We are seeking a passionate and dedicated research technician to join our team Neuronal Circuits & Brain Dynamics at the Paris Brain Institute (ICM). Our work focuses on unraveling the fascinating mysteries of how the brain generates internal states and how neuromodulators, such as dopamine and serotonin, influence neuronal activity during behavior. To achieve our goals, we employ state-of-the-art techniques, including behavioral, optogenetic, imaging, electrophysiological, and genetic approaches in mice. Main Responsibilities • As a research technician, you are at the epicenter of our research activities and you will serve as a point of reference of the lab know-how across generations of lab members. • As a hands-on research technician, your primary responsibilities will include organizing the laboratory, maintaining basic lab infrastructure, performing routine tasks, regularly updating lab databases, ensuring the lab runs efficiently, and contributing to the team's research efforts. • Collaborating closely with the team, you will contribute to ongoing research projects and you will conduct behavioral and optogenetic experiments, carry out stereotaxic surgeries, and handle histological processing, including tissue slicing, immunostaining, and fluorescent microscopy. • You will be responsible for learning, developing, and passing on Standard Operating Procedures (SOPs) for the techniques utilized in our lab. • Additionally, in coordination with the head of the animal facility, you will supervise and ensure adherence to animal welfare guidelines, as well as maintain project permits and annual reports. • This role provides the opportunity to lead and participate in research projects to the extent of your desire. We offer competitive compensation and benefits within an interactive, interdisciplinary working environment, where cutting-edge science thrives and a dynamic, international research community awaits. As part of your role, you will receive extensive training in traditional and cutting-edge neuroscience techniques related to mice. If you are eager to join our vibrant research community and contribute to groundbreaking discoveries, we warmly welcome your application. The position is available immediately, with the potential for a permanent contract based on performance. If you would like to know more, visit our website: neuronaldynamics.eu and read about our team's mission and values. Why join our team • We are a young and vibrant group of scientists, fueled by curiosity and passion for understanding the brain. • We work as a team and use or invent cutting-edge neurotechnologies to answer fundamental questions in neuroscience. • Our team is committed to the training, mentorship, and career development of the next generation of neuroscientists. To achieve that, we foster an inclusive and supportive environment, where we can learn and advance science while having fun in the process. • Our work is multi-disciplinary, and so is our team. Irrespective of your background and project, our research environment will expose you to a diverse range of experimental and computational aspects of systems and circuits neuroscience. We thus encourage everyone to apply, especially those from underrepresented minorities. • Our team is affiliated with Inserm and is located in the Paris Brain Institute (ICM), where we have access to state-of-the-art facilities and resources. • Our vibrant community at the ICM and throughout Paris promotes broad collaboration and learning opportunities. <b>How to apply</b> If you are eager to join our vibrant research community and contribute to groundbreaking discoveries, we warmly welcome your application. The position is available immediately, with the potential for a permanent contract based on performance. Please send a statement of your past work and interests, your CV, and contact information for 1-3 references to the address: contact@neuronaldynamics.eu

If you are a data scientist, programmer, or engineer, with a keen interest in helping to understand the brain, consider joining our team Neuronal Circuits & Brain Dynamics at the Paris Brain Institute (ICM). We study the principles of neuronal circuit organization and brain dynamics. Our work focuses on unraveling the fascinating mysteries of how the brain generates internal states and how neuromodulators, such as dopamine and serotonin, influence neuronal activity and communication between brain regions during behavior. To achieve our goals, we perform large-scale recordings from thousands of neurons simultaneously using multimodal recordings, including electrophysiological or optical imaging approaches. We employ state-of-the-art techniques, including behavioral, optogenetic, imaging, electrophysiological, and genetic approaches in mice to record and manipulate the brain activity during behavior. Using this unprecedented data, we will be able to understand information flow in the brain in ways that would be unimaginable only a few years ago. However, the scale and complexity of this data provide major challenges and unique opportunities. We are looking for computationally-orientated researchers to join our team as temporary or permanent staff members, to help us develop methods to interact and analyze our multi-dimensional neurophysiological and behavioral data, and to develop innovative analysis approaches and efficient processing pipelines, to accelerate the progress of our research on our path to understanding the brain. As a data analyst in our group, you will interact closely with experimentalists and contribute crucially to the research. Our team values diversity and welcomes researchers from all backgrounds and profiles. If your profile aligns with our research needs, we encourage you to get in touch with us. Main responsibilities • Organize data management pipeline • Analyze neurophysiological and behavioral data • Develop analysis methods and software tools to facilitate the analysis of multi-modal and multi-dimensional neurophysiological data • Implement cutting-edge data science approaches (statistical, computational, and ML) for complex neuroscience problems • Create robust and efficient data pipelines to extract, transform, and visualize data • Develop, test, and implement scientific software (e.g., for reproducible analysis pipelines and data storage) • Interact with experimentalists to design experiments and implement analyses • Analyze current technologies, algorithms, models, and methods • As part of your role, you will have the opportunity to collaborate with other teams, attend trainings, mentor students, have independent projects, and present at major relevant conferences (Cosyne, NeurIPS). We offer competitive compensation and benefits within an interactive, interdisciplinary working environment, where cutting-edge science thrives and a dynamic, international research community awaits.

Full listing: https://www.medewerkers.universiteitleiden.nl/vacatures/2022/kwartaal-2/22-25911465postdoc-in-cognitive-and-computational-neuroscience The way that neural computations give rise to behavior is shaped by ever-fluctuating internal states. These states (such as arousal, fear, stress, hunger, motivation, engagement, or drowsiness) are characterized by spontaneous neural dynamics that arise independent of task demands. Across subfields of neuroscience, internal states have been quantified using a variety of measurements and markers (based on physiology, brain activity or behavioral motifs), but these are rarely explicitly compared or integrated. It is thus unclear if such different state markers quantify the same, or even related underlying processes. Instead, the simplified concept of internal states likely obscures a multi-dimensional set of biologically relevant processes, which may affect behavior in distinct ways. In this project, we will take an integrative approach to quantify the structure and dimensionality of internal states and their effects on decision-making behavior. We will apply several state-of-the-art methods to extract different markers of internal states from facial video data, pupillometry, and high-density neural recordings. We will then quantify the unique and shared dimensionality of internal states, and their relevance for predicting choice behavior. By combining existing, publicly available datasets in mice with additional experiments in humans, we will directly test the cross-species relevance of our findings. Lastly, we will investigate how internal states change over a range of timescales: from sub-second fluctuations relevant for choice behavior to the very slow changes that take place with aging. This project is a collaboration between the Cognitive, Computational and Systems Neuroscience lab led by Dr. Anne Urai (daily supervisor) and the Temporal Attention Lab led by Prof. Sander Nieuwenhuis. We are based in Leiden University’s Cognitive Psychology Unit, and we participate in the Leiden Institute for Brain and Cognition (LIBC), an interfaculty center for interdisciplinary research on brain and cognition ( https://www.libc-leiden.nl ). There are further options for collaborating with the International Brain Laboratory ( https://www.internationalbrainlab.com ). Leiden is a small, friendly town near the beach, with great public transport connections to larger cities nearby. The Netherlands has excellent support for families. The working language at the university is English, and you can comfortably get by with only minimal knowledge of Dutch. Our team is small, and we value a collegial and supportive environment. Open science is a core value in our work, and we actively pursue ways to make academia a better place. We support postdocs in developing their own ideas and research line, and we offer opportunities to gain small-scale teaching and grant writing experience. More information on our groups’ research interests, scientific vision and working environment can be found at https://anneurai.net, https://anne-urai.github.io/lab_wiki/Vision.html and https://www.temporalattentionlab.com If you like asking hard questions, making things work, and pursuing creative ideas in a collaborative team, then this position may be for you. Please do not be discouraged from applying if your current CV is not a ‘perfect fit’. This job could suit someone from a range of different career backgrounds, and there is great scope for the right applicant to develop the role and make it their own.

The way that neural computations give rise to behavior is shaped by ever-fluctuating internal states. These states (such as arousal, fear, stress, hunger, motivation, engagement, or drowsiness) are characterized by spontaneous neural dynamics that arise independent of task demands. Across subfields of neuroscience, internal states have been quantified using a variety of measurements and markers (based on physiology, brain activity or behavioral motifs), but these are rarely explicitly compared or integrated. It is thus unclear if such different state markers quantify the same, or even related underlying processes. Instead, the simplified concept of internal states likely obscures a multi-dimensional set of biologically relevant processes, which may affect behavior in distinct ways. In this project, we will take an integrative approach to quantify the structure and dimensionality of internal states and their effects on decision-making behavior. We will apply several state-of-the-art methods to extract different markers of internal states from facial video data, pupillometry, and high-density neural recordings. We will then quantify the unique and shared dimensionality of internal states, and their relevance for predicting choice behavior. By combining existing, publicly available datasets in mice with additional experiments in humans, we will directly test the cross-species relevance of our findings. Lastly, we will investigate how internal states change over a range of timescales: from sub-second fluctuations relevant for choice behavior to the very slow changes that take place with aging. This project is a collaboration between the Cognitive, Computational and Systems Neuroscience lab led by Dr. Anne Urai (daily supervisor) and the Temporal Attention Lab led by Prof. Sander Nieuwenhuis. We are based in Leiden University’s Cognitive Psychology Unit, and we participate in the Leiden Institute for Brain and Cognition (LIBC), an interfaculty center for interdisciplinary research on brain and cognition ( https://www.libc-leiden.nl ). There are further options for collaborating with the International Brain Laboratory ( https://www.internationalbrainlab.com ). Leiden is a small, friendly town near the beach, with great public transport connections to larger cities nearby. The Netherlands has excellent support for families. The working language at the university is English, and you can comfortably get by with only minimal knowledge of Dutch. Our team is small, and we value a collegial and supportive environment. Open science is a core value in our work, and we actively pursue ways to make academia a better place. We support postdocs in developing their own ideas and research line, and we offer opportunities to gain small-scale teaching and grant writing experience. More information on our groups’ research interests, scientific vision and working environment can be found at https://anneurai.net, https://anne-urai.github.io/lab_wiki/Vision.html and https://www.temporalattentionlab.com If you like asking hard questions, making things work, and pursuing creative ideas in a collaborative team, then this position may be for you. Please do not be discouraged from applying if your current CV is not a ‘perfect fit’. This job could suit someone from a range of different career backgrounds, and there is great scope for the right applicant to develop the role and make it their own. See the full listing and apply at: https://www.medewerkers.universiteitleiden.nl/vacatures/2022/kwartaal-2/22-25911465postdoc-in-cognitive-and-computational-neuroscience

A post-doctoral position in theoretical neuroscience is open to explore the impact of cardiac inputs on cortical dynamics. Understanding the role of internal states in human cognition has become a hot topic, with a wealth of experimental results but limited attempts at analyzing the computations that underlie the link between bodily organs and brain. Our particular focus is on elucidating how the different mechanisms for heart-to-cortex coupling (e.g., phase-resetting, gating, phasic arousal,..) can account for human behavioral and neural data, from somatosensory detection to more high-level concepts such as self-relevance, using data-based dynamical models.

Biological agents continually reconcile the internal states of their brain circuits with incoming sensory and environmental evidence to evaluate when and how to act. The brains of biological agents, including animals and humans, exploit many evolutionary innovations, chiefly modularity—observable at the level of anatomically-defined brain regions, cortical layers, and cell types among others—that can be repurposed in a compositional manner to endow the animal with a highly flexible behavioral repertoire. Accordingly, their behaviors show their own modularity, yet such behavioral modules seldom correspond directly to traditional notions of modularity in brains. It remains unclear how to link neural and behavioral modularity in a compositional manner. We propose a comprehensive framework—compositional modes—to identify overarching compositionality spanning specialized submodules, such as brain regions. Our framework directly links the behavioral repertoire with distributed patterns of population activity, brain-wide, at multiple concurrent spatial and temporal scales. Using whole-brain recordings of zebrafish brains, we introduce an unsupervised pipeline based on neural network models, constrained by biological data, to reveal highly conserved compositional modes across individuals despite the naturalistic (spontaneous or task-independent) nature of their behaviors. These modes provided a scaffolding for other modes that account for the idiosyncratic behavior of each fish. We then demonstrate experimentally that compositional modes can be manipulated in a consistent manner by behavioral and pharmacological perturbations. Our results demonstrate that even natural behavior in different individuals can be decomposed and understood using a relatively small number of neurobehavioral modules—the compositional modes—and elucidate a compositional neural basis of behavior. This approach aligns with recent progress in understanding how reasoning capabilities and internal representational structures develop over the course of learning or training, offering insights into the modularity and flexibility in artificial and biological agents.

The nervous system orchestrates adaptive behaviors by intricately coordinating responses to internal cues and environmental stimuli. This involves integrating sensory input, managing competing motivational states, and drawing on past experiences to anticipate future outcomes. While traditional models attribute this complexity to interactions between the mesocorticolimbic system and hypothalamic centers, the specific nodes of integration have remained elusive. Recent research, including our own, sheds light on the midline thalamus's overlooked role in this process. We propose that the midline thalamus integrates internal states with memory and emotional signals to guide adaptive behaviors. Our investigations into midline thalamic neuronal circuits have provided crucial insights into the neural mechanisms behind flexibility and adaptability. Understanding these processes is essential for deciphering human behavior and conditions marked by impaired motivation and emotional processing. Our research aims to contribute to this understanding, paving the way for targeted interventions and therapies to address such impairments.

Animals modify their behavioral outputs in response to changes in external and internal environments. We use the nematode, C. elegans to probe the pathways linking changes in internal states like hunger with behavior. We find that acute food deprivation alters the localization of two transcription factors, likely releasing an insulin-like peptide from the intestine, which in turn modifies chemosensory neurons and alters behavior. These results present a model for how inter-tissue signals to generate flexible behaviors via gut-brain signaling.

The brain represents the external world through the bottleneck of sensory organs. The network of hierarchically organized neurons is thought to recover the causes of sensory inputs to reconstruct the reality in the brain in idiosyncratic ways depending on individuals and their internal states. How can we understand the world model represented in an individual’s brain, or the neuroverse? My lab has been working on brain decoding of visual perception and subjective experiences such as imagery and dreaming using machine learning and deep neural network representations. In this talk, I will outline the progress of brain decoding methods and present how subjective experiences are externalized as images and how they could be shared across individuals via neural code conversion. The prospects of these approaches in basic science and neurotechnology will be discussed.

Voluntary control of behavior requires the ability to dynamically integrate internal states and external evidence to achieve one’s goals. However, neuroscientific studies of intentional action and critical philosophical commentary of that research have taken a rather narrow turn in recent years, focussing on the neural precursors of spontaneous simple actions as potential realizers of intentions. In this session, we show how the debate can benefit from incorporating other types of experimental approaches, focussing on agency in dynamic contexts.

Motivational drives are internal states that can be different even in similar interactions with external stimuli. Curiosity as the motivational drive for novelty-seeking and investigating the surrounding environment is for survival as essential and intrinsic as hunger. Curiosity, hunger, and appetitive aggression drive three different goal-directed behaviors—novelty seeking, food eating, and hunting— but these behaviors are composed of similar actions in animals. This similarity of actions has made it challenging to study novelty seeking and distinguish it from eating and hunting in nonarticulating animals. The brain mechanisms underlying this basic survival drive, curiosity, and novelty-seeking behavior have remained unclear. In spite of having well-developed techniques to study mouse brain circuits, there are many controversial and different results in the field of motivational behavior. This has left the functions of motivational brain regions such as the zona incerta (ZI) still uncertain. Not having a transparent, nonreinforced, and easily replicable paradigm is one of the main causes of this uncertainty. Therefore, we chose a simple solution to conduct our research: giving the mouse freedom to choose what it wants—double freeaccess choice. By examining mice in an experimental battery of object free-access double-choice (FADC) and social interaction tests—using optogenetics, chemogenetics, calcium fiber photometry, multichannel recording electrophysiology, and multicolor mRNA in situ hybridization—we uncovered a cell type–specific cortico-subcortical brain circuit of the curiosity and novelty-seeking behavior. We found in mice that inhibitory neurons in the medial ZI (ZIm) are essential for the decision to investigate an object or a conspecific. These neurons receive excitatory input from the prelimbic cortex to signal the initiation of exploration. This signal is modulated in the ZIm by the level of investigatory motivation. Increased activity in the ZIm instigates deep investigative action by inhibiting the periaqueductal gray region. A subpopulation of inhibitory ZIm neurons expressing tachykinin 1 (TAC1) modulates the investigatory behavior.

Animals produce behavior by responding to a mixture of cues that arise both externally (sensory) and internally (neural dynamics and states). These cues are continuously produced and can be combined in different ways depending on the needs of the animal. However, the integration of these external and internal cues remains difficult to understand in natural behaviors. To address this gap, we have developed an unsupervised method to identify internal states from behavioral data, and have applied it to the study of a dynamic social interaction. During courtship, Drosophila melanogaster males pattern their songs using cues from their partner. This sensory-driven behavior dynamically modulates courtship directed at their partner. We use our unsupervised method to identify how the animal integrates sensory information into distinct underlying states. We then use this to identify the role of courtship neurons in either integrating incoming information or directing the production of the song, roles that were previously hidden. Our results reveal how animals compose behavior from previously unidentified internal states, a necessary step for quantitative descriptions of animal behavior that link environmental cues, internal needs, neuronal activity, and motor outputs.

Social interactions such as mating and fighting are driven by internal emotional states. How can we study internal states of an animal when it cannot tell us its subjective feelings? Especially when the meaning of the animal’s behavior is not clear to us, can we understand the underlying internal states of the animal? In this talk, I will introduce our recent work in which we used male mounting behavior in mice as an example to understand the underlying internal state of the animals. In many animal species, males exhibit mounting behavior toward females as part of the mating behavior repertoire. Interestingly, males also frequently show mounting behavior toward other males of the same species. It is not clear what the underlying motivation is - whether it is reproductive in nature or something distinct. Through detailed analysis of video and audio recordings during social interactions, we found that while male-directed and female-directed mounting behaviors are motorically similar, they can be distinguished by both the presence of ultrasonic vocalization during female-directed mounting (reproductive mounting) and the display of aggression following male-directed mounting (aggressive mounting). Using optogenetics, we further identified genetically defined neural populations in the medial preoptic area (MPOA) that mediate reproductive mounting and the ventrolateral ventromedial hypothalamus (VMHvl) that mediate aggressive mounting. In vivo microendocsopic imaging in MPOA and VMHvl revealed distinct neural ensembles that mainly encode either a reproductive or an aggressive state during which male or female directed mounting occurs. Together, these findings demonstrate that internal states are represented in the hypothalamus and that motorically similar behaviors exhibited under different contexts may reflect distinct internal states.

Neural responses in the visual system are usually not purely visual but depend on behavioural and internal states such as arousal. This dependence is seen both in primary visual cortex (V1) and in subcortical brain structures receiving direct retinal input. In this talk, I will show that modulation by behavioural state arises as early as in the output of the retina.To measure retinal activity in the awake, intact brain, we imaged the synaptic boutons of retinal axons in the superficial superior colliculus (sSC) of mice. The activity of about half of the boutons depended not only on vision but also on running speed and pupil size, regardless of retinal illumination. Arousal typically reduced the boutons’ visual responses to preferred direction and their selectivity for direction and orientation.Arousal may affect activity in retinal boutons by presynaptic neuromodulation. To test whether the effects of arousal occur already in the retina, we recorded from retinal axons in the optic tract. We found that, in darkness, more than one third of the recorded axons was significantly correlated with running speed. Arousal had similar effects postsynaptically, in sSC neurons, independent of activity in V1, the other main source of visual inputs to colliculus. Optogenetic inactivation of V1 generally decreased activity in collicular neurons but did not diminish the effects of arousal. These results indicate that arousal modulates activity at every stage of the visual system. In the future, we will study the purpose and the underlying mechanisms of behavioural modulation in the early visual system

Many innate behaviours are the result of multiple sensorimotor programs that are dynamically coordinated to produce higher-order behaviours such as courtship or architecture construction. Extendend phenotypes such as architecture are especially useful for ethological study because the structure itself is a physical record of behavioural intent. A particularly elegant and easily quantifiable structure is the spider orb-web. The geometric symmetry and regularity of these webs have long generated interest in their behavioural origin. However, quantitative analyses of this behaviour have been sparse due to the difficulty of recording web-making in real-time. To address this, we have developed a novel assay enabling real-time, high-resolution tracking of limb movements and web structure produced by the hackled orb-weaver Uloborus diversus. With its small brain size of approximately 100,000 neurons, the spider U. diversus offers a tractable model organism for the study of complex behaviours. Using deep learning frameworks for limb tracking, and unsupervised behavioural clustering methods, we have developed an atlas of stereotyped movement motifs and are investigating the behavioural state transitions of which the geometry of the web is an emergent property. In addition to tracking limb movements, we have developed algorithms to track the web’s dynamic graph structure. We aim to model the relationship between the spider’s sensory experience on the web and its motor decisions, thereby identifying the sensory and internal states contributing to this sensorimotor transformation. Parallel efforts in our group are establishing 2-photon in vivo calcium imaging protocols in this spider, eventually facilitating a search for neural correlates underlying the internal and sensory state variables identified by our behavioural models. In addition, we have assembled a genome, and are developing genetic perturbation methods to investigate the genetic underpinnings of orb-weaving behaviour. Together, we aim to understand how complex innate behaviours are coordinated by underlying neuronal and genetic mechanisms.