This webinar convened researchers at the intersection of Artificial Intelligence and Neuroscience to investigate how large language models (LLMs) can serve as valuable “model organisms” for understanding human language processing. Presenters showcased evidence that brain recordings (fMRI, MEG, ECoG) acquired while participants read or listened to unconstrained speech can be predicted by representations extracted from state-of-the-art text- and speech-based LLMs. In particular, text-based LLMs tend to align better with higher-level language regions, capturing more semantic aspects, while speech-based LLMs excel at explaining early auditory cortical responses. However, purely low-level features can drive part of these alignments, complicating interpretations. New methods, including perturbation analyses, highlight which linguistic variables matter for each cortical area and time scale. Further, “brain tuning” of LLMs—fine-tuning on measured neural signals—can improve semantic representations and downstream language tasks. Despite open questions about interpretability and exact neural mechanisms, these results demonstrate that LLMs provide a promising framework for probing the computations underlying human language comprehension and production at multiple spatiotemporal scales.

Cells and microorganisms are motile, yet the stationary nature of conventional microscopes impedes comprehensive, long-term behavioral and biomechanical analysis. The limitations are twofold: a narrow focus permits high-resolution imaging but sacrifices the broader context of organism behavior, while a wider focus compromises microscopic detail. This trade-off is especially problematic when investigating rapidly motile ciliates, which often have to be confined to small volumes between coverslips affecting their natural behavior. To address this challenge, we introduce Trackoscope, an 2-axis autonomous tracking microscope designed to follow swimming organisms ranging from 10μm to 2mm across a 325 square centimeter area for extended durations—ranging from hours to days—at high resolution. Utilizing Trackoscope, we captured a diverse array of behaviors, from the air-water swimming locomotion of Amoeba to bacterial hunting dynamics in Actinosphaerium, walking gait in Tardigrada, and binary fission in motile Blepharisma. Trackoscope is a cost-effective solution well-suited for diverse settings, from high school labs to resource-constrained research environments. Its capability to capture diverse behaviors in larger, more realistic ecosystems extends our understanding of the physics of living systems. The low-cost, open architecture democratizes scientific discovery, offering a dynamic window into the lives of previously inaccessible small aquatic organisms.

Mobile organisms must be capable of deciding both where and when to move in order to keep up with a changing environment; therefore, a strong sense of time is necessary, otherwise, we would fail in many of our movement goals. Despite this intrinsic link between movement and timing, only recently has research begun to investigate the interaction. Two primary effects that have been observed include: movements biasing time estimates (i.e., affecting accuracy) as well as making time estimates more precise. The goal of this presentation is to review this literature, discuss a Bayesian cue combination framework to explain these effects, and discuss the experiments I have conducted to test the framework. The experiments herein include: a motor timing task comparing the effects of movement vs non-movement with and without feedback (Exp. 1A & 1B), a transcranial magnetic stimulation (TMS) study on the role of the supplementary motor area (SMA) in transforming temporal information (Exp. 2), and a perceptual timing task investigating the effect of noisy movement on time perception with both visual and auditory modalities (Exp. 3A & 3B). Together, the results of these studies support the Bayesian cue combination framework, in that: movement improves the precision of time perception not only in perceptual timing tasks but also motor timing tasks (Exp. 1A & 1B), stimulating the SMA appears to disrupt the transformation of temporal information (Exp. 2), and when movement becomes unreliable or noisy there is no longer an improvement in precision of time perception (Exp. 3A & 3B). Although there is support for the proposed framework, more studies (i.e., fMRI, TMS, EEG, etc.) need to be conducted in order to better understand where and how this may be instantiated in the brain; however, this work provides a starting point to better understanding the intrinsic connection between time and movement

Running, swimming, or flying through the world, animals are constantly making decisions while on the move—decisions that allow them to choose where to eat, where to hide, and with whom to associate. Despite this most studies have considered only on the outcome of, and time taken to make, decisions. Motion is, however, crucial in terms of how space is represented by organisms during spatial decision-making. Employing a range of new technologies, including automated tracking, computational reconstruction of sensory information, and immersive ‘holographic’ virtual reality (VR) for animals, experiments with fruit flies, locusts and zebrafish (representing aerial, terrestrial and aquatic locomotion, respectively), I will demonstrate that this time-varying representation results in the emergence of new and fundamental geometric principles that considerably impact decision-making. Specifically, we find that the brain spontaneously reduces multi-choice decisions into a series of abrupt (‘critical’) binary decisions in space-time, a process that repeats until only one option—the one ultimately selected by the individual—remains. Due to the critical nature of these transitions (and the corresponding increase in ‘susceptibility’) even noisy brains are extremely sensitive to very small differences between remaining options (e.g., a very small difference in neuronal activity being in “favor” of one option) near these locations in space-time. This mechanism facilitates highly effective decision-making, and is shown to be robust both to the number of options available, and to context, such as whether options are static (e.g. refuges) or mobile (e.g. other animals). In addition, we find evidence that the same geometric principles of decision-making occur across scales of biological organisation, from neural dynamics to animal collectives, suggesting they are fundamental features of spatiotemporal computation.

Life Perceives is a symposium bringing together scientists and artists for an open exploration of how “perception” can be understood as a phenomenon that does not only belong to humans, or even the so-called “higher organisms”, but exists across the entire spectrum of life in a myriad of forms. The symposium invites leading practitioners from the arts and sciences to present unique insights through short talks, open discussions, and artistic interventions that bring us slightly closer to the life worlds of plants and fungi, microbial communities and immune systems, cuttlefish and crows. What do we mean when we talk about perception in other species? Do other organisms have an experience of the world? Or does our human-centred perspective make understanding other forms of life on their own terms an impossible dream? Whatever your answers to these questions may be, we hope to unsettle them, and leave you more curious than when you arrived.

The emergent dynamics exhibited by collections of living organisms often shows signatures of symmetries that are broken at the single-organism level. At the same time, organism development itself encompasses a well-coordinated sequence of symmetry breaking events that successively transform a single, nearly isotropic cell into an animal with well-defined body axis and various anatomical asymmetries. Combining these key aspects of collective phenomena and embryonic development, we describe here the spontaneous formation of hydrodynamically stabilized active crystals made of hundreds of starfish embryos that gather during early development near fluid surfaces. We describe a minimal hydrodynamic theory that is fully parameterized by experimental measurements of microscopic interactions among embryos. Using this theory, we can quantitatively describe the stability, formation and rotation of crystals and rationalize the emergence of mechanical properties that carry signatures of an odd elastic material. Our work thereby quantitatively connects developmental symmetry breaking events on the single-embryo level with remarkable macroscopic material properties of a novel living chiral crystal system.

Living organisms have mastered the dynamic control of stresses within sheets to induce shape transformation and locomotion. For instance, the spatiotemporal pattern of action potential in a heart yields a dynamical stress field leading to shape changes and biological function. Such structures inspired the development of theoretical tools and responsive materials alike. Yet, present attempts to mimic their rich dynamics and phenomenology in autonomous synthetic matter are still very limited. In this talk, I will present several complementing innovations toward this goal: novel shaping mechanisms that were overlooked by previous research, new fabrication techniques for programmable matter via 4D printing of gel structures, and most prominently, the first autonomous shape morphing membranes. The dynamical control over the geometry of the material is a prevalent theme in all of these achievements. In particular, the latter system demonstrates localized deformations, induced by a pattern-forming chemical reaction, that prescribe the patterns of curvature, leading to global shape evolution. Together, these developments present a route for modeling and producing fully autonomous soft membranes mimicking some of the locomotive capabilities of living organisms.

In this talk I will introduce the central notions of the theory of autonomy, as it is being currently developed in biology and cognitive science. The theory of autonomy puts forward the capacity of self-determination of organisms as whole systems, and constitutes thereby an alternative to more reductionist and mechanistic approaches. I will discuss how the theory of autonomy provides a justification for the scientific use of notions as function, norm, agency and teleology, whose epistemological legitimacy is highly debated. I will conclude by describing the difficult challenges that poses the transition from biological to cognitive autonomy.

Bioluminescence, which is rare on land, is extremely common in the deep sea, being found in 80% of the animals living between 200 and 1000 m. These animals rely on bioluminescence for communication, feeding, and/or defense, so the generation and detection of light is essential to their survival. Our present knowledge of this phenomenon has been limited due to the difficulty in bringing up live deep-sea animals to the surface, and the lack of proper techniques needed to study this complex system. However, new genomic techniques are now available, and a team with extensive experience in deep-sea biology, vision, and genomics has been assembled to lead this project. This project is aimed to study three questions 1) What are the evolutionary patterns of different types of bioluminescence in deep-sea shrimp? 2) How are deep-sea organisms’ eyes adapted to detect bioluminescence? 3) Can bioluminescent organs (called photophores) detect light in addition to emitting light? Findings from this study will provide valuable insight into a complex system vital to communication, defense, camouflage, and species recognition. This study will bring monumental contributions to the fields of deep sea and evolutionary biology, and immediately improve our understanding of bioluminescence and light detection in the marine environment. In addition to scientific advancement, this project will reach K-college aged students through the development and dissemination of educational tools, a series of molecular and organismal-based workshops, museum exhibits, public seminars, and biodiversity initiatives.

A great deal of understanding can be gleaned from direct observation of organismal growth, development, and behavior. However, direct observation can be time consuming and influence the organism through unintentional stimuli. Additionally, video capturing equipment can often be prohibitively expensive, difficult to modify to one’s specific needs, and may come with unnecessary features. Here, we describe the PiSpy, a low-cost, automated video acquisition platform that uses a Raspberry Pi computer and camera to record video or images at specified time intervals or when externally triggered. All settings and controls, such as programmable light cycling, are accessible to users with no programming experience through an easy-to-use graphical user interface. Importantly, the entire PiSpy system can be assembled for less than $100 using laser-cut and 3D-printed components. We demonstrate the broad applications and flexibility of the PiSpy across a range of model and non-model organisms. Designs, instructions, and code can be accessed through an online repository, where a global community of PiSpy users can also contribute their own unique customizations and help grow the community of open-source research solutions.

The last twenty years have witnessed extraordinarily rapid progress in basic neuroscience, including breakthrough technologies such as optogenetics, and the collection of unprecedented amounts of neuroimaging, genetic and other data relevant to neuroscience and mental health. However, the translation of this progress into improved understanding of brain function and dysfunction has been comparatively slow. As a result, the development of therapeutics for mental health has stagnated too. One central challenge has been to extract meaning from these large, complex, multivariate datasets, which requires a shift towards systems-level mathematical and computational approaches. A second challenge has been reconciling different scales of investigation, from genes and molecules to cells, circuits, tissue, whole-brain, and ultimately behaviour. In this talk I will describe several strands of work using mathematical, statistical, and bioinformatic methods to bridge these gaps. Topics will include: using artificial neural networks to link the organization of large-scale brain connectivity to cognitive function; using multivariate statistical methods to link disease-related changes in brain networks to the underlying biological processes; and using network-based approaches to move from genetic insights towards drug discovey. Finally, I will discuss how simple organisms such as C. elegans can serve to inspire, test, and validate new methods and insights in networks neuroscience.

Our world is full of living creatures that must share information to survive and reproduce. As humans, we easily forget how hard it is to communicate within natural environments. So how do organisms solve this challenge, using only natural resources? Ideas from computer science, physics and mathematics, such as energetic cost, compression, and detectability, define universal criteria that almost all communication systems must meet. We use insect swarms as a model system for identifying how organisms harness the dynamics of communication signals, perform spatiotemporal integration of these signals, and propagate those signals to neighboring organisms. In this talk I will focus on two types of communication in insect swarms: visual communication, in which fireflies communicate over long distances using light signals, and chemical communication, in which bees serve as signal amplifiers to propagate pheromone-based information about the queen’s location.

Choosing among spatially distributed options is a central challenge for animals, from deciding among alternative potential food sources or refuges, to choosing with whom to associate. Here, using an integrated theoretical and experimental approach (employing immersive Virtual Reality), with both invertebrate and vertebrate models—the fruit fly, desert locust and zebrafish—we consider the recursive interplay between movement and collective vectorial integration in the brain during decision-making regarding options (potential ‘targets’) in space. We reveal that the brain repeatedly breaks multi-choice decisions into a series of abrupt (critical) binary decisions in space-time where organisms switch, spontaneously, from averaging vectorial information among, to suddenly excluding one of, the remaining options. This bifurcation process repeats until only one option—the one ultimately selected—remains. Close to each bifurcation the ‘susceptibility’ of the system exhibits a sharp increase, inevitably causing small differences among the remaining options to become amplified; a property that both comes ‘for free’ and is highly desirable for decision-making. This mechanism facilitates highly effective decision-making, and is shown to be robust both to the number of options available, and to context, such as whether options are static (e.g. refuges) or mobile (e.g. other animals). In addition, we find evidence that the same geometric principles of decision-making occur across scales of biological organisation, from neural dynamics to animal collectives, suggesting they are fundamental features of spatiotemporal computation.

Microbes have shaped the evolution of eukaryotes and contribute significantly to the physiology and behavior of animals. Some of these traits are inherited by the progenies. Despite the vast importance of microbe-host communication, we still do not know how bacteria change short term traits or long-term decisions in individuals or communities. In this seminar I will present our work on how commensal and pathogenic bacteria impact specific neuronal phenotypes and decision making. The traits we specifically study are the degeneration and regeneration of neurons and survival behaviors in animals. We use the nematode Caenorhabditis elegans and its dietary bacteria as model organisms. Both nematode and bacteria are genetically tractable, simplifying the detection of specific molecules and their effect on measurable characteristics. To identify these molecules we analyze their genomes, transcriptomes and metabolomes, followed by functional in vivo validation. We found that specific bacterial RNAs and bacterially produced neurotransmitters are key to trigger a survival behavioral and neuronal protection respectively. While RNAs cause responses that lasts for many generations we are still investigating whether bacterial metabolites are capable of inducing long lasting phenotypic changes.

In an ever-changing environment, uncertainty is omnipresent. To deal with this, organisms have evolved mechanisms that allow them to take advantage of environmental regularities in order to make decisions robustly and adjust their behavior efficiently, thus maximizing their chances of survival. In this talk, I will present behavioral evidence that animals perform model-based state inference to predict environmental state changes and adjust their behavior rapidly, rather than slowly updating choice values. This model-based inference process can be described using Bayesian change-point models. Furthermore, I will show that neural populations in the prefrontal cortex accurately predict behavioral switches, and that the activity of these populations is associated with Bayesian estimates. In addition, we will see that learning leads to the emergence of a high-dimensional representational subspace that can be reused when the animals re-learn a previously learned set of action-value associations. Altogether, these findings highlight the role of the PFC in representing a belief about the current state of the world.

Organisms face challenges to survival throughout life. When we freeze or flee in danger, we often feel fear. Tracing the deep history of danger gives a different perspective. The first cells living billions of years ago had to detect and respond to danger in order to survive. Life is about not being dead, and behavior is a major way that organisms hold death off. Although behavior does not require a nervous system, complex organisms have brain circuits for detecting and responding to danger, the deep roots of which go back to the first cells. But these circuits do not make fear, and fear is not the cause of why we freeze or flee. Fear a human invention; a construct we use to account for what happens in our minds when we become aware that we are in harm’s way. This requires a brain that can personally know that it existed in the past, that it is the entity that might be harmed in the present, and that it will cease to exist it the future. If other animals have conscious experiences, they cannot have the kinds of conscious experiences we have because they do not have the kinds of brains we have. This is not meant as a denial of animal consciousness; it is simply a statement about the fact that every species has a different brain. Nor is it a declaration about the wonders of the human brain, since we have done some wonderful, but also horrific, things with our brains. In fact, we are on the way to a climatic disaster that will not, as some suggest, destroy the Earth. But it will make it inhabitable for our kind, and other organisms with high energy demands. Bacteria have made it for billions of years and will likely be fine. The rest is up for grabs, and, in a very real sense, up to us.

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.

Flies represent nearly 10% of all species described by science and are arguably unmatched among flying organisms in their aerial agility. The flight trajectory of flies often consists of crisp straight flight segments interspersed with rapid changes in course called body saccades. Recent advances in genetic tools have made it possible to explore the neurobiological circuitry underlying these two distinct modes of fly flight behavior.

Pain has both a sensory and emotional component and is driven by activation of sensory neurones called nociceptors that are tuned to detect noxious stimuli in a process called nociception. Although nociception functions as a detect and protect mechanism. and is found in many organisms, this system becomes dysregulated in a number of conditions where chronic pain presents as a key symptom, for example osteoarthritis. Nociceptors do not innervate empty space though and do not act alone. Going beyond the neurone, other cell types, such as fibroblast-like synoviocytes interact with and modify the function of nociceptors, which is likely a key contributor to the chronification of pain. In this talk, I will look at how combining pre-clinical mouse work with human tissue and genetics might provide a way to accelerate new analgesics from bench to bedside, giving examples from our work in joint pain, bowel pain and labour pain.

Many microorganisms and cells function in complex (non-Newtonian) fluids, which are mixtures of different materials and exhibit both viscous and elastic stresses. For example, mammalian sperm swim through cervical mucus on their journey through the female reproductive tract, and they must penetrate the viscoelastic gel outside the ovum to fertilize. In micro-scale swimming the dynamics emerge from the coupled interactions between the complex rheology of the surrounding media and the passive and active body dynamics of the swimmer. We use computational models of swimmers in viscoelastic fluids to investigate and provide mechanistic explanations for emergent swimming behaviors. I will discuss how flexible filaments (such as flagella) can store energy from a viscoelastic fluid to gain stroke boosts due to fluid elasticity. I will also describe 3D simulations of model organisms such as C. Reinhardtii and mammalian sperm, where we use experimentally measured stroke data to separate naturally coupled stroke and fluid effects. We explore why strokes that are adapted to Newtonian fluid environments might not do well in viscoelastic environments.

The settling speeds of small biological particles influence the distribution of organisms such as plants, corals, and phytoplankton, but these speeds are difficult to quantify without magnification. In this talk, I highlight my novel method,  using dynamic scaling principles and 3D printed models to solve this problem. Dynamic scaling involves creating models with differ in size to the original system and match the physical forces acting upon the model to the original system. I discuss the methodology behind the technique and show how it differs to previous works using dynamically scaled models. I show the flexibility of the technique and suggest how it can be applied to other free-falling particles (e.g. seeds and spores).

Organisms modify their behavior in response to its consequences, a phenomenon referred to as operant learning. Contemporary modeling of this learning behavior is based on reinforcement learning algorithms. I will discuss some of the challenges that these models face, and proposed a new approach to model-selection that is based on testing their ability to engineer behavior. Finally, I will present the results of The Choice Engineering Competition – an academic competition that compared the efficacies of qualitative and quantitative models of operant learning in shaping behavior.

A key challenge in modern soft matter is to identify the principles that govern the organisation and functionality in non-equilibrium systems. Current research efforts largely focus on non-equilibrium processes that occur either at the single-molecule scale (e.g. protein and DNA conformations under driving forces), or at the scale of whole tissues, organisms, and active colloidal and microscopic objects. However, the range of the scales in-between — from molecules to large-scaled molecular assemblies that consume energy and perform work — remains under-explored. This is, nevertheless, the scale that is crucial for the function of a living cell, where molecular self-assembly driven far from equilibrium produces mechanical work needed for cell reshaping, transport, motility, division, and healing. Today I will discuss physical modelling of active elastic filaments, called ESCRT-III filaments, that dynamically assemble and disassemble on cell membranes. This dynamic assembly changes the filaments’ shape and mechanical properties and leads to the remodelling and cutting of cells. I will present a range of experimental comparisons of our simulation results: from ESCRT-III-driven trafficking in eukaryotes to division of evolutionary simple archaeal cells.

Collective behavior of organisms creates environmental micro-niches that buffer them from environmental fluctuations e.g., temperature, humidity, mechanical perturbations, etc., thus coupling organismal physiology, environmental physics, and population ecology. This talk will focus on a combination of biological experiments, theory, and computation to understand how a collective of bees can integrate physical and behavioral cues to attain a non-equilibrium steady state that allows them to resist and respond to environmental fluctuations of forces and flows. We analyze how bee clusters change their shape and connectivity and gain stability by spread-eagling themselves in response to mechanical perturbations. Similarly, we study how bees in a colony respond to environmental thermal perturbations by deploying a fanning strategy at the entrance that they use to create a forced ventilation stream that allows the bees to collectively maintain a constant hive temperature. When combined with quantitative analysis and computations in both systems, we integrate the sensing of the environmental cues (acceleration, temperature, flow) and convert them to behavioral outputs that allow the swarms to achieve a dynamic homeostasis.

When was the last time you ran into a giant? Chances are never. Almost 100 years ago, JBS Haldane posed an outwardly simple yet complex question – what is the most optimal size (for a biological system)? The living world around us contains a huge diversity of organisms, each with its own characteristic size. Even the size of subcellular organelles is tightly controlled. In absence of physical rulers, how do cells and organisms truly “know” how large is large enough? What are the mechanisms in place to enforce size control? Many of these questions have motivated generations of scientists to look for physical principles underlying size control in biological systems. In the next edition of Emory's Theory and Modeling of Living Systems (TMLS) workshop series, our panel of speakers will take a close look at these questions, across the entire scale - from the molecular, all the way to the ecosystem.

Over the past five years, our understanding of how mechanical processes act across multiple scales to direct morphogenesis has advanced significantly. Yet, there remain numerous open questions, including the role of mechanics in tissue shaping, cancer dissemination, and cellular aging. The From Molecules to Organs:The Mechanobiology of Morphogenesis conference will bring together world leaders in the fields of mechanobiology and morphogenesis. The three-day conference will span scales, from single molecules up to whole organisms.

Over the past five years, our understanding of how mechanical processes act across multiple scales to direct morphogenesis has advanced significantly. Yet, there remain numerous open questions, including the role of mechanics in tissue shaping, cancer dissemination, and cellular aging. The From Molecules to Organs:The Mechanobiology of Morphogenesis conference will bring together world leaders in the fields of mechanobiology and morphogenesis. The three-day conference will span scales, from single molecules up to whole organisms.

It is often assumed that biological swimmers conform faithfully to certain stereotypes assigned to them by physicists and mathematicians, when the reality is in fact much more complicated. In this talk we will use a combination of theory, experiments, and robotics, to understand the physical and evolutionary basis of motility control in a number of distinguished organisms. These organisms differ markedly in terms of their size, shape, and arrangement of locomotor appendages, but are united in their use of cilia - the ultimate shape-shifting organelle - to achieve self-propulsion and navigation.

Understanding individual and macroscopic transport properties of motile micro-organisms in complex environments is a timely question, relevant to many ecological, medical and technological situations. At the fundamental level, this question is also receiving a lot of attention as fluids loaded with swimming micro-organisms has become a rich domain of applications and a conceptual playground for the statistical physics of “active matter”. The existence of microscopic sources of energy borne by the motile character of these micro-swimmers is driving self-organization processes at the origin of original emergent phases and unconventional macroscopic properties leading to revisit many standard concepts in the physics of suspensions. In this presentation, I will report on a recent exploration on the question of spontaneous formation of large scale collective motion in relation with the rheological response of active suspensions. I will also present new experiments showing how the motility of bacteria can be controlled such as to extract work macroscopically.

Internal organs constantly exchange signals, and can respond with striking anatomical and functional transformations, even in fully developed organisms. We are exploring the mechanisms that drive and sustain such plasticity using the intestine and its neurons as experimental systems. I will present some of our recent work, which has characterised the enteric nervous system of Drosophila, and has explored its physiological plasticity as well as that of the intestine itself. This work has uncovered unexpected sexual dimorphisms, intestinal contributions to reproductive success and metabolic crosstalk between the gut and the brain. Interestingly, this crosstalk appears to be spatially constrained by the three dimensional arrangement of viscera, revealing a previously unrecognised layer of inter-organ signalling regulation. I may also describe our attempts to explore how broadly applicable our findings may be using mammalian systems.

The ability to read the DNA sequences of different organisms has transformed biology in much the same way that the telescope transformed astronomy. And yet, much of the sequence found in these genomes is as enigmatic as the Rosetta Stone was to early Egyptologists. With the aim of making steps to crack the genomic Rosetta Stone, I will describe unexpected ways of using the physics of information transfer first developed at Bell Labs for thinking about telephone communications to try to decipher the meaning of the regulatory features of genomes. Specifically, I will show how we have been able to explore genes for which we know nothing about how they are regulated by using a combination of mutagenesis, deep sequencing and the physics of information, with the result that we now have falsifiable hypotheses about how those genes work. With those results in hand, I will show how simple tools from statistical physics can be used to predict the level of expression of different genes, followed by a description of precision measurements used to test those predictions. Bringing the two threads of the talk together, I will think about next steps in reading and writing genomes at will.

Life of biological molecules spans time and length scales relevant at atomic to cellular time and length scales. Hence, novel molecular modeling approaches are required to be inherently multi-scale. Here we describe multiple methodologies developed in our laboratory: rapid discrete molecular dynamics simulation algorithm, protein design and structural refinement tools. Using these methodologies, we describe therapeutic strategies to combat this HIV and cancer, as well as design novel approaches for controlling proteins in living cells and organisms.

Organisms sense light for purposes that range from recognizing objects to synchronizing activity with environmental cycles. What mechanisms serve these diverse tasks? This seminar will examine the specializations of two cell types. First are the foveal cone photoreceptors. These neurons are used by primates to see far greater detail than other mammals, which lack them. How do the biophysical properties of foveal cones support high-acuity vision? Second are the melanopsin retinal ganglion cells, which are conserved among mammals and essential for processes that include regulation of the circadian clock, sleep, and hormone levels. How do these neurons encode light, and is encoding customized for animals of different niches? In pursuing these questions, a broad goal is to learn how various levels of biological organization are shaped to behavioural needs.

A globally invasive form of the mosquito Aedes aegypti has evolved to specialize in biting humans, making it an efficient vector of dengue, yellow fever, Zika, and chikungunya. Host-seeking females identify humans primarily by smell, strongly preferring human odour over the odor of non-human animals. Exactly how they discriminate, however, is unclear. Human and animal odors are complex blends that share most of the same chemical components, presenting an interesting challenge in sensory coding. I will talk about recent work from the lab showing that (1) human and animal blends can be distinguished by the relative concentration of a diverse array of compounds and that (2) these complex chemical differences translate into a neural code for human odor that involves as few as two to three olfactory glomeruli in the mosquito brain. Our work demonstrates how organisms may evolve to discriminate complex odor stimuli of special biological relevance with a surprisingly simple combinatorial code and reveals novel targets for the design of next-generation mosquito control strategies.

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.

In recent years it has become increasingly clear that (Shannon) information is a central resource for organisms, akin in importance to energy. Any decision that an organism or a subsystem of an organism takes involves the acquisition, selection, and processing of information and ultimately its concentration and enaction. It is the consequences of this balance that will occupy us in this talk. This perception-action loop picture of an agent's life cycle is well established and expounded especially in the context of Fuster's sensorimotor hierarchies. Nevertheless, the information-theoretic perspective drastically expands the potential and predictive power of the perception-action loop perspective. On the one hand information can be treated - to a significant extent - as a resource that is being sought and utilized by an organism. On the other hand, unlike energy, information is not additive. The intrinsic structure and dynamics of information can be exceedingly complex and subtle; in the last two decades one has discovered that Shannon information possesses a rich and nontrivial intrinsic structure that must be taken into account when informational contributions, information flow or causal interactions of processes are investigated, whether in the brain or in other complex processes. In addition, strong parallels between information and control theory have emerged. This parallelism between the theories allows one to obtain unexpected insights into the nature and properties of the perception-action loop. Through the lens of information theory, one can not only come up with novel hypotheses about necessary conditions for the organization of information processing in a brain, but also with constructive conjectures and predictions about what behaviours, brain structure and dynamics and even evolutionary pressures one can expect to operate on biological organisms, induced purely by informational considerations.

Maintaining posture is a vital challenge for all freely-moving organisms. As animals grow, their relationship to destabilizing physical forces changes. How does the nervous system deal with this ongoing challenge? Vertebrates use highly conserved vestibular reflexes to stabilize the body. We established the larval zebrafish as a new model system to understand the development of the vestibular reflexes responsible for balance. In this talk, I will begin with the biophysical challenges facing baby fish as they learn to swim. I’ll briefly review published work by David Ehrlich, Ph.D., establishing a fundamental relationship between postural stability and locomotion. The bulk of the talk will highlight unpublished work by Kyla Hamling. She discovered that a small (~50) population of molecularly-defined brainstem neurons called vestibulo-spinal cells act as a nexus for postural development. Her loss-of-function experiments show that these neurons contribute more to postural stability as animals grow older. I’ll end with brief highlights from her ongoing work examining tilt-evoked responses of these neurons using 2-photon imaging and the consequences of downstream activity in the spinal cord using single-objective light-sheet (SCAPE) microscopy

Olfactory navigation is essential for the survival of living beings from unicellular organisms to mammals. In the wild, rodents combine odor information with an internal spatial representation of the environment for foraging and navigation. What are the neural circuits in the brain that implement these behaviours? My research addresses this question by examining the synaptic circuits and neural population activity in the olfactory cortex to understand the integration of olfactory and spatial information. Primary olfactory (piriform) cortex (PCx) has long been recognized as a highly associative brain structure. What is the behavioural and functional role of these associative synapses in PCx? We designed an odor-cued navigation task, where rats must use both olfactory and spatial information to obtain water rewards. We recorded from populations of posterior piriform cortex (pPCx) neurons during behaviour and found that individual neurons were not only odor-selective, but also fired differentially to the same odor sampled at different locations, forming an “olfactory place map”. Spatial locations can be decoded from simultaneously recorded pPCx population, and spatial selectivity is maintained in the absence of odors, across behavioural contexts. This novel olfactory place map is consistent with our finding for a dominant role of associative excitatory synapses in shaping PCx representations, and suggest a role for PCx spatial representations in supporting olfactory navigation. This work not only provides insight into the neural basis for how odors can be used for navigation, but also reveals PCx as a prime site for addressing the general question of how sensory information is anchored within memory systems and combined with cognitive maps to guide flexible behaviour.

Olfactory navigation provides a tractable model for studying the circuit basis of sensori-motor transformations and goal-directed behaviour. Macroscopic organisms typically navigate in odor plumes that provide a noisy and uncertain signal about the location of an odor source. Work in many species has suggested that animals accomplish this task by combining temporal processing of dynamic odor information with an estimate of wind direction. Our lab has been using adult walking Drosophila to understand both the computational algorithms and the neural circuits that support navigation in a plume of attractive food odor. We developed a high-throughput paradigm to study behavioural responses to temporally-controlled odor and wind stimuli. Using this paradigm we found that flies respond to a food odor (apple cider vinegar) with two behaviours: during the odor they run upwind, while after odor loss they perform a local search. A simple computational model based one these two responses is sufficient to replicate many aspects of fly behaviour in a natural turbulent plume. In on-going work, we are seeking to identify the neural circuits and biophysical mechanisms that perform the computations delineated by our model. Using electrophysiology, we have identified mechanosensory neurons that compute wind direction from movements of the two antennae and central mechanosensory neurons that encode wind direction are are involved in generating a stable downwind orientation. Using optogenetic activation, we have traced olfactory circuits capable of evoking upwind orientation and offset search from the periphery, through the mushroom body and lateral horn, to the central complex. Finally, we have used optogenetic activation, in combination with molecular manipulation of specific synapses, to localize temporal computations performed on the odor signal to olfactory transduction and transmission at specific synapses. Our work illustrates how the tools available in fruit fly can be applied to dissect the mechanisms underlying a complex goal-directed behaviour.