Real Time Closed Loop Brain Computer Interfaces allow recording of neural signals via electrodes implanted on the surface of the brain or inner cortical issue. The main aim of this thesis is to probe the brain activity by generating a visual stimulation. The real time Brain Computer Interfaces records data from 32 channels, performs real time spike detection to perform a visual stimulation based on the spike activity recorded from the brain. The requirement of the closed loop BCI system is to record data at the high sampling rate, and perform high speed filtering on each channel to remove noise, detect the spikes simultaneously on all channels, and drive the visual stimuli based on the spike activity detected. The focus of this study is divided into two parts: The first focus of this thesis is to develop a system which can record the brain signals at a rate of 10kSamples/s thus acquiring the actions of high frequency spikes. This study uses ZYNQ7000 chip which consist of ARM core and FPGA core. ARM core is used to fetch data from sensor and FPGA core is used for performing real time spike detection on 32 channels. The second focus of this study is to generate a visual stimulation based on the spike activity which acts as a feedback to the brain and completes the closed loop BCI system. This would allow us to generate controlled visual stimuli based on the spike information rather than generating random visual patterns.