Publications by authors named "Medha Shekhar"

A central goal of research in perceptual decision making is to determine the internal computations underlying choice and confidence in complex, multi-alternative tasks. However, revealing these computations requires knowledge of the internal representation upon which the computations operate. Unfortunately, it is unknown how traditional stimuli (e.

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The Bayesian confidence hypothesis (BCH), which postulates that confidence reflects the posterior probability that a decision is correct, is currently the most prominent theory of confidence. Although several recent studies have found evidence against it in the context of relatively complex tasks, BCH remains dominant for simpler tasks. The major alternative to BCH is the confidence in raw evidence space (CRES) hypothesis, according to which confidence is based directly on the raw sensory evidence without explicit probability computations.

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Prior research has shown that manipulating stimulus energy by changing both stimulus contrast and variability results in confidence-accuracy dissociations in humans. Specifically, even when performance is matched, higher stimulus energy leads to higher confidence. The most common explanation for this effect, derived from cognitive modeling, is the positive evidence heuristic where confidence neglects evidence that disconfirms the choice.

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Article Synopsis
  • The high prevalence of underweight among women of reproductive age in South Asia leads to serious health issues, including impaired immunity and complications during pregnancy, which the WING study addresses through targeted interventions.
  • The study involved 13,500 women in low- to lower-middle-income neighborhoods of Delhi, providing food supplements tailored to their nutritional needs during preconception and pregnancy phases.
  • Findings revealed that around 35% of participants were underweight; the intervention led to significant improvements in nutritional status and weight gain for two-thirds of these women over 9-12 months and 4 weeks, respectively.
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Convolutional neural networks show promise as models of biological vision. However, their decision behaviour, including the facts that they are deterministic and use equal numbers of computations for easy and difficult stimuli, differs markedly from human decision-making, thus limiting their applicability as models of human perceptual behaviour. Here we develop a new neural network, RTNet, that generates stochastic decisions and human-like response time (RT) distributions.

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Prior research has shown that manipulating stimulus energy by changing both stimulus contrast and variability results in confidence-accuracy dissociations in humans. Specifically, even when performance is matched, higher stimulus energy leads to higher confidence. The most common explanation for this effect is the positive evidence heuristic where confidence neglects evidence that disconfirms the choice.

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Humans have the metacognitive ability to assess the accuracy of their decisions via confidence judgments. Several computational models of confidence have been developed but not enough has been done to compare these models, making it difficult to adjudicate between them. Here, we compare 14 popular models of confidence that make various assumptions, such as confidence being derived from postdecisional evidence, from positive (decision-congruent) evidence, from posterior probability computations, or from a separate decision-making system for metacognitive judgments.

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We recently found a positive relationship between estimates of metacognitive efficiency and metacognitive bias. However, this relationship was only examined on a within-subject level and required binarizing the confidence scale, a technique that introduces methodological difficulties. Here we examined the robustness of the positive relationship between estimates of metacognitive efficiency and metacognitive bias by conducting two different types of analyses.

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The period of making a perceptual decision is often followed by a period of rating confidence where one evaluates the likely accuracy of the initial decision. However, it remains unclear whether the same or different neural circuits are engaged during periods of perceptual decision making and confidence report. To address this question, we conducted two functional MRI experiments in which we dissociated the periods related to perceptual decision making and confidence report by either separating their respective regressors or asking for confidence ratings only in the second half of the experiment.

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Confidence judgments are typically less informative about one's accuracy than they could be; a phenomenon we call metacognitive inefficiency. We review the existence of different sources of metacognitive inefficiency and classify them into four categories based on whether the corruption is due to: (i) systematic or nonsystematic influences, and (ii) the input to or the computation of the metacognitive system. Critically, the existence of different sources of metacognitive inefficiency provides an alternative explanation for behavioral findings typically interpreted as evidence for domain-specific (and against domain-general) metacognitive systems.

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Humans have the metacognitive ability to judge the accuracy of their own decisions via confidence ratings. A substantial body of research has demonstrated that human metacognition is fallible but it remains unclear how metacognitive inefficiency should be incorporated into a mechanistic model of confidence generation. Here we show that, contrary to what is typically assumed, metacognitive inefficiency depends on the level of confidence.

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Understanding how people rate their confidence is critical for the characterization of a wide range of perceptual, memory, motor and cognitive processes. To enable the continued exploration of these processes, we created a large database of confidence studies spanning a broad set of paradigms, participant populations and fields of study. The data from each study are structured in a common, easy-to-use format that can be easily imported and analysed using multiple software packages.

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Background: Coverage of kangaroo mother care remains very low despite WHO recommendations for its use for babies with low birthweight in health facilities for over a decade. Initiating kangaroo mother care at the community level is a promising strategy to increase coverage. However, knowledge of the efficacy of community-initiated kangaroo mother care is still lacking.

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Metacognitive efficiency quantifies people's ability to introspect into their own decision making relative to their ability to perform the primary task. Despite years of research, it is still unclear how visual metacognitive efficiency can be manipulated. Here, we show that a hierarchical model of confidence generation makes a counterintuitive prediction: Higher sensory noise should increase metacognitive efficiency.

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Visual metacognition depends on regions within the prefrontal cortex (PFC). Two areas in particular have been implicated repeatedly: the dorsolateral PFC (DLPFC) and the anterior PFC (aPFC). However, it is still unclear what the function of each of these areas is and how they differ from each other.

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Trial Design: Three feeding regimens-centrally produced ready-to-use therapeutic food, locally produced ready-to-use therapeutic food, and augmented, energy-dense, home-prepared food-were provided in a community setting for children with severe acute malnutrition (SAM) in the age group of 6-59 months in an individually randomised multicentre trial that enrolled 906 children. Foods, counselling, feeding support and treatment for mild illnesses were provided until recovery or 16 weeks.

Methods: Costs were estimated for 371 children enrolled in Delhi in a semiurban location after active survey and identification, enrolment, diagnosis and treatment for mild illnesses, and finally treatment with one of the three regimens, both under the research and government setting.

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Background: Low and middle income countries (LMICs), including India, contribute to a major proportion of low birth weight (LBW) infants globally. These infants require special care. Kangaroo Mother Care (KMC) in hospitals is a cost effective and efficacious intervention.

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