Category Archives: Neuroscience

Neuroscience

AI’s memory-forming mechanism found to be strikingly similar to that of the brain – EurekAlert

image:

(a) Diagram illustrating the ion channel activity in post-synaptic neurons. AMPA receptors are involved in the activation of post-synaptic neurons, while NMDA receptors are blocked by magnesium ions (Mg) but induce synaptic plasticity through the influx of calcium ions (Ca) when the post-synaptic neuron is sufficiently activated. (b) Flow diagram representing the computational process within the Transformer AI model. Information is processed sequentially through stages such as feed-forward layers, layer normalization, and self-attention layers. The graph depicting the current-voltage relationship of the NMDA receptors is very similar to the nonlinearity of the feed-forward layer. The input-output graph, based on the concentration of magnesium (), shows the changes in the nonlinearity of the NMDA receptors.

Credit: Institute for Basic Science

An interdisciplinary team consisting of researchers from the Center for Cognition and Sociality and the Data Science Group within the Institute for Basic Science (IBS) revealed a striking similarity between the memory processing of artificial intelligence (AI) models and the hippocampus of the human brain. This new finding provides a novel perspective on memory consolidation, which is a process that transforms short-term memories into long-term ones, in AI systems.

In the race towards developing Artificial General Intelligence (AGI), with influential entities like OpenAI and Google DeepMind leading the way, understanding and replicating human-like intelligence has become an important research interest. Central to these technological advancements is the Transformer model [Figure 1], whose fundamental principles are now being explored in new depth.

The key to powerful AI systems is grasping how they learn and remember information. The team applied principles of human brain learning, specifically concentrating on memory consolidation through the NMDA receptor in the hippocampus, to AI models.

The NMDA receptor is like a smart door in your brain that facilitates learning and memory formation. When a brain chemical called glutamate is present, the nerve cell undergoes excitation. On the other hand, a magnesium ion acts as a small gatekeeper blocking the door. Only when this ionic gatekeeper steps aside, substances are allowed to flow into the cell. This is the process that allows the brain to create and keep memories, and the gatekeeper's (the magnesium ion) role in the whole process is quite specific.

The team made a fascinating discovery: the Transformer model seems to use a gatekeeping process similar to the brain's NMDA receptor [see Figure 1]. This revelation led the researchers to investigate if the Transformer's memory consolidation can be controlled by a mechanism similar to the NMDA receptor's gating process.

In the animal brain, a low magnesium level is known to weaken memory function. The researchers found that long-term memory in Transformer can be improved by mimicking the NMDA receptor. Just like in the brain, where changing magnesium levels affect memory strength, tweaking the Transformer's parameters to reflect the gating action of the NMDA receptor led to enhanced memory in the AI model. This breakthrough finding suggests that how AI models learn can be explained with established knowledge in neuroscience.

C. Justin LEE, who is a neuroscientist director at the institute, said, This research makes a crucial step in advancing AI and neuroscience. It allows us to delve deeper into the brain's operating principles and develop more advanced AI systems based on these insights.

CHA Meeyoung, who is a data scientist in the team and at KAIST, notes, The human brain is remarkable in how it operates with minimal energy, unlike the large AI models that need immense resources. Our work opens up new possibilities for low-cost, high-performance AI systems that learn and remember information like humans.

What sets this study apart is its initiative to incorporate brain-inspired nonlinearity into an AI construct, signifying a significant advancement in simulating human-like memory consolidation. The convergence of human cognitive mechanisms and AI design not only holds promise for creating low-cost, high-performance AI systems but also provides valuable insights into the workings of the brain through AI models.

Experimental study

Not applicable

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Neuroscience

Navigating the neuroscientific landscape with Dr Judy Illes – Drug Target Review

In a world grappling with the growing spectre of eco-anxiety and the pressing challenges posed by climate change, Dr Judy Illes, a distinguished figure in the field of neuroscience, sheds light on the role neuroscientists play in contributing to the discourse on environmental issues and their profound impact on individual and collective well-being. In this interview, Judy emphasises the need for evidence-based neuroscience to address the mental health implications of environmental changes, urging a departure from geographical silos to foster global collaboration. The discussion extends to strategies for disseminating neuroscientific research across diverse cultural landscapes and the practical implications of bridging the gap between research and public awareness.

I dont think it is a question of neuroscientists having to shoulder the responsibility of responding to and addressing questions of eco-anxiety, climate change, and environmental change, but rather a matter of upping the interest in this space and delivering more evidence through great research. We need more good neuroscience discovery and meaningful clinical translation to address the issues that were seeing and that are being debated. On the mental health side, there is anxiety around climate change Eco-Anxiety. On the neurologic side, there are findings about neurotoxins and environmental contaminants showing correlations with a variety of neurologic diseases across the lifespan from children to adults. Good study design, solid evidence, and good information dissemination with explicit evidence-based mitigation of misinformation will really contribute to climate change and environmental decision-making, policymaking, and improvements in brain-related health systems and care.

That is such an important question and it speaks directly to the global movement in neuroscience today. Global neuroscience cross-national, cross-geographic collaboration is so important to bring the kind of evidence about which I spoke in response to your first question. There is no point in addressing climate change, environmental change, contaminants from neurotoxins and so on in geographic silos. These affect all people across all nations. We have so much to learn from each other. We have different perspectives, different languages, and potentially different belief systems. When we combine these into an integrated, concerted collaborative program, we will be able to advance the kind of neuroscience that I hope that my lecture at the Society for Neuroscience inspired and also help to propel forward the work of the International Brain Initiative whose headquarters reside with me now in Canada. This is precisely what were trying to achieve: geopolitically conscious, border-free global cooperation in neuroscience.

This question is a good segue from the previous one. Thank you. First, let me say that I am a person of European background and I have had the privilege and the honour of working with indigenous peoples across Canada to learn about indigenous ways of knowing, of knowledge, of methods. My team has done empirical work through systematic literature reviews, scoping reviews, and a variety of research collaborations with indigenous Canadian people. I am also currently working around questions about portable MRI, for example, with colleagues across the USA, led by the University of Minnesota, to understand the important relationships and ethical considerations that come into play when were talking about work, research, and clinical translation that has to do with expanded access to MRI scanning with people from multiple cultures, and many who are in rural and remote regions of North America and the world.

With that preamble, to respond, I respectfully refer to Elder Albert Marshall and to what he called two-eyed seeing, which is a powerful way to bring together traditional belief systems, rooted in the medicine wheel, holism, relationships with the land and the earth, sky, water, air and fire, with biomedical explanations of mental health and neurologic disease. On the neuroscience side, we think about cells to systems: genes, brain development, demyelination, degeneration. It is equally meaningful to integrate this thinking with learnings and knowledge that preceded our understanding about genes and neuroanatomy and neurophysiology. In the past, we to dismissed traditional forms of belief systems. Today, we are seeing through the work of people in neuroscience, health sciences, ethics and law, anthropology and sociology that coupling the two can really bring wellness to an understanding of some of the major burdens of brain and mental health that affect people and societies today.

Again, a wonderful question, Taylor. So there are innumerable strategies. I will only mention three that immediately come to mind.

The first is about data and evidence. Evidence, good science, and design that takes into account not only Western approaches but approaches from different people of different backgrounds and ways of knowing and doing that might date back to time immemorial. That is number one: data, and irrefutable evidence that are respectful of all methods of doing.

The second is working collaboratively in a very engaged way with people of different cultures and different geographies, whether they are Elders from communities or whether they are neuroscientists from different communities and geographic locations. In this way, the maximum breadth and potential of neuroscience discovery will be realised.

The third is collaboration among people who have expertise in the ethics of communication and dissemination of results, or with science communicators to maximize not only what results or findings are disseminated but how they are disseminated. That takes the form of K-12 teaching, undergraduate teaching, graduate teaching, postdoctoral teaching, teaching and communicating throughout the academic ranks, and equally importantly, through public outreach. I think what weve seen over the past 25 years of neuroethics is a tremendous improvement in the way that science reporting is taking place around brain and mind around neuroscience. There really is a commitment, I believe, to working in a far more reciprocal way between the communication side and the science side to ensure that what gets out there is meaningful and appropriately-tailored to distinct audiences. It is multi-layered. It starts well before data collection, at the design and planning phases of research, and then all the way through engaging with the public as I mentioned, and with students of all ages.

I think the responsible way to answer your question is to speak to the importance of systematic neuroscience discovery and systematic engagement. A very small study pharmacologic, behavioral, whatever that is robust can have a huge impact on changing the way health and policymakers think about an aspect of climate change, or a neurotoxin. For example, in my lecture, I spoke about glyphosates. I talked about methylmercury. Neuroscientists could not possibly take on the whole scope of neurotoxic contaminants for a research platform. The challenge is to choose one, choose an important one, and help decode and disentangle why there seems to be still controversies and debates around harms versus benefits that are leading to heterogeneous and conflicting international policies. Solve critical questions for one neurotoxin. Then move on to the next.

I talked a lot about fracking and how data show that the pushing hydrochloric acid into the earth to create fissures not great for the environment, for keeping the land and water clean, or for ensuring that traditional relationships with the land are preserved. The risk of fracking have to be taken in balance though with the economic benefits to communities that dont have a lot of resources, for example, and may even be faced with food and water security. We must look at harms and benefits always, always in balance. We have to take these problems and tackle them bit by bit. Climate change, too big as a whole. But finding ways to protect children with severe brain disorders such as epilepsy whose condition might be exacerbated by extreme heat that can be tackled. Environmental change with respect to neurotoxins too big. Discovering and addressing differential proximate and epigenetic effects of different neurotoxins that can be tackled.

Neuroscience requires patience and systematic, rigorous deliberate methods. Today there is a new openness to thinking about all aspects of what results may suggest and how they may inform how people behave, govern, and invest in each other going forward.

About the author

Dr Judy Illes, CM, PhD, FCAHS, FRSC

University of British Columbia (UBC)

Dr Judy Illes is Professor of Neurology at the University of British Columbia (UBC),Distinguished University Scholar, UBC Distinguished Scholar in Neuroethics, and Director of Neuroethics Canada. She is a pioneer of the field of neuroethics through which she has made groundbreaking contributions to cross-cultural ethical, legal, social and policy challenges at the intersection of the brain sciences and biomedical ethics. Among her many commitments, she is Chair of the International Brain Initiative and co-Lead of the IBIs Canadian Brain Research Strategy. She serves as Director-at-Large of the Canadian Academy of Health Sciences,and is a member of the Ethics, Law and Humanities Committee of the American Academy of Neurology.

Dr Illes is the immediate past Vice Chair of the Advisory Board of the Institute for Neuroscience, Mental Health and Addiction of the Canadian Institutes of Health Research (CIHR), and of CIHRs Standing Committee on Ethics.Her recent books, a series calledDevelopments in Neuroethics and Bioethics, focus on pain, global mental health, neurotechnology, transnational laws, environmental neuroethics, neurodevelopment, and neuroAI. Dr Illes was awarded the Order of Canada, the countrys highest recognition of its citizens, in 2017.

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Neuroscience

URI’s new neuro-learning center to boost brain education – EurekAlert

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A young study participant wears a functional Near Infrared Spectroscopy system cap, which allows neuro scientists to measure brain activity by monitoring changes in blood flow in the brain.

Credit: Submitted Photo

University of Rhode Island students and faculty members in multiple health disciplines will soon have access to state-of-the-art neuroscientific technology to enhance classroom lessons and research education, thanks to a grant from the Champlin Foundation.

College of Health Sciences Professors Mariusz Furmanek and Alisa Baron, along with collaborators Mark Hartman, Nicole Logan, Ellen McGough and Kunal Mankodiya, will establish a Neuro-Learning Center that includes some of the most cutting-edge equipment available to neuroscientific researchers, allowing for the non-invasive study of relationships between brain activity and behavior, functional brain mapping, and mechanisms of neuroplasticity. The equipment will be available to undergraduate and graduate students as well as faculty in such disciplines as communicative disorders, physical therapy, kinesiology and biomedical engineering.

We are planning to establish the Neuro-Learning Center, which will allow that interdisciplinary interaction with faculty members from different departments, Furmanek said. In the majority of institutions, these are only used for research. Primarily, we would use them for education. There is, of course, a research component with this equipment, but the primary goal is to educate our students in neuroscience and knowledge about the brain.

The non-invasive technology includes a Transcranial Magnetic Stimulation system, which uses low-intensity magnetic stimulation to facilitate or inhibit neural activity in areas of the brain; and a functional Near Infrared Spectroscopy system (fNIRS), which is an advanced neuroimaging technique used to measure brain activity by monitoring changes in blood flow in the brain. The TMS is used in conjunction with a NeuroNavigation System to target specific areas of the brain for neurostimulation. Basically, the technology will allow students to look at specific areas of the brain and determine which areas of the brain are active and which should be stimulated.

Its a cap thats put on the head and it can be configured in any way depending on the part of the brain you want to look at, Baron said of the fNIRS system. You put the sources and detectors in the areas you are interested in on the scalp, and when a participant does a particular task, you can analyze the data to see what part of the brain lights upthe part of the brain that has more blood circulating to it. That shows the part of the brain that is the most active in trying to process that information from whatever task youre asking the participant to do. This is a non-invasive system thats used across the lifespan, which is a big benefit since a lot of people think of an MRI when thinking about neuroimaging techniques, having to put people into a scanner thats quite loud and not child friendly.

The systems are essential to study, diagnose and treat neurological diseases, such as depression, Alzheimers, Parkinsons, stroke and more. Both systems can be used together by multiple clinicians. For example, the fNIRS system can identify parts of the brain that have died or have decreased function due to a stroke. Physical therapists can then use the TMS system to apply stimulation to those parts of the brain. If needed, a neurosurgeon would use the NeuroNavigation system to improve precision and safety of surgery, then a speech language pathologist could use fNIRS again to examine the post-procedure brain activity and its impact on communication.

Such a collaborative and interdisciplinary approach will be emphasized when teaching our students to ensure the patients comprehensive care and recovery, the professors wrote in their funding proposal. There have been rapid advancements in the neuroscience field, including the types of equipment used. University courses and the training they provide must simultaneously evolve to ensure students are familiar with the techniques and technologies that will be utilized during their careers in patient care and research.

Having the advanced equipment available to undergraduate students will be unique to URI. Furmanek and Baron are unaware of any other institutions that have the equipment for training undergraduate students and early-career graduate students, despite their widespread use by researchers and clinicians in the field. As important as the research capabilities is the educational component for students seeking careers in multiple health disciplines.

The huge benefit to these systems is their portability. We can actually take them into the classroom so students can see how to use it, how to put it on someone, how to analyze the data, all in the classroom without having to pull them out of the class into the lab, Baron said. A lot of these technologies are only available in laboratory spaces, which creates a lot of inequity for students. Were getting students access to these technologies early so they can understand and get comfortable using them, so thats one more marketable skill when they go on the job market.

Baron and Furmanek expect to begin acquiring the advanced technology in the spring, and expect to have it available for classroom use by fall 2024. The Neuro-Learning Center and the equipment will be housed between Furmaneks and Barons labs in Independence Square on the Kingston campus.

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Neuroscience

Metabolic Markers of Depression Identified – Neuroscience News

Summary: Researchers revealed a crucial link between cellular metabolism and major depressive disorder, particularly in treatment-refractory cases and suicidal ideation. This research found specific blood metabolites that differ in people with depression, providing new biomarkers for risk assessment.

The study also highlights sex-based differences in depressions metabolic impact and suggests that mitochondrial dysfunction plays a role in suicidal ideation. These insights offer new avenues for personalized treatment and prevention strategies, potentially utilizing supplements like folate and carnitine to address metabolic gaps.

Key Facts:

Source: UCSD

Major depressive disorder affects 16.1 million adults in the United States and costs $210 billion annually. While the primary symptoms of depression are psychological, scientists and doctors have come to understand that depression is a complex disease with physical effects throughout the body.

For example, measuring markers of cellular metabolism has become an important approach to studying mental illnesses and developing new ways to diagnose, treat and prevent them.

Researchers at University of California San Diego School of Medicine have now advanced this line of work in a new study, revealing a connection between cellular metabolism and depression.

They found that people with depression and suicidal ideation had detectable compounds in their blood that could help identify individuals at higher risk of becoming suicidal. The researchers also found sex-based differences in how depression impacts cell metabolism.

The findings, published December 15, 2023 inTranslational Psychiatry, could help personalize mental health care and potentially identify new targets for future drugs.

Mental illnesses like depression have impacts and drivers well beyond the brain, saidRobert Naviaux, MD, PhD, a professor in the Department of Medicine, Pediatrics and Pathology at UC San Diego School of Medicine.

Prior to about ten years ago it was difficult to study how the chemistry of the whole body influences our behavior and state of mind, but modern technologies like metabolomics are helping us listen in on cells conversations in their native tongue, which is biochemistry.

While many people with depression experience improvement with psychotherapy and medication, some peoples depression is treatment-refractory, meaning treatment has little to no impact. Suicidal thoughts are experienced by the majority of patients with treatment-refractory depression, and as many as 30% will attempt suicide at least once in their lifetime.

Were seeing a significant rise in midlife mortality in the United States, and increased suicide incidence is one of many things driving that trend, said Naviaux. Tools that could help us stratify people based on their risk of becoming suicidal could help us save lives.

The researchers analyzed the blood of 99 study participants with treatment-refractory depression and suicidal ideation, as well as an equal number of healthy controls.

Among the hundreds of different biochemicals circulating in the blood of these individuals, they found that five could be used as a biomarker to classify patients with treatment-refractory depression and suicidal ideation. However, which five could be used differed between men and women.

If we have 100 people who either dont have depression or who have depression and suicidal ideation, we would be able to correctly identify 85-90 of those at greatest risk based on five metabolites in males and another 5 metabolites in females, said Naviaux.

This could be important in terms of diagnostics, but it also opens up a broader conversation in the field about whats actually leading to these metabolic changes.

While there were clear differences in blood metabolism between males and females, some metabolic markers of suicidal ideation were consistent across both sexes. This included biomarkers for mitochondrial dysfunction, which occurs when the energy-producing structures of our cells malfunction.

Mitochondria are some of the most important structures of our cells and changed mitochondrial functions occur in a host of human diseases, added Naviaux.

Mitochondria produce ATP, the primary energy currency of all cells. ATP is also an important molecule for cell-to-cell communication, and the researchers hypothesize it is this function that is most dysregulated in people with suicidal ideation.

When ATP is inside the cell it acts like an energy source, but outside the cell it is a danger signal that activates dozens of protective pathways in response to some environmental stressor, said Naviaux.

We hypothesize that suicide attempts may actually be part of a larger physiological impulse to stop a stress response that has become unbearable at the cellular level.

Because some of the metabolic deficiencies identified in the study were in compounds that are available as supplements, such as folate and carnitine, the researchers are interested in exploring the possibility of individualizing depression treatment with these compounds to help fill in the gaps in metabolism that are needed for recovery. Naviaux hastens to add that these supplements are not cures.

None of these metabolites are a magic bullet that will completely reverse somebodys depression, said Naviaux.

However, our results tell us that there may be things we can do to nudge the metabolism in the right direction to help patients respond better to treatment, and in the context of suicide, this could be just enough to prevent people from crossing that threshold.

In addition to suggesting a new approach to personalize medicine for depression, the research could help scientists discover new drugs that can target mitochondrial dysfunction, which could have wide implications for human health in general.

Many chronic diseases are comorbid with depression, because it can be extremely stressful to deal with an illness for years at a time, said Naviaux.

If we can find ways to treat depression and suicidal ideation on a metabolic level, we may also help improve outcomes for the many diseases that lead to depression.

Many chronic illnesses, such as post-traumatic stress disorder and chronic fatigue syndrome, are not lethal themselves unless they lead to suicidal thoughts and actions. If metabolomics can be used to identify the people at greatest risk, it could ultimately help us save more lives.

Co-authors include: Jane C. Naviaux, Lin Wang, Kefeng Li, Jonathan M. Monk and Sai Sachin Lingampelly at UC San Diego, Lisa A. Pan, Anna Maria Segreti, Kaitlyn Bloom, Jerry Vockley, David N. Finegold and David G. Peters at University of Pittsburgh School of Medicine, and Mark A. Tarnopolsky at McMaster University.

Author: Miles Martin Source: UCSD Contact: Miles Martin UCSD Image: The image is credited to Neuroscience News

Original Research: Open access. Metabolic features of treatment-refractory major depressive disorder with suicidal ideation by Robert Naviaux et al. Translational Psychiatry

Abstract

Metabolic features of treatment-refractory major depressive disorder with suicidal ideation

Peripheral blood metabolomics was used to gain chemical insight into the biology of treatment-refractory Major Depressive Disorder with suicidal ideation, and to identify individualized differences for personalized care.

The study cohort consisted of 99 patients with treatment-refractory major depressive disorder and suicidal ideation (trMDD-SIn=52 females and 47 males) and 94 age- and sex-matched healthy controls (n=48 females and 46 males). The median age was 29 years (IQR 2242). Targeted, broad-spectrum metabolomics measured 448 metabolites. Fibroblast growth factor 21 (FGF21) and growth differentiation factor 15 (GDF15) were measured as biomarkers of mitochondrial dysfunction.

The diagnostic accuracy of plasma metabolomics was over 90% (95%CI: 0.801.0) by area under the receiver operator characteristic (AUROC) curve analysis. Over 55% of the metabolic impact in males and 75% in females came from abnormalities in lipids.

Modified purines and pyrimidines from tRNA, rRNA, and mRNA turnover were increased in the trMDD-SI group. FGF21 was increased in both males and females. Increased lactate, glutamate, and saccharopine, and decreased cystine provided evidence of reductive stress. Seventy-five percent of the metabolomic abnormalities found were individualized.

Personalized deficiencies in CoQ10, flavin adenine dinucleotide (FAD), citrulline, lutein, carnitine, or folate were found. Pathways regulated by mitochondrial function dominated the metabolic signature.

Peripheral blood metabolomics identified mitochondrial dysfunction and reductive stress as common denominators in suicidal ideation associated with treatment-refractory major depressive disorder.

Individualized metabolic differences were found that may help with personalized management.

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Neuroscience

Brain Imaging Reveals Altered Brain Connectivity in Autism – Neuroscience News

Summary: Researchers advanced brain imaging and machine learning to uncover altered functional brain connectivity in individuals with Autism Spectrum Disorder (ASD), acknowledging the diversity within the disorder.

The research distinguishes between shared and individual-specific connectivity patterns in ASD, revealing both common and unique brain alterations. This approach marks a significant shift from group-based analysis to a more personalized understanding of ASD.

The findings open pathways for tailored treatments, addressing the unique needs of individuals with ASD.

Key Facts:

Source: Elsevier

What happens in the brain to cause many neurodevelopmental disorders, including autism spectrum disorder (ASD), remains a mystery. A major limitation for researchers is the lack of biomarkers, or objective biological outputs, for these disorders, and in the case of ASD, for specific subtypes of disease.

Now, anew studyuses brain imaging and machine learning to identify altered functional brain connectivity (FC) in people with ASD importantly, taking into consideration differences between individuals.

The study appears inBiological Psychiatry, published by Elsevier.

John Krystal, MD, Editor ofBiological Psychiatry, said of the work,ASD has long been known to be a highly heterogeneous condition. While genetic studies have provided some clues to different causes of the disorder in different groups of ASD patients, it has been challenging to separate subtypes of ASD using other types of biomarkers, such as brain imaging.

Brain imaging scans are also extremely heterogenous, varying greatly from one individual to another, making such data difficult to use as a biomarker. Previous studies have identified both increased and decreased FC in people with ASD compared to healthy controls, but because those studies focused on groups of participants, they failed to appreciate heterogeneous autism-related atypical FC.

In the new study, the researchers showed that although heterogenous brain imaging subtypes could be distinguished among participants with ASD.

Xujun Duan, PhD, senior author of the work at the University of Electronic Science and Technology of China, explained,In this study, we used a technique to project altered FC of autism onto two subspaces: an individual-shared subspace, which represents altered connectivity pattern shared across autism, and an individual-specific subspace, which represents the remaining individual characteristics after eliminating the individual-shared altered connectivity patterns.

The investigators found that the individual-shared subspace altered FC of autism reflects differences at the group level, while individual-specific subspace altered FC represents individual variation in autistic traits. These findings suggest a requirement to move beyond group effects and to capture and capitalize on the individual-specific brain features for dissecting clinical heterogeneity.

Dr. Krystal added,Part of the challenge to finding subtypes of ASD has been the enormous complexity of neuroimaging data. This study uses a sophisticated computational approach to identify aspects of brain circuit alterations that are common to ASD and others that are associated with particular ASD traits.

This type of strategy may help to more effectively guide the development of personalized treatments for ASD, i.e., treatments that meet the specific needs of particular patients.

Author: Eileen Leahy Source: Elsevier Contact: Eileen Leahy Elsevier Image: The image is credited to Neuroscience News

Original Research: Open access. Disentangling the Individual-Shared and Individual-Specific Subspace of Altered Brain Functional Connectivity in Autism Spectrum Disorder by Xujun Duan et al. Biological Psychiatry

Abstract

Disentangling the Individual-Shared and Individual-Specific Subspace of Altered Brain Functional Connectivity in Autism Spectrum Disorder

Despite considerable effort toward understanding the neural basis of autism spectrum disorder (ASD) using case-control analyses of resting-state functional magnetic resonance imaging data, findings are often not reproducible, largely due to biological and clinical heterogeneity among individuals with ASD. Thus, exploring the individual-shared and individual-specific altered functional connectivity (AFC) in ASD is important to understand this complex, heterogeneous disorder.

We considered 254 individuals with ASD and 295 typically developing individuals from the Autism Brain Imaging Data Exchange to explore the individual-shared and individual-specific subspaces of AFC. First, we computed AFC matrices of individuals with ASD compared with typically developing individuals. Then, common orthogonal basis extraction was used to project AFC of ASD onto 2 subspaces: an individual-shared subspace, which represents altered connectivity patterns shared across ASD, and an individual-specific subspace, which represents the remaining individual characteristics after eliminating the individual-shared altered connectivity patterns.

Analysis yielded 3 common components spanning the individual-shared subspace. Common components were associated with differences of functional connectivity at the group level. AFC in the individual-specific subspace improved the prediction of clinical symptoms. The default mode networkrelated and cingulo-opercular networkrelated magnitudes of AFC in the individual-specific subspace were significantly correlated with symptom severity in social communication deficits and restricted, repetitive behaviors in ASD.

Our study decomposed AFC of ASD into individual-shared and individual-specific subspaces, highlighting the importance of capturing and capitalizing on individual-specific brain connectivity features for dissecting heterogeneity. Our analysis framework provides a blueprint for parsing heterogeneity in other prevalent neurodevelopmental conditions.

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Brain Imaging Reveals Altered Brain Connectivity in Autism - Neuroscience News

Neuroscience

AI Vulnerabilities Exposed: Adversarial Attacks More Common and Dangerous Than Expected – Neuroscience News

Summary: A new study reveals that artificial intelligence systems are more susceptible to adversarial attacks than previously believed, making them vulnerable to manipulation that can lead to incorrect decisions.

Researchers found that adversarial vulnerabilities are widespread in AI deep neural networks, raising concerns about their use in critical applications. To assess these vulnerabilities, the team developed QuadAttacK, a software that can test neural networks for susceptibility to adversarial attacks.

The findings highlight the need to enhance AI robustness against such attacks, particularly in applications with potential human life implications.

Key Facts:

Source: North Carolina State University

Artificial intelligence tools hold promise for applications ranging from autonomous vehicles to the interpretation of medical images. However, a new study finds these AI tools are more vulnerable than previously thought to targeted attacks that effectively force AI systems to make bad decisions.

At issue are so-called adversarial attacks, in which someone manipulates the data being fed into an AI system in order to confuse it. For example, someone might know that putting a specific type of sticker at a specific spot on a stop sign could effectively make the stop sign invisible to an AI system. Or a hacker could install code on an X-ray machine that alters the image data in a way that causes an AI system to make inaccurate diagnoses.

For the most part, you can make all sorts of changes to a stop sign, and an AI that has been trained to identify stop signs will still know its a stop sign, says Tianfu Wu, co-author of a paper on the new work and an associate professor of electrical and computer engineering at North Carolina State University.

However, if the AI has a vulnerability, and an attacker knows the vulnerability, the attacker could take advantage of the vulnerability and cause an accident.

The new study from Wu and his collaborators focused on determining how common these sorts of adversarial vulnerabilities are in AI deep neural networks. They found that the vulnerabilities are much more common than previously thought.

Whats more, we found that attackers can take advantage of these vulnerabilities to force the AI to interpret the data to be whatever they want, Wu says.

Using the stop sign example, you could make the AI system think the stop sign is a mailbox, or a speed limit sign, or a green light, and so on, simply by using slightly different stickers or whatever the vulnerability is.

This is incredibly important, because if an AI system is not robust against these sorts of attacks, you dont want to put the system into practical use particularly for applications that can affect human lives.

To test the vulnerability of deep neural networks to these adversarial attacks, the researchers developed a piece of software called QuadAttacK. The software can be used to test any deep neural network for adversarial vulnerabilities.

Basically, if you have a trained AI system, and you test it with clean data, the AI system will behave as predicted. QuadAttacKwatches these operations and learns how the AI is making decisions related to the data. This allows QuadAttacKto determine how the data could be manipulated to fool the AI.

QuadAttacKthen begins sending manipulated data to the AI system to see how the AI responds. If QuadAttacKhas identified a vulnerability it can quickly make the AI see whatever QuadAttacKwants it to see.

In proof-of-concept testing, the researchers used QuadAttacKto test four deep neural networks: two convolutional neural networks (ResNet-50 and DenseNet-121) and two vision transformers (ViT-B and DEiT-S). These four networks were chosen because they are in widespread use in AI systems around the world.

We were surprised to find that all four of these networks were very vulnerable to adversarial attacks, Wu says. We were particularly surprised at the extent to which we could fine-tune the attacks to make the networks see what we wanted them to see.

The research team has made QuadAttacKpublicly available, so that the research community can use it themselves to test neural networks for vulnerabilities. The program can be found here:https://thomaspaniagua.github.io/quadattack_web/.

Now that we can better identify these vulnerabilities, the next step is to find ways to minimize those vulnerabilities, Wu says. We already have some potential solutions but the results of that work are still forthcoming.

The paper, QuadAttacK: A Quadratic Programming Approach to Learning Ordered Top-KAdversarial Attacks, will be presented Dec. 16 at the Thirty-seventh Conference on Neural Information Processing Systems (NeurIPS 2023), which is being held in New Orleans, La. First author of the paper is Thomas Paniagua, a Ph.D. student at NCState. The paper was co-authored by Ryan Grainger, a Ph.D. student at NCState.

Funding: The work was done with support from the U.S. Army Research Office, under grants W911NF1810295 and W911NF2210010; and from the National Science Foundation, under grants 1909644, 2024688 and 2013451.

Author: Matt Shipman Source: North Carolina State University Contact: Matt Shipman North Carolina State University Image: The image is credited to Neuroscience News

Original Research: The findings will be presented at the Thirty-seventh Conference on Neural Information Processing Systems (NeurIPS)

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Neuroscience

AI Revolutionizes Neuron Tracking in Moving Animals – Neuroscience News

Summary: Researchers developed an AI-based method to track neurons in moving and deforming animals, a significant advancement in neuroscience research. This convolutional neural network (CNN) method overcomes the challenge of tracking brain activity in organisms like worms, whose bodies constantly change shape.

By employing targeted augmentation, the AI significantly reduces the need for manual image annotation, streamlining the neuron identification process. Tested on the roundworm Caenorhabditis elegans, this technology has not only increased analysis efficiency but also deepened insights into complex neuronal behaviors.

Key Facts:

Source: EPFL

Recent advances allow imaging of neurons inside freely moving animals. However, to decode circuit activity, these imaged neurons must be computationally identified and tracked. This becomes particularly challenging when the brain itself moves and deforms inside an organisms flexible body, e.g. in a worm. Until now, the scientific community has lacked the tools to address the problem.

Now, a team of scientists from EPFL and Harvard have developed a pioneering AI method to track neurons inside moving and deforming animals. The study, now published inNature Methods, was led bySahand Jamal Rahiat EPFLs School of Basic Sciences.

The new method is based on a convolutional neural network (CNN), which is a type of AI that has been trained to recognize and understand patterns in images. This involves a process called convolution, which looks at small parts of the picture like edges, colors, or shapes at a time and then combines all that information together to make sense of it and to identify objects or patterns.

The problem is that to identify and track neurons during a movie of an animals brain, many images have to be labeled by hand because the animal appears very differently across time due to the many different body deformations. Given the diversity of the animals postures, generating a sufficient number of annotations manually to train a CNN can be daunting.

To address this, the researchers developed an enhanced CNN featuring targeted augmentation. The innovative technique automatically synthesizes reliable annotations for reference out of only a limited set of manual annotations. The result is that the CNN effectively learns the internal deformations of the brain and then uses them to create annotations for new postures, drastically reducing the need for manual annotation and double-checking.

The new method is versatile, being able to identify neurons whether they are represented in images as individual points or as 3D volumes. The researchers tested it on the roundwormCaenorhabditis elegans, whose 302 neurons have made it a popular model organism in neuroscience.

Using the enhanced CNN, the scientists measured activity in some of the worms interneurons (neurons that bridge signals between neurons). They found that they exhibit complex behaviors, for example changing their response patterns when exposed to different stimuli, such as periodic bursts of odors.

The team have made their CNN accessible, providing a user-friendly graphical user interface that integrates targeted augmentation, streamlining the process into a comprehensive pipeline, from manual annotation to final proofreading.

By significantly reducing the manual effort required for neuron segmentation and tracking, the new method increases analysis throughput three times compared to full manual annotation, says Sahand Jamal Rahi.

The breakthrough has the potential to accelerate research in brain imaging and deepen our understanding of neural circuits and behaviors.

Other contributors

Swiss Data Science Center

Author: Nik Papageorgiou Source: EPFL Contact: Nik Papageorgiou EPFL Image: The image is credited to Neuroscience News

Original Research: The findings will appear in Nature Methods

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Mirror Insight: Mice Show Glimpses of Self-Recognition – Neuroscience News

Summary: Mice display behavior akin to self-recognition when viewing their reflections in mirrors. This behavior emerges under specific conditions: familiarity with mirrors, socialization with similar-looking mice, and visible markings on their fur.

The study also identifies a subset of neurons in the hippocampus that are crucial for this self-recognition-like behavior. These findings provide valuable insights into the neural mechanisms behind self-recognition, a previously enigmatic aspect of neurobehavioral research.

Key Facts:

Source: Cell Press

Researchers report December 5 in the journalNeuronthat mice display behavior that resembles self-recognition when they see themselves in the mirror. When the researchers marked the foreheads of black-furred mice with a spot of white ink, the mice spent more time grooming their heads in front of the mirrorpresumably to try and wash away the ink spot.

However, the mice only showed this self-recognition-like behavior if they were already accustomed to mirrors, if they had socialized with other mice who looked like them, and if the ink spot was relatively large.

The team identified a subset of neurons in the hippocampus that are involved in developing and storing this visual self-image, providing a first glimpse of the neural mechanisms behind self-recognition, something that was previously a black box in neurobehavioral research.

To form episodic memory, for example, of events in our daily life, brains form and store information about where, what, when, and who, and the most important component is self-information or status, says neuroscientist and senior author Takashi Kitamura of University of Texas Southwestern Medical Center.

Researchers usually examine how the brain encodes or recognizes others, but the self-information aspect is unclear.

The researchers used a mirror test to investigate whether mice could detect a change in their own appearancein this case, a dollop of ink on their foreheads. Because the ink also provided a tactile stimulus, the researchers tested the black-furred mice with both black and white ink.

Though the mirror test was originally developed to test consciousness in different species, the authors note that their experiments only show that mice can detect a change in their own appearance, but this does not necessarily mean that they are self-aware.

They found that mice could indeed detect changes to their appearance, but only under certain conditions. Mice who were familiar with mirrors spent significantly more time grooming their heads (but not other parts of their bodies) in front of the mirror when they were marked with dollops of white ink that were 0.6 cm2or 2 cm2.

However, the mice did not engage in increased head grooming when the ink was blackthe same color as their furor when the ink mark was small (0.2 cm2), even if the ink was white, and mice who were not habituated to mirrors before the ink test did not display increased head grooming in any scenario.

The mice required significant external sensory cues to pass the mirror testwe have to put a lot of ink on their heads, and then the tactile stimulus coming from the ink somehow enables the animal to detect the ink on their heads via a mirror reflection, says first author Jun Yokose of University of Texas Southwestern Medical Center. Chimps and humans dont need any of that extra sensory stimulus.

Using gene expression mapping, the researchers identified a subset of neurons in the ventral hippocampus that were activated when the mice recognized themselves in the mirror. When the researchers selectively rendered these neurons non-functional, the mice no longer displayed the mirror-and-ink-induced grooming behavior.

A subset of these self-responding neurons also became activated when the mice observed other mice of the same strain (and therefore similar physical appearance and fur color), but not when they observed a different strain of mouse that had white fur.

Because previous studies in chimpanzees have suggested that social experience is required for mirror self-recognition, the researchers also tested mice who had been socially isolated after weaning. These socially isolated mice did not display increased head grooming behavior during the ink test, and neither did black-furred mice that were reared alongside white-furred mice.

The gene expression analysis also showed that socially isolated mice did not develop self-responding neuron activity in the hippocampus, and neither did the black-furred mice that were reared by white-furred mice, suggesting that mice need to have social experiences alongside other similar-looking mice in order to develop the neural circuits required for self-recognition.

A subset of these self-responding neurons was also reactivated when we exposed the mice to other individuals of the same strain, says Kitamura.

This is consistent with previous human literature that showed that some hippocampal cells fire not only when the person is looking at themselves, but also when they look at familiar people like a parent.

Next, the researchers plan to try to disentangle the importance of visual and tactile stimuli to test whether mice can recognize changes in their reflection in the absence of a tactile stimulusperhaps by using technology similar to the filters on social media apps that allow people to give themselves puppy-dog faces or bunny ears.

They also plan to study other brain regions that might be involved in self-recognition and to investigate how the different regions communicate and integrate information.

Now that we have this mouse model, we can manipulate or monitor neural activity to comprehensively investigate the neural circuit mechanisms behind how self-recognition-like behavior is induced in mice, says Yokose.

Funding: This research was supported by the Endowed Scholar Program, the Brain & Behavior Research Foundation, the Daiichi Sankyo Foundation of Life Science, and Uehara Memorial Foundation.

Author: Kristopher Benke Source: Cell Press Contact: Kristopher Benke Cell Press Image: The image is credited to Neuroscience News

Original Research: Open access. Visuotactile integration facilitates mirror-induced self-directed behavior through activation of hippocampal neuronal ensembles in mice by Takashi Kitamura et al. Neuron

Abstract

Visuotactile integration facilitates mirror-induced self-directed behavior through activation of hippocampal neuronal ensembles in mice

Remembering the visual features of oneself is critical for self-recognition. However, the neural mechanisms of how the visual self-image is developed remain unknown because of the limited availability of behavioral paradigms in experimental animals.

Here, we demonstrate a mirror-induced self-directed behavior (MSB) in mice, resembling visual self-recognition. Mice displayed increased mark-directed grooming to remove ink placed on their heads when an ink-induced visual-tactile stimulus contingency occurred. MSB required mirror habituation and social experience.

The chemogenetic inhibition of dorsal or ventral hippocampal CA1 (vCA1) neurons attenuated MSB. Especially, a subset of vCA1 neurons activated during the mirror exposure was significantly reactivated during re-exposure to the mirror and was necessary for MSB.

The self-responding vCA1 neurons were also reactivated when mice were exposed to a conspecific of the same strain.

These results suggest that visual self-image may be developed through social experience and mirror habituation and stored in a subset of vCA1 neurons.

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Mapping Ketamine’s Impact on the Brain – Neuroscience News

Summary: A study reveals that repeated use of ketamine leads to structural changes in the brains dopamine system, emphasizing the need for targeted ketamine therapies.

The research suggests that specific brain regions should be addressed to minimize unintended effects on other dopamine areas. Repeated ketamine exposure decreases dopamine neurons linked to mood regulation and increases dopamine neurons related to metabolism and basic functions.

These findings may explain ketamines potential in treating eating disorders and the dissociative behavioral effects observed in users. The study paves the way for improved ketamine applications in clinical settings.

Key Facts:

Source: Columbia University

Ketamine an anesthetic also known for its illicit use as a recreational drug has undergone a thorough reputational rehabilitation in recent years as the medical establishment has begun to recognize its wide-ranging therapeutic effects.

The drug is increasingly used for a range of medical purposes, including as a painkiller alternative to opioids, and as a therapy for treatment-resistant depression.

In a new study published in the journalCell Reports, Columbia biologists and biomedical engineers mapped ketamines effects on the brains of mice, and found that repeated use over extended periods of time leads to widespread structural changes in the brains dopamine system.

The findings bolster the case for developing ketamine therapies that target specific areas of the brain, rather than administering doses that wash the entire brain in ketamine.

Instead of bathing the entire brain in ketamine, as most therapies now do, our whole-brain mapping data indicates that a safer approach would be to target specific parts of the brain with it, so as to minimize unintended effects on other dopamine regions of the brain, Raju Tomer, the senior author of the paper said.

The study found that repeated ketamine exposure leads to a decrease in dopamine neurons in regions of the midbrain that are linked to regulating mood, as well as an increase in dopamine neurons in the hypothalamus, which regulates the bodys basic functions like metabolism and homeostasis.

The former finding, that ketamine decreases dopamine in the midbrain, may indicate why long-term abuse of ketamine could cause users to exhibit similar symptoms to people with schizophrenia, a mood disorder.

The latter finding, that ketamine increases dopamine in the parts of the brain that regulate metabolism, on the other hand, may help explain why it shows promise in treating eating disorders.

The researchers highly-detailed data also enabled them to track how ketamine affects dopamine networks across the brain. They found that ketamine reduced the density of dopamine axons, or nerve fibers, in the areas of the brain responsible for our hearing and vision, while increasing dopamine axons in the brains cognitive centers. These intriguing findings may help explain the dissociative behavioral effects observed in individuals exposed to ketamine.

The restructuring of the brains dopamine system that we see after repeated ketamine use may be linked to cognitive behavioral changes over time, Malika Datta, a co-author of the paper said.

Most studies of ketamines effects on the brain to-date have looked at the effects of acute exposure how one dose affects the brain in the immediate term. For this study, researchers examined repeated daily exposure over the course of up to ten days. Statistically significant alterations to the brains dopamine makeup were only measurably detectable after ten days of daily ketamine use.

The researchers assessed the effects of repeated exposure to the drug at two doses, one dose analogous to the dose used to model depression treatment in mice, and another closer to the dose that induces anesthesia. The drugs effects on dopamine system were visible at both doses.

The study is charting a new technological frontier in how to conduct high-resolution studies of the entire brain, said Yannan Chen, a co-author of the paper. It is the first successful attempt to map changes induced by chronic ketamine exposure at what is known as sub-cellular resolution, in other words, down to the level of seeing ketamines effects on parts of individual cells.

Most sub-cellular studies of ketamines effects conducted to-date have been hypothesis-driven investigations of one area of the brain that researchers have targeted because they believed that it might play an important role in how the brain metabolizes the drug. This study is the first sub-cellular study to examinethe entire brain without first forming such a hypothesis.

Bradley Miller, a Columbia psychiatrist and neuroscientist who focuses on depression, said: Ketamine rapidly resolves depression in many patients with treatment resistant depression, and it is being investigated for longer term use to prevent the relapse of depression.

This study reveals how ketamine rewires the brain with repeated use. This is an essential step for developing targeted treatments that effectively treat depression without some of the unwanted side effects of ketamine.

The research was supported by the National Institutes of Health (NIH) and the National Institute of Mental Health (NIMH). The papers lead authors are Malika Datta and Yannan Chen, who completed their research in Raju Tomers lab at Columbia. Datta is now a postdoctoral fellow at Yale.

This study gives us a deeper brain-wide perspective of how ketamine functions that we hope will contribute to improved uses of this highly promising drug in various clinical settings as well as help minimize its recreational abuse. Morebroadly, the study demonstrates that the same type of neurons located in different brain regions can be affected differently by the same drug, said Tomer.

Author: Christopher Shea Source: Columbia University Contact: Christopher Shea Columbia University Image: The image is credited to Neuroscience News

Original Research: The findings will be published in Cell Reports

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Neuroscience

Stickleback Fish Reveal Insights into Animal Decision-Making – Neuroscience News

Summary: A new study provides significant insights into how animals, specifically three-spined stickleback fish, make decisions under competing demands. The study explored the fishs behaviors during the breeding season, where males must simultaneously defend territory, court females, and care for offspring.

By exposing male sticklebacks to various stimuli and analyzing their behavioral responses and brain gene expression, the researchers discovered a complex interaction between territorial defense and courtship, with some prioritizing defense.

This research not only sheds light on animal decision-making processes but also suggests ancient mechanisms driving complex decision-making across many taxa.

Key Facts:

Source: University of Illinois

How do animals make decisions when faced with competing demands, and how have decision making processes evolved over time?

In a recent publication in Biology Letters, Tina Barbasch, a postdoctoral researcher at the Carl R. Woese Institute for Genomic Biology, and Alison Bell (GNDP), a professor in the Department of Ecology, Evolution and Behavior, explored these questions using three-spined stickleback fish (Gasterosteus aculeatus).

Whether you are in school, working, raising children, managing a social life, or just trying to relax for a moment, managing multiple responsibilities at once can quickly become overwhelming. You may find yourself wondering how much simpler life would be if you were a fish floating along a river or a hawk soaring through the sky.

Yet, animals also face the burdens of multitasking, whether it be searching for their next meal while avoiding becoming someone elses next meal or attracting a mate while defending their territory.

During my PhD, I studied parental care in clownfish, and how they decide how much care to provide for their offspring, says Barbasch.

This requires the integration of many sources of social and environmental information. Recently, I have become interested in understanding the mechanisms underlying how animals make decisions and integrate different sources of information.

Despite the importance of decision making for an animals fitness, the mechanisms that shape decision-making are not well understood. Stickleback are a powerful model for investigating these questions because of their complex life history and reproductive behavior.

During the breeding season, male sticklebacks establish territories to build nests to attract females. Males must simultaneously defend their territories from other males, court females that enter their territory with performative swimming motions, called zig-zags, and ultimately provide care for offspring if they can successfully court a female.

This study was inspired by an experiment where we looked at brain gene expression in male three-spined stickleback during parental care or when defending their territory, explained Bell.

We found that the same genes were involved in both experiments, but in opposite directions genes turned on in one condition were turned off in the other. This idea that the brain might be using the same molecular machinery, but in opposite ways, could have major implications for the evolution of decision making.

To explore the underlying molecular mechanisms of decision making, Barbasch exposed male stickleback to one of three stimuli: a female stickleback (courtship treatment); another male stickleback (territorial intruder treatment), or both a male and female stickleback (trade-off treatment).

Some male stickleback were left alone as a control. Aggressive behaviors (biting) and courtship behaviors (zig-zags) were quantified, and then the brains of the male stickleback were dissected to look at gene expression using RNA sequencing.

Barbasch found that, when faced with a trade-off, males generally prioritized territorial defense over courtship. There was also substantial variation across males in how they responded, suggesting that there might be different strategies that males employ when faced with a trade-off.

Furthermore, the gene expression results identified groups of genes that were differentially expressed across each of the experimental treatments relative to a control. Of particular interest are the genes that are only present in the trade-off treatment, because they suggest that males have a unique molecular response when faced with conflicting demands.

We performed gene ontology analysis on these trade-off genes to look into what the identity and function of these genes might be, describes Barbasch. Preliminary results suggest the trade-off genes may be related to the dopamine response pathway, which modulates reward and motivation in the brain, or neurogenesis, which is important for cognition.

Ultimately, these findings highlight the importance of exploring the molecular basis of animal behavior, as Bell outlines. Animals are living really complicated lives, across many taxa. This suggests that the mechanisms that are driving complex decision-making are probably really ancient and animals have been managing complex decisions for a long time.

Barbaschs study also sets the foundation for a wide range of exciting follow-up studies. She has already started to explore the behavioral and molecular responses by stickleback to other trade-offs including those involving predation risk, foraging, and parental care.

She also plans on expanding her molecular toolkit by quantifying gene expression in finer detail using single-cell RNA sequencing and weighted gene co-expression network analysis, which helps capture gene function by identifying networks of genes with related patterns of expression.

So, the next time you notice an animal doing something, think a bit deeper about their day-to-day life, and how they are finding a way to manage all their responsibilities.

Author: Nicholas Vasi Source: University of Illinois Contact: Nicholas Vasi University of Illinois Image: The image is credited to Neuroscience News

Original Research: Open access. A distinct neurogenomic response to a trade-off between social challenge and opportunity in male sticklebacks (Gasterosteus aculeatus) by Alison Bell et al. Biology Letters

Abstract

A distinct neurogenomic response to a trade-off between social challenge and opportunity in male sticklebacks (Gasterosteus aculeatus)

Animals frequently make adaptive decisions about what to prioritize when faced with multiple, competing demands simultaneously.

However, the proximate mechanisms of decision-making in the face of competing demands are not well understood.

We explored this question using brain transcriptomics in a classic model system: threespined sticklebacks, where males face conflict between courtship and territorial defence. We characterized the behaviour and brain gene expression profiles of males confronted by a trade-off between courtship and territorial defence by comparing them to males not confronted by this trade-off.

When faced with the trade-off, males behaviourally prioritized defence over courtship, and this decision was reflected in their brain gene expression profiles. A distinct set of genes and biological processes was recruited in the brain when males faced a trade-off and these responses were largely non-overlapping across two brain regions.

Combined, these results raise new questions about the interplay between the neural and molecular mechanisms involved in decision-making.

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