Since the beginning of the 20th century, oscillatory patterns have been identified in recordings of human brain activity. Neural oscillation research is a highly active area of investigation, with several competing hypotheses about the role oscillations might play in human cognition. Here we focus on the spatial dimension and look at the emergent topic of oscillations in the form of ‘traveling waves’. These have been detected in different cortical areas, but there is no clear computational role. In the proposed project, I will first develop the waveSCOPE toolbox for the spatiotemporal characterization of propagating events. This open source toolbox (WP1) uses a novel-to-the-research-field algorithm. The algorithm leverages the fact that we can record cortical activity with many sensors (e.g. using MEG or EEG) and arrive at multivariate estimation of phases across recording channels. This allows tracking traveling waves across many frequencies, without the selection of a prior frequency-of-interest. The procedure will be validated in resting state data and compared systematically to other state-of-the-art wave detection algorithms. I then will apply the novel methodology to speech processing data acquired via magnetoencephalography (WP2). During the processing of speech, one typically observes a complex coordinated hierarchy of rhythmic activity. We will investigate whether wave propagation direction is congruent to directions expected by functional anatomic organization and known auditory processing stages. The knowledge and skills gained from this interdisciplinary project, using a new recording modality as well as a new domain of study, will allow me to further develop a competitive scientific career as an independent researcher. In terms of scientific impact, the characterization of propagating activity will be helpful in the hunt for well-motivated abstractions in the amount of ever-increasing brain data and therefore of fundamental importance for neuroscience.

During active wakefulness, cortical activity organizes itself into highly coherent patterns of gamma waves (30-80Hz). These waves are believed to be essential for cortical communication and synaptic plasticity. Their impairment is a hallmark of neurological and psychiatric disorders. Yet, it remains heavily debated what gamma waves encode, and what their precise role in information transmission is. I have recently proposed a new theory about gamma in visual cortex, building on the predictive coding theory. The predictive coding theory holds that the brain makes active top-down predictions about its own sensory inputs. By comparing these, it generates bottom-up prediction errors to drive learning and the updating of priors. The standard view in predictive coding theories is that gamma waves carry prediction errors. However, I recently hypothesized the opposite: 1) Gamma waves signal a match between predictions and sensory inputs (i.e. predictability), and 2) Columns that predict each other's visual input engage in long-range gamma-synchronization. To test this hypothesis, it is critical to develop a new method to quantify predictions and prediction errors in the context of natural vision. I will solve this by using recently developed deep-learning networks for prediction. By making multi-areal recordings from visual cortex in marmosets and humans (MEG), I will test if predictability indeed determines gamma waves and their synchronization pattern across space. Because stimulus priors have to be acquired through learning, I will further determine whether gamma waves depend on experience and perceptual learning. In marmosets, I will develop an optogenetics approach to test whether gamma waves drive perceptual learning, and test the prediction that V1 gamma waves depend on top-down feedback. In sum, I expect to provide evidence for a new, unified theory about the role of gamma waves in information transmission and the integration of sensory evidence with predictions.

Neuroscience Neuroscience is an advanced field of science still poorly represented in Eastern Europe. Individual efforts have created some centres of excellence over the past years, mostly by scientists returning home from western labs. One such centre is the Transylvanian Institute of Neuroscience (TINS), located in Transylvania, Romania. TINS hosts one of the most important training centres in experimental neurosciences worldwide: the Transylvanian Experimental Neuroscience Summer School (TENSS). We propose a twinning between TINS and three internationally-leading European institutions from countries where neuroscience is most developed: Germany, France, and UK. TINS will twin with the Ernst Stüngmann Institute for Neuroscience in Frankfurt, Imagine Institute in Paris, and University College London. The objectives of the twinning are: i) to increase the scientific competence of TINS researchers; ii) to increase the innovation capacity of TINS; iii) to enhance the international visibility and prestige of TINS; iv) to improve TINS’ capability to compete for research funding; v) to promote the involvement of early stage researchers at TINS; vi) to enable TINS to become a neuroscience development pole in Romania and Eastern Europe. To attain these objectives, TINS and its three top international partners will organize periodically mutual research staff exchanges (short stays), training lectures at each institution, a top profile neuroscience seminar series at TINS, the TENSS summer school, periodic consortium retreats, dissemination and outreach activities with patient associations and industry, and collaboration among technology-transfer offices to implement best practices at TINS. The twinning will increase the scientific competence at TINS in neurosciences, develop a competitive innovation and technology transfer strategy, raise significantly its international visibility, and enable it to successfully partner with top institutions for future collaborative projects.