Bilingualism is associated with structural adaptations of subcortical regions taking part in controlling multiple languages. The thalamus is a paired gray matter structure located near the center of the brain, regulating the information transmission to cortical regions. In a recent FMRI study, the sensitivity of the thalamus to grammatical and ungrammatical stimuli has been shown at whole-brain level in the first language (L1) of bilinguals. This study explored the activation patterns of bilateral thalamus in both L1 and L2 using a ROI-based approach. To do so, the percentage of signal change for grammatical and ungrammatical stimuli in L1 and L2 was extracted as the intensity measure per participant. Thirty-six Turkish-Persian bilinguals (21 women) who had acquired their L2 at the age of 7 were selected. Based on the Bilingual Dominance Scale, there was no significant difference between the proficiency level of participants in L1 (Turkish) and L2 (Persian). Participants carried out an auditory grammaticality judgment task in an alternating language switching paradigm while FMRI images were acquired. ROI-based results confirmed the grammaticality effect only in L1 and the left thalamus. Considering that L1 was the dominant language in this study and gave rise to larger reversed language dominance effects, it was suggested that the engagement of the thalamus in L1 is not associated with syntactic processing but instead may exert an overall monitoring and control function for language-specific cortical activities.

An integrated modelmagnetoencephalography (MEG) and functional Magnetic Resonance Imaging (FMRI) is proposed. In the proposed model, MEG and FMRI outputs are related to the corresponding aspects of neural activities in a voxel. Post synaptic potentials (PSPs) and action potentials (APs) are two main signals generated by neural activities. In the model, both of MEG and FMRI are related to the PSPs without any correlation to the APs. Each PSP is modeled by the direction and strength of its current flow, which are treated as random variables. The overall neural activity in each voxel is used for equivalent current dipole in MEG and as input of the extended Balloon model for producing Blood Oxygen Level Dependent (BOLD) signal in FMRI. The proposed model shows possibility of detecting activation by FMRI in a voxel while the voxel is silent for MEG and vice versa. This is according to the fact that FMRI signal reflects the sum of PSPs’ strengths (independent of their directions) but MEG signal reflects the vector sum of the PSPs (which depends on their directions). The model also shows that the crosstalk from neural activities of adjacent voxels in FMRI and properties of the inverse problem in MEG generate different spatial responses in the two modalities.We use real auditory MEG and FMRI datasets from 2 normal subjects to estimate the parameters of the model. Goodness of the real data our model shows the possibility of using the proposed model to simulate realistic datasets.

This is the first report of using FMRI in Iran. A normal subject underwent FMRI scanning while generating visual mental images from concrete words in a block designed paradigm; while, passive listening to abstract words and rest conditions were control trials. We found activation in Primary Visual Area (PVA) during mental imagery; as well as activation in regions participated in object recognition, memory retrieval, visual working memory and comprehension of complex auditory stimuli. Also we observed more activity in PVA when the subject was given more time for generation of mental images from concrete words. These findings are further indicative of shared mechanisms between visual-mental imagery and visual perception.

Functional magnetic resonance imaging (FMRI) is a safe and non-invasive way to assess brain functions by using signal changes associated with brain activity. The technique has become a ubiquitous tool in basic, clinical and cognitive neuroscience. This method can measure little metabolism changes that occur in active part of the brain. We process the FMRI data to be able to find the parts of brain that are involve in a mechanism, or to determine the changes that occur in brain activities due to a brain lesion. In this study we will have an overview over the methods that are used for the analysis of FMRI data.