Almost 200 years ago, Jan Purkinje examined the visual illusions induced by flickering light. Since then, scientists, clinicians, and artists have been fascinated by the effects of flicker on brain rhythms. When entrained with rhythmic light of ~10, ~20, ~40 Hz, visual cortex responds more strongly, or resonates. In the visual and cognitive neurosciences, resonance flicker is used to study perception and attention; in clinical domain, aberrant resonance responses to flicker are used as a diagnostic tool and potential treatment. However, the neural mechanisms by which flicker engages resonant properties of local cortical circuits and entrains brain rhythms at the level they are generated remain unknown. Over the past decade, this level became accessible to neuroscientists due to the rapid development of new neurobiological tools such as cell-type-specific optical stimulation (optogenetics). In this project, using recordings that span multiple spatial scales (from neurons and local field potentials across cortical layers to EEG), I will characterize the neural mechanisms by which flicker stimuli engage resonant properties of brain rhythms. I will use optogenetic tools to identify and manipulate genetically targeted cell types, and will combine it with simultaneous EEG and high-density laminar recordings in primary visual cortex of awake mice. I will determine the laminar profile of neural activity underlying flicker resonance observed at the EEG level (Study 1). By recording from distinct GABAergic interneuron classes and optogenetically silencing them, I will test the novel hypothesis that distinct classes of interneurons mediate flicker resonance to low (theta, alpha) and high (beta, gamma) frequencies (Study 2). This research will allow me to uncover the neurophysiological basis of resonance responses to flicker in unprecedented detail, and provide means to exploit the untapped potential of flicker as a tool to study and modulate brain rhythms in a targeted way.

At first blush entities and concepts such as “Dutch East India Company” or “coffee” may seem straightforward, but in fact they are complex and multifaceted. The wealth of digital sources presents the massive potential to study these notions at an unprecedented scale. However, current technologies for distant reading are not capable of dealing with this. TRIFECTA aims to create a database that describes complex entities and concepts and their contexts by combining language and semantic web technology to extract and relate information from different texts over time. In addition, a key aim of TRIFECTA is to advance the state of the art in these technologies to deal with change over time and connections to many different narratives. Sophisticated knowledge representation methods from the semantic web can mitigate the failing that many language technology methods do not incorporate enough background knowledge to recognise and interpret complex entities and concepts in their historical contexts. By treating them as rich networks (or graphs) of knowledge that can express change and relationships to different concepts in space and time, semantic databases can handle the complexity needed to make the outputs of language technology tools suited to humanities research. Via two use cases, I identify a set of core contentious entities and concepts in maritime and food history. Next, through a data-driven, iterative approach, I advance beyond the state-of-the-art in natural language technology for the humanities by targeting three key aspects of the recognition and modelling of complex concepts (i.e. identity, change, and the long tail). I propose a novel peer-evaluation approach in which a team of humanities scholars, computational linguists, and semantic web researchers collaborate closely to create truly hybrid artificial intelligence systems that will enable humanities research to scale to big data without losing sight of the contextual complexity.

The proposed research aims to understand biophysical embryo-uterine interactions during peri-implantation to identify factors that guide processes such as embryo orientation, egg cylinder morphogenesis, and embryonic axis formation. Recent studies on implantation have gone beyond the traditional biochemical approach to reveal that mechanical interactions at the embryo-uterine interface are abundant and indispensable for proper implantation and development. Due to difficulties in recreating embryo implantation ex-vivo setups and lack of in-utero accessibility, the physical forces and mechano-chemical feedbacks involved in embryo implantation, however, still remain unknown. In this proposal, I will study how mechanical interactions at the embryo-uterine interface during implantation affect embryo development by directly measuring physical force at the interface, identifying the role of major mechanotransducer pathways, and making in-utero observations. In Objective 1, I will build an experimental setup with 2D polyacrylamide (PAA) gels of varying mechanical properties to recapitulate the characteristics of the uterine surface in ex-vivo setups and observe how embryo development depends on the mechanical properties of the substrate. In Objective 2, I will combine traction force microscopy (TFM) and live imaging to quantify how physical forces affect molecular and cellular events during the mouse implantation process. In Objective 3, I will identify how the mechanical forces are transduced into biochemical cues through live-imaging and genetic/pharmaceutical perturbations. Finally, I will investigate the implantation process live in-utero using multiphoton intravital imaging to validate my findings from ex-vivo studies. I hypothesize that mechanical cues will be spatiotemporally linked with biochemical signaling to significantly affect embryo development.

Moral-conflicts arise when individuals need to decide whether to perform actions that benefit themselves, yet at the price of possibly hurting others. The effects of temporal-delays in the outcomes of these decisions are critical, as real-life consequences often unfold over varying timeframes in everyday life, as well as in public-policy, healthcare and economic decisions. While temporal lags are known to affect subjective reward valuation, their effects on moral decisions with conflicting self-benefit and harm-to-others outcomes, remain unexplored. This project will investigate how individuals assign subjective value to delayed outcomes in such conflicts, focusing on the behavioural and cognitive biases that arise due to temporal-discounting, and aim to uncover the neural mechanisms underlying them. Participants will perform moral-decisions, choosing between small self-monetary rewards associated with an unpainful small shock to another individual, to a larger self-reward coupled with a more intense shock to the other, with varied time-delays in the different outcomes. By combining behavioural, fMRI and physiological methods, and integrating them with computational modelling approaches, we will obtain a comprehensive picture of the neurocomputational effects of temporal-discounting in this context, aiming to explain and predict individuals decisions in single-trials. By revealing the effects of temporal-discounting on moral decisions, this project will offer insights for social neuroscience, psychology and neuro-economics, and real-life implications for everyday decision-making, as well as for long-term, high-impact decisions by policymakers. The project will be performed at the Social Brain Lab at the Netherlands Institute for Neuroscience, supervised by Prof C. Keysers and V. Gazzola, world-leading experts in social neuroscience, ensuring I will develop novel theoretical and methodological skills, having a valuable impact on my training and career advancement.