Sharif Digital Repository

Brain-inspired methods are now widely used to process the data generated by the brain with the aim of improving our understanding of how the brain functions and produces the remarkable intelligence exhibited by humans, which is the source of all realizations, perception and actions. Therefore brain-computer interface (BCI) is one of the most challenging scientific problems which focuses scientists attention, in most cases these systems are based on EEG signals recorded from the surface of the scalp because this method of the brain activity monitoring is noninvasive, easy to use and quit inexpensive. Brain computer interface (BCI) systems analyse the EEG signals and translate person’s... 

Attention is a cognitive process in which the mind reacts to certain stimuli or stimuli of the environment while other environmental stimuli are ignored. Attention might be an overt or covert process. Overt attention is a process in which based on the purpose, we selectively choose an object or place among other objects and places to focus on and we are aware of it. However, the covert attention originates from hidden source, and we are not aware of it. In fact, the covert attention causes a clear and rapid movement of the eye toward the stimulus or space to be taken into consideration and the time when the movement of the eye it means overt attention has occurred. Visual attention is given... 

Recent studies of brain activities indicate that Phase-Amplitude Coupling (PAC) between several regions of the brain, are meaningfully related to Parkinson’s Disease. In this research, we have studied PAC as a statistical measure in Parkinsonian patients’ brains while Deep Brain Stimulation treatment with different stimulation frequencies are being applied. In order to do so, we have investigated patients’ brain signals, and estimated PAC between regions of interest; afterwards, by using the estimated PAC values, we have found significant effects of the treatments on parkinsonian brains; furthermore, two treatments that are using 130 Hz and 340 Hz stimuli signals are compared. In this... 

According to clinical surveys, it is estimated that chronic tinnitus is experienced by 10 to 15% of the adult population. Tinnitus is defined as the conscious and involuntary perception of noise or ringing without involvement of either mechanical or external audio source. In recent years, a limited number of studies have investigated the effects of applying transcranial magnetic stimulation (TMS) to ameliorate this condition. TMS is a noninvasive intervention in which magnetic pulses are applied by a coil adjacent to the individual's head. In this study, electroencephalogram (EEG) signals are recorded concurrent and as a follow-up to TMS. This makes it possible to study changes caused by... 

Localization of electrical activity in the brain is one of the major problems in cognitive science and neuroscience. Indeed, Source localization is the inverse processing procedure on brain signals to estimate the location and position of resources in the human brain. Current technics for neurological imaging is included fMRI، PET، MEG and ERP. These methods is not appropriated to answer the question that when does each of different components of the brain begin their activity. The EEG signals could be useful to eliminate some of limitations of above methods. The problem with EEG signals collected from the skull is that they don’t refer directly to the location of active neurons. The... 

The processing of brain signals, including the electrocorticogram (ECoG) signal, is widely used in the investigation of neurological diseases. Conventionally, the ECoG signal has frequency components up to the range of 80 Hz. Studies have proven that in some conditions, such as epilepsy, the brain signal includes frequency components higher than 80 Hz, which are called high-frequency oscillations (HFO). Therefore, HFOs are recognized as a biomarker for epilepsy. The aim of this thesis is to review the previous methods of detecting HFOs and to present new methods with greater efficiency in the direction of diagnosis or treatment of epileptic patients. For this purpose, we used the ECoG data... 

EEG brain signals have gained particular attention among researchers in the field of brain signal processing due to their easy and cheap recording, high temporal resolution, and non-invasiveness. On the other hand, defects such as high vulnerability to various types of noise and artifacts have caused the main challenge before processing them to improve the signal-to-noise ratio and the interpretability of brain connectivity obtained from them. In order to solve these challenges, two important problems of "separation of desired and undesired signal subspace" and "functional and effective connectivity analysis" have been raised, respectively. In solving both problems, EEG signals are usually... 

The brain is constantly anticipating the future of sensory inputs based on past experiences. When new sensory data is different from predictions shaped by recent trends, neural signals are generated to report this surprise. Surprise leads to garnering attention, causes arousal, and motivates engagement. It motivates the formation of an explanation or updating of current models. Three models have been proposed for quantifying surprise as the Shannon, Bayesian, and confidence-corrected surprises. In this thesis, we analyze EEG and MEG signals recorded during oddball tasks to examine and statistically compare the value of temporal/ spatial components in decoding the brain’s surprise. We...