How to write a letter to the editor when submitting a manuscript for publication.

First of all, check the submission guidelines for the journal that you want to submit to. If there is any information regarding cover letters to editors for manuscript submission, this will overwrite everything I say here.

Second, disciplines vary widely in their conventions regarding cover letters and in some it is in fact considered bad taste to write one. If you don’t know what the standard in your field and there is no information on the journal page, ask senior colleagues or email the journal or editorial office if you should submit one or not. (Be ready to receive an arrogant reply because people are often ignorant of the fact that cultures and conventions can differ substantially but by no means take it personal.)

If there are no clear guidelines against a cover letter and you have not encountered horrified faces/email replies when asking around, just write it. Even if it is not obligatory, just do it. The goal of this letter is to make the editor’s job easier (remember these are overworked academics who do this as a side job) and this ultimately can have a positive effect on how and how fast your submission will be processed. Here are tips how I do it (template and mini-summary below):

Here  is my template for a cover letter. Feel free to use this alternative template (sorry I forgot where I got it from) or another template from one of these pages with more helpful tips:

What I need you to take home from this:

  • Know and communicate what article type you are submitting and make sure it fits ALL requirements in the guidelines for authors!!!!
  • be concise and professional, jokes are strictly prohibited (even if you are best friends with the editor!)
  • do not oversell your research
  • avoid jargon and name dropping
  • clearly communicate why your article should be published in this journal
  • make sure you include all legally required statements (Guide for authors!)

How to review a manuscript for a journal.

Good reviews are supportive, constructive, thoughtful and fair. They identify both strengths and weaknesses alike and offer concrete suggestions for improvement. Good reviewers acknowledge their own biases and knowledge limitations and justify their conclusions.

Bad reviews are superficial, petty, and arrogant. Bad reviewers are very opinionated but typically don’t justify their biases. Their reports focus on weaknesses only but don’t offer solutions or other form of helpful feedback.

In today’s session, I walked you through the review process and told you how I write review reports:


Here you can find a template for the review report.

Additional ressources: offers a detailed step by step guide. offer additional advice and concrete examples of how to express criticism diplomatically. features a lot of personal strategies and experiences which are often different from what I do.

Where I stole the summary from (almost word by word):

How to stay on top of trends and findings in your field.

Keeping up with the literature and current issues is challenging. But thanks to different tools you can make this an easier task. The best tool in my experience is Google Scholar ( If you don’t have a profile yet, make one today. You can use it to follow colleagues’ publications, track citations of seminal papers, and get recommendations based on your usage or core papers in your field.

If you are interested in the output of a certain lab and they are not active on google scholar, you can use tools like to track their publications. This obviously only works for labs that have a frequently updated website.

Twitter is an amazing tool to stay up to date with current discussions and topics in your field. It takes a while until you figure out whom to follow, but it’s worth the investment.

Another useful tool to find older but still important papers is Mendeley. Technically this is a citation manager and library tool, but you get recommendations based on the articles in your library. Most of the time I find them very useful.

Journal updates are useful but should be limited to a few journals. The maximum of what I find manageable is 3. I follow Brain and Language, Behavioural and Brain Sciences, and Neuroscience and Biobehavioural Reviews. I only scan the headlines when the articles come in and decide if and what i will read in detail.

Researchgate can be useful if a lab is very active, but most of the time it is only selectively helpful to keep in touch/utd with a certain group. These ~10people I interact with on Researchgate only are the single reason why I still have my profile there.

Search alerts for journal databases like PubMed ( or Web of Science ( can be great tools if you figure out good search  terms and restrictions. I have not succeeded with this, but I found this blog with seemingly useful recommendations: There are also tools like Pubcrawler or Pub-Chase (which I will certainly try out next because it looks great!).

The mist important thing is to get 2 types of reading integrated into you academic life:

  1. Quick scanning of the newest output and deciding what  to read (should be done weekly at least).
  2. Extensive reading and broader researches for articles.

More details and tips in the video:

A practical guide to linear mixed effect models in Rstudio

In this episode of the Academic Crisis Line, Stacey Humphries and I gave a practical introduction to linear mixed-effects models. We talked about the background and key concepts about LMEMs, focused around 5 key questions that people often have when starting to encounter LMEMs for the first time.

  1. Why is a LMEM better than an ANOVA?
  2. What are fixed- and random-effects?
  3. What is the difference between a random intercept and a random slope?
  4. Should I include random slopes in my model?
  5. How can I tell if my model predictors significantly affect my dependent variable?

For answers to all these questions and more, check out the video! We also briefly walked through some practical aspects of running these analyses in R, but unfortunately the stream died at this point. We tried to re-record the parts that were lost, so this is annoyingly split over 3 videos. We hope it is useful nonetheless.

Video links:

Part 1:


Part 2:

Part 3:


We mentioned a lot of different papers and links in the video which are listed here for your convenience, along with a few others you might find interesting:

You can find the visualisations of random intercepts and random slopes that we walked through here:

Bodo Winter put together some fantastic tutorial for LMEMs:

Clark (1973) The language-as-fixed-effect-fallacy:

Baayen et al. (2008) Mixed-effects modeling with crossed random effects for subjects and items

Barr et al. (2013) Random effects structure for confirmatory hypothesis testing: Keep it maximal

Bates et al. (2015) Parsimonious mixed models

Matuschek et al. (2017) Balancing Type I error and power in linear mixed models

Baayen et al. (2017) The cave of shadows: Addressing the human factor with generalized additive mixed models

Luke (2017) Evaluating significance in linear mixed-effects models in R

Summary of Luke (2017) by Richard Morey:

Brysbaert (2018) Power analysis and effect size in mixed effects models: A tutorial




If you have any questions that we didn’t cover, please feel free to tweet us (@_SHumphries, @FranHartung, @Ph_Dial), or email us (hstace[AT], fhartung[AT]

Reblog from Cogtales: Rejection report Part 1


Sometimes, things just fall into place:  The evening before the most recent Academic Crisis Line on dealing with rejection and frustration, I got a pre-holiday manuscript rejection. As pointed out by the crisis liners, rejection in academia happens to everyone on a rather regular basis. So what we should really be concentrating on is to deal with it in the most self-preserving and productive ways possible. One thing that can really help is to talk through it, and to connect with others in similar situations.

So I thought it would be an interesting experiment to share my unfiltered thoughts while I deal with this rejected paper here on this blog.

View original post 886 more words

How to deal with rejection & frustration

Being able to deal with rejection and frustration is a key academic skill. The earlier you learn it, the better. Whether you get roasted in a Q&A session, have to deal with constant cynical remarks from peers, get a series of papers or grant proposals rejected, or deal with the endless frustration of university bureaucracy and interpersonal conflicts – negativity lures around every corner. It’s time to pick your weapons.

With my friends Dr Molly Berenhaus and Dr Christina Bergmann, I chatted today about our strategies to deal with the everyday rejection and frustration in academia. In the session we talked about First Aid as well as Long Term Prevention strategies. You can rewatch the discussion here (most important take home messages below):

  1. Understand that this is part of your job. Your experience is not unique to you -everybody deals with the same shit. Promised.
  2. It is also rarely personal.
  3. Never, NEVER act in the heat of the moment. Buy yourself some time and try to keep the situation under control.
  4. No public rants about your failures, unfair treatment, or colleagues. There is a time and place for the much needed venting, but this is not on social media and not in public.
  5. Take it as a lesson to become better as a researcher, as a writer, as a reviewer, as a teacher or supervisor, as a colleague, as a recruiter.
  6. Try to localize the problem and be open to change.
  7. Internalize the constructive message, not the negative feedback.
  8. Reach out for help. Avoid getting isolated at all costs.
  9. Protect yourself from negativity by keeping a lot of work in the pipeline. Don’t put everything on one project.
  10. Celebrate each success.

How to manage your supervisor

Today I talked about the relationship with your supervisor. The role of your supervisor is to provide you with an environment suitable to develop your academic skills in order to become independent and to finish your thesis in a reasonable time. In turn, your supervisor expects from you commitment, involvement, and accountability. It is important to understand that your supervisor is also a person with strengths, shortcomings and an own agenda. Luckily, it is usually in your supervisors best interest if you succeed because your success is also their’s. In order to have a functional relationship with them it is crucial to build on strengths and develop strategies to deal with difficulties. You are just as responsible to nurture your relationship with your supervisor as they are. In the live session, I discussed different types of supervisors sand how to deal with them:

Most supervisors are a combination of the different types and you will have to figure out TOGETHER what works and what not. Keep in mind that academics usually never receive any training for supervising. They depend on your feedback and openness to try different strategies.

There are a few general rules which will help your relationship with all of them:

#1 Talk open about expectations, communication, and concerns. Most catastrophic supervisor-student relations I have seen are the result of not talking about problem for too long and some cases so long that it was too late to fix it. This is always sad and frustrating for everybody involved, first and foremost because it is so unnecessary. If you run into trouble or feel something does not work out for, schedule a meeting and talk immediately!

#2 Their job is to help you get independent, so do not expect to get pampered or to do your work. As hard and painful as their feedback can be, make the most out of it. And always keep in mind that this is not personal and well meant.

#3 Always be proactive and prepared. Don’t wait for your supervisor to manage you. Scheduling meetings, planning projects, making deadlines, finding relevant training etc. is your job. Their job is to advice you on your work and projects, not to manage it.

Last but not least, if there are irreconcilable differences and you cannot make it work together, this is not the end of the world. Most institutes have procedures (and mediators) in place to deal with this. Contact your graduate school for more information!

Academic side hustles

Today, I talked about academic side hustles. You can rewatch the session here (mini summary below):

Most side hustles are helpful for networking, developing and communicating your skills, and can generate a side income. You should only invest in side hustles which will help you achieve your goals or are fun. Keep in mind that these are usually voluntary activities which should in the first place benefit you and your career.

If you are very early in your career, I suggest you focus on fewer things. Most helpful side hustles for pre-doc researchers are reviewing (you can ask your supervisor to help you get experience or volunteer for conference abstract review), teaching (don’t overdo that, it is very time and energy consuming), as well as volunteer and science communication services (public outreach, valorization).

If you are at least halfway through your PhD and have finished one project from start to publication, you can also think about doing a side project (one is enough for the beginning). This can be a research project unrelated to your thesis work, supervising an undergrad or master’s thesis, or a collaboration with people outside your lab.

Towards the end of your PhD or in your first postdoc, your focus should be on networking and communicating your skills in order to increase your visibility and establish yourself in the research community. Good side hustles for this career stage are (co-)editing special issues, organizing lecture series or a symposium, online tutorials, external collaborations (the latter two go well with research tool development).

Once you are a more experienced postdoc, you should figure out what your ideal career path is and what skill set you need. This should define which side hustles to pick above everything else. You want a managing position but don’t have much experience? Get some students or RAs and volunteer for some committee you find interesting. You want an internationally established research lab? Get external collaborations (maybe through editing a special issue?) and good students to do some exciting extra projects. You want the security of a tenure or teaching position? Apply for a guest lectureship or volunteer to take over a course. You want to explore your market value outside academia? Time to get your website shiny and communicate your skills (maybe via a blog or online tutorials). You can also consider starting to freelance and rent out your skills to companies on the side (e.g. consulting, data analysis and data visualization, editorial services, research tool development (hardware and software)).

Not for everyone are admin and committee services. You should only volunteer for these if you want to learn about institute politics and management. Same goes for non-obligatory teaching.  If you don’t care about teaching, don’t want to learn it, and rather change career paths than doing it regularly, just don’t. Teaching is often treated as a central post of every academic position and it is not. If you would rather quit academia and do private sector research than teaching undergrads, don’t waste your time on this. Rather make sure that you do things which help you get around teaching in the future (e.g. research grants, industry interface research). Another thing which is only great if you enjoy it, is having a blog or online tutorial series (or a very active twitter account). If you don’t think this would be something for you, stick to a clean personal website and keep the rest of your online presence clear.

Actually making money on the side can be done by offering editorial services, teaching, consulting (e.g. a friend of mine is external adviser for a gaming company who value the input from a psychologist/neuroscientist), analyzing data or data visualization. Keep in mind that making money with this requires that you already have the skill set or are able to develop it fast. These can also be great opportunities to set a foot outside of academia and explore your market value.

Time and energy management: My take on work-life-balance

Today I talked about how I try to optimize my energy to work at my best as often as I can. You can rewatch the session here and read a brief summary below:


  1. A perfectly balanced day to day life is a lie! Stop reading internet posts like ‘These are 10 everyday habits among the most successful achievers’. These super successful people might do all of these things on their best days, but trust me: Nobody has their best day everyday. The sooner you accept that there will be more and less productive times, the better. It will save you a lot of frustration and feeling like a failure.
  2. The good news is: You CAN have a perfectly balanced life on a larger time scale. There will be busy times where you will have to pull these extra hours. But there will be slow times, where you can go home early (or take off for some days) and should not feel guilty about it. The best advice I ever got: Work hard when it goes well. And when it doesn’t, do the most necessary things and take care of yourself.
  3. A happy and healthy academic is a productive academic. Sometimes the most productive thing you can do is to take a day off. When you are exhausted, you cannot work your best. Stop wasting your time being tired in the office without getting important work done.
  4. Sufficient daily sleep, reasonably healthy and regular meals, and regular exercise are the basis of being a functional human being. These 3 things are non-negotiable. You cannot go even a few days neglecting them without taking a hit in your productivity. If you want to be productive, these 3 things are your highest priority!
  5. Positive energy in, more productivity out. Downtime and relaxation are important, but make sure your private life is also filled with other activities which give you energy, purpose, confidence, and a social life outside of work. This is crucial for me to stay sane and keep in touch with reality.
  6. Don’t fall for the failure trap! If you take your projects too personal and things go wrong (and I promise they will eventually), you easily fall into the failure trap (failure trap = your project sucks >> your work sucks >> you suck as a researcher >> you suck). Having your self-value not solely dependent on your work success will prevent you from falling for this negative thinking and help you find solutions faster.
  7. If something worries you and distracts you from your work constantly, take care of it. NOW. If there is something draining your energy, get it out of the way.
  8. Forget the haters. There will always be people who think that being an academic means to be a cynical and miserable and they will make it their priority to remind everybody how much their job sucks, how underpaid they are, how desperate your future is, and how you should feel guilty for being a functional human being outside your job. Keep them on distance. Your job is to be the best person you can be. This will also make you a better researcher.
  9. Stop telling #youshouldbewriting jokes.

Live saving archiving and documentation strategies.

What are the best practices in documentation, archiving, publishing of code, data, and other materials? How to keep your file structure organized on your own computers?

This series featured two awesome guests from University of Pennsylvania:

Steven Weissberg ( from the Chatlab at Upenn ( talked about OSF and how to use it for open science and archiving (from 5:14).

Giulia Frazetta ( from Geoffrey Aguirre’s lab at UPenn ( talked about versioning and how to make the best use of github (from 11:39).


Quick summary of the most important points:

  1. Always keep future you in mind. And with future, we don’t mean the next few weeks, but the next few years.
  2. Keep your files on your computer tidy. Organize things which you are likely to recycle (e.g. slides, writing, graphics) together. Organize your research material (e.g. data, analysis files, stimuli) in project folders and stay consistent with folder structure and naming.
  3. Don’t panic-save everything. Archive data files at the most important steps in a separate folder (raw, preprocessed, analysis#1, analysis#2, wide format) and use the  copies in your analysis directory for ongoing analyses and trying out things. Overwrite old files when moving on (Don’t panic, you have that safety copy).
  4. Write up the documentation of your study directly into a manuscript file which will later be the basis of a published paper. Writing up the experiment protocols, materials and methods descriptions, analysis steps, and the results right away will save you a lot of time and frustration.
  5. Use OSF ( to archive your materials and data. This is also great for working with multiple people on one project. Keep this as tidy as possible. As soon as you make it public eventually (which we recommend for most projects) this should be the best reflection of your work as a scientist with highest standards.
  6. If your work entails any kind of coding or writing analysis scripts, github is a great way to keep version control and publish your code.
  7. Always work as if a stranger would have to pick up your project at any time and finish it for you.