Research Projects

The central nervous system (CNS) is our most complex organ system. Despite tremendousprogress in our understanding of the biochemical, electrical, and geneticregulation of CNS functioning and malfunctioning, many fundamental processesand diseases are still not fully understood. For example, axon growth patterns inthe developing brain can currently not be well-predicted based solely on thechemical landscape that neurons encounter, several CNS-related diseases cannotbe precisely diagnosed in living patients, and neuronal regeneration can stillnot be promoted after spinal cord injuries.

Duringmany developmental and pathological processes, neurons and glial cells aremotile. Fundamentally, motion is drivenby forces. Hence, CNS cells mechanicallyinteract with their surrounding tissue. They adhere to neighbouring cells and extracellular matrix using celladhesion molecules, which provide friction, and generate forces usingcytoskeletal proteins.  These forces aretransmitted to the outside world not only to locomote but also to probe themechanical properties of the environment, which has a long overseen huge impacton cell function.

Onlyrecently, groups of several project leaders in this consortium, and a few other groupsworldwide, have discovered an important contribution of mechanical signalsto regulating CNS cell function. For example, they showed that brain tissuemechanics instructs axon growth and pathfinding in vivo, that mechanicalforces play an important role for cortical folding in the developing humanbrain, that the lack of remyelination in the aged brain is due to an increasein brain stiffness in vivo, and that many neurodegenerative diseases areaccompanied by changes in brain and spinal cord mechanics. These first insights strongly suggest thatmechanics contributes to many other aspects of CNS functioning, and it islikely that chemical and mechanical signals intensely interact at the cellularand tissue levels to regulate many diverse cellular processes.

The CRC 1540 EBM synergises the expertise of engineers, physicists,biologists, medical researchers, and clinicians in Erlangen to explore mechanicsas an important yet missing puzzle stone in our understanding of CNSdevelopment, homeostasis, and pathology. Our strongly multidisciplinary teamwith unique expertise in CNS mechanics integrates advanced invivo, in vitro, and in silico techniques across time(development, ageing, injury/disease) and length (cell, tissue, organ) scalesto uncover how mechanical forces and mechanical cell and tissue properties,such as stiffness and viscosity, affect CNS function. We especially focus on(A) cerebral, (B) spinal, and (C) cellular mechanics. Invivo and in vitro studies provide a basic understanding ofmechanics-regulated biological and biomedical processes in different regions ofthe CNS. In addition, they help identify key mechano-chemical factors forinclusion in in silico models and provide data for model calibration andvalidation. In silico models, in turn, allow us to test hypotheses without the need of excessive or even inaccessibleexperiments. In addition, they enable the transfer and comparison of mechanics data and findingsacross species and scales. They also empower us to optimise processparameters for the development of in vitro brain tissue-like matricesand in vivo manipulation of mechanical signals, and, eventually, pavethe way for personalised clinical predictions.

Insummary, we exploit mechanics-based approaches to advance ourunderstanding of CNS function and to provide the foundation for futureimprovement of diagnosis and treatment of neurological disorders.

Recent evidence suggests that mechanical forces drive cortical folding during brain development. While analytical, computational, and experimental models have significantly advanced our understanding of the mechanisms underlying the folding process, such models have so far not been used to tackle specific clinical challenges. For example, folding patterns are an important clinical hallmark of cortical development and brain malformations, such as those related to epilepsy. Assisting clinicians in the diagnosis and treatment of brain folding-related neurological disorders, e.g., by reverse-engineering the cellular processes that could have led to the macroscopic malformation, requires the close collaboration between clinicians, who define open clinical questions, and engineers, who develop targeted simulation tools to address them. To tackle some of the open questions concerning malformations associated with epilepsy analyzed in A02, we plan to use mechanical modelling approaches. A01 aims to develop a computational framework to numerically predict the mechanisms underlying abnormal brain development. Based on qualitative and quantitative insights into the interplay between mechanics, cell migration, cell differentiation, and brain malformations obtained through projects A02 through A05, we will establish a multifield theoretical framework to predict brain development under physiological and pathological conditions. For model calibration and validation, we will use the various human data sets generated in project A02 supplemented by mechanical tests under compression, tension, and torsional shear on fresh human brain tissue obtained from neurosurgical procedures. We will incorporate data from patients into the modelling framework to lay the foundation for later use in clinical practice – to advance from benchmark problems to disease-specific predictions and eventually assist the diagnosis and treatment of neurological diseases such as epilepsy.

B01 aims to establish a continuum-based computational framework to predict the regeneration of spinal cord tissue after injury or disease. The computational model will capture the temporal and spatial evolution of growth, remodelling and healing processes, as experimentally observed in B02-B05. We will specifically focus on mechanics-driven processes that are involved in the regeneration of the spinal cord after traumatic injury and in multiple sclerosis. We will capture the evolving connectivity of cells in the central nervous system by continuous order parameters driven by mechanics and biochemical factors. To calibrate the constitutive models, we will exploit mechanical tests on human and animal spinal cord tissue performed in B01-B05. Modelling in B01 will help correlating the comprehensive set of ex vivo and in vivo mechanical data, data from various species, and multiple measurement techniques within EBM. B01 will in particular enter into a close feedback loop with B03, which provides data on in vivo tissue mechanics based on Brillouin microscopy (BM) measurements and ex vivo tissue mechanics based on atomic force microscopy (AFM) measurements and correlated structural and compositional information. B01 will in turn provide information about mechanical determinants identified through modelling and simulation. B01 will furthermore provide testable hypotheses for targeted experiments in B03 and the associated results will be directly fed back into our computational framework.

The aim of this project is to develop a platform technology to produce gradients that are clearly defined and reproducible in space and time, to analyze them and to model them in silico in order to be able to investigate their effect on cell-biomaterial interactions. To this end, we will first develop printheads that can be used to generate controlled transitions of materials from the A/B projects, drugs, and cells. Through comprehensive characterization of the printed gradients using mechanical test methods in combination with imaging techniques, the results will be continuously analyzed and improved with respect to the requirements of the C-projects. In addition, continuum mechanical modeling and simulation are used specifically to optimize process parameters, the print pattern and the 3D arrangement in the construct.