Susceptibility to the rubber hand illusion (RHI) varies. To date, however, there is no consensus explanation of this variability. Previous studies, focused on the role of multisensory integration, have searched for neural correlates of the illusion. But those studies have failed to identify a sufficient set of functionally specific neural correlates. Because some evidence suggests that frontal α power is one means of tracking neural instantiations of self, we hypothesized that the higher the frontal α power during (...) the eyes-closed resting state, the more stable the self. As a corollary, we infer that the more stable the self, the less susceptible are participants to a blurring of boundaries—to feeling that the rubber hand belongs to them. Indeed, we found that frontal α amplitude oscillations negatively correlate with susceptibility. Moreover, since lower frequencies often modulate higher frequencies, we explored the possibility that this might be the case for the RHI. Indeed, some evidence suggests that high frontal α power observed in low-RHI participants is modulated by δ frequency oscillations. We conclude that while neural correlates of multisensory integration might be necessary for the RHI, sufficient explanation involves variable intrinsic neural activity that modulates how the brain responds to incompatible sensory stimuli. (shrink)

The brain’s intrinsic activity plays a fundamental role in its function. In normal conditions this activity is responsive to behavioural context, changing as an individual switches between directed tasks and task‐free conditions. A key feature of such changes is the movement of the brain between corresponding critical and sub‐critical states, with these dynamics supporting efficient cognitive processing. Breakdowns in processing efficiency can occur, however, in brain disorders such as depression. It was therefore hypothesised that depressive symptoms would (...) be related to reduced intrinsic activity responsiveness to changes in behavioural state. This was tested in a mixed group of major depressive disorder patients (n = 26) and healthy participants (n = 37) by measuring intrinsic EEG activity temporal structure, quantified with detrended fluctuation analysis (DFA), in eyes‐closed and eyes‐open task‐free states and contrasting between the conditions. The degree to which DFA values changed between the states was found to be negatively correlated with depressive symptoms. DFA values did not differ between states at all in those with higher symptom levels, meaning that the brain remained in a less flexible sub‐critical condition. This sub‐critical condition in the eyes‐closed state was further found to correlate with levels of maladaptive rumination. This may reflect a general cognitive inflexibility resulting from a lack in neural activity reactivity that may predispose people to overly engage in self‐directed attention. These results provide an initial link between intrinsic activity reactivity and psychological features found in psychiatric disorders. (shrink)

Evidence that minds are neural electromagnetic fields comes from research into how separate brain activities bind to form unified percepts and unified minds. Explanations of binding using synchrony, attention, and convergence are all problematic. But the unity of EM fields explains binding without these problems. These unified fields neatly explain correlations and divergences between synchrony, attention, convergence, and unified minds. The simplest explanation for the unity of both minds and fields is that minds are fields. Treating minds as the (...) fields' underlying, intrinsic nature has the further virtue of avoiding mind-body problems. There's also rising evidence that EM fields interact with brains. McFadden argues here that fields help shift the focus of attention by initiating synchrony in different neural networks, which boosts their own fields and thereby binds their activity. This evidence that minds are fields that bind and guide brain activities supports free will over epiphenomenalism and supervenience. (shrink)

In recent times we have seen an explosion in the amount of attention paid to the conscious brain from scientists and philosophers alike. One message that has emerged loud and clear from scientific work is that the brain is a dynamical system whose operations unfold in time. Any theory of consciousness that is going to be physically realistic must take account of the intrinsic nature of neurons and brain activity. At the same time a long discussion on consciousness (...) among philosophers has resulted in our distinguishing several kinds of consciousness. So when we ask where the place of consciousness is in nature we may mean several different things. In this chapter I will argue that it is plausible that all of the kinds of consciousness turn out to be nothing but patterns of synchronized neural activity in various frequencies against a dynamically changing chemical background. (shrink)

This paper presents the unification of all knowledge and the framework of all sciences, so it goes the theory of consciousness, the method to measure consciousness, and the three keys of the Strong AI. “Logicality and non-absoluteness” is found out to be the intrinsicality of nature, so the “Fundamental Law of Nature” is discovered. Then, the “general methodology of research” and the “model system of nature” are developed to explain everything, especially consciousness. The Coupling Theory of Consciousness tells that nature (...) has the MFEs (More Fundamental Element) that couple to show as material and consciousness, and the brain has a CNS (central nervous system)-independent consciousness system that couples to give off the consciousness signals, with their three excitation levels to show as memory, sub-consciousness, and subjective consciousness. As consciousness is not from neurons, the method to measure consciousness via NCC (neural correlates of consciousness) is to find out participants with the same kinds of consciousness systems. And make them to produce paralleled “conscious information processes” to filtrate out the “noise” neural activities, to obtain the “real” NCC data. Examining the property of consciousness may advance not only neuroscience and physics, but also cognitive science and AI technology. First, the “conscious information processing” model has shown that the Strong AI should process the beyond-domain concepts with a self-controlled intention, second, as the “general methodology of research” is just the other name of the “principle of cognition”, we have already known the running style of the Strong AI. Hopefully, we could develop the Strong AI technology to upgrade human civilization very soon. (shrink)

Neurovascular coupling (NVC), the transient regional hyperemia following the evoked neuronal responses, is the basis of blood oxygenation level-dependent techniques and is generally adopted across physiological conditions, including the intrinsic resting state. However, the possibility of neurovascular dissociations across physiological alterations is indicated in the literature. To examine the NVC stability across sleep–wake states, we used electroencephalography (EEG) as the index of neural activity and functional magnetic resonance imaging (fMRI) as the measure of cerebrovascular response. Eight healthy (...) adults were recruited for simultaneous EEG-fMRI recordings in nocturnal sleep. We compared the cross-modality (EEG vs. fMRI) consistency of functional indices (spectral amplitude and functional connectivity) among five states of wakefulness and sleep (state effect). We also segregated the brain into three main partitions (anterior, middle and posterior) for spatial assessments (regional effect). Significant state effects were found on δ, α and fMRI indices and regional effects on the α and fMRI indices. However, the cross-state EEG changes in spectral amplitude and functional connectivity did not consistently match the changes in the fMRI indices across sleep–wake states. In spectral amplitude, the δ band peaked at the N3 stage for all brain regions, while the fMRI fluctuation amplitude peaked at the N2 stage in the central and posterior regions. In regional connectivity, the inter-hemispheric connectivity of the δ band peaked at the N3 stage for all regions, but the bilateral fMRI connectivity showed the state changes in the anterior and central regions. The cross-modality inconsistencies across sleep–wake states provided preliminary evidence that the neurovascular relationship may not change in a linear consistency during NREM sleep. Thus, caution shall be exercised when applying the NVC presumption to investigating sleep/wake transitions, even among healthy young adults. (shrink)

Logic is useful as a neutral formalism for expressing the contents of mental representations. It can be used to extract crisp conclusions regarding the higher-order theory of phenomenal consciousness developed in (McDermott 2001, 20007). A key aspect of conscious perceptions is their connection to the distinction between appearance and reality. Perceptions must often be corrected. To do so requires that the logic of perception be able to represent the logical structure of judgment events, that is, to include the formulas of (...) the logic as objects to be reasoned about. However, there is a limit to how finely humans can examine their own representations. Terms representing primary and secondary qualities seemed to be _locked,_ so that the numbers (or levels of neural activation) that are their essence are not directly accessible. Humans feel a need to invoke ``intrinsic,'' ``nonrelational'' properties of many secondary qualities --- their _qualia_ --- to ``explicate'' how we compare and discriminate among them, although this is not actually how the comparisons are accomplished. This model of qualia explains several things: It accounts for the difference between ``normal'' and ``introspective'' access to a perceptual module in terms of quotation. It dissolves Jackson's knowledge argument by explaining what Mary learns as a fictional but undoubtable belief structure. It makes spectrum inversion logically impossible by providing a degree of freedom between the physical structure of the brain and the representations it contains that redescribes putative cases of spectrum inversion as alternative but equivalent ways of mapping physical states to representational states. (shrink)

Objective: Alterations in psychomotor dimension cut across different psychiatric disorders, such as schizophrenia (SCZ) and bipolar disorder (BD). This preliminary study aimed to investigate the organization of intrinsic brain activity in the subcortical-cortical sensorimotor system in SCZ (and BD) as characterized according to psychomotor dimension. -/- Method: In this resting-state functional magnetic resonance imaging (fMRI) study, functional connectivity (FC) between thalamus and sensorimotor network (SMN), along with FC from substantia nigra (SN) and raphe nuclei (RN) to basal ganglia (...) (BG) and thalamic regions, were investigated by using an a-priori-driven and dimensional approach. This was done in two datasets: SCZ patients showing inhibited psychomotricity (n = 18) vs. controls (n = 19); SCZ patients showing excited psychomotricity (n = 20) vs. controls (n = 108). Data from a third dataset of BD in inhibited depressive or manic phases (reflecting inhibited or excited psychomotricity) were used as control. -/- Results: SCZ patients suffering from psychomotor inhibition showed decreased thalamus-SMN FC toward around-zero values paralleled by a concomitant reduction of SN-BG/thalamus FC and RN-BG/thalamus FC (as BD patients in inhibited depression). By contrast, SCZ patients suffering from psychomotor excitation exhibited increased thalamus-SMN FC toward positive values paralleled by a concomitant reduction of RN-BG/thalamus FC (as BD patients in mania). -/- Conclusions: These findings suggest that patients exhibiting low or high levels of psychomotor activity show distinct patterns of thalamus-SMN coupling, which could be traced to specific deficit in SN- or RN-related connectivity. Notably, this was independent from the diagnosis of SCZ or BD, supporting an RDoC-like dimensional approach to psychomotricity. (shrink)

A model of consciousness and conscious experience is introduced. Starting with a non-Lipschitz Chaotic dynamics of neural activity, we propose that the synaptic transmission between adjacent as well as distant neurons should be regulated in brain dynamics through quantum tunneling. Further, based on various studies of different previous authors, we consider the emergence of very large quantum mechanical system representable by an abstract quantum net entirely based on quantum-like entities having in particular the important feature of expressing self-reference (...) similar to what occurs in consciousness. The properties of such quantum-like mind entities are discussed in detail. A quantum-like model of conscious experience is also discussed. It is shown that such quantum mechanical entities are able to arrange themselves alternatively on the basis of the subject story, memory, and pain-pleasure in response to an external stimulus, thus giving the subject the possibility to response to the stimulus on the basis of his emotion as well as cognitive state. Finally, we discuss the possible connections between the quantum-like model introduced in this paper and the chaotic behaviors often identified experimentally in studies on brain dynamics. Part I of this article contains: Introduction; 1. Non Lipschitz Terminal Dynamics of Single Neuron Activity; and References; 2. Quantum Mechanical Properties of Neuron Dynamics; and 3. A Quantum Model of Consciousness I. (shrink)

Despite the huge and constant progress in the molecular and cellular neuroscience fields, our capability to understand brain alterations and treat mental illness is still limited. Therefore, a paradigm shift able to overcome such limitation is warranted. Behavior and the associated mental states are the interface between the central nervous system and the living environment. Since, in any system, the interface is a key regulator of system organization, behavior is proposed here as a unique and privileged level of control and (...) orchestration of brain structure and activity. This view has relevant scientific and clinical implications. First, the study of behavior represents a singular starting point for the investigation of neural activity in an integrated and comprehensive fashion. Second, behavioral changes, accomplished through psychotherapy or environmental interventions, are expected to have the highest impact to specifically reorganize the complexity of the human mind and thus achieve a solid and long-lasting improvement in mental health. (shrink)

The origin and development of consciousness is poorly understood. Although it is clearly a naturalistic phenomenon evolved through Darwinian evolution, explaining it in terms of physicochemical, neural, or symbolic mechanisms remains elusive. Here I propose that two steps had to be taken in its evolution. First, living systems evolved an intrinsic goal-directedness by internalizing Darwinian fitness as a self-estimated fitness. The self-estimated fitness participates in a feedback loop that effectively produces intrinsic meaning in the organism. Second, animals (...) with advanced nervous systems evolved a special form of communication that modifies the way each partner estimates fitness. The resulting change in intrinsic meaning is experienced subjectively as a primary form of consciousness. This primary form is subsequently used to generate, partly through internalized dialogue, more complex forms of consciousness, such as consciousness of the natural and social worlds, consciousness of the self, and language-dependent forms of consciousness. An updated version of the theory in this paper can be found as Chapter 12 ('Consciousness') in my book 'The estimator theory of life and mind: how agency and consciousness can emerge', see VANTET-8 at philpapers . (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)

Recently, active suspension system will become important to the vehicle industries because of its advantages in improving road managing and ride comfort. This paper offers the development of mathematical modelling and design of a neural network control approach. The paper will begin with a mathematical model designing primarily based at the parameters of the active suspension system. A nonlinear three by four-way valve-piston hydraulic actuator became advanced which will make the suspension system under the active condition. Then, the model (...) can be analyzed thru MATLAB/Simulink software program. Finally, the NARMA-L2, model reference and predictive controllers are designed for the active suspension system. The results are acquired after designing the simulation of the quarter-car nonlinear active suspension system. From the simulation end result using MATLAB/Simulink, the response of the system might be as compared between the nonlinear active suspension system with NARMA-L2, model reference and predictive controllers. Besides that, the evaluation has been made between the proposed controllers thru the characteristics of the manage objectives suspension deflection, body acceleration and body travel of the active suspension system. . As a conclusion, designing a nonlinear active suspension system with a nonlinear hydraulic actuator for quarter car model has improved the car performance by using a NARMA-L2 controller. The improvements in performance will improve road handling and ride comfort performance of the active suspension system. (shrink)

To find the neural substrates of consciousness, researchers compare subjects’ neural activity when they are aware of stimuli against neural activity when they are not aware. Ideally, to guarantee that the neural substrates of consciousness—and nothing but the neural substrates of consciousness—are isolated, the only difference between these two contrast conditions should be conscious awareness. Nevertheless, in practice, it is quite challenging to eliminate confounds and irrelevant differences between conscious and unconscious conditions. In (...) particular, there is an often-neglected confound that is crucial to eliminate from neuroimaging studies: task performance. Unless subjects’ task performance is matched (and hence perceptual signal processing is matched), researchers risk finding the neural correlates of perception, rather than conscious perception. Here, we discuss the theoretical motivations for the performance matching framework and review empirical demonstrations of, and theoretical inferences derived from, obtaining differences in consciousness while controlling for task performance. We summarize signal detection theoretic modeling frameworks that explain how it is that we can derive performance-matched differences in consciousness without the effect being trivially driven by differences in criterion setting, and also provide principles for designing experimental paradigms that yield performance-matched differences in awareness. Finally, we address potential technical and theoretical issues that stem from matching performance across conditions of awareness, and we introduce the notion of “triangulation” for designing comprehensive experimental sets that can better reveal the neural substrates of consciousness. (shrink)

We explore the contribution made by oscillatory, synchronous neural activity to representation in the brain. We closely examine six prominent examples of brain function in which neural oscillations play a central role, and identify two levels of involvement that these oscillations take in the emergence of representations: enabling (when oscillations help to establish a communication channel between sender and receiver, or are causally involved in triggering a representation) and properly representational (when oscillations are a constitutive part of (...) the representation). We show that even an idealized informational sender–receiver account of representation makes the representational status of oscillations a non-trivial matter, which depends on rather minute empirical details. (shrink)

Multivariate pattern analysis, or MVPA, has become one of the most popular analytic methods in cognitive neuroscience. Since its inception, MVPA has been heralded as offering much more than regular univariate analyses, for—we are told—it not only can tell us which brain regions are engaged while processing particular stimuli, but also which patterns of neural activity represent the categories the stimuli are selected from. We disagree, and in the current paper we offer four conceptual challenges to the use (...) of MVPA to make claims about neural representation. Our view is that the use of MVPA to make claims about neural representation is problematic. (shrink)

Neural activity varies continually from moment to moment. Such temporal variability (TV) has been highlighted as a functionally specific brain property playing a fundamental role in cognition. We sought to investigate the mechanisms involved in TV changes between two basic behavioral states, namely having the eyes open (EO) or eyes closed (EC) in vivo in humans. To these ends we acquired BOLD fMRI, ASL, and [18F]-fluoro-deoxyglucose PET in a group of healthy participants (n = 15), along with BOLD (...) fMRI and [18F]-flumazenil PET in a separate group (n = 19). Focusing on an EO- vs EC-sensitive region in the occipital cortex (identified in an independent sample), we show that TV is constrained in the EO condition compared to EC. This reduction is correlated with an increase in energy consumption and with regional GABAA receptor density. This suggests that the modulation of TV by behavioral state involves an increase in overall neural activity that is related to an increased effect from GABAergic inhibition in addition to any excitatory changes. These findings contribute to our understanding of the mechanisms underlying activity variability in the human brain and its control. (shrink)

Neural structural representations are cerebral map- or model-like structures that structurally resemble what they represent. These representations are absolutely central to the “cognitive neuroscience revolution”, as they are the only type of representation compatible with the revolutionaries’ mechanistic commitments. Crucially, however, these very same commitments entail that structural representations can be observed in the swirl of neuronal activity. Here, I argue that no structural representations have been observed being present in our neuronal activity, no matter the spatiotemporal (...) scale of observation. My argument begins by introducing the “cognitive neuroscience revolution” (Sect. 1 ) and sketching a prominent, widely adopted account of structural representations (Sect. 2 ). Then, I will consult various reports that describe our neuronal activity at various spatiotemporal scales, arguing that none of them reports the presence of structural representations (Sect. 3 ). After having deflected certain intuitive objections to my analysis (Sect. 4 ), I will conclude that, in the absence of neural structural representations, representationalism and mechanism can’t go together, and so the “cognitive neuroscience revolution” is forced to abandon one of its commitments (Sect. 5 ). (shrink)

Spontaneous activity levels prior to stimulus presentation can determine how that stimulus will be perceived. It has also been proposed that such spontaneous activity, particularly in the default-mode network (DMN), is involved in self-related processing. We therefore hypothesised that pre-stimulus activity levels in the DMN predict whether a stimulus is judged as self-related or not. Method: Participants were presented in the MRI scanner with a white noise stimulus that they were instructed contained their name or another. They (...) then had to respond with which name they thought they heard. Regions where there was an activity level difference between self and other response trials two seconds prior to the stimulus being presented were identified. Results: Pre-stimulus activity levels were higher in the right temporoparietal junction (RTPJ), the right temporal pole (RTP), and the left superior temporal gyrus in trials where the participant responded that they heard their own name than trials where they responded that they heard another. Conclusion: Pre-stimulus spontaneous activity levels in particular brain regions, largely overlapping with the DMN, predict the subsequent judgement of stimuli as self-related. This extends our current knowledge of self-related processing and its apparent relationship with intrinsic brain activity in what can be termed a rest-self overlap. (shrink)

The connection between brain and mind is an important scientific and philosophical question that we are still far from completely understanding. A crucial point to our work is noticing that thermodynamics provides a convenient framework to model brain activity, whereas cognition can be modeled in information-theoretical terms. In fact, several models have been proposed so far from both approaches. A second critical remark is the existence of deep theoretical connections between thermodynamics and information theory. In fact, some well-known authors (...) claim that the laws of thermodynamics are nothing but principles in information theory. Unlike in physics or chemistry, a formalization of the relationship between information and energy is currently lacking in neuroscience. In this paper we propose a framework to connect physical brain and cognitive models by means of the theoretical connections between information theory and thermodynamics. Ultimately, this article aims at providing further insight on the formal relationship between cognition and neural activity. (shrink)

Metacontrast is a visual illusion in which the visibility of a target stimulus is virtually lost when immediately followed by a nonoverlapping mask stimulus. For a colored target, metacontrast is color-selective, with target visibility markedly reduced when the mask and target are the same color, but only slightly reduced when the colors differ. This study investigated neural correlates of color-selective metacontrast for cone-opponent red and green stimuli in the human V1, V2, and V3 using functional magnetic resonance imaging. (...) class='Hi'>Neural activity was suppressed when the target was rendered less visible by the same-colored mask, and the suppression was localized in the cortical region retinotopically representing the target, correlating with the perceptual topography of visibility/invisibility rather than the physical topography of the stimulus. Retinotopy-based group analysis found that activity suppression was statistically significant for V2 and V3 and that its localization to the target region was statistically significant for V2. These results suggest that retinotopic color representations in early visual areas, especially in V2, are closely linked to the visibility of color. (shrink)

Recent advancements in the brain sciences have enabled researchers to determine, with increasing accuracy, patterns and locations of neural activation associated with various psychological functions. These techniques have revived a longstanding debate regarding the relation between the mind and the brain: while many authors claim that neuroscientific data can be employed to advance theories of higher cognition, others defend the so-called ‘autonomy’ of psychology. Settling this significant issue requires understanding the nature of the bridge laws used at the psycho- (...) class='Hi'>neural interface. While these laws have been the topic of extensive discussion, such debates have mostly focused on a particular type of link: reductive laws. Reductive laws are problematic: they face notorious philosophical objections and they are too scarce to substantiate current research at the intersection of psychology and neuroscience. The aim of this article is to provide a systematic analysis of a different kind of bridge laws—associative laws—which play a central, albeit overlooked role in scientific practice. (shrink)

Abstract: This research paper presents a novel approach to predict audit risks using a neural network model. The dataset used for this study was obtained from Kaggle and comprises 774 samples with 18 features, including Sector_score, PARA_A, SCORE_A, PARA_B, SCORE_B, TOTAL, numbers, marks, Money_Value, District, Loss, Loss_SCORE, History, History_score, score, and Risk. The proposed neural network architecture consists of three layers, including one input layer, one hidden layer, and one output layer. The neural network model was trained (...) and validated, achieving an impressive accuracy of 100% and an average error of 0.000015, indicating its robust predictive capability. Moreover, we conducted feature importance analysis to identify the most influential features for predicting audit risk. The key features found to be critical for classifying fraudulent activities in audit risk prediction are Sector_score, PARA_A, SCORE_A, PARA_B, SCORE_B, TOTAL, numbers, marks, Money_Value, District, Loss, Loss_SCORE, History, and History_score. This research contributes to the field of audit risk prediction by demonstrating the effectiveness of a neural network-based approach and highlighting the importance of specific features in detecting fraudulent activities. The findings have significant implications for auditors and organizations seeking to enhance their audit risk assessment processes, ultimately leading to improved financial transparency and fraud detection. (shrink)

This study compares the neural substrate of moral decision making processes between Korean and American participants. By comparison with Americans, Korean participants showed increased activity in the right putamen associated with socio-intuitive processes and right superior frontal gyrus associated with cognitive control processes under a moral-personal condition, and in the right postcentral sulcus associated with mental calculation in familiar contexts under a moral-impersonal condition. On the other hand, American participants showed a significantly higher degree of activity in (...) the bilateral anterior cingulate cortex (ACC) associated with conflict resolution under the moral-personal condition, and in the right medial frontal gyrus (MFG) associated with simple cognitive branching in non-familiar contexts under the moral-impersonal condition when a more lenient threshold was applied, than Korean participants. These findings support the ideas of the interactions between the cultural background, education, and brain development, proposed in the field of cultural psychology and educational psychology. The study introduces educational implications relevant to moral psychologists and educators. (shrink)

The higher-order thought (HOT) theory of consciousness is a reductive representational theory of consciousness which says that what makes a mental state conscious is that there is a suitable HOT directed at that mental state. Although it seems that any neural realization of the theory must be somewhat widely distributed in the brain, it remains unclear just how widely distributed it needs to be. In section I, I provide some background and define some key terms. In section II, I (...) argue against the view that HOT theory should treat first-order (i.e. world-directed) conscious states as requiring prefrontal cortical activity though it is reasonable to suppose that conscious states are realized in the brain. In section III, I then explore some of the key background metaphysical issues involved in understanding the nature of consciousness, such as the debate between realism and idealism as well as the prospects for solving the so-called “hard problem” of consciousness. Some of the differences in question often mirror the traditional differences between Western and Eastern perspectives on the nature of consciousness. Overall, I argue that some form of realism and physicalism is more plausible than the opposing views. I also argue that materialists (and especially HOT theorists) can offer plausible replies to the hard problem. (shrink)

We consider the relationship between neural and behavioural evidence for animal consciousness. We critically examine two recent studies: one neural and one behavioural. The first, on crows, finds different neural activity depending on whether a stimulus is reported as seen or unseen. However, to implicate this neural activity in consciousness, we must assume that a specific conditioned behaviour is a report of conscious experience. The second study, on macaques, records behaviours strikingly similar to patterns (...) of conscious and unconscious perception in humans. However, confounds are only ruled out in human subjects, presupposing substantial neural similarity between humans and macaques. Taken together, the two studies reveal a sense in which neural and behavioural research rely on each other. Looking ahead, these two types of evidence could prove to be either mutually reinforcing or mutually undermining. The science of animal consciousness needs both neural and behavioural evidence, ideally obtained as part of a single coordinated programme. (shrink)

The so-called Baldwin Effect generally says how learning, as a form of ontogenetic adaptation, can influence the process of phylogenetic adaptation, or evolution. This idea has also been taken into computation in which evolution and learning are used as computational metaphors, including evolving neural networks. This paper presents a technique called evolving self-taught neural networks – neural networks that can teach themselves without external supervision or reward. The self-taught neural network is intrinsically motivated. Moreover, the self-taught (...) neural network is the product of the interplay between evolution and learning. We simulate a multi-agent system in which neural networks are used to control autonomous agents. These agents have to forage for resources and compete for their own survival. Experimental results show that the interaction between evolution and the ability to teach oneself in self-taught neural networks outperform evolution and self-teaching alone. More specifically, the emergence of an intelligent foraging strategy is also demonstrated through that interaction. Indications for future work on evolving neural networks are also presented. (shrink)

Computer assisted theorem proving is an increasingly important part of mathematical methodology, as well as a long-standing topic in artificial intelligence (AI) research. However, the current generation of theorem proving software have limited functioning in terms of providing new proofs. Importantly, they are not able to discriminate interesting theorems and proofs from trivial ones. In order for computers to develop further in theorem proving, there would need to be a radical change in how the software functions. Recently, machine learning results (...) in solving mathematical tasks have shown early promise that deep artificial neural networks could learn symbolic mathematical processing. In this paper, I analyze the theoretical prospects of such neural networks in proving mathematical theorems. In particular, I focus on the question how such AI systems could be incorporated in practice to theorem proving and what consequences that could have. In the most optimistic scenario, this includes the possibility of autonomous automated theorem provers (AATP). Here I discuss whether such AI systems could, or should, become accepted as active agents in mathematical communities. (shrink)

People display recognizably characteristic behavioral patterns across time and situations, with a given degree of regularity. These patterns may justify the attribution of personality traits. It is arguably the commonsense view that the proper explanation of these behavioral regularities is given by intrinsic properties of the agent’s psychology. In this paper, I argue for an externalistic view of the causal basis of personality-characteristic behaviors. According to the externalistic view, the relevant behavioral regularities are better understood as the result of (...) a systematic interaction between features internal to the agent and environmental-situational factors. Moreover, if the premise is granted that people are typically able to exercise a certain degree of control over the environmental-situational conditions they find themselves in, the resulting picture is of active sort of externalism, as people may at times engage in selection and manipulation of environmental-situational conditions as a way of managing their own behavioral tendencies. (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)

Visual imagery is a form of sensory imagination, involving subjective experiences typically described as similar to perception, but which occur in the absence of corresponding external stimuli. We used the Activation Likelihood Estimation algorithm (ALE) to identify regions consistently activated by visual imagery across 40 neuroimaging studies, the first such meta-analysis. We also employed a recently developed multi-modal parcellation of the human brain to attribute stereotactic co-ordinates to one of 180 anatomical regions, the first time this approach has been combined (...) with the ALE algorithm. We identified a total 634 foci, based on measurements from 464 participants. Our overall comparison identified activation in the superior parietal lobule, particularly in the left hemisphere, consistent with the proposed ‘top-down’ role for this brain region in imagery. Inferior premotor areas and the inferior frontal sulcus were reliably activated, a finding consistent with the prominent semantic demands made by many visual imagery tasks. We observed bilateral activation in several areas associated with the integration of eye movements and visual information, including the supplementary and cingulate eye fields (SCEFs) and the frontal eye fields (FEFs), suggesting that enactive processes are important in visual imagery. V1 was typically activated during visual imagery, even when participants have their eyes closed, consistent with influential depictive theories of visual imagery. Temporal lobe activation was restricted to area PH and regions of the fusiform gyrus, adjacent to the fusiform face complex (FFC). These results provide a secure foundation for future work to characterise in greater detail the functional contributions of specific areas to visual imagery. (shrink)

Gassendi holds that matter is intrinsically active - it possesses an innate active force or power. This paper explains what that active power consists in and why Gassendi adopted this view.

When dissimilar images are presented to the two eyes, binocular rivalry (BR) occurs, and perception alternates spontaneously between the images. Although neural correlates of the oscillating perception during BR have been found in multiple sites along the visual pathway, the source of BR dynamics is unclear. Psychophysical and modeling studies suggest that both low- and high-level cortical processes underlie BR dynamics. Previous neuroimaging studies have demonstrated the involvement of high-level regions by showing that frontal and parietal cortices responded time (...) locked to spontaneous perceptual alternation in BR. However, a potential contribution of early visual areas to BR dynamics has been overlooked, because these areas also responded to the physical stimulus alternation mimicking BR. In the present study, instead of focusing on activity during perceptual switches, we highlighted brain activity during suppression periods to investigate a potential link between activity in human early visual areas and BR dynamics. We used a strong interocular suppression paradigm called continuous flash suppression to suppress and fluctuate the visibility of a probe stimulus and measured retinotopic responses to the onset of the invisible probe using functional MRI. There were ∼130-fold differences in the median suppression durations across 12 subjects. The individual differences in suppression durations could be predicted by the amplitudes of the retinotopic activity in extrastriate visual areas (V3 and V4v) evoked by the invisible probe. Weaker responses were associated with longer suppression durations. These results demonstrate that retinotopic representations in early visual areas play a role in the dynamics of perceptual alternations during BR. (shrink)

In his paper ‘Words on Play’, Bernard Suits famously defines play as an autotelic activity. Some philosophers like Stephen E. Schmid argue against Suits’s position by pointing out that the concept of autotelicity in Suits’s work is too unclear to serve as a defining feature for play. Due to that fact, Schmid dismisses autotelicity in favor of a definition of play in terms of the player’s engagement in an activity for intrinsic reasons. The purpose of this paper (...) is to defend Suits’s claim by clarifying the concept of autotelicity in the context of play and by arguing against some typical misconceptions about autotelicity in Schmid’s work and in the work of others. First, I define autotelic activities as activities that are engaged in for their own sake. Then, I argue that the engagement in an activity for its own sake is neither in conflict with the activity’s potential internal instrumental structure nor with the existence of certain intrinsic rea-sons (such as pleasure). (shrink)

Neuroimaging studies have found that adult male psychopaths show reduced engagement of limbic and paralimbic circuitry while making moral judgments. The goal of this study was to investigate whether these findings extend to adolescent males with psychopathic traits. Functional MRI was used to record hemodynamic activity in 111 incarcerated male adolescents while they viewed unpleasant pictures that did or did not depict moral transgressions and rated each on “moral violation severity”. Adolescents were assessed for psychopathic traits using the Psychopathy (...) Checklist-Youth Version (PCL-YV), Kiddie Schedule for Affective Disorders and Schizophrenia-Present and Lifetime Version (KSADS-PL) Conduct Disorder supplement, and Inventory of Callous and Unemotional Traits-Youth Version (ICU-Y). While viewing pictures depicting moral transgressions, CD scores were negatively correlated with hemodynamic responses in the anterior temporal cortex. Adolescents scoring low on the ICU-Y showed a positive correlation between right amygdala responses and severity of violation ratings; those with high ICU-Y scores showed a negative correlation. While viewing unpleasant pictures with and without moral transgressions, PCL-YV scores were negatively correlated with hemodynamic responses in the left amygdala. Overall, the results are consistent with those previously found in adult male psychopaths, but vary depending on the type of psychopathy assessment. (shrink)

We argue that human consciousness may be a property of single electron in the brain. We suppose that each electron in the universe has at least primitive consciousness. Each electron subjectively “observes” its quantum dynamics (energy, momentum, “shape” of wave function) in the form of sensations and other mental phenomena. However, some electrons in neural cells have complex “human” consciousnesses due to complex quantum dynamics in complex organic environment. We discuss neurophysiological and physical aspects of this hypothesis and show (...) that: (1) single chemically active electron has enough informational capacity to “contain” the richness of human subjective experience; (2) quantum states of some electrons might be directly influenced by human sensory data and have direct influence upon human behavior in real brain; (3) main physical and philosophical drawbacks of “conventional” “quantum theories of consciousness” may be solved by our hypothesis without much changes in their conceptual basis. We do not suggest any “new physics”, and our neuroscientific assumptions are similar to those used by other proponents of “quantum consciousness”. However, our hypothesis suggests radical changes in our view on human and physical reality. (shrink)

Using Kantian starting points, we develop a notion of ‘pre-determinant intentionality,’ which refers to the intentionality of judgments that support objective truth-claims. We show how the weight-selections of neural networks can be taken to involve this form of intentionality. We argue that viewing weight selection or ‘internodal and meta-internodal selection’ as involving pre-determinant intentionality allows us to better conceptualize the coordination of computational systems. In particular, it allows us to better conceptualize the coordination of computational activity concerned with (...) the promotion of learning in neural networks.. (shrink)

Lying is one of the characteristic features of psychopathy, and has been recognized in clinical and diagnostic descriptions of the disorder, yet individuals with psychopathic traits have been found to have reduced neural activity in many of the brain regions that are important for lying. In this study, we examine brain activity in sixteen individuals with varying degrees of psychopathic traits during a task in which they are instructed to falsify information or tell the truth about autobiographical (...) and non-autobiographical facts, some of which was related to criminal behavior. We found that psychopathic traits were primarily associated with increased activity in the anterior cingulate, various regions of the prefrontal cortex, insula, angular gyrus, and the inferior parietal lobe when participants falsified information of any type. Associations tended to be stronger when participants falsified information about criminal behaviors. Although this study was conducted in a small sample of individuals and the task used has limited ecological validity, these findings support a growing body of literature suggesting that in some contexts, individuals with higher levels of psychopathic traits may demonstrate heightened levels of brain activity. (shrink)

This paper describes one style of functional analysis commonly used in the neurosciences called task-bound functional analysis. The concept of function invoked by this style of analysis is distinctive in virtue of the dependence relations it bears to transient environmental properties. It is argued that task-bound functional analysis cannot explain the presence of structural properties in nervous systems. An alternative concept of neural function is introduced that draws on the theoretical neuroscience literature, and an argument is given to show (...) that this alternative concept of may help to overcome the explanatory limitations of task-bound functional analysis. (shrink)

The article considers the problem of images and the role they play in our reflection turning to evidence provided by two seemingly very distant theories of mind together with two sorts of corresponding visions: dreams as analyzed by Freud who claimed that they are pictures of our thoughts, and their mechanical counterparts produced by neural networks designed for object recognition and classification. Freud’s theory of dreams has largely been ignored by philosophers interested in cognition, most of whom focused solely (...) on the linguistic incarnation of thoughts, but even though commonly neglected by respectable theories of thinking, dream images may prove to be the key to the black box of thought. As argued in this article, when seen from the right perspective and approached with the right set of questions, oneiric visions yield groundbreaking insights into the mechanism of how concepts and judgments are formed. Support for this conclusion comes from a tradition seemingly remote, if not opposed to psychoanalysis: the mechanical model of the mind conceived by information sciences and embodied in the form of artificial neural nets which mirror the activity of human visual cortex producing visions strikingly similar to those created by the sleeping mind. These purely mechanical, artificial ‘dreams’ constitute byproducts of algorithms designed for object recognition and classification, which, as I shall argue, reveals the true purpose of our own oneiric visual formations. Just like their mechanical counterparts produced by neural networks, condensations and displacements encountered in dreams are in fact visual universals. (shrink)

Current research on the various forms of autoscopic phenomena addresses the clinical and neurological correlates of out-of-body experiences, autoscopic hallucinations,and heautoscopy. Yet most of this research is based on functional magnetic resonance imaging results and focuses predominantly on abnormal cortical activity. Previously we proposed that visual consciousness resulted from the dynamic retinogeniculo-cortical oscillations, such that the photoreceptors dynamically integrated with visual and other vision-associated cortices, and was theorized to be mapped out by photoreceptor discs and rich retinal networks which (...) synchronized with the retinotopic mapping and the associated cortex. The feedback from neural input that is received from the thalamus and cortex via retinogeniculo-cortical oscillations and sent to the retina is multifold higher than feed-forward input to the cortex. This can effectively translate into out-of-body experiences projected onto the screen formed by the retina as it is perceived via feedback and feed-forward oscillations from the reticular thalamic nucleus, or “internal searchlight”. This article explores the role of the reticular thalamic nucleus and the retinogeniculo-cortical oscillations as pivotal internal components in vision and various autoscopic phenomena. (shrink)

In his rich and provocative paper, Peter Carruthers announces two related theses: (a) a positive thesis that “central cognition is sensory based, depending on the activation and deployment of sensory images of various sorts” (Carruthers 2013) and (b) a negative thesis that the “central mind does not contain any workspace within which goals, decisions, intentions, or non-sensory judgments can be active” (Carruthers 2013). These are striking claims suggesting that a natural view about cognition, namely that explicit theoretical reasoning involves direct (...) operations over beliefs, is wrong. Our beliefs, on this natural view, interact with each other to yield new beliefs. If Carruthers is right, beliefs have only an indirect or mediated influence in cognition with sensory states playing the direct role. I think it an important feature of Carruthers’ discussion that he draws support from work on the neural circuits and mechanisms that subserve these processes. In what follows, I want to regis. (shrink)

Metacognition is the capacity to evaluate the success of one's own cognitive processes in various domains; for example, memory and perception. It remains controversial whether metacognition relies on a domain-general resource that is applied to different tasks or if self-evaluative processes are domain specific. Here, we investigated this issue directly by examining the neural substrates engaged when metacognitive judgments were made by human participants of both sexes during perceptual and memory tasks matched for stimulus and performance characteristics. By comparing (...) patterns of fMRI activity while subjects evaluated their performance, we revealed both domain-specific and domain-general metacognitive representations. Multivoxel activity patterns in anterior prefrontal cortex predicted levels of confidence in a domain-specific fashion, whereas domain-general signals predicting confidence and accuracy were found in a widespread network in the frontal and posterior midline. The demonstration of domain-specific metacognitive representations suggests the presence of a content-rich mechanism available to introspection and cognitive control. (shrink)

: One of the most active study fields in natural language processing, web mining, and text mining is sentiment analysis. Big data is an important research component in education that is used to advance the value of education by watching students' performance and understanding their learning habits. Real-time student feedback will enable teachers and students to understand teaching and learning challenges in the most user-friendly manner for students. By linking learning analytics to grounded theory, the proposed Deep Convolutional Neural (...) Network (DCNN) analyses students' sentiments and emotions through feedback using a Lexicon-based emotional analysis approach. The sentiment analysis approach is a computer procedure that identifies and classifies subjective information from the source material as good, negative, or neutral. (shrink)

Pranayamic breathing, defined as a manipulation of breath movement, has been shown to contribute to a physiologic response characterized by the presence of decreased oxygen consumption, decreased heart rate, and decreased blood pressure, as well as increased theta wave amplitude in EEG recordings, increased parasympathetic activity accompanied by the experience of alertness and reinvigoration. The mechanism of how pranayamic breathing interacts with the nervous system affecting metabolism and autonomic functions remains to be clearly understood. It is our hypothesis that (...) voluntary slow deep breathing functionally resets the autonomic nervous system through stretchinduced inhibitory signals and hyperpolarization currents propagated through both neural and non-neural tissue which synchronizes neural elements in the heart, lungs, limbic system and cortex. During inspiration, stretching of lung tissue produces inhibitory signals by action of slowly adapting stretch receptors (SARs) and hyperpolarization current by action of fibroblasts. Both inhibitory impulses and hyperpolarization current are known to synchronize neural elements leading to the modulation of the nervous system and decreased metabolic activity indicative of the parasympathetic state. In this paper we propose pranayama’s physiologic mechanism through a cellular and systems level perspective,involving both neural and non-neural elements. This theoretical description describes a common physiological mechanism underlying pranayama and elucidate the role of the respiratory and cardiovascular system on modulating the autonomic nervous system. Along with facilitating the design of clinical breathing techniques for the treatment of autonomic nervous system and other disorders, this model will also validate pranayama as a topic requiring more research. (shrink)

Abstract: Heart attacks, or myocardial infarctions, are a leading cause of mortality worldwide. Early prediction and accurate analysis of potential risk factors play a crucial role in preventing heart attacks and improving patient outcomes. In this study, we conduct a comprehensive review of datasets related to heart attack analysis and prediction. We begin by examining the various types of datasets available for heart attack research, encompassing clinical, demographic, and physiological data. These datasets originate from diverse sources, including hospitals, research institutions, (...) and public health agencies. Our analysis aims to identify common features, data quality, and potential biases in these datasets. Next, we explore the predictive modeling techniques employed in heart attack prediction. Machine learning algorithms, such as decision trees, support vector machines, and deep neural networks, have gained prominence in predicting heart attacks. We discuss the strengths and limitations of these methods and highlight recent advancements in predictive modeling. Furthermore, we delve into the critical risk factors associated with heart attacks. Factors such as age, gender, hypertension, diabetes, and cholesterol levels are examined for their significance in predicting cardiac events. We also investigate the role of lifestyle factors, including smoking, diet, and physical activity, in heart attack risk assessment. Additionally, this review addresses the importance of data preprocessing and feature engineering in improving prediction accuracy. Feature selection methods, missing data handling, and data scaling techniques are discussed to enhance the robustness of heart attack prediction models. In conclusion, this comprehensive dataset review provides valuable insights into the state of heart attack analysis and prediction. It serves as a resource for researchers and healthcare professionals seeking to better understand the datasets available for heart attack research and the methods employed for accurate prediction. Ultimately, our efforts in dataset analysis and predictive modeling contribute to the advancement of preventive cardiology and the reduction of heart attack-related morbidity and mortality. (shrink)

In this paper we argue that the current paradigm for AGN and quasars is essentially incomplete and a rivision is needed. Remind that the current paradigm for AGN and quasars is that their radio emission is explained by synchrotron radiation from relativistic electrons that are Doppler boosted through bulk motion. In this model, the intrinsic brightness temperatures cannot exceed 1011 to 1012 K. Typical Doppler boosting is expected to be able to raise this temperature by a factor of 10. (...) The observed brightness temperature of the most compact structures in BL Lac, constrained by baselines longer than 5.3Gλ, must indeed exceed 2×1013K and can reach as high as ˜ 3 × 1014K. This is difficult to reconcile with current incoherent synchrotron emission models from relativistic electrons, requiring alternative models such as emission from relativistic protons. However the proton, as we know, is 1836 times heavier than an electron and absolutely huge energy is required to accelerated it to sublight speed. These alternative models such as emission from relativistic protons can be suported by semiclassical gravity effect finds its roots in the singular behavior of quantum fields on curved distributional space- times presented by rotating gravitational singularities. (shrink)

Recent fndings illustrate how changes in consciousness accommodated by neural correlates and plasticity of the brain advance a model of perceptual change as a function of meditative practice. During the mindbody response neural correlates of changing awareness illustrate how the autonomic nervous system shifts from a sympathetic dominant to a parasympathetic dominant state. Expansion of awareness during the practice of meditation techniques can be linked to the Default Mode Network (DMN), a network of brain regions that is active (...) when the one is not focused on the outside world and the brain is restful yet awake (Chen et al., 2008). A model is presented illustrating the dynamic mindbody response before and after mindfulness meditation, and connections are made with prefrontal cortex activity, the cardiac and respiratory center, the thalamus and amygdala, the DMN and cortical function connectivity. The default status of the DMN changes corresponding to autonomic modulation resulting from meditation practice. (shrink)

The physical basis of conscious experience is revealed by direct observation and analysis of any conscious experience. Human conscious experience has an invariant structural mode of organization based on the three types of space-time intervals (light-like, time-like, space-like). Sensory input activates the autonomic nervous system, endocrine system, and ascending reticular activating system to produce the awake conscious state. The dorsal and ventral frontoparietal attention networks are activated. Dorsal and ventral cortical functional streams carry “what”, “where”, and “when” information to the (...) medial temporal lobe for the encoding, storage, and recall of conscious experience (episodic memory). Hippocampal place cells and time cells encode events in space and time within spatiotemporal contexts conveyed by entorhinal cortex grid cells and ramping cells. Theta phase precession unifies the encoding of space and time in the hippocampus so that segments of space and time are encoded in the hippocampus. Theta travelling waves ensure that the instantaneous output of the hippocampus consists of topographically-organized segments of space and time, space-time intervals. By parsing spatiotemporal contexts into quantal units of where and when events occur (spacetime intervals), hippocampal neurons bridge, and thereby organize events, in a conceptual organization of events (conscious experience). Space-time intervals are extracted from the hippocampus by a prefrontal cortex-basal ganglia-thalamic-prefrontal cortex loop for the cognitive, affective, and motivational aspects of conscious experience. (shrink)

Electrical brain activity modulation in terms of changes in its intensity and spatial distribution is a function of age and task demand. However, the dynamics of brain modulation is unknown when it depends on external factors such as training. The aim of this research is to verify the effect of deductive reasoning training on the modulation in the brain activity of healthy younger and older adults ( (mean age of 21 ± 3.39) and (mean age of 68.92 ± (...) 5.72)). The analysis reveals the benefits of training, showing that it lowers cerebral activation while increasing the number of correct responses in the trained reasoning task (). The brain source generators were identified by time-averaging low-resolution brain electromagnetic tomography (sLORETA) current density images. In both groups, a bilateral overactivation associated with the task and not with age was identified. However, while the profile of bilateral activation in younger adults was symmetrical in anterior areas, in the older ones, the profile was located asymmetrically in anterior and posterior areas. Consequently, bilaterality may be a marker of how the brain adapts to maintain cognitive function in demanding tasks in both age groups. However, the differential bilateral locations across age groups indicate that the tendency to brain modulation is determined by age. (shrink)