TL;DR
- Many electronic devices today are dependent on semiconductor logic circuits based on switches hard-wired to perform predefined logic functions. Physicists from the National University of Singapore (NUS), together with an international team of researchers, have developed a novel molecular memristor, or an electronic memory device, that has exceptional memory reconfigurability. Unlike hard-wired standard circuits, the molecular device can be reconfigured using voltage to embed different computational tasks. The energy-efficient new technology, which is capable of enhanced computational power and speed, can potentially be used in edge computing, as well as handheld devices and applications with limited power resources.
- Contrary to common thinking, cocaine triggers an addiction only in 20% of the consumers. But what happens in their brains when they lose control of their consumption? Thanks to a recent experimental method, neuroscientists at the University of Geneva (UNIGE), Switzerland, have revealed a brain mechanism specific to cocaine, which has the particularity of triggering a massive increase in serotonin in addition to the increase in dopamine common to all drugs. Indeed, serotonin acts as an intrinsic brake on the overexcitement of the reward system elicited by dopamine, the neurotransmitter that causes addiction. These results are published in the journal Science.
- Recreating major pathological features of Parkinson’s disease in a lab-grown, human mini-brain will help researchers to explore new treatments. This is the first time that Lewy bodies, a hallmark of Parkinson’s disease in patients’ brains, have been produced in the laboratory, offering new insights into the disease.
- An image of a beautiful beach conjures up certain sensations — one can imagine the sun’s warmth and the sound of waves breaking on the shore. But how is it that the brain produces these impressions when someone isn’t actually standing on a beach? Using massage stones, pictures of sunny beaches and snowy landscapes, and sounds of noisy cities and quiet forests, research suggests the prefrontal cortex generalizes perceptual experiences from information received through different senses.
- For millions of people with epilepsy and movement disorders such as Parkinson’s disease, electrical stimulation of the brain already is widening treatment possibilities. In the future, electrical stimulation may help people with psychiatric illness and direct brain injuries, such as stroke. However, studying how brain networks interact with each other is complicated. Brain networks can be explored by delivering brief pulses of electrical current in one area of a patient’s brain while measuring voltage responses in other areas. In principle, one should be able to infer the structure of brain networks from these data. However, with real-world data, the problem is difficult because the recorded signals are complex, and a limited amount of measurements can be made. To make the problem manageable, Mayo Clinic researchers developed a set of paradigms, or viewpoints, that simplify comparisons between effects of electrical stimulation on the brain. Because a mathematical technique to characterize how assemblies of inputs converge in human brain regions did not exist in the scientific literature, the Mayo team collaborated with an international expert in artificial intelligence (AI) algorithms to develop a new type of algorithm called “basis profile curve identification.”
- Research has discovered that the strength of the connection between our brain and internal organs is linked to how we feel about our appearance. The study has investigated the association between body image and the brain’s processing of internal signals that occur unconsciously. It found that adults whose brains are less efficient at detecting these internal messages are more likely to experience body shame and weight preoccupation.
- As mice watched movies, scientists watched their brains to see how the vision could be represented reliably. The answer is that consistency in representation is governed by a circuit of inhibitory neurons.
- Brain regulation of feeding behavior traits has remained incompletely understood. In their latest study, researchers at the Turku PET Centre, Finland, discovered a connection between the function of the opioid system and food craving triggered by appetitive external stimuli.
- We are all used to seeing the 3D world that we live in reduced to 2D, whether in art, photography, or film. But, when we close our eyes, how do we visualize things that we have already seen? A new study led by the Universities or Plymouth and Essex investigated this question, discovering that many adults are resistant to imagining their own vision as if it were a flat image — seeing it in its fully processed, knowledge-laden form instead.
- Researchers examined the differences in prefrontal cortex (PFC) activation between two distinct drawing tasks in virtual reality. Results of the study indicated significant differences between a rote tracing task and a creative self-expression task, with the rote tracing task showing an increase in PFC activity. It also showed there was reduced PFC activation for creative self-expressive tasks, indicating a possible relaxation response.
- And more!
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Latest news and researches
Decision trees within a molecular memristor
by Sreetosh Goswami, Rajib Pramanick, Abhijeet Patra, Santi Prasad Rath, Martin Foltin, A. Ariando, Damien Thompson, T. Venkatesan, Sreebrata Goswami, R. Stanley Williams in Nature
Many electronic devices today are dependent on semiconductor logic circuits based on switches hard-wired to perform predefined logic functions. Physicists from the National University of Singapore (NUS), together with an international team of researchers, have developed a novel molecular memristor, or an electronic memory device, that has exceptional memory reconfigurability.
Unlike hard-wired standard circuits, the molecular device can be reconfigured using voltage to embed different computational tasks. The energy-efficient new technology, which is capable of enhanced computational power and speed, can potentially be used in edge computing, as well as handheld devices and applications with limited power resources.
“This work is a significant breakthrough in our quest to design low-energy computing. The idea of using multiple switching in a single element draws inspiration from how the brain works and fundamentally reimagines the design strategy of a logic circuit,” said Associate Professor Ariando from the NUS Department of Physics who led the research.
The research was first published in the journal Nature on 1 September 2021, and carried out in collaboration with the Indian Association for the Cultivation of Science, Hewlett Packard Enterprise, the University of Limerick, the University of Oklahoma, and Texas A&M University.
“This new discovery can contribute to developments in edge computing as a sophisticated in-memory computing approach to overcome the von Neumann bottleneck, a delay in computational processing seen in many digital technologies due to the physical separation of memory storage from a device’s processor,” said Assoc Prof Ariando. The new molecular device also has the potential to contribute to designing next generation processing chips with enhanced computational power and speed.
“Similar to the flexibility and adaptability of connections in the human brain, our memory device can be reconfigured on the fly for different computational tasks by simply changing applied voltages. Furthermore, like how nerve cells can store memories, the same device can also retain information for future retrieval and processing,” said first author Dr Sreetosh Goswami, Research Fellow from the Department of Physics at NUS.
Research team member Dr Sreebrata Goswami, who was a Senior Research Scientist at NUS and previously Professor at the Indian Association for the Cultivation of Science, conceptualised and designed a molecular system belonging to the chemical family of phenyl azo pyridines that have a central metal atom bound to organic molecules called ligands. “These molecules are like electron sponges that can offer as many as six electron transfers resulting in five different molecular states. The interconnectivity between these states is the key behind the device’s reconfigurability,” explained Dr Sreebrata Goswami.
Dr Sreetosh Goswami created a tiny electrical circuit consisting a 40-nanometer layer of molecular film sandwiched between a top layer of gold, and a bottom layer of gold-infused nanodisc and indium tin oxide. He observed an unprecedented current-voltage profile upon applying a negative voltage to the device. Unlike conventional metal-oxide memristors that are switched on and off at only one fixed voltage, these organic molecular devices could switch between on-off states at several discrete sequential voltages.
Using an imaging technique called Raman spectroscopy, spectral signatures in the vibrational motion of the organic molecule were observed to explain the multiple transitions. Dr Sreebrata Goswami explained, “Sweeping the negative voltage triggered the ligands on the molecule to undergo a series of reduction, or electron-gaining which caused the molecule to transition between off and on states.”
The researchers described the behavior of the molecules using a decision tree algorithm with “if-then-else” statements, which is used in the coding of several computer programs, particularly digital games, as compared to the conventional approach of using basic physics-based equations.
Building on their research, the team used molecular memory devices to run programs for different real-world computational tasks. As a proof of concept, the team demonstrated that their technology could perform complex computations in a single step, and could be reprogrammed to perform another task in the next instant. An individual molecular memory device could perform the same computational functions as thousands of transistors, making the technology a more powerful and energy-efficient memory option.
“The technology might first be used in handheld devices, like cell phones and sensors, and other applications where power is limited,” added Assoc Prof Ariando.
The team is in the midst of building new electronic devices incorporating their innovation, and working with collaborators to conduct simulation and benchmarking relating to existing technologies.
Synaptic mechanism underlying serotonin modulation of transition to cocaine addiction
by Yue Li, Linda D. Simmler, Ruud Van Zessen, Jérôme Flakowski, Jin-Xia Wan, Fei Deng, Yu-Long Li, Katherine M. Nautiyal, Vincent Pascoli, Christian Lüscher in Science
Contrary to common thinking, cocaine triggers an addiction only in 20% of the consumers. But what happens in their brains when they lose control of their consumption? Thanks to a recent experimental method, neuroscientists at the University of Geneva (UNIGE), Switzerland, have revealed a brain mechanism specific to cocaine, which has the particularity of triggering a massive increase in serotonin in addition to the increase in dopamine common to all drugs. Indeed, serotonin acts as an intrinsic brake on the overexcitement of the reward system elicited by dopamine, the neurotransmitter that causes addiction.
Addiction is defined as the compulsive search for a substance despite the negative consequences, whereas dependence is characterised as the occurrence of a withdrawal symptom — the physical effects of which vary greatly from one substance to another — when consumption is stopped abruptly. It thus affects everyone, whereas addiction affects only a minority of users, even after prolonged exposure. For example, it is estimated that 20% of cocaine users and 30% of opiate users are addicted. “The same principle applies to all potentially addictive products,” says Christian Lüscher, a professor in the Department of Basic Neurosciences at the UNIGE Faculty of Medicine, who led the research. “Here in Switzerland, for instance, almost all adults consume alcohol from time to time, which is a strong stimulator of the reward system. However, only a small proportion of us will become alcoholics.”
To assess how cocaine addiction arises in the brain, the research team developed a series of experiments.
“Most of the time, scientific experiments aim to reproduce a systematic mechanism. Here, the difficulty lies in observing a random phenomenon, which is triggered only once in five times,” explains Yue Li, a researcher in Christian Lüscher’s laboratory and first author of the study.
The scientists first taught a large group of mice to self-administer cocaine voluntarily, and then added a constraint: each time they self-administered cocaine, the mice received a slightly unpleasant stimulus (electric shock or air jet). Two groups then emerged: 80% of the mice stopped their consumption, while 20% continued, despite the unpleasantness.
“This compulsive behaviour is precisely what defines addiction, which affects 20% of individuals, in mice as well as in humans,” emphasizes Vincent Pascoli, a scientific collaborator in the Geneva group and co-author of this study.
The experiment was repeated with mice in which cocaine was no longer linked to the serotonin transporter, so that only dopamine increased when the substance was taken. 60% of the animals then developed an addiction. The same was found in other animals with a reward system stimulation protocol that did not affect serotonin.
“If serotonin is administered to the latter group, the rate of addiction falls to 20%,” says Christian Lüscher. “Cocaine, therefore, has a kind of natural brake that is effective four times out of five.”
When cocaine is consumed, two forces are at work in the brain: dopamine on the one hand, whose sudden increase leads to compulsion, and serotonin on the other, which acts as a brake on compulsion. Addiction, therefore, occurs when an imbalance is created between these two neuroregulators and dopamine overtakes serotonin.
“Actually, dopamine triggers a phenomenon of synaptic plasticity, through the strengthening of connections between synapses in the cortex and those in the dorsal striatum. This intense stimulation of the reward system then triggers compulsion. Serotonin has the opposite effect by inhibiting the reinforcement induced by dopamine to keep the reward system under control,” explains Christian Lüscher.
Apart from the increase in dopamine, each substance has its own specificity and effect on the brain. If the addictive effect of cocaine is naturally reduced by serotonin, what about other drugs? The Geneva neuroscientists will now look at opiates — which are more addictive than cocaine — and ketamine, which is much less so. The aim is to understand in detail how the brain reacts to these drugs and why some people are much more vulnerable to their harmful effects than others.
Lewy Body–like Inclusions in Human Midbrain Organoids Carrying Glucocerebrosidase and α‐Synuclein Mutations
by Junghyun Jo, Lin Yang, Hoang‐Dai Tran, Weonjin Yu, Alfred Xuyang Sun, Ya Yin Chang, Byung Chul Jung, Seung‐Jae Lee, Tzuen Yih Saw, Bin Xiao, Audrey Tze Ting Khoo, Lai‐Ping Yaw, Jessica Jiaxin Xie, Hidayat Lokman, Wei‐Yi Ong, Grace Gui Yin Lim, Kah‐Leong Lim, Eng‐King Tan, Huck‐Hui Ng, Hyunsoo Shawn Je in Annals of Neurology
Tiny brains-in-a-dish that mimic the major pathological features of Parkinson’s disease have been made for the first time. The research, led by scientists from the Agency for Science, Technology and Research (A*STAR)’s Genome Institute of Singapore (GIS), the National Neuroscience Institute (NNI) and Duke-NUS Medical School, published in the Annals of Neurology, offers a new way to study how the degenerative brain disease progresses and explore possible new treatments.
Parkinson’s disease is a common age-related neurodegenerative disorder affecting three in 1,000 Singaporeans aged 50 years and above. Worldwide, neurological disorders are the leading cause of disability, and Parkinson’s disease is the fastest-growing disorder. Prior research has mostly relied on mice, which do not reproduce all major pathological features seen in patients.
“Recreating models of Parkinson’s disease in animal models is hard as these do not show the progressive and selective loss of neurons that produce the neurotransmitter dopamine, a major feature of Parkinson’s disease,” said Professor Ng Huck Hui, Senior Group Leader at GIS, A*STAR, who is a senior co-author of the study. “Another limitation is that experimental mouse models of Parkinson’s disease do not develop characteristic clumps of proteins called Lewy bodies, which are often seen in the brain cells of people with Parkinson’s disease and a type of progressive dementia known as Lewy body dementia.”
The team decided to turn to human mini-brains that they created previously.
“We called these ‘human midbrain-like organoids’,” said first author Dr Junghyun Jo, previously a Research Fellow at GIS and now a Principal Investigator at the Okinawa Institute of Science and Technology Graduate University. “They are essentially three-dimensional, multicellular, in vitro tissue constructs that mimic the human midbrain.”
The small pea-sized human midbrain-like organoids are grown from human stem cells into a bundle of neurons and other cells found in the brain. The organoids enable scientists to study how the human brain develops and communicates.
“These experiments are the first to recreate the distinctive features of Parkinson’s disease that we see only in human patients,” said Associate Professor Hyunsoo Shawn Je, a senior co-author from the Neuroscience and Behavioural Disorders Programme at Duke-NUS. “We have created a new model of the pathology involved, which will allow us to track how the disease develops and how it might be slowed down or stopped.”
By manipulating the DNA of the starting stem cells to match genetic risk factors found in patients with Parkinson’s disease, the study scientists were able to grow organoids with neurons that showed both Lewy bodies and the progressive loss of dopamine-producing neurons.
“It’s a major challenge to extend healthy living years in an ageing global population, whose physical and cognitive performance often declines due to neurodegenerative disorders,” said Professor Tan Eng King, Deputy Medical Director, Academic Affairs, at NNI, a senior co-author of the study. “This discovery provides insights and a ‘humanised’ disease model that can facilitate drug testing against Parkinson’s disease and dementia. Our organoid model with a genetic mutation on the GBA gene is also highly relevant as we have several of these genetic mutation carriers locally.”
The organoid system will enable research into Parkinson’s disease and other conditions not possible with current animal models. The team is already using organoids to investigate why and how Lewy bodies form in human brain cells, and screen drugs that can potentially stop disease progression.
Neural Representations in the Prefrontal Cortex Are Task Dependent for Scene Attributes But Not for Scene Categories
by Yaelan Jung, Dirk B. Walther in The Journal of Neuroscience
An image of a beautiful beach conjures up certain sensations — one can imagine the warmth of the sun as it caresses the skin, and the sound of the water as waves break on the shore. But how is it that the human brain produces these impressions even when an individual isn’t actually standing on a beach, basking in the sun’s rays and listening to the sound of the waves?
Scientists at the University of Toronto (U of T) exploring this mystery found that the brain’s prefrontal cortex — a region known primarily for its role in regulating behaviour, impulse inhibition, and cognitive flexibility — produces such general sensations based on information provided by various senses. The findings provide new insights into the poorly understood role of the prefrontal cortex in human perception.
Using a combination of photographs, sounds and even heated massage stones, the researchers investigated patterns of neural activity in the prefrontal cortex as well as the other regions of the brain known to be responsible for processing stimulation from all the senses and found significant similarities.
“Whether an individual was directly exposed to warmth, for example, or simply looking at a picture of a sunny scene, we saw the same pattern of neural activity in the prefrontal cortex,” said Dirk Bernhardt-Walther, professor in the Department of Psychology in the Faculty of Arts & Science at the U of T, and coauthor of a study describing the findings. “The results suggest that the prefrontal cortex generalizes perceptual experiences that originate from different senses.”
To understand how the human brain processes the torrent of information from the environment, researchers often study the senses in isolation, with much of prior work focused on the visual system. Bernhardt-Walther says that while such work is illuminating and important, it is equally important to find out how the brain integrates information from the different senses, and how it uses the information in a task-directed manner. “Understanding the basics of these capabilities provides the foundation for research of disorders of perception,” he said.
Using functional magnetic resonance imaging (fMRI) technology to capture brain activity the researchers conducted two experiments with the same participants, based on knowing how regions of the brain respond differently depending on the intensity of stimulation.
In the first, the participants viewed a series of images of various scenes — including beaches, city streets, forests, and train stations — and were asked to judge if the scenes were warm or cold and noisy or quiet. Throughout, neural activity across several regions of the brain was tracked.
In the second experiment, participants were first handed a series of massage stones that were either heated to 45C or cooled to 9C, and later exposed to sounds both quiet and noisy — such as birds, people, and waves at a beach.
“When we compared the patterns of activity in the prefrontal cortex, we could determine temperature both from the stone experiment and from the experiment with pictures as the neural activity patterns for temperature were so consistent between the two experiments,” said lead author of the study Yaelan Jung, who recently completed her PhD at U of T working with Bernhardt-Walther and is now a postdoctoral researcher at Emory University.
“We could successfully determine whether a participant was holding a warm or a cold stone from patterns of brain activity in the somatosensory cortex, which is the part of the brain that receives and processes sensory information from the entire body, while brain activity in the visual cortex told us if they were looking at an image of a warm or cold scene,” said Jung.
The patterns were so compatible that a decoder trained on prefrontal brain activity from the stone experiment was able to predict the temperature of a scene depicted in an image as it was viewed.
“It tells us about the relationship between someone feeling warmth by looking at a picture versus actually touching a warm object,” Jung said.
Similarly, the researchers could decode noisy versus quiet sounds from the brain’s auditory cortex and pictures of noisy versus quiet scenes from the visual cortex.
“Overall, the neural activity patterns in the prefrontal cortex produced by participants viewing the images were the same as those triggered by actual experience of temperature and noise level,” said Jung.
The researchers suggest the findings may open a new avenue to study how the brain manages to process and represent complex real-world attributes that span multiple senses, even without directly experiencing them.
“In understanding how the human brain integrates information from different senses into higher-level concepts, we may be able to pinpoint the causes of specific inabilities to recognize particular kinds of objects or concepts,” said Bernhardt-Walther.
“Our results might help people with limitations in one sensory modality to compensate with another and reach the same or very similar conceptual representations in their prefrontal cortex, which is essential for making decisions about their environment.”
Basis profile curve identification to understand electrical stimulation effects in human brain networks
by Kai J. Miller, Klaus-Robert Müller, Dora Hermes in PLOS Computational Biology
For millions of people with epilepsy and movement disorders such as Parkinson’s disease, electrical stimulation of the brain already is widening treatment possibilities. In the future, electrical stimulation may help people with psychiatric illness and direct brain injuries, such as stroke.
However, studying how brain networks interact with each other is complicated. Brain networks can be explored by delivering brief pulses of electrical current in one area of a patient’s brain while measuring voltage responses in other areas. In principle, one should be able to infer the structure of brain networks from these data. However, with real-world data, the problem is difficult because the recorded signals are complex, and a limited amount of measurements can be made.
To make the problem manageable, Mayo Clinic researchers developed a set of paradigms, or viewpoints, that simplify comparisons between effects of electrical stimulation on the brain. Because a mathematical technique to characterize how assemblies of inputs converge in human brain regions did not exist in the scientific literature, the Mayo team collaborated with an international expert in artificial intelligence (AI) algorithms to develop a new type of algorithm called “basis profile curve identification.”
In a study, a patient with a brain tumor underwent placement of an electrocorticographic electrode array to locate seizures and map brain function before a tumor was removed. Every electrode interaction resulted in hundreds to thousands of time points to be studied using the new algorithm.
“Our findings show that this new type of algorithm may help us understand which brain regions directly interact with one another, which in turn may help guide placement of electrodes for stimulating devices to treat network brain diseases,” says Kai Miller, M.D., Ph.D., a Mayo Clinic neurosurgeon and first author of the study. “As new technology emerges, this type of algorithm may help us to better treat patients with epilepsy, movement disorders like Parkinson’s disease, and psychiatric illnesses like obsessive compulsive disorder and depression.”
“Neurologic data to date is perhaps the most challenging and exciting data to model for AI researchers,” says Klaus-Robert Mueller, Ph.D., study co-author and member of the Google Research Brain Team. Dr. Mueller is co-director of the Berlin Institute for the Foundations of Learning and Data and director of the Machine Learning Group — both at Technical University of Berlin.
In the study, the authors provide a downloadable code package so others may explore the technique. “Sharing the developed code is a core part of our efforts to help reproducibility of research,” says Dora Hermes, Ph.D., a Mayo Clinic biomedical engineer and senior author.
Weaker implicit interoception is associated with more negative body image: Evidence from gastric-alpha phase amplitude coupling and the heartbeat evoked potential
by Jennifer Todd, Pasquale Cardellicchio, Viren Swami, Flavia Cardini, Jane E. Aspell in Cortex
New research has discovered that the strength of the connection between our brain and internal organs is linked to how we feel about our appearance. The study is the first to investigate, and first to identify, the association between body image and the brain’s processing of internal signals that occur unconsciously.
Carried out by a team of psychologists and neuroscientists at Anglia Ruskin University (ARU), the study found that adults whose brains are less efficient at detecting these internal messages are more likely to experience body shame and weight preoccupation.
This research could have therapeutic implications for people suffering with conditions in which body image plays a significant role. For example, the unconscious signals could be made conscious. Further research could even be applied to the clinic as it may be the case that brain responses to gut signals could indicate a predisposition to eating disorders.
The study participants — a group of healthy UK adults — first took part in four body image assessments to measure their feelings of body appreciation, body functionality appreciation, body shame, and weight preoccupation.
The researchers then carried out measurements of the participants’ internal signals. Some of the messages from the heart and gut are processed at an unconscious level and the nervous system interprets these signals to provide the brain with continuously updated information about the body’s internal state.
The strength of the connection between the gut and the brain was measured by recording the electrical activity of both regions at the same time. The researchers also measured brain responses to heartbeats.
They found that weaker brain responses to the gut and heart were both significantly associated with greater levels of body shame and weight preoccupation amongst the participants.
Senior author Dr Jane Aspell, Associate Professor of Cognitive Neuroscience at Anglia Ruskin University (ARU), said: “We experience our body both from the inside and out: we can be aware of how our skin and limbs look, but also of how hungry we feel or how strongly our heart is beating during exercise. The brain also continuously processes internal signals that we are not conscious of.
“We found that when the brain is less responsive to these implicit signals from inside the body, individuals are more likely to hold negative views about their external bodily appearance. It may be that when the brain has a weaker connection to the internal body, the brain puts more emphasis on the external body and so appearance becomes much more important for self-evaluation.”
Lead author Dr Jennifer Todd, a Postdoctoral Research Fellow at Anglia Ruskin University (ARU), said:
“Our research could have implications for those experiencing negative body image, which can have a serious impact on people’s lives.
“The gut and heart signal measurements used in our study could potentially act as a biomarker to help identify, or even predict, negative body image and associated conditions, such as eating disorders. Additionally, by training people to become more aware of internal sensations, it might be possible to amplify these unconscious signals.
“We need to understand why some brains are better at detecting these internal signals than others. We expect it is partly due to differences in neuro-anatomical connections between the brain and internal organs, and this will be the subject of future research.”
Meanwhile, Dr Jane Aspell will be speaking about her research on the body and sense of self in a talk at the British Science Festival 2021, 7–11 September hosted by the British Science Association at Anglia Ruskin University. The talk will explore research on out of body experiences (OBEs), and she will share case studies from neurological patients.
Dr Aspell’s work investigates what happens in the brain during an OBE and she will present evidence that these are caused by abnormal functioning in parts of the brain that process and combine signals from our bodies. This research on neurological patients sheds light on how the healthy brain generates the experience of one’s self, and what happens when that construction temporarily goes ‘wrong’.
Reliable sensory processing in mouse visual cortex through cooperative interactions between somatostatin and parvalbumin interneurons
by Rikhye RV, Yildirim M, Hu M, Breton-Provencher V, Sur M. in J Neurosci
When it comes to processing vision, the brain is full of noise. Information moves from the eyes through many connections in the brain. Ideally, the same image would be reliably represented the same way each time, but instead different groups of cells in the visual cortex can become stimulated by the same scenes. So how does the brain ultimately ensure fidelity in processing what we see? A team of neuroscientists in The Picower Institute for Learning and Memory at MIT found out by watching the brains of mice while they watched movies.
What the researchers discovered is that while groups of “excitatory” neurons respond when images appear, thereby representing them in the visual cortex, activity among two types of “inhibitory” neurons combines in a neatly arranged circuit behind the scenes to enforce the needed reliability. The researchers were not only able to see and analyze the patterns of these neurons working, but also once they learned how the circuit operated, they took control of the inhibitory cells to directly manipulate how consistently excitatory cells represented images.
“The question of reliability is hugely important for information processing and particularly for representation — in making vision valid and reliable,” said Mriganka Sur, Newton Professor of Neuroscience in MIT’s Department of Brain and Cognitive Sciences and senior author of the new study in the Journal of Neuroscience. “The same neurons should be firing in the same way when I look at something, so that the next time and every time I look at it, it’s represented consistently.”
Research scientist Murat Yildirim and former graduate student Rajeev Rikhye led the study, which required a number of technical feats. To watch hundreds of excitatory neurons and two different inhibitory neurons at work, for instance, they needed to engineer them to flash in distinct colors under different colors of laser light in their two-photon microscope. Taking control of the cells using a technology called “optogenetics” required adding even more genetic manipulations and laser colors. Moreover, to make sense of the cellular activity they were observing, the researchers created a computer model of the tripartite circuit.
“It was exciting to be able to combine all these experimental elements, including multiple different laser colors, to be able to answer this question,” Yildirim said.
The team’s main observation was that as mice watched the same movies repeatedly, the reliability of representation among excitatory cells varied along with the activity levels of two different inhibitory neurons. When reliability was low, activity among parvalbumin-expressing (PV) inhibitory neurons was high and activity among somatostatin-expressing (SST) neurons was low. When reliability was high, PV activity was low and SST activity was high. They also saw that SST activity followed PV activity in time after the excitatory activity had become unreliable.
PV neurons inhibit excitatory activity to control their gain, Sur said. If they didn’t, excitatory neurons would become saturated amid a flood of incoming images and fail to keep up. But this gain suppression apparently comes at the cost of making representation of the same scenes by the same cells less reliable, the study suggests. SST neurons meanwhile, can inhibit the activity of PV neurons. In the team’s computer model, they represented the tripartite circuit and were able to see that SST neuron inhibition of PV neurons kicks in when excitatory activity has become unreliable.
The team was able to directly show this dynamic by taking control of PV and SST cells with optogenetics. For instance, when they increased SST activity they could make unreliable neuron activity more reliable. And when they increased PV activity, they could ruin reliability if it was present.
Importantly, though, they also saw that SST neurons cannot enforce reliability without PV cells being in the mix. They hypothesize that this cooperation is required because of differences in how SST and PV cells inhibit excitatory cells. SST cells only inhibit excitatory cell activity via connections, or “synapses,” on the spiny tendrils called dendrites that extend far out from the cell body, or “soma.” PV cells inhibit activity at the excitatory cell body itself. The key to improving reliability is enabling more activity at the cell body. To do that, SST neurons must therefore inhibit the inhibition provided by PV cells. Meanwhile, suppressing activity in the dendrites might reduce noise coming into the excitatory cell from synapses with other neurons.
“We demonstrate that the responsibility of modulating response reliability does not lie exclusively with one neuronal subtype,” the authors wrote in the study. “Instead, it is the co-operative dynamics between SST and PV [neurons] which is important for controlling the temporal fidelity of sensory processing. A potential biophysical function of the SSTàPV circuit may be to maximize the signal-to-noise ratio of excitatory neurons by minimizing noise in the synaptic inputs and maximizing spiking at the soma.”
Sur noted that the activity of SST neurons is not just modulated by automatic feedback from within this circuit. They might also be controlled by “top down” inputs from other brain regions. For instance, if we realize a particular image or scene is important, we can volitionally concentrate on it. That may be implemented by signaling SST neurons to enforce greater reliability in excitatory cell activity.
Cerebral μ-opioid and CB1 receptor systems have distinct roles in human feeding behavior
by Tatu Kantonen, Tomi Karjalainen, Laura Pekkarinen, Janne Isojärvi, Kari Kalliokoski, Valtteri Kaasinen, Jussi Hirvonen, Pirjo Nuutila, Lauri Nummenmaa in Translational Psychiatry
Brain regulation of feeding behavior traits has remained incompletely understood. In their latest study, researchers at the Turku PET Centre, Finland, discovered a connection between the function of the opioid system and food craving triggered by appetitive external stimuli.
Animal studies have established that the brain’s opioid and endocannabinoid systems are important in regulating eating behavior and mediate the food reward experience. For instance, alterations in these systems’ signaling have been associated with obesity. In general, both internal signals of the body, such as fluctuation in blood sugar levels, and external stimuli, such as food advertisements, can spark an appetite in humans.
In their new study, researchers at the University of Turku, Finland, investigated the connection between the brain’s opioid and endocannabinoid signaling and different types of eating behavior. They discovered that the function of the opioid system is connected to eating triggered by external stimuli.
“The less binding sites there were for the opioids, the greater was the tendency to eat in response to external stimuli, such as seeing appetizing food. Moreover, the number of binding sites for endocannabinoids was connected to several different types of eating behavior, describes first author,” Doctoral Candidate Tatu Kantonen from the University of Turku.
According to Kantonen, the results indicate that especially the opioid system could be a potential target for anti-obesity drugs in humans.
‘Seeing’ proximal representations: Testing attitudes to the relationship between vision and images
by Samuel S, Hagspiel K, Cole GG, Eacott MJ in PLOS ONE
We are all used to seeing the 3D world that we live in reduced to 2D, whether in art, photography, or film. But, when we close our eyes, how do we visualize things that we have already seen? A new study led by the Universities or Plymouth and Essex investigated this question, discovering that many adults are resistant to imagining their own vision as if it were a flat image — seeing it in its fully processed, knowledge-laden form instead.
The results came as the researchers showed 58 adults two lines on a wall, both of which were the same length but one was closer to the participant and hence appeared visually longer (see picture attached).
Despite the instruction to base their judgements on appearance specifically (ie the closer line should be longer) approximately half of the participants judged the lines to appear the same. When they took a photo of the lines and were asked how long they appeared in the image their responses shifted; now the closer line appeared longer. However, when they were asked again about their own view they reverted to their original response.
This suggests that even when participants are made explicitly aware of what a 2D image of their vision might look like they treated actual sensory input differently — with considerable resistance to seeing what are called our “proximal representations” of vision (how things appear before our brains have had a chance to correct for things like relative size and distance).
Lead author Dr Steven Samuel, a Lecturer in Psychology at the University of Plymouth, said: “It’s complex and exciting to uncover how each of us sees and visualises different things — and the fact that half of our study population did not think in 2D was a very interesting finding.
“The next question to ask is why did these people think in that way? Is it that they could not think in 2D, or that they chose not to? We do not know for certain, but one explanation is that people are resistant to the principle that vision can be equated to a flat image — with ‘corrected’ vision the only type of vision they could reasonably conceive of. This implies that adults are disinclined to entertain vision in as a proximal image, even when the context is favourable to such behaviour. However, it does not mean that they are necessarily unable to do so.”
Exploratory fNIRS Assessment of Differences in Activation in Virtual Reality Visual Self-Expression Including With a Fragrance Stimulus
by Girija Kaimal, Katrina Carroll-Haskins, Yigit Topoglu, Arun Ramakrishnan, Asli Arslanbek, Hasan Ayaz in Art Therapy
Virtual reality (VR) continues to expand its uses in medicine, specifically in treatments for psychological conditions like trauma, phobias and eating disorders. The technology is also emerging as a tool in creative arts therapies. In one of the first studies of its kind, researchers from Drexel University’s College of Nursing and Health Professions and School of Biomedical Engineering, Science and Health Systems, examined the differences in prefrontal cortex (PFC) activation between two distinct drawing tasks in VR, including with the introduction of a calming fragrance stimulus.
Results of the study indicated significant differences between a rote tracing task and a creative self-expression task, with the rote tracing task showing an increase in PFC activity. It also showed there was reduced PFC activation for creative self-expressive tasks, indicating a possible relaxation response.
“The study demonstrates that repetitive tasks, like rote tracing, can enhance focus and the creative self-expressive tasks can reduce PFC load and induce relaxation and flow. The findings offer evidence for therapeutic aspects of creative self-expression,” said the study’s lead author Girija Kaimal, EdD, an associate professor in the College of Nursing and Health Professions.
Because VR makes participants detach temporarily from their physical reality into a virtual space, the sense of smell was considered in this study as an impactful stimulus, and also to promote a sense of awareness and grounding during the artmaking tasks. Although there was no significant impact of fragrance overall on PFC activation, emergent differences in responsiveness to fragrance were seen by age and gender. A fragrance, consisting of a blend of essential oils, was diffused into the lab on alternating weeks and dissipated within 30 minutes after turning off the diffuser.
Participants of the study included 24 adults (18 women and six men) ranging in age from 18 to 54. They attended two one-hour sessions, scheduled at least one week apart. Participants were blinded to the fragrance stimulus and were assigned to receive either the fragrance or the non-fragrance condition for the first session through a simple randomization plan.
During the sessions, participants wore an optical brain imaging sensor — the functional near-infrared spectroscopy (fNIRS) — to measure brain function while they engaged in VR artmaking. fNIRS has been used to monitor underlying mechanisms in neural functioning, including creativity and neural functioning. Each participant’s PFC was monitored throughout the entire time the participants were engaged with the artmaking and rest conditions. fNIRS served as an objective biomarker of PFC activation in response to drawing tasks. Participants also wore a VR headset, with hand-controller equipment, that used the virtual software program, Tilt Brush by Google, to create 3-D drawings in VR.
“Wearable optical neuroimaging enables continuous measurement of brain function during VR use and allows studying natural dynamic processes like creating art in virtual spaces,” said Hasan Ayaz, PhD, an associate professor in the School of Biomedical Engineering, Science and Health Systems, and co-author of the study.
The facilitator of the session, an art therapist, read from a protocol script with step by step instructions for the two VR drawing tasks. The rote tracing consisted of tracing basic shapes on a pre-drawn virtual template, while the creative self-expression consisted of participants creating an adapted version of the scribble drawing technique, an approach frequently used in art therapy to encourage creativity and spontaneous artistic expression. Each drawing task lasted approximately five minutes, with participants completing both tasks during the session. The directives were created also to align with the experimental method enabling comparable conditions between the rote task and the creative task.
“The findings also highlight how drawing tasks can potentially be used in tandem to engage different brain networks in patients,” said Kaimal.
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