Drosophila olfactory sensory hairs ("sensilla") typically house two olfactory receptor neurons (ORNs) which can laterally inhibit each other via electrical ("ephaptic") coupling. ORN pairing is highly stereotyped and genetically determined. Thus, olfactory signals arriving in the Antennal Lobe (AL) have been pre-processed by a fixed and shallow network at the periphery. To uncover the functional significance of this organization, we developed a nonlinear phenomenological model of asymmetrically coupled ORNs responding to odor mixture stimuli. We derived an analytical solution to the ORNs’ dynamics, which shows that the peripheral network can extract the valence of specific odor mixtures via transient amplification. Our model predicts that for efficient read-out of the amplified valence signal there must exist specific patterns of downstream connectivity that reflect the organization at the periphery. Analysis of AL→Lateral Horn (LH) fly connectomic data reveals evidence directly supporting this prediction. We further studied the effect of ephaptic coupling on olfactory processing in the AL→Mushroom Body (MB) pathway. We show that stereotyped ephaptic interactions between ORNs lead to a clustered odor representation of glomerular responses. Such clustering in the AL is an essential assumption of theoretical studies on odor recognition in the MB. Together our work shows that preprocessing of olfactory stimuli by a fixed and shallow network increases sensitivity to specific odor mixtures, and aids in the learning of novel olfactory stimuli. Work led by Palka Puri, in collaboration with Chih-Ying Su and Shiuan-Tze Wu.

Evolutionarily, the expansion of the human neocortex accounts for many of the unique cognitive abilities of humans. This expansion appears to reflect the increased proliferative potential of basal progenitors (BPs) in mammalian evolution. Further cortical progenitors generate both glutamatergic excitatory neurons (ENs) and GABAergic inhibitory interneurons (INs) in human cortex, whereas they produce exclusively ENs in rodents. The increased proliferative capacity and neuronal subtype generation of cortical progenitors in mammalian evolution may have evolved through epigenetic alterations. However, whether or how the epigenome in cortical progenitors differs between humans and other species is unknown. Here, we report that histone H3 acetylation is a key epigenetic regulation in BP profiling of sorted BPs, we show that H3K9 acetylation is low in murine BPs and high in amplification, neuronal subtype generation and cortical expansion. Through epigenetic profiling of sorted BPs, we show that H3K9 acetylation is low in murine BPs and high in human BPs. Elevated H3K9ac preferentially increases BP proliferation, increasing the size and folding of the normally smooth mouse neocortex. Furthermore, we found that the elevated H3 acetylation activates expression of IN genes in in developing mouse cortex and promote proliferation of IN progenitor-like cells in cortex of Pax6 mutant mouse models. Mechanistically, H3K9ac drives the BP amplification and proliferation of these IN progenitor-like cells by increasing expression of the evolutionarily regulated gene, TRNP1. Our findings demonstrate a previously unknown mechanism that controls neocortex expansion and generation of neuronal subtypes. Keywords: Cortical development, neurogenesis, basal progenitors, cortical size, gyrification, excitatory neuron, inhibitory interneuron, epigenetic profiling, epigenetic regulation, H3 acetylation, H3K9ac, TRNP1, PAX6

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.

Three intimately related dimensions of the mammalian genome—linear DNA sequence, gene transcription, and 3D genome architecture—are crucial for the development of nervous systems. Changes in the linear genome (e.g., de novo mutations), transcriptome, and 3D genome structure lead to debilitating neurodevelopmental disorders, such as autism and schizophrenia. However, current technologies and data are severely limited: (1) 3D genome structures of single brain cells have not been solved; (2) little is known about the dynamics of single-cell transcriptome and 3D genome after birth; (3) true de novo mutations are extremely difficult to distinguish from false positives (DNA damage and/or amplification errors). Here, I filled in this longstanding technological and knowledge gap. I recently developed a high-resolution method—diploid chromatin conformation capture (Dip-C)—which resolved the first 3D structure of the human genome, tackling a longstanding problem dating back to the 1880s. Using Dip-C, I obtained the first 3D genome structure of a single brain cell, and created the first transcriptome and 3D genome atlas of the mouse brain during postnatal development. I found that in adults, 3D genome “structure types” delineate all major cell types, with high correlation between chromatin A/B compartments and gene expression. During development, both transcriptome and 3D genome are extensively transformed in the first month of life. In neurons, 3D genome is rewired across scales, correlated with gene expression modules, and independent of sensory experience. Finally, I examined allele-specific structure of imprinted genes, revealing local and chromosome-wide differences. More recently, I expanded my 3D genome atlas to the human and mouse cerebellum—the most consistently affected brain region in autism. I uncovered unique 3D genome rewiring throughout life, providing a structural basis for the cerebellum’s unique mode of development and aging. In addition, to accurately measure de novo mutations in a single cell, I developed a new method—multiplex end-tagging amplification of complementary strands (META-CS), which eliminates nearly all false positives by virtue of DNA complementarity. Using META-CS, I determined the true mutation spectrum of single human brain cells, free from chemical artifacts. Together, my findings uncovered an unknown dimension of neurodevelopment, and open up opportunities for new treatments for autism and other developmental disorders.

Animals depend on fast and reliable detection of novel stimuli in their environment. Neurons in multiple sensory areas respond more strongly to novel in comparison to familiar stimuli. Yet, it remains unclear which circuit, cellular, and synaptic mechanisms underlie those responses. Here, we show that spike-timing-dependent plasticity of inhibitory-to-excitatory synapses generates novelty responses in a recurrent spiking network model. Inhibitory plasticity increases the inhibition onto excitatory neurons tuned to familiar stimuli, while inhibition for novel stimuli remains low, leading to a network novelty response. The generation of novelty responses does not depend on the periodicity but rather on the distribution of presented stimuli. By including tuning of inhibitory neurons, the network further captures stimulus-specific adaptation. Finally, we suggest that disinhibition can control the amplification of novelty responses. Therefore, inhibitory plasticity provides a flexible, biologically plausible mechanism to detect the novelty of bottom-up stimuli, enabling us to make experimentally testable predictions.

Rapidly changing inputs such as visual scenes and auditory landscapes are transmitted over several synaptic interfaces and perceived with little loss of detail, but individual neurons are typically “noisy” and cortico-cortical connections are typically “weak”. To understand how information embodied in spike train is transmitted in a lossless manner, we focus on a single synaptic interface: between pyramidal cells and putative interneurons. Using arbitrary white noise patterns injected intra-cortically as photocurrents to freely-moving mice, we find that directly-activated cells exhibit precision of several milliseconds, but post-synaptic, indirectly-activated cells exhibit higher precision. Considering multiple identical messages, the reliability of directly-activated cells peaks at a timescale of dozens of milliseconds, whereas indirectly-activated cells exhibit an order-of-magnitude faster timescale. Using data-driven modelling, we find that error correction is consistent with non-linear amplification of coincident spikes.

Basket cells are key GABAergic inhibitory interneurons that target the somata and proximal dendrites, enabling efficient control of the timing and rate of spiking of their postsynaptic targets. In all cortical circuits, there are two major types of basket cell that exhibit striking developmental, molecular, anatomical, and physiological differences. In this talk, I will discuss recent results that reveal the tightly coupled complementarity of these two key microcircuit regulatory modules, demonstrating a novel form of brain-state-specific segregation of inhibition during spontaneous behavior, with implications for the assessment of dysregulated inhibition in epilepsy. In addition, I will describe recent advances in our understanding of the spatio-temporal dynamics of endocannabinoid signaling in hippocampal circuits and discuss how abnormal amplification of these activity-dependent signaling processes leads to surprising downstream effects in seizures.

The ability to experience pain is old in evolutionary terms. It is an experience shared across species. Acute pain is the body’s alarm system, and as such it is a good thing. Pain that persists beyond normal tissue healing time (3-4 months) is defined as chronic – it is the system gone wrong and it is not a good thing. Chronic pain has recently been classified as both a symptom and disease in its own right. It is one of the largest medical health problems worldwide with one in five adults diagnosed with the condition. The brain is key to the experience of pain and pain relief. This is the place where pain emerges as a perception. So, relating specific brain measures using advanced neuroimaging to the change patients describe in their pain perception induced by peripheral or central sensitization (i.e. amplification), psychological or pharmacological mechanisms has tremendous value. Identifying where amplification or attenuation processes occur along the journey from injury to the brain (i.e. peripheral nerves, spinal cord, brainstem and brain) for an individual and relating these neural mechanisms to specific pain experiences, measures of pain relief, persistence of pain states, degree of injury and the subject's underlying genetics, has neuroscientific and potential diagnostic relevance. This is what neuroimaging has afforded – a better understanding and explanation of why someone’s pain is the way it is. We can go ‘behind the scenes’ of the subjective report to find out what key changes and mechanisms make up an individual’s particular pain experience. A key area of development has been pharmacological imaging where objective evidence of drugs reaching the target and working can be obtained. We even now understand the mechanisms of placebo analgesia – a powerful phenomenon known about for millennia. More recently, researchers have been investigating through brain imaging whether there is a pre-disposing vulnerability in brain networks towards developing chronic pain. So, advanced neuroimaging studies can powerfully aid explanation of a subject’s multidimensional pain experience, pain relief (analgesia) and even what makes them vulnerable to developing chronic pain. The application of this goes beyond the clinic and has relevance in courts of law, and other areas of society, such as in veterinary care. Relatively far less work has been directed at understanding what changes in the brain occur during altered states of consciousness induced either endogenously (e.g. sleep) or exogenously (e.g. anaesthesia). However, that situation is changing rapidly. Our recent multimodal neuroimaging work explores how anaesthetic agents produce altered states of consciousness such that perceptual experiences of pain and awareness are degraded. This is bringing us fascinating insights into the complex phenomenon of anaesthesia, consciousness and even the concept of self-hood. These topics will be discussed in my talk alongside my ‘side-story’ of life as a scientist combining academic leadership roles with doing science and raising a family.

In order to re-install neurogenesis after loss of neurons upon injury or neurodegeneration, we need to understand the basic principles of neurogenesis. I will first discuss about our discovery of a novel centrosome protein (Camargo et al., 2019) and discuss unpublished work about the great diversity of interphase centrosome proteomes and their relevance for neurodevelopmental disorders. I would then present work on a master regulator of neural stem cell amplification and brain folding (Stahl et al., 2013; Esgleas et al., 2020) to proceed presenting data on utilizing some of these factors for turning astrocytes into neurons. I will present data on the critical role of mitochondria in this conversion process (Gascon et al., 2016, Russo et al., 2020) and how it regulates the speed of conversion also showing unpublished data. If time permits I may touch on recent progress in in vivo reprogramming (Mattugini et al., 2019). Taken together, these data highlight the surprising specificity and importance of organelle diversity from centrosome, nucleolus and mitochondria as key regulators in development and reprogramming.

In a few months, human infants develop complex capacities in numerous cognitive domains. They learn their native language, recognize their parents, refine their numerical capacities and their perception of the world around them but are they conscious and how can we study consciousness when no verbal report is possible? One way to approach this question is to rely on the neural responses correlated with conscious perception in adults (i.e. a global increase of activity in notably frontal regions with top-down amplification of the sensory levels). We can thus study at what age the developing anatomical architecture might be mature enough to allow this type of responses, but moreover we can use similar experimental paradigms than in adults in which we expect to observe a similar pattern of functional responses.

The dominant view of perception right now is that information travels from the environment to the sensory system, then to the nervous systems which processes it to generate a percept and behaviour. Ongoing behaviour is thought to occur largely through simple iterations of this process. However, this linear view, where information flows only in one direction and the properties of the environment and the sensory system remain static and unaffected by behaviour, is slowly fading. Many of us are beginning to appreciate that perception is largely active, i.e. that information flows back and forth between the three systems modulating their respective properties. In other words, in the real world, the environment and sensorimotor loop is pretty much always closed. I study the loop; in particular I study how the reverse arm of the loop affects sound and vibration perception. I will present two examples of motor modulation of perception at two very different temporal and spatial scales. First, in crickets, I will present data on how high-speed molecular motor activity enhances hearing via the well-studied phenomenon of active amplification. Second, in spiders I will present data on how body posture, a slow macroscopic feature, which can barely be called ‘active’, can nonetheless modulate vibration perception. I hope these results will motivate a conversation about whether ‘active’ perception is an optional feature observed in some sensory systems, or something that is ultimately necessitated by both evolution and physics.