Tootfinder

"Schrimpf and his colleagues trained a model to generate sentences that, when read, would activate or suppress neural activity in the reader’s brain," exerting "noninvasive control over high-level brain activity" https://www.quantamagazine.org…

How AI Models Are Helping to Understand — and Control — the Brain | Quanta Magazine
Martin Schrimpf is crafting bespoke AI models that can induce control over high-level brain activity.

An MIT study of 54 ChatGPT users: using it for SAT essays led to the lowest brain engagement and poorer neural performance than using Google or writing unaided (Andrew R. Chow/Time)
https://time.com/7295195/ai-chatgpt-google-learning-school/

ChatGPT May Be Eroding Critical Thinking Skills, According to a New MIT Study
The study, from MIT Lab scholars, measured the brain activity of subjects writing SAT essays with and without ChatGPT.

Happy #AutisticPrideDay! ♾️💙
I’m proudly autistic, my brain works in its own unique way, full of different thoughts and feelings all at once. Being autistic is part of who I am, not something to fix. 🧠🧠
I’m also queer and genderfluid, and that’s just another part of my colorful identity. Some days I feel one way, some days another, and that’s okay. 🏳️‍🌈☂️
Neurodiver…

Watching the 1967 movie "Billion Dollar Brain" and totally distracted by the fact that Harry Palmer's seedy office is, I think, roughly the location of my office desk.
https://www.imdb.com/title/tt0061405/mediaviewer/rm2192045569/

Billion Dollar Brain (1967)
Michael Caine in Billion Dollar Brain (1967)

New study on the effects of LLM use (in this case on essay writing):
https://arxiv.org/abs/2506.08872
Quote:
"LLM users also struggled to accurately quote their own work. While LLMs offer immediate convenience, our findings highlight potential cognitive costs. Over four month…

Your Brain on ChatGPT: Accumulation of Cognitive Debt when Using an AI Assistant for Essay Writing Task
This study explores the neural and behavioral consequences of LLM-assisted essay writing. Participants were divided into three groups: LLM, Search Engine, and Brain-only (no tools). Each completed three sessions under the same condition. In a fourth session, LLM users were reassigned to Brain-only group (LLM-to-Brain), and Brain-only users were reassigned to LLM condition (Brain-to-LLM). A total of 54 participants took part in Sessions 1-3, with 18 completing session 4. We used electroencephalo…

Disruption of parkinsonian brain oscillations
C\'edric Join, Jakub Or{\l}owski, Antoine Chaillet, Madeleine Lowery, Hugues Mounier, Michel Fliess
https://arxiv.org/abs/2506.15384

Disruption of parkinsonian brain oscillations
Deep brain stimulation (DBS) is an advanced surgical treatment for the symptoms of Parkinson's disease (PD), involving electrical stimulation of neurons within the basal ganglia region of the brain. DBS is traditionally delivered in an open-loop manner using fixed stimulation parameters, which may lead to suboptimal results. In an effort to overcome these limitations, closed loop DBS, using pathological subthalamic beta (13--30 Hz) activity as a feedback signal, offers the potential to adapt DB…

„While LLMs offer immediate convenience, our findings highlight potential cognitive costs. Over four months, #LLM users consistently underperformed at neural, linguistic, and behavioral levels.“ #AI

Wissenschaftler:innen haben herausgefunden: Wer ChatGPT oder andere Bullshit-Generatoren nutzt, verblödet innerhalb kurzer Zeit.
#LLM

"Your Brain on ChatGPT: Accumulation of Cognitive Debt when Using an AI Assistant for Essay Writing Task"
https://doi.org/10.48550/arXiv.2506.08872
"[…] While LLMs offer immediate convenience, our findings highlight potential cognitive costs. Over four mont…

#Wordle 1,460 4/6*
⬜⬜⬜⬜⬜ <1% of 218,228 (881)
⬜⬜⬜⬜⬜ 0 of 2 (151)
⬜⬜🟨🟩🟩 0 of 0 (3)
🟩🟩🟩🟩🟩
WordleBot
Skill 85/99
Luck 41/99
Wow one of my most brain off days ever!
Liked the word and entered it before really thinking and it had a double letter, AND THEN my 2nd word reused a letter from the first word. Yikes, I really better double check things the rest of today!
1st word had a skill score of 71, and 2nd word's skill was 64.

I read "Then I Am Myself the World: What Consciousness Is and How to Expand It" by Christof Koch.
Interesting book which spends like 8 or 9 chapters detailing all the experiments which prove beyond much doubt that consciousness, and self awareness, is a thing done by a brain.
It describes how perception is a construction of a description, has a chapter called "computational mind"
And then spends the last two chapters describing why he thinks the mind can't be computed, because drugs have made him think experience is some kind of magic associated with highly interconnected causal structures.
Apparently, he thinks, once things become interconnected enough they become able to cause things independently of the physics running those connections.
Which is crazy, obviously. There's nothing causal in direct connections between neurons that isn't equally causal in modeled connections between virtual neurons.
All his evidence in the book from neural MRI scans to the effects of psychedelic drugs and symptoms of strokes and disease point to the brain simulating a virtual reality which is the basis of perception.
That simulated world in which we live is full of colour and shape and sounds and emotions and millions of mental constructs that are built to be correlated by the senses with the outside world, but are not equal to the world itself. We live in a dream constructed to correlate with reality.
But then instead of taking the next step: That consciousness itself is a property of a simulated being inside that mental model of the universe, a property which the brain simulates and applies to the virtual self that's doing the experiencing inside that model, he jumps towards some magic implying pan-psychism or that sufficiently interconnected networks become causally self-complete for some reason nobody can fathom.
Sure, colour and shape and emotions are all made up by the brain but experience can't be! For some reason.
You see in truth dualism is false, in that there is no spirit realm in which ghosts animate the matter of the body somehow.
Yet also, dualism is true, in that there is a simulated mental reality which we live in, computed by the brain in which all perception and experience are created, which is related-to but separate-from the unfolding complicated dance of energy that is the universe our bodies interact with.
People take some DMT trip, and the model of the universe emulated by their brain collapses and breaks. Their virtual simulated self inside their mind has these experiences of being one with the universe or the experience of feeling dead yet conscious or whatever, and these hippies think that the broken down simulated experience is real and reflects how consciousness is more fundamental than the atoms that make up the neurons in their brain.
Instead of realizing it shows them that their experienced universe is a simulacrum, they think they get a more direct experience of reality somehow. A consciousness more pure than any mere base atom.
"Then I am myself the world" is a great title. Everything you ever experience is created and simulated in your brain like a dream, the whole universe is inside your head. Even the fact of experience itself.
But that isn't the conclusion Koch reaches somehow, he just jumps from describing the evidence that this is so straight into ascribing super-causal magic consciousness to particular arrangements of atoms that integrated information theory suggest have high correlation, and thinks therefore conciousness is itself the entire universe.
Ah well, fun book. I like arguing in my head with authors that are wrong.
#reading #books #consciousness #thenIAmMyselfTheWorld

BraTS orchestrator : Democratizing and Disseminating state-of-the-art brain tumor image analysis
Florian Kofler, Marcel Rosier, Mehdi Astaraki, Ujjwal Baid, Hendrik M\"oller, Josef A. Buchner, Felix Steinbauer, Eva Oswald, Ezequiel de la Rosa, Ivan Ezhov, Constantin von See, Jan Kirschke, Anton Schmick, Sarthak Pati, Akis Linardos, Carla Pitarch, Sanyukta Adap, Jeffrey Rudie, Maria Correia de Verdier, Rachit Saluja, Evan Calabrese, Dominic LaBella, Mariam Aboian, Ahmed W. Moawad, …

BraTS orchestrator : Democratizing and Disseminating state-of-the-art brain tumor image analysis
The Brain Tumor Segmentation (BraTS) cluster of challenges has significantly advanced brain tumor image analysis by providing large, curated datasets and addressing clinically relevant tasks. However, despite its success and popularity, algorithms and models developed through BraTS have seen limited adoption in both scientific and clinical communities. To accelerate their dissemination, we introduce BraTS orchestrator, an open-source Python package that provides seamless access to state-of-the-…

It still breaks my brain sometimes that in Krita I can simply lasso select multiple layers and transform them at the same time.
My years in Photoshop trained my brain to always think of this as impossible.

"Anyone you’re talking to has had decreased funding, or lost almost all of their funding, or is having trouble continuing their funding...
That, along with the pretty pervasive and growing anti-science establishment narrative … have been strong motivators to look elsewhere,” Eric Schuster said.
Schuster is one of many budding academics reflecting what could become a significant American brain drain,
sending the brightest minds in the country to flee the US and take their…

Things almost impossible to do without good LLM software (in one minute).
I hear a music on a radio. Google music search gives me "Robbie Williams - forbidden road". But I know the words are somewhat different and I want to know what movie I have in mind.
Gemini says it's in fact, similar song to "I got a name", then my brain clicks and connects it with Quentin Tarantino.
Bingo - it's Django.

Regulating Next-Generation Implantable Brain-Computer Interfaces: Recommendations for Ethical Development and Implementation
Renee Sirbu, Jessica Morley, Tyler Schroder, Mariarosaria Taddeo, Raghavendra Pradyumna Pothukuchi, Muhammed Ugur, Abhishek Bhattacharjee, Luciano Floridi
https://arxiv.org/abs/2506.12540

Regulating Next-Generation Implantable Brain-Computer Interfaces: Recommendations for Ethical Development and Implementation
Brain-computer interfaces offer significant therapeutic opportunities for a variety of neurophysiological and neuropsychiatric disorders and may perhaps one day lead to augmenting the cognition and decision-making of the healthy brain. However, existing regulatory frameworks designed for implantable medical devices are inadequate to address the unique ethical, legal, and social risks associated with next-generation networked brain-computer interfaces. In this article, we make nine recommendatio…

"At the end of the day - who cares what you choose. Just choose something. Stop looking at it as 'blogging' or trying to 'capture an audience'."
Great piece by @… from a few years back on the importance of brain dumps and blogging:

TikTok is absolute brain rot—a toxic, data-harvesting black hole designed to zombify your mind. This is my firm self-reminder never to sign up for that corporate cesspool.
I’d rather be on the Fediverse, where I control my data, engage in genuine conversations, and avoid the manipulative algorithms that TikTok weaponizes to steal your attention and sanity.
No thanks, TikTok. I’m choosing freedom over digital decay.

i wonder if brainrot humor worked the same way back before the internet existed. like did victorian era youth make themselves laugh by inserting vulgar slang or opium and alcohol or women dressing like men or charles darwin or edgy jack the ripper references into phrases coined within a children's author / humorist's "nonsense book" or whatever trashy pulp magazines were popular

Towards Unified Neural Decoding with Brain Functional Network Modeling
Di Wu, Linghao Bu, Yifei Jia, Lu Cao, Siyuan Li, Siyu Chen, Yueqian Zhou, Sheng Fan, Wenjie Ren, Dengchang Wu, Kang Wang, Yue Zhang, Yuehui Ma, Jie Yang, Mohamad Sawan
https://arxiv.org/abs/2506.12055

Towards Unified Neural Decoding with Brain Functional Network Modeling
Recent achievements in implantable brain-computer interfaces (iBCIs) have demonstrated the potential to decode cognitive and motor behaviors with intracranial brain recordings; however, individual physiological and electrode implantation heterogeneities have constrained current approaches to neural decoding within single individuals, rendering interindividual neural decoding elusive. Here, we present Multi-individual Brain Region-Aggregated Network (MIBRAIN), a neural decoding framework that co…

Hierarchical Deep Feature Fusion and Ensemble Learning for Enhanced Brain Tumor MRI Classification
Zahid Ullah, Jihie Kim
https://arxiv.org/abs/2506.12363 …

Hierarchical Deep Feature Fusion and Ensemble Learning for Enhanced Brain Tumor MRI Classification
Accurate brain tumor classification is crucial in medical imaging to ensure reliable diagnosis and effective treatment planning. This study introduces a novel double ensembling framework that synergistically combines pre-trained deep learning (DL) models for feature extraction with optimized machine learning (ML) classifiers for robust classification. The framework incorporates comprehensive preprocessing and data augmentation of brain magnetic resonance images (MRI), followed by deep feature e…

Inhibiting Alzheimer's Disease by Targeting Aggregation of Beta-Amyloid
Ananya Joshi, George Khoury, Christodoulas Floudas
https://arxiv.org/abs/2506.14052

Inhibiting Alzheimer's Disease by Targeting Aggregation of Beta-Amyloid
Alzheimer's disease is characterized by dangerous amyloid plaques formed by deposits of the protein Beta-Amyloid aggregates in the brain. The specific amino acid sequence that is responsible for the aggregates of Beta-Amyloid is lys-leu-val-phe-phe (KLVFF). KLVFF aggregation inhibitors, which we design in this paper, prevent KLVFF from binding with itself to form oligomers or fibrils (and eventually plaques) that cause neuronal death. Our binder-blocker peptides are designed such that, on one s…

The phenomenological renormalization group in neuronal models near criticality
Kaio F. R. Nascimento, Daniel M. Castro, Gustavo G. Cambrainha, Mauro Copelli
https://arxiv.org/abs/2506.14053

The phenomenological renormalization group in neuronal models near criticality
The phenomenological renormalization group (PRG) has been applied to the study of scaleinvariant phenomena in neuronal data, providing evidence for critical phenomena in the brain. However, it remains unclear how reliably these observed signatures indicate genuine critical behavior, as it is not well established how close to criticality a system must be for them to emerge. Here, we rely on neuronal models with known critical points to investigate under which conditions the PRG procedure yields …

Since halving my #sertraline dose, down to 50mg / day, my brain feels like it’s halved in processing power. Words are more difficult to find, my speech is slower, my thought patterns and creativity are stifled. I’m generally more lethargic. On the plus side I’m less agitated and less prone to angry outbursts. If only I could have all of the good bits and none of the bad. That’s not really h…

fascinating episode of Neil deGrasse Tyson's #StarTalk on the gut-brain connection: #podcast #health

Brain-dead mother. Brain-damaged fetus. No hope for either. So torture their family by keeping both alive until the at-least horribly disabled baby can be delivered and then suffer for months or years with their brain damage. This is what "pro-life" means...
https://www.newsweek.co…

Abortion Law Forces Doctors to Keep Pregnant Brain Dead Woman Alive
"This decision should've been left to us," said the mother of a woman who is pregnant and has been brain dead for over 90 consecutive days.

GHz spiking neuromorphic photonic chip with in-situ training
Jinlong Xiang, Xinyuan Fang, Jie Xiao, Youlve Chen, An He, Yaotian Zhao, Zhenyu Zhao, Yikai Su, Min Gu, Xuhan Guo
https://arxiv.org/abs/2506.14272

GHz spiking neuromorphic photonic chip with in-situ training
Neuromorphic photonic computing represents a paradigm shift for next-generation machine intelligence, yet critical gaps persist in emulating the brain's event-driven, asynchronous dynamics,a fundamental barrier to unlocking its full potential. Here, we report a milestone advancement of a photonic spiking neural network (PSNN) chip, the first to achieve full-stack brain-inspired computing on a complementary metal oxide semiconductor-compatible silicon platform. The PSNN features transformative i…

Let's play POLO: Integrating the probability of lesion origin into proton treatment plan optimization for low-grade glioma patients
Tim Ortkamp, Habiba Sallem, Semi Harrabi, Martin Frank, Oliver J\"akel, Julia Bauer, Niklas Wahl
https://arxiv.org/abs/2506.13539

Let's play POLO: Integrating the probability of lesion origin into proton treatment plan optimization for low-grade glioma patients
In proton therapy of low-grade glioma (LGG) patients, contrast-enhancing brain lesions (CEBLs) on magnetic resonance imaging are considered predictive of late radiation-induced lesions. From the observation that CEBLs tend to concentrate in regions of increased dose-averaged linear energy transfer (LET) and proximal to the ventricular system, the probability of lesion origin (POLO) model has been established as a multivariate logistic regression model for the voxel-wise probability prediction o…

Replaced article(s) found for cs.NE. https://arxiv.org/list/cs.NE/new
[1/1]:
LLMs Help Alleviate the Cross-Subject Variability in Brain Signal and Language Alignment

fly_hemibrain: Fly hemibrain (2020)
A synaptic map of the hemibrain connectome of fruit fly Drosophila melanogaster. Nodes are neurons, and edges are synaptic connections, traced individually from brain image sections using EM reconstruction techniques. Neurons are labeled by their type. Edges are annotated by the connection strength between the neurons.
This network has 21739 nodes and 4259624 edges.
Tags: Biological, Connectome, Weighted, Metadata

BRISC: Annotated Dataset for Brain Tumor Segmentation and Classification with Swin-HAFNet
Amirreza Fateh, Yasin Rezvani, Sara Moayedi, Sadjad Rezvani, Fatemeh Fateh, Mansoor Fateh
https://arxiv.org/abs/2506.14318

BRISC: Annotated Dataset for Brain Tumor Segmentation and Classification with Swin-HAFNet
Accurate segmentation and classification of brain tumors from Magnetic Resonance Imaging (MRI) remain key challenges in medical image analysis, largely due to the lack of high-quality, balanced, and diverse datasets. In this work, we present a new curated MRI dataset designed specifically for brain tumor segmentation and classification tasks. The dataset comprises 6,000 contrast-enhanced T1-weighted MRI scans annotated by certified radiologists and physicians, spanning three major tumor types-g…

Meta is preparing to unveil a new artificial intelligence research lab
dedicated to pursuing “superintelligence,”
a hypothetical A.I. system that exceeds the powers of the human brain,
as the tech giant jockeys to stay competitive in the technology race,
according to four people with the knowledge of the company’s plans.
Meta has tapped Alexandr Wang, 28,
the founder and chief executive of the A.I. start-up Scale AI,
to join the new lab, the people s…

Meta Is Creating a New A.I. Lab to Pursue ‘Superintelligence’
The new lab, set to include the Scale AI founder Alexandr Wang, is part of a reorganization of Meta’s artificial intelligence efforts under Mark Zuckerberg.

Brain-wide interpolation and conditioning of gene expression in the human brain using Implicit Neural Representations
Xizheng Yu, Justin Torok, Sneha Pandya, Sourav Pal, Vikas Singh, Ashish Raj
https://arxiv.org/abs/2506.11158

Brain-wide interpolation and conditioning of gene expression in the human brain using Implicit Neural Representations
In this paper, we study the efficacy and utility of recent advances in non-local, non-linear image interpolation and extrapolation algorithms, specifically, ideas based on Implicit Neural Representations (INR), as a tool for analysis of spatial transcriptomics data. We seek to utilize the microarray gene expression data sparsely sampled in the healthy human brain, and produce fully resolved spatial maps of any given gene across the whole brain at a voxel-level resolution. To do so, we first obt…

This is the future #Republicans want for you and your children

Imagine your brain just being non-existent that you _must_ refer to an #AI slop pot to do some basic task, and even though the information that the slop pot produces is either inaccurate or flat out false... you still use it as a response regardless. #AIBollocks

Oh, boo, am I irrationally angry about genocide?
Do gently fuck off. https://autistics.life/@VulcanTourist/114659503436582815

🧠 A new tool can help predict brain-damaging seizures and free up continuous EEG machines for high-risk patients
https://medicalxpress.com/news/2025-05-tool-brain-seizures-free-eeg.html

A new tool can help predict brain-damaging seizures and free up continuous EEG machines for high-risk patients
In hospital intensive care units, neurologists often use a simple scorecard to quickly evaluate a critically ill patient's likelihood of having a brain-damaging seizure so they can prevent it. The scorecard saves lives, lowers costs and helps doctors make far more efficient use of important, expensive medical equipment.

A late addition to stroke awareness month (May).
From my article: #health #stroke

Chinese state media: researchers successfully implanted a brain-computer interface in a tetraplegia patient in March, the second country after the US to do so (Karoline Kan/Bloomberg)
https://www.bloomberg.com/news/articles/20

Towards real-time additive-free dopamine detection at $10^{-8}$ mM with hardware accelerated platform integrated on camera
Ning Li, Qizhou Wang, Zhao He, Arturo Burguete-Lopez, Fei Xiang, Andrea Fratalocchi
https://arxiv.org/abs/2506.13447

Towards real-time additive-free dopamine detection at $10^{-8}$ mM with hardware accelerated platform integrated on camera
Tracing physiological neurotransmitters such as dopamine (DA) with detection limits down to $\mathrm{1\times10^{-8}}$ mM is a critical goal in neuroscience for studying brain functions and progressing the understanding of cerebral disease. Addressing this problem requires enhancing the current state-of-the-art additive-free electrochemical workstation methods by over two orders of magnitude. In this work, we implement an ultra-sensitive, additive-free platform exploiting suitably engineered lig…

"Brain-only participants exhibited the strongest, most distributed networks; Search Engine users showed moderate engagement; and LLM users displayed the weakest connectivity."
"LLM users also struggled to accurately quote their own work."
"Over four months, LLM users consistently underperformed at neural, linguistic, and behavioral levels."

"Smart glasses offering a combination of sensory substitution based 'raw' vision and AI-based scene description and OCR appears to be technically and economically the most feasible and sustainable way toward meeting expectations, needs and interests of many blind people." https://www.artificialvision…

I know some of the money is thinking what @… says here. The trouble here is that Tesla is currently wildly, absurdly, comically overvalued wrt its fundamentals, and there are really only two rationalizations for that:
(1) Musk is a brain genius who will innovate the company into magic unicorn fairyland of world domination.
(2) Musk has Trump on a leash and will reap the benefits of kleptocratic plundering of the US Federal budget.
Both of those justifications depend on Musk remaining at Tesla. If he leaves, there’s little reason for the P/E ratio not to correct to normal car company levels — which AIUI would mean a stock price drop of >90%.
https://hachyderm.io/@zzzeek/114637505037473139

My brain's been serving up some real darkness lately.
(And when an #ActuallyAutistic brain latches onto something, it COMMITS 🙃)
So I'm reminding myself that in this world (especially at this time) ✨#Autistic Joy✨ is an act of defiant resistance.
And I'll be d…

"Climate disasters can alter kids’ brains — before they’re even born"
#Climate #ClimateChange #Health

Climate disasters can alter kids’ brains — before they’re even born
"What we are seeing is compelling evidence that the climate crisis is not just an environmental emergency, it is potentially a neurological one."

This https://arxiv.org/abs/2505.01287 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csDS_…

Shuffling Cards When You Are of Very Little Brain: Low Memory Generation of Permutations
How can we generate a permutation of the numbers $1$ through $n$ so that it is hard to guess the next element given the history so far? The twist is that the generator of the permutation (the ``Dealer") has limited memory, while the ``Guesser" has unlimited memory. With unbounded memory (actually $n$ bits suffice), the Dealer can generate a truly random permutation where $\ln n$ is the expected number of correct guesses. Our main results establish tight bounds for the relationship between the…

#Blakes7 Series D, Episode 02 - Power
VILA: No. Must be brain warp. Think I'll just go off and die somewhere. [starts to exit]
TARRANT: Vila.
VILA: What?
TARRANT: The door.
VILA: Which door?
https://

Blakes7Bot | Search
Companion site to the Blakes7Bot Twitter, Mastodon, and Bluesky accounts. Automated lines of Blakes 7 dialog. Includes a script search facility.

One of the best things about the @… meeting is the chance to connect with experts in different but related fields. Dinner this evening covered low level jets, atmospheric rivers, carbon cycling by biological processes in the southern ocean, permafrost decay and vegetation processes in the Arctic and how wildfires will spread in the future.
We are a very diverse group.
Brain full, it's time to sleep

"For more than half a century, Argentina has tried as hard as it could to push intellectuals out of the country, committing a slow institutionalized suicide. This almost imperceptible rotting process is at the root of the decadence of what was considered one of the richest and most advanced countries at the beginning of the 20th century."
Watching the US repeating this pattern in real time is unbearable yet completely predictable.

The Argentine Brain Drain
Argentina is currently experiencing a brain drain so strong that it made the headlines on Swiss television.

The enteric nervous system is 10 times stiffer than the brain
Nicolas R. Chevalier (IJPB), Alexis Peaucelle (IJPB), Thomas Guilbert (IC UM3), Pierre Bourdoncle, Wang Xi
https://arxiv.org/abs/2506.08583

The enteric nervous system is 10 times stiffer than the brain
Neural tissues of the central nervous system are among the softest and most fragile in the human body, protected from mechanical perturbation by the skull and the spine. In contrast, the enteric nervous system is embedded in a compliant, contractile tissue and subject to chronic, high-magnitude mechanical stress. Do neurons and glia of the enteric nervous system display specific mechanical properties to withstand these forces? Using nano-indentation combined with immunohistochemistry and second…

Magnetoencephalography (MEG) Based Non-Invasive Chinese Speech Decoding
Zhihong Jia, Hongbin Wang, Yuanzhong Shen, Feng Hu, Jiayu An, Kai Shu, Dongrui Wu
https://arxiv.org/abs/2506.12817

Magnetoencephalography (MEG) Based Non-Invasive Chinese Speech Decoding
As an emerging paradigm of brain-computer interfaces (BCIs), speech BCI has the potential to directly reflect auditory perception and thoughts, offering a promising communication alternative for patients with aphasia. Chinese is one of the most widely spoken languages in the world, whereas there is very limited research on speech BCIs for Chinese language. This paper reports a text-magnetoencephalography (MEG) dataset for non-invasive Chinese speech BCIs. It also proposes a multi-modality assis…

A large-scale heterogeneous 3D magnetic resonance brain imaging dataset for self-supervised learning
Asbj{\o}rn Munk, Stefano Cerri, Jakob Ambsdorf, Julia Machnio, Sebastian N{\o}rgaard Llambias, Vardan Nersesjan, Christian Hedeager Krag, Peirong Liu, Pablo Rocamora Garc\'ia, Mostafa Mehdipour Ghazi, Mikael Boesen, Michael Eriksen Benros, Juan Eugenio Iglesias, Mads Nielsen

A large-scale heterogeneous 3D magnetic resonance brain imaging dataset for self-supervised learning
We present FOMO60K, a large-scale, heterogeneous dataset of 60,529 brain Magnetic Resonance Imaging (MRI) scans from 13,900 sessions and 11,187 subjects, aggregated from 16 publicly available sources. The dataset includes both clinical- and research-grade images, multiple MRI sequences, and a wide range of anatomical and pathological variability, including scans with large brain anomalies. Minimal preprocessing was applied to preserve the original image characteristics while reducing barriers t…

“The String… will be much faster”
my brain is breaking https://mastodon.social/@Catfish_Man/114655168110161214

Delighted to see these two new papers come out in Nature (they've been on bioRxiv for a while).
How does Pavlov's dog learn that the bell predicts the food? One answer is that the bell appears ``close'' in time to the food and that enables learning. We're certain that dopamine has something to do with learning these kinds of associations. But the definition of ``close'' in time is actually really difficult to pin down. You can get associations over prett…

Bookmark this for when you ask yourself why skepticism turns to hatred on the use of unconstrained LLMs.
https://infosec.exchange/@dvandal/114638324336575392

Reconfigurable Digital RRAM Logic Enables In-Situ Pruning and Learning for Edge AI
Songqi Wang, Yue Zhang, Jia Chen, Xinyuan Zhang, Yi Li, Ning Lin, Yangu He, Jichang Yang, Yingjie Yu, Yi Li, Zhongrui Wang, Xiaojuan Qi, Han Wang
https://arxiv.org/abs/2506.13151

Reconfigurable Digital RRAM Logic Enables In-Situ Pruning and Learning for Edge AI
The human brain simultaneously optimizes synaptic weights and topology by growing, pruning, and strengthening synapses while performing all computation entirely in memory. In contrast, modern artificial-intelligence systems separate weight optimization from topology optimization and depend on energy-intensive von Neumann architectures. Here, we present a software-hardware co-design that bridges this gap. On the algorithmic side, we introduce a real-time dynamic weight-pruning strategy that moni…

Genndy Tartakovsky's developing a new show 'Heist Safari' that looks pretty great. Loved what he did with Dexter's Lab. This one's about three estranged frog brothers who meet up at their dad's funeral, have to rob a bank to inherit their late dad's fortune, and have issues when they cut side deals with mobsters. Every episode will be executed as just one shot, the events won't be in chronological order, and it'll have an EDM score. Looks & sounds prom…

Genndy Tartakovsky Developing 'Heist Safari' Animated Series for Adult Swim
Celebrated animator Genndy Tartakovsky — the tooned-up brain behind the adult-comedy movie Fixed (coming to Netflix on August 13), Sony's Hotel Transylvania

Quanta Magazine Staff Writer Yasemin Saplakoglu describes the various ongoing inter-disciplinary efforts to advance our scientific understanding of the Human brain. Computer scientists and computational neuroscientists collaborate as the latter borrow mathematical models from the former, and studies ways to incorporate new biological data to enhance, or supplant existing computational models.
"AI Is Nothing Like a Brain, and That's OK."

AI Is Nothing Like a Brain, and That’s OK | Quanta Magazine
The brain’s astounding cellular diversity and networked complexity could show how to make AI better.

Synaptic plasticity in Co/Nb:STO memristive devices: The role of oxygen vacancies
Walter Qui\~nonez, Anouk Goossens, Diego Rubi, Tamalika Banerjee, Mar\'ia Jos\'e S\'anchez
https://arxiv.org/abs/2506.11965

Synaptic plasticity in Co/Nb:STO memristive devices: The role of oxygen vacancies
Neuromorphic computing aims to develop energy-efficient devices that mimic biological synapses. One promising approach involves memristive devices that can dynamically adjust their electrical resistance in response to stimuli, similar to synaptic weight changes in the brain. However, a key challenge is understanding and controlling the coexistence of different types of synaptic plasticity, such as short-term and long-term plasticity. In this work, we show that plasticity behaviors in Co/Nb:STO …

An 11,000-Study Open-Access Dataset of Longitudinal Magnetic Resonance Images of Brain Metastases
Saahil Chadha, David Weiss, Anastasia Janas, Divya Ramakrishnan, Thomas Hager, Klara Osenberg, Klara Willms, Joshua Zhu, Veronica Chiang, Spyridon Bakas, Nazanin Maleki, Durga V. Sritharan, Sven Schoenherr, Malte Westerhoff, Matthew Zawalich, Melissa Davis, Ajay Malhotra, Khaled Bousabarah, Cornelius Deuschl, MingDe Lin, Sanjay Aneja, Mariam S. Aboian

An 11,000-Study Open-Access Dataset of Longitudinal Magnetic Resonance Images of Brain Metastases
Brain metastases are a common complication of systemic cancer, affecting over 20% of patients with primary malignancies. Longitudinal magnetic resonance imaging (MRI) is essential for diagnosing patients, tracking disease progression, assessing therapeutic response, and guiding treatment selection. However, the manual review of longitudinal imaging is time-intensive, especially for patients with multifocal disease. Artificial intelligence (AI) offers opportunities to streamline image evaluation…

Sparse Autoencoders Bridge The Deep Learning Model and The Brain
Ziming Mao, Jia Xu, Zeqi Zheng, Haofang Zheng, Dabing Sheng, Yaochu Jin, Guoyuan Yang
https://arxiv.org/abs/2506.11123

Sparse Autoencoders Bridge The Deep Learning Model and The Brain
We present SAE-BrainMap, a novel framework that directly aligns deep learning visual model representations with voxel-level fMRI responses using sparse autoencoders (SAEs). First, we train layer-wise SAEs on model activations and compute the correlations between SAE unit activations and cortical fMRI signals elicited by the same natural image stimuli with cosine similarity, revealing strong activation correspondence (maximum similarity up to 0.76). Depending on this alignment, we construct a vo…

PORTLAND, Ore. — Health officials in Hood River County confirmed Monday that two local deaths have been linked to a rare brain disease within the last eight months.
During that period, the county said, there have been one confirmed and two probable cases of
Creutzfeldt-Jakob Disease, or CJD, a prion disorder somewhat similar to the more commonly known "mad cow disease."
So far, two of those cases have resulted in death

#FreeLuigi

Brain Network Analysis Based on Fine-tuned Self-supervised Model for Brain Disease Diagnosis
Yifei Tang, Hongjie Jiang, Changhong Jing, Hieu Pham, Shuqiang Wang
https://arxiv.org/abs/2506.11671

Brain Network Analysis Based on Fine-tuned Self-supervised Model for Brain Disease Diagnosis
Functional brain network analysis has become an indispensable tool for brain disease analysis. It is profoundly impacted by deep learning methods, which can characterize complex connections between ROIs. However, the research on foundation models of brain network is limited and constrained to a single dimension, which restricts their extensive application in neuroscience. In this study, we propose a fine-tuned brain network model for brain disease diagnosis. It expands brain region representati…

The great poaching: America's brain drain begins (Erica Pandey/Axios)
https://www.axios.com/2025/06/07/us-science-brain-drain
http://www.memeorandum.com/250607/p9#a250607p9

Auch im #Schlaf wirkt #Koffein auf das Gehirn.
Es verändert die nächtliche Gehirnaktivität und kann die Erholung stören. Besonders bei jungen Erwachsenen schwächt es wichtige #Hirnwellen, die fü…

Caffeine Has a Weird Effect on Your Brain While You're Asleep
We already know that the stimulating powers of caffeine make it an unsuitable choice for a late-night drink – at least if you want to get any shut-eye.

I have many thoughts about generative AI, but the overarching one is this: the better metaphor is not a new brain acquiring human thoughts, but a complex search engine for existing human-generated ideas.

fly_hemibrain: Fly hemibrain (2020)
A synaptic map of the hemibrain connectome of fruit fly Drosophila melanogaster. Nodes are neurons, and edges are synaptic connections, traced individually from brain image sections using EM reconstruction techniques. Neurons are labeled by their type. Edges are annotated by the connection strength between the neurons.
This network has 21739 nodes and 4259624 edges.
Tags: Biological, Connectome, Weighted, Metadata

Neuromorphic Online Clustering and Its Application to Spike Sorting
James E. Smith
https://arxiv.org/abs/2506.12555 https://arxiv.org…

Neuromorphic Online Clustering and Its Application to Spike Sorting
Active dendrites are the basis for biologically plausible neural networks possessing many desirable features of the biological brain including flexibility, dynamic adaptability, and energy efficiency. A formulation for active dendrites using the notational language of conventional machine learning is put forward as an alternative to a spiking neuron formulation. Based on this formulation, neuromorphic dendrites are developed as basic neural building blocks capable of dynamic online clustering. …

10:42—Good Morning #Fediverse!
Being #ActuallyAutistic, I am currently hyperfixated on this image. I have been staring at it for an extended period, analyzing every detail.
I keep noticing new things every time I look at it. My brain is in “info-dump mode” and I could pr…

Pondering how to best prepare for the upcoming onslaught of Neuralink Blindsight brain implant hype/PR after the first blind patient receives one in UAE. Most scientists are open to reason, but they make up a tiny minority under funding stress, while the mass media profit from maximizing hype.
https://www.artifi…

Cross-Channel Unlabeled Sensing over a Union of Signal Subspaces
Taulant Koka, Manolis C. Tsakiris, Benjam\'in B\'ejar Haro, Michael Muma
https://arxiv.org/abs/2506.09773 …

Cross-Channel Unlabeled Sensing over a Union of Signal Subspaces
Cross-channel unlabeled sensing addresses the problem of recovering a multi-channel signal from measurements that were shuffled across channels. This work expands the cross-channel unlabeled sensing framework to signals that lie in a union of subspaces. The extension allows for handling more complex signal structures and broadens the framework to tasks like compressed sensing. These mismatches between samples and channels often arise in applications such as whole-brain calcium imaging of freely…

(1/2) Can you trust what you hear? 🎧 Episode 344 of the EdTech Situation Room (from 15 Jan 2025) explores AI voice tech, misinformation, and media ethics in the digital age.
on Substack:
https://open.substack.com/p…

Voxel-Level Brain States Prediction Using Swin Transformer
Yifei Sun, Daniel Chahine, Qinghao Wen, Tianming Liu, Xiang Li, Yixuan Yuan, Fernando Calamante, Jinglei Lv
https://arxiv.org/abs/2506.11455

Voxel-Level Brain States Prediction Using Swin Transformer
Understanding brain dynamics is important for neuroscience and mental health. Functional magnetic resonance imaging (fMRI) enables the measurement of neural activities through blood-oxygen-level-dependent (BOLD) signals, which represent brain states. In this study, we aim to predict future human resting brain states with fMRI. Due to the 3D voxel-wise spatial organization and temporal dependencies of the fMRI data, we propose a novel architecture which employs a 4D Shifted Window (Swin) Transfo…

The Trump administration’s spending cuts and restrictions on foreign students are triggering a brain drain — and American scientists are panicking.
U.S. researchers' fears are coming true.
America’s science pipeline is drying up,
and countries like China are seizing the opportunity to surge ahead.

“This is such a race for being the science powerhouse that you never fully recover,”
says Marcia McNutt, president of the National Academy of Sciences.

The great poaching: America's brain drain begins
China and Europe are recruiting heavily from U.S. labs.

Paradromics implanted and removed its Connexus brain implant in a patient for ~10 minutes during epilepsy surgery on May 14, a first for the Neuralink rival (Emily Mullin/Wired)
https://www.wired.com/story/paradromics-neuralink-rival-tested-brain-impl…

A Neuralink Rival Just Tested a Brain Implant in a Person
Paradromics, a brain-computer-interface startup, inserted its brain implant in a person—briefly—in an early test of its technology.

Leveraging Transfer Learning and User-Specific Updates for Rapid Training of BCI Decoders
Ziheng Chen, Po T. Wang, Mina Ibrahim, Shivali Baveja, Rong Mu, An H. Do, Zoran Nenadic
https://arxiv.org/abs/2506.14120

Leveraging Transfer Learning and User-Specific Updates for Rapid Training of BCI Decoders
Lengthy subject- or session-specific data acquisition and calibration remain a key barrier to deploying electroencephalography (EEG)-based brain-computer interfaces (BCIs) outside the laboratory. Previous work has shown that cross subject, cross-session invariant features exist in EEG. We propose a transfer learning pipeline based on a two-layer convolutional neural network (CNN) that leverages these invariants to reduce the burden of data acquisition and calibration. A baseline model is traine…

Score-based Generative Diffusion Models to Synthesize Full-dose FDG Brain PET from MRI in Epilepsy Patients
Jiaqi Wu, Jiahong Ouyang, Farshad Moradi, Mohammad Mehdi Khalighi, Greg Zaharchuk
https://arxiv.org/abs/2506.11297

Score-based Generative Diffusion Models to Synthesize Full-dose FDG Brain PET from MRI in Epilepsy Patients
Fluorodeoxyglucose (FDG) PET to evaluate patients with epilepsy is one of the most common applications for simultaneous PET/MRI, given the need to image both brain structure and metabolism, but is suboptimal due to the radiation dose in this young population. Little work has been done synthesizing diagnostic quality PET images from MRI data or MRI data with ultralow-dose PET using advanced generative AI methods, such as diffusion models, with attention to clinical evaluations tailored for the e…

fly_hemibrain: Fly hemibrain (2020)
A synaptic map of the hemibrain connectome of fruit fly Drosophila melanogaster. Nodes are neurons, and edges are synaptic connections, traced individually from brain image sections using EM reconstruction techniques. Neurons are labeled by their type. Edges are annotated by the connection strength between the neurons.
This network has 21739 nodes and 4259624 edges.
Tags: Biological, Connectome, Weighted, Metadata

How to turn the tide? Both brain implants and sensory substitution can only restore very limited forms of vision to blind people, nothing like normal vision. We should be cooperating, not just competing, ignoring mass media incentives, investors and AI. Let's be true leaders. 😇

First positronium imaging using $^{44}$Sc with the J-PET scanner: a case study on the NEMA-Image Quality phantom
Manish Das, Sushil Sharma, Aleksander Bilewicz, Jaros{\l}aw Choi\'nski, Neha Chug, Catalina Curceanu, Eryk Czerwi\'nski, Jakub Hajduga, Sharareh Jalali, Krzysztof Kacprzak, Tevfik Kaplanoglu, {\L}ukasz Kap{\l}on, Kamila Kasperska, Aleksander Khreptak, Grzegorz Korcyl, Tomasz Kozik, Karol Kubat, Deepak Kumar, Anoop Kunimmal Venadan, Edward Lisowski, Filip Lisowski, Ju…

First positronium imaging using $^{44}$Sc with the J-PET scanner: a case study on the NEMA-Image Quality phantom
Positronium Lifetime Imaging (PLI), an emerging extension of conventional positron emission tomography (PET) imaging, offers a novel window for probing the submolecular properties of biological tissues by imaging the mean lifetime of the positronium atom. Currently, the method is under rapid development in terms of reconstruction and detection systems. Recently, the first in vivo PLI of the human brain was performed using the J-PET scanner utilizing the $^{68}$Ga isotope. However, this isotope …

(Bloomberg) Neuralink device helps monkey to see something that's not there https://archive.ph/tQTqw
"At least two-thirds of the time, the monkey moved its eyes toward something researchers were trying to trick the brain into visualizing."
That thus far sounds far less impressive …

Decoding Cortical Microcircuits: A Generative Model for Latent Space Exploration and Controlled Synthesis
Xingyu Liu, Yubin Li, Guozhang Chen
https://arxiv.org/abs/2506.11062

Decoding Cortical Microcircuits: A Generative Model for Latent Space Exploration and Controlled Synthesis
A central idea in understanding brains and building artificial intelligence is that structure determines function. Yet, how the brain's complex structure arises from a limited set of genetic instructions remains a key question. The ultra high-dimensional detail of neural connections vastly exceeds the information storage capacity of genes, suggesting a compact, low-dimensional blueprint must guide brain development. Our motivation is to uncover this blueprint. We introduce a generative model, t…

Let me think about what really radicalized me. I’m autistic, so I forget things fast. I need to dig into my brain and find that quirky, weird thing or topic that made me feel radical years ago.
It might be something I hyperfocused on or a strange idea that stuck with me for a long time. I’ll try to find it and figure out what pushed me to where I am now.
I’ll post it when I find it. Sometimes it takes me a bit to dig through all the thoughts and memories in my brain, especially w…

Localizing synergies of hidden factors across complex systems: resting brain networks and HeLa gene expression profile as case studies
Marlis Ontivero-Ortega, Gorana Mijatovic, Luca Faes, Daniele Marinazzo, Sebastiano Stramaglia
https://arxiv.org/abs/2506.09053

Localizing synergies of hidden factors across complex systems: resting brain networks and HeLa gene expression profile as case studies
Factor analysis is a well-known statistical method to describe the variability of observed variables in terms of a smaller number of unobserved latent variables called factors. Even though latent factors are conceptually independent of each other, their influence on the observed variables is often joint and synergistic. We propose to quantify the synergy of the joint influence of factors on the observed variables using the O-information, a recently introduced metrics to assess high order depend…

Functional and structural plasticity induced by audiovisual associations and sensory experiences https://link.springer.com/article/10.1007/s00429-025-02951-3 "widespread increases in functional connectivity between the trained region and higher-order frontal…

Functional and structural plasticity induced by audiovisual associations and sensory experiences - Brain Structure and Function
Crossmodal associations and correspondences play important roles in shaping perception and guiding our actions. However, we still have a limited understanding of association-induced changes in the adult human brain. An important question to address is to what extent passive exposure to crossmodal associations leads to functional and structural changes in the brain. Utilizing an audiovisual association paradigm in which motion stimuli presented in the left visual field were paired with auditory …

Instruction-Tuned Video-Audio Models Elucidate Functional Specialization in the Brain
Subba Reddy Oota, Khushbu Pahwa, Prachi Jindal, Satya Sai Srinath Namburi, Maneesh Singh, Tanmoy Chakraborty, Bapi S. Raju, Manish Gupta
https://arxiv.org/abs/2506.08277

Instruction-Tuned Video-Audio Models Elucidate Functional Specialization in the Brain
Recent voxel-wise multimodal brain encoding studies have shown that multimodal large language models (MLLMs) exhibit a higher degree of brain alignment compared to unimodal models in both unimodal and multimodal stimulus settings. More recently, instruction-tuned multimodal models have shown to generate task-specific representations that align strongly with brain activity. However, prior work evaluating the brain alignment of MLLMs has primarily focused on unimodal settings or relied on non-ins…

Rethinking Brain Tumor Segmentation from the Frequency Domain Perspective
Minye Shao, Zeyu Wang, Haoran Duan, Yawen Huang, Bing Zhai, Shizheng Wang, Yang Long, Yefeng Zheng
https://arxiv.org/abs/2506.10142

Rethinking Brain Tumor Segmentation from the Frequency Domain Perspective
Precise segmentation of brain tumors, particularly contrast-enhancing regions visible in post-contrast MRI (areas highlighted by contrast agent injection), is crucial for accurate clinical diagnosis and treatment planning but remains challenging. However, current methods exhibit notable performance degradation in segmenting these enhancing brain tumor areas, largely due to insufficient consideration of MRI-specific tumor features such as complex textures and directional variations. To address t…

Can adults grow new brain cells? https://www.livescience.com/health/neuroscience/can-adults-grow-new-brain-cells "Scientists are still debating whether the human brain is capable of growing new cells past childhood"

Can adults grow new brain cells?
Scientists are still debating whether the human brain is capable of growing new cells past childhood.

Conditional diffusion models for guided anomaly detection in brain images using fluid-driven anomaly randomization
Ana Lawry Aguila, Peirong Liu, Oula Puonti, Juan Eugenio Iglesias
https://arxiv.org/abs/2506.10233

Conditional diffusion models for guided anomaly detection in brain images using fluid-driven anomaly randomization
Supervised machine learning has enabled accurate pathology detection in brain MRI, but requires training data from diseased subjects that may not be readily available in some scenarios, for example, in the case of rare diseases. Reconstruction-based unsupervised anomaly detection, in particular using diffusion models, has gained popularity in the medical field as it allows for training on healthy images alone, eliminating the need for large disease-specific cohorts. These methods assume that a …

The Predictive Brain: Neural Correlates of Word Expectancy Align with Large Language Model Prediction Probabilities
Nikola K\"olbl, Konstantin Tziridis, Andreas Maier, Thomas Kinfe, Ricardo Chavarriaga, Achim Schilling, Patrick Krauss
https://arxiv.org/abs/2506.08511

The Predictive Brain: Neural Correlates of Word Expectancy Align with Large Language Model Prediction Probabilities
Predictive coding theory suggests that the brain continuously anticipates upcoming words to optimize language processing, but the neural mechanisms remain unclear, particularly in naturalistic speech. Here, we simultaneously recorded EEG and MEG data from 29 participants while they listened to an audio book and assigned predictability scores to nouns using the BERT language model. Our results show that higher predictability is associated with reduced neural responses during word recognition, as…

Geometry Reduced Order Modeling (GROM) with application to modeling of glymphatic function
Andreas Solheim, Geir Ringstand, Per Kristian Eide, Kent-Andre Mardal
https://arxiv.org/abs/2506.09442

Geometry Reduced Order Modeling (GROM) with application to modeling of glymphatic function
Computational modeling of the brain has become a key part of understanding how the brain clears metabolic waste, but patient-specific modeling on a significant scale is still out of reach with current methods. We introduce a novel approach for leveraging model order reduction techniques in computational models of brain geometries to alleviate computational costs involved in numerical simulations. Using image registration methods based on magnetic resonance imaging, we compute inter-brain mappin…

Object knowledge representation in the human visual cortex requires a connection with the language system https://journals.plos.org/plosbiology/article?id=10.1371/journal.pbio.3003161 "Our experiments reveal the contribution of the vision-la…

Object knowledge representation in the human visual cortex requires a connection with the language system
This study shows that communication between the visual cortex and the brain language system is necessary for the representation of object knowledge in the visual cortex and for corresponding behaviors in humans. This highlights the significance of connections between sensory and language systems for object knowledge in the human brain.

Visual mental imagery and #aphantasia lesions map onto a convergent brain network https://www.medrxiv.org/content/10.1101/2025.05.23.25328072v1 by @…

Visual Mental Imagery and Aphantasia Lesions Map onto a Convergent Brain Network
Background Visual mental imagery, the ability to volitionally form perceptual representations without corresponding external stimuli, allows reliving of past events, solving problems and imagining the future. The absence of visual mental imagery, called aphantasia, has recently been recognized to occur in about 1% of the general population but the cause is uncertain. By studying rare cases of acquired aphantasia we can identify regions that when injured cause loss of visual mental imagery. Met…

The global communication pathways of the human brain transcend the cortical-subcortical-cerebellar division
Julian Schulte, Mario Senden, Gustavo Deco, Xenia Kobeleva, Gorka Zamora-L\'opez
https://arxiv.org/abs/2505.22893

The global communication pathways of the human brain transcend the cortical-subcortical-cerebellar division
Neural communication across the cortex, subcortex, and cerebellum is orchestrated by the structural connectome, forming the indispensable anatomical framework for capabilities spanning from elementary motor actions to higher cognitive functions. Yet, despite this importance, the core organizational rules that govern this connectivity remain insufficiently understood. Here we show, for the first time, how the integrated cortical, subcortical, and cerebellar brain areas shape the structural archi…

This https://arxiv.org/abs/2305.12844 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_ees…

An Optimized Ensemble Deep Learning Model For Brain Tumor Classification
Brain tumors present a grave risk to human life, demanding precise and timely diagnosis for effective treatment. Inaccurate identification of brain tumors can significantly diminish life expectancy, underscoring the critical need for precise diagnostic methods. Manual identification of brain tumors within vast Magnetic Resonance Imaging (MRI) image datasets is arduous and time-consuming. Thus, the development of a reliable deep learning (DL) model is essential to enhance diagnostic accuracy and…

Go for a Neuralink Blindsight brain implant, or opt for cheaper and replaceable smart glasses? #BCI