Seminars

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.

The internal and external world is thought to be represented by distributed patterns of cortical activity. The emergence of these cortical representations over the course of development remains an unresolved question. In this talk, I share results from a series of recent studies combining theory and experiments in the cortex of the ferret, a species with a well-defined columnar organization and modular network of orientation-selective responses in visual cortex. I show that prior to the onset of structured sensory experience, endogenous mechanisms set up a highly organized cortical network structure that is evident in modular patterns of spontaneous activity characterized by strong, clustered local and long-range correlations. This correlation structure is remarkably consistent across both sensory and association areas in the early neocortex, suggesting that diverse cortical representations initially develop according to similar principles. Next, I explore a classical candidate mechanism for producing modular activity – local excitation and lateral inhibition. I present the first empirical test of this mechanism through direct optogenetic cortical activation and discuss a plausible circuit implementation. Then, focusing on the visual cortex, I demonstrate that these endogenously structured networks enable orientation-selective responses immediately after eye opening. However, these initial responses are highly variable, lacking the reliability and low-dimensional structure observed in the mature cortex. Reliable responses are achieved after an experience-dependent co-reorganization of stimulus- evoked and spontaneous activity following eye opening. Based on these observations, I propose the hypothesis that the alignment between feedforward inputs and the recurrent network plays a crucial role in transforming the initially variable responses into mature and reliable representations. Presented in the van Vreeswijk Theoretical Neuroscience Seminar series (formerly WWTNS) on 2023-11-22. Recording duration: 00:56:31.

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.

To generate brain circuits that are both flexible and stable requires the coordination of powerful developmental mechanisms acting at different scales, including activity-dependent synaptic plasticity and changes in single neuron properties. The brain prepares to efficiently compute information and reliably generate behavior during early development without any prior sensory experience but through patterned spontaneous activity. After the onset of sensory experience, ongoing activity continues to modify sensory circuits, and plays an important functional role in the mature brain. Using quantitative data analysis, experiment-driven theory and computational modeling, I will present a framework for how neural circuits are built and organized during early postnatal development into functional units, and how they are modified by intact and perturbed sensory-evoked activity. Inspired by experimental data from sensory cortex, I will then show how neural circuits use the resulting non-random connectivity to flexibly gate a network’s response, providing a mechanism for routing information.

Leonard Maler will focus on a specialized caudal portion of the cerebellum of teleost fish whose structure and physiology has been especially well studies to the point that we now have detailed computational analyses of its function. Idoia Quintana-Urzainqui will talk about what sharks can tell us about the evolution of the telencephalon, mainly focusing on the evolutionary expansion of the pallium and how shark embryos can hold key information to interpret the origin of the developmental processes that triggered this phenomenon.

In our everyday lives, we form connections and build up social networks that allow us to function successfully as individuals and as a society. Our social networks tend to include well-connected individuals who link us to other groups of people that we might otherwise have limited access to. In addition, we are more likely to befriend individuals who a) live nearby and b) have mutual friends. Interestingly, neurons tend to do the same…until development is perturbed. Just like social networks, neuronal networks require highly connected hubs to elicit efficient communication at minimal cost (you can’t befriend everybody you meet, nor can every neuron wire with every other!). This talk will cover some of Alex’s work showing that microscopic (cellular scale) brain networks inferred from spontaneous activity show similar complex topology to that previously described in macroscopic human brain scans. The talk will also discuss what happens when neurodevelopment is disrupted in the case of a monogenic disorder called Rett Syndrome. This will include simulations of neuronal activity and the effects of manipulation of model parameters as well as what happens when we manipulate real developing networks using optogenetics. If functional development can be restored in atypical networks, this may have implications for treatment of neurodevelopmental disorders like Rett Syndrome.

Macroscopic brain organisation emerges early in life, even prenatally, and continues to develop through adolescence and into early adulthood. The emergence and continual refinement of large-scale brain networks, connecting neuronal populations across anatomical distance, allows for increasing functional integration and specialisation. This process is thought crucial for the emergence of complex cognitive processes. But how and why is this process so diverse? We used structural neuroimaging collected from a large diverse cohort, to explore how different features of macroscopic brain organisation are associated with diverse cognitive trajectories. We used diffusion-weighted imaging (DWI) to construct whole-brain white-matter connectomes. A simulated attack on each child's connectome revealed that some brain networks were strongly organized around highly connected 'hubs'. The more children's brains were critically dependent on hubs, the better their cognitive skills. Conversely, having poorly integrated hubs was a very strong risk factor for cognitive and learning difficulties across the sample. We subsequently developed a computational framework, using generative network modelling (GNM), to model the emergence of this kind of connectome organisation. Relatively subtle changes within the wiring rules of this computational framework give rise to differential developmental trajectories, because of small biases in the preferential wiring properties of different nodes within the network. Finally, we were able to use this GNM to implicate the molecular and cellular processes that govern these different growth patterns.

The human brain network architecture can reveal crucial aspects of brain function and dysfunction. The topology of this network (known as the connectome) is shaped by a trade-off between wiring cost and network efficiency, and it has highly connected hub regions playing a prominent role in many brain disorders. By studying a landscape of plausible brain networks that preserve the wiring cost, fragile and resilient hubs can be identified. In this webinar, Dr Leonardo Gollo and Dr James Pang from Monash University will discuss this approach across the lifespan and some of its implications for neurodevelopmental and neurodegenerative diseases. Dr Leonardo Gollo is a Senior Research Fellow at the Turner Institute for Brain and Mental Health, School of Psychological Sciences, Monash University. He holds an ARC Future Fellowship and his research interests include brain modelling, systems neuroscience, and connectomics. Dr James Pang is a Research Fellow at the Turner Institute for Brain and Mental Health, School of Psychological Sciences, Monash University. His research interests are on combining neuroimaging and biophysical modelling to better understand the mechanisms of brain function in health and disease.

The emergence of large-scale brain networks, and their continual refinement, represent crucial developmental processes that can drive individual differences in cognition and which are associated with multiple neurodevelopmental conditions. But how does this organization arise, and what mechanisms govern the diversity of these developmental processes? There are many existing descriptive theories, but to date none are computationally formalized. We provide a mathematical framework that specifies the growth of a brain network over developmental time. Within this framework macroscopic brain organization, complete with spatial embedding of its organization, is an emergent property of a generative wiring equation that optimizes its connectivity by renegotiating its biological costs and topological values continuously over development. The rules that govern these iterative wiring properties are controlled by a set of tightly framed parameters, with subtle differences in these parameters steering network growth towards different neurodiverse outcomes. Regional expression of genes associated with the developmental simulations converge on biological processes and cellular components predominantly involved in synaptic signaling, neuronal projection, catabolic intracellular processes and protein transport. Together, this provides a unifying computational framework for conceptualizing the mechanisms and diversity of childhood brain development, capable of integrating different levels of analysis – from genes to cognition. (Pre-print: https://www.biorxiv.org/content/10.1101/2020.08.13.249391v1)

Synaptic inputs on cortical dendrites are organized with remarkable subcellular precision at the micron level. This organization emerges during early postnatal development through patterned spontaneous activity and manifests both locally where synapses with similar functional properties are clustered, and globally along the axis from dendrite to soma. Recent experiments reveal species-specific differences in the local and global synaptic organization in mouse, ferret and macaque visual cortex. I will present a computational framework that implements functional and structural plasticity from spontaneous activity patterns to generate these different types of organization across species and scales. Within this framework, a single anatomical factor - the size of the visual cortex and the resulting magnification of visual space - can explain the observed differences. This allows us to make predictions about the organization of synapses also in other species and indicates that the proximal-distal axis of a dendrite might be central in endowing a neuron with powerful computational capabilities.

Unlike even the most sophisticated current forms of artificial intelligence, developing biological organisms must build their neural hardware from scratch. Furthermore they must start to evade predators and find food before this construction process is complete. I will discuss an interdisciplinary program of mathematical and experimental work which addresses some of the computational principles underlying neural development. This includes (i) how growing axons navigate to their targets by detecting and responding to molecular cues in their environment, (ii) the formation of maps in the visual cortex and how these are influenced by visual experience, and (iii) how patterns of neural activity in the zebrafish brain develop to facilitate precisely targeted hunting behaviour. Together this work contributes to our understanding of both normal neural development and the etiology of neurodevelopmental disorders.

Plasticity shapes the brain during development, and mechanisms of plasticity continue into adulthood to enable learning and memory. Nearly all brain functions are influenced by past events, reinforcing the view that the confluence of plasticity and computation in the same circuit elements is a core component of biological intelligence. My laboratory studies plasticity in the cerebral cortex during development, and plasticity during behaviour that is manifest as cortical dynamics. I will describe how cortical plasticity is implemented by learning rules that involve not only Hebbian changes and synaptic scaling but also dendritic renormalization. By using advanced techniques such as optical measurements of single-synapse function and structure in identified neurons in awake behaving mice, we have recently demonstrated locally coordinated plasticity in dendrites whereby specific synapses are strengthened and adjacent synapses with complementary features are weakened. Together, these changes cooperatively implement functional plasticity in neurons. Such plasticity relies on the dynamics of activity-dependent molecules within and between synapses. Alongside, it is increasingly clear that risk genes associated with neurodevelopmental disorders disproportionately target molecules of plasticity. Deficits in renormalization contribute fundamentally to dysfunctional neuronal circuits and computations, and may be a unifying mechanistic feature of these disorders.