Sergey I. Kartashov

Effective Connectivity within the Default Mode Network: Dynamic Causal Modeling of Resting-State fMRI Data.

The Default Mode Network (DMN) is a brain system that mediates internal modes of cognitive activity, showing higher neural activation when one is at rest. Nowadays, there is a lot of interest in assessing functional interactions between its key regions, but in the majority of studies only association of Blood-oxygen-level dependent (BOLD) activation patterns is measured, so it is impossible to identify causal influences. There are some studies of causal interactions (i.e., effective connectivity), however often with inconsistent results. The aim of the current work is to find a stable pattern of connectivity between four DMN key regions: the medial prefrontal cortex (mPFC), the posterior cingulate cortex (PCC), left and right intraparietal cortex (LIPC and RIPC). For this purpose functional magnetic resonance imaging (fMRI) data from 30 healthy subjects (1000 time points from each one) was acquired and spectral dynamic causal modeling (DCM) on a resting-state fMRI data was performed. The endogenous brain fluctuations were explicitly modeled by Discrete Cosine Set at the low frequency band of 0.0078–0.1 Hz. The best model at the group level is the one where connections from both bilateral IPC to mPFC and PCC are significant and symmetrical in strength (p < 0.05). Connections between mPFC and PCC are bidirectional, significant in the group and weaker than connections originating from bilateral IPC. In general, all connections from LIPC/RIPC to other DMN regions are much stronger. One can assume that these regions have a driving role within the DMN. Our results replicate some data from earlier works on effective connectivity within the DMN as well as provide new insights on internal DMN relationships and brain’s functioning at resting state.

Dynamic causal modeling of hippocampal links within the human default mode network: Lateralization and computational stability of effective connections

The purpose of this paper was to study causal relationships between left and right hippocampal regions (LHIP and RHIP, respectively) within the default mode network (DMN) as represented by its key structures: the medial prefrontal cortex (MPFC), posterior cingulate cortex (PCC), and the inferior parietal cortex of left (LIPC) and right (RIPC) hemispheres. Furthermore, we were interested in testing the stability of the connectivity patterns when adding or deleting regions of interest. The functional magnetic resonance imaging (fMRI) data from a group of 30 healthy right-handed subjects in the resting state were collected and a connectivity analysis was performed. To model the effective connectivity, we used the spectral Dynamic Causal Modeling (DCM). Three DCM analyses were completed. Two of them modeled interaction between five nodes that included four DMN key structures in addition to either LHIP or RHIP. The last DCM analysis modeled interactions between four nodes whereby one of the main DMN structures, PCC, was excluded from the analysis. The results of all DCM analyses indicated a high level of stability in the computational method: those parts of the winning models that included the key DMN structures demonstrated causal relations known from recent research. However, we discovered new results as well. First of all, we found a pronounced asymmetry in LHIP and RHIP connections. LHIP demonstrated a high involvement of DMN activity with preponderant information outflow to all other DMN regions. Causal interactions of LHIP were bidirectional only in the case of LIPC. On the contrary, RHIP was primarily affected by inputs from LIPC, RIPC, and LHIP without influencing these or other DMN key structures. For the first time, an inhibitory link was found from MPFC to LIPC, which may indicate the subjects’ effort to maintain a resting state. Functional connectivity data echoed these results, though they also showed links not reflected in the patterns of effective connectivity. We suggest that such lateralized architecture of hippocampal connections may be related to lateralization phenomena in verbal and spatial domains documented in human neurophysiology, neuropsychology, and neurolinguistics.

“Cognovisor” for the Human Brain: Towards Mapping of Thought Processes by a Combination of fMRI and Eye-Tracking

The aim of this work was to describe localization of active brain of different types of thinking—spatial and verbal. The method of functional magnetic resonance imaging (fMRI) was used. Seven right-handed healthy volunteers aged from 19 to 30 participated in the experiment. In the experiment, the subject was brought against 6 types of tasks (about 30 of each type) distributed from the figurative to the semantic thought. The results obtained in the statistical parametric and covariance analysis is that interactions of neural networks that are activated to perform the categorization of mental tasks are different. This makes it possible to use this approach to develop a model of “Cognovisor”.

Network activity of mirror neurons depends on experience

In this work, the investigation of network activity of mirror neurons systems in animal brains depending on experience (existence or absence performance of the shown actions) was carried out. It carried out the research of mirror neurons network in the C57/BL6 line mice in the supervision task of swimming mice-demonstrators in Morris water maze. It showed the presence of mirror neurons systems in the motor cortex M1, M2, cingular cortex, hippocampus in mice groups, having experience of the swimming and without it. The conclusion is drawn about the possibility of the new functional network systems formation by means of mirror neurons systems and the acquisition of new knowledge through supervision by the animals in non-specific tasks.

Research of Neurocognitive Mechanisms of Revealing of the Information Concealing by the Person

This work is related to the creation of an MR-compatible polygraph and the development of methods for detecting the hierarchy of neural networks of the cognitive organization of hidden memory markers. At the moment, there is practically no scientific work on lie detection, in which both the classical polygraph and the MRI scanner were simultaneously used. Combining these methods will help increase the probability of recognizing the facts of hiding important information and carry out an objective assessment of the truthfulness of the reported information. This method can also be used to detect the level of resistance of operators for emotional stress, assess the perception of emotional stimuli by subjects in neurocognitive tasks.

fMRI and Tractographic Studies of Cognitive Systems in the Human Brain at the Norm and the Paranoid Schizophrenia

This study is aimed at a systematic study of the work of neural networks of the human brain and their architecture in norm and in schizophrenia. To obtain the neurophysiological data, a unique complex of experimental equipment for world-class neurocognitive studies was used. The data obtained showed a significant decrease in the structural connectivity relationships for the rich club coefficient for a group of schizophrenic patients compared with the norm. Perception of emotionally negative visual and audio stimuli related to delusions in patients with schizophrenia does not lead to a significant decrease in BOLD signal as compared with the norm in Calcarine_L, Cerebelum_4_5_R, ParaHippocampal_LR, Precuneus_L, Temporal_Sup_R areas. The differences found in the structural and functional patterns of cognitive-affective disorders can serve as prognostic biomarkers in patients with schizophrenia and will make a significant contribution to the development of high-tech diagnostics in the early stages of mental illness.

Contrasting Human Brain Responses to Literature Descriptions of Nature and to Technical Instructions

The problem of semantic mapping of the brain is one of the urgent problems in human neurocognitive studies. At the present time there are only few studies reported in the world literature, all of which are made on the material and with the participation of English language native speakers. Russian language can thus become the second language for which this kind of research will be carried out, namely, finding out a correspondence between the semantic classes of the Russian vocabulary and the cortical areas responsible for processing these semantic classes when the text is orally presented. To solve this problem, it is necessary to develop techniques that allow us to investigate cognitive and neurolinguistic mechanisms of perception and understanding of the continuous text segments in natural language. In this paper, we present data on the comparative mapping of the human brain structures involved in the perception of meaningful texts containing technical instructions and literature descriptions of nature.

Functional Neural Networks in Behavioral Motivations

Functional magnetic resonance imaging (fMRI) is an effective non-invasive tool for exploration and analysis of brain functions. Here functional neural networks involved in behavioral motivations are studied using fMRI. It was found that behavioral conditions producing different motivations for action can be associated with different patterns of functional network activity. At the same time, connection can be made to dynamics of socio-emotional cognition, decision making and action control, described by the Virtual Actor model based on the eBICA cognitive architecture. These preliminary observations encourage further fMRI-based study of human social-emotional cognition. The impact is expected on the emergent technology of humanlike collaborative robots (cobots) and creative cognitive assistants.

Lateral Asymmetry in Weekly Reproducibility of Resting State Amygdala Functional Connectivity

Abnormal functional connectivity of the amygdala with several other brain regions has been observed in patients with higher anxiety or post-traumatic stress disorder, both in a resting state and threatening conditions. However, findings on the specific connections of the amygdala might be varied due to temporal and individual fluctuations in the resting state functional connectivity (rsFC) of the amygdala and its lateral asymmetry, as well as possible variability in anxiety among healthy subjects. We studied reproducibility of rsFC data for the right and left amygdala, obtained by functional magnetic resonance imaging twice in a one-week interval in 20 healthy volunteers with low to moderate anxiety. We found resting-state amygdala network, which included not only areas involved in the emotion circuit, but regions of the default mode network (DMN) associated with memory and other brain areas involved in motor inhibition and emotion suppression. The amygdala network was stable in time and within subjects, but between-session reproducibility was asymmetrical for the right and left amygdala rsFC. The right amygdala had more significant connections with DMN regions and the right ventrolateral prefrontal cortex. The rsFC values of the right amygdala were more sustained across the week than the left amygdala rsFC. Our results support a hypothesis of functional lateralization of the amygdala. The left amygdala is more responsible for the conscious processing of threats, which may produce more variable rsFC; the right amygdala rsFC is more stable due to its greater engagement in continuous automatic evaluation of stimuli. Highlights Amygdala resting state network included areas of emotion circuit and motor control During rest amygdala was functionally connected with areas of default mode network Functional connectivity of the right amygdala was more sustained across the week Functional connections of amygdala network were more stable in the right hemisphere

The Concept of Functional Tractography Method for Cognitive Brain Studies

The aim of this work is to develop method of functional tractography based on the fast MRI sequence (Multi-Band EPI). It is planned to identify active areas of white matter (active tracts) responsible for the realization of motor function and visual perception. The functional MRI method, universally recognized and quite popular in cognitive brain studies, clearly reveals sources of activity in the gray matter of the brain. Proposed method of functional tractography supposed to make it possible to determine the activity in the deep structures of white matter tracts, which gives a number of advantages in understanding the network interaction of human brain regions among themselves both in healthy people and in patients.