̽��ֱ�� of Cambridge - Templeton World Charity Foundation

AI system self-organises to develop features of brains of complex organisms

cjb250 — Mon, 20 Nov 2023 16:00:47 +0000

As neural systems such as the brain organise themselves and make connections, they have to balance competing demands. For example, energy and resources are needed to grow and sustain the network in physical space, while at the same time optimising the network for information processing. This trade-off shapes all brains within and across species, which may help explain why many brains converge on similar organisational solutions.

Jascha Achterberg, a Gates Scholar from the Medical Research Council Cognition and Brain Sciences Unit (MRC CBU) at the ̽��ֱ�� of Cambridge said: “Not only is the brain great at solving complex problems, it does so while using very little energy. In our new work we show that considering the brain’s problem solving abilities alongside its goal of spending as few resources as possible can help us understand why brains look like they do.”

Co-lead author Dr Danyal Akarca, also from the MRC CBU, added: “This stems from a broad principle, which is that biological systems commonly evolve to make the most of what energetic resources they have available to them. ̽��ֱ��solutions they come to are often very elegant and reflect the trade-offs between various forces imposed on them.”

In a study published today in Nature Machine Intelligence, Achterberg, Akarca and colleagues created an artificial system intended to model a very simplified version of the brain and applied physical constraints. They found that their system went on to develop certain key characteristics and tactics similar to those found in human brains.

Instead of real neurons, the system used computational nodes. Neurons and nodes are similar in function, in that each takes an input, transforms it, and produces an output, and a single node or neuron might connect to multiple others, all inputting information to be computed.

In their system, however, the researchers applied a ‘physical’ constraint on the system. Each node was given a specific location in a virtual space, and the further away two nodes were, the more difficult it was for them to communicate. This is similar to how neurons in the human brain are organised.

̽��ֱ��researchers gave the system a simple task to complete – in this case a simplified version of a maze navigation task typically given to animals such as rats and macaques when studying the brain, where it has to combine multiple pieces of information to decide on the shortest route to get to the end point.

One of the reasons the team chose this particular task is because to complete it, the system needs to maintain a number of elements – start location, end location and intermediate steps – and once it has learned to do the task reliably, it is possible to observe, at different moments in a trial, which nodes are important. For example, one particular cluster of nodes may encode the finish locations, while others encode the available routes, and it is possible to track which nodes are active at different stages of the task.

Initially, the system does not know how to complete the task and makes mistakes. But when it is given feedback it gradually learns to get better at the task. It learns by changing the strength of the connections between its nodes, similar to how the strength of connections between brain cells changes as we learn. ̽��ֱ��system then repeats the task over and over again, until eventually it learns to perform it correctly.

With their system, however, the physical constraint meant that the further away two nodes were, the more difficult it was to build a connection between the two nodes in response to the feedback. In the human brain, connections that span a large physical distance are expensive to form and maintain.

When the system was asked to perform the task under these constraints, it used some of the same tricks used by real human brains to solve the task. For example, to get around the constraints, the artificial systems started to develop hubs – highly connected nodes that act as conduits for passing information across the network.

More surprising, however, was that the response profiles of individual nodes themselves began to change: in other words, rather than having a system where each node codes for one particular property of the maze task, like the goal location or the next choice, nodes developed a flexible coding scheme. This means that at different moments in time nodes might be firing for a mix of the properties of the maze. For instance, the same node might be able to encode multiple locations of a maze, rather than needing specialised nodes for encoding specific locations. This is another feature seen in the brains of complex organisms.

Co-author Professor Duncan Astle, from Cambridge’s Department of Psychiatry, said: “This simple constraint – it’s harder to wire nodes that are far apart – forces artificial systems to produce some quite complicated characteristics. Interestingly, they are characteristics shared by biological systems like the human brain. I think that tells us something fundamental about why our brains are organised the way they are.”

Understanding the human brain

̽��ֱ��team are hopeful that their AI system could begin to shed light on how these constraints, shape differences between people’s brains, and contribute to differences seen in those that experience cognitive or mental health difficulties.

Co-author Professor John Duncan from the MRC CBU said: “These artificial brains give us a way to understand the rich and bewildering data we see when the activity of real neurons is recorded in real brains.”

Achterberg added: “Artificial ‘brains’ allow us to ask questions that it would be impossible to look at in an actual biological system. We can train the system to perform tasks and then play around experimentally with the constraints we impose, to see if it begins to look more like the brains of particular individuals.”

Implications for designing future AI systems

̽��ֱ��findings are likely to be of interest to the AI community, too, where they could allow for the development of more efficient systems, particularly in situations where there are likely to be physical constraints.

Dr Akarca said: “AI researchers are constantly trying to work out how to make complex, neural systems that can encode and perform in a flexible way that is efficient. To achieve this, we think that neurobiology will give us a lot of inspiration. For example, the overall wiring cost of the system we've created is much lower than you would find in a typical AI system.”

Many modern AI solutions involve using architectures that only superficially resemble a brain. ̽��ֱ��researchers say their works shows that the type of problem the AI is solving will influence which architecture is the most powerful to use.

Achterberg said: “If you want to build an artificially-intelligent system that solves similar problems to humans, then ultimately the system will end up looking much closer to an actual brain than systems running on large compute cluster that specialise in very different tasks to those carried out by humans. ̽��ֱ��architecture and structure we see in our artificial ‘brain’ is there because it is beneficial for handling the specific brain-like challenges it faces.”

This means that robots that have to process a large amount of constantly changing information with finite energetic resources could benefit from having brain structures not dissimilar to ours.

Achterberg added: “Brains of robots that are deployed in the real physical world are probably going to look more like our brains because they might face the same challenges as us. They need to constantly process new information coming in through their sensors while controlling their bodies to move through space towards a goal. Many systems will need to run all their computations with a limited supply of electric energy and so, to balance these energetic constraints with the amount of information it needs to process, it will probably need a brain structure similar to ours.”

̽��ֱ��research was funded by the Medical Research Council, Gates Cambridge, the James S McDonnell Foundation, Templeton World Charity Foundation and Google DeepMind.

Reference
Achterberg, J & Akarca, D et al. Spatially embedded recurrent neural networks reveal widespread links between structural and functional neuroscience findings. Nature Machine Intelligence; 20 Nov 2023; DOI: 10.1038/s42256-023-00748-9

Cambridge scientists have shown that placing physical constraints on an artificially-intelligent system – in much the same way that the human brain has to develop and operate within physical and biological constraints – allows it to develop features of the brains of complex organisms in order to solve tasks.

Not only is the brain great at solving complex problems, it does so while using very little energy

Jascha Achterberg

DeltaWorks

Graphic representing an artificially intelligent brain

̽��ֱ��text in this work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License. Images, including our videos, are Copyright © ̽��ֱ�� of Cambridge and licensors/contributors as identified. All rights reserved. We make our image and video content available in a number of ways – as here, on our main website under its Terms and conditions, and on a range of channels including social media that permit your use and sharing of our content under their respective Terms.

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Teenagers at greatest risk of self-harming could be identified almost a decade earlier

cjb250 — Tue, 15 Jun 2021 06:00:46 +0000

̽��ֱ��team, based at the MRC Cognition and Brain Sciences Unit, ̽��ֱ�� of Cambridge, found that while sleep problems and low self-esteem were common risk factors, there were two distinct profiles of young people who self-harm – one with emotional and behavioural difficulties, and a second group without those difficulties but with different risk factors.

Between one in five and one in seven adolescents in England self-harms, for example by deliberately cutting themselves. While self-harm is a significant risk factor for subsequent suicide attempts, many do not intend suicide but face other harmful outcomes, including repeatedly self-harming, poor mental health, and risky behaviours like substance abuse. Despite its prevalence and lifelong consequences, there has been little progress in the accurate prediction of self-harm.

̽��ֱ��Cambridge team identified adolescents who reported self-harm at age 14, from a nationally representative UK birth cohort of approximately 11,000 individuals. They then used a machine learning analysis to identify whether there were distinct profiles of young people who self-harm, with different emotional and behavioural characteristics. They used this information to identify risk factors from early and middle childhood. ̽��ֱ��results are published in the Journal of the American Academy of Child and Adolescent Psychiatry.

Because the data tracked the participants over time, the researchers were able to distinguish factors that appear alongside reported self-harm behaviour, such as low self-esteem, from those that precede it, such as bullying.

̽��ֱ��team identified two distinct subgroups among young people who self-harm, with significant risk factors present as early as age five, nearly a decade before they reported self-harming. While both groups were likely to experience sleep difficulties and low self-esteem reported at age 14, other risk factors differed between the two groups.

̽��ֱ��first group showed a long history of poor mental health, as well as bullying before they self-harmed. Their caregivers were more likely to have mental health issues of their own.

For the second group, however, their self-harming behaviour was harder to predict early in childhood. One of the key signs was a greater willingness to take part in risk-taking behaviour, which is linked to impulsivity. Other research suggests these tendencies may predispose the individual towards spending less time to consider alternate coping methods and the consequences of self-harm. Factors related to their relationships with their peers were also important for this subgroup, including feeling less secure with friends and family at age 14 and a greater concern about the feelings of others as a risk factor at age 11.

Stepheni Uh, a Gates Cambridge Scholar and first author of the study, said: “Self-harm is a significant problem among adolescents, so it’s vital that we understand the nuanced nature of self-harm, especially in terms of the different profiles of young people who self-harm and their potentially different risk factors.

“We found two distinct subgroups of young people who self-harm. ̽��ֱ��first was much as expected – young people who experience symptoms of depression and low self-esteem, face problems with their families and friends, and are bullied. ̽��ֱ��second, much larger group was much more surprising as they don’t show the usual traits that are associated with those who self-harm.”

̽��ֱ��researchers say that their findings suggest that it may be possible to predict which individuals are most at risk of self-harm up to a decade ahead of time, providing a window to intervene.

Dr Duncan Astle said: “ ̽��ֱ��current approach to supporting mental health in young people is to wait until problems escalate. Instead, we need a much better evidence base so we can identify who is at most risk of mental health difficulties in the future, and why. This offers us the opportunity to be proactive, and minimise difficulties before they start.

“Our results suggest that boosting younger children’s self-esteem, making sure that schools implement anti-bullying measures, and providing advice on sleep training, could all help reduce self-harm levels years later.

“Our research gives us potential ways of helping this newly-identified second subgroup. Given that they experience difficulties with their peers and are more willing to engage in risky behaviours, then providing access to self-help and problem-solving or conflict regulation programmes may be effective.”

Professor Tamsin Ford from the Department of Psychiatry added: “We might also help at-risk adolescents by targeting interventions at mental health leaders and school-based mental health teams. Teachers are often the first people to hear about self-harm but some lack confidence in how to respond. Providing them with training could make a big difference.”

̽��ֱ��research was supported by the Gates Cambridge Trust, Templeton World Charity Foundation, and the UK Medical Research Council.

Reference
Uh, S et al. Two pathways to self-harm in adolescence. Journal of the American Academy of Child and Adolescent Psychiatry; 14 June 2021; DOI: 10.1016/j.jaac.2021.03.010

Researchers have identified two subgroups of adolescents who self-harm and have shown that it is possible to predict those individuals at greatest risk almost a decade before they begin self-harming.

̽��ֱ��current approach to supporting mental health in young people is to wait until problems escalate. Instead, we need a much better evidence base so we can identify who is at most risk of mental health difficulties in the future, and why

Duncan Astle

Adrien Olichon

A man sitting in front of a screen

̽��ֱ��text in this work is licensed under a Creative Commons Attribution 4.0 International License. Images, including our videos, are Copyright © ̽��ֱ�� of Cambridge and licensors/contributors as identified. All rights reserved. We make our image and video content available in a number of ways – as here, on our main website under its Terms and conditions, and on a range of channels including social media that permit your use and sharing of our content under their respective Terms.

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Significant increase in depression seen among children during first lockdown

cjb250 — Tue, 08 Dec 2020 23:30:57 +0000

In response to the COVID-19 pandemic, the UK Government implemented a national 'lockdown' involving school closures and social distancing. There has been widespread concern that these measures would negatively impact child and adolescent mental health. To date, however, there is relatively little direct evidence of this.

̽��ֱ��most direct way of measuring the association between the onset of lockdown and children’s mental health is to follow the same individuals over a length of time and look for changes – so-called ‘longitudinal’ changes.

To test whether changes in emotional wellbeing, anxiety and depression symptoms occurred during lockdown since their initial assessment, a team at the Medical Research Council (MRC) Cognition and Brain Sciences Unit, ̽��ֱ�� of Cambridge, examined data from mental health assessments on 168 children (aged 8-12 years) before and during the UK lockdown. These assessments included self-reports, caregiver-reports, and teacher-reports.

̽��ֱ��results of their study are published today in Archives of Disease in Childhood.

Relative to their own pre-pandemic scores, children tended to show more symptoms of depression during lockdown. Even though these symptoms are variable across children, the impact of lockdown can still be seen because the effect size is large. ̽��ֱ��researchers used the variability in scores to estimate how big an increase this is.

“To give an indication of how large this effect is, imagine ranking the children into 100 ‘centiles’ depending on their scores,” explained Dr Duncan Astle from the MRC Cognition and Brain Sciences Unit and senior author of the study. “A child in the 50th centile would be exactly at the middle of the distribution. But a child at this position before the pandemic, could expect to be at the equivalent of the 77th centile during the lockdown.

“Put differently, if you randomly selected a child from the sample there is a 70% chance that their depression symptoms were worse during lockdown than before the pandemic.”

“National lockdowns with mass school closures are unprecedented, so going into this crisis, no one could say definitively what impact it would have on children,” said Giacomo Bignardi, a PhD student at the MRC Cognition and Brain Sciences Unit.

“Our study is one of the first to follow the same children over time during lockdown and suggests that symptoms of depression among children got much worse during this period. This effect was independent of children’s age, gender and family socio-economic status.”

̽��ֱ��team found only very small and not statistically significant changes in children’s scores for emotional problems and anxiety during lockdown.

Dr Astle added: “Childhood is a period where mental health may be particularly vulnerable to reduced peer interaction and loneliness. Now that children have returned to school, their wellbeing, socialisation and enjoyment are crucial. Teachers may need additional resources and training to help them support children with low mood.

“Even before lockdown resources for Child and Adolescent Mental Health Services were stretched thin – and that was against a backdrop of worsening mental health among children. Our findings suggest that lockdown measures will likely exacerbate this. ̽��ֱ��education sector will bear the initial brunt of this.”

̽��ֱ��researchers say that how the lockdown measures impact children’s mental health may depend on a variety of factors. A recent study found that loneliness in children was associated with subsequent mental health problems, particularly depression. Also, during lockdown children had fewer opportunities to engage in play and other fun activities that help improve mood.

̽��ֱ��research was supported by the Templeton World Charity Foundation and the Medical Research Council.

Reference
Bignardi, G et al. Longitudinal increases in childhood depression symptoms during the COVID-19 lockdown. Archives of Disease in Childhood; 9 Dec 2020; DOI: 10.1136/archdischild-2020-320372

̽��ֱ��first lockdown led to a significant increase in symptoms of depression among children, highlighting the unintended consequences of school closures, according to a new study from the ̽��ֱ�� of Cambridge.

Our study is one of the first to follow the same children over time during lockdown and suggests that symptoms of depression among children got much worse during this period

Giacomo Bignardi

Rod Long

Child looking out of a window

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Transgender and gender-diverse individuals are more likely to be autistic and report higher autistic traits

cjb250 — Fri, 07 Aug 2020 08:50:07 +0000

This research, conducted using data from over 600,000 adult individuals, confirms previous smaller scale studies from clinics. ̽��ֱ��results are published today in Nature Communications.

A better understanding of gender diversity in autistic individuals will help provide better access to health care and post-diagnostic support for autistic transgender and gender-diverse individuals.

̽��ֱ��team used five different datasets, including a dataset of over 500,000 individuals collected as a part of the Channel 4 documentary “Are you autistic?”. In these datasets, participants had provided information about their gender identity, and if they received a diagnosis of autism or other psychiatric conditions such as depression or schizophrenia. Participants also completed a measure of autistic traits.

Strikingly, across all five datasets, the team found that transgender and gender-diverse adult individuals were between three and six times more likely to indicate that they were diagnosed as autistic compared to cisgender individuals. While the study used data from adults who indicated that they had received an autism diagnosis, it is likely that many individuals on the autistic spectrum may be undiagnosed. As around 1.1% of the UK population is estimated to be on the autistic spectrum, this result would suggest that somewhere between 3.5.-6.5% of transgender and gender-diverse adults is on the autistic spectrum.

Dr Meng-Chuan Lai, a collaborator on the study at the ̽��ֱ�� of Toronto, said: “We are beginning to learn more about how the presentation of autism differs in cisgender men and women. Understanding how autism manifests in transgender and gender-diverse people will enrich our knowledge about autism in relation to gender and sex. This enables clinicians to better recognize autism and provide personalised support and health care.”

Transgender and gender-diverse individuals were also more likely to indicate that they had received diagnoses of mental health conditions, particularly depression, which they were more than twice as likely as their cisgender counterparts to have experienced. Transgender and gender-diverse individuals also, on average, scored higher on measures of autistic traits compared to cisgender individuals, regardless of whether they had an autism diagnosis.

Dr Varun Warrier, who led the study, said: “This finding, using large datasets, confirms that the co-occurrence between being autistic and being transgender and gender-diverse is robust. We now need to understand the significance of this co-occurrence, and identify and address the factors that contribute to well-being of this group of people.”

̽��ֱ��study investigates the co-occurrence between gender identity and autism. ̽��ֱ��team did not investigate if one causes the other.

Professor Simon Baron-Cohen, Director of the Autism Research Centre at Cambridge, and a member of the team, said: “Both autistic individuals and transgender and gender-diverse individuals are marginalized and experience multiple vulnerabilities. It is important that we safe-guard the rights of these individuals to be themselves, receive the requisite support, and enjoy equality and celebration of their differences, free of societal stigma or discrimination.”

Dr Warrier is a Research Fellow at St Catharine's College and Professor Baron Cohen is a Fellow at Trinity College.

This study was supported by the Autism Research Trust, the Medical Research Council, the Wellcome Trust, and the Templeton World Charity Foundation., Inc. It was conducted in association with the NIHR CLAHRC for Cambridgeshire and Peterborough NHS Foundation Trust, and the NIHR Cambridge Biomedical Research Centre.

Reference
Warrier, V et al. Elevated rates of autism, other neurodevelopmental and psychiatric diagnoses and autistic traits in transgender and gender-diverse individuals. Nat Comms; 7 Aug 2020; DOI: 10.1038/s41467-020-17794-1

Transgender and gender-diverse adults are three to six times more likely as cisgender adults (individuals whose gender identity corresponds to their sex assigned at birth) to be diagnosed as autistic, according to a new study by scientists at the ̽��ֱ�� of Cambridge’s Autism Research Centre.

Both autistic individuals and transgender and gender-diverse individuals are marginalized and experience multiple vulnerabilities. It is important that we safe-guard the rights of these individuals to be themselves, receive the requisite support, and enjoy equality and celebration of their differences, free of societal stigma or discrimination

Simon Baron Cohen

katlove

Transgender flag

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Genetic variants for autism linked to higher rates of self-harm and childhood maltreatment

cjb250 — Tue, 29 Oct 2019 01:03:43 +0000

Previous studies by the Cambridge team established that autistic individuals experience higher levels of self-harm, including suicidal thoughts and feelings, and higher rates of childhood maltreatment. This new study shows that the findings hold true even for those with a higher genetic likelihood of autism rather than a formal diagnosis.

̽��ֱ��team calculated the genetic likelihood for autism in 100,000 individuals from the UK Biobank Study who had their DNA analysed and who had also provided self-reported information about childhood maltreatment, suicidal ideation, and self-harm. They found that individuals with higher number of genetic variants associated with autism are more likely to report childhood maltreatment, self-harm and suicidal ideation. Those with the highest genetic predisposition to autism on average have a 28% increase in childhood maltreatment, and a 33% increase in self-harm and suicidal ideation, compared to those with the lowest genetic predisposition to autism.

Dr Varun Warrier, who led the study, said: “While we have found an association between a genetic likelihood for autism and adverse life events, we cannot conclude the former causes the latter. We suspect this association reflects that genes partly influence how many autistic traits you have, and some autistic traits such as difficulties in social understanding may lead to a person to be vulnerable to maltreatment. This research highlights the risks of such adverse outcomes for those with a high number of autistic traits, if adequate safe-guarding and support aren’t provided.”

Professor Simon Baron-Cohen, Director of the Autism Research Centre at Cambridge, said: “This new study extends our earlier work by showing that individuals who carry more of the genes associated with autism have higher risks for maltreatment and self-harm. Our work highlighting unacceptably high rates of suicide in autistic people was published 5 years ago, yet almost no new support has been provided. Governments need to provide far greater support for autistic individuals and for those with a high number of autistic traits.”

He added: “Autistic individuals may need a variety of interventions – there’s no ‘one size fits all’ – and these may include an individual support worker, a mentor, opportunities to build social and communication skills and self confidence through activities that the person enjoys, peer support groups, and supported employment schemes. Schools may also need to increase safe-guarding given the risks of victimisation.”

This study was supported by the Autism Research Trust, the Medical Research Council, Wellcome, and the Templeton World Charity Foundation., Inc. It was conducted in association with the NIHR CLAHRC for Cambridgeshire and Peterborough NHS Foundation Trust, and the NIHR Cambridge Biomedical Research Centre.

Reference
Warrier, V and Baron-Cohen, S. Childhood trauma, life-time self-harm, and suicidal behaviour and ideation are associated with polygenic scores for autism. Molecular Psychiatry; 29 Oct 2019; DOI: 10.1038/s41380-019-0550-x

People with a higher genetic likelihood of autism are more likely to report higher childhood maltreatment, self-harm and suicidal thoughts according to a new study by researchers at the ̽��ֱ�� of Cambridge. A better understanding of these issues is critical to improving wellbeing in autistic people. ̽��ֱ��results are published today in Molecular Psychiatry.

Our work highlighting unacceptably high rates of suicide in autistic people was published 5 years ago, yet almost no new support has been provided. Governments need to provide far greater support for autistic individuals and for those with a high number of autistic traits

Simon Baron Cohen

Sasha Freemind

Man standing in front of window

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Over half a million people take part in largest ever study of psychological sex differences and autistic traits

cjb250 — Mon, 12 Nov 2018 20:00:52 +0000

Working with the television production company Channel 4, they tested over half a million people, including over 36,000 autistic people. ̽��ֱ��results are published today in the Proceedings of the National Academy of Sciences.

̽��ֱ��Empathising-Systemising theory predicts that women, on average, will score higher than men on tests of empathy, the ability to recognize what another person is thinking or feeling, and to respond to their state of mind with an appropriate emotion. Similarly, it predicts that men, on average, will score higher on tests of systemising, the drive to analyse or build rule-based systems.

̽��ֱ��Extreme Male Brain theory predicts that autistic people, on average, will show a masculinised shift on these two dimensions: namely, that they will score lower than the typical population on tests of empathy and will score the same as if not higher than the typical population on tests of systemising.

Whereas both theories have been confirmed in previous studies of relatively modest samples, the new findings come from a massive sample of 671,606 people, which included 36,648 autistic people. They were replicated in a second sample of 14,354 people. In this new study, the scientists used very brief 10-item measures of empathy, systemising, and autistic traits.

Using these short measures, the team identified that in the typical population, women, on average, scored higher than men on empathy, and men, on average, scored higher than women on systemising and autistic traits. These sex differences were reduced in autistic people. On all these measures, autistic people’s scores, on average, were ‘masculinised’: that is, they had higher scores on systemising and autistic traits and lower scores on empathy, compared to the typical population.

̽��ֱ��team also calculated the difference (or ‘d-score’) between each individual’s score on the systemising and empathy tests. A high d-score means a person’s systemising is higher than their empathy, and a low d-score means their empathy is higher than their systemising.

They found that in the typical population, men, on average, had a shift towards a high d-score, whereas women, on average, had a shift towards a low d-score. Autistic individuals, on average, had a shift towards an even higher d-score than typical males. Strikingly, d-scores accounted for 19 times more of the variance in autistic traits than other variables, including sex.

Finally, men, on average, had higher autistic trait scores than women. Those working in STEM (Science, Technology, Engineering and Mathematics), on average, had higher systemising and autistic traits scores than those in non-STEM occupations. And conversely, those working in non-STEM occupations, on average, had had higher empathy scores than those working in STEM.

In the paper, the authors discuss how it is important to bear in mind that differences observed in this study apply only to group averages, not to individuals. They underline that these data say nothing about an individual based on their gender, autism diagnosis, or occupation. To do that would constitute stereotyping and discrimination, which the authors strongly oppose.

Further, the authors reiterate that the two theories are applicable to only two dimensions of typical sex differences: empathy and systemising. They do not apply to all sex differences, such as aggression, and to extrapolate the theories beyond these two dimensions would be a misinterpretation.

Finally, the authors highlight that although autistic people on average struggle with ‘cognitive’ empathy – recognizing other people’s thoughts and feelings – they nevertheless have intact ‘affective’ empathy – they care about others. It is a common misunderstanding that autistic people struggle with all forms of empathy, which is untrue.

Dr Varun Warrier, from the Cambridge team, said: “These sex differences in the typical population are very clear. We know from related studies that individual differences in empathy and systemising are partly genetic, partly influenced by our prenatal hormonal exposure, and partly due to environmental experience. We need to investigate the extent to which these observed sex differences are due to each of these factors, and how these interact.”

Dr David Greenberg, from the Cambridge team, said: “Big data is important to draw conclusions that are replicable and robust. This is an example of how scientists can work with the media to achieve big data science.”

Dr Carrie Allison, from the Cambridge team, said: “We are grateful to both the general public and to the autism community for participating in this research. ̽��ֱ��next step must be to consider the relevance of these findings for education, and support where needed.”

Professor Simon Baron-Cohen, Director of the Autism Research Centre at Cambridge who proposed these two theories nearly two decades ago, said: “This research provides strong support for both theories. This study also pinpoints some of the qualities autistic people bring to neurodiversity. They are, on average, strong systemisers, meaning they have excellent pattern-recognition skills, excellent attention to detail, and an aptitude in understanding how things work. We must support their talents so they achieve their potential – and society benefits too.”

Reference
Greenberg, DM et al. Testing the Empathizing-Systemising theory of sex differences and the Extreme Male Brain theory of autism in half a million people. PNAS; 12 Nov 2018; DOI: 10.1073/pnas.1811032115

If you'd like to complete these measures and participate in studies at the Autism Research Centre please register here.

Scientists at the ̽��ֱ�� of Cambridge have completed the world’s largest ever study of typical sex differences and autistic traits. They tested and confirmed two long-standing psychological theories: the Empathising-Systemising theory of sex differences and the Extreme Male Brain theory of autism.

Big data is important to draw conclusions that are replicable and robust. This is an example of how scientists can work with the media to achieve big data science

David Greenberg

Mario Purisic on Unsplash

Crowd at a party

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Bridging the divide: philosophy meets science

sjr81 — Thu, 12 Jul 2018 15:03:08 +0000

̽��ֱ��Templeton World Charity Foundation Project, spearheaded by Professor Sarah Coakley, the Norris-Hulse Professor of Divinity at Cambridge, saw three postdoctoral researchers placed into science labs around the ̽��ֱ�� with the aim of addressing the ever-widening gap between those working in the fields of science and those working in fields of philosophy and theology.

For three years, Daniel De Haan, Natalja Deng and Peter Woodford worked side-by-side with colleagues from the Department of Experimental Psychology, the Department of Applied Mathematics and Theoretical Physics (DAMTP) and the Department of Zoology respectively – taking part in cutting-edge research, and being mentored by world-leading thinkers in their subject fields.

It is hoped that the huge success of this project – which saw unusually deep philosophical engagement with working scientists – will be a catalyst for similar experiments both in Cambridge and beyond.

Professor Coakley said: “Top level, path-breaking science can often go on in universities without any connections to the history and philosophy of science which is coming at the same material from a different direction. ̽��ֱ��philosophical questions are enormously pressing so we were delighted that some truly leading scientists at Cambridge were open to the possibility of having our three young researchers embedded with them.”

Dr Peter Woodford, who worked both in Cambridge’s Zoology labs and in the field in Africa to look at cooperation among meerkats, what makes them behaves the way they do, and how we as humans understand the value of selflessness, altruism and the care of others.

He said: “It was obviously a unique experience for any philosopher to have, seeing what animals are doing in their natural environment and asking why animals do what they do – that’s a central question of philosophy as well as science. ̽��ֱ��value of pursuing these big questions is to understand what we believe and why we believe it in a better way.”

Dr Natalja Deng, who worked on the cosmology strand of the project, alongside colleagues in DAMPT, said: “What does it mean to ask if God exists? And what does it mean to say that the universe had a beginning? If you ask yourself questions like this, you are doing philosophy.

“In order to do that, you need to talk to both theologians and physicists. They may not be used to talking to one another, but that’s all the more reason to bring them together in conversation. We were an experiment for this.”

Dr De Haan looked at the connections between cognitive neuroscience, psychology and philosophy for his strand of the project. As with his other Templeton colleagues, Daniel received formal training in his chosen subject areas to ensure they were up to date with the latest research and scientific developments in that particular field.

He said: “It was enormously helpful to spend time seeing what the day-to-day routines are, working in a lab and attending lectures. ̽��ֱ��people in my lab were open to the idea of having someone around from a different background and a different perspective.

“Academics in the humanities as well as the sciences are beginning to appreciate some of the difficulties arising from the extreme degrees of specialisation – where we are losing the ability to talk to each other.”

Added Coakley: “I’m more happy than I could have hoped. This was a unique experiment in how to create a new generation of scholars to learn this agility early in their careers and we have shown that if it’s possible in one of the top universities in the world for scientific and mathematical endeavour, it should be possible in other places, too.”

A unique three-year project to bridge the divide between science and philosophy – which embedded early-career philosophers into some of Cambridge’s ground-breaking scientific research clusters – is the subject of a new film released today.

Academics in the humanities as well as the sciences are beginning to appreciate some of the difficulties arising from the extreme degrees of specialisation – where we are losing the ability to talk to each other.

Daniel De Haan

Bridging the divide: Philosophy meets science

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Scientists link genes to brain anatomy in autism

cjb250 — Mon, 26 Feb 2018 18:59:50 +0000

Previous studies have reported differences in brain structure of autistic individuals. However, until now, scientists have not known which genes are linked to these differences.

̽��ֱ��team at the Autism Research Centre analysed magnetic resonance imaging (MRI) brain scans from more than 150 autistic children and compared them with MRI scans from similarly aged children but who did not have autism. They looked at variation in the thickness of the cortex, the outermost layer of the brain, and linked this to gene activity in the brain.

They discovered a set of genes linked to differences in the thickness of the cortex between autistic kids and non-autistic children. Many of these genes are involved in how brain cells (or neurons) communicate with each other. Interestingly, many of the genes identified in this study have been shown to have lower gene activity at the molecular level in autistic post mortem brain tissue samples.

̽��ֱ��study was led by two postdoctoral scientists, Dr Rafael Romero-Garcia and Dr Richard Bethlehem, and Varun Warrier, a PhD student. ̽��ֱ��study is published in the journal Molecular Psychiatry and provides the first evidence linking differences in the autistic brain to genes with atypical gene activity in autistic brains.

Dr Richard Bethlehem said: “This takes us one step closer to understanding why the brains of people with and without autism may differ from one another. We have long known that autism itself is genetic, but by combining these different data sets (brain imaging and genetics) we can now identify more precisely which genes are linked to how the autistic brain may differ. In essence, we are beginning to link molecular and macroscopic levels of analysis to better understand the diversity and complexity of autism.”

Varun Warrier added: “We now need to confirm these results using new genetic and brain scan data so as to understand how exactly gene activity and thickness of the cortex are linked in autism.”

“ ̽��ֱ��identification of genes linked to brain changes in autism is just the first step,” said Dr Rafael Romero-Garcia. “These promising findings reveal how important multidisciplinary approaches are if we want to better understand the molecular mechanisms underlying autism. ̽��ֱ��complexity of this condition requires a joint effort from a wide scientific community.”

̽��ֱ��research was supported by the Medical Research Council, the Autism Research Trust, the Wellcome Trust, and the Templeton World Charity Foundation, Inc.

Reference
Romero-Garcia, R et al. Synaptic and transcriptionally downregulated genes are associated with cortical thickness differences in autism. Molecular Psychiatry; 26 Feb; DOI: 10.1038/s41380-018-0023-7

A team of scientists at the ̽��ֱ�� of Cambridge has discovered that specific genes are linked to individual differences in brain anatomy in autistic children.

This takes us one step closer to understanding why the brains of people with and without autism may differ from one another

Richard Bethlehem

Lance Neilson

What are you looking at?

̽��ֱ��text in this work is licensed under a Creative Commons Attribution 4.0 International License. For image use please see separate credits above.

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