Pinned post

Just published‼🎇
nature.com/articles/s41467-023
We found contradictions in brain-wide associations of sleep 😴 and depression when participants were doing a task vs. resting state.
What does that mean❓❗

Resting-state brain dynamics were found to change sleep duration increase in a similar fashion as .... (wait for it)... insomnia frequency increase AND depression symptoms increase 🤨🤨
This was very robust observed in over 30k participants from
UK Biobank & Human Connectome Project.

Similarly, we found hyperconnectivity ⏫ associations of insomnia & depression in resting state but hypoconnectivity ⏬ in task
What does that all tell us ⁉

In insomnia and depression, resting-state dynamics are resembling those of rested-wakefulness... Your brain is giving you a signal that you don't need to sleep which looks like a hyperconnected state (hyperarousal?).

BUT in task connectivity drops which could be signifying a "local sleep" phase which decreases your cognitive performance as the brain is unable to recruit its resources to perform the task.

Pinned post

Happy to finally get this paper out. We devised MFCL, a DNN layer with weights that can be modulated. It is a simple all-in-one solution to multiple issues with data quality.

Missing data: by putting missingness flags as input to the weight modulation network, classification models performed better than models with imputation and even XGBoost on various missingness paradigms. When more missingness was introduced at testing, MFCL was the most robust...

We also removed a whole input feature and MFCL did better than all other networks in almost all the tasks. Use case? Think of transferring a model to a low-resource setting where the healthcare facility has less capability to do all measurements...

Data quality and missingness: We cannot even use imputation when input data has both quality measures and missing data. MFCL though can have these as a modulating signal and it outperforms networks with these signals concatenated with input...

Imputation: want to impute the data using DL? We tested adding MFCL at the first layer in an autoencoder-based imputer and it improved its performance in the non-random removal case...

Interestingly, it outperformed XGBoost which is known to perform better on tabular data (check: hal.science/hal-03723551), especially with additional removal of data and on larger datasets

Published papers at TMLR  
A Modulation Layer to Increase Neural Network Robustness Against Data Quality Issues Mohamed Abdelhack, Jiaming Zhang, Sandhya Tripathi et al. htt...

Just published‼🎇
nature.com/articles/s41467-023
We found contradictions in brain-wide associations of sleep 😴 and depression when participants were doing a task vs. resting state.
What does that mean❓❗

Resting-state brain dynamics were found to change sleep duration increase in a similar fashion as .... (wait for it)... insomnia frequency increase AND depression symptoms increase 🤨🤨
This was very robust observed in over 30k participants from
UK Biobank & Human Connectome Project.

Similarly, we found hyperconnectivity ⏫ associations of insomnia & depression in resting state but hypoconnectivity ⏬ in task
What does that all tell us ⁉

In insomnia and depression, resting-state dynamics are resembling those of rested-wakefulness... Your brain is giving you a signal that you don't need to sleep which looks like a hyperconnected state (hyperarousal?).

BUT in task connectivity drops which could be signifying a "local sleep" phase which decreases your cognitive performance as the brain is unable to recruit its resources to perform the task.

Happy to finally get this paper out. We devised MFCL, a DNN layer with weights that can be modulated. It is a simple all-in-one solution to multiple issues with data quality.

Missing data: by putting missingness flags as input to the weight modulation network, classification models performed better than models with imputation and even XGBoost on various missingness paradigms. When more missingness was introduced at testing, MFCL was the most robust...

We also removed a whole input feature and MFCL did better than all other networks in almost all the tasks. Use case? Think of transferring a model to a low-resource setting where the healthcare facility has less capability to do all measurements...

Data quality and missingness: We cannot even use imputation when input data has both quality measures and missing data. MFCL though can have these as a modulating signal and it outperforms networks with these signals concatenated with input...

Imputation: want to impute the data using DL? We tested adding MFCL at the first layer in an autoencoder-based imputer and it improved its performance in the non-random removal case...

Interestingly, it outperformed XGBoost which is known to perform better on tabular data (check: hal.science/hal-03723551), especially with additional removal of data and on larger datasets

Published papers at TMLR  
A Modulation Layer to Increase Neural Network Robustness Against Data Quality Issues Mohamed Abdelhack, Jiaming Zhang, Sandhya Tripathi et al. htt...

🔔Job alert🔔
Fully funded postdoc position at the brand new Adaptive Control group (Lyon, France). Since more positions will be open soon, a broad range of profiles and background will be considered for this first one!
👉adaptivecontrol.org/positions
Please RT🔁🙏
#neurotwitter

RT @adric_dunn
Math in comp neuro summer camp!!
Apply now!!!
10-28/July in lovely Norway (amazing/middle of nowhere). No tuition and room/board/food(good) is covered. Great experience/speakers/students/activities!!!!
“fire together, wire together”
Do it!

compneuronrsn.org/

We’re looking to hire a Research Assistant this summer! Someone especially excited about sleep/EEG work. Apply here:
wd1.myworkdaysite.com/en-US/re

The lab may also have a post doc position! Email me directly if interested in that.

Research Specialist A, Penn Psychology

University Overview The University of Pennsylvania, the largest private employer in Philadelphia, is a world-renowned leader in education, research, and innovation. This historic, Ivy League school consistently ranks among the top 10 universities in the annual U.S. News & World Report survey. Penn has 12 highly-regarded schools that provide opportunities for undergraduate, graduate and continuing education, all influenced by Penn’s distinctive interdisciplinary approach to scholarship and learning. As an employer Penn has been ranked nationally on many occasions with the most recent award from Forbes who named Penn one of America’s Best Employers By State in 2021. Penn offers a unique working environment within the city of Philadelphia. The University is situated on a beautiful urban campus, with easy access to a range of educational, cultural, and recreational activities. With its historical significance and landmarks, lively cultural offerings, and wide variety of atmospheres, Philadelphia is the perfect place to call home for work and play. The University offers a competitive benefits package that includes excellent healthcare and tuition benefits for employees and their families, generous retirement benefits, a wide variety of professional development opportunities, supportive work and family benefits, a wealth of health and wellness programs and resources, and much more. COVID-19 vaccination is a requirement for all positions at the University of Pennsylvania. New hires are expected to be fully vaccinated before beginning work at the University. For more information about Penn’s vaccine requirements, visit the Penn COVID-19 Response website for the latest information. Posted Job Title Research Specialist A, Penn Psychology Job Profile Title Research Specialist A Job Description Summary Dr. Anna Schapiro is hiring a research specialist to begin in Spring or Summer of 2023. The applicant must have a college degree and programming experience and/or experience collecting EEG data. The position will involve assisting in sleep, behavioral, neuroimaging, and computational modeling investigations of human learning and memory. Job Description Job Information: Dr. Anna Schapiro’s lab at the University of Pennsylvania (schapirolab.org) is seeking a full-time lab manager/research assistant to start Spring or Summer 2023. The lab studies human learning and memory using behavioral, sleep, neuroimaging, and computational modeling approaches. Responsibilities include: 1) day-to-day management of the lab and assisting Dr. Schapiro with administrative matters (e.g. managing the sleep lab, submitting IRB protocols), 2) assisting other lab members with sleep, behavioral, and neuroimaging research projects, and 3) independently conducting empirical and/or computational modeling research. Duties: The primary duties will involve managing lab operations and collecting and analyzing behavioral, polysomnography/EEG, and/or fMRI data. Qualifications: Applicants should have a BA or BS degree in psychology, neuroscience, computer science, or a related field by the time of employment, be eligible to work in the United States, and be willing to make a two-year commitment. Requirements include programming experience or experience with acquisition and analysis of EEG data, strong organizational and interpersonal skills, ability to problem solve and work independently, and research experience. *For consideration, please submit a cover letter, a resume and a transcript in the CV section of your application. You can upload multiple documents to the \"Resume/CV\" section. Job Location - City, State Philadelphia, Pennsylvania Department / School School of Arts and Sciences Pay Range $36,368.00 - $50,522.66 Salary offers are made based on the candidate’s qualifications, experience, skills, and education as they directly relate to the requirements of the position, as well as internal and market factors and grade profile. Affirmative Action Statement Penn adheres to a policy that prohibits discrimination on the basis of race, color, sex, sexual orientation, gender identity, religion, creed, national or ethnic origin, citizenship status, age, disability, veteran status, or any other legally protected class. Special Requirements Background check required after a conditional job offer is made. Consideration of the background check will be tailored to the requirements of the job. University Benefits Health, Life, and Flexible Spending Accounts: Penn offers comprehensive medical, prescription, behavioral health, dental, vision, and life insurance benefits to protect you and your family’s health and welfare. You can also use flexible spending accounts to pay for eligible health care and dependent care expenses with pre-tax dollars. Tuition: Take advantage of Penn's exceptional tuition benefits. You, your spouse, and your dependent children can get tuition assistance here at Penn. Your dependent children are also eligible for tuition assistance at other institutions. Retirement: Penn offers generous retirement plans to help you save for your future. Penn’s Basic, Matching, and Supplemental retirement plans allow you to save for retirement on a pre-tax or Roth basis. Choose from a wide variety of investment options through TIAA and Vanguard. Time Away from Work: Penn provides you with a substantial amount of time away from work during the course of the year. This allows you to relax, take vacations, attend to personal affairs, recover from illness or injury, spend time with family—whatever your personal needs may be. Long-Term Care Insurance: In partnership with Genworth Financial, Penn offers faculty and staff (and your eligible family members) long-term care insurance to help you cover some of the costs of long-term care services received at home, in the community or in a nursing facility. If you apply when you’re newly hired, you won’t have to provide proof of good health or be subject to underwriting requirements. Eligible family members must always provide proof of good health and are subject to underwriting. Wellness and Work-life Resources: Penn is committed to supporting our faculty and staff as they balance the competing demands of work and personal life. That’s why we offer a wide variety of programs and resources to help you care for your health, your family, and your work-life balance. Professional and Personal Development: Penn provides an array of resources to help you advance yourself personally and professionally. University Resources: As a member of the Penn community, you have access to a wide range of University resources as well as cultural and recreational activities. Take advantage of the University’s libraries and athletic facilities, or visit our arboretum and art galleries. There’s always something going on at Penn, whether it’s a new exhibit at the Penn Museum, the latest music or theater presentation at the Annenberg Center, or the Penn Relays at Franklin Field to name just a few examples. As a member of the Penn community, you’re right in the middle of the excitement—and you and your family can enjoy many of these activities for free. Discounts and Special Services: From arts and entertainment to transportation and mortgages, you'll find great deals for University faculty and staff. Not only do Penn arts and cultural centers and museums offer free and discounted admission and memberships to faculty and staff. You can also enjoy substantial savings on other goods and services such as new cars from Ford and General Motors, cellular phone service plans, movie tickets, and admission to theme parks. Flexible Work Hours: Flexible work options offer creative approaches for completing work while promoting balance between work and personal commitments. These approaches involve use of non-traditional work hours, locations, and/or job structures. Penn Home Ownership Services: Penn offers a forgivable loan for eligible employees interested in buying a home or currently residing in West Philadelphia, which can be used for closing costs or home improvements. Adoption Assistance: Penn will reimburse eligible employees on qualified expenses in connection with the legal adoption of an eligible child, such as travel or court fees, for up to two adoptions in your household. To learn more, please visit: https://www.hr.upenn.edu/PennHR/benefits-pay The University of Pennsylvania's special character is reflected in the diversity of the Penn community. We seek talented faculty and staff who will constitute a vibrant community that draws on the strength that comes with a substantive institutional commitment to diversity along dimensions of race, ethnicity, gender, sexual orientation, age, religion, disability, veteran status, interests, perspectives, and socioeconomic status. Grounded in equal opportunity, nondiscrimination, and affirmative action, Penn's robust commitment to diversity is fundamental to the University's mission of advancing knowledge, educating leaders for all sectors of society, and public service. The University of Pennsylvania prohibits unlawful discrimination based on race, color, sex, sexual orientation, gender identity, religion, creed, national or ethnic origin, citizenship status, age, disability, veteran status, or any other legally protected class.

wd1.myworkdaysite.com

Hey friends at UW School of Medicine - we are currently recruiting an Assistant Dean for EDI in Research and Graduate Education. Find all the details here: apply.interfolio.com/119491. Please spread the word!

RT @TessaMontague
Pls RT: We’re hiring a research tech to work with us on the neural basis of cuttlefish camouflage! We’re generating transgenics, doing neural imaging and behavior in these cute cephalopods. Soon-to-be and recent grads encouraged to apply to our team. Info: tessamontague.com/hiring

With a happy new year, a reminder that the 9th of Jan is the deadline for applications for funded PhDs in the @ECOLOGICALBRAIN programme at @ucl
---
RT @UCLPALS
Want to study the #brain & #human #behaviour in the real-world using new methods and #digital #technologies? e.g. #VR, #fMRI, #WearableTech

Apply for one of our @ucl studentships! Find more information here: buff.ly/2DF3Pqz
twitter.com/UCLPALS/status/160

So you have a #BIDS #fmri dataset and wished you coud have the #eyetracking data to tell you where participants were looking during the experiment.

So here is "bidsmreye": a BIDS app that wraps around the deepmreye python package that uses a pre trained machine learning model to decode gaze position from the time series extracted from the eye voxels.

pypi.org/project/bidsmreye

github.com/cpp-lln-lab/bidsMRe

github.com/DeepMReye/DeepMReye

How science can do better for #neurodivergent people
Researchers share their experiences and suggest changes to the structure of science. #neurodon #neurosceince nature.com/articles/d41586-022

Hello world!
Since I'm still discovering this Mastodon thing, I will be posting sporadically (well... that's not much different from my Twitter anyway). I will be mainly sharing interesting science stuff and job/educational opportunities that I stumble upon.
Happy Holidays!

First post on this site:

I am advertising an *open post-doc position*.

Topics connected to my current interests: how people use theory of mind to influence other’s thoughts and feelings and/or to make inferences about punishment and other acts of social control; cognitive processes by which individuals create, evaluate, sustain, and undermine legitimate power. Multidisciplinary or interdisciplinary applications are welcome.

Details here: bit.ly/saxelab-postdoc-ad.

Qoto Mastodon

QOTO: Question Others to Teach Ourselves
An inclusive, Academic Freedom, instance
All cultures welcome.
Hate speech and harassment strictly forbidden.