Past events

The study of human memory is a rich field with a history that spans over a century, traditionally investigated through the prism of psychology. Drawing inspiration from this vast pool of findings, we approached the subject with a more physics-oriented mindset based on first principles. For this reason, we combined mathematical modelling of established ideas from the literature of psychology with large-scale experimentation. In particular, we created a model based on the concept of retroactive interference that states that newly encoded items hinder the retention of older ones in memory. We show that this simple mechanism is sufficient to describe a variety of experimental data of recognition memory with different categories of verbal and pictorial stimuli. The model has a single free parameter and can be solved analytically. We then focus on recall and recognition memory of stories. This transition from discrete random lists to coherent continuous stimuli such as stories introduces a new challenge when it comes to the quantification and the analysis of the results. To address this, we have developed a pipeline that employs large language models and showed that it performs comparably to human evaluators. Using this tool we were able to show that recall scales linearly with recognition and story size for the range we examined. Finally, we discovered that when stories are presented in a scrambled manner, even though recall performance drops, subjects seem to reconstruct the material in their recall in alignment to the unscrambled version.

During sleep, our memories are reactivated and consolidated in an active process that significantly influences our memory and decision-making. In this talk, I will present two studies about sleep-memory consolidation. The first study investigated sleep memory consolidation's local versus global properties within the brain. By exploiting the unique functional neuroanatomy of olfactory system, we were able to manipulate sleep oscillations and enhance memories locally within a single hemisphere during sleep. These findings underscore the local nature of sleep memory consolidation, which can be selectively manipulated within the brain, thereby creating an important link between theories of local sleep and learning. The second research explored the relationship between generalization processes and sleep, acknowledging that overgeneralization of negative stimuli and disruptions in sleep quality contribute to anxiety and PTSD disorders. Specifically, we studied participants' responses to stimuli associated with positive, negative, or neutral outcomes. Our findings revealed significant correlations between brain activity, as detected by fMRI, during the association of a stimulus with an outcome and the perceptual generalization of these stimuli. While activity in limbic brain areas was correlated with immediate negative stimulus generalization, we observed that the activation in these areas predicted recovery and positively related generalization following sleep. Moreover, we identified specific sleep oscillations correlated with this recovery generalization using high-density EEG recordings. These results highlight the crucial role of sleep in both generalization processes and the restoration of balanced responses to stimuli. Understanding these mechanisms can offer valuable insights into developing therapeutic strategies for anxiety and PTSD.

For centuries, consciousness was considered to be outside the reach of scientific investigation. Yet in recent decades, more and more studies have tried to probe the neural correlates of conscious experience, and several neuronally-inspired theories for consciousness have emerged. In this talk, I will focus on four leading theories of consciousness: Global Neuronal Workspace (GNW), integrated Information Theory (IIT), Recurrent Processing Theory (RPT) and Higher Order Theory (HOT). I will first shortly present the guiding principles of these theories. Then, I will provide a bird's-eye view of the field, using the results of a large-scale quantitative and analytic review we conducted, examining all studies that either empirically tested these theories or interpreted their findings with respect to at least one of them. Finally, I will describe the first results of the Cogitate consortium - an adversarial collaboration aimed at testing GNW and IIT.

The study of human memory is a rich field with a history that spans over a century, traditionally investigated through the prism of psychology. Drawing inspiration from this vast pool of findings, we approached the subject with a more physics-oriented mindset based on first principles. For this reason, we combined mathematical modelling of established ideas from the literature of psychology with large-scale experimentation. In particular, we created a model based on the concept of retroactive interference that states that newly encoded items hinder the retention of older ones in memory. We show that this simple mechanism is sufficient to describe a variety of experimental data of recognition memory with different categories of verbal and pictorial stimuli. The model has a single free parameter and can be solved analytically. We then focus on recall and recognition memory of stories. This transition from discrete random lists to coherent continuous stimuli such as stories introduces a new challenge when it comes to the quantification and the analysis of the results. To address this, we have developed a pipeline that employs large language models and showed that it performs comparably to human evaluators. Using this tool we were able to show that recall scales linearly with recognition and story size for the range we examined. Finally, we discovered that when stories are presented in a scrambled manner, even though recall performance drops, subjects seem to reconstruct the material in their recall in alignment to the unscrambled version.

During sleep, our memories are reactivated and consolidated in an active process that significantly influences our memory and decision-making. In this talk, I will present two studies about sleep-memory consolidation. The first study investigated sleep memory consolidation's local versus global properties within the brain. By exploiting the unique functional neuroanatomy of olfactory system, we were able to manipulate sleep oscillations and enhance memories locally within a single hemisphere during sleep. These findings underscore the local nature of sleep memory consolidation, which can be selectively manipulated within the brain, thereby creating an important link between theories of local sleep and learning. The second research explored the relationship between generalization processes and sleep, acknowledging that overgeneralization of negative stimuli and disruptions in sleep quality contribute to anxiety and PTSD disorders. Specifically, we studied participants' responses to stimuli associated with positive, negative, or neutral outcomes. Our findings revealed significant correlations between brain activity, as detected by fMRI, during the association of a stimulus with an outcome and the perceptual generalization of these stimuli. While activity in limbic brain areas was correlated with immediate negative stimulus generalization, we observed that the activation in these areas predicted recovery and positively related generalization following sleep. Moreover, we identified specific sleep oscillations correlated with this recovery generalization using high-density EEG recordings. These results highlight the crucial role of sleep in both generalization processes and the restoration of balanced responses to stimuli. Understanding these mechanisms can offer valuable insights into developing therapeutic strategies for anxiety and PTSD.

For centuries, consciousness was considered to be outside the reach of scientific investigation. Yet in recent decades, more and more studies have tried to probe the neural correlates of conscious experience, and several neuronally-inspired theories for consciousness have emerged. In this talk, I will focus on four leading theories of consciousness: Global Neuronal Workspace (GNW), integrated Information Theory (IIT), Recurrent Processing Theory (RPT) and Higher Order Theory (HOT). I will first shortly present the guiding principles of these theories. Then, I will provide a bird's-eye view of the field, using the results of a large-scale quantitative and analytic review we conducted, examining all studies that either empirically tested these theories or interpreted their findings with respect to at least one of them. Finally, I will describe the first results of the Cogitate consortium - an adversarial collaboration aimed at testing GNW and IIT.