Coding Theory Research Articles

Posttraumatic reexperiencing and alcohol use: Mediofrontal theta as a neural mechanism for negative reinforcement.

Over half of U.S. military veterans with posttraumatic stress disorder (PTSD) use alcohol heavily, potentially to cope with their symptoms. This study investigated the neural underpinnings of PTSD symptoms and heavy drinking in veterans. We focused on brain responses to salient outcomes within predictive coding theory. This framework suggests the brain generates prediction errors (PEs) when outcomes deviate from expectations. Alcohol use might provide negative reinforcement by reducing the salience of negatively valenced PEs and dampening experiences like loss. We analyzed electroencephalography responses to unpredictable gain/loss feedback in n = 82 veterans of Operations Enduring and Iraqi Freedom. We used time-frequency principal components analysis of event-related potentials to isolate neural responses indicative of PEs, identifying mediofrontal theta linked to losses (feedback-related negativity) and central delta associated with gains (reward positivity). Intrusive reexperiencing symptoms of PTSD were associated with intensified mediofrontal theta signaling during losses, suggesting heightened negative PE sensitivity. Conversely, increased hazardous alcohol use was associated with reduced theta responses, implying a dampening of these negative PEs. The separate delta-reward positivity component showed associations with alcohol use but not PTSD symptoms. The findings suggest a common neural component of PTSD and hazardous alcohol use involving altered PE processing. We suggest that reexperiencing enhances the intensity of salient negative PEs, while chronic alcohol use may reduce their intensity, thereby providing negative reinforcement by muting posttraumatic distress and associated brain responses. Modifying the mediofrontal theta response could address the intertwined nature of PTSD symptoms and alcohol use, providing new avenues for treatment. (PsycInfo Database Record (c) 2025 APA, all rights reserved).

Localizing hierarchical prediction errors and precisions during an oddball task with volatility: Computational insights and relationship with psychosocial functioning in healthy individuals

Abstract The auditory mismatch negativity (MMN) has been widely used to investigate deficits in early auditory information processing, particularly in psychosis. Predictive coding theories suggest that impairments in sensory learning may arise from disturbances in hierarchical message passing, likely due to aberrant precision-weighting of prediction errors (PEs). This study employed a modified auditory oddball paradigm with varying phases of stability and volatility to disentangle the impact of hierarchical PEs on auditory MMN generation in 43 healthy controls (HCs). Single-trial EEG data were modeled with a hierarchical Bayesian model of learning to identify neural correlates of low-level PEs about tones and high-level PEs about environmental volatility. Our analysis revealed a reduced expression of the auditory MMN in volatile compared to stable phases of the paradigm. Additionally, lower Global Functioning (GF): Social scores were associated with a reduced difference waveform at 332 ms after stimulus presentation across the entire MMN paradigm. Further analysis revealed that this association was present during the volatile phase but not the stable phase of the paradigm. Source reconstruction suggested that the association between the stable difference waveform and psychosocial functioning originated in the left superior temporal gyrus. Finally, we found significant EEG signatures of both low- and high-level PEs and precision ratios. Our findings highlight the value of computational models in understanding the neural mechanisms involved in early auditory information processing and their connection to psychosocial functioning.

Quantitative Coding and Complexity Theory of Continuous Data: Part I: Motivation, Definition, Consequences

When encoding real numbers as (necessarily infinite) bit-strings, the naïve binary/decimal expansion is well-known [ doi:10.1112/plms/s2-43.6.544 ] computably “ un reasonable”, rendering, for example, tripling qualitatively discontinuous on Cantor’s sequence space. Encoding reals as sequences of (finite integer numerators and denominators, in binary, of) rational approximations does make common operations qualitatively computable, yet admits no bounds on their computational complexity/quantitative continuity. Dyadic approximations, on the other hand, are known polynomially, and signed binary expansions even linearly, “reasonable” in a rigorous sense recalled in the introduction of this work. But how to distinguish between un/suitable encodings of spaces common in Calculus beyond the reals, such as Banach or Sobolev? With respect to qualitative computability/continuity on topological spaces, the technical condition of admissibility had been identified [ doi:10.1016/0304-3975(85)90208-7 ] for an encoding over Cantor space (historically called a representation ) to be “reasonable” [ doi:10.1007/978-3-030-59234-9_9 ] . Roughly speaking, admissibility requires the representation to be (i) continuous, and to be (ii) maximal with respect to continuous reduction. Admissible representations exist for a large class of spaces. And for (precisely) these does the Kreitz–Weihrauch—sometimes aka Main —Theorem of Computable Analysis hold, which characterizes continuity of functions by continuity of mappings translating codes, so-called realizers . We refine qualitative computability/continuity on topological spaces to quantitative continuity/complexity on metric spaces by proposing a notion, and investigating the properties, of polynomially/linearly admissible representations. Roughly speaking, these are (i) close to “optimally” continuous, namely linearly/polynomially relative to the space’s entropy, and they are (ii) maximal with respect to relative linear/polynomial quantitatively continuous reductions defined in the main text. Quantitatively admissible representations are closed under composition over generalized ground spaces beyond Cantor’s. Such representations exhibit a quantitative strengthening of the qualitative Main Theorem , namely now characterizing quantitative continuity of functions by quantitative continuity of realizers. A large class of compact metric spaces is shown to admit polynomially admissible representations over compact ultra metric spaces, and some even a generalization of the linearly admissible signed binary encoding. Quantitative admissibility thus provides the desired criterion for complexity-theoretically “reasonable” encodings.

Enhancing economics education: the impact of upside-down drawing exercises on cognitive and analytical skills

As the world economy evolves, there is a growing need for educational methods that foster students’ creative problem-solving abilities. This study examines integrating Betty Edwards’ Upside-Down Drawing Exercise (UDE) into economics education to enhance cognitive and analytical skills. Using a mixed-methods approach with 90 economics students, the study reveals that the UDE helped solidify students’ understanding of theoretical economic concepts, promoting holistic and intuitive thinking. Specifically, the study focused on creativity, creative thinking, decision-making processes, thinking outside the box (innovative thinking), and brain functions in the hemispheres. Semi-structured interviews and Python-based template matching identified patterns in student responses and were analyzed using MAXQDA software. Results show significant improvements in understanding theoretical economic concepts, advocating for including creative exercises in the curriculum. Grounded in Dual Coding Theory and Cognitive Load Theory, this study hypothesizes that engaging in the UDE reduces cognitive load and enhances mental and analytical skills.

Beyond inter- and transdisciplinarity

Abstract While English-medium instruction (EMI) is growing rapidly as a field of practice, there is a lack of agreement around its conceptual and terminological boundaries, and its purposes are often ill defined. To deal with the complexity of the phenomena it addresses, it has been argued that EMI should adopt an interdisciplinary or transdisciplinary perspective. This conceptual article adopts a different position, arguing that EMI is best seen as an example of a “practical assemblage” (Pennycook, 2024), which draws on different epistemic resources to engage with its own set of problems, rather than vying to become a discipline in itself. Using the sociological lens of Legitimation Code Theory (Maton, 2014), the article proposes a framework for positioning EMI as an autonomous field of inquiry, addressing its own problem-situations and research questions. The analysis finds that, rather than building boundaries around itself, EMI as a practical assemblage would be better placed to open itself to ideas from other domains of enquiry while maintaining its autonomy in working on its own problems for its own purposes.

Over-the-Air Distributed Matrix-Vector Multiplication with Analog Coding

Over-the-Air Distributed Matrix-Vector Multiplication with Analog Coding

Representation and Ideology of Feminism in the Remake of the First Indonesian Heroine Character "Sri Asih"

The figure of Sri Asih became a pioneer in the symbolism of women's strength free from the influence of marital status, which was a reaction to the strong patriarchal culture in Indonesia. The figure of Sri Asih was then remade by Studio Bumi Langit and shown in Indonesian cinemas in 2022. The figure of Sri Asih was chosen because she is the first superhero figure from Indonesia. The aspects studied are the elements that form an identity, such as the representation of beauty, characteristics, and the role of women that appear in the figure of Sri Asih. This study uses a descriptive qualitative method and John Fiske's code theory. The urgency of this study is to reveal how the figure of Sri Asih is able to reconstruct the values ​​of women's identity in Indonesian society in the millennial era. The purpose is to explain what codes of reality, representation, and ideology exist in the figure of Sri Asih, and the research study results are the ideas for applying John Fiske's code theory to the figure of Sri Asih. In conclusion, the ideology of feminism in the character of Sri Asih is represented in the form of women's empowerment, gender equality, rejection of violence against women and the collapse of gender stereotypes.

Whose ‘useful’ is it anyway? Considering the complexity of ‘useful feedback’ to improve the feedback dialogue

ABSTRACT The concept of ‘useful feedback’ is often used in the literature and practice without fully acknowledging the many (and sometimes conflicting) meanings embedded in it. This conceptual paper, using the Legitimation Code Theory (LCT) dimension of Semantics, aims to unpack the complexity within the idea of ‘useful feedback’ to improve the feedback dialogue between staff and students. In this paper, we organise the notion of ‘useful’ around five central nodes, namely the purpose of feedback, the characteristics of feedback, the implementability of feedback, the feedback giver, and the feedback receiver. A Feedback Usefulness Tool is presented that may be used to further feedback conversations, training, and research, and highlights that ‘useful feedback’ may be contextual, complex, and contradictory.

Using Legitimation Code Theory to Underpin the Development of Undergraduate Nursing Students' Breastfeeding Knowledge: A Qualitative Study.

To explore how undergraduate nursing students develop knowledge during a breastfeeding module. A qualitative study using a single case-study approach. This study was conducted in Australia over 2 years during the period between July 2021 and December 2022. Semi-structured interviews and artefact collection were conducted with a purposive sample of undergraduate nurses (n = 10) who completed a paediatric elective subject that included a breastfeeding module. Thematic and content analysis were used. The specialisation dimension in Legitimation Code Theory (LCT) was used for the content analysis, and students' data was mapped on the specialisation plane. This study reveals how participants developed knowledge by linking personal breastfeeding experiences to theoretical components within the nursing program. Using the LCT dimension of specialisation, this study provides new insights into how participants move through distinct quadrants of the specialisation plane. Learners tour between the knowledge, knower, and elite quadrants of the plane as they integrate their knowledge. The research maps the journey towards becoming the 'right kind of knower' and reveals how personal experience and theoretical knowledge intersect to create disciplinary expertise. This study advances the LCT dimension of specialisation by illustrating the fluid, non-linear nature of knowledge acquisition and knower development. This study highlights the value of integrating personal experiences into nursing education, demonstrating how students use these to build knowledge and professional identity. The findings emphasise the dynamic knowledge development process in preparing future healthcare professionals. Integrating lived experiences and interprofessional education equips nurses to address complex health issues, leading to more effective, personalised care and better health outcomes for breastfeeding mothers and infants. This approach signals a transformative shift in nursing education. By personalising and contextualising learning, fostering reflective practice, deepening disciplinary knowledge, and promoting a collaborative practice environment, this approach enriches nursing education. The consolidated criteria for reporting qualitative research (COREQ). No patient or public contribution.

Heights of error-correcting codes

In this work, we investigate the evaluation of odd polynomials P defined on a finite field on the class of error-correcting codes C. We exploit the correspondence between codes and Tanner graphs. Thus, we formally define P(C), a polynomial code. Then the new notion of height of a code emerges, whose properties are studied. We extended the lower bound of Tanner on the minimum distance of a code to the case of a polynomial code, by using spectral graph theory. Computer algebra software enable us to give numerical results to illustrate the theory of polynomial codes for various classes of error-correcting codes.

Exploring the Themes of Horrors of The War, Power and Hegemony in The Manga “Barefoot Gen Vol. 1” in the Light of Dual Coding Theory

This study explores the themes of hegemony, power dynamics, and the horrors of war in the manga "Barefoot Gen Vol. 1" using Allan Paivio's Dual Coding Theory as a framework. A semi-autobiographical historical manga titled "Barefoot Gen Volume 1" by Keiji Nakazawa is based on the Hiroshima bombing and all the hardships people endured before and after the attack. The research gap that has been identified highlights the lack of previous applications of Dual Coding Theory to Barefoot Gen Volume 1 as well as the lack of acknowledgement of manga as a helpful information source with visually appealing content. Six participants – comprising both manga-experienced and non-manga readers –were recruited using a semi-structured interview technique with deliberate sampling to assess images' significance in comprehension. A thematic analysis of the provided interviews was conducted using the Braun and Clarke model. The findings highlight visuals' pivotal role in improving comprehension of narratives related to history or war and show broad consensus regarding the theory's applicability. By filling in the gaps in the literature, this work advances knowledge about the multifaceted role manga plays in narrating historical events and capturing readers' attention through a dual-channel cognitive process.

Genome Galaxy Identified by the Circular Code Theory.

The genome galaxy identified in bacteria is studied by expressing the reading frame retrieval (RFR) function according to the YZ-content (GC-, AG- and GT-content) of bacterial codons. We have developed a simple probabilistic model for ambiguous sequences in order to show that the RFR function is a measure of the gene reading frame retrieval. Indeed, the RFR function increases with the ratio of ambiguous sequences and the ratio of ambiguous sequences decreases when the codon usage dispersion increases. The classical GC-content is the best parameter for characterizing the upper arm, which is related to bacterial genes with a lowGC-content, and the lower arm, which is related to bacterial genes with a highGC-content. The galaxy center has aGC-content around 0.5. Then, these results are confirmed by expressing the GC-content of bacterial codons as a function of the codon usage dispersion. Finally, the bacterial genome galaxy is better described with the GC3-content in the 3rd codon site compared to the GC1-content and GC2-content in the 1st and 2nd codons sites, respectively. Whereas the codon usage is used extensively by biologists, its dispersion, which is an important parameter to reveal this genome galaxy, is surprisingly little known and unused. Therefore, we have developed a mathematical theory of codon usage dispersion by deriving several formulæ. It shows three important parameters in codon usage: the minimum and maximum codon probabilities and the number of codons with high frequency, i.e. with a probability at least1/64. By applying this theory to the evolution of the genetic code, we see that bacteria have optimised the number of codons with high frequency to maximise the codon dispersion, thus maximising the capacity to retrieve the reading frame in genes. The derived formulæ of dispersion can be easily extended to any weighted code over a finite alphabet.

‘I don’t need professional development; I want institutional development’: legitimising marginalised epistemic capital that disrupts generative AI discourse

ABSTRACT Responding to GenAI technologies, academics press for PLD that informs pedagogical practice and policy development. However, insufficient critical evaluation of whose knowledge informs this and its underlying complexity has resulted in excessively reductive offerings that either champion specific tools or advocate for their prohibition. Engaging with critically complex perspectives provides an opportunity to deepen discourse through untapped funds of knowledge, while considering PLD’s broader role in policy and institutional development. English for Academic Purposes (EAP) lecturers are typically peripheral within universities, positioned as a remedial or technical service who ‘fix’ academic integrity and student language development issues. GenAI disruption has created a heightened demand for language expertise, offering an opportunity for EAP lecturers to advocate for the critical complexity underpinning their funds of knowledge. Using Legitimation Code Theory (LCT) within a Delphi study with senior EAP academics, we argue that engaging with critical complexity can empower institutionally marginalised expertise. The panel established design principles and actionable measures to (i) move beyond individualistic PLD and (ii) formalise the voicing and valuing of diverse expertise through collaboration across institutional hierarchies. Taken together, these offer ways to leverage epistemic relations to disrupt entrenched power structures through transformative PLD and thus catalyse institutional change.

Computational Algebra, Coding Theory, and Cryptography: Theory and Applications

The primary aim of this Special Issue is to explore innovative encoding and decoding procedures that leverage various algebraic structures to enhance error-control coding techniques [...]

Diverse Frontoparietal Connectivity Supports Semantic Prediction and Integration in Sentence Comprehension.

Predictive processing in the parietal, temporal, frontal, and sensory cortex allows us to anticipate future meanings to maximize the efficiency of language comprehension, with the temporoparietal junction (TPJ) and inferior frontal gyrus (IFG) thought to be situated toward the top of a predictive hierarchy. Although the regions underpinning this fundamental brain function are well-documented, it remains unclear how they interact to achieve efficient comprehension. To this end, we recorded functional magnetic resonance imaging (fMRI) in 22 participants (11 males) while they comprehended sentences presented part by part, in which we manipulated the constraint provided by sentential contexts on upcoming semantic information. Using this paradigm, we examined the connectivity patterns of bilateral TPJ and IFG during anticipatory phases (i.e., before the onset of targets) and integration phases (i.e., after the onset of targets). When upcoming semantic content was highly predictable in strong constraint contexts, both the left TPJ and bilateral IFG showed stronger visual coupling, while the right TPJ showed stronger connectivity with regions within control, default mode, and visual networks, including the IFG, parahippocampal gyrus, posterior cingulate, and fusiform gyrus. These connectivity patterns were weaker when predicted semantic content appeared, in line with predictive coding theory. Conversely, for less-predictable content, these connectivity patterns were stronger during the integration phase. Overall, these results suggest that both top-down semantic prediction and bottom-up integration during predictive processing are supported by flexible coupling of frontoparietal regions with control, memory, and sensory systems.

Individual and Sociocultural Determinants of Suicide in an Indian Community: A Qualitative Study

India has a significant number of people exposed to suicide. The traumatic effects of these experiences, and the healing process of suicide survivors are poorly understood. We investigated suicide survivors’ experiences and post-suicide healing. Interviews were conducted with suicide survivors who received different types of support—home visits before COVID-19 and telephonic outreach during lockdown. Two researchers used “active listening” and “human capacity for response” theory for deductive and inductive coding. Personal and socio-cultural factors affect recovery after suicide. Protective factors include religious or spiritual beliefs, as well as a sense of life purpose. Factors that hinder recovery include lack of social support, unmet need for compassionate understanding, insufficient acknowledgment of personal struggles, and social stigma. Interventions for suicide survivors should consider personal and cultural factors, including psychological and religious needs. Interventions should create safe environments that allow individuals to draw on personal and social resources for healing.

Deterministic fault-tolerant connectivity labeling scheme

AbstractThe f-fault-tolerant connectivity labeling (f-FTC labeling) is a scheme of assigning each vertex and edge with a small-size label such that one can determine the connectivity of two vertices s and t under the presence of at most f faulty edges only from the labels of s, t, and the faulty edges. This paper presents a new deterministic f-FTC labeling scheme attaining $$O(f^2 \textrm{polylog}(n))$$ O ( f 2 polylog ( n ) ) -bit label size and a polynomial construction time, which settles the open problem left by Dory and Parter (in: Proceedings of the 2021 ACM symposium on principles of distributed computing (PODC), pp 445–455, 2021). The key ingredient of our construction is to develop a deterministic counterpart of the graph sketch technique by Ahn et al. (in: Proceedings of the 31st ACM SIGMOD-SIGACT-SIGAI symposium on principles of database systems (PODS), pp 5–14, 2012), via some natural connection with the theory of error-correcting codes. This technique removes one major obstacle in de-randomizing the Dory–Parter scheme. The whole scheme is obtained by combining this technique with a new deterministic graph sparsification algorithm derived from the seminal $$\epsilon $$ ϵ -net theory, which is also of independent interest. As byproducts, our result deduces the first deterministic fault-tolerant approximate distance labeling scheme with a non-trivial performance guarantee and an improved deterministic fault-tolerant compact routing. The authors believe that our new technique is potentially useful in the future exploration of more efficient FTC labeling schemes and other related applications based on graph sketches.

Learning probability distributions of sensory inputs with Monte Carlo predictive coding.

It has been suggested that the brain employs probabilistic generative models to optimally interpret sensory information. This hypothesis has been formalised in distinct frameworks, focusing on explaining separate phenomena. On one hand, classic predictive coding theory proposed how the probabilistic models can be learned by networks of neurons employing local synaptic plasticity. On the other hand, neural sampling theories have demonstrated how stochastic dynamics enable neural circuits to represent the posterior distributions of latent states of the environment. These frameworks were brought together by variational filtering that introduced neural sampling to predictive coding. Here, we consider a variant of variational filtering for static inputs, to which we refer as Monte Carlo predictive coding (MCPC). We demonstrate that the integration of predictive coding with neural sampling results in a neural network that learns precise generative models using local computation and plasticity. The neural dynamics of MCPC infer the posterior distributions of the latent states in the presence of sensory inputs, and can generate likely inputs in their absence. Furthermore, MCPC captures the experimental observations on the variability of neural activity during perceptual tasks. By combining predictive coding and neural sampling, MCPC can account for both sets of neural data that previously had been explained by these individual frameworks.

Rethinking contextualization in physics education: a perspective from semantic gravity

This study examines the applicability of Semantic Gravity (SG), a concept derived from Legitimation Codes Theory, as a tool to enhance contextualization in physics teaching. SG offers a framework for analyzing how educators and students navigate between abstract concepts and concrete applications, addressing one of the persistent challenges in physics education: the gap between theoretical understanding and practical application. The study reveals that implementing SG presents both significant opportunities and considerable challenges. Opportunities include the development of a more profound and transferable understanding of physics concepts, more inclusive teaching practices, and more authentic assessment methods. Challenges encompass teachers' need for a deep understanding of the concept, adaptation of existing curricular materials, and development of rigorous methods to assess their impact. Research suggests integrating SG into teacher training and curriculum design could significantly transform physics teaching. However, further empirical research is required to validate its effectiveness fully in diverse educational contexts.

Computing MEMs and Relatives on Repetitive Text Collections

We consider the problem of computing the Maximal Exact Matches (MEMs) of a given pattern \(P[1\mathinner{.. }m]\) on a large repetitive text collection \(T[1\mathinner{.. }n]\) over an alphabet of size \(\sigma\) , which is represented as a (hopefully much smaller) run-length context-free grammar of size \(g_{rl}\) . We show that the problem can be solved in time \(O(m^{2}\log^{\epsilon}n)\) , for any constant \(\epsilon\gt0\) , on a data structure of size \(O(g_{rl})\) . Further, on a locally consistent grammar of size \(O(\delta\log\frac{n\log\sigma}{\delta\log n})\) , the time decreases to \(O(m\log m(\log m+\log^{\epsilon}n))\) . The value \(\delta\) is a function of the substring complexity of \(T\) and \(\Omega(\delta\log\frac{n\log\sigma}{\delta\log n})\) is a tight lower bound on the compressibility of repetitive texts \(T\) , so our structure has optimal size in terms of \(n\) , \(\sigma\) , and \(\delta\) . We extend our results to several related problems, such as finding \(k\) -MEMs, MUMs, rare MEMs, and applications. Categories and Subject Descriptors: E.1 [Data structures] ; E.2 [Data storage representations] ; E.4 [Coding and information theory]: Data compaction and compression; F.2.2 [Analysis of algorithms and problem complexity] : Nonnumerical algorithms and problems— Pattern matching, Computations on discrete structures, Sorting and searching