Service
Service
Steven M. Weisberg
The Department of PSYCHOLOGY at the UNIVERSITY OF FLORIDA, College of Liberal Arts and Sciences, invites applications for a full-time, nine-month, tenure-accruing, OPEN-AREA Assistant Professor with special emphasis in QUANTITATIVE METHODS, beginning August 16, 2024. We encourage applications from any research orientation in psychology and the position is open to candidates who employ a wide variety of methodological tools or approaches (including, but not limited to, computational modeling, statistics, artificial intelligence, structural equation modeling, multilevel modeling, network analysis, and longitudinal data analysis). Applicants will be expected to maintain an outstanding program of research with high potential for external funding, teach psychology graduate and undergraduate courses, advise students, and provide service to the institution.
Characterizing the causal role of large-scale network interactions in supporting complex cognition
Neuroimaging has greatly extended our capacity to study the workings of the human brain. Despite the wealth of knowledge this tool has generated however, there are still critical gaps in our understanding. While tremendous progress has been made in mapping areas of the brain that are specialized for particular stimuli, or cognitive processes, we still know very little about how large-scale interactions between different cortical networks facilitate the integration of information and the execution of complex tasks. Yet even the simplest behavioral tasks are complex, requiring integration over multiple cognitive domains. Our knowledge falls short not only in understanding how this integration takes place, but also in what drives the profound variation in behavior that can be observed on almost every task, even within the typically developing (TD) population. The search for the neural underpinnings of individual differences is important not only philosophically, but also in the service of precision medicine. We approach these questions using a three-pronged approach. First, we create a battery of behavioral tasks from which we can calculate objective measures for different aspects of the behaviors of interest, with sufficient variance across the TD population. Second, using these individual differences in behavior, we identify the neural variance which explains the behavioral variance at the network level. Finally, using covert neurofeedback, we perturb the networks hypothesized to correspond to each of these components, thus directly testing their casual contribution. I will discuss our overall approach, as well as a few of the new directions we are currently pursuing.
The Insights and Outcomes of the Wellcome-funded Waiting Times Project
Waiting is one of healthcare’s core experiences. It is there in the time it takes to access services; through the days, weeks, months or years needed for diagnoses; in the time that treatment takes; and in the elongated time-frames of recovery, relapse, remission and dying.Funded by the Wellcome Trust, our project opens up what it means to wait in and for healthcare by examining lived experiences, representations and histories of delayed and impeded time.In an era in which time is lived at increasingly different and complex tempos, Waiting Times looks to understand both the difficulties and vital significance of waiting for practices of care, offering a fundamental re-conceptualisation of the relation between time and care in contemporary thinking about health, illness, and wellbeing.
Children-Agent Interaction For Assessment and Rehabilitation: From Linguistic Skills To Mental Well-being
Socially Assistive Robots (SARs) have shown great potential to help children in therapeutic and healthcare contexts. SARs have been used for companionship, learning enhancement, social and communication skills rehabilitation for children with special needs (e.g., autism), and mood improvement. Robots can be used as novel tools to assess and rehabilitate children’s communication skills and mental well-being by providing affordable and accessible therapeutic and mental health services. In this talk, I will present the various studies I have conducted during my PhD and at the Cambridge Affective Intelligence and Robotics Lab to explore how robots can help assess and rehabilitate children’s communication skills and mental well-being. More specifically, I will provide both quantitative and qualitative results and findings from (i) an exploratory study with children with autism and global developmental disorders to investigate the use of intelligent personal assistants in therapy; (ii) an empirical study involving children with and without language disorders interacting with a physical robot, a virtual agent, and a human counterpart to assess their linguistic skills; (iii) an 8-week longitudinal study involving children with autism and language disorders who interacted either with a physical or a virtual robot to rehabilitate their linguistic skills; and (iv) an empirical study to aid the assessment of mental well-being in children. These findings can inform and help the child-robot interaction community design and develop new adaptive robots to help assess and rehabilitate linguistic skills and mental well-being in children.
Can we have jam today and jam tomorrow ?Improving outcomes for older people living with mental illness using applied and translational research
This talk will examine how approaches such as ‘big data’ and new ways of delivering clinical trials can improve current services for older people with mental illness (jam today) and identify and deliver new treatments in the future (jam tomorrow).
Prefrontal top-down projections control context-dependent strategy selection
The rules governing behavior often vary with behavioral contexts. As a result, an action rewarded in one context may be discouraged in another. Animals and humans are capable of switching between behavioral strategies under different contexts and acting adaptively according to the variable rules, a flexibility that is thought to be mediated by the prefrontal cortex (PFC). However, how the PFC orchestrates the context-dependent switch of strategies remains unclear. Here we show that pathway-specific projection neurons in the medial PFC (mPFC) differentially contribute to context-instructed strategy selection. In mice trained in a decision-making task in which a previously established rule and a newly learned rule are associated with distinct contexts, the activity of mPFC neurons projecting to the dorsomedial striatum (mPFC-DMS) encodes the contexts and further represents decision strategies conforming to the old and new rules. Moreover, mPFC-DMS neuron activity is required for the context-instructed strategy selection. In contrast, the activity of mPFC neurons projecting to the ventral midline thalamus (mPFC-VMT) does not discriminate between the contexts, and represents the old rule even if mice have adopted the new one. Furthermore, these neurons act to prevent the strategy switch under the new rule. Our results suggest that mPFC-DMS neurons promote flexible strategy selection guided by contexts, whereas mPFC-VMT neurons favor fixed strategy selection by preserving old rules.
The future of neuropsychology will be open, transdiagnostic, and FAIR - why it matters and how we can get there
Cognitive neuroscience has witnessed great progress since modern neuroimaging embraced an open science framework, with the adoption of shared principles (Wilkinson et al., 2016), standards (Gorgolewski et al., 2016), and ontologies (Poldrack et al., 2011), as well as practices of meta-analysis (Yarkoni et al., 2011; Dockès et al., 2020) and data sharing (Gorgolewski et al., 2015). However, while functional neuroimaging data provide correlational maps between cognitive functions and activated brain regions, its usefulness in determining causal link between specific brain regions and given behaviors or functions is disputed (Weber et al., 2010; Siddiqiet al 2022). On the contrary, neuropsychological data enable causal inference, highlighting critical neural substrates and opening a unique window into the inner workings of the brain (Price, 2018). Unfortunately, the adoption of Open Science practices in clinical settings is hampered by several ethical, technical, economic, and political barriers, and as a result, open platforms enabling access to and sharing clinical (meta)data are scarce (e.g., Larivière et al., 2021). We are working with clinicians, neuroimagers, and software developers to develop an open source platform for the storage, sharing, synthesis and meta-analysis of human clinical data to the service of the clinical and cognitive neuroscience community so that the future of neuropsychology can be transdiagnostic, open, and FAIR. We call it neurocausal (https://neurocausal.github.io).
Perception during visual disruptions
Visual perception is perceived as continuous despite frequent disruptions in our visual environment. For example, internal events, such as saccadic eye-movements, and external events, such as object occlusion temporarily prevent visual information from reaching the brain. Combining evidence from these two models of visual disruption (occlusion and saccades), we will describe what information is maintained and how it is updated across the sensory interruption. Lina Teichmann will focus on dynamic occlusion and demonstrate how object motion is processed through perceptual gaps. Grace Edwards will then describe what pre-saccadic information is maintained across a saccade and how it interacts with post-saccadic processing in retinotopically relevant areas of the early visual cortex. Both occlusion and saccades provide a window into how the brain bridges perceptual disruptions. Our evidence thus far suggests a role for extrapolation, integration, and potentially suppression in both models. Combining evidence from these typically separate fields enables us to determine if there is a set of mechanisms which support visual processing during visual disruptions in general.
Growing a world-class precision medicine industry
Monash Biomedical Imaging is part of the new $71.2 million Australian Precision Medicine Enterprise (APME) facility, which will deliver large-scale development and manufacturing of precision medicines and theranostic radiopharmaceuticals for industry and research. A key feature of the APME project is a high-energy cyclotron with multiple production clean rooms, which will be located on the Monash Biomedical Imaging (MBI) site in Clayton. This strategic co-location will facilitate radiochemistry, PET and SPECT research and clinical use of theranostic (therapeutic and diagnostic) radioisotopes produced on-site. In this webinar, MBI’s Professor Gary Egan and Dr Maggie Aulsebrook will explain how the APME will secure Australia’s supply of critical radiopharmaceuticals, build a globally competitive Australian manufacturing hub, and train scientists and engineers for the Australian workforce. They will cover the APME’s state-of-the-art 30 MeV and 18-24 MeV cyclotrons and radiochemistry facilities, as well as the services that will be accessible to students, scientists, clinical researchers, and pharmaceutical companies in Australia and around the world. The APME is a collaboration between Monash University, Global Medical Solutions Australia, and Telix Pharmaceuticals. Professor Gary Egan is Director of Monash Biomedical Imaging, Director of the ARC Centre of Excellence for Integrative Brain Function and a Distinguished Professor at the Turner Institute for Brain and Mental Health, Monash University. He is also lead investigator of the Victorian Biomedical Imaging Capability, and Deputy Director of the Australian National Imaging Facility. Dr Maggie Aulsebrook obtained her PhD in Chemistry at Monash University and specialises in the development and clinical translation of radiopharmaceuticals. She has led the development of several investigational radiopharmaceuticals for first-in-human application. Maggie leads the Radiochemistry Platform at Monash Biomedical Imaging.
Improving the identification of cardiometabolic risk in early psychosis
People with chronic schizophrenia die on average 10-15 years sooner than the general population, mostly due to physical comorbidity. While sociodemographic, chronic lifestyle and iatrogenic factors are important contributors to this comorbidity, a growing body of research is beginning to suggest that early signs of cardiometabolic dysfunction may be present from the onset of psychosis in some young adults, and may even be detectable before the onset of psychosis. Given that primary prevention is the best means to prevent the onset of more chronic and severe cardiometabolic phenotypes such as CVD, there is clear need to be able to identify young adults with psychosis who are most at risk of future adverse cardiometabolic outcomes, such that the most intensive interventions can be directed in an informed way to attenuate the risk or even prevent those adverse outcomes from occurring.In this talk, Ben will first outline some recent advances in our understanding of the association between cardiometabolic and schizophrenia spectrum disorders. He will then introduce the field of cardiometabolic risk prediction, and highlight how existing tools developed for older general population adults are unlikely to be suitable for young people with psychosis. Finally, he will discuss the current state of play and the future of the Psychosis Metabolic Risk Calculator (PsyMetRiC), a novel clinically useful cardiometabolic risk prediction algorithm tailored for young people with psychosis, which has been developed and externally validated using data from three psychosis early intervention services in the UK.
Computational Principles of Event Memory
Our ability to understand ongoing events depends critically on general knowledge about how different kinds of situations work (schemas), and also on recollection of specific instances of these situations that we have previously experienced (episodic memory). The consensus around this general view masks deep questions about how these two memory systems interact to support event understanding: How do we build our library of schemas? and how exactly do we use episodic memory in the service of event understanding? Given rich, continuous inputs, when do we store and retrieve episodic memory “snapshots”, and how are they organized so as to ensure that we can retrieve the right snapshots at the right time? I will develop predictions about how these processes work using memory augmented neural networks (i.e., neural networks that learn how to use episodic memory in the service of task performance), and I will present results from relevant fMRI and behavioral studies.
The evolutionary and psychological origins of reciprocal cooperation
If only those behaviours evolve that increase the actor’s own survival and reproductive success, then it might come as a surprise that cooperative behaviours, i.e. providing benefits to others, are a widespread phenomenon. Many animals cooperate even with unrelated individuals in various contexts, like providing care or food. One possibility to explain these behaviours is reciprocity. Reciprocal cooperation, i.e. helping those that were helpful before, is a ubiquitous and important trait of human sociality. Still, the evolutionary origin of it is largely unclear, mainly because it is believed that other animals do not exchange help reciprocally. Consequently, reciprocity is suggested to have evolved in the human lineage only. In contrast to this, I propose that reciprocity is not necessarily cognitively demanding and likely to be widespread. In my talk, I will first shed light on the mechanisms of reciprocal cooperation in Norway rats (Rattus norvegicus). In a series of studies, my colleagues and I have demonstrated that Norway rats reciprocally exchange goods and services between and within different commodities and independent of kinship. Furthermore, to understand the evolutionary origins of human reciprocity, and whether it is shared with other animals, I will then discuss evidence for reciprocity in non-human primates, which are our closest living relatives. A thorough analysis of the findings showed that reciprocity is present and, for example, not confined to unrelated individuals, but that the choice of commodities can impact the likelihood of reciprocation. Based on my findings, I conclude that reciprocal cooperation in non-human animals is present but largely neglected and not restricted to humans. In order to deepen our understanding of the evolutionary origins of reciprocity in more general, future studies should investigate when and how reciprocity in non-human animals emerged and how it is maintained.
The BHP Chronic Pain Health Integration Team: Helping those with chronic pain to access the support they need / A bit of a To and Fro with population pain science
Candy will provide an overview of Bristol Health Partners' Chronic Pain Health Integration Team which brings together clinicians, academics, patients and carers to focus on improving the lives of those with chronic pain and supporting those who provide chronic pain services or care. Tony will describe recent and ongoing studies that have been forward and reverse translating pain neuroscience from animal to human including functional imaging in patients, microneurography, industrial partnerships and trials of novel preventative approaches that are benefitting from the people, expertise and facilities available in Bristol and GW4.
Multitask performance humans and deep neural networks
Humans and other primates exhibit rich and versatile behaviour, switching nimbly between tasks as the environmental context requires. I will discuss the neural coding patterns that make this possible in humans and deep networks. First, using deep network simulations, I will characterise two distinct solutions to task acquisition (“lazy” and “rich” learning) which trade off learning speed for robustness, and depend on the initial weights scale and network sparsity. I will chart the predictions of these two schemes for a context-dependent decision-making task, showing that the rich solution is to project task representations onto orthogonal planes on a low-dimensional embedding space. Using behavioural testing and functional neuroimaging in humans, we observe BOLD signals in human prefrontal cortex whose dimensionality and neural geometry are consistent with the rich learning regime. Next, I will discuss the problem of continual learning, showing that behaviourally, humans (unlike vanilla neural networks) learn more effectively when conditions are blocked than interleaved. I will show how this counterintuitive pattern of behaviour can be recreated in neural networks by assuming that information is normalised and temporally clustered (via Hebbian learning) alongside supervised training. Together, this work offers a picture of how humans learn to partition knowledge in the service of structured behaviour, and offers a roadmap for building neural networks that adopt similar principles in the service of multitask learning. This is work with Andrew Saxe, Timo Flesch, David Nagy, and others.
The early impact of COVID-19 on mental health and community physical health services and their patients’ mortality in Cambridgeshire and Peterborough, UK
COVID -19 has affected social interaction and healthcare worldwide. This talk will focus on the impact of the pandemic and “lockdown” on mental health services, community physical health services, and patient mortality in Cambridgeshire and Peterborough, based on the analysis of de-identified data from the primary NHS provider of secondary care mental health services to this population (~0.86 million)
Population studies and ageing brains, in a time of COVID
This presentation will include a brief resume of research in older populations led from Cambridge that have informed current clinical understanding and policy regarding services and prevention for and of dementia. These population studies have more recently been ‘re-purposed’ with enthusiasm from participants into a trial platform, and this also has enabled ongoing follow-up by telephone during the COVID pandemic. Although there are no formal outputs from these latter developments general impressions will be shared.
Cerebro Parental: La biología aun invisible del desarrollo infantil
Desde la investigación en antropología evolutiva, las neurociencias del comportamiento parental y los estudios de cohortes de orfelinatos, los nuevos conocimientos confluyen en la mayor importancia critica del periodo postnatal inmediato para el desarrollo social humano. Surge la explicación biológica de la interdependencia de los cambios comportamentales en los adultos que crían y el recién nacido: Nature of Nurture. Del concepto unidireccional clásico de la necesidad de estimular un cerebro inmaduro, se comienza a comprender la naturaleza de la interacción en red entre el cerebro neonatal y el cerebro parental que también debe ser estimulado. Concebir, engendra y criar son etapas sucesivas de la reproducción pero no indispensablemente continuas. La función parental es primariamente dependiente de la disponibilidad para cuidar al recién nacido.
Sensory priors, and choice and outcome history in service of optimal behaviour in noisy environments
COSYNE 2023