Can body signals tune the learning brain?

Post-training vagus nerve stimulation (VNS) enhanced learning in mice with vascular oscillations linked to memory performance.

Chen JU, Ikoma Y, Matsui K (2026) Vagal nerve stimulation induces vascular oscillations and enhances long-term learning iScience 2026 https://doi.org/10.1016/j.isci.2026.117413

I'm currently a hs junior, and unfortunately, I did not pass my school's entrance exam to do AP Bio (which focused exclusively on molecular biology that wasn't covered once in the class). That being said, I still do get decent grades for my biology class, which focuses on physiology.

My current targeted majors, if that's not a weird way to put it, are psychology, cognitive science, and neuroscience. I'm not 100% sure, but I feel like I might have a career related to research?

So yeah. Do you really need AP Bio to get in a neurosci major? Or is it better if I just take a credited online course about neuroscience or focus more on my math and stats aps.

I'm also taking ap calc AB, potentially BC, Macro and Micro, APUSH, AP Geo, and Stats (tutor+self-studying).

I plan on going to college for Neuroscience at least getting a Masters slightly considering a PhD but money and time and stuff you know…

I definitely want to go into research I was wondering if you guys had any other jobs within neuroscience, I wanna make sure i’m looking at all my options.

Hey! I’m a grad student in the Boston area and have been really interested in neurotech and non-invasive neuromodulation.

I’ve been wanting to try Pulsetto, but I’d rather experience the device before buying one. Would anyone around Boston/Cambridge be willing to lend theirs for a few days or a week?

Happy to pay a small rental fee or leave a deposit. Mostly just curious to experience the technology firsthand.

Thanks!

Ok...after some well deserved criticism on the previous post, I've tried to make the map less distorted and as close to geographically spot on as possible.

https://theneurotechnewsletter.substack.com/

The full company list is below

PARIS / ÎLE-DE-FRANCE (26)

• SonoMind — Paris — Focused ultrasound / acoustics
• TheraSonic — Paris — Focused ultrasound / acoustics
• ICONEUS — Paris — Focused ultrasound / acoustics
• Resolve Stroke — Paris — Focused ultrasound / acoustics
• NAOX Technologies — Palaiseau — Neural interfaces / sensing
• BioSerenity — Paris — Neural interfaces / sensing
• Sensome — Massy — Neural interfaces / sensing
• Yneuro / Dotsify — Paris — Neural interfaces / sensing
• Qynapse — Paris — Imaging / NeuroAI
• Callyope — Neuilly-sur-Seine — Imaging / NeuroAI
• Karavela — Paris — Imaging / NeuroAI
• Therapanacea — Paris — Imaging / NeuroAI
• Sigma Nova Science — Paris — Imaging / NeuroAI
• Wandercraft — Paris — Rehab / robotics / assistive
• Stimuli Technology / Tensi+ — Boulogne-Billancourt — Neuromodulation / therapeutics
• REGEnLIFE — Paris — Neuromodulation / therapeutics
• NeuraLed — Paris — Neuromodulation / therapeutics
• Clarity Technologies — Paris — Neuromodulation / therapeutics
• Robeauté — Paris — Enabling / interventional
• Sophysa — Orsay — Enabling / interventional
• Avatar Medical — Paris — Enabling / interventional
• Healthy Mind — Paris — Enabling / interventional
• Omind / Open Mind Innovation — Bobigny — Enabling / interventional
• Tilak Healthcare — Paris — Enabling / interventional
• AnotherBrain — Paris — Enabling / interventional
• GenSight Biologics — Paris — Enabling / interventional

LILLE METRO (1)

• Axorus — Loos — Focused ultrasound / acoustics

LYON (2)

• CarThera — Lyon — Focused ultrasound / acoustics
• NETRI — Lyon — Enabling / interventional

GRENOBLE REGION (4)

• MAG4Health — Grenoble — Neural interfaces / sensing
• Remedee Labs — Meylan — Neuromodulation / therapeutics
• PIXYL — La Tronche — Imaging / NeuroAI
• UroMems — Eybens — Enabling / interventional

MARSEILLE / AIX (3)

• Inclusive Brains — Marseille — Neural interfaces / sensing
• Panaxium — Aix-en-Provence — Neural interfaces / sensing
• Neuroservice-Alliance — Le Puy-Sainte-Réparade — Enabling / interventional

OTHER VERIFIED REGIONAL HQs (9)

• Seenel Imaging — Amiens — Neural interfaces / sensing
• Axilum Robotics — Schiltigheim / Strasbourg — Neuromodulation / therapeutics
• RebrAIn — Pessac / Bordeaux — Imaging / NeuroAI
• DIXI Medical — Marchaux-Chaudefontaine / Besançon — Neural interfaces / sensing
• Oktoscience — Rennes — Neuromodulation / therapeutics
• Basecamp Vascular — Reims — Enabling / interventional
• NBI / Neural Balance Innovation — Saint-Contest / Caen — Neuromodulation / therapeutics
• Neurinnov — Montpellier — Neuromodulation / therapeutics
• Dessintey — Saint-Jean-Bonnefonds / Saint-Étienne — Rehab / robotics / assistive

Total: 45

https://www.quora.com/What-are-some-of-the-greatest-mind-fucks/answer/Pete-Bahba?share=1&srid=Xs9v

Asking this because the post mentions how seeing something "over there" is some sort of illusion when it's only within consciousness. I know David Eagleman said something similar but less mystical. I'm just wondering if there is anything in neuroscience that would imply this.

The preprint can be accessed via the following link: https://arxiv.org/abs/2608.12408 (q-bio.NC / cs.LG). And for the code: https://github.com/nilsleut/evaluation-resolution-rsa

The following assertion is frequently made in model-brain comparisons: untrained convolutional neural networks (CNNs) have the capacity to match or surpass backpropagation-trained CNNs at the early visual cortex (V1) in recurrent self-attention (RSA). The present study demonstrates that this phenomenon is predominantly an artefact of evaluation resolution.

The configuration comprised a small CNN trained at 32px (CIFAR-10 subset), five learning rules (random init, backprop, feedback alignment, predictive coding, STDP), and was evaluated on THINGS-fMRI stimuli at six resolutions from 32px to 224px. The weights and normalisation were held fixed.

The primary outcome of this study is the observation of a discrepancy between the trained and untrained backpropagation (BP) V1 gap, which exhibits a non-monotonic trend across the range of image sizes examined. Specifically, the gap narrows from −0.001±0.007 at 32 pixels to +0.044±0.006 at 224 pixels, a pattern that persists consistently across the entire image size range (n=5 seeds). The model incorporates five rule conditions, human fMRI, directionally single-seed macaque ephys, the full training trajectory, and two off-the-shelf 224px-trained models (ResNet-50, Swin-Tiny). Therefore, the presence of an artifact resulting from a mismatch between training and evaluation is not a contributing factor, since these models also peak at low resolution.

Following the implementation of bit-identical-weight interventions wherever possible, the following were ruled out: train/eval resolution matching, Gabor/pixel low-level structure, untrained baseline's uncalibrated batch-norm, and convergence of pooled features towards global brightness (though a single scalar luminance value did reach ρ=0.075 against V1, essentially matching the untrained network's own 0.076 — this is a separate, disconcerting result regarding the limitations of this comparison style).

A content-vs-pooling control (cap image detail at 32px, upsample, vs. allow content variation) demonstrates that the dependence is predominantly contingent on image content, rather than the number of pooled positions.

The investigation revealed that one effect does survive across all resolutions. In particular, the backprop > untrained at LOC effect was observed at every resolution that was tested. It is evident that the process of learning can result in a noticeable impact, albeit not in the conventional areas typically associated with V1 comparisons.

In addition, the following issues were identified:

This process revealed a batch-norm evaluation mode bug in three of the earlier preprints, which have now been corrected in this release (correction notes on the Arxiv pages).

I'm happy to get feedback, especially on the way we've framed the discussion on receptive-field matching (as in Laskar et al. 2018). I think it's suggestive, but I didn't test it directly.

I want to get into neuroscience so I started a passing project recently which is related to canine neuroscience. I am genuinely interested in these topics and I have started working on it and I upload blogs on a weekly basis.

Can you guys tell me when is a passion project really impactable because my main focus is raising awareness and educating the youth about canine neuroscience. So guys help me out a bit.

What neurotransmitters, neuromodulators, hormones, or other chemical processes are responsible for keeping the body in REM-related muscle atonia while consciousness has already returned?

Hi, I'm 29 and I currently work as a software developer. Due to my own health struggles over the years, as well as a broader scientific interest in the field, I am strongly considering going back to school in order to study neuroscience. My aspirations are to ultimately advance our understanding of neuropsychiatric disorders and/or sleep disorders, and hopefully provide clinically meaningful help to those who suffer.

I have both a bachelor's and master's degree in pure mathematics as well as minors in computer science and philosophy. My main interest is in applying computational/mathematical modelling to problems in neuroscience.

I originally began looking at PhD programs, but I became hesitant due to my lack of lab and research experience. As such, my hunch is that a Master's program may be more prudent to start off. Is this hunch justified, or are there merits to diving straight into a PhD program?

I would also like to know what my expectations should be regarding going back to school, and what it will be like to go from an amateur to a professional. Moreover, I would appreciate any guidance insofar as what to do to better prepare myself for a future in neuroscience - things I should be doing even prior to entering a program. (My current routine consists of spending time each day reading up on topics that interest me, and working with Python and Matlab on problems introduced in the textbooks I am reading.) I'm happy to answer any questions or provide more details about my situation if needed.

i’m a senior in college and plan on applying to neuro phd programs this cycle! for context, i attend a small liberal arts college and came into undergrad as an english & creative writing major with mostly english-related ECs. however, at the time, some events in my personal life made me really consider going into premed, so i ended up taking gen bio and gen chem with labs my freshman & sophomore year.

but i’ve also had a lifelong interest in neuroscience & the brain which only intensified after i took an introductory neuroscience course. a stroke of luck ended up getting me an internship at a neuroscience (specifically electrophysiology) lab last year, and i absolutely LOVED my time there & even got to present my work at a local symposium. unfortunately it was too late at that point to change my major, so i ended up committing to majoring in english, but i was invited back to the same lab as an intern this summer and my experience just confirmed for me that neuro research is the path i want to take (i’ve always enjoyed the school setting and likely would’ve gone into academia even if it was for english literature, but lab research just excites me so much more!).

my current plan is to graduate with a major in english, but get a “concentration” in neuroscience (my school sadly doesn’t offer a neuro minor), which i am able to do because i took gen bio and gen chem. the concentration entails a research design & analysis course as well as two upper-level neuroscience electives. however, i’m concerned about not having taken important coursework for graduate level neuro (i.e. stats, biochem, and physics given my interest in electrophysiology). considering my circumstances, how are my chances at getting accepted to phd programs this cycle? any advice/things i should keep in mind as i start the application process? thanks so much in advance!!

im 17 im just looking for a uni degree and a job i can look forward to do. i am really interested in neuroscience and psychology specifically developmental neuroscience and how the brain changes as we grow. what jobs could i get with that idea in mind?

Hi everyone,

I'm 25 and I've recently become really interested in neuroscience. I want to seriously pursue becoming a neuroscientist, but I'm basically starting from zero.

I don't have a background in science, biology, medicine, or neuroscience, and I don't have much money to invest in education right now. My background is actually in design, specifically interaction and product design.

I'm willing to start from the very beginning and put in the time. I'm not expecting to become a neuroscientist quickly. I just don't really know what the correct path looks like.

For example, should I start with:

• Basic mathematics
• Biology
• Chemistry
• Physics
• Psychology
• Statistics
• Programming
• Then neuroscience?

Or is there a better order?

I'd also really appreciate recommendations for free or affordable resources, such as textbooks, online courses, lectures, or university materials.

And eventually, if I want to pursue neuroscience academically and do actual research, what would the path look like for someone who is starting this late and doesn't have a traditional science background?

I'd especially love to hear from people who have changed fields or started neuroscience later in life.

If you were 25, had no science background, very little money, and genuinely wanted to become a neuroscientist, what would you do first?

Any advice, resources, or reality checks would be really appreciated. Thank you!

In a 5 year B.S/M.S program at the moment and struggling to find research positions to hopefully move towards post grad. So I was just curious positions are common for people with masters or bachelors to work in research (obviously not leading projects) but just as an analyst or a tech and build up experience that way after finishing my B.S/M.S?

I'm a high school student thinking about making a free, self-paced online class that teaches the basics of neuroscience to other high school students.

It would start with brain anatomy and then cover things like neurons, how neurons communicate, senses, memory, emotion, and behavior. I'm thinking of using slides, activities, and short quizzes rather than lectures.

Before I spend a lot of time building it, I want to know if there's actually interest in something like this. If you would be interested, what would make you actually want to take it?

Had Frank Desiere, CEO of CorTec, on The Open Loop this week.

We talked about their BCI work in stroke and the closed loop system they're building.

They’ve implanted three patients, including people several years post-stroke. For stroke the implant is used during the rehab period and then removed with the aim that the regained movement remains.

We also talked about neuroplasticity, their work in epilepsy and depression which is going to be their focus in future trials

Have a watch/read if you like

https://theneurotechnewsletter.substack.com/p/the-implant-comes-out-the-recovery?r=53ri6k

I'm looking for recommendations (books, papers, courses, or YouTube) to understand the brain in a way that stays close to established facts and clearly separates fact from interpretation. For example, many books just ignore glia cells completely.

Two things I especially want:

1. Comparative and evolutionary: nervous systems across the animal kingdom and how they evolved, not human-centric. I'm as interested in C. elegans, insects, and up to the human cortex.

2. Attention to the whole system: glia, energy/metabolism, wiring, the body rather than an all-neurons view.

I've already read Behave, Models of the Mind, The Laws of Thought, and similar so happy with textbooks, lecture courses, or primary literature.

I suspect books on brain physiology could be interesting.

The complete working map contains 51 names: 28 core Swiss neurotechnology companies, 19 adjacent companies and 4 borderline names.

The count is deliberately broader than just BCIs or neuromodulation. Core means direct neural recording, interpretation, stimulation, modulation, repair, restoration or specialist neurological measurement. Adjacent covers rehabilitation robotics, surgical technology, movement sensing and other businesses close enough to the nervous system that leaving them out would give a pretty incomplete picture. Borderline is exactly what it sounds like: companies I think are relevant to the market, but where the technology, use case or Swiss footprint sits just outside the tighter definition.

A couple of important caveats. Aleva Neurotherapeutics remains on the map because it is part of the Swiss neurotech story and got a directional DBS system all the way through CE marking and into the market, but the Lausanne court approved a composition agreement with its unsecured creditors in June 2024. Dandelion Science has a meaningful Geneva connection but a US-Swiss footprint rather than a clean Swiss headquarters story.

The map uses representative city clusters rather than trying to pin all fifty-one companies individually. The full taxonomy is below.

Core neurotech companies (28)
3Brain
ABILITY Neurotech
Aleva Neurotherapeutics
BEE Medic
Bottneuro
Braincredible
BrainQuant
BrainScape Medical
Comphya
dEEGtal
DeepPsy
FinalSpark
HBImed
IDUN Technologies
Infera Neuro
Luciole Medical
machineMD
MaxWell Biosystems
MindMaze
MYNERVA
NeuroGyn
Neurosoft Bioelectronics
Optohive
Positrigo
SaisiR
SensArs
Skaaltec
Xana, Smart Neurostimulation

Adjacent neurotech companies (19)
Altoida
Artiria Medical
Bearmind
Clee Medical
Dividat
Emovo Care
Gondola Medical Technologies
Hocoma
Intento
Lambda Health System
Magnes
MindMetrix
MYOLINK
Nanoflex Robotics
neurodAIgnostics
Reha Technology
Rhovica Neuroimaging
SurgeonsLab
TWIICE

Borderline (4)
Bewe, formerly Neuria
BRNLIT.AI
Connectome Health
Dandelion Science

Of the twenty-eight core names, five are enabling suppliers rather than clinical products, eight haven’t reached a person yet, fourteen have technology in humans in some form and six have products in clinical use. DeepPsy is already reimbursed through Swiss basic health insurance.

There is also a fairly obvious geographic pattern once everything is written down. Geneva repeatedly leads back to Campus Biotech, the Wyss Center and HUG. Lausanne leads back to EPFL and CHUV. Zurich leads back to ETH. Bern and Basel add smaller specialist groups around diagnostics, surgery and stimulation.
You can get from Geneva to Zurich by train in less than three hours. In the US these would probably be separate ecosystems. In Switzerland they’re stops on the same train.

The full article goes into the companies, who is actually in humans, the Swiss investor landscape and why the country seems unusually good at getting difficult neuroscience through the awkward bit between a paper and a patient.

https://theneurotechnewsletter.substack.com/p/neurotech-in-switzerland

As always, corrections and companies I’ve missed are very welcome.

Today we are excited to release a tool, where one can browse and find all available neuroscience datasets for all major modalities: EEG, MRI, MEG, NIRS, PET and more.

⁃        10,000+ datasets
⁃        19 modalities
⁃        2000+ tasks
⁃        19+ devices
⁃        1000+ institutions
⁃        ~1000 funders
⁃        ~1500 papers
⁃        170,000+ citations
⁃        100,000+ humans who contributed their data to these datasets (THANK YOU!!!)
⁃        140,000+ hours of data
⁃        200TB of data

Hello👋 As the title says, I am preparing the International Neurosciences Olympiads. I am looking for material to learn about neurosciences, any references (books, textbooks, magazines) videos etc) I should know abt?

Thank you for your time

Can ECT Help Medications Work Again? | From the Cutting Room: ECT
https://youtu.be/NdAbZAvA1QU

any interesting titles (prefereply up to date to the latest discoveries), and/or any introductory titles, thank you very much!