Visual restoration after decades of blindness is now becoming possible by means of retinal and cortical prostheses, as well as emerging stem cell and gene therapeutic approaches. After restoring visual perception, however, a key question remains. Are there optimal means and methods for retraining the visual cortex to process visual inputs, and for learning or relearning to “see”? Up to this point, it has been largely assumed that if the sensory loss is visual, then the rehabilitation focus should also be primarily visual. However, the other senses play a key role in visual rehabilitation due to the plastic repurposing of visual cortex during blindness by audition and somatosensation, and also to the reintegration of restored vision with the other senses. I will present multisensory neuroimaging results, cortical thickness changes, as well as behavioral outcomes for patients with Retinitis Pigmentosa (RP), which causes blindness by destroying photoreceptors in the retina. These patients have had their vision partially restored by the implantation of a retinal prosthesis, which electrically stimulates still viable retinal ganglion cells in the eye. Our multisensory and structural neuroimaging and behavioral results suggest a new, holistic concept of visual rehabilitation that leverages rather than neglects audition, somatosensation, and other sensory modalities.

Fast periodic visual stimulation (FPVS) has emerged as a promising tool for assessing cognitive function in individuals with dementia. This technique leverages electroencephalography (EEG) to measure brain responses to rapidly presented visual stimuli, offering a non-invasive and objective method for evaluating a range of cognitive functions. Unlike traditional cognitive assessments, FPVS does not rely on behavioural responses, making it particularly suitable for individuals with cognitive impairment. In this talk I will highlight a series of studies that have demonstrated its ability to detect subtle deficits in recognition memory, visual processing and attention in dementia patients using EEG in the lab, at home and in clinic. The method is quick, cost-effective, and scalable, utilizing widely available EEG technology. FPVS holds significant potential as a functional biomarker for early diagnosis and monitoring of dementia, paving the way for timely interventions and improved patient outcomes.

Humans and other animals approach reward and avoid punishment and pay attention to cues predicting these events. Such motivated behavior thus appears to be guided by value, which directs behavior towards or away from positively or negatively valenced outcomes. Moreover, it is facilitated by (top-down) salience, which enhances attention to behaviorally relevant learned cues predicting the occurrence of valenced outcomes. Using human neuroimaging, we recently separated value (ventral striatum, posterior ventromedial prefrontal cortex) from salience (anterior ventromedial cortex, occipital cortex) in the domain of liquid reward and punishment. Moreover, we investigated potential drivers of learned salience: the probability and uncertainty with which valenced and non-valenced outcomes occur. We find that the brain dissociates valenced from non-valenced probability and uncertainty, which indicates that reinforcement matters for the brain, in addition to information provided by probability and uncertainty alone, regardless of valence. Finally, we assessed learning signals (unsigned prediction errors) that may underpin the acquisition of salience. Particularly the insula appears to be central for this function, encoding a subjective salience prediction error, similarly at the time of positively and negatively valenced outcomes. However, it appears to employ domain-specific time constants, leading to stronger salience signals in the aversive than the appetitive domain at the time of cues. These findings explain why previous research associated the insula with both valence-independent salience processing and with preferential encoding of the aversive domain. More generally, the distinction of value and salience appears to provide a useful framework for capturing the neural basis of motivated behavior.

Contrary to the original normative decision-making standpoint, empirical studies have repeatedly reported that risk preferences are affected by the disclosure of choice outcomes (feedback). Although no consensus has yet emerged regarding the properties and mechanisms of this effect, a widespread and intuitive hypothesis is that repeated feedback affects risk preferences by means of a learning effect, which alters the representation of subjective probabilities. Here, we ran a series of seven experiments (N= 538), tailored to decipher the effects of feedback on risk preferences. Our results indicate that the presence of feedback consistently increases risk-taking, even when the risky option is economically less advantageous. Crucially, risk-taking increases just after the instructions, before participants experience any feedback. These results challenge the learning account, and advocate for a dispositional effect, induced by the mere anticipation of feedback information. Epistemic curiosity and regret avoidance may drive this effect in partial and complete feedback conditions, respectively.

2024 BACN Early-Career Prize Lecture Many of our decisions affect other people. Our choices can decelerate climate change, stop the spread of infectious diseases, and directly help or harm others. Prosocial behaviours – decisions that help others – could contribute to reducing the impact of these challenges, yet their computational and neural mechanisms remain poorly understood. I will present recent work that examines prosocial motivation, how willing we are to incur costs to help others, prosocial learning, how we learn from the outcomes of our choices when they affect other people, and prosocial preferences, our self-reports of helping others. Throughout the talk, I will outline the possible computational and neural bases of these behaviours, and how they may differ from young adulthood to old age.

Psychedelics like psilocybin have shown rapid and long-lasting efficacy on depressive and anxiety symptoms. Other psychedelics with shorter half-lives, such as DMT and 5-MeO-DMT, have also shown promising preliminary outcomes in major depression, making them interesting candidates for clinical practice. Despite several promising clinical studies, the influence of the context on therapeutic responses or adverse effects remains poorly documented. To address this, we conducted preclinical studies evaluating the psychopharmacological profile of 5-MeO-DMT in contexts previously validated in mice as either pleasant (positive setting) or aversive (negative setting). Healthy C57BL/6J male mice received a single intraperitoneal (i.p.) injection of 5-MeO-DMT at doses of 0.5, 5, and 10 mg/kg, with assessments at 2 hours, 24 hours, and one week post-administration. In a corticosterone (CORT) mouse model of depression, 5-MeO-DMT was administered in different settings, and behavioral tests mimicking core symptoms of depression and anxiety were conducted. In CORT-exposed mice, an acute dose of 0.5 mg/kg administered in a neutral setting produced antidepressant-like effects at 24 hours, as observed by reduced immobility time in the Tail Suspension Test (TST). In a positive setting, the drug also reduced latency to first immobility and total immobility time in the TST. However, these beneficial effects were negated in a negative setting, where 5-MeO-DMT failed to produce antidepressant-like effects and instead elicited an anxiogenic response in the Elevated Plus Maze (EPM).Our results indicate a strong influence of setting on the psychopharmacological profile of 5-MeO-DMT. Future experiments will examine cortical markers of pre- and post-synaptic density to correlate neuroplasticity changes with the behavioral effects of 5-MeO-DMT in different settings.

Parvalbumin-positive GABAergic interneurons (PV-INs) provide inhibitory control of excitatory neuron activity, coordinate circuit function, and regulate behavior and cognition. PV-INs are uniquely susceptible to loss and dysfunction in traumatic brain injury (TBI) and epilepsy but the cause of this susceptibility is unknown. One hypothesis is that PV-INs use specialized metabolic systems to support their high-frequency action potential firing and that metabolic stress disrupts these systems, leading to their dysfunction and loss. Metabolism-based therapies can restore PV-IN function after injury in preclinical TBI models. Based on these findings, we hypothesize that (1) PV-INs are highly metabolically specialized, (2) these specializations are lost after TBI, and (3) restoring PV-IN metabolic specializations can improve PV-IN function as well as TBI-related outcomes. Using novel single-cell approaches, we can now quantify cell-type-specific metabolism in complex tissues to determine whether PV-IN metabolic dysfunction contributes to the pathophysiology of TBI.

The nervous system orchestrates adaptive behaviors by intricately coordinating responses to internal cues and environmental stimuli. This involves integrating sensory input, managing competing motivational states, and drawing on past experiences to anticipate future outcomes. While traditional models attribute this complexity to interactions between the mesocorticolimbic system and hypothalamic centers, the specific nodes of integration have remained elusive. Recent research, including our own, sheds light on the midline thalamus's overlooked role in this process. We propose that the midline thalamus integrates internal states with memory and emotional signals to guide adaptive behaviors. Our investigations into midline thalamic neuronal circuits have provided crucial insights into the neural mechanisms behind flexibility and adaptability. Understanding these processes is essential for deciphering human behavior and conditions marked by impaired motivation and emotional processing. Our research aims to contribute to this understanding, paving the way for targeted interventions and therapies to address such impairments.

Advancements in cognitive neuroscience have provided profound insights into the workings of the human brain and the methods used offer opportunities to enhance performance, cognition, and mental health. Drawing upon interdisciplinary collaborations in the University of California San Diego, Human Performance Optimization Lab, this talk explores the application of cognitive neuroscience principles in three domains to improve human performance and alleviate mental health challenges. The first section will discuss studies addressing the role of vision and oculomotor function in athletic performance and the potential to train these foundational abilities to improve performance and sports outcomes. The second domain considers the use of electrophysiological measurements of the brain and heart to detect, and possibly predict, errors in manual performance, as shown in a series of studies with surgeons as they perform robot-assisted surgery. Lastly, findings from clinical trials testing personalized interventional treatments for mood disorders will be discussed in which the temporal and spatial parameters of transcranial magnetic stimulation (TMS) are individualized to test if personalization improves treatment response and can be used as predictive biomarkers to guide treatment selection. Together, these translational studies use the measurement tools and constructs of cognitive neuroscience to improve human performance and well-being.

Filmmakers and editors have empirically developed techniques to ensure the spatiotemporal continuity of a film's narration. In terms of time, editing techniques (e.g., elliptical, overlapping, or cut minimization) allow for the manipulation of the perceived duration of events as they unfold on screen. More specifically, a scene can be edited to be time compressed, expanded, or real-time in terms of its perceived duration. Despite the consistent application of these techniques in filmmaking, their perceptual outcomes have not been experimentally validated. Given that viewing a film is experienced as a precise simulation of the physical world, the use of cinematic material to examine aspects of time perception allows for experimentation with high ecological validity, while filmmakers gain more insight on how empirically developed techniques influence viewers' time percept. Here, we investigated how such time manipulation techniques of an action affect a scene's perceived duration. Specifically, we presented videos depicting different actions (e.g., a woman talking on the phone), edited according to the techniques applied for temporal manipulation and asked participants to make verbal estimations of the presented scenes' perceived durations. Analysis of data revealed that the duration of expanded scenes was significantly overestimated as compared to that of compressed and real-time scenes, as was the duration of real-time scenes as compared to that of compressed scenes. Therefore, our results validate the empirical techniques applied for the modulation of a scene's perceived duration. We also found interactions on time estimates of scene type and editing technique as a function of the characteristics and the action of the scene presented. Thus, these findings add to the discussion that the content and characteristics of a scene, along with the editing technique applied, can also modulate perceived duration. Our findings are discussed by considering current timing frameworks, as well as attentional saliency algorithms measuring the visual saliency of the presented stimuli.

People are confronted every day with internal or external stimuli that can elicit emotions. In order to avoid negative ones, or to pursue individual aims, emotions are often regulated. The available emotion regulation strategies have been previously described as efficient or inefficient, but many studies highlighted that the strategies’ efficiency may be influenced by some different aspects such as personality. In this project, the efficiency of several strategies (e.g., reappraisal, suppression, distraction, …) has been studied according to personality profiles, by using the Big Five personality model and the Maladaptive Personality Trait Model. Moreover, the strategies’ efficiency has been tested according to the main emotional responses, namely experience, expressivity and physiological arousal. Results mainly highlighted the differential impact of strategies on individuals and a slight impact of personality. An important factor seems however to be the emotion parameter we are considering, potentially revealing a complex interplay between strategy, personality, and the considered emotion response. Based on these outcomes, further clinical aspects and recommendations will be also discussed.

We use rapid eye, head, and body movements to extract information from a new part of the visual scene upon each new gaze fixation. But the consequences of such visual actions go beyond their intended sensory outcomes. On the one hand, intrinsic consequences accompany movement preparation as covert internal processes (e.g., predictive changes in the deployment of visual attention). On the other hand, visual actions have incidental consequences, side effects of moving the sensory surface to its intended goal (e.g., global motion of the retinal image during saccades). In this talk, I will present studies in which we investigated intrinsic and incidental sensory consequences of visual actions and their sensorimotor functions. Our results provide insights into continuously interacting top-down and bottom-up sensory processes, and they reify the necessity to study perception in connection to motor behavior that shapes its fundamental processes.

Trends in NeuroAI is a reading group hosted by the MedARC Neuroimaging & AI lab (https://medarc.ai/fmri). Title: SwiFT: Swin 4D fMRI Transformer Abstract: Modeling spatiotemporal brain dynamics from high-dimensional data, such as functional Magnetic Resonance Imaging (fMRI), is a formidable task in neuroscience. Existing approaches for fMRI analysis utilize hand-crafted features, but the process of feature extraction risks losing essential information in fMRI scans. To address this challenge, we present SwiFT (Swin 4D fMRI Transformer), a Swin Transformer architecture that can learn brain dynamics directly from fMRI volumes in a memory and computation-efficient manner. SwiFT achieves this by implementing a 4D window multi-head self-attention mechanism and absolute positional embeddings. We evaluate SwiFT using multiple large-scale resting-state fMRI datasets, including the Human Connectome Project (HCP), Adolescent Brain Cognitive Development (ABCD), and UK Biobank (UKB) datasets, to predict sex, age, and cognitive intelligence. Our experimental outcomes reveal that SwiFT consistently outperforms recent state-of-the-art models. Furthermore, by leveraging its end-to-end learning capability, we show that contrastive loss-based self-supervised pre-training of SwiFT can enhance performance on downstream tasks. Additionally, we employ an explainable AI method to identify the brain regions associated with sex classification. To our knowledge, SwiFT is the first Swin Transformer architecture to process dimensional spatiotemporal brain functional data in an end-to-end fashion. Our work holds substantial potential in facilitating scalable learning of functional brain imaging in neuroscience research by reducing the hurdles associated with applying Transformer models to high-dimensional fMRI. Speaker: Junbeom Kwon is a research associate working in Prof. Jiook Cha’s lab at Seoul National University. Paper link: https://arxiv.org/abs/2307.05916

Changes in ocular hemodynamics may be indicative of pathological conditions in the eye (e.g. glaucoma, age-related macular degeneration), but also elsewhere in the body (e.g. systemic hypertension, diabetes, neurodegenerative disorders). Thanks to its transparent fluids and structures that allow the light to go through, the eye offers a unique window on the circulation from large to small vessels, and from arteries to veins. Deciphering the causes that lead to changes in ocular hemodynamics in a specific individual could help prevent vision loss as well as aid in the diagnosis and management of diseases beyond the eye. In this talk, we will discuss how mathematical and computational modelling can help in this regard. We will focus on two main factors, namely blood pressure (BP), which drives the blood flow through the vessels, and intraocular pressure (IOP), which compresses the vessels and may impede the flow. Mechanism-driven models translates fundamental principles of physics and physiology into computable equations that allow for identification of cause-to-effect relationships among interplaying factors (e.g. BP, IOP, blood flow). While invaluable for causality, mechanism-driven models are often based on simplifying assumptions to make them tractable for analysis and simulation; however, this often brings into question their relevance beyond theoretical explorations. Data-driven models offer a natural remedy to address these short-comings. Data-driven methods may be supervised (based on labelled training data) or unsupervised (clustering and other data analytics) and they include models based on statistics, machine learning, deep learning and neural networks. Data-driven models naturally thrive on large datasets, making them scalable to a plethora of applications. While invaluable for scalability, data-driven models are often perceived as black- boxes, as their outcomes are difficult to explain in terms of fundamental principles of physics and physiology and this limits the delivery of actionable insights. The combination of mechanism-driven and data-driven models allows us to harness the advantages of both, as mechanism-driven models excel at interpretability but suffer from a lack of scalability, while data-driven models are excellent at scale but suffer in terms of generalizability and insights for hypothesis generation. This combined, integrative approach represents the pillar of the interdisciplinary approach to data science that will be discussed in this talk, with application to ocular hemodynamics and specific examples in glaucoma research.

Web-based self-help interventions for coping with prolonged grief have established their efficacy. However, few programs address recent losses and investigate the effect of self-tailoring of the content. In an international project, the text-based self-help program LIVIA was adapted and complemented with an Embodied Conversational Agent, an initial risk assessment and a monitoring tool. The new program SOLENA was evaluated in three trials in Switzerland, the Netherlands and Portugal. The aim of the trials was to evaluate the clinical efficacy for reducing grief, depression and loneliness and to examine client satisfaction and technology acceptance. The talk will present the SOLENA program and report results of the Portuguese and Dutch trial as well as preliminary results of the Swiss RCT. The ongoing Swiss trial compares a standardised to a self-tailored delivery format and analyses clinical outcomes, the helpfulness of specific content and the working alliance. Finally, lessons learned in the development and evaluation of a web-based self-help intervention for older adults will be discusses.

Theories from reinforcement learning have been highly influential for interpreting neural activity in the biological circuits critical for animal and human learning. Central among these is the identification of phasic activity in dopamine neurons as a reward prediction error signal that drives learning in basal ganglia and prefrontal circuits. However, recent findings suggest that dopaminergic prediction error signals have access to complex, structured reward predictions and are sensitive to more properties of outcomes than learning theories with simple scalar value predictions might suggest. Here, I will present recent work in which we probed the identity-specific structure of reward prediction errors in an odor-guided choice task and found evidence for multiple predictive “threads” that segregate reward predictions, and reward prediction errors, according to the specific sensory features of anticipated outcomes. Our results point to an expanded class of neural reinforcement learning algorithms in which biological agents learn rich associative structure from their environment and leverage it to build reward predictions that include information about the specific, and perhaps idiosyncratic, features of available outcomes, using these to guide behavior in even quite simple reward learning tasks.

Studies show that abuse, neglect or trauma during childhood can lead to lifelong struggles including with mental health. Fortunately research also indicates that solutions and interventions at various stages of life can be developed to help. But even among people who remain resilient or do not experience acute stresses, a lack of opportunity early in life due to poverty or systemic racism can still constrain their ability to realize their full potential. In what ways are health and other outcomes affected by early life difficulty? What can individuals and institutions do to enhance opportunity?" "This daylong event will feature talks by neuroscientists, policy experts, physicians, educators and activists as they discuss how our experiences and biology work together to affect how our minds develop and what can be accomplished in helping people overcome early disadvantages.

Different prefrontal areas contribute in distinctly different ways to rule-guided behaviour in the context of a Wisconsin Card Sorting Test (WCST) analog for macaques. For example, causal evidence from circumscribed lesions in NHPs reveals that dorsolateral prefrontal cortex (dlPFC) is necessary to maintain a reinforced abstract rule in working memory, orbitofrontal cortex (OFC) is needed to rapidly update representations of rule value, and the anterior cingulate cortex (ACC) plays a key role in cognitive control and integrating information for correct and incorrect trials over recent outcomes. Moreover, recent lesion studies of frontopolar cortex (FPC) suggest it contributes to representing the relative value of unchosen alternatives, including rules. Yet we do not understand how these functional specializations relate to intrinsic neuronal activities nor the extent to which these neuronal activities differ between different prefrontal regions. After reviewing the aforementioned causal evidence I will present our new data from studies using multi-area multi-electrode recording techniques in NHPs to simultaneously record from four different prefrontal regions implicated in rule-guided behaviour. Multi-electrode micro-arrays (‘Utah arrays’) were chronically implanted in dlPFC, vlPFC, OFC, and FPC of two macaques, allowing us to simultaneously record single and multiunit activity, and local field potential (LFP), from all regions while the monkey performs the WCST analog. Rule-related neuronal activity was widespread in all areas recorded but it differed in degree and in timing between different areas. I will also present preliminary results from decoding analyses applied to rule-related neuronal activities both from individual clusters and also from population measures. These results confirm and help quantify dynamic task-related activities that differ between prefrontal regions. We also found task-related modulation of LFPs within beta and gamma bands in FPC. By combining this correlational recording methods with trial-specific causal interventions (electrical microstimulation) to FPC we could significantly enhance and impair animals performance in distinct task epochs in functionally relevant ways, further consistent with an emerging picture of regional functional specialization within a distributed framework of interacting and interconnected cortical regions.

In vision, there is, surprisingly, very little evidence of common factors. Most studies have found only weak correlations between performance in different visual tests; meaning that, a participant performing better in one test is not more likely to perform also better in another test. Likewise in ageing, cross-sectional studies have repeatedly shown that older adults show deteriorated performance in most visual tests compared to young adults. However, within the older population, there is no evidence for a common factor underlying visual abilities. To investigate further the decline of visual abilities, we performed a longitudinal study with a battery of nine visual tasks three times, with two re-tests after about 4 and 7 years. Most visual abilities are rather stable across 7 years, but not visual acuity. I will discuss possible causes of these paradoxical outcomes.

Post-diagnostic research on rare genetic developmental disorders presents new opportunities (and a few challenges) for discovery neuroscience and translation. In this talk, Kate will describe and discuss neurodevelopmental phenotypes arising from rare, high penetrance genomic variants which directly influence pre-synaptic vesicle cycling (SVC disorders). She will focus on Synaptotagmin-1 Associated Neurodevelopmental Disorder (also known as Baker Gordon Syndrome), first described in 2015 and now diagnosed in more than 50 children and young people worldwide. She will then present work-in-progress by her group on the neurodevelopmental spectrum of SVC disorders more broadly, and discuss opportunities for collaborative neuroscience which can bridge the gaps between genetic cause and complex neurological, cognitive and mental health outcomes.

The circadian release of endogenous glucocorticoids is essential in preparing and synchronizing the body’s daily physiological needs. Disruption in the rhythmic activity of glucocorticoids has been observed in individuals with a variety of cancer types, and blunting of this rhythm has been shown to predict cancer mortality and declines in quality of life. This suggests that a disrupted glucocorticoid rhythm is potentially a shared phenotype across cancers. However, where this phenomenon is driven by the cancer itself, and the causal mechanisms that link glucocorticoid rhythm dysfunction and cancer outcomes remain preliminary at best. The regulation of daily glucocorticoid activity has been well-characterized and is maintained, in part, by the coordinated response of the hypothalamic-pituitary-adrenal (HPA) axis, consisting of the suprachiasmatic nucleus (SCN) and corticotropin-releasing hormone-expressing neurons of the paraventricular nucleus of the hypothalamus (PVNCRH). Consequently, we set out to examine if cancer-induced glucocorticoid dysfunction is regulated by disruptions within these hypothalamic nuclei. In comparison to their tumor-free baseline, mammary tumor-bearing mice exhibited a blunting of glucocorticoid rhythms across multiple timepoints throughout the day, as measured by the overall levels and the slope of fecal corticosterone rhythms, during tumor progression. We further examined how peripheral tumors shape hypothalamic activity within the brain. Serial two-photon tomography for whole-brain cFos imaging suggests a disrupted activation of the PVN in mice with tumors. Additionally, we found GFP labeled CRH+ neurons within the PVN after injection of pseudorabies virus expressing GFP into the tumor, pointing to the PVN as a primary target disrupted by mammary tumors. Preliminary in vivo fiber photometry data show that PVNCRH neurons exhibit enhanced calcium activity during tumor progression, as compared to baseline (no tumor) activity. Taken together, this suggests that there may be an overactive HPA response during tumor progression, which in turn, may result in a subsequent negative feedback on glucocorticoid rhythms. Current studies are examining whether tumor progression modulates SCN calcium activity, how the transcriptional profile of PVNCRH neurons is changed, and test if manipulation of the neurocircuitry surrounding glucocorticoid rhythmicity alters tumor characteristics.

In this talk I will present our recent behavioural and neuroscience research on how the brain motivates itself to form particular beliefs and why it does so. I will propose that the utility of a belief is derived from the potential outcomes associated with holding it. Outcomes can be internal (e.g., positive/negative feelings) or external (e.g., material gain/loss), and only some are dependent on belief accuracy. We show that belief change occurs when the potential outcomes of holding it alters, for example when moving from a safe environment to a threatening environment. Our findings yield predictions about how belief formation alters as a function of mental health. We test these predictions using a linguistic analysis of participants’ web searches ‘in the wild’ to quantify the affective properties of information they consume and relate those to reported psychiatric symptoms. Finally, I will present a study in which we used our framework to alter the incentive structure of social media platforms to reduce the spread of misinformation and improve belief accuracy.

How do children learn to read in different countries? How do deficits in various components of the reading network affect learning outcomes? What are the consequences of such deficits in different languages? In this talk, I will present a full-blown developmentally plausible computational model of reading acquisition that has been implemented in English, French, Italian and German. The model can simulate individual learning trajectories and intervention outcomes on the basis of three component skills: orthography, phonology, and vocabulary. I will use the model to show how cross-language differences affect the learning-to-read process in different languages and to investigate to what extent similar deficits will produce similar or different manifestations of dyslexia in different languages.

Chronic exercise is a powerful intervention that lowers the incidence of most age-related diseases while promoting healthy metabolism in humans. However, illness, injury or age prevent many humans from consistently exercising. Thus, identification of molecular targets that can mimic the benefits of exercise would be a valuable tool to improve health outcomes of humans with neurodegenerative or mitochondrial diseases, or those with enforced sedentary lifestyles. Using a novel exercise platform for Drosophila, we have identified octopaminergic neurons as a key subset of neurons that are critical for the exercise response, and shown that periodic daily stimulation of these neurons can induce a systemic exercise response in sedentary flies. Octopamine is released into circulation where it signals through various octopamine receptors in target tissues and induces gene expression changes similar to exercise. In particular, we have identified several key molecules that respond to octopamine in skeletal muscle, including the mTOR modulator Sestrin, the PGC-1α homolog Spargel, and the FNDC5/Irisin homolog Iditarod. We are currently testing these molecules as potential therapies for multiple diseases that reduce mobility, including the PolyQ disease SCA2 and the mitochondrial disease Barth syndrome.

Inhibition of seizures can come from expected – and surprising – sources. In this talk I will explore circuit elements, both within and external to the temporal lobe, which may be able inhibit hippocampal seizures, and how specific aspects of intervention strategies can be critical for outcomes. We’ll discuss novel sources of inhibition within the hippocampus, the cerebellum as a potential target, and closed-loop optimization of stimulation parameters

Habitual consumption of a “Western diet”, containing higher than recommended levels of simple sugars and saturated fatty acids, is associated with cognitive impairments in humans and in various experimental animal models. Emerging findings reveal that the specific mnemonic processes that are disrupted by Western diet consumption are those that rely on the hippocampus, a brain region classically linked with memory control and more recently with the higher-order control of food intake. Our laboratory has established rat models in which excessive consumption of different components of a Western diet during the juvenile and adolescent periods of development yields long-term impairments in hippocampal-dependent memory function without concomitant increases in total caloric intake, body weight, or adiposity. Our ongoing work is investigating alterations in the gut microbiome as a potential underlying neurobiological mechanism linking early life unhealthy dietary factors to adverse neurocognitive outcomes.

Abuse, neglect, and other forms of uncontrollable stress during childhood and early adolescence can lead to adverse outcomes later in life, including especially perturbations in the regulation of mood and emotional states, and specifically anxiety disorders and depression. However, stress experiences vary from one individual to the next, meaning that causal relationships and mechanistic accounts are often difficult to establish in humans. This interdisciplinary talk considers the value of research in experimental animals where stressor experiences can be tightly controlled and detailed investigations of molecular, cellular, and circuit-level mechanisms can be carried out. The talk will focus on the widely used repeated maternal separation procedure in rats where rat offspring are repeatedly separated from maternal care during early postnatal life. This early life stress has remarkably persistent effects on behaviour with a general recognition that maternally-deprived animals are susceptible to depressive-like phenotypes. The validity of this conclusion will be critically appraised with convergent insights from a recent longitudinal study in maternally separated rats involving translational brain imaging, transcriptomics, and behavioural assessment.

A key insight from the foraging literature is the importance of assessing the overall environmental quality — via global reward rate or similar measures, which capture the opportunity cost of time and can guide behavioral allocation toward relatively richer options. Meanwhile, the majority of research in decision neuroscience and computational psychiatry has focused instead on how choices are guided by much more local, event-locked evaluations: of individual situations, actions, or outcomes. I review a combination of research and theoretical speculation from my lab and others that emphasizes the role of foraging's average rewards and opportunity costs in a much larger range of decision problems, including risk, time discounting, vigor, cognitive control, and deliberation. The broad range of behaviors affected by this type of evaluation gives a new theoretical perspective on the effects of stress and autonomic mobilization, and on mood and the broad range of symptoms associated with mood disorders.

Analogical reasoning is related to everyday learning and scholastic learning and is a robust predictor of g. Therefore, children's ability to reason by analogy is often measured in a school context to gain insight into children's cognitive and intellectual functioning. Often, the ability to reason by analogy is measured by means of conventional, static instruments. Static tests are criticised by researchers and practitioners to provide an overview of what individuals have learned in the past and for this reason are assumed not to tap into the potential for learning, based on Vygotsky's zone of proximal development. This seminar will focus on children's potential for reasoning by analogy, as measured by means of a dynamic test, which has a test-training-test design. In so doing, the potential relationship between dynamic test outcomes and executive functioning will be explored.

Our everyday behaviours, such as physical activity, sleep, diet, meditation, and social connections, have a potent impact on our mental health and the health of our brain. BrainPark is working to harness this power by developing lifestyle-based interventions for mental health and investigating how they do and don’t change the brain, and for whom they are most effective. In this webinar, Dr Rebecca Segrave and Dr Chao Suo will discuss BrainPark’s approach to developing lifestyle-based interventions to help people get better control of compulsive behaviours, and the multi-modality neuroimaging approaches they take to investigating outcomes. The webinar will explore two current BrainPark trials: 1. Conquering Compulsions - investigating the capacity of physical exercise and meditation to alter reward processing and help people get better control of a wide range of unhelpful habits, from drinking to eating to cleaning. 2. The Brain Exercise Addiction Trial (BEAT) - an NHMRC funded investigation into the capacity of physical exercise to reverse the brain harms caused by long-term heavy cannabis use. Dr Rebecca Segrave is Deputy Director and Head of Interventions Research at BrainPark, the David Winston Turner Senior Research Fellow within the Turner Institute for Brain and Mental Health, and an AHRPA registered Clinical Neuropsychologist. Dr Chao Suo is Head of Technology and Neuroimaging at BrainPark and a Research Fellow within the Turner Institute for Brain and Mental Health.

Executive functions refer to a collection of mental processes such as attention, planning and problem solving, supported by a frontoparietal distributed brain network. These functions are essential for everyday life. Specifically in the context of patients with brain tumours there is a need to preserve them in order to enable good quality of life for patients. During surgeries for the removal of a brain tumour, the aim is to remove as much as possible of the tumour and at the same time prevent damage to the areas around it to preserve function and enable good quality of life for patients. In many cases, functional mapping is conducted during an awake surgery in order to identify areas critical for certain functions and avoid their surgical resection. While mapping is routinely done for functions such as movement and language, mapping executive functions is more challenging. Despite growing recognition in the importance of these functions for patient well-being in recent years, only a handful of studies addressed their intraoperative mapping. In the talk, I will present our new approach for mapping executive function areas using electrocorticography during awake brain surgery. These results will be complemented by neuroimaging data from healthy volunteers, directed at reliably localizing executive function regions in individuals using fMRI. I will also discuss more broadly challenges ofß using neuroimaging for neurosurgical applications. We aim to advance cross-modality neuroimaging of cognitive function which is pivotal to patient-tailored surgical interventions, and will ultimately lead to improved clinical outcomes.

Research evidence indicates that psychosocial stressors such as work-life stress serves as a negative occupational exposure relating to poor health behaviors including smoking, poor food choices, low levels of exercise, and even decreased sleep time, as well as a number of chronic health outcomes. The association between work-life stress and adverse health behaviors and chronic health suggests that Occupational Health Psychology (OHP) interventions such as leadership support trainings may be helpful in mitigating effects of work-life stress and improving health, consistent with the Total Worker Health approach. This presentation will review workplace psychosocial stressors and leadership training approaches to reduces stress and improve health, highlighting a randomized controlled trial, the Military Employee Sleep and Health study.

Precise synaptic connectivity is a prerequisite for the function of neural circuits, yet individual neurons, taken out of their developmental context, readily form unspecific synapses. How does genetically encoded brain wiring deal with this apparent contradiction? Brain wiring is a developmental growth process that is not only characterized by precision, but also flexibility and robustness. As in any other growth process, cellular interactions are restricted in space and time. Correspondingly, molecular and cellular interactions are restricted to those that 'get to see' each other during development. This seminar will explore the question how neurons decide when and where to make synapses using the Drosophila visual system as a model. New findings reveal that pattern formation during growth and the kinetics of live neuronal interactions restrict synapse formation and partner choice for neurons that are not otherwise prevented from making incorrect synapses in this system. For example, cell biological mechanisms like autophagy as well as developmental temperature restrict inappropriate partner choice through a process of kinetic exclusion that critically contributes to wiring specificity. The seminar will explore these and other neuronal strategies when and where to make synapses during developmental growth that contribute to precise, flexible and robust outcomes in brain wiring.

Nearly all motivated behaviors require the ability to associate outcomes with specific actions and make adaptive decisions about future behavior. The nucleus accumbens (NAc) is integrally involved in these processes. The NAc is a heterogeneous population primarily composed of D1 and D2 medium spiny projection (MSN) neurons that are thought to have opposed roles in behavior, with D1 MSNs promoting reward and D2 MSNs promoting aversion. Here we examined what types of information are encoded by the D1 and D2 MSNs using optogenetics, fiber photometry, and cellular resolution calcium imaging. First, we showed that mice responded for optical self-stimulation of both cell types, suggesting D2-MSN activation is not inherently aversive. Next, we recorded population and single cell activity patterns of D1 and D2 MSNs during reinforcement as well as Pavlovian learning paradigms that allow dissociation of stimulus value, outcome, cue learning, and action. We demonstrated that D1 MSNs respond to the presence and intensity of unconditioned stimuli – regardless of value. Conversely, D2 MSNs responded to the prediction of these outcomes during specific cues. Overall, these results provide foundational evidence for the discrete aspects of information that are encoded within the NAc D1 and D2 MSN populations. These results will significantly enhance our understanding of the involvement of the NAc MSNs in learning and memory as well as how these neurons contribute to the development and maintenance of substance use disorders.

Humans and other animals make decisions in order to satisfy their goals. However, it remains unknown how neural circuits compute which of multiple possible goals should be pursued (e.g., when balancing hunger and thirst) and how to combine these signals with estimates of available reward alternatives. Here, humans undergoing fMRI accumulated two distinct assets over a sequence of trials. Financial outcomes depended on the minimum cumulate of either asset, creating a need to maintain “value equilibrium” by redressing any imbalance among the assets. Blood-oxygen-level-dependent (BOLD) signals in the rostral anterior cingulate cortex (rACC) tracked the level of imbalance among goals, whereas the ventromedial prefrontal cortex (vmPFC) signaled the level of redress incurred by a choice rather than the overall amount received. These results suggest that a network of medial frontal brain regions compute a value signal that maintains value equilibrium among internal goals.

Over the last few decades, the use of deep brain stimulation (DBS) to improve the treatment of those with neurological movement disorders represents a critical success story in the development of invasive neurotechnology and the promise of brain-computer interfaces (BCI) to improve the lives of those suffering from incurable neurological disorders. In the last decade, investigational devices capable of recording and streaming neural activity from chronically implanted therapeutic electrodes has supercharged research into clinical applications of BCI, enabling in-human studies investigating the use of adaptive stimulation algorithms to further enhance therapeutic outcomes and improve future device performance. In this talk, Dr. Herron will review ongoing clinical research efforts in the field of adaptive DBS systems and algorithms. This will include an overview of DBS in current clinical practice, the development of bidirectional clinical-use research platforms, ongoing algorithm evaluation efforts, a discussion of current adoption barriers to be addressed in future work.

Despite the challenges COVID-19 has continued to present, Monash Biomedical Imaging (MBI) has had another outstanding year in terms of publications and scientific output. In this webinar, Professor Gary Egan, Director of MBI, will present an overview of MBI’s achievements during 2021 and outline the biomedical imaging research programs and partnerships in 2022. His presentation will cover: • MBI operational and research achievements during 2021 • Biomedical imaging technology developments and research outcomes during 2021 • Linked laboratories and research teams at MBI • Progress on the development of a cyclotron and precision radiopharmaceutical facility at Clayton • Emerging research opportunities at the Monash Heart Hospital in cardiology and cardiovascular disease. 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. His substantive body of published work has made a significant impact on the neuroimaging and neuroscience fields. He has sustained success in obtaining significant grants to support his own research and the development of facilities to advance biomedical imaging.

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.

When making decision under risk, people often exhibit behaviours that classical economic theories cannot explain. Newer models that attempt to account for these ‘irrational’ behaviours often lack neuroscience bases and require the introduction of subjective and problem-specific constructs. Here, we present a decision-making model inspired by the prediction error signals and introspective neuronal replay reported in the brain. In the model, decisions are chosen based on ‘anticipated surprise’, defined by a nonlinear average of the differences between individual outcomes and a reference point. The reference point is determined by the expected value of the possible outcomes, which can dynamically change during the mental simulation of decision-making problems involving sequential stages. Our model elucidates the contribution of each stage to the appeal of available options in a decision-making problem. This allows us to explain several economic paradoxes and gambling behaviours. Our work could help bridge the gap between decision-making theories in economics and neurosciences.

Atherosclerosis is the underlying cause of major cardiovascular events, including heart attack and stroke. The build-up of plaque in coronary arteries can be a major risk for events, but risk is significantly higher in patients with vulnerable rather than stable plaque. Diagnostic imaging of vulnerable plaque is extremely useful for both stratifying patient risk and for determining effectiveness of experimental intervention in reducing cardiovascular risk. In the preclinical setting, being able to distinguish between stable and vulnerable plaque development and pair this with biochemical measures is critical for identification of new experimental candidates. In this webinar, Professor Stephen Nicholls and Dr Kristen Bubb from the Victorian Heart Institute will discuss the benefits of being able to visualise vulnerable plaque for both clinical and preclinical research. Professor Stephen Nicholls is a clinician-researcher and the Head of the Victorian Heart Institute. He is the lead investigator on multiple large, international, cardiovascular outcomes trials. He has attracted over $100 million in direct research funding and published more than 400 peer-reviewed manuscripts. He is focused on both therapeutic intervention to reduce vascular inflammation and lipid accumulation and precision medicine approaches to prevent cardiovascular mortality. Dr Kristen Bubb is a biomedical researcher and Group Leader within the Monash Biomedicine Discovery Institute Cardiovascular Program and Victorian Heart Institute. She focuses on preclinical/translational research into mechanisms underlying vascular pathologies including atherosclerosis and endothelium-driven hypertension within specific vascular systems, including pulmonary and pregnancy-induced. She has published >30 high impact papers in leading cardiovascular journals and attracted category 1&2 funding of >$750,000.

There is an avalanche of new data on activity in neural networks and the biological brain, revealing the collective dynamics of vast numbers of neurons. In principle, these collective dynamics can be of almost arbitrarily high dimension, with many independent degrees of freedom — and this may reflect powerful capacities for general computing or information. In practice, neural datasets reveal a range of outcomes, including collective dynamics of much lower dimension — and this may reflect other desiderata for neural codes. For what networks does each case occur? We begin by exploring bottom-up mechanistic ideas that link tractable statistical properties of network connectivity with the dimension of the activity that they produce. We then cover “top-down” ideas that describe how features of connectivity and dynamics that impact dimension arise as networks learn to perform fundamental computational tasks.

After more than 4 million deaths worldwide, the ongoing vaccination to conquer the COVID-19 disease is now competing with the emergence of increasingly contagious mutations, repeatedly supplanting earlier strains. Following the near-absence of historical examples of the long-time evolution of infectious diseases under similar circumstances, models are crucial to exemplify possible scenarios. Accordingly, in the present work we systematically generalize the popular susceptible-infected-recovered model to account for mutations leading to repeatedly occurring new strains, which we coarse grain based on tools from statistical mechanics to derive a model predicting the most likely outcomes. The model predicts that mutations can induce a super exponential growth of infection numbers at early times, which self-amplify to giant infection waves which are caused by a positive feedback loop between infection numbers and mutations and lead to a simultaneous infection of the majority of the population. At later stages -- if vaccination progresses too slowly -- mutations can interrupt an ongoing decrease of infection numbers and can cause infection revivals which occur as single waves or even as whole wave trains featuring alternative periods of decreasing and increasing infection numbers. Our results might be useful for discussions regarding the importance of a release of vaccine-patents to reduce the risk of mutation-induced infection revivals but also to coordinate the release of measures following a downwards trend of infection numbers.

Natural systems provide both puzzles to unravel and demonstrations of what's possible. The natural world is full of complex systems of dynamically interchangeable, individually unreliable components that produce effective and reliable outcomes at the group level. A complementary goal to understanding the operation of such systems is that of being able to engineer artifacts that work in a similar way. One notable type of collective behavior is collective construction, epitomized by mound-building termites, which build towering, intricate mounds through the joint activity of millions of independent and limited insects. The artificial counterpart would be swarms of robots designed to build human-relevant structures. I will discuss work on both aspects of the problem, including studies of cues that individual termite workers use to help direct their actions and coordinate colony activity, and development of robot systems that build user-specified structures despite limited information and unpredictable variability in the process. These examples illustrate principles used by the insects and show how they can be applied in systems we create.

Spatial neglect is a syndrome that is most frequently associated with damage to the right hemisphere, although damage to the left hemisphere can also result in signs of spatial neglect. It is characterised by absent or deficient awareness of the contralesional side of space. The screening and diagnosis of spatial neglect lacks a universal gold standard, but is usually achieved by using various modes of assessment. Spatial neglect is also difficult to treat, although prism adaptation training (PAT) has in the past reportedly showed some promise. This seminar will include highlights from a series of studies designed to identify knowledge gaps, and will suggest ways in which these can be bridged. The first study was conducted to identify and quantify clinicians’ use of assessment tools for spatial neglect, finding that several different tools are in use, but that there is an emerging consensus and appetite for harmonisation. The second study included PAT, and sought to uncover whether PAT can improve engagement in recommended therapy in order to improve the outcomes of stroke survivors with spatial neglect. The final study, a systematic review and meta-analysis, sought to investigate the scientific efficacy (rather than clinical effectiveness) of PAT, identifying several knowledge gaps in the existing literature and a need for a new approach in the study of PAT in the clinical setting.

Sensory stimuli are often predictable consequences of one’s actions, and behavior exerts a correspondingly strong influence over sensory responses in the brain. Closed-loop experiments with the ability to control the sensory outcomes of specific animal behaviors have revealed that neural responses to self-generated sounds are suppressed in the auditory cortex, suggesting a role for prediction in local sensory processing. However, it is unclear whether this phenomenon derives from a precise movement-based prediction or how it affects the neural representation of incoming stimuli. We address these questions by designing a behavioral paradigm where mice learn to expect the predictable acoustic consequences of a simple forelimb movement. Neuronal recordings from auditory cortex revealed suppression of neural responses that was strongest for the expected tone and specific to the time of the sound-associated movement. Predictive suppression in the auditory cortex was layer-specific, preceded by the arrival of movement information, and unaffected by behavioral relevance or reward association. These findings illustrate that expectation, learned through motor-sensory experience, drives layer-specific predictive processing in the mouse auditory cortex.

COVID-19 non-pharmaceutical intervention (NPI) policies have been one of the most important and contentious decisions of our time. Beyond even the "normal" inherent difficulties in impact evaluation with observational data, COVID-19 NPI policy evaluation is complicated by additional challenges related to infectious disease dynamics and lags, lack of direct observation of key outcomes, and a multiplicity of interventions occurring on an accelerated time scale. Randomized controlled trials also suffer from what is feasible and ethical to randomize as well as the sheer scale, scope, time, and resources required for an NPI trial to be informative (or at least not misinformative). In this talk, Dr. Haber will discuss the challenges in generating useful evidence for COVID-19 NPIs, the landscape of the literature, and highlight key controversies in several high profile studies over the course of the pandemic. Chasing after unknowables poses major problems for the metascience/replicability movement, institutional research science, and decision makers. If the only choices for informing an important topic are "weak study design" vs "do nothing," when is "do nothing" the best choice?

Our research investigates how processes of attention, visual working memory (VWM), and decision-making combine to translate perception into action. Within this framework, the role of VWM is to form stable representations of transient stimulus events that allow them to be identified by a decision process, which we model as a diffusion process. In psychophysical tasks, we find the capacity of VWM is well defined by a sample-size model, which attributes changes in VWM precision with set-size to differences in the number evidence samples recruited to represent stimuli. In the first part of the talk, I review evidence for the sample-size model and highlight the model's strengths: It provides a parameter-free characterization of the set-size effect; it has plausible neural and cognitive interpretations; an attention-weighted version of the model accounts for the power-law of VWM, and it accounts for the selective updating of VWM in multiple-look experiments. In the second part of the talk, I provide a characterization of the theoretical relationship between two-choice and continuous-outcome decision tasks using the circular diffusion model, highlighting their common features. I describe recent work characterizing the joint distributions of decision outcomes and response times in continuous-outcome tasks using the circular diffusion model and show that the model can clearly distinguish variable-precision and simple mixture models of the evidence entering the decision process. The ability to distinguish these kinds of processes is central to current VWM studies.

While traumatic brain injury (TBI) acutely disrupts the cortex, most TBI-related disabilities reflect secondary injuries that accrue over time. The thalamus is a likely site of secondary damage because of its reciprocal connections with the cortex. Using a mouse model of mild cortical injury that does not directly damage subcortical structures (mTBI), we found a chronic increase in C1q expression specifically in the corticothalamic circuit. Increased C1q expression co-localized with neuron loss and chronic inflammation, and correlated with disruption in sleep spindles and emergence of epileptic activities. Blocking C1q counteracted these outcomes, suggesting that C1q is a disease modifier in mTBI. Single-nucleus RNA sequencing demonstrated that microglia are the source of thalamic C1q. Since the corticothalamic circuit is important for cognition and sleep, which can be impaired by TBI, this circuit could be a new target for treating TBI-related disabilities

In highly volatile environments, performing actions that address current needs and desires is an ongoing challenge for living organisms. For example, the predictive value of environmental signals needs to be updated when predicted and actual outcomes differ. Furthermore, organisms also need to gain control over the environment through actions that are expected to produce specific outcomes. The data to be presented will show that these processes are highly reliant on thalamocortical circuits wherein thalamic nuclei make a critical contribution to adaptive decision-making, challenging the view that the thalamus only acts as a relay station for the cortical stage. Over the past few years, our work has highlighted the specific contribution of multiple thalamic nuclei in the ability to update the predictive link between events or the causal link between actions and their outcomes via the combination of targeted thalamic interventions (lesion, chemogenetics, disconnections) with behavioral procedures rooted in experimental psychology. We argue that several features of thalamocortical architecture are consistent with a prominent role for thalamic nuclei in shaping mental representations.

Uncertainty regarding which psychological mechanisms are fundamental in mediating SSRI treatment outcomes and wide-ranging variability in their efficacy has raised more questions than it has solved. Since subjective mood states are an abstract scientific construct, only available through self-report in humans, and likely involving input from multiple top-down and bottom-up signals, it has been difficult to model at what level SSRIs interact with this process. Converging translational evidence indicates a role for serotonin in modulating context-dependent parameters of action selection, affect, and social cognition; and concurrently supporting learning mechanisms, which promote adaptability and behavioural flexibility. We examine the theoretical basis, ecological validity, and interaction of these constructs and how they may or may not exert a clinical benefit. Specifically, we bridge crucial gaps between disparate lines of research, particularly findings from animal models and human clinical trials, which often seem to present irreconcilable differences. In determining how SSRIs exert their effects, our approach examines the endogenous functions of 5-HT neurons, how 5-HT manipulations affect behaviour in different contexts, and how their therapeutic effects may be exerted in humans – which may illuminate issues of translational models, hierarchical mechanisms, idiographic variables, and social cognition.

Though studies show that abuse, neglect or trauma during childhood can lead to lifelong lifelong struggles including in mental health, research also indicates that solutions and interventions at various stages of life can be developed to help. And while many people manage to remain resilient, a lack of opportunity early in life, including because of poverty and systemic racism, can constrain their ability to realize their full potential. In what ways are health and other outcomes affected? How can systems instead restore opportunity? "The Picower Institute for Learning and Memory's biennial spring symposium, 'Early Life Stress & Mental Health,' will examine these issues. The daylong event will feature talks by neuroscientists, policy experts, physicians, educators and activists as they discuss how our experiences and biology work together to affect how our minds develop and what can be accomplished in helping people overcome early disadvantages.

Core body temperature is regulated to a setpoint between 36.1 to 37.8°C, with an average fluctuation of 0.5°C during a 24-hour day. Despite mechanistic safeguards, major temperature deviations (1-3°C) from the setpoint occur in the body and in turn the brain. For unknown reasons, in most mammals (humans included), these increases in brain temperature are benign. However, macro-fluctuations in brain temperature in some cases result in deleterious outcomes such as seizures. In this talk, I will describe a mechanism for circuit-level adaptive regulation of cortical activity during macro-fluctuations in brain temperature. I will also discuss how this mechanism can be applied towards the understanding of the pathology of Autism Spectrum Disorder.

On April 22, 2021, Dr. Alan J Thompson of the University College London and the UCL Institute of Neurology, London, UK will deliver the Hughlings Jackson Lecture entitled, “Making Progress in Progressive MS – the Ultimate Challenge!” Established in 1935, the Hughlings Jackson Lecture is The Neuro’s premier scientific lecture. It honors the legacy of British neurologist John Hughlings Jackson (1835-1911) who pioneered the development of neurology as a medical specialty. Talk Abstract : The international focus on progressive MS, driven by the Progressive MS Alliance amongst others, together with recent encouraging results from clinical trials have raised the profile and emphasised the importance of understanding, treating and ultimately preventing progression in MS. Effective treatment for Progressive MS is now regarded as the single most important issue facing the MS community. There are several important challenges to developing new treatments for progressive MS. Fundamental to any development in treatment is a better understanding of the mechanisms of tissue injury underpinning progression which will in turn allow the identification of new targets against which treatments can be directed. There are additional complications in determining when progression actually starts, determining the impact of aging and defining the progressive clinical phenotypes – an area which has become increasingly complex in recent months. Evaluating potential new treatments in progressive MS also poses particular challenges including trial design and the selection of appropriate clinical and imaging outcomes - in particular, identifying an imaging biomarker for phase II trials of progressive MS. Despite these challenges, considerable progress is being made in developing new treatments targeting the innate immune system and exploring neuroprotective strategies. Further advances are being driven by a number of international networks, funded by the Progressive MS Alliance. Overall we are seeing encouraging progress as a result of co-ordinated global collaboration which offers real possibilities for truly effective treatment of progression.

Black Americans experience diverse racism-related stressors throughout the lifespan. Disproportionately high trauma exposure, economic disadvantage, explicit racism and inequitable treatment are stressors faced by many Black Americans. These experiences have a cumulative negative impact on psychological and physical health. However, little is understood about how experiences of racism, such as discrimination, can mediate health outcomes via their effects on neurobiology. I will present clinical, behavioral, physiological and neurobiological data from Black American participants in the Grady Trauma Project, a longstanding study of trauma conducted in inner-city Atlanta. These data will be discussed in the context of both risk and resilience/adaptation perspectives. Finally, recommendations for future clinical neuroscience research and targets for intervention in marginalized populations will be discussed.

Constipation is a common but not a universal feature in early PD, suggesting that gut involvement is heterogeneous and may be part of a distinct PD subtype with prognostic implications. We analysed data from the Parkinson’s Incidence Cohorts Collaboration, composed of incident community-based cohorts of PD patients assessed longitudinally over 8 years. Constipation was assessed with the MDS-UPDRS constipation item or a comparable categorical scale. Primary PD outcomes of interest were dementia, postural instability and death. PD patients were stratified according to constipation severity at diagnosis: none (n=313, 67.3%), minor (n=97, 20.9%) and major (n=55, 11.8%). Clinical progression to all 3 outcomes was more rapid in those with more severe constipation at baseline (Kaplan Meier survival analysis). Cox regression analysis, adjusting for relevant confounders, confirmed a significant relationship between constipation severity and progression to dementia, but not postural instability or death. Early constipation may predict an accelerated progression of neurodegenerative pathology. Conclusions: We show widespread cortical and subcortical grey matter micro-structure associations with schizophrenia PRS. Across all investigated phenotypes NDI, a measure of the density of myelinated axons and dendrites, showed the most robust associations with schizophrenia PRS. We interpret these results as indicative of reduced density of myelinated axons and dendritic arborization in large-scale cortico-subcortical networks mediating the genetic risk for schizophrenia.