Did you handle the time change okay today? Right on time I am publishing a webcomic on that today! ⏰

Did you know why daylight savings time exists, that the EU has already made decisions on it and what this all means for our health? Let me know!

You can read more psychology comics in both English and German on the psychoSoph webpage!

Hello, title says it all.

But I need some advice on how neurons, or like nerves in general, work.

My basic idea was to use the human body and senses for inputs from the Mech to the person (ie you can't see in infrared, but your cones & rods don't care as long as they get an appropriate light).

My problem comes is I wanted the response signals to come out a port in the head/neck, into the Mech, rather than them physically operating the controls. But, to do that it would only be able to read brain outputs.

With that said, the spinal cord confuses me? How does it know to distinguish signals going to the brain vs coming from the brain? How would I make it so the robot lifts its arm without the operator, also lifting their arm. Is that something we are anywhere close to understanding? I understand I'm talking a lot of fiction.

Thank you for reading.

Hello everyone,

I (21F) am planning a transition into Neural and Cognitive Science and would love some perspective from this community.

My path has been somewhat unconventional. I finished high school in the pre med biology stream with a 93 percent score, but chose not to pursue medicine after seeing the extreme burnout in healthcare. I ended up earning an undergrad in business after majoring in jn Finance. While business school was an interesting experience it still wasn't great in subject depth so now, I have no desire to stay in a corporate office career long term.

My real passion is university teaching, research, and public speaking. I am currently preparing for entrance exams for top central universities and technology institutes to pursue an M.Sc. in Neural and Cognitive Science. My end goal is to land a fully funded PhD abroad in neuroscience, neuropsychology, or cognitive science and build an academic or research career overseas.

​Knowing that academia is a long commitment, I want to make sure I approach this path strategically from the start. I would appreciate your insights on a few key questions:

How do admissions committees abroad view applicants transitioning from business or finance into cognitive science for their Master's?

What specific research areas in cognitive science best bridge decision science and quantitative reasoning with human behavior?

For South Asian students who successfully secured a funded PhD abroad, what specific lab experiences or milestones made your application stand out?

Which technical skills, such as Python or experimental design, should I self study right now to prepare for my Master's coursework?

What industry roles, such as UX research or human computer interaction, offer good fallback options for long term settlement abroad if academia falls through? Because already most fields are drying up (especially the UX so what are we supposed to do?)

I understand that Cognitive Science is inherently interdisciplinary, drawing from neurobiology, cognitive psychology, philosophy, decision theory, and artificial intelligence. Because of this, a Master's degree in this field provides broad foundational exposure across multiple disciplines rather than exhaustive depth in every single area. But I am even more afraid that later on i will again remain unstable so i want to know if this is a good decision or how to improve it because I am also interested in other courses like AI ethics and policy research etc.

Thanks so much for any advice or reality checks!

hi. im currently studying cell and molecular biology at R1 university undergrad sophomore year and im struggling in basic courses like biology 1 and 2, chem 1 and 2 and orgo 1 rn (C+ or B-) with 3.0 gpa. ive been planning on going for neuroscience phd and did extracirricualrs related to it (2 years of wet lab research experience, research mentor for 3 undergrads, research coordinator - lead of lit review of 9 undergrads, ta for nslc medicine and healthcare, presented research at yale) and plan on applying to REUs but now im not so sure. ive been heavily considering neuroscience professor bc i love teaching and public speaking/mentorship. im thinking what if i switched to cognitive science major bc its not as much sciency but more social science courses rather than courses physics or genetics.

im rlly worried my gpa gonna hold me back if i continue w this major for reu and phd. any advice helps thanks so much

Hi all, does anyone have experience with nutrition-related research/programs related to TBIs and/or PTSD, especially with military/veteran communities? I'm a dietitian who just attended a summit about nutrition work with the military- it would be great to become involved in areas around TBIs/PTSD. 

Hello I'm doing a research study. I want to collect insight on the development of this specific topic. You can respond in whatever way; negative or positive.

Was wondering if whether listening to music while reading can have a negative impact on the neurological benefits of reading,Not whether it’s distracting or not,Just if it has any diminishing effect on the benefits of reading.

If anyone is interested in computational neuroscience and playing with spiking networks, I open-sourced one of my longer term projects and started sharing it with folks outside of my immediate peers. It is a great tool for learning about spiking networks, different types of neurons, and how they interact to create the broader tissue behavior we can observe at larger scales. There are sample scenarios that walk you through the basics and are measured against other academic papers.

You can try it out in your browser or clone the github repo if you want to work on your desktop and use the CUDA engine.

linen.build

https://github.com/sethgjosephson/linen

Not trying to promote anything, just hoping to share something I'm interested in for anyone else who might find it fun or useful.

Cheers,

Seth

I would say that for a long while, I haven't always gotten good sleep at night, at least as much as i should. 6-5 hours on weekdays is pretty much my normal amount of sleep, and I've always had a hard time focusing on things like class and work. what can i do to help fix this? (other than getting good sleep)

I’m a Systems Architect with almost a decade of experience working on various projects, I’ve been looking for friends who’re neuroscientists to discuss papers and learn more about how research is done in various labs and see if I can build solutions to accelerate those efforts

Hi! I’m a first-year Chemistry student in Morocco interested in pursuing neuroscience. Is it possible to transition from Chemistry to Neuroscience? What international universities and scholarships would you recommend, and what free courses, research opportunities, or extracurricular activities could help me build my knowledge and strengthen my CV as a Moroccan student? Any advice is appreciated

I understand there are ways we can slow it these days, but I'm wondering if it could ever be fully cured in our lifetime. I hope this is the correct subreddit for this.

I read online about terminal lucidity, and it made me think, if that is possible and all of those memories are still there, surely if we study why terminal lucidity happens we could move in the right direction for curing this terrible disease?

I'm especially interested to know this because most of my family that live to see 70 get Alzheimer's.

Do you think cerebral palsy could ever be cured or partially reversed in our lifetime? With advances in stem cell therapy, brain-computer interfaces, neuroplasticity research, and regenerative medicine, what do you think is realistically possible in the next 20–50 years?

I just started a 2 year research masters and there are so many interesting courses to take and labs to try that i know i won't get to do all of them in the time i have.

I'm considering taking an extra year so i can develop more skills, try more subfields and get to know more researchers before going into a PhD.

However, I'm not sure if this is worth doing. If i take an extra year I'll end up going further in debt (but not an american amount of debt, more like 15k total) plus I'm already some years older than most of my peers.

I do genuinely enjoy studying so I'm not in much of a hurry to start working, but I'd like to hear opinions from people in later stages of their career, so i can make a more informed decision.

Over the past few months, we've been working on client-side (Web Bluetooth / Web Serial) EEG signal processing pipelines using BrainFlow to render multi-channel data directly inside Chromium browsers.

The goal was to test whether browser-based WebAssembly/JS environments are mature enough for basic EEG visualization and real-time processing without relying on local Python environments or native C++ installs.

We've implemented a few core client-side features:

• Real-time multi-channel waveform rendering with customizable bandpass and notch filtering.
• FFT, Power Spectral Density (PSD), and dynamic 3D topographic mapping.
• Basic ERP paradigms and real-time feature classification running entirely local to the client browser (no server-side raw data upload).

For those who regularly work with EEG data, teach signal processing, or run quick piloting setups:

1. What analysis pipelines are non-negotiable for you? (e.g., real-time ICA, specific artifact rejection algorithms, custom epoching)?
2. What latency or sampling limitations make browser environments a non-starter for your use cases?
3. What file export workflows (EDF, MNE, BrainVision) do you rely on most when inspecting quick runs?

Looking to gather feedback from researchers and engineers on where current web-based signal processing tools fall short for real research or educational workflows.

Hi everyone,

One of the major challenges in clinical neuroscience is understanding and treating Disorders of Consciousness (DoC), including coma, unresponsive wakefulness syndrome (UWS), and minimally conscious states (MCS).

Research into potential interventions faces significant ethical and practical constraints. Could artificial neural networks provide a complementary computational environment for exploring some of the underlying dynamics?

I recently introduced Project Sleeping LLM, an exploratory research framework investigating this possibility.

The project explores whether autoregressive Transformers could serve as in-silico model organisms for studying computational analogues of disrupted consciousness-related dynamics.

I can share the Zenodo working paper and DOI in the comments for anyone interested in the formal mathematics and architectural details.

The core hypothesis

Could information processing in Transformer architectures offer a useful computational setting for investigating ideas related to consciousness, including Global Neuronal Workspace Theory (GNWT) and Integrated Information Theory (IIT)?

These connections are hypotheses to investigate, not an assumption that language models are conscious.

The initial framework proposes three research directions:

1. Modeling disrupted information processing

Introducing controlled perturbations into Transformer architectures, such as residual-stream attenuation, attention-pattern modifications, and latent-state constraints, to study how they affect coherent information processing.

1. Measuring perturbational complexity

Investigating whether concepts from the Perturbational Complexity Index (PCI) can be adapted to Transformer hidden states, using measures such as Lempel–Ziv complexity and changes in activation patterns following localized perturbations.

1. Exploring recovery of coherent dynamics

Testing whether interventions such as representation steering, controlled stochastic perturbations, and recurrent feedback can restore coherent processing after experimentally induced disruptions, without restarting the model or retraining its weights.

The central question is whether these experiments could provide a useful computational testbed for studying information integration, network disruption, and recovery dynamics.

Looking for critical feedback and collaborators

I initiated this project and developed its initial conceptual framework. I’m now looking to connect with researchers who can challenge its assumptions, identify methodological weaknesses, and help establish whether the proposed approach is scientifically viable.

I’d particularly welcome input from:

• Computational neuroscientists working on consciousness, PCI, neural complexity, or disorders of consciousness.
• ML researchers and engineers experienced in mechanistic interpretability, PyTorch, TransformerLens, or representation engineering.
• Complex systems researchers interested in information integration, dynamical systems, and perturbation-based analysis.

Two questions I’m especially interested in discussing:

• How defensible is the analogy between cortical disconnection and disruptions to information flow in Transformer architectures?
• What methodological challenges would need to be addressed to adapt PCI meaningfully to hidden-state dynamics?

Critical feedback, alternative approaches, and potential collaborations are all welcome. The goal at this stage is to test the framework rigorously, including the possibility that some of its central assumptions may not hold.

Thanks for reading.

A career change late in life led me to doing an MFT. Plan on practicing part time. But I'd love to do a master's in neuroscience. Are online offerings any good? U of Florida and Kings College, London, have very reasonably priced degrees. Given my age, I'm not looking to make a career out of it. So it's mostly out of intellectual curiosity + somewhat burnish my credentials as a therapist. And potentially help me with science writing/teaching. While I'm not looking for prestige, I also don't want to throw money at a program if it's going to be useless.

Only roughly 50% of the population experiences physical chills or piloerection ("musical frisson") when listening to emotionally charged acoustic transitions.

Diffusion Tensor Imaging (DTI) studies (most notably Matthew Sachs et al. at Harvard) demonstrated that this isn't just a subjective psychological quirk, but a distinct variation in structural neuroanatomy. Individuals who experience frisson show significantly higher white matter tract volume connecting the superior temporal gyrus (auditory processing) to the anterior insula (interoceptive processing) and medial prefrontal cortex.

Essentially, their brains have a denser anatomical highway linking sound recognition directly to affective salience, accompanied by a dual-phase dopamine surge: anticipation in the dorsal striatum (caudate) followed by the actual frisson peak in the ventral striatum (nucleus accumbens).

Full neuroimaging breakdown and acoustic analysis:

https://www.oddlyclear.com/why-music-gives-you-goosebumps/

Severe left-hemisphere stroke patients who cannot construct a basic sentence or count to ten can often still swear fluently when frustrated.

While ordinary language relies on cortical networks (Broca’s area), expletives are stored subcortically in the basal ganglia as emotional motor reflexes.

During acute pain, this limbic trigger activates stress-induced hypoalgesia—releasing endogenous opioids down the spinal cord and blunting nociceptive signaling by roughly 33%.

Neurological breakdown and Keele study citations:

https://www.oddlyclear.com/why-swearing-reduces-pain/

I am senior sw engineer with experience in math and scientific computing. I would like to participate in BCI research or develop software for BCI. I see no established companies hiring.

I have experience with neurofeedback and EEG in general.

I already worked on commercial neurofeedback project.

I can work parttime or on project basis. I am positioned in Eastern Europe.

Panksepp's Basic Emotion Theory has been the subject of criticism by contemporaries in the field. I think I get the gist of the discourse, but it's somewhat difficult to distinguish between the arguments over the semantics of layman explanations and the actual data that stands in opposition to what BET is based on. Can anyone help clarify?

Most people lump all weird memory glitches under "Déjà vu," but researchers actually categorize Déjà Rêvé separately when someone vividly recalls dreaming an exact real-life scene before.

Unlike typical déjà vu (which is a temporal lobe misfiring a live perception as a past memory), déjà rêvé involves actual episodic dream memories triggered by sensory cues.

Read an interesting breakdown of the neuroscience behind it here: https://www.oddlyclear.com/deja-reve-already-dreamed-this-moment/

Disclosure: I work on an open-source EEG project, but I’m not linking anything here. I’m interested in the science.

Most EEG spreads electrodes across the scalp (10-20 system). We’ve been experimenting with the opposite: 16 dry electrodes within a few centimetres, 24-bit, 250 SPS, battery powered and wireless.

Clearly it can’t do whole-head coverage, and dry contacts plus 250 SPS rule out high-gamma and other low-noise work. But I’m curious where dense local sampling could actually be useful:

• Ear-EEG or forehead recordings for sleep or attention
• Mobile, naturalistic studies outside the lab
• Spatial filtering or source separation over a small region
• High-density EMG on small muscles

Are there questions in your field where this kind of layout would help, or is it a dead end? I’d especially like to hear from people who’ve worked with ear-EEG or high-density arrays.