In a famous philosophical paradox, Buridan's ass perishes because he is equally hungry and thirsty, and cannot make up his mind whether to first drink or eat. We are faced daily with the need to pick between alternatives that are equally attractive (or not) to us. What are the processes that allow us to avoid paralysis and to rapidly select between such equal options when there are no preferences or rational reasons to rely on? One solution that was offered is that although on a higher cognitive level there is symmetry between the alternatives, on a neuronal level the symmetry does not maintain. What is the nature of this asymmetry of the neuronal level? In this talk I will present experiments addressing this important phenomenon using measures of human behavior, EEG, EMG and large scale neural network modeling, and discuss mechanisms involved in the process of intention formation and execution, in the face of alternatives to choose from. Specifically, I will show results revealing the temporal dynamics of rapid intention formation and, moreover, ‘change of intention’ in a free choice picking scenario, in which the alternatives are on a par for the participant. The results suggest that even in arbitrary choices, endogenous or exogenous biases that are present in the neural system for selecting one or another option may be implicitly overruled; thus creating an implicit and non-conscious ‘change of mind’. Finally, the question is raised: in what way do such rapid implicit ‘changes of mind’ help retain one’s self-control and free-will behavior?

Several excellent computational frameworks exist that enable high-throughput and consistent tracking of freely moving unmarked animals. SimBA introduce and distribute a plug-and play pipeline that enables users to use these pose-estimation approaches in combination with behavioral annotation for the generation of supervised machine-learning behavioral predictive classifiers. SimBA was developed for the analysis of complex social behaviors, but includes the flexibility for users to generate predictive classifiers across other behavioral modalities with minimal effort and no specialized computational background. SimBA has a variety of extended functions for large scale batch video pre-processing, generating descriptive statistics from movement features, and interactive modules for user-defined regions of interest and visualizing classification probabilities and movement patterns.

Large scale genetic studies and associated functional investigations have tremendously augmented our knowledge about the mechanisms underlying epileptic seizures, and sometimes also accompanying developmental problems. Pharmacotherapy of the epilepsies is routinely guided by trial and error, since predictors for a response to specific antiepileptic drugs are largely missing. The recent advances in the field of genetic epilepsies now offer an increasing amount of either well fitting established or new re-purposing therapies for genetic epilepsy syndromes based on understanding of the pathophysiological principles. Examples are provided by variants in ion channel or transporter encoding genes which cause a broad spectrum of epilepsy syndromes of variable severity and onset, (1) the ketogenic diet for glucose transporter defects of the blood-brain barrier, (2) Na+ channel blockers (e.g. carbamazepine) for gain-of-function Na+ channel mutations and avoidance of those drugs for loss-of-function mutations, and (3) specific K+ channel blockers for mutations with a gain-of-function defect in respective K+ channels. I will focus in my talk on the latter two including the underlying mechanisms, their relation to clinical phenotypes and possible therapeutic implications. In conclusion, genetic and mechanistic studies offer promising tools to predict therapeutic effects in rare epilepsies.

Age-associated dementias are neuropathologically characterized by the identification of hallmark intracellular and extracellular deposition of proteins, i.e., hyperphosphorylated-tau, amyloid-β, and α-synuclein, or cerebrovascular lesions. The neuropathological assessment and staging of these pathologies allows for a diagnosis of a distinct disease, e.g., amyloid-β plaques and hyperphosphorylated tau pathology in Alzheimer's disease. Neuropathological assessment in large scale cohorts, such as the UK’s Brains for Dementia Research (BDR) programme, has made it increasingly clear that the ageing brain is characterized by the presence of multiple age-associated pathologies rather than just the ‘pure’ hallmark lesion as commonly perceived. These additional pathologies can range from low/intermediate levels, that are assumed to have little if any clinical significance, to a full-blown mixed disease where there is the presence of two distinct diseases. In our recent paper (McAleese et al. 2021 Concomitant neurodegenerative pathologies contribute to the transition from mild cognitive impairment to dementia, https://alz-journals.onlinelibrary.wiley.com/doi/full/10.1002/alz.12291, Alzheimer's & Dementia), using the BDR cohort, we investigated the frequency of multimorbidity and specifically investigated the impact of additional low-level pathology on cognition. In this study, of 670 donated post-mortem brains, we found that almost 70% of cases exhibited multimorbidity and only 22% were considered a pure diagnosis. Importantly, no case of Lewy Body dementia or vascular dementia was considered pure. A key finding is that the presence of low levels of additional pathology increased the likelihood of having mild dementia vs mild cognitive impairment by almost 20-fold, indicating low levels of additional pathology do impact the clinical progression of a distinct disease. Given the high prevalence and the potential clinical impact, cerebral multimorbidity should be at the forefront of consideration in dementia research.

The spontaneous collective motion of self-propelled agents is ubiquitous in the natural world, and it often occurs in complex environments, be it bacteria and cells migrating through polymeric extracellular matrix or animal herds and human crowds navigating structured terrains. Much is known about flocking dynamics in pristine backgrounds, but how do spatio-temporal heterogeneities in the environment impact such collective self-organization? I will present two model systems, a colloidal active fluid negotiating disordered obstacles and a confined dense bacterial suspension in a viscoelastic medium, as controllable platforms to explore this question and highlight general mechanisms for active self-organization in complex environments. By combining theory and experiment, I will show how flocks on disordered substrates organize into a novel dynamic vortex glass phase, akin to vortex glasses in dirty superconductors, while the presence of viscoelasticity can calm the otherwise turbulent swarming of bacteria, allowing the emergence of a large scale coherent and even oscillatory vortex when confined on the millimetre scale.

Active matter systems are composed of constituents, each one in nonequilibrium, that consume energy in order to move [1]. A characteristic feature of active matter is collective motion leading to nonequilibrium phase transitions or large scale directed motion [2]. A number of recent works have featured active particles interacting with obstacles, either moving or fixed [3,4,5]. When an active particle encounters an asymmetric obstacle, different behaviours are detected depending on the nature of its active motion. On the one side, rectification effects arise in a suspension of run-and-tumble particles interacting with a wall of funnelled-shaped openings, caused by particles persistence length [6]. The same trapping mechanism could be responsible for the intake of microorganisms in the underground leaves [7] of Carnivorous plants [8]. On the other side, for aligning particles [9] interacting with a wall of funnelled-shaped openings, trapping happens on the (opposite) wider opening side of the funnels [10,11]. Interestingly, when funnels are located on a circular array, trapping is more localised and depends on the nature of the Vicsek model. Active particles can be synthetic (such as synthetic active colloids) or alive (such as living bacteria). A prototypical model to study living microswimmers is P. fluorescens, a rod shaped and biofilm forming bacterium. Biofilms are microbial communities self-assembled onto external interfaces. Biofilms can be described within the Soft Matter physics framework [12] as a viscoelastic material consisting of colloids (bacterial cells) embedded in a cross-linked polymer gel (polysaccharides cross-linked via proteins/multivalent cations), whose water content vary depending on the environmental conditions. Bacteria embedded in the polymeric matrix control biofilm structure and mechanical properties by regulating its matrix composition. We have recently monitored structural features of Pseudomonas fluorescens biofilms grown with and without hydrodynamic stress [13,14]. We have demonstrated that bacteria are capable of self-adapting to hostile hydrodynamic stress by tailoring the biofilm chemical composition, thus affecting both the mesoscale structure of the matrix and its viscoelastic properties that ultimately regulate the bacteria-polymer interactions. REFERENCES [1] C. Bechinger et al. Rev. Mod. Phys. 88, 045006 (2016); [2] T. Vicsek, A. Zafeiris Phys. Rep. 517, 71 (2012); [3] C. Bechinger, R. Di Leonardo, H. Lowen, C. Reichhardt, G. Volpe, and G. Volpe, Reviews of Modern Physics 88, 045006 (2016); [4] R Martinez, F Alarcon, DR Rodriguez, JL Aragones, C Valeriani The European Physical Journal E 41, 1 (2018); [5] DR Rodriguez, F Alarcon, R Martinez, J Ramírez, C Valeriani, Soft matter 16 (5), 1162 (2020); [6] C. O. Reichhardt and C. Reichhardt, Annual Review of Condensed Matter
Physics 8, 51 (2017); [7] W Barthlott, S Porembski, E Fischer, B Gemmel Nature 392, 447 (1998); [8] C B. Giuliano, R Zhang, R.Martinez Fernandez, C.Valeriani and L.Wilson (in preparation, 2021); [9] R Martinez, F Alarcon, JL Aragones, C Valeriani Soft matter 16 (20), 4739 (2020); [10] P. Galajada, J. Keymer, P. Chaikin and R.Austin, Journal of bacteriology, 189, 8704 (2007); [11] M. Wan, C.O. Reichhardt, Z. Nussinov, and C. Reichhardt, Physical Review Letters 101, 018102 (2008); [12] J N. Wilking , T E. Angelini , A Seminara , M P. Brenner , and D A. Weitz MRS Bulletin 36, 385 (2011); [13]J Jara, F Alarcón, A K Monnappa, J Ignacio Santos, V Bianco, P Nie, M Pica Ciamarra, A Canales, L Dinis, I López-Montero, C Valeriani, B Orgaz, Frontiers in microbiology 11, 3460 (2021); [14] P Nie, F Alarcon, I López-Montero, B Orgaz, C Valeriani, M Pica Ciamarra

Bats are extreme aviators and amazing navigators. Many bat species nightly commute dozens of kilometres in search of food, and some bat species annually migrate over thousands of kilometres. Studying bats in their natural environment has always been extremely challenging because of their small size (mostly <50 gr) and agile nature. We have recently developed novel miniature technology allowing us to GPS-tag small bats, thus opening a new window to document their behaviour in the wild. We have used this technology to track fruit-bats pups over 5 months from birth to adulthood. Following the bats’ full movement history allowed us to show that they use novel short-cuts which are typical for cognitive-map based navigation. In a second study, we examined how nectar-feeding bats make foraging decisions under competition. We show that by relying on a simple reinforcement learning strategy, the bats can divide the resource between them without aggression or communication. Together, these results demonstrate the power of the large scale natural approach for studying animal behavior.

Over the past years, genetic studies have uncovered hundreds of genetic variants to be associated with complex brain disorders. While this really represents a big step forward in understanding the genetic etiology of brain disorders, the functional interpretation of these variants remains challenging. We aim to help with the functional characterization of variants through transcriptomic data analysis. For instance, we rely on brain transcriptome atlases, such as Allen Brain Atlases, to infer functional relations between genes. One example of this is the identification of signaling mechanisms of steroid receptors. Further, by integrating brain transcriptome atlases with neuropathology and neuroimaging data, we identify key genes and pathways associated with brain disorders (e.g. Parkinson's disease). With technological advances, we can now profile gene expression in single-cells at large scale. These developments have presented significant computational developments. Our lab focuses on developing scalable methods to identify cells in single-cell data through interactive visualization, scalable clustering, classification, and interpretable trajectory modelling. We also work on methods to integrate single-cell data across studies and technologies.

My lab seeks to understand how the mammalian brain performs the computations that underlie cognitive functions, including decision-making, short-term memory, and spatial navigation, at the level of the building blocks of the nervous system, cell types and neural populations organized into circuits. We have developed methods to measure, manipulate, and analyze neural circuits across various spatial and temporal scales, including technology for virtual reality, optical imaging, optogenetics, intracellular electrophysiology, molecular sensors, and computational modeling. I will present recent work that uses large scale calcium imaging to reveal the functional organization of the mouse posterior cortex for flexible decision-making during spatial navigation in virtual reality. I will also discuss work that uses optogenetics and calcium imaging during a variety of decision-making tasks to highlight how cognitive experience and context greatly alter the cortical circuits necessary for navigation decisions.

Bats are extreme aviators and amazing navigators. Many bat species nightly com-mute dozens of kilometres in search of food, and some bat species annually migrate over thousands of kilometres. Studying bats in their natural environment has al-ways been extremely challenging because of their small size (mostly <50 gr) and agile nature. We have recently developed novel miniature technology allowing us to GPS-tag small bats, thus opening a new window to document their behaviour in the wild. We have used this technology to track fruit-bats pups over 5 months from birth to adulthood. Following the bats’ full movement history allowed us to show that they use novel short-cuts which are typical for cognitive-map based naviga-tion. In a second study, we examined how nectar-feeding bats make foraging deci-sions under competition. We show that by relying on a simple reinforcement learn-ing strategy, the bats can divide the resource between them without aggression or communication. Together, these results demonstrate the power of the large scale natural approach for studying animal behavior.

Multi-agent reinforcement learning (MARL) has recently shown great promise as an approach to networked system control. Arguably, one of the most difficult and important tasks for which large scale networked system control is applicable is common-pool resource (CPR) management. Crucial CPRs include arable land, fresh water, wetlands, wildlife, fish stock, forests and the atmosphere, of which proper management is related to some of society’s greatest challenges such as food security, inequality and climate change. This talk will consist of three parts. In the first, we will briefly look at climate change and how it poses a significant threat to life on our planet. In the second, we will consider the potential of multi-agent systems for climate change mitigation and adaptation. And finally, in the third, we will discuss recent research from InstaDeep into better understanding the behaviour of networked MARL systems used for CPR management. More specifically, we will see how the tools from empirical game-theoretic analysis may be harnessed to analyse the differences in networked MARL systems. The results give new insights into the consequences associated with certain design choices and provide an additional dimension of comparison between systems beyond efficiency, robustness, scalability and mean control performance.

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