Lab guide

1. Welcome

Welcome to the lab. I’m glad you’re here. That’s not a platitude, it’s a fact – you’re here because I want you here.

This guide exists to tell you what you’re joining, what I expect from you, what you can expect from me, and how things work day to day. Some of it is practical — systems, schedules, protocols. Some of it is harder to put on paper: the culture we’re trying to build and the kind of work we’re trying to do. I’ve tried to be honest about both.

Read this when you arrive. Come back to it whenever something is unclear. And if something in here doesn’t match how the lab actually works in practice, tell me. This document should be a reliable guide, not a fiction.

Note: Claude helped me write this document (but not this paragraph). I asked Claude to give me hundreds of multiple-choice questions to write the guide. Not because I want to pass off mentorship to AI, but because I wanted to make sure I don’t miss anything essential. Then I went through the whole document in-depth to make sure that everything is accurate, reliable, and in my own voice.

2. Mission, Vision, and Purpose

The One-Liner

“We turn brain circuits into targeted treatments to fix some of the fundamental problems in psychiatry.”

(Yes, I know it doesn’t fit in one line. Simon pointed that out to me already. You still get the point.)

The Mission

The mission of this lab is to improve the mental health of society by bringing neuroscience into the clinical practice of mental health.

Psychiatry has been practicing for over a century largely without thinking about the biology of the brain. We diagnose by symptom clusters, with no biological context. We prescribe by trial and error, not by target. Patients cycle through medications and therapies for years without any principled strategy. That is not good enough.

Neuroscience has given us tools to change this. We can aim for specific brain circuits in specific patients. Maybe someday we’ll be able to measure whether the stimulation reached its intended target. When treatment becomes science-based, it pushes the whole field forward – better training, better standardization, better outcomes, less suffering.

The Vision

The long-term vision is a clinical universe in which every psychiatrist knows how to use neuroimaging for brain stimulation. The subspecialists at the academic centers may be the experts – but every psychiatrist should at least know how to start thinking about it.

Getting there requires decades of work: building the methods, running the trials, training the next generation, and building the field-level infrastructure that makes circuit targeting standard practice. This lab is one piece of that larger project. We also work on training standards, clinical implementation, industry (devices, software, clinics), etc.

We are not just trying to publish papers. We are trying to build something that will outlast us.

The Day-to-Day

In practice, this means using neuroimaging — primarily fMRI — to improve clinical outcomes with brain stimulation. We identify neuroimaging targets, develop methods for reaching them, test those methods in clinical trials, and build the evidence base that moves the field forward.

Why I’m Telling You This

The work is hard, and there will be days when it doesn’t feel like it’s going anywhere. On those days, I want you to remember why it matters. Patients with mental illness are waiting for better treatments. Some have tried everything available. That’s why we do this work carefully, rigorously, and with real scientific standards.

I come from a family with a lot of mental illness. I take care of patients who are suffering. I care a lot about those people, and I hope that you do too. That’s why you see me working hard. And I expect the people around me to share that humanity. I’m not a taskmaster – I don’t micromanage, I don’t ask people to work overtime, etc – but when people cut corners, avoid work, or compete with each other, it’s frustrating and disappointing to me. We’re here to solve human suffering together.

3. The Lab’s Science

The lab’s work spans two overarching themes, plus several areas of active interest. Even if your role sits primarily in one, understanding the whole picture will make you a better contributor and a better scientist.

Theme 1: Neuroimaging / Neuroinformatics

We use fMRI to identify targets for brain stimulation. Our core methods include causal brain network mapping, precision functional MRI, and related techniques to trace functional connectivity from symptom-relevant brain regions to stimulation-accessible cortical sites. Adam Pines (starting late 2026) leads the lab’s computational neuroimaging infrastructure, which is the methodological core of everything else we do.

Theme 2: Clinical Trials

We run clinical trials testing fMRI-guided brain stimulation, primarily transcranial magnetic stimulation (TMS). This lab is not disease-focused, as brain stimulation targets can span multiple psychiatric conditions, including depression, bipolar disorder, OCD, PTSD, psychosis-spectrum conditions, addiction, and beyond. We are launching a master protocol enabling multiple simultaneous clinical trials evaluate circuit-specific versus conventional targeting across multiple conditions. Mohammad Lesanpezeshki is the study physician and point of contact for clinical trial operations.

Other Themes

Several other themes are not our primary area of expertise, but active areas of keen interest:

• Big data approaches to understanding brain stimulation outcomes
• Neuropathology, establishing correlations between radiological and postmortem studies
• Clinical implementation, which includes private clinics, commercialization, etc.

Key Faculty

Early-Career Faculty Within Our Lab

• Simon Kwon, PhD (Research Associate) — human memory, experimental psychology, and brain stimulation. PhD in experimental psychology from Cambridge, postdoc with Shan at Harvard.
• Mohammad Lesanpezeshki, MD (Study physician) — clinical neuropsychiatrist, TMS study supervisor. He is part-time in the lab (30%), and spends the rest of his time as a clinician.
• Andrew Pines, MD (incoming) — translational psychiatrist specialized in psychosis-spectrum conditions; research-track residency with Shan at Harvard.
• Adam Pines, PhD (incoming) — computational neuroimager, imaging lead. PhD in neuroimaging from Penn, recently finished postdoc at Stanford.

Note: Adam Pines and Andrew Pines are brothers. They are distinct people with distinct roles in the lab. Yes, we checked. Simon Pines is an alter ego created by Simon Kwon in hopes of blending in with the Pines brothers.

Senior Collaborators

• Sachin Patel, MD, PhD — chair of psychiatry, our boss.
• Linda Teplin, PhD — vice chair for research in psychiatry, our domain leader.
• Jordan Grafman, PhD (Shirley Ryan AbilityLab / Northwestern) — among the world’s foremost experts on prefrontal cortex lesion studies and abstract phenomena such as altruism, empathy, etc. A longstanding collaborator who will hopefully become closer to our group.
• TBI TMS research group (Theresa Pape, Amy Herrold, Alex Aaronson) — longstanding collaborators who run small-scale studies in highly complex TBI patients.
• Many other developing collaborations with epilepsy, movement disorders, cognitive neurology, and other groups within Northwestern and beyond.

Neurotech Neighbors

Other faculty on Abbott 13 (our offices) and 680 N Lake Shore (the lab):

• Ivan Alekseichuk, PhD — neuroengineer focused on TMS modeling and electrophysiology.
• Stewart Shankman, PhD — psychologist focused on phenotyping and electrophysiology.
• Ben Rapaport, PhD – recently promoted to full faculty position, trained under Shankman.

4. Who’s in the Lab

The PI: Shan Siddiqi, MD

Shan is the Stephen M. Stahl Associate Professor of Psychiatry and Scientific Director of the Dauten Bipolar Center of Excellence. He sets the scientific direction, manages external relationships (funding, collaborations, industry partnerships), and is ultimately responsible for everything that happens in the lab. He comes to Northwestern after nine years at the Center for Brain Targeting Foundry at Brigham and Women’s Hospital / Harvard.

Domain Leads

Imaging and Computational Methods — Adam Pines, PhD

Adam is a computational neuroimager from Penn and Stanford. He is the go-to person for anything related to fMRI analysis, imaging pipelines, data standards, and computational methods. Adam owns the lab’s imaging infrastructure, code standards, and data management documentation. If you are doing imaging work, Adam is your first stop for technical questions.

Translational and Experimental Work — Simon Kwon, PhD and Andrew Pines, MD

Simon Kwon leads the experimental neuromodulation work, focusing on targeting methods. Andrew Pines (no relation to Adam, though they are in fact brothers) focuses on translational psychiatry and psychosis-spectrum conditions.

Study Physician — Mohammad Lesanpezeshki, MD

Mohammad is the study physician and clinical trials point of contact. Anything related to clinical trial operations, subject safety, adverse event reporting, and study-specific clinical protocols runs through Mohammad.

Lab Manager — Suman Premkumar, MD

Suman was a fully-qualified doctor and Army officer before coming to the US. He has lots of experience with general medicine and also with team leadership and organization. He is new to lab management, so we will all learn together.

The lab manager owns onboarding, day-to-day clinical trial coordination, scheduling, and administrative logistics. On your first day, Suman is your primary guide. When you’re not sure who to ask, start with him.

Getting Help: When to Go Where

• Technical / methods questions → your domain lead (Adam for imaging, Simon for experimental, Andrew for translational, Mohammad for clinical)
• Direction, priorities, career development → any faculty member
• Administrative and operational questions → Suman
• Clinical trial and subject safety questions → Mohammad or Suman

The overriding rule: don’t stay stuck. It doesn’t matter who you ask first. It matters that you ask. No wrong door.

Students, Rotators, and Short-Term Visitors

Undergraduates, rotating students, and short-term visitors are welcome in the lab. If you are interested in joining for a rotation, a summer, or a project, reach out to any faculty member directly. If we decide together that this is the right fit, we will work together find a project that matches your timeline and interests — with the caveat that short stays work best when the scope is realistic. Mentoring these folks well is part of everyone’s job, not just the faculty’s.

5. Getting Started

Your First Day

Your first day is managed by the lab manager. He will walk you through building access, accounts, required systems, and key introductions. The checklist below is what you should expect to complete in your first week. The lab manager will drive it — but know what’s on it.

First-Week Checklist

• Northwestern NetID and email active
• Building and room key / card access
• Added to lab Teams workspace, shared calendar, and shared drives
• REDCap access (subject-facing and clinical trial roles)
• Imaging archive access
• Brief introductory meeting with Shan
• Introductory meeting with your domain lead
• Introductory meeting with the lab manager
• All required trainings identified and scheduled

Required Training

The following training is non-negotiable before you interact with subjects or identifiable data. Complete it within your first two weeks — don’t wait to be reminded.

• CITI human subjects research training — required for everyone
• HIPAA training — required for everyone
• MRI safety training — required before attending any scanning session
• GCP (Good Clinical Practice) — required for anyone working on clinical trials
• TMS device operation and adverse event / seizure protocol — required for device operators only (see Section 12)

Required Reading

The reading list is tiered. The first tier is for everyone. Role-specific reading should be completed in your first month.

Tier 1: Everyone (Shan’s Favorite Blatant Self-Citations)

• The fundamentals of causal brain mapping — Siddiqi et al., Nature Rev Neuroscience 2022
  https://www.nature.com/articles/s41583-022-00583-8
• My best paper — Siddiqi et al., American Journal of Psychiatry 2026
  https://psychiatryonline.org/doi/10.1176/appi.ajp.20250198
• A paper that uses many of my favorite imaging methods — Siddiqi et al., Nature Neuroscience 2024
  https://www.nature.com/articles/s41593-024-01772-7
• A paper that uses precision functional mapping — Siddiqi et al., Science Translational Medicine 2023
  https://www.science.org/doi/10.1126/scitranslmed.abn0441
• Our strongest statistical result — Pines et al., JAMA Psychiatry 2024
  https://jamanetwork.com/journals/jamapsychiatry/fullarticle/2829812
• Our first clinical trial — JAMA Psychiatry
  https://jamanetwork.com/journals/jamapsychiatry/article-abstract/2850583
• Our second clinical trial — Molecular Psychiatry
  https://www.nature.com/articles/s41380-026-03535-1
• A review of how I want clinicians to think — Biological Psychiatry
  https://www.biologicalpsychiatryjournal.com/article/S0006-3223(23)01723-7/abstract
• A review of how I want researchers to think — Neuropsychopharmacology
  https://www.nature.com/articles/s41386-023-01670-9

Tier 2: Imaging-Oriented (Adam made this list)

• Where did fMRI come from? — Read from “Invention of functional MRI (BOLD – I)” through “Critique and Limitations (BOLD – II)”
  https://www.mriquestions.com/who-invented-fmri.html
• How we use fMRI to study brain organization — Yeo BT, Krienen FM, Sepulcre J, et al. The organization of the human cerebral cortex estimated by intrinsic functional connectivity. J Neurophysiol. 2011;106(3):1125-65. PMID: 21653723.

I would rather folks read the first two carefully than skim all five sources, but:

• How to classify brain regions using fMRI — Schaefer A, Kong R, Gordon EM, et al. Local-Global Parcellation of the Human Cerebral Cortex from Intrinsic Functional Connectivity MRI. Cereb Cortex. 2018;28(9):3095-3114. PMID: 28981612.
• Inconsistent processing leads to inconsistent conclusions — Botvinik-Nezer R, Holzmeister F, Camerer CF, et al. Variability in the analysis of a single neuroimaging dataset by many teams. Nature. 2020;582:84-88.
• fMRI preprocessing using a common pipeline — Esteban O, Markiewicz CJ, Blair RW, et al. fMRIPrep: a robust preprocessing pipeline for functional MRI. Nat Methods. 2019;16:111-116.
• Modern noise reduction techniques — DuPre et al. TE-dependent analysis of multi-echo fMRI with tedana. Journal of Open Source Software. 2021;6(66):3669.

Tier 2: Translational / Experimental (Simon made this list)

• Introduction — Hallett M. Transcranial Magnetic Stimulation: A Primer. Neuron. 2007;55(2):187-99.
• Textbook — Walsh V, Pascual-Leone A. Transcranial Magnetic Stimulation: A Neurochronometrics of Mind. MIT Press, 2003.
• Expert guideline — Rossi S, et al. Safety and recommendations for TMS use in healthy subjects and patient populations, with updates on training, ethical and regulatory issues. Clin Neurophysiol. 2021;132(1):269-306. PMID: 33243615.

Tier 2: Clinical Trials

• The SAINT trial
  https://psychiatryonline.org/doi/10.1176/appi.ajp.2021.20101429
• The Expedition protocol (our lab’s current top priority)
  https://www.sciencedirect.com/science/article/abs/pii/S1551714425001727?via%3Dihub

6. Day-to-Day Operations

Presence and Hours

The assumption is that everybody will be on site during business hours. Most importantly, we should all be able to find each other whenever needed. I’ve learned that people collaborate much more effectively when they’re in the same room. Secondarily, if we don’t use our space, the university will take it away. They monitor how many people are swiping in.

• When you are seeing study participants: primarily on-site during study hours. Your schedule is driven by subject visits and protocol needs. Hours may be extra-long on treatment days — if this occurs, you can take a short day to make up for it.
• When you don’t have participants: more flexible, with expected presence during a core overlap window (approximately 10am–4pm on weekdays) so the lab can function as a team. Beyond that, it’s up to you if you want to arrive earlier and leave at 4, or arrive at 10 and leave later.
• Either way: attend required meetings in person unless there’s a participant visit.
• Note from Shan: I will be in and out of the office while managing multiple responsibilities including clinical work, administrative meetings, teaching, traveling for conferences, etc. Usually I’ll try to be in my office during core hours, and will try to see patients in the early morning and late afternoon.

Role-Specific Clarifications

Postdocs, junior faculty: You’re in control of your own destiny. Some weeks you may be working extra-hard to meet a deadline, other weeks may be lighter. Once you reach that level of seniority, I assume you’ve figured out how to manage your own schedule. If not, we can discuss.

Students, residents/fellows: We’ll plan hours case-by-case around your didactic and/or clinical schedule. For senior grad students, you may gradually develop independence to become more like a postdoc.

Research staff (RAs, lab manager, coordinators, etc.): Schedule will be determined by daily tasks. Some days may be longer than others — for instance, if you’re delivering TMS treatments and/or covering for somebody else who is sick or on vacation. When you work extra hours due to clinical trial operations, you can add them up to get extra vacation time or leave early on other days, with a 50% time-off bonus, rounded up to the nearest hour. In other words, if you accumulate 5 extra hours, you can use it to take off 7.5 hours, which rounds up to a whole day.

At first, the schedule will be the same for all RAs. If it becomes clear that some people like getting time-off bonuses while others prefer a predictable schedule, we can try to accommodate different preferences.

If your circumstances require flexibility beyond this, talk to Shan. We’ll work something out.

Time Off

Request time off through the lab manager, who coordinates coverage. If you have participant visits, treatments, or study obligations during the time you’ll be out, coverage needs to be arranged before the time off is finalized — Suman handles that, but flag it early so he has room to work with.

Beyond that: do what you want with your time off. I don’t expect people to work on vacation. Some people like using vacation time to catch up on work tasks — that’s your own business. Personally I like sitting on a tropical beach and writing an essay. But I don’t give extra brownie points for working on vacation.

Locations

The lab is spread across multiple locations around campus.

• Northwestern Psychiatric Neurotech Labs — us and a few other labs
  • Offices: Abbott Hall, 710 N Lake Shore Dr, 13th floor (Shan is in 1318). This is where you sit when you’re not with a study participant. We have enough offices, desks, and coffee for everybody.
  • TMS/imaging labs: 680 N Lake Shore Dr, 15th floor. This is where we conduct physiological/translational studies and some preliminary clinical trials. Two TMS rooms, several rooms for behavioral assessments, and lots of touchdown space.
• Northwestern Memorial Hospital — larger-scale clinical trials
• Dauten Behavioral Health Institute — outpatient psychiatry clinics
  • Arkes Pavilion, 676 N St Clair St, 11th floor. This is where we conduct large-scale clinical trials. Two TMS rooms and a workroom where three staff members can sit.
• Norman and Ida Stone Institute of Psychiatry — inpatient psychiatry unit
  • Galter Pavilion, 675 N St Clair St, 13th floor. This is where we conduct inpatient clinical trials. One TMS room.
• Emergency Department and Observation Unit
  • Feinberg Pavilion, 251 E Huron St, Mezzanine Level. We will sometimes bring the TMS device down for treatment. We don’t have any dedicated space here.
• Center for Translational Imaging — MRI scans and MRI-TMS experiments
  • Olson Pavilion, 710 N Fairbanks Ct. One TMS room and two MRI scanners.

Purchasing, Expenses, and Reimbursement

I’m new here and haven’t yet figured out how this works at Northwestern. We will fill this section in as we learn the process. In the meantime, route purchasing and reimbursement questions through the lab manager, and if you figure out something useful about how the system works, tell us so we can write it down. Barbara Sutcliffe is the go-to person for purchasing through the psychiatry department.

Communication

First Choice: In-Person

In-person communication is always preferred. If someone is nearby and you have a question, walk over and ask. This is a lab, not a message queue.

Primary Digital Channel: Microsoft Teams

Teams is the lab’s primary digital platform. It is Northwestern’s enterprise-supported, HIPAA-compliant system, and the appropriate tool for anything touching subjects, clinical data, or Protected Health Information (PHI).

A non-negotiable rule: PHI and identifiable subject information must never appear in Teams messages, emails, or any informal communication. Use REDCap and the appropriate clinical systems for anything identifiable.

Response Time Expectations

• Please don’t make me chase you to get a response to a message. I have too many things going on – once I send you a message about something, I want to be able to unload that thing from my brain.
• During business hours: respond to Teams messages within a few hours.
• Email: respond within one business day for routine matters.
• After hours: Shan sometimes works at odd hours and may send messages late at night or on weekends (as I type this, it’s 1am on a Monday night/Tuesday morning; as I proofread it, it’s 9:30pm on a Sunday). I expect a response on the next business day. Your time outside of work is yours.

A Note on Slack

The lab may evaluate Slack for the computational subgroup at a later stage, given its developer tool integrations. This would be a deliberate decision, not a default. Until then, Teams is the platform.

7. Meetings

Weekly Lab Meeting

The full lab meets weekly. Lab meeting is where we share work in progress, give and receive feedback, and stay connected as a group. Attendance is expected. Format will evolve — expect a mix of in-progress presentations, paper discussions, and occasional external speakers. The lab manager coordinates scheduling.

Biweekly Methods and Data Meeting

A methods and data meeting runs every two weeks, led by Adam Pines. This is the space for getting into the details of analysis pipelines, imaging methods, data quality, and technical questions. If you are doing any computational or imaging work, this meeting is important for you.

Other Group Meetings

I encourage attendance at meetings for the computational neuroimaging workgroup, Jordan Grafman’s lab, the movement disorders clinical trials group, and potentially others as relevant.

1:1 Meetings with Shan

Everyone has a 1:1 with Shan. Cadence is individually titrated — set together at the start based on your role, career stage, and what you need. For some people this will be weekly; for others less frequent. The cadence should be revisited as needs change. If you feel you need more time, ask for it.

How to Prepare for 1:1 Meetings

This section is critical. I have a lot of meetings, and it’s exhausting for me if I have to run the show every time. When we have 1:1 meetings, I want you to take the lead.

Tell me what you’ve done, what you’re stuck on, and what’s next. If you have nothing to show, that’s fine — but know why, and say so.

Different people have different ways of preparing and presenting their progress at 1:1 meetings. That’s fine with me. But regardless of how you want to do it, please pre-write your results and/or discussion topics as notes or slides. If you want to show me brain images or graphs, put screenshots into your notes/slides beforehand. Prepare to take notes during the meeting, because you’ll forget stuff.

• Postdocs, students, faculty: I expect to focus more on scientific questions, results, etc.
• RAs/coordinators, lab manager, other staff: I expect to focus on the to-do list — what is done, what is pending, what is getting in the way, what needs to be added.

8. Projects and Authorship

Getting Your First Project

• Staff (coordinators, data staff, lab manager): projects and responsibilities are assigned based on lab needs. The lab manager and study physician will orient you.
• Trainees (graduate students, postdocs, clinical fellows): your first project is co-developed with Shan in early 1:1 meetings. Bring ideas; Shan will bring constraints. The goal is a project that fits the lab’s direction, has a realistic timeline, and is genuinely yours.

What Earns First Authorship

First authorship in this lab means owning the project from start to finish:

• You drove the intellectual question and the study design.
• You ran the analysis.
• You wrote the paper.
• You made the figures.
• You submitted to journals, responded to reviewers, and saw it through to acceptance.

That last phase — submission through acceptance — takes time. Budget at minimum several months; often longer. First authorship is not just running the analysis. It is the entire pipeline from question to published paper.

Grad students, postdocs, and junior faculty: Your job is to take the lead on first-author papers, grants, patents, etc. My job is to help you do it well. I expect you to figure out the next steps, and I’ll tell you when I disagree (which will probably happen a lot).

RAs/coordinators, lab manager, other staff: Your job is to handle tasks to help unclog my brain, enabling faculty to focus on higher-order science. Your tasks are just as important as everything else we’re doing — tasks are delegated based on capabilities/ availability, not based on importance. If I have to ask you to do something twice, then you haven’t unclogged my brain, which means your job hasn’t been done.

What Earns Middle Authorship

Middle authorship requires meaningful contribution to at least two of the following: study design, data collection, data analysis, and writing. Reading and substantively approving or revising the final manuscript counts as writing — so in practice, one meaningful contribution to design, data, or analysis, combined with genuine engagement with the final manuscript, earns middle authorship.

Have the authorship conversation early, not at the end. If you are contributing to a project, raise it at the start so expectations are set.

Last Authorship

Shan, Adam, Andrew, or Simon takes last authorship on most papers depending on who provided scientific direction. Exceptions — co-senior arrangements with external collaborators — will be discussed explicitly.

Authorship Disputes

The best way to prevent disputes is to document contributions from the beginning. When contributions are visible, order usually resolves itself. If a dispute arises, the process is sequential: (1) document what each person contributed; (2) discuss together, with Shan mediating if needed; (3) if still unresolved, Shan makes the final call. Prevention first, mediation second, adjudication last.

When Someone Leaves Mid-Project

The ideal outcome when someone leaves mid-project is that they finish the paper remotely. If that’s possible, the lab will make it work. If it’s not possible, whoever completes the project takes first authorship — with co-first authorship available, the order between co-first authors reflecting how much of the work was done before versus after departure. This is negotiated case by case with the goal of being fair to everyone involved.

Preregistration

Preregistration and analysis plans are governed by journal and funder requirements. There is no additional lab-level requirement beyond that. If you’re unsure whether a study should be preregistered, ask.

9. Data, Code, and Reproducibility

Data Management

The lab uses BIDS (Brain Imaging Data Structure) as the standard format for neuroimaging data. Clinical and behavioral data lives in REDCap. Adam Pines owns the detailed data management documentation, including directory structures, naming conventions, and backup procedures. When you arrive, ask Adam to walk you through the system.

A few non-negotiables across all roles:

• Raw data is never modified. All processing happens on copies.
• PHI is handled only in IRB-approved systems (REDCap, clinical records). It does not go in shared drives, email, or chat.
• Your data must be backed up. If you are not certain it is, check with Adam.

Imaging Preprocessing Pipelines

• The lab-standard for preprocessing is the CBIG (Computational Brain Imaging Group) pipeline from Thomas Yeo’s group at the National University of Singapore. Thomas might be the best neuroimaging engineer in the world, and also a close collaborator, so they can always help us troubleshoot if needed.
• Clinical trial data: the lab-standard preprocessing pipeline is mandatory. Consistency across the trial is non-negotiable, and deviations are not permitted.
• All other studies: Deviations from the standard pipeline are allowed when scientifically justified.

Adam Pines owns the standard pipeline. See him for documentation and onboarding.

Code and Version Control

Code standards are set and maintained by Adam Pines. See Adam for the lab’s code organization, version control practices, and expectations around reproducibility. The general expectation is that analysis code used in published papers should be documented well enough for an independent person to reproduce the result.

Data Sharing

• Final products — circuit maps, connectivity results — are deposited on NeuroVault and linked on the lab website when a paper is accepted for publication. Not before. The version you post should be the version in the paper; maps can change during revision.
• Raw data is handled case by case. Each dataset carries different IRB restrictions and consent agreements. Before sharing any data externally, talk to Shan.

10. Artificial Intelligence

AI tools are genuinely useful and they are not going away. My posture is cautious but open: there are situations where they save us a lot of time, and other situations where they are risky.

The guiding principle: AI should amplify your thinking, never replace it. Be honest with yourself – if AI is doing the intellectual work, you are not growing (and, best case scenario, you’re making yourself replaceable). Use it where it adds value; avoid it where it undermines your own intellectual development.

The Hard Limits

These are not negotiable and apply to everyone regardless of role.

• PHI and identifiable subject data may only be entered into a HIPAA-compliant AI tool within the NM clinical infrastructure.
• De-identified and aggregate data is not PHI and can be used freely with any tool.
• Tell Shan about any AI use before submitting a manuscript or grant, regardless of what the journal or funder policy says.

Writing Papers and Grants

Follow the journal or funder’s policy first. Most journals currently say you can’t use AI at all — so if you get caught, you’re in trouble, and that trouble is yours. Within that constraint, two uses are genuinely valuable:

• Critical feedback. Have AI critique your draft, then address the criticism yourself. This is one of the best uses of the technology.
• Proofreading. Catching errors, typos, and inconsistencies is a legitimate and low-risk use.

What AI should not do is write your paper. The same rules apply to grants and to abstracts — an abstract gets no special exemption just because it’s short.

Responding to Peer Reviewers

AI can help you think through how to approach a reviewer and make sure you haven’t missed anything. The scientific substance of the rebuttal is yours.

Reviewing Papers for Journals

Fact-checking only. Peer review is a confidential professional obligation and the judgment must be entirely yours.

Code

Use AI for boilerplate and infrastructure — not for analysis logic. The reasoning behind an analysis is the part that has to be yours.

For AI-assisted code that ends up in a published pipeline, three rules apply together: it must be reviewed and tested before use, its use must be noted in the methods, and the person submitting it takes full responsibility for it working correctly.

A real example: Claude once wrote me a script that treated infinite values as NaN. The result was a drastically inaccurate p-value. The code looked fine. This is exactly the failure mode to watch for — AI-generated code often runs cleanly while being silently wrong.

Statistics

Brainstorming only. AI frequently recommends the wrong analysis, and it makes subtle implementation errors that produce confident, incorrect results. Talk to Adam or a statistician before committing to a statistical approach.

Ideas and Hypotheses

Encouraged. AI is genuinely good for brainstorming, and using it to generate and pressure-test ideas is a legitimate part of the scientific process.

Literature and Learning

AI is a great learning tool, particularly for getting context and history of the field, and for explaining complicated methods. Use it to guide you to the right papers and to help you interpret them in context — it’s a good way to discuss how a particular result fits into the arc of the field.

Do not let it do the search or read the papers for you. It hallucinates, it sometimes leaves out key information, and it often says “yes, you’re right” when actually you’re wrong. Read the original papers.

Regulatory Documents

• IRB applications: formatting and boilerplate sections only. Scientific content — the rationale, the risk/benefit analysis — must be written by you.
• Informed consent forms: AI may draft a template, but every word must be reviewed and approved by the PI before submission.

Figures and Presentations

AI can assist with figure aesthetics and layout, but the underlying data visualization must be yours.

For slides: it’s fine for informal internal talks, but go through and trim the fat — AI-generated presentations tend to carry a lot of unnecessary fluff. Don’t use it for formal presentations outside the lab. AI-generated slides are easy to pick out from their design motifs, and that’s not the impression you want to make.

Communication

Write your own professional emails and messages. AI drafting leads to an impersonal lab culture, and how we write to each other is part of how this lab feels to work in.

Meeting Notes

AI transcription and note-taking tools are fine and are a real time-saver. Standard PHI rules apply.

Keeping This Section Current

None of us knows how this technology will evolve. If you think something here should change — because a tool got better, because a policy got stricter, or because we ran into a case this doesn’t cover — tell me and we’ll update it.

11. Conflicts of Interest and Industry

I have industry relationships, and I want to be completely transparent about them — both because you deserve to know, and because how to handle them well is something worth teaching.

Why We Engage With Industry At All

Thoughtful industry relationships help us get our treatments to patients faster. That is the whole point. We help companies design better studies; they help fund our work. We get equipment for free or cheap, which leaves more funding to hire staff and execute studies. And having those relationships in place means I can help trainees who eventually want a job in industry — which is a real and good career path, not a consolation prize.

The alternative – refusing all industry contact – sounds principled but mostly just slows down the translation of research into treatments that reach patients. If we refuse to work with industry, it means that drugs and devices are developed without input from real clinicians and scientists.

Investigator-Initiated Support: An Important Distinction

I have only ever accepted investigator-initiated industry support. This distinction matters and you should understand it:

• Investigator-initiated studies: we design the study, we write the protocol, we own the data, we decide what gets published regardless of the result. The company provides funding or equipment and has no control over the science.
  This works well when there’s a research question we want to study and we find a private company that also wants the answer to a similar question. Finding that intersection can be a nuanced process.
• Industry-sponsored studies: the company designs the study, owns the data, and controls publication. Academic institutions or private clinics may be involved to help collect data.
  This is a perfectly reasonable path for people who want to work in research but don’t want to design the experiments, managing the budget, etc. But it’s generally not a path towards becoming a PI of independent research.

Both of these approaches constitute a conflict of interest. Investigator-initiated studies can be part of a broader portfolio of funding for an independent academic research lab. Industry-sponsored studies are generally not considered part of a lab’s independent funding portfolio, but may be used for supplementary funding

How I Hedge My Conflicts

I deliberately maintain relationships across multiple companies rather than tying myself to one. The goal is that my overall bias points toward neuroscience-guided psychiatry in general, not toward any particular product. In particular I’m biased in favor of image-guided brain stimulation targeting. My NIH funding is also focused on these tools.

But scattering my biases doesn’t save me from bias. Our lab’s funding, the bulk of which comes from the federal government and nonprofit organizations, depends on the success of image-guided brain stimulation. I try my best to acknowledge and account for this bias in day-to-day decision-making, but sometimes I’ll also recuse myself from making decisions about situations in which I’m too biased to remain objective.

My Current Relationships

These are disclosed formally through Northwestern and on every paper and talk. In brief:

• Brain Circuit Targeting (BCT) — a startup developing TMS targeting software, which I co-founded.
• A private accelerated TMS clinic launching in Chicago.
• Medical director and advisory roles with TMS clinic networks.
• Various consulting and advisory relationships across the neuromodulation industry.
• Investigator-initiated grant support or equipment from various companies.

If you ever think one of these is affecting the science in a way it shouldn’t, say so. That is exactly the kind of thing I want to hear about, and Section 17 applies.

Your Own Industry Opportunities

Trainees taking industry consulting, advisory, or speaking roles is encouraged. More than that — I’ll actively help you figure out:

• How to do a good job in the role
• How to use it to enhance your career rather than distract from it
• How to negotiate the best deal for yourself
• How to structure it so it doesn’t compromise your science

Most trainees get no guidance on any of this and end up either avoiding industry entirely or accepting the first thing offered. Neither is good. Come talk to me before you commit to something significant, and disclose it through Northwestern’s formal process.

Intellectual Property

Intellectual property (IP) includes patents, trademarks, copyrights, and know-how. IP developed using Northwestern resources is generally owned by the university, and Northwestern’s Innovation and New Ventures Office (INVO) handles patenting and licensing. What matters for you:

• If you make an inventive contribution, you should be named as an inventor. I will make sure we follow the standard regulations — inventorship is a legal determination based on contribution, not a favor.
• A common misconception is that patents usually lead to considerable revenue for the inventors. The inventors get a small share of what the university gets, which in turn is a small share of what the company sells, which only happens if a company licenses the invention. The process is complicated, but I’ve been involved in every stage of it, so feel free to come to me for advice if you’re interested in this topic.
• If you think you’ve invented something, tell me before you present or publish it. Public disclosure before a filing can forfeit patent rights permanently.

Media and Press

Tell me before talking to any journalist, so I can help make sure you don’t make any of the same mistakes I’ve made in the past. Northwestern’s communications office is also a resource, and they’re good at this.

12. Human Subjects and Safety

Participant Emergencies

If a participant becomes acutely suicidal, medically unstable, or is otherwise in crisis during a study visit, start by calling the designated person for that study. If it isn’t clear who that is, or if they don’t answer, work down this chain:

1. Mohammad Lesanpezeshki (study physician)

2. Shan Siddiqi

3. Andrew Pines

4. The on-call physician for the TMS clinic

Never handle something alone if you are not explicitly trained to handle it. Nobody in this lab will ever be criticized for escalating something that turned out to be fine. The reverse is not true.

TMS Safety and Adverse Events

Only lab members who operate TMS devices are required to know the adverse event and seizure protocol. The lab manager owns the clinical safety protocols and certifies device operators. The study physician handles day-to-day clinical decisions.

MRI Safety Screening

Any lab member who has completed MRI safety training can screen subjects before scanning sessions. There is no designated screener role — it is a trained-person responsibility. MRI safety training is required before you are present for any scanning session. If you’re unsure whether you’re trained, you are not.

IRB and Protocol Literacy

If you interact with human subjects in any capacity — recruitment, consent, data collection, study visits — you are required to understand the IRB protocol under which that work is being conducted. This means knowing the inclusion and exclusion criteria, consent procedures, what constitutes a protocol deviation, and how to report one.

If your role is analysis-only, deep IRB literacy is not required. But you should understand the basics of informed consent and data governance for the studies whose data you use.

If something feels like it might be a deviation, assume it is and ask Mohammad or Shan before proceeding. It is always better to ask.

PHI Handling

Identifiable subject information is PHI. PHI belongs in REDCap and clinical systems only. It does not belong in Teams messages, shared drives, email, or any informal channel. If you are unsure whether something is PHI, treat it as PHI.

13. Career advancement in academia

Academia runs on a set of titles, tracks, and reporting lines that nobody ever formally explains. People absorb it by osmosis over years, and in the meantime they nod along in meetings without quite knowing who has authority over what. This is the orientation I wish someone had given me.

None of this is a test. But knowing where you sit, who the people around you are, and what the next rung looks like will make you more effective and less anxious.

The Two Pipelines

Academic medicine has two career pipelines that run in parallel and occasionally merge. Most confusion comes from not knowing which one someone is on.

Undergrad prep

• Undergraduate years: get involved in research, maybe do a thesis project. This could involve course credit or a side project. The earlier you get started, the more likely you are to get your name on publications.
• Research assistant (RA) or post-baccalaureate — typically at least 2 years of paid research work, often between college and graduate or medical school. Depending on your field, you may need more than 2 years. These days it’s hard to get into PhD programs with only 2 years of research experience. For medical school often 2 years is enough research experience, but you also need clinical experience – we can help you get that via clinical trials.

The PhD Pipeline

• Graduate student (PhD student) — roughly 4–7 years, ending in an original body of research and a dissertation. Most of our PhD students will be either in the neuroscience program (more “pure research”) or the clinical psychology program (research intermixed with clinical training).
• Postdoctoral fellow (“postdoc”) — roughly 2–5 years. You have the PhD (or, in some cases, MD post-residency) but not yet a faculty position. This is where you build the publication record and independent funding that make you hireable as faculty.
• Faculty — you run your own lab, or a defined program within someone else’s. If you are unable to get your own funding and a strong publication record within a few years of postdoc, you may also consider other non-faculty pathways.

The Clinical Pipeline

• Medical school — 4 years, ending in an MD or DO.
• Resident — 4 years for psychiatry or neurology, but different for other specialties. A licensed physician in training, salaried, seeing patients under supervision.
• Fellow — 1–2 additional years of subspecialty training. Note that “fellow” is overloaded: a clinical fellow is a physician in subspecialty training, while a postdoctoral fellow is a PhD in research training. Same word, different pipeline.
• Attending physician — fully independent clinical practice, supervising trainees. Mohammad Lesanpezeshki is a neuropsychiatrist serving as our study physician, the attending responsible for clinical decisions on our trials.

The Hybrid

Physician-scientists straddle both. Some do combined MD/PhD programs (7–8 years). Some do research-track residencies, which protect research time during clinical residency — the path Andrew Pines took with me. Some come to research towards the end of residency or during a research fellowship/postdoc – that’s what I did. All of these are legitimate; the field has no single correct route.

The hybrid path takes longer and requires actively defending research time against clinical demand, which is always more urgent and always expands to fill the space available.

Faculty Ranks

Colloquially, people often use the word “professor” to mean “a person who teaches at a university.” Within academia, we’re a bit more nuanced about terminology. These terms can differ between different countries.

• Research Associate — a PhD-level research position past the postdoc stage, doing independent scientific work without a full faculty appointment.
• Instructor — an entry rank, often transitional, common for physicians finishing training. At some institutions (e.g. Harvard), all faculty start at the instructor level rather than assistant professor level.
• Assistant Professor — the first full faculty rank. Usually signifies that they have confirmed funding for at least two years, either through research grants or clinical work.
• Associate Professor — promotion signals established independence: sustained funding, a recognizable body of work, a national reputation. At tenure-eligible institutions, tenure usually arrives here.
• Professor (“full professor”) — senior rank, national or international standing, at least 10 years since first faculty appointment (usually more).
• Named or endowed professorship — a title attached to a donated endowment, layered on top of rank. My Stephen M. Stahl Professorship is an example. It is a distinction and a funding source, not a separate rung. This is generally a highly desirable position, but the criteria for achieving it are somewhat subjective – it generally signifies a role or expertise that is highly valuable to the institution, independent of seniority or international reputation.
• Emeritus — semi-retired, retaining title and often some affiliation. Emeritus faculty will often remain involved in teaching/mentorship, but are no longer running a full lab.

Tracks

Most academic medical centers (including Northwestern) run parallel tracks. Same rank names, different expectations.

• Tenure-track — evaluated primarily on research productivity, funding, and scholarly reputation. Tenure-track faculty are responsible for managing grants, budgets, staff, research directions. At Northwestern, tenure-track positions can only be approved by the Dean of the medical school. Every tenure-track position comes with funding from the Dean to establish the lab infrastructure. For this reason, they are rare and highly sought-after.
• Clinician-educator track — evaluated primarily on clinical excellence and teaching. Research expectations are lower; the criteria are different, not easier. Clinician-educators may sometimes also have research responsibilities – this usually involves collaborating with a tenure-track or research-track faculty member.
• Research track (non-tenure) — titles like Research Assistant Professor. Full faculty status, usually fully grant-supported. Funding for research-track positions can come from various different sources, so the roles and responsibilities can vary widely. Some research-track faculty run fully independent labs, similar to tenure-track; others may be part of a broader center.
• Team scientist (non-tenure) – these faculty support the operations of a broader center or institute, but don’t run their own lab.

Everybody’s situation is different. There are many pros and cons to each of these positions. No one track is “superior” to any other track.

Roles That Aren’t Ranks

Several titles describe a job rather than a rung on the ladder. People hold these on top of whatever rank they have.

• Principal Investigator (PI) — officially, this is the person responsible for a specific grant or study. A role, not a rank. The same person can be PI on one study and co-investigator on another.
  Colloquially, the term “PI” also often refers to the person who is the head of any given lab. But that doesn’t mean that the head of the lab is the PI on every single study. In reality, junior faculty may take the PI role on some individual studies.
• Co-Investigator (Co-I) — a collaborator with defined responsibility on a study who is not the PI. Many large complex studies require multiple different types of expertise beyond the PI’s own skills. In that case, the PI will reach out to other colleagues to serve as a co-I responsible for specific parts of the study. Shan serves as co-I for multiple studies – usually when a TMS clinical trial needs an imaging expert.
• Study Physician — the licensed physician responsible for participant safety and clinical decisions on a trial. For our team this is usually Mohammad Lesanpezeshki.
• Lab Manager — runs lab operations, onboarding, scheduling, and trial coordination. Our lab manager will be Suman Premkumar.
• Domain Lead — our internal term, not a formal academic title. The person you go to first in a given area: Adam Pines for imaging and computation, Simon Kwon for experimental work, Andrew Pines for translational, Mohammad for clinical.
• Scientific Director — sets the research agenda for a center or program. I hold this role for the Bipolar Center of Excellence.
• Medical Director — the physician responsible for clinical quality and oversight at a clinic or company. I hold roles like this in industry (see Section 11).
• Chair — runs an academic department. At a top-tier medical school, this will generally be a senior clinician-scientist with a long track record of successful research work and clinical leadership. Sachin Patel chairs Psychiatry and Behavioral Sciences.
• Vice Chair — senior faculty with a defined portfolio. Linda Teplin is Vice Chair for Research.
• Division Chief — leads a clinical or thematic subunit within a department. Currently we are not part of a division.
• Dean — leads the medical school. Promotion and tenure decisions ultimately land in the Dean’s office.

You will also meet faculty whose titles describe their discipline rather than their rank — Ivan Alekseichuk is a neuroengineer, Stewart Shankman is a psychologist. Both are faculty; the descriptor tells you what they do, not where they sit.

Soft Money vs. Hard Money

This is the single most important thing to understand about how academic research works, and almost nobody explains it to trainees.

Hard money means your salary is paid by the institution regardless of your grants. Soft money means your salary comes from grants you win — if the grants stop, the salary stops. Most research faculty in psychiatry departments at academic medical centers are substantially soft-money funded.

This explains a great deal of academic behavior that otherwise looks strange: why grant deadlines dominate the calendar, why people care intensely about percent effort on budgets, why funding conversations carry an emotional weight that seems disproportionate. When you understand that a grant is somebody’s salary, it makes sense.

So what is hard money and how do you get it?

Hard-money positions are more common at public universities, where a portion of your salary comes from the state’s educational budget. The downside is that these positions usually (but not always) come with somewhat lower salaries and more institutional responsibilities (such as teaching and administration). Also they’re more common in less desirable locations – in Chicago, hard-money research positions are rare. They’re also more common in Europe, but those positions are extremely competitive.

The best of both worlds is an endowed position. This means that the university received a multimillion-dollar donation to support a particular program. The money is invested, and a faculty member is appointed to manage the program. That faculty member holds an “endowed professorship” – a professorship that is named after the donor. The proceeds from the investment will act as hard money to support that faculty member’s research.

Endowed positions are generally the most desirable jobs in academia. There are three ways to get one: (1) find a donor who wants to create a new endowment, (2) wait for somebody with an endowed position to retire or leave, or (3) find a place where #1 or #2 already happened, and apply for that position. I got my endowed position through the third pathway. These positions are not usually allocated based on seniority – to get one, you have to convince the university that your presence will bring them something they really want.

Grant Mechanisms

NIH funding comes in lettered mechanisms. You only need a working vocabulary, but the letters map roughly onto career stage, which makes them useful shorthand for where someone is. Note that other agencies (such as NSF, DoD, etc) also give grants that may sometimes be similar in mechanism.

• F31 / F32 — individual fellowships. F31 for predoctoral (graduate students), F32 for postdoctoral. Your first solo grant, and mostly a training award.
• T32 – institutional fellowships. A particular program within the university may already be funded to train some students or fellows in a particular area. If you find a T32 within the university that overlaps with your interests, definitely apply for it.
• K awards (K23, K08, K01, K99) — career development awards. Several years of protected research time for someone transitioning to independence. The classic bridge from postdoc or fellowship to faculty.
• R21 — exploratory or pilot funding. Smaller, shorter, higher risk tolerance, no preliminary data required. R03 is a similar, even smaller grant.
• R01 — the standard independent research grant, typically five years. Holding one is the conventional marker of an independent investigator, and often what promotion committees look for. There are other similar-scale grants (R33 is like an R01, but only three years and only for clinical trials). Other agencies have similar grants, such as CDMRP from DoD, etc.
• U and P mechanisms — cooperative agreements and center grants. Larger, multi-site, multi-investigator.

Foundation and industry funding sits alongside these and follows different rules. See Section 11 for the investigator-initiated distinction, which matters more than the dollar amount.

How Grant Review Works

Applications go to a study section — a panel of scientists in the field who read, score, and discuss them. Scores drive funding decisions, but the institute makes the final call, and funding lines shift year to year.

The practical points: the process takes roughly nine months from submission to money, most applications are not funded on the first try, and resubmission after revision is normal rather than a mark of failure. Most of my applications are rejected.

Promotion

Promotion criteria are written down, vary by track, and are available before you need them. A typical packet includes a CV, a personal statement, evidence of independent funding, a publication record, teaching and mentorship history, service contributions, and external letters from senior people outside the institution.

Two things worth knowing early: external letters mean your reputation beyond Northwestern matters, and the timeline is long enough that you should understand the criteria years before you are evaluated against them. Ask to see them.

Journals and Where We Publish

Where a paper lands affects who reads it, who cites it, and — fairly or not — how the work is judged. When you publish in a high-tier journal, people automatically take it more seriously, for better or for worse. The landscape sorts roughly into tiers. This is approximate, contested at the edges, and shifts over time, but it is close enough to navigate by.

Most journals have an “impact factor” – average annual number of citations per paper. This is a rough guide to how reputable the journal is, although there are exceptions. Some journals inflate their impact factor by publishing a lot of consensus statements that pick up lots of citations, even though they’re not “research” per se. Other journals have lower impact factors because they serve a specific niche, but are still well-respected within that niche.

• General-interest flagships —Broad readership, very low acceptance rates. Reserved for findings that change how a wide audience thinks. Impact factors > 50. A paper in one of these journals will singlehandedly catapult your career. I still haven’t hit one.
  • General science: Nature, Science
  • General medicine: NEJM, JAMA, The Lancet.
• Field-leading journals — The top of any given field. A first-author paper in one of these journals can be career-defining. With ~2-3 papers in these types of journals, you’ll be seen as a serious expert in the field. Most of our lab’s highest-profile work targets this tier. Impact factors > 15ish.
  • Neuroscience: Nature Neuroscience, Neuron, Nature Reviews Neuroscience
  • Biomedical sciences: Nature Medicine, Science Translational Medicine
  • Psychiatry: JAMA Psychiatry, American Journal of Psychiatry, Lancet Psychiatry.
  • Neurology: JAMA Neurology, Brain, Annals of Neurology, Neurology
• Strong specialty journals — A bit more specialized than the ones above, but still considered “strong”. A paper in one of these journals would be a huge accomplishment during a PhD or postdoc. Impact factors >10ish.
  • Psychiatric neuroscience: Molecular Psychiatry, Biological Psychiatry
  • Biomedical research: Journal of Clinical Investigation
  • General Science: Proceedings of the National Academy of Sciences
• Core field journals — Where much of the substantive work in our field actually lives. A well-executed paper here is a real contribution. Impact factors >5ish. Neuropsychopharmacology, Brain Stimulation, Imaging Neuroscience, Human Brain Mapping, Journal of Neuroscience, Translational Psychiatry.
• Solid, faster-turnaround journals — Transcranial Magnetic Stimulation, Journal of Affective Disorders, some others. Appropriate for incremental, niche, or negative results that deserve to be in the literature without a long fight.

Do not confuse tier with quality. A rigorous paper in a core field journal is worth more than a thin paper in a famous one, and the people whose opinion you actually want — the ones working on your problem — read the specialty journals closely.

Choosing Where to Submit

We decide this together, case by case. The variables to weigh are your career stage, how important the finding actually is, and the state of the field.

Sometimes an important finding gets disregarded simply because it did not appear in a top journal — that alone can justify aiming higher and absorbing the extra cycles. Other times the question is genuinely niche, and the faster route serves both the work and you better. A trainee who needs publications on a timeline is in a different position from an established investigator who can afford to wait out three rejections for the venue.

What I want to avoid is either failure mode: reflexively aiming at a flagship out of vanity and burning two years, or reflexively settling low and burying something that deserved a wider audience.

Preprints

Preprints are generally encouraged. Post to bioRxiv, medRxiv, ResearchSquare, etc, as appropriate. The practical benefit is that a preprint is citable immediately — you can cite your own work in your grants and manuscripts long before it clears peer review, which matters a great deal when you are building a record on a deadline. Check the target journal’s preprint policy first; nearly all now permit it, but confirm rather than assume.

Open Access and Publication Costs

Open access means the paper is free to read, paid for by an article processing charge (APC) that the authors cover — often several thousand dollars. Some journals are fully open access; others are hybrid, where open access is an optional paid add-on. For NIH-funded work like ours, the journal is required to make it open-access after 6 months anyway – so I try to avoid journals with APCs.

Ask before you assume a charge is unavoidable — and factor publication costs into grant budgets from the start.

Predatory Journals

Predatory journals take your money, publish nearly anything, and provide no meaningful peer review. A paper in one is worse than no paper at all: it signals either poor judgment or an attempt to inflate a CV, and it is permanent.

The signals are recognizable once you know them: unsolicited flattering emails inviting a submission, promises of review within days, journal names that closely mimic established titles, editorial boards you cannot verify, and fees disclosed only after acceptance. When something arrives in your inbox asking for a manuscript, the answer is almost always no. If you are unsure about a venue, ask me before submitting — that is a thirty-second conversation that prevents a permanent mistake.

There are also some journals that are considered “lower-tier”, but are not predatory. These are journals that accept almost anything even if the peer review was unfavorable, but still have legitimate editorial processes. Examples include Frontiers, PLoS, Scientific Reports, etc. These journals aren’t bad – they serve an important role, publishing data that may not be interesting enough for other venues, but still not totally meaningless. But it’s also not great for your CV to say “my PhD thesis was not totally meaningless.” So these could be targets for side projects or negative results, but ideally we’ll aim higher for your core project.

How Peer Review Actually Goes

Set your expectations now, because the process is slower and bumpier than anyone expects the first time.

• Desk rejection — an editor declines without sending the paper out for review, usually within days to a couple of weeks. Common at high-tier journals and not a judgment on rigor, only on fit and priority.
• Under review — typically one to three months, sometimes longer. Two to four reviewers.
• Revise and resubmit — the normal good outcome. Major or minor revisions, with a point-by-point response required. This can go multiple rounds.
• Rejection after review — also normal. You take the reviews, improve the paper, and submit elsewhere. The reviews are usually useful even when the outcome is not.

From first submission to acceptance, several months is typical and a year is not unusual, particularly if the paper is rejected once or twice along the way. This is why Section 9 says to budget months for the post-submission phase.

Rejection is a routine feature of the process, not a verdict on you. Every person in this lab, including me, has a folder of rejected manuscripts. The people who publish well are not the ones who never get rejected — they are the ones who revise and resubmit without taking it personally.

Metrics, and What They Actually Mean

You will hear these numbers thrown around and should know what they measure.

• Impact factor — the average citations per paper for a journal, not for your paper. It describes the venue, not your work.
• Citation count — how often a specific paper has been cited. A reasonable signal of influence, with a long lag and heavy field dependence.
• h-index — the number h such that you have h papers with at least h citations each. It rewards a sustained body of cited work over one big hit, and it rises with career length almost automatically.

These are crude proxies, useful in aggregate and misleading individually. They are worth understanding because other people use them to make decisions about you, and worth not optimizing for, because optimizing for them produces bad science. If you write a lot of bad papers and cite yourself a lot, you’ll still have a high h-index. But if you do work that matters, the numbers follow adequately.

Building a Reputation — and the Right Order to Do It

Conferences and professional societies are where a field talks to itself. In our world that means meetings focused on brain stimulation, neuromodulation, biological psychiatry, and neuroimaging. Attend, present, and meet people.

But the framing matters. Go to grow — personally, professionally, and as a contributor to the field. Reputation follows from that. If you invert it and chase reputation directly, the growth often does not follow, and people can tell.

A chess analogy: you win far more games by building a strong position first and then looking for the winning move. Players who hunt for flashy gamewinning moves before their position supports them lose to the people who did the quiet work first.

Your CV

For PhD students, postdocs, etc: start one now and update it as things happen, not annually from memory. An academic CV differs from a resume: it is comprehensive rather than curated, it has no length limit, and it lists everything — publications, presentations, grants, teaching, service, training.

Two related items worth setting up early:

• ORCID — a free persistent identifier that permanently links your publications to you. Register once; it prevents your work being confused with someone of a similar name.
• NIH Biosketch — a specific formatted document required for federal grant applications, including a personal statement and contributions to science. Different from a CV, and always needed on a deadline.

Mentors, Sponsors, and Collaborators

These three are frequently conflated, and the distinction is practical.

• A mentor advises you. They help you think through decisions, give feedback, and tell you the truth about your work. Mentorship is a conversation.
• A sponsor advocates for you when you are not in the room. They put your name forward for a talk, a committee, a job, an award. Sponsorship is an action, and it costs the sponsor something — their own credibility.
• A collaborator works with you. The relationship is peer-to-peer and centered on a shared project, not on your development.

You need all three, and you need more than one mentor. No single person can cover science, career strategy, clinical training, and life. Build a small set of people who each cover something, and don’t expect me to be all of them.

If I am your mentor, I will aim to also act as your sponsor and will try to help you find collaborators.

Departmental Structure

The nesting, from outside in:

• Northwestern University — the whole institution.
• Feinberg School of Medicine (FSM) — the medical school, where the Dean sits and where promotion decisions are finalized.
• Department of Psychiatry and Behavioral Sciences — our administrative home, chaired by Sachin Patel.
• Centers and institutes — the Stahl Center for Psychiatric Neuroscience, the Dauten Behavioral Health Institute, the Bipolar Center of Excellence. Thematic groupings, often donor-funded, that cut across departments.
• Labs — individual PIs and their groups. Us.

The University / Hospital Distinction

Northwestern University and Northwestern Memorial Hospital are separate corporate entities with separate systems, badges, and approval chains. Faculty who see patients typically hold appointments at both. When an approval is stuck and you cannot work out why, this split is often the reason.

Who Actually Controls What

• Whether your study can run — the IRB. Not your PI, not the chair.
• Whether your grant goes out — research administration, on their internal deadlines, which precede the funder’s.
• Whether you get promoted — the department committee and the Dean’s office, against published criteria.
• Intellectual property — INVO, Northwestern’s Innovation and New Ventures Office.
• Space, recruitment, and salary support — the Chair.
• Your day-to-day work, mentorship, and letters — me.

Where Staff Roles Go

Research staff positions are not a lesser track — they are a distinct one, with real trajectories.

• Research assistant → study coordinator → senior coordinator → lab manager → research program manager or director. A genuine career with increasing scope and compensation.
• Into training — many RAs use the position as a launchpad into medical school, graduate school, or a PhD program. If that is your goal, we will shape your work and your letter around it.
• Into industry — clinical research associate, clinical operations, project management, medical science liaison, regulatory affairs. Clinical trial experience is directly transferable and well compensated.

International Trainees

A significant share of academic research staff and trainees are international, and visa status shapes real constraints: which positions you can hold, how long you can stay, how job changes work, and how much lead time everything needs. I came to this country as an immigrant, so I’m empathetic to the cause – but I was nine years old, so I didn’t understand the process. Fortunately there are lots of people within the university who do understand the process.

Leaving Academia Is Not Failure

Industry, biotech, pharma, policy, clinical practice, data science, and medical communications are all real destinations, and for many people they are better ones. Compensation is often higher, the work is often faster, and the impact can be larger.

It is tempting to assume academia is the “best” path, mostly because you are surrounded by academics who chose it — that is a selection effect, not evidence. With the right position, leaving academia should be considered a success. What matters is finding the place where your particular combination of skills does the most good. Tell me if you are thinking that way and I will help you go, not talk you out of it.

An Honest Note

Academia has real problems. Funding is scarce and slow. Publishing is uneven and sometimes unfair. Some people figure out how to play weird games via which prestige starts to compound in the absence of merit – the Paris Hilton phenomenon. There is politics, because there are humans.

None of that is a reason for cynicism. It is a reason to be strategic: understand how the system works, build genuine skills, do work you can defend, and treat people well. The people who thrive are usually the ones who did the unglamorous work consistently, not the ones who gamed something.

A Worked Example: My Own Path

I include this because trajectories look inevitable in retrospect and never feel that way from the inside.

I did not go to a fancy high school or a prestigious college — local public schools for both. I worked around 25 hours a week throughout college, selling computers and cameras at Circuit City (a now-defunct chain similar to Best Buy), teaching chess, and various other jobs. I did not get good grades. I went to Australia for medical school because they were willing to accept a good MCAT score in lieu of good grades.

I did not know my research path until well into residency. When I started fellowship, my publication record was probably the weakest among my colleagues. At the time I thought I was starting late and was far behind my peers.

I was wrong about that. I had not been late — I had spent that time gathering a great deal of valuable experience without realizing it:

• I knew how to sell a computer to someone with no knowledge of computers. That translates directly into writing a complex paper or grant.
• I had built a strategist’s mindset through chess, which shaped how I think about establishing fundamental knowledge before launching a clinical trial.
• I saw third-world suffering during my early upbringing in Pakistan, which instilled grit and resourcefulness.
• I grew up bilingual and had all of my education in my second language, which forced me to learn how to translate concepts that don’t neatly fall into one category.
• I had been there for family and friends when they struggled, which helped me understand the patient’s perspective.
• I modified cars, built computers, and repaired guitars — so I became a technologist.
• I stayed in touch with friends who didn’t go to college, and with friends who became highly successful. Both kept my sense of people calibrated.

Those skills, built during the years when many of my now-colleagues were getting a head start in the lab, are a large part of why my career accelerated so rapidly once I was in science full-time.

The point for you: if your path has not been linear, that is not a deficit to apologize for. The experience you have that your peers lack is frequently the thing that will distinguish you — but only if you learn to recognize it and use it.

Where You’re Going

Wherever you are on this map, the next step is knowable and the criteria are usually written down somewhere. Part of my job is to tell you what those criteria actually are, help you meet them, and be honest about how you are tracking. If you are not sure what the next rung looks like for you specifically, raise it in a 1:1 — and raise it early rather than late.

14. Career Development

Goals and Individual Development Plans

For trainees — graduate students, postdocs, clinical fellows — career development is tracked through a formal Individual Development Plan (IDP). The IDP is reviewed annually and drives your 1:1 conversations with Shan. It should reflect your career goals, the skills you’re building, and the milestones you’re working toward. Format is flexible; what matters is that you’ve thought about where you’re going.

For staff, goals are tracked more lightly through 1:1 conversations. If you want more structure, ask for it.

What You Can Expect from This Lab

Research Assistants, Study Staff, and Lab Manager

Expertise in clinical trial operations, TMS protocols, neuroimaging logistics, and regulatory compliance. Co-authorship where contributions meet the threshold. A strong reference letter reflecting your specific work. Access to the lab’s global professional network in neuromodulation, psychiatric research, and industry.

Graduate Students

The skills to independently design and execute original research. At least one major first-author publication, as well as opportunities to do additional projects. Active support in applying for trainee funding (F31 and relevant foundation grants) at the appropriate stage. Conference presentations each year. A strong letter from Shan that speaks to specific things you did — not a generic endorsement.

Postdocs, Junior Clinical Faculty, and Research-Track Residents

Development of a research niche. A publication record competitive for faculty positions. Support in pursuing larger grants. Shan’s active investment in your scientific identity — not just extending his. Letters that are specific, detailed, and proportional to what you’ve done.

Clinical Fellows and Residents

Expertise in the clinical application of brain stimulation and the science behind circuit-targeted approaches. Fellows aim for at least one first-author publication during fellowship, positioning for a subspecialist career in academia, industry, or private practice. Residents get enough exposure to decide if they want to pursue this field.

Independent Funding

Applying for independent funding is a required part of training at the appropriate career stage — not optional. The nature of funding applications will vary depending on seniority and long-term goals (academia vs. industry, US vs. international, etc.). Grad students should ideally aim to apply around the middle of their program. Postdocs and junior faculty should be thinking about independent funding already.

The purpose is not to fund the lab. The purpose is to develop your scientific identity and funding track record, which will serve you throughout your career regardless of where you go. If you want to stay in academia, you need independent funding.

Conferences

Each lab member is funded for one major conference per year as the baseline. Additional travel may be covered if you are explicitly invited to present a symposium, deliver a major lecture, or participate in a featured session — discuss the specifics with Shan. Submit abstracts. Present your work. This is how the field moves and how you build a reputation in it.

Practicing your talk before a conference or external presentation is strongly encouraged. If you want feedback on slides or delivery, ask — lab meeting is a good venue for it.

I also strongly encourage taking every possible opportunity to present your work at local conferences. There are lots of poster sessions and other events within Northwestern. If you only want to present your work at desirable out-of-town locations and never care to present locally, it gives off the impression that you care more about the trip than the work.

Letters of Recommendation

Shan will write a letter for anyone who asks. The letter will reflect what you actually did. The best letters are the ones where he can point to specific things that demonstrate thoughtfulness, mission focus, and initiative beyond what was expected — where he can say that you didn’t just do what was asked, but saw the next question and answered it. That’s the same bar as being excellent at this job.

Social Media and Public Communication

You are free to post about the lab’s work on social media without prior approval. One firm limit: no patient or subject information in any form, identifiable or otherwise. One soft limit: be careful about posting unpublished data, as the content could change during the peer review process. When in doubt, ask before posting.

15. Culture and Values

What “Getting It” Looks Like

There are two behaviors that tell me someone understands what we’re trying to do here.

The first is reliability. If I ask you to do something, I need it done – the first time, without a follow-up. Not because I’m demanding, but because I’m managing multiple projects simultaneously, each with countless moving parts. Every task I have to track twice is attention I don’t have. Closing the loop without being chased is a form of respect for everyone’s bandwidth.

The second, and the one that separates good from great, is anticipation. The best people in this lab don’t just do what was asked. They take the task, find the next question it implies, answer that question too, and bring it all back. They make the work go faster and the science go deeper. If you want to know what thriving here looks like, it looks like that.

Effort and Honesty

Being wrong is fine. Hypotheses fail. Data surprises us. Analyses don’t replicate. All of that is science. What is not fine is knowingly cutting corners to finish something with minimal effort. The line is not correctness - it’s whether you tried your best and were honest about your limitations. Working hard and being upfront about what you don’t know are always acceptable. Deliberate shortcuts are not.

Making mistakes is normal and acceptable. But covering up your mistakes is a form of dishonesty. It’s always really obvious when people are doing that. I’ve been doing this for a long time, and I can usually tell when somebody made a mistake and is trying to cover it up. Admitting fault is a sign of maturity.

Respectful Disagreement

Disagreeing with me is always okay. Disagreeing with each other is always okay. People express disagreement differently — some directly, some with more care — and all styles are welcome. Respectful disagreement is not just tolerated here; it is at the core of good science. If you’re not sure how to voice a disagreement with a colleague, come to me and we’ll figure out the right approach together.

Conduct

Integrity matters. When you fail, admit it honestly and move on to the next step. When something works but you don’t know why, acknowledge it. Sounds simple, right? Everyone wants success — beware of this human bias. We may inadvertently be biased to report a positive outcome when, in fact, it is not. Another bias is the desire to be right. When something works but in an unexpected way, we may mistakenly dismiss the outcome. These types of mistakes must be fixed, and my door is open.

Research misconduct is not an honest mistake. It means tampering with data, fudging results, plagiarism, or unprofessional behavior to influence the outcome. Note well that this lab does not tolerate any form of threats, harassment, or discrimination. Misconduct undermines our mission, and everyone involved. It also ends careers — don’t do it.

Effort and intelligence are commodities. Distinguish yourself by character.

A Note on Being Part of a New Lab

This lab is new. Some infrastructure is still being built, some processes are still being refined, and some things in this document will turn out to be wrong in practice. That’s the nature of starting something. If you run into something that doesn’t work or doesn’t match what’s written here, flag it — and we’ll fix it. The goal is a lab that works well, not a document that looks like one.

16. Wellbeing

I’ll for everybody to be assigned a 40-hour work week. If study demands require overtime in a given week — study subjects, grant deadlines, covering for somebody else who is out sick — we can compensate with lighter weeks (see the hours section). Your time outside of work is yours.

If you want to take on extra projects beyond your assigned responsibilities — maybe you want to strengthen your publication record, maybe you’re passionate about something, maybe you just enjoy the work — I will support you and will provide you with the mentorship and resources to get it done. That is your choice, and I’m not here to tell you what to do with your spare time.

Do not prioritize extra work over your family or your physical or mental health. If you find yourself doing that, or feel like you have no choice, come talk to me. I’ll try to point you in the right direction – I do know a lot about mental health – and will do it without becoming your psychiatrist.

Note that work-life balance is just that – a balance. Just like I don’t want work obligations getting into your personal life, I also want everybody to stay committed to our core mission during work hours. If you’re having personal difficulties that interfere with your ability to do that, talk to me and I’ll try to help.

17. Raising Concerns

If you have a concern – about a project, about a colleague, about the lab, or about me – come to me directly. There is no intermediary required and no wrong way to raise something.

This includes concerns about me specifically. If I’ve done something that bothered you, or handled a situation in a way you think was wrong, I want to know. I will not penalize anyone for raising something difficult honestly. That’s not the kind of PI I want to be, and if I fall short of it, I want someone to tell me.

If for any reason direct conversation with me is not possible — or if the concern involves me in a way that makes it uncomfortable — Northwestern’s Department of Psychiatry and the Feinberg School of Medicine have formal channels for raising concerns. The lab manager can direct you to the appropriate resources.

18. Exits and Alumni

A good exit from this lab looks like:

• All data has been handed off, documented, and is accessible to whoever continues the work.
• Papers you owe the lab — or that the lab owes you — have a clear completion plan.
• You leave knowing where the work stands and who is responsible for what.

I will actively help you leave well. That means making sure you have what you need for your next position: a strong letter, introductions to relevant people, and a clear narrative of what you built here. I will also do everything I can to make you want to stay, because the best outcome is that talented people keep doing important work together.

Good exits are celebrated. When someone leaves for a great opportunity, that is a success — for them and for the lab. People who trained here are part of this project for as long as they want to be.

19. Glossary

Terms you’ll hear constantly. Ask if something isn’t here.

Brain Stimulation

• TMS — transcranial magnetic stimulation. Non-invasive brain stimulation using magnetic pulses.
• rTMS — repetitive TMS. The standard clinical form of treatment.
• aTMS — accelerated TMS. Multiple treatment sessions per day, compressing a course from weeks into days.
• iTBS — intermittent theta burst stimulation. A patterned, faster TMS protocol.
• SAINT — Stanford Accelerated Intelligent Neuromodulation Therapy. The accelerated, imaging-guided protocol that established much of this approach.
• LIFU — low-intensity focused ultrasound. Non-invasive stimulation that reaches deeper structures than TMS.
• DBS — deep brain stimulation. Surgically implanted electrodes.
• MEP — motor evoked potential. Muscle response used to determine stimulation intensity.
• RMT — resting motor threshold. The individualized dosing baseline for TMS.

Imaging and Analysis

• fMRI — functional magnetic resonance imaging.
• BOLD — blood-oxygen-level-dependent signal. What fMRI actually measures.
• rsfMRI — resting-state fMRI. Scanning without a task, used for connectivity mapping.
• BIDS — Brain Imaging Data Structure. Our standard data organization format.
• fMRIPrep — the standard preprocessing pipeline.
• LNM — lesion network mapping. Tracing networks from lesion locations to identify symptom circuits.
• PFM — precision functional mapping. Extended scanning to characterize an individual’s brain organization.
• NeuroVault — public repository where we deposit circuit maps at publication.

Clinical and Regulatory

• PHI — protected health information. Anything identifiable about a patient.
• IRB — Institutional Review Board. Approves and oversees human subjects research.
• CITI — the standard human subjects research training program.
• GCP — Good Clinical Practice. Required training for clinical trial work.
• REDCap — the secure database system for clinical and behavioral data.
• AE / SAE — adverse event / serious adverse event. Both have mandatory reporting requirements.
• COI — conflict of interest.
• DSMB — Data Safety Monitoring Board. Independent oversight for clinical trials.
• MDD — major depressive disorder. Also OCD, PTSD, TBI, AUD (alcohol use disorder).

Northwestern-Specific

• FSM — Feinberg School of Medicine.
• NMH — Northwestern Memorial Hospital.
• NetID — your Northwestern login credential for everything.
• INVO — Innovation and New Ventures Office. Handles patents and licensing.
• CTI — Center for Translational Imaging. Where we scan (Olson Pavilion).
• Dauten — the Dauten Behavioral Health Institute (Arkes Pavilion).
• Stone Institute — the inpatient psychiatry unit (Galter Pavilion).
• Abbott 13 — our offices, 710 N Lake Shore Dr, 13th floor.
• Shirley Ryan AbilityLab — rehabilitation institute; Jordan Grafman’s home base.

One last thing.

The work we’re doing here matters. I know that can sound like something everyone says, but I mean it in a specific way: there are people who are suffering from psychiatric illness right now, for whom the current tools are not enough, who will have better options because of what we build. Don’t forget that.

— Shan Siddiqi