N/A

FAA™ VaultMesh Brand Deployment — Developer Required. We are building a mass-scale HTML deployment system for a sovereign economic network called FAA™. The system includes over 80 brands under the Housing & Infrastructure sector, with 4 subnodes per brand and 12 HTML pages per node — totaling 3,840 FAA-compliant web pages. Your Role: You will be responsible for: Setting up a Cloudflare Workers deployment pipeline, Building out 12 FAA-standard pages per brand subnode (index.html, dashboard.html, pricing.html, etc.), Maintaining the FAA.zone public structure, especially under /sectors/housing/..., Integrating with existing admin panels at /admin/admin-portal.html and /admin/admin-portal-approval.html, Ensuring all files match Shapely visual styling (we will provide templates).

Functional Imaging of the Human Brain: A Window into the Organization of the Human Mind

Neural control of internal affective states”

“Development and application of gaze control models for active perception”

Gaze shifts in humans serve to direct high-resolution vision provided by the fovea towards areas in the environment. Gaze can be considered a proxy for attention or indicator of the relative importance of different parts of the environment. In this talk, we discuss the development of generative models of human gaze in response to visual input. We discuss how such models can be learned, both using supervised learning and using implicit feedback as an agent interacts with the environment, the latter being more plausible in biological agents. We also discuss two ways such models can be used. First, they can be used to improve the performance of artificial autonomous systems, in applications such as autonomous navigation. Second, because these models are contingent on the human’s task, goals, and/or state in the context of the environment, observations of gaze can be used to infer information about user intent. This information can be used to improve human-machine and human robot interaction, by making interfaces more anticipative. We discuss example applications in gaze-typing, robotic tele-operation and human-robot interaction.

Open Hardware Microfluidics

What’s the point of having scientific and technological innovations when only a few can benefit from them? How can we make science more inclusive? Those questions are always in the back of my mind when we perform research in our laboratory, and we have a strong focus on the scientific accessibility of our developed methods from microfabrication to sensor development.

Multisensory perception in the metaverse

Pharmacological exploitation of neurotrophins and their receptors to develop novel therapeutic approaches against neurodegenerative diseases and brain trauma

Neurotrophins (NGF, BDNF, NT-3) are endogenous growth factors that exert neuroprotective effects by preventing neuronal death and promoting neurogenesis. They act by binding to their respective high-affinity, pro-survival receptors TrkA, TrkB or TrkC, as well as to p75NTR death receptor. While these molecules have been shown to significantly slow or prevent neurodegeneration, their reduced bioavailability and inability to penetrate the blood-brain-barrier limit their use as potential therapeutics. To bypass these limitations, our research team has developed and patented small-sized, lipophilic compounds which selectively resemble neurotrophins’ effects, presenting preferable pharmacological properties and promoting neuroprotection and repair against neurodegeneration. In addition, the combination of these molecules with 3D cultured human neuronal cells, and their targeted delivery in the brain ventricles through soft robotic systems, could offer novel therapeutic approaches against neurodegenerative diseases and brain trauma.

Brain Emulation Challenge Workshop

Brain Emulation Challenge workshop will tackle cutting-edge topics such as ground-truthing for validation, leveraging artificial datasets generated from virtual brain tissue, and the transformative potential of virtual brain platforms, such as applied to the forthcoming Brain Emulation Challenge.

Analyzing Network-Level Brain Processing and Plasticity Using Molecular Neuroimaging

Behavior and cognition depend on the integrated action of neural structures and populations distributed throughout the brain. We recently developed a set of molecular imaging tools that enable multiregional processing and plasticity in neural networks to be studied at a brain-wide scale in rodents and nonhuman primates. Here we will describe how a novel genetically encoded activity reporter enables information flow in virally labeled neural circuitry to be monitored by fMRI. Using the reporter to perform functional imaging of synaptically defined neural populations in the rat somatosensory system, we show how activity is transformed within brain regions to yield characteristics specific to distinct output projections. We also show how this approach enables regional activity to be modeled in terms of inputs, in a paradigm that we are extending to address circuit-level origins of functional specialization in marmoset brains. In the second part of the talk, we will discuss how another genetic tool for MRI enables systematic studies of the relationship between anatomical and functional connectivity in the mouse brain. We show that variations in physical and functional connectivity can be dissociated both across individual subjects and over experience. We also use the tool to examine brain-wide relationships between plasticity and activity during an opioid treatment. This work demonstrates the possibility of studying diverse brain-wide processing phenomena using molecular neuroimaging.

Gene regulatory mechanisms of neocortex development and evolution

The neocortex is considered to be the seat of higher cognitive functions in humans. During its evolution, most notably in humans, the neocortex has undergone considerable expansion, which is reflected by an increase in the number of neurons. Neocortical neurons are generated during development by neural stem and progenitor cells. Epigenetic mechanisms play a pivotal role in orchestrating the behaviour of stem cells during development. We are interested in the mechanisms that regulate gene expression in neural stem cells, which have implications for our understanding of neocortex development and evolution, neural stem cell regulation and neurodevelopmental disorders.

“Open Raman Microscopy (ORM): A modular Raman spectroscopy setup with an open-source controller”

Raman spectroscopy is a powerful technique for identifying chemical species by probing their vibrational energy levels, offering exceptional specificity with a relatively simple setup involving a laser source, spectrometer, and microscope/probe. However, the high cost of Raman systems lacking modularity often limits exploratory research hindering broader adoption. To address the need for an affordable, modular microscopy platform for multimodal imaging, we present a customizable confocal Raman spectroscopy setup alongside an open-source acquisition software, ORM (Open Raman Microscopy) Controller, developed in Python. This solution bridges the gap between expensive commercial systems and complex, custom-built setups used by specialist research groups. In this presentation, we will cover the components of the setup, the design rationale, assembly methods, limitations, and its modular potential for expanding functionality. Additionally, we will demonstrate ORM’s capabilities for instrument control, 2D and 3D Raman mapping, region-of-interest selection, and its adaptability to various instrument configurations. We will conclude by showcasing practical applications of this setup across different research fields.

Decision and Behavior

This webinar addressed computational perspectives on how animals and humans make decisions, spanning normative, descriptive, and mechanistic models. Sam Gershman (Harvard) presented a capacity-limited reinforcement learning framework in which policies are compressed under an information bottleneck constraint. This approach predicts pervasive perseveration, stimulus‐independent “default” actions, and trade-offs between complexity and reward. Such policy compression reconciles observed action stochasticity and response time patterns with an optimal balance between learning capacity and performance. Jonathan Pillow (Princeton) discussed flexible descriptive models for tracking time-varying policies in animals. He introduced dynamic Generalized Linear Models (Sidetrack) and hidden Markov models (GLM-HMMs) that capture day-to-day and trial-to-trial fluctuations in choice behavior, including abrupt switches between “engaged” and “disengaged” states. These models provide new insights into how animals’ strategies evolve under learning. Finally, Kenji Doya (OIST) highlighted the importance of unifying reinforcement learning with Bayesian inference, exploring how cortical-basal ganglia networks might implement model-based and model-free strategies. He also described Japan’s Brain/MINDS 2.0 and Digital Brain initiatives, aiming to integrate multimodal data and computational principles into cohesive “digital brains.”

Trackoscope: A low-cost, open, autonomous tracking microscope for long-term observations of microscale organisms

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.

Charting the fetal development of neural complexity

A novel tool to combat stress (-hormone receptor) signatures

Immature brain insults and possible effects on cholinergic system neuroplasticity

Metabolic Remodelling in the Developing Forebrain in Health and Disease

Little is known about the critical metabolic changes that neural cells have to undergo during development and how temporary shifts in this program can influence brain circuitries and behavior. Motivated by the identification of autism-associated mutations in SLC7A5, a transporter for metabolically essential large neutral amino acids (LNAAs), we utilized metabolomic profiling to investigate the metabolic states of the cerebral cortex across various developmental stages. Our findings reveal significant metabolic restructuring occurring in the forebrain throughout development, with specific groups of metabolites exhibiting stage-specific changes. Through the manipulation of Slc7a5 expression in neural cells, we discovered an interconnected relationship between the metabolism of LNAAs and lipids within the cortex. Neuronal deletion of Slc7a5 influences the postnatal metabolic state, resulting in a shift in lipid metabolism and a cell-type-specific modification in neuronal activity patterns. This ultimately gives rise to enduring circuit dysfunction.

Computational and mathematical approaches to myopigenesis

Myopia is predicted to affect 50% of all people worldwide by 2050, and is a risk factor for significant, potentially blinding ocular pathologies, such as retinal detachment and glaucoma. Thus, there is significant motivation to better understand the process of myopigenesis and to develop effective anti-myopigenic treatments. In nearly all cases of human myopia, scleral remodeling is an obligate step in the axial elongation that characterizes the condition. Here I will describe the development of a biomechanical assay based on transient unconfined compression of scleral samples. By treating the scleral as a poroelastic material, one can determine scleral biomechanical properties from extremely small samples, such as obtained from the mouse eye. These properties provide proxy measures of scleral remodeling, and have allowed us to identify all-trans retinoic acid (atRA) as a myopigenic stimulus in mice. I will also describe nascent collaborative work on modeling the transport of atRA in the eye.

Synaptic mechanisms of pattern completion in the hippocampal CA3 region

Freeze or flee ? New insights from rodent models of autism

Individuals afflicted with certain types of autism spectrum disorder often exhibit impaired cognitive function alongside enhanced emotional symptoms and mood lability. However, current understanding of the pathogenesis of autism and intellectual disabilities is based primarily on studies in the hippocampus and cortex, brain areas involved in cognitive function. But, these disorders are also associated with strong emotional symptoms, which are likely to involve changes in the amygdala and other brain areas. In this talk I will highlight these issues by presenting analyses in rat models of ASD/ID lacking Nlgn3 and Frm1 (causing Fragile X Syndrome). In addition to identifying new circuit and cellular alterations underlying divergent patterns of fear expression, these findings also suggest novel therapeutic strategies.

How a fungus overcomes the defence of C. elegans

Children-Agent Interaction For Assessment and Rehabilitation: From Linguistic Skills To Mental Well-being

Socially Assistive Robots (SARs) have shown great potential to help children in therapeutic and healthcare contexts. SARs have been used for companionship, learning enhancement, social and communication skills rehabilitation for children with special needs (e.g., autism), and mood improvement. Robots can be used as novel tools to assess and rehabilitate children’s communication skills and mental well-being by providing affordable and accessible therapeutic and mental health services. In this talk, I will present the various studies I have conducted during my PhD and at the Cambridge Affective Intelligence and Robotics Lab to explore how robots can help assess and rehabilitate children’s communication skills and mental well-being. More specifically, I will provide both quantitative and qualitative results and findings from (i) an exploratory study with children with autism and global developmental disorders to investigate the use of intelligent personal assistants in therapy; (ii) an empirical study involving children with and without language disorders interacting with a physical robot, a virtual agent, and a human counterpart to assess their linguistic skills; (iii) an 8-week longitudinal study involving children with autism and language disorders who interacted either with a physical or a virtual robot to rehabilitate their linguistic skills; and (iv) an empirical study to aid the assessment of mental well-being in children. These findings can inform and help the child-robot interaction community design and develop new adaptive robots to help assess and rehabilitate linguistic skills and mental well-being in children.

Minute-scale periodic sequences in medial entorhinal cortex

The medial entorhinal cortex (MEC) hosts many of the brain’s circuit elements for spatial navigation and episodic memory, operations that require neural activity to be organized across long durations of experience. While location is known to be encoded by a plethora of spatially tuned cell types in this brain region, little is known about how the activity of entorhinal cells is tied together over time. Among the brain’s most powerful mechanisms for neural coordination are network oscillations, which dynamically synchronize neural activity across circuit elements. In MEC, theta and gamma oscillations provide temporal structure to the neural population activity at subsecond time scales. It remains an open question, however, whether similarly coordination occurs in MEC at behavioural time scales, in the second-to-minute regime. In this talk I will show that MEC activity can be organized into a minute-scale oscillation that entrains nearly the entire cell population, with periods ranging from 10 to 100 seconds. Throughout this ultraslow oscillation, neural activity progresses in periodic and stereotyped sequences. The oscillation sometimes advances uninterruptedly for tens of minutes, transcending epochs of locomotion and immobility. Similar oscillatory sequences were not observed in neighboring parasubiculum or in visual cortex. The ultraslow periodic sequences in MEC may have the potential to couple its neurons and circuits across extended time scales and to serve as a scaffold for processes that unfold at behavioural time scales.

Meta-learning functional plasticity rules in neural networks

Synaptic plasticity is known to be a key player in the brain’s life-long learning abilities. However, due to experimental limitations, the nature of the local changes at individual synapses and their link with emerging network-level computations remain unclear. I will present a numerical, meta-learning approach to deduce plasticity rules from either neuronal activity data and/or prior knowledge about the network's computation. I will first show how to recover known rules, given a human-designed loss function in rate networks, or directly from data, using an adversarial approach. Then I will present how to scale-up this approach to recurrent spiking networks using simulation-based inference.

The medial prefrontal cortex replays generalized sequences

Whilst spatial navigation is a function ascribed to the hippocampus, flexibly adapting to a change in rule depends on the medial prefrontal cortex (mPFC). Single-units were recorded from the hippocampus and mPFC of rats shifting between a spatially- and cue-guided rule on a plus-maze. The mPFC population coded for the relative position between start and goal arm. During awake immobility periods, the mPFC replayed organized sequences of generalized positions which positively correlated with rule-switching performance. Conversely, hippocampal replay negatively correlated with performance and occurred independently of mPFC replay. Sequential replay in the hippocampus and mPFC may thus serve different functions.

Probabilistic simplicity in the study of sensory systems

Taking the pulse of ageing: the role of cerebrovascular risk factors in ageing and dementia

Cerebrovascular support is critical for healthy cognitive ageing. Reduced cerebral blood flow in ageing is caused, among other things, by hypertension, arteriosclerosis (i.e. stiffening of the arteries) and plaque formation. Arterial stiffness is predictive of cognitive decline, is a critical risk factor for cerebrovascular accidents, and has been linked to heightened risks for Alzheimer’s Disease and other forms of dementia. The elasticity of cerebral arteries is influenced by lifestyle factors, including cardiorespiratory fitness. Monica will discuss data obtained in their laboratory with new noninvasive measures of cerebrovascular health (pulse-DOT, a diffuse optical tomographic method for studying cerebral arteriosclerosis), in conjunction with structural and functional brain measures and cognitive assessments. These findings support a model in which localised changes in arteriosclerosis lead to specific profiles of structural, functional, and cognitive declines, paving a way to individualised interventions.

Why dendrites matter for biological and artificial circuits

Brian2CUDA: Generating Efficient CUDA Code for Spiking Neural Networks

Graphics processing units (GPUs) are widely available and have been used with great success to accelerate scientific computing in the last decade. These advances, however, are often not available to researchers interested in simulating spiking neural networks, but lacking the technical knowledge to write the necessary low-level code. Writing low-level code is not necessary when using the popular Brian simulator, which provides a framework to generate efficient CPU code from high-level model definitions in Python. Here, we present Brian2CUDA, an open-source software that extends the Brian simulator with a GPU backend. Our implementation generates efficient code for the numerical integration of neuronal states and for the propagation of synaptic events on GPUs, making use of their massively parallel arithmetic capabilities. We benchmark the performance improvements of our software for several model types and find that it can accelerate simulations by up to three orders of magnitude compared to Brian’s CPU backend. Currently, Brian2CUDA is the only package that supports Brian’s full feature set on GPUs, including arbitrary neuron and synapse models, plasticity rules, and heterogeneous delays. When comparing its performance with Brian2GeNN, another GPU-based backend for the Brian simulator with fewer features, we find that Brian2CUDA gives comparable speedups, while being typically slower for small and faster for large networks. By combining the flexibility of the Brian simulator with the simulation speed of GPUs, Brian2CUDA enables researchers to efficiently simulate spiking neural networks with minimal effort and thereby makes the advancements of GPU computing available to a larger audience of neuroscientists.

INC Day 2022: Neuroethics

Organized by the INC in partnership with the BioMedical Engineering Paris international Master’s program and the NeuroParis Master’s programs and is supported by the Faculty of Sciences of Paris Cité University and the Graduate school Psychological science.

AI-assisted language learning: Assessing learners who memorize and reason by analogy

Vocabulary learning applications like Duolingo have millions of users around the world, but yet are based on very simple heuristics to choose teaching material to provide to their users. In this presentation, we will discuss the possibility to develop more advanced artificial teachers, which would be based on modeling of the learner’s inner characteristics. In the case of teaching vocabulary, understanding how the learner memorizes is enough. When it comes to picking grammar exercises, it becomes essential to assess how the learner reasons, in particular by analogy. This second application will illustrate how analogical and case-based reasoning can be employed in an alternative way in education: not as the teaching algorithm, but as a part of the learner’s model.

September webinar

Time as its own representation? Exploring a link between timing of cognition and time perception

The way we represent and perceive time has crucial implications for studying temporality in conscious experience. Contrasting positions posit that temporal information is separately abstracted out like any other perceptual property, or that time is represented through representations having temporal properties themselves. To add to this debate, we investigated alterations in felt time in conditions where only conscious visual experience is altered while a bistable figure remains physically unchanged. In this talk, I will discuss two studies that we have done in relation to answering this question. In study 1, we investigated whether perceptual switches in fixed intervals altered felt time. In three experiments we showed that a break in visual experience (via a perceptual switch) also leads to a break in felt time. In study 2, we are currently looking at figure-ground perception in ambigous displays. Here, in experiment 1 we show that differences in flicker frequencies on ambigous regions can induce figure-ground segregation. To see if a reverse complementarity exists for felt time, we ask participants to view ambigous regions as figure/ground and show that they have different temporal resolutions for the same region based on whether it is seen as figure or background. Overall, the two studies provide evidence for temporal mirroring and isomorphism in visual experience, arguing for a link between the timing of experience and time perception.

An open-source miniature two-photon microscope for large-scale calcium imaging in freely moving mice

Due to the unsuitability of benchtop imaging for tasks that require unrestrained movement, investigators have tried, for almost two decades, to develop miniature 2P microscopes-2P miniscopes–that can be carried on the head of freely moving animals. In this talk, I would first briefly review the development history of this technique, and then report our latest progress on developing the new generation of 2P miniscopes, MINI2P, that overcomes the limits of previous versions by both meeting requirements for fatigue-free exploratory behavior during extended recording periods and satisfying demands for further increasing the cell yield by an order of magnitude, to thousands of neurons. The performance and reliability of MINI2P are validated by recordings of spatially tuned neurons in three brain regions and in three behavioral assays. All information about MINI2P is open access, with instruction videos, code, and manuals on public repositories, and workshops will be organized to help new users getting started. MINI2P permits large-scale and high-resolution calcium imaging in freely-moving mice, and opens the door to investigating brain functions during unconstrained natural behaviors.

Learning static and dynamic mappings with local self-supervised plasticity

Animals exhibit remarkable learning capabilities with little direct supervision. Likewise, self-supervised learning is an emergent paradigm in artificial intelligence, closing the performance gap to supervised learning. In the context of biology, self-supervised learning corresponds to a setting where one sense or specific stimulus may serve as a supervisory signal for another. After learning, the latter can be used to predict the former. On the implementation level, it has been demonstrated that such predictive learning can occur at the single neuron level, in compartmentalized neurons that separate and associate information from different streams. We demonstrate the power such self-supervised learning over unsupervised (Hebb-like) learning rules, which depend heavily on stimulus statistics, in two examples: First, in the context of animal navigation where predictive learning can associate internal self-motion information always available to the animal with external visual landmark information, leading to accurate path-integration in the dark. We focus on the well-characterized fly head direction system and show that our setting learns a connectivity strikingly similar to the one reported in experiments. The mature network is a quasi-continuous attractor and reproduces key experiments in which optogenetic stimulation controls the internal representation of heading, and where the network remaps to integrate with different gains. Second, we show that incorporating global gating by reward prediction errors allows the same setting to learn conditioning at the neuronal level with mixed selectivity. At its core, conditioning entails associating a neural activity pattern induced by an unconditioned stimulus (US) with the pattern arising in response to a conditioned stimulus (CS). Solving the generic problem of pattern-to-pattern associations naturally leads to emergent cognitive phenomena like blocking, overshadowing, saliency effects, extinction, interstimulus interval effects etc. Surprisingly, we find that the same network offers a reductionist mechanism for causal inference by resolving the post hoc, ergo propter hoc fallacy.

The role of astroglia-neuron interactions in generation and spread of seizures

Astroglia-neuron interactions are involved in multiple processes, regulating development, excitability and connectivity of neural circuits. Accumulating number of evidences highlight a direct connection between aberrant astroglial genetics and physiology in various forms of epilepsies. Using zebrafish seizure models, we showed that neurons and astroglia follow different spatiotemporal dynamics during transitions from pre-ictal to ictal activity. We observed that during pre-ictal period neurons exhibit local synchrony and low level of activity, whereas astroglia exhibit global synchrony and high-level of calcium signals that are anti correlated with neural activity. Instead, generalized seizures are marked by a massive release of astroglial glutamate release as well as a drastic increase of astroglia and neuronal activity and synchrony across the entire brain. Knocking out astroglial glutamate transporters leads to recurrent spontaneous generalized seizures accompanied with massive astroglial glutamate release. We are currently using a combination of genetic and pharmacological approaches to perturb astroglial glutamate signalling and astroglial gap junctions to further investigate their role in generation and spreading of epileptic seizures across the brain.

Imperial Neurotechnology 2022 - Annual Research Symposium

A diverse mix of neurotechnology talks and posters from researchers at Imperial and beyond. Visit our event page to find out more. The event is in-person but talk sessions will be broadcast via Teams.

Social immunity in ants: disease defense of the colony

Social insects fight disease as a collective. Their colonies are protected against disease by the combination of the individual immune defenses of all colony members and their jointly performed nest- and colony-hygiene. This social immunity is achieved by cooperative behaviors to reduce pathogen load of the colony and to prevent transmission along the social interaction networks of colony members. Individual and social immunity interact: performance of sanitary care can affect future disease susceptibility, yet also vice versa, individuals differing in susceptibility adjust their sanitary care performance to their individual risk of infection. I present the integrated approach we use to understand how colony protection arises from the individual and collective actions of colony members and how it affects pathogen communities and hence disease ecology.

Light-induced moderations in vitality and sleep in the field

Retinal light exposure is modulated by our behavior, and light exposure patterns show strong variations within and between persons. Yet, most laboratory studies investigated influences of constant lighting settings on human daytime functioning and sleep. In this presentation, I will discuss a series of studies investigating light-induced moderations in sleepiness, vitality and sleep, with a strong focus on the temporal dynamics in these effects, and the bi-directional relation between persons' light profiles and their behavior.

Let's talk about failure!

Try again. Fail again. Fail better. (Samuel Beckett)

From a by-stander to an influencer: How microglia adapt to altered environments and influence neuronal activity

Microglia, traditionally classified as immune-responsive, adjust synaptic connections during development and disease. However, their role in the adult nervous system has been mostly diminished to an observer. In my research group, we are interested in how microglia are involved in establishing and maintaining accurate neuronal circuit function in the retina and in the visual cortex. In my talk, I will introduce our strategies how to decipher the microglia’s functional identity and how this information guided us to microglia enabled extracellular matrix remodeling and reinstatment of juvenile-like plasticity in the adult brain.

Remembering Immunity, Central regulation of peripheral immune processes

Thoughts and emotions can impact physiology. This connection is evident by the emergence of disease following stress, psychosomatic disorders, or recovery in response to placebo treatment. Nevertheless, this fundamental aspect of physiology remains largely unexplored. In this talk, I will focus on the brain’s involvement in regulating the peripheral immune response and explore the question of how the brain evaluates and represents the state of the immune system it regulates.

Network resonance: a framework for dissecting feedback and frequency filtering mechanisms in neuronal systems

Resonance is defined as a maximal amplification of the response of a system to periodic inputs in a limited, intermediate input frequency band. Resonance may serve to optimize inter-neuronal communication, and has been observed at multiple levels of neuronal organization including membrane potential fluctuations, single neuron spiking, postsynaptic potentials, and neuronal networks. However, it is unknown how resonance observed at one level of neuronal organization (e.g., network) depends on the properties of the constituting building blocks, and whether, and if yes how, it affects the resonant and oscillatory properties upstream. One difficulty is the absence of a conceptual framework that facilitates the interrogation of resonant neuronal circuits and organizes the mechanistic investigation of network resonance in terms of the circuit components, across levels of organization. We address these issues by discussing a number of representative case studies. The dynamic mechanisms responsible for the generation of resonance involve disparate processes, including negative feedback effects, history-dependence, spiking discretization combined with subthreshold passive dynamics, combinations of these, and resonance inheritance from lower levels of organization. The band-pass filters associated with the observed resonances are generated by primarily nonlinear interactions of low- and high-pass filters. We identify these filters (and interactions) and we argue that these are the constitutive building blocks of a resonance framework. Finally, we discuss alternative frameworks and we show that different types of models (e.g., spiking neural networks and rate models) can show the same type of resonance by qualitative different mechanisms.

Making a Mesh of Things: Using Network Models to Understand the Mechanics of Heterogeneous Tissues

Networks of stiff biopolymers are an omnipresent structural motif in cells and tissues. A prominent modeling framework for describing biopolymer network mechanics is rigidity percolation theory. This theory describes model networks as nodes joined by randomly placed, springlike bonds. Increasing the amount of bonds in a network results in an abrupt, dramatic increase in elastic moduli above a certain threshold – an example of a mechanical phase transition. While homogeneous networks are well studied, many tissues are made of disparate components and exhibit spatial fluctuations in the concentrations of their constituents. In this talk, I will first discuss recent work in which we explained the structural basis of the shear mechanics of healthy and chemically degraded cartilage by coupling a rigidity percolation framework with a background gel. Our model takes into account collagen concentration, as well as the concentration of peptidoglycans in the surrounding polyelectrolyte gel, to produce a structureproperty relationship that describes the shear mechanics of both sound and diseased cartilage. I will next discuss the introduction of structural correlation in constructing networks, such that sparse and dense patches emerge. I find moderate correlation allows a network to become rigid with fewer bonds, while this benefit is partly erased by excessive correlation. We explain this phenomenon through analysis of the spatial fluctuations in strained networks’ displacement fields. Finally, I will address our work’s implications for non-invasive diagnosis of pathology, as well as rational design of prostheses and novel soft materials.

Designing a transmodal technology to feel sound through touch: The multichannel vibrotactile gloves

FENS Forum 2024

Exploring social hierarchies: An experimental study using RFID technology in mice

FENS Forum 2024

Investigating design parameters for improved tissue integration in brain-computer-interface technology

FENS Forum 2024

Organoid technology: A new way to model ischemic stroke

FENS Forum 2024

Three-dimensional structural analysis of GABAergic neurons in the mouse claustrum using tissue-clearing technology

FENS Forum 2024

Unravelling the role of prefrontal α7 nicotinic acetylcholine receptors in inhibitory control in physiological and pathological contexts: A behavioral investigation using touchscreen technology

FENS Forum 2024