Neuralink is developing "neural laces", a mesh of electrodes that can be injected into the brain via arteries. The laces would connect the brain to a computer, allowing for direct uploading and downloading of thoughts. The laces are a polymer mesh with embedded nanowires and transistors that can monitor and stimulate individual neurons. Once injected, the laces unravel and integrate with the brain, potentially treating neurological disorders or allowing brain-computer interfaces without devices. The goal is for humans to keep pace with advancing artificial intelligence.
Neuralink white-paper. Elon Musk & Neuralink
Abstract
Brain-machine interfaces (BMIs) hold promise for the restoration of sensory and motor function and
the treatment of neurological disorders, but clinical BMIs have not yet been widely adopted, in part
because modest channel counts have limited their potential. In this white paper, we describe Neuralink’s first steps toward a scalable high-bandwidth BMI system. We have built arrays of small and
flexible electrode “threads”, with as many as 3,072 electrodes per array distributed across 96 threads.
We have also built a neurosurgical robot capable of inserting six threads (192 electrodes) per minute.
Each thread can be individually inserted into the brain with micron precision for avoidance of surface vasculature and targeting specific brain regions. The electrode array is packaged into a small
implantable device that contains custom chips for low-power on-board amplification and digitization: the package for 3,072 channels occupies less than (23 × 18.5 × 2) mm3
. A single USB-C cable
provides full-bandwidth data streaming from the device, recording from all channels simultaneously.
This system has achieved a spiking yield of up to 85.5 % in chronically implanted electrodes. Neuralink’s approach to BMI has unprecedented packaging density and scalability in a clinically relevant
package.
Neuralink white-paper. Elon Musk & Neuralink
Abstract
Brain-machine interfaces (BMIs) hold promise for the restoration of sensory and motor function and
the treatment of neurological disorders, but clinical BMIs have not yet been widely adopted, in part
because modest channel counts have limited their potential. In this white paper, we describe Neuralink’s first steps toward a scalable high-bandwidth BMI system. We have built arrays of small and
flexible electrode “threads”, with as many as 3,072 electrodes per array distributed across 96 threads.
We have also built a neurosurgical robot capable of inserting six threads (192 electrodes) per minute.
Each thread can be individually inserted into the brain with micron precision for avoidance of surface vasculature and targeting specific brain regions. The electrode array is packaged into a small
implantable device that contains custom chips for low-power on-board amplification and digitization: the package for 3,072 channels occupies less than (23 × 18.5 × 2) mm3
. A single USB-C cable
provides full-bandwidth data streaming from the device, recording from all channels simultaneously.
This system has achieved a spiking yield of up to 85.5 % in chronically implanted electrodes. Neuralink’s approach to BMI has unprecedented packaging density and scalability in a clinically relevant
package.
Here is very good and amazing presentation on Brain chipss...
read this carefully and work on this because the work on brain is very good for future research...
Presentation on Brain Computer Interface. It describes how our brain is used as a signaling mechanism for computer. different types of BCIs and its applications.
Here is very good and amazing presentation on Brain chipss...
read this carefully and work on this because the work on brain is very good for future research...
Presentation on Brain Computer Interface. It describes how our brain is used as a signaling mechanism for computer. different types of BCIs and its applications.
PPT of my technical Seminar titled Brain-computer interface (BCI). This is a collaboration between a brain and a device that enables signals from the brain to direct some external activity, such as control of a cursor or a prosthetic limb.
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POWER EFFICIENT SOFTWARE DEFINED RADIO FOR DISASTER AFFECTED REGIONS USING R...Nishmi Suresh
INTRODUCTION Radio communication is extremely critical for public safety, national safety and emergency communications systems.During emergency situation all forms of communication are break down.Solve the problem of inter-operability and incompatible. Inter-operability is solved by implementing large part of radio functionality in software.Software defined radio, communicate with multiple incompatible radios or act as a bridge between them.Present a method and design of implementing an SDR system using Raspberry Pi
Provide enough computational power to perform all the required signal processing in real time.
Introduction:
RNA interference (RNAi) or Post-Transcriptional Gene Silencing (PTGS) is an important biological process for modulating eukaryotic gene expression.
It is highly conserved process of posttranscriptional gene silencing by which double stranded RNA (dsRNA) causes sequence-specific degradation of mRNA sequences.
dsRNA-induced gene silencing (RNAi) is reported in a wide range of eukaryotes ranging from worms, insects, mammals and plants.
This process mediates resistance to both endogenous parasitic and exogenous pathogenic nucleic acids, and regulates the expression of protein-coding genes.
What are small ncRNAs?
micro RNA (miRNA)
short interfering RNA (siRNA)
Properties of small non-coding RNA:
Involved in silencing mRNA transcripts.
Called “small” because they are usually only about 21-24 nucleotides long.
Synthesized by first cutting up longer precursor sequences (like the 61nt one that Lee discovered).
Silence an mRNA by base pairing with some sequence on the mRNA.
Discovery of siRNA?
The first small RNA:
In 1993 Rosalind Lee (Victor Ambros lab) was studying a non- coding gene in C. elegans, lin-4, that was involved in silencing of another gene, lin-14, at the appropriate time in the
development of the worm C. elegans.
Two small transcripts of lin-4 (22nt and 61nt) were found to be complementary to a sequence in the 3' UTR of lin-14.
Because lin-4 encoded no protein, she deduced that it must be these transcripts that are causing the silencing by RNA-RNA interactions.
Types of RNAi ( non coding RNA)
MiRNA
Length (23-25 nt)
Trans acting
Binds with target MRNA in mismatch
Translation inhibition
Si RNA
Length 21 nt.
Cis acting
Bind with target Mrna in perfect complementary sequence
Piwi-RNA
Length ; 25 to 36 nt.
Expressed in Germ Cells
Regulates trnasposomes activity
MECHANISM OF RNAI:
First the double-stranded RNA teams up with a protein complex named Dicer, which cuts the long RNA into short pieces.
Then another protein complex called RISC (RNA-induced silencing complex) discards one of the two RNA strands.
The RISC-docked, single-stranded RNA then pairs with the homologous mRNA and destroys it.
THE RISC COMPLEX:
RISC is large(>500kD) RNA multi- protein Binding complex which triggers MRNA degradation in response to MRNA
Unwinding of double stranded Si RNA by ATP independent Helicase
Active component of RISC is Ago proteins( ENDONUCLEASE) which cleave target MRNA.
DICER: endonuclease (RNase Family III)
Argonaute: Central Component of the RNA-Induced Silencing Complex (RISC)
One strand of the dsRNA produced by Dicer is retained in the RISC complex in association with Argonaute
ARGONAUTE PROTEIN :
1.PAZ(PIWI/Argonaute/ Zwille)- Recognition of target MRNA
2.PIWI (p-element induced wimpy Testis)- breaks Phosphodiester bond of mRNA.)RNAse H activity.
MiRNA:
The Double-stranded RNAs are naturally produced in eukaryotic cells during development, and they have a key role in regulating gene expression .
Multi-source connectivity as the driver of solar wind variability in the heli...Sérgio Sacani
The ambient solar wind that flls the heliosphere originates from multiple
sources in the solar corona and is highly structured. It is often described
as high-speed, relatively homogeneous, plasma streams from coronal
holes and slow-speed, highly variable, streams whose source regions are
under debate. A key goal of ESA/NASA’s Solar Orbiter mission is to identify
solar wind sources and understand what drives the complexity seen in the
heliosphere. By combining magnetic feld modelling and spectroscopic
techniques with high-resolution observations and measurements, we show
that the solar wind variability detected in situ by Solar Orbiter in March
2022 is driven by spatio-temporal changes in the magnetic connectivity to
multiple sources in the solar atmosphere. The magnetic feld footpoints
connected to the spacecraft moved from the boundaries of a coronal hole
to one active region (12961) and then across to another region (12957). This
is refected in the in situ measurements, which show the transition from fast
to highly Alfvénic then to slow solar wind that is disrupted by the arrival of
a coronal mass ejection. Our results describe solar wind variability at 0.5 au
but are applicable to near-Earth observatories.
The increased availability of biomedical data, particularly in the public domain, offers the opportunity to better understand human health and to develop effective therapeutics for a wide range of unmet medical needs. However, data scientists remain stymied by the fact that data remain hard to find and to productively reuse because data and their metadata i) are wholly inaccessible, ii) are in non-standard or incompatible representations, iii) do not conform to community standards, and iv) have unclear or highly restricted terms and conditions that preclude legitimate reuse. These limitations require a rethink on data can be made machine and AI-ready - the key motivation behind the FAIR Guiding Principles. Concurrently, while recent efforts have explored the use of deep learning to fuse disparate data into predictive models for a wide range of biomedical applications, these models often fail even when the correct answer is already known, and fail to explain individual predictions in terms that data scientists can appreciate. These limitations suggest that new methods to produce practical artificial intelligence are still needed.
In this talk, I will discuss our work in (1) building an integrative knowledge infrastructure to prepare FAIR and "AI-ready" data and services along with (2) neurosymbolic AI methods to improve the quality of predictions and to generate plausible explanations. Attention is given to standards, platforms, and methods to wrangle knowledge into simple, but effective semantic and latent representations, and to make these available into standards-compliant and discoverable interfaces that can be used in model building, validation, and explanation. Our work, and those of others in the field, creates a baseline for building trustworthy and easy to deploy AI models in biomedicine.
Bio
Dr. Michel Dumontier is the Distinguished Professor of Data Science at Maastricht University, founder and executive director of the Institute of Data Science, and co-founder of the FAIR (Findable, Accessible, Interoperable and Reusable) data principles. His research explores socio-technological approaches for responsible discovery science, which includes collaborative multi-modal knowledge graphs, privacy-preserving distributed data mining, and AI methods for drug discovery and personalized medicine. His work is supported through the Dutch National Research Agenda, the Netherlands Organisation for Scientific Research, Horizon Europe, the European Open Science Cloud, the US National Institutes of Health, and a Marie-Curie Innovative Training Network. He is the editor-in-chief for the journal Data Science and is internationally recognized for his contributions in bioinformatics, biomedical informatics, and semantic technologies including ontologies and linked data.
Professional air quality monitoring systems provide immediate, on-site data for analysis, compliance, and decision-making.
Monitor common gases, weather parameters, particulates.
Richard's entangled aventures in wonderlandRichard Gill
Since the loophole-free Bell experiments of 2020 and the Nobel prizes in physics of 2022, critics of Bell's work have retreated to the fortress of super-determinism. Now, super-determinism is a derogatory word - it just means "determinism". Palmer, Hance and Hossenfelder argue that quantum mechanics and determinism are not incompatible, using a sophisticated mathematical construction based on a subtle thinning of allowed states and measurements in quantum mechanics, such that what is left appears to make Bell's argument fail, without altering the empirical predictions of quantum mechanics. I think however that it is a smoke screen, and the slogan "lost in math" comes to my mind. I will discuss some other recent disproofs of Bell's theorem using the language of causality based on causal graphs. Causal thinking is also central to law and justice. I will mention surprising connections to my work on serial killer nurse cases, in particular the Dutch case of Lucia de Berk and the current UK case of Lucy Letby.
A brief information about the SCOP protein database used in bioinformatics.
The Structural Classification of Proteins (SCOP) database is a comprehensive and authoritative resource for the structural and evolutionary relationships of proteins. It provides a detailed and curated classification of protein structures, grouping them into families, superfamilies, and folds based on their structural and sequence similarities.
2. INTRODUCTION
• SpaceX and Tesla CEO Elon Musk is developing ultra-high bandwidth
brain-computer interface venture called Neuralink.
• The company, which is still in the earliest stages of existence.
• Is centered on creating devices that can be implanted in the human
brain.
• Aim to helping human beings merge with software and keep pace
with advancements in artificial intelligence.
3. • These enhancements could improve memory or allow for more direct
interfacing with computing devices.
• Neuralink, is developing a science fiction concept called “neural laces”
• It is a “digital layer” located above the cortex, built into the brain.
• Neural lace could be the next advancement in the field of AI.
• It would help prevent humans from becoming “house cats” to AI.
• Which involves implanting electrodes into human brains that allow for the
uploading and downloading of thoughts to a computer.
4. NEURAL LACES
• Developed by a group of chemists and engineers who works with
nanotechnology.
• Allows for direct connection between a human brain and a computer.
• It is also called a Brain Computer Interface (BCI).
• Neural lace is a very tiny polymer mesh.
• Which can be injected via the arterial system.
5. • Neural laces are surgically connected to a human brain and allows
users to interact with a computer without the need for input methods
like keyboards or trackpads.
6. How neural laces are made
• The process for fabricating the scaffold is similar to that used to etch microchips.
• Begins with a dissolvable layer deposited on a biocompatible nanoscale polymer mesh
substrate, with embedded nanowires ,are made of a 10-nm-wide core of germanium,
surrounded by a 2-nm-thick shell of silicon , transistors, and other microelectronic devices
attached.
• To cover nanowires with a three-layer dielectric—first aluminum oxide, then zirconium
oxide, then another layer of aluminum oxide.
• The three-layer material lets the wires trap charge carriers, allowing them to act as a
nonvolatile memory, holding a positive or negative state even when no current is applied.
• The nanowires are laid out parallel to one another, with a source and drain on either end
7. • A series of metal gate electrodes crosses the wires perpendicularly.
• Each nanowire contains multiple transistors, because each cross point between the
nanowire and metal gate makes an individual transistor.
• The mesh is then tightly rolled up, allowing it to be sucked up into a syringe via a
thin glass needle having 100um internal diameter.
• Once in the brain, the mesh uncurls to about 80% of its original configuration, sits
on top of the neurons, and starts monitoring.
• The input-output connection of the mesh electronics can be connected to standard
electronics devices, allowing the mesh-embedded devices to be individually
addressed and used to precisely stimulate or record individual neural activity.
8. How neural laces works
• Inserting a neural lace involve injecting a biocompatible polymer scaffold
mesh with attached microelectronic devices into the brain via syringe.
• When the mesh leaves the needle it unravels, spanning the brain as the
blood flows through the brain.
• If the mesh is inserted, accepted by the brain and will even move with it as
it grows or very slightly changes size.
• The brain would essentially be able to wirelessly connect to a computer,
providing an interface between your brain and a computer.
9. • Lieber’s team has demonstrated this in live mice and verified continuous
monitoring and recordings of brain signals on 16 channels.
• Electronic mesh was injected in two parts of their brain: the lateral ventricle and
the hippocampus.
• Over the course of five weeks, the mice’s immune system seemed to accept the
new electronics, moreover, even signs of merging with the healthy biological
neurons.
• Mesh-brain implants continued to enable neuronal recordings for at least eight
months, according to their followup report, with limited observable health impact
for the hosts.
10. What can neural lace be used for?
• Could treat neurodegenerative disorders such as Parkinson’s disease
and other life-altering brain disorders.
• Help people with missing limbs use 'connected' artificial body parts
unassisted, using only brain power.
• Neural lace could be used by the US military, via the US Air Force’s
Cyborg cell programme, 'which focuses on small-scale electronics for
the performance enhancement of cells'.