Perception necessitates interaction among neuronal ensembles, the dynamics of which can be conceptualized as the emergent behavior of coupled dynamical systems. Here, we propose a detailed neurobiologically realistic model that captures the neural mechanisms of inter-individual variability observed in cross-modal speech perception. From raw EEG signals recorded from human participants when they were presented with speech vocalizations of McGurk-incongruent and congruent audiovisual (AV) stimuli, we computed the global coherence metric to capture the neural variability of large-scale networks. We identified that participants' McGurk susceptibility was negatively correlated to their alpha band global coherence. The proposed biophysical model conceptualized the global coherence dynamics emerge from coupling between the interacting neural masses-representing the sensory-specific auditory/visual areas and modality nonspecific associative/integrative regions. Subsequently, we could predict that an extremely weak direct AV coupling results in a decrease in alpha band global coherence-mimicking the cortical dynamics of participants with higher McGurk susceptibility. Source connectivity analysis also showed decreased connectivity between sensory-specific regions in participants more susceptible to McGurk effect, thus establishing an empirical validation to the prediction. Overall, our study provides an outline to link variability in structural and functional connectivity metrics to variability of performance that can be useful for several perception and action task paradigms.

Abstract-In this paper we present a novel recognition approach that results in a 15% decrease in word error rate on heavily degraded Indian language document images. OCRs have considerably good performance on good quality documents, but fail easily in presence of degradations. Also, classical OCR approaches perform poorly over complex scripts such as those for Indian languages. We address these issues by proposing to recognize character n-gram images, which are basically groupings of consecutive character/component segments. Our approach is unique, since we use the character n-grams as a primitive for recognition rather than for postprocessing. By exploiting the additional context present in the character n-gram images, we enable better disambiguation between confusing characters in the recognition phase. The labels obtained from recognizing the constituent n-grams are then fused to obtain a label for the word that emitted them. Our method is inherently robust to degradations such as cuts and merges which are common in digital libraries of scanned documents. We also present a reliable and scalable scheme for recognizing character n-gram images. Tests on English and Malayalam document images show considerable improvement in recognition in the case of heavily degraded documents.

Melody in Carnatic Music is based on the concept of a raga. Characteristic motif is a signature melodic phrase that determines the identity of a raga. This paper addresses locating these motifs in an alapana, given a query motif. A twostep approach approach is employed. The first is to identify the location of snippets of phrases that exists in the Alapana. Next the conventional approach to the rough longest common subsequence algorithm to spot motifs is modified. In the modified algorithm a more appropriate measure of match is proposed. The algorithm is particularly relevant for short but good matches. The modification enables logical choices of empirical parameters. In this paper, the motifs that are chosen are also long compared to our earlier work. The modified RLCS algorithm reduces the number of false alarms from 130 to 94 and also performs better localization of motifs.

10A widely used experimental design in multisensory integration is the McGurk paradigm that 11 entail illusory (cross-modal) perception of speech sounds when presented with incongruent 12 audio-visual (AV) stimuli. However, the distribution of responses across trials and 13 individuals is heterogeneous and not necessarily everyone in a given group of individuals 14 perceives the effect. Nonetheless, existing studies in the field primarily focus on addressing 15 the correlation between subjective behavior and cortical activations to reveal the neuronal 16 mechanisms underlying the perception of McGurk effect, typically in the "frequent 17 perceivers". Additionally, a solely neuroimaging approach does not provide mechanistic 18 explanation for the observed inter-trial or inter-individual heterogeneity. In the current study 19we employ high density electroencephalogram (EEG) recordings in a group of 25 human 20 subjects that allow us to distinguish "frequent perceivers" from "rare perceivers" using 21 behavioral responses as well as from the perspective of large-scale brain functional 22 connectivity (FC). Using global coherence as a measure of large-scale FC, we find that alpha 23 band coherence, a distinctive feature in frequent perceivers is absent in the rare perceivers. 24 Secondly, a decrease in alpha band coherence and increase in gamma band coherence occur 25 during illusory perception trials in both frequent and rare perceivers. Source analysis 26 followed up with source time series reconstructions reveals a large scale network of brain 27 areas involving frontal, temporal and parietal areas that are involved in network level 28 processing of cross-modal perception. Finally, we demonstrate that how a biophysically 29 realistic computational model representing the interaction among key neuronal systems 30 (visual, auditory and multisensory cortical regions) can explain the empirical observations. 31 Each system involves a group of excitatory and inhibitory Hindmarsh Rose neurons that are 32 coupled amongst each other. Large-scale FC between areas is conceptualized using coupling 33 2 functions and the identity of a specific system, e.g., visual/ auditory/ multisensory is chosen 34 using empirical estimates of the time-scale of information processing in these systems. The 35 model predicts that the disappearance of alpha band coherence observed in rare perceivers 36 stems from a negligible direct A-V (audio-visual) coupling however, an increase in indirect 37 interaction via multisensory node leads to enhanced gamma band and reduced alpha band 38 coherences observed during illusory perception. Overall, we establish the mechanistic basis 39 of large-scale FC patterns underlying cross-modal perception.40 41

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