06 June 2018 , 18:30 - 20:30

Alumni talk series: Tomás Goucha (Leipzig) and Nikos Green (Berlin)

Goucha: “Conciliating language differences with universal competence in brain structure and function” and Green: "Neuroscience and digital health"

Map to venue:
Café Flora soft on Campus Nord (pdf)

Tomás Goucha was a member of doctoral cohort 2011−2014. His doctoral project on the influence of interpersonal abilities on social decisions and their physiological correlates was supervised by Angela Friederici and Elke van der Meer. He is currently a postdoctoral researcher with Angela Friederici at the Max Planck Institute for Human Cognitive and Brain Sciences, coordinating the group of Language Learning and Plasticity. The current project investigates brain changes while learning a second language. For this purpose, Tomás and his group recruited a group of Arabic mother tongue speakers newly arrived in Germany and provided them with an intensive language course. Along the course, these participants received both structural and functional MRI scans. With this project, they intend to understand why some people learn a foreign language more successfully than others and how the adult brain adapts to the challenge of learning a new language.

Abstract: “Conciliating language differences with universal competence in brain structure and function”
Humans share the brain infrastructure that allows them to learn their
mother tongue. This process happens with seemingly little effort
regardless of how different the word languages are. We therefore face
the challenge to explain how this shared brain biology can adapt
to each language and its specific processing demands. One of the keys to
this question lies in the underlying computations, in particular
the capability to combine different meanings according to certain rules,
which is transversal to all languages. First, I will present
an fMRI study where we could dissociate the brain localization of
meaning (i.e., semantics) from the abstract rules that build sentences
(i.e., syntax).
Second, I will present data from diffusion MRI, where we compared the
structural connectivity in the language network of speakers with
different mother tongues.
Studying Chinese, English, and German, we showed that the white matter
connectivity is modulated by the specific processing demands of these
languages.
Finally, I will give a theoretical outlook of how the computations
underlying language can be approached from an evolutionary point of view,
and how we can bring those insights together with our knowledge of brain
structure and function. In sum, I will try to conciliate the
language-specific aspects
of brain structure and function with universal principles in the way
language is implemented in the brain.

Nikos Green was a member of doctoral cohort 1 (2007-2010). His doctoral project on perceptual decision making & decision thresholds was supervised by Hauke Heekeren and Shu Chen Li. After completion of his PhD he did a short Postdoc at FU Berlin. Since 2013/2014 he is working in the startup scene. The first project
was based on research by Isabel Dziobek's group and was spun off with the help of an EXIST Stipend. Unfortunately,
this project never made it to the market and was abandoned.
With a new team he started another company with focus on affective
computing and education technology which midway pivoted to digital health.
As of 2018 this company has been liquidated and he works with his former
Business Angels on Digital Health projects.
Currently he works as Scientist-in-Residence @Flying Health Incubator.

Abstract: "Neuroscience and digital health"
In this talk I will give a small overview on the commercialization of mind and brain (mainly cognitive science, neuroscience, artificial intelligence and psychology) inspired products with a focus on digital health and
education technology. Current technological, regulatory as well as economic circumstances lead to a wealth of scientific inspired (digital) product innovation. On the one hand these are fascinating projects that have a lot of potential to improve state of the art processes, treatments, etc ...

For instance there is great expectation within digital health for earlier diagnosis, better treatments etc. On the other hand, when using (popular) scientific results to conceptualize and build new (digital) products, great care has to be taken, as the way from bench to bedside and back is challenging and expectations can be inflated.