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Although stress can be considered as an ongoing process that helps an organism to cope with present and future challenges, when it is too intense or uncontrollable, it can lead to adverse consequences for physical and mental health. Social stress specifically, is a highly prevalent traumatic experience, present in multiple contexts, such as war, bullying and interpersonal violence, and it has been linked with increased risk for major depression and anxiety disorders. Nevertheless, not all individuals exposed to strong stressful events develop psychopathology, with the mechanisms of resilience and vulnerability being still under investigation. During this talk, I will identify key gaps in our knowledge about stress vulnerability and I will present our recent data from our contextual fear learning protocol based on social defeat stress in mice.

The Varela lab is expanding, and we are excited to announce a new postdoctoral position to grow our current team in the Psychology Department at Florida State University (https://varelalab.create.fsu.edu/). Start date flexible within 2024. 1-2 years with possibility of extension. About us: The Varela Laboratory is dedicated to understanding the neural underpinnings of learning and memory in rodents, with a strong focus on investigating the role of the thalamus in sleep-dependent memory consolidation. We employ a wide array of cutting-edge neuroscience techniques, including electrode recordings in freely behaving rodents, closed-loop brain activity manipulations, optogenetics, and computational approaches. *** What you get *** • Work on exciting and impactful projects aimed at understanding the role of higher-order thalamic circuits in learning and memory. • Develop research skills utilizing state-of-the-art techniques in systems, behavioral and computational neuroscience. • Receive mentorship within a supportive lab environment situated in a large, multidisciplinary department spanning work in neuroscience and psychology (https://psychology.fsu.edu/).

A postdoctoral position is available in Dr. Tom Franken’s laboratory in the Department of Neuroscience at the Washington University School of Medicine in St. Louis. The project will study the neural circuits that parse visual scenes into organized collections of objects. We use a variety of techniques including high-density electrophysiology, behavior, optogenetics, and viral targeting in non-human primates. For more information on the lab, please visit sites.wustl.edu/frankenlab/. The PI is committed to mentoring and to nurturing a creative, thoughtful and collaborative lab culture. The laboratory is in an academic setting in the Department of Neuroscience at the Washington University School of Medicine in St. Louis, a large and collaborative scientific community. This provides an ideal environment to train, conduct research, and launch a career in science. Postdoctoral appointees at Washington University receive a competitive salary and a generous benefits package (hr.wustl.edu/benefits/). WashU Neuroscience is consistently ranked as one of the top 10 places worldwide for neuroscience research and offers an outstanding interdisciplinary training environment for early career researchers. In addition to high-quality research facilities, career and professional development training for postdoctoral researchers is provided through the Career Center, Teaching Center, Office of Postdoctoral Affairs, and campus groups. St. Louis is a city rich in culture, green spaces, free museums, world-class restaurants, and thriving music and arts scenes. On top of it all, St. Louis is affordable and commuting to campus is stress-free, whether you go by foot, bike, public transit, or car. The area combines the attractions of a major city with affordable lifestyle opportunities (postdoc.wustl.edu/prospective-postdocs/why-st-louis/). Washington University is dedicated to building a diverse community of individuals who are committed to contributing to an inclusive environment – fostering respect for all and welcoming individuals from diverse backgrounds, experiences and perspectives. Individuals with a commitment to these values are encouraged to apply. Additional information on being a postdoc at Washington University in St. Louis can be found at neuroscience.wustl.edu/education/postdoctoral-research/ and postdoc.wustl.edu/prospective-postdocs. Required Qualifications Ph.D. (or equivalent doctoral) degree in neuroscience (broadly defined). Strong background in either electrophysiology, behavioral techniques or scientific programming/machine learning. Preferred Qualifications Experience with training of larger animals. Experience with electrophysiology. Experience with studies of the visual system. Ability to think creatively to solve problems. Well organized and attention to detail. Excellent oral and written communication skills. Team player with a high level of initiative and motivation. Working Conditions This position works in a laboratory environment with potential exposure to biological and chemical hazards. The individual must be physically able to wear protective equipment and to provide standard care to research animals. Salary Range Base pay is commensurate with experience. Applicant Special Instructions Applicants should submit the following materials to Dr. Tom Franken at ftom@wustl.edu: 1) A cover letter explaining how their interest in the position matches their background and career goals. 2) CV or Biosketch. 3) Contact information for at least three professional references. Accommodation If you are unable to use our online application system and would like an accommodation, please email CandidateQuestions@wustl.edu or call the dedicated accommodation inquiry number at 314-935-1149 and leave a voicemail with the nature of your request. Pre-Employment Screening All external candidates receiving an offer for employment will be required to submit to pre-employment screening for this position. The screenings will include criminal background check and, as applicable for the position, other background checks, drug screen, an employment and education or licensure/certification verification, physical examination, certain vaccinations and/or governmental registry checks. All offers are contingent upon successful completion of required screening. Benefits Statement Washington University in St. Louis is committed to providing a comprehensive and competitive benefits package to our employees. Benefits eligibility is subject to employment status, full-time equivalent (FTE) workload, and weekly standard hours. Please visit our website at https://hr.wustl.edu/benefits/ to view a summary of benefits. EEO/AA Statement Washington University in St. Louis is committed to the principles and practices of equal employment opportunity and especially encourages applications by those from underrepresented groups. It is the University’s policy to provide equal opportunity and access to persons in all job titles without regard to race, ethnicity, color, national origin, age, religion, sex, sexual orientation, gender identity or expression, disability, protected veteran status, or genetic information. Diversity Statement Washington University is dedicated to building a diverse community of individuals who are committed to contributing to an inclusive environment – fostering respect for all and welcoming individuals from diverse backgrounds, experiences and perspectives. Individuals with a commitment to these values are encouraged to apply.

The Department of Biological Science at The University of Tulsa invites applications for a Postdoctoral Fellow position in Neuroscience. We seek a creative and interactive individual who would like to advance their research program in this area, while also obtaining training and experience in teaching. Fellows will devote at least 60% effort to research and up to 40% to teaching. Research topics are flexible within the realm of Neuroscience, but should have overlap with the expertise of one of the faculty mentors for these positions (listed below). Ron Bonett (ron-bonett@utulsa.edu) – Amphibian Evolution and Development https://ronbonett.weebly.com Alex Kingston (alex-kingston@utulsa.edu) – Invertebrate Neurobiology https://www.kingston-lab.com Katie Mika (kmmika12@gmail.com) – Vertebrate Molecular Evolution https://www.katelynmika.com/research Matthew Toomey (mbt6332@utulsa.edu) – Mechanisms and Evolution of Coloration and Vision http://mbtoomey.net Questions could be sent to individual faculty or: NeuroPostdoc_search@utulsa.edu Applications should submitted to: https://universitytulsa.peopleadmin.com/postings/7719 We are also hiring a second Postdoctoral Fellow in Integrative Biology https://universitytulsa.peopleadmin.com/postings/7711 Please indicate if you would like to be considered for both positions. Applications will be considered until the position is filled. The University of Tulsa is an Equal Opportunity Employer and is especially interested in candidates who can contribute to the diversity and excellence of the academic community through their research, teaching and/or service.

Postdoctoral position in Human Visual Psychophysics with fMRI/MRI, (m/f/d) (TVöD-Bund E13, 100%) The Department of Sensory and Sensorimotor Systems (PI Prof. Li Zhaoping) at the Max Planck Institute for Biological Cybernetics and at the University of Tübingen is currently looking for highly skilled and motivated individuals to work on projects aimed towards understanding visual attentional and perceptual processes using fMRI/MRI. The framework and motivation of the projects can be found at: https://www.lizhaoping.org/zhaoping/AGZL_HumanVisual.html. The projects can involve, for example, visual search tasks, stereo vision tasks, visual illusions, and will be discussed during the application process. fMRI/MRI technology can be used in combination with other methods such as eye tracking, TMS and/or EEG methodologies, and other related methods as necessary. The postdoc will be working closely with the principal investigator and other members of Zhaoping's team when needed. Responsibilities: • Conduct and participate in research projects such as lab and equipment set up, data collection, data analysis, writing reports and papers, and presenting at scientific conferences. • Participate in routine laboratory operations, such as planning and preparations for experiments, lab maintenance and lab procedures. • Coordinate with the PI and other team members for strategies and project planning. • Coordinate with the PI and other team members for project planning, and in supervision of student projects or teaching assistance for university courses in our field. Who we are: We use a multidisciplinary approach to investigate sensory and sensory-motor transforms in the brain (www.lizhaoping.org). Our approaches consist of both theoretical and experimental techniques including human psychophysics, fMRI imaging, EEG/ERP, and computational modelling. One part of our group is located in the University, in the Centre for Integrative Neurosciences (CIN), and the other part is in the Max Planck Institute (MPI) for Biological Cybernetics as the Department for Sensory and Sensorimotor Systems. You will have the opportunity to learn other skills in our multidisciplinary group and benefit from interactions with our colleagues in the university, at MPI, as well as internationally. This job opening is for the CIN or the MPI working group. The position (salary level TVöD-Bund E13, 100%) is for a duration of two years. Extension or a permanent contract after two years is possible depending on situations. We seek to raise the number of women in research and teaching and therefore urge qualified women to apply. Disabled persons will be preferred in case of equal qualification. Your application: The position is available immediately and will be open until filled. Preference will be given to applications received by March 19th, 2023. We look forward to receiving your application that includes (1) a cover letter, including a statement on roughly when you would like to start this position, (2) a motivation statement, (3) a CV, (4) names and contact details of three people for references, (5) if you have them, transcripts from your past and current education listing the courses taken and their grades, (6) if you have them, please also include copies of your degree certificates, (7) you may include a pdf file of your best publication(s), or other documents and information that you think could strengthen your application. Please use pdf files for these documents (and you may combine them into a single pdf file) and send to jobs.li@tuebingen.mpg.de, where also informal inquiries can be addressed. Please note that applications without complete information in (1)-(4) will not be considered, unless the cover letter includes an explanation and/or information about when the needed materials will be supplied. For further opportunities in our group, please visit https://www.lizhaoping.org/jobs.html

My team is looking for a person who will continue our current research on brain plasticity in deaf individuals. This work uses natural stimuli, for example, in our last experiment, we used half-hour animated movie without dialogue (“The triplets of Belleville”). We offer a possibility to work on a PhD using this novel and exciting research technique (see Hasson et al., Projections, 2008; Baldassano et al.., 2017) in a strong, international scientific team. The research will be a continuation of our previous work on mechanisms of brain plasticity in deaf individuals (Bola et al., 2017, Zimmermann et al., 2021). We plan to use functional magnetic resonance imaging (fMRI). The project will be carried out in cooperation with the team of prof. Christopher Baldassano (Columbia University, NYC, www.dpmlab.org/), the Nencki Institute of Experimental Biology PAN In Warsaw (prof. Artur Marchewka, lobi.nencki.gov.pl/) and with the Research Laboratory on Polish Sign Language on University of Warsaw (team of prof. Piotr Tomaszewski).

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

Are you a leading researcher in the field of brain, cognition and behaviour with experience in managerial leadership? Do you have a clear vision on the future of cognitive neuroscience and are you able to translate this into a coherent business strategy for one of the leading neuroscience institutes in Europe? Then combine your scientific and leadership skills as the scientific director of the Donders Institute. In 2023, a new governance structure will be implemented at the Donders Institute. As part of this development, the Donders Institute has an opening for a scientific director who will spend 0.5 FTE as director of the institute and 0.5 FTE for research activities and teaching. As scientific director, you will be the head and chair of the Executive Board of the Donders Institute Network. The Scientific Director is ultimately responsible for the overarching research activities and research strategy and for managerial and financial aspects of the Donders Institute. The latter include among others various portfolio's, such as the Donders Graduate School's graduate programme, talent development, societal impact, external relations, public outreach, diversity and sustainable science. Since most researchers at the Donders Institute are based at partners of the Donders Institute (Faculty of Science, Faculty of Social Sciences, the Radboud university medical center, Donders Centre for Cognitive Neuroimaging, Max-Planck Institute for Psycholinguistics), you will consult with the deans/directors involved at the Supervisory and Strategy Boards' meetings to set out a long-term research strategy, financial commitment and investment programme. You will chair the Executive Board of the Donders Institute, the Research Platform with the leaders of the Institute's four research themes, and the Strategy Board, which includes the directors of the four Donders Centres and the Max Planck Institute for Psycholinguistics (MPI). The Research Platform and the Strategy Board operate as advisory bodies to the Executive Board for all strategic issues of the Donders Institute Network. As scientific director, you will be accountable to the Supervisory Board, which will respond to Radboud University's Executive Board.

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.

A postdoctoral position is available immediately in the lab of Dr. Paul Shaw in the Neuroscience Department at Washington University School of Medicine in St. Louis to study the molecular and cellular bases for sleep regulation, plasticity and memory consolidation in the fruit fly Drosophila melanogaster. Successful candidates will have the opportunity to learn and apply molecular, genetic, physiological, and behavioral tools to study mechanisms by which sleep might influence plasticity. Qualified applicants are expected to hold a recent doctoral degree in the biological sciences, or in related disciplines. Prior experience in working with flies and broad understanding of genetic principles are highly preferred. Highly competitive salary and benefits are available and will commensurate with experience. Washington University School of Medicine offers a highly collaborative, top-notch training and research environment in neuroscience and the biomedical sciences. Wash U’s community is a very active and highly regarded neuroscience community, and is an excellent training environment for postdoctoral fellows. Interested candidates should email their curriculum vitae, a letter of interest outlining experience and research goals, and the names and contact information of at least three references to shawp@wustl.edu EOE Washington University is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, age, sex, sexual orientation, gender identity or expression, national origin, genetic information, disability, or protected veteran status.

The Neuroscience Department of the International School for Advanced Studies (SISSA; https://www.sissa.it/research/neuroscience) invites expressions of interest from scientists from various fields of Neuroscience for multiple tenure-track positions with anticipated start in 2025. Ongoing neuroscience research at SISSA includes cognitive neuroscience, computational and theoretical neuroscience, systems neuroscience, molecular and cellular research as well as genomics and genetics. The Department intends to potentiate its activities in these fields and to strengthen cross-field interactions. Expressions of interest from scientists in any of these fields are welcome. The working and teaching language of SISSA is English. This is an equal opportunity career initiative and we encourage applications from qualified women, racial and ethnic minorities, and persons with disabilities. Candidates should have a PhD in a relevant field and a proven record of research achievements. A clear potential to promote and lead research activities, and a specific interest in training and supervising PhD students is essential. Interested colleagues should present an original and innovative plan for their independent future research. We encourage both proposals within existing fields at SISSA as well as novel ideas outside of those or spanning various topics and methodologies of Neuroscience. SISSA is an international school promoting basic and applied research in Neuroscience, Mathematics and Physics and dedicated to the training of PhD students. Lab space and other resources will be commensurate with the appointment. Shared facilities include cell culture rooms, viral vector facilities, confocal microscopes, animal facilities, molecular and biochemical facilities, human cognition labs with EEG, TMS, and eye tracking systems, mechatronics workshop, and computing facilities. Agreements with national and international MRI scanning facilities are also in place. SISSA encourages fruitful exchanges between neuroscientists and other researchers including data scientists, physicists and mathematicians. Interested colleagues are invited to send a single pdf file including a full CV, a brief description of past and future research interests (up to 1,000 words), and the names of three referees to neuro.search@sissa.it. Selected candidates will be invited for an online or in-person seminar and 1- on-1 meetings in summer/autumn 2024. Deadline: A first evaluation round will consider all applications submitted before 15 May 2024. Later applications might be considered if no suitable candidates have been identified yet.

Traditionally, touch is associated with exteroception and is rarely considered a relevant sensory cue for controlling movements in space, unlike vision. We developed a technique to isolate and measure tactile involvement in controlling sliding finger movements over a surface. Young adults traced a 2D shape with their index finger under direct or mirror-reversed visual feedback to create a conflict between visual and somatosensory inputs. In this context, increased reliance on somatosensory input compromises movement accuracy. Based on the hypothesis that tactile cues contribute to guiding hand movements when in contact with a surface, we predicted poorer performance when the participants traced with their bare finger compared to when their tactile sensation was dampened by a smooth, rigid finger splint. The results supported this prediction. EEG source analyses revealed smaller current in the source-localized somatosensory cortex during sensory conflict when the finger directly touched the surface. This finding supports the hypothesis that, in response to mirror-reversed visual feedback, the central nervous system selectively gated task-irrelevant somatosensory inputs, thereby mitigating, though not entirely resolving, the visuo-somatosensory conflict. Together, our results emphasize touch’s involvement in movement control over a surface, challenging the notion that vision predominantly governs goal-directed hand or finger movements.

Over the last 20 years, neuroimaging and electrophysiology techniques have become central to understanding the mechanisms that accompany loss and recovery of consciousness. Much of this research is performed in the context of healthy individuals with neurotypical brain dynamics. Yet, a true understanding of how consciousness emerges from the joint action of neurons has to account for how severely pathological brains, often showing phenotypes typical of unconsciousness, can nonetheless generate a subjective viewpoint. In this presentation, I will start from the context of Disorders of Consciousness and will discuss recent work aimed at finding generalizable signatures of consciousness that are reliable across a spectrum of brain electrophysiological phenotypes focusing in particular on the notion of edge-of-chaos criticality.

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.

The Nature versus Nurture debate has generally been considered from the lens of genome versus experience dichotomy and has dominated our thinking about behavioral individuality and personality traits. In contrast, the role of nonheritable noise during brain development in behavioral variation is understudied. Using the Drosophila melanogaster visual system, I will discuss our efforts to dissect how individuality in circuit wiring emerges during development, and how that helps generate individual behavioral variation.

Accurate perception of the environment is a constructive process that requires integration of external bottom-up sensory signals with internally-generated top-down information reflecting past experiences and current aims. Decades of work have elucidated how sensory neocortex processes physical stimulus features. In contrast, examining how memory-related-top-down information is encoded and integrated with bottom-up signals has long been challenging. Here, I will discuss our recent work pinpointing the outermost layer 1 of neocortex as a central hotspot for processing of experience-dependent top-down information threat during perception, one of the most fundamentally important forms of sensation.

Thalamic networks, at the core of thalamocortical and thalamosubcortical communications, underlie processes of perception, attention, memory, emotions, and the sleep-wake cycle, and are disrupted in mental disorders, including schizophrenia and autism. However, the underlying mechanisms of pathology are unknown. I will present novel evidence on key organizational principles, structural, and molecular features of thalamocortical networks, as well as critical thalamic pathway interactions that are likely affected in disorders. This data can facilitate modeling typical and abnormal brain function and can provide the foundation to understand heterogeneous disruption of these networks in sleep disorders, attention deficits, and cognitive and affective impairments in schizophrenia and autism, with important implications for the design of targeted therapeutic interventions

The cortex comprises many neuronal types, which can be distinguished by their transcriptomes: the sets of genes they express. Little is known about the in vivo activity of these cell types, particularly as regards the structure of their spike trains, which might provide clues to cortical circuit function. To address this question, we used Neuropixels electrodes to record layer 5 excitatory populations in mouse V1, then transcriptomically identified the recorded cell types. To do so, we performed a subsequent recording of the same cells using 2-photon (2p) calcium imaging, identifying neurons between the two recording modalities by fingerprinting their responses to a “zebra noise” stimulus and estimating the path of the electrode through the 2p stack with a probabilistic method. We then cut brain slices and performed in situ transcriptomics to localize ~300 genes using coppaFISH3d, a new open source method, and aligned the transcriptomic data to the 2p stack. Analysis of the data is ongoing, and suggests substantial differences in spike time coordination between ET and IT neurons, as well as between transcriptomic subtypes of both these excitatory types.

Functional connectomics reveals general wiring rule in mouse visual cortex

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}.

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}.

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}.

Distinguishing near and far visual cues is an essential computation that animals must carry out to guide behavior using vision. When animals move, self-motion creates motion parallax — an important but poorly understood source of depth information — whereby the speed of optic flow generated by self-motion depends on the depth of visual cues. This enables animals to estimate depth by comparing visual motion and self-motion speeds. As neurons in the mouse primary visual cortex (V1) are broadly modulated by locomotion, we hypothesized that they may integrate visual- and locomotion-related signals to estimate depth from motion parallax. To test this hypothesis, we designed a virtual reality (VR) environment for mice, where visual cues were presented at different virtual distances from the mouse and motion parallax was the only cue for depth, and recorded neuronal activity in V1 using two-photon calcium imaging. We found that the majority of excitatory neurons in layer 2/3 of V1 were selective for virtual depth. Neurons with different depth preferences were spatially intermingled, with nearby cells often tuned for disparate depths. Moreover, depth tuning could not be fully accounted for by either running speed or optic flow speed tuning in isolation, but arose from the integration of both signals. Specifically, depth selectivity of V1 neurons was explained by the ratio of preferred running and optic flow speeds. Finally, many neurons responded selectively to visual stimuli presented at a specific retinotopic location and virtual depth, demonstrating that during active locomotion V1 neuronal responses can be characterized by three-dimensional receptive fields. These results challenge the traditional view of V1 as a feed-forward filter bank, and suggest that the widespread modulation of V1 neurons by locomotion and other movements plays an essential role in estimation of depth from motion parallax.

Birdsong is an important model for vocal learning and sequential motor behavior. Similarly to human language, songs, notably those of Bengalese finches and canaries, exhibit higher-order sequence structure, meaning that the statistics of one syllable may depend on a number of previous syllables. However, this number (the context depth) varies in a manner that has challenged previous formal approaches. Here we used a hierarchical non-parametric Bayesian sequence model (based on Teh, 2006; Elteto et al., 2022) that seamlessly combines predictive information from shorter and longer contexts of previous syllables, weighing them proportionally to their predictive power. We fit our model to songs of 8 different Bengalese finches, each with > 300 song bouts (Veit et al., 2021). The model inferred the context depth, showing that it varied substantially, with some syllables depending just on one deterministic predecessor, but others depending on $>10$ previous syllables. Underlying this variability was syllables forming alternating and repeating chunks, i.e. strings of fixed subsequences. When fitted at the chunk-level, our model revealed different chunk-motifs that characterize how bouts typically start, unfold, and end. The model was also able to predict the flexibility with which birds can learn to switch between syllable transitions based on external cues.

Stimuli trigger a pattern of activity across neurons in cortex, whose firing rates define a stimulus's representation in a high-dimensional vector space. Learning a visuomotor task can affect the responses of visual cortical neurons, but how and why training modifies population-level representations is unclear. One hypothesis is that representational plasticity in visual cortex facilitates visuomotor associations by downstream motor systems. Learning systems exhibit "inductive biases", meaning they form some stimulus-motor associations more easily than others. An animal's inductive biases presumably reflect its neuronal representations; its ability to form distinct motor associations for different stimuli depends on the representational similarity of the stimuli. Thus, the plasticity of sensory cortical representations may change inductive bias: for an animal to make different associations to two stimuli, the cortical representations of the stimuli must differentiate, such as if the evoked firing vectors were orthogonalized. A second hypothesis is that task training increases the fidelity of stimulus coding in sensory cortex, which improves decoding accuracy by downstream regions. However, this hypothesis presupposes that the population code in naive cortex suffers from low fidelity, which recent recordings of large cortical populations have questioned. We used two-photon calcium imaging to study how the tuning of V1 populations changes after mice learn to associate opposing actions with differently oriented gratings. Training did not improve the fidelity of stimulus coding, as it was already perfect in naive animals thanks to a subpopulation of highly reliable neurons. Instead, training caused the population's responses to motor-associated stimuli to become more orthogonal. The basis of this training-evoked orthogonalization was the sparsening of stimulus representations, an effect which could be summarized by a simple nonlinear transformation of naive neuronal firing rates and whose convexity was largest for motor-associated stimuli.

Parkinson's disease (PD), characterized by the absence of dopamine in the striatum[1], is caused by the death of the substantia nigra pars compacta dopamine (SNcDA) neurons in the mid-brain. The cause of this cell loss is attributed to irreparable damage due to a dysregulation cascade originating from excess cytosolic dopamine[2]. However, it is unresolved if dopamine dysregulation in SNcDA neurons themselves is the cause of PD or if it is a mere symptom. Here, we introduce a theory of specialized non-causal action potentials that serve metabolic homeostasis called `metabolic spikes' which can account for spontaneous activity observed in many neuron types including SNcDA. We propose that loss of these metabolic spikes in SNcDA can account for both, the cause of PD and the subsequent dopamine dysregulation. Neurons, presumably in anticipation of synaptic inputs, keep their ATP levels at a maximum such that they are ATP-surplus/ADP-scarce during synaptic quiescence. With ADP availability as the rate-limiting step, ATP production stalls in their mitochondria when energy consumption is low, leading to the formation of toxic Reactive Oxygen Species(ROS). Under these circumstances, `metabolic spikes’ serve to restore ATP production and relieve ROS toxicity. In a metabolism-coupled model of SNcDA that senses ROS and initiates spikes, we identified three categories of deficits that could decrease metabolic spikes and consequently deplete the dopamine tone seen in PD. Importantly in PD, such lowered extracellular dopamine level is misread by D2-autoreceptors and dopamine synthesis is increased. With dopamine vesicles being already full, excess dopamine produces disruptive aldehyde (DOPAL) leading to dysregulation and ultimately cell death. Metabolic spikes, though relevant for cellular health, may thus be an integrated neuronal mechanism that operates in synergy with synaptic integration and forms a basic principle of network dynamics and behaviour, as exemplified in PD.

While sleeping, many vertebrate groups alternate between at least two sleep stages: rapid eye movement (REM) and slow wave sleep (SWS), in part characterized by wake-like and synchronous brain activity respectively. Sleep stage alternation has been implicated in learning and memory function experimentally1, and has motivated several techniques in training artificial neural networks2. If the functions ascribed to 2-stage sleep are truly general, one might expect to find similar phenomena outside the vertebrate lineage. Here we delineate neural and behavioral correlates of 2-stage sleep in octopuses, marine invertebrates which evolutionarily diverged from vertebrates ~550 MYA and have independently evolved large brains and behavioral sophistication. Octopus sleep is rhythmically interrupted by ~60 second bouts of pronounced body movements and rapid changes in their neurally controlled skin patterns. We show that this constitutes a distinct ‘active’ sleep stage, being homeostatically regulated, rapidly reversible, and coming with increased arousal threshold. Neuropixels recordings from the octopus central brain reveal that local field potential (LFP) activity during active sleep resembles that of waking. LFP activity differs across brain regions, with the strongest activity during active sleep seen in the Superior Frontal and Vertical lobes, anatomically connected regions associated with learning and memory function. During ‘quiet’ sleep, these regions are relatively silent but generate LFP oscillations resembling mammalian sleep spindles in frequency and duration. Computational analysis reveals the rich skin pattern dynamics of active sleep, which move through states strongly resembling waking skin patterns. The range of similarities with vertebrates implies that aspects of 2-stage sleep in octopuses may represent convergent features of complex cognition.

When foraging in dynamic and uncertain environments, animals can benefit from basing their decisions on smart inferences about hidden properties of the world. Typical theoretical approaches for understanding the strategies that animals use in such settings combine Bayesian inference and value iteration to derive optimal behavioral policies that maximize total reward given changing beliefs about the environment. However, specifying these beliefs requires infinite numerical precision; with limited resources, this problem can no longer be decomposed into the separate steps of optimizing inference and optimizing action selection. To understand the space of behavioral policies in this constrained setting, we enumerate and evaluate all possible behavioral programs that can be constructed from just a handful of states. We show that only a small fraction of the top-performing programs can be constructed by approximating Bayesian inference; the remaining programs are structurally or even functionally distinct from Bayesian. To assess structural and functional relationships among all programs, we developed novel tree-embedding algorithms; these embeddings, which are capable of extracting different relational structures within the program space, reveal that nearly all good programs are closely connected through single algorithmic “mutations”. We demonstrate how one can use such relational structures to efficiently search for good solutions via an evolutionary algorithm. Moreover, these embeddings reveal that the diversity of non-Bayesian behaviors originates from a handful of key mutations that broaden the functional repertoire within the space of good programs. The fact that this diversity of non-optimal behavior does not significantly compromise performance suggests that these same strategies might generalize across tasks.

Network models are often designed to capture selective aspects of cortical circuits. On one end, mechanistic models such as balanced spiking networks resemble activity regimes observed in data, but are often limited to simple computations. On the other end, functional models like trained deep networks can show comparable performance and dynamical motifs, but are far removed from experimental physiology. Here, we put forth a new framework for excitatory-inhibitory spiking networks which retains key properties of both mechanistic and functional models. Based on previous studies of the geometry of spike-coding networks, we consider a population of spiking neurons with low-rank connectivity, allowing each neuron’s threshold to be cast as a boundary in a space of population modes, or latent variables. Each neuron’s boundary divides this latent space into subthreshold and suprathreshold areas, which determines its contribution to the input-output function of the network. Then, incorporating Dale’s law as a connectivity constraint, we demonstrate how a network of inhibitory (I) neurons forms a convex, stable boundary in the latent coding space, and a network of excitatory (E) neurons forms a concave, unstable boundary. Finally, we show how the combination of the two yields stable dynamics at the crossing of the E and I boundaries. The resultant E/I networks are balanced, inhibition-stabilized, and exhibit asynchronous irregular activity, thereby closely resembling cortical dynamics. Moreover, the latent variables can be mapped onto a constrained optimization problem, and are capable of universal function approximation. The combination of these dynamical and functional properties leads to unique insights, including specified computational roles for E/I balance and Dale’s law. Finally, the intuitive geometry of the representations, plus the link to constrained optimization, makes our framework a promising candidate for scalable and interpretable computation in biologically-plausible spiking networks.

Understanding the basis of shared, across trial fluctuations in neural activity in mammalian cortex is critical to uncovering the nature of information processing in the brain. This correlated variability has often been related to the structure of cortical connectivity since variability not accounted for by signal changes likely arises from local circuit inputs. However, recent recordings from segregated networks of excitatory neurons in mouse primary visual cortex (V1) complicate this relationship. These results found that despite weak cross-network connection probability, noise correlations were significantly larger than one would expect. We aim to explore possible circuit mechanisms responsible for these enhanced positive correlations through biologically motivated cortical network models, with the hypothesis that they arise from unobserved inhibitory neurons. In particular, we consider networks with weakly interconnected excitatory populations, but either global or subpopulation-specific inhibitory populations. We then ask how correlations can be enhanced or marred via the strength of outgoing and incoming connections to these inhibitory populations. By performing a pathway expansion of the covariance matrix, we find that a single inhibitory population with sufficiently strong I to E connections can lead to stronger than expected positive correlations across excitatory populations. However, this result is highly parameter dependent. When considering an inhibition-stabilized network (ISN) the viable parameter regime shrinks dramatically into a narrow band close to the edge of stability. We find that both non-ISN and ISN regimes can recover the ability to robustly explain the experimental results by allowing for two tuned inhibitory populations, meaning that each inhibitory population preferentially connects to one of the two excitatory populations. Our results therefore imply that complexity in excitation should be mirrored by complexity in the structure of inhibition.

Cortical activity is characterized by state-specific dynamics arising from the interplay between connectivity, cellular diversity, and intrinsic properties. During non-Rapid Eye Movement (NREM) sleep, cortical population activity alternates between periods of neuronal firing (“UP” states) and neuronal silence (“DOWN” states). Patterns of neuronal activity at DOWN-to-UP (DU) transitions have functional relevance beyond sleep: they are related to sensory coding during wakefulness and support homeostatic processes and memory consolidation. Despite this functional importance, the factors that organize these spiking patterns remain unknown but mechanisms that rely on network connectivity or intrinsic excitability have been proposed. In order to elucidate the mechanisms that organize spontaneous activity, we recorded populations of neurons in the head-direction cortex (HDC, i.e., post-subiculum), where the behavioral correlates of most neurons are well accounted for. Neuronal tuning to HD was independent of anatomical position. However, while UP-DOWN (UD) transitions were synchronous along the dorsoventral (DV) axis, we observed sequential activation of neurons at DU transitions. To understand the mechanisms underlying these traveling waves at UP state onset, we built a computational model with a linear array of recurrently connected adapting units and compared the effects of different biophysical gradients. We found that, unlike gradients in local connectivity, excitability/input, and adaptive current, a gradient in rectifying current (Ih) was able to uniquely reproduce the experimental observations, and predict a yet-unobserved relationship between UP onset and post-DOWN rebound activity. Subsequent ex vivo intracellular recordings confirmed the predicted DV gradient of Ih in HDC. In conclusion, precisely organized spontaneous population activity patterns may be independent of circuit features and sensory coding but instead may only reflect intrinsic neuronal properties. Yet, the resulting traveling waves have the potential to anatomically segment computation in output structures like the medial entorhinal cortex (MEC) and indirectly, the hippocampus.

Exploring novel approaches to auditory rehabilitation, we aim to demonstrate, in mice, the efficiency of an optogenetic cortical implant. Several studies have shown that mice can use patterned optogenetic stimulations of the sensory cortex to drive their behaviour. It was however never tested if it is possible to provide a detailed representation of sensory inputs through such stimulation patterns. To explore this key question for cortical implant devices, we developed a novel sensory encoding model based on a convolutional autoencoder, which is able to temporally compress and denoise 500ms sounds into a 10x10 array of stimulation sites while preserving latent space continuity and detailed sound information. To minimize spatial crosstalk between stimulation sites, we actually limit the latent representations to the 10 largest activations and impose spatial sparseness constraints during model training. We could then demonstrate that mice can discriminate these activity patterns when applied onto their auditory cortex using a video-projector setup for mesoscopic patterned optogenetic stimulation. After mastery of the discrimination task, we presented in catch trials various new patterns from the model and observed that several mice elicit similar behavioural categorization responses across patterns. This demonstrates that the artificial patterns imposed to auditory cortex produce a robust representation structure that can be used to solve a task. These results indicate that constrained autoencoder model can be used for generating artificial auditory perception via an array of cortical stimulators. We aim to further benchmark these artificial perceptions against already acquired auditory discrimination performances of normally-hearing mice.

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}.