[This is an edited and improved version of "You Are Not Your Brain: Against 'Teaching to the Brain'" previously published in *Review of Higher Education and Self-Learning* 5(15), Summer 2012.] Since educators are always looking for ways to improve their practice, and since empirical science is now accepted in our worldview as the final arbiter of truth, it is no surprise they have been lured toward cognitive neuroscience in hopes that discovering how the brain learns will (...) provide a nutshell explanation for student learning in general. I argue that identifying the person with the brain is scientism (not science), that the brain is not the person, and that it is the person who learns. In fact the brain only responds to the learning of embodied experience within the extra-neural network of intersubjective communications. Learning is a dynamic, cultural activity, not a neural program. Brain-based learning is unnecessary for educators and may be dangerous in that a culturally narrow ontology is taken for granted, thus restricting our creativity and imagination, and narrowing the human community. (shrink)

Artificial intelligence (AI) is an area of computer science that emphasizes the creation of intelligent machines or software that work and reacts like humans, some of the computer activities with artificial intelligence are designed to include speech, recognition, learning, planning and problem solving. Deep learning is a collection of algorithms used in machine learning, it is part of a broad family of methods used for machine learning that are based on learning representations of data. Deep (...) learning is used as a technique to produce brain tumor detection and classification models using Magnetic Resonance Imaging (MRI) imaging for rapid and easy detection and identification of brain tumor. In this thesis, some ways and mechanisms will be reviewed to use deep learning techniques to produce a model for brain tumor detection. The goal is to find a good and effective way to detect brain tumor based on MRI to help the brain doctor in making decisions easily, accurately and rapidly. A recent report by the World Health Organization in February 2018 showed that the death rate from brain cancer or central nervous system (CNS) is the highest in the Asian continent. It is important to detect cancer early so that many of these lives can be saved. The model has been designed and implemented, including a dataset which consist of 10,000 images for brain tumor detection through the use of Deep learning algorithms based on neural networks. For testing, we have used our model, Inception, VGG16, MobileNet and ResNet models. The f-score accuracy we got for each model was as follows: Our model was 98.28, VGG16 was 99.86%, ResNet50 was 98.14%, MobileNet was 88,98%, and InceptionV3 was 99.88%. (shrink)

his study aims to determine whether the application of brain-friendly learning through whole brain teaching gives a positive effect on the creative character of students, to know the response of the students against the application of brain-friendly learning through whole brain teaching, and to find out if the student response against the application of brain-friendly learning through whole brain teaching correlates positively with the creative character of students in learning mathematics. (...) The research method used that is quantitative. The instruments used, namely the now student response related application of brain-friendly learning through whole brain teaching, and sheets of observation about the creativity of students in learning mathematics after implementing this method. The correlation analysis with the results of the study showed that the value of the larger significance of the alpha values (5%) which means accepting and rejecting H0 Ha which means student response against the application of brain-friendly learning through whole brain teaching not correlated positively with the creative character of students in learning mathematics. The average student response score against this method is found on very good i.e. amounted to 85%. As for the observations of the creative character of the students, after this method is applied, the average score of 68% is found quite creative. (shrink)

The purpose of this study was to determine whether the application of learning brain-friendly through the whole brain teaching a positive effect on the character of creative students, to study the response of the students, and to determine whether the students' response to the application of learning brain-friendly through the whole brain teaching positively correlated with the character of creative students in mathematics. The research method used is quantitative. The instruments used are student questionnaire (...) responses related to the application of brain-friendly learning through the whole brain teaching and observation sheet on student creativity in the learning of mathematics after the implementation of this method. Results of research with correlation analysis show that the greater significance of the alpha value (5%), which means accepting and rejecting H0 Ha which means students' response to the application of brain-friendly learning through the whole brain teaching is not positively correlated with the creative character of students in the learning of mathematics. The average score of the students' response to this methodology very well categorized in the amount of 85%. The results of the observation of the creative character of the students after the implementation of this method, the average score of 68% were categorized quite creative. (shrink)

This study explores the effectiveness of brain-based learning (BBL) as a pedagogical approach to address the challenges of poor conceptual understanding, which may have worsened due to the COVID-19 pandemic aftermath. In this meta- analysis, 14 studies qualified using the Publish or Perish software and the Preferred Reporting Items for Systematic Reviews and Meta-analyses. Statistical analysis conducted using Comprehensive Meta-Analysis (CMA) Version 4 software by Biostat, Inc. Based on the results, the overall effect size (ES = 3.135) indicates (...) that the use and integration of BBL principles and strategies have a significantly large and positive effect on student conceptual understanding. The moderator analysis revealed a significant difference between individual studies (p < .001); however, the overall results for academic level (p > .05) and discipline (p > .05) revealed no significant differences. Hence, each study included in this analysis may differ from one another due to the differences in various BBL strategies implemented; however, when grouped, they shared common effect sizes. With these findings, the researchers advocate the use of BBL principles and strategies to improve students' conceptual understanding at various levels in basic education, be it in English and STEM. Moreover, empirical studies focusing on a particular BBL variable, such as health and nutrition, are recommended for in-depth analysis and discussion. (shrink)

Today, artificial intelligence, especially machine learning, is structurally dependent on human participation. Technologies such as Deep Learning (DL) leverage networked media infrastructures and human-machine interaction designs to harness users to provide training and verification data. The emergence of DL is therefore based on a fundamental socio-technological transformation of the relationship between humans and machines. Rather than simulating human intelligence, DL-based AIs capture human cognitive abilities, so they are hybrid human-machine apparatuses. From a perspective of media philosophy and social-theoretical (...) critique, I differentiate five types of “media technologies of capture” in AI apparatuses and analyze them as forms of power relations between humans and machines. Finally, I argue that the current hype about AI implies a relational and distributed understanding of (human/artificial) intelligence, which I categorize under the term “cybernetic AI”. This form of AI manifests in socio-technological apparatuses that involve new modes of subjectivation, social control and discrimination of users. (shrink)

Since educators are always looking for ways to improve their practice, and since empirical science is now accepted in our worldview as the final arbiter of truth, it is no surprise they have been lured toward cognitive neuroscience in hopes that discovering how the brain learns will provide a nutshell explanation for student learning in general. I argue that identifying the person with the brain is scientism (not science), that the brain is not the person, and (...) that it is the person who learns. In fact the brain only responds to the learning of embodied experience within the extra-neural network of intersubjective communications. Learning is a dynamic, cultural activity, not a neural program. Brain-based learning is unnecessary for educators and may be dangerous in that a culturally narrow ontology is taken for granted, thus restricting our creativity and imagination, and narrowing the human community. (shrink)

The biological brain creates a mind, and the mental mind creates a brain. Learn how the brain creates consciousness and how it generates momentaneous time moments. Discover how at each moment in Time, our body runs the whole program of Evolution. Neuroscience and Philosophy.

Extended and distributed cognition theories argue that human cognitive systems sometimes include non-biological objects. On these views, the physical supervenience base of cognitive systems is thus not the biological brain or even the embodied organism, but an organism-plus-artifacts. In this paper, we provide a novel account of the implications of these views for learning, education, and assessment. We start by conceptualising how we learn to assemble extended cognitive systems by internalising cultural norms and practices. Having a better grip (...) on how extended cognitive systems are assembled, we focus on the question: If our cognition extends, how should we educate and assess such extended cognitive systems? We suggest various ways to minimize possible negative effects of extending one’s cognition and to efficiently find and organise (online) information by adopting a virtue epistemology approach. Educational and assessment implications are foregrounded, particularly in the case of Danish students’ use of the Internet during exams. (shrink)

Delicate Tissue Tumors (STT) are a type of sarcoma found in tissues that interface, backing, and encompass body structures. Due to their shallow recurrence in the body and their extraordinary variety, they seem, by all accounts, to be heterogeneous when seen through Magnetic Resonance Imaging (MRI). They are effortlessly mistaken for different infections, for example, fibro adenoma mammae, lymphadenopathy, and struma nodosa, and these indicative blunders have an extensive unfavorable impact on the clinical treatment cycle of patients. Analysts have proposed (...) a few AI models to characterize cancers, however none have sufficiently tended to this misdiagnosis issue. Likewise, comparative investigations that have proposed models for assessment of such cancers generally don't think about the heterogeneity and the size of the information. Thusly, we propose an AI based approach which joins another strategy of pre handling the information for highlights change, resampling methods to dispense with the predisposition and the deviation of precariousness and performing classifier tests in light of the and Deep learning Algorithm as Artificial brain organization. -/- Tumors (STT). (shrink)

Mathematical cognition is one of the most important cognitive functions of human beings. The latest brain and cognitive research have shown that mathematical cognition is a system with multiple components and subsystems. It has phylogenetic root, also is related to ontogenetic development and learning, relying on a large-scale cerebral network including parietal, frontal and temporal regions. Especially, the parietal cortex plays an important role during mathematical cognitive processes. This indicates that language and visuospatial functions are both key to (...) mathematical cognition. All of those advances have important implications for basic mathematical education. (shrink)

What type of artificial systems will claim to be conscious and will claim to experience qualia? The ability to comment upon physical states of a brain-like dynamical system coupled with its environment seems to be sufficient to make claims. The flow of internal states in such systems, guided and limited by associative memory, is similar to the stream of consciousness. A specific architecture of an artificial system, termed articon, is introduced that by its very design has to claim being (...) conscious. Non-verbal discrimination of the working memory states of the articon gives it the ability to experience different qualities of internal states. Analysis of the flow of inner states of such a system during typical behavioral process shows that qualia are inseparable from perception and action. The role of consciousness in learning of skills — when conscious information processing is replaced by subconscious — is elucidated. Arguments confirming that phenomenal experience is a result of cognitive processes are presented. Possible philosophical objections based on the Chinese room and other arguments are discussed, but they are insufficient to refute articon’s claims that it is conscious. Conditions for genuine understanding that go beyond the Turing test are presented. Articons may fulfill such conditions and in principle the structure of their experiences may be arbitrarily close to human. (shrink)

The high prevalence of brain injury incidents in adolescence and adulthood demands effective models for re-learning lost cognitive abilities. Impairment in brain injury survivors’ higher-level cognitive functions is common and a negative predictor for long-term outcome. We conducted two small-scale interventions (N = 12; 33.33% female) with persons with acquired brain injuries in two municipalities in Sweden. Age ranged from 17 to 65 years (M = 51.17, SD = 14.53). The interventions were dialogic, inquiry-based, and inspired (...) by the Philosophy for Children Programme, a participatory thinking skills approach with documented higher-order cognitive outcomes, such as developed argumentation skills, in other target groups. Philosophical dialogues were conducted once a week in the two groups, totalling 12 dialogues per group. Group argumentation development was measured through compared scores from structured observations of filmed dialogues early and late in the intervention. Large positive changes in mean scores from early to late in the intervention, together with constantly high facilitator quality, suggest argumentation development in the sample due to the intervention. (shrink)

In recent years, neuroscience has begun to transform itself into a “big data” enterprise with the importation of computational and statistical techniques from machine learning and informatics. In addition to their translational applications such as brain-computer interfaces and early diagnosis of neuropathology, these tools promise to advance new solutions to longstanding theoretical quandaries. Here I critically assess whether these promises will pay off, focusing on the application of multivariate pattern analysis (MVPA) to the problem of reverse inference. I (...) argue that MVPA does not inherently provide a new answer to classical worries about reverse inference, and that the method faces pervasive interpretive problems of its own. Further, the epistemic setting of MVPA and other decoding methods contributes to a potentially worrisome shift towards prediction and away from explanation in fundamental neuroscience. (shrink)

The biological Brain createst the mental Mind. Today our collective Mind becomes so fascinated by its source, the Brain, that all sciences incorporate neuro models in their concepts to increase global brainpower with technology. The most significant discovery is probably technology. We learn how the Brain creates consciousness and how the Brain generates momentaneous Time. Discover how at each moment in Time, our body runs the whole program of Evolution. What we know about the Brain (...) is phantasy from the Mind. (shrink)

In 1959 two French neurologists, Pierre Mollaret and Maurice Goullon, coined the term coma dépassé to designate a state beyond coma. In this state, patients are not only permanently unconscious; they lack the endogenous drive to breathe, as well as brainstem reflexes, indicating that most of their brain has ceased to function. Although legally recognized in many countries as a criterion for death, brain death has not been universally accepted by bioethicists, by the medical community, or by the (...) public. I this paper, I defend brain death as a biological concept. I challenge two assumptions in the brain death literature that have shaped the debate and have stood in the way of an argument for brain death as biological. First, I challenge the dualism established in the debate between the body and the brain. Second, I contest the emphasis on consciousness, which prevents the inclusion of psychological phenomena into a biological criterion of death. I propose that the term organism should apply both to the functioning of the body and the brain. I argue that the cessation of the organism as a whole should take into account three elements of integrated function. Those three elements are: 1) the loss of integrated bodily function; 2) the loss of psychophysical integration required for processing of external stimuli and those required for behavior; and, 3) the loss of integrated psychological function, such as memory, learning, attention, and so forth. The loss of those three elements of integrated function is death. (shrink)

Persons with aphasia suffer from a loss of communication ability as a consequence of a brain injury. A small strand of research indicates effec- tiveness of dialogic interventions for communication development for persons with aphasia, but a vast amount of research studies shows its effectiveness for other target groups. In this paper, we describe the main parts of the hitherto technological development of an application named Dialogica that is (i) aimed at facilitating increased communicative participation in dialogic settings for (...) persons with aphasia and other communication disorders, (ii) based on comput- er game technology as well as on theory in dialogic education and argumenta- tion theory, and (iii) designed for mobile devices with larger screens. (shrink)

Scientific studies have shown that non-conscious stimuli and représentations influence information processing during conscious experience. In the light of such evidence, questions about potential functional links between non-conscious brain representations and conscious experience arise. This article discusses models capable of explaining how statistical learning mechanisms in dedicated resonant circuits could generate specific temporal activity traces of non-conscious representations in the brain. How reentrant signaling, top-down matching, and statistical coincidence of such activity traces may lead to the progressive (...) consolidation of neural signatures of conscious experience in networks extending across large distances beyond functionally specialized brain regions is then explained. (shrink)

Capacity of conscious agents to perform genuine choices among future alternatives is a prerequisite for moral responsibility. Determinism that pervades classical physics, however, forbids free will, undermines the foundations of ethics, and precludes meaningful quantification of personal biases. To resolve that impasse, we utilize the characteristic indeterminism of quantum physics and derive a quantitative measure for the amount of free will manifested by the brain cortical network. The interaction between the central nervous system and the surrounding environment is shown (...) to perform a quantum measurement upon the neural constituents, which actualize a single measurement outcome selected from the resulting quantum probability distribution. Inherent biases in the quantum propensities for alternative physical outcomes provide varying amounts of free will, which can be quantified with the expected information gain from learning the actual course of action chosen by the nervous system. For example, neuronal electric spikes evoke deterministic synaptic vesicle release in the synapses of sensory or somatomotor pathways, with no free will manifested. In cortical synapses, however, vesicle release is triggered indeterministically with probability of 0.35 per spike. This grants the brain cortex, with its over 100 trillion synapses, an amount of free will exceeding 96 terabytes per second. Although reliable deterministic transmission of sensory or somatomotor information ensures robust adaptation of animals to their physical environment, unpredictability of behavioral responses initiated by decisions made by the brain cortex is evolutionary advantageous for avoiding predators. Thus, free will may have a survival value and could be optimized through natural selection. (shrink)

Forty years have passed since video-games were first made widely available to the public and subsequently playing games has become a favorite past-time for many. Players continuously engage with dynamic visual displays with success contingent on the time-pressured deployment, and flexible allocation, of attention as well as precise bimanual movements. Evidence to date suggests that both brief and extensive exposure to video-game play can result in a broad range of enhancements to various cognitive faculties that generalize beyond the original context. (...) Despite promise, video-game research is host to a number of methodological issues that require addressing before progress can be made in this area. Here an effort is made to consolidate the past 30 years of literature examining the effects of video-game play on cognitive faculties and, more recently, neural systems. Future work is required to identify the mechanism that allows the act of video-game play to generate such a broad range of generalized enhancements. (shrink)

The principle of self-organization has acquired a fundamental significance in the newly emerging field of computational philosophy. Self-organizing systems have been described in various domains in science and philosophy including physics, neuroscience, biology and medicine, ecology, and sociology. While system architecture and their general purpose may depend on domain-specific concepts and definitions, there are (at least) seven key properties of self-organization clearly identified in brain systems: 1) modular connectivity, 2) unsupervised learning, 3) adaptive ability, 4) functional resiliency, 5) (...) functional plasticity, 6) from-local-to-global functional organization, and 7) dynamic system growth. These are defined here in the light of insight from neurobiology, cognitive neuroscience and Adaptive Resonance Theory (ART), and physics to show that self-organization achieves stability and functional plasticity while minimizing structural system complexity. A specific example informed by empirical research is discussed to illustrate how modularity, adaptive learning, and dynamic network growth enable stable yet plastic somatosensory representation for human grip force control. Implications for the design of “strong” artificial intelligence in robotics are brought forward. (shrink)

The abstract basis of modern computation is the formal description of a finite state machine, the Universal Turing Machine, based on manipulation of integers and logic symbols. In this contribution to the discourse on the computer-brain analogy, we discuss the extent to which analog computing, as performed by the mammalian brain, is like and unlike the digital computing of Universal Turing Machines. We begin with ordinary reality being a permanent dialog between continuous and discontinuous worlds. So it is (...) with computing, which can be analog or digital, and is often mixed. The theory behind computers is essentially digital, but efficient simulations of phenomena can be performed by analog devices; indeed, any physical calculation requires implementation in the physical world and is therefore analog to some extent, despite being based on abstract logic and arithmetic. The mammalian brain, comprised of neuronal networks, functions as an analog device and has given rise to artificial neural networks that are implemented as digital algorithms but function as analog models would. Analog constructs compute with the implementation of a variety of feedback and feedforward loops. In contrast, digital algorithms allow the implementation of recursive processes that enable them to generate unparalleled emergent properties. We briefly illustrate how the cortical organization of neurons can integrate signals and make predictions analogically. While we conclude that brains are not digital computers, we speculate on the recent implementation of human writing in the brain as a possible digital path that slowly evolves the brain into a genuine (slow) Turing machine. (shrink)

Sleep has long been a topic of fascination for artists and scientists. Why do we sleep? What function does sleep serve? Why do we dream? What significance can we attach to our dreams? We spend so much of our lives sleeping, yet its precise function is unclear, in spite of our increasing understanding of the processes generating and maintaining sleep. We now know that sleep can be accompanied by periods of intense cerebral activity, yet only recently has experimental data started (...) to provide us with some insights into the type of processing taking place in the brain as we sleep. There is now strong evidence that sleep plays a crucial role in learning and in the consolidation of memories. Once the preserve of psychoanalysts, 'dreaming' is now a topic of increasing interest amongst scientists. With research into sleep growing, this volume is both timely and valuable in presenting a unique study of the relationship between sleep, learning, and memory. It brings together a team of international scientists researching sleep in both human and animal subjects. Aimed at researchers within the fields of neuroscience, cognitive neuroscience, psychiatry, and neurology, this book will be an important first step in developing a full scientific understanding of the most intriguing state of consciousness. (shrink)

The Brain and the Meaning of Life Paul Thagard Princeton: Princeton University Press, 2010 274 pages, ISBN: 9780691142722 (hbk): $29.95 This paper criticizes central arguments in Paul Thagard's The Brain and the Meaning of Life, concluding, contrary to Thagard, that there is very little that we can learn from brain research about the meaning of life. The paper offers a critical review of Thagard's argument against nihilism and his argument that it is love, work, and play, rather (...) than other activities, that make life meaningful. Moreover, the paper argues that the rich neurological information Thagard presents throughout the book does not contribute at all to his arguments and, more generally, that neurological research is irrelevant also to almost all other aspects of meaning of life research. (shrink)

This article provides the foundation for a new predictive theory of animal learning that is based upon a simple logical model. The knowledge of experimental subjects at a given time is described using logical equations. These logical equations are then used to predict a subject’s response when presented with a known or a previously unknown situation. This new theory suc- cessfully anticipates phenomena that existing theories predict, as well as phenomena that they cannot. It provides a theoretical account for (...) phenomena that are beyond the domain of existing models, such as extinction and the detection of novelty, from which “external inhibition” can be explained. Examples of the methods applied to make predictions are given using previously published results. The present theory proposes a new way to envision the minimal functions of the nervous system, and provides possible new insights into the way that brains ultimately create and use knowledge about the world. (shrink)

This contribution proposes how beholders may internally process unfinished works of art. It does so by considering five of Michelangelo Buonarroti’s interrupted sculptures and pointing out their empathic and imaginative potential. The beholder focused on the surface, I propose, is inclined to mentally simulate the artist’s gesture that drafted the sculptures through the visible graphic signs of the chisels. This inner simulation takes place within the activation of various brain networks, located in the brain’s motor system. Renaissance authors (...) associated the observation of the unfinished to learning and, as this article shows, this assumption seems to find confirmation in recent neuroscientific studies on mirror neurons and imitation learning. In this way, the empathic engagement established between the beholder and the work of art observed – as well as the role played by embodied simulation and imagination in this kind of visual perception – clarifies how the incompleteness can also have that pedagogical function recognised by Giorgio Vasari and Benvenuto Cellini. (shrink)

In recent years, there have been many attempts at defining learning as a social phenomenon as opposed to an individual and primarily psychological matter. The move towards understanding learning as social processes has also altered the concept of knowledge as a well-defined element stored in books, brains, CD-Roms, disks, videos or on the Internet. Instead, knowledge has been perceived as a social and context related construction. The roots of the social angle within theories on learning and knowledge (...) are much older than the current literature suggests. This paper illustrates how these theories can be traced back to pragmatism as a philosophy and foundation for an educational approach introduced by the American, John Dewey, more than one hundred years ago. The paper also suggests that Dewey avoids some pitfalls that have come with the new theories, particularly the strong division between individual vs. social and school vs. everyday life learning. (shrink)

This essay examines the relationship between metabolic brain processes and psycho-physiological activities or mental activity. It is argued that metabolic brain processes, including those involved in the production of energy, proteins and other molecules are restorative and conditional, rather than directly involved in mental activities. This stance suggests that life-time acquired learning and memory is precipitated as a permanent and personal configuration of the brain, that is in principle accessible to neurophysiological examination. Current neuroscience largely ignores (...) implicitly or explicitly the search for new emergent configurations of the brain. (shrink)

Henrich et al.'s conclusion that psychologists ought not assume uniformity of psychological phenomena depends on their descriptive claim that there is no pattern to the great diversity in psychological phenomena. We argue that there is a pattern: uniformity of learning processes (broadly construed), and diversity of (some) mental contents (broadly construed).

Background Men with antisocial personality disorder show lifelong abnormalities in adaptive decision making guided by the weighing up of reward and punishment information. Among men with antisocial personality disorder, modifi cation of the behaviour of those with additional diagnoses of psychopathy seems particularly resistant to punishment. Methods We did a case-control functional MRI (fMRI) study in 50 men, of whom 12 were violent off enders with antisocial personality disorder and psychopathy, 20 were violent off enders with antisocial personality disorder but (...) not psychopathy, and 18 were healthy non-off enders. We used fMRI to measure brain activation associated with the representation of punishment or reward information during an event-related probabilistic response-reversal task, assessed with standard general linear-model-based analysis. Findings Offenders with antisocial personality disorder and psychopathy displayed discrete regions of increased activation in the posterior cingulate cortex and anterior insula in response to punished errors during the task reversal phase, and decreased activation to all correct rewarded responses in the superior temporal cortex. This finding was in contrast to results for off enders without psychopathy and healthy non-off enders. Interpretation Punishment prediction error signalling in off enders with antisocial personality disorder and psychopathy was highly atypical. This finding challenges the widely held view that such men are simply characterised by diminished neural sensitivity to punishment. Instead, this fi nding indicates altered organisation of the information processing system responsible for reinforcement learning and appropriate decision making. This difference between violent offenders with antisocial personality disorder with and without psychopathy has implications for the causes of these disorders and for treatment approaches. (shrink)

We contest the unsubstantiated assumption of both materialists and non-materialist that the ontological status they propose applies to all humans and that the competing claim is false for all - ie we reject both the claim of non-materialists that all humans share the same fundamental aspect of having a "non-material consciousness" (nmc), as well as the contrasting claim of materialists that none do (being fully material as according to eliminative materialists/reductive physicalists etc). Instead, the basic proposition of this paper, our (...) ‘ontological conecture’ (OC) - an updated version of our 1998 website article “Mindless Materialists” - is that the central tenets of proponents on both sides are true, but only regarding themselves. A signature feature of nmc is that brains associated to it are capable of knowing of its existence directly, and as a corollary we would propose that if a sophisticated brain does not know it is associated to nmc then most likely this is because it is in fact not so associated. Thus, in accordance with our OC we will consider a brain’s statements on this issue (that it does or does not possess nmc) as not merely its ‘philosophical position’ but as an authoritative statement, a reflection of an ontological fact. Furthermore, we propose that only those who possess nmc are capable of understanding what it is, so that although they are well-qualified to know directly that they themselves possess it, in contrast those who lack nmc and possess only material consciousness (mc) cannot even comprehend what non-materiality means - they will understandably tend to consider it a non-existent absurdity, which contention would be quite correct in a purely-material reality, such as they effectively inhabit. -/- Terminology reflecting ontological status: Since according to our OC those brains which categorize themselves as non-materialists are presumed to indeed be associated to nmc, for usefulness in phraseology we’ll refer to people whose brain is so associated as being nmc’s (not merely “espousing nmc”). Materialists say they are conscious but that theirs is a material consciousness (abbrev: “mc”) , and since according to our OC we accept this self-determination we will refer to them as being “mc’s” or being materialist (not merely “espousing materialism”). -/- Are materialists mindless or are non-materialists delusional? Notoriously, it is impossible to prove that one possesses nmc (which is a sort of corollary to the fact that it is directly self-known) - being non-material, nmc cannot be detected via the scientific method. However just as those with nmc cannot prove they possess it so too one cannot prove or determine via measurement that materialists do not possess it. Nevertheless we feel that our OC is the simplest solution to the conundrum of how there are materialists if a brain can directly sense its associated nmc. In sum, although of course it is impossible to prove that any particular person possesses or lacks nmc, given all the above our OC considers - as stated by the title of this paper - a brain’s self-identification as "materialist" or “non-materialist” (dualist, panpsychist, idealist etc) as reflecting the absence or presence of an associated real non-material awareness/consciousness, rather than merely as a statement of a philosophical stance. An alternative solution is implicit in the above - that all humans possess nmc just that materialists are those whose brains lack the awareness of theirs, or that the brain-aspect which communicates to others has no access to it. -/- Towards developing more constructive dialogue between mc’s/nmc’s, and greater self-confidence and independence among nmc’s in the face of materialist dominance of the intellectual-climate: A large part of the overall paper is devoted to not just pointing out the futility of communication of the sort usually engaged in - ie based on the erroneous underlying assumption that both sides of the debate are ontologically the same - but also suggesting ways to make the debate less frustrating by a recognition of the OC. Greater clarity in discussions can be achieved partly via a deeper understanding of the different meanings the same term might have to nmc’s/mc’s and suggestions relevant the construction of a sort of translation algorithm to utilize in discussions (as a simple example, substituting ‘higher-level cognitive material brain-processes’ for ‘mind’ when that term is used by an mc); by the frank statement by nmc’s engaged in dialogue with mc’s that the existence of nmc is not up for discussion; by learning how the existence of our nmc colors the meaning we give to certain terms in ways we were not aware of, meanings which are absent for mc’s; and in general via the recognition by the nmc that the dialogue is with a person lacking nmc. -/- Perhaps materialists are right: In the interest of ‘reciprocity’, the paper also offers an alternative/opposing view to the central proposition, to the effect that the materialist claim is correct, and it is a defect of brain wiring or structure which is the source of an active illusion of "self-awareness" underlying the philosophical claims of non-materialists. A prospective source of this illusion is offered - an analog of the sense of presence experienced during ‘sleep paralysis’. (shrink)

Humans are uncontroversially better than other species at learning from their peers. A key example of this is imitation, the ability to reproduce both the means and ends of others’ behaviours. Imitation is critical to the acquisition of a number of uniquely human cultural and cognitive traits. However, while authors largely agree on the importance of imitation, they disagree about the origins of imitation in humans. Some argue that imitation is an adaptation, connected to the ‘Mirror Neuron System’ that (...) evolved to facilitate action understanding and the learning of social behaviours. Others argue that imitation is a cultural practice learned in childhood, and that there is no evidence that it evolved genetically. We offer a third alternative that is consistent with both data that the human brain is optimised for imitation, and consistent with its being substantially learned. We hypothesise that at some point in human history humans underwent natural selection for two imitation-relevant abilities – specifically, (i) the tendency to be more attentive to our peers, and (ii) fine motor skill in the manual and oro-facial domains. These changes enabled us to excel at both learning to imitate, and learning by imitating. (shrink)

I often hear people say about children: “They learn like a sponge.” It is clear young brains have a lot more neuroplasticity, which makes it easier for them to learn. But we know from decades of research on neuroplasticity, the capacity for the brain to change and adapt to new situations is there for a lifetime.

Vast archives of fragmentary structural brain scans that are routinely acquired in medical clinics for diagnostic purposes have so far been considered to be unusable for neuroscientific research. Yet, recent studies have proposed that by deploying machine learning algorithms to fill in the missing anatomy, clinical scans could, in future, be used by researchers to gain new insights into various brain disorders. This chapter focuses on a study published in2019, whose authors developed a novel unsupervised machine (...) class='Hi'>learning algorithm for synthesising missing anatomy in extremely sparse clinical MRI scans of thousands of stroke patients. By approaching the study from a media-theoretical perspective, I analyse how its authors dis-cursively negotiated the anatomical and operative plausibility of the unobserved anatomy that their black-boxed algorithm reconstructed from the existing sparse data. My analysis fore-grounds the processual, relational, context-dependent, and essentially unstable character of the thus established plausibility of the algorithmically synthesised neuroanatomy. (shrink)

We propose that Saussure’s signifiers must be processed in the left brain hemisphere (in right handed people) and the signified may be processed in the right. This proposition has consequences for understanding human cognitive phenomena and their pathologies, and can also be related to the passive and active process of thinking, as described by Karl Jaspers. Saussure studied signifiers and their relationships. He left the signified to be studied by psychologists, but there is no consensus about it. According to (...) some linguists, the signified, or the meaning, is the specific activity or succession of bodily states related to each signifier. Learning is the process of linking a signifier (a represented object) to a signified or meaning (a specific activity). However, human beings can represent signifiers autonomously because words and drawings are easily produced with small movements and have syntactic, referential and logical rules of combination. If they are processed in the left hemisphere, the meaning (the signified) is only found when the right hemisphere is reached. The right hemisphere can also work independently, as for instance, when we imagine a story which has to find the words in the left hemisphere. The complex relationship between the hemispheres through the corpus callosum is decisive for telling stories and having self-consciousness. (shrink)

The author has extensive law enforcement experience and the paper is intended to provoke thought on the use of technology as it pertains to information sharing between the police and the private sector. -/- As the world edges closer and closer to the convergence of man and machine, the human capacity to retrieve information is increasing by leaps and bounds. We are on the verge of knowing everything and anything there is to know, and literally in the blink of an (...) eye! -/- This means that police will have the capacity to learn everything about everyone with the only restriction being privacy legislation. But it also means that those involved in immoral, unlawful or illegal activity will have that same capacity and with no such restriction. ‘Bad Brother’ may be far more dangerous than ‘Big Brother!' -/- The global community requires a secure and credible system to retrieve and assess all of the information ‘generally available to the public.' A system that will strive to keep ‘Big Brother’ in check and ‘Bad Brother’ out, all the while providing a means of alerting citizens to genuine risks or to dangerous people. Such as system would help diffuse the systemic inaccurate and harmful profiling that is often based on rumours and innuendo. -/- There is an identified public-private partnership opportunity. A chance to work with privacy advocate groups and background checking private companies to define, design and deliver on something that will be of immense benefit to citizens around the globe. -/- We have an opportunity to create something that will work to ensure that only the best information gets used and in a moralistic, lawful and legal way! Technology continues to move forward at incomprehensible speeds – failure to act could have serious consequences. (shrink)

In this paper, we focus on the most efficacious AI applications for life extension and anti-aging at three expected stages of AI development: narrow AI, AGI and superintelligence. First, we overview the existing research and commercial work performed by a select number of startups and academic projects. We find that at the current stage of “narrow” AI, the most promising areas for life extension are geroprotector-combination discovery, detection of aging biomarkers, and personalized anti-aging therapy. These advances could help currently living (...) people reach longevity escape velocity and survive until more advanced AI appears. When AI comes close to human level, the main contribution to life extension will come from AI integration with humans through brain-computer interfaces, integrated AI assistants capable of autonomously diagnosing and treating health issues, and cyber systems embedded into human bodies. Lastly, we speculate about the more remote future, when AI reaches the level of superintelligence and such life-extension methods as uploading human minds and creating nanotechnological bodies may become possible, thus lowering the probability of human death close to zero. We suggest that medical AI based superintelligence could be safer than, say, military AI, as it may help humans to evolve into part of the future superintelligence via brain augmentation, uploading, and a network of self-improving humans. Medical AI’s value system is focused on human benefit. (shrink)

Ontologies formally represent reality in a way that limits ambiguity and facilitates automated reasoning and data fusion, but is often daunting to the non-technical user. Thus, many researchers have endeavored to hide the formal syntax and semantics of ontologies behind the constructs of Controlled Natural Languages (CNLs), which retain the formal properties of ontologies while simultaneously presenting that information in a comprehensible natural language format. In this paper, we build upon previous work in this field by evaluating prospects of implementing (...) International Technology Alliance Controlled English (ITACE) as a middleware for ontology editing. We also discuss at length a prototype of a natural language conversational interface application designed to facilitate ontology editing via the formulation of CNL constructs. (shrink)

Two universal functional principles of Grossberg’s Adaptive Resonance Theory decipher the brain code of all biological learning and adaptive intelligence. Low-level representations of multisensory stimuli in their immediate environmental context are formed on the basis of bottom-up activation and under the control of top-down matching rules that integrate high-level, long-term traces of contextual configuration. These universal coding principles lead to the establishment of lasting brain signatures of perceptual experience in all living species, from aplysiae to primates. They (...) are re-visited in this concept paper on the basis of examples drawn from the original code and from some of the most recent related empirical findings on contextual modulation in the brain, highlighting the potential of Grossberg’s pioneering insights and groundbreaking theoretical work for intelligent solutions in the domain of developmental and cognitive robotics. (shrink)

Two universal functional principles of Grossberg’s Adaptive Resonance Theory [19] decipher the brain code of all biological learning and adaptive intelligence. Low-level representations of multisensory stimuli in their immediate environmental context are formed on the basis of bottom-up activation and under the control of top-down matching rules that integrate high-level long-term traces of contextual configuration. These universal coding principles lead to the establishment of lasting brain signatures of perceptual experience in all living species, from aplysiae to primates. (...) They are re-visited in this concept paper here on the basis of examples drawn from the original code and from some of the most recent related empirical findings on contextual modulation in the brain, highlighting the potential of Grossberg’s pioneering insights and groundbreaking theoretical work for intelligent solutions in the domain of developmental and cognitive robotics. (shrink)

Brain-related diseases are among the most difficult diseases due to their sensitivity, the difficulty of performing operations, and their high costs. In contrast, the operation is not necessary to succeed, as the results of the operation may be unsuccessful. One of the most common diseases that affect the brain is Alzheimer’s disease, which affects adults, a disease that leads to memory loss and forgetting information in varying degrees. According to the condition of each patient. For these reasons, it (...) is important to classify memory loss and to know the patient at what level and his assessment of Alzheimer's disease through CT scans of the brain. In this thesis, we review ways and techniques to use deep learning classification to classifying the Alzheimer's Disease The proposed method used to improve patient care, reduce costs, and allow fast and reliable analysis in large studies. The model will be designed using Python language for implementing the system, which is very useful for doctors, classifying the Alzheimer's Disease, was used. The model used 70% from image for training and 30% from image for validation, our trained model achieved an accuracy of 100% on a held-out test set. (shrink)

This book consists of an edited collection of original essays of the highest academic quality by seasoned experts in their fields of cognitive science. The essays are interdisciplinary, drawing from many of the fields known collectively as “the cognitive sciences.” Topics discussed represent a significant cross-section of the most current and interesting issues in cognitive science. Specific topics include matters regarding machine learning and cognitive architecture, the nature of cognitive content, the relationship of information to cognition, the role of (...) language and communication in cognition, the nature of embodied cognition, selective topics in visual cognition, brain connectivity, computation and simulation, social and technological issues within the cognitive sciences, and significant issues in the history of neuroscience. This book will be of interest to both professional researchers and newer students and graduate students in the fields of cognitive science—including computer science, linguistics, philosophy, psychology and neuroscience. The essays are in English and are designed to be as free as possible of technical jargon and therefore accessible to young scholars and to scholars who are new to the cognitive neurosciences. In addition to several entries by single authors, the book contains several interesting roundtables where researchers contribute answers to a central question presented to those in the focus group on one of the core areas listed above. This exciting approach provides a variety of perspectives from across disciplines on topics of current concern in the cognitive sciences. (shrink)

The traditional approach to explanation in cognitive neuroscience is realist about psychological constructs, and treats them as explanatory. On the “standard framework,” cognitive neuroscientists explain behavior as the result of the instantiation of psychological functions in brain activity. This strategy is questioned by results suggesting the distribution of function in the brain, the multifunctionality of individual parts of the brain, and the overlap in neural realization of purportedly distinct psychological constructs. One response to this in the field (...) has been to employ the tools of databasing and machine learning to attempt to find and quantify specific correlations between psychological kinds such as ‘memory’ or ‘attention’ (or sub-kinds thereof) and patterns of activity in the brain. I assess the status and prospects of these projects. I argue that current proponents of the project are vague about their aims, vis-à-vis the standard framework, sometimes suggesting substantiation of the framework, sometimes suggesting retaining the framework but revising the ontology of mental constructs, and sometimes suggesting abandonment of the framework. I argue that extant results from within the projects fail to substantiate the standard framework, and propose an alternative. On my view, psychological constructs should not be viewed as explanantia, but instead as heuristic concepts that help us uncover ways that behaviors can vary and the ways that the brain implements those distinctions. I then discuss the normative upshot of these views for databasing and brain mapping projects. (shrink)

Inspired by the eminently successful physical theories and informed by commonplace experiences such as seeing a cat upon looking at a cat, conscious experience is thought of as a measurement or photocopy of given stimulus. Conscious experience, unlike a photocopy, is symbolic—like language—in that the relation between conscious experience and physical stimulus is analogous to that of the word "cat" and its meaning, i.e., arbitrary and yet systematic. We present arguments against the photocopy model and arguments for a symbolic conception (...) of conscious experience. Learning and the corresponding plasticity of the brain make a strong case for the symbolic conception of conscious experience, while many extra-ordinary conscious experiences argue against the formalisation of consciousness as a measuring device. The notions of place-value notation and grammar, which organise quantitative measurements and conscious experiences in the medium of numbers and language, respectively, are suggested as model systems for putting together a comprehensive theory of conscious experience. (shrink)

The creation-evolution “controversy” has been with us for more than a century. Here I argue that merely teaching more science will probably not improve the situation; we need to understand the controversy as part of a broader problem with public acceptance of pseudoscience, and respond by teaching how science works as a method. Critical thinking is difficult to teach, but educators can rely on increasing evidence from neurobiology about how the brain learns, or fails to.

Mathematicians and software developers use the word "function" very differently, and yet, sometimes, things that are in practice implemented using the software developer's "function", are mathematically formalized using the mathematician's "function". This mismatch can lead to inaccurate formalisms. We consider a special case of this meta-problem. Various kinds of agents might, in actual practice, make use of private memory, reading and writing to a memory-bank invisible to the ambient environment. In some sense, we humans do this when we silently subvocalize (...) thoughts about the actions we are taking (at least when the environment we're in is too primitive to probe the contents of our brains). Mathematical function formalizations of agents often ignore this ability. We show that in a general agent-environment framework (of which reinforcement learning is a special case), in a technical sense, such private memories do not enable qualitatively different agent behavior. (shrink)

Clinical evidence has shown that physical exercise during pregnancy may alter brain devel- opment and improve cognitive function of offspring. However, the mechanisms through which maternal exercise might promote such effects are not well understood. The present study examined levels of brain-derived neurotrophic factor (BDNF) and absolute cell num- bers in the hippocampal formation and cerebral cortex of rat pups born from mothers exer- cised during pregnancy. Additionally, we evaluated the cognitive abilities of adult offspring in different behavioral (...) paradigms (exploratory activity and habituation in open field tests, spatial memory in a water maze test, and aversive memory in a step-down inhibitory avoid- ance task). Results showed that maternal exercise during pregnancy increased BDNF lev- els and absolute numbers of neuronal and non-neuronal cells in the hippocampal formation of offspring. No differences in BDNF levels or cell numbers were detected in the cerebral cortex. It was also observed that offspring from exercised mothers exhibited better cognitive performance in nonassociative (habituation) and associative (spatial learning) mnemonic tasks than did offspring from sedentary mothers. Our findings indicate that maternal exer- cise during pregnancy enhances offspring cognitive function (habituation behavior and spa- tial learning) and increases BDNF levels and cell numbers in the hippocampal formation of offspring. (shrink)

The Morris water maze has been put forward in the philosophy of neuroscience as an example of an experimental arrangement that may be used to delineate the cognitive faculty of spatial memory (e.g., Craver and Darden, Theory and method in the neurosciences, University of Pittsburgh Press, Pittsburgh, 2001; Craver, Explaining the brain: Mechanisms and the mosaic unity of neuroscience, Oxford University Press, Oxford, 2007). However, in the experimental and review literature on the water maze throughout the history of its (...) use, we encounter numerous responses to the question of “what” phenomenon it circumscribes ranging from cognitive functions (e.g., “spatial learning”, “spatial navigation”), to representational changes (e.g., “cognitive map formation”) to terms that appear to refer exclusively to observable changes in behavior (e.g., “water maze performance”). To date philosophical analyses of the water maze have not been directed at sorting out what phenomenon the device delineates nor the sources of the different answers to the question of what. I undertake both of these tasks in this paper. I begin with an analysis of Morris’s first published research study using the water maze and demonstrate that he emerged from it with an experimental learning paradigm that at best circumscribed a discrete set of observable changes in behavior. However, it delineated neither a discrete set of representational changes nor a discrete cognitive function. I cite this in combination with a reductionist-oriented research agenda in cellular and molecular neurobiology dating back to the 1980s as two sources of the lack of consistency across the history of the experimental and review literature as to what is under study in the water maze. (shrink)

We chart how neuroscience and philosophy have together advanced our understanding of moral judgment with implications for when it goes well or poorly. The field initially focused on brain areas associated with reason versus emotion in the moral evaluations of sacrificial dilemmas. But new threads of research have studied a wider range of moral evaluations and how they relate to models of brain development and learning. By weaving these threads together, we are developing a better understanding of (...) the neurobiology of moral judgment in adulthood and to some extent in childhood and adolescence. Combined with rigorous evidence from psychology and careful philosophical analysis, neuroscientific evidence can even help shed light on the extent of moral knowledge and on ways to promote healthy moral development. (shrink)

Does the human mind resemble the machines that can behave like it? Biologically inspired machine-learning systems approach “human-level” accuracy in an astounding variety of domains, and even predict human brain activity—raising the exciting possibility that such systems represent the world like we do. However, even seemingly intelligent machines fail in strange and “unhumanlike” ways, threatening their status as models of our minds. How can we know when human–machine behavioral differences reflect deep disparities in their underlying capacities, vs. when (...) such failures are only superficial or peripheral? This article draws on a foundational insight from cognitive science—the distinction between performance and competence—to encourage “species-fair” comparisons between humans and machines. The performance/competence distinction urges us to consider whether the failure of a system to behave as ideally hypothesized, or the failure of one creature to behave like another, arises not because the system lacks the relevant knowledge or internal capacities (“competence”), but instead because of superficial constraints on demonstrating that knowledge (“performance”). I argue that this distinction has been neglected by research comparing human and machine behavior, and that it should be essential to any such comparison. Focusing on the domain of image classification, I identify three factors contributing to the species-fairness of human–machine comparisons, extracted from recent work that equates such constraints. Species-fair comparisons level the playing field between natural and artificial intelligence, so that we can separate more superficial differences from those that may be deep and enduring. (shrink)