The highly demanding study of meaning, intention, and communication including miscommunication, in human interaction seems to call for the development of powerful new approaches and in that context the astonishing raw power of modern computers may eventually be harnessed, given that adequate models, methods, algorithms and software be developed and made available. In this context, a proposed data structure, pattern definitions, algorithms, and a new statistical validation test are proposed. New additions are introduced to this theoretical/methodological system (called t-system) including special definitions of well known phenomena such as bursts and cyclical occurrence as well as of more novel concepts called “t-blocks”, “t-metronomes” and “ghost cycles”. A method is introduced to deal with the estimation of a priori probability (or statistical significance) of individual patterns without consideration of the arbitrary binary trees used for their detection and in this context “t-templates” and their matching are introduced. Statistical validation through shuffling of data is compared with a suggested method called (random series) rotation (t-rotation) and results obtained with each are compared for both human and neuronal interactions. It is pointed out that brain behavior as observed with brain scanners does not offer direct insight into meaning and intentions, but essentially means more behavior to observe and more patterns to be detected, while limitations in social neuroscience seem to repeat to those of earlier human interaction studies and also due to technical difficulties. Finally some thoughts and questions are put forward concerning possible relations between on one hand hidden patterns and symmetry in interactions and on the other hand meaning, intentions, communication and miscommunication in highly patterned human interactions as well as about the possible need for new and specialized mathematics for the study of these phenomena.