magnet brain

MRI of the Fetal Brain

Advancements in MRI are giving us an unprecedented look at the fetal brain.

Until approximately a decade ago, what researchers knew about the developing prenatal brain came primarily from analyzing the brains of aborted or miscarried fetuses. But studying postmortem brains can be confounding because scientists can’t definitively pinpoint whether the injuries to the brain occurred before or during birth. 

Over the years, however, improvements to MRI are finally enabling researchers to study the developing brain in real time. With these advancements, researchers are just beginning to understand how normal brains develop, and how abnormalities can manifest over the course of development. Scientists cataloguing typical infant brain development with the mini-MRI hope to use it eventually to study the brains of premature babies, who have a high risk of brain damage. Ultimately, clinicians hope to intervene early with therapies, if available and approved, to prevent developmental disorders when there are signs of brain damage in utero or shortly after birth.

Read more here in Nature Medicine. 

The Morphogenic Field is a term we use to describe the field of energy around the body. It is an extension of the electrical energy of the nervous system. The brain is an electrical generator with its own field of energy that extends away from the physical body. Many cultures and disciplines recognize this field and give it other names. When people discuss auras, chakras, life force or chi, they are possibly talking about this same energy field.

So there’s loads of different neuroimaging methods out there that are used depending on what it is you’re looking for! I’ve had the privilege of actually studying it and there’s so so many different types more than just functional MRI that people don’t really know about so here are a few and what they’re used for an how they work.

MRI - Magnetic Resonance Imaging

The most commonly used form of neuroimaging and for good reason. MRI uses the body’s tissue density and magnetic properties of water to visualise structures within the body. It has really incredible spatial and temporal quality and is predominantly used in neuroscience/neurology for looking for any structural abnormalities such as tumours, tissue degeneration etc. It’s fantastic a fantastic form of imaging and is used in numerous amounts of research.

Functional MRI (fMRI)

These images are captured the same way as MRI but the quality is a little bit lower because the aim is to capture function (those blobs you can see) as quickly and accurately as possible so the quality is compromised a little bit. Nonetheless, fMRI usually uses the BOLD response to measure function. It measures the amount of activity in different areas of the brain when doing certain things, so during a memory test for example, and it does that by measuring the amount oxygen that a certain area requires. The increased oxygen is believed to be sent to an area where there is more neuronal activity, so it’s not a direct measurement but rather we’re looking at a byproduct. There are numerous studies trying to find the direct link between the haemodynamic response and neuronal activity, particularly at TUoS (where I’m doing my masters!) but for the moment this is all we have. This sort of imaging is used a lot for research and checking the general function of the brain, so if you were to have had surgery on your brain, they may run one of these just to see which areas might be affected from it and how, or in research we’ve used this a lot to research cognition - which areas are affected during certain cognitive tasks (ie my MSc thesis - Cognition in schizophrenia and consanguinity). 

Diffusion Tensor Imaging (DTI)

This is my current favourite type of NI right now! DTI is beautiful, unique and revolutionary in this day and age, it’s almost like sci-fi stuff! DTI measures the rate of water diffusion along white matter tracts and with that calculates the directions and structural integrity of them to create these gorgeous white matter brain maps. They are FANTASTIC for finding structural damage in white matter - something that is making breakthroughs in research lately ie. schizophrenia, genetics and epilepsy. It measures the rate of diffusion which tells you about possible myelin/axonal damage and anisotropy, so the directions and if they are “tightly wound” or loosely put together - think of it like rope, good FA is a good strong rope, poor FA is when it starts to fray and go off in different directions - like your white matter tracts. My current research used DTI and it was honestly surreal to work with, the images are also acquired through an MRI scanner so you can actually get these images the same time you’re getting MRI’s done, functional or otherwise! 

Positron Emission Tomography (PET)

One of the “controversies” (if you could call it that) is the use of radioactive substances in PET scanning. It requires the injection of a nuclear medicine to have the metabolic processes in your brain light up like Christmas! It uses a similar functional hypothesis to BOLD fMRI, in that it is based on the assumption that higher functional areas would have higher radioactivity and that’s why it lights up in a certain way. It depends on glucose or oxygen metabolism, so high amounts of glucose/oxygen metabolism would show up red and less active areas would show up blue, perfect for showing any functional abnormalities in the overall brain. However it has incredibly poor temporal resolution and due to it’s invasive nature, MRI is chosen more often. (The pictures are gorgeous though!) 

Electroencephalography/Magnetoencephalography (EEG & MEG)

These are not “imaging” types in the stereotypical sense. They create a series of waves that you can physically see (think of the lines you get on a lie detector!). Electrodes/Tiny magnets are placed on the scalp/head in specific areas corresponding to certain brain structures. EEG picks up on electrical activity which is the basis of neuronal function, whereas MEG picks up on magnetic fields - the same property that is utilised by MRI. One of the biggest issues with EEG is that deeper structures passing through tissues get distorted, whereas MEG doesn’t because it only measures the magnetic properties. I’ve not had a lot of experience with either of these but I do know EEG is used in a lot of medical procedures to measure brain activity, from measuring seizures and sleep disorders to measuring brain activity in a coma. It’s fantastic and if you can actually figure out how to conduct and interpret results it’s an invaluable tool into looking at electrical activity. 

Actual things said by my dad playing Pokemon Go

“We live in a Pokemon poor village.”

“Look I caught one! It’s a Rat-tat

“Oh wait no it’s a rat-tat-A

“Hakunah Ratata”

“Look that dumpster’s a Pokemon!”

“I think that ladies a Pokemon”

Zoobat if that even is your real name” (it was not)

“HE’S DODGING”

“Pinche Zoobat”

“I wasted like six balls on that bat”

“Look I caught one it’s a Red Bird

“Oh wait no it’s a Pigeoto”

“Look at that dude thinking he’s so tough”

“I need to put him in his place”

“Once I’m level five”

“Alas I am level three still”

“Ok I got two, this one’s a poisonous bug. A weed bug.”

“This one has a magnet in his brain.”

Bonus:”Your mom married me because she thought I was serious.”

Brain scan method may help detect autism

Many doctors and scientists think they could improve the diagnosis and understanding of autism spectrum disorders if they had reliable means to identify specific abnormalities in the brain. Such “biomarkers” have proven elusive, often because methods that show promise with one group of patients fail when applied to another. In a new study in Nature Communications, however, scientists report a new degree of success. Their proposed biomarker worked with a comparably high degree of accuracy in assessing two diverse sets of adults.

(Image caption: Crucial connections A map of the brain connections that proved useful in distinguishing patients diagnosed with autism from people without an autism diagnosis)

The technology, principally developed at the Advanced Telecommunications Research Institute International in Kyoto, Japan, with the major contributions from three co-authors at Brown University, is a computer algorithm called a “classifier” because it can classify sets of subjects – those with an autism spectrum disorder and those without – based on functional magnetic resonance imaging (fMRI) brain scans. By analyzing thousands of connections of brain network connectivity in scores of people with and without autism, the software found 16 key interregional functional connections that allowed it to tell, with high accuracy, who had been traditionally diagnosed with autism and who had not. The team developed the classifier with 181 adult volunteers at three sites in Japan and then applied it in a group of 88 American adults at seven sites. All the study volunteers with autism diagnoses had no intellectual disability.

“It is the first study to [successfully] apply a classifier to a totally different cohort,” said co-corresponding author Yuka Sasaki, a research associate professor of cognitive, linguistic and psychological sciences at Brown. “There have been numerous attempts before. We finally overcame the problem.”

The classifier, which blends two machine-learning algorithms, worked well in each population, averaging 85 percent accuracy among the Japanese volunteers and 75 percent accuracy among the Americans. The researchers calculated that the probability of seeing this degree of cross-population performance purely by chance was 1.4 in a million.

“These results indicate that although we developed a highly reliable classifier using the training data only in Japan, it is sufficiently universal to classify [autism] in the U.S.A. validation cohort,” wrote the team of clinicians and basic researchers led by Mitsuo Kawato of ATR.

Further validation

In another way of validating the classifier, the researchers asked whether the differences it notes in the 16 connections were predictive not only of whether a person had an autism diagnosis at all, but whether they relate to performance on the main diagnostic method currently available to clinicians, the Autism Diagnostic Observation Schedule. ADOS is based not on markers of biology or physiology, but instead on a doctor’s interviews and observations of behavior. The classifier was able to predict scores on the ADOS communications component with a statistically significant correlation of 0.44.

The correlation suggests that the 16 connections identified by the classifier relate to attributes of importance in ADOS. When the researchers examined where these 16 connections are and what brain networks they affect, they found that 41 percent of the specific brain regions in which the 16 connections reside belonged within the cingulo-opercular network, which matters to brain functions such as conceiving of other people, face processing and emotional processing. Difficulties with such social and emotional perception tasks are important symptoms in autism spectrum disorders.

Finally, the team looked to see whether the classifier appropriately reflects the similarities and differences between autism spectrum disorders and other psychiatric conditions. Autism, for example, is known to share some similarities with schizophrenia but not with depression or attention deficit hyperactivity disorder, as indicated by a previous genome study. Applied to patients with each of these other disorders compared to similar people without the conditions, the classifier showed moderate but statistically significant accuracy in distinguishing schizophrenia patients, but not depression or ADHD patients.

Eventual clinical usefulness?

The MRI scans required to gather the data were simple, Sasaki said. Subjects only needed to spend about 10 minutes in the machine and didn’t have to perform any special tasks. They just had to stay still and rest.

Despite that simplicity and even though the classifier performed unprecedentedly well as a matter of research, Sasaki said, it is not yet ready to be a clinical tool. While the future may bring that development, refinements will be necessary first.

“The accuracy level needs to be much higher,” Sasaki said. “Eighty percent accuracy may not be useful in the real world.”

It’s also not clear how it would work among children, as the volunteers in this study were all adults.

But if the classifier’s accuracy can be improved further, the researchers hope that it can be used not only as a physiology-based diagnostic tool but also for monitoring treatment. Doctors perhaps will be able to use the tool someday to monitor whether therapies produce changes in brain connectivity, Sasaki said.

Ways of studying the brain

Post Mortem studies

Studying the brain after death, allows us to discover underlying neurobiology and explain a pre-death disorder 

  • Falkai: used to learn more about schizophrenia: more dopamine in the amygdala
  • HM: related hippocampus to memory
  • Phineas Gage: showed frontal lobe is linked to personality

Evaluation:

  • Cause of death could change the brain anyway
  • Retrospective: no chance for follow up questions
  • Allows for detail as deep regions are examined
  • Integral to add to our understanding of schizophrenia and memory

FMRI scans

Functional magnetic resonance imaging

  • Detects changes in blood oxygenation flow which sugests indreased enuronal activity
  • Measures activity while a specific task is being carried out, indicating the structure and function of the brain:
    • Structure: magnetic field picks up hydrogen molecule activity, of which there is different amounts in different tissues
    • Function: oxygen in blood flow, more active= more blood= more oxygen: indicative of increased activity

Evaluation:

  • Overlooks networks of communication, only looking at localised areas
  • Not a direct measure of neural activity: measure blood flow and assume this means activity
  • Physical images allow for inter-rater reliability, objective judgements and reliable conclusions
  • Non-invasive

Electroencephalogram (EEG)

  • 20 electrodes attached to the scalp to monitor electrical activity
  • Activity plotted on a graph to be examined by a neuropsychologist
  • Allows for diagnosis and monitoring of disorders such as epilepsy, dementia, and brain tumors 
    • Beta:REM: sleepy
    • Alpha: relaxed, sleepy
    • Theta: asleep
    • Delta: deep sleep

Evaluation:

  • Doesn’t look at what is happening in the deeper regions of the brain such as the hippocampus
  • Can’t pinpoint the source of activity, can only say it comes from a general area
  • Examines in real time rather than producing a still image for later inspection
  • Useful in clinical diagnoses

Event-Related Potential (ERP)

Measurement of cognitive processing to a specific stimuli

  • Measures a sequence of stimui multiple times, then averages out readings to get rid of any unusual spikes
    • within first 100 ms: sensory
    • after 100 ms: cognitive processing

Evaluation:

  • Lots of trials needed to gather information
  • Only examines neocortex, nothing within the brain
  • Measures changes in relation to experimental manipulation
  • Even when there is no behavioural response, cognitive processing can still be measured
vimeo

RESONANCE is a sensational eye opening documentary which reveals the harm we are doing by existing in an ocean of man made wireless frequencies.

Two billion years ago life first arrived on this planet; a planet, which was filled with a natural frequency. As life slowly evolved, it did so surrounded by this frequency. and Inevitably, it began tuning in.

By the time mankind arrived on earth an incredible relationship had been struck; a relationship that science is just beginning to comprehend.

Research is showing that being exposed to this frequency is absolutely integral to us. It controls our mental and physical health, it synchronizes our circadian rhythms, and it aids our immune system and improves our sense of wellbeing.

Not only are we surrounded by natural frequencies, our bodies are filled with them too. Our cells communicate using electro magnetic frequencies. Our brain emits a constant stream of frequencies and our DNA delivers instructions, using frequency waves. Without them we couldn’t exist for more than a second.

This delicate balance has taken billions of years to perfect. But over the last 25 years the harmony has been disturbed. and disturbed dramatically.

Mankind has submerged itself in an ocean of artificial frequencies. They are all around us, filling the air and drowning out the earth’s natural resonance.

To the naked eye the planet appears to be the same. But at a cellular level it is the biggest change that life on earth has endured; the affects of which we are just starting to see and feel.

Genetic Engineering, Nanotechnology & Magnets Combine For Potential Neurological Disorder Treatment

This gif shows two sets of living neurons, the cells that make up the brain, spinal cord and nervous system. They were recorded using a method that makes them glow when they are working and doing their neuron thing. 

The ones on the left are your regular, old-fashioned neurons occasionally receiving, processing and sending information through electrical and chemical signals. The ones on the right were first augmented to produce heat-sensitive proteins by inserting genes into their DNA. Then researchers injected the re-engineered neurons with nanoscopically small magnetic particles of iron oxide. Finally, someone turned on a magnet.

MIT scientists who did the work found that they could remotely stimulate brain tissue by exciting the nanoparticles through magnetic fields. The energy causes the iron oxide to rapidly heat, which activates the neuron by triggering the engineered heat-sensitive proteins within the cell, the team says. 

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