Neuroscience seminars

It is clear that the cause of obesity is a result of eating more than you burn. It is physics. What is more complex to answer is why some people eat more than others? Differences in our genetic make-up mean some of us are slightly more hungry all the time and so eat more than others. We now know that the genetics of body-weight, on which obesity sits on one end of the spectrum, is in actuality the genetics of appetite control. In contrast to the prevailing view, body-weight is not a choice. People who are obese are not bad or lazy; rather, they are fighting their biology.

Migraine is much more than an episodic headache. It is a complex brain disorder, characterized by a global dysfunction in multisensory information processing and integration. In a third of patients, the headache is preceded by transient sensory disturbances (aura), whose neurophysiological correlate is cortical spreading depression (CSD). The molecular, cellular and circuit mechanisms of the primary brain dysfunctions that underlie migraine onset, susceptibility to CSD and altered sensory processing remain largely unknown and are major open issues in the neurobiology of migraine. Genetic mouse models of a rare monogenic form of migraine with aura provide a unique experimental system to tackle these key unanswered questions. I will describe the functional alterations we have uncovered in the cerebral cortex of genetic mouse models and discuss the insights into the cellular and circuit mechanisms of migraine obtained from these findings.

The Miniscope Project -- an open-source collaborative effort—was created to accelerate innovation of miniature microscope technology and to increase global access to this technology. Currently, we are working on advancements ranging from optogenetic stimulation and wire-free operation to simultaneous optical and electrophysiological recording. Using these systems, we have uncovered mechanisms underlying temporal memory linking and investigated causes of cognitive deficits in temporal lobe epilepsy. Through innovation and optimization, this work aims to extend the reach of neuroscience research and create new avenues of scientific inquiry.

Large-scale neural recordings contain high-dimensional structure that cannot be easily captured by existing data visualization methods. We therefore developed an embedding algorithm called Rastermap, which captures highly nonlinear relationships between neurons, and provides useful visualizations by assigning each neuron to a location in the embedding space. Compared to standard algorithms such as t-SNE and UMAP, Rastermap finds finer and higher dimensional patterns of neural variability, as measured by quantitative benchmarks. We applied Rastermap to a variety of datasets, including spontaneous neural activity, neural activity during a virtual reality task, widefield neural imaging data during a 2AFC task, artificial neural activity from an agent playing atari games, and neural responses to visual textures. We found within these datasets unique subpopulations of neurons encoding abstract properties of the environment.

I will discuss the mechanisms that determine whether a weak visual stimulus will reach consciousness or not. If the stimulus is simple, early visual cortex acts as a relay station that sends the information to higher visual areas. If the stimulus arrives at a minimal strength, it will be stored in working memory and can be reported. However, during more complex visual perceptions, which for example depend on the segregation of a figure from the background, early visual cortex’ role goes beyond a simply relay. It now acts as a cognitive blackboard and conscious perception depends on it. Our results inspire new approaches to create a visual prosthesis for the blind, by creating a direct interface with the visual brain. I will discuss how high-channel-number interfaces with the visual cortex might be used to restore a rudimentary form of vision in blind individuals.

On behalf of NeurotechEU, we are pleased to invite you to participate in the Summit 2021 pre-selection event on October 23, 2021. The event will be held online via the Platform Crowdcast.io, and it is going to be organized by NeurotechEU-The European University of Brain and Technology. Students from all over NeurotechEU have the chance to present their research (bachelor’s thesis, Master’s thesis, PhD, post-doc…) following the methodology of three minutes thesis (3MT from the University of Queensland): https://threeminutethesis.uq.edu.au/resources/3mt-competitor-guide. There will be one session per university and at the end of it, two semi-finalists will be selected from each university. They will compete in the Summit 2021 on November 22nd. There will be prizes for the winners who will be selected by voting of the audience.

In this talk he will present current work in progress on “irruption theory”, a new theory of consciousness that integrates an embodied-enactive account of basic mind with radical formulations of the freedom and efficacy of intentional agency.

Karl Deisseroth explains how light-sensitive microbial proteins became tools for investigating brain circuits in living, freely moving animals. By controlling selected classes of neurons, and sometimes individual cells, optogenetics allows researchers to ask how cellular activity contributes to behaviour and mental experience. The lecture connects the discovery and development of these tools with questions about emotions, the neural pathways that generate our inner experience, and processes disrupted in psychiatric illness. It considers both basic research and clinical possibilities, including the importance of neuronal and social connections for emotional well-being.

Sensory experience often depends on one’s own actions, including self-motion. Theories of predictive coding postulate that actions are regulated by calculating prediction error, which is the difference between sensory experience and expectation based on self-generated actions. Signals consistent with prediction error have been reported in mouse visual cortex (V1) when visual flow coupled to running was unexpectedly stopped. Here, we show such signals can be elicited by visual stimuli uncoupled to animal’s running. We recorded V1 neurons while presenting drifting gratings that unexpectedly stopped. We found strong responses to visual perturbations, which were enhanced during running. Perturbation responses were strongest in the preferred orientation of individual neurons and perturbation responsive neurons were more likely to prefer slow visual speeds. Our results indicate that prediction error signals can be explained by the convergence of known motor and sensory signals, providing a purely sensory and motor explanation for purported mismatch signals.

The long-term goal of our research is to understand the mechanisms of SUDEP, defined as Sudden, Unexpected, witnessed or unwitnessed, nontraumatic and non-drowning Death in patients with EPilepsy, excluding cases of documented status epilepticus. The majority of SUDEP patients die during sleep. SUDEP is the most devastating consequence of epilepsy, yet little is understood about its causes and no biomarkers exist to identify at risk patients. While SUDEP accounts for 7.5-20% of all epilepsy deaths, SUDEP risk in the genetic epilepsies varies with affected genes. Patients with ion channel gene variants have the highest SUDEP risk. Indirect evidence variably links SUDEP to seizure-induced apnea, pulmonary edema, dysregulation of cerebral circulation, autonomic dysfunction, and cardiac arrhythmias. Arrhythmias may be primary or secondary to hormonal or metabolic changes, or autonomic discharges. When SUDEP is compared to Sudden Cardiac Death secondary to Long QT Syndrome, especially to LQT3 linked to variants in the voltage-gated sodium channel (VGSC) gene SCN5A, there are parallels in the circumstances of death. To gain insight into SUDEP mechanisms, our approach has focused on channelopathies with high SUDEP incidence. One such disorder is Dravet syndrome (DS), a devastating form of developmental and epileptic encephalopathy (DEE) characterized by multiple pharmacoresistant seizure types, intellectual disability, ataxia, and increased mortality. While all patients with epilepsy are at risk for SUDEP, DS patients may have the highest risk, up to 20%, with a mean age at SUDEP of 4.6 years. Over 80% of DS is caused by de novo heterozygous loss-of-function (LOF) variants in SCN1A, encoding the VGSC Nav1.1  subunit, resulting in haploinsufficiency. A smaller cohort of patients with DS or a more severe DEE have inherited, homozygous LOF variants in SCN1B, encoding the VGSC 1/1B non-pore-forming subunits. A related DEE, Early Infantile EE (EIEE) type 13, is linked to de novo heterozygous gain-of-function variants in SCN8A, encoding the VGSC Nav1.6. VGSCs underlie the rising phase and propagation of action potentials in neurons and cardiac myocytes. SCN1A, SCN8A, and SCN1B are expressed in both the heart and brain of humans and mice. Because of this, we proposed that cardiac arrhythmias contribute to the mechanism of SUDEP in DEE. We have taken a novel approach to the development of therapeutics for DS in collaboration with Stoke Therapeutics. We employed Targeted Augmentation of Nuclear Gene Output (TANGO) technology, which modulates naturally occurring, non-productive splicing events to increase target gene and protein expression and ameliorate disease phenotype in a mouse model. We identified antisense oligonucleotides (ASOs) that specifically increase the expression of productive Scn1a transcript in human and mouse cell lines, as well as in mouse brain. We showed that a single intracerebroventricular dose of a lead ASO at postnatal day 2 or 14 reduced the incidence of electrographic seizures and SUDEP in the F1:129S-Scn1a+/- x C57BL/6J mouse model of DS. Increased expression of productive Scn1a transcript and NaV1.1 protein were confirmed in brains of treated mice. Our results suggest that TANGO may provide a unique, gene-specific approach for the treatment of DS.

One of Tali's cherished goals was to transform biology into physics. In his view, biologists were far too enamored by the details of the specific models they studied, losing sight of the big principles that may govern the behavior of these models. One such big principle that he suggested was the 'information bottleneck (IB) principle'. The iIB principle is an information-theoretical approach for extracting the relevant information that one random variable carries about another. Tali applied the IB principle to numerous problems in biology, gaining important insights in the process. Here I will describe two applications of the IB principle to neurobiological data. The first is the formalization of the notion of surprise that allowed us to rigorously estimate the memory duration and content of neuronal responses in auditory cortex, and the second is an application to behavior, allowing us to estimate 'optimal policies under information constraints' that shed interesting light on rat behavior.

Smooth pursuit eye movements are among our most intriguing motor behaviors. They are able to keep the line of sight on smoothly moving targets with little or no overt effort or deliberate planning, and they can respond quickly and accurately to changes in the trajectory of motion of targets. Nevertheless, despite these seeming automatic characteristics, pursuit is highly sensitive to high-level factors, such as the choices made about attention, or beliefs about the direction of upcoming motion. Investigators have struggled for decades with the problem of incorporating both high- and low-level processes into a single coherent model. This talk will present an overview of the current state of efforts to incorporate high- and low-level influences, as well as new observations that add to our understanding of both types of influences. These observations (in contrast to much of the literature) focus on the directional properties of pursuit. Studies will be presented that show: (1) the direction of smooth pursuit made to pursue fields of noisy random dots depends on the relative reliability of the sensory signal and the expected motion direction; (2) smooth pursuit shows predictive responses that depend on the interpretation of cues that signal an impending collision; and (3) smooth pursuit during a change in target direction displays kinematic properties consistent with the well-known two-thirds power law. Implications for incorporating high- and low-level factors into the same framework will be discussed.

The human gut microbiome has emerged as a key player in the bidirectional communication of the gut-brain axis, affecting various aspects of homeostasis and pathophysiology. Until recently, the majority of studies that seek to explore the mechanisms underlying the microbiome-gut-brain axis cross-talk relied almost exclusively on animal models, and particularly gnotobiotic mice. Despite the great progress made with these models, various limitations, including ethical considerations and interspecies differences that limit the translatability of data to human systems, pushed researchers to seek for alternatives. Over the past decades, the field of in vitro modelling of tissues has experienced tremendous growth, thanks to advances in 3D cell biology, materials, science and bioengineering, pushing further the borders of our ability to more faithfully emulate the in vivo situation. Organ-on-chip technology and bioengineered tissues have emerged as highly promising alternatives to animal models for a wide range of applications. In this talk I’ll discuss our progress towards generating a complete platform of the human microbiota-gut-brain axis with integrated monitoring and sensing capabilities. Bringing together principles of materials science, tissue engineering, 3D cell biology and bioelectronics, we are building advanced models of the GI and the BBB /NVU, with real-time and label-free monitoring units adapted in the model architecture, towards a robust and more physiologically relevant human in vitro model, aiming to i) elucidate the role of microbiota in the gut-brain axis communication, ii) to study how diet and impaired microbiota profiles affect various (patho-)physiologies, and iii) to test personalised medicine approaches for disease modelling and drug testing.