Biology subjects

Sengupta, A.

Publications and source records attributed to Sengupta, A..

8 recordsLinked to original sources

bioRxiv2018

Imaging human cortical responses to intraneural microstimulation using magnetoencephalography

The sensation of touch in the glabrous skin of the human hand is conveyed by thousands of fast-conducting mechanoreceptive afferents, which can be categorised into four distinct types. The spiking properties of these afferents in the periphery in response to varied tactile stimuli are well-characterised, but relatively little is known about the spatiotemporal properties of the neural representations of these different receptor types in the human cortex. Here, we use the novel methodological combination of single-unit intraneural microstimulation (INMS) with magnetoencephalography (MEG) to localise cortical representations of individual touch afferents in humans, by measuring the extracranial magnetic fields from neural currents. We found that by assessing the modulation of the beta (13-30 Hz) rhythm during single-unit INMS, significant changes in oscillatory amplitude occur in the contralateral primary somatosensory cortex within and across a group of fast adapting type I mechanoreceptive 20 afferents, which corresponded well to the induced response from matched vibrotactile stimulation. Combining the spatiotemporal specificity of MEG with the selective single-unit stimulation of INMS enables the interrogation of the central representations of different aspects of tactile afferent signalling within the human cortices. The fundamental finding that single-unit INMS ERD responses are robust and consistent with natural somatosensory stimuli will permit us to more dynamically probe the central nervous system responses in humans, to address questions about the processing of touch from the different classes of mechanoreceptive afferents and the effects of varying the stimulus frequency and patterning.

neuroscience↗

bioRxiv2018

Chemical Characterization of Interacting Genes in Few Subnetworks of Alzheimer’s Disease

A number of genes have been identified as a key player in Alzheimers disease (AD). Topological analysis of co-expression network reveals that key genes are mostly central or hub genes. The association between a hub gene and its neighbour genes can be derived easily using relative abundance of their expression levels. However, it is still unexplored fact that whether any hub and its neighbour genes within a sub-network exhibits any kind of proximity with respect to their chemical properties of the DNA sequences or not, that code for a sequence of amino acids.\n\nIn this work, we try to make a quantitative investigation of the underlying biological facts in DNA sequential and primary protein level in mathematical paradigm. It may gives a holistic view of the interrelationships existing between hub genes and neighbour genes in few selective AD subnetworks. We define a mapping model from physicochemical properties of DNA sequence to chemical characterization of amino acid sequences. We use distribution of chemical groups present in a sequence after decoding into corresponding amino acids to investigate the fact that whether any hub genes are associated closely with its neighbour genes chemically in the subnetworks. Interestingly, our preliminary results confirm the fact the dependent genes that are coexpressed with its hub gene are also having proximity with respect to their amino acid chemical group distributions.\n\nCCS Concepts*Applied computing [->] Computational genomics;

synthetic biology↗

bioRxiv2018

Manifold-tiling Localized Receptive Fields are Optimal in Similarity-preserving Neural Networks

Many neurons in the brain, such as place cells in the rodent hippocampus, have localized receptive fields, i.e., they respond to a small neighborhood of stimulus space. What is the functional significance of such representations and how can they arise? Here, we propose that localized receptive fields emerge in similarity-preserving networks of rectifying neurons that learn low-dimensional manifolds populated by sensory inputs. Numerical simulations of such networks on standard datasets yield manifold-tiling localized receptive fields. More generally, we show analytically that, for data lying on symmetric manifolds, optimal solutions of objectives, from which similarity-preserving networks are derived, have localized receptive fields. Therefore, nonnegative similarity-preserving mapping (NSM) implemented by neural networks can model representations of continuous manifolds in the brain.

neuroscience↗

bioRxiv2018

Effective Variations of related Physicochemical Properties of Nucleotides Leading to Amino Acids for Characterizing Genes and Proteins

The aim of this paper is to make quantitative analysis of the properties which is really being carried from DNA sequence and finally landing up to the properties of a protein structure through its primary protein sequence. Thus, the paper has a theory which is applicable for any arbitrary DNA sequence whether it is of various species or mutated data or a bunch of genes responsible for a function to be occurred. Irrespective to genes of any families, species, wild type or mutated, our paper here gives a standard model which defines a mapping between physicochemical properties of any arbitrary DNA sequence and physicochemical properties of its amino acid sequence. Experiments have been carried out with PPCA protein family and its four homologs PPC(B E) which establishes that DNA sequence keeps its signature even after its translation into the corresponding amino acid sequence.

systems biology↗

bioRxiv2018

The effect of acquisition resolution on orientation decoding from V1: comparison of 3T and 7T

Previously published results indicate that the accuracy of decoding visual orientation from 7T fMRI data of V1 peaks at spatial acquisition resolutions that are routinely accessible with more conventional 3T scanners. This study directly compares the decoding performance between a 3T and a 7T dataset that were acquired using the same stimulation paradigm by applying an identical analysis procedure. The results indicate that decoding models built on 3T data are comparatively impaired. Moreover, we found no evidence for a strong coupling of BOLD signal change magnitude or temporal signal to noise ratio (tSNR) with decoding performance. Direct enhancement of tSNR via multiband fMRI acquisition at the same resolution did not translate into improved decoding performance. Additional voxel selection can boost 3T decoding performance to the 7T level only at a 3mm acquisition resolution. In both datasets the BOLD signal available for orientation decoding is spatially broadband, but, consistent with the size of the BOLD point-spread-function, decoding models at 3T utilize spatially coarser image components.

neuroscience↗

bioRxiv2018

Characterizing glutamate receptor genes of Rat having vertebrate nervous system and Arabidopsis thaliana a plant having equivalent nervous system based on chemical properties of amino acids and investigating evolutionary relationships between them.

iGluR gene family of a vertebrate, Rat and AtGLR gene family of a plant, Arabidopsis thaliana [4] perform some common functionalities in neuro-transmission, which have been compared quantitatively. Our attempt is based on the chemical properties of amino acids [6, 7, 8] comprising the primary protein sequences of the aforesaid genes. 19 AtGLR genes of length varying from 808 amino acid (aa) to 1039 aa and 16 iGluR genes length varying from 902aa to 1482 aa have been taken as data sets. Thus, we detected the commonalities (conserved elements) during the long evolution of plants and animals from a common ancestor [4]. Eight different conserved regions have been found based on individual amino acids. Two different conserved regions are also found, which are based on chemical groups of amino acids. We have tried too to find different possible patterns which are common throughout the data set taken. 9 such patterns have been found with size varying from 2 to 5 amino acids at different regions in each primary protein sequences. Phylogenetic trees of AtGLR and iGluR families have also been constructed. This approach is likely to shed light on the long course of evolution.

systems biology↗

bioRxiv2017

Basolateral amygdala glutamatergic neurons maintain aversive emotional salience

Basolateral amygdala (BLA) glutamatergic neurons serve a well-accepted role in fear conditioning and fear extinction. However, the specific learning processes related to their activity at different times during learning remain poorly understood. We addressed this using behavioral tasks isolating distinct aspects of fear learning in rats. We show that brief optogenetic inhibition of BLA glutamatergic neurons around moments of aversive reinforcement or non-reinforcement causes reductions in the salience of conditioned stimuli, rendering these stimuli less able to be learned about and less able to control fear or safety behaviours. This salience reduction was stimulus-specific, long-lasting, and specific to aversive emotional states - precisely the goals of therapeutic interventions in human anxiety disorders. Our findings identify a core learning process disrupted by brief BLA optogenetic inhibition. They show that a primary function of BLA glutamatergic neurons is to maintain the salience of conditioned stimuli. This is a necessary precursor for these stimuli to gain and maintain control over fear and safety behavior.\n\nSignificance statementThe amygdala is essential for learning to fear and learning to reduce fear. However, the specific roles served by activity of different amygdala neurons at different times during learning is poorly understood. We used behavioral tasks isolating distinct aspects of learning in rats to show that brief optogenetic inhibition of BLA glutamatergic neurons around moments of reinforcement or non-reinforcement disrupts maintenance of conditioned stimulus (CS) salience. This causes a stimulus-specific, long-lasting, and aversive emotion specific deficit in the ability of the CS to be learned about or control fear responses. These consequences are the precisely goals of therapeutic interventions in human anxiety disorders. Our findings identify a core learning process disrupted by brief BLA optogenetic inhibition.

neuroscience↗

bioRxiv2016

The effect of acquisition resolution on orientation decoding from V1 BOLD fMRI at 7 Tesla

A decade after it was shown that the orientation of visual grating stimuli can be decoded from human visual cortex activity by means of multivariate pattern classification of BOLD fMRI data, numerous studies have investigated which aspects of neuronal activity are reflected in BOLD response patterns and are accessible for decoding. However, it remains inconclusive what the effect of acquisition resolution on BOLD fMRI decoding analyses is. The present study is the first to provide empirical ultra high-field fMRI data recorded at four spatial resolutions (0.8 mm, 1.4 mm, 2 mm, and 3 mm isotropic voxel size) on this topic -- in order to test hypotheses on the strength and spatial scale of orientation discriminating signals. We present detailed analysis, in line with predictions from previous simulation studies, about how the performance of orientation decoding varies with different acquisition resolutions. Moreover, we also examine different spatial filtering procedures and its effects on orientation decoding. Here we show that higher-resolution scans with subsequent down-sampling or low-pass filtering yield no benefit over scans natively recorded in the corresponding lower resolution regarding decoding accuracy. The orientation-related signal in the BOLD fMRI data is spatially broadband in nature, includes both high spatial frequency components, as well as large-scale biases previously proposed in the literature. Moreover, we found above chance-level contribution from large draining veins to orientation decoding. Acquired raw data were publicly released to facilitate further investigation.

neuroscience↗