July 2024 - Comp-neuro - lists.cnsorg.org

Ph.D. position in Theoretical and Applied Neuroscience - Deadline 29th July 2024.

by Eleonora Russo

One Ph.D. position is available within the National Ph.D. Program in ‘Theoretical and Applied Neuroscience’. The Ph.D. will be held in the Brain Dynamics Lab<https://www.santannapisa.it/en/institute/biorobotics/brain-dynamics-laborat…> at the Biorobotics Institute of Sant'Anna School of Advanced Studies, Pisa (Italy) in collaboration with the Kelsch Group<http://www.synapticwiring.com/index.html> at the University Medical Center, Johannes Gutenberg University, Mainz (Germany). Information about the call can be found here<https://www.unicam.it/bandi/2024/bando-n0046958-del-28062024>. The deadline for applying to the position is at 13:00 on 29 July 2024. The project description can be found here<https://www.unicam.it/sites/default/files/bandi/2024/06/ANNEX%201_TAN_ciclo…> under ‘Code 4.2’. Project title: Functional modeling of brain dynamics: understanding reinforcement learning through the lens of dynamical systems. Keywords: neural coding, neuronal manifolds, modelling, dynamical system reconstruction, RNN, statistical mechanics, machine learning, reinforcement learning, dopamine. Host Institution: Sant'Anna School of Advanced Studies, BioRobotics Institute Reference person/supervisor: Russo Eleonora; eleonora.russo(a)santannapisa.it Research topic description Understanding the dynamical systems governing neuronal activity is crucial for unraveling how the brain performs cognitive functions. Historically, various forms of recurrent neural networks (RNNs) have been proposed as simplified models of the cortex. Recently, due to remarkable advancements in machine learning, RNNs' ability to capture temporal dependencies has been used to develop tools for approximating unknown dynamical systems by training them on observed time-series data. This approach allows us to use time series of electrophysiological multi-single unit recordings as well as whole brain ultra-high field functional imaging (fMRI) to parametrize neuronal population dynamics and build functional models of cognitive functions. The objective of this research project is to investigate the neuronal mechanisms underlying the reinforcement and depreciation of perceived stimuli in the extended network of the mouse forebrain regions. Research team and environment The PhD student will carry out his/her/their studies primarily at the BioRobotics Institute of Sant'Anna School of Advanced Studies. The project will expose the student to a highly international and interdisciplinary context, in tight collaboration with theoretical and experimental neuroscientists in Italy and abroad. At the BioRobotics Institute, the research groups involved will be the Brain Dynamics Lab, the Computational Neuroengineering Lab, and the Bioelectronics and Bioengineering Area. Moreover, the project will be carried out in tight collaboration with the experimental group of Prof. Wolfgang Kelsch, Johannes Gutenberg University, Mainz, Germany. During the PhD, the student will have the opportunity to spend a period abroad. Preferred Research Skills and Competences The ideal candidate has a strong interest in neuroscience and a background in physics/math/biomedical engineering with computational and programming skills (ideally, knowledge of Matlab and/or Python). The ideal candidate carries out his/her/their work in a diligent, independent, and highly collaborative manner. The project will not require any experimental work. Best wishes, Eleonora Russo --------------------------------------------------------------------------------------------------------------------- Eleonora Russo, Ph.D. PI of the Brain Dynamics Laboratory Assistant Professor at Sant’Anna School of Advanced Studies, The BioRobotics Institute, P.za Martiri della Liberta', 33 56127 Pisa, Italy

July 2, 2024

12th rTAIM Online Seminar | Francesco Prinzi (Uni. Palermo) | 24 July 2024 - 2pm Lisbon Time Zone | Zoom

by steven gouveia

Dear All, Following the 11th rTAIM Online Seminar (by Walter Sinnott-Armstrong, Duke University) available here: https://www.youtube.com/watch?v=iL8fYl-I0d8, we are happy to announce the final seminar of this academic year, the 12th rTAIM Online Seminar, with the participation of Professor Francesco Prinzi (University of Palermo, IT), 24th July 2024, 14h-15h30 Lisbon Time Zone, via Zoom. Title: From Theory to Practice: Overcoming Challenges in Implementing AI-Based CDSSs in Healthcare Abstract: In recent years, the adoption of computer-assisted tools employing Artificial Intelligence (AI) techniques has increased in several fields. These tools, which harness machine-learning and deep-learning architectures, have been pivotal in Medicine with the development of Clinical Decision Support Systems (CDSSs). CDSSs are designed to assist clinicians in critical healthcare processes, where understanding the decision-making process and ensuring system reliability are paramount. Despite the potential of data-driven AI, its application in medicine remains fraught with challenges, including the creation of high-performing yet non-interpretable CDSSs. Consequently, only a few CDSSs have transitioned from theoretical frameworks to clinical practice. Several factors hinder this transition: insufficient clinician involvement in data preparation, limited datasets, a lack of external validation, etc. The engagement of clinicians in model interpretation is crucial, as relying solely on accuracy metrics raises significant concerns about the models' validity. Regulatory agencies have responded by proposing frameworks and guidelines such as the GDPR and the AI Act to address concerns about applications of machine learning models. This presentation aims to elucidate these critical challenges and provide recommendations for implementing reliable CDSS. In particular, the discussion will focus on achieving explainability in AI models, highlighting the importance of transparent and interpretable results. The concept of Trustworthy AI is central to this integration, emphasizing that explainability, one of the key features in trustworthy AI, is essential for developers to technically validate results, for clinicians to align models with clinical literature, and for patients to understand the decisions. The presentation will cover methods to achieve explainability in both shallow and deep learning architectures, considering tabular and image inputs. Additionally, a new paradigm addressing the accuracy-explainability trade-off will be discussed, offering insights into future developments in this field. Short Bio: Francesco Prinzi received his Ph.D. in biomedicine, neuroscience and advanced diagnostics in 2023, University of Palermo. He is currently Assistant Professor at University of Palermo and affiliated with the Computer Laboratory of the University of Cambridge (UK). His research is focused on the development of diagnostic and predictive models through Machine Learning, Explainable Artificial Intelligence and Medical Imaging Analysis methods. Link: https://videoconf-colibri.zoom.us/j/93235662066?pwd=4JGunJeQskC2DOVbALXGu2P… ID Meeting: 932 3566 2066 Password: 761386 We are also happy to announce that the Call for Abstract for the 3rd International Conference on the Ethics of Artificial Intelligence that will happen in the São Miguel Islands in the Azores (Portugal), between 19-25 September 2024 (online and in-person), is OPEN for submissions (notifications of acceptance/rejectance) are given in 7-10 days). Pending peer review/editorial board acceptance, some of the papers accepted at the 3ICEAI will be selected for inclusion in the Palgrave Handbook of the Ethics of Artificial Intelligence, currently under development with Palgrave Macmillan. We will also have the ETHICS OF AI AWARD 2024 (in-person talks only): the best-submitted abstract will receive the opportunity to deliver a special Award Talk similar to a keynote talk (note: the selected author will have the fee waived). You can find the information related to the 3ICEAI here: https://trustaimedicine.weebly.com/3iceai.html Organizer

July 2, 2024

Two postdoc positions in decision-making and learning at the University of Zurich, Switzerland

by mailinglists.4svr4＠simplelogin.com

Postdoc in neuroscience of reward learning The successful candidate will work with Prof. Todd Hare and other SNS Lab researchers on the neuro-computational basis of human learning and decision making using cutting-edge neuroimaging techniques. For example, the successful candidate will work on a project aimed to determine if reward learning and corresponding striatal responses incorporate causal knowledge during Pavlovian conditioning. Using theoretically grounded and empirically verified reward learning predictions – blocking, conditioned inhibition, and overexpectation – we will test how Pavlovian conditioning operates over stimuli that are known to be either causal generators or correlated predicters of reward outcomes. Knowledge of the causal mechanisms should, in principle, determine how a reward learning agent summates predictions over two or more conditioned stimuli and whether a specific conditioned inhibitor will block a given causal state. We will test these hypotheses using modified versions of the standard conditioned inhibition and overexpectation paradigms together with functional neuroimaging. The results of these studies will provide important new insights into the fundamental nature of reward learning. They will reveal if Pavlovian conditioning mechanisms, which are generally thought to be model-free, incorporate model-based knowledge of cause-and-effect relationships in the environment or if instead they remain agnostic about causality and operate via predictiveness alone. https://jobs.uzh.ch/offene-stellen/postdoc-in-neuroscience-of-reward-learni… Postdoc in physiology of learning and decision making The successful candidate will work with Prof. Todd Hare and other SNS Lab researchers on projects testing the dynamic interplay between decision-making and attention, arousal, memory, emotion regulation and executive functions. These studies will make use of eye-tracking, pupil dilation, cardiac and respiratory data in combination with behavioral paradigms, validated questionnaires, and computational modeling. The use of neuroimaging data (EEG, fMRI), pharmacological manipulations, or brain stimulation is also possible. https://jobs.uzh.ch/offene-stellen/postdoc-in-physiology-of-learning-and-de…

July 1, 2024

Postodoc Research Fellow Position at Birkbeck/UCL, London, UK

by Fabrizi, Lorenzo

Dear all, Please see below for a postdoctoral position at the Centre for Brain and Cognitive Development, Birkbeck University of London with Prof. Emily Jones (with co-I’s Dr Lorenzo Fabrizi at University College London and Dr Judith Meek at University College London Hospital). Postdoctoral Researcher at Centre for Brain and Cognitive Development (1864) - Birkbeck, University of London<https://cis7.bbk.ac.uk/vacancy/postdoctoral-researcher-at-centre-for-brain-…> cis7.bbk.ac.uk<https://cis7.bbk.ac.uk/vacancy/postdoctoral-researcher-at-centre-for-brain-…> The project will be examining sensory processing in infants born prematurely and later trajectories of neurodevelopment, using a variety of neurocognitive methods. Infants were recruited as neonates and the postholder will be leading and conducting the follow up visits (when the infant is 18 months). The post would suit someone who is interested in infant development, neurodevelopmental conditions and has experience with infant/toddler EEG and eye tracking. Closing date: 24th July, online interviews: 26th July Lorenzo Fabrizi, PhD Associate Professor Medical Research Foundation Fellow Neuroscience, Physiology and Pharmacology Department Room G17A, Medawar Building Bloomsbury Campus University College London Gower St, London WC1E 6BT office tel. 02031081888 (int. 51888)

July 1, 2024

Open PhD position at the University of Bern

by jeanpascal.pfister＠unibe.ch

The Theoretical Neuroscience Group of the University of Bern is seeking applications for a PhD position, funded by a Swiss National Science Foundation grant titled “Why Spikes?”. This project aims at answering a nearly century-old question in Neuroscience: “What are spikes good for?”. Indeed, since the discovery of action potentials by Lord Adrian in 1926, it has remained largely unknown what the benefits of spiking neurons are, when compared to analog neurons. Traditionally, it has been argued that spikes are good for long-distance communication or for temporally precise computation. However, there is no systematic study that quantitatively compares the communication as well as the computational benefits of spiking neuron w.r.t analog neurons. The aim of the project is to systematically quantify the benefits of spiking at various levels by developing and analyzing appropriate mathematical models. The PhD student will be supervised by Prof. Jean-Pascal Pfister (Theoretical Neuroscience Group, Department of Physiology, University of Bern). The project will involve close collaborations within a highly motivated team as well as regular exchange of ideas with the other theory groups at the institute. The PhD candidates should hold a Master degree in Physics, Mathematics, Computer Science, Computational Neuroscience, Neuroscience or a related field. She/he should have keen interests in developing theories that can be tested experimentally. Preference will be given to candidates with strong mathematical and programming skills. Expertise in stochastic dynamical systems, point processes, control theory, information theory and nonlinear Bayesian filtering will be a plus. The applicant should submit a CV (including contacts of two referees), a statement of research interests, marks obtained for the Master, and the abstract of the Master thesis in electronic format to Jean-Pascal Pfister (jeanpascal.pfister(a)unibe.ch<mailto:jeanpascal.pfister@unibe.ch>) The position is offered for a period of three years and can be extended. Salary scale is provided by the Swiss National Science Foundation (http://www.snf.ch/SiteCollectionDocuments/allg_doktorierende_e.pdf) The application deadline is August 8, 2024, or until the position is filled. ---------------------------------- Prof. Jean-Pascal Pfister Theoretical Neuroscience Group Department of Physiology University of Bern Bühlplatz 5 3012 Bern, Switzerland https://physio.unibe.ch/~pfister/group/ Tel: ++ 41 31 631 87 78

July 1, 2024