Resting-state network connectivity has been associated with a variety of cognitive abilities, yet it remains unclear how these properties might contribute to the neurocognitive computations underlying abilities. We developed new approach-information transfer mapping-to test hypothesis that resting-state functional topology describes computational mappings between brain regions carry task information. Here, we report diverse, task-rule information in distributed can be predicted based on...

Pain is a symptom of many disorders associated with actual or potential tissue damage in human body. Managing pain not only duty but also highly cost prone. The most primitive state management the assessment pain. Traditionally it was accomplished by self-report visual inspection experts. However, automatic systems from facial videos are rapidly evolving due to need managing robust and effective way. Among different challenges video data two issues increasingly prevalent: first, exploiting...

Humans modify their facial expressions in order to communicate internal states and sometimes mislead observers regarding true emotional states. Evidence experimental psychology shows that discriminative responses are short subtle. This suggests such behavior would be easier distinguish when captured high resolution at an increased frame rate. We proposing SASE-FE, the first dataset of either congruent or incongruent with underlying emotion show overall problem recognizing whether movements...

Abstract A wide variety of mental disorders have been associated with resting-state functional network alterations, which are thought to contribute the cognitive changes underlying illness. These observations appear support theories postulating large-scale disruptions brain systems in However, existing approaches isolate differences organization without putting those a broad, whole-brain perspective. Using graph distance approach—connectome-wide similarity—we found that is highly similar...

Abstract Crises such as the COVID-19 pandemic are known to exacerbate depression and anxiety, though their temporal trajectories remain under-investigated. The present study aims investigate fluctuations in anxiety using a model crisis. A total of 1512 adults living United States enrolled this online beginning April 2, 2020 were assessed weekly for 10 weeks (until June 4, 2020). We measured Zung Self-Rating Depression scale State-Trait Anxiety Inventory (state subscale), respectively, along...

Efficient contact tracing and testing are fundamental tools to contain the transmission of SARS-CoV-2. We used multi-agent simulations estimate daily capacity required find isolate a number infected agents sufficient break chain SARS-CoV-2, so decreasing risk new waves infections. Depending on non-pharmaceutical mitigation policies in place, size secondary infection clusters allowed or percentage asymptomatic paucisymptomatic (i.e., subclinical) infections, we estimated that disease varies...

Much of our lives are spent in unconstrained rest states, yet cognitive brain processes primarily investigated using task-constrained states. It may be possible to utilize the insights gained from experimental control task as reference points for investigating rest. To facilitate comparison and functional magnetic resonance imaging data, we focused on activation amplitude patterns, commonly used but not analyses. During rest, identified spontaneous changes temporally extended whole-brain...

Abstract A wide variety of mental disorders have been associated with resting-state functional network alterations, which are thought to contribute the cognitive changes underlying illness. These observations seemed support various theories postulating large-scale disruptions brain systems in However, existing approaches isolate differences organization without putting those broad, whole-brain perspective. Using a graph distance measure – connectome-wide correlation we found that humans is...

Understanding complex systems such as the human brain requires characterization of system's architecture across multiple levels organization - from neurons, to local circuits, regions, and ultimately large-scale networks. Here we focus on characterizing brain's network organization, it provides an overall framework for all other levels. We developed a highly principled approach identify cortical communities at level functional systems, calibrating our community detection algorithm using...

Abstract We used multi-agent simulations to estimate the testing capacity required find and isolate a number of infections sufficient break chain transmission SARS-CoV-2. Depending on mitigation policies in place, daily between 0.7 3.6 tests per thousand was contain disease. However, if contact tracing efficacy dropped below 60% (e.g. due false negatives or reduced capability), kept growing exponentially, irrespective any capacity. Under these conditions, population’s geographical...

We propose a novel framework for continuous speech recognition (CSR) based on non-parametric acoustic modeling using multiple phoneme templates set in modified one-pass DP decoding algorithm, contrast to the conventional HMM models Viterbi decoding. particularly emphasis 'selectivity' property of as proposed algorithm and explore various contextual definitions their relative performances range small vocabulary tasks with TIMIT database only models. Based this, we show that template is viable...

Abstract Resting-state network connectivity has been associated with a variety of cognitive abilities, yet it remains unclear how these properties might contribute to the neurocognitive computations underlying abilities. We developed new approach – information transfer mapping test hypothesis that resting-state functional topology describes computational mappings between brain regions carry task information. Here we report diverse, task-rule in distributed can be predicted based on estimated...

Transfer learning aims at adapting a model learned from source dataset to target dataset. It is beneficial approach especially when annotating on the expensive or infeasible. has demonstrated its powerful capabilities in various vision tasks. Despite transfer being promising approach, it still an open question how adapt One big challenge prevent impact of category bias classification performance. Dataset exists two images same category, but different datasets, are not classified as same. To...

Abstract Much of our lives are spent in unconstrained rest states, yet cognitive brain processes primarily investigated using task-constrained states. It may be possible to utilize the insights gained from experimental control task as reference points for investigating rest. To facilitate comparison and functional MRI (fMRI) data we focused on activation amplitude patterns, commonly used but not analyses. During rest, identified spontaneous changes temporally extended whole-brain pattern...

The problem of the effect accent on performance Automatic Speech Recognition (ASR) systems is well known. In this paper, we study variability Indian English ASR task. We evaluate test vocabularies HMMs trained (a) Accent specific training data (b) pooled which combines all (c) reduced size matching data. demonstrate that set performs best phonetically rich isolated word recognition But perform better than HMMs, indicating a possible approach using first stage identification to choose correct...

Abstract Dopamine (DA) signals originating from substantia nigra (SN) neurons are centrally involved in the regulation of motor and reward processing. DA behaviorally relevant events where outcomes differ expectations (reward prediction errors, RPEs). RPEs play a crucial role learning optimal courses action determining response vigor when an agent expects rewards. Nevertheless, how expectations, for RPE calculations, conveyed to represented dopaminergic system is not fully understood,...

The excessive consumption of marijuana can induce substantial psychological and social consequences. In this investigation, we propose an elucidative framework termed high-order graph attention neural networks (HOGANN) for the classification Marijuana addiction, coupled with analysis localized brain network communities exhibiting abnormal activities among chronic users. HOGANN integrates dynamic intrinsic functional networks, estimated from magnetic resonance imaging (fMRI), using...