Category: human brain

Researchers Reveal the Human Brain Remembers Visual Features Backwards

Rethinking How the Human Brain Remembers

New research from scientists at the Zuckerman Institute of Columbia University has turned our classical understanding of the way the human brain perceives and recalls on its head. The work shows that when the brain observes it first processes details to construct internal models of more complex objects. However, when it recalls, the brain first thinks of those complex representational models, and then goes back to the details it first perceived to create them. The research relied upon Bayes theorem and other mathematical modeling, and may have practical applications in many places — from evaluating testimony in the courtroom to treating people with sensory processing differences such as those with autism.

Lacking direct evidence, scientists have always assumed that perception and decoding followed the same hierarchy: from details to complex objects. This research proves that this assumption was incorrect as to the decoding process that takes place during recall.

The team unraveled the decoding hierarchy of the human brain by focusing on simple recall tasks that could be clearly interpreted. In the first task, subjects had half a second to view a line angled at 50 degrees on a computer screen. After it disappeared, they moved two dots on the screen to approximate the angle they remembered, and repeated this task 50 times. The second task was identical, except the angle of the line was 53 degrees. In the third task, the subjects saw both lines at the same time, and then tried to match pairs of dots to each angle.

 

Image Credit: Ning Qian/Columbia University, Zuckerman Institute
Image Credit: Ning Qian/Columbia University, Zuckerman Institute

“Memories of exact angles are usually imprecise, which we confirmed during the first set of one-line tasks. So, in the two-line task, traditional models predicted that the angle of the 50-degree line would frequently be reported as greater than the angle of the 53-degree line,” Mortimer B. Zuckerman Mind Brain Behavior Institute neuroscientist and study principal investigator Ning Qian said in a press release. However, that wasn’t what happened, and several other findings also contrasted with traditional models.

Explaining the Process

The authors proposed that context is more important than details are in everyday life, so reverse decoding makes sense. For example, when we see a new face, their expression — such as anger or friendliness — is what really matters, and we only focus on details such as the shape of their features later, if need be, and we do so by estimating. “Even your daily experience shows that perception seems to go from high to low levels,” Dr. Qian said in the press release.

The Evolution of Brain-Computer Interfaces [INFOGRAPHIC]
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The team then created a mathematical model to explain what they believe happens in the brain using Bayesian inference, with the higher-level complex features as the prior information in the statistical model for decoding lower-level features, rather than the details being used to decode or recall the bigger picture. The model’s predictions were a good fit for the behavioral data.

Moving forward, the researchers plan to apply their work in studies of long-term memory, not just simple perception. This could have major implications in many areas, from assessing the credibility of witnesses in court and treating people with sensory processing issues to assessing the credibility of presidential candidates. It could even help computer scientists study the progression of microchips that rival the power of the human brain, as they begin to possess similar perceptual acuity.

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Researchers Discover New Vessel System in the Human Brain

Exploring the Human Brain

The human brain is a complicated organ that’s difficult to understand, so it’s only natural that we always have more to learn. But recently, researchers at the U.S. National Institute of Neurological Disorders and Stroke published images of a previously undocumented system of vessels that are part of the lymphatic system in the brain. That’s right, up until this very moment many weren’t even positive that these vessels, which transport fluids critical to metabolic and inflammatory processing, existed at all.

Up until the present, not only were these deep-purple vessels largely unheard of, most doctors have been taught that the skull contains no lymphatic vessels. This previous notion however existed in complete contradiction with how the rest of the body works. The lymphatic system both collects and drains fluids, removing waste, facilitating infection response and inflammation, and so much more. In-the-know about the necessity of the lymphatic system of the human brain, it feels like an absurdity in retrospect to think that somehow our brains would not work with the lymphatic system.

3D rendering of human dural lymphatics. Image Credit: National Institute of Neurological Disorders and Stroke

Undiscovered Human Biology

About this finding, Senior Investigator Daniel Reich stated that “The discovery of the central-nervous-system lymphatic system may call for a reassessment of basic assumptions in neuroimmunology.” In other words, while this is a major discovery, it could lead to other, greater discoveries in the exploration of our own biology.

In 2015, researchers discovered the “glymphatic system,” or fluids that were found in the brains of both humans and mice that could transport things like glucose and lipids. But at the time, they didn’t know how these fluids might connect and communicate with the rest of the body. This most recent discovery bridges that knowledge gap.

Because these vessels were so unknown, the initial reaction to this discovery varied, from, in Reich’s words, “No way, it’s not true,” to “Yeah, we’ve known that.”

But this discovery doesn’t just identify this system of vessels, it explores how it operates and just how complex and intricate it is. “The study shows that these vessels exist. We haven’t shown that they’re involved in any disease process,” Reich carefully worded, “but it’s reasonable to think that they might be.”

As we explore the far reaches of the Universe and stretch our knowledge far beyond our modest, planet-bound selves, it’s surprising to learn that we still have so much to learn about our own bodies. With this discovery, it is possible that there “is a connection between [the] two systems, glymphatic and lymphatic,” according to Reich. When a discovery this major is made, it creates a well of new questions about the human condition that no one ever suspected await our attention.

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A New Study Reveals How the Brain “Sees” Faces

How Our Brains “See”

It’s common knowledge that our vision is determined by how our eyes takes in light and color, sending these stimuli as signals to the brain, which are then processed and rendered into an image. But how exactly does the brain process what the eyes pick up into composite images? A study by researchers from the California Institute of Technology is the first to provide a full and simple explanation of how this process works, and they started by examining how the brain recognizes human faces.

“We’ve cracked the brain’s code for facial identity,” author Doris Tsao from CalTech told New Scientist. Their study, published in the journal Cell, looked at face-recognition function in the brains of macaque monkeys.

They identified individual brain cells that work together to create an infinite range of facial images by encoding 50 different dimensions of a face, such as its shape, the size of and distances between eyes, skin texture, and other features. By inserting electrodes into three patches of these so-called “face cells” in the brains of the macaques, Tsao and colleague Steven Le Chang were able to record the activity of 205 neurons.

Image credit: Doris Tsao/Cell
Image credit: Doris Tsao/Cell

The Brain’s Imaging Powers

By showing 2,000 images of human faces to the macaques, they discovered that each face cell’s view of the face was different, but when combined, a clear composite image was produced. In order to see what these monkeys saw, the researchers developed an algorithm that tracked the face cell feedback in their brains.

This discovery could extend to research into how the brain retains memories of facial images and associates these with specific individuals. Previous work by researchers from the Allen Institute for Brain Science have identified individual cells in the hippocampus, the brain’s memory center, responsible for remembering the faces of people — the so-called “Jennifer Aniston cells.”

“Tsao’s work provides the first specific hypothesis for how the response of face cells in the cortex can be utilized by cells in the hippocampus to form memories of individuals we’ve seen before,” Ueli Rutishauser, from the Cedars-Sinai Medical Center, told New Scientist.

The study could also provide insight into how the brain forms other images, too: “Our work suggests that other objects could be encoded by analogous metric coordinate systems,” the authors wrote.

Another potential application of the research into how the brain processes memories of people’s faces would be in the development of treatments for memory-related diseases, such as Alzheimer’s. The applications could extend beyond humans, too: such work could also help to improve the image recognition abilities of artificial neural networks.

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Our Brains May be 100 Times More Powerful Than We Thought

The human brain is so powerful that some intelligent computers called neural networks are patterned after how the human brain works. As such, figuring out how the many processes of the brain work continues to be the subject of much research.

A recent study published in the journal Science by a team of researchers from the University of California Los Angeles (UCLA) has uncovered new information about the brain’s inner workings, and it could change our understanding of how learning happens.

Our Brains May be 100 Times More Powerful Than We Thought
Credit: sydney g / Flickr

The study focused on a particular part of neurons, called dendrites. Dendrites are long and branch-like structures that connected to the roundish cell body, called the soma. Dendrites were thought to serve only as conduits that transfer spikes of electrical activity from the cell body to other neurons. The UCLA study, however, found that dendrites may actually be generating their own electrical spikes — and at rates 10 times more frequently than previously thought.

The researchers arrived at this conclusion by studying mice. Instead of implanting electrodes into dendrites themselves, they put them next to dendrites. They found that dendrites were five times more active than somas when the rats were asleep, and 10 times more when awake and exploring.

Understanding the Brain

“A fundamental belief in neuroscience has been that neurons are digital devices. They either generate a spike or not,” said Mayank Mehta, the study’s senior author, in a UCLA press release. “These results show that the dendrites do not behave purely like a digital device. Dendrites do generate digital, all-or-none spikes, but they also show large analog fluctuations that are not all or none. This is a major departure from what neuroscientists have believed for about 60 years.”

Since dendrites are estimated to make up more than 90 percent of neural tissue — about 100 times larger in volume compared to somas — this could mean that the human brain has 100 times more capacity then previously believed.

Reprogramming the Human Mind: Here’s How We’ll Make Humanity 2.0 [INFOGRAPHIC]
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Ultimately, this research could help medical professionals develop new ways to treat neurological disorders. The study may also shed a new light how learning really occurs.

“Many prior models assume that learning occurs when the cell bodies of two neurons are active at the same time,” explained author Jason Moore in the press release. “Our findings indicate that learning may take place when the input neuron is active at the same time that a dendrite is active — and it could be that different parts of dendrites will be active at different times, which would suggest a lot more flexibility in how learning can occur within a single neuron.”

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