We are living in a time of meta-organics and post-biology, where we perceive everything in our world as customizable and changeable. Modelling biology within a technological context allows us to investigate GEO-volutionary alternatives/alterations to our original natural systems, where augmentation and transmutation become standards in search of overall betterment (Genetically Engineered Organics). Our expectations for technology exceeds ubiquitous access and functional perfection and enters the world of technoetics, where our present hyper-functional, immersively multi-apped, borderline-prosthetic, global village devices fail to satiate (...) our desires to be synaptically surpassed. Most real-time interactive behavioural systems in art utilize two and three dimensions. Artificial neural networks and prediction (Latin: from pr- before plus dicere to say) systems give rise to experimentation within the third-plus-one (3+1) dimension of the spacetime continuum. Spacetime in accordance with string theory requires the where and when to describe something in existence, rather than mere points in space. It explains the workings of the universe from both super-galactic and subatomic levels. Physical cosmology studies the motions of the celestial bodies in relation to the first cause (ie. primum movens) or the source of all-being. In book 12 of Metaphysics, Aristotle spoke of something which moves without (itself) being moved (by anything), and referred to being as motion. In quantum mechanics, a particle is described by a wave. Physiognomy is an evolving area of psychological research that describes a direct correlation between human gesture (or movement) and thought. Early twentieth-century Persian philosopher Abdul-Baha mentioned that the reality of man is his thought, not his material body. Prediction systems apply models of the mind, or artificial neural networks and machine learning strategies, to use the recorded past with the present to anticipate the future. This article investigates existing human and artificial psychic systems in hopes of identifying tools necessary in building a gesture prediction system. The relationship of intent to gesture and whether intent can be perceived without the evidence of gesture are two factors that must be tested. (shrink)

BackgroundElectronic cigarettes as substitute devices for regular tobacco cigarettes have been increasing in recent times. We investigated neuronal substrates of vaping e-cigs and smoking r-cigs from r-cig smokers.MethodsTwenty-two r-cig smokers made two visits following overnight smoking cessation. Functional magnetic resonance imaging data were acquired while participants watched smoking images. Participants were then allowed to smoke either an e-cig or r-cig until satiated and fMRI data were acquired. Their craving levels and performance on the Montreal Imaging Stress Task and a 3-back (...) alphabet/digit recognition task were obtained and analyzed using two-way repeated-measures analysis of variance. Regions-of-interest were identified by comparing the abstained and satiated conditions. Neuronal activation within ROIs was regressed on the craving and behavioral data separately.ResultsCraving was more substantially reduced by smoking r-cigs than by vaping e-cigs. The response time for the 3-back task was significantly shorter following smoking r-cigs than following vaping e-cigs = 5.3, p = 0.035). Neuronal activations of the right vermis, right caudate, and right superior frontal gyrus were significantly correlated with the RT for the 3-back task only for smoking r-cigs.ConclusionOur findings suggest that insufficient satiety from vaping e-cigs for r-cigs smokers may be insignificant effect on working memory function. (shrink)

Arguably, emotion is always valenced—either pleasant or unpleasant—and dependent on the pleasure system. This system serves adaptive evolutionary functions; relying on separable wanting, liking, and learning neural mechanisms mediated by mesocorticolimbic networks driving pleasure cycles with appetitive, consummatory, and satiation phases. Liking is generated in a small set of discrete hedonic hotspots and coldspots, while wanting is linked to dopamine and to larger distributed brain networks. Breakdown of the pleasure system can lead to anhedonia and other features of (...) affective disorders. Eudaimonia and well-being are difficult to study empirically, yet whole-brain computational models could offer novel insights potentially linking eudaimonia to optimal metastability in the pleasure system. (shrink)

A number of conditioning experiments utilize food as a reward. Hunger is considered to be a critical factor governing the animal's behavior in these experiments. Despite its significance, most theories of animal conditioning fail to take hunger into consideration while analyzing the behavioral data. In this paper, we analyze the neuroscientific data supporting the hypothesis that hunger and food consumption affect the brain's dopamine system, which in turn governs the animal's behavior. According to this hypothesis, chronic hunger results in a (...) decrease in the extra-cellular dopamine levels in the animal's brain. This decrease is believed to trigger a series of reactions that increase the responsivity of the phasic dopamine system. A direct consequence of this is an increased vigor of all dopamine-dependent behaviors. The level of extra-cellular dopamine is also modulated by the process of food consumption via the neurotransmitter Acetylcholine. Food consumption raises the dopamine above the baseline level. This rise depends on the animals' hunger, which when satisfied increases the level of Acetylcholine, which causes the dopamine level to fall back to the baseline. Thus, extra-cellular dopamine governs the response vigor, with an increase in dopamine resulting in a more vigorous response. This paper makes two primary contributions. Firstly, we present an abstract mathematical model based on the above hypothesis. Our mathematical model is able to provide a simple explanation for a number of behavioral findings. Another contribution of this paper is the development of a neurocomputational Leabra model of dopamine and acetylcholine activity in the basal ganglia to incorporate hunger and satiation. The experimental results obtained from this neural model are also largely in agreement with behavioral findings. (shrink)

In this chapter, we discuss a selection of current views of the neural correlates of consciousness (NCC). We focus on the different predictions they make, in particular with respect to the role of prefrontal cortex (PFC) during visual experiences, which is an area of critical interest and some source of contention. Our discussion of these views focuses on the level of functional anatomy, rather than at the neuronal circuitry level. We take this approach because we currently understand more about (...) experimental evidence at this coarse level and because these results are appropriate for arbitrating between current theoretical frameworks. We discuss the Two-Visual-Systems Hypothesis (Milner & Goodale 1995; 2006), Local Recurrency (Lamme 2010; Lamme 2006), Higher Order (Lau 2008; Lau & Rosenthal 2011) and Global Workspace theories (Baars 1997; Baars 2005; Dehaene & Naccache 2001; Dehaene 2014). Despite the apparent stark differences between conscious and unconscious perceptual processing, available evidence suggests that their neural substrates must be largely shared. This indicates that the difference in neural activity between conscious and unconscious perceptual processing is likely to be subtle and highly specialized. We argue that current experimental evidence about the involvement of specific activity in prefrontal cortex supports the higher order neural theory of consciousness. In consequence, imaging techniques that focus only on marked differences between conscious and unconscious level of activity are likely to be insensitive to the relevant neural activity patterns that underlie conscious experiences. Finally, it follows from the evidence we discuss that the functional advantages of conscious over unconscious perceptual processing may be more limited than commonly thought. (shrink)

This article argues that the defamiliarization caused by extensive repetition, termed ‘semantic satiation’ in psychology, was used by ancient poets for specific effects. Five categories of repetition are identified. First, words undergo auditory deformation through syllable and sound repetition, as commonly in ancient etymologies. Second, a tradition of emphatic proper-name repetition is identified, in which the final instance of the name is given special emphasis; this tradition spans Greek and Latin poetry, and ultimately goes back to the Nireus entry (...) in the Catalogue of Ships. Third, repetition is used for wordplay, where the final instance of the repeated term not only is emphasized but also incurs some change to its meaning or shape. Fourth, the incantatory repetition of divine names in hymns and cultic invocations amplifies a sense of divine presence behind and beyond the repetend. Fifth, repetition of half and full lines by different speakers in Old Comedy serves to undercut and parody the original sense of the repeated words. Extensive repetition in ancient literature was never merely ornamental but was used for a range of specific auditory and semantic effects with distinct and identifiable structures. (shrink)

In this paper an Artificial Neural Network (ANN) model was used to help cars dealers recognize the many characteristics of cars, including manufacturers, their location and classification of cars according to several categories including: Make, Model, Type, Origin, DriveTrain, MSRP, Invoice, EngineSize, Cylinders, Horsepower, MPG_Highway, Weight, Wheelbase, Length. ANN was used in prediction of the number of miles per gallon when the car is driven in the city(MPG_City). The results showed that ANN model was able to predict MPG_City with (...) 97.50 % accuracy. The factor of DriveTrain has the most influence on MPG_City evaluation. Similar studies can be carried out for the evaluation of other characteristics of cars. (shrink)

Human neural organoid research is advancing rapidly. As Greely notes in the target article, this progress presents an “onrushing ethical dilemma.” We can’t rule out the possibility that suff...

An emerging class of theories concerning the functional structure of the brain takes the reuse of neural circuitry for various cognitive purposes to be a central organizational principle. According to these theories, it is quite common for neural circuits established for one purpose to be exapted (exploited, recycled, redeployed) during evolution or normal development, and be put to different uses, often without losing their original functions. Neural reuse theories thus differ from the usual understanding of the role (...) of neural plasticity (which is, after all, a kind of reuse) in brain organization along the following lines: According to neural reuse, circuits can continue to acquire new uses after an initial or original function is established; the acquisition of new uses need not involve unusual circumstances such as injury or loss of established function; and the acquisition of a new use need not involve (much) local change to circuit structure (e.g., it might involve only the establishment of functional connections to new neural partners). Thus, neural reuse theories offer a distinct perspective on several topics of general interest, such as: the evolution and development of the brain, including (for instance) the evolutionary-developmental pathway supporting primate tool use and human language; the degree of modularity in brain organization; the degree of localization of cognitive function; and the cortical parcellation problem and the prospects (and proper methods to employ) for function to structure mapping. The idea also has some practical implications in the areas of rehabilitative medicine and machine interface design. (shrink)

Syntactic satiation is the phenomenon where some sentences that initially seem ungrammatical appear more acceptable after repeated exposures (Snyder 2000). We investigated satiation by manipulating two factors known to affect syntactic priming, a phenomenon where recent exposure to a grammatical structure facilitates subsequent processing of that structure (Bock 1986). Specifically, we manipulated (i) Proximity of exposure (number of sentences between primes and targets) and (ii) Lexical repetition (type of phrase repeated across primes and targets). Experiment 1 investigated whether (...) acceptability ratings of Complex-NP Constraint (CNPC) and Subject islands improve as consequence of these variables. If so, priming and satiation may be linked. When primes were separated from targets by one sentence, CNPC islands’ acceptability was improved by a preceding island of the same type, but Subject islands’ acceptability was not. When prime-target pairs were separated by five sentences, we found no improvement for either island type. Experiment 2 asked whether improvements in Experiment 1 reflected online processing or offline end-of-sentence effects. We used a self-paced reading paradigm to diagnose online structure-building and processing facilitation (Ivanova 2012) during processing. We found priming for Subject islands when primes and targets were close together, but not when they were further apart. No effects were detected when CNPC islands were close together, but there was a localized effect when sentences were further apart. The disjunction between Experiments 1 and 2 suggests repetition of the structure in Subject islands facilitated online processing but did not ‘spill over’ to acceptability ratings. Meanwhile, results for CNPC islands suggest that acceptability rating improvements in Experiment 1 may be driven by factors distinct from online processing facilitation. Together, our experiments show that satiation may not be a one-size-fit-all phenomenon but, instead, appears to manifest itself differently for different types of structures. Priming is possible and may be linked to satiation in some purportedly “unbuildable” structures (e.g. Subject islands), but not for all types (e.g. CNPC islands). Despite this, it appears that while the types of mechanisms targeting different island types are distinct, they are nevertheless similarly sensitive to the proximity between individual exposures. (shrink)

The search for neural correlates of consciousness (or NCCs) is arguably the cornerstone in the recent resurgence of the science of consciousness. The search poses many difficult empirical problems, but it seems to be tractable in principle, and some ingenious studies in recent years have led to considerable progress. A number of proposals have been put forward concerning the nature and location of neural correlates of consciousness. A few of these include.

In this paper an Artificial Neural Network (ANN) model was used to help cars dealers recognize the many characteristics of cars, including manufacturers, their location and classification of cars according to several categories including: Buying, Maint, Doors, Persons, Lug_boot, Safety, and Overall. ANN was used in forecasting car acceptability. The results showed that ANN model was able to predict the car acceptability with 99.12 %. The factor of Safety has the most influence on car acceptability evaluation. Comparative study method (...) is suitable for the evaluation of car acceptability forecasting, can also be extended to all other areas. (shrink)

While neuroscientists often characterize brain activity as representational, many philosophers have construed these accounts as just theorists’ glosses on the mechanism. Moreover, philosophical discussions commonly focus on finished accounts of explanation, not research in progress. I adopt a different perspective, considering how characterizations of neural activity as representational contributes to the development of mechanistic accounts, guiding the investigations neuroscientists pursue as they work from an initial proposal to a more detailed understanding of a mechanism. I develop one illustrative example (...) involving research on the information-processing mechanisms mammals employ in navigating their environments. This research was galvanized by the discovery in the 1970s of place cells in the hippocampus. This discovery prompted research in what the activity of these cells represents and how place representations figure in navigation. It also led to the discovery of a host of other types of neurons—grid cells, head-direction cells, boundary cells—that carry other types of spatial information and interact with place cells in the mechanism underlying spatial navigation. As I will try to make clear, the research is explicitly devoted to identifying representations and determining how they are constructed and used in an information processing mechanism. Construals of neural activity as representations are not mere glosses but are characterizations to which neuroscientists are committed in the development of their explanatory accounts. (shrink)

Neural decoding studies seem to show that the “private” experiences of others are more accessible than philosophers have traditionally believed. While these studies have many limitations, they do demonstrate that by capturing patterns in brain activity, we can discover a great deal about what a subject is experiencing. We present a thought experiment about a super-decoder — the Atlantis machine — and argue that given plausible assumptions, an Atlantis machine could one day be built. On the basis of this (...) argument, we then argue for the rejection of robust notions of consciousness, which have generated numerous puzzles, including puzzles about the possibility of philosophical zombies. In light of the Atlantis machine, it can be seen that robust notions of consciousness do not earn their explanatory or descriptive keep. More modest concepts of consciousness are sufficient to account for all phenomena — in both senses of the term. This kind of antirobustness about consciousness is a deflationary approach to conscious experience that differs in important ways from illusionist approaches. (shrink)

How do minds emerge from developing brains? According to the representational features of cortex are built from the dynamic interaction between neural growth mechanisms and environmentally derived neural activity. Contrary to popular selectionist models that emphasize regressive mechanisms, the neurobiological evidence suggests that this growth is a progressive increase in the representational properties of cortex. The interaction between the environment and neural growth results in a flexible type of learning: minimizes the need for prespecification in accordance with (...) recent neurobiological evidence that the developing cerebral cortex is largely free of domain-specific structure. Instead, the representational properties of cortex are built by the nature of the problem domain confronting it. This uniquely powerful and general learning strategy undermines the central assumption of classical learnability theory, that the learning properties of a system can be deduced from a fixed computational architecture. Neural constructivism suggests that the evolutionary emergence of neocortex in mammals is a progression toward more flexible representational structures, in contrast to the popular view of cortical evolution as an increase in innate, specialized circuits. Human cortical postnatal development is also more extensive and protracted than generally supposed, suggesting that cortex has evolved so as to maximize the capacity of environmental structure to shape its structure and function through constructive learning. (shrink)

We begin by distinguishing computationalism from a number of other theses that are sometimes conflated with it. We also distinguish between several important kinds of computation: computation in a generic sense, digital computation, and analog computation. Then, we defend a weak version of computationalism—neural processes are computations in the generic sense. After that, we reject on empirical grounds the common assimilation of neural computation to either analog or digital computation, concluding that neural computation is sui generis. Analog (...) computation requires continuous signals; digital computation requires strings of digits. But current neuroscientific evidence indicates that typical neural signals, such as spike trains, are graded like continuous signals but are constituted by discrete functional elements (spikes); thus, typical neural signals are neither continuous signals nor strings of digits. It follows that neural computation is sui generis. Finally, we highlight three important consequences of a proper understanding of neural computation for the theory of cognition. First, understanding neural computation requires a specially designed mathematical theory (or theories) rather than the mathematical theories of analog or digital computation. Second, several popular views about neural computation turn out to be incorrect. Third, computational theories of cognition that rely on non-neural notions of computation ought to be replaced or reinterpreted in terms of neural computation. (shrink)

In "Brainshy: Non-neural theories of conscious experience," (this volume) Patricia Churchland considers three "non-neural" approaches to the puzzle of consciousness: 1) Chalmers' fundamental information, 2) Searle's "intrinsic" property of brain, and 3) Penrose-Hameroff quantum phenomena in microtubules. In rejecting these ideas, Churchland flies the flag of "neuralism." She claims that conscious experience will be totally and completely explained by the dynamical complexity of properties at the level of neurons and neural networks. As far as consciousness goes, (...) class='Hi'>neural network firing patterns triggered by axon-to-dendrite synaptic chemical transmissions are the fundamental correlates of consciousness. There is no need to look elsewhere. (shrink)

This book brings together an international group of neuroscientists and philosophers who are investigating how the content of subjective experience is...

Colombo’s (Phenomenology and the Cognitive Sciences, 2013) plea for neural representationalism is the focus of a recent contribution to Phenomenology and Cognitive Science by Daniel D. Hutto and Erik Myin. In that paper, Hutto and Myin have tried to show that my arguments fail badly. Here, I want to respond to their critique clarifying the type of neural representationalism put forward in my (Phenomenology and the Cognitive Sciences, 2013) piece, and to take the opportunity to make a few (...) remarks of general interest concerning what Hutto and Myin have dubbed “the Hard Problem of Content.”. (shrink)

and apply it to various examples of neural plasticity in which input is rerouted intermodally or intramodally to nonstandard cortical targets. In some cases but not others, cortical activity ‘defers’ to the nonstandard sources of input. We ask why, consider some possible explanations, and propose a dynamic sensorimotor hypothesis. We believe that this distinction is important and worthy of further study, both philosophical and empirical, whether or not our hypothesis turns out to be correct. In particular, the question of (...) how the distinction should be explained is linked to explanatory gap issues for consciousness. Comparative and absolute explanatory gaps should be distinguished: why does neural activity in a particular area of cortex have this qualitative expression rather than that, and why does it have any qualitative expression at all? We use the dominance/deference distinction to address the comparative gaps, both intermodal and intramodal. We do so not by inward scrutiny but rather by expanding our gaze to include relations between brain, body and environment. (shrink)

Why is neural activity in a particular area expressed as experience of red rather than green, or as visual experience rather than auditory? Indeed, why does it have any conscious expression at all? These familiar questions indicate the explanatory gap between neural activity and ‘what it’s like’-- qualities of conscious experience. The comparative explanatory gaps, intermodal and intramodal, can be separated from the absolute explanatory gap and associated zombie issues--why does neural activity have any conscious expression at (...) all?. Here I focus on comparative gaps: why is neural activity in a given area expressed as this type of experience rather than that type of experience? (shrink)

Neural reuse theories suggest that, in the course of evolution, a brain structure may acquire or lose a number of cognitive uses while maintaining its cognitive workings (or low-level operations) fixed. This, in turn, suggests that homologous structures may have very different cognitive uses, while sharing the same workings. And this, essentially, is homology thinking applied to brain function.

Despite the ubiquity of knowledge attribution in human social cognition, its associated neural and cognitive mechanisms are poorly documented. A wealth of converging evidence in cognitive neuroscience has identified independent perspective-taking and inhibitory processes for belief attribution, but the extent to which these processes are shared by knowledge attribution isn't presently understood. Here, we present the findings of an EEG study designed to directly address this shortcoming. These findings suggest that belief attribution is not a component process in knowledge (...) attribution, contra a standard attitude taken by philosophers. Instead, observed differences in P3b amplitude indicate that knowledge attribution doesn't recruit the strong self-perspective inhibition characteristic of belief attribution. However, both belief and knowledge attribution were observed to display a late slow wave widely associated with mental state attribution, indicating that knowledge attribution also shares in more general processing of others' mental states. These results provide a new perspective both on how we think about knowledge attribution, as well as Theory of Mind processes generally. (shrink)

The neural coding metaphor is so ubiquitous that we tend to forget its metaphorical nature. What do we mean when we assert that neurons encode and decode? What kind of causal and representational model of the brain does the metaphor entail? What lies beneath the neural coding metaphor, I argue, is a bureaucratic model of the brain.

In this paper we defend structural representations, more specifically neural structural representation. We are not alone in this, many are currently engaged in this endeavor. The direction we take, however, diverges from the main road, a road paved by the mathematical theory of measure that, in the 1970s, established homomorphism as the way to map empirical domains of things in the world to the codomain of numbers. By adopting the mind as codomain, this mapping became a boon for all (...) those convinced that a representation system should bear similarities with what was being represented, but struggled to find a precise account of what such similarities mean. The euforia was brief, however, and soon homomorphism revealed itself to be affected by serious weaknesses, the primary one being that it included systems embarrassingly alien to representations. We find that the defense attempts that have followed, adopt strategies that share a common format: valid structural representations come as “homomorphism plus X”, with various “X”, provided in descriptive format only. Our alternative direction stems from the observation of the overlooked departure from homomorphism as used in the theory of measure and its later use in mental representations. In the former case, the codomain or the realm of numbers, is the most suited for developing theorems detailing the existence and uniqueness of homomorphism for a wide range of empirical domains. In the latter case, the codomain is the realm of the mind, possibly more vague and more ill-defined than the empirical domain itself. The time is ripe for articulating the mapping between represented domains and the mind in formal terms, by exploiting what is currently known about coding mechanisms in the brain. We provide a sketch of a possible development in this direction, one that adopts the theory of neural population coding as codomain. We will show that our framework is not only not in disagreement with the “plus X” proposals, but can lead to natural derivation of several of the “X”. (shrink)

Colombo (Phenomenology and the Cognitive Sciences, 2012) argues that we have compelling reasons to posit neural representations because doing so yields unique explanatory purchase in central cases of social norm compliance. We aim to show that there is no positive substance to Colombo’s plea—nothing that ought to move us to endorse representationalism in this domain, on any level. We point out that exposing the vices of the phenomenological arguments against representationalism does not, on its own, advance the case for (...) representationalism one inch—beyond establishing its mere possibility. We criticize the continual confounding of constitutive and explanatory claims and the lack of recognition of a Hard Problem of having to provide a naturalistic account of content, coupled with an inability to face up to it. We point at the inadequacy of various deflationary moves that end up driving representationalists towards the idea of neural representations with non-standard contents or without content altogether, both of which either render neural representationalism unfit for purpose or vacuous. Referring to possibilities for neural manipulation and control, or to established scientific practice does not help representationalism either. (shrink)

How does the human brain link relational concepts to perceptual experience? For example, a speaker may say “the cup to the left of the computer” to direct the listener's attention to one of two cups on a desk. We provide a neural dynamic account for both perceptual grounding, in which relational concepts enable the attentional selection of objects in the visual array, and for the generation of descriptions of the visual array using relational concepts. In the model, activation in (...) neural populations evolves dynamically under the influence of both inputs and strong interaction as formalized in dynamic field theory. Relational concepts are modeled as patterns of connectivity to perceptual representations. These generalize across the visual array through active coordinate transforms that center the representation of target objects in potential reference objects. How the model perceptually grounds or generates relational descriptions is probed in 104 simulations that systematically vary the spatial and movement relations employed, the number of feature dimensions used, and the number of matching and nonmatching objects. We explain how sequences of decisions emerge from the time‐ and state‐continuous neural dynamics, how relational hypotheses are generated and either accepted or rejected, followed by the selection of new objects or the generation of new relational hypotheses. Its neural realism distinguishes the model from information processing accounts, its capacity to autonomously generate sequences of processing steps distinguishes it from deep neural network accounts. The model points toward a neural dynamic theory of higher cognition. (shrink)

Neural Geographies draws together recent feminist and deconstructive theories, early Freudian neurology and contemporary connectionist theories of cognition. In this original work, Elizabeth A. Wilson explores the convergence between Derrida, Freud and recent cognitive theory to pursue two important issues: the nature of cognition and neurology, and the politics of feminist and critical interventions into contemporary scientific psychology. This book seeks to reorient the usual presumptions of critical studies of the sciences by addressing the divisions between the static and (...) the changeable; the natural and the political; the neuro-cognitive and the cultural that have been traditional to both scientific and critical accounts of neurology and cognition. (shrink)