Interfacing Apple and IBM computers for the analysis of clinical biofeedback

This paper demonstrates a method of transferring research data from a remote clinic to a large university mainframe for data manipulation and statistical analysis. Data collected by an Apple //e computer were transferred to an IBM 3031 mainframe by sending data files to an IBM PC by telephone modem or by direct hardwire connection to the PC. The IMB PC performed data-formatting routines and then uploaded the files to the mainframe for storage. Advantages and disadvantages of sending data over telephone lines via a modem are discussed.     

Single-subject statistical analysis of computer-assisted biofeedback

Single-subject statistics were used to analyze physiological data [electromyographic (EMG) temperature] recorded from two patients receiving computer-assisted biofeedback treatment in a clinic. When the data were analyzed by an ANOVA method or a regression technique, the results demonstrated that both patients learned to significantly reduce EMG levels. The rationale of using single-subject statistics is discussed, and the applicability of the statistical technique to the clinic population is illustrated.     

Teaching students to model neural circuits and neural networks using an electronic spreadsheet simulator

An electronic spreadsheet simulator can be used to enable students to conduct simulated microelectrode recording experiments. In addition, it can be used both to let students explore the operation of models of hypothetical neural networks and to let them design and develop their own neural models.     

Instructional programs for psychology: A review and analysis

This paper presents 10 general observations about current software for instruction in psychology and examines selected examples employing four instructional techniques for computer-assisted instruction. We find that although the number of programs employing experimental or data-oriented approaches to psychology as a primary vehicle of instruction is increasing, tutorial drill and practice programs and gaming are not well represented.     

FORTRAN subroutine for an EEG feedback digital filter

A method of constructing digital filters is outlined and illustrated in an application for research uses of EEG feedback. The method is based on least squares estimation with geometric weighting. Old data in the time series are discounted according to age, as new data arrive. Recurrence relations are used, allowing the computations to be performed in real time. A FORTRAN digital filter is formulated that simultaneously estimates (1) the spectral power in a band centered at a target frequency, (2) the total spectral power, and (3) the dominant frequency.