ERC FUNDED PROJECTS

If you suddenly hear your song on the radio and spontaneously decide to burst into dance in your living room, you need to precisely time your movements if you do not want to find yourself on your bookshelf. Most of what we do or perceive depends on how accurately we represent the temporal properties of the environment however we cannot see or touch time. As such, time in the millisecond range is both a fundamental and elusive dimension of everyday experiences. Despite the obvious importance of time to information processing and to behavior in general, little is known yet about how the human brain process time. Existing approaches to the study of the neural mechanisms of time mainly focus on the identification of brain regions involved in temporal computations (‘where’ time is processed in the brain), whereas most computational models vary in their biological plausibility and do not always make clear testable predictions. BiT is a groundbreaking research program designed to challenge current models of time perception and to offer a new perspective in the study of the neural basis of time. The groundbreaking nature of BiT derives from the novelty of the questions asked (‘when’ and ‘how’ time is processed in the brain) and from addressing them using complementary but distinct research approaches (from human neuroimaging to brain stimulation techniques, from the investigation of the whole brain to the focus on specific brain regions). By testing a new biologically plausible hypothesis of temporal representation (via duration tuning and ‘chronotopy’) and by scrutinizing the functional properties and, for the first time, the temporal hierarchies of ‘putative’ time regions, BiT will offer a multifaceted knowledge of how the human brain represents time. This new knowledge will challenge our understanding of brain organization and function that typically lacks of a time angle and will impact our understanding of how the brain uses time information for perception and action

1 670 830 €

Start date: 2016-10-01, End date: 2021-09-30

The ability to construct new meanings by combining words into larger constituents is one of the fundamental and peculiarly human characteristics of language. Systems that induce the meaning and combinatorial properties of linguistic symbols from data are highly desirable both from a theoretical perspective (modeling a core aspect of cognition) and for practical purposes (supporting human-computer interaction). COMPOSES tackles the meaning induction and composition problem from a new perspective that brings together corpus-based distributional semantics (that is very successful at inducing the meaning of single content words, but ignores functional elements and compositionality) and formal semantics (that focuses on functional elements and composition, but largely ignores lexical aspects of meaning and lacks methods to learn the proposed structures from data). As in distributional semantics, we represent some content words (such as nouns) by vectors recording their corpus contexts. Implementing instead ideas from formal semantics, functional elements (such as determiners) are represented by functions mapping from expressions of one type onto composite expressions of the same or other types. These composition functions are induced from corpus data by statistical learning of mappings from observed context vectors of input arguments to observed context vectors of composite structures. We model a number of compositional processes in this way, developing a coherent fragment of the semantics of English in a data-driven, large-scale fashion. Given the novelty of the approach, we also propose new evaluation frameworks: On the one hand, we take inspiration from cognitive science and experimental linguistics to design elicitation methods measuring the perceived similarity and plausibility of sentences. On the other, specialized entailment tests will assess the semantic inference properties of our corpus-induced system.

1 117 636 €

Start date: 2011-11-01, End date: 2016-10-31

The foundation of lived experience is that it occurs in a particular space and time. Objects, events and actions happen in the present moment in a unified space which surrounds our body. As noted by Immanuel Kant, space and time are a priori concepts that organize our thoughts and experiences. Yet basic laboratory experiments reveal the cracks in this illusion of a unified perceptual space-time. Our subjective experience is a construction created out of the responses of numerous sensory detectors which give only limited information. In terms of space, the sensory input from a multitude of tiny windows is organized based on the coordinates of the receptor system, such as the fingertip or a specific location on the retina. In terms of time, sensory input is summed over a limited period which varies widely across different receptor types. Critically, none of these sensory detectors has a spatial-temporal response that corresponds to our subjective experience. Nonetheless, the mind constructs an illusion of unified space and continuous time out of the variegated responses. The goal of this project is to uncover the mechanisms underlying smooth and continuous perception. This project builds on a decade of groundwork in studying specific instances of the integration of visual information over space and time with a new focus on the mechanisms that unite the various phenomena which have up to now been studied separately. A combination of behavioral, neuroimaging and computational approaches will be used to identify the mechanisms underlying spatio-temporal continuity in high-level perception. We will track the dynamic shifts between the various temporal and spatial coordinate frames used to encode information in the brain, a topic which has remained largely unexplored. This research project, driven by specific hypotheses, aims to uncover how uni-sensory, ego-centric sensory responses give rise to the rich, multisensory experience of unified space-time.

1 002 102 €

Start date: 2013-01-01, End date: 2017-12-31

Neuronal plasticity is an important mechanism for memory and cognition, and also fundamental to fine-tune perception to the environment. It has long been thought that sensory neural systems are plastic only in very young animals, during the so-called “critical period”. However, recent evidence – including work from our laboratory – suggests that the adult brain may retain far more capacity for plastic change than previously assumed, even for basic visual properties like ocular dominance. This project probes the underlying neural mechanisms of adult human plasticity, and investigates its functional role in important processes such as response optimization, auto-calibration and recovery of function. We propose a range of experiments employing many experimental techniques, organized within four principle research lines. The first (and major) research line studies the effects of brief periods of monocular deprivation on functional cortical reorganization of adults, measured by psychophysics (binocular rivalry), ERP, functional imaging and MR spectroscopy. We will also investigate the clinical implications of monocular patching of children with amblyopia. Another research line looks at the effects of longer-term deprivation, such as those induced by hereditary cone dystrophy. Another examines the interplay between plasticity and visual adaptation in early visual cortex, with techniques aimed to modulate retinotopic organization of primary visual cortex. Finally we will use fMRI to study development and plasticity in newborns, providing benchmark data to assess residual plasticity of older humans. Pilot studies have been conducted on most of the proposed lines of research (including fMRI recording from alert newborns), attesting to their feasibility and the likelihood of them being completed within the timeframe of this grant. The PI has considerable experience in all these research areas.

2 493 000 €

Start date: 2014-05-01, End date: 2019-04-30

How do we rapidly and effortlessly compute a vivid veridical representation of the external world from the noisy and ambiguous input supplied by our sensors? One possibility is that the brain does not process all incoming sensory information anew, but actively generates a model of the world from past experience, and uses current sensory data to update that model. This classic idea has been well formulised within the modern framework of Generative Bayesian Inference. However, despite these recent theoretical and empirical advances, there is no definitive proof that generative mechanisms prevail in perception, and fundamental questions remain. The ambitious aim of GenPercept is to establish the importance of generative processes in perception, characterise quantitatively their functional role, and describe their underlying neural mechanisms. With innovative psychophysical and pupillometry techniques, it will show how past perceptual experience is exploited to manage and mould sensory analysis of the present. With ultra-high field imaging, it will identify the underlying neural mechanisms in early sensory cortex. With EEG and custom psychophysics it will show how generative predictive mechanisms mediate perceptual continuity at the time of saccadic eye movements, and explore the innovative idea that neural oscillations reflect reverberations in the propagation of generative prediction and error signals. Finally, it will look at individual differences, particularly in autistic perception, where generative mechanisms show interesting atypicalities. A full understanding of generative processes will lead to fundamental insights in understanding how we perceive and interact with the world, and how past perceptual experience influences what we perceive. The project is also of clinical relevance, as these systems are prone to dysfunction in several neuro-behavioural conditions, including autism spectrum disorder.

2 480 969 €

Start date: 2019-06-01, End date: 2024-05-31

"From observing other people’s movements, humans make inferences that go far beyond the appearance of the observed stimuli: inferences about unobservable mental states such as goals and intentions. Although this ability is critical for successful social interaction, little is known about how – often fast and reliably – we are able to make such inferences. I.MOVE.U intends to provide the first comprehensive account of how intentions are extracted from body motion during interaction with conspecifics. Covert mental states such as intentions become visible to the extent they contribute as dynamic factors to generate the kinematics of a given action. By combining advanced methods in psychophysics and neuroscience with kinematics and virtual reality technologies, this project will study i) to what extent observers are sensitive to intention information conveyed by body movements; ii) what mechanisms and neural processes mediate the ability to extract intention from body motion; iii) how, during on-line social interaction with another agent, agents use their own actions to predict the partner’s intention. These issues will be addressed at different levels of analysis (motor, cognitive, neural) in neurotypical participants and participants with autism spectrum disorders. For the first time, to investigate real-time social interaction, full-body tracking will be combined with online generation of biological motion stimuli to obtain visual biological motion stimuli directly dependent on the actual behavior of participants. I.MOVE.U pioneers a new area of research at the intersection of motor cognition and social cognition, providing knowledge of direct scientific, clinical, and technological impact. The final outcome of the project will result in a new quantitative methodology to investigate the decoding of intention during interaction with conspecifics."

999 920 €

Start date: 2013-09-01, End date: 2018-08-31

Human life is full of joint action and our achievements are, to a large extent, joint achievements that require the coordination of two or more individuals. Piano duets and tangos, but also complex technical and medical operations rely on and exist because of coordinated actions. In recent years, research has begun to identify the basic mechanisms of joint action. This work focused on simple tasks that can be performed together without practice. However, a striking aspect of human joint action is the expertise interaction partners acquire together. How people acquire joint expertise is still poorly understood. JAXPERTISE will break new ground by identifying the behavioural, cognitive, and neural mechanisms underlying the learning of joint action. Participating in joint activities is also a motor for individual development. Although this has long been recognized, the mechanisms underlying individual learning through engagement in joint activities remain to be spelled out from a cognitive science perspective. JAXPERTISE will make this crucial step by investigating how joint action affects source memory, semantic memory, and individual skill learning. Carefully designed experiments will optimize the balance between capturing relevant interpersonal phenomena and maximizing experimental control. The proposed studies employ behavioural measures, electroencephalography, and physiological measures. Studies tracing learning processes in novices will be complemented by studies analyzing expert performance in music and dance. New approaches, such as training participants to regulate each other’s brain activity, will lead to methodological breakthroughs. JAXPERTISE will generate basic scientific knowledge that will be relevant to a large number of different disciplines in the social sciences, cognitive sciences, and humanities. The insights gained in this project will have impact on the design of robot helpers and the development of social training interventions.

1 992 331 €

Start date: 2014-08-01, End date: 2019-07-31

Visual awareness affords flexibility and experiential richness, and its loss following brain damage has devastating effects. However, patients with blindness following cortical damage may retain visual functions, despite visual awareness is lacking (blindsight). But, how can we translate non-conscious visual abilities into conscious ones after damage to the visual cortex? To place our understanding of visual awareness on firm neurobiological and mechanistic bases, I propose to integrate human and monkey neuroscience. Next, I will translate this wisdom into evidence-based clinical intervention. First, LIGHTUP will apply computational neuroimaging methods at the micro-scale level, estimating population receptive fields in humans and monkeys. This will enable analyzing fMRI signal similar to the way tuning properties are studied in neurophysiology, and to clarify how brain areas translate visual properties into responses associated with awareness. Second, LIGHTUP leverages a behavioural paradigm that can dissociate nonconscious visual abilities from awareness in monkeys, thus offering a refined animal model of visual awareness. Applying behavioural-Dynamic Causal Modelling to combine fMRI and behavioral data, LIGHTUP will build up a Bayesian framework that specifies the directionality of information flow in the interactions across distant brain areas, and their causal role in generating visual awareness. In the third part, I will devise a rehabilitation protocol that combines brain stimulation and visual training to promote the (re)emergence of lost visual awareness. LIGHTUP will exploit non-invasive transcranial magnetic stimulation (TMS) in a novel protocol that enables stimulation of complex cortical circuits and selection of the direction of connectivity that is enhanced. This associative stimulation has been proven to induce Hebbian plasticity, and we have piloted its effects in fostering visual awareness in association with visual restoration training.

1 994 212 €

Start date: 2018-08-01, End date: 2023-07-31

"Your brain is among the most complex existing systems, and it processes every second an amazing amount of data. The most amazing thing, however, is that you get to know some of it. Declarative knowledge, meaning the portion of knowledge that we can consciously access and manipulate, is one of the most enduring mysteries of the human mind. How did it evolve? And what are the mechanisms behind it? One possibility is that the complex neural machinery that mammals evolved to navigate space has been recycled to ""navigate"" declarative knowledge. Research from single cell recordings in rodents to brain imaging studies with humans is converging toward the fascinating hypothesis that conscious declarative knowledge is spatially organized, and can be stored, retrieved and manipulated through the same computations used to represent and navigate physical space. Crucially, this spatial scaffolding may be what makes knowledge accessible to us. The time is mature for an integral and ambitious attempt to test and develop this innovative hypothesis. NOAM will be at the frontline of this endeavour relying upon cutting-edge neuroimaging and analysis techniques. In this project we will test the relationships between spatial and conceptual navigation asking whether people that navigate space in a different way (congenitally blind individuals) also navigate concepts in a different way. Then, we will explore how low-dimensional cognitive maps interact with multidimensional semantic information, and we will test whether the spatial organization is a trademark of conscious declarative knowledge or extends to unconscious conceptual processing. Finally we will adopt a translational approach to characterize the neural basis of pre-clinical Alzheimer Disease. Thanks to its groundbreaking nature and high-risk/high-gain approach, NOAM has the potential to ensure major progresses in cognitive neuroscience, artificial intelligence and related fields, changing the way we think about the human mind"

1 498 644 €

Start date: 2019-04-01, End date: 2024-03-31