M-Theory on the Orbifold C^2/Z_N

We construct M-theory on the orbifold C^2/Z_N by coupling 11-dimensional supergravity to a seven-dimensional Yang-Mills theory located on the orbifold fixed plane. It is shown that the resulting action is supersymmetric to leading non-trivial order in the 11-dimensional Newton constant. This action provides the starting point for a reduction of M-theory on G_2 spaces with co-dimension four singularities.Comment: 33 pages, Late

An integration of integrated information theory with fundamental physics

To truly eliminate Cartesian ghosts from the science of consciousness, we must describe consciousness as an aspect of the physical. Integrated Information Theory states that consciousness arises from intrinsic information generated by dynamical systems; however existing formulations of this theory are not applicable to standard models of fundamental physical entities. Modern physics has shown that fields are fundamental entities, and in particular that the electromagnetic field is fundamental. Here I hypothesize that consciousness arises from information intrinsic to fundamental fields. This hypothesis unites fundamental physics with what we know empirically about the neuroscience underlying consciousness, and it bypasses the need to consider quantum effects

Measures of metacognition on signal-detection theoretic models

Analysing metacognition, specifically knowledge of accuracy of internal perceptual, memorial or other knowledge states, is vital for many strands of psychology, including determining the accuracy of feelings of knowing, and discriminating conscious from unconscious cognition. Quantifying metacognitive sensitivity is however more challenging than quantifying basic stimulus sensitivity. Under popular signal detection theory (SDT) models for stimulus classification tasks, approaches based on type II receiver-operator characteristic (ROC) curves or type II d-prime risk confounding metacognition with response biases in either the type I (classification) or type II (metacognitive) tasks. A new approach introduces meta-d′: the type I d-prime that would have led to the observed type II data had the subject used all the type I information. Here we (i) further establish the inconsistency of the type II d-prime and ROC approaches with new explicit analyses of the standard SDT model, and (ii) analyse, for the first time, the behaviour of meta-d′ under non-trivial scenarios, such as when metacognitive judgments utilize enhanced or degraded versions of the type I evidence. Analytically, meta-d′ values typically reflect the underlying model well, and are stable under changes in decision criteria; however, in relatively extreme cases meta-d′ can become unstable. We explore bias and variance of in-sample measurements of meta-d′ and supply MATLAB code for estimation in general cases. Our results support meta-d′ as a useful measure of metacognition, and provide rigorous methodology for its application. Our recommendations are useful for any researchers interested in assessing metacognitive accuracy

Granger causality analysis in neuroscience and neuroimaging

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Optimal learning rules for discrete synapses

There is evidence that biological synapses have a limited number of discrete weight states. Memory storage with such synapses behaves quite differently from synapses with unbounded, continuous weights, as old memories are automatically overwritten by new memories. Consequently, there has been substantial discussion about how this affects learning and storage capacity. In this paper, we calculate the storage capacity of discrete, bounded synapses in terms of Shannon information. We use this to optimize the learning rules and investigate how the maximum information capacity depends on the number of synapses, the number of synaptic states, and the coding sparseness. Below a certain critical number of synapses per neuron (comparable to numbers found in biology), we find that storage is similar to unbounded, continuous synapses. Hence, discrete synapses do not necessarily have lower storage capacity

Blind insight: metacognitive discrimination despite chance task performance

Blindsight and other examples of unconscious knowledge and perception demonstrate dissociations between judgment accuracy and metacognition: Studies reveal that participants’ judgment accuracy can be above chance while their confidence ratings fail to discriminate right from wrong answers. Here, we demonstrated the opposite dissociation: a reliable relationship between confidence and judgment accuracy (demonstrating metacognition) despite judgment accuracy being no better than chance. We evaluated the judgments of 450 participants who completed an AGL task. For each trial, participants decided whether a stimulus conformed to a given set of rules and rated their confidence in that judgment. We identified participants who performed at chance on the discrimination task, utilizing a subset of their responses, and then assessed the accuracy and the confidence-accuracy relationship of their remaining responses. Analyses revealed above-chance metacognition among participants who did not exhibit decision accuracy. This important new phenomenon, which we term blind insight, poses critical challenges to prevailing models of metacognition grounded in signal detection theory

Practical measures of integrated information for time-series data

A recent measure of ‘integrated information’, ΦDM, quantifies the extent to which a system generates more information than the sum of its parts as it transitions between states, possibly reflecting levels of consciousness generated by neural systems. However, ΦDM is defined only for discrete Markov systems, which are unusual in biology; as a result, ΦDM can rarely be measured in practice. Here, we describe two new measures, ΦE and ΦAR, that overcome these limitations and are easy to apply to time-series data. We use simulations to demonstrate the in-practice applicability of our measures, and to explore their properties. Our results provide new opportunities for examining information integration in real and model systems and carry implications for relations between integrated information, consciousness, and other neurocognitive processes. However, our findings pose challenges for theories that ascribe physical meaning to the measured quantities

An extended case study on the phenomenology of sequence-space synesthesia

Investigation of synesthesia phenomenology in adults is needed to constrain accounts of developmental trajectories of this trait. We report an extended phenomenological investigation of sequence-space synesthesia in a single case (AB). We used the Elicitation Interview (EI) method to facilitate repeated exploration of AB's synesthetic experience. During an EI the subject's attention is selectively guided by the interviewer in order to reveal precise details about the experience. Detailed analysis of the resulting 9 h of interview transcripts provided a comprehensive description of AB's synesthetic experience, including several novel observations. For example, we describe a specific spatial reference frame (a "mental room") in which AB's concurrents occur, and which overlays his perception of the real world (the "physical room"). AB is able to switch his attention voluntarily between this mental room and the physical room. Exemplifying the EI method, some of our observations were previously unknown even to AB. For example, AB initially reported to experience concurrents following visual presentation, yet we determined that in the majority of cases the concurrent followed an internal verbalization of the inducer, indicating an auditory component to sequence-space synesthesia. This finding is congruent with typical rehearsal of inducer sequences during development, implicating cross-modal interactions between auditory and visual systems in the genesis of this synesthetic form. To our knowledge, this paper describes the first application of an EI to synesthesia, and the first systematic longitudinal investigation of the first-person experience of synesthesia since the re-emergence of interest in this topic in the 1980's. These descriptions move beyond rudimentary graphical or spatial representations of the synesthetic spatial form, thereby providing new targets for neurobehavioral analysis

[Letter] Misunderstandings regarding the application of Granger causality in neuroscience

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