Validating of Neurofeedback Practice by Utilizing TMS as an Assessment Tool

NeuroFeedback can be described as a form of Biofeedback that is based on recordings of brain act ivity reflected by imaging techniques such as real-time fMRI (Johnston at al, 2010) but mainly using scalp EEG recordings (Angelakis et al., 2007). This method based on classical and operant learning paradigm and has been applied for the last 40 years as a therapeutic method to a range of clinical conditions such as epilepsy, attention deficit hyperactivity disorder and the locked-in syndrome (Kübler et al., 2009; Vernon, Frick, & Gruzelier, 2004) , and to optimise performance in healthy subjects (Egner & Gruzelier, 2003). Participants can experience their real time brain activity in the form of animated visual or auditory stimuli (the feedback) co-vary with a specific property of the recorded activity. By being reinforced for obtaining goals, participants learn to volitionally modulate their brain activity. The feedback continuously represents brain activity with a minimum delay, which in modern equipment is on the order of a few tens of millisecond.

sLORETA is a widespread linear, discrete, instantaneous, full-volume inverse solution proximity for brain electromagnetic measurements (Pascual-Marqui, Esslen, Kochi, & Lehmann, 2002; Pascual-Marqui, 2002). Whereas EEG is a measure of electric potential variations on a two dimensional surface, sLORETA estimates the current density in a three dimensional space that results in the potential divergence on the scalp.

EEG Tomography directed bio-feedback correlates the physiological signal with a continuous feedback signal; however, the physiological signal is defined as the current density in a specified region of interest (ROI) calculated by means of sLORETA algorithm. This allows the continuous feedback signal to become a function of the intracranial current density and to co-vary with it.

In the first LORETA neuro-feedback study designed to assess the possibility of using this protocol on a healthy subjects, Condego (2004) et al recorded current density from their subjects' anterior cingulate cortex (ACC) and feedback it to the subject as the size of a disk presented on a computer screen. Larger size of a disk represented higher current density recorded from the subject's ACC. The subjects were instructed to make the circle size as larger they can, therefore reinforced for higher ACC activity. The results of this study supported the effect of LORETA neuro-feedback protocol on the subject's performance on a sustained attention task.

This supports the 'LORETA neurofeedback' effect on cognitive performance yet there is still no direct evidence for the effect of LORETA neurofeedback on the excitability of the neural tissue itself. One such direct evidence can be achieved by single pulse TMS measure of the motor cortex plasticity.