Predictive processing offers a unifying view of neural computation, proposing that brains continuously anticipate sensory input and update internal models based on prediction errors. In this talk, I will present converging evidence for the computational mechanisms underlying this framework across human neuroscience and deep neural networks. I will begin with recent work showing that large-scale distributed prediction-error encoding in the human brain directly predicts how sensory representations reorganize through predictive learning. I will then turn to PredNet, a popular predictive coding inspired deep network that has been widely used to model real-world biological vision systems. Using dynamic stimuli generated with our Spatiotemporal Style Transfer algorithm, we demonstrate that PredNet relies primarily on low-level spatiotemporal structure and remains insensitive to high-level content, revealing limits in its generalization capacity. Finally, I will discuss new recurrent vision models that integrate top-down feedback connections with intrinsic neural variability, uncovering a dual mechanism for robust sensory coding in which neural variability decorrelates unit responses, while top-down feedback stabilizes network dynamics. Together, these results outline how prediction error signaling and top-down feedback pathways shape adaptive sensory processing in biological and artificial systems.

Up to 6 PhD positions in Cognitive Neuroscience are available at SISSA, Trieste, starting October 2024. SISSA is an elite postgraduate research institution for Maths, Physics and Neuroscience, located in Trieste, Italy. SISSA operates in English, and its faculty and student community is diverse and strongly international. The Cognitive Neuroscience group (https://phdcns.sissa.it/) hosts 7 research labs that study the neuronal bases of time and magnitude processing, visual perception, motivation and intelligence, language and reading, tactile perception and learning, and neural computation. Our research is highly interdisciplinary; our approaches include behavioural, psychophysics, and neurophysiological experiments with humans and animals, as well as computational, statistical and mathematical models. Students from a broad range of backgrounds (physics, maths, medicine, psychology, biology) are encouraged to apply. This year, one of the PhD scholarships is set aside for joint PhD projects across PhD programs within the Neuroscience department (https://www.sissa.it/research/neuroscience). The selection procedure is now open. The application deadline is 28 March 2024. To learn how to apply, please visit https://phdcns.sissa.it/admission-procedure . Please contact the PhD Coordinator Mathew Diamond (diamond@sissa.it) and/or your prospective supervisor for more information and informal inquiries.

The role The School of Engineering Mathematics and Technology at the University of Bristol is seeking to appoint a Senior Lecturer / Associate Professor whose research encompasses neural computation, machine learning and AI. If you are earlier in your career the post is also available at Lecturer level. The University of Bristol is an exciting centre for research into the nature of computation and inference in humans, animals and machines. Our computational neuroscience group has made important contributions in, for example, Bayesian approaches to data and inference, biomimetic deep learning, anatomically-constrained neural networks and the theory of neural networks. The University has a long tradition of cross-disciplinary research and Computational Neuroscience is part of both the Bristol Neuroscience Network and the Intelligent Systems Group; we are recognised for our central role in the local neuroscience and machine learning/AI communities. You would be joining the University at an exciting time as we embark on a £500M investment in our new campus and while we create a home for the UK’s AI Research Resource with the UK’s most powerful supercomputer. We are committed to an inclusive and diverse environment where everyone can thrive. We welcome applicants from all backgrounds, especially those from under-represented communities. We offer flexible working arrangements to help balance professional and personal commitments. What will you be doing? You will conduct research at the interface between computational neuroscience and machine learning and contribute to the associated teaching on our degree programmes and to academic administration. You will take part in our lively research community and join our internationally renowned researchers in producing high-quality research with the potential to secure research funding.

Assistant Professor in Cognitive Psychology and Neuroscience at Leiden University The Cognitive Psychology Unit at Leiden University (the Netherlands) is inviting candidates to apply for an assistant professor position in cognitive psychology and neuroscience. The position will result in tenure, conditional on a positive probation period of 12-18 months. For the advertisement and application procedure, see https://www.universiteitleiden.nl/vacatures/2023/q1/13481-assistant-professor-in-cognitive-psychology-and-neuroscience

Up to 6 PhD positions in Cognitive Neuroscience are available at SISSA, Trieste, starting October 2023. SISSA is an elite postgraduate research institution for Maths, Physics and Neuroscience, located in Trieste, Italy. SISSA operates in English, and its faculty and student community is diverse and strongly international. The Cognitive Neuroscience Department (https://phdcns.sissa.it/) hosts 7 research labs that study the neuronal bases of time and magnitude processing, visual perception, motivation and intelligence, language and reading, tactile perception and learning, and neural computation. The Department is highly interdisciplinary; our approaches include behavioural, psychophysics, and neurophysiological experiments with humans and animals, as well as computational, statistical and mathematical models. Students from a broad range of backgrounds (physics, maths, medicine, psychology, biology) are encouraged to apply. The selection procedure is now open. The first application deadline is 31 March 2023. To learn how to apply, please visit https://phdcns.sissa.it/admission-procedure. Please contact the PhD Coordinator Mathew Diamond (diamond@sissa.it) and/or your prospective supervisor for more information and informal inquiries.

The Department for Sensory and Sensorimotor Systems of the Max-Planck-Institute for Biological Cybernetics studies the processing of sensory information (visual, auditory, tactile, olfactory) in the brain and the use of this information for directing body movements and making cognitive decisions. The research is highly interdisciplinary and uses theoretical and experimental approaches in humans. Our methodologies include visual psychophysics, eye tracking, fMRI, EEG, TMS in humans. For more information, please visit the department website: www.lizhaoping.org We are currently looking for a Research Operation Assistant with Scientific Experience (m/f/d) 100% to join us at the next possible opportunity. The position: You will provide hardware, software and managerial support for a diverse set of brain and neuroscience research activities. This includes: • Computer and IT support of Windows and Linux systems • Programming and debugging of computer code, especially at the stage of setting up new equipment or new experimental platforms • Provide technical, administrative, and operational support in the research data taking and analysis process. (The position holder should have the ability to quickly learn the data taking processes involved in the labs.) • Responsibility and free decision for purchases of laboratory equipment out to tender and evaluation of quotes with final decision making • Hardware repairs and troubleshooting including consultation of manufacturers, deliverers and scientific staff • Equipment setting up, inventory and maintenance • Supervising and training of new equipment users • Setting up, updating and managing the database of knowledge and data from research projects, personnel and activities to ensure smooth transition from one to another team member Our department is interdisciplinary, with research activities including human visual psychophysics, eye tracking, fMRI, EEG, TMS. We are looking for a person with a broad technical knowledge base, who loves working in a scientific environment and who is curious, open-minded, and able to adapt and learn new skills and solve new problems quickly. The set of skills that the individual should either already have or can quickly learn includes: MATLAB/Psychotoolbox, Python/OpenCV, Julia/OpenGL, Java, graphics and display technologies, EEG equipment and similar, eye tracking, optics, electronics/controllers/sensors, Arduino/Raspberry Pi, etc. We offer: We offer highly interesting, challenging and varied tasks; you will work closely and collaboratively with scientists, students, programmers, administrative staff, and central IT and mechanical/electronic workshop support to help achieve the scientific goals of the department. A dedicated team awaits you in an international environment with regular opportunities for further education and training. The salary is paid in accordance with the collective agreement for the public sector (TVöD Bund), based on qualification and experience and will include social security benefits and additional fringe benefits in accordance with public service provisions. This position is initially limited to two years, with the possibility of extensions and a permanent contract. The Max Planck Society seeks to employ more handicapped people and strongly encourages them to apply. Furthermore, we actively support the compatibility of work and family life. The Max Planck Society also seeks to increase the number of women in leadership positions and strongly encourages qualified women to apply. The Max Planck Society strives for gender equality and diversity. Your application The position is available immediately and will be open until filled. Preference will be given to applications received by April 3rd, 2023. We look forward to receiving your application that includes a cover letter, your curriculum vitae, relevant certificates, and three names and contacts for reference letters electronically by e-mail to jobs.li@tuebingen.mpg.de, where informal inquiries can also be addressed to. Please note that incomplete applications will not be considered. For further opportunities in our group, please visit http://www.lizhaoping.org/jobs.html.

The Insanally Lab is hiring postdocs to study the neural basis of auditory perception and learning. We incorporate a wide range of techniques including behavioral paradigms, in vivo multi-region neural recordings, optogenetics, chemogenetics, fiber photometry, and novel computational methods. Our lab is super supportive, collaborative, and we take mentoring seriously! Located at Pitt, our lab is part of a large systems neuroscience community that includes CNBC and CMU. For inquiries, feel free to reach out to me here: mni@pitt.edu. To find out more about our work, visit Insanallylab.com

The PhD in Medical Sciences: The University of Nicosia Medical School offers the degree PhD in Medical Sciences. The degree is awarded to students who successfully complete an independent research programme that breaks new ground in the chosen field of study. The PhD programme aspires to empower students to become independent researchers, thus advancing innovation and development. The Research Project: We are currently inviting application through a competitive process for high calibre candidates to apply for one PhD Scholarship in the fields of Neuroscience and Biomedical Engineering. The successful candidate will enrol on the PhD programme in Medical Sciences and will work under the Supervision of Dr Nicoletta Nicolaou with expertise in the fields of Neuroscience and Biomedical Engineering at the University of Nicosia Medical School. Project Description: Title of research project: Development of a closed-loop controller for automatic administration of anaesthetic and analgesic agents during surgery using machine learning methods. Background and Rationale: Current practice of anaesthesia during surgery involves administration of a “cocktail” of drugs (anaesthetics, analgesics, myorelaxants) to achieve the desired state of surgical anaesthesia. During surgery the patient is connected to a number of sensors that monitor vital signs (e.g. cardiovascular parameters, breathing etc.). The anaesthesiologist monitors these vital signs (visually on the monitoring device) and makes manual adjustments to the dosages of the different agents (anaesthetics, analgesics, muscle relaxants). In this open-loop approach the anaesthesiologist is effectively the one who manually closes the loop. The disadvantages of this open-loop approach are related mainly to the fact that the anaesthesiologist monitors the vital signs and is required to make a judgement call based on these visual observations as to whether or not adjustments are required to the dosages of the agents administered. These vital signs provide clues as to the underlying patient state, but they are not considered to be reliable indicators of the underlying “level of consciousness” or “depth of anaesthesia”. In a closed-loop system, the loop is closed automatically: the patient state is estimated from the patient vital signs, and the dosages of agents are adjusted automatically by the device. The anaesthesiologist is not part of the automated closed loop, but still has the ability to bypass this automation and intervene manually. Closed-loop (CL) systems provide better stability of cardiovascular parameters (longer duration of heart rate and mean arterial pressure control), better performance and faster recovery compared to open-loop systems. The development of a CL anaesthetic administration system is a very complex process that must integrate information from a number of biological signals coming from the central and autonomic nervous systems. To date there are only a handful of CL systems that have been developed, but not yet routinely available for commercial use in routine surgery. Aims and Objectives: In this PhD Research Project, a CL system for automatic agent administration during surgery under general anaesthesia will be developed and simulated, using machine learning methods. The system will utilize features from the central and autonomic nervous systems (CNS and ANS respectively) for discrimination between awareness, anaesthesia and different levels of anaesthesia (light, surgical, deep anaesthesia). The system will offer improved anaesthetic experience that will be individualized, leading to a better experience (e.g. maintenance at surgical anaesthetic level, stability of cardiovascular activity, less time in recovery, minimal side effects from over-anaesthesia, faster release from hospital). The main aims and objectives of this PhD research project are: 1. Characterize the relationships of real brain and brain-cardiovascular data recorded during surgeries under general anaesthesia using machine learning methods, as well as the relationships between these physiological signals and concentration of anaesthetic and analgesic agents. 2. Develop a closed-loop controller that utilizes the developed machine learning models to automatically modify the volume of anaesthetics and analgesics to achieve and maintain a desired level of (un)consciousness. 3. Develop a simulation that maps an observed or desired anaesthetic state to specific anaesthetic and analgesic dosages. 4. Test the performance of the developed machine learning controller on automatically modifying the anaesthetic and analgesic dosages to maintain a desired level of (un)consciousness as defined in the simulated data. The Scholarship: The Scholarship will have a duration of three to four years and will cover: • The tuition fees for the PhD programme which are €13,500 in total for the first 3 years and €1,500 for year 4. Application for the PhD Scholarship: Candidates should submit an online application through this link (https://www.med.unic.ac.cy/education/phd-in-medical-sciences/?utm_source=PhD-Scholarships-2022) and upload the following supporting documents: • A cover letter clearly stating that they apply for the PhD Scholarship in the fields of Neuroscience and Biomedical Engineering for the PhD Research Project ‘Development of a closed-loop controller for automatic administration of anaesthetic and analgesic agents during surgery using machine learning methods.’ • Copies of the applicant’s qualifications/degree(s) – the application can be assessed with scanned copies, but certified true copies must be provided if the candidate is successful and prior to enrolment on the PhD programme. • Copies of the applicant’s transcript(s) - the application can be assessed with scanned copies, but certified true copies must be provided if the candidate is successful and prior to enrolment on the PhD programme. • Proof of English language proficiency such as IELTS with a score of 7 overall and with a minimum score of 7 in writing or TOEFL iBT with a score of 94 overall and a minimum score of 27 in Writing. Other internationally recognized English language qualifications might be considered upon review. Students from the UK, Ireland USA, Canada (from English speaking provinces), Australia and New Zealand are exempt from the English language requirement. • Two reference letters, of which at least one should be from an academic. • A full Curriculum Vitae (CV). Applications should be submitted by Friday, July 29, 2022 at 5pm. Only fully completed applications, containing all necessary supporting documents will be reviewed. Please use reference number C2 next to your surname when you start your application. Only candidates who are shortlisted will be contacted and invited to an interview.

The PhD in Medical Sciences: The University of Nicosia Medical School offers the degree PhD in Medical Sciences. The degree is awarded to students who successfully complete an independent research programme that breaks new ground in the chosen field of study. The PhD programme aspires to empower students to become independent researchers, thus advancing innovation and development. The Research Project: We are currently inviting application through a competitive process for high calibre candidates to apply for one PhD Scholarship in the field of Neuroscience. The successful candidate will enrol on the PhD programme in Medical Sciences and will work under the Supervision of Prof Avgis Hadjipapas, Professor for Neuroscience and Research Methods at the University of Nicosia Medical School. The project is based on an international collaboration between the University of Nicosia Medical School, (UN) the University Maastricht University Medical Center (MUMC), Maastricht University (MU) and McGill University (McGill U). The project predominantly involves data-analysis (signal processing), which means that a large part of the project can be conducted remotely. Project Description: Title of research project: Characterization of circadian rhythm modulations in intracranial EEG and their relationship to seizure onsets in focal epilepsy Background, rationale and objectives: Epilepsy affects roughly 1% of the population, and about a third of patients have unpredictable seizures which cannot be adequately controlled with medication (Kuhlmann et al., 2018). Therefore, better understanding of seizure generation and improving seizure predictability are central goals in epilepsy research to prevent seizures from occurring. Recent investigations by our own (Mitsis et al., 2020) and other groups (Leguia et al., 2021) have shown that seizure onsets exhibit a tight correlation to certain phases of circadian rhythms, which leads to improved seizure predictability. However, our previous work (Mitsis et al., 2020) only utilized surface EEG. In this project, and based on a collaboration formed between the University of Nicosia Medical School (UN), Maastricht University Medical Center (MUMC), Maastricht University (MU), and McGill University (McGill U), we will address this question by examining intracranial recordings provided by the MUMC partner, obtained directly from the area of the suspected epileptogenic focus. We will first characterize in detail the circadian variation of signal parameters extracted from the intracranial EEG. We will then examine whether seizure onsets are phase coupled (correlated) to these circadian modulations. This will inform both important pathophysiological questions in terms of the extent of the functional seizure generating network. Further, analysis of this correlation at the level of individual patient recordings will inform the feasibility of seizure forecasting informed by circadian rhythms. Successful candidates will benefit from interacting with an international and interdisciplinary consortium of neuroscientists, neurologists and engineers throughout the duration of the project. References Karoly, P.J., Ung, H., Grayden, D.B., Kuhlmann, L., Leyde, K., Cook, M.J., Freestone, D.R., 2017. The circadian profile of epilepsy improves seizure forecasting. Brain 140, 2169–2182. https://doi.org/10.1093/brain/awx173 Kuhlmann, L., Lehnertz, K., Richardson, M.P., Schelter, B., Zaveri, H.P., 2018. Seizure prediction — ready for a new era. Nat. Rev. Neurol. https://doi.org/10.1038/s41582-018-0055-2 Leguia, M.G., Andrzejak, R.G., Rummel, C., Fan, J.M., Mirro, E.A., Tcheng, T.K., Rao, V.R., Baud, M.O., 2021. Seizure Cycles in Focal Epilepsy. JAMA Neurol. In press, 1–10. https://doi.org/10.1001/jamaneurol.2020.5370 Mitsis, G.D., Anastasiadou, M.N., Christodoulakis, M., Papathanasiou, E.S., Papacostas, S.S., Hadjipapas, A., 2020. Functional brain networks of patients with epilepsy exhibit pronounced multiscale periodicities, which correlate with seizure onset. Hum. Brain Mapp. hbm.24930. https://doi.org/10.1002/hbm.24930 The Scholarship: The Scholarship will have a duration of three to four years and will cover: • The tuition fees for the PhD programme which are €13,500 in total for the first 3 years and €1,500 for year 4. • A monthly stipend of €1,000 for the duration of three to four years. Application for the PhD Scholarship: Candidates should submit an online application through this link and upload the following supporting documents: • A cover letter clearly stating that they apply for the PhD Scholarship in the field of Neuroscience for the PhD Research Project ‘Characterization of circadian rhythm modulations in intracranial EEG and their relationship to seizure onsets in focal epilepsy.’ • Copies of the applicant’s qualifications/degree(s) – the application can be assessed with scanned copies, but certified true copies must be provided if the candidate is successful and prior to enrolment on the PhD programme. • Copies of the applicant’s transcript(s) - the application can be assessed with scanned copies, but certified true copies must be provided if the candidate is successful and prior to enrolment on the PhD programme. • Proof of English language proficiency such as IELTS with a score of 7 overall and with a minimum score of 7 in writing or TOEFL iBT with a score of 94 overall and a minimum score of 27 in Writing. Other internationally recognized English language qualifications might be considered upon review. Students from the UK, Ireland USA, Canada (from English speaking provinces), Australia and New Zealand are exempt from the English language requirement. • Two reference letters, of which at least one should be from an academic. • A full Curriculum Vitae (CV). Applications should be submitted by Friday, July 29, 2022 at 5pm. Only fully completed applications, containing all necessary supporting documents will be reviewed. Only candidates who are shortlisted will be contacted and invited to an interview.

Research Fellow / Postdoc positions in Complex Networks and Brain Dynamics We are looking for new team members to join the Complex Networks and Brain Dynamics group to work on its interdisciplinary projects. The group is part of the Department of Complex Systems, Institute of Computer Science of the Czech Academy of Sciences - based in Prague, Czech Republic, https://www.cs.cas.cz/. We focus on the development and application of methods of analysis and modelling of real-world complex networked systems, with particular interest in the structure and dynamics of human brain function. Our main research areas are neuroimaging data analysis (fMRI & EEG, iEEG, anatomical and diffusion MRI), brain dynamics modelling, causality and information flow inference, nonlinearity and nonstationarity, graph theory, machine learning and multivariate statistics; with applications in neuroscience, climate research, economics and general communication networks. More information about the group at http://cobra.cs.cas.cz/. Conditions: • Contract is for 6-24 months duration. • Positions are available immediately or upon agreement. • Applications will be reviewed on a rolling basis with a first cut-off point on 30. 09. 2022, until the positions are filled. • This is a full-time fixed term contract appointment. Part time contract negotiable. • Monthly gross salary: 42 000 – 55 000 CZK based on qualifications and experience. Cost Of Living Comparison • Bonuses and travel funding for conferences and research stays depending on performance. • No teaching duties.

Columbia University’s Mortimer B. Zuckerman Mind Brain Behavior Institute (the Zuckerman Institute) brings together world-class researchers from varied scientific disciplines to explore aspects of mind and brain, through the exchange of ideas and active collaboration. The Zuckerman Institute’s home, the Jerome L. Greene Science Center is a state-of-the-art facility on Columbia’s Manhattanville campus. Situated in the heart of Manhattan in New York City, the Zuckerman Institute houses over 50 laboratories employing a broad range of interdisciplinary approaches to transform our understanding of the mind and brain. In this highly collaborative environment, experimental, computational, and theoretical labs work together to gain critical insights into how the brain develops, performs, endures and recovers. The El-Shamayleh lab within the Zuckerman Institute is seeking a Staff Associate I to study the neural basis of vision. The Staff Associate I will assist in conducting behavioral and neurophysiological studies in large research mammals in a scientific wet-lab environment. The Staff Associate I will be responsible for the following: • Will assist in conducting wet-lab mammal training and the collection of behavioral and neural data. • Will assist in conducting behavioral and neurophysiological studies in research mammals. • Will assist the Principal Investigator in basic surgical procedures, in the daily care of large research mammals, experimental setup and will maintain lab supplies and reagents. Minimum Qualifications Bachelor’s degree in Neuroscience or Biological Sciences, required. At least one year of previous experience working in a wet lab; experience working with large mammals is highly desirable, as is knowledge of visual neuroscience and experience in performing basic surgical techniques. Qualified candidates must be capable of working independently on husbandry and training duties once instructed. Inquiries about this role should be directed to yasmine.shamayleh@columbia.edu and applications can be submitted to https://apply.interfolio.com/105441.

The Georgia Institute of Technology is one of the top ranked institutions in the country and ranks as one of the best places to work. The School of Psychology and Undergraduate Program in Neuroscience in the College of Sciences invites applications for a full-time, non-tenure-track Academic Professional faculty position, which is a Teaching Faculty and Academic Advisor position, beginning July 1st 2022 (earlier start possible). The successful candidate will join a vibrant group of faculty with interests in brain, cognition, behavior and (neuro)technology as well as innovative pedagogy and research in those fields. The Academic Professional faculty member will be primarily responsible for teaching courses in the undergraduate neuroscience curriculum. Additional duties include academic advising, course development, and program assessment. The position provides opportunities for program and professional development, as well as for promotion through the non-tenured faculty track. Preference will be given to applicants who are well prepared to teach neuroscience and who have strong background in quantitative and computational methods. The applicant must have a PhD in neuroscience, psychology or a related discipline and experience with teaching undergraduate neuroscience and/or psychology-related coursework. Applicants should provide a letter of intent, curriculum vita, teaching statement, and the names and contact information for two references. Applications can be submitted electronically in PDF format to (applicant portal). Review of applications will begin immediately and will continue until the position is filled. Georgia Tech is a top-ranked public research university situated in the heart of Atlanta, a diverse and vibrant city with great economic and cultural strengths. The Institute is a member of the University System of Georgia, the Georgia Research Alliance, and the Association of American Universities. Georgia Tech prides itself on its technology resources, collaborations, high-quality student body, and its commitment to diversity, equity, and inclusion. Georgia Tech is an equal education/employment opportunity institution dedicated to building a diverse community. We strongly encourage applications from women, underrepresented minorities, individuals with disabilities, and veterans. Georgia Tech has policies to promote a healthy work-life balance and is aware that attracting faculty may require meeting the needs of two careers.

The Georgia Institute of Technology is one of the top ranked institutions in the country and ranks as one of the best places to work. The School of Psychology and Undergraduate Program in Neuroscience in the College of Sciences invites applications for a full-time, non-tenure-track Academic Professional faculty position, which is a Teaching Faculty and Academic Advisor position, beginning July 1st 2022 (earlier start possible). The successful candidate will join a vibrant group of faculty with interests in brain, cognition, behavior and (neuro)technology as well as innovative pedagogy and research in those fields. The Academic Professional faculty member will be primarily responsible for teaching courses in the undergraduate neuroscience curriculum. Additional duties include academic advising, course development, and program assessment. The position provides opportunities for program and professional development, as well as for promotion through the non-tenured faculty track. Preference will be given to applicants who are well prepared to teach neuroscience and who have strong background in quantitative and computational methods. The applicant must have a PhD in neuroscience, psychology or a related discipline and experience with teaching undergraduate neuroscience and/or psychology-related coursework. Applicants should provide a letter of intent, curriculum vita, teaching statement, and the names and contact information for two references. Applications can be submitted electronically in PDF format to (applicant portal). Review of applications will begin immediately and will continue until the position is filled. Georgia Tech is a top-ranked public research university situated in the heart of Atlanta, a diverse and vibrant city with great economic and cultural strengths. The Institute is a member of the University System of Georgia, the Georgia Research Alliance, and the Association of American Universities. Georgia Tech prides itself on its technology resources, collaborations, high-quality student body, and its commitment to diversity, equity, and inclusion. Georgia Tech is an equal education/employment opportunity institution dedicated to building a diverse community. We strongly encourage applications from women, underrepresented minorities, individuals with disabilities, and veterans. Georgia Tech has policies to promote a healthy work-life balance and is aware that attracting faculty may require meeting the needs of two careers.

Applications are invited for the role of Post-doctoral Researcher at Trinity College Institute of Neuroscience (TCIN). The aim of the project is to elucidate the behavioural and brain processes underpinning combined visual, auditory and haptic object categorization, in children and in adults, and assess the extent to which such categories adapt to changes in task conditions. The research adopts a multidisciplinary approach involving cognitive neuroscience, statistical modelling, and psychophysics. The candidate will work within the Multisensory Cognition lab, headed by Professor Fiona Newell, and will also work in collaboration with Prof. Robert Whelan and his research team. Both groups are based in TCIN and affiliated with the School of Psychology. The Multisensory Cognition lab has dedicated laboratory facility equipped with state-of art facilities for behavioural testing, including eye tracking and VR technology (HTC Vive and Oculus). TCIN also houses a research-dedicated MRI scanner, accessible to all principal investigators and their groups. The position is funded for 2 years initially, with a possibility for continuation, and is available immediately. Ideally, successful candidates are expected to take up the position no later than March 2022. The post-doctoral researcher will join a research team of PhD students, postdoctoral researchers, and a research assistant/lab manager and have the opportunity to collaborate with colleagues within the Institute of Neuroscience, across other disciplines in Trinity College, and industrial partners. They will participate in regular lab and collaborator meetings, learn about diverse methodologies in perceptual science and have the opportunity to attend major international conferences in the field. Funding Information The position is funded by Science Foundation Ireland, from a Future Frontiers Award to Fiona Newell (Principal Investigator).

The PhD in Medical Sciences: The University of Nicosia Medical School offers the degree PhD in Medical Sciences. The degree is awarded to students who successfully complete an independent research programme that breaks new ground in the chosen field of study. The PhD programme aspires to empower students to become independent researchers, thus advancing innovation and development. The Research Project: We are currently inviting application through a competitive process for high calibre candidates to apply for the below PhD Project in the field of Neuroscience. The successful candidate will enrol on the PhD programme in Medical Sciences and will work under the Supervision of Dr Avgis Hadjipapas, Professor of Neuroscience and Research Methods at the University of Nicosia Medical School. The project is based on an international collaboration between the University of Nicosia Medical School, and Maastricht University (MU). Project Description: Title of research project: Laminar interactions and information flow in primary visual cortex. Background, rationale and objectives: Understanding how neuronal networks in the brain communicate in order to perform various computations is a major goal of systems neuroscience today. Networks in the cortex are exquisitely organized in layers and form well defined and repeating microcircuits (Gilbert and Wiesel, 1983). The anatomical connectivity between layers and the single cell behaviour in these layers have been studied in the past leading to important insights into the workings of the cortical circuit (reviewed in (Bastos et al., 2012)). At the same time, it has become clear that neurons engage in synchronous oscillations in the gamma band (20-90Hz). These have been observed in all laminar compartments of the cortex (Maier et al., 2010; Roberts et al., 2013; Xing et al., 2012). How are these oscillations to be reconciled with the laminar structure of the cortical microcircuits? Does the presence of oscillations constrain the way that layers communicate with each other? What is the means of communication between layers in the presence of these oscillations? These are important open questions that this project will help address. The main aim of the project will be to characterize interactions between different laminar compartments, and the observed frequencies of the oscillations expressed in these compartments. This search for interactions is theoretically- motivated; the main argument is that laminar compartments can be viewed as weakly coupled oscillators and therefore powerful concepts of synchronization theory apply. Depending on the relationship between the expressed oscillation frequencies in each compartment and their anatomical coupling, synchronization can be employed to derive theoretical predictions(Hadjipapas et al., 2009; Lowet et al., 2017, 2015). Among other possibilities, it is possible that directed interactions between laminar compartments may ensue, resulting in a directed flow of information across the cortical circuit (Ferro et al., 2021; van Kerkoerle et al., 2014). In directed interactions, frequency differences between laminar compartments are important because these, shape the ensuing synchronization process (Hadjipapas et al., 2009; Lowet et al., 2017, 2015). Directed interactions may be important to prioritize feedforward (bottom-up) influences from feedback influences (top down) when these are required by the stimulus or task at hand. In this project interactions across laminar compartments will be characterized and the information flow between compartments will be examined as a function of stimulus luminance contrast (bottom up input) and attention (top down input). This will be pursued in already existing data acquired by laminar probes in the awake behaving monkey, provided by the Maastricht collaboration. This data allows for the characterization of oscillations across laminar compartments. A computational neuronal model for communication between the layers will also be produced , which will be constrained by the data similar to the approach taken in (Zachariou et al., 2021). This model will aid data interpretations and produce further testable predictions. In sum, this project aims to help reconcile oscillatory activity with appropriate/adaptive information flow in the cortical circuit by producing a framework for studying the interactions within the fundamental cortical circuit including a computational model. Successful candidates will further benefit from interacting with an international consortium of neuroscientists throughout the duration of the project. References Bastos, A.M., Usrey, W.M., Adams, R.A., Mangun, G.R., Fries, P., Friston, K.J., 2012. Canonical Microcircuits for Predictive Coding. Neuron 76, 695–711. https://doi.org/10.1016/j.neuron.2012.10.038 Ferro, D., Kempen, J. van, Boyd, M., Panzeri, S., Thiele, A., 2021. Directed information exchange between cortical layers in macaque V1 and V4 and its modulation by selective attention. Proc. Natl. Acad. Sci. 118. https://doi.org/10.1073/PNAS.2022097118 Gilbert, C.D., Wiesel, T.N., 1983. Functional Organization of the Visual Cortex. Prog. Brain Res. 58, 209–218. https://doi.org/10.1016/S0079-6123(08)60022-9 Hadjipapas, A, Casagrande, E., Nevado, A., Barnes, G.R., Green, G., Holliday, I.E., 2009. Can we observe collective neuronal activity from macroscopic aggregate signals? Neuroimage 44, 1290–1303. Lowet, E., Roberts, M., Hadjipapas, A., Peter, A., van der Eerden, J., De Weerd, P., 2015. Input-Dependent Frequency Modulation of Cortical Gamma Oscillations Shapes Spatial Synchronization and Enables Phase Coding. PLOS Comput. Biol. 11, e1004072. https://doi.org/10.1371/journal.pcbi.1004072 Lowet, E., Roberts, M.J., Peter, A., Gips, B., Weerd, P. De, 2017. A quantitative theory of gamma synchronization in macaque V1 1–44. Maier, A., Adams, G.K., Aura, C., Leopold, D. a, 2010. Distinct superficial and deep laminar domains of activity in the visual cortex during rest and stimulation. Front. Syst. Neurosci. 4, 1–11. https://doi.org/10.3389/fnsys.2010.00031 Roberts, M.J., Lowet, E., Brunet, N.M., Ter Wal, M., Tiesinga, P., Fries, P., De Weerd, P., 2013. Robust gamma coherence between macaque V1 and V2 by dynamic frequency matching. Neuron 78, 523–36. https://doi.org/10.1016/j.neuron.2013.03.003 van Kerkoerle, T., Self, M.W., Dagnino, B., Gariel-Mathis, M.A., Poort, J., van der Togt, C., Roelfsema, P.R., 2014. Alpha and gamma oscillations characterize feedback and feedforward processing in monkey visual cortex. Proc Natl Acad Sci U S A 111, 14332–14341. https://doi.org/10.1073/pnas.1402773111 Xing, D., Yeh, C.-I., Burns, S., Shapley, R.M., 2012. Laminar analysis of visually evoked activity in the primary visual cortex. Proc. Natl. Acad. Sci. U. S. A. 109, 13871–6. https://doi.org/10.1073/pnas.1201478109 Zachariou, M., Roberts, M., Lowet, E., De Weerd, P., Hadjipapas, A., 2021. Empirically constrained network models for contrast-dependent modulation of gamma rhythm in V1. Neuroimage 229, 117748. https://doi.org/10.1016/j.neuroimage.2021.117748 Tuition Fees: The tuition fees are €13,500 in total for the first 3 years. For each additional academic year, tuition is €1,500 per year. Application for the PhD Research Project: Candidates should submit an online application through this link (https://bit.ly/2Zet5QZ) and upload the following supporting documents: • A cover letter clearly stating that they apply for the PhD Research Project in the field of Neuroscience ‘Laminar interactions and information flow in primary visual cortex.’ • Copies of the applicant’s qualifications/degree(s) – the application can be assessed with scanned copies, but certified true copies must be provided if the candidate is successful and prior to enrolment on the PhD programme. • Copies of the applicant’s transcript(s) - the application can be assessed with scanned copies, but certified true copies must be provided if the candidate is successful and prior to enrolment on the PhD programme. • Proof of English language proficiency: the candidate should either complete previous degree(s) in an English-speaking country or should have passed IELTS (score of 7 overall, with a minimum score of 7 in writing) or should have achieved an equivalent score in an internationally recognized English language qualification. • Two reference letters, of which at least one should be from an academic. • A full Curriculum Vitae (CV).

Up to 2 PhD positions in Cognitive Neuroscience are available at SISSA, Trieste, starting October 2024. SISSA is an elite postgraduate research institution for Maths, Physics and Neuroscience, located in Trieste, Italy. SISSA operates in English, and its faculty and student community is diverse and strongly international. The Cognitive Neuroscience group (https://phdcns.sissa.it/) hosts 6 research labs that study the neuronal bases of time and magnitude processing, visual perception, motivation and intelligence, language, tactile perception and learning, and neural computation. Our research is highly interdisciplinary; our approaches include behavioural, psychophysics, and neurophysiological experiments with humans and animals, as well as computational, statistical and mathematical models. Students from a broad range of backgrounds (physics, maths, medicine, psychology, biology) are encouraged to apply. The selection procedure is now open. The application deadline is 27 August 2024. Please apply here (https://www.sissa.it/bandi/ammissione-ai-corsi-di-philosophiae-doctor-posizioni-cofinanziate-dal-fondo-sociale-europeo), and see the admission procedure page (https://phdcns.sissa.it/admission-procedure) for more information. Note that the positions available for the Fall admission round are those funded by the "Fondo Sociale Europeo Plus", accessible through the first link above. Please contact the PhD Coordinator Mathew Diamond (diamond@sissa.it) and/or your prospective supervisor for more information and informal inquiries.

In this talk, I will discuss the OpenNeuro Fitlins GLM package and provide an illustration of the analytic workflow. OpenNeuro FitLins GLM is a semi-automated pipeline that reduces barriers to analyzing task-based fMRI data from OpenNeuro's 600+ task datasets. Created for psychology, psychiatry and cognitive neuroscience researchers without extensive computational expertise, this tool automates what is largely a manual process and compilation of in-house scripts for data retrieval, validation, quality control, statistical modeling and reporting that, in some cases, may require weeks of effort. The workflow abides by open-science practices, enhancing reproducibility and incorporates community feedback for model improvement. The pipeline integrates BIDS-compliant datasets and fMRIPrep preprocessed derivatives, and dynamically creates BIDS Statistical Model specifications (with Fitlins) to perform common mass univariate [GLM] analyses. To enhance and standardize reporting, it generates comprehensive reports which includes design matrices, statistical maps and COBIDAS-aligned reporting that is fully reproducible from the model specifications and derivatives. OpenNeuro Fitlins GLM has been tested on over 30 datasets spanning 50+ unique fMRI tasks (e.g., working memory, social processing, emotion regulation, decision-making, motor paradigms), reducing analysis times from weeks to hours when using high-performance computers, thereby enabling researchers to conduct robust single-study, meta- and mega-analyses of task fMRI data with significantly improved accessibility, standardized reporting and reproducibility.

Understanding the neural mechanisms of reward-guided learning is a long-standing goal of computational neuroscience. Recent methodological innovations enable us to collect ever larger neural and behavioral datasets. This presents opportunities to achieve greater understanding of learning in the brain at scale, as well as methodological challenges. In the first part of the talk, I will discuss our recent insights into the mechanisms by which zebra finch songbirds learn to sing. Dopamine has been long thought to guide reward-based trial-and-error learning by encoding reward prediction errors. However, it is unknown whether the learning of natural behaviours, such as developmental vocal learning, occurs through dopamine-based reinforcement. Longitudinal recordings of dopamine and bird songs reveal that dopamine activity is indeed consistent with encoding a reward prediction error during naturalistic learning. In the second part of the talk, I will talk about recent work we are doing at DeepMind to develop tools for automatically discovering interpretable models of behavior directly from animal choice data. Our method, dubbed CogFunSearch, uses LLMs within an evolutionary search process in order to "discover" novel models in the form of Python programs that excel at accurately predicting animal behavior during reward-guided learning. The discovered programs reveal novel patterns of learning and choice behavior that update our understanding of how the brain solves reinforcement learning problems.

n the neurosciences the need for some 'overarching' theory is sometimes expressed, but it is not always obvious what is meant by this. One can perhaps agree that in modern science observation and experimentation is normally complemented by 'theory', i.e. the development of theoretical concepts that help guiding and evaluating experiments and measurements. A deeper discussion of 'brain theory' will require the clarification of some further distictions, in particular: theory vs. model and brain research (and its theory) vs. neuroscience. Other questions are: Does a theory require mathematics? Or even differential equations? Today it is often taken for granted that the whole universe including everything in it, for example humans, animals, and plants, can be adequately treated by physics and therefore theoretical physics is the overarching theory. Even if this is the case, it has turned out that in some particular parts of physics (the historical example is thermodynamics) it may be useful to simplify the theory by introducing additional theoretical concepts that can in principle be 'reduced' to more complex descriptions on the 'microscopic' level of basic physical particals and forces. In this sense, brain theory may be regarded as part of theoretical neuroscience, which is inside biophysics and therefore inside physics, or theoretical physics. Still, in neuroscience and brain research, additional concepts are typically used to describe results and help guiding experimentation that are 'outside' physics, beginning with neurons and synapses, names of brain parts and areas, up to concepts like 'learning', 'motivation', 'attention'. Certainly, we do not yet have one theory that includes all these concepts. So 'brain theory' is still in a 'pre-newtonian' state. However, it may still be useful to understand in general the relations between a larger theory and its 'parts', or between microscopic and macroscopic theories, or between theories at different 'levels' of description. This is what I plan to do.

Astrocytes release glutamate by regulated exocytosis in health and disease Vladimir Parpura, International Translational Neuroscience Research Institute, Zhejiang Chinese Medical University, Hangzhou, P.R. China Parpura will present you with the evidence that astrocytes, a subtype of glial cells in the brain, can exocytotically release the neurotransmitter glutamate and how this release is regulated. Spatiotemporal characteristic of vesicular fusion that underlie glutamate release in astrocytes will be discussed. He will also present data on a translational project in which this release pathway can be targeted for the treatment of glioblastoma, the deadliest brain cancer.

Understanding the neural mechanisms of reward-guided learning is a long-standing goal of computational neuroscience. Recent methodological innovations enable us to collect ever larger neural and behavioral datasets. This presents opportunities to achieve greater understanding of learning in the brain at scale, as well as methodological challenges. In the first part of the talk, I will discuss our recent insights into the mechanisms by which zebra finch songbirds learn to sing. Dopamine has been long thought to guide reward-based trial-and-error learning by encoding reward prediction errors. However, it is unknown whether the learning of natural behaviours, such as developmental vocal learning, occurs through dopamine-based reinforcement. Longitudinal recordings of dopamine and bird songs reveal that dopamine activity is indeed consistent with encoding a reward prediction error during naturalistic learning. In the second part of the talk, I will talk about recent work we are doing at DeepMind to develop tools for automatically discovering interpretable models of behavior directly from animal choice data. Our method, dubbed CogFunSearch, uses LLMs within an evolutionary search process in order to "discover" novel models in the form of Python programs that excel at accurately predicting animal behavior during reward-guided learning. The discovered programs reveal novel patterns of learning and choice behavior that update our understanding of how the brain solves reinforcement learning problems.

Neuroscience is experiencing unprecedented growth in dataset size both within individual brains and across populations. Large-scale, multimodal datasets are transforming our understanding of brain structure and function, creating opportunities to address previously unexplored questions. However, managing this increasing data volume requires new training and technology approaches. Modern data technologies are reshaping neuroscience by enabling researchers to tackle complex questions within a Ph.D. or postdoctoral timeframe. I will discuss cloud-based platforms such as brainlife.io, that provide scalable, reproducible, and accessible computational infrastructure. Modern data technology can democratize neuroscience, accelerate discovery and foster scientific transparency and collaboration. Concrete examples will illustrate how these technologies can be applied to mapping brain connectivity, studying human learning and development, and developing predictive models for traumatic brain injury (TBI). By integrating cloud computing and scalable data-sharing frameworks, neuroscience can become more impactful, inclusive, and data-driven..

Join Us for the Memory Decoding Journal Club! A collaboration of the Carboncopies Foundation and BPF Aspirational Neuroscience. This time, we’re diving into a groundbreaking paper: "Motor learning selectively strengthens cortical and striatal synapses of motor engram neurons

Join us for the Memory Decoding Journal Club, a collaboration between the Carboncopies Foundation and BPF Aspirational Neuroscience. This month, we're diving into a groundbreaking paper: 'Reconstructing a new hippocampal engram for systems reconsolidation and remote memory updating' by Bo Lei, Bilin Kang, Yuejun Hao, Haoyu Yang, Zihan Zhong, Zihan Zhai, and Yi Zhong from Tsinghua University, Beijing Academy of Artificial Intelligence, IDG/McGovern Institute of Brain Research, and Peking Union Medical College. Dr. Randal Koene will guide us through an engaging discussion on these exciting findings and their implications for neuroscience and memory research.

The COSYNE 2025 conference was held in Montreal with post-conference workshops in Mont-Tremblant, continuing to provide a premier forum for computational and systems neuroscience. Attendees exchanged cutting-edge research in a single-track main meeting and in-depth specialized workshops, reflecting Cosyne’s mission to understand how neural systems function:contentReference[oaicite:6]{index=6}:contentReference[oaicite:7]{index=7}.

Over the past thirty years or so, cognitive neuroscience has made spectacular progress understanding the biological mechanisms of consciousness. Consciousness science, as this field is now sometimes called, was not only inexistent thirty years ago, but its very name seemed like an oxymoron: how can there be a science of consciousness? And yet, despite this scepticism, we are now equipped with a rich set of sophisticated behavioural paradigms, with an impressive array of techniques making it possible to see the brain in action, and with an ever-growing collection of theories and speculations about the putative biological mechanisms through which information processing becomes conscious. This is all good and fine, even promising, but we also seem to have thrown the baby out with the bathwater, or at least to have forgotten it in the crib: consciousness is not just mechanisms, it’s what it feels like. In other words, while we know thousands of informative studies about access-consciousness, we have little in the way of phenomenal consciousness. But that — what it feels like — is truly what “consciousness” is about. Understanding why it feels like something to be me and nothing (panpsychists notwithstanding) for a stone to be a stone is what the field has always been after. However, while it is relatively easy to study access-consciousness through the contrastive approach applied to reports, it is much less clear how to study phenomenology, its structure and its function. Here, I first overview work on what consciousness does (the "how"). Next, I ask what difference feeling things makes and what function phenomenology might play. I argue that subjective experience has intrinsic value and plays a functional role in everything that we do.

This webinar brings together three leaders in theoretical and computational neuroscience—Larry Abbott, Haim Sompolinsky, and Terry Sejnowski—to discuss how neural circuits generate fundamental aspects of the mind. Abbott illustrates mechanisms in electric fish that differentiate self-generated electric signals from external sensory cues, showing how predictive plasticity and two-stage signal cancellation mediate a sense of self. Sompolinsky explores attractor networks, revealing how discrete and continuous attractors can stabilize activity patterns, enable working memory, and incorporate chaotic dynamics underlying spontaneous behaviors. He further highlights the concept of object manifolds in high-level sensory representations and raises open questions on integrating connectomics with theoretical frameworks. Sejnowski bridges these motifs with modern artificial intelligence, demonstrating how large-scale neural networks capture language structures through distributed representations that parallel biological coding. Together, their presentations emphasize the synergy between empirical data, computational modeling, and connectomics in explaining the neural basis of cognition—offering insights into perception, memory, language, and the emergence of mind-like processes.

This webinar convened researchers at the intersection of Artificial Intelligence and Neuroscience to investigate how large language models (LLMs) can serve as valuable “model organisms” for understanding human language processing. Presenters showcased evidence that brain recordings (fMRI, MEG, ECoG) acquired while participants read or listened to unconstrained speech can be predicted by representations extracted from state-of-the-art text- and speech-based LLMs. In particular, text-based LLMs tend to align better with higher-level language regions, capturing more semantic aspects, while speech-based LLMs excel at explaining early auditory cortical responses. However, purely low-level features can drive part of these alignments, complicating interpretations. New methods, including perturbation analyses, highlight which linguistic variables matter for each cortical area and time scale. Further, “brain tuning” of LLMs—fine-tuning on measured neural signals—can improve semantic representations and downstream language tasks. Despite open questions about interpretability and exact neural mechanisms, these results demonstrate that LLMs provide a promising framework for probing the computations underlying human language comprehension and production at multiple spatiotemporal scales.

Each year the Bernstein Network invites the international computational neuroscience community to the annual Bernstein Conference for intensive scientific exchange:contentReference[oaicite:8]{index=8}. Bernstein Conference 2024, held in Frankfurt am Main, featured discussions, keynote lectures, and poster sessions, and has established itself as one of the most renowned conferences worldwide in this field:contentReference[oaicite:9]{index=9}:contentReference[oaicite:10]{index=10}.

Keynote Address to British Association of Cognitive Neuroscience, London, 10th September 2024

Organised by FENS in partnership with the Austrian Neuroscience Association and the Hungarian Neuroscience Society, the FENS Forum 2024 will take place on 25–29 June 2024 in Vienna, Austria:contentReference[oaicite:0]{index=0}. The FENS Forum is Europe’s largest neuroscience congress, covering all areas of neuroscience from basic to translational research:contentReference[oaicite:1]{index=1}.

Advancements in cognitive neuroscience have provided profound insights into the workings of the human brain and the methods used offer opportunities to enhance performance, cognition, and mental health. Drawing upon interdisciplinary collaborations in the University of California San Diego, Human Performance Optimization Lab, this talk explores the application of cognitive neuroscience principles in three domains to improve human performance and alleviate mental health challenges. The first section will discuss studies addressing the role of vision and oculomotor function in athletic performance and the potential to train these foundational abilities to improve performance and sports outcomes. The second domain considers the use of electrophysiological measurements of the brain and heart to detect, and possibly predict, errors in manual performance, as shown in a series of studies with surgeons as they perform robot-assisted surgery. Lastly, findings from clinical trials testing personalized interventional treatments for mood disorders will be discussed in which the temporal and spatial parameters of transcranial magnetic stimulation (TMS) are individualized to test if personalization improves treatment response and can be used as predictive biomarkers to guide treatment selection. Together, these translational studies use the measurement tools and constructs of cognitive neuroscience to improve human performance and well-being.

Recent insights from auditory neuroscience provide a new perspective on how the brain encodes speech. Using these recent insights, I will provide an overview of key factors underpinning individual differences in children’s development of language and phonology, providing a context for exploring atypical reading development (dyslexia). Children with dyslexia are relatively insensitive to acoustic cues related to speech rhythm patterns. This lack of rhythmic sensitivity is related to the atypical neural encoding of rhythm patterns in speech by the brain. I will describe our recent data from infants as well as children, demonstrating developmental continuity in the key neural variables.

Understanding how macroscale brain dynamics are shaped by microscale mechanisms is crucial in neuroscience. We investigate this relationship in animal models by directly manipulating cellular properties and measuring whole-brain responses using resting-state fMRI. Specifically, we explore the impact of chemogenetically neuromodulating D1 medium spiny neurons in the dorsomedial caudate putamen (CPdm) on BOLD dynamics within a striato-thalamo-cortical circuit in mice. Our findings indicate that CPdm neuromodulation alters BOLD dynamics in thalamic subregions projecting to the dorsomedial striatum, influencing both local and inter-regional connectivity in cortical areas. This study contributes to understanding structure–function relationships in shaping inter-regional communication between subcortical and cortical levels.

We are very much looking forward to host Francisca Ferreira and Birte Forstmann on December 14th, 2023, at noon ET / 6PM CET. Francisca Ferreira is a PhD student and Neurosurgery trainee at the University College of London Queen Square Institute of Neurology and a Royal College of Surgeons “Emerging Leaders” program laureate. Her presentation title will be: “Microstructural and connectivity correlates of outcome variability in functional neurosurgery for movement disorders”. Birte Forstmann, PhD, is the Director of the Amsterdam Brain and Cognition Center, a Professor of Cognitive Neuroscience at the University of Amsterdam, and a Professor by Special Appointment of Neuroscientific Testing of Psychological Models at the University of Leiden. Besides her scientific presentation (“Imaging the human subcortex”), she will give us a glimpse at the “Person behind the science”. You can register via talks.stimulatingbrains.org to receive the (free) Zoom link!

Psychology and neuroscience are increasingly looking to fine-grained analyses of decision-making behaviour, seeking to characterise not just the variation between subjects but also a subject's variability across time. When analysing the behaviour of each subject in a choice task, we ideally want to know not only when the subject has learnt the correct choice rule but also what the subject tried while learning. I introduce a simple but effective Bayesian approach to inferring the probability of different choice strategies at trial resolution. This can be used both for inferring when subjects learn, by tracking the probability of the strategy matching the target rule, and for inferring subjects use of exploratory strategies during learning. Applied to data from rodent and human decision tasks, we find learning occurs earlier and more often than estimated using classical approaches. Around both learning and changes in the rewarded rules the exploratory strategies of win-stay and lose-shift, often considered complementary, are consistently used independently. Indeed, we find the use of lose-shift is strong evidence that animals have latently learnt the salient features of a new rewarded rule. Our approach can be extended to any discrete choice strategy, and its low computational cost is ideally suited for real-time analysis and closed-loop control.

With this webinar series, the ALBA Disability & Accessibility Working Group aims to bring down the ivory tower of ableism among the brain research community, one extraordinary neuroscientist at a time. These webinars give a platform to scientists with disabilities across the globe and neuroscience disciplines, while reflecting on how to promote inclusive working environments and accessibility to research. For this 4th episode, Dr. Maria José Diógenes (iMM - ULisboa, PT) will talk about how her personal story changed her professional life: from the pharmacy to the laboratory bench and from ageing to Rett Syndrome.

Neural entrainment has become a phenomenon of exceptional interest to neuroscience, given its involvement in rhythm perception, production, and overt synchronized behavior. Yet, traditional methods fail to quantify neural entrainment due to a misalignment with its fundamental definition (e.g., see Novembre and Iannetti, 2018; Rajandran and Schupp, 2019). The definition of entrainment assumes that endogenous oscillatory brain activity undergoes dynamic frequency adjustments to synchronize with environmental rhythms (Lakatos et al., 2019). Following this definition, we recently developed a method sensitive to this process. Our aim was to isolate from the electroencephalographic (EEG) signal an oscillatory component that is attuned to the frequency of a rhythmic stimulation, hypothesizing that the oscillation would adaptively speed up and slow down to achieve stable synchronization over time. To induce and measure these adaptive changes in a controlled fashion, we developed the event-related frequency adjustment (ERFA) paradigm (Rosso et al., 2023). A total of twenty healthy participants took part in our study. They were instructed to tap their finger synchronously with an isochronous auditory metronome, which was unpredictably perturbed by phase-shifts and tempo-changes in both positive and negative directions across different experimental conditions. EEG was recorded during the task, and ERFA responses were quantified as changes in instantaneous frequency of the entrained component. Our results indicate that ERFAs track the stimulus dynamics in accordance with the perturbation type and direction, preferentially for a sensorimotor component. The clear and consistent patterns confirm that our method is sensitive to the process of frequency adjustment that defines neural entrainment. In this Virtual Journal Club, the discussion of our findings will be complemented by methodological insights beneficial to researchers in the fields of rhythm perception and production, as well as timing in general. We discuss the dos and don’ts of using instantaneous frequency to quantify oscillatory dynamics, the advantages of adopting a multivariate approach to source separation, the robustness against the confounder of responses evoked by periodic stimulation, and provide an overview of domains and concrete examples where the methodological framework can be applied.

A central question in neuroscience is how the structure of brain circuits determines their activity and function. To explore this systematically, we developed a 230,000-neuron model of mouse primary visual cortex (area V1). The model integrates a broad array of experimental data:Distribution and morpho-electric properties of different neuron types in V1.

The COSYNE 2023 conference provided an inclusive forum for exchanging experimental and theoretical approaches to problems in systems neuroscience, continuing the tradition of bringing together the computational neuroscience community:contentReference[oaicite:5]{index=5}. The main meeting was held in Montreal followed by post-conference workshops in Mont-Tremblant, fostering intensive discussions and collaboration.

Neuromatch 5 (Neuromatch Conference 2022) was a fully virtual conference focused on computational neuroscience broadly construed, including machine learning work with explicit biological links:contentReference[oaicite:11]{index=11}. After four successful Neuromatch conferences, the fifth edition consolidated proven innovations from past events, featuring a series of talks hosted on Crowdcast and flash talk sessions (pre-recorded videos) with dedicated discussion times on Reddit:contentReference[oaicite:12]{index=12}.

The annual Cosyne meeting provides an inclusive forum for the exchange of empirical and theoretical approaches to problems in systems neuroscience, in order to understand how neural systems function:contentReference[oaicite:2]{index=2}. The main meeting is single-track, with invited talks selected by the Executive Committee and additional talks and posters selected by the Program Committee based on submitted abstracts:contentReference[oaicite:3]{index=3}. The workshops feature in-depth discussion of current topics of interest in a small group setting:contentReference[oaicite:4]{index=4}.