Psychology Researchers Map Neurological Process Of Learning, Deciding

Scientists at The University of Texas at Austin can now map what happens neurologically when new information influences a person to change his or her mind, a finding that offers more insight into the mechanics of learning.


The study, which was published Nov. 1 in the Proceedings of the National Academy of Sciences, examined how dynamic shifts in a person’s knowledge are updated in the brain and impact decision making.

“At a fundamental level, it is difficult to measure what someone knows,” said co-author and psychology associate professor Alison Preston. “In our new paper, we employ brain decoding techniques that allow us deeper insight into the knowledge people have available to make decisions. We were able to measure when a person’s knowledge changes to reflect new goals or opinions.”

The process, researchers said, involves two components of the brain working together to update and “bias” conceptual knowledge with new information to form new ideas.

“How we reconcile that new information with our prior knowledge is the essence of learning. And, understanding how that process happens in the brain is the key to solving the puzzle of why learning sometimes fails and how to put learning back on track,” said the study’s lead author Michael Mack, who was a postdoctoral researcher in the Center for Learning & Memory.

In the study, researchers monitored neural activity while participants learned to classify a group of images in two different ways. First participants had to learn how to conceptualize the group of images, or determine how the images were similar to each other based on similar features. Once they grouped the images, participants were then asked to switch their attention to other features within the images and group them based on these similarities instead.

“By holding the stimuli constant and varying which features should be attended to across tasks, the features that were once relevant become irrelevant, and the items that were once conceptually similar may become very different,” said Preston, who holds a joint faculty appointment in neuroscience.

For example, the researchers report that many Americans may have chosen their preferred presidential candidate many months ago based on political platforms or core issues. But as the election cycle continued, voters were presented with new information, influencing some to change their perspectives on the candidates and, potentially, their votes.

This requires rapid updating of conceptual representations, a process that occurs in the hippocampi (HPC) — two seahorse-shaped areas near the center of the brain responsible for recording experiences, or episodic memory — researchers said. It’s also one of the first areas to suffer damage in Alzheimer’s disease.

According to the study, the prefrontal cortex (PFC) — the front part of the brain that orchestrates thoughts and actions — tunes selective attention to relevant features and compares that information with the existing conceptual knowledge in the HPC, updating the organization of items based on the new relevant features, researchers said.

“Looking forward, our findings place HPC as a central component of cognition — it is the brain’s code builder. I think these findings will motivate future research to consider the more general-purpose function of the hippocampus,” said Mack, who is now an assistant professor of psychology at the University of Toronto. “For example, understanding how we dynamically update conceptual knowledge may be essential to understanding how biases and prejudices are coded into our views of other people.”

These findings add to the growing, though limited, body of literature on the function of the HPC beyond episodic memory by providing direct evidence of its role, in concert with the PFC, in building conceptual knowledge.

“With an understanding of the mechanics of learning, we can develop educational practices and training protocols that optimally engage the brain’s learning circuits to build lasting knowledge,” Mack said.

Measuring Forces In The DNA Molecule

DNA, our genetic material, normally has the structure of a twisted rope ladder. Experts call this structure a double helix. Among other things, it is stabilized by stacking forces between base pairs. Scientists at the Technical University of Munich (TUM) have succeeded at measuring these forces for the very first time on the level of single base pairs. This new knowledge could help to construct precise molecular machines out of DNA.


Over 60 years ago, the researchers Crick and Watson identified the structure of deoxyribonucleic acid, which is more commonly known as DNA. They compared the double helix to a rope ladder that had been twisted into a spiral. The rungs of this ladder consisted of guanine/cytosine and thymine/adenine base pairs. But what keeps the DNA strands in that spiral structure?

Special measuring system for molecular interactions

Prof. Hendrik Dietz from the Chair of Experimental Biophysics uses DNA as construction material to create molecular structures. Hence, he is greatly interested in gaining a better understanding of this material. “There are two types of interactions which stabilize double helices,” he explains. For one, DNA contains hydrogen bonds.

For another, there are what experts call base pair stacking forces, which act between the stacked base pairs along the spiral axis. The forces of the hydrogen bonds, on the other hand, act perpendicular to the axis. “So far, it is not quite clear to which extent these two forces each contribute to the overall stability of the DNA double helix,” explains Dietz.

Directly measuring the weak stacking forces between base pairs was a big technical challenge for the researchers, who worked on the problem for six years. In collaboration with the TUM Chair of Molecular Biophysics (Prof. Matthias Rief) and the TUM Chair of Theoretical Biophysics — Biomolecular Dynamics (Prof. Martin Zacharias), they succeeded in developing a special experimental setup that now makes it possible to measure extremely weak contact interactions between individual molecules.

A trillionth of a bar of chocolate

To put it simply, the measurement system is designed hierarchically and involves microscopic beams, at the tips of which one or more double helix structures running in parallel are located. These have been modified such that each end carries one base pair. Two of these microscopic beams are connected with a flexible polymer. On the other side, the beams are coupled to microscopic spheres which can be pulled apart using optical laser tweezers. In solution, the base pairs on the end of one of the beam can now interact with the base pairs on the end of the other beam. This also makes it possible to measure how long a stacking bond between them lasts before they fall apart again, as well as the force acting between the base pairs.

The forces measured by the researchers were in the range of piconewtons. “A newton is the weight of a bar of chocolate,” explains Dietz. “What we have here is a thousandth of a billionth of that, which is practically nothing.” Forces in the range of two piconewtons are sufficient to separate the bond created by stacking forces.

Furthermore, the scientists also observed that the bonds spontaneously broke up and formed again within just a few milliseconds. The strength and the lifetime of the interactions depends to a great extent on which base pairs are stacked on each other.

Creating DNA machines

The results of the measurements may help to better understand mechanical aspects of fundamental biological processes such as DNA replication, i.e. the reproduction of genetic material. For example, the short life of the stacking interactions could mean that an enzyme tasked with separating the base pairs during this process just needs to wait for the stacking bonds break up on their own — instead of having to apply force to separate them.

However, Dietz also intends to apply the data directly to his current research: He uses DNA as programmable building material to construct machines on the order of nanometers. When doing so, he draws inspiration from the complex structures which can e.g. be found in cells and, among other things, serve as molecular “factories” to synthesize important compounds such as ATP, which stores energy. “We now know what would be possible if we could just build structures that were sufficiently sophisticated,” says Dietz. “Naturally, when we have a better understanding of the properties of the molecular interactions, we are better able to work with these molecules.”

At the moment, the lab is building a molecular rotational motor out of DNA, the components of which interlock and are held together via stacking forces. The goal is to be able to control a directed rotation via chemical or thermal stimuli. To do so, the timing of the movement of the rotor in the stator is crucial, and this task has now been made significantly easier with the new findings on the stacking forces.

How The Brain Builds Panoramic Memory

When asked to visualize your childhood home, you can probably picture not only the house you lived in, but also the buildings next door and across the street. MIT neuroscientists have now identified two brain regions that are involved in creating these panoramic memories.


These brain regions help us to merge fleeting views of our surroundings into a seamless, 360-degree panorama, the researchers say.

“Our understanding of our environment is largely shaped by our memory for what’s currently out of sight,” says Caroline Robertson, a postdoc at MIT’s McGovern Institute for Brain Research and a junior fellow of the Harvard Society of Fellows. “What we were looking for are hubs in the brain where your memories for the panoramic environment are integrated with your current field of view.”

Robertson is the lead author of the study, which appears in the Sept. 8 issue of the journal Current Biology. Nancy Kanwisher, the Walter A. Rosenblith Professor of Brain and Cognitive Sciences and a member of the McGovern Institute, is the paper’s lead author.

Building memories

As we look at a scene, visual information flows from our retinas into the brain, which has regions that are responsible for processing different elements of what we see, such as faces or objects. The MIT team suspected that areas involved in processing scenes — the occipital place area (OPA), the retrosplenial complex (RSC), and parahippocampal place area (PPA) — might also be involved in generating panoramic memories of a place such as a street corner.

If this were true, when you saw two images of houses that you knew were across the street from each other, they would evoke similar patterns of activity in these specialized brain regions. Two houses from different streets would not induce similar patterns.

“Our hypothesis was that as we begin to build memory of the environment around us, there would be certain regions of the brain where the representation of a single image would start to overlap with representations of other views from the same scene,” Robertson says.

The researchers explored this hypothesis using immersive virtual reality headsets, which allowed them to show people many different panoramic scenes. In this study, the researchers showed participants images from 40 street corners in Boston’s Beacon Hill neighborhood. The images were presented in two ways: Half the time, participants saw a 100-degree stretch of a 360-degree scene, but the other half of the time, they saw two noncontinuous stretches of a 360-degree scene.

After showing participants these panoramic environments, the researchers then showed them 40 pairs of images and asked if they came from the same street corner. Participants were much better able to determine if pairs came from the same corner if they had seen the two scenes linked in the 100-degree image than if they had seen them unlinked.

Brain scans revealed that when participants saw two images that they knew were linked, the response patterns in the RSC and OPA regions were similar. However, this was not the case for image pairs that the participants had not seen as linked. This suggests that the RSC and OPA, but not the PPA, are involved in building panoramic memories of our surroundings, the researchers say.

Priming the brain

In another experiment, the researchers tested whether one image could “prime” the brain to recall an image from the same panoramic scene. To do this, they showed participants a scene and asked them whether it had been on their left or right when they first saw it. Before that, they showed them either another image from the same street corner or an unrelated image. Participants performed much better when primed with the related image.

“After you have seen a series of views of a panoramic environment, you have explicitly linked them in memory to a known place,” Robertson says. “They also evoke overlapping visual representations in certain regions of the brain, which is implicitly guiding your upcoming perceptual experience.”

Fix For 3-Billion-Year-Old Genetic Error Could Dramatically Improve Genetic Sequencing

For 3 billion years, one of the major carriers of information needed for life, RNA, has had a glitch that creates errors when making copies of genetic information. Researchers at The University of Texas at Austin have developed a fix that allows RNA to accurately proofread for the first time. The new discovery, published June 23 in the journal Science, will increase precision in genetic research and could dramatically improve medicine based on a person’s genetic makeup.


Certain viruses called retroviruses can cause RNA to make copies of DNA, a process called reverse transcription. This process is notoriously prone to errors because an evolutionary ancestor of all viruses never had the ability to accurately copy genetic material.

The new innovation engineered at UT Austin is an enzyme that performs reverse transcription but can also “proofread,” or check its work while copying genetic code. The enzyme allows, for the first time, for large amounts of RNA information to be copied with near perfect accuracy.

“We created a new group of enzymes that can read the genetic information inside living cells with unprecedented accuracy,” says Jared Ellefson, a postdoctoral fellow in UT Austin’s Center for Systems and Synthetic Biology. “Overlooked by evolution, our enzyme can correct errors while copying RNA.”

Reverse transcription is mainly associated with retroviruses such as HIV. In nature, these viruses’ inability to copy DNA accurately may have helped create variety in species over time, contributing to the complexity of life as we know it.

Since discovering reverse transcription, scientists have used it to better understand genetic information related to inheritable diseases and other aspects of human health. Still, the error-prone nature of existing RNA sequencing is a problem for scientists.

“With proofreading, our new enzyme increases precision and fidelity of RNA sequencing,” says Ellefson. “Without the ability to faithfully read RNA, we cannot accurately determine the inner workings of cells. These errors can lead to misleading data in the research lab and potential misdiagnosis in the clinical lab.”

Ellefson and the team of researchers engineered the new enzyme using directed evolution to train a high-fidelity (proofreading) DNA polymerase to use RNA templates. The new enzyme, called RTX, retains the highly accurate and efficient proofreading function, while copying RNA. Accuracy is improved at least threefold, and it may be up to 10 times as accurate. This new enzyme could enhance the methods used to read RNA from cells.

“As we move towards an age of personalized medicine where everyone’s transcripts will be read out almost as easily as taking a pulse, the accuracy of the sequence information will become increasingly important,” said Andy Ellington, a professor of molecular biosciences. “The significance of this is that we can now also copy large amounts of RNA information found in modern genomes, in the form of the RNA transcripts that encode almost every aspect of our physiology. This means that diagnoses made based on genomic information are far more likely to be accurate. ”

In addition to Ellefson and Ellington, authors include Jimmy Gollihar, Raghav Shroff, Haridha Shivram and Vishwanath Iyer. All are affiliated with the Department of Molecular Biosciences at The University of Texas at Austin.

This research was supported by grants from the Defense Advanced Research Projects Agency, National Security Science and Engineering Faculty Fellows, NASA and the Welch Foundation. A provisional patent was filed on the new sequence of the enzyme.

Scientists Reveal Single-Neuron Gene Landscape of the Human Brain

A team of scientists at The Scripps Research Institute (TSRI), University of California, San Diego (UC San Diego) and Illumina, Inc., has completed the first large-scale assessment of single neuronal “transcriptomes.” Their research reveals a surprising diversity in the molecules that human brain cells use in transcribing genetic information from DNA to RNA and producing proteins.

brain cell

The researchers accomplished this feat by isolating and analyzing single-neuronal nuclei from the human brain, allowing classification of 16 neuronal subtypes in the brain’s cerebral cortex, the “gray matter” involved in thought, cognition and many other functions.

“Through a wonderful scientific collaboration, we found an enormous amount of transcriptomic diversity from cell to cell that will be relevant to understanding the normal brain and its diseases such as Alzheimer’s, Parkinson’s, ALS and depression,” said TSRI Professor and neuroscientist Jerold Chun, who co-led the study with bioengineers Kun Zhang and Wei Wang of UC San Diego and Jian-Bing Fan of Illumina.

The study was published on June 24 in the journal Science.

All the Same

While parts of the cerebral cortex look different under a microscope–with different cell shapes and densities that form cortical layers and larger regions having functional roles called “Brodmann Areas”–most researchers treat neurons as a fairly uniform group in their studies.

“From a tiny brain sample, researchers often make assumptions that obtained information is true for the entire brain,” said Chun.

But the brain isn’t like other organs, Chun explained. There’s a growing understanding that individual brain cells are unique, and a possibility has been that the microscopic differences among cerebral cortical areas may also reflect unique transcriptomic differences–i.e., differences in the expressed genes, or messenger RNAs (mRNAs), which carry copies of the DNA code outside the nucleus and determine which proteins the cell makes.

To better understand this diversity, the researchers in the new study analyzed more than 3,200 single human neurons–more than 10-fold greater than prior publications–in six Brodmann Areas of one human cerebral cortex.

With the help of newly developed tools to isolate and sequence individual cell nuclei (where genetic material is housed in a cell), the researchers deciphered the minute quantities of mRNA within each nucleus, revealing that various combinations of the 16 subtypes tended to cluster in cortical layers and Brodmann Areas, helping explain why these regions look and function differently.

Neurons exhibited anticipated similarities, yet also many differences in their transcriptomic profiles, revealing single neurons with shared, as well as unique, characteristics that likely lead to differences in cellular function.

“Now we can actually point to an enormous amount of molecular heterogeneity in single neurons of the brain,” said Gwendolyn E. Kaeser, a UC San Diego Biomedical Sciences Graduate Program student studying in Chun’s lab at TSRI. Kaeser was co-first author of the study with Blue B. Lake and Rizi Ai of UC San Diego and Neeraj S. Salathia of Illumina.

Many New Questions

Interestingly, some of these differences in gene expression have roots in very early brain development taking place before birth. The researchers found markers on some neurons showing that they originated from a specific region of fetal brain called the ganglionic eminence, which generates inhibitory neurons destined for the cerebral cortex. These neurons may have particular relevance to developmental brain disorders.

The enormous transcriptomic diversity of single neurons was predicted by earlier work from Chun’s laboratory and others showing that the genomes–the DNA–of individual brain cells can be different from cell to cell. In future studies, the researchers hope to investigate how single-neuron DNA and mRNA differs in single neurons, groups and between human brains–and how these may be influenced by factors such as stress, medications or disease.

Additional authors of the study, “Neuronal subtypes and diversity revealed by single-nucleus RNA sequencing of the human brain,” were Yun C. Yung, Julian Wong, Allison Chen and Xiaoyan Sheng of TSRI; Rui Liu, Andre Wildberg, Derek Gao, Ho-Lim Fung and Song Chen of UC San Diego; and Raakhee Vijayaraghavan, Fiona Kaper, Richard Shen and Mostafa Ronaghi of Illumina.

The study was supported by the National Institutes of Health Common Fund Single Cell Analysis Program (1U01MH098977-01) and a Neuroplasticity of Aging Training Grant (5T32AG000216-24).