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Mathematical Foundations of Artificial Intelligence (MFAI)
NSF support for interdisciplinary collaborations developing mathematical and theoretical foundations for explainable, reliable, sustainable and trustworthy artificial intelligence.
Project Grants in the Natural and Technical Sciences 2026
Supports fundamental research within the natural and technical sciences with potential future applications in life science, health science or sustainability; up to DKK 4 million per project from a DKK 77 million grant capital in 2026. Call opened 19 June 2026.
Pathways to Enable Secure Open-Source Ecosystems (PESOSE)
NSF support for creating, strengthening and sustaining secure open-source ecosystems that advance scientific and technological innovation and broaden participation.
Decoding ketamine: Neurobiological mechanisms underlying its rapid antidepressant efficacy
Unlike traditional monoamine-based antidepressants that require weeks to exert effects, ketamine alleviates depression within hours, though its clinical use is limited by side effects. While ketamine was initially thought to work primarily through NMDA receptor (NMDAR) inhibition, our research reveals a more complex mechanism. We demonstrate that NMDAR inhibition alone cannot explain ketamine's sustained antidepressant effects, as other NMDAR antagonists like MK-801 lack similar efficacy. Instead, the (2R,6R)-hydroxynorketamine (HNK) metabolite appears critical, exhibiting antidepressant effects without ketamine's side effects. Paradoxically, our findings suggest an inverted U-shaped dose-response relationship where excessive NMDAR inhibition may actually impede antidepressant efficacy, while some level of NMDAR activation is necessary. The antidepressant actions of ketamine and (2R,6R)-HNK require AMPA receptor activation, leading to synaptic potentiation and upregulation of AMPA receptor subunits GluA1 and GluA2. Furthermore, NMDAR subunit GluN2A appears necessary and possibly sufficient for these effects. This research establishes NMDAR-GluN2A activation as a common downstream effector for rapid-acting antidepressants, regardless of their initial targets, offering promising directions for developing next-generation antidepressants with improved efficacy and reduced side effects.
Neural makers of lapses in attention during sustained ‘real-world’ task performance
Lapses in attention are ubiquitous and, unfortunately, the cause of many tragic accidents. One potential solution may be to develop assistance systems which can use objective, physiological signals to monitor attention levels and predict a lapse in attention before it occurs. As it stands, it is unclear which physiological signals are the most reliable markers of inattention, and even less is known about how reliably they will work in a more naturalistic setting. My project aims to address these questions across two experiments: a lab-based experiment and a more ‘real-world’ experiment. In this talk I will present the findings from my lab experiment, in which we combined EEG and pupillometry to detect markers of inattention during two computerised sustained attention tasks. I will then present the methods for my second, more ‘naturalistic’ experiment in which we use the same methods (EEG and pupillometry) to examine whether these markers can still be extracted from noisier data.
Gender, trait anxiety and attentional processing in healthy young adults: is a moderated moderation theory possible?
Three studies conducted in the context of PhD work (UNIL) aimed at proving evidence to address the question of potential gender differences in trait anxiety and executive control biases on behavioral efficacy. In scope were male and female non-clinical samples of adult young age that performed non-emotional tasks assessing basic attentional functioning (Attention Network Test – Interactions, ANT-I), sustained attention (Test of Variables of Attention, TOVA), and visual recognition abilities (Object in Location Recognition Task, OLRT). Results confirmed the intricate nature of the relationship between gender and health trait anxiety through the lens of their impact on processing efficacy in males and females. The possibility of a gendered theory in trait anxiety biases is discussed.
Degrees of Consciousness
In the science of consciousness, it’s often assumed that some creatures (or mental states) are more conscious than others. But a number of philosophers have argued that the notion of degrees of consciousness is conceptually confused. I'll (1) argue that the most prominent objections to degrees of consciousness are unsustainable, and (2) develop an analysis of degrees of consciousness. On my view, whether consciousness comes in degrees ultimately depends on which theory of consciousness turns out to be correct. But I'll also argue that most theories of consciousness entail that consciousness comes in degrees.
From pecking order to ketamine - neural mechanism of social and emotional behavior
Emotions and social interactions color our lives and shape our behaviors. Using animal models and engineered manipulations, we aim to understand how social and emotional behaviors are encoded in the brain, focusing on the neural circuits underlying dominance hierarchy and depression. This lecture will highlight our recent discoveries on how downward social mobility leads to depression; how ketamine tames depression by blocking burst firing in the brain’s antireward center; and, how glia-neuron interaction plays a surprising role in this process. I will also present our recent work on the mechanism underlying the sustained antidepressant activity of ketamine and its brain region specificity. With these results, we hope to illuminate on a more unified theory on ketamine’s mode of action and inspire new treatment strategies for depression.
From pecking order to ketamine - neural mechanism of social and emotional behavior
Emotions and social interactions color our lives and shape our behaviors. Using animal models and engineered manipulations, we aim to understand how social and emotional behaviors are encoded in the brain, focusing on the neural circuits underlying dominance hierarchy and depression. This lecture will highlight our recent discoveries on how downward social mobility leads to depression; how ketamine tames depression by blocking burst firing in the brain’s antireward center; and, how glia-neuron interaction plays a surprising role in this process. I will also present our recent work on the mechanism underlying the sustained antidepressant activity of ketamine and its brain region specificity. With these results, we hope to illuminate on a more unified theory on ketamine’s mode of action and inspire new treatment strategies for depression.
A sense without sensors: how non-temporal stimulus features influence the perception and the neural representation of time
Any sensory experience of the world, from the touch of a caress to the smile on our friend’s face, is embedded in time and it is often associated with the perception of the flow of it. The perception of time is therefore a peculiar sensory experience built without dedicated sensors. How the perception of time and the content of a sensory experience interact to give rise to this unique percept is unclear. A few empirical evidences show the existence of this interaction, for example the speed of a moving object or the number of items displayed on a computer screen can bias the perceived duration of those objects. However, to what extent the coding of time is embedded within the coding of the stimulus itself, is sustained by the activity of the same or distinct neural populations and subserved by similar or distinct neural mechanisms is far from clear. Addressing these puzzles represents a way to gain insight on the mechanism(s) through which the brain represents the passage of time. In my talk I will present behavioral and neuroimaging studies to show how concurrent changes of visual stimulus duration, speed, visual contrast and numerosity, shape and modulate brain’s and pupil’s responses and, in case of numerosity and time, influence the topographic organization of these features along the cortical visual hierarchy.
Spatially-embedded recurrent neural networks reveal widespread links between structural and functional neuroscience findings
Brain networks exist within the confines of resource limitations. As a result, a brain network must overcome metabolic costs of growing and sustaining the network within its physical space, while simultaneously implementing its required information processing. To observe the effect of these processes, we introduce the spatially-embedded recurrent neural network (seRNN). seRNNs learn basic task-related inferences while existing within a 3D Euclidean space, where the communication of constituent neurons is constrained by a sparse connectome. We find that seRNNs, similar to primate cerebral cortices, naturally converge on solving inferences using modular small-world networks, in which functionally similar units spatially configure themselves to utilize an energetically-efficient mixed-selective code. As all these features emerge in unison, seRNNs reveal how many common structural and functional brain motifs are strongly intertwined and can be attributed to basic biological optimization processes. seRNNs can serve as model systems to bridge between structural and functional research communities to move neuroscientific understanding forward.
A multi-level account of hippocampal function in concept learning from behavior to neurons
A complete neuroscience requires multi-level theories that address phenomena ranging from higher-level cognitive behaviors to activities within a cell. Unfortunately, we don't have cognitive models of behavior whose components can be decomposed into the neural dynamics that give rise to behavior, leaving an explanatory gap. Here, we decompose SUSTAIN, a clustering model of concept learning, into neuron-like units (SUSTAIN-d; decomposed). Instead of abstract constructs (clusters), SUSTAIN-d has a pool of neuron-like units. With millions of units, a key challenge is how to bridge from abstract constructs such as clusters to neurons, whilst retaining high-level behavior. How does the brain coordinate neural activity during learning? Inspired by algorithms that capture flocking behavior in birds, we introduce a neural flocking learning rule to coordinate units that collectively form higher-level mental constructs ("virtual clusters"), neural representations (concept, place and grid cell-like assemblies), and parallels recurrent hippocampal activity. The decomposed model shows how brain-scale neural populations coordinate to form assemblies encoding concept and spatial representations, and why many neurons are required for robust performance. Our account provides a multi-level explanation for how cognition and symbol-like representations are supported by coordinated neural assemblies formed through learning.
Reconstructing inhibitory circuits in a damaged brain
Inhibitory interneurons govern the sparse activation of principal cells that permits appropriate behaviors, but they among the most vulnerable to brain damage. Our recent work has demonstrated important roles for inhibitory neurons in disorders of brain development, injury and epilepsy. These studies have motivated our ongoing efforts to understand how these cells operate at the synaptic, circuit and behavioral levels and in designing new technologies targeting specific populations of interneurons for therapy. I will discuss our recent efforts examining the role of interneurons in traumatic brain injury and in designing cell transplantation strategies - based on the generation of new inhibitory interneurons - that enable precise manipulation of inhibitory circuits in the injured brain. I will also discuss our ongoing efforts using monosynaptic virus tracing and whole-brain clearing methods to generate brain-wide maps of inhibitory circuits in the rodent brain. By comprehensively mapping the wiring of individual cell types on a global scale, we have uncovered a fundamental strategy to sustain and optimize inhibition following traumatic brain injury that involves spatial reorganization of local and long-range inputs to inhibitory neurons. These recent findings suggest that brain damage, even when focally restricted, likely has a far broader affect on brain-wide neural function than previously appreciated.
NaV Long-term Inactivation Regulates Adaptation in Place Cells and Depolarization Block in Dopamine Neurons
In behaving rodents, CA1 pyramidal neurons receive spatially-tuned depolarizing synaptic input while traversing a specific location within an environment called its place. Midbrain dopamine neurons participate in reinforcement learning, and bursts of action potentials riding a depolarizing wave of synaptic input signal rewards and reward expectation. Interestingly, slice electrophysiology in vitro shows that both types of cells exhibit a pronounced reduction in firing rate (adaptation) and even cessation of firing during sustained depolarization. We included a five state Markov model of NaV1.6 (for CA1) and NaV1.2 (for dopamine neurons) respectively, in computational models of these two types of neurons. Our simulations suggest that long-term inactivation of this channel is responsible for the adaptation in CA1 pyramidal neurons, in response to triangular depolarizing current ramps. We also show that the differential contribution of slow inactivation in two subpopulations of midbrain dopamine neurons can account for their different dynamic ranges, as assessed by their responses to similar depolarizing ramps. These results suggest long-term inactivation of the sodium channel is a general mechanism for adaptation.
Monash Biomedical Imaging highlights from 2021 and looking ahead to 2022
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.
The processing of price during purchase decision making: Are there neural differences among prosocial and non-prosocial consumers?
International organizations, governments and companies are increasingly committed to developing measures that encourage adoption of sustainable consumption patterns among the population. However, their success requires a deep understanding of the everyday purchasing decision process and the elements that shape it. Price is an element that stands out. Prior research concluded that the influence of price on purchase decisions varies across consumer profiles. Yet no consumer behavior study to date has assessed the differences of price processing among consumers adopting sustainable habits (prosocial) as opposed to those who have not (non-prosocial). This is the first study to resort to neuroimaging tools to explore the underlying neural mechanisms that reveal the effect of price on prosocial and non-prosocial consumers. Self-reported findings indicate that prosocial consumers place greater value on collective costs and benefits while non-prosocial consumers place a greater weight on price. The neural data gleaned from this analysis offers certain explanations as to the origin of the differences. Non-prosocial (vs. prosocial) consumers, in fact, exhibit a greater activation in brain areas involved with reward, valuation and choice when evaluating price information. These findings could steer managers to improve market segmentation and assist institutions in their design of campaigns fostering environmentally sustainable behaviors
Dysfunctional synaptic vesicle recycling – links to epilepsy
Accurate and synchronous neurotransmitter release is essential for brain communication and occurs when neurotransmitter-containing synaptic vesicles (SVs) fuse to release their content in response to neuronal activity. Neurotransmission is sustained by the process of SV recycling, which generates SVs locally at the presynapse. Until relatively recently it was believed that most mutations in genes that were essential for SV recycling would be incompatible with life, due to this fundamental role. However, this is not the case, with mutations in essential genes for SV fusion, retrieval and recycling identified in individuals with epilepsy. This seminar will cover our laboratory’s progress in determining how genetic mutations in people with epilepsy translate into presynaptic dysfunction and ultimately into seizure activity. The principal focus of these studies will be in vitro investigations of, 1) the biological role of these gene products and 2) how their dysfunction impacts SV recycling, using live fluorescence imaging of genetically-encoded reporters. The gene products to be discussed in more detail will be the SV protein SV2A, the protein kinase CDKL5 and the translation repressor FMRP.
Can connectomics help us understand the brain and sustain the revolution in AI?
3 short talks and a panel discussion on the topic of "Can connectomics help us understand the brain and sustain the revolution in AI?" Expect beautiful connectomics data, provocative dreaming, realistic critiques and everything in between. Students & post-docs, stay on to meet our 3 amazing speakers. Moderator: Dr Greg Jefferis https://www2.mrc-lmb.cam.ac.uk/group-leaders/h-to-m/gregory-jefferis/
Playing StarCraft and saving the world using multi-agent reinforcement learning!
This is my C-14 Impaler gauss rifle! There are many like it, but this one is mine!" - A terran marine If you have never heard of a terran marine before, then you have probably missed out on playing the very engaging and entertaining strategy computer game, StarCraft. However, don’t despair, because what we have in store might be even more exciting! In this interactive session, we will take you through, step-by-step, on how to train a team of terran marines to defeat a team of marines controlled by the built-in game AI in StarCraft II. How will we achieve this? Using multi-agent reinforcement learning (MARL). MARL is a useful framework for building distributed intelligent systems. In MARL, multiple agents are trained to act as individual decision-makers of some larger system, while learning to work as a team. We will show you how to use Mava (https://github.com/instadeepai/Mava), a newly released research framework for MARL to build a multi-agent learning system for StarCraft II. We will provide the necessary guidance, tools and background to understand the key concepts behind MARL, how to use Mava building blocks to build systems and how to train a system from scratch. We will conclude the session by briefly sharing various exciting real-world application areas for MARL at InstaDeep, such as large-scale autonomous train navigation and circuit board routing. These are problems that become exponentially more difficult to solve as they scale. Finally, we will argue that many of humanity’s most important practical problems are reminiscent of the ones just described. These include, for example, the need for sustainable management of distributed resources under the pressures of climate change, or efficient inventory control and supply routing in critical distribution networks, or robotic teams for rescue missions and exploration. We believe MARL has enormous potential to be applied in these areas and we hope to inspire you to get excited and interested in MARL and perhaps one day contribute to the field!
(Un)consciousness & (In)attention
In this talk, I shall not argue for any single thesis or theory in the realm of the (un)consciousness and (in)attention. Instead I will discuss specific examples where philosophers and psychologists can have genuine collaborations in this area. Since issues concerning phenomenological overflow is already too familiar for this audience, I will briefly discuss it only, and focus on other issues that have not been overworked. The exact contents are to be determined, but I will perhaps focus on recent controversies over “sustained representation of perspectival shape” (Morales, Bax, and Firestone, 2020, 2021).
Will it keep me awake? Common caffeine intake habits and sleep in real life situations
Daily caffeine consumption and chronic sleep restriction are highly prevalent in society. It is well established that acute caffeine intake under controlled conditions enhances vigilance and promotes wakefulness but can also delay sleep initiation and reduce electroencephalographic (EEG) markers of sleep intensity, particularly in susceptible individuals. To investigate whether these effects are also present during chronic consumption of coffee/caffeine, we recently conducted several complementary studies. We examined whether repeated coffee intake in dose and timing mimicking ‘real world’ habits maintains simple and complex attentional processes during chronic sleep restriction, such as during a busy work week. We found in genetically caffeine-sensitive individuals that regular coffee (300 mg caffeine/day) benefits most attentional tasks for 3-4 days when compared to decaffeinated coffee. Genetic variants were also used in the population-based HypnoLaus cohort, to investigate whether habitual caffeine consumption causally affects time to fall asleep, number of awakenings during sleep, and EEG-derived sleep intensity. The multi-level statistical analyses consistently showed that sleep quality was virtually unaffected when >3 caffeine-containing beverages/day were compared to 0-3 beverages/day. This conclusion was further corroborated by quantifying the sleep EEG in the laboratory in habitual caffeine consumers. Compared to placebo, daily intake of 3 x 150 mg caffeine over 10 days did not strongly impair nocturnal sleep nor subjective sleep quality in good sleepers. Finally, we tested whether an engineered delayed, pulsatile-release caffeine formula can improve the quality of morning awakening in sleep-restricted volunteers. We found that 160 mg caffeine taken at bedtime ameliorated the quality of awakening, increased positive and reduced negative affect scores, and promoted sustained attention immediately upon scheduled wake-up. Such an approach could prevent over-night caffeine withdrawal and provide a proactive strategy to attenuate disabling sleep inertia. Taken together, the studies suggest that common coffee/caffeine intake habits can transiently attenuate detrimental consequences of reduced sleep virtually without disturbing subjective and objective markers of sleep quality. Nevertheless, coffee/caffeine consumption cannot compensate for chronic sleep restriction.
The processing of price during purchase decision making: Are there neural differences among prosocial and non-prosocial consumers?
International organizations, governments and companies are increasingly committed to developing measures that encourage adoption of sustainable consumption patterns among the population. However, their success requires a deep understanding of the everyday purchasing decision process and the elements that shape it. Price is an element that stands out. Prior research concluded that the influence of price on purchase decisions varies across consumer profiles. Yet no consumer behavior study to date has assessed the differences of price processing among consumers adopting sustainable habits (prosocial) as opposed to those who have not (non-prosocial). This is the first study to resort to neuroimaging tools to explore the underlying neural mechanisms that reveal the effect of price on prosocial and non-prosocial consumers. Self-reported findings indicate that prosocial consumers place greater value on collective costs and benefits while non-prosocial consumers place a greater weight on price. The neural data gleaned from this analysis offers certain explanations as to the origin of the differences. Non-prosocial (vs. prosocial) consumers, in fact, exhibit a greater activation in brain areas involved with reward, valuation and choice when evaluating price information. These findings could steer managers to improve market segmentation and assist institutions in their design of campaigns fostering environmentally sustainable behaviors
Dynamical population coding during defensive behaviours in prefrontal circuits
Coping with threatening situations requires both identifying stimuli predicting danger and selecting adaptive behavioral responses in order to survive. The dorso medial prefrontal cortex (dmPFC) is a critical structure involved in the regulation of threat-related behaviour, yet it is still largely unclear how threat-predicting stimuli and defensive behaviours are associated within prefrontal networks in order to successfully drive adaptive responses. To address these questions, we used a combination of extracellular recordings, neuronal decoding approaches, and optogenetic manipulations to show that threat representations and the initiation of avoidance behaviour are dynamically encoded in the overall population activity of dmPFC neurons. These data indicate that although dmPFC population activity at stimulus onset encodes sustained threat representations and discriminates threat- from non-threat cues, it does not predict action outcome. In contrast, transient dmPFC population activity prior to action initiation reliably predicts avoided from non-avoided trials. Accordingly, optogenetic inhibition of prefrontal activity critically constrained the selection of adaptive defensive responses in a time-dependent manner. These results reveal that the adaptive selection of active fear responses relies on a dynamic process of information linking threats with defensive actions unfolding within prefrontal networks.
Environmental Impact of Research
Research, whether direct or indirect, aims to advance knowledge and change the world for the better. But whether you are spike-sorting with high-performance computers, getting through 100 single-use plastic pipette tips in a day or receiving regular shipments of metal-rich equipment, your research is having a long-term and detrimental impact on the environment. This session will explore how life sciences research contributes to the climate crisis and negatively impacts local and global environments. Practical advice will be given on ways to reduce the footprint of your own research.
A reward-learning framework of knowledge acquisition
Recent years have seen a considerable surge of research on interest-based engagement, examining how and why people are engaged in activities without relying on extrinsic rewards. However, the field of inquiry has been somewhat segregated into three different research traditions which have been developed relatively independently --- research on curiosity, interest, and trait curiosity/interest. The current talk sets out an integrative perspective; the reward-learning framework of knowledge acquisition. This conceptual framework takes on the basic premise of existing reward-learning models of information seeking: that knowledge acquisition serves as an inherent reward, which reinforces people’s information-seeking behavior through a reward-learning process. However, the framework reveals how the knowledge-acquisition process is sustained and boosted over a long period of time in real-life settings, allowing us to integrate the different research traditions within reward-learning models. The framework also characterizes the knowledge-acquisition process with four distinct features that are not present in the reward-learning process with extrinsic rewards --- (1) cumulativeness, (2) selectivity, (3) vulnerability, and (4) under-appreciation. The talk describes some evidence from our lab supporting these claims.
A reward-learning framework of knowledge acquisition: How we can integrate the concepts of curiosity, interest, and intrinsic-extrinsic rewards
Recent years have seen a considerable surge of research on interest-based engagement, examining how and why people are engaged in activities without relying on extrinsic rewards. However, the field of inquiry has been somewhat segregated into three different research traditions which have been developed relatively independently -- research on curiosity, interest, and trait curiosity/interest. The current talk sets out an integrative perspective; the reward-learning framework of knowledge acquisition. This conceptual framework takes on the basic premise of existing reward-learning models of information seeking: that knowledge acquisition serves as an inherent reward, which reinforces people’s information-seeking behavior through a reward-learning process. However, the framework reveals how the knowledge-acquisition process is sustained and boosted over a long period of time in real-life settings, allowing us to integrate the different research traditions within reward-learning models. The framework also characterizes the knowledge-acquisition process with four distinct features that are not present in the reward-learning process with extrinsic rewards -- (1) cumulativeness, (2) selectivity, (3) vulnerability, and (4) under-appreciation. The talk describes some evidence from our lab supporting these claims.
Neural mechanisms for memory and emotional processing during sleep
The hippocampus and the amygdala are two structures required for emotional memory. While the hippocampus encodes the contextual part of the memory, the amygdala processes its emotional valence. During Non-REM sleep, the hippocampus displays high frequency oscillations called “ripples”. Our early work shows that the suppression of ripples during sleep impairs performance on a spatial task, underlying their crucial role in memory consolidation. We more recently showed that the joint amygdala-hippocampus activity linked to aversive learning is reinstated during the following Non-REM sleep epochs, specifically during ripples. This mechanism potentially sustains the consolidation of aversive associative memories during Non REM sleep. On the other hand, REM sleep is associated with regular 8 Hz theta oscillations, and is believed to play a role in emotional processing. A crucial, initial step in understanding this role is to unravel sleep dynamics related to REM sleep in the hippocampus-amygdala network
The suprachiasmatic nucleus: the brain's circadian clock
Sleep and all of the other circadian rhythms that adapt us to the 24 hour world are controlled by the suprachiasmatic nucleus (SCN), the brain's central circadian clock. And yet, the SCN consists of only 20,000 neurons and astrocytes, so what makes it such a powerful clock, able to set the tempo to our lives? Professor Hastings will consider the cell-autonomus and neural circuit-level mechanisms that sustain the SCN clock and how it regulates rest, activity and sleep.
A neuronal model for learning to keep a rhythmic beat
When listening to music, we typically lock onto and move to a beat (1-6 Hz). Behavioral studies on such synchronization (Repp 2005) abound, yet the neural mechanisms remain poorly understood. Some models hypothesize an array of self-sustaining entrainable neural oscillators that resonate when forced with rhythmic stimuli (Large et al. 2010). In contrast, our formulation focuses on event time estimation and plasticity: a neuronal beat generator that adapts its intrinsic frequency and phase to match the extermal rhythm. The model quickly learns new rhythms, within a few cycles as found in human behavior. When the stimulus is removed the beat generator continues to produce the learned rhythm in accordance with a synchronization continuation task.
A Manifesto for Big Team Science
Progress in psychology has been frustrated by challenges concerning replicability, generalizability, strategy selection, inferential reproducibility, and computational reproducibility. Although often discussed separately, I argue that these five challenges share a common cause: insufficient investment of resources into the typical psychology study. I further suggest that big team science can help address these challenges by allowing researchers to pool their resources to efficiently and drastically increase the amount of resources available for a single study. However, the current incentives, infrastructure, and institutions in academic science have all developed under the assumption that science is conducted by solo Principal Investigators and their dependent trainees. These barriers must be overcome if big team science is to be sustainable. Big team science likely also carries unique risks, such as the potential for big team science institutions to monopolize power, become overly conservative, make mistakes at a grand scale, or fail entirely due to mismanagement and a lack of financial sustainability. I illustrate the promise, barriers, and risks of big team science with the experiences of the Psychological Science Accelerator, a global research network of over 1400 members from 70+ countries.
The physics of cement cohesion
Cement is the main binding agent in concrete, literally gluing together rocks and sand into the most-used synthetic material on Earth. However, cement production is responsible for significant amounts of man- made greenhouse gases—in fact if the cement industry were a country, it would be the third largest emitter in the world. Alternatives to the current, environmentally harmful cement production process are not available essentially because the gaps in fundamental understanding hamper the development of smarter and more sustainable solutions. The ultimate challenge is to link the chemical composition of cement grains to the nanoscale physics of the cohesive forces that emerge when mixing cement with water. Cement nanoscale cohesion originates from the electrostatics of ions accumulated in a water-based solution between like-charged surfaces but it is not captured by existing theories because of the nature of the ions involved and the high surface charges. Surprisingly enough, this is also the case for unexplained cohesion in a range of colloidal and biological matter. About one century after the early studies of cement hydration, we have quantitatively solved this notoriously hard problem and discovered how cement cohesion develops during hydration. I will discuss how 3D numerical simulations that feature a simple but molecular description of ions and water, together with an analytical theory that goes beyond the traditional continuum approximations, helped us demonstrate that the optimized interlocking of ion-water structures determine the net cohesive forces and their evolution. These findings open the path to scientifically grounded strategies of material design for cements and have implications for a much wider range of materials and systems where ionic water-based solutions feature both strong Coulombic and confinement effects, ranging from biological membranes to soils. Construction materials are central to our society and to our life as humans on this planet, but usually far removed from fundamental science. We can now start to understand how cement physical-chemistry determines performance, durability and sustainability.
Dynamical population coding during defensive behaviours in prefrontal circuits
Coping with threatening situations requires both identifying stimuli predicting danger and selecting adaptive behavioral responses in order to survive. The dorso medial prefrontal cortex (dmPFC) is a critical structure involved in the regulation of threat-related behaviour, yet it is still largely unclear how threat-predicting stimuli and defensive behaviours are associated within prefrontal networks in order to successfully drive adaptive responses. To address these questions, we used a combination of extracellular recordings, neuronal decoding approaches, and optogenetic manipulations to show that threat representations and the initiation of avoidance behaviour are dynamically encoded in the overall population activity of dmPFC neurons. These data indicate that although dmPFC population activity at stimulus onset encodes sustained threat representations and discriminates threat- from non-threat cues, it does not predict action outcome. In contrast, transient dmPFC population activity prior to action initiation reliably predicts avoided from non-avoided trials. Accordingly, optogenetic inhibition of prefrontal activity critically constrained the selection of adaptive defensive responses in a time-dependent manner. These results reveal that the adaptive selection of active fear responses relies on a dynamic process of information linking threats with defensive actions unfolding within prefrontal networks.
Sustainability in Space and on Earth: Research Initiatives of the Space Enabled Research Group
The presentation will present the work of the Space Enabled Research Group at the MIT Media Lab. The mission of the Space Enabled Research Group is to advance justice in Earth’s complex systems using designs enabled by space. Our message is that six types of space technology are supporting societal needs, as defined by the United Nations Sustainable Development Goals. These six technologies include satellite earth observation, satellite communication, satellite positioning, microgravity research, technology transfer, and the infrastructure related to space research and education. While much good work has been done, barriers remain that limit the application of space technology as a tool for sustainable development. The Space Enabled Research Group works to increase the opportunities to apply space technology in support of the Sustainable Development Goals and to support space sustainability. Our research applies six methods, including design thinking, art, social science, complex systems, satellite engineering and data science. We pursue our work by collaborating with development leaders who represent multilateral organizations, national and local governments, non-profits and entrepreneurial firms to identify opportunities to apply space technology in their work. We strive to enable a more just future in which every community can easily and affordably apply space technology. The work toward our mission covers three themes: 1) Research to apply existing space technology to support the United Nations Sustainable Development Goals; 2) Research to design space systems that are accessible and sustainable; and 3) Research to study the relationship between technology design and justice. The presentation will give examples of research projects within each of these themes.
Ex vivo gene therapy for epilepsy. Seizure-suppressant and neuroprotective effects of encapsulated GDNF-producing cells
A variety of pharmacological treatments exist for patients suffering from focal seizures, but systemically administered drugs offer only symptomatic relief and frequently cause unwanted side effects. Moreover, available drugs are ineffective in one third of the patients. Thus, developing more targeted and effective treatment strategies is highly warranted. Neurotrophic factors are candidates for treating epilepsy, but their development has been hampered by difficulties in achieving stable and targeted delivery of efficacious concentrations within the brain. We have developed an implantable cell encapsulation system that delivers high and consistent levels of neurotrophic molecules directly to a specific brain region. The potential of this approach has been tested by delivering glial cell line-derived neurotrophic factor (GDNF) to the hippocampus of epileptic rats. In vivo studies demonstrated that these intrahippocampal implants continue to secrete GDNF and produce high hippocampal GDNF tissue levels in a long-lasting manner. Identical implants rapidly and greatly reduced seizure frequency in the pilocarpine model. This effect increased in magnitude over 3 months, ultimately leading to a reduction of spontaneous seizures by more than 90%. Importantly, these effects were accompanied by improvements in cognition and anxiety, and by the normalization of many histological alterations that are associated with chronic epilepsy. In addition, the antiseizure effect persisted even after device removal. Finally, by establishing a unilateral epileptic focus using the intrahippocampal kainate model, we found that delivery of GDNF exclusively within the focus suppressed already established spontaneous recurrent seizures. Together, these results support the concept that the implantation of encapsulated GDNF-secreting cells can deliver GDNF in a sustained, targeted, and efficacious manner. These findings may form the basis for clinical translation of this approach.
Neural correlates of belief updates in the mouse secondary motor cortex
To make judgments, brain must be able to infer the state of the world based on often incomplete and ambiguous evidence. To probe neural circuits that perform the computations underlying such judgments, we developed a behavioral task for mice that required them to detect sustained increases in the speed of a continuously varying visual stimulus. In this talk, I will present evidence that the responses of secondary motor cortex to stimulus fluctuations in this task are consistent with updates of the animal’s state of belief that the change has occurred. These results establish a framework for mechanistic inquiries into neural circuits underlying inference during perceptual decision-making.
Plasticity in hypothalamic circuits for oxytocin release
Mammalian babies are “sensory traps” for parents. Various sensory cues from the newborn are tremendously efficient in triggering parental responses in caregivers. We recently showed that core aspects of maternal behavior such as pup retrieval in response to infant vocalizations rely on active learning of auditory cues from pups facilitated by the neurohormone oxytocin (OT). Release of OT from the hypothalamus might thus help induce recognition of different infant cues but it is unknown what sensory stimuli can activate OT neurons. I performed unprecedented in vivo whole-cell and cell-attached recordings from optically-identified OT neurons in awake dams. I found that OT neurons, but not other hypothalamic cells, increased their firing rate after playback of pup distress vocalizations. Using anatomical tracing approaches and channelrhodopsin-assisted circuit mapping, I identified the projections and brain areas (including inferior colliculus, auditory cortex, and posterior intralaminar thalamus) relaying auditory information about social sounds to OT neurons. In hypothalamic brain slices, when optogenetically stimulating thalamic afferences to mimic high-frequency thalamic discharge, observed in vivo during pup calls playback, I found that thalamic activity led to long-term depression of synaptic inhibition in OT neurons. This was mediated by postsynaptic NMDARs-induced internalization of GABAARs. Therefore, persistent activation of OT neurons following pup calls in vivo is likely mediated by disinhibition. This gain modulation of OT neurons by infant cries, may be important for sustaining motivation. Using a genetically-encoded OT sensor, I demonstrated that pup calls were efficient in triggering OT release in downstream motivational areas. When thalamus projections to hypothalamus were inhibited with chemogenetics, dams exhibited longer latencies to retrieve crying pups, suggesting that the thalamus-hypothalamus noncanonical auditory pathway may be a specific circuit for the detection of social sounds, important for disinhibiting OT neurons, gating OT release in downstream brain areas, and speeding up maternal behavior.
Building a synthetic cell: Understanding the clock design and function
Clock networks containing the same central architectures may vary drastically in their potential to oscillate, raising the question of what controls robustness, one of the essential functions of an oscillator. We computationally generate an atlas of oscillators and found that, while core topologies are critical for oscillations, local structures substantially modulate the degree of robustness. Strikingly, two local structures, incoherent and coherent inputs, can modify a core topology to promote and attenuate its robustness, additively. The findings underscore the importance of local modifications to the performance of the whole network. It may explain why auxiliary structures not required for oscillations are evolutionary conserved. We also extend this computational framework to search hidden network motifs for other clock functions, such as tunability that relates to the capabilities of a clock to adjust timing to external cues. Experimentally, we developed an artificial cell system in water-in-oil microemulsions, within which we reconstitute mitotic cell cycles that can perform self-sustained oscillations for 30 to 40 cycles over multiple days. The oscillation profiles, such as period, amplitude, and shape, can be quantitatively varied with the concentrations of clock regulators, energy levels, droplet sizes, and circuit design. Such innate flexibility makes it crucial to studying clock functions of tunability and stochasticity at the single-cell level. Combined with a pressure-driven multi-channel tuning setup and long-term time-lapse fluorescence microscopy, this system enables a high-throughput exploration in multi-dimension continuous parameter space and single-cell analysis of the clock dynamics and functions. We integrate this experimental platform with mathematical modeling to elucidate the topology-function relation of biological clocks. With FRET and optogenetics, we also investigate spatiotemporal cell-cycle dynamics in both homogeneous and heterogeneous microenvironments by reconstructing subcellular compartments.
Rapid State Changes Account for Apparent Brain and Behavior Variability
Neural and behavioral responses to sensory stimuli are notoriously variable from trial to trial. Does this mean the brain is inherently noisy or that we don’t completely understand the nature of the brain and behavior? Here we monitor the state of activity of the animal through videography of the face, including pupil and whisker movements, as well as walking, while also monitoring the ability of the animal to perform a difficult auditory or visual task. We find that the state of the animal is continuously changing and is never stable. The animal is constantly becoming more or less activated (aroused) on a second and subsecond scale. These changes in state are reflected in all of the neural systems we have measured, including cortical, thalamic, and neuromodulatory activity. Rapid changes in cortical activity are highly correlated with changes in neural responses to sensory stimuli and the ability of the animal to perform auditory or visual detection tasks. On the intracellular level, these changes in forebrain activity are associated with large changes in neuronal membrane potential and the nature of network activity (e.g. from slow rhythm generation to sustained activation and depolarization). Monitoring cholinergic and noradrenergic axonal activity reveals widespread correlations across the cortex. However, we suggest that a significant component of these rapid state changes arise from glutamatergic pathways (e.g. corticocortical or thalamocortical), owing to their rapidity. Understanding the neural mechanisms of state-dependent variations in brain and behavior promises to significantly “denoise” our understanding of the brain.
Sex, guts and babies: the plasticity of the adult intestine and its neurons
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 ecology of collective behaviour
Collective behaviour operates without central control, through interactions among individuals. The collective behaviour of ant colonies is based on simple olfactory interactions. Ant species differ enormously in the algorithms that regulate collective behaviour, reflecting diversity in ecology. I will contrast two species in very different ecological situations. Harvester ant colonies in the desert, where water is scarce but conditions are stable, regulate foraging to conserve water. Response to positive feedback from olfactory interactions depends on the risk of water loss, mediated by dopamine neurophysiology. For arboreal turtle ants in the tropical forest, life is easy but unpredictable, and a highly modular system uses negative feedback to sustain activity. In all natural systems, from ant colonies to brains, collective behaviour evolves in relation with changing conditions. Similar dynamics in environmental conditions may lead to the evolution of similar processes to regulate collective behaviour.
Flexible motor sequencing through thalamic control of cortical dynamics
The mechanisms by which neural circuits generate an extensible library of motor motifs and flexibly string them into arbitrary sequences are unclear. We developed a model in which inhibitory basal ganglia output neurons project to thalamic units that are themselves bidirectionally connected to a recurrent cortical network. During movement sequences, electrophysiological recordings of basal ganglia output neurons show sustained activity patterns that switch at the boundaries between motifs. Thus, we model these inhibitory patterns as silencing some thalamic neurons while leaving others disinhibited and free to interact with cortex during specific motifs. We show that a small number of disinhibited thalamic neurons can control cortical dynamics to generate specific motor output in a noise robust way. If the thalamic units associated with each motif are segregated, many motor outputs can be learned without interference and then combined in arbitrary orders for the flexible production of long and complex motor sequences.