCs can easily do this. [The ADCs I used in the Mosers' lab were actually 16 bit, but the software decided to throw away the lower 8 bits, storing the signal at 8 bit per sample.]

Check the dynamic range of the ADC board (typically about 3 V) and its resolution (bits per sample) and then calculate what measurement precision you get with your level of amplification. The trick when recording spikes and LFP simultaneously is to keep the amplification so low that the LFP does not saturate the ADC. This requires lower amplification than what you would use to record spikes without LFP (by a factor of 10 or so) and thus higher ADC resolution is required to get the same precision on the measured spike waveforms.

I assume you have made sure the hot plate is actually at 45 degrees and that there isnt an issue with the kit. 

There an numerous factors what can affect pain behaviour:

Firstly, have you changed supplier or have the supplier started sending you rats from a different colony? Are you certian they are sending SD rats? Has the constituents of the diet changed? (Seltzer et al saw a significant reduction in neuropathic pain behaviour when soy protein was added to their rat chow without them knowing). Have you changed experimenters, if not have you changed after shave or shampoo? Have there been any changed in animal care staff? Are there any works in the facility or in the surrounding buildings? Stress induced hyperalgesia is as real a problem as stress induced analgesia. The list could go on!

Another point is that over the years I've seen dramatic alteration of pain behaviour over the course of a year with a marked reduction over winter months. I've never had the resource to look into this effect methodically but I'm certain its not an artifact.