טכניון מכון טכנולוגי לישראל
הטכניון מכון טכנולוגי לישראל - בית הספר ללימודי מוסמכים  
Ph.D Thesis
Ph.D StudentCohen Netta
SubjectThe Development of Spontaneous Beating Activity in Cultured
Heart Cells: From Cells to Networks
DepartmentDepartment of Physics
Supervisor Professor Erez Braun


Abstract

This thesis considers the spontaneous spatio-temporal dynamics of a developing culture of heart cells and of self-assembled networks of cells. Issues dealing with rhythm generation, the onset of synchronization and temporal correlations within and among cells are addressed. Special emphasis was placed on understanding the functional transitions from cells to groups of cells and to extended networks.

           

To capture the spontaneous beating activity of the cells throughout their development, a novel optical method of continuous, non-invasive and high-resolution measurement and real-time motion detection was introduced, allowing contractions of single cells as well as networks to be recorded at high spatial resolution for unprecedented durations limited, in practice, only by the lifetime of the culture (typically 3-4 weeks).

           

Long-term statistics of the beating in (i) isolated cells, (ii) cells embedded in a network of passive (non-muscle) cells, (iii) groups of 2-10 cells and (iv) extended networks are presented and analyzed. It was found that cells at different organizational and developmental stages of the culture exhibit very different temporal patterns of activity. For instance, single cells may experience lapses of quiescence, ranging from seconds to many hours. In addition, sudden and gradual rate and variance modulations appeared on a wide range of time scales. As cells coupled to each other in groups, they synchronized their activity, and their beating became more regular, but was still dominated by noise. By contrast, large networks often exhibited highly periodic beating for hours and days. An examination of the spatio-temporal patterns of beating indicated the possibility of pacemakers developing in the dish and stimulating the rest of the cells. Interestingly, long term statistics performed on recordings from single cells, groups and networks all reveal long-range correlated fluctuations of event counts per unit time.

           

Nonlinear dynamical models are presented which capture the main features of the activity on a wide range of time scales and for all of these different levels of organization. Put together, these models provide a cohesive picture of the development from the wide repertoire of activities in single cells, through suppressed fluctuations and preferred time scales in small groups of cells, to the much more regular and deterministic characteristics in extensive networks.