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Of all publications in the section: 6
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Working paper
Keramati M., Gutkin B. Biorxiv. 005140. Cold Spring Harbor Laboratory, 2014
Efficient regulation of internal homeostasis and defending it against perturbations requires complex behavioral strategies. However, the computational principles mediating brain's homeostatic regulation of reward and associative learning remain undefined. Here we use a definition of primary rewards, as outcomes fulfilling physiological needs, to build a normative theory showing how learning motivated behavior is modulated by the internal state of the animal. The theory proves that seeking rewards is equivalent to the fundamental objective of physiological stability, defining the notion of physiological rationality of behavior. We further give a formal basis for temporal discounting of reward. It also explains how animals learn to act predictively to preclude prospective homeostatic challenges, and attributes a normative computational role to the modulation of midbrain dopaminergic activity by hypothalamic signals. 
Added: Dec 29, 2014
Working paper
Razorenova A., Yavich N., Malovichko M. et al. Biorxiv. 005140. Cold Spring Harbor Laboratory, 2020
Electroencephalography (EEG) is a well-established non-invasive technique to measure the brain activity, albeit with a limited spatial resolution. Variations in electric conductivity between different tissues distort the electric fields generated by cortical sources, resulting in smeared potential measurements on the scalp. One needs to solve an ill-posed inverse problem to recover the original neural activity. In this article, we present a generic method of recovering the cortical potentials from the EEG measurement by introducing a new inverse-problem solver based on deep Convolutional Neural Networks (CNN) in paired (U-Net) and unpaired (DualGAN) configurations. The solvers were trained on synthetic EEG-ECoG pairs that were generated using a head conductivity model computed using the Finite Element Method (FEM). These solvers are the first of their kind, that provide robust translation of EEG data to the cortex surface using deep learning. Providing a fast and accurate interpretation of the tracked EEG signal, our approach promises a boost to the spatial resolution of the future EEG devices.  
Added: Nov 10, 2020
Working paper
Pich i Rosello O., Vlasova A., Shichkova P. et al. Biorxiv. 005140. Cold Spring Harbor Laboratory, 2017
Human genetic variability is thought to account for a substantial fraction of individual biochemical characteristics — in biomedical sense, of individual drug response. However, only a handful of human genetic variants have been linked to medication outcomes. Here, we combine data on drug-protein interactions and human genome sequences to assess the impact of human variation on their binding affinity. Using data from the complexes of FDA-drugs and drug-like compounds, we predict SNPs substantially affecting the protein-ligand binding affinities. We estimate that an average individual carries ~6 SNPs affecting ~5 different FDA-approved drugs from among all of the approved compounds. SNPs affecting drug-protein binding affinity have low frequency in the population indicating that the genetic component for many ADEs may be highly personalized with each individual carrying a unique set of relevant SNPs. The reduction of ADEs, therefore, may primarily rely on the application of computational genome analysis in the clinic rather than the experimental study of common SNPs.
Added: Jul 7, 2017
Working paper
Svedberg J., Shchur V., Reinman S. et al. Biorxiv. 005140. Cold Spring Harbor Laboratory, 2020
Adaptive introgression - the flow of adaptive genetic variation between species or populations - has attracted significant interest in recent years and it has been implicated in a number of cases of adaptation, from pesticide resistance and immunity, to local adaptation. Despite this, methods for identification of adaptive introgression from population genomic data are lacking. Here, we present Ancestry_HMM-S, a Hidden Markov Model based method for identifying genes undergoing adaptive introgression and quantifying the strength of selection acting on them. Through extensive validation, we show that this method performs well on moderately sized datasets for realistic population and selection parameters. We apply Ancestry_HMM-S to a dataset of an admixed Drosophila melanogaster population from South Africa and we identify 18 loci which show signatures of adaptive introgression, four of which have previously been shown to confer resistance to insecticides. Ancestry_HMM-S provides a powerful method for inferring adaptive introgression in datasets that are typically collected when studying admixed populations. This method will enable powerful insights into the genetic consequences of admixture across diverse populations. Ancestry_HMM-S can be downloaded from https://github.com/jesvedberg/Ancestry_HMM-S/.
Added: Oct 17, 2020
Working paper
Tumialis A., Alikovskaia T., Smirnov A. et al. Biorxiv. 005140. Cold Spring Harbor Laboratory, 2019
Perception of yourself involves the integration of information from various sources. In a number of studies, it was found that the perception of one’s own face is accompanied by an increase in the accuracy of perception of heartbeats and the amplitude of brain potentials caused by heart beats. In this study, subjects had to do a heartbeat count test to determine the accuracy of the interception. Then, the subjects were presented with the faces of an unknown person, a friend and the subject’s own face. The simultaneous registration of EEG was organized. We analyzed the relationship between the amplitude of the evoked potentials when viewing these faces and the accuracy of interoception. It was found that the amplitude of the late EP component (850 - 1106 ms) has a positive correlation with IAcc in the central and right parietal and occipital areas when perceiving one’s own face. According to the localization of distributed sources of activity, it was found that the connection is localized in the right anterior upper temporal cortex. Thus, the association between exteroceptive perception of one’s own face and IAcc occurs in the late period of EP. Moreover it is localized in the right temporal region of the cortex, associated with multisensory integration and recognition of personal information.
Added: Apr 26, 2021
Working paper
Razorenova A., Chernyshev B. V., Nikolaeva A. et al. Biorxiv. 005140. Cold Spring Harbor Laboratory, 2019
Whether short-term learning of new words can induce rapid changes in cortical areas involved in distributed neural representation of the lexicon is a hotly debated topic. To answer this question, we examined magnetoencephalographic phase-locked responses elicited in the cerebral cortex by passive presentation of eight novel pseudowords before and immediately after an operant conditioning task. This procedure forced participants to perform an active search for unique meaning of four word-forms that referred to movements of their own body parts. While familiarization with novel word-forms led to bilateral repetition suppression of cortical responses to all eight pseudowords, these reduced responses became more selectively tuned towards newly learned action words in the left hemisphere. Our results suggest that stimulus repetition and active learning of semantic association have separable effects on cortical activity. They also evidence rapid plastic changes in cortical representations of meaningful auditory word-forms after active learning.
Added: Sep 1, 2019