Biology subjects

Ossadtchi, A.

Publications and source records attributed to Ossadtchi, A..

5 recordsLinked to original sources

bioRxiv2018

Towards zero-latency neurofeedback

Neurofeedback (NFB) is a real-time paradigm, where subjects monitor their own brain activity presented to them via one of the sensory modalities: visual, auditory or tactile. NFB has been proposed as an approach to treat neurological conditions and augment brain functions. In many applications, especially in the automatic learning scenario it is important to decrease NFB latency, so that appropriate brain mechanisms can be efficiently engaged. To this end, we propose a novel algorithm that significantly reduces feedback signal presentation in the electroencephalographic (EEG) NFB paradigm. The algorithm is based on the least squares optimization of the finite impulse response (FIR) filter weights and analytic signal reconstruction. In this approach, the trade-off between NFB latency and the accuracy of EEG envelope estimation can be achieved depending on the application needs. Moreover, the algorithm allows to implement predictive NFB by setting latency to negative values while maintaining acceptable envelope estimation accuracy. As such, our algorithm offers significant improvements in cases where subjects need to detect neural events as soon as possible and even in advance.

bioinformatics↗

bioRxiv2018

On the Orientation of Entorhinal Grids

In the groundbreaking paper that eventually led to the 2014 Nobel prize in Physiology or Medicine, Hafting et al. (2005) reported that when rats forage for chocolate crumbs in a large open field, some neurons in their entorhinal cortex, called grid cells, exhibit crystalline-like responses to animal position, i.e. grids. Among several key findings documented in this article, the authors noted for the first time that the grids of different neurons can be tilted relative to each other, particularly if these neurons are far apart. In support of this claim, the researchers illustrated two neuronal subpopulations with a 7-10{degrees} difference in their grid orientations. Since these data are available online, we were able to reexamine these findings. Here we report several clarifications to the original observations of Hafting et al. First, we show that the relationship between the entorhinal grids is more complex than a single rotation: for the neuronal subpopulations analyzed by Hafting et al., one axis of the hexagonal grid is indeed tilted, but the other axes are not. Second, we show that local ensembles of entorhinal neurons are preferentially tuned to certain directions defined by the grid; this effect is unclear when single neurons are analyzed in isolation. Third, we argue that rat navigation traces are patterned instead of being random. For example, the orientation of the vector field representing average velocity appears to match the orientation of the neuronal grid. Overall, our observations indicate that additional insights into the function of entorhinal grids could be provided by ensemble-level analyses and thorough examination of the connection between the navigation behavior and neuronal patterns.\n\nHighlightsO_LIWhile our examination of the online dataset from Hafting et al. generally confirms their original findings, several clarifications should be made.\nC_LIO_LIFor the two neuronal subpopulations, where Hafting et al. reported a 7-10{degrees} relative tilt between the grids, only one of the grid axes is tilted, whereas the others are not.\nC_LIO_LIWhen spatial response fields are plotted for neuronal subpopulations instead of single neurons, it is clear that each subpopulation exhibits spatially periodic bands aligned with one of the grid axes.\nC_LIO_LINavigation traces are not random and appear to match the orientation and periodicity of the neuronal grid.\nC_LI

neuroscience↗

bioRxiv2017

Testing the Efforts Model of Simultaneous Interpreting: An ERP Study

We utilized the event-related potential (ERP) technique to study neural activity associated with different levels of working memory (WM) load during simultaneous interpretation (SI) in an ecologically valid setting. The amplitude of N1 and P1 components elicited by task-irrelevant tone probes was significantly modulated as a function of WM load but not the direction of interpretation. Furthermore, the latency of the N1 increased insignificantly with WM load. The P1 latency, however, mostly did not depend on either WM load or direction of interpretation. Larger negativity under lower WM loads suggests deeper processing of the auditory stimuli, providing tentative electrophysiological evidence in support of the Efforts Model of SI. Relationships between the direction of interpretation and median WM load are also discussed.

neuroscience↗

bioRxiv2017

Power and shift invariant detection of dynamically coupled networks (PSIICOS) from non-invasive MEG data

MEG reflects electrical activity of neuronal assemblies that coalesce and decoalesce in time providing for massively parallel and dynamic flow of information exchange in the brain. There is a growing evidence that our behavior is mediated by simultaneous activity of several interacting and simultaneously active cortical networks. Not only the location of network nodes but also the temporal profiles of such interaction are of interest. The existing methods are primarily concerned with proposing novel measures of synchrony to be applied to the cortical region activity signals extracted from the MEG data using beamforming or other spatial filtering approaches.\n\nIn this work we propose to render the task of estimating network topology and temporal profiles as a source estimation problem but in the space of interacting topographies. The proposed point of view has a number of benefits as it allows to use the wealth of techniques and intuition accumulated in the community when dealing with source estimation problems. Operating in the interacting topographies space we first propose subspace projection method to significantly reduce the spatial leakage effect in the cross-spectral matrix. We then use subspace matching metrics to extract a set of networks with their synchronicity profiles that explain the variance in the sensor space cross-spectral matrix, much like regular dipoles and their activations explain the variance in the regular evoked responses.\n\nThe preliminary results of application of this method to a simple self-paced voluntary finger movement paradigm comparing allowed to observe functional coupling between primary motor and supplementary motor area and establish that this coupling can be characterized with near-zero phase delay between the oscillatory activity of these two regions. This observed synchrony pattern is physiologically plausible and is in agreement with the current hypothesis about the neural mechanics of the motor acts.

neuroscience↗

bioRxiv2016

Localizing hidden regularities with known temporal structure in the EEG evoked response data

In this paper we describe a novel data driven spatial filtering technique that can be applied to the ERP analysis in order to find statistically significant hidden differential activations in the EEG data. The technique is based on the known morphological characteristics of the response. Underlying optimization problem is formulated as a generalized Rayleigh quotient maximization problem. We supply our tech-nique with a relevant randomization-based statistical test to assess the significance of the discovered phenomenon. Furthermore, we describe an application of the proposed method to the EEG data acquired in the study devoted to the analysis of the auditory neuroplasticity. We show how the mismatch negativity component, a tiny and short-lasting negative response that hallmarks the novel stimuli activating primary error-detection mechanisms, can be detected after filtration.

animal behavior and cognition↗