Research
​
​
​
​
​
​
​
​
Note: Documents are provided for educational or personal use only. Downloading a document is considered a request by you for a single copy. Do not circulate or disseminate.
​
(+ = Student Co-Author)
Favela, L. H. (2024). What is NExT for affordances? Taking brains seriously in organism-environment systems. In The modern legacy of Gibson’s affordances for the sciences of organisms.
​
Abstract. Gibsonian ecological psychology can be viewed as an alternative to behaviorism’s fixation on the individual’s overt actions and cognitivism’s solipsistic flavor. Instead, the target of inquiry is the organism-environment system and affordances. A long-standing criticism of this approach is the apparent absence of even a sketch of the contributions made by the brain, which has led to the caricatured Gibsonian creature as being filled with “foam rubber” and “wonder tissue.” Here, I provide a path forward to understanding the brain’s contribution to affordances: the NeuroEcological Nexus Theory (NExT). NExT hypothesizes that affordances emerge via systematic relationships between environmental (ecological) information and low-dimensional neural manifolds. This approach is motivated by recent neuroscience research demonstrating that neural population dynamics are preserved in low-dimensional manifolds within and across animals performing similar actions. Accordingly, it is hypothesized that neural population dynamics map to particular affordance events with regularity. Taken together, the theory of affordances successfully appealed to for decades by Gibsonians is complemented by methods from manifold theory. In this way, ecological psychologists will no longer be accused of believing in creatures filled with foam rubber and wonder tissue.
Favela, L. H., & Amon, M. J. (2023). The ethics of human digital twins: Counterfeit people, personhood, and the right to privacy. 2023 IEEE 3rd International Conference on Digital Twins and Parallel Intelligence (DTPI).
​
Abstract. In recent years, generative artificial intelligence (AI) in the form of large language models (LLM) have sparked the interest of society at large. The perceived capabilities of such systems have reignited discussions concerning the actual or potential threats posed by AI. According to Daniel Dennett, these systems make possible the creation of counterfeit people, who can pass as real in digital environments like social media. Dennett claims that by undermining trust in relationships, counterfeit people pose a threat to democracy and human freedom. While the idea of counterfeit people is worrisome in the context of digital manipulation, we claim that human digital twins have the potential to facilitate human rights violations that may pose even greater challenges. High-fidelity human digital twins necessitate encroaching into features that constitute a human’s personhood, such as physical aspects and mental contents. In view of that, their creation raises pressing issues of consent and violations of privacy rights. As a result, because rights to privacy are rights of persons, such violations will simultaneously be human rights violations. Even with consent to use an individual’s data, human digital twins may still cause issues of personhood. The rapid adoption of technologies that facilitate counterfeit people and human digital twins demands that ethical issues not be treated as aside concerns, but at the forefront of technology development.
Favela, L. H., & Chemero, A. (2023). Plural methods for plural ontologies: A case study from the life sciences. In Situated cognition research: Methodological foundations.
​
Abstract. As with much contemporary philosophical and scientific research, the predominant metaphysics of situatedness is monism, particularly, physicalism. Here, we claim that while monism is the proper metaphysical thesis, empirically-supported theories of situated phenomena require ontological pluralism as well. We defend this position via the example of bird flocks, which are situated systems that exhibit ontologically plural features, namely, component dominance and interaction dominance. The description of these features will illustrate that understanding these phenomena requires a coevolution of conceptual and methodological development. Specifically, ontological features are partially identified and evaluated by way of the analyses applied to them. Both descriptive and normative lessons are drawn. Descriptively, research on bird flocks demonstrate that natural phenomena may not be readily cast via a monistic ontology (e.g., component dominant), even at the same scale of investigation. The normative consequence is that while research on situated systems need not reject metaphysical monism, it ought to begin from a pluralistic position concerning ontology.
Favela, L. H. (2023). Review of Gualtiero Piccinini’s Neurocognitive mechanisms: Explaining biological cognition. Philosophy of Science.
​
Introduction. It is common for philosophers of neuroscience to be deeply engaged with the relevant experimental literature. This may be why the last couple of decades have seen an increase in philosophers of neuroscience obtaining formal training in neuroscience concurrently with philosophy or coming to philosophy from a previous life as a neuroscientist. By the turn of the twenty-first century, scientific practice came to inform and inspire the new mechanist movement. Philosophers of neuroscience interested in cognition often find themselves attempting to integrate work on experimentation and mechanisms with research in the cognitive sciences and psychology that commonly centers on computational understandings of cognition. It is within this background that Gualtiero Piccinini’s latest book is situated.
Favela, L. H., & Machery, E. (2023). Investigating the concept of representation in the neural and psychological sciences. Frontiers in Psychology: Cognition.
​
Abstract. The concept of representation is commonly treated as indispensable to research on brains, behavior, and cognition. Nevertheless, systematic evidence about the ways the concept is applied remains scarce. We present results of an experiment aimed at elucidating what researchers mean by “representation.” Participants were an international group of psychologists, neuroscientists, and philosophers (N = 736). Applying elicitation methodology, participants responded to a survey with experimental scenarios aimed at invoking applications of “representation” and of five other ways of describing how the brain responds to stimuli. While we find little disciplinary variation in the application of “representation” and other expressions (e.g., “about,” “carry information,” etc.), results suggest that researchers exhibit uncertainty about what sorts of brain activity involve representations or not; they also prefer non-representational, causal characterizations of the brain’s response to stimuli. Potential consequences of these findings are explored, such as reforming or eliminating the concept of representation from use.
Favela, L. H., & Amon, M. J. (2023). Reframing cognitive science as a complexity science. Cognitive Science.
​
Abstract. Complexity science is an investigative framework that stems from a number of tried and tested disciplines—including systems theory, nonlinear dynamical systems theory, and synergetics—and extends a common set of concepts, methods, and principles to understand how natural systems operate. By quantitatively employing concepts such as emergence, nonlinearity, and self-organization, complexity science offers a way to understand the structures and operations of natural cognitive systems in a manner that is conceptually compelling and mathematically rigorous. Thus, complexity science both transforms understandings of cognition and reframes more traditional approaches. Consequently, if cognitive systems are indeed complex systems, then cognitive science ought to consider complexity science as a centerpiece of the discipline.
Favela, L. H. (2023). Nested dynamical modeling of neural systems: A strategy and some consequences. Journal of Multiscale Neuroscience.
​
Abstract. Neuroscience has become a big data enterprise. This is due in large part to the rapidly growing quantity and quality of data and increased apprciation of nonneuronal physiology and environments in explaining behavior, cognition, and consciousness. One way neuroscience is dealing with this embarrassment of riches is by appealing to investigative frameworks that put the multiscale nature of neural systems at the forefront. The current work offers one such approach: nested dynamical modeling, a strategy for creating models of phenomena comprised of multiple spatial and/or temporal scales for purposes of exploration, explanation, and understanding. Building from dynamical systems theory and synergetics, nested dynamical modeling applies a methodological approach aimed at nesting models at one scale of inquiry within models at other scales without compromising biological realism. This strategy is demonstrated via a proof of concept. Some consequences this approach has for the epistemological and theoretical commitments of neuroscience are discussed.
Favela, L. H., & Amon, M. J. (2023). Enhancing Bayesian approaches in the cognitive and neural sciences via complex dynamical systems theory. Dynamics.
​
Abstract. In the cognitive and neural sciences, Bayesianism refers to a collection of concepts and methods stemming from various implementations of Bayes’ theorem, which is a formal way to calculate the conditional probability of a hypothesis being true based on prior expectations and updating priors in the face of errors. Bayes’ theorem has been fruitfully applied to describe and explain a wide range of cognitive and neural phenomena (e.g., visual perception and neural population activity) and is at the core of various theories (e.g., predictive processing). Despite these successes, we claim that Bayesianism has two interrelated shortcomings: its calculations and models are predominantly linear and noise is assumed to be random and unstructured versus deterministic. We outline ways that Bayesianism can address those shortcomings: first, by making more central the nonlinearities characteristic of biological cognitive systems, and second, by treating noise not as random and unstructured dynamics, but as the kind of structured nonlinearities of complex dynamical systems (e.g., chaos and fractals). We provide bistable visual percepts as an example of a real-world phenomenon that demonstrates the fruitfulness of integrating complex dynamical systems theory in Bayesian treatments of perception. Doing so facilitates a Bayesianism that is more capable of explaining a number of currently out-of-reach natural phenomena on their own, biologically realistic terms.
Favela, L. H. (2022). “It takes two to make a thing go right”: The coevolution of technological and mathematical tools in neuroscience. In The tools of neuroscience experiment: Philosophical and scientific perspectives.
​
Abstract. Some philosophers of neuroscience have recently argued that the history of neuroscience is principally a history of technological tool development. Across these claims, there is little to no mention of data analysis methods nor their underlying assumptions. Here, I argue that mathematical tools have played crucial—though often underappreciated—roles in the history of neuroscience. First, I present the Hodgkin-Huxley model as an example of research constrained by technological limitations and mathematical assumptions. Second, I highlight scale-invariant neuronal dynamics and explain how that discovery required both technological and mathematical advancements. I conclude by discussing consequences for explanations in neuroscience.
Favela, L. H., Amon, M. J., Lobo, L., & Chemero, A. (2021). Empirical evidence for extended cognitive systems. Cognitive Science.
​
Abstract. We present an empirically-supported theoretical and methodological framework for quantifying the system-level properties of person-plus-tool interactions in order to answer the question: “Are person-plus-tool-systems extended cognitive systems?” Nineteen participants provided perceptual judgments regarding their ability to pass through apertures of various widths while using visual information, blindfolded wielding a rod, or blindfolded wielding an Enactive Torch—a vibrotactile sensory-substitution device for detecting distance. Monofractal, multifractal, and recurrence quantification analyses were conducted to assess features of person-plus-tool movement dynamics. Trials where people utilized the rod or Enactive Torch demonstrated stable “self-similarity,” or indices of healthy and adaptive single systems, regardless of aperture width, trial order, features of the participants’ judgments, and participant characteristics. Enactive Torch trials exhibited a somewhat greater range of dynamic fluctuations than the rod trials, as well as less movement recurrence, suggesting that the Enactive Torch allowed for more exploratory movements. Findings provide support for the notion that person-plus-tool systems can be classified as extended cognitive systems and a framework for quantifying system-level properties of these systems. Implications concerning future research on extended cognition are discussed.
Favela, L. H. (2021). The dynamical renaissance in neuroscience. Synthese.
​
Abstract. Although there is a substantial philosophical literature on dynamical systems theory in the cognitive sciences, the same is not the case for neuroscience. This paper attempts to motivate increased discussion via a set of overlapping issues. The first aim is primarily historical and is to demonstrate that dynamical systems theory is currently experiencing a renaissance in neuroscience. Although dynamical concepts and methods are becoming increasingly popular in contemporary neuroscience, the general approach should not be viewed as something entirely new to neuroscience. Instead, it is more appropriate to view the current developments as making central again approaches that facilitated some of neuroscience’s most significant early achievements, namely, the Hodgkin-Huxley and FitzHugh-Nagumo models. The second aim is primarily critical and defends a version of the “dynamical hypothesis” in neuroscience. Whereas the original version centered on defending a noncomputational and nonrepresentational account of cognition, the version I have in mind is broader and includes both cognition and the neural systems that realize it as well. In view of that, I discuss research on motor control as a paradigmatic example demonstrating that the concepts and methods of dynamical systems theory are increasingly and successfully being applied to neural systems in contemporary neuroscience. More significantly, such applications are motivating a stronger metaphysical claim, that is, understanding neural systems as being dynamical systems, which includes not requiring appeal to representations to explain or understand those phenomena. Taken together, the historical claim and the critical claim demonstrate that the dynamical hypothesis is undergoing a renaissance in contemporary neuroscience.
Favela, L. H. (2020). When the flame goes out: The horror of connected consciousness. In Philosophy, Film, and the Dark Side of Interdependence.
​
Abstract. A commonly held central feature of personhood is consciousness. Technological advances related to the expansion or improvement of consciousness are on the horizon, for example, efficient communication, mind uploading, and preserved memory. These technologies are not without risk and potentially dangerous outcomes. From the loss of privacy to a widening sphere of personal assault, the alteration, enhancement, and expansion of one’s consciousness is likely to come with unintended adverse consequences. Here I draw attention to one potential consequence of consciousness-altering technology that is not discussed in the relevant literature and that may prove to be more horrifying than the rest: the extinction of one’s consciousness and, therefore, one’s self. My claim is motivated by one of the most popular and promising theories of consciousness: the integrated information theory (IIT). If IIT is a correct theory of consciousness and if each system has a single consciousness, then the consequence for consciousness-expanding technologies are horrifying. Consider, for example, an Internet-like network of consciousness. If IIT is correct, and if single systems can only have one consciousness, then the more integrated the network becomes, then the more each person’s individual consciousness will fade. More horrifying still, perhaps individuals would not notice their fading consciousness. I draw on examples from horror and science fiction media—Star Trek: The Next Generation, Star Trek: Voyager, Rick and Morty, and The Strain–in order to make more vivid the possibility that as we become more connected through technology, the flame of our consciousness may diminish.
Favela, L. H. (2020). Teaching and learning guide for Dynamical systems theory in cognitive science and neuroscience. Philosophy Compass.
​
This teaching and learning guide accompanies Favela, L. H. (2020). Dynamical systems theory in cognitive science and neuroscience. Philosophy Compass, 15(8), e12695, 1-16.
Favela, L. H. (2020). Dynamical systems theory in cognitive science and neuroscience. Philosophy Compass.
​
Abstract. Dynamical systems theory (DST) is a branch of mathematics that assesses abstract or physical systems that change over time. It has a quantitative part (mathematical equations) and a related qualitative part (plotting equations in a state space). Nonlinear dynamical systems theory applies the same tools in research involving phenomena such as chaos and hysteresis. These approaches have provided different ways of investigating and understanding cognitive systems in cognitive science and neuroscience. The “dynamical hypothesis” claims that cognition is and can be understood as dynamical systems. Common consequences for such an approach include rejecting understanding cognition as information-processing in nature, including eschewing explanatory roles for computation or representation. Contemporary applications of DST include mouse- tracking studies in cognitive science and nonrepresentational perspectives on motor control in neuroscience. Such work has philosophical implications concerning the boundaries of cognition, explanation, and representations. DST offers powerful methodology and theories that raise many topics of philosophical significance.
Favela, L. H. (2021). Fundamental theories in neuroscience: Why neural Darwinism encompasses neural reuse. Neural mechanisms: New challenges in the philosophy of neuroscience.
​
Abstract. Various theories have been put forward to provide theoretical unification in neuroscience. The “data rich and theory poor” state of neuroscience makes such theories worth pursuing. An overarching theory can facilitate data interpretation and provide a general framework for explanation and understanding across the various subfields of neuroscience. Neural reuse is a recent and increasingly popular attempt at such a unifying theory. At its core, neural reuse is a claim about the brain’s architecture that centers on the idea that brain regions are used for multiple tasks across multiple domains. Here, I claim that although neural reuse has many merits, it does not provide a fundamental theory of brain structure and function. Neural reuse is appropriately understood as a general organizational principle that is encompassed by a more fundamental theory. That theory is Neural Darwinism, which applies broadly Darwinian selectionist principles across scales of investigation to explain and under-stand brain structure and function.
Favela, L. H. (2020). Cognitive science as complexity science. Wiley Interdisciplinary Reviews: Cognitive Science.
​
Abstract. It is uncontroversial to claim that cognitive science studies many complex phenomena. What is less acknowledged are the contradictions among many traditional commitments of its investigative approaches and the nature of cognitive systems. Consider, for example, methodological tensions that arise due to the fact that like most natural systems, cognitive systems are nonlinear; and yet, traditionally cognitive science has relied on linear statistical data analyses. Cognitive science as complexity science is offered as an interdisciplinary framework for the investigation of cognition that can dissolve such contradictions and tensions. Here, cognition is treated as exhibiting the following four key features: emergence, nonlinearity, self-organization, and universality. This framework integrates concepts, methods, and theories from such disciplines as systems theory, nonlinear dynamical systems theory, and synergetics. By adopting this approach, the cognitive sciences benefit from a common set of practices to investigate, explain, and understand cognition in its varied and complex forms.
+ Ross, B. A., & Favela, L. H. (2019). A definition of memory for the cognitive sciences. Proceedings of the 41st annual conference of the Cognitive Science Society.
​
Abstract. We provide a definition of 'memory’ that is broad enough to apply to both natural and artificial systems. Inspired by computation and information theory, we define memory as a process that preserves information through time while maintaining its usefulness as an object to be computed. We defend the extensiveness of our definition by explaining how it applies to both brains and modern computers. We then consider potential objections to our definition. Our primary goal is to provide a definition of ‘memory’ that is broadly applicable across various cognitive sciences subfields.
Favela, L. H. (2019). Soft-assembled human-machine perceptual systems. Adaptive Behavior.
​
Abstract. Cognitive systems are highly adaptable and flexible, such that action and perception capabilities can be achieved with the body in various ways, and incorporate features of the environment and nonbiological tools. Perceptual learning refers to enduring changes to a system’s ability to perceive and respond to environmental stimuli. Here I present an integrative framework for understanding how such capabilities occur in human-machine systems comprised of brain-body-tool-environment interactions. Central to this work is the claim that the capacity for high degrees of adaptation, flexibility, and learning are possible because human-machine systems are soft-assembled systems, that is, systems whose material constitution is not rigidly constrained so as to achieve goals via a variety of configurations. I begin by presenting the foundations of the framework on offer: the concepts, methods, and theories of ecological psychology, embodied cognition, dynamical systems theory, and machine intelligence. Next, I apply the framework to the case of visually-guided action. I conclude by explaining how this framework provides the explanatory and investigative tools to understand human-machine perceptual systems as soft-assembled systems that span brains-bodies-tools-environments.
Amon, M. J., & Favela, L. H. (2019). Distributed cognition criteria: Defined, operationalized, and applied to human-dog systems. Behavioural Processes.
​
Abstract. Distributed cognition generally refers to situations in which task requirements are shared among multiple agents or, potentially, off-loaded onto the environment. With few exceptions, socially distributed cognition has largely been discussed in terms of intraspecific interactions. This conception fails to capture some forms of group-level cognition among human and non-human animals that are not readily measured or explained in mentalistic or verbal terms. In response to these limitations, we argue for a more stringent set of empirically-verifiable criteria for assessing whether a system is an instance of distributed cognition: interaction-dominant dynamics, agency, and shared task orientation. We apply this framework to humans and working dogs, and contrast the human-dog socially distributed cognitive system with humans using non-biological tools and human interaction with draft animals. The human-dog system illustrates three operationalizable factors for classifying phenomena as socially distributed cognition and extends the framework to interspecies distributed cognition.
Favela, L. H. (2019). Integrated information theory as a complexity science approach to consciousness. Journal of Consciousness Studies.
​
Abstract. I claim that the integrated information theory of consciousness (IIT) is a complexity science approach to consciousness. In general, complexity science investigates phenomena comprised of numerous nonlinearly interacting parts, where global-scale behavior and structures are irreducible to activities and properties of its constituent parts at local-scales. I draw attention to some key features of IIT (i.e., cause-effect power and information integration) and complexity science (i.e., the search for and application of principles and interaction dominance) in order to defend the claim that IIT is properly understood within the broader theoretical framework of complexity science. Doing so has the advantage of making IIT an even more compelling theory of consciousness, which has the added benefit of strengthening its ability to respond to some common criticisms.
Favela, L. H. (2019). Emergence by way of dynamic interactions. Southwest Philosophy Review.
​
Abstract. I defend the claim that emergence is always a kind of interaction dominance. I utilize Francescotti’s (2007) definition of emergence, which captures five features typically thought crucial for emergence: downward causal influence, novelty, relationality, supervenience, and unpredictability. I then explicate interaction dominance, a concept from complexity science. In short, a system is interaction dominant when the interactions of the parts give rise to features that override the features of the parts in isolation or linked via additive and linear dynamics. Locust swarms are presented as an illustrative case of a natural phenomenon that meets the definition for emergent properties. Moreover, locust swarms provide a case of an emergent property arising via interaction-dominant dynamics. I conclude by discussing the relationship of emergence and interaction dominance, with emphasis on the claim that all emergent properties occur due to interaction dominance, but not all systems that exhibit interaction-dominant dynamics have emergent properties.
Favela, L. H., & van Rooij, M. M. J. W. (2019). Reasoning across continuous landscapes: A nonlinear dynamical systems theory approach to reasoning. Cognitive Systems Research.
​
Abstract. Dual-processing theories of reasoning have gained renewed attention in recent years, particularly in the fields of decision-making under uncertainty, learning, and social judgment. Although the various accounts differ, the common thread is the distinction between two qualitatively different reasoning processes, such as automatic/controlled, fast/slow, and unconscious/conscious. Accordingly, much research is focused on elucidating the nature of the two processes in terms of the kinds of information they process and respond to. Less extensive are attempts to identify mediators that underlie changes between the two reasoning strategies. We argue that nonlinear dynamical systems theory may be able to provide a fresh perspective on reasoning. Nonlinear dynamical systems theory allows us to shift the perspective to the dynamic interactions and transitions among continuous yet qualitatively different reasoning processes. We apply the approach to reasoning in decision-making and judgment under uncertainty. Our primary claim is that using different reasoning strategies is better understood as phase transitions among a landscape of continuous reasoning capacities.
Favela, L. H. (2019). Octopus umwelt or umwelten? Commentary on Mather (2019) “What is in an octopus’s mind?” Animal Sentience.
​
Abstract. Even if its intelligent behaviors are the product of decentralized control systems, Mather argues that the octopus has an “Umwelt,” and, thus, a mind. I argue that Umwelt does not provide a conceptual basis for understanding the octopus as having a mind. First, Umwelt does not refer only to an organism’s perceptual abilities. Second, in providing evidence for decentralized control systems that underlie intelligent behaviors, Mather makes a case against an octopus Umwelt. Instead, the octopus is more akin to a collection of systems, or Umwelten, than a single system with an Umwelt.
Favela, L. H., Riley, M. A., Shockley, K., & Chemero, A. (2018). Perceptually equivalent judgments made visually and via haptic sensory-substitution devices. Ecological Psychology.
​
Abstract. According to the ecological theory of perception-action, perception is primarily of affordances, which are directly perceivable opportunities for behavior. The current study evaluated participants’ ability to use vision and haptic sensory-substitution devices to support perceptual judgments of affordances involving the task of passing through apertures. Sighted participants made perceptual judgments about whether they could walk through apertures of various widths and their level of confidence in each judgment, using unrestricted vision and, when blindfolded, using two haptic sensory-substitution instruments: a cane-like wooden rod and the Enactive Torch, a device that converts distance information into vibrotactile stimuli. The boundary between aperture widths that were judged as pass-through-able versus non-pass-through-able was statistically equivalent across sensory modalities. However, participants were not as confident in their judgments using the rod or Enactive Torch as they were using vision. Additionally, participants’ judgments with the haptic instruments were significantly more accurate than with vision. The results underscore the need to assess sensory-substitution devices in the context of functional behaviors.
+ Neemeh, Z. A., Favela, L. H., & Amon, M. J. (2018). Interspecies distributed cognition. Proceedings of the 40th annual conference of the Cognitive Science Society.
​
Abstract. Studies in distributed cognition (d-cog) almost exclusively focus on human-centered technological systems, such as ships, aircraft, automobiles, scientific and medical institutions, human-computer interfaces, and transactive memory systems. First, we review the literature and claim that d-cog is species-neutral. We then propose three experimentally operationalizable, necessary, and jointly-sufficient criteria for identifying d-cog: task orientation, interaction dominance, and agency. Here we build on previous research on nonhuman intraspecies d-cog by presenting human-dog systems as cases of interspecies d-cog. Domestic dogs’ (Canis familiaris) unique working relationships with humans allow for interspecies coordination and synchronization. Contrasting them with wolves (Canis lupus) and dingoes (Canis dingo), we suggest evolutionary history plays an important role in determining whether different species can form interspecies d-cog systems.
Costa, A. A., Amon, M. J., Sporns, O. & Favela, L. H. (2018). Fractal analyses of networks of integrate-and-fire stochastic spiking neurons. Complex networks IX: Proceedings of the 9th conference on complex networks CompleNet 2018.
​
Abstract. Although there is increasing evidence of criticality in the brain, the processes that guide neuronal networks to reach or maintain criticality remain unclear. The present research examines the role of neuronal gain plasticity in time-series of simulated neuronal networks composed of integrate-and-fire stochastic spiking neurons, and the utility of fractal methods in assessing network criticality. Simulated time-series were derived from a network model of fully connected discrete-time stochastic excitable neurons. Monofractal and multifractal analyses were applied to neuronal gain time-series. Fractal scaling was greatest in networks with a mid-range of neuronal plasticity, versus extremely high or low levels of plasticity. Peak fractal scaling corresponded closely to additional indices of criticality, including average branching ratio. Networks exhibited multifractal structure, or multiple scaling relationships. Multifractal spectra around peak criticality exhibited elongated right tails, suggesting that the fractal structure is relatively insensitive to high-amplitude local fluctuations. Networks near critical states exhibited mid-range multifractal spectra width and tail length, which is consistent with literature suggesting that networks poised at quasi-critical states must be stable enough to maintain organization but unstable enough to be adaptable. Lastly, fractal analyses may offer additional information about critical state dynamics of networks by indicating scales of influence as networks approach critical states.
Favela, L. H. (2018). An introduction to radical embodied cognitive neuroscience. Proceedings of a body of knowledge - Embodied cognition and the arts conference CTSA UCI 8-10 Dec 2016.
​
Abstract. Embodied cognition is no longer a fringe movement in the mind sciences. With few exceptions, embodied cognition is generally relegated to investigating and explaining lower-order cognitive processes involving perception-action and not higher-order cognitive processes such as abstract thinking and imagination. Two major reasons that could explain why those who accept that lower-order cognition could be cases of embodied cognition, but who still resist the idea that higher-order cognition is also embodied are: first, a commitment to the idea that cognition is essentially computational and representational in nature; and second, smallism, which is the view that cognitive phenomena are not explained until the account stops at “lower levels” like neurons or molecules. What follows is an introduction to an embodied approach to investigating and understanding both lower- and higher-order cognition that is not committed to computationalism, representationalism, or smallism: radical embodied cognitive neuroscience. Radical embodied cognitive neuroscience treats cognition as systems phenomena that spread across brain, body, and environment. Unlike its predecessor, radical embodied cognitive science, radical embodied cognitive neuroscience explicitly places the brain and central nervous system within its explanatory purview. By utilizing a novel modeling approach (i.e., nested dynamical modeling) and conducting research guided by the search for and application of scale-free principles of activity (e.g., self-organized criticality), radical embodied cognitive neuroscience provides a framework for investigating both lower-order and higher-order cognition. Such a framework can facilitate accounts of phenomena as apparently disparate as single neurons and neural networks, to coordination activities among dyads and larger groups of agents.
Favela, L. H. (2018). How to defend embodied cognition against the locked-in syndrome challenge. Journal of Cognition and Neuroethics.
​
Abstract. Embodied cognition is the idea that cognition is causally related to and/or constituted by bodily activities. In spite of accumulating reasons to accept embodied cognition, critics seem to have a knockdown argument: appealing to locked-in syndrome (LIS). Patients with LIS are said to be at least minimally conscious to fully awake, except they have no motor control of their body and cannot produce speech. LIS seems to undermine embodied cognition: If cognition is embodied, then LIS patients cannot have intact cognitive capacities because they do not have motor control of their body. The present goal is to provide supporters of embodied cognition with a set of three responses when faced with the challenge from LIS. The first is deflationary and highlights the fact that most cases of LIS are not total and that much evidence of LIS are not actually cases of LIS. The second is skeptical and provides reasons to question the evidence of LIS based on neuroimaging data. The third is that the types of pathologies that cause LIS are likely to alter cognition in radical ways. With these responses at the ready, the supporter of embodied cognition need not surrender at the mere mention of LIS.
Favela, L. H., Amon, M. J., & van Rooij, M. M. J. W. (2018). The incommensurability of emergence and modularity in complex systems: A commentary on Wastell’s (2014). Theory & Psychology.
​
Abstract. To answer the interaction problem, dual-process theories of reasoning must explain how seemingly disparate reasoning systems affect each other and underlie the apparent unity of subjective experience. Wastell proposes complex emergence modular theory, which asserts that complex virtual reasoning modules emerge from basic reasoning modules. We contend that Wastell’s proposal fails to address the interaction problem. First, we claim that the attempt to integrate emergence with virtual modules proliferates the interaction problem instead of solving it. Second, we argue that there is no interaction problem in human reasoning if ‘emergence’ is employed in accordance with typical applications of complex systems theory in cognitive science and psychology. Alternatively, we suggest that in order to understand human reasoning within a complex systems framework, researchers should forego conceiving of reasoning as informationally-encapsulated modular systems, and instead investigate system state transitions.
Favela, L. H. (2017). Mental representations are not necessary for fish consciousness: Commentary on Woodruff (2017) “Consciousness in teleosts: There is something it feels like to be a fish.” Animal Sentience.
​
Abstract. Woodruff (2017) argues that teleost fishes are capable of phenomenal consciousness. Central to his argument is the assumption that phenomenal consciousness is representational in nature. I think the commitment to a representational theory of consciousness undermines Woodruff’s case for teleost phenomenal consciousness. The reason is that organisms do not need to indirectly perceive the world via mental images/representations in order to have phenomenological experiences. My argument is based on considerations of ecological psychology and comparative ethology.
Favela, L. H. (2017). Consciousness is (probably) still only in the brain, even though cognition is not. Mind and Matter.
​
Abstract. There is increasing theoretical justification and empirical support for non-brain-centric approaches to cognition. The body, non-biological tools, and environment are understood as playing causally significant roles in or are constitutive of many instances of cognition. Although not without critics, such non-brain-centric approaches are doing so well that some argue that not only is cognition situated, embodied, extended, and distributed (cognition^SEED) but so too is consciousness (consciousness^SEED). Here ‘cognition’ refers to an organism’s abilities to engage with its world, which includes perceiving and acting skillfully, as well as capacities such as decision-making, planning, and reasoning. ‘Consciousness’ refers to states of a system with subjective phenomenal character. Some defend Consciousness^SEED by appealing to affordances and complex systems theory. I argue that these do not support the claim that cognition^SEED entails consciousness^SEED as well. I then present phenomenological and neurophysiological considerations to think that consciousness is (probably) still only in the brain, even though cognition is not.
Favela, L. H., & Martin, J. (2017). "Cognition" and dynamical cognitive science. Minds and Machines.
Abstract. Several philosophers have expressed concerns with some recent uses of the term ‘cognition.’ Underlying a number of these concerns are claims that cognition is only located in the brain and that no compelling case has been made to use ‘cognition’ in any way other than as a cause of behavior that is representational in nature. These concerns center on two primary misapprehensions: First, that some adherents of dynamical cognitive science (DCS) think DCS implies the thesis of extended cognition and the rejection of representation, and second, that cognition is mistakenly equated with behavior. We make three points in response to these claims: First, there is no thoroughly entrenched conception of cognition as distinct from behavior that is being illegitimately disregarded. Second, we present Shapiro’s (2013) exposition of dynamical systems theory as revealing a misunderstanding of the way that dynamical models are used in explanations of cognition and related phenomena. Accordingly, a proper conception of DCS’s methods facilitates an appreciation of extended cognition as a legitimate phenomenon of scientific investigation. Finally, we demonstrate that practicing cognitive scientists and psychologists are far more pluralistic in the phenomena they apply ‘cognition’ to than is suggested by some. At the heart of our disagreement with these concerned folks is that although we think it likely that some cognitive phenomena are representational, non-extended, and only in-between the ears, we also think there are good conceptual and empirical reasons to believe that many cognitive phenomena are non-representational, extended, and not confined to the brain.
+ Neemeh, Z., & Favela, L. H. (2017). Beyond distributed cognition: Towards a taxonomy of nonreductive social cognition. Proceedings of the 39th annual conference of the Cognitive Science Society.
​
Abstract. Studies of social cognition often assume a reductionist, computational-representational conceptual framework. Distributed cognition is one of the few extant conceptual frameworks for a nonreductive understanding of social cognition. This concept’s prototypical cases are exclusively of technical-scientific human institutions, including ships, cockpits, and the Hubble Space Telescope. In the first part of the paper, we outline the properties of distributed cognitive systems. We look at the case of wolf (Canis lupus) packs as an instance of distributed cognition in nonhuman systems. Nevertheless, a broad range of social cognitive phenomena across human and animal populations may not fit into this conceptual framework. We present a case study of bird flocks as a counterexample to distributed cognition. We propose “swarm intelligence” as an alternative concept of nonreductive social cognition. This is not to replace distributed cognition as a concept, but to add to and diversify the taxonomy of nonreductive social cognitive systems.
Favela, L. H., & Chemero, A. (2016). An ecological account of visual "illusions." Florida Philosophical Review.
​
Abstract. Direct realism in one form or another is gaining traction as an approach to perception. With the hope of bolstering such positions, we offer a framework upon which to base an argument for direct realism in matters of perception. Better yet, we offer an empirically supported framework. The framework on offer is that of ecological psychology. With the framework in place, we then discuss how it can address visual illusions, one of the major challenges facing proponents of direct realism.
Favela, L. H. (2016). Commentary: Purves, Morgenstern, & Wojtach. (2015). Perception and reality: Why a wholly empirical paradigm is needed to understand vision. Frontiers in Systems Neuroscience.
​
Abstract. This commentary attempts to make two points: First, although Purves, Morgenstern, and Wojtach (PMW) are likely correct that the retinal image alone is an insufficient basis for successful visually guided action, their “vision as reflexive” strategy emphasizes the perceptual associations and neural portions of the visual system at the cost of understating the central role environmental information plays in vision. Second, although PMW are correct that early empirical strategies did not sufficiently incorporate neural aspects of the visual system, recent attempts to demonstrate how affordances relate to the nervous system help demonstrate that ecological psychology remains a viable empirical framework for investigating and explaining vision.
van Rooij, M. M. J. W., & Favela, L. H. (2016). A nonlinear dynamical systems theory perspective on dual-processing accounts of decision-making under uncertainty. Proceedings of the 38th annual conference of the Cognitive Science Society.
​
Abstract. Dual-processing accounts of reasoning have gained renewed attention in the past decade, particularly in the fields of social judgment, learning, and decision-making under uncertainty. Although the various accounts differ, the common thread is the distinction between two qualitatively different types of reasoning: explicit/implicit, rational/affective, fast/slow, etc. Consequently, much research has focused on characterizing the two different processes. Less extensive are the attempts to find mediators that influence which process is used. In this paper, we argue that the missing perspective on these dual-processing theories is rooted in dynamical systems theory. By shifting the perspective to the dynamic interaction and transitions between different types of reasoning, we provide a theoretical framework for dual-processing with an emphasis on phase transitions. As a special case, we focus on dual-processing in decision-making and judgment under uncertainty for which we will propose suggestions for future experimental evaluation.
+ Moralez, L., & Favela, L. H. (2016). Thermodynamics and cognition: Towards a lawful explanation of the mind. Proceedings of the 38th annual conference of the Cognitive Science Society.
​
Abstract. An argument is developed to show that explanations of biological and physical systems can be unified via the second law of thermodynamics (SLT). The SLT’s influence on the evolutionary history of life at the scale of the global Earth system justifies reunifying phenomena—i.e., mind and matter—whose separation dates back to Modern Western philosophy and still influences contemporary scientific investigations. From this perspective it appears that the necessity of ever-increasing entropy in nature may constrain the organization and behavior of living organisms and cognitive processes. Via an example of explaining memory at the scale of the brain-body-environment system, we recommend understanding cognition with respect to its role in increasing entropy in nature. This framework may lead to a fruitful understanding of cognition by appealing to the necessity of physical laws.
Favela, L. H., Coey, C. A., Griff, E. R., & Richardson, M. J. (2016). Fractal analysis reveals subclasses of neurons and suggests an explanation of their spontaneous activity. Neuroscience Letters.
​
Abstract. The present work used fractal time series analysis (detrended fluctuation analysis; DFA) to examine the spontaneous activity of single neurons in an anesthetized animal model, specifically, the mitral cells in the rat main olfactory bulb. DFA bolstered previous research in suggesting two subclasses of mitral cells. Although there was no difference in the fractal scaling of the interspike interval series at the shorter timescales, there was a significant difference at longer timescales. Neurons in Group B exhibited fractal, power-law scaled interspike intervals, whereas neurons in Group A exhibited random variation. These results raise questions about the role of these different cells within the olfactory bulb and potential explanations of their dynamics. Specifically, self-organized criticality has been proposed as an explanation of fractal scaling in many natural systems, including neural systems. However, this theory is based on certain assumptions that do not clearly hold in the case of spontaneous neural activity, which likely reflects intrinsic cell dynamics rather than activity driven by external stimulation. Moreover, it is unclear how self-organized criticality might account for the random dynamics observed in Group A, and how these random dynamics might serve some functional role when embedded in the typical activity of the olfactory bulb. These theoretical considerations provide direction for additional experimental work.
Favela, L. H. (2016). Review of Discovering the human connectome by Olaf Sporns. Philosophical Psychology.
​
Introduction. Karl Popper (2002) once instructed a group of physics students to carefully write down what they observed. Popper relates that the students asked what he wanted them to observe and said that the sole instruction to “observe” was absurd. This story motivated Popper’s claim that, especially in science: "Observation is always selective. It needs a chosen object, a definite task, an interest, a point of view, a problem. And its description presupposes a descriptive language . . . , which in its turn presupposes interests, points of view, and problems (2002, p. 62)." In Discovering the Human Connectome, the problem is how the brain works, and from Olaf Sporns’ point of view, the brain can be understood as a network (p. ix). One of Sporns’ main goals in his previous book (2011) was to introduce neuroscientists to the theory and methods of network science. That book was Sporns’ attempt to answer the “how?” questions of integrating the methods of network science with neuroscience. The current book builds on the previous one and attempts to answer more theoretical questions such as why network science is an appropriate framework for investigating the brain.
Favela, L. H., & Chemero, A. (2016). The animal-environment system. Foundations of embodied cognition: Volume 1: Perceptual and emotional embodiment.
​
Abstract. Embodied cognition is a well-established and increasingly influential branch of the cognitive, neural, and psychological sciences. Unlike embodied cognition, extended cognition is not as well-established or influential. Our goal is to defend the idea that if cognition is truly embodied, then it is embodied in systems, and if it is embodied in systems, then it extends beyond animal boundaries. In order to demonstrate this, we situate the idea of extended cognitive systems in a historical context. Then, we present a theoretical and methodological framework for investigating extended cognitive systems. Finally, we discuss some potential experimental work that could adjudicate the existence of extended cognitive systems.
Amon, M. J., & Favela, L. H. (2015). The complex experience of touching metallic, damp, and slimy things. Theory & Psychology.
​
Introduction. The importance of touch to mammalian survival and well-being cannot be overstated. The capacity for action depends on the sense of touch, which is a necessary feature of an animal’s being-in-the-world (O’Shaughnessy, 1989, pp. 38–39). Interpersonal touch has been shown to be an important part of human welfare, including disease prevention and treatment (see Field, 2001 for review). Throughout a mammal’s lifespan, social relationships are also mediated by touch behavior (see Thayer, 1986 for review). Given these facts, the sense of touch is relevant to a variety of topics in psychology, including but not limited to: perception, action, nonverbal behavior, relationships, development, emotion, and health.
Favela, L. H. (2014). Radical embodied cognitive neuroscience: Addressing “grand challenges” of the mind sciences. Frontiers in Human Neuroscience.
​
Abstract. It is becoming ever more accepted that investigations of mind span the brain, body, and environment. To broaden the scope of what is relevant in such investigations is to increase the amount of data scientists must reckon with. Thus, a major challenge facing scientists who study the mind is how to make big data intelligible both within and between fields. One way to face this challenge is to structure the data within a framework and to make it intelligible by means of a common theory. Radical embodied cognitive neuroscience can function as such a framework, with dynamical systems theory as its methodology, and self-organized criticality as its theory.
Favela, L. H., & Chemero, A. (2014). The value of affordances. Religion, Brain, & Behavior.
​
Introduction. Ecological psychology (see Gibson, 1979) is generally thought of as comprising two main claims. The first is that perception is direct insofar as it is not the result of information added to sensory representations. The second is that perception is comprised of affordances (at least most of the time) or opportunities for action that exist in the environment. Barrett explores the possibility of giving an objective account of perceiving religious meaning and value by means of ecological psychology. The attempt to utilize ecological psychology to account for values is not without precedent, however. Jayawickreme and Chemero (2008), for instance, used the ecological concept of ‘‘affordance’’ to sketch an account of both virtues and morally relevant situations. Surprisingly, Barrett never mentions this central ecological concept, choosing instead to focus solely on the directness of perception. We believe that this constricts his ecological account of religious value. While we agree with Barrett that the cognitive science of religion treats presence as an insider’s experience, such that religious experience is a ‘‘black box’’ phenomenon, intractable, and mysterious, and that ecological theory might provide an account of values, we are not convinced by his particular attempt at an ecological account of religious meaning.
van Rooij, M. M. J. W., Favela, L. H., Malone, M. L., & Richardson, M. J. (2013). Modeling the dynamics of risky choice. Ecological Psychology.
​
Abstract. Individuals make decisions under uncertainty every day. Decisions are based on incomplete information concerning the potential outcome or the predicted likelihood with which events occur. In addition, individuals’ choices often deviate from the rational or mathematically objective solution. Accordingly, the dynamics of human decision making are difficult to capture using conventional, linear mathematical models. Here, we present data from a 2-choice task with variable risk between sure loss and risky loss to illustrate how a simple nonlinear dynamical system can be employed to capture the dynamics of human decision making under uncertainty (i.e., multistability, bifurcations). We test the feasibility of this model quantitatively and demonstrate how the model can account for up to 86% of the observed choice behavior. The implications of using dynamical models for explaining the nonlinear complexities of human decision making are discussed as well as the degree to which the theory of nonlinear dynamical systems might offer an alternative framework for understanding human decision making processes.
van Rooij, M. M. J. W., Favela, L. H., Malone, M. L., & Richardson, M. J. (2013). A dynamical model of risky choice. Proceedings of the 35th annual conference of the Cognitive Science Society.
​
Abstract. Individuals make decisions under uncertainty every day based on incomplete information concerning the potential outcome of the choice or chance levels. The choices individuals make often deviate from the rational or mathematically objective solution. Accordingly, the dynamics of human decision-making are difficult to capture using conventional, linear mathematical models. Here, we present data from a two-choice task with variable risk between sure loss and risky loss to illustrate how a simple nonlinear dynamical system can be employed to capture the dynamics of human decision-making under uncertainty (i.e., multi-stability, bifurcations). We test the feasibility of this model quantitatively and demonstrate how the model can account for up to 86% of the observed choice behavior. The implications of using dynamical models for explaining the nonlinear complexities of human decision-making are discussed, as well as the degree to which nonlinear dynamical systems theory might offer an alternative framework for understanding human decision-making processes.