new to the lab? The lab manual is a great place to start

 
 

Introduction

Welcome to the MCAB Lab! The purpose of this extensive document is to orient you to the rules and regulations for everything related to the Motivated Cognition and Aging Brain Lab. Hopefully any questions you have related to the general goings-on, procedures, and expectations within the lab will be answered below. If not, feel free to reach out and ask, but not before making sure the answer isn’t right in front of you! This manual is a first point of reference for current lab members as we strive to achieve these goals, and serves as a general introduction for prospective members. You can also find the lab elsewhere:

•          Lab website: http://www.mcablab.science

•          Github *work in progress!*: https://github.com/orgs/MCABLab/

•          Twitter: This is Greg’s personal account, but most of the tweets are decision neuro related. If there’s a need or desire for an official lab twitter account, we’ll make one!: https://twitter.com/GregoryRSL

There are also a couple of sites that will be important (and exclusive) for lab members:

•          Journal Club: https://sites.duke.edu/mcablabjc//

•          Asana: https://app.asana.com/0/1133385694023257/overview

•          Trello: https://trello.com/b/eQ6xkHXZ/mcab-lab-pipeline/

•          Slack: https://mcablab.slack.com/

•          OSF: https://osf.io/faets/

In general, firm policies are in the lab manual, whereas ways of implementing these policies (i.e., getting stuff done) will eventually be on the GitHub so that they can be updated by anyone in the lab. Asana and Trello organize tasks that need to be done (and relevant discussions) for specific projects, rather than general principles.  Slack is for both general and specific conversations about lab and lab projects, and OSF is where we publish info about projects. Any information that is potentially private should go in a protected location. (You can read more about various lab resources further below.)

Although some information may need to be updated in the manual, assume that it’s an accurate source. This means that you should follow all of the policies and protocols contained in the manual. If you notice something that seems to be wrong, please let someone on staff know. If there is something in the lab manual that you notice people aren’t doing, please feel free to bring this up at lab meeting. In other words, if you see something, say something!

 
 

General

 
 

Funding

External funding supplies the vast majority of resources needed to conduct our research, including salary for personnel, equipment, subject payment, and so on. It is important that we run the lab in a way that shows we use our research funding wisely.

A few of our current funding sources include:

•          R01-AG043458 from NIH, ‘Dopaminergic Neuromodulation Of Decision Making In Young And Middle-Aged Adults’.

•          R24-AG054355 from NIH, ‘The Scientific Research Network On Decision Neuroscience And Aging’. An ongoing project.

•          R25-AG053213 from NIH, ‘Summer School In Social Neuroscience And Neuroeconomics’. Educational courses offered in the summer.

•          R25-AG053252 from NIH, ‘Forming Science-Industry Partnerships To Link Everyday Behaviors To Well-Being’.

Funding from NIH (through our own grants or those to collaborators) means that work in the lab is supported by the taxpaying public.

Big picture

We expect each other to:

•          Push the envelope of scientific discovery and personal excellence.

•          Do work we are proud of individually and as a group.

•          Double-check our work, and then triple check for good measure.

•          Be supportive—we’re all in this together. (Please don’t gossip/talk shit about people.)

•          Be independent when possible, ask for help when necessary.

•          Communicate honestly and transparently, even when it’s difficult.

•          Share your knowledge. Mentorship takes many forms, but frequently involves looking out for those more junior.

•          Work towards proficiency in Python and R.

•          Be patient. Including with your PI. He will forget things you just talked about, and repeat some stories over and over. He might change his mind without realizing it, so please remind him if that happens. He also may not text you back, but don’t worry, he still cares (and will always like your tweets).

•          Advocate for our own needs, including personal and career goals.

•          Respect each other’s strengths, weaknesses, differences, and beliefs.

•          Not make social comparisons. Everyone is on their own path and started in different places. Celebrate others successes and reach out for support when you feel inadequate (we all do at times).

•          Be great and stay great.

We should also expect everyone to have a professional and appropriate online presence. Try to keep any professional profiles (e.g. LinkedIn, OSF, ResearchGate) as updated and accurate as possible. Use of personal profiles (e.g. Twitter, Instagram, Facebook, etc.) is left up to you, but be responsible and aware as you would with any accessible information. Remember, we all represent the lab and the lab represents us.

Small picture

We’re sharing a relatively small space, so please be thoughtful of others, including (but not limited to):

•          With few exceptions, do not come to the lab if you are sick. Your health and the health of those around you is important, so save yourself a STINF and assume it’s okay to rest. If you are sick, email the lab manager or your supervisor to let them know you won’t be coming in, and update your lab calendar to reflect the change.

•          Don’t touch the thermostat… Unless the change is welcome by everyone.

•          Do not leave food, drinks, or crumbs out in the lab. Keep the fridge organized and clean. Please try to put food trash in another trash can (not in the lab), especially late in the day or on Friday.

•          Lock the door if there is no one in the lab, or if you’re the last person to leave. Ask for the lockbox combo in case you ever get locked out, but please don’t take the key with you anywhere.

•          To save energy, and for security, computers and monitors should be turned off at the end of the day if they are not being used overnight for analysis.

•          If you use the microwave, make sure it’s as clean and closed when you finish as it was when you started. No one wants to clean up other people’s splattered food.

•          All in all, keep the lab neat. Items left unattended may be cleaned, reclaimed, or recycled.

•          Make sure to fill up the coffee machine if you’re the last to have used it.

•          If there is a problem with any equipment in the lab or the lab space, contact Shuntoya (shuntoya@duke.edu).

Other Need-to-Knows

Always keep these in mind, and practice them regularly:

•          Dress Code: TAKE NOTE that there is a difference between dress code for the lab and dress code when running participants.

–         For the lab: Just wear clothes (appropriate for any academic/everyday setting).

–         When running participants: Please dress in a manner appropriate for a work setting. If you are going to be at BIAC at the scanner, at meetings with our collaborators, or running subjects, you are there as a representative of our lab and of our study. It is important to look like a professional, as this helps the participants and medical center staff perceive the study as professional. It gives the participants confidence in you when they undergo potentially intimidating experiences such as MRIs. This means no graphic T-shirts, no excessive bare skin, no ripped or baggy jeans, nothing that anyone would consider loungewear/pajamas, no flip-flops or crocs. Feel free to ask if you have questions about something being appropriate.

•          Communication is key. If you are going to be late for your lab slot, a meeting, or any other scheduled event, make sure to let someone know well ahead of time.

•          Some lab functions – lab lunches and social events – are recreational, however attendance to lab meetings and more formal functions is expected. Inability to attend the aforementioned events should be discussed in advance with the lab manager directly.

•          Information shared in the lab regarding ongoing studies/projects, about participants or lab personnel, or anything that would otherwise be considered ’sensitive’ should be shared only within the lab space.

 
 

The lab staff

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PI

MEET GREG!

You can expect me to:

•          Have a vision of where the lab is going.

•          Care about your happiness and success.

•          Obtain the funding to support the science, and the people, in the lab.

•          Support you in your career development for whatever career you choose, including writing letters of recommendation, introductions to other scientists, conference travel, and promoting your work as often as possible.

•          Support you in your personal growth by giving you flexibility in working hours and environment, and encouraging you to do things other than science.

•          Treat you to coffee or lunch. I always accept FLUNCH requests from undergraduates to share a meal with you or a group of students.

•          Make the time to meet with you regularly, read through your manuscripts, and talk about science.

•          Obsess over font choice, punctuation, and graphic design.

•          Be a human being who is also trying to manage my own personal and professional life. I will make mistakes. I will get stressed and overworked. I will lose track of things. You may feel ignored/neglected/underappreciated. Please communicate with me. I am very open to criticism. Know that I always want to do better and understand that everyone has their own unique style and needs.

Postdocs and Staff Scientists

I expect postdocs to transition to independence (i.e., move towards being more PI-like), including giving talks, writing grants, and cultivating an independent research program while still supporting the lab’s research. And, to have (or acquire) the technical and open science skills listed for PhD students, below.

Postdoc salaries generally follow NIH guidelines (regardless of the source of funding).

PhD students

I expect PhD students to:

•          Know (or make an effort to get to know) the literature related to their topic like the back of their hand.

•          Seek out and apply for fellowships and awards (including travel awards, etc.) and encourage me to nominate you for awards.

•          Realize there are times for pulling all-nighters (NOT in the lab!), and times for leaving early to go to the park and enjoy the sunshine or taking a mental health day off.

By the time you’re done, you will have to know how to do statistics and plots in R, share your work with me using Rmarkdown, use scripts for data analyses, know enough Python to navigate presentation in PsychoPy, compile figures and create posters using Adobe Illustrator or a similar graphics program, and give a clear and accessible public talk. You will also preregister your experiments when appropriate (which it almost certainly will be) and share your data and analysis scripts publicly. The learning curve can be a little steep on these but it’s well worth it. (If these aren’t compatible with your goals or interests, my lab is probably not a good fit for you!)

Employees

Employees – whether full-time or part-time – are expected to use their time efficiently to support the projects to which they are assigned. Paid employees will typically have the most interaction with other staff, and with research participants, and in these contexts especially should be a model of professionalism.

Hours

Full time employees are expected to satisfy the equivalent of 40 hours worth of work per week (typically within the 9:00–5:00 window). If you are testing participants outside of this time, we will adjust accordingly for those weeks. You are expected to hold yourself accountable for fulfilling these hours. Per HR policy, you must work at least 40 hours per week to maintain full-time benefits eligibility.

Time off should be requested in advance, via email. Once approved (via email) please add to the lab calendar.

Sick time should also be requested over email. Per HR policy, full-time employees are allowed up to 5 unverified sick instances per fiscal year (beyond this medical verification is required).

(Note that graduate students, postdocs, and staff scientists are given more flexibility in their hours, provided they make sufficient progress on their projects. This flexibility does not extend to other paid positions because we need to maintain a consistent lab presence for scheduling, supporting undergrads, interacting with other staff, and so on.)

It is important to document these requests (and subsequent approval) over email so that we have a record. It is your responsibility to make sure this happens.

Timesheets

•          Hours entered on your timesheet should reflect hours actually at work.

•          Web clock times should be entered from the lab (from a lab computer—not your cell phone).

•          Submit your timesheet before the due date.

 
 

Undergraduate students

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All Undergraduates

We expect undergraduates to be reliable and willing to help with whatever projects need it. At a bare minimum, reliability includes showing up on time, regularly checking in, and making sure that all of your work is accurate (double-check everything). If you find yourself without a specific project:

•          Ask around to see if you can help with anything.

•          Look on Trello to see if all tasks are up to date.

•          Ask around (again!)

There is enough to do that you should not be bored!

Your first semester in the lab is an opportunity to see whether continuing in the lab is a good fit; after your first semester we can discuss whether you will continue. If your interests shift, we will not be offended and will be more than happy to help you find a new lab and make that connection for you.

GwD capstone students

We expect GwD students will be organized and independent, and manage their time and responsibilities so that they complete a project by the end of the year, which requires being somewhat strategic in the topic we pick. The written report is typically due at the end of April, with an oral presentation in early May.

To actually collect a reasonable amount of data, it is almost always necessary to start collecting data during the Fall semester, which may be challenging because of class scheduling. Be prepared ahead of time!

At the outset of your capstone project, please make a to-do list on Trello with planned due dates and keep this updated throughout the year.

It is your responsibility to check what the requirements are in your program and department, and make sure to get your project submitted by the deadline.

Deadlines for the GwD Project can be found here: https://dibs.duke.edu/undergraduate/program/graduation-with-distinction

Independent study students

Undergraduate students in the lab during the year can enroll in an independent study section to receive credit and a grade for time in the lab.

Independent study students should plan on producing an annotated bibliography of 5–10 articles on their selected topic, and making a 15-minute presentation at lab meeting sometime during the semester and completing the research paper at the end of the semester.

 
 

university policies

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Sexual harassment

University policy requires that if any faculty member (such as me) becomes aware of sexual harassment or abuse involving students or employees we must report it to the Title IX Sexual Harassment Response Coordinator. Counselors and other medical professionals on campus who discuss these issues in their professional capacity can keep patient confidentiality.

 
 

Communication

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Communicating With Greg

I love the many responsibilities of being a professor and scientist, but I am almost always busier than I’d like to be. As a result I have less time for talking to folks than I’d like. However, you (lab members) are the most important parts of my job, and I need your help to stay organized and involved in the things I need to be involved in. Some general rules of thumb are:

1.        Be proactive—tell me what you need. This includes coming to knock on my door even if it seems like you are interrupting, texting/emailing me to set up a time to meet, or catching me before or after lab meeting. In all likelihood I will not check in with you as often as I’d/you’d like, so it is up to you to make sure nothing falls through the cracks.

2.        Write things down and remind me what we’ve talked about. I would love to remember everything we decided when we met last week, but this doesn’t always happen. Don’t hesitate to bring me up to speed when we meet. Even if I already remember what we are talking about, a couple of introductory topic sentences will help get me in the right frame of mind. Be sure to write down everything in your lab notebook and Trello!

3.        Read all of the lab documentation: this lab manual, the Slack and Trello. You are responsible for knowing what is in each of these places, following the rules and guidelines we have set up, and notifying someone if you find incorrect information (or if you have questions).

4.        I can be the most helpful to everyone if you are a little bit strategic in what you ask me. Please check with other people in the lab, and a Google search before shooting me off a question

My office

My door is always open, but if I am in a meeting please only interrupt for something very urgent. Otherwise, please send me a slack message or try another time.

Communication within the lab

Lab meeting

We meet once each week to talk about science together, and to make sure we have a chance to touch base on administrative and practical issues. There may even be a snack if the lab manager has the time to bring one. Regular attendance and participation is expected (unless you have a class during that time).

ASANA + Slack

All lab related communications should be directed to Slack. Before starting a new discussion thread or conversation, ensure that your specific topic/question/inquiry has not already been addressed on one of the #channels. Please use these channels appropriately, we can all see them! 

Asana is the main tool for lab task organization communication. Please help by keeping Asana up to date and neat! A few thoughts and tips:

•          Use the to-do lists, both for yourself and others.  Oftentimes pre-existing lists will have already been created, and you will be ‘tagged’ in specific tasks under a topic.

•          When you post a message, you can optionally have it emailed to people on the project. One of the nice things about Asana is that it can reduce the amount of email we have to read. It’s still advisable to hold important discussions on Slack or in person, though.

Email

Just to reiterate, again, use Slack when you can. But for projects that include collaboration with other labs or the need for document sharing, email is also appropriate. 

With this in mind, please prioritize reading any emails related to MCAB lab staff or projects. These will usually be time-sensitive and should be addressed as soon as possible (especially if you’re directly mentioned!).

Google Calendar

We have a lab calendar! Please refer to it for any upcoming trips/conferences and other key information. If you have yet to be added, speak to the lab manager.

Communication outside the lab

Communicating to people outside the lab is extremely important: your actions reflect not only on yourself, but also on the lab, the lab director, the department, and the university. This is true both for participants (who volunteer for our studies) and scientific colleagues (whose opinions have a direct impact on our success and opportunity—they are the ones reviewing our grants and papers and our future promotions!). It is important that every time one of us represents the lab to a high level of quality. The less experience you have, the more preparation is required. Don’t skimp!

Phone

•          If the phone rings in the lab, answer it: identify the lab and your name. Most calls will be from potential (or current) research participants, so it’s important they view us as professional and competent. “MCAB Lab. This is [your name here]. How may I help you?” is a great start. Remember that many people calling will be older and/or have hearing loss, so speak slowly and clearly.

•          Try to check voicemail messages daily to make sure nothing important slips through.

•          If someone calls the lab and leaves a message, call them back within one business day to confirm that we received the call. If they would like to participate in a study but we can’t schedule them, thank them for their interest and ask if we can contact them in the future should one come up (if you actually will). If you are not going to contact them (or they do not qualify), tell them that we are done recruiting for that study and do not have anything else available, but thank them for their interest.

 
 

 MCAB LAB PURCHASE POLICY

 
 

All Lab-Specific Purchases — including but not limited to Office Supplies, Food/Beverage/Condiments, and other miscellaneous items for lab use — will be going through Addison Troutman

A link to the Lab Order Request Form can be found here. Please use this portal to submit item requests (e.g anything from coffee filters to manila folders to snacks for a Methods Meeting).

All P-Card Purchases — including but not limited to Conference Travel, Registration Fees, and other miscellaneous purchases related to sponsored external lab activities — will be going through Addison Troutman.

If you are planning to make a P-Card Purchase:

    1. Email or Slack the lab manager (LM) directly prior to your planned purchase.

    2. After receiving the text, you will receive a digital copy of the P-Card Purchase Info Page (note: this page has very sensitive card information which should only be used for approved purposes).

    3. Use the Purchase Info Page to complete your transaction.

    4. Immediately after the payment goes through and you receive the receipt, go to this page and fill out the P-Card Order Request Form, where you will fill out information about the Purchase as well as attach the receipts.

Please note that failure to follow through with these guidelines may result in the removal of your P-Card use privileges (meaning all your purchases will need to be done through the reimbursement process instead). 

If you have any questions or concerns, or any issues or feedback on the form, please reach out to the LM.

For Reimbursementsincluding but not limited to Conference Travel, Registration Fees, and approved food purchases:

If you are planning to submit a Reimbursement Expense Report (with approval from the PI):

  1. Go to work.duke.edu

  2. Log in using your netID

  3. Click the tabs in the following order:

    MyInfo > MyExpenses > Create My Travel Expense Report

  4. Under Schema select Domestic Trip (698600)

  5. Put in the following information on the first page:

    Start Date: (has to be before date of first receipt)

    End Date: (has to be after date of last receipt)

    Activity: Conference (or other activity depending on trip specifics)

    Reason: (example: SRNDNA Research Conference)

  6. Important: Change the cost assignment to 4314639 (this is the PI Startup Code)

  7. On the next page, click New Entry

  8. Note that you’ll have to select the correct g/l code for the given expense type

    ***note that these g/l codes are subject to change

  9. Depending on what fundcode these charges should be charged to, you may have to click change cost assignment under each receipt and modify the entered fund code (note that a fund code can be either a cost center or a WBS Element, but not both)

  10. Once the receipts have been entered, you’ll want to save the draft and manually upload the associated paper/electronic receipts for each charge you listed

    ***note that these must be in PDF form and should be itemized in accordance with the order of invoice entry

 
 

all things scientific writing

 
 

Manuscripts

General

•          Always show a manuscript (or revision) to all authors two weeks (unless minor revision, then one week is okay) before submitting it, giving them the opportunity to comment.

•          Go over page proofs carefully, including the references. There is almost always a mistake (ours, or introduced by the publisher).

•          All of your figures should be EPS files with print resolution raster images (at least 300dpi).

•          Always give the senior author the opportunity to look at page proofs (most importantly to make sure they didn’t rasterize the mf figures).

•          Life span or life-span development but not lifespan. Decision making or decision-making task but not decision-making (f you for even suggesting that Word).

•          For intervals and minus signs use en-dash (–) not a hyphen (-). Em-dash (­—) is used to separate out a phrase within a sentence — such as this one right here — but not otherwise. Hyphens (-) are used for joining words as in life-span development.

Naming Files

•          When naming files, always use underscores to separate words, never spaces or dashes.

I generally do not like to get files in email. Share a Dropbox folder (or Box if you have to) that contains the file you want me to edit or comment on. I will track changes but not save it as a new version (since these things have version control/history). I prefer not to have more than one manuscript file, supplement file, etc. in each folder. I don’t want to see 6 versions with different dates. If you want to save a whole bunch of versions separately, please do that in another folder called “versions” or something.

See also: http://www2.stat.duke.edu/~rcs46/lectures_2015/01-markdown-git/slides/naming-slides/naming-slides.pdf

Figures

If we are still trying to work out what a good figure looks like, I’m happy to talk this through with you and look at rough drafts. However, if we have a good idea of what we want in the figure, please send me something as finished and polished as you can make it—this makes it easy for me to give the most helpful feedback. If you give me something that isn’t your best work, I will probably just tell you things you already know.

Most figures should be vector art (saved as PDF or EPS files). Vector-based files don’t suffer the artifacts and poor quality that raster-based images show when magnified. Use a graphing program (such as R, Matlab, or JASP) to export to an EPS or PDF file, and then compile/arrange/modify these elements in Adobe Illustrator or other image-editing program.

Don’t use Microsoft Excel/PowerPoint for your figures! It’s always the worst option and the figures paste terribly into anything else. If you must organize your data in Excel, that’s fine, but then do plotting in a better plotting program (e.g., R, Matlab, Python, STATA, JASP).

Abstracts

Anyone submitting an abstract for a conference, symposium, etc. should clear this with me first, and circulate to all authors at least one week before the submission deadline.

Talks

Anyone giving a talk to a non-lab audience is required to give a practice talk to the lab at least one week before the real talk. If this is your first public talk on a lab project, plan on at least two practice talks (starting at least 2 weeks before the real talk). Practice talks should be mostly finished (final slides, practiced, and the right length) so that our comments will be as helpful as possible. Schedule one or more meetings with me ahead of time to plan or go over your slides, especially if you haven’t given many talks before.

Posters

Anyone presenting a poster should circulate an initial version to all authors at least one week before the printing deadline. Use something similar to another lab member’s recent template so that our posters have a somewhat consistent look to them. If this is your first time using Illustrator or Pages, make sure to leave plenty of extra time so you can learn how to use the software.

Make sure to double check the poster size and orientation for the conference, and the size of the paper or canvas it will be printed on.

For many conferences you will want to bring a sign-up sheet where people can request an emailed PDF or print a QR code that links directly to: https://www.mcablab.science/presentations

 
 

Big picture science

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Big picture science

Scientific integrity

You have a responsibility to me, the institutions that support our work, and the broader scientific community to uphold the highest standards of scientific accuracy and integrity. By being in the lab you agree to adhere to professional ethical standards. There is never an excuse for fabricating or misrepresenting data. If you have any questions, or in the unlikely event that you have concerns about a research practice you have seen in the lab, please talk to me immediately.

It is also important that you prioritize the accuracy of your work while in the lab. Unintentional errors due to inattentiveness or rushing can be extremely damaging and produce results that turn out to be incorrect. Although you may feel pressure for a high quantity of research, it is critical that everything we do is of the highest quality. Please double-check your work frequently. In many cases multiple people will double-check a data set to ensure no mistakes have crept in along the way.

Open, accurate, and reproducible science

Open science

We are working towards putting all stimuli, data, and analyses online and linked to each research publication. The idea is not to simply tick a box of “open science”, but to make these resources readable and useable for reviewers and other researchers. In service of this:

•          Items need to be documented and described. At a minimum, each collection should have a README file at the top level that provides details about the item in question (such as a set of stimuli or an analysis).

•          Code should be tested, bug-free, and helpfully commented.

•          Links should be permanent (ideally a DOI).

In pursuit of this high level of organization and documentation, lab members will frequently be asked to review and error-check lab materials (including video files, text lists of stimuli, etc.). Lab members creating stimuli or conducting research projects should organize them from the outset in a way that is conducive to eventual sharing (GitHub, iPython notebooks, etc.).

Accurate science

A key part of accuracy is anticipating and avoiding “adverse events” (including near misses), and creating structures in the lab that facilitate a high level of reliability.

Examples of adverse events include:

•          Any of the lab computers malfunctioning (including freezing or crashing)

•          Not being able to find the installation information for a software program

•          Nearly running out of money to pay participants (this counts as a “near miss” which we also need to discuss)

As a lab member it is your responsibility to be aware of times when things don’t go as planned and bring these to the attention of the rest of the group. Even better, let’s all work together to find ways of preventing such occurrences in the future.

 
 

Practical science

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Setting up a research study

Anyone starting a new research project should follow this approach, which I’ve adapted from other labs. The goal is to have a consistent way of doing things in the lab that encourages open science, collaboration, and me being able to understand your project after you have left the lab.

•          The main repository. Start a project on Open Science Framework (OSF) with me as a contributor for your project. This project should contain a descriptive README.md file that gives the study background and hypotheses, a description of all of the files in the repository, and links to any relevant files not in the repository. Basically, with the README.md file, another researcher should be able to understand and repeat the study.

•          Data. The OSF repository should contain the programs used to collect the data (e.g., EPrime, PsychoPy, etc.), any raw non-MRI data, processed data used for statistics, etc.

•          Stimuli. Stimuli should be uploaded to OSF before data collection starts. These could be in the main repository, but if they might be used by another study—which is often the case—they should have their own repository, and be linked from the lab website.

•          Statistics. Scripts for analysis—for example, from R or JASP—should be in the OSF repository. Scripts should be written to use the open data as much as possible; for example, by getting data directly from OSF rather than from the local disk, or by including code to handle MRI data downloaded from a shared repository. Wherever possible scripts should also generate figures as close to those in the paper as practical.

•          Final figures. EPS and PNG images of final figures should be in the repository with an explicit CC-BY creative commons license so that the figures can be re-used without charge by us and others (e.g., in review articles).

EXEMPT RESEARCH studies

There are formal procedures for conducting anonymous online studies in the lab. We have an exempt protocol (Pro00101720: Online Studies on Decision Making Across the Lifespan) that includes many online activities that do not involve identifiers or protected health information (PHI). If you are planning to launch an anonymous online study, you should familiarize yourself with this protocol.

You should include the following text at the beginning of every anonymous online survey:

The purpose of our research is to understand decision making across the lifespan.

Then, you will include one or more of the following, depending on which apply to your particular study:

- You may be asked to complete tasks used to measure cognitive abilities.

- You may be shown words, sounds, or pictures and asked to rate them.

- You may be asked to answer questions regarding financial and/or health related choices. You may also be asked to complete tasks involving social and/or monetary rewards.

Finally, you will include the following:

Participation is voluntary and refusal to participate will involve no penalty or loss of benefits to which you are otherwise entitled. You may discontinue participation at any time without penalty.

For questions about the study or a research-related injury, or if you have problems, concerns, questions or suggestions about the research, contact Dr. Gregory Samanez-Larkin at (919) 681-5575 during regular business hours. For questions about your rights as a research participant, or to discuss problems, concerns or suggestions related to the research, or to obtain information or offer input about the research, contact the Duke University Health System Institutional Review Board (IRB) Office at (919) 668-5111.

The above statement will be displayed instead of an informed consent.

Participants

Our research is made possible by the goodwill and generosity of our research participants. We not only need people to participate in our studies, but to try hard to do their best, and potentially return for a future study. Caring for our participants is one of the most important parts of the lab and something in which every member plays a role.

The most important thing is that participants must always be confident that we are professional and treating them with respect. All of the specific advice supports these goals. In general, it is helpful to model our interactions off of other professional situations, such as a doctor’s office.

For all participants:

•          Dress professionally: No jeans, t-shirts, sweatshirts, sneakers, or sandals. When in doubt, ask! This is true for both young and older adults—dressing professionally will help participants to take the experiment seriously.

•          Answer the phone, and return all phone calls (and emails) promptly. Tell participants who you are, and where you are calling from: “Hello, this is [name] calling from the MCAB Lab at Duke University. I am returning your call from yesterday regarding a research study.”

•          Be prepared to answer questions. If you don’t know the answer, it is completely fine to ask the participant if someone else can call them back. You are then responsible for making sure this happens quickly.

•          Arrive at least 30 minutes prior to testing time to make sure equipment and paperwork are all set, and to be around in the event the participant shows up early. Everything should be set up before the participant arrives. For people coming from off campus, you should be at the designated meeting spot 15 minutes before the agreed upon time.

For non-students, and especially older adults:

•          Always use a title (Dr./Ms./Mr.) and a participant’s last name when addressing them. If you aren’t sure how to pronounce their name, ask them.

We can also help participants feel more at ease by being thoughtful about the language we use. For example, participating in a “research study” is more friendly than being a “subject” in an “experiment”.

Terms associated with research studies

Instead of Saying - Say This:

Experiment - Study, Research Study

Subject - Volunteer, Participant

Test - Task, Screening

Some participants are involved in multiple studies, and they may lose track of which person is associated with which study. Make sure to remind participants you are calling or emailing that you are from the MCAB Lab and a general study name, and clarify the location for testing when the time comes.

Subject payment

We typically pay our subjects in cash—this is easier for them, and thus we are more likely to get repeat subjects. One of the lab members takes out a cash advance, and then people testing participants will take out what they need to pay the subjects. Each subject signs a payment sheet to document that they got paid. Naturally, it is very important that we keep track of this money.

•          If you are running subjects and take cash from the advance, you are responsible for returning signed forms and/or cash equaling that amount. If you lose the forms, you will have to track down the subject and have them sign a new one, or pay back the missing cash out of your pocket.

•          If you are the one taking out the advance, you are responsible for reconciling the advance (and any shortfall not otherwise accounted for).

Testing locations

•          Many of our shared testing locations are shared with other researchers, so it is very important that we are good citizens when it comes to using these spaces. Being a good citizen includes scheduling the time as required, not using more than our allotted time, and leaving the room as clean as we found it (or preferably cleaner).

•          No lab equipment should be left in testing rooms—this includes laptop, chargers, etc. (It all lives in the lab.)

•          No one should test a subject without signing out the testing room.

Lab notebook

Anyone conducting an independent research project should have a lab notebook for keeping track of discussions, experiments, and taking notes. You may also want to use an electronic notebook (e.g., Evernote) as your primary lab notebook, or to supplement a paper copy. The important thing is that you are keeping notes, and they are in one place.

Computers and data

General guidelines

•          Testing laptops should never leave the lab except for testing. Always sign out the computer and any other equipment (such as the EPrime key) on the lab resources calendar.

•          Do not install extraneous software or store personal files on the computers.

Backing up your files and data

Always assume that as soon as you turn your back the computer on which you have been working will explode. Thinking such dire thoughts will make it easier to follow these guidelines:

•          If you save files to the shared lab drive, backup will automatically happen. When working on a lab computer save all of your files to the shared drive. If you are working on lab projects on your own computer, transfer these files to the shared lab drive regularly to make sure they are in one place, and backed up.

•          Full-time employees should back up their computers on an external hard drive, preferably through an automated backup program (such as Apple’s Time Machine or SuperDuper!) that runs at least daily.

•          Data from participants is irreplaceable and should be removed from testing computers immediately following testing and onto the lab server in the “outputs” folder for the appropriate study (found in the “projects” folder).

Make sure your work is always backed up.

 
 

Recommendation letters

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REc letters

It is part of my job (and, thankfully, quite often a pleasure) to write letters of recommendation for people in the lab. Please give me as much notice as possible, and make sure I know the deadline, format (electronic? printed?), official name of the organization, what you are applying for, and so on. Please also send along a current CV.

If you are an undergraduate in the lab, I will write your letters on my own. For undergraduate who only take my courses (or are brand new to the lab), I will ask for much more assistance in preparing the letter. For more senior lab members, I will also write your letters on my own, but please send me a draft of at least a few paragraphs (which I will extensively modify) that you think should be in the letter. The first few times you do this it will probably feel awkward. However, keep in mind that your goal is to make it as easy as possible for a letter writer (in this case, me) to complete the task by the deadline and without error. Even though I will re-word a lot of the letter, it will still have the name of what you are applying for and details regarding how long I have known you, the projects you have worked on, and so on. This is extremely helpful in jogging my memory and will give me more time to focus on saying good things about you. Don’t worry about being too “braggy”; I have no problem toning things down if needed (but it probably won’t be needed). Also, you should get used to taking pride in what you do. Expressing how great you are in someone else’s voice will probably feel a bit awkward but hopefully also helps you appreciate your own greatness.

Like everything else, communication is key, and when in doubt, ask!

 
 

LEARNING TO CODE

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Computer programming (i.e., coding) is an essential skill that all students within psychology and neuroscience should develop. Being comfortable with computer programming—especially Python and R—will enable you to develop your own task scripts and wrangle data much more effectively.

Yet, learning computer programming is a challenging task and the learning curve can be rather steep. In most situations, you will not learn how to code from psychology/neuroscience classes at Duke. Instead, you will learn from online training materials, software manuals/tutorials, other students/trainees, and your own experiences. Having a specific problem or goal in mind (e.g., program a new task or analyze a new dataset) helps considerably.

 

While you’re learning to code, keep the following points in mind:

·    Be patient and persistent. No one “gets it” immediately, and you will sometimes have to work through dozens of errors before arriving at a solution.

·    Be careful and obsessive. Most coding mishaps occur because of a tiny typo. If you’re thorough, you will catch these mistakes and save yourself time and frustration.

·    Understand input and output for all scripts you use.

·    Have a basic sense of how each line of code relates to other lines of code in your script. Everything is connected.

·    Paths errors are common. Avoid them by shoring up your understanding directory structures. Every input and output file lives in a specific location that you control.

·    Avoid staring at the same error for more than 30 minutes. If you haven’t solved it in 30 minutes, switch to some other work or take a walk outside.

·    Don’t be shy about asking for help. Other students/trainees and Internet forums (e.g., NeuroStars, Cookbook for R) are great places to find help.

 

·    Utilize as many resources as you can find. Duke has a great hub of information on specific languages, such as R and Python, that can be accessed either online or through the range of workshops they do throughout the year (https://library.duke.edu/data/data-visualization).

 

Although learning to code can be a daunting and frustrating task, it is well worth the investment. Coding is a skill that will generalize well beyond the laboratory