Seminars

Almost everybody that has seen neurons under a microscope for the first time is fascinated by their beauty and their complex shape. Early on during development, however, there are hardly any signs of their future complexity, but the neurons look round and simple. How do neurons develop their sophisticated structure? How do they initially generate domains that later have distinct function within neuronal circuits, such as the axon? And, can a better understanding of the underlying developmental mechanisms help us in pathological conditions, such as a spinal cord injury, to induce axons to regenerate? Here, I will talk about the cytoskeleton as a driving force for neuronal polarization. We will then explore how cytoskeletal changes help to reactivate the growth program of injured CNS axons to elicit axon regeneration after a spinal cord injury. Finally, we will discuss whether axon growth and synapse formation may be processes in neurons that might exclude each other. Following this developmental hypothesis, it will help us to generate a novel perspective on regeneration failure in the adult CNS, and how we can overcome this failure to induce axon regeneration. Thus, this talk will describe how we can exploit developmental mechanisms to induce axon regeneration after a spinal cord injury.

In the Learning Salon, we will discuss the similarities and differences between biological and machine learning, including individuals with diverse perspectives and backgrounds, so we can all learn from one another.

Our ability to perceive the world around us can be affected by a number of factors including the nature of the external information, prior experience of the environment, and the integrity of the underlying perceptual system. A particular challenge for the brain is to maintain a coherent perception from information encoded by the peripheral sensory organs whose function is affected by typical, developmental changes across the lifespan. Yet, how the brain adapts to the maturation of the senses, as well as experiential changes in the multisensory environment, is poorly understood. Over the past few years, we have used a range of multisensory tasks to investigate the role of ageing on the brain’s ability to merge sensory inputs. In particular, we have embedded an audio-visual task based on the sound-induced flash illusion (SIFI) into a large-scale, longitudinal study of ageing. Our findings support the idea that the temporal binding window (TBW) is modulated by age and reveal important individual differences in this TBW that may have clinical implications. However, our investigations also suggest the TWB is experience-dependent with evidence for both long and short term behavioural plasticity. An overview of these findings, including recent evidence on how multisensory integration may be associated with higher order functions, will be discussed.

This talk will focus on the importance of using natural behaviors in neuroscience research – the “Natural Neuroscience” approach. I will illustrate this point by describing studies of neural codes for spatial behaviors and social behaviors, in flying bats – using wireless neurophysiology methods that we developed – and will highlight new neuronal representations that we discovered in animals navigating through 3D spaces, or in very large-scale environments, or engaged in social interactions. In particular, I will discuss: (1) A multi-scale neural code for very large environments, which we discovered in bats flying in a 200-meter long tunnel. This new type of neural code is fundamentally different from spatial codes reported in small environments – and we show theoretically that it is superior for representing very large spaces. (2) Rapid modulation of position × distance coding in the hippocampus during collision-avoidance behavior between two flying bats. This result provides a dramatic illustration of the extreme dynamism of the neural code. (3) Local-but-not-global order in 3D grid cells – a surprising experimental finding, which can be explained by a simple physics-inspired model, which successfully describes both 3D and 2D grids. These results strongly argue against many of the classical, geometrically-based models of grid cells. (4) I will also briefly describe new results on the social representation of other individuals in the hippocampus, in a highly social multi-animal setting. The lecture will propose that neuroscience experiments – in bats, rodents, monkeys or humans – should be conducted under evermore naturalistic conditions.

During navigation, animals estimate their position using path integration and landmarks, engaging many brain areas. Whether these areas follow specialized or universal cue integration principles remains incompletely understood. We combine electrophysiology with virtual reality to quantify cue integration across thousands of neurons in three navigation-relevant areas: primary visual cortex (V1), retrosplenial cortex (RSC), and medial entorhinal cortex (MEC). Compared with V1 and RSC, path integration influences position estimates more in MEC, and conflicts between path integration and landmarks trigger remapping more readily. Whereas MEC codes position prospectively, V1 codes position retrospectively, and RSC is intermediate between the two. Lowered visual contrast increases the influence of path integration on position estimates only in MEC. These properties are most pronounced in a population of MEC neurons, overlapping with grid cells, tuned to distance run in darkness. These results demonstrate the specialized role that path integration plays in MEC compared with other navigation-relevant cortical areas.

Environmental boundaries anchor cognitive maps that support memory. However, trapezoidal boundary geometry distorts the regular firing patterns of entorhinal grid cells proposedly providing a metric for cognitive maps. Here, we test the impact of trapezoidal boundary geometry on human spatial memory using immersive virtual reality. Consistent with reduced regularity of grid patterns in rodents and a grid-cell model based on the eigenvectors of the successor representation, human positional memory was degraded in a trapezoid compared to a square environment; an effect particularly pronounced in the trapezoid’s narrow part. Congruent with spatial frequency changes of eigenvector grid patterns, distance estimates between remembered positions were persistently biased; revealing distorted memory maps that explained behavior better than the objective maps. Our findings demonstrate that environmental geometry affects human spatial memory similarly to rodent grid cell activity — thus strengthening the putative link between grid cells and behavior along with their cognitive functions beyond navigation.

Dr. Ryan C.N. D’Arcy is a Canadian neuroscientist, researcher, innovator and entrepreneur. Dr. D'Arcy co-founded HealthTech Connex Inc. and serves as President and Chief Scientific Officer. HealthTech Connex translates neuroscience advances into health technology breakthroughs. D'Arcy is most known for coining the term "brain vital signs" and for leading the research and development of the brain vital signs framework. Dr. D’Arcy also holds a BC Leadership Chair in Medical Technology, is a full Professor at Simon Fraser University, and a member of the DM Centre for Brain Health at the University of British Columbia. He has published more than 260 academic works, attracted more than $85 Million CAD in competitive research and innovation funding, and been recognized through numerous awards and distinctions. Please join us for an exciting virtual talk with Dr. D'Arcy who will speak on some of the current research he is involved in, how he is translating this research into real-life applications, and the development of HealthTech Connects Inc.

How the brain represents the body is a fundamental question in cognitive neuroscience. Experimental studies are difficult because ‘the body is always there’ (William James). In recent years immersive virtual reality techniques have been introduced that deliver apparent changes to the body extending earlier techniques such as the rubber hand illusion, or substituting the whole body by a virtual one visually collocated with the real body, and seen from a normal first person perspective. This talk will introduce these techniques, and concentrate on how changing the body can change the mind and behaviour, especially in the context of combatting aggression based on gender or race.

Learning entails self-modification of a system under closed-loop dynamics with its environment. Not only the system's components may change, but also the way they interact with one another - like synapses during learning in the brain, that modify interactions between neurons. Such processes, however, are not limited to the brain but can be found also in other areas of biology. I will describe a framework for a primitive form of learning that takes place within the single cell. This type of learning is composed of random modifications guided by global feedback. The capacity to utilize exploratory dynamics, improvisational in nature, provide cells with the plasticity required to overcome extreme challenges and to develop novel phenotypes.

Nearly every aspect of life involves decisions between options that differ in both their expected rewards and the potential costs (such as delay to reward delivery or risk of harm) that accompany those rewards. The ability to choose adaptively when faced with such decisions is critical for well-being and overall quality of life. In neuropsychiatric conditions such as substance use disorders, however, decision making is often compromised, which can prolong and exacerbate their severity and co-morbidities. In this seminar, Dr. Setlow will discuss research in rodent models investigating behavioral and biological mechanisms of cost-benefit decision making. In particular, he will focus on factors (including sex) that contribute to differences in cost-benefit decision making across the population, how variability in decision making is related to substance use, and how substance use can produce long-lasting changes in decision preference.

Neurons in the suprachiasmatic nucleus (SCN, the brain’s master circadian clock) display a 24 hour cycle in the their rate of action potential discharge whereby firing rates are high during the light phase and lower during the dark phase. Although it is generally agreed that this cycle of activity is a key mediator of the clock’s neural and humoral output, surprisingly little is known about how changes in clock electrical activity can mediate scheduled physiological changes at different times of day. Using opto- and chemogenetic approaches in mice we have shown that the onset of electrical activity in vasopressin releasing SCN neurons near Zeitgeber time 22 (ZT22) activates glutamatergic thirst-promoting neurons in the OVLT (organum vasculosum lamina terminalis) to promote water intake prior to sleep. This effect is mediated by activity-dependent release of vasopressin from the axon terminals of SCN neurons which acts as a neurotransmitter on OVLT neurons. More recently we found that the clock receives excitatory input from a different subset of sodium sensing neurons in the OVLT. Activation of these neurons by a systemic salt load delivered at ZT19 stimulated the electrical activity of SCN neurons which are normally silent at this time. Remarkably, this effect induced an acute reduction in non-shivering thermogenesis and body temperature, which is an adaptive response to the salt load. These findings provide information regarding the mechanisms by which the SCN promotes scheduled physiological rhythms and indicates that the clock’s output circuitry can also be recruited to mediate an unscheduled homeostatic response.

The dream of a systems neuroscientist is to be able to unravel neural mechanisms that give rise to behavior. It is increasingly appreciated that behavior involves the concerted distributed activity of multiple brain regions so the focus on single or few brain areas might hinder our understanding. There have been quite a few technological advancements in this domain. Functional ultrasound imaging (fUSi) is an emerging technique that allows us to measure neural activity from medial frontal regions down to subcortical structures up to a depth of 20 mm. It is a method for imaging transient changes in cerebral blood volume (CBV), which are proportional to neural activity changes. It has excellent spatial resolution (~100 μm X 100 μm X 400 μm); its temporal resolution can go down to 100 milliseconds. In this talk, I will present its use in two model systems: marmoset monkeys and rats. In marmoset monkeys, we used it to delineate a social – vocal network involved in vocal communication while in rats, we used it to gain insights into brain wide networks involved in evidence accumulation based decision making. fUSi has the potential to provide an unprecedented access to brain wide dynamics in freely moving animals performing complex behavioral tasks.

An intriguing, relatively unexplored therapeutic avenue to investigate epilepsy is the interaction of sleep mechanisms and seizures. Multiple lines of clinical observations suggest a strong, bi-directional relationship between epilepsy and sleep. Epilepsy and sleep disorders are common comorbidities. Seizures occur more commonly in sleep in many types of epilepsy, and in turn, seizures can cause disrupted sleep. Sudden unexplained death in epilepsy (SUDEP) is strongly associated with sleep. The biological mechanisms underlying this relationship between seizures and sleep are poorly understood, but if better delineated, could offer novel therapeutic approaches to treating both epilepsy and sleep disorders. In this presentation, I will explore this sleep-seizure relationship in mouse models of epilepsy. First, I will present general approaches for performing detailed longitudinal sleep and vigilance state analysis in mice, including pre-weanling neonatal mice. I will then discuss recent data from my laboratory demonstrating an abnormal sleep phenotype in a mouse model of the genetic epilepsy, tuberous sclerosis complex (TSC), and its relationship to seizures. The potential mechanistic basis of sleep abnormalities and sleep-seizure interactions in this TSC model will be investigated, focusing on the role of the mechanistic target of rapamycin (mTOR) pathway and hypothalamic orexin, with potential therapeutic applications of mTOR inhibitors and orexin antagonists. Finally, similar sleep-seizure interactions and mechanisms will be extended to models of acquired epilepsy due to status epilepticus-related brain injury.

I will present my recent work on mathematical modeling of human memory. I will argue that memory recall of random lists of items is governed by the universal algorithm resulting in the analytical relation between the number of items in memory and the number of items that can be successfully recalled. The retention of items in memory on the other hand is not universal and differs for different types of items being remembered, in particular retention curves for words and sketches is different even when sketches are made to only carry information about an object being drawn. I will discuss the putative reasons for these observations and introduce the phenomenological model predicting retention curves.