Integrating a cognitive computational model of planning and decision-making considering affective information

Planning and decision-making are two of the cognitive functions involved in the solution of problems. These functions, among others, have been studied from the point of view of a new field known as cognitive informatics focused on the development of cognitive architectures, autonomous agents, and human robots that are capable of showing human-like behavior. We present an exhaustive study of current biological and computational models proposed in the fields of neuroscience, psychology, and cognitive informatics. Also, we present a deep review of the brain areas involved in planning, decision-making, and affection. However, the majority of the proposed computational models are seeking to mimic human external behavior. This paper aims to contribute to the cognitive informatics field with an innovative cognitive computational model of planning and decision-making. The two main differences of our model with respect to the current models in the literature are: (i) our model considers affective and motivational information as a basic and essential trigger in planning and decision-making processes; (ii) our model attempts to mimic both the internal human brain as well as the external human behavior. We developed a computational model capable of offering a direct mapping from human brain areas to computational modules of our model. Thus, in this paper we present our model from a conceptual, formal, and computational approach in order to show how our proposal must be implemented. Finally, a set of tests were conducted in order to validate our proposal. These tests show an interesting comparison between the behavior of our prototype and the behavior exhibited by some people involved in a case study.     

The neural, evolutionary, developmental, and bodily basis of metaphor

We propose that there are four fundamental kinds of metaphor that are uniquely mapped onto specific brain “networks” and present preliterate (i.e., evolutionary, including before the appearance of written language in the historical record), prelinguistic (i.e., developmental, before the appearance of speech in human development), and extralinguistic (i.e., neuropsychological, cognitive) evidence supportive of this view. We contend that these basic metaphors are largely nonconceptual and entail (a) perceptual-perceptual, (b) cross-modal, (c) movement-movement, and (d) perceptual-affective mappings that, at least, in the initial stages of processing may operate largely outside of conscious awareness. In opposition to our basic metaphor theory (B_mT), the standard theory (S_mT) maintains that metaphor is a conceptual mapping from some base domain to some target domain and/or represents class-inclusion (categorical) assertions. The S_mT captures aspects of secondary or conceptual metaphoric relations but not primary or basic metaphoric relations in our view. We believe our theory (B_mT) explains more about how people actually recognize or create metaphoric associations across disparate domains of experience partly because they are “pre-wired” to make these links.     

Confirmation of correlation between brain nerve conduction velocity and intelligence level in normal adults

In 1992, Reed and Jensen [Intelligence 16 (1992) 259–272] reported a positive correlation (.26; p=.002; .37 after correcting for restricted intelligence range) between a brain nerve conduction velocity (NCV) and intelligence level in 147 normal male students. In the first follow-up of their study, we report on a study using similar NCV methodologies, but testing both male and female students and using more extensive measures of cognitive abilities. One-hundred eighty-six males and 201 females, aged 18–25 years, were tested in three different NCV conditions and with nine cognitive tests, including Raven Progressive Matrices as used by Reed and Jensen. None of the 27 independent correlations in either the males or in the females are significant at Bonferroni-corrected probability levels, but 25 of 27 correlations in males and 20 of 27 correlations in females have positive signs. The exact binomial probabilities for these results are 5.6×10⁻⁶ and .002, respectively. We discuss possible reasons for the differences between the results of Reed and Jensen and our results. We also find that males have four percent faster NCVs than females with each of the three test conditions, probably due to their faster increase of white matter in the brain during adolescence.     

实验性恶心与呕吐——大脑皮层与内脏相关研究的新途径

大脑皮层与内脏关系的脑机制是揭示心身疾病和心理疾病的重要依据。本文综述了经典条件学习与期待性恶心与呕吐的关系以及实验性恶心与呕吐的研究方法。作者认为,实验性恶心与呕吐结合脑成像技术是研究大脑皮层与内脏关系神经机制的重要途径。     

Emergence from brain architectures: a new cognitive science?

The way in which artificial intelligence has developed over the last 50 years has had a major role in shaping cognitive science as it is today. This has generated computational models of behaviour. The connectionist revival of the 1980s added a tinge of neurodynamics to this. Here I suggest that some post-connectionist work in artificial intelligence is turning towards an understanding and formalisation of the mechanisms of brain architectures which contribute to an emergence of cognition providing a closer link between brain mechanisms and experienced brain states. This even addresses the neurological basis of consciousness.     

Smoking reduces language lateralization: a dichotic listening study with control participants and schizophrenia patients

Schizophrenia has been associated with deficits in functional brain lateralization. According to some authors, the reduction of asymmetry could even promote this psychosis. At the same time, schizophrenia is accompanied by a high prevalence of nicotine dependency compared to any other population. This association is very interesting, because sex-dependent effects of smoking in auditory language asymmetries have been reported recently, and the verbal domain is also one major focus in cognitive deficit studies of schizophrenia. Thus, the altered laterality pattern in schizophrenia could, at least in part, result from secondary artefacts due to smoking rather than being a pure cause of the disease itself. To test this hypothesis, the present study examined auditory language lateralization in 67 schizophrenia patients and in 72 healthy controls in a phonemic and an emotional dichotic listening task. Our findings replicate previous research, in that smoking reduces language lateralization in men in phonemic dichotic listening. In addition, we show that smoking also reduces laterality in women in the emotional dichotic listening task. Thus, smoking alters phonemic and emotional language asymmetries differentially for men and women, with a stronger effect for men in the left hemisphere phonemic task, and a stronger effect for women in the right hemisphere emotional task. Together, these findings point towards an effect of smoking which is possibly independent of sex and hemisphere. Importantly, by testing equal numbers of smoking and non-smoking patients and controls, we found no schizophrenia-associated asymmetry effect. Possible neurobiological mechanisms with which smoking may alter auditory microcircuits and thereby diminish left-right differences are discussed.     

Towards a computational theory of experience

A standing challenge for the science of mind is to account for the datum that every mind faces in the most immediate – that is, unmediated – fashion: its phenomenal experience. The complementary tasks of explaining what it means for a system to give rise to experience and what constitutes the content of experience (qualia) in computational terms are particularly challenging, given the multiple realizability of computation. In this paper, we identify a set of conditions that a computational theory must satisfy for it to constitute not just a sufficient but a necessary, and therefore naturalistic and intrinsic, explanation of qualia. We show that a common assumption behind many neurocomputational theories of the mind, according to which mind states can be formalized solely in terms of instantaneous vectors of activities of representational units such as neurons, does not meet the requisite conditions, in part because it relies on inactive units to shape presently experienced qualia and implies a homogeneous representation space, which is devoid of intrinsic structure. We then sketch a naturalistic computational theory of qualia, which posits that experience is realized by dynamical activity-space trajectories (rather than points) and that its richness is measured by the representational capacity of the trajectory space in which it unfolds.     

Sleep EEG changes during adolescence: An index of a fundamental brain reorganization

Delta (1–4 Hz) EEG power in non-rapid eye movement (NREM) sleep declines massively during adolescence. This observation stimulated the hypothesis that during adolescence the human brain undergoes an extensive reorganization driven by synaptic elimination. The parallel declines in synaptic density, delta wave amplitude and cortical metabolic rate during adolescence further support this model. These late brain changes probably represent the final ontogenetic manifestation of nature’s strategy for constructing nervous systems: an initial overproduction of neural elements followed by elimination. Errors in adolescent brain reorganization may cause mental illness; this could explain the typical age of onset of schizophrenia. Longitudinal studies of sleep EEG are enhancing our knowledge of adolescent brain maturation. Our longitudinal study of sleep EEG changes in adolescence showed that delta power, which may reflect frontal cortex maturation, begins its decline between ages 11 and 12 years and falls by 65% by age 17 years. In contrast, NREM theta power begins its decline much earlier. Delta and theta EEG frequencies are important to sleep theory because they behave homeostatically. Surprisingly, these brain changes are unrelated to pubertal maturation but are strongly linked to age. In addition to these (and other) maturational EEG changes, sleep schedules in adolescence change in response to a complex interaction of circadian, social and other influences. Our data demonstrate that the daytime sleepiness that emerges in adolescence is related to the decline in NREM delta as well as to altered sleep schedules. These longitudinal sleep data provide guideposts for studying cognitive and behavioral correlates of adolescent brain reorganization.     

Neuroimaging and neuroenergetics: Brain activations as information-driven reorganization of energy flows

There is increasing focus on the neurophysiological underpinnings of brain activations, giving birth to an emerging branch of neuroscience – neuroenergetics. However, no common definition of “brain activation” exists thus far. In this article, we define brain activation as the information-driven reorganization of energy flows in a population of neuroglial units that leads to an overall increase in energy utilization in this population. On the basis of this definition, the key aspects of modern biochemical and biophysical approaches to neuroenergetics are considered from the perspective of the links between these approaches within the context of the free energy minimization principle and the neurophysiological conception of deviance detection. In this light, we consider brain basal activity as subserving internal representations of the environment (predictive coding), and brain activation as reflecting the level of deviance from predictive coding.     

A New View of Language, Emotion and the Brain

Linguistic theory since the Cognitive Revolution has followed one of the premises of that revolution by largely sidelining the issue of emotions and concentrating on those aspects of language that are more strictly cognitive. However, during the last two decades research in cognitive science, especially in neuropsychology, has begun to fill in the gaps left by the exclusion of emotions from cognitive research. This article proposes a model for applying the fruits of this new research in emotion to our understanding of language itself. Building on Karl Pribram`s integrated model of emotions and motivations, the presentation it offers a propositional explanation for how the emotions may have contributed to the emergence of symbolic formation and, ultimately, to every aspect of language from lexis to literature.