CNS 2026 Annual Meeting | Conference Videos
Opening Ceremonies and Keynote Address - Our Language-Ready Brain
Peter Hagoort, PhD, Max Planck Institute for Psycholinguistics, Donders Centre for Cognitive Neuroimaging, Nijmegen, The Netherlands
Language is a central feature of human uniqueness. Undeniably members of the species homo sapiens produce and understand speech, and many of them can read and write. They do this in quite different varieties. The sound repertoires of the more than 7000 languages that are still around today vary widely, as do their grammatical structures, and the meanings that their lexical items code for. It is equally undisputable that the human brain provides the shared neurobiological infrastructure for our language skills. This infrastructure requires the contribution of multiple neural networks, some more specialized for language than others. In addition, there is substantial neural plasticity that enables the accommodation of language variation and individual variation in language skills. I will discuss the brain’s infrastructure for this uniquely human capacity from a multiple neural networks perspective. Next to the neuro-architectural features I will discuss the neuro-functional aspects of language processing. I will also discuss fMRI results that indicate the insufficiency of the Mirror Neuron Hypothesis to explain language understanding. Instead, understanding the message that the speaker wants to convey requires the contribution of the Theory of Mind network. Finally, I will illustrate why it is hard to give a good presentation.
The 32nd Annual George A. Miller Prize in Cognitive Neuroscience (GAM) - Putting the 'Mental' Back Into 'Mental' Disorders by Fusing the Science of Emotion with the Science of Consciousness
Joseph LeDoux, Ph.D., Professor Emeritus, New York University
People often seek help for mental problems because they suffer subjectively. Yet, for decades, the subjective experiences of patients have been marginalized due to the dominant medical model of mental illness, which arose in the mid Twentieth Century and viewed subjective experiences as quaint relics from less enlightened scientific time. To the extent that subjective symptoms reflect a latent disease, it was assumed that with subjective treatment of objective symptoms, such as behavioral and physiological responses, subjective mental symptoms will go away. But given that 'mental’ disorders are named for, and defined by, their subjective mental qualities, it is perhaps not surprising, in retrospect, that treatments that have sidelined subjective experiences have been disappointing at best. There were few avenues for rigorously studying conscious experiences when these negative views about subjective experience took root in psychiatry and allied fields. Today, however, research on consciousness is thriving, and could potentially help achieve a deeper understanding of mental disorders and their treatment. But a new approach is needed, one that fuses the science of emotion with the science of consciousness. Presently, both fields are diminished by mutual ignorance, and much could be gained by a science of emotional consciousness in which emotion researchers accept that emotions are conscious experiences, and consciousness researchers accept that emotions are our most important conscious experiences.
Young Investigator Award Lecture 1 - Neural signatures of sustained attention across time scales and individuals
Monica Rosenberg, Ph.D., University of Chicago
Maintaining focus is critical for goal-directed behavior, yet sustained attention is inherently dynamic—fluctuating across seconds, waning across minutes to hours, and developing across childhood and adolescence. How and why does attention vary over time and across individuals? I will show that large-scale functional brain networks can serve as generalizable neural signatures of sustained attention, predicting individual differences and within-person changes when measured during tasks, narratives, and rest. Moreover, I will argue that the primary utility of such brain-based predictive models lies in revealing how attention operates and interacts with broader cognitive processes, offering a framework for understanding variability in cognition across individuals and over time.
Young Investigator Award Lecture 2 - Generalized prediction errors in the human cerebellum
Samuel D. McDougle, Ph.D., Department of Psychology, Yale University
Your cerebellum contains more neurons and uses more energy than the rest of the brain combined. Evolutionarily, the cerebellum expanded hand-in-hand with the expansion of our species’ cerebral cortex. It may not be surprising, then, that in addition to the cerebellum’s well-known role in sensorimotor behavior, this remarkable structure is implicated in language, working memory, cognitive control, and social cognition. One enduring mystery, however, is how specifically the cerebellum supports cognition. My lab has begun to explore the idea that cerebellar contributions to nonmotor tasks may involve the same prediction and error-based learning principles observed in cerebellar sensorimotor computations. Our recent neuroimaging results point to nonmotor prediction errors in ‘cognitive’ regions of the human cerebellar cortex. We observe these signals in both reinforcement learning and statistical learning contexts. Moreover, these signals appear to share constraints with cerebellar sensorimotor computations, including a preference for subsecond temporal intervals between associated events. Our findings suggest that the cerebellum contributes to rapid coordination of cognitive representations, directly echoing its role in motor control. These results expand our understanding of the computational functions of the human cerebellum and blur the lines between the sensorimotor and cognitive domains.
