Bapi Raju Surampudi

International Institute of Information Technology, Hyderabad | IIIT · Centre for Cognitive Science (CogSci)

We present a general, trainable oscillatory neural network as a large-scale model of brain dynamics. The model has a cascade of two stages - an oscillatory stage and a complex-valued feedforward stage - for modelling the relationship between structural connectivity and functional connectivity from neuroimaging data under resting brain conditions. E...

How does the brain represent different modes of information? Can we design a system that automatically understands what the user is thinking? Such questions can be answered by studying brain recordings like functional magnetic resonance imaging (fMRI). As a first step, the neuroscience community has contributed several large cognitive neuroscience...

In the rapidly growing computing world, the data is being generated every minute, and it has been a big challenge to manage and maintain privacy of the data when it is required to share among different locations. In this regard the privacy preserving data mining is playing a major role to design and develop the methods and models to preserve privac...

Preserving privacy of data in data mining domain has been a challenging objective to achieve. There has been lot of progress in applying secure algorithms in order to achieve privacy preserving of sensitive information. In distributed data mining perspective, there is necessity to share the information among the different parties aiming for combine...

A theory of magnitude (ATOM) suggests that a generalized magnitude system in the brain processes magnitudes such as space, time, and numbers. Numerous behavioral and neurocognitive studies have provided support to ATOM theory. However, the evidence for common magnitude processing primarily comes from the studies in which numerical and temporal info...

Classical Conditioning is a fundamental learning mechanism where the Ventral Striatum is generally thought to be the source of inhibition to Ventral Tegmental Area (VTA) Dopamine neurons when a reward is expected. However, recent evidences point to a new candidate in VTA GABA encoding expectation for computing the reward prediction error in the VTA...

Enabling effective brain-computer interfaces requires understanding how the human brain encodes stimuli across modalities such as visual, language (or text), etc. Brain encoding aims at constructing fMRI brain activity given a stimulus. There exists a plethora of neural encoding models which study brain encoding for single mode stimuli: visual (pre...

How the brain captures the meaning of linguistic stimuli across multiple views is still a critical open question in neuroscience. Consider three different views of the concept apartment: (1) picture (WP) presented with the target word label, (2) sentence (S) using the target word, and (3) word cloud (WC) containing the target word along with other...

ECG analysis comprises the following steps: preprocessing, segmentation, feature extraction, and classification of heart-beat instances to detect cardiac arrhythmias. This work focuses on the first three steps in cardiac arrhythmia analysis. Since no publicly available feature sets are available for the ECG arrhythmia detection problem, researchers...

In this smart and rapidly growing computing world, most of the organizations and companies needs to share necessary information (data) to third parties for their analysis which plays major role in decision making. Any data generally consists of sensitive (personal) information about people and organizations and when the sensitive information to be...

Background Life‐course experiences such as education and bilingualism can be protective against dementia. The cognitive effects of bilingualism are specific while education has a more pervasive effect on general cognitive abilities, indicating that there is a likelihood of a variability in mechanisms underlying resilience. India is characterised by...

This paper presents a bio-inspired intelligent controller to enhance the performance of a nonlinear system. The controller is designed by capturing the emotional intelligence of mammalian brain mediated by the limbic system in which certain parts are responsible for generating emotions and these can be combined together as brain affective system in...

The processing of time and numbers has been fundamental to human cognition. One of the prominent theories of magnitude processing, a theory of magnitude (ATOM), suggests that a generalized magnitude system processes space, time, and numbers; thereby, the magnitude dimensions could potentially interact with one another. However, more recent studies...

Several canonical experimental paradigms (e.g., serial reaction time task, discrete sequence production task, m × n task) have been proposed to study the typical behavioral phenomenon and the nature of learning in sequential keypress tasks. A characteristic feature of most paradigms is that they are representative of externally-specified sequencing...

Motor skill learning involves the acquisition of sequential motor movements with practice. Studies have shown that we learn to execute these sequences efficiently by chaining several elementary actions in sub-sequences called motor chunks. Several experimental paradigms, such as serial reaction task, discrete sequence production, and m × n task, ha...

A Theory of Magnitude (ATOM) suggests that space, time, and quantities are processed through a generalized magnitude system. ATOM posits that task-irrelevant magnitudes interfere with the processing of task-relevant magnitudes as all the magnitudes are processed by a common system. Many behavioral and neuroimaging studies have found support in favo...

Manual identification of ECG heartbeat classes by cardiologists is time consuming and cumbersome. These professionals rely on computer based methods for determination of these heart-disease types. In this work, existing literature is organized into a proposed taxonomy based on dichotomies involving full time series-based versus feature-based, AAMI...

Due to mood-congruency effects, we expect the emotion perceived on a face to be biased towards one's own mood. But the findings in the scant literature on such mood effects in normal healthy populations have not consistently and adequately supported this expectation. Employing effective mood manipulation techniques that ensured that the intended mo...

Classical Conditioning is a fundamental learning mechanism where the Ventral Striatum is generally thought to be the source of inhibition to Ventral Tegmental Area (VTA) Dopamine neurons when a reward is expected. However, recent evidences point to a new candidate in VTA GABA encoding expectation for computing the reward prediction error in the VTA...

Manual identification of ECG heart-beat classes by cardiologists is time consuming and cumbersome. These professionals rely on computer based methods for determination of these heart-disease types. In this work, existing literature is organized into a proposed taxonomy based on dichotomies involving full time series-based versus feature-based, AAMI...

There have been numerous attempts in explaining the general learning behaviours using model-based and model-free methods. While the model-based control is flexible yet computationally expensive in planning, the model-free control is quick but inflexible. The model-based control is therefore immune from reward devaluation and contingency degradation...

Social, Emotional and Affective Factors [SEA] are critical to academic and career success [1]. Affective Education helps children better understand their feelings and respond to challenging situations. Although the importance of affect on learning and cognition is widely accepted in Education Research, the research so far has treated affect and cog...

Investigating the functional connectivity (FC) patterns of the brain using resting-state functional magnetic resonance imaging (rs-fMRI) has been instrumental in revealing the effects of neurological disorders. Several studies have established that brain connectivity is dynamic in nature, and that brain diseases have an impact on both FC and its te...

Exploration of brain imaging data with machine learning methods has been beneficial in identifying and probing the impacts of neurological disorders. Psychopathological ailments that disrupt brain activity can be discerned with the help of resting-state functional magnetic resonance imaging (rs-fMRI). Research has revealed that brain connectivity i...

fMRI semantic category understanding using linguistic encoding models attempts to learn a forward mapping that relates stimuli to the corresponding brain activation. Classical encoding models use linear multivariate methods to predict brain activation (all the voxels) given the stimulus. However, these methods mainly assume multiple regions as one...

Learning a forward mapping that relates stimuli to the corresponding brain activation measured by functional magnetic resonance imaging (fMRI) is termed as estimating encoding models. Computational tractability usually forces current encoding as well as decoding solutions to typically consider only a small subset of voxels from the actual 3D volume...

Resting-state functional connectivity (FC) analyses have shown atypical connectivity in autism spectrum disorder (ASD) as compared to typically developing (TD). However, this view emerges from investigating static FC overlooking the whole brain transient connectivity patterns. In our study, we investigated how age and disease influence the dynamic...

There have been numerous attempts in explaining the general learning behaviours by various cognitive models. Multiple hypotheses have been put further to qualitatively argue the best-fit model for motor skill acquisition task and its variations. In this context, for a discrete sequence production (DSP) task, one of the most insightful models is Ver...

There have been numerous attempts in explaining the general learning behaviours by various cognitive models. Multiple hypotheses have been put further to qualitatively argue the best-fit model for motor skill acquisition task and its variations. In this context, for a discrete sequence production (DSP) task, one of the most insightful models is Ver...

fMRI semantic category understanding using linguistic encoding models attempt to learn a forward mapping that relates stimuli to the corresponding brain activation. Classical encoding models use linear multi-variate methods to predict the brain activation (all voxels) given the stimulus. However, these methods essentially assume multiple regions as...

The dispute of how the human brain represents conceptual knowledge has been argued in many scientific fields. Brain imaging studies have shown that the spatial patterns of neural activation in the brain are correlated with thinking about different semantic categories of words (for example, tools, animals, and buildings) or when viewing the related...

Affective education is a formal curriculum designed to help children better understand their feelings and respond to challenging situations, thereby transforming themselves and the world around them. Emotions impact the learning ability at multiple levels (Attention, Memory and decision making etc.). Though they have been advancements in terms of t...

Over the last decade there has been growing interest in understanding the brain activity, in the absence of any task or stimulus, captured by the resting-state functional magnetic resonance imaging (rsfMRI). The resting state patterns have been observed to be exhibiting complex spatio-temporal dynamics and substantial effort has been made to charac...

Resting-state functional connectivity (FC) analyses have shown atypical connectivity in autism spectrum disorder (ASD) as compared to typically developing (TD). However, this view emerges from investigating static FC overlooking the age, disease phenotype and their interaction in the whole brain transient connectivity patterns. Contrasting with mos...

Extreme learning machine (ELM) is a new algorithm for training single-hidden layer feedforward neural networks which provides good performance as well as fast learning speed. ELM tends to produce good generalization performance with large number of hidden neurons as the input weights and hidden neurons biases are randomly initialized and remain unc...

Brain connectivity analysis has provided crucial insights to pinpoint the differences between autistic and typically developing (TD) children during development. The aim of this study is to investigate the functional connectomics of Autism Spectrum Disorder (ASD) versus TD and underpin the effects of development, disease, and their interactions on...

Over the last decade there has been growing interest in understanding the brain activity in the absence of any task or stimulus captured by the resting-state functional magnetic resonance imaging (rsfMRI). These resting state patterns are not static, but exhibit complex spatio-temporal dynamics. In the recent years substantial effort has been put t...

Intensity and duration are both pertinent aspects of an emotional experience, yet how they are related is unclear. Though stronger emotions usually last longer, sometimes they abate faster than the weaker ones. We present a quantitative model of affective adaptation, the process by which emotional responses to unchanging affective stimuli weaken wi...

The dispute of how the human brain represents conceptual knowledge has been argued in many scientific fields. Brain imaging studies have shown that the spatial patterns of neural activation in the brain are correlated with thinking about different semantic categories of words (for example, tools, animals, and buildings) or when viewing the related...

Papillary Renal Cell Carcinoma (PRCC) is a heterogeneous disease with variations in disease progression and clinical outcomes. The advent of next generation sequencing techniques (NGS) has generated data from patients that can be analysed to develop a predictive model. In this study, we have adopted a machine learning approach to identify biomarker...

Automatic photo aesthetic assessment is a challenging artiicial intelligence task. Existing computational approaches have focused on modeling a single aesthetic score or class (good or bad photo), however these do not provide any details on why the photograph is good or bad; or which attributes contribute to the quality of the photograph. To obtain...

Autism spectrum disorder (ASD) is a neurodevelopmental disorder affecting 1 in 50 children between the ages of 6 and 17 years. Brain connectivity and graph theoretic methods have been particularly very useful in shedding light on the differences between high functioning autistic children compared to typically developing (TD) ones. However, very rec...

A challenging problem in cognitive neuroscience is to relate the structural connectivity (SC) to the functional connectivity (FC) to better understand how large-scale network dynamics underlying human cognition emerges from the relatively fixed SC architecture. Recent modeling attempts point to the possibility of a single diffusion kernel giving a...

Feminine facial features enhance the expressive cues associated with happiness but not sadness. This makes a woman look happier than a man even when their smiles have the same intensity. So, to correctly infer the actual happiness of a woman, one would have to subtract the effect of these facial features. We hypothesised that our perceptual system...

Details on ”Metastability of cortical BOLD Signals in Maturation and Senescence”

Papillary Renal Cell Carcinoma (PRCC) is a heterogeneous disease accounting for 10%-15% of renal cell carcinomas. A comprehensive analysis is required to find the genes that are responsible for the stage progression in PRCC. The advent of next generation sequencing techniques (NGS) has produced a lot of high throughput data from patients that can b...

Automatic photo aesthetic assessment is a challenging artificial intelligence task. Existing computational approaches have focused on modeling a single aesthetic score or a class (good or bad), however these do not provide any details on why the photograph is good or bad, or which attributes contribute to the quality of the photograph. To obtain bo...

The brain during healthy aging exhibits gradual deterioration of structure but maintains a high level of cognitive ability. These structural changes are often accompanied by reorganization of functional brain networks. Existing neurocognitive theories of aging have argued that such changes are either beneficial or detrimental. Despite numerous empi...

The stability analysis of dynamical neural network systems generally follows the route of finding a suitable Liapunov function after the fashion Hopfield’s famous paper on content addressable memory network or by finding conditions that make divergent solutions impossible. For the current work we focused on biological recurrent neural networks (bRN...

Bilingualism has been found to delay onset of dementia and this has been attributed to an advantage in executive control in bilinguals. However, the relationship between bilingualism and cognition is complex, with costs as well as benefits to language functions. To further explore the cognitive consequences of bilingualism, the study used Frontotem...

The capacity to sequence information is central to human performance. Sequencing ability forms the foundation stone for higher order cognition related to language and goal-directed planning. Information related to the order of items, their timing, chunking and hierarchical organization are important aspects in sequencing. Past research on sequencin...

The existence of perceptually distinct numerosity ranges has been proposed for small (i.e., subitizing range) and larger numbers based on differences in precision, Weber fractions, and reaction times. This raises the question of whether such dissociations reflect distinct mechanisms operating across the two numerosity ranges. In the present work, w...

An ElectroCardiogram (ECG) inter-patient heartbeat time series classification method by a hierarchical system of based on support vector machine and Decision rule, using full heart-beat time series by alignment of R-peaks of all beats, is proposed. PQRST Time series of heart-beats having converted into equal length series by alignment of R-peaks of...

The activation of the brain at rest is thought to be at the core of cognitive functions. There have been many attempts at characterizing the functional connectivity at rest from the structure. Recent attempts with diffusion kernel models point to the possibility of a single diffusion kernel that can give a good estimate of the functional connectivi...

Stroke is the leading cause of severe chronic disability and the second cause of death worldwide with 15 million new cases and 50 million stroke survivors. The post stroke chronic disability may be ameliorated with early neurorehabilitation where non-invasive brain stimulation (NIBS) techniquescan be used as an adjuvant treatment to hasten the effe...

Identification of protein coding regions in genomic sequences is a significant problem in bioinformatics. A significant number of techniques for identifying coding regions in genomic sequences are based on Fourier representation for the sequence of nucleotides and spectral analysis methods in order to detect protein coding regions. These methods us...

Clustering or classification of data described by categorical attributes is a challenging task in data mining. This is because it is difficult to define a measure between pairs of values of a categorical attributes. The difficulty arises due to lack of ordering information between various pairs of categorical attributes. In this paper we introduce...

In view of present advancements in computing, with the development of distributed environment, many problems have to deal with distributed input data where individual data privacy is the most important issue to be addressed, for the concern of data owner by extending the privacy preserving notion to the original learning algorithms. Privacy Preserv...

Background and purpose: Bilingualism has been associated with slower cognitive aging and a later onset of dementia. In this study, we aimed to determine whether bilingualism also influences cognitive outcome after stroke. Methods: We examined 608 patients with ischemic stroke from a large stroke registry and studied the role of bilingualism in p...

The visual system is able to rapidly and accurately enumerate a small number of items (subitizing) or, instead, to estimate less precisely a large number of items (estimation). Recent computational, behavioral (Sengupta et al, 2014) and fMRI (Roggeman et al.2010; Knops et al, 2014) studies are consistent with the idea that a single enumeration mech...