Mehdi Behroozi

RDLPFC area of the brain encodes sentence polarity: a study using fMRI

In this study, we use functional magnetic resonance imaging (fMRI) in combination with multivoxel pattern analysis to address the question of how mental activities that correspond to sentence polarity (affirmative or negative sentences) are encoded in the brain. This approach allows us to investigate the role of left/right dorsolateral prefrontal cortex (DLPFC) in predicting the neural activity of fMRI associated with sentence polarities. Subjects in the experiment were asked to judge the matching of the presented picture with the meaning of affirmative and negative sentences. Our results highlight the role of RDLPFC in encoding of the related mental activity to sentence polarities such that the right hemisphere (RDLPFC) can predict sentence polarity with high accuracy as compared to the left hemisphere (LDLPFC), and that the negative sentences are decoded with high performance as compared to affirmative sentences from the RDLPFC across subjects. In addition, this experiment’s results show that negative sentences involve more syntactic structure than affirmative sentences.

Predicting brain states associated with object categories from fMRI data.

Recently, the multivariate analysis methods have been widely used for predicting the human cognitive states from fMRI data. Here, we explore the possibility of predicting the human cognitive states using a pattern of brain activities associated with thinking about concrete objects. The fMRI signals in conjunction with pattern recognition methods were used for the analysis of cognitive functions associated with viewing of 60 object pictures named by the words in 12 categories. The important step in Multi Voxel Pattern Analysis (MVPA) is feature extraction and feature selection parts. In this study, the new feature selection method (accuracy method) was developed for multi-class fMRI dataset to select the informative voxels corresponding to the objects category from the whole brain voxels. Here the result of three multivariate classifiers namely, Naïve Bayes, K-nearest neighbor and support vector machine, were compared for predicting the category of presented objects from activation BOLD patterns in human whole brain. We investigated whether the multivariate classifiers are capable to find the associated regions of the brain with the visual presentation of categories of various objects. Overall Naïve Bayes classifier perfumed best and it was the best method for extracting features from the whole brain data. In addition, the results of this study indicate that thinking about different semantic categories of objects have an effect on different spatial patterns of neural activation, and so it is possible to identify the category of the objects based on the patterns of neural activation recorded during representation of object line drawing from participants with high accuracy. Finally we demonstrated that the selected brain regions that were informative for object categorization were similar across subjects and this distribution of selected voxels on the cortex may neutrally represent the various objects category properties.

In vivo measurement of T1 and T2 relaxation times in awake pigeon and rat brains at 7T

Establishment of regional longitudinal (T1) and transverse (T2) relaxation times in awake pigeons and rats at 7T field strength. Regional differences in relaxation times between species and between two different pigeon breeds (homing pigeons and Figurita pigeons) were investigated.

Functional MRI in the Nile crocodile: a new avenue for evolutionary neurobiology

Crocodilians are important for understanding the evolutionary history of amniote neural systems as they are the nearest extant relatives of modern birds and share a stem amniote ancestor with mammals. Although the crocodilian brain has been investigated anatomically, functional studies are rare. Here, we employed functional magnetic resonance imaging (fMRI), never tested in poikilotherms, to investigate crocodilian telencephalic sensory processing. Juvenile Crocodylus niloticus were placed in a 7 T MRI scanner to record blood oxygenation level-dependent (BOLD) signal changes during the presentation of visual and auditory stimuli. Visual stimulation increased BOLD signals in rostral to mid-caudal portions of the dorso-lateral anterior dorsal ventricular ridge (ADVR). Simple auditory stimuli led to signal increase in the rostromedial and caudocentral ADVR. These activation patterns are in line with previously described projection fields of diencephalic sensory fibres. Furthermore, complex auditory stimuli activated additional regions of the caudomedial ADVR. The recruitment of these additional, presumably higher-order, sensory areas reflects observations made in birds and mammals. Our results indicate that structural and functional aspects of sensory processing have been likely conserved during the evolution of sauropsids. In addition, our study shows that fMRI can be used to investigate neural processing in poikilotherms, providing a new avenue for neurobiological research in these critical species.

Functional Connectivity Pattern of the Internal Hippocampal Network in Awake Pigeons: A Resting-State fMRI Study

In the last two decades, the avian hippocampus has been repeatedly studied with respect to its architecture, neurochemistry, and connectivity pattern. We review these insights and conclude that we unfortunately still lack proper knowledge on the interaction between the different hippocampal subregions. To fill this gap, we need information on the functional connectivity pattern of the hippocampal network. These data could complement our structural connectivity knowledge. To this end, we conducted a resting-state fMRI experiment in awake pigeons in a 7-T MR scanner. A voxel-wise regression analysis of blood oxygenation level-dependent (BOLD) fluctuations was performed in 6 distinct areas, dorsomedial (DM), dorsolateral (DL), triangular shaped (Tr), dorsolateral corticoid (CDL), temporo-parieto-occipital (TPO), and lateral septum regions (SL), to establish a functional connectivity map of the avian hippocampal network. Our study reveals that the system of connectivities between CDL, DL, DM, and Tr is the functional backbone of the pigeon hippocampal system. Within this network, DM is the central hub and is strongly associated with DL and CDL BOLD signal fluctuations. DM is also the only hippocampal region to which large Tr areas are functionally connected. In contrast to published tracing data, TPO and SL are only weakly integrated in this network. In summary, our findings uncovered a structurally otherwise invisible architecture of the avian hippocampal formation by revealing the dynamic blueprints of this network.

Decoding the different states of visual attention using functional and effective connectivity features in fMRI data

The present paper concentrates on the impact of visual attention task on structure of the brain functional and effective connectivity networks using coherence and Granger causality methods. Since most studies used correlation method and resting-state functional connectivity, the task-based approach was selected for this experiment to boost our knowledge of spatial and feature-based attention. In the present study, the whole brain was divided into 82 sub-regions based on Brodmann areas. The coherence and Granger causality were applied to construct functional and effective connectivity matrices. These matrices were converted into graphs using a threshold, and the graph theory measures were calculated from it including degree and characteristic path length. Visual attention was found to reveal more information during the spatial-based task. The degree was higher while performing a spatial-based task, whereas characteristic path length was lower in the spatial-based task in both functional and effective connectivity. Primary and secondary visual cortex (17 and 18 Brodmann areas) were highly connected to parietal and prefrontal cortex while doing visual attention task. Whole brain connectivity was also calculated in both functional and effective connectivity. Our results reveal that Brodmann areas of 17, 18, 19, 46, 3 and 4 had a significant role proving that somatosensory, parietal and prefrontal regions along with visual cortex were highly connected to other parts of the cortex during the visual attention task. Characteristic path length results indicated an increase in functional connectivity and more functional integration in spatial-based attention compared with feature-based attention. The results of this work can provide useful information about the mechanism of visual attention at the network level.