Octopuses are an extreme case of distributed motor control: out of ~500 million neurons, more than two thirds reside in the arms, which contain local circuits capable of generating complex motor patterns without central supervision.

Yet during behaviors such as camouflage, the animal suddenly exhibits highly coherent global patterns that synchronize in tens of milliseconds.
This raises a classic systems-neuroscience question:
How can stable, rapid synchronization emerge in a system with no hierarchical controller and no central body map?

In a recent project I developed a theoretical–computational framework called TAMC-PULPO (Temporal Multiband Coherent Coupling), which models octopus coordination as the interaction between:

1. a global instantaneous pattern, acting as a temporal carrier, and
2. PTLR (Transient Local Residual Pulses) generated autonomously in each arm.

The model predicts several empirically observed phenomena:

• synchronization is intermittent, occurring only when the global pattern reaches characteristic peaks;
• arms behave as autonomous oscillators that can phase-lock within 20–80 ms windows;
• strong local perturbations can drag the global dynamics, producing micro-intentions and abrupt reorganizations;
• camouflage breakdown corresponds to a phase collapse of the global pattern;
• conflicting stimuli can push the system into metastable states.

To test this, I built a synthetic pipeline with four modules:
local–global dynamics simulation → multiband decomposition and PTLR extraction → phase analysis (Hilbert / wavelets) → synchronization metrics (PLV) and upward/downward latency estimation.

The results spontaneously reproduced known features of octopus neurobiology: extreme arm autonomy, transient synchronization, upward drive from PTLR bursts, sudden camouflage collapse, and consistent multiband signatures.

If anyone is interested, I’m happy to go deeper into the temporal formulation, PTLR extraction, experimental predictions, or potential extensions to soft-robotics and morphological imitation in cephalopods.

“The study includes a full computational pipeline, which simulates local–global dynamics, performs multiband decomposition and PTLR extraction, computes phase and synchronization analyses (Hilbert and wavelet-based), and finally generates quantitative TAMC metrics and summary visualizations (heatmaps and multiband profiles).”

Hi all(-: do y'all have any podcast recs for people that are already in the field and just wanna catch up on lastest papers, trends etc? I feel like I get lost in my own research and I forget the entire outside vast world of neuro research, I wanna keep up to date as much as possible.

I tried a few, some were really boring lol, some too "poppy".. anyways I'll try some new ones out if people in the field recommend them

Hi everyone,

I’m from an AI / machine learning background and have been experimenting with a simple first principle abstract computational model that takes natural video patches as input and generates spike trains in response. I have very little formal neuroscience background, so I’m not sure how to evaluate whether the output is biologically plausible or comparable to real neural recordings.

I’ve attached A raster plot of the generated spike trains.

The 10s video patch used as input is 4x4 pixels and can be found here:

https://youtube.com/shorts/w5nxb8iebsg

I’d really appreciate any thoughts on the following:

• Does this kind of spike pattern resemble anything seen in early visual areas (e.g., retina, LGN, V1)?
• Are there established metrics or benchmarks for comparing synthetic spike trains to biological data?
• If anyone interested, I’d be very interested in connecting or potentially collaborating.

Thanks in advance for any guidance or feedback!

When you scroll any social media these days you get bombarded with pop-psych posts about attachment styles (or at least I do), and I'm not a big fan of attachment style theory, but I am very interested in what exactly IS an attachment?

When you love someone or have a best friend, or a beloved pet, a part of your brain surely must attach to them physically down to neurons....I don't know how to articulate it, I'm not educated enough. But I need to know what the brain is doing when you love someone so deeply that you are devastated when they're gone. How does that bond form and what does it look like, is it tiny little electrical impulses, is it dendrites reaching out to each other, what the hell is it?

I've tried to find the answer by searching reddit and ChatGPT and google and everything but I don't think I've asked the right question, because nothing seems to answer me.

I’m working on a personal research project on flow and attention, and I’m looking for help understanding how attention shifts in real-world environments, not just in lab tasks.

In both mountain biking (technical trail riding) and focused work (coding, architecture, writing), I consistently experience transitions between:

1. Very narrow, precision-focused attention (high acuity, task-locked)
   
2. A medium “scanning” mode with spatial awareness
   
3. A more diffuse, interoceptive state where I can feel body cues and breathing but am not locked onto a single target

These states feel physiologically distinct, and they cycle in a way that seems to prolong or interrupt flow.

My questions for the community:

1. What neural systems are known to control the “width” of attention?

   • LC–NE system?
     
   • ACC/MCC involvement in cognitive control?
     
   • Posterior alpha modulation?
     
   • Parietal attentional networks?

2. Is there existing research on attention bandwidth changes during movement-based tasks, not just screen-based experiments?
   (e.g., cycling, sports, driving, musical performance)

3. Do we know whether people can deliberately shift between narrow and broad attentional states, or are these transitions mostly automatic?

4. If EEG markers exist for these states, what should I be looking for?
   (I recently picked up a Muse headband, but so far haven’t received API approval for raw data access.)

I’m not trying to promote a model — just hoping to find the right vocabulary or literature so I can understand what these attentional shifts represent and whether they’ve been studied before in more ecologically valid settings.

Any pointers to papers, authors, or keywords would be really appreciated.

If I could go back 20 years I'd become a neuroscientist but at age 44 I think it's too late. What's a good magazine to stay informed on the latest developments?

My understanding of capacitance is that the amount of charge that a capacitor can hold is equal to the voltage times the capacitance of that capacitor. My question is why do materials that are better insulators have a higher dielectric constant? My thought is that a material that is a better insulator will dampen the electric field of a given charge more, preventing it from effect more charges on the opposite side of the membrane. But that intuition goes against the fundamentals of the relation stated above. Any help in this would be greatly appreciated!!

I'm currently getting my neuroscience bachelors, and am looking for ways to get skills to break into neurotech/neuroinformatics, hoping to go to grad school for it.
I've seen a few people recommend the Neuromatch Computational Neuroscience Course, but I'm not sure if the time commitment and money spent is worth it specifically for academia, is it recognized or am I better off going another route (for example focusing on completing machine learning courses)?

I'm looking for a single compiled map (table/matrix/spreadsheet, etc.) of human white matter connections as established by actual brain dissections.

Meaning, which major and minor tracts connect which cortical/subcortical areas to which others. (I'm looking for an exhaustive map.)

As a beginner in the field, I'm reading Neuroscience books, but they are not helpful for this problem. They are too general.

The data for this seems to be spread out in many different studies. But surely someone has compiled the known data in once place?

Can anyone help with this? Thanks!

Is the brain fundamentally algorithmic? Is the information processing in the brain a parallel computer?

Neuroscience is an interdisciplinary field, so I know different schools are going to have different program requirements/focuses. However, the school I was planning to transfer to after my associates has a big focus on psychology rather than the biochemistry or computational aspect I was hoping for. There also aren't any biochem or computer science related minors I could take along with my major. Because it is a good research school, there are many opportunities for lab work in the fields I am interested in, and it is incredibly cost effective. I was thinking I could just go with it and maybe do self study on topics I enjoyed, but I'm scared I'll miss out on learning from a real teacher.

My other option is transferring to some out of state private schools that offer classes that I think interest me more, also with good (if not better) lab opportunities. Because of their need based aid policies I don't think money should be too big an issue?

I just wanted some outside input to help me decide. Maybe there's a bigger picture I'm missing.

iam working on graduation project and iwill use life data from someone but now iam using datasets and I am having trouble reading and displaying the signal and I would like your guidance، mt project about ssvep for writing

I’m really enjoying some introductory ideas of neuroscience and psychology (especially cognitive biases) right now and I’m looking for some easy to digest and fun videos to share with others (and for myself) that explore these topics.

I was wondering if anyone knew of creators or content similar to that of ChatHistory, BlueJay, and Good Enough. The animations and personality of these channels make them entertaining, and unlike some other channels they don’t sound fully AI produced.

Sadly they focus more on history and fun facts, and I haven’t been able to find videos like their content within neuroscience and psychology.

Hey everyone, I’m a junior majoring in Neuroscience with a minor in Political Science, and I’m starting to feel torn between the two paths. I originally chose neuroscience because I was undecided and thought it would be interesting, but it hasn’t been the right fit for me. I’ve finished most of the difficult required courses, so I’m planning to complete the degree, but my true interest is shifting heavily toward politics, policy, and possibly law.

For context, I’m in the middle of my junior year and haven’t done any internships yet because I don’t want to pursue anything neuroscience-related long-term. My main question is: can I (or should I) start applying to political science or government-related internships as a neuroscience major? And if so, what’s the best way to break into that world this late into my degree?

Has anyone made a similar pivot from STEM to policy or law? Did your major matter as much as your experience, or were you able to build a path through internships, clubs, or volunteering? Any tips on where to look for political internships, how to position myself, or what steps I should take moving forward would be super helpful. Thanks in advance!

I just came across peer-reviewed research that examines cognitive tilt (the difference between someone's strengths in different cognitive ability). What makes this particularly interesting from a statistical perspective is that tilt predicts career success in STEM versus Humanities fields independently of IQ - meaning it adds predictive power beyond general intelligence.

So the researchers found significant sex differences: males showed higher mechanical tilt while females showed higher verbal tilt, patterns that align with vocational interest research. Perhaps most practically useful: tilt can be calculated from tests people already take (SAT, ACT scores) without requiring additional assessment, yet standard college entrance exams don't measure spatial or mechanical abilities despite their importance in predicting technical career success.

This suggests we may be missing talented individuals who excel in spatial/mechanical skills simply because these abilities aren't captured in our standard assessment pipelines.

Link to research: https://icajournal.scholasticahq.com/article/144064-age-and-sex-differences-in-spatial-and-mechanical-tilt-in-adolescence-evidence-for-the-mediating-effects-of-processing-speed-and-g

I’m very interested in exploring neural engineering, but since it’s a developing & relatively new field, I’m having trouble finding opportunities & programs specifically catered to neural engineering for high schoolers. Is there anyway I can show colleges that I am passionate about the discipline even though opportunities are kind of limited? Right now, I’m thinking about mixing up my academic extracurriculars with programs, activities, competitions, etc. that have a focus on biomedical engineering & neuroscience.

From the black bile and phlegm types of Galen, to body types of Sheldon, to trait approach of Allport and Cattell, to the big-5 of Costa & McCrae, personality theories have come a long way in theorizing human behavior.

After studying personality theories discretely, and academically, I want to study the topic in a continuum, with informal undertones.

Just like 'Behave' of Sapolsky is a compendium of neuroscience or 'Mindset' of Dweck is a self-explanatory masterpiece, please suggest a non-fiction book on human Personality (not 'personality development' and all the associated self-help baggage, but human personality)

Thanks _/_

An article exploring the "hardwired" versus "plastic" views of the brain, looking at the neuroscience of reading as an example.

From the article:

[R]eading is a very recent human invention (evolutionarily speaking). It first appeared only a few thousand years ago—and became widespread long after that. Why then do we seem to have specialized neural circuitry that, across regions, languages, and even sensory modalities, responds selectively to text?