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People Read Facial Expressions Differently

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Credit: Lydia Polimeni, NIH

What do you see in the faces above? We constantly make assumptions about what others are feeling based on their facial expressions, such as smiling or frowning. Many have even suggested that human facial expressions represent a universal language. But an NIH-funded research team recently uncovered evidence that different people may read common facial expressions in surprisingly different ways.

In a study published in Nature Human Behaviour, the researchers found that each individual’s past experience, beliefs, and conceptual knowledge of emotions will color how he or she interprets facial expressions [1]. These findings are not only fascinating, they might lead to new ways to help people who sometimes struggle with reading social cues, including those with anxiety, depression, bipolar disorder, schizophrenia, or autism spectrum disorder.


Study Shows Genes Unique to Humans Tied to Bigger Brains

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cortical organoid

Caption: Cortical organoid, showing radial glial stem cells (green) and cortical neurons (red).
Credit: Sofie Salama, University of California, Santa Cruz

In seeking the biological answer to the question of what it means to be human, the brain’s cerebral cortex is a good place to start. This densely folded, outer layer of grey matter, which is vastly larger in Homo sapiens than in other primates, plays an essential role in human consciousness, language, and reasoning.

Now, an NIH-funded team has pinpointed a key set of genes—found only in humans—that may help explain why our species possesses such a large cerebral cortex. Experimental evidence shows these genes prolong the development of stem cells that generate neurons in the cerebral cortex, which in turn enables the human brain to produce more mature cortical neurons and, thus, build a bigger cerebral cortex than our fellow primates.

That sounds like a great advantage for humans! But there’s a downside. Researchers found the same genomic changes that facilitated the expansion of the human cortex may also render our species more susceptible to certain rare neurodevelopmental disorders.


Teaching Computers to “See” the Invisible in Living Cells

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Brain Cell Analysis

Caption: While analyzing brain cells, a computer program “thinks” about which cellular structure to identify.
Credit: Steven Finkbeiner, University of California, San Francisco and the Gladstone Institutes

For centuries, scientists have trained themselves to look through microscopes and carefully study their structural and molecular features. But those long hours bent over a microscope poring over microscopic images could be less necessary in the years ahead. The job of analyzing cellular features could one day belong to specially trained computers.

In a new study published in the journal Cell, researchers trained computers by feeding them paired sets of fluorescently labeled and unlabeled images of brain tissue millions of times in a row [1]. This allowed the computers to discern patterns in the images, form rules, and apply them to viewing future images. Using this so-called deep learning approach, the researchers demonstrated that the computers not only learned to recognize individual cells, they also developed an almost superhuman ability to identify the cell type and whether a cell was alive or dead. Even more remarkable, the trained computers made all those calls without any need for harsh chemical labels, including fluorescent dyes or stains, which researchers normally require to study cells. In other words, the computers learned to “see” the invisible!


Creative Minds: Mapping the Biocircuitry of Schizophrenia and Bipolar Disorder

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Bruce Yankner

Bruce Yankner

As a graduate student in the 1980s, Bruce Yankner wondered what if cancer-causing genes switched on in non-dividing neurons of the brain. Rather than form a tumor, would those genes cause neurons to degenerate? To explore such what-ifs, Yankner spent his days tinkering with neural cells, using viruses to insert various mutant genes and study their effects. In a stroke of luck, one of Yankner’s insertions encoded a precursor to a protein called amyloid. Those experiments and later ones from Yankner’s own lab showed definitively that high concentrations of amyloid, as found in the brains of people with Alzheimer’s disease, are toxic to neural cells [1].

The discovery set Yankner on a career path to study normal changes in the aging human brain and their connection to neurodegenerative diseases. At Harvard Medical School, Boston, Yankner and his colleague George Church are now recipients of an NIH Director’s 2016 Transformative Research Award to apply what they’ve learned about the aging brain to study changes in the brains of younger people with schizophrenia and bipolar disorder, two poorly understood psychiatric disorders.


Creative Minds: Modeling Neurobiological Disorders in Stem Cells

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Feng Zhang

Feng Zhang

Most neurological and psychiatric disorders are profoundly complex, involving a variety of environmental and genetic factors. Researchers around the world have worked with patients and their families to identify hundreds of possible genetic leads to learn what goes wrong in autism spectrum disorder, schizophrenia, and other conditions. The great challenge now is to begin examining this growing cache of information more systematically to understand the mechanism by which these gene variants contribute to disease risk—potentially providing important information that will someday lead to methods for diagnosis and treatment.

Meeting this profoundly difficult challenge will require a special set of laboratory tools. That’s where Feng Zhang comes into the picture. Zhang, a bioengineer at the Broad Institute of MIT and Harvard, Cambridge, MA, has made significant contributions to a number of groundbreaking research technologies over the past decade, including optogenetics (using light to control brain cells), and CRISPR/Cas9, which researchers now routinely use to edit genomes in the lab [1,2].

Zhang has received a 2015 NIH Director’s Transformative Research Award to develop new tools to study multiple gene variants that might be involved in a neurological or psychiatric disorder. Zhang draws his inspiration from nature, and the microscopic molecules that various organisms have developed through the millennia to survive. CRISPR/Cas9, for instance, is a naturally occurring bacterial defense system that Zhang and others have adapted into a gene-editing tool.


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