Andy Murray, PhD – Brain Blogger Health and Science Blog Covering Brain Topics Wed, 30 May 2018 15:00:03 +0000 en-US hourly 1 Picking Apart Schizophrenia Fri, 26 Feb 2016 16:00:13 +0000 In A Beautiful Mind , John Nash, played by Russell Crowe, is immersed in a fantasy world of conspiracy and paranoia. All of this we later learn is a product of his mind and a symptom of his untreated schizophrenia.

This story is a powerful example of what’s known as the ‘positive’ symptoms of schizophrenia, meaning that they are in addition to our normal everyday experience. This is contrasted by ‘negative’ symptoms, such as social withdrawal and depression. The observation of these seemingly opposing groups of symptoms form the basis of an argument that schizophrenia, rather than being a single disease, is in fact a collection of different disorders each with their own specific set of symptoms.

What some patients consider the most debilitating group of symptoms though, are not the hallucinations or social anxiety, but are actually a third group, which affects cognition (or the mental processes of memory, perception or judgment).

Cognitive problems include issues with working memory or how well you can hold information in your mind for short periods, and something called “cognitive flexibility”.

As an example of everyday cognitive flexibility, think about how you may park your car in the same spot every day. One day though your usual space is taken and your car has to be parked on the next block. Your memory is normally flexible enough to suppress your old memories (of where your car is usually parked), in favor of today’s parking spot, but someone with schizophrenia may struggle with this. Think how difficult daily life would be if you could not remember where you had put your keys moments before, where your car was parked or what needed to be picked up at the supermarket. This is why cognitive symptoms in schizophrenia can be so debilitating, and this is made even more problematic when we consider that currently available medications can treat positive and negative, but not cognitive symptoms.

A recent study in Scientific Reports goes some way to strengthen the argument that schizophrenia is a group of distinct disorders, and that cognitive problems are related to the dysfunction of specific neural circuits. For full disclosure, I was a researcher on the study and I am one of the authors of the paper.

In this study, we looked at the function of a particular type of neuron in the prefrontal cortex of the mouse brain. The prefrontal cortex is part of the brain’s frontal lobe and is often linked with cognition and complex thought and many studies have found that the prefrontal cortex malfunctions in schizophrenics. In this area one particular type of neuron has been repeatedly found to be damaged, those known as parvalbumin-positive interneurons, or PVIs for short.

PVIs are an inhibitory type of neuron, meaning they can block the electrical firing in neurons to which they are connected. By inhibiting groups of neighboring neurons PVIs are believed to “tune” the larger, excitatory, principle neurons in the prefrontal cortex. In this way then, PVI dysfunction in schizophrenia could lead to a malfunctioning prefrontal cortex and therefore cognitive problems. This idea though has been very difficult to test directly. It can be tricky to study the function of one particular type of neuron in the prefrontal cortex, without having undesired effects on the numerous other types that are found in the same area.

We were able to devise a method to block the synaptic transmission (the mechanism by which neurons communicate with each other) only in PVIs in the prefrontal cortex of mice. Doing this meant that we were able to look at different types of behaviour that were closely linked to the positive, negative and cognitive symptoms of schizophrenia. From previous studies we knew that less selective damage to the prefrontal cortex would lead to symptoms in all of the positive, negative and cognitive groups.

After blocking PVI synaptic transmission, we examined how sociable the mice were with other animals, as a means to assess their negative-like symptoms. They showed similar levels of interaction when compared to a control group. We took this to mean that PVIs are not involved in schizophrenia’s negative symptoms. Similarly, when we looked to see if they were hyperactive, a correlate of positive symptoms, their activity was normal. So, neither positive nor negative symptoms were created when we disrupted PVIs.

The story was a little different when we looked for cognitive problems. When placed in a maze the animals were unable to recall where they had been just moments before. Then when they needed to suppress a strong memory of a particular place in a different maze (where they would normally find some food) in favour of a new location, they were very slow at learning this new place. It seemed then that disrupting PVIs in the prefrontal cortex resulted in problems with working memory (where have I just been?) and cognitive flexibility (why is the food not in the same place it usually is?). The important part though, is that these were the only problems that they had, otherwise they displayed completely normal behaviour.

If we can block the actions of one type of neuron in one brain area and recreate just one set of schizophrenia symptoms then this supports the idea that schizophrenia is multiple disorders, perhaps with different neural circuits involved in each. Indeed, other studies have implicated different types of neurons in positive symptoms. Here, the malfunction of the chemical messengers, or neurotransmitters in the brain, called dopamine, could underlie problems like hallucinations.

While we hope that this study helps to unravel the complicated neurobiology of schizophrenia, there is obviously still a long way to go. It is extremely difficult, and not necessarily accurate, to relate the behaviour of a mouse to the complex feelings and emotions of a schizophrenic patient. But, by picking apart the neural circuits that map to different aspects of the disease we can gain both a greater understanding of the disease itself and the potential to generate more symptomatically targeted therapies in the future.


Lewis, D. (2014). Inhibitory neurons in human cortical circuits: substrate for cognitive dysfunction in schizophrenia Current Opinion in Neurobiology, 26, 22-26 DOI: 10.1016/j.conb.2013.11.003

Murray, A., Woloszynowska-Fraser, M., Ansel-Bollepalli, L., Cole, K., Foggetti, A., Crouch, B., Riedel, G., & Wulff, P. (2015). Parvalbumin-positive interneurons of the prefrontal cortex support working memory and cognitive flexibility Scientific Reports, 5 DOI: 10.1038/srep16778

Image via / Shutterstock.

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Shining a Light on How We Remember Sun, 11 Oct 2015 15:00:15 +0000 For an agent of Men in Black , a neuralyzer is standard issue equipment. The “alien technology”, looking a bit like a silver cigar could be used to “isolate the electronic impulses in your brains, more specifically the ones for memory”. The device allowed Will Smith or Tommy Lee Jones to simply and safely erase the memory of anyone they want, simply by making them look at a flash of light.

The technology is pretty impressive, very useful for MiB agents, but from a science standpoint perhaps a little far-fetched. However, a finding from a new study by researchers based in Japan and the USA bears a surprisingly striking resemblance to this technique. Essentially, by shining a light into the brain of a mouse, the researchers were able to erase specific memories that the animals had just formed. However, rather than aiming to construct a science fiction memory eraser, the group were instead trying to answer some very important, fundamental, questions about how the brain forms memories.

For many years, neuroscientists have believed that memories are generated and stored by altering the strength of the connections, or synapses, between neurons. Put simply, the output part of one neuron (or the axon) sends a signal to the input area of the next neuron (or the dendrite). Repeated firing between the same cells strengthens the connection these two cells have, meaning that in the future they can communicate more efficiently – forming a proposed cellular basis of memory.

One way in which these connections could be strengthened is by the enlarging of small swellings on the dendrite of the input neuron – called dendritic spines. The size of dendritic spines (which are usually just a couple of micrometers) correlates closely with the strength of the synapse, and it is well described that spines can form, disappear or change in size during learning. Never before though, have we been able to directly implicate these tiny protrusions on a neuron as a direct physical correlate of memory.

Theoretically, pinpointing the function of dendritic spines is simple. You watch them grow as an animal is forming a memory, artificially erase them, and check to see if the animal has forgotten what it just learned. In practice though, this is far from easy.

In order to investigate the role of dendritic spines in memory the researchers first designed a protein to be expressed in neurons of the mouse motor cortex – the area of the brain involved in learning new motor skills. This protein had two parts. The first ensured it was transported selectively to newly growing dendritic spines. The second was something called Rac1, activation of which can collapse dendritic spines. The clever part, Rac1 would only be active when a laser of the correct wavelength is shined on it though – the researchers called this AS-pRac1.

With the protein lying in wait in their motor cortex, mice were trained to run on either on a rotating rod (or rotarod) or a narrow balance beam. Both of these tasks are picked up very simply by mice, but they do require an amount of learning to become proficient. Once the mice had learned these skills, the researchers could watch new dendritic spines formed in their motor cortex.

The AS-pRac1 was transported to these growing regions, then simply by shining a light the researchers collapsed the newly formed dendritic spines. After the laser was turned on, and the spines collapsed, the mice were no longer able to run on the rotarod or the balance beam. So amazingly, simply by removing some micrometer (a thousandth of a millimeter) sized swellings from the dendrites of a few neurons, mice completely forgot a motor skill they had just recently mastered.

In a further advance in our understanding of memory, by training mice sequentially on either the rotarod or the balance beam it was possible to erase the dendritic spines associated with just one of the tasks. Here, when collapsing only the rotarod dendritic spines the animals forgot how to run on the rotarod, but were still able to run on the balance beam – clearly showing that different neurons and dendritic spines were required for different memories.

So, what does this mean? Are we just one step closer to a Men in Black-style neuralyzer? Thankfully, that’s still a long time away. This study does, however, make a much more important contribution to science. We now have a much clearer understanding of what changes in the brain when we form a memory. Crucially, only by understanding how memories are formed and stored in the brain will be able to one day understand what causes memory to be lost or degraded in disorders like dementia.


Hayashi-Takagi, A., Yagishita, S., Nakamura, M., Shirai, F., Wu, Y., Loshbaugh, A., Kuhlman, B., Hahn, K., & Kasai, H. (2015). Labelling and optical erasure of synaptic memory traces in the motor cortex Nature, 525 (7569), 333-338 DOI: 10.1038/nature15257

Lu J, Zuo Y. (2015) Neuroscience: Forgetfulness illuminated. Nature. 525, 324-325. doi: 10.1038/nature15211
Lu J, & Zuo Y (2015). Neuroscience: Forgetfulness illuminated. Nature, 525 (7569), 324-5 PMID: 26352474

Image via Patrice6000 / Shutterstock.

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Mapping The Brain – Just How Hard Is It? Sat, 29 Aug 2015 15:00:21 +0000 Some say it’s the most complex object in the universe, but just how difficult is it going to be to finally understand how the human brain works?

If we take a purely anatomical view, the numbers become a little daunting. The brain is made up of maybe a hundred billion neurons, 100 trillion connections (synapses), and a 100 billion non-neuronal cells (glia). Our knowledge of the human brain is so sparse that even these numbers have to be taken with a pinch of salt. This is without mention of what’s going on inside the cells with its different neurotransmitters, synaptic vesicles, transport proteins and the unbelievable number of other proteins that allow neurons to function normally.

This complexity is what drives neuroscience research and hints at why treatments for neurological disorders such as Alzheimer’s or schizophrenia lag so far behind that of other conditions: Without understanding how the normal brain is wired we can never know how it can go wrong. The sheer scale, intricacy and complexity of the brain is one of the main reasons why large initiatives like the White House’s BRAIN Initiative are so important – but the magnitude of the task at hand can be daunting.

A recent study from researchers at Harvard University demonstrates just how complicated, densely packed and intricate mammalian brains are, but provides hope that these problems one day may become tractable. The Lichtman lab took an area of the mouse neocortex, the most recently evolved and arguably most complex part of the brain, measuring just 1500 cubic microns and set out to reconstruct every 3-dimensional object in this area.

To do this, the piece of tissue was cut into impossibly thin sections measuring of 29 nanometres. To put this into context, a standard piece of paper of paper is around 100 microns (or 0.1 millimeters) thick, you would have to slice that piece of paper into about 3,448 sections to get slices of the same thickness. Each of these brain sections was then imaged with a scanning electron microscope, which blasts a beam of electrons at the sections measuring how they are scattered when they come into contact with the sample.

2,250 sections later, the tiny piece of mouse brain was digitally reconstructed. For this reconstruction the authors had to design new ways to analyze the imaging data, and they have made these techniques freely available to other researchers. This means other groups will now be able to tackle similar problems on a larger scale.

This is not to say that this was a mere proof of principle study, even understanding tiny area can give us important information about how the brain works. Just by looking at the roughly 1,600 fragments of neurons and 1,700 connections, they were able to solve a fundamental problem in neuroanatomy. They showed that when neurons form connections with each other, they do not just make contact with whoever happens to be their neighbor, they can ignore those cells closest to them and seek out a more appropriate wiring partner somewhere else.

What about mapping the whole brain though, is all lost, is it just too large and complicated to tackle? Indeed, it would take an incredible amount of time to reconstruct an entire mouse brain – it took six years for this tiny fragment, and the mouse brain is obviously much smaller than that of a human. But there are several reasons for hope.

First, the technology used in this study is advancing all the time, meaning that future investigations can advance more quickly. Second, and perhaps more importantly, it’s likely not necessary to reconstruct the entire brain in such exquisite detail. The principles of connectivity and structural features that this study unveiled will likely be applicable to many other parts of the brain – meaning that future studies can take a broader look at neuroanatomy.

It may have only been 1,500 cubic microns, but it represents a great chunk of progress in understanding brain connections.


Abbott, A. (2015). Crumb of mouse brain reconstructed in full detail Nature, 524 (7563), 17-17 DOI: 10.1038/nature.2015.18105

Kasthuri, N., Hayworth, K., Berger, D., Schalek, R., Conchello, J., Knowles-Barley, S., Lee, D., Vázquez-Reina, A., Kaynig, V., Jones, T., Roberts, M., Morgan, J., Tapia, J., Seung, H., Roncal, W., Vogelstein, J., Burns, R., Sussman, D., Priebe, C., Pfister, H., & Lichtman, J. (2015). Saturated Reconstruction of a Volume of Neocortex Cell, 162 (3), 648-661 DOI: 10.1016/j.cell.2015.06.054

Ostroff, L., & Zeng, H. (2015). Electron Microscopy at Scale Cell, 162 (3), 474-475 DOI: 10.1016/j.cell.2015.07.031

Image via vitstudio / Shutterstock.

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