Richard Levins has advocated the scientific merits of qualitative modeling throughout his career. He believed an excessive and uncritical focus on emulating the models used by physicists and maximizing quantitative precision was hindering biological theorizing in particular. Greater emphasis on qualitative properties of modeled systems would help counteract this tendency, and Levins subsequently developed one method of qualitative modeling, loop analysis, to study a wide variety of biological phenomena. Qualitative modeling has been criticized for being conceptually (...) and methodologically problematic. As a clear example of a qualitative modeling method, loop analysis shows this criticism is indefensible. The method has, however, some serious limitations. This paper describes loop analysis, its limitations, and attempts to clarify the differences between quantitative and qualitative modeling, in content and objective. Loop analysis is but one of numerous types of qualitative analysis, so its limitations do not detract from the currently underappreciated and underdeveloped role qualitative modeling could have within science. (shrink)

Loop analysis is a method of qualitative modeling anticipated by Sewall Wright and systematically developed by Richard Levins. In Levins’ (1966) distinctions between modeling strategies, loop analysis sacrifices precision for generality and realism. Besides criticizing the clarity of these distinctions, Orzack and Sober (1993) argued qualitative modeling is conceptually and methodologically problematic. Loop analysis of the stability of ecological communities shows this criticism is unjustified. It presupposes an overly narrow view of qualitative modeling (...) and underestimates the broad role models play in scientific research, especially in helping scientists represent and understand complex systems. (shrink)

Reflexive observations and observations of reflexivity: such agendas are by now standard practice in anthropology. Dynamic feedback loops between self and other, cause and effect, represented and representamen may no longer seem surprising; but, in spite of our enhanced awareness, little deliberate attention is devoted to modeling or grounding such phenomena. Attending to both linguistic and extra-linguistic modalities of chiasmus (the X figure), a group of anthropologists has recently embraced this challenge. Applied to contemporary problems in linguistic anthropology, chiasmus (...) functions to highlight and enhance relationships of interdependence or symbiosis between contraries, including anthropology’s four fields, the nature of human being and facets of being human. (shrink)

Recent rapid advances in Artificial Intelligence and Machine Learning have raised many questions about the regulatory and governance mechanisms for autonomous machines. Many commentators, scholars, and policy-makers now call for ensuring that algorithms governing our lives are transparent, fair, and accountable. Here, I propose a conceptual framework for the regulation of AI and algorithmic systems. I argue that we need tools to program, debug and maintain an algorithmic social contract, a pact between various human stakeholders, mediated by machines. To achieve (...) this, we can adapt the concept of human-in-the-loop from the fields of modeling and simulation, and interactive machine learning. In particular, I propose an agenda I call society-in-the-loop, which combines the HITL control paradigm with mechanisms for negotiating the values of various stakeholders affected by AI systems, and monitoring compliance with the agreement. In short, ‘SITL = HITL + Social Contract.’. (shrink)

In the recent history of psychology and cognitive neuroscience, the notion of habit has been reduced to a stimulus-triggered response probability correlation. In this paper we use a computational model to present an alternative theoretical view (with some philosophical implications), where habits are seen as self-maintaining patterns of behavior that share properties in common with self-maintaining biological processes, and that inhabit a complex ecological context, including the presence and influence of other habits. Far from mechanical automatisms, this organismic and self-organizing (...) concept of habit can overcome the dominating atomistic and statistical conceptions, and the high temporal resolution effects of situatedness, embodiment and sensorimotor loops emerge as playing a more central, subtle and complex role in the organization of behavior. The model is based on a novel “iterant deformable sensorimotor medium” (IDSM), designed such that trajectories taken through sensorimotor-space increase the likelihood that in the future, similar trajectories will be taken. We couple the IDSM to sensors and motors of a simulated body and environment and show that under certain conditions, the IDSM forms self-maintaining patterns of activity that operate across the IDSM, the body, and the environment. We present various environments and the resulting habits that form in them. The model acts as an abstraction of habits at a much needed sensorimotor “meso-scale” between microscopic neuron-based models and macroscopic descriptions of behavior. Finally, we discuss how this model and extensions of it can help us understand aspects of behavioral self-organization, historicity and autonomy that remain out of the scope of contemporary representationalist frameworks. (shrink)

In the present study, we have demonstrated hysteresis phenomena in the excitability of single, enzymatically dissociated guinea pig ventricular myocytes. Membrane potentials were recorded with patch pipettes in the whole-cell current clamp configuration. Repetitive stimulation with depolarizing current pulses of constant cycle length and duration but varying strength led to predictable excitation (1:l) and non-excitation (1:0) patterns depending on current strength. In addition, transition between patterns depended on the direction of current intensity change and stable hysteresis loops were obtained in (...) stimulus:response pattern vs. current intensity plots in 14 cells. Increase of pulse duration and decrease of stimulation rate contributed to a reduction in hysteresis loop areas. Changes in amplitude and shape of the subthreshold responses during the transitions from one stable pattern to the other, suggested that activity led to an increase in membrane resistance, particularly in the voltage domain between resting potential, and threshold. Therefore, we modelled the dynamic behaviour of the single cells as a function of diastolic membrane resistance, using previously published analytical solutions. Numerical iteration of the analytical model equations closely reproduced the experimental hysteresis loops in both qualitative and quantitative ways. In particular, the effect of stimulation frequency on the model was similar to the experimental findings. The overall study suggests that the excitability pattern of guinea pig ventricular myocytes accounts for hysteresis and bistabilities when current intensity is allowed to fluctuate around threshold levels. (shrink)

In this article, the authors present the framework of a model that integrates strategic product development decisions with the product's impact on future conditions of resources and the environment. The impact of a product on stocks of nonrenewable sources and sinks is linked in a feedback loop to the cost of manufacturing and using the product and to the end-users' preference for a sustainable product. Two product development scenarios are analyzed to illustrate the model's capabilities. These cases represent widely (...) different market conditions and strategies in product development vis-à-vis sustainable product design and manufacturing. Future work must focus on application of the present framework to cases of realistic products and markets to further develop the model as a useful decision-making tool. The model might also serve as a means of analyzing normative resource-cost scenarios in regulatory policy mechanisms for sustainability. (shrink)

Modeling of evolution and development of language has principally utilized mature units of spoken language, phonemes and words, as both targets and inputs. This approach cannot address the earliest phases of development because young infants are unable to produce such language features. We argue that units of early vocal development—protophones and their primitive illocutionary/perlocutionary forces—should be targeted in evolutionary modeling because they suggest likely units of hominin vocalization/communication shortly after the split from the chimpanzee/bonobo lineage, and because early (...) development of spontaneous vocal capability is a logically necessary step toward vocal language, a root capability without which other crucial steps toward vocal language capability are impossible. Modeling of language evolution/development must account for dynamic change in early communicative units of form/function across time. We argue for interactive contributions of sender/infants and receiver/caregivers in a feedback loop involving both development and evolution and propose to begin computational modeling at the hominin break from the primate communicative background. (shrink)

Vector autoregression (VAR) modeling allows probing bidirectional relationships in gender/sex development and may support hypothesis testing following multi-modal data collection. We show VAR in three lights: supporting a hypothesis, rejecting a hypothesis, and opening up new questions. To illustrate these capacities of VAR, we reanalyzed longitudinal data that recorded dyadic mother-infant interactions for 15 boys and 15 girls aged 3 to 11 months of age. We examined monthly counts of 15 infant behaviors and 13 maternal behaviors (Seifert et al., (...) 1994). VAR models demonstrated that infant crawling predicted a subsequently close feedback loop from mothers of boys but a subsequently open ended, branched response from mothers of girls. A different finding showed that boys’ standing independently later predicted significant later increases of four maternal behaviors: rocking/jiggling, lifting, affectionate touching, and stimulation of infant gross-motor activity. In contrast, crawling by girls led mothers to later decrease the same maternal behaviors. Thus, VAR might allow us to identify how mothers respond differently during daily interactions depending on infant gender/sex. The present work intends mainly to showcase the VAR method in the specific context of the empirical study of gender/sex development. (shrink)

Introduction. Analyzing the popularity of television series in the XXI century makes it possible to conclude that this format of video production has changed significantly in comparison with the second half of the XX century: the fascinating (seductive, enchanting) function in it dominates over the narrative-entertaining one. At the same time, not only the individual performer becomes the instrument of fascination, but the entire specially created visual environment of the series. This situation makes it possible for a researcher, on the (...) one hand, to identify the most significant emotional and psychological needs of modern society and thereby clarify some of the philosophical and anthropological aspects of today’s culture. On the other hand, it makes it possible to classify serial production on the basis of hedonistic values, that is, to identify the basic models by which the fascinating environments of popular serials are created. One of such models, the existential one, becomes the subject of special attention in the article. The purpose of the study is to present the existential model as one of five generative models of the screen spectacle on the basis of analyzing visual cues from the 2020 television series (Tales from the Loop. Amazon Studio, Fox 21 Television Studios, USA, 2020); to consider «Tales from the Loop» as a screen model that gives a viewer the experience of philosophical and anthropological reflection. Methods: In the course of the study, the authors use general scientific methods of analysis and synthesis; the method of phenomenological reduction, which makes it possible to record the sensually perceived qualities of object-spatial screen images; a hermeneutic method that makes it possible, on the basis of visible sign structures, to reveal the deep intentions of a visual image. The scientific novelty lies in the fact that we consider the television series as an anthropological phenomenon, not only reflecting the interests, aspirations and values of the society, but also modeling the society through a deep suggestive (fascinating) influence. A typology of such environments is created, corresponding to basic hedonistic needs and reflecting the degree of demand for certain states of pleasure in modern society. The method of creating a visual environment that draws a viewer into a state of philosophical reflection, which in this case is interpreted as a way to achieve «the fulfillment of being» (Aristippus), is specially clarified. Results. In the course of the analysis, the authors applied to television production a hedonistic-ontological typology of a visual image, which includes five generative models; a targeted analysis of the popularity of the most influential television series of the 2000s – 2020s was carried out, taking into account the level and causes of spectator fascination; as exemplified by the television series «Stories from the Loop» and in the course of the analysis of its visual components, it becomes clear how the modern series succeeds in involving a viewer in a state of philosophical reflection. Conclusions. The philosophical and anthropological analysis of the modern television series shows that the entertainment and narrative functions that are relevant for the twentieth century have been replaced by the function of fascination, a deep influence on a viewer at a suggestive level. In this case, the purpose of fascination is to involve a viewer not only in hedonistic states of pleasure, but also in states of faith or philosophical reflection. (shrink)

Literacy is an essential skill. Learning to read is a requirement for becoming a self-providing human being. However, while spoken language is acquired naturally with exposure to language without explicit instruction, reading and writing need to be taught explicitly. Decades of research have shown that well-structured teaching of phonological awareness, letter knowledge, and letter-to-sound mapping is crucial in building solid foundations for the acquisition of reading. During the COVID-19 pandemic, children worldwide did not have access to consistent and structured teaching (...) and are, as a consequence, predicted to be behind in the development of their reading skills. Subsequent evidence confirms this prediction. With the best evidence-based practice in mind, we developed an online version of a well-structured early literacy training program for 5-year-old children. This 2-week online Reading Camp program is designed for pre-K children. It incorporates critical components of the fundamental skills essential to learning to read and is taught online in an interactive, multi-sensory, and peer-learning environment. We measure the participants’ literacy skills and other related skills before and after participating in the online Reading Camp and compare the results to no-treatment controls. Results show that children who participated in the online Reading Camp improved significantly on all parameters in relation to controls. Our results demonstrate that a well-structured evidence-based reading instruction program, even if online and short-term, benefits 5-year-old children in learning to read. With the potential to scale up this online program, the evidence presented here, alongside previous evidence for the efficacy of the in-person program, indicates that the online Reading Camp program is effective and can be used to tackle a variety of questions regarding structural and functional plasticity in the early stages of reading acquisition. (shrink)

This study aimed to explore practices and strategies that have successfully reduced time-to-proficiency of the workforce in large multinational organisations and develop a model based on them. The central research question of this study was: How can organisations accelerate time-to-proficiency of employees in the workplace? The study addressed three aspects: the meaning of accelerated proficiency, as seen by business leaders; the business factors driving the need for shorter time-to-proficiency and benefits accrued from it; and practices and strategies to shorten time-to-proficiency (...) of the workforce. 85 participants (n=85) from 7 countries who represented 10 economic sectors, 20 business sectors and 28 industry groups contributed 66 successful bounded project cases. A qualitative research approach was used. Data were collected through in-depth interviews with project leaders and by collecting additional project case documents. Data were analysed using thematic analysis to identify the themes in the data. Matrix analysis was then used to perform within-case and cross-case analysis to compare the project cases. 11 overarching themes were developed from the data analysis, out of which two overarching themes explained the characteristics of job-role proficiency and accelerated proficiency, while three overarching themes described the magnituide and scale of time-to-proficiency business problem, business drivers for accelerating proficiency and business benefits of reduced time-to-proficiency. Six overarching themes revealed the business practices employed by organisations to reduce time-to-proficiency: (1) Defining business-driven proficiency measures in terms of expected business outcomes from a job role; (2) Developing a proficiency reference map of all the inputs, conditions and roadblocks that determine or influence how required business outcomes are being produced in a job role; (3) Sequencing an efficient proficiency path of activities and experiences ordered to produce the desired business outcomes in the shortest possible time; (4) Manufacturing accelerated contextual experiences by leveraging on-the-job opportunities or training interventions in a compressed time-frame; (5) Promoting an active emotional immersion through engagements, consequences, stakes, feedback and proficiency assessments; and (6) Setting up a proficiency eco-system, providing timely support to performers while doing the job such as enabling job environment, highly involved manager, structured mentoring from experts, purposeful social connectivity with peers, leveraging subject matter experts and on-demand performance support systems. Organisations orchestrated these six business practices as an input-output-feedback system to reduce time-to-proficiency of the workforce. A conceptual model (Accelerated Proficiency Model) was developed representing interactions among six business-level practices/processes as a closed-loop system to explain the concept and process of accelerated proficiency in the workplace. These practices were implemented through a set of twenty-four strategies proven successful in various contexts. The strategies employed were much beyond the boundaries of conventional training interventions. The job itself acted as the primary mechanism to accelerate proficiency. A two-level hierarchical framework (6/24 framework of strategies) was also constructed in the form of a checklist consisting of six practices and twenty-four strategies for practitioners. Overall, the findings of this research study contribute significantly to the body of knowledge on accelerated proficiency. In particular, the conceptual model and the framework developed in this study can be implemented across a range of contexts, business sectors, job types and settings to reduce time-to-proficiency of the workforce. (shrink)

Loop regions in proteins have traditionally been described as ‘random coil’, although they are known to adopt well‐defined conformations in most globular proteins. In this contribution we summarize the results of detailed analysis of the structures and sequences of these loop regions in proteins of known three‐dimensional structure. We also describe how these results can be used as an aid to protein design, modification and modelling.

It was, until recently, accepted that the two classes of acetylcholine (ACh) receptors are distinct in an important sense: muscarinic ACh receptors signal via heterotrimeric GTP binding proteins (G proteins), whereas nicotinic ACh receptors (nAChRs) open to allow flux of Na+, Ca2+, and K+ ions into the cell after activation. Here we present evidence of direct coupling between G proteins and nAChRs in neurons. Based on proteomic, biophysical, and functional evidence, we hypothesize that binding to G proteins modulates the activity (...) and signaling of nAChRs in cells. It is important to note that while this hypothesis is new for the nAChR, it is consistent with known interactions between G proteins and structurally related ligand‐gated ion channels. Therefore, it underscores an evolutionarily conserved metabotropic mechanism of G protein signaling via nAChR channels.Also watch the Video Abstract. (shrink)

It was, until recently, accepted that the two classes of acetylcholine (ACh) receptors are distinct in an important sense: muscarinic ACh receptors signal via heterotrimeric GTP binding proteins (G proteins), whereas nicotinic ACh receptors (nAChRs) open to allow flux of Na+, Ca2+, and K+ ions into the cell after activation. Here we present evidence of direct coupling between G proteins and nAChRs in neurons. Based on proteomic, biophysical, and functional evidence, we hypothesize that binding to G proteins modulates the activity (...) and signaling of nAChRs in cells. It is important to note that while this hypothesis is new for the nAChR, it is consistent with known interactions between G proteins and structurally related ligand‐gated ion channels. Therefore, it underscores an evolutionarily conserved metabotropic mechanism of G protein signaling via nAChR channels.Also watch the Video Abstract. (shrink)

A novel fuzzy control scheme with adaptation algorithms is developed for robot manipulators’ system. At the beginning, one adjustable parameter is introduced in the fuzzy logic system, the robot manipulators system with uncertain nonlinear terms as the master device and a reference model dynamic system as the slave robot system. To overcome the limitations such as online learning computation burden and logic structure in conventional fuzzy logic systems, a parameter should be used in fuzzy logic system, which composes fuzzy logic (...) system with updated parameter laws, and can be formed for a new fashioned adaptation algorithms controller. The error closed-loop dynamical system can be stabilized based on Lyapunov analysis, the number of online learning computation burdens can be reduced greatly, and the different kinds of fuzzy logic systems with fuzzy rules or without any fuzzy rules are also suited. Finally, effectiveness of the proposed approach has been shown in simulation example. (shrink)

Top-down feedback does not benefit speech recognition; on the contrary, it can hinder it. No experimental data imply that feedback loops are required for speech recognition. Feedback is accordingly unnecessary and spoken word recognition is modular. To defend this thesis, we analyse lexical involvement in phonemic decision making. TRACE (McClelland & Elman 1986), a model with feedback from the lexicon to prelexical processes, is unable to account for all the available data on phonemic decision making. The modular Race model (Cutler (...) & Norris 1979) is likewise challenged by some recent results, however. We therefore present a new modular model of phonemic decision making, the Merge model. In Merge, information flows from prelexical processes to the lexicon without feedback. Because phonemic decisions are based on the merging of prelexical and lexical information, Merge correctly predicts lexical involvement in phonemic decisions in both words and nonwords. Computer simulations show how Merge is able to account for the data through a process of competition between lexical hypotheses. We discuss the issue of feedback in other areas of language processing and conclude that modular models are particularly well suited to the problems and constraints of speech recognition. Key Words: computational modeling; feedback; lexical processing; modularity; phonemic decisions; reading; speech recognition; word recognition. (shrink)

X‐chromosome inactivation ensures dosage compensation between the sexes in mammals by randomly choosing one out of the two X chromosomes in females for inactivation. This process imposes a plethora of questions: How do cells count their X chromosome number and ensure that exactly one stays active? How do they randomly choose one of two identical X chromosomes for inactivation? And how do they stably maintain this state of monoallelic expression? Here, different regulatory concepts and their plausibility are evaluated in the (...) context of theoretical studies that have investigated threshold behavior, ultrasensitivity, and bistability through mathematical modeling. It is discussed how a twofold difference between a single and a double dose of X‐linked genes might be converted to an all‐or‐nothing response and how mutually exclusive expression can be initiated and maintained. Finally, candidate factors that might mediate the proposed regulatory principles are reviewed. (shrink)

Neural organization: Structure, function, and dynamics shows how theory and experiment can supplement each other in an integrated, evolving account of the brain's structure, function, and dynamics. (1) Structure: Studies of brain function and dynamics build on and contribute to an understanding of many brain regions, the neural circuits that constitute them, and their spatial relations. We emphasize Szentágothai's modular architectonics principle, but also stress the importance of the microcomplexes of cerebellar circuitry and the lamellae of hippocampus. (2) Function: Control (...) of eye movements, reaching and grasping, cognitive maps, and the roles of vision receive a functional decomposition in terms of schemas. Hypotheses as to how each schema is implemented through the interaction of specific brain regions provide the basis for modeling the overall function by neural networks constrained by neural data. Synthetic PET integrates modeling of primate circuitry with data from human brain imaging. (3) Dynamics: Dynamic system theory analyzes spatiotemporal neural phenomena, such as oscillatory and chaotic activity in both single neurons and (often synchronized) neural networks, the self-organizing development and plasticity of ordered neural structures, and learning and memory phenomena associated with synaptic modification. Rhythm generation involves multiple levels of analysis, from intrinsic cellular processes to loops involving multiple brain regions. A variety of rhythms are related to memory functions. The Précis presents a multifaceted case study of the hippocampus. We conclude with the claim that language and other cognitive processes can be fruitfully studied within the framework of neural organization that the authors have charted with John Szentágothai. Key Words: cognitive maps; computational neuroscience; dynamics; hippocampus; memory; modular architectonics; neural modeling; neural organization; neural plasticity; rhythmogenesis; Szentágothai. (shrink)

We contrast reactive and endogenously active perspectives on brain activity. Both have been pursued continuously in neurophysiology laboratories since the early 20thcentury, but the endogenous perspective has received relatively little attention until recently. One of the many successes of the reactive perspective was the identification, in the second half of the 20th century, of the distinctive contributions of different brain regions involved in visual processing. The recent prominence of the endogenous perspective is due to new findings of ongoing oscillatory activity (...) in the brain at a wide range of time scales, exploiting such techniques as single-cell recording, EEG, and fMRI. We recount some of the evidence pointing to ways in which this endogenous activity is relevant to cognition and behavior. Our major objective is to consider certain implications of the contrast between the reactive and endogenous perspectives. In particular, we relate these perspectives to two different characterizations of explanation in the new mechanistic philosophy of science. In a basic mechanistic explanation, the operations of a mechanism are characterized qualitatively and as functioning sequentially until a terminating condition is realized. In contrast, a dynamic mechanistic explanation allows for non-sequential organization and emphasizes quantitative modeling of the mechanisms's behavior. For example, with appropriate parameter values a set of differential equations can be used to demonstrate ongoing oscillations in a system organized with feedback loops. We conclude that the basic conception of mechanistic explanation is adequate for reactive accounts of brain activity, but dynamical accounts are required to explain sustained, endogenous activity. (shrink)

The paper discusses how systems biology is working toward complex accounts that integrate explanation in terms of mechanisms and explanation by mathematical models—which some philosophers have viewed as rival models of explanation. Systems biology is an integrative approach, and it strongly relies on mathematical modeling. Philosophical accounts of mechanisms capture integrative in the sense of multilevel and multifield explanations, yet accounts of mechanistic explanation have failed to address how a mathematical model could contribute to such explanations. I discuss how (...) mathematical equations can be explanatorily relevant. Several cases from systems biology are discussed to illustrate the interplay between mechanistic research and mathematical modeling, and I point to questions about qualitative phenomena, where quantitative models are still indispensable to the explanation. Systems biology shows that a broader philosophical conception of mechanisms is needed, which takes into account functional-dynamical aspects, interaction in complex networks with feedback loops, system-wide functional properties such as distributed functionality and robustness, and a mechanism’s ability to respond to perturbations. I offer general conclusions for philosophical accounts of explanation. (shrink)

Real causal systems are complicated. Despite this, causal learning research has traditionally emphasized how causal relations can be induced on the basis of idealized events, i.e. those that have been mapped to binary variables and abstracted from time. For example, participants may be asked to assess the efficacy of a headache-relief pill on the basis of multiple patients who take the pill (or not) and find their headache relieved (or not). In contrast, the current study examines learning via interactions with (...) continuous dynamic systems, systems that include continuous variables that interact over time (and that can be continuously observed in real time by the learner). To explore such systems, we develop a new framework that represents a causal system as a network of stationary Gauss--Markov (``\OU'') processes and show how such \textit{OU networks} can express complex dynamic phenomena such as feedback loops and oscillations. To assess adult's abilities to learn such systems, we conducted an experiment in which participants were asked to identify the causal relationships of a number of OU networks, potentially carrying out multiple, temporally-extended interventions. We compared their judgments to a normative model for learning OU networks as well as a range of alternative and heuristic learning models from the literature. We found that, although participants exhibited substantial learning of such systems, they committed certain systematic errors. These successes and failures were best accounted for by a model that describes people as focusing on pairs of variables, rather than evaluating the evidence with respect to the full space of possible structural models. We argue that our approach provides both a principled framework for exploring the space of dynamic learning environments as well as new algorithmic insights into how people interact successfully with a continuous causal world. (shrink)

Online educational technologies offer opportunities for providing individualized feedback and detailed profiles of students' skills. Yet many technologies for mathematics education assess students based only on the correctness of either their final answers or responses to individual steps. In contrast, examining the choices students make for how to solve the equation and the ways in which they might answer incorrectly offers the opportunity to obtain a more nuanced perspective of their algebra skills. To automatically make sense of step‐by‐step solutions, we (...) propose a Bayesian inverse planning model for equation solving that computes an assessment of a learner's skills based on her pattern of errors in individual steps and her choices about what sequence of problem‐solving steps to take. Bayesian inverse planning builds on existing machine learning tools to create a generative model relating (mis)‐understandings to equation solving choices. Two behavioral experiments demonstrate that the model can interpret people's equation solving and that its assessments are consistent with those of experienced teachers. A third experiment uses this model to tailor guidance for learners based on individual differences in misunderstandings, closing the loop between assessing understanding, and using that assessment within an educational technology. Finally, because the bottleneck in applying inverse planning to a new domain is in creating the model of possible student misunderstandings, we show how to combine inverse planning with an existing production rule model to make inferences about student misunderstandings of fraction arithmetic. (shrink)

Neural organization: Structure, function, and dynamics shows how theory and experiment can supplement each other in an integrated, evolving account of the brain's structure, function, and dynamics. Structure: Studies of brain function and dynamics build on and contribute to an understanding of many brain regions, the neural circuits that constitute them, and their spatial relations. We emphasize Szentágothai's modular architectonics principle, but also stress the importance of the microcomplexes of cerebellar circuitry and the lamellae of hippocampus. Function: Control of eye (...) movements, reaching and grasping, cognitive maps, and the roles of vision receive a functional decomposition in terms of schemas. Hypotheses as to how each schema is implemented through the interaction of specific brain regions provide the basis for modeling the overall function by neural networks constrained by neural data. Synthetic PET integrates modeling of primate circuitry with data from human brain imaging. Dynamics: Dynamic system theory analyzes spatiotemporal neural phenomena, such as oscillatory and chaotic activity in both single neurons and neural networks, the self-organizing development and plasticity of ordered neural structures, and learning and memory phenomena associated with synaptic modification. Rhythm generation involves multiple levels of analysis, from intrinsic cellular processes to loops involving multiple brain regions. A variety of rhythms are related to memory functions. The Précis presents a multifaceted case study of the hippocampus. We conclude with the claim that language and other cognitive processes can be fruitfully studied within the framework of neural organization that the authors have charted with John Szentágothai. (shrink)

The phenomenon of mutual support presents a specific challenge to the foundationalist epistemologist: Is it possible to model mutual support accurately without using circles of evidential support? We argue that the appearance of loops of support arises from a failure to distinguish different synchronic lines of evidential force. The ban on loops should be clarified to exclude loops within any such line, and basing should be understood as taking place within lines of evidence. Uncertain propositions involved in mutual support relations (...) are conduits to each other of independent evidence originating ultimately in the foundations. We examine several putative examples of benign loops of support and show that, given the distinctions noted, they can be accurately modeled in a foundationalist fashion. We define an evidential "tangle," a relation among three propositions that appears to require a loop for modeling, and prove that all such tangles are trivial in a sense that precludes modeling them with an evidential circle. (shrink)

Purpose: This, the second part of a two-part paper, describes how the concerns of enactive cognitive science have been realized in actual research: methodological issues, proposed explanatory mechanisms and models, some of the potential as both a theoretical and applied science, and several of the major open research questions. Findings: Despite some skepticism about "mechanisms" in constructivist literature, enactive cognitive science attempts to develop cognitive formalisms and models. Such techniques as feedback loops, self-organization, autocatalytic networks, and dynamical systems modeling (...) are used to develop alternatives to cognitivist models. A number of technical similarities are starting to emerge in the different models being proposed. Research Implications: The need to resolve the interplay between autonomy and coupling with the environment suggests the need for further technical research. And the reintroduction of first-person concerns into cognitive science raises some questions of method, particularly with regard to the relationship between first-person experience, neuroscience, and methods of description, analysis, and explanation. Results to date suggest that insights from enactive cognitive science could lead to innovations in the design of artifacts. (shrink)

Prism adaptation is a form of visuomotor training that produces both sensorimotor and cognitive aftereffects depending on the direction of the visual displacement. Recently, a neural framework explaining both types of PA-induced aftereffects has been proposed, but direct evidence for it is lacking. We employed Structural Equation Modeling, a form of effective connectivity analysis, to establish directionality among connected nodes of the brain network thought to subserve PA. The findings reveal two distinct network branches: a loop involving connections (...) from the parietal cortices to the right parahippocampal gyrus, and a branch linking the lateral premotor cortex to the parahippocampal gyrus via the cerebellum. Like the sensorimotor aftereffects, the first branch exhibited qualitatively different modulations for left versus right PA, and critically, changes in these connections were correlated with the magnitude of the sensorimotor aftereffects. Like the cognitive aftereffects, changes in the second branch were qualitatively similar for left and right PA, with greater change for left PA and a trend correlation with cognitive aftereffects. These results provide direct evidence that PA is supported by two functionally distinct subnetworks, a parietal–temporal network responsible for sensorimotor aftereffects and a fronto-cerebellar network responsible for cognitive aftereffects. (shrink)

Most studies of motifs of biological regulatory networks focus on the analysis of asymptotical behaviours, but transient properties are rarely addressed. In the line of our previous study devoted to isolated circuits 19:172–178, 2003), we consider chorded circuits, that are motifs made of an elementary positive or negative circuit with a chord, possibly a self-loop. We provide detailed descriptions of the boolean dynamics of chorded circuits versus isolated circuits, under the synchronous and asynchronous updating schemes within the logical formalism. (...) To this end, we address the description of the trajectories in the dynamics of isolated circuits with coding techniques and adapt them for chorded circuits. The use of the logical modeling gives access to mathematical tools allowing complete analytical analysis of basic yet important motifs. In particular, we show that whatever the chosen updating rule, the dynamics depends on a small number of parameters. (shrink)

The human masticatory system is a complex functional unit characterized by a multitude of skeletal components, muscles, soft tissues, and teeth. Muscle activation dynamics cannot be directly measured on live human subjects due to ethical, safety, and accessibility limitations. Therefore, estimation of muscle activations and their resultant forces is a longstanding and active area of research. Reinforcement learning (RL) is an adaptive learning strategy which is inspired by the behavioral psychology and enables an agent to learn the dynamics of an (...) unknown system via policy-driven explorations. The RL framework is a well-formulated closed-loop system where high capacity neural networks are trained with the feedback mechanism of rewards to learn relatively complex actuation patterns. In this work, we are building on a deep RL algorithm, known as the Soft Actor-Critic, to learn the inverse dynamics of a simulated masticatory system, i.e., learn the activation patterns that drive the jaw to its desired location. The outcome of the proposed training procedure is a parametric neural model which acts as the brain of the biomechanical system. We demonstrate the model’s ability to navigate the feasible three-dimensional (3D) envelope of motion with sub-millimeter accuracies. We also introduce a performance analysis platform consisting of a set of quantitative metrics to assess the functionalities of a given simulated masticatory system. This platform assesses the range of motion, metabolic efficiency, the agility of motion, the symmetry of activations, and the accuracy of reaching the desired target positions. We demonstrate how the model learns more metabolically efficient policies by integrating a force regularization term in the RL reward. We also demonstrate the inverse correlation between the metabolic efficiency of the models and their agility and range of motion. The presented masticatory model and the proposed RL training mechanism are valuable tools for the analysis of mastication and other biomechanical systems. We see this framework’s potential in facilitating the functional analyses aspects of surgical treatment planning and predicting the rehabilitation performance in post-operative subjects. (shrink)

Open peer commentary on the article “Constructivism and Computation: Can Computer-Based Modeling Add to the Case for Constructivism?” by Manfred Füllsack. Upshot: The environment is not slowly constructed by the agent but is an integral part of being an agent because both, agent and environment, are part of a closed loop system. By identifying the perturbations impacting on the loops, with the help of second-order cybernetics, the agent can identify them as its environment.

What principles and mechanisms allow humans to encode complex 3D information, and how can it be so fast, so accurately and so flexibly transformed into coordinated action? How do these processes work when developed to the limit of human physiological and cognitive capacity—as they are in high-speed sports, such as alpine skiing or motor racing? High-speed sports present not only physical challenges, but present some of the biggest perceptual-cognitive demands for the brain. The skill of these elite athletes is in (...) many ways an attractive model for studying human performance “in the wild”, and its neurocognitive basis. This article presents a framework theory for how these abilities may be realized in high-speed sports. It draws on a careful analysis of the case of the motorsport athlete, as well as theoretical concepts from: (1) cognitive neuroscience of wayfinding, steering, and driving; (2) cognitive psychology of expertise; (3) cognitive modeling and machine learning; (4) human-in-the loop modellling in vehicle system dynamics and human performance engineering; (5) experimental research (in the laboratory and in the field) on human visual guidance. The distinctive contribution is the way these are integrated, and the concept ofchunkingis used in a novel way to analyze a high-speed sport. The mechanisms invoked are domain-general, and not specific to motorsport or the use of a particular type of vehicle (or any vehicle for that matter); theegocentric chunking hypothesisshould therefore apply to any dynamic task that requires similar core skills. It offers a framework for neuroscientists, psychologists, engineers, and computer scientists working in the field of expert sports performance, and may be useful in translating fundamental research into theory-based insight and recommendations for improving real-world elite performance. Specific experimental predictions and applicability of the hypotheses to other sports are discussed. (shrink)

Theories related to cognitive sciences, Human-in-the-loop Cyber-physical systems, data analysis for decision-making, and computational ethics make clear the need to create transdisciplinary learning, research, and application strategies to bring coherence to the paradigm of a truly human-oriented technology. Autonomous objects assume more responsibilities for individual and collective phenomena, they have gradually filtered into routines and require the incorporation of ethical practice into the professions related to the development, modeling, and design of algorithms. To make this possible, it is (...) pertinent and urgent to bring them closer to the problems and approaches of the humanities. Increasingly transdisciplinary research must be part of the construction of systems that provide developers and scientists with the necessary bases to understand the ethical debate and therefore their commitment to society. This article considers two theories as articulating axes: Blumenberg’s, coming from the field of philosophy, for whom the process of technification and especially the implementation of mathematical models in their algorithmic form leads to an emptying of meaning and therefore makes programmers who implement their functions to be alien to the concerns that gave them origin; Daston’s, belonging to the field of the history of science and according to which the division of labor in the processes of technification of the calculation implies a kind of subordination in which those who implement the inventions of a small group of privileged mathematicians ignore the procedures that put them into operation. Given these two theories, the black box models prevalent in AI development, and the urgency of establishing explanatory frameworks for the development of computational ethics, this article exposes the need to give a voice to the cultural history of consciousness for promoting the discussions around the implementation of mathematical algorithms. The paper takes as a reference the different points of view that have emerged around the study of technological ethics, its applicability, management, and design. It criticizes the current state of studies from a humanistic perspective and explains how the historical perspective allows promoting the training of software engineers, developers and creators so that they assume intuitions and moral values in the development of their work. Specifically, it aims to expose how cultural history, applied to the study of consciousness and its phenomena, makes those involved in this technological revolution aware of the effect that they, through their algorithms, have on society in general and on human beings in particular. (shrink)

DNA–protein interactions are fundamental to many biological processes, including the regulation of gene expression. Determining the binding affinities of transcription factors (TFs) to different DNA sequences allows the quantitative modeling of transcriptional regulatory networks and has been a significant technical challenge in molecular biology for many years. A recent paper by Maerkl and Quake1 demonstrated the use of microfluidic technology for the analysis of DNA–protein interactions. An array of short DNA sequences was spotted onto a glass slide, which was (...) then covered with a microfluidic device allowing each spot to be within a chamber into which the flow of materials was controlled by valves. By trapping the DNA–protein complexes on the surface and measuring their concentrations microscopically, they could determine the binding affinity to a large number of DNA sequences that were varied systematically. They studied four TFs from the basic helix–loop–helix family of proteins, all of which bind to E‐box sites with the consensus CAnnTG (where “n” can be any base), and showed that variations in affinity for different sites allows each TF to regulate different genes. BioEssays 29:717–721, 2007. © 2007 Wiley Periodicals, Inc. (shrink)

Climatology is a paradigmatic complex systems science. Understanding the global climate involves tackling problems in physics, chemistry, economics, and many other disciplines. I argue that complex systems like the global climate are characterized by certain dynamical features that explain how those systems change over time. A complex system's dynamics are shaped by the interaction of many different components operating at many different temporal and spatial scales. Examining the multidisciplinary and holistic methods of climatology can help us better understand the nature (...) of complex systems in general. -/- Questions surrounding climate science can be divided into three rough categories: foundational, methodological, and evaluative questions. "How do we know that we can trust science?" is a paradigmatic foundational question (and a surprisingly difficult one to answer). Because the global climate is so complex, questions like "what makes a system complex?" also fall into this category. There are a number of existing definitions of `complexity,' and while all of them capture some aspects of what makes intuitively complex systems distinctive, none is entirely satisfactory. Most existing accounts of complexity have been developed to work with information-theoretic objects (signals, for instance) rather than the physical and social systems studied by scientists. -/- Dynamical complexity, a concept articulated in detail in the first third of the dissertation, is designed to bridge the gap between the mathematics of contemporary complexity theory (in particular the formalism of "effective complexity" developed by Gell-Mann and Lloyd [2003]) and a more general account of the structure of science generally. Dynamical complexity provides a physical interpretation of the formal tools of mathematical complexity theory, and thus can be used as a framework for thinking about general problems in the philosophy of science, including theories, explanation, and lawhood. -/- Methodological questions include questions about how climate science constructs its models, on what basis we trust those models, and how we might improve those models. In order to answer questions about climate modeling, it's important to understand what climate models look like and how they are constructed. Climate model families are significantly more diverse than are the model families of most other sciences (even sciences that study other complex systems). Existing climate models range from basic models that can be solved on paper to staggeringly complicated models that can only be analyzed using the most advanced supercomputers in the world. I introduce some of the central concepts in climatology by demonstrating how one of the most basic climate models might be constructed. I begin with the assumption that the Earth is a simple featureless blackbody which receives energy from the sun and releases it into space, and show how to model that assumption formally. I then gradually add other factors (e.g. albedo and the greenhouse effect) to the model, and show how each addition brings the model's prediction closer to agreement with observation. After constructing this basic model, I describe the so-called "complexity hierarchy" of the rest of climate models, and argue that the sense of "complexity" used in the climate modeling community is related to dynamical complexity. -/- With a clear understanding of the basics of climate modeling in hand, I then argue that foundational issues discussed early in the dissertation suggest that computation plays an irrevocably central role in climate modeling. "Science by simulation" is essential given the complexity of the global climate, but features of the climate system--the presence of non-linearities, feedback loops, and chaotic dynamics--put principled limits on the effectiveness of computational models. This tension is at the root of the staggering pluralism of the climate model hierarchy, and suggests that such pluralism is here to stay, rather than an artifact of our ignorance. Rather than attempting to converge on a single "best fit" climate model, we ought to embrace the diversity of climate models, and view each as a specialized tool designed to predict and explain a rather narrow range of phenomena. Understanding the climate system as a whole requires examining a number of different models, and correlating their outputs. This is the most significant methodological challenge of climatology. -/- Climatology's role contemporary political discourse raises an unusually high number of evaluative questions for a physical science. The two leading approaches to crafting policy surrounding climate change center on mitigation (i.e. stopping the changes from occurring) and adaptation (making post hoc changes to ameliorate the harm caused by those changes). Crafting an effective socio-political response to the threat of anthropogenic climate change, however, requires us to integrate multiple perspectives and values: the proper response will be just as diverse and pluralistic as the climate models themselves, and will incorporate aspects of both approaches. I conclude by offering some concrete recommendations about how to integrate this value pluralism into our socio-political decision making framework. (shrink)

At the core of Pickering & Garrod's (P&G's) theory is a monitor that uses forward models. I argue that this account is challenged by neuropsychological findings and visual world eye-tracking data and that it has two conceptual problems. I propose that conflict monitoring avoids these issues and should be considered a promising alternative to perceptual loop and forward modeling theories.

This paper discusses the suitability of using systemic thinking for teaching environmental rehabilitation to undergraduate students at Federal Universityof Viçosa. This is a predominantly agricultural sciences-based institution located in southeast Brazil. Student receptivity is discussed given concurrent campus paradigms of positivism, Marxism, and individualistic utilitarianism. Student projects using causal-loop diagrams to model degradation and land reclamation are presented. Eight archetypes common to systemic thinking are explained in reclamation contexts. Limitations of systemic thinking are discussed, including theoretical modeling problems (...) and practical teaching considerations. (shrink)

In lieu of an abstract, here is a brief excerpt of the content:Complex Mimetic SystemsHans Weigand (bio)The goal of science is to make the wonderful and complex understandable and simple—but not less wonderful.—Herb Simon, The Sciences of the Artificial11. IntroductionComplex systems theory stands for an approach in the social as well as natural and computational sciences that studies how interactions between parts give rise to collective behaviors of a system, and how the system interacts and forms relationships with its environment. (...) A typical example is the market economy, in which the order is emergent: it is the result of human action, but not the execution of any human design.2 Complex systems theory is currently a popular vehicle for understanding the complexities of the Internet; other examples of its application are as diverse as the stock market, ant colonies, epidemics, and the spread of business innovations. The focus in this article is on modeling social systems rather than physical or biological phenomena. [End Page 63]The mimetic theory developed by René Girard fits well with a systems perspective, as it has specific ideas about the drivers of human action (at the micro level) and cultural processes (at the macro level). The relationship has been explored earlier in several books and articles;3 in particular, in the work of the Centre de Recherche en Epistémologie Appliquée (CREA) in Paris. The systems perspective received a new stimulus in the 1990s in the form of complex adaptive systems (CAS),4 not least because of the agent-based computer simulations adopted at that time. The objective of this article is to introduce a special version of CAS, called complex mimetic systems (CMS), which builds on mimetic theory. The purpose of this article is twofold. On the one hand, the phrasing of mimetic theory in terms of CMS poses an interesting challenge to the theory to formalize its concepts and explicate possible limitations. On the other hand, CMS might be a useful contribution to the CAS field, as it incorporates concepts such as “social influence” that are very basic to but typically not spelled out in current CAS work.The structure of this article is as follows. In section 2, I briefly review the CAS literature and introduce the idea of complex mimetic systems. Section 3 describes a straw-man agent architecture for CMS, whereas in section 4, I move to the macro level and formalize the culture reproduction cycle. To illustrate the applicability of the CMS framework, I discuss in section 5 Ingo Piepers’s recent CAS analysis of the European international system in the period 1490–1945, and comment on it from a CMS perspective.2. Complex Mimetic SystemsThe characteristic features of complex systems are as follows:• Nonlinear effects: a small perturbation may have a large effect.• Feedback loops: the effects of an element’s behavior are fed back to it in some way. The feedback can be positive (amplification, runaway) or negative (damping).• Openness: a typical complex system interacts with its environment.• Memory: the history of a complex system may be important. Prior states may have an influence on present states.• Nesting, hierarchy: a complex system may itself be an element of a larger complex system. For example, clans in a tribal society, nation-states in an international system, or divisions in a company. [End Page 64]• Topology: the interactions of the elements are enabled and constrained by the network, or grid, of relationships between them.Complex Adaptive SystemsComplex adaptive systems (CAS) are a modern variant of complex systems theory. The elements of a complex adaptive system are called agents, as CAS builds on computational research in the field of multiagent systems.5 Although there is not much difference in the overall objectives, the use of agent simulation opens up interesting research opportunities. Let me clarify this by means of an introductory example given by Miller and Page, the standing ovation problem.6Standing ovations, in which waves of audience members stand up to express their particular appreciation of a performance, usually arise and evolve spontaneously. Suppose that we want to model this phenomenon. A starting point could be a simple mathematical model in which we distinguish N people, each receiving a signal... (shrink)

Chronic myeloid leukemia (CML) is a cancer of the hematopoietic system initiated by a single genetic mutation which results in the oncogenic fusion protein Bcr-Abl. Untreated, patients pass through different phases of the disease beginning with the rather asymptomatic chronic phase and ultimately culminating into blast crisis, an acute leukemia resembling phase with a very high mortality. Although many processes underlying the chronic phase are well understood, the exact mechanisms of disease progression to blast crisis are not yet revealed. In (...) this paper we develop a mathematical model of CML based on causal Bayesian networks in order to study possible disease progression mechanisms. Our results indicate that an increase of Bcr-Abl levels alone is not sufficient to explain the phenotype of blast crisis and that secondary changes such as additional mutations are necessary to explain disease progression and the poor therapy response of patients in blast crisis. (shrink)

Unmanned aerial vehicles, particularly quadcopters, have several medical, agriculture, surveillance, and security applications. However, the use of this innovative technology for civilian applications is still very limited in low-income countries due to the high cost, whereas low-cost controllers available in the market are often tuned using the hit and trial approach and are limited for specific applications. This paper addresses this issue and presents a novel proof of concept low-cost quadcopter UAV design approach using a systematic Model-Based Design method for (...) mathematical modeling, simulation, real-time testing, and prototyping. The quadcopter dynamic model is developed, and controllers are designed using Proportional Integral, and Derivative, Pole Placement, and Linear Quadratic Regulator control strategies. The stability of the controllers is also checked using Lyapunov stability analysis. For verification and validation of the design, Software-in-the-Loop, Processor-in-the-Loop, Hardware-in-the-loop testing, and Rapid Control Prototyping have been performed. The V&V methods of the MBD approach showed practically valid results with a stable flight of the quadcopter prototype. The proposed low-cost POC quadcopter design approach can be easily modified to have enhanced features, and quadcopters with different design parameters can be assembled using this approach for a diverse range of applications. (shrink)

Frequency selective surface -based intelligent spatial filters are capturing the eyes of the researchers by offering a dynamic behavior when exposed to the electromagnetic radiations. In this manuscript, a concept of creating complementary structures which stems from Babinet’s principle is illustrated. A hybrid complementary pair of FSS comprising double square loop FSS and double square slot FSS on either side of the dielectric substrate is proposed. DSLFSS offers band-pass behavior and can be placed as a superstrate, whereas DSSFSS behaves (...) as a band-stop intelligent spatial filter that blocks the radiations falling on it, thus making them applicable for use as a substrate. The technique utilized for analyzing DSLFSS and DSSFSS structures is based on the equivalent circuit modeling and transmission line methodology. The CPFSS structure offers the design simplicity, hence, suitable for placing them with the printed patch antenna radiators in wireless networking devices operating in sub-6 GHz 5G spectrum. DSLFSS offers band-pass behavior ranging from 2.99 to 5.56 GHz, whereas DSSFSS offers band-stop behavior ranging from 2.85 to 5.42 GHz covering all n77, n78, and n79 bands of FR1 spectrum of sub-6 GHz 5G range. The passband and the stopband offered by the two structures of CPFSS geometry are stable to oblique angles of incidence and the proposed design also offers polarization-independent behavior. The thickness of the dielectric region existing within the pair of designed structures is critical for the location of the passbands and the stopbands. The impact of the overall thickness of the dielectric substrate on the passbands and stopbands is also reported in this article. (shrink)

The ability to improve in speed and accuracy as a result of repeating some task is an important hallmark of intelligent biological systems. Although gradual behavioral improvements from practice have been modeled in spiking neural networks, few such models have attempted to explain cognitive development of a task as complex as addition. In this work, we model the progression from a counting-based strategy for addition to a recall-based strategy. The model consists of two networks working in parallel: a slower basal (...) ganglia loop and a faster cortical network. The slow network methodically computes the count from one digit given another, corresponding to the addition of two digits, whereas the fast network gradually “memorizes” the output from the slow network. The faster network eventually learns how to add the same digits that initially drove the behavior of the slower network. Performance of this model is demonstrated by simulating a fully spiking neural network that includes basal ganglia, thalamus, and various cortical areas. Consequently, the model incorporates various neuroanatomical data, in terms of brain areas used for calculation and makes psychologically testable predictions related to frequency of rehearsal. Furthermore, the model replicates developmental progression through addition strategies in terms of reaction times and accuracy, and naturally explains observed symptoms of dyscalculia. (shrink)

This paper explores a special kind of loop of grounding: cosmic loops. A cosmic loop is a loop that intuitively requires us to go "around" the entire universe to come back to the original ground. After describing several kinds of cosmic loop scenarios, I will discuss what we can learn from these scenarios about constraints on grounding; the conceivability of cosmic loops; the possibility of cosmic loops; and the prospects for salvaging local reflexivity, asymmetry and transitivity (...) of grounding in a world containing a cosmic loop of ground. The considerations raised in this paper also bear on what we should think about relations that are meant to support grounding relations: in particular, revisions to theories of the part-whole relation are discussed. (shrink)

According to Hugh Mellor in Real Time II, assuming the logical independence of causal facts and the ‘law of large numbers’, causal loops are impossible because if they were possible they would produce inconsistent sets of frequencies. I clarify the argument, and argue that it would be preferable to abandon the relevant independence assumption in the case of causal loops.

Background: Newer “closed-loop” neurostimulation devices in development could, in theory, induce changes to patients’ personalities and self-perceptions. Empirically, however, only limited data of patient and family experiences exist. Responsive neurostimulation (RNS) as a treatment for refractory epilepsy is the first approved and commercially available closed-loop brain stimulation system in clinical practice, presenting an opportunity to observe how conceptual neuroethical concerns manifest in clinical treatment. Methods: We conducted ethnographic research at a single academic medical center with an active RNS (...) treatment program and collected data via direct observation of clinic visits and in-depth interviews with 12 patients and their caregivers. We used deductive and inductive analyses to identify the relationship between these devices and patient changes in personality and self-perception. Results: Participants generally did not attribute changes in patients’ personalities or self-perception to implantation of or stimulation using RNS. They did report that RNS affected patients’ experiences and conceptions of illness. In particular, the capacity to store and display electrophysiological data produced a common frame of reference and a shared vocabulary among patients and clinicians .Discussion: Empirical experiences of a clinical population being treated with closed-loop neuromodulation do not corroborate theoretical concerns about RNS devices described by neuroethicists and technology developers. However, closed-loop devices demonstrated an ability to change illness experiences. Even without altering identify and self-perception, they provided new cultural tools and metaphors for conceiving of epilepsy as an illness and of the process of diagnosis and treatment. These findings call attention to the need to situate neuroethical concerns in the broader contexts of patients’ illness experiences and social circumstances. (shrink)