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.

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.

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.

TU Dresden is one of eleven German Universities of Excellence. It provides an outstanding scientific infrastructure and ideal environment for interdisciplinary cooperation. The Faculty of Psychology offers a position as Research Associate (m/f/x) (subject to personal qualification employees are remunerated according to salary group E 13 TV-L) starting as soon as possible and limited until December 31, 2022 with the option of extension. The period of employment is governed by the Fixed Term Research Contracts Act (WissZeitVG). The position offers the chance to obtain further academic qualification and is funded by the Saxonian Ministry of Science, Culture, and Tourism (SMWK) and aimed at facilitating major funding initiatives at the TU Dresden. Tasks: The successful candidate will work together with the Faculty of Psychology in applying for major funding initiatives (e.g., Excellence Cluster) within the topics of psychology and neuroscience. The position will entail the following tasks: - preparation and editing of grant proposals including literature review, project descriptions, budget, and work plans - writing scientific publications such as reviews in close collaboration with an interdisciplinary team - research work in the field of psychology and cognitive neuroscience - scientific preparation of events such as workshops and conferences - writing executive summaries, high-level summaries, infographics, and other tools. For questions about the position please contact Prof. Dr. Katharina von Kriegstein (katharina.von_kriegstein@tu-dresden.de). The TU Dresden is an equal opportunities employer, committed to the advancement of individuals without regard to ethnicity, religion, gender, or disability. In case of equal suitability, people with severe disabilities or those with equivalence to the German Social Code IX (SGB IX) will be preferred for employment. Please submit your comprehensive application including a cover letter that briefly describes your personal qualifications and future career interests, CV, 1 to 2 publications, and contact details of two personal references by January 10, 2022 (stamped arrival date of the university central mail service applies), preferably via the TU Dresden SecureMail Portal https://securemail.tu-dresden.de by sending it as a single pdf document to julia.herdin@tu-dresden.de or by mail to: TU Dresden, Fakultät Psychologie, Institut für Allgemeine Psychologie, Biopsychologie und Methoden der Psychologie, Professur für Kognitive und Klinische Neurowissenschaft, Frau Prof. Dr. Katharina von Kriegstein, Helmholtzstr. 10, 01069 Dresden. Please submit copies only, as your application will not be returned to you. Expenses incurred in attending interviews cannot be reimbursed.

We are seeking a full-time post-doctoral research fellow to study computational and neuroscientific models of perception and cognition. The research fellow will be jointly supervised by Dr. David Brang (https://sites.lsa.umich.edu/brang-lab/) and Zhongming Liu (https://libi.engin.umich.edu). The goal of this collaboration is to build computational models of cognitive and perceptual processes using data combined from electrocorticography (ECoG) and fMRI. The successful applicant will also have freedom to conduct additional research based on their interests, using a variety of methods -- ECoG, fMRI, DTI, lesion mapping, and EEG. The ideal start date is from spring to fall 2021 and the position is expected to last for at least two years, with the possibility of extension for subsequent years. We are also recruiting a Post-Doc for research on multisensory interactions (particularly how vision modulates speech perception) using Cognitive Neuroscience techniques or to help with our large-scale brain tumor collaboration with Shawn Hervey-Jumper at UCSF (https://herveyjumperlab.ucsf.edu). In this latter collaboration we collect iEEG (from ~50 patients/year) and lesion mapping data (from ~150 patients/year) in patients with a brain tumor to study sensory and cognitive functions in patients. The goals of this project are to better understand the physiology of tumors, study causal mechanisms of brain functions, and generalize iEEG/ECoG findings from epilepsy patients to a second patient population.

We are seeking to fill a fully funded PhD position (75% TV-L 13 state employees salary scheme) in cognitive neuroscience. The successful applicant will contribute to a project, investigating selective attention and working memory processes in a multisensory context. In particular, we are interested in how the auditory and the visual system interact during the deployment of attention in multisensory environments and how audio-visual information is integrated. To answer those research questions, we primarily use the EEG in combination with cutting edge analysis methods (e.g., multivariate pattern classification). Beyond that, the application of eye-tracking or (functional) MRI is possible within the project. Your responsibilities will include conducting (EEG-) experiments, data analysis, preparation of manuscripts for publication in peer-reviewed journals, as well as presentation of scientific results at (inter-)national conferences. Official job ad: https://www.ifado.de/ifadoen/careers/current-job-offers/#job3

The Chair of Lifespan Developmental Neuroscience investigates neurocognitive mechanisms underlying perceptual, cognitive, and motivational development across the lifespan. The main themes of our research are neurofunctional mechanisms underlying lifespan development of episodic and spatial memory, cognitive control, reward processing, decision making, perception and action. We also pursue applied research to study effects of behavioral intervention, non-invasive brain stimulation, or digital technologies in enhancing functional plasticity for individuals of difference ages. We utilize a broad range of neurocognitive (e.g., EEG, fNIRs, fMRI, tDCS) and computational methods. The here announced position is embedded in a newly established research group funded by the DFG (FOR5429), with a focus on modulating brain networks for memory and learning by using focalized transcranial electrical stimulation (tES). The subproject with which this position is associated will study effects of focalized tES on value-based sequential learning at the behavioral and brain levels in adults. The data collection for this subproject will mainly be carried out at the Berlin site (Center for Cognitive Neuroscience, FU Berlin).

This Master’s is centered on research and on preparing students for a PhD in Psychology. Most of its core courses focus on hands-on in-lab research, science management and communication, and statistics, while offering the possibility of having many elective courses in computational biology/neuroscience, neuroimaging and others. The Master’s in Psychological Sciences has an English-only program available for those interested (the official languages are Portuguese and English). A major concentration of this Master’s will be in Cognitive Neuroscience, and will be associated with lab work and mentoring at the Proaction Lab lead by Jorge Almeida and within the transformative ERA Chair grant from the European Union to FPCE-UC CogBooster (lead by Alfonso Caramazza).

The Department of Psychological and Brain Sciences at the University of Massachusetts, Amherst is inviting applications for a tenure track, academic year, faculty position at the Assistant Professor level in its Cognition and Cognitive Neuroscience Psychology program, starting in Fall 2024. We are seeking outstanding applicants with expertise in any area of cognitive psychology or cognitive neuroscience, including interdisciplinary fields connected to cognitive psychology, whose work complements and broadens existing strengths in our program. The program has current strengths in attention, decision-making, psycholinguistics, and mathematical modeling, with connections to our Behavioral Neuroscience, Clinical Psychology, Developmental Science, and Social Psychology programs. Across the university, our faculty have strong connections to Linguistics, Information and Computer Sciences, and Speech, Language, and Hearing Sciences, as well as the Initiative in Cognitive Science, the Computational and Social Science Institute, the Institute for Diversity Sciences, and the Institute for Applied Life Sciences.

The postdoc will be involved in cognitive neuroscience research, specifically in the intracranial EEG recordings. The projects include 'the interplay of movement and touch', which involves analysis of iEEG dynamics during reaching to tactile stimuli on the body, and 'from simple to natural and ecologically valid stimuli', which involves investigating brain responses measured by iEEG among stimuli gradually ranging from the simplest to very complex. The postdoc will also have the opportunity to propose new ideas for research.

The PhD research topic will focus on understanding key mechanisms that enable specific cognitive functions in the brain, such as language comprehension, using a combination of computational neuroscience, machine learning, and experimental cognitive neuroscience techniques. The student will develop novel integrations of mechanistic physiological and generative AI-based theories of brain organization, and test these by designing, conducting, and analyzing experiments using advanced neuroimaging and neurostimulation technologies (EEG, fNIRS, TMS, MEG, fMRI, including mobile w/ VR/AR integration).

The PhD research topic will focus on understanding key mechanisms that enable specific cognitive functions in the brain, such as language comprehension, using a combination of computational neuroscience, machine learning, and experimental cognitive neuroscience techniques. The student will develop novel integrations of mechanistic physiological and generative AI-based theories of brain organization, and test these by designing, conducting, and analyzing experiments using advanced neuroimaging and neurostimulation technologies (EEG, fNIRS, TMS, MEG, fMRI, including mobile w/ VR/AR integration).

The Faculty of Psychology and Educational Sciences of the University of Coimbra, Portugal, is seeking applications for 3 Post-Doctoral positions in Cognitive Science and Cognitive Neuroscience as part of the ERA Chair grant CogBooster. The positions are aimed at contributing to the renewal of Psychological Sciences in Portugal and involve working with Alfonso Caramazza and Jorge Almeida. The selected applicants will be based in Coimbra with opportunities to spend time at Harvard University in Alfonso Caramazza’s laboratory. The positions are focused on: 1) lexical processing, visual object recognition, reading, or action recognition; 2) visual object recognition and how object knowledge is organized and represented; 3) object dimensionality and dimensional mapping using population receptive field analysis/connective field modeling.

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.

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.

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

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.

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!

An understanding of the self helps explain not only human thoughts, feelings, attitudes but also many aspects of everyday behaviour. This talk focuses on a viewpoint - self as processes. This viewpoint emphasizes the dynamics of the self that best connects with the development of the self over time and its realist orientation. We are combining psychological experiments and data mining to comprehend the stability and adaptability of the self across various populations. In this talk, I draw on evidence from experimental psychology, cognitive neuroscience, and machine learning approaches to demonstrate why and how self-association affects cognition and how it is modulated by various social experiences and situational factors

On Thursday, May 25th we will host Darcy Diesburg and Mark Richardson. Darcy Diesburg, PhD, is a post-doctoral research fellow at Brown University. She will tell us about “Deep brain stimulation and action-stopping: A cognitive neuroscience perspective on the contributions of fronto-basal ganglia circuits to inhibitory control”. Mark Richardson, MD, PhD, is the Director of Functional Neurosurgery at the Massachusetts General Hospital, Charles Pappas Associate Professor of Neurosciences at Harvard Medical School and Visiting Associate Professor of Brain and Cognitive Sciences at MIT. Beside his scientific presentation on “Auditory input to the basal ganglia”, he will give us a glimpse at the “Person behind the science”. The talks will be followed by a shared discussion. You can register via talks.stimulatingbrains.org to receive the (free) Zoom link!

This talk aims to highlight the immense potential of Artificial Intelligence (AI) in advancing the field of psychology and cognitive neuroscience. Through the integration of machine learning algorithms, big data analytics, and neuroimaging techniques, AI has the potential to revolutionize the way we study human cognition and brain characteristics. In this talk, I will highlight our latest scientific advancements in utilizing AI to gain deeper insights into variations in cognitive performance across the lifespan and along the continuum from healthy to pathological functioning. The presentation will showcase cutting-edge examples of AI-driven applications, such as deep learning for automated scoring of neuropsychological tests, natural language processing to characeterize semantic coherence of patients with psychosis, and other application to diagnose and treat psychiatric and neurological disorders. Furthermore, the talk will address the challenges and ethical considerations associated with using AI in psychological research, such as data privacy, bias, and interpretability. Finally, the talk will discuss future directions and opportunities for further advancements in this dynamic field.

Cognitive science and cognitive neuroscience researchers have agreed that the replication of findings is important for establishing which ideas (or theories) are integral to the study of cognition across the lifespan. Recently, high-profile papers have called into question findings that were once thought to be unassailable. Much attention has been paid to how p-hacking, publication bias, and sample size are responsible for failed replications. However, much less attention has been paid to the fidelity by which researchers enact study protocols. Researchers conducting education or clinical trials are aware of the importance in fidelity – or the extent to which the protocols are delivered in the same way across participants. Nevertheless, this idea has not been applied to cognitive contexts. This seminar discusses factors that impact the replicability of findings alongside recent models suggesting that even small fidelity deviations have real impacts on the data collected.

We will explore how neuropsychology can be leveraged to directly test cognitive neuroscience theories using the case of frontotemporal dementias affecting the language network. Specifically, we will focus on pathological, neuroimaging, and cognitive data from primary progressive aphasia. We will see how they can help us investigate the reading network, semantic knowledge organisation, and grammatical categories processing. Time permitting, the end of the talk will cover the temporal dynamics of semantic dimensions recovery and the role played by the task.

Understanding Human ability to learn novel concepts from just a few sensory experiences is a fundamental problem in cognitive neuroscience. I will describe a recent work with Ben Sorcher and Surya Ganguli (PNAS, October 2022) in which we propose a simple, biologically plausible, and mathematically tractable neural mechanism for few-shot learning of naturalistic concepts. We posit that the concepts that can be learned from few examples are defined by tightly circumscribed manifolds in the neural firing-rate space of higher-order sensory areas. Discrimination between novel concepts is performed by downstream neurons implementing ‘prototype’ decision rule, in which a test example is classified according to the nearest prototype constructed from the few training examples. We show that prototype few-shot learning achieves high few-shot learning accuracy on natural visual concepts using both macaque inferotemporal cortex representations and deep neural network (DNN) models of these representations. We develop a mathematical theory that links few-shot learning to the geometric properties of the neural concept manifolds and demonstrate its agreement with our numerical simulations across different DNNs as well as different layers. Intriguingly, we observe striking mismatches between the geometry of manifolds in intermediate stages of the primate visual pathway and in trained DNNs. Finally, we show that linguistic descriptors of visual concepts can be used to discriminate images belonging to novel concepts, without any prior visual experience of these concepts (a task known as ‘zero-shot’ learning), indicated a remarkable alignment of manifold representations of concepts in visual and language modalities. I will discuss ongoing effort to extend this work to other high level cognitive tasks.

Cognitive neuroscience has witnessed great progress since modern neuroimaging embraced an open science framework, with the adoption of shared principles (Wilkinson et al., 2016), standards (Gorgolewski et al., 2016), and ontologies (Poldrack et al., 2011), as well as practices of meta-analysis (Yarkoni et al., 2011; Dockès et al., 2020) and data sharing (Gorgolewski et al., 2015). However, while functional neuroimaging data provide correlational maps between cognitive functions and activated brain regions, its usefulness in determining causal link between specific brain regions and given behaviors or functions is disputed (Weber et al., 2010; Siddiqiet al 2022). On the contrary, neuropsychological data enable causal inference, highlighting critical neural substrates and opening a unique window into the inner workings of the brain (Price, 2018). Unfortunately, the adoption of Open Science practices in clinical settings is hampered by several ethical, technical, economic, and political barriers, and as a result, open platforms enabling access to and sharing clinical (meta)data are scarce (e.g., Larivière et al., 2021). We are working with clinicians, neuroimagers, and software developers to develop an open source platform for the storage, sharing, synthesis and meta-analysis of human clinical data to the service of the clinical and cognitive neuroscience community so that the future of neuropsychology can be transdiagnostic, open, and FAIR. We call it neurocausal (https://neurocausal.github.io).

Artificial neural networks can be useful for studying brain functions. In cognitive neuroscience, recurrent neural networks are often used to model cognitive functions. I will first offer my opinion on what is missing in the classical use of recurrent neural networks. Then I will discuss two lines of ongoing efforts in our group to move beyond the classical recurrent neural networks by studying multi-system neural networks (the talk will focus on two-system networks). These are networks that combine modules for several neural systems, such as vision, audition, prefrontal, hippocampal systems. I will showcase how multi-system networks can potentially be constrained by experimental data in fundamental ways and at scale.

We examine consciousness from the perspective of theoretical computer science (TCS), a branch of mathematics concerned with understanding the underlying principles of computation and complexity, including the implications and surprising consequences of resource limitations. We propose a formal TCS model, the Conscious Turing Machine (CTM). The CTM is influenced by Alan Turing's simple yet powerful model of computation, the Turing machine (TM), and by the global workspace theory (GWT) of consciousness originated by cognitive neuroscientist Bernard Baars and further developed by him, Stanislas Dehaene, Jean-Pierre Changeux, George Mashour, and others. However, the CTM is not a standard Turing Machine. It’s not the input-output map that gives the CTM its feeling of consciousness, but what’s under the hood. Nor is the CTM a standard GW model. In addition to its architecture, what gives the CTM its feeling of consciousness is its predictive dynamics (cycles of prediction, feedback and learning), its internal multi-modal language Brainish, and certain special Long Term Memory (LTM) processors, including its Inner Speech and Model of the World processors. Phenomena generally associated with consciousness, such as blindsight, inattentional blindness, change blindness, dream creation, and free will, are considered. Explanations derived from the model draw confirmation from consistencies at a high level, well above the level of neurons, with the cognitive neuroscience literature. Reference. L. Blum and M. Blum, "A theory of consciousness from a theoretical computer science perspective: Insights from the Conscious Turing Machine," PNAS, vol. 119, no. 21, 24 May 2022. https://www.pnas.org/doi/epdf/10.1073/pnas.2115934119

While non-invasive Brain-to-Computer interface can accurately classify the lateralization of hand moments, the distinction of fingers activation in the same hand is limited by their local and overlapping representation in the motor cortex. In particular, the low signal-to-noise ratio restrains the opportunity to identify meaningful patterns in a supervised fashion. Here we combined Magnetoencephalography (MEG) recordings with advanced decoding strategy to classify finger movements at single trial level. We recorded eight subjects performing a serial reaction time task, where they pressed four buttons with left and right index and middle fingers. We evaluated the classification performance of hand and finger movements with increasingly complex approaches: supervised common spatial patterns and logistic regression (CSP + LR) and unsupervised linear finite convolutional neural network (LF-CNN). The right vs left fingers classification performance was accurate above 90% for all methods. However, the classification of the single finger provided the following accuracy: CSP+SVM : – 68 ± 7%, LF-CNN : 71 ± 10%. CNN methods allowed the inspection of spatial and spectral patterns, which reflected activity in the motor cortex in the theta and alpha ranges. Thus, we have shown that the use of CNN in decoding MEG single trials with low signal to noise ratio is a promising approach that, in turn, could be extended to a manifold of problems in clinical and cognitive neuroscience.

Solving complex planning problems efficiently and flexibly requires reusing expensive previous computations. The brain can do this, but how? I present a new theory that addresses this question and connects planning to hitherto distinct areas within cognitive neuroscience, such as entorhinal representation of cognitive maps and cognitive control.

Executive control processes and flexible behaviors rely on the integrity of, and dynamic interactions between, large-scale functional brain networks. The right insular cortex is a critical component of a salience/midcingulo-insular network that is thought to mediate interactions between brain networks involved in externally oriented (central executive/lateral frontoparietal network) and internally oriented (default mode/medial frontoparietal network) processes. How these brain systems reconfigure with development is a critical question for cognitive neuroscience, with implications for neurodevelopmental pathologies affecting brain connectivity. I will describe studies examining how brain network dynamics support flexible behaviors in typical and atypical development, presenting evidence suggesting a unique role for the dorsal anterior insular from studies of meta-analytic connectivity modeling, dynamic functional connectivity, and structural connectivity. These findings from adults, typically developing children, and children with autism suggest that structural and functional maturation of insular pathways is a critical component of the process by which human brain networks mature to support complex, flexible cognitive processes throughout the lifespan.

How the brain represents the body is a fundamental question in cognitive neuroscience. Experimental studies are difficult because ‘the body is always there’ (William James). In recent years immersive virtual reality techniques have been introduced that deliver apparent changes to the body extending earlier techniques such as the rubber hand illusion, or substituting the whole body by a virtual one visually collocated with the real body, and seen from a normal first person perspective. This talk will introduce these techniques, and concentrate on how changing the body can change the mind and behaviour, especially in the context of combatting aggression based on gender or race.

I will build from Niccolo's discussion of the Blockhead argument to argue that having an FeedForward Network (FN) responding like an recurrent network (RN) in a consciousness experiment is not enough to convince us the two are the same with regards to the posession of mental states and conscious experience. I will then argue that a robust functional equivalence between FFN and RN is akso not supported by the mathematical work on the Universal Approximator theorem, and is also unlikely to hold, as a conjecture, given data in cognitive neuroscience; I will argue that an equivalence of RN and FFN may only apply to static functions between input/output layers and not to the temporal patterns or to the network's reactions to structural perturbations. Finally, I review data indicating that consciousness has functional characteristics, such as a flexible control of behavior, and that cognitive/brain dynamics reveal interacting top-down and bottom-up processes, which are necessary for the mediation of such control processes.

Self-control is a central aspect of free will. Because self-control is often described in terms of resisting temptations, research on the cognitive neuroscience of free will often focuses on mechanisms of top-down regulation. We argue that this obscures a crucial temporal dimension of free will: now-then regulation. We distinguish now-then regulation from top-down regulation, and situate now-then regulation within a broader account of temporally extended agency. In highlighting this temporal dimension of control, we aim to provide a more nuanced account of how motivation informs action over time, different kinds of regulatory processes underlying the planning and execution of action, and the temporal components of reasons-responsiveness.

The question of how syntactic structure can be built at the neural level has come to the forefront of cognitive neuroscience in the last decade. Neural oscillations have been widely recognised as playing an important role in building syntactic representations. In this talk I will review existing oscillatory approaches to syntactic structure building and assess their functionality in light of basic properties of a hierarchical syntactic structure, such as varied length of syntactic phrases, nesting of constituents, overlap in length between different levels of the syntactic hierarchy and others. I will also briefly discuss key requirements on neural structure building mechanisms from the perspective of a real-time parser.

A major challenge of cognitive neuroscience is to understand how the brain as a network gives rise to our cognition. Simultaneous [18F]-fluorodeoxyglucose positron emission tomography functional magnetic resonance imaging (FDG-PET/fMRI) provides the opportunity to investigate brain connectivity not only via spatially distant, synchronous cerebrovascular hemodynamic responses (functional connectivity), but also glucose metabolism (metabolic connectivity). However, how these two modalities of brain connectivity differ in their relation to cognition is unknown. In this webinar, Dr Katharina Voigt will discuss recent findings demonstrating the advantage of simultaneous FDG-PET/fMRI in providing a more complete picture of the neural mechanisms underlying cognition, that calls for a combination of both modalities in future cognitive neuroscience. Dr Katharina Voigt is a Research Fellow within the Turner Institute for Brain and Mental Health, Monash University. Her research interests include systems neuroscience, simultaneous PET-MRI, and decision-making.

In this talk, Dr. Quandt will share results from behavioral and cognitive neuroscience studies from the past few years of her work in the Action & Brain Lab, an EEG lab at Gallaudet University, the world's premiere university for deaf and hard-of-hearing students. These results will center upon the question of how extensive knowledge of signed language changes, and in some cases enhances, people's perception and cognition. Evidence for this effect comes from studies of human biological motion using point light displays, self-report, and studies of action perception. Dr. Quandt will also discuss some of the lab's efforts in designing and testing a virtual reality environment in which users can learn American Sign Language from signing avatars (virtual humans).

At any given moment the brain receives more sensory information than it can use to guide adaptive behaviour, creating the need for mechanisms that promote efficient processing of incoming sensory signals. One way in which the brain might reduce its sensory processing load is to encode successive presentations of the same stimulus in a more efficient form, a process known as neural adaptation. Conversely, when a stimulus violates an expected pattern, it should evoke an enhanced neural response. Such a scheme for sensory encoding has been formalised in predictive coding theories, which propose that recent experience establishes expectations in the brain that generate prediction errors when violated. In this webinar, Professor Jason Mattingley will discuss whether the encoding of elementary visual features is modulated when otherwise identical stimuli are expected or unexpected based upon the history of stimulus presentation. In humans, EEG was employed to measure neural activity evoked by gratings of different orientations, and multivariate forward modelling was used to determine how orientation selectivity is affected for expected versus unexpected stimuli. In mice, two-photon calcium imaging was used to quantify orientation tuning of individual neurons in the primary visual cortex to expected and unexpected gratings. Results revealed enhanced orientation tuning to unexpected visual stimuli, both at the level of whole-brain responses and for individual visual cortex neurons. Professor Mattingley will discuss the implications of these findings for predictive coding theories of sensory encoding. Professor Jason Mattingley is a Laureate Fellow and Foundation Chair in Cognitive Neuroscience at The University of Queensland. His research is directed toward understanding the brain processes that support perception, selective attention and decision-making, in health and disease.

To date, neuroimaging research has had a limited focus on non-social features of autism. As a result, neurobiological explanations for atypical sensory perception in autism are lacking. To address this, we quantitively condensed findings from the non-social autism fMRI literature in line with the current best practices for neuroimaging meta-analyses. Using activation likelihood estimation (ALE), we conducted a series of robust meta-analyses across 83 experiments from 52 fMRI studies investigating differences between autistic (n = 891) and typical (n = 967) participants. We found that typical controls, compared to autistic people, show greater activity in the prefrontal cortex (BA9, BA10) during perception tasks. More refined analyses revealed that, when compared to typical controls, autistic people show greater recruitment of the extrastriate V2 cortex (BA18) during visual processing. Taken together, these findings contribute to our understanding of current theories of autistic perception, and highlight some of the challenges of cognitive neuroscience research in autism.

The cognitive neuroscience of conscious perception has seen considerable growth over the past few decades. Confirming an influential hypothesis driven by earlier studies of neuropsychological patients, we have found that the lateral and polar prefrontal cortices play important causal roles in the generation of subjective experiences. However, this basic empirical finding has been hotly contested by researchers with different theoretical commitments, and the differences are at times difficult to resolve. To address the controversies, I suggest one alternative venue may be to look for clinical applications derived from current theories. I outline an example in which we used closed-loop fMRI combined with machine learning to nonconsciously manipulate the physiological responses to threatening stimuli, such as spiders or snakes. A clinical trial involving patients with phobia is currently taking place. I also outline how this theoretical framework may be extended to other diseases. Ultimately, a truly meaningful understanding of the fundamental nature of our mental existence should lead to useful insights for our colleagues on the clinical frontlines. If we use this as a yardstick, whoever loses the esoteric theoretical debates, both science and the patients will always win.

John O’Keefe is a Professor of Cognitive Neuroscience at UCL and he received the Nobel Prize in Physiology or Medicine in 2014 for his “discoveries of cells that constitute a positioning system in the brain". His revolutionary research on hippocampal place cells provided deeper insight into the neural processes underlying the sense of space. His lab in Sainsbury Wellcome Centre applies a wide range of methods to facilitate our understanding of the role of the entorhinal cortex and hippocampus in spatial memory and the neural mechanisms underlying short-term memories in the amygdala.

Computational and cognitive neuroscience techniques have made great strides towards describing the neural computations underlying perceptual inference and decision-making under uncertainty. These tools tell us how and why perceptual illusions occur, which brain areas may represent noisy information in a probabilistic manner, and so on. However, an understanding of the subjective, qualitative aspects of perception remains elusive: qualia, or the personal, intrinsic properties of phenomenal awareness, have remained out of reach of these computational analytic insights. Here, I propose that metacognitive computations, and the subjective feelings that go along with them, give us a solid starting point for understanding subjective experience in general. Specifically, perceptual metacognition possesses ontological and practical properties that provide a powerful and unique opportunity for studying the studying the neural and computational correlates of subjective experience using established tools of computational and cognitive neuroscience. By capitalizing on decades of developments in formal computational model comparisons as applied to the specific properties of perceptual metacognition, we are now in a privileged position to reveal new and exciting insights about how the brain constructs our subjective conscious experiences.

In many ways, cognitive neuroscience is the attempt to use physiological observation to clarify the mechanisms that shape behavior. Over the past 25 years, fMRI has provided a system-wide and yet somewhat spatially precise view of the response in human cortex evoked by a wide variety of stimuli and task contexts. The current talk focuses on the other direction of inference; the implications of this observed functional organization for behavior. To begin, we must interrogate the methodological and empirical frameworks underlying our derivation of this organization, partially by exploring its relationship to and predictability from gross neuroanatomy. Next, across a series of studies, the implications of two properties of functional organization for behavior will be explored: 1) the co-localization of visual working memory and perceptual processing and 2) implicit learning in the context of distributed responses. In sum, these results highlight the limitations of our current approach and hint at a new general mechanism for explaining observed behavior in context with the neural substrate.

Speakers will highlight research on the developmental processes underlying cognitive control and the effects of environmental risk factors on neural pathways in human cognitive development. Gaia Scerif, from University of Oxford, will be giving a talk on Using developmental cognitive neuroscience tools to investigate mechanisms of atypical cognitive control, followed by Kirsten Donald, from University of Cape Town, who will give a talk titled Neuroimaging the very young high risk brain: lessons from a south African birth cohort.