Mind-life continuity: A qualitative study of conscious experience

MODeLING.Vis: A Graphical User Interface Toolbox Developed for Machine Learning and Pattern Recognition of Biomolecular Data

Many scientific publications that affect machine learning have set the basis for pattern recognition and symmetry. In this paper, we revisit the concept of “Mind-life continuity” published by the authors, testing the symmetry between cognitive and electrophoretic strata. We opted for machine learning to analyze and understand the total protein profile of neurotypical subjects acquired by capillary electrophoresis. Capillary electrophoresis permits a cost-wise solution but lacks modern proteomic techniques’ discriminative and quantification power. To compensate for this problem, we developed tools for better data visualization and exploration in this work. These tools permitted us to examine better the total protein profile of 92 young adults, from 19 to 25 years old, healthy university students at the University of Lisbon, with no serious, uncontrolled, or chronic diseases affecting the nervous system. As a result, we created a graphical user interface toolbox named MODeLING.Vis, which showed specific expected protein profiles present in saliva in our neurotypical sample. The developed toolbox permitted data exploration and hypothesis testing of the biomolecular data. In conclusion, this analysis offered the data mining of the acquired neuroproteomics data in the molecular weight range from 9.1 to 30 kDa. This molecular weight range, obtained by pattern recognition of our dataset, is characteristic of the small neuroimmune molecules and neuropeptides. Consequently, MODeLING.Vis offers a machine-learning solution for probing into the neurocognitive response.

Pre-Molecular Assessment of Self-Processes in Neurotypical Subjects Using a Single Cognitive Behavioral Intervention Evoking Autobiographical Memory

In the last 20 years, several contributions have been published on what concerns the conceptual and empirical connections between self-processes. However, only a limited number of publications addressed the viability of those processes to characterize mental health in neurotypical subjects with a normative pattern of neurodevelopment. Furthermore, even fewer experiments focused explicitly on the complexity of studying neurotypical phenomenal data. On the one hand, this normative pattern is commonly associated with mental health and a multifaceted self-concept and well-being. On the other hand, well-being is often related to a healthy cognitive life. However, how such intricate and complex relation between self-processes is established in neurotypical subjects requires further evidence. The novelty of this work is thus studying the first-person experience, which is correlated with the mental events aroused by a cognitive behavioral intervention. The prior methodology that led to the complete characterization of a neurotypical sample was already published by the authors, although the materials, the methods, the sample screening, and the sample size study required further explanation and exploration. This paper's innovation is hence the phenomenological assessment of subjects' self-regulation, which is used for mental health profiling, providing the basis for subsequent molecular typing. For that matter, a convenience sample of 128 (19-25-year-old) neurotypical young adults, healthy university students at the University of Lisbon, non-medicated and with no serious, uncontrolled, or chronic diseases, are characterized according to their cognitive functioning and self-concept. The procedure comprised (i) a mental status examination (psychological assessment) and (ii) a psychological intervention, i.e., a single cognitive behavioral intervention (intervention protocol). The psychological assessment was a standardized and structured clinical interview, which comprised the use of 4 psychological scales complementary to the classical Mental Status Examination (MSE). The intervention protocol applied a combined exercise of psychophysical training and autobiographical-self memory-recalling. The results permitted identifying and isolating four different subgroups (self awareness, self consciousness, reflective self, and pre-reflective self) in neurotypical subjects with discrete self-processes. The outcome of this study is screening four different aspects of self-reflection and the isolation between various forms of self-directed attention and their interconnections in these four mental health strata. The practical implication of this study is to fulfill an a priori pre-molecular assessment of self-regulation with separate cognitive characteristics. The reliability of these mental strata, their distinct neurophysiology, and discrete molecular fingerprint will be tested in a future publication by in silico characterization, total protein profiling, and simultaneous immunodetection of the neuropeptide and neuroimmune response of the same participants.

Embodied skillful performance: where the action is

When someone masters a skill, their performance looks to us like second nature: it looks as if their actions are smoothly performed without explicit, knowledge-driven, online monitoring of their performance. Contemporary computational models in motor control theory, however, are instructionist: that is, they cast skillful performance as a knowledge-driven process. Optimal motor control theory (OMCT), as representative par excellence of such approaches, casts skillful performance as an instruction, instantiated in the brain, that needs to be executed-a motor command. This paper aims to show the limitations of such instructionist approaches to skillful performance. We specifically address the question of whether the assumption of control-theoretic models is warranted. The first section of this paper examines the instructionist assumption, according to which skillful performance consists of the execution of theoretical instructions harnessed in motor representations. The second and third sections characterize the implementation of motor representations as motor commands, with a special focus on formulations from OMCT. The final sections of this paper examine predictive coding and active inference-behavioral modeling frameworks that descend, but are distinct, from OMCT-and argue that the instructionist, control-theoretic assumptions are ill-motivated in light of new developments in active inference.