Type 2 diabetes mellitus is associated with cognitive impairment in many domains. There are several pieces of evidence that changes in neuronal neuropathies and metabolism have been observed in T2DM. Structural and functional MRI shows that abnormal connections and synchronization occur in T2DM brain circuits and related networks. Neuroplasticity and energy metabolism appear to be principal effector systems, which may be related to amyloid beta deposition, although there is no unified explanation that includes the complex etiology of T2DM with cognitive (...) impairment. Herein, we assume that cognitive impairment in diabetes may lead to abnormalities in neuroplasticity and energy metabolism in the brain, and those reflected to MRI structural connectivity and functional connectivity, respectively. (shrink)

A vexing problem in contemporary epistemology—one with origins in Plato’s Meno—concerns the value of knowledge, and in particular, whether and how the value of knowledge exceeds the value of mere true opinion. The recent literature is deeply divided on the matter of how best to address the problem. One point, however, remains unquestioned: that if a solution is to be found, it will be at the personal level, the level at which states of subjects or agents, as such, appear. We (...) take exception to this orthodoxy, or at least to its unquestioned status. We argue that subpersonal states play a significant—arguably, primary—role in much epistemically relevant cognition and thus constitute a domain in which we might reasonably expect to locate the “missing source” of epistemic value, beyond the value attached to mere true belief. (shrink)

This study aims to disclose how the magnetic resonance imaging neuroimaging approach has been applied in education studies, and what kind of learning themes has been investigated in the reviewed MRI neuroimaging research. Based on the keywords “brain or neuroimaging or neuroscience” and “MRI or diffusion tensor imaging or white matter or gray matter or resting-state,” a total of 25 papers were selected from the subject areas “Educational Psychology” and “Education and Educational Research” from the Web of Science and Scopus (...) from 2000 to 2019. Content analysis showed that MRI neuroimaging and learning were studied under the following three major topics and nine subtopics: cognitive function, science education, and brain development. As for the type of MRI neuroimaging research, the most frequently used approaches were functional MRI, followed by structural MRI and DTI, although the choice of approach was often motivated by the specific research question. Research development trends show that the neural plasticity theme has become more prominent recently. This study concludes that in educational research, the MRI neuroimaging approach provides objective and empirical evidence to connect learning processes, outcomes, and brain mechanisms. (shrink)

Explaining the behaviour of ecosystems is one of the key challenges for the biological sciences. Since 2000, new-mechanicism has been the main model to account for the nature of scientific explanation in biology. The universality of the new-mechanist view in biology has been however put into question due to the existence of explanations that account for some biological phenomena in terms of their mathematical properties (mathematical explanations). Supporters of mathematical explanation have argued that the explanation of the behaviour of ecosystems (...) is usually provided in terms of their mathematical properties, and not in mechanistic terms. They have intensively studied the explanation of the properties of ecosystems that behave following the rules of a non-random network. However, no attention has been devoted to the study of the nature of the explanation in those that form a random network. In this paper, we cover that gap by analysing the explanation of the stability behaviour of the microbiome recently elaborated by Coyte and colleagues, to determine whether it fits with the model of explanation suggested by the new-mechanist or by the defenders of mathematical explanation. Our analysis of this case study supports three theses: (1) that the explanation is not given solely in terms of mechanisms, as the new-mechanists understand the concept; (2) that the mathematical properties that describe the system play an essential explanatory role, but they do not exhaust the explanation; (3) that a non-previously identified appeal to the type of interactions that the entities in the network can exhibit, as well as their abundance, is also necessary for Coyte and colleagues’ account to be fully explanatory. From the combination of these three theses we argue for the necessity of an integrative pluralist view of the nature of behaviour explanation when this is given by appealing to the existence of a random network. (shrink)

The target article argues memory reconsolidation demonstrates how therapeutic change occurs, grounding psychotherapy in brain science. However, consolidation has become an ambiguous term, a disadvantage applying also to its derivative – reconsolidation. The concept of re-association brings greater specificity and explanatory power to the possible brain correlates of therapeutic change.

Modularity in the human brain remains a controversial issue, with disagreement over the nature of the modules that exist, and why, when, and how they emerge. It is a natural assumption that modularity offers some form of computational advantage, and hence evolution by natural selection has translated those advantages into the kind of modular neural structures familiar to cognitive scientists. However, simulations of the evolution of simplified neural systems have shown that, in many cases, it is actually non-modular architectures that (...) are most efficient. In this paper, the relevant issues are discussed and a series of simulations are presented that reveal crucial dependencies on the details of the learning algorithms and tasks that are being modelled, and the importance of taking into account known physical brain constraints, such as the degree of neural connectivity. A pattern is established which provides one explanation of why modularity should emerge reliably across a range of neural processing tasks. (shrink)

Embodied cognitive science has argued that cognition is embodied principally in virtue of grossmorphological and sensorimotor features. This thesis argues that cognition is also internally embodied in affective and fine-grained physiological features whose transformative roles remain mostly unnoticed in contemporary cognitive science. I call this ‘proper embodiment’. I approach this larger subject by examining various emotion theories in philosophy and psychology. These tend to emphasise one of the many gross components of emotional processes, such as ‘feeling’ or ‘judgement’ to the (...) detriment of the others, often leading to an artificial emotion-cognition distinction even within emotion science itself. Attempts to reconcile this by putting the gross components back together, such as JessePrinz’s “embodied appraisal theory”, are, I argue, destined to failure because the vernacular concept of emotion which is used as the explanandum is not a natural kind and is not amenable to scientific explication.I examine Antonio Damasio’s proposal that emotion is involved in paradigmatic ‘cognitive’ processing such as rational decision making and argue (1) that the research he discusses does not warrant the particular hypothesis he favours, and (2) that Damasio’s account, though in many ways a step in the right direction, nonetheless continues to endorse a framework which sees affect and cognition as separate (though now highly interacting) faculties. I further argue that the conflation of ‘affect’ and 'emotion' may be the source of some confusion in emotion theory and that affect needs to be properly distinguished from ‘emotion’. I examine some dissociations in the pain literature which give us further empirical evidence that, as with the emotions, affect is a distinct component along with more cognitive elements of pain. I then argue that affect is distinctive in being grounded in homeostatic regulative activity in the body proper. With the distinction between affect, emotion, and cognition in hand, and the associated grounding of affect in bodily activity, I then survey evidence that bodily affect is also involved in perception and in paradigmatic cognitive processes such as attention and executive function. I argue that this relation is not ‘merely’ casual. Instead, affect (grounded in fine-grained details of internal bodily activity) is partially constitutive of cognition, participating in cognitive processing and contributing to perceptual and cognitive phenomenology. Finally I review some work in evolutionary robotics which reaches a similar conclusion, suggesting that the particular fine details of embodiment, such as molecular signalling between both neural and somatic cells matters to cognition. I conclude that cognition is properly embodied’ in that it is partially constituted by the many fine-grained bodily processes involved in affect (as demonstrated in the thesis) and plausibly by a wide variety of other fine-grained bodily processes that likewise tend to escape the net of contemporary cognitive science. (shrink)

Cognitive systems research has predominantly been guided by the historical distinction between emotion and cognition, and has focused its efforts on modelling the “cognitive” aspects of behaviour. While this initially meant modelling only the control system of cognitive creatures, with the advent of “embodied” cognitive science this expanded to also modelling the interactions between the control system and the external environment. What did not seem to change with this embodiment revolution, however, was the attitude towards affect and emotion in cognitive (...) science. This paper argues that cognitive systems research is now beginning to integrate these aspects of natural cognitive systems into cognitive science proper, not in virtue of traditional “embodied cognitive science”, which focuses predominantly on the body’s gross morphology, but rather in virtue of research into the interoceptive, organismic basis of natural cognitive systems. (shrink)

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)

This paper describes how Tononi’s information integration theory of consciousness was used to make detailed predictions about the distribution of phenomenal states in a spiking neural network. This network had approximately 18,000 neurons and 700,000 connections and it used models of emotion and imagination to control the eye movements of a virtual robot and avoid ‘negative’ stimuli. The first stage in the analysis was the development of a formal definition of Tononi’s theory of consciousness. The network was then analysed for (...) information integration and detailed predictions were made about the distribution of consciousness for each time step of recorded activity. This work demonstrates how an artificial system can be analysed for consciousness using a particular theory and in the future this approach could be used to make predictions about the phenomenal states associated with biological systems. (shrink)

The cognitive unbinding paradigm suggests that the synthesis of neural information is attenuated by general anesthesia. Here, we analyzed the functional organization of brain activities in the conscious and anesthetized states, based on functional segregation and integration. Electroencephalography recordings were obtained from 14 subjects undergoing induction of general anesthesia with propofol. We quantified changes in mean information integration capacity in each band of the EEG. After induction with propofol, mean information integration capacity was reduced most prominently in the γ band (...) of the EEG . Furthermore, we demonstrate that loss of consciousness is reflected by the breakdown of the spatiotemporal organization of γ waves. We conclude that induction of general anesthesia with propofol reduces the capacity for information integration in the brain. These data directly support the information integration theory of consciousness and the cognitive unbinding paradigm of general anesthesia. (shrink)

Social network theory is an important paradigm of social structure research, which has been widely used in various fields of research. This paper reviews the development process and the latest progress of social network theory research and analyzes the research application of social network. In order to reveal the deep social structure, this paper analyzes the structure of social networks from three levels: microlevel, mesolevel, and macrolevel and reveals the origin, development, perfection, and latest achievements of complex network models. The (...) regular graph model, P1 model, P2 model, exponential random graph model, small-world network model, and scale-free network model are introduced. In the end, the research on the social network structure is reviewed, and social support network and social discussion network are introduced, which are two important contents of social network research. At present, the research on social networks has been widely used in coauthor networks, citation networks, mobile social networks, enterprise knowledge management, and individual happiness, but there are few research studies on multilevel structure, dynamic research, complex network research, whole network research, and discussion network research. This provides space for future research on social networks. (shrink)

In spite of the remarkable progress made in the burgeoning field of social neuroscience, the neural mechanisms that underlie social encounters are only beginning to be studied and could —paradoxically— be seen as representing the ‘dark matter’ of social neuroscience. Recent conceptual and empirical developments consistently indicate the need for investigations, which allow the study of real-time social encounters in a truly interactive manner. This suggestion is based on the premise that social cognition is fundamentally different when we are in (...) interaction with others rather than merely observing them. In this article, we outline the theoretical conception of a second-person approach to other minds and review evidence from neuroimaging, psychophysiological studies and related fields to argue for the development of a second-person neuroscience, which will help neuroscience to really go social; this may also be relevant for our understanding of psychiatric disorders construed as disorders of social cognition. (shrink)

An important shift is taking place in social cognition research, away from a focus on the individual mind and toward embodied and participatory aspects of social understanding. Empirical results already imply that social cognition is not reducible to the workings of individual cognitive mechanisms. To galvanize this interactive turn, we provide an operational definition of social interaction and distinguish the different explanatory roles – contextual, enabling and constitutive – it can play in social cognition. We show that interactive processes are (...) more than a context for social cognition: they can complement and even replace individual mechanisms. This new explanatory power of social interaction can push the field forward by expanding the possibilities of scientific explanation beyond the individual. (shrink)

Joint attention has been extensively studied in the developmental literature because of overwhelming evidence that the ability to socially coordinate visual attention to an object is essential to healthy developmental outcomes, including language learning. The goal of this study was to understand the complex system of sensory-motor behaviors that may underlie the establishment of joint attention between parents and toddlers. In an experimental task, parents and toddlers played together with multiple toys. We objectively measured joint attention—and the sensory-motor behaviors that (...) underlie it—using a dual head-mounted eye-tracking system and frame-by-frame coding of manual actions. By tracking the momentary visual fixations and hand actions of each participant, we precisely determined just how often they fixated on the same object at the same time, the visual behaviors that preceded joint attention and manual behaviors that preceded and co-occurred with joint attention. We found that multiple sequential sensory-motor patterns lead to joint attention. In addition, there are developmental changes in this multi-pathway system evidenced as variations in strength among multiple routes. We propose that coordinated visual attention between parents and toddlers is primarily a sensory-motor behavior. Skill in achieving coordinated visual attention in social settings—like skills in other sensory-motor domains—emerges from multiple pathways to the same functional end. (shrink)

The resurgence of interest in collective behavior is in large part due to tools recently made available for conducting laboratory experiments on groups, statistical methods for analyzing large data sets reflecting social interactions, the rapid growth of a diverse variety of online self‐organized collectives, and computational modeling methods for understanding both universal and scenario‐specific social patterns. We consider case studies of collective behavior along four attributes: the primary motivation of individuals within the group, kinds of interactions among individuals, typical dynamics (...) that result from these interactions, and characteristic outcomes at the group level. With this framework, we compare the collective patterns of noninteracting decision makers, bee swarms, groups forming paths in physical and abstract spaces, sports teams, cooperation and competition for resource usage, and the spread and extension of innovations in an online community. Some critical issues surrounding collective behavior are then reviewed, including the questions of “Does group behavior always reduce to individual behavior?”“Is ‘group cognition’ possible?” and “What is the value of formal modeling for understanding group behavior?”. (shrink)

Various methods have been employed to investigate different aspects of the brain activity modulation related to the performance of a cycling task. In our study we examined how functional connectivity and brain network efficiency varied during an endurance cycling task. To this purpose, we reconstructed EEG signals at source level: we computed current densities in 28 anatomical regions of interest (ROIs) through the eLORETA algorithm, then we calculated the Lagged Coherence of the 28 current density signals to define the adjacency (...) matrix. To quantify changes of functional network efficiency during an exhaustive cycling task, we computed three graph theoretical indices: local efficiency (LE), global efficiency (GE) and Density (D) in two different frequency bands, Alpha and Beta bands, that indicate alertness processes and motor binding/fatigue respectively. This analysis was conducted for six different task intervals: pre-cycling, initial, intermediate and final stages of cycling, active recovery and passive recovery. Fourteen participants performed an incremental cycling task with simultaneous EEG recording and RPE monitoring to detect participants’ exhaustion. LE remained constant during the endurance cycling task in both bands. Therefore, we speculate that fatigue processes did not affect segregated neural processing. We observed an increase of GE in the Alpha band only during cycling, that could be due to greater alertness processes and preparedness to stimuli during exercise. Conversely, although D did not change significantly over time in the Alpha band, its general reduction in the Beta bands during cycling could be interpreted within the framework of the neural efficiency hypothesis, which posits a reduced neural activity for expert/automated performances. We argue that the use of graph theoretical indices represents a clear methodological advancement in studying endurance performance. (shrink)

1. Dal mito delle facoltà alle reti neurali «Neurophysiologica sunt, non leguntur!» Rifacendo il verso a una celebre battuta fregeana, questa esortazione sembra condensare il fastidio di molti filosofi di fronte all’ingerenza dei neuroscienziati, i quali s’illuderebbero di risolvere i massimi problemi di filosofia della mente, soprattutto quelli legati al sorgere della coscienza e agli aspetti qualitativi delle sensazioni. Viceversa, forse per sentirsi legittimati a trattare quei problemi, g...

We propose a model of evolving protection against systemic risk related to recovery. Using the failure potential in network-agent dynamics, we present a process-based simulation that provides insights into alternative interventions and their mechanical uniqueness. The fundamental operating principle of this model is that computation allows greater emphasis on optimizing the recovery within the general regularity of random network dynamics. The rules and processes that are used here could be regarded as useful techniques in systemic risk measurement relative to numerical (...) failure reduction analyses. (shrink)

We argue that Anderson's (MRH) needs further development in several directions. First, a thoroughgoing criticism of the several alternatives is required. Second, the course between the Scylla of full holism and the Charybdis of structural-functional modularism must be plotted more distinctly. Third, methodologies better suited to reveal brain circuits must be brought in. Finally, the constraints that naturalistic settings provide should be considered.