WORKING IN THE MREMONDES LAB
We’re an intense, vibrant, and highly collaborative group, tackling fundamental problems in Neuroscience with an ultimate goal of understanding the neural bases of behaviour in health and disease. We train rodents in behavioural tasks modelling learning and memory, we build devices to record and manipulate neural activity during behaviour using optogenetics, we perform long (6 hr+) cranial surgeries to implant such devices in the living rodent, and record from as many neurons possible over the course of weeks-months. We use anatomical tracing methods to understand the structures communicating information between brain regions in order to inform neural recordings and optogenetic manipulation. We spend 60% of our time analyzing neural, and other acquired data, all the while thinking about the data and how it relates to our scientific questions.
This entails hard-work, discipline, extreme commitment, rigor, dedication, and deep thinking.
If this sounds like you, please drop me a line explaining your interests, and we can then meet to talk about possibilities, funding, and projects. Please do not write to me with general, vague ideas, or standard plans or texts, these will not be replied to (sorry, no time).
We’re an intense, vibrant, and highly collaborative group, tackling fundamental problems in Neuroscience with an ultimate goal of understanding the neural bases of behaviour in health and disease. We train rodents in behavioural tasks modelling learning and memory, we build devices to record and manipulate neural activity during behaviour using optogenetics, we perform long (6 hr+) cranial surgeries to implant such devices in the living rodent, and record from as many neurons possible over the course of weeks-months. We use anatomical tracing methods to understand the structures communicating information between brain regions in order to inform neural recordings and optogenetic manipulation. We spend 60% of our time analyzing neural, and other acquired data, all the while thinking about the data and how it relates to our scientific questions.
This entails hard-work, discipline, extreme commitment, rigor, dedication, and deep thinking.
If this sounds like you, please drop me a line explaining your interests, and we can then meet to talk about possibilities, funding, and projects. Please do not write to me with general, vague ideas, or standard plans or texts, these will not be replied to (sorry, no time).
WORK SMART AND BE HAPPY TOWARDS YOUR PhD/MSc
As your advisor, I am supposed to give you tools for you to do your research, and to provide you with my expert advice, given my extensive experience in the field. All this I do, to the best of my knowledge and capacities.
However, I am not a policeman, I will not survey your work and schedules, since I believe each PhD candidate is responsible for its time management and work strategies (i.e. “we’re not in High School anymore”), and the end result is ultimately your individual achievement, on which you will be judged.
At the end of your journey, you will need at least two things:
A) an article in a serious peer-reviewed international journal.
B) a thesis that I feel comfortable approving of and signing under (note that this might be harder than A).
For this to happen, you will need to complete in 4 years (duration of a fellowship granted by FCT), the work I believe a normal PhD candidate should have 7 to do. To be concise, your schedule must accommodate considerably (30-50%) more (hard)work than the usual (and more desirable) relaxed schedule, itself already 10-20% more work than in a non-scientific endeavor. While this might seem like an impossible task, it only requires common sense, and smart time management (STM).
STM entails a few common-sense principles that are general to all scientific work, and that I will detail here, non-exhaustively, with the specificities of our experimental procedures, and hoping they are not entirely novel to you:
1- Things will fail, the sooner you realize it, the better. Create all needed animal resources for permanent data acquisition and compensation of accidents. This means, having a pool of pre-trained rats to do surgery on.
This pool can be shared among people insofar as their behaviour protocols are similar. Namely, one person one day could handle a whole batch of young rats for everybody, and different people could schedule the daily handling of such a batch. Also, for instance, a batch of rats could be habituated to the behavioural apparatus (maze) by one experimenter at a time.
Once the pre training is specific, each project should have access to a batch of 2-4 pre-trained, relatively young animals (3-6 months) ready to be surgically implanted at all times, in case a fatality happens. This is possible as long as you communicate with everyone in the lab.
2- Create all material resources needed for permanent data acquisition, and compensate for accidents. This means having 2-3 recording devices (drives) ready for implantation in short notice, so you can implant one animal (from point 1 above) as soon as you’re done with a previous one, and never have down times in data acquisition, until you have the number of datasets judged necessary. This requires good supplies stock control as well...
3- Don’t single-task. Whenever you have an implanted rat, you should not only do data acquisition. All the time outside data acquisition should be used for data analysis (the most time-consuming code to run needs no human supervision), and for the above provisions, as appropriate. In the limit, you should switch between data acquisition, drive building, data analysis, rat training, reading, and so on, so there is no down time.
4- Do whatever is necessary to prevent reinventing the wheel, and re-doing stuff you’ve already done, and should do only once (write down protocols, learn procedures, take notes, order and store materials, and so on…).
5- Take time off such that your personal life and your work schedules do not conflict. When you rest, rest, when you work, work.
6- Once your project is ready, start writing your thesis as soon as you start working on your project. Use your project document to start reporting experimental results, update your literature review, create figures, and create a slide presentation of the ongoing state of your project(s), write a Discussion section were you start interpreting your data in light of your hypothesis and published literature. Maintain these two documents updated and polish them as you go along. By the time you’re done with your 4 years you’ll have a thesis and a thesis presentation almost ready. During those 4 years you’ll have enough material to write publications (reviews, commentaries, grants, book chapters) and present your progress in labmeetings, talks, reports, and posters.
I finish like I started, I am not a policeman, so I won’t voluntarily question your time management (unless you ask me, of course), but I will also not play along in pretending you have a proper thesis once your time is up, unless you do.
We’re an open lab. All the above can (and should) be discussed openly, as it is customary in the Remondes Lab, and we can also talk about it in lab meetings if something isn’t clear.
I am always available to provide you guidance and teach you (that is my job) on how to acquire, quantify and analyze your data, I am here to help you, and I can repeat things to you more than once...(though I expect you to take notes in case you doubt you'll remember everything later). I will not do your work for you.
WHY ARE LABMEETINGS “SACRED” AND HOW TO MAKE THEM ROUTINE (we have one bi-weekly):
To the extent that it involves progressing from one situation to a better one, science is no different that any other job. You’re supposed to constantly progress towards completing your PhD tasks, increasing your knowledge and making sure it is available for others to profit from. Also, you’re not supposed to sit in lonely desperation when stuff does not work for more time than reasonably predicted. Finally, you need to keep up with the literature and make sure your data are analyzed and published as soon as judged solid. The above demands meet substantial answer in that staple of lab science: “the LABMEETING”.
More than once some of you feel unsure of what to present when you have no new data. This is normal, since a lot of the time you devote to work is analysis of acquired data. In labmeeting you don't need to present new data, you can present new analysis of acquired data, incomplete analyses (intermediate steps towards a concluding picture), explain your plans to analyze data (to get advice), discuss some new analytical tool you plan to use, discuss a methodological problem you've come across, the structure of a paper you plan to write, and so on. No one is asking for complete stories or definitive analyses. Labmeeting is a place for discussion, problem-solving, and brainstorming.
It is, however, a fundamental tool in maintaining the fabric of any research group. In this respect, discipline is necessary. Attendance is strongly encouraged, and re-scheduling and swapping are fine, provided everyone agrees, and it is done timely.
Only a fraction of our work is data collection, 60-70% is quantification and analysis. You don't need "new data" to present labmeeting, the most important is where does the data take you in search for the truth......So most of your labmeetings will be data analysis and conclusions (even if tentative) thereof. Your work is not collecting new data, only the data you need to perform the most important: quantification, and analysis, that which allows you to ascertain whether or not your experiment provided you a clear answer to the question you asked, and whether you should perform other experiments. You should always have data quantified, analyzed (stats included), and plotted, and not drag this part of your work. It is a first priority....
HOW TO BEHAVE IN A CONFERENCE
Going to conferences to present your work is something you should “jump on” as soon as you have findings. This is how you “exist” as a scientist. See a conference as an opportunity to expose your work, thinking and scientific “persona”. Don’t worry, everyone else is there for the same thing. Below are some rules you should follow in a meeting:
a) Don´t clump up with aggregates of people you already know, reach out and hang out with scientists you don’t yet know, and aspiring scientists such as yourselves.
b) Don't hang out among friends and acquaintances speaking science (or other subjects) in languages other than English. If you see this behavior around you, please don't imitate it, you will project a really poor image of yourself.
c) Be there for the sessions, ask plausible questions, discuss everything with everyone, ......that's what you're there for.
d) Do your homework; search and target your favorite sessions, talks, and speakers, be prepared for challenging one-to-one conversations. Let me know if you need an introduction to someone you don't know.
e) Be cool, but not excessively so....:))))
f) Make connections, take contacts, follow-up later with emails.
For those of you wishing to pursue a relevant career in science, a postdoctoral position out of Portugal, namely (but not only) in the US, this is a time to look for prospective supervisors and leave a good impression.
Talk to me before planning or going to a conference.
GIVING A TALK
Short talks (15min) are the hardest ones to give, and provide the best training to practice any length talks.
In 15 min you can mostly present snapshots of your work, to favorably impress everyone in a very short time. As such, you must:
1- Be brief, clear, but not superficial.
2- Scrupulously respect allocated time, but not rush so that no one understands your talk.
3- Present information that is interesting, raising pertinent scientific questions, but tailored not to raise questions from the audience (if someone interrupts with a question, you must stop to answer, you'll loose at least 2 min of your allocated time - and it will be on you. No one will care who caused you to waste time. Also, a question is rarely asked in isolation, for reasons we might discuss).
4- Be aware that you have these 15 min to do justice to your work, and to yourself.
Let me explain what I believe is an interesting short-talk scheme:
5 slides (~3 min each of the 1st 4):
Slide 1: Intro to the project's main scientific questions.
Slide 2: Methods currently used in the lab to answer the above questions.
Slide 3: The data that most directly answers the above questions.
Slide 4: Conclusions drawn from 2 and 3 in response to 1.
Slide 5: An acknowledgement slide with no oral presentation. The research group, the help, and the financial support.
ABOUT THESIS COMMITTEES (GET YOURS AS YOU THINK OF YOUR PhD PROJECT)
Many PhD programs do not make it mandatory to have a Thesis Committee (TC). However, a thesis committee is mandatory in any reputable Doctoral program, and it makes sense for whoever wishes to go beyond MSc and towards a career in science.
TC will usually meet every year, unless contingencies make it necessary more often. This is a yearly opportunity for the candidate to receive important feedback from people within the field, other than supervisor, from people who have evaluated the progress and the work schedule for the rest of the time the candidate has to finish research work, as well as specifics on individual experiments.
One day, if the candidate may choose to do so, it will apply for Post-doctoral positions. If this postdoc is to be something meaningful, the candidate will apply to top labs, with extremely high standards. Without knowing the candidate, prospective employers will look at three things before even replying to an email. They are, by order of relevance:
1- Publications (which will condition the chances of having a Postdoctoral fellowship, and the lab securing funding on its own)
2- Recommendation letters and other references (especially from me, but also other people).
3- Motivation letter and research plans.
If you want your recommendation letters to be taken seriously, you want them to be genuine, and their authors to have a name in the field,...a pedigree (Yes. Science is snob and cares about scientific genealogy). Within the field of Neuroscience, you might find such authors in Portugal, but, a) they do not abound, b) they are busy.
Finally, they will want to recommend someone who's points 1 and 3 above are solid. Besides a group of people you talk to, and seek advice from, 1-2 times a year (or more), TC members are people you can go to, later on, for recommendation letters. This is probably the most important factor about the TC, under your circumstances. So please choose carefully, wisely, but promptly. The sooner you choose, the sooner you'll get their advice and help, and the more they will get to know you enough so they can write a rec letter....
MONEY IS ALLWAYS SHORT...EVERYWHERE.
At iMM-JLA students selected for Doctoral studies regardless of the Program they got into, will spend 6 months in the Lisbon BioMed Program (courses, etc) where affinities with iMM groups will be identified and students and group leaders will manifest mutual interests. However, the possibility of staying will always depend on an FCT individual fellowship. FCT individual fellowship evaluation is now highly competitive/demanding. I've heard that, unless you have an excellent score average (BSc/MSc), and outstanding track record (read "publications"), you stand little chance. So you need competitive academic achievements and shoot for at least one publication.
This publication will be ranked among the IF quartiles in its field (e.g. Q1 means the IF ranks within the top 25% in its respective field). Postdoctoral fellowships will progressively disappear to give way for contracts. These will be given to the best candidates (publications, presentations in relevant meetings, etc), and be managed/assumed by the Institutes/Universities.
WHAT ARE SPIKES, WHAT ARE NOT…
SPIKES are SPIKES, when in doubt ask me....
Fortunately, more and more of the MRemondes Lab members are either looking at electrophysiological data and/or about to be collecting data of your own. For those of you in this line of work, I felt the need to produce a tutorial on spike identification and detection so no one wastes time looking for 5 legs in a cat, pink chestnuts, or flying pigs.
In a power point I can make available for those interested, I tried to convey onto everyone, and once and for all, what is the MRemondes standard for "what does an action potential look like when recorded externally to the neuron"? Anything not looking like that, is NOT a spike, and when in doubt you should show it to me, and I'll let you know.
Also, this .ppt contains SWR, gamma frequency events, usually correlated with increased spike density, and one theta period.
Before starting to identify spikes, your homework is to look at that .ppt presentation, train your eyes in the identification of a canonical spike shape and then go to the GDrive, look for a folder in the "Data Analysis and ...." folder called Homework, open up a Matlab figure therein called "HIPP_Data_MR", and practice two things:
1 - Using your preferred software (Matlab, Python) to eyeball raw ephys data (zoom in, pan, scroll through, move to an interesting point to see what is going on there).
2- Identifying spikes in the raw and filtered traces and matching them.
Raw data exploration should always be the first step in your analysis work. Always.
You need to be assured that you are looking at good quality LFP and that you have spikes in the raw data, rather than black-boxing the whole thing inside some "sophisticated" analysis that will tell you nothing....or worse, tell you stuff that is not there, or throw you onto a journey into the realm of imaginary findings.
Ask me to look at your raw data. Don't waste time in tortuous paths that will end in anxiety, stress, and confusion.
Happy training!
