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.

Various clinical cases have provided evidence linking cardiovascular, neurological, and psychiatric disorders to changes in the brain-heart interaction. Our recent experimental evidence on patients with disorders of consciousness revealed that observing brain-heart interactions helps to detect residual consciousness, even in patients with absence of behavioral signs of consciousness. Those findings support hypotheses suggesting that visceral activity is involved in the neurobiology of consciousness and sum to the existing evidence in healthy participants in which the neural responses to heartbeats reveal perceptual and self-consciousness. Furthermore, the presence of non-linear, complex, and bidirectional communication between brain and heartbeat dynamics can provide further insights into the physiological state of the patient following severe brain injury. These developments on methodologies to analyze brain-heart interactions open new avenues for understanding neural functioning at a large-scale level, uncovering that peripheral bodily activity can influence brain homeostatic processes, cognition, and behavior.

On a fast timescale, neurons mostly interact by short, stereotypical electrical impulses or spikes. Why? A common answer is that spikes are useful for long-distance communication, to avoid alterations while traveling along axons. But as it turns out, spikes are seen in many places outside neurons: in the heart, in muscles, in plants and even in protists. From these examples, it appears that action potentials mediate some form of coordinated action, a timed event. From this perspective, spikes should not be seen simply as noisy implementations of underlying continuous signals (a sort of analog-to-digital conversion), but rather as events or actions. I will give a number of examples of functional spike-based interactions in living systems.

Decades of research have investigated the relationship between perception of time and heart rate with often mixed results. In search of such a relationship, I will present my far journey between two projects: from time perception in the realistic VR experience of crowded subway trips in the order of minutes (project 1); to the perceived duration of sub-second white noise tones (project 2). Heart rate had multiple concurrent relationships with subjective temporal distortions for the sub-second tones, while the effects were lacking or weak for the supra-minute subway trips. What does the heart have to do with sub-second time perception? We addressed this question with a cardiac drift-diffusion model, demonstrating the sensory accumulation of temporal evidence as a function of heart rate.

Analogical reasoning –learning about new things by relating it to previous knowledge– lies at the heart of human intelligence and creativity and forms the core of educational practice. Children start creating and using analogies early on, making incredible progress moving from associative processes to successful analogical reasoning. For example, if we ask a four-year-old “Horse belongs to stable like chicken belongs to …?” they may use association and reply “egg”, whereas older children will likely give the intended relational response “chicken coop” (or other term to refer to a chicken’s home). Interestingly, despite state-of-the-art AI-language models having superhuman encyclopedic knowledge and superior memory and computational power, our pilot studies show that these large language models often make mistakes providing associative rather than relational responses to verbal analogies. For example, when we asked four- to eight-year-olds to solve the analogy “body is to feet as tree is to …?” they responded “roots” without hesitation, but large language models tend to provide more associative responses such as “leaves”. In this study we examine the similarities and differences between children's and six large language models' (Dutch/multilingual models: RobBERT, BERT-je, M-BERT, GPT-2, M-GPT, Word2Vec and Fasttext) responses to verbal analogies extracted from an online adaptive learning environment, where >14,000 7-12 year-olds from the Netherlands solved 20 or more items from a database of 900 Dutch language verbal analogies.

Cognitive and emotional processes are shaped by the dynamic integration of brain and body. A major channel of interoceptive information comes from the heart, where phasic signals are conveyed to the brain to indicate how fast and strong the heart is beating. This talk will discuss how interoceptive processes operate across conscious and unconscious levels to influence emotion and memory. The interoceptive channel is disrupted in distinct ways in individuals with autism and anxiety. Selective interoceptive disturbance is related to symptomatology including dissociation and the transdiagnostic expression of anxiety. Interoceptive training can reduce anxiety, with enhanced interoceptive precision associated with greater insula connectivity following targeted interoceptive feedback. The discrete cardiac effects on emotion and cognition have broad relevance to clinical neuroscience, with implications for peripheral treatment targets and behavioural interventions.

If the mind controls the brain, then there is free will and its corollaries, dignity and responsibility. You are king in your skull-sized kingdom and the architect of your destiny. If, on the other hand, the brain controls the mind, an incendiary conclusion follows: There can be no free will, no praise, no punishment and no purgatory. In this webinar, Professor George Paxinos will discuss his highly respected work on the construction of human and experimental animal brain atlases. He has discovered 94 brain regions, 64 homologies and published 58 books. His first book, The Rat Brain in Stereotaxic Coordinates, is the most cited publication in neuroscience and, for three decades, the third most cited book in science. Professor Paxinos will also present his recently published novel, A River Divided, which was 21 years in the making. Neuroscience principles were used in the formation of charters, such as those related to the mind, soul, free will and consciousness. Environmental issues are at the heart of the novel, including the question of whether the brain is the right ‘size’ for survival. Professor Paxinos studied at Berkeley, McGill and Yale and is now Scientia Professor of Medical Sciences at Neuroscience Research Australia and The University of New South Wales in Sydney.

In most animals including in humans, emotions occur together with changes in the body, such as variations in breathing or heart rate, sweaty palms, or facial expressions. It has been suggested that this interoceptive information acts as a feedback signal to the brain, enabling adaptive modulation of emotions that is essential for survival. As such, fear, one of our basic emotions, must be kept in a functional balance to minimize risk-taking while allowing for the pursuit of essential needs. However, the neural mechanisms underlying this adaptive modulation of fear remain poorly understood. In this talk, I want to present and discuss the data from my PhD work where we uncover a crucial role for the interoceptive insular cortex in detecting changes in heart rate to maintain an equilibrium between the extinction and maintenance of fear memories in mice.

The World Health Organization (WHO) estimates that untreated mental disorders accountfor 13% of the total global burden of disease, and by 2030, depression alone will be the leadingcause of disability around the world – outpacing heart disease, cancer, and HIV. This grim pictureis further compounded by the mental health burden delivered by the coronavirus pandemic.The lack of novel treatment options in psychiatry is restricted by a limited understanding in theneuroscience basis of mental disorders, availability of relevant biomarkers, poor predictability inanimal models, and high failure rates in psychiatric drug development. However, theannouncement in 2019 from the Federal Drug Administration (FDA) for approvals of newinterventions for treatment-resistant depression (intranasal esketamine) and postpartumdepression (i.v. brexanolone), demand critical attention. Novel public-private partnerships indrug discovery, new translational data on co-morbid biology, in particular the ascendance ofpsycho-immunology, have highlighted the arrival of a new frontier in biological psychiatryresearch for depressive disorders.

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.

We at Neuromatch 4.0 wish to open up science conferences to everyone and that is why we have included a session for kids and the young at heart. The NMC for kids has three excellent speakers from around the globe to talk about the balance system from bird butts to space: 1. Birds balance with their butts” by Bing Wen Brunton (Associate Prof of Biology at University of Washington, Seattle) 2. “The brain in motion” by Jenifer L. Campos (Associate Prof, University of Toronto) 3. “Getting ready for Mars: what happens to the brain in space?” By Elisa R Ferre (Senior Lecturer, Birkbeck University of London)

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.

The long-term goal of our research is to understand the mechanisms of SUDEP, defined as Sudden, Unexpected, witnessed or unwitnessed, nontraumatic and non-drowning Death in patients with EPilepsy, excluding cases of documented status epilepticus. The majority of SUDEP patients die during sleep. SUDEP is the most devastating consequence of epilepsy, yet little is understood about its causes and no biomarkers exist to identify at risk patients. While SUDEP accounts for 7.5-20% of all epilepsy deaths, SUDEP risk in the genetic epilepsies varies with affected genes. Patients with ion channel gene variants have the highest SUDEP risk. Indirect evidence variably links SUDEP to seizure-induced apnea, pulmonary edema, dysregulation of cerebral circulation, autonomic dysfunction, and cardiac arrhythmias. Arrhythmias may be primary or secondary to hormonal or metabolic changes, or autonomic discharges. When SUDEP is compared to Sudden Cardiac Death secondary to Long QT Syndrome, especially to LQT3 linked to variants in the voltage-gated sodium channel (VGSC) gene SCN5A, there are parallels in the circumstances of death. To gain insight into SUDEP mechanisms, our approach has focused on channelopathies with high SUDEP incidence. One such disorder is Dravet syndrome (DS), a devastating form of developmental and epileptic encephalopathy (DEE) characterized by multiple pharmacoresistant seizure types, intellectual disability, ataxia, and increased mortality. While all patients with epilepsy are at risk for SUDEP, DS patients may have the highest risk, up to 20%, with a mean age at SUDEP of 4.6 years. Over 80% of DS is caused by de novo heterozygous loss-of-function (LOF) variants in SCN1A, encoding the VGSC Nav1.1  subunit, resulting in haploinsufficiency. A smaller cohort of patients with DS or a more severe DEE have inherited, homozygous LOF variants in SCN1B, encoding the VGSC 1/1B non-pore-forming subunits. A related DEE, Early Infantile EE (EIEE) type 13, is linked to de novo heterozygous gain-of-function variants in SCN8A, encoding the VGSC Nav1.6. VGSCs underlie the rising phase and propagation of action potentials in neurons and cardiac myocytes. SCN1A, SCN8A, and SCN1B are expressed in both the heart and brain of humans and mice. Because of this, we proposed that cardiac arrhythmias contribute to the mechanism of SUDEP in DEE. We have taken a novel approach to the development of therapeutics for DS in collaboration with Stoke Therapeutics. We employed Targeted Augmentation of Nuclear Gene Output (TANGO) technology, which modulates naturally occurring, non-productive splicing events to increase target gene and protein expression and ameliorate disease phenotype in a mouse model. We identified antisense oligonucleotides (ASOs) that specifically increase the expression of productive Scn1a transcript in human and mouse cell lines, as well as in mouse brain. We showed that a single intracerebroventricular dose of a lead ASO at postnatal day 2 or 14 reduced the incidence of electrographic seizures and SUDEP in the F1:129S-Scn1a+/- x C57BL/6J mouse model of DS. Increased expression of productive Scn1a transcript and NaV1.1 protein were confirmed in brains of treated mice. Our results suggest that TANGO may provide a unique, gene-specific approach for the treatment of DS.

A brain-machine interface (BMI) is a system that enables users to interact with computers and robots through the voluntary modulation of their brain activity. Such a BMI is particularly relevant as an aid for patients with severe neuromuscular disabilities, although it also opens up new possibilities in human-machine interaction for able-bodied people. Real-time signal processing and decoding of brain signals are certainly at the heart of a BMI. Yet, this does not suffice for subjects to operate a brain-controlled device. In the first part of my talk I will review some of our recent studies, most involving participants with severe motor disabilities, that illustrate additional principles of a reliable BMI that enable users to operate different devices. In particular, I will show how an exclusive focus on machine learning is not necessarily the solution as it may not promote subject learning. This highlights the need for a comprehensive mutual learning methodology that foster learning at the three critical levels of the machine, subject and application. To further illustrate that BMI is more than just decoding, I will discuss how to enhance subject learning and BMI performance through appropriate feedback modalities. Finally, I will show how these principles translate to motor rehabilitation, where in a controlled trial chronic stroke patients achieved a significant functional recovery after the intervention, which was retained 6-12 months after the end of therapy.

Tuberous sclerosis complex (TSC) and focal cortical dysplasia type II (FCDII) are caused by mutations in mTOR pathway genes leading to mTOR hyperactivity, focal malformations of cortical development (fMCD), and seizures in 80-90% of the patients. The current definitive treatments for epilepsy are surgical resection or treatment with everolimus, which inhibits mTOR activity (only approved for TSC). Because both options have severe limitations, there is a major need to better understand the mechanisms leading to seizures to improve life-long epilepsy treatment in TSC and FCDII. To investigate such mechanisms, we recently developed a murine model of fMCD-associated epilepsy that recapitulates the human TSC and FCDII disorders. fMCD are defined by the presence of misplaced, dysmorphic cortical neurons expressing hyperactive mTOR – for simplicity we will refer to these as “mutant” neurons. In our model and in human TSC tissue, we made a surprising finding that mutant neurons express HCN4 channels, which are not normally functionally expressed in cortical neurons, and increased levels of filamin A (FLNA). FLNA is an actin-crossing linking molecule that has also multiple binding partners inside cells. These data led us to ask several important questions: (1) As HCN4 channels are responsible for the pacemaking activity of the heart, can HCN4 channel expression lead to repetitive firing of mutant neurons resulting in seizures? (2) HCN4 is the most cAMP-sensitive of the four HCN isoforms. Does increase in cAMP lead to the firing of mutant neurons? (3) Does increase in FLNA contribute to neuronal alterations and seizures? (4) Is the abnormal HCN4 and FLNA expression in mutant neurons due to mTOR? These questions will be discussed and addressed in the lecture.

Activity patterns of neural populations in natural and artificial neural networks constitute representations of data. The nature of these representations and how they are learned are key questions in neuroscience and deep learning. In his talk, I will describe my group's efforts in building a theory of representations as feature maps leading to sample efficient function approximation. Kernel methods are at the heart of these developments. I will present applications to deep learning and neuronal data.