Information

What differentiates neurons in different parts of the brain?


For example: what makes a neuron in the hippocampus of the brain different from a neuron in, say, the amygdala, or the frontal lobe, or anywhere else in the brain? Do neurons in different parts of the brain have different structures, or are they differentiated solely by location? By "different structure", I mean things like receptors that other neurons don't have and things like that.


During development of the brain neurons undergo several steps of differentiation. They transition from neuronal progenitors to mature neurons, resulting in different types of neurons, characterized most prominently by their primary neurotransmitter. During the differentiation, different genes are expressed, which in research is used to label specific cell types (to e.g. observe their distribution in the brain). Since timing is important in development and neurons migrate to their side of action, later born neurons often display different features than earlier ones. The final differentiation is also dependent on the environment, meaning surrounding cells can influence the outcome.

Not just neurotransmitters, also other surface molecules, types of synapses formed, morphology and many other genetic differences influence neuron function and their diversity. Each brain area has many different neuronal cell types, some are similar between brain areas, while others might be very specific to one area. As an example, there is a microRNA, expressed in only 6 neurons of the nematode worm C. elegans, that is essential for their specific function to sense CO2 by repressing other genes (publication).

Taking the example of your question, here is a paper on the diversity of GABAergic neurons in the amygdala (there are several different types of neurons having the same neurotransmitter but expressing otherwise specific markers, which results in different specific functions in the circuits). The author compares them to GABAergic neurons in the cortex (including hippocampus), where a similar function might be taken over by a different cell type (expression profiles are distinct due to different lineages and environments and can be labeled by different markers).


Parts of the brain and their functions

The brain is one of the most important parts of the human body. Thanks to the brain we can feel and process all the information that reaches our body through the senses. In addition, we must not forget that our thinking and ideas are born in the brain. The brain is integrated into the Central Nervous System and is composed of thousands of neurons that promote the constant mind and body relationship. We can divide the brain according to its four main lobes and according to its functions.

For this reason, in our article today, in Psychology-Online, we want to provide you with more information about the parts of the brain and their functions. In this way, you will be able to understand how our mind works. The brain is present in the most important processes of the human being, for example, in the daily act of breathing, eating, walking


Difference Between H1 and H2 Blockers

The key difference between H1 and H2 blockers is that H1 blockers refer to compounds that inhibit the activity of the H1 histamine receptors that occur throughout the vascular endothelial cells in the heart and central nervous system, while H2 blockers refer to compounds that inhibit the activity of the H2 histamine receptors that mainly occur in the parietal cells of [&hellip]


Similar brains but with differences

That may be why mouse studies don’t always tell the right story.

The most detailed study of its kind has found human brains are remarkably similar to mouse brains. But it also found subtle differences that could explain why many psych drugs that show promise in mouse studies don’t work in people.

The outer layer of the human brain, called the cortex, is a bona fide biological marvel, playing a leading role in thinking, talking, remembering, moving limbs and, for good measure, consciousness.

Such superpowers call for serious kit.

Our brain boasts 16 billion neurons, the cells that relay messages, and a supporting cast of 61 billion other cells that provide neurons with scaffolding, insulation, nutrition and protection from disease.

In all, the human cortex is 1000 times bigger than that of the mouse, a species we parted company with 65 million years ago when our last common ancestor is believed to have lived.

Despite that evolutionary gulf, research led by Ed Lein from the Allen Institute for Brain Science in Seattle, US, has found that we share a surprising amount of brain architecture with our rodent cousins.

The team used a method called single-nucleus RNA-sequencing analysis to pin down gene expression and classify brain cells in a part of the cortex called the middle temporal gyrus.

The brain samples, which came from eight human donors aged 24-66, were removed either post mortem or during a special type of brain surgery done to treat epilepsy.

The result was quite a tally.

The researchers identified a total of 75 brain cell types, of which 24 were excitatory neurons, 45 were inhibitory neurons and six were non-neuronal cells.

Incredibly, that variability carried over when the team analysed the mice brains, with the majority of those cell types having counterparts in the smaller critters.

“Many people would assume that the human brain is more complex than the mouse brain,” says Lein.

“It’s somewhat of a surprise that at least in terms of cellular diversity, that doesn’t seem to be the case.”

But there was also an area of critical contrast.

Even with many neuron types shared, there was a big difference in the spread of receptors for the chemical messenger serotonin, which regulates appetite, memory, thinking and, perhaps most famously, mood. Serotonin is the primary target of the common class of antidepressant drugs known as SSRIs.

It’s an illuminating finding given the large number of drugs, including ones for mental illness, that show promise in mouse studies but just don’t work, or have intolerable side effects when trialled in people.

“[T]hese results help to resolve the paradox of failures in the use of mouse for preclinical studies despite conserved structure across mammals,” the authors write.

By nailing down a more refined list of brain “parts”, the current study may go some way to reversing those failures, according to Joshua Gordon, Director of the National Institute of Mental Health, which supported the study.

“The parts list of the human brain is key. That list allows us to understand what’s different between mice and human beings and what’s similar. The ultimate impact of this understanding will be better treatments for mental illnesses,” says Gordon.

But the results may also push researchers to study animals whose brain connections better mirror those of humans, a shift that would raise its own unique issues.

“The magnitude of differences between human and mouse suggests similar profiling of closely related non-human primates is necessary to study many aspects of human brain structure and function,” the authors conclude.

The study appears in the journal Nature.

Paul Biegler

Paul Biegler is a philosopher, physician and Adjunct Research Fellow in Bioethics at Monash University. He received the 2012 Australasian Association of Philosophy Media Prize and his book The Ethical Treatment of Depression (MIT Press 2011) won the Australian Museum Eureka Prize for Research in Ethics.

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Study Defines Differences Among Brain Neurons That Coincide With Psychiatric Conditions

It’s no surprise to scientists that variety is the very essence of biology, not just the seasoning, but most previous studies of key brain cells have found little variability in a common cell process that involves how genetic information is read and acted on.

The process, called epigenetics, involves chemical or structural “tweaks” to gene activity that don’t affect the underlying genetic code itself, but do affect when and how a gene becomes available to be read for its protein-encoding instructions. When epigenetic changes strike at the wrong time or place, the process turns genes on or off at the wrong time and place, too.

Now, in a new study focusing on four regions of normal human brain tissue, Johns Hopkins scientists have found about 13,000 regions of epigenetic differences between neurons in different brain regions that vary by at least 10 percent. Using whole genome sequencing and computational statistical tools, they also found that the location of those epigenetic changes — covering about 12 million bases in the genome — co-locate with the genetic signal contributing to addictive behavior, schizophrenia and neuroses such as biopolar disorder.

“We believe we have figured out what parts of the neuronal genome are epigenetically different among these four brain regions,” says Andrew Feinberg, M.D., the Bloomberg Distinguished Professor of Medicine, Oncology and Molecular Biology and Genetics. “And these areas are enriched with inherited genetic variants linked to certain psychiatric conditions.”

Scientists have long suspected that epigenetics plays a significant role in psychiatric conditions, other neurologic diseases such as Alzheimer’s, and a long list of other human ailments, including cancer. The current study does not definitively prove an epigenetics link to psychiatric conditions, but provides a road map to further study epigenetic diversity in the gene locations identified by the Johns Hopkins team, Feinberg says.

“We do know that both epigenetic and genetic changes contribute to the problem of cells not doing what they’re supposed to do,” adds Feinberg, who has studied epigenetics for decades. Results of the study are described online Jan. 14 in Nature Neuroscience.

Biostatistician Kasper Hansen, Ph.D., who co-led the study with Feinberg, says one of the main differences between their study and previous attempts to look at epigenetic diversity is that the Johns Hopkins scientists used a strong experimental design focused on different cell populations, including neurons. Other studies did not separate neurons from brain glial cells, which support neurons, acting as scaffolding, cleaners and nutrient suppliers.

The Johns Hopkins scientists, including first authors Lindsay Rizzardi and Peter Hickey, began their research with 45 brain tissue samples taken from six people (three males and three females, ages 37–57) who were not diagnosed with psychiatric or neurologic conditions and, upon their death, had donated their brains to biobanks at the National Institutes of Health and University of Maryland.

The samples were taken from four regions of the brain: the dorsolateral prefrontal cortex, which controls decision-making and social behaviors the anterior cingulate gyrus, known for its link to emotions and behavior the hippocampus, which is responsible for learning and memory and the nucleus accumbens, the site for processing reward behavior. By comparing samples from the same individual across different brain regions and cell populations, it is possible to rule out the confounding effect of genetics and many environmental exposures, such as smoking, says Hansen.

The scientists purified the brain tissue samples to isolate neurons and glia, sequenced the neurons’ genome and compared the sequencing results of neurons in each brain region. Looking at the distribution of epigenetic changes across the genome, the scientists found more epigenetic diversity in 12 million base pairs (out of 3 billion) of the genome than what would normally occur in those regions by chance alone. They found that most of the differences in epigenetics occurred in neurons of the nucleus accumbens, the brain’s reward center.

Using statistical tools to evaluate the genomic sequencing results, the researchers found that at least one of eight types of epigenetic changes was positively correlated with known genetic code changes among nearly half (13 of 27) of traits linked to heritable forms of addictive behavior, schizophrenia and neuroticism. Epigenetic changes were not linked to genetic differences among heritable, non-brain-related traits such as body mass index and height.

Hansen, who is an associate professor of biostatistics at the Johns Hopkins Bloomberg School of Public Health and McKusick Nathans Institute of Genetic Medicine, explains that the strong experimental design helps eliminate differences between individuals by comparing multiple samples from different brain regions from the same individual. “Furthermore, the strength of the genetic association is also determined by existing results on the genetic architecture of these traits, which have been established from tens to hundreds of thousands of samples,” says Hansen.

“Epigenetic changes may alter cells’ identity as well as their function,” suggests Feinberg, who also is a professor of biomedical engineering, biostatistics and psychiatry and behavioral science at Johns Hopkins. “To reveal how epigenetics is linked to psychiatric conditions, the next step is to develop customized genomic arrays that capture the areas of the genome that we identified and compare them to more samples of people with and without psychiatric disease.”

The research was supported by the Office of the Director of the National Institutes of Health and the National Cancer Institute (U01MH104393n, U24CA180996).

The Johns Hopkins team of researchers also includes Varenka Rodriguez DiBlasi, Rakel Tryggvadóttir, Colin M. Callahan and Adrian Idrizi.


Summary – Cerebrum vs Cerebral Cortex

In summarizing the difference between cerebrum and cerebral cortex, the cerebrum is the largest and prominent part of the brain, whereas the cerebral cortex is a part of the cerebrum. In fact, it is the outer layer of the gray matter of the cerebrum. Moreover, the cerebrum consists of two hemispheres while cerebral cortex consists of four lobes. Furthermore, cerebrum has cell bodies and nerve fibers while cerebral cortex has cell bodies and dendrites.

Reference:

1. “Cerebrum.” Wikipedia, Wikimedia Foundation, 21 Feb. 2019, Available here.
2. “Cerebral Cortex.” Wikipedia, Wikimedia Foundation, 25 Feb. 2019, Available here.


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Autism is a neurodevelopmental condition. Although it is diagnosed based on the presence of two core behaviors — restricted interests and repetitive behaviors, as well as difficulties with social interactions and communication — those traits are thought to arise because of alterations in how different parts of the brain form and connect to one another.

No research has uncovered a ‘characteristic’ brain structure for autism, meaning that no single pattern of changes appears in every autistic person. Studies of brain structure often turn up dissimilar results — there is great variety across individuals in general. But some trends have begun to emerge for subsets of autistic people. These differences might one day provide some insight into how some autistic people’s brains function. They may also point to bespoke treatments for particular subtypes of autism.

Here is what we know about how brain structure differs between people with and without autism.

Which brain regions are known to be structurally different between autistic and non-autistic people?
Studies that make use of a brain-scanning technique called magnetic resonance imaging (MRI) have highlighted a few brain regions that are structurally distinct in people with autism.

Children and adolescents with autism often have an enlarged hippocampus, the area of the brain responsible for forming and storing memories, several studies suggest, but it is unclear if that difference persists into adolescence and adulthood 1,2 .

The size of the amygdala also seems to differ between people with and without autism, although researchers from different labs have turned up conflicting results. Some find that people with autism have smaller amygdalae than people without autism, or that their amygdalae are only smaller if they also have anxiety 3 . Others have found that autistic children have enlarged amygdalae early in development and that the difference levels off over time 2,4 .

Autistic people have decreased amounts of brain tissue in parts of the cerebellum, the brain structure at the base of the skull, according to a meta-analysis of 17 imaging studies 5 . Scientists long thought the cerebellum mostly coordinates movements, but they now understand it plays a role in cognition and social interaction as well.

On a more global level, the cortex — the brain’s outer layer — seems to have a different pattern of thickness in people with and without autism. This difference tracks with alterations to a single type of neuron during development, a 2020 study suggests.

How do these structural differences change during development?
Some infants who are later diagnosed with autism have unusually fast growth in certain brain regions, according to multiple studies 6,7,8 . Compared with their non-autistic peers, autistic children have significantly faster expansion of the surface area of their cortex from 6 to 12 months of age. In the second year of life, brain volume increases much faster in autistic children than in their non-autistic peers.

The results support earlier research that saw enlarged heads and brains in a fraction of autistic people: Their cortex seems to expand too quickly in infancy and early childhood, even before autism traits can be detected behaviorally. During late childhood, neurotypical brains continue to grow in size in adulthood, they begin to shrink. By contrast, the brains of some people with autism start to shrink prematurely, before their mid-20s.

Some children who are later diagnosed with autism also have excess cerebrospinal fluid — the liquid that surrounds the brain — compared with their non-autistic peers, which may contribute to having an enlarged head. Those with the most fluid tend to also have the most prominent autism traits later in life 7 . The excess fluid appears as early as 6 months of age and persists through age 3 9 .

What about the structure of the connections between brain regions?
A solid body of evidence suggests that white matter, the bundles of long neuron fibers that connect brain regions, is also altered in people with autism. Researchers typically infer the structure of white matter by using a technique called diffusion MRI, which measures the flow of water throughout the brain.

People who lack all or part of one white matter tract called the corpus callosum, which connects the brain’s two hemispheres, have an increased likelihood of being autistic or having traits of the condition 10 . The corpus callosum contains many of the long-range connections that extend throughout the brain the fact that disrupting those connections may lead to autism traits supports the connectivity theory of autism.

Preschoolers with autism show significant differences in the structure of multiple white-matter tracts, according to a 2020 study. Autistic toddlers and adolescents, too, show alterations in white matter throughout the brain 11,12 .

Are there sex differences in the brain structure of people with autism?
It’s unclear. Identifying sex differences in autism remains challenging because fewer girls than boys are diagnosed with autism, says Mark Shen, assistant professor of psychiatry at the University of North Carolina at Chapel Hill.

Still, a few recent studies have turned up hints of sex differences in the brain in autism. A 2020 study showed that the amygdala is more affected in autistic girls than in autistic boys 13 . An enlarged amygdala is associated with more severe emotional problems specifically in autistic girls, according to other work.

White-matter changes in preschoolers with autism also differ by sex: Autistic girls have an increased measure of structural integrity in their corpus callosum compared with non-autistic girls, whereas that measure is lower in autistic boys than in non-autistic boys 14 .

Other structural differences, such as the rate of brain growth and amount of cerebrospinal fluid, appear similar between the sexes 6,9 .

Why is brain structure in autism important to study?
Because autism is a heterogeneous condition, “when we talk about autism, we’re probably talking about different biological subtypes,” Shen says.

Though not every baby who is later diagnosed with autism will have excess brain fluid at 6 months of age, and not every autistic adult has an underdeveloped corpus callosum, learning more about these subtypes can help researchers develop biologically based treatments for individuals with autism.

Additionally, finding structural biomarkers that can identify subtypes of autism in a noninvasive way, even before autism behaviors can be detected, will help “move the needle earlier” for autism diagnoses, Shen says.


The paper
C. Fecher et al., “Cell-type-specific profiling of brain mitochondria reveals functional and molecular diversity,” Nat Neurosci, 22:1731–42, 2019.

For many years, Thomas Misgeld, a neuroscientist at the Technical University of Munich in Germany, has studied mitochondria, often in the context of neurodegenerative and neuroinflammatory diseases. One thing he’s learned is that mitochondria in different cells or cell types, or even in different parts of the same cell, can behave quite differently. “Mitochondria are not as uniform as I always thought,” Misgeld says.

He wanted to develop a tool to capture that diversity. Taking inspiration from a decade-old technology called RiboTag, developed by researchers at the University of Washington (UW) to isolate ribosomes, Misgeld’s approach involved creating a line of mutant mice called MitoTag. These animals carry a gene that encodes a mitochondrial outer membrane protein tagged with green fluorescent protein, but as with RiboTag, the fluorescent fusion protein is only produced in the presence of an enzyme called Cre recombinase. Crossing the MitoTag mice with animals that express Cre recombinase in one of three types of brain cells, Misgeld and his colleagues were able to label only the mitochondria from those cell types. They then sacrificed the mice and used antibodies to isolate tagged mitochondria from their brain tissue.

Comparing protein levels in these three cerebellar cell types—excitatory neurons called granule cells, inhibitory neurons called Purkinje cells, and nonneuronal cells called astrocytes—Misgeld’s team looked for notable variation. Among these few cell types, “that already gives you variability in about 10 percent of the proteins that people believe make up a mitochondrion,” says Misgeld. If the analysis were expanded to all the different types of cells in the body, “you could imagine that the variability probably comprises a significant part of the mitochondrial proteome.”

While proteins involved in many critical biological pathways such as the electron transport chain were consistent across mitochondria from different cell types, those for other seemingly important processes, such as calcium handling, varied. For example, granule cells had noticeably higher levels of the mitochondrial calcium uniporter (MCU) complex than the other two cell types. And sure enough, the mitochondria isolated from granule cells showed more-efficient uptake of calcium in vitro. Misgeld notes that such variation doesn’t necessarily translate to functional differences in vivo—if, for example, Purkinje cells need less MCU than granule cells to get the same amount of calcium because it’s more concentrated at the site of uptake.

Purkinje cell mitochondria showed enriched production of Rmdm3, which binds mitochondria to the endoplasmic reticulum (ER), and electron microscopy confirmed that Purkinje cells had more mitochondria-ER contacts than granule cells or astrocytes. Meanwhile, the proteome in astrocyte mitochondria suggested the cells may break down lipids faster than their neuronal neighbors, a finding supported by in vitro assays of lipid metabolism in the isolated organelles.

“I think it’s a solid paper,” says molecular biologist David Morris, an emeritus professor at UW who helped develop RiboTag. He adds that the potential to cross the MitoTag mice with murine models of disease provides a new way to interrogate the mitochondria’s involvement in various disorders. “It should be a very useful tool.”


Study defines differences among brain neurons that coincide with psychiatric conditions

It's no surprise to scientists that variety is the very essence of biology, not just the seasoning, but most previous studies of key brain cells have found little variability in a common cell process that involves how genetic information is read and acted on.

The process, called epigenetics, involves chemical or structural "tweaks" to gene activity that don't affect the underlying genetic code itself, but do affect when and how a gene becomes available to be read for its protein-encoding instructions. When epigenetic changes strike at the wrong time or place, the process turns genes on or off at the wrong time and place, too.

Now, in a new study focusing on four regions of normal human brain tissue, Johns Hopkins scientists have found about 13,000 regions of epigenetic differences between neurons in different brain regions that vary by at least 10 percent. Using whole genome sequencing and computational statistical tools, they also found that the location of those epigenetic changes -- covering about 12 million bases in the genome -- co-locate with the genetic signal contributing to addictive behavior, schizophrenia and neuroses such as biopolar disorder.

"We believe we have figured out what parts of the neuronal genome are epigenetically different among these four brain regions," says Andrew Feinberg, M.D., the Bloomberg Distinguished Professor of Medicine, Oncology and Molecular Biology and Genetics. "And these areas are enriched with inherited genetic variants linked to certain psychiatric conditions."

Scientists have long suspected that epigenetics plays a significant role in psychiatric conditions, other neurologic diseases such as Alzheimer's, and a long list of other human ailments, including cancer. The current study does not definitively prove an epigenetics link to psychiatric conditions, but provides a road map to further study epigenetic diversity in the gene locations identified by the Johns Hopkins team, Feinberg says.

"We do know that both epigenetic and genetic changes contribute to the problem of cells not doing what they're supposed to do," adds Feinberg, who has studied epigenetics for decades. Results of the study are described online Jan. 14 in Nature Neuroscience.

Biostatistician Kasper Hansen, Ph.D., who co-led the study with Feinberg, says one of the main differences between their study and previous attempts to look at epigenetic diversity is that the Johns Hopkins scientists used a strong experimental design focused on different cell populations, including neurons. Other studies did not separate neurons from brain glial cells, which support neurons, acting as scaffolding, cleaners and nutrient suppliers.

The Johns Hopkins scientists, including first authors Lindsay Rizzardi and Peter Hickey, began their research with 45 brain tissue samples taken from six people (three males and three females, ages 37-57) who were not diagnosed with psychiatric or neurologic conditions and, upon their death, had donated their brains to biobanks at the National Institutes of Health and University of Maryland.

The samples were taken from four regions of the brain: the dorsolateral prefrontal cortex, which controls decision-making and social behaviors the anterior cingulate gyrus, known for its link to emotions and behavior the hippocampus, which is responsible for learning and memory and the nucleus accumbens, the site for processing reward behavior. By comparing samples from the same individual across different brain regions and cell populations, it is possible to rule out the confounding effect of genetics and many environmental exposures, such as smoking, says Hansen.

The scientists purified the brain tissue samples to isolate neurons and glia, sequenced the neurons' genome and compared the sequencing results of neurons in each brain region. Looking at the distribution of epigenetic changes across the genome, the scientists found more epigenetic diversity in 12 million base pairs (out of 3 billion) of the genome than what would normally occur in those regions by chance alone. They found that most of the differences in epigenetics occurred in neurons of the nucleus accumbens, the brain's reward center.

Using statistical tools to evaluate the genomic sequencing results, the researchers found that at least one of eight types of epigenetic changes was positively correlated with known genetic code changes among nearly half (13 of 27) of traits linked to heritable forms of addictive behavior, schizophrenia and neuroticism. Epigenetic changes were not linked to genetic differences among heritable, non-brain-related traits such as body mass index and height.

Hansen, who is an associate professor of biostatistics at the Johns Hopkins Bloomberg School of Public Health and McKusick Nathans Institute of Genetic Medicine, explains that the strong experimental design helps eliminate differences between individuals by comparing multiple samples from different brain regions from the same individual. "Furthermore, the strength of the genetic association is also determined by existing results on the genetic architecture of these traits, which have been established from tens to hundreds of thousands of samples," says Hansen.

"Epigenetic changes may alter cells' identity as well as their function," suggests Feinberg, who also is a professor of biomedical engineering, biostatistics and psychiatry and behavioral science at Johns Hopkins. "To reveal how epigenetics is linked to psychiatric conditions, the next step is to develop customized genomic arrays that capture the areas of the genome that we identified and compare them to more samples of people with and without psychiatric disease."

The research was supported by the Office of the Director of the National Institutes of Health and the National Cancer Institute (U01MH104393n, U24CA180996).

The Johns Hopkins team of researchers also includes Varenka Rodriguez DiBlasi, Rakel Tryggvadóttir, Colin M. Callahan and Adrian Idrizi.

Disclaimer: AAAS and EurekAlert! are not responsible for the accuracy of news releases posted to EurekAlert! by contributing institutions or for the use of any information through the EurekAlert system.


Denying the Neuroscience of Sex Differences

Imagine your response to picking up a copy of the leading scientific journal Nature and reading the headline: “The myth that evolution applies to humans.” Anyone even vaguely familiar with the advances in neuroscience over the past 15–20 years regarding sex influences on brain function might have a similar response to a recent headline in Nature: “Neurosexism: the myth that men and women have different brains” subtitled “the hunt for male and female distinctions inside the skull is a lesson in bad research practice.”

Neurosexism: the myth that men and women have different brains https://t.co/OOtJaICQ0t

&mdash Gina Rippon (@ginarippon1) February 27, 2019

Turns out that yet another book, this one with a fawning review in Nature, claims to “shatter” myths about sex differences in the brain while in fact perpetuating the largest one. Editors at Nature decided to give this book their imprimatur. Ironically, within a couple of days of the Nature review being published came a news alert from the American Association for the Advancement of Science titled, “Researchers discover clues to brain differences between males and females,” and a new editorial in Lancet Neurology titled “A spotlight on sex differences in neurological disorders,” both of which contradict the book’s core thesis. So what in the name of good science is going on here?

For decades neuroscience, like most research areas, overwhelmingly studied only males, assuming that everything fundamental to know about females would be learned by studying males. I know — I did this myself early in my career. Most neuroscientists assumed that differences between males and females, if they exist at all, are not fundamental, that is, not essential for understanding brain structure or function. Instead, we assumed that sex differences result from undulating sex hormones (typically viewed as a sort of pesky feature of the female), and/or from different life experiences (“culture”). In either case, they were dismissable in our search for the fundamental. In truth, it was always a strange assumption, but so it was.

Gradually however, and inexorably, we neuroscientists are seeing just how profoundly wrong — and in fact disproportionately harmful to women — that assumption was, especially in the context of understanding and treating brain disorders. Any reader wishing to confirm what I am writing can easily start by perusing online the January/February 2017 issue of the Journal of Neuroscience Research, the first ever of any neuroscience journal devoted to the topic of sex differences in its entirety. All 70 papers, spanning the neuroscience spectrum, are open access to the public.

In statistical terms, something called effect size measures the size of the influence of one variable on another. Although some believe that sex differences in the brain are small, in fact, the average effect size found in sex differences research is no different from the average effect size found in any other large domain of neuroscience. So here is a fact: It is now abundantly clear to anyone honestly looking, that the variable of biological sex influences all levels of mammalian brain function, down to the cellular/genetic substrate, which of course includes the human mammalian brain.

The mammalian brain is clearly a highly sex-influenced organ. Both its function and dysfunction must therefore be sex influenced to an important degree. How exactly all of these myriad sex influences play out is often hard, or even impossible to pinpoint at present (as it is for almost every issue in neuroscience). But that they must play out in many ways, both large and small, having all manner of implications for women and men that we need to responsibly understand, is now beyond debate — at least among non-ideologues.

Recognizing our obligation to carefully study sex influences in essentially all domains (not just neuroscience), the National Institute of Health on January 25, 2016 adopted a policy (called “Sex as a Biological Variable,” or SABV for short) requiring all of its grantees to seriously incorporate the understanding of females into their research. This was a landmark moment, a conceptual corner turned that cannot be unturned.

Sex can influence health & disease in many ways, which is why NIH requires that researchers consider sex as a biological variable (SABV) in all stages of research: https://t.co/G2fy2PxLrJ. Visit @NIH_ORWH for #SABV research tips. #WomensHealthInFocus #ThisIsNIH

&mdash NIH (@NIH) January 8, 2019

But the remarkable and unprecedented growth in research demonstrating biologically-based sex influences on brain function triggered 5-alarm fire bells in those who believe that such biological influences cannot exist.

Since Simone de Beauvoir in the early 1950s famously asserted that “One is not born, but rather becomes, a woman,” and John Money at Johns Hopkins shortly thereafter introduced the term “gender” (borrowed from linguistics) to avoid the biological implications of the word “sex,” a belief that no meaningful differences exist in the brains of women and men has dominated U.S. culture. And God help you if you suggest otherwise! Gloria Steinem once called sex differences research “anti-American crazy thinking.” Senior colleagues warned me as an untenured professor around the year 2000 that studying sex differences would be career suicide. This new book by Rippon marks the latest salvo by a very small but vocal group of anti-sex difference individuals determined to perpetuate this cultural myth.

A book like this is very difficult for someone knowledgeable about the field to review seriously. It is so chock-full of bias that one keeps wondering why one is bothering with it. Suffice to say it is replete with tactics that are now standard operating procedure for the anti-sex difference writers. The most important tactic is a comically biased, utterly non-representative view of the enormous literature of studies ranging from humans to single neurons. Other tactics include magnifying or inventing problems with disfavored studies, ignoring even fatal problems with favored studies, dismissing what powerful animal research reveals about mammalian brains, hiding uncomfortable facts in footnotes, pretending not to be denying biologically based sex-influences on the brain while doing everything possible to deny them, pretending to be in favor of understanding sex differences in medical contexts yet never offering a single specific research example why the issue is important for medicine, treating “brain plasticity” as a magic talisman with no limitations that can explain away sex differences, presenting a distorted view of the “stereotype” literature and what it really suggests, and resurrecting 19th century arguments almost no modern neuroscientist knows of, or cares about. Finally, use a catchy name to slander those who dare to be good scientists and investigate potential sex influences in their research despite the profound biases against the topic (“neurosexists!”). These tactics work quite well with those who know little or nothing about the neuroscience. Here are some lowlights:

Rippon praises a truly awful study that received extraordinary press attention (something she claims to dislike about studies of sex differences). In an analysis of structural brain scans of women and men led by Daphna Joel and published in 2015 in the Proceedings of the National Academy of Sciences (PNAS), a large number of differences were found on average between the sexes. But Joel’s team then claimed that, using a novel analysis, individual women and men possessed a rather random collection of the male-average and female-average traits. They correctly argued that we all possess a “mosaic” of female and male traits (which neuroscience already knew since the 1970s), but crucially, that the two sexes are actually unisex, that is, largely indistinguishable on average in the nature of these masculine/feminine mosaics.

This conclusion confused me, since there is nothing in our understanding of sex influences on the brain that predicts it. But, I gave them the benefit of the doubt and sat down to carefully read the study. I started to laugh in the methods section. The authors constructed their key measure (called “internal consistency”) to make it essentially impossible for them to not get the results they got. Or put another way, the study was basically rigged (although not necessarily consciously so), as subsequently shown by three other groups also published in PNAS. Marco Del Giudice and his colleagues at the University of New Mexico, for example, re-analyzed the same data used by Joel’s team, using a non-rigged methodology, and got the opposite results — individual women and men could be discriminated about 69–77 percent of the time by the same brain variables. Even higher levels of discriminability between the sexes have been reported by other teams regarding human brain structure and function, and regarding personality.

Rippon also utterly misrepresents a landmark study of human brain connectivity by Madhura Ingalhalikar, Raquel and Ruben Gur and colleagues, conducted at the University of Pennsylvania and published in PNAS in 2014. This impressive study reported sex differences in brain connectivity using standard, very defensible methods, and in fact a key finding (regarding the corpus callosum) confirmed earlier work by others. An illustration of a key result that Rippon criticizes is perfectly appropriate (and in fact would not be disputed in any other context), and is clearly labeled. This team offered a plausible speculation about what their anatomical findings might mean behaviorally, then as excellent scientists published another large, follow-up study directly relating the anatomical sex differences to behavior, a study not mentioned by Rippon. Instead, Rippon tells you about ridiculous comments people made in blogs about the first study. Finally, Rippon describes a study from a group in Zurich that ostensibly disconfirmed the original Ingahalikar et al report, yet did no such thing. In fact, the Zurich group confirmed the key sex difference of Ingahalikar et al (albeit with a smaller sample size), then suggested a plausible reason why the sex difference in brain connectivity that they confirmed existed, namely, the difference in overall brain size between the sexes.

The book is downright farcical when it comes to modern animal research, simply ignoring the vast majority of it. The enormous power of animal research, of course, is that it can establish sex influences in particular on mammalian brain function (such as sex differences in risk-taking, play behavior, and responses to social defeat as just three examples) that cannot be explained by human culture, (although they may well be influenced in humans by culture.) Rippon engages in what is effectively a denial of evolution, implying to her reader that we should ignore the profound implications of animal research (“Not those bloody monkeys again!”) when trying to understand sex influences on the human brain. She is right only if you believe evolution in humans stopped at the neck.

Rippon tries to convince you (and may even believe herself) that it is impossible to disentangle biology from culture when investigating sex differences in humans. This is false. I encourage the interested reader to see the discussion of the excellent work doing exactly this by a sociologist named J. Richard Udry in an article I wrote in 2014 for the Dana Foundation’s “Cerebrum,” free online.

To start treating women as equal to men, we have to stop treating women as if they are men. #womenarenotsmallmen https://t.co/TYeO8vc9Ha

&mdash Lara Briden, ND (@LaraBriden) December 4, 2017

Rippon does not mention Udry’s work, or its essential replication by Udry’s harshest critic, a leading sociologist who has described herself as a “feminist” who now “wrestles” with testosterone. (The Dana paper “Equal ≠ Same” also deconstructs the specious “brain plasticity” argument on which Rippon’s narrative heavily rests.)

Of course, Rippon is completely correct in arguing that neuroscientists (and the general public) should remember that “nature” interacts with “nurture,” and should not run wild with implications of sex difference findings for brain function and behavior. We must also reject the illogical conclusion that sex influences on the brain will mean that women are superior, or that men are superior. I genuinely do not know a single neuroscientist who disagrees with these arguments. But she studiously avoids an equally important truth: That neuroscientists should not deny that biologically-based sex differences exist and likely have important implications for understanding brain function and behavior, nor should they fear investigating them.

You may ask: What exactly are people like Rippon so afraid of? She cites potential misuse of the findings for sexist ends, which has surface plausibility. But by that logic we should also stop studying, for example, genetics. The potential to misuse new knowledge has been around since we discovered fire and invented the wheel. It is not a valid argument for remaining ignorant.

After almost 20 years of hearing the same invalid arguments (like Bill Murray in “Groundhog Day” waking up to the same song every day), I have come to see clearly that the real problem is a deeply ingrained, implicit, very powerful yet 100 percent false assumption that if women and men are to be considered “equal,” they have to be “the same.” Conversely, the argument goes, if neuroscience shows that women and men are not the same on average, then it somehow shows that they are not equal on average. Although this assumption is false, it still creates fear of sex differences in those operating on it. Ironically, forced sameness where two groups truly differ in some respect means forced inequality in that respect, exactly as we see in medicine today.

Women are not treated equally with men in biomedicine today because overwhelmingly they are still being treated the same as men (although this is finally changing). Yet astoundingly, and despite claiming she is not anti-sex difference, Rippon says “perhaps we should just stop looking for [sex] differences altogether?” Such dumbfounding statements from a nominal expert make me truly wonder whether the Rippons of the world even realize that, by constantly denying and trivializing and even vilifying research into biologically-based sex influences on the brain they are in fact advocating for biomedical research to retain its male subject-dominated status quo so disproportionately harmful to women.

So are female and male brains the same or different? We now know that the correct answer is “yes”: They are the same or similar on average in many respects, and they are different, a little to a lot, on average in many other respects. The neuroscience behind this conclusion is now remarkably robust, and not only won’t be going away, it will only grow. And yes, we, of course, must explore sex influences responsibly, as with all science. Sadly, the anti-sex difference folks will doubtless continue their ideological attacks on the field and the scientists in it.

Thus one can at present only implore thinking individuals to be wary of ideologues on both sides of the sex difference issue — those who want to convince you that men and women are always as different as Mars and Venus (and that perhaps God wants it that way), and those who want to convince you of the demonstrably false idea that the brains of women and men are for all practical purposes the same (“unisex”), that all differences between women and men are really due to an arbitrary culture (a “gendered world”), and that you are essentially a bad person if you disagree.

No one seems to have a problem accepting that, on average, male and female bodies differ in many, many ways. Why is it surprising or unacceptable that this is true for the part of our body that we call “brain”? Marie Curie said, “ Nothing in life is to be feared, it is only to be understood. Now is the time to understand more, so that we may fear less.” Her sage advice applies perfectly to discussions about the neuroscience of sex differences in 2019.


Larry Cahill is a professor in the Department of Neurobiology and Behavior at the University of California, Irvine and an internationally recognized leader on the topic of sex influences on brain function.