Lise Meitner Research Group Neurobiosocial 

The interaction between the human brain and its social environment is fundamental in shaping cognition through social learning and nurturing. Social support may also buffer against the effects of adverse experiences on mental health and promotes "brain health" through several protective mechanisms. Despite this, more than 800 million people worldwide experience loneliness, which is associated with numerous health problems, including increased risk of mental disorders and cognitive decline[1][2]. Adverse experiences and chronic stress can also alter brain architecture, underscoring the need for stable and supportive environments to promote healthy neurodevelopment and aging[3][4].

At the Lise Meitner Group ‘Neurobiosocial’, we are an interdisciplinary and international team of neuroscientists, biologists, psychologists, medical researchers, and computational scientists dedicated to understanding how biological and social factors shape human brain function, cognition, and mental health. Using advanced brain imaging techniques and computational models, we investigate brain-environment interactions to explore how the brain balances stability and plasticity throughout the lifespan. Given the extended period of human neurodevelopment and our reliance on social relationships for nurture and learning, we recognize the crucial role social factors play in shaping brain structure and cognitive function.

To address these questions, we draw on a diverse range of data, including MRI-based neuroanatomy, histological data, genomics, geocoded data, task-based assessments, and self-reports. This broad approach clarifies the complex interplay between neurobiology and its social context.

Our research team, led by Dr. Sofie Valk, is based at the Max Planck Institute for Human Cognitive and Brain Sciences in Leipzig and the Forschungszentrum Jülich in Germany. Our work spans three core areas: theoretical neuroscience, neurobiology, and social neuroscience. These fields are intricately connected and form the foundation of our inquiries. Computational methods are central to our research—we apply biophysical modeling, machine learning techniques, and develop new analytical methods.

We value open and transparent science, making all our code available on GitHub and publishing our papers with open access. Our lab fosters a culture of inquiry, collaboration, and mutual respect, where we learn and grow together. Below, we outline our key research areas and goals:

Theoretical Neuroscience: Principles of Brain Organization

To understand how brain structure both constrains and enables function, we investigate its neurobiological, genetic, and evolutionary basis. Our previous research has shown that brain structure is genetically organized along large-scale axes (Valk et al., 2020, Science Advances) and elucidated the layer-specific organization of the human brain (Saberi et al., 2023, PLOS Biology). In addition, we have identified heritable intrinsic microstructural and functional asymmetries in brain regions involved in language and attention (Wan et al., 2022, eLife; Wan et al., accepted).

Future directions: We aim to deepen our understanding of human brain organization by integrating multiscale datasets, including newly acquired ultra-high resolution data using 7-Tesla MRI. This research will extend biophysical models and develop computational frameworks to better map the relationship between brain structure and function. In addition, we will explore the interactions between the cerebral cortex and non-cortical regions to gain a broader perspective on how these interactions contribute to overall brain function.

Neurobiology: Lifespan and Plasticity

Our second area of research focuses on how biological factors - including genetics, hormones, and immune responses - influence brain structure and function across the lifespan. Stress hormones such as cortisol can influence brain function, and genetic predispositions shape neural development in interaction with the social environment. For example, our recent studies have demonstrated sex differences in brain structure and function, highlighting the importance of considering sex-specific factors in brain research (Küchenhoff et al., 2024, Nature Communications; Serio et al., 2024, Nature Communications).

Future directions: We aim to extend these findings by using advanced computational models to explore the complex interactions between different biological factors and brain structure. Using longitudinal analyses and large open MRI datasets, we will investigate how brain development is influenced by endocrine factors and how genes contribute to variability in brain structure both between individuals and within individuals over time.

Social neuroscience: Individual variability in health and disease

While genetic factors shape brain structure, environmental influences play a critical role in shaping brain function throughout the lifespan. We believe that the social environment is particularly influential because of the extended maturation of the cerebral cortex and the effects of sociocultural learning. In previous work, I demonstrated that changes in social-environmental demands, such as through mental training, can alter cortical structure and function while improving social cognitive abilities (Valk, 2017, Science Advances; Valk, 2023, eLife). More recently, we showed that microstructural reconfiguration in the brain is associated with resilient adaptation during adolescence, suggesting a complex interplay between neurobiological factors, internal functional models, and adaptation to adverse experiences (Hettwer et al., 2024, Nature Communications). Importantly, the brain is not a passive recipient of the social environment, but actively produces social cognition to navigate interactions with others. In recent findings, we identified the cerebellar crus I/II as playing a central role in the development of social cognitive functions in early childhood (Manoli et al., bioRxiv).

Future directions: We will continue to investigate how social factors interact with brain structure and function, with a focus on social stress and socio-cognitive processes, through cross-sectional and longitudinal studies using advanced brain models. Our collaboration with the ENIGMA gradient workgroup will also investigate transdiagnostic markers of mental disorders, deepening our understanding of the biological mechanisms underlying these conditions.

Implications and applications

Our neurobiosocial framework provides a comprehensive approach to understanding the interplay between biological factors, social environments, and human behavior, with important implications for multiple domains:

Neuroscience: Our research provides new insights and models to better understand how the brain functions in an ever-changing environment, emphasizing the dynamic interaction between biology and context.

Mental health: By studying the neurobiological impact of social environments-such as trauma or supportive relationships-we aim to develop more precise prevention strategies, diagnostics, and treatments for mental disorders such as depression and anxiety.

Public health: Our work underscores the importance of addressing social inequalities to improve health outcomes. Initiatives that reduce childhood poverty and improve access to mental health care can have a profound impact on the brain health of the entire population.

Developmental and lifespan psychology: We study how life experiences interact with biological factors to shape brain development and associated cognitive/emotional development across the lifespan.
Ethical Considerations: Our research prompts important discussions about the societal implications of genetic and neurological information. We emphasize the importance of ensuring that such findings are used to support rather than stigmatize individuals.

We sincerely thank all those who have contributed to open data initiatives. Access to these vast datasets has enabled us to conduct cutting-edge, multiscale integrative neuroscience. During the Lise Meitner period, we will continue to leverage open data, develop tools for broader use, and create new datasets to benefit the broader neuroscience community.


[1] World Health Organization. (2021). "Mental health and substance use: Improving mental health services."
[2] World Health Organization. (2022). "Social isolation and loneliness among older adults: An urgent public health problem."
[3] United Nations. (2018). "Early Childhood Development: A Global Strategy to Accelerate Action."
[4] United Nations. (2019). "A Child Rights-Based Approach to Nurturing Care."

Go to Editor View