The role of the cerebellum in unconsciuos and conscious processing of emotions: a review

Studies from the past three decades have demonstrated that there is cerebellar involvement in the emotional domain. Emotional processing in humans requires both unconscious and conscious mechanisms. A significant amount of evidence indicates that the cerebellum is one of the cerebral structures that subserve emotional processing, although conflicting data have been reported on its function in unconscious and conscious mechanisms. This review discusses the available clinical, neuroimaging and neurophysiological data on this issue. We also propose a model in which the cerebellum acts as a mediator between the internal state and external environment for the unconscious and conscious levels of emotional processing

Neurophysiological Assessment of Affective Experience

In the field of Affective Computing the affective experience (AX) of the user during the interaction with computers is of great interest. The automatic recognition of the affective state, or emotion, of the user is one of the big challenges. In this proposal I focus on the affect recognition via physiological and neurophysiological signals. Long‐standing evidence from psychophysiological research and more recently from research in affective neuroscience suggests that both, body and brain physiology, are able to indicate the current affective state of a subject. However, regarding the classification of AX several questions are still unanswered. The principal possibility of AX classification was repeatedly shown, but its generalisation over different task contexts, elicitating stimuli modalities, subjects or time is seldom addressed. In this proposal I will discuss a possible agenda for the further exploration of physiological and neurophysiological correlates of AX over different elicitation modalities and task contexts

Autonomic arousal and attentional orienting to visual threat are predicted by awareness

The rapid detection and evaluation of threat is of fundamental importance for survival. Theories suggest that this evolutionary pressure has driven functional adaptations in a specialized visual pathway that evaluates threat independently of conscious awareness. This is supported by evidence that threat-relevant stimuli rendered invisible by backward masking can induce physiological fear responses and modulate spatial attention. The validity of these findings has since been questioned by research using stringent, objective measures of awareness. Here, we use a modified continuous flash suppression paradigm to ask whether threatening images induce adaptive changes in autonomic arousal, attention, or perception when presented outside of awareness. In trials where stimuli broke suppression to become visible, threatening stimuli induced a significantly larger skin conductance response than nonthreatening stimuli and attracted spatial attention over scrambled images. However, these effects were eliminated in trials where observers were unaware of the stimuli. In addition, concurrent behavioral data provided no evidence that threatening images gained prioritized access to awareness. Taken together, our data suggest that the evaluation and spatial detection of visual threat are predicted by awareness

Perceiving Pain in Others: Automatic and Controlled Mechanisms

A

Machine Understanding of Human Behavior

A widely accepted prediction is that computing will move to the background, weaving itself into the fabric of our everyday living spaces and projecting the human user into the foreground. If this prediction is to come true, then next generation computing, which we will call human computing, should be about anticipatory user interfaces that should be human-centered, built for humans based on human models. They should transcend the traditional keyboard and mouse to include natural, human-like interactive functions including understanding and emulating certain human behaviors such as affective and social signaling. This article discusses a number of components of human behavior, how they might be integrated into computers, and how far we are from realizing the front end of human computing, that is, how far are we from enabling computers to understand human behavior

Human Amygdala in Sensory and Attentional Unawareness: Neural Pathways and Behavioural Outcomes

One of the neural structures more often implicated in the processing of emotional signals in the absence of visual awareness is the amygdala. In this chapter, we review current evidence from human neuroscience in healthy and brain-damaged patients on the role of amygdala during non-conscious (visual) perception of emotional stimuli. Nevertheless, there is as of yet no consensus on the limits and conditions that affect the extent of amygdala’s response without focused attention or awareness. We propose to distinguish between attentional unawareness, a condition wherein the stimulus is potentially accessible to enter visual awareness but fails to do so because attention is diverted, and sensory unawareness, in which the stimulus fails to enter awareness because its normal processing in the visual cortex is suppressed. Within this conceptual framework, some of the apparently contradictory findings seem to gain new coherence and converge on the role of the amygdala in supporting different types of non-conscious emotion processing. Amygdala responses in the absence of awareness are linked to different functional mechanisms and are driven by more complex neural networks than commonly assumed. Acknowledging this complexity can be helpful to foster new studies on amygdala functions without awareness and their impact on human behaviour

Artificial consciousness and the consciousness-attention dissociation

Artificial Intelligence is at a turning point, with a substantial increase in projects aiming to implement sophisticated forms of human intelligence in machines. This research attempts to model specific forms of intelligence through brute-force search heuristics and also reproduce features of human perception and cognition, including emotions. Such goals have implications for artificial consciousness, with some arguing that it will be achievable once we overcome short-term engineering challenges. We believe, however, that phenomenal consciousness cannot be implemented in machines. This becomes clear when considering emotions and examining the dissociation between consciousness and attention in humans. While we may be able to program ethical behavior based on rules and machine learning, we will never be able to reproduce emotions or empathy by programming such control systems—these will be merely simulations. Arguments in favor of this claim include considerations about evolution, the neuropsychological aspects of emotions, and the dissociation between attention and consciousness found in humans. Ultimately, we are far from achieving artificial consciousness

Digitizing arquetypal human expereience through physiological signals

The problem of capturing human experience is relevant in many application domains. In fact, the process of describing and sharing individual experience lies at the heart of human culture. This advancement came at a price of losing some of the multidimensional aspects of primary, bodily experience during its projection into the symbolic formThroughout the courses of our lives we learn a great deal of information about the world from other people's experience. Besides the ability to share utilitarian experience such as whether a particular plant is poisonous, humans have developed a sophisticated competency of social signaling that enables us to express and decode emotional experience. The natural way of sharing emotional experiences requires those who share to be co-present during this event. However, people have overcome the limitation of physical presence by creating a symbolic system of representations.Recent research in the field of affective computing has addressed the question of digitization and transmission of emotional experience through monitoring and interpretation of physiological signals. Although the outcomes of this research represent a great step forward in developing a technology that supports sharing of emotional experiences, they do not seem to help in preserving the original phenomenological experience during the aforementioned projection. This circumstance is explained by the fact that in affective computing the focus of investigation has been aimed at emotional experiences which can be consciously evaluated and described by individuals themselves. Therefore, generally speaking, applying an affective computing technique for capturing emotions of an individual is not a deeper or more precise way to project her experience into the symbolic form than asking this person to write down a description of her emotions on a piece of paper. One can say that so far the research in affective computing has aimed at delivering technology that could automate the projection but it has not considered the problem of improving the projection in order to preserve more of the multidimensional aspects of human experience.This dissertation examines whether human experience, which individuals are not able to consciously transpose into the symbolic representation, can still be captured using the techniques of affective computing.First, a theoretical framework for description of human experience which is not accessible for conscious awareness was formulated. This framework was based on the work of Carl Jung who introduced a model of a psyche that includes three levels: consciousness, the personal unconscious and the collective unconscious. Consciousness is the external layer of the psyche that consists of those thoughts and emotions which are available for one¿s conscious recollection. The personal unconscious represents a repository for all of an individual¿s feelings, memories, knowledge and thoughts that are not conscious at a given moment of time.The collective unconscious is a repository of universal modes and behaviors that are similar in all individuals. According to Jung, the collective unconscious is populated with archetypes. Archetypes are prototypical categories of objects, people and situations that existed across evolutionary time and in different cultures.Esta tesis doctoral examina si la experiencia humana, que los individuos no pueden transponer conscientemente a la representación simbólica, aún puede capturarse utilizando las técnicas de computación afectiva. Primero, se formula un marco teórico para la descripción de la experiencia humana que no es accesible para la conciencia consciente. Este marco se basó en el trabajo de Carl Jung, quien introdujo un modelo de psique que incluye tres niveles: la conciencia, el inconsciente personal y el inconsciente colectivo. Habiendo definido nuestro marco teórico, realizamos un experimento en el que se mostraron a los sujetos estímulos visuales y auditivos de bases de datos estandarizadas para la obtención de emociones conscientes. Aparte de los estímulos para las emociones conscientes, los sujetos fueron expuestos a estímulos que representaban el arquetipo del yo. Durante la presentación de los estímulos cardiovasculares se registraron las señales de los sujetos. Los resultados experimentales indicaron que las respuestas de la frecuencia cardíaca de los participantes fueron únicas para cada categoría de estímulos, incluido el arquetípico. Estos hallazgos dieron impulso a realizar otro estudio en el que se examinó un espectro más amplio de experiencias arquetípicas. En nuestro segundo estudio, hicimos un cambio de estímulos visuales y auditivos a estímulos audiovisuales porque se esperaba que los videos fueran más eficientes en la obtención de emociones conscientes y experiencias arquetípicas que las imágenes fijas o los sonidos. La cantidad de arquetipos aumentó y los sujetos en general fueron estimulados a sentir ocho experiencias arquetípicas diferentes. También preparamos estímulos para emociones conscientes. En este experimento, las señales fisiológicas incluyeron actividades cardiovasculares, electrodérmicas, respiratorias y temperatura de la piel. El análisis estadístico sugirió que las experiencias arquetípicas podrían diferenciarse en función de las activaciones fisiológicas. Además, se construyeron varios modelos de predicción basados en los datos fisiológicos recopilados. Estos modelos demostraron la capacidad de clasificar los arquetipos con una precisión que era considerablemente más alta que el nivel de probabilidad. Como los resultados del segundo estudio sugirieron una relación positiva entre las experiencias arquetípicas y las activaciones de señales fisiológicas, parecía razonable realizar otro estudio para confirmar la generalización de nuestros hallazgos. Sin embargo, antes de comenzar un nuevo experimento, se decidió construir una herramienta que pudiera facilitar la recopilación de datos fisiológicos y el reconocimiento de experiencias arquetípicas, así como de emociones conscientes. Tal herramienta nos ayudaría a nosotros y a otros investigadores a realizar experimentos sobre la experiencia humana. Nuestra herramienta funciona en "tablets" y admite la recopilación y el análisis de datos de sensores fisiológicos. El último estudio se realizó utilizando una metodología similar al segundo experimento con varias modificaciones que tenían como objetivo obtener resultados más sólidos. El esfuerzo de realizar este estudio se redujo considerablemente al usar la herramienta desarrollada. Durante el experimento, sólo medimos las actividades cardiovasculares y electrodérmicas de los sujetos porque nuestros experimentos anteriores mostraron que estas dos señales contribuyeron significativamente a la clasificación de las emociones conscientes y las experiencias arquetípicas. El análisis estadístico indicó una relación significativa entre los arquetipos retratados en los videos y las respuestas fisiológicas de los sujetos. Además, utilizando métodos de minería de datos, creamos modelos de predicción que fueron capaces de reconocer las experiencias arquetípicas con una precisión menor que en el segundo estudio, pero todavía considerablemente..

Digitizing arquetypal human expereience through physiological signals

The problem of capturing human experience is relevant in many application domains. In fact, the process of describing and sharing individual experience lies at the heart of human culture. This advancement came at a price of losing some of the multidimensional aspects of primary, bodily experience during its projection into the symbolic formThroughout the courses of our lives we learn a great deal of information about the world from other people's experience. Besides the ability to share utilitarian experience such as whether a particular plant is poisonous, humans have developed a sophisticated competency of social signaling that enables us to express and decode emotional experience. The natural way of sharing emotional experiences requires those who share to be co-present during this event. However, people have overcome the limitation of physical presence by creating a symbolic system of representations.Recent research in the field of affective computing has addressed the question of digitization and transmission of emotional experience through monitoring and interpretation of physiological signals. Although the outcomes of this research represent a great step forward in developing a technology that supports sharing of emotional experiences, they do not seem to help in preserving the original phenomenological experience during the aforementioned projection. This circumstance is explained by the fact that in affective computing the focus of investigation has been aimed at emotional experiences which can be consciously evaluated and described by individuals themselves. Therefore, generally speaking, applying an affective computing technique for capturing emotions of an individual is not a deeper or more precise way to project her experience into the symbolic form than asking this person to write down a description of her emotions on a piece of paper. One can say that so far the research in affective computing has aimed at delivering technology that could automate the projection but it has not considered the problem of improving the projection in order to preserve more of the multidimensional aspects of human experience.This dissertation examines whether human experience, which individuals are not able to consciously transpose into the symbolic representation, can still be captured using the techniques of affective computing.First, a theoretical framework for description of human experience which is not accessible for conscious awareness was formulated. This framework was based on the work of Carl Jung who introduced a model of a psyche that includes three levels: consciousness, the personal unconscious and the collective unconscious. Consciousness is the external layer of the psyche that consists of those thoughts and emotions which are available for one¿s conscious recollection. The personal unconscious represents a repository for all of an individual¿s feelings, memories, knowledge and thoughts that are not conscious at a given moment of time.The collective unconscious is a repository of universal modes and behaviors that are similar in all individuals. According to Jung, the collective unconscious is populated with archetypes. Archetypes are prototypical categories of objects, people and situations that existed across evolutionary time and in different cultures.Esta tesis doctoral examina si la experiencia humana, que los individuos no pueden transponer conscientemente a la representación simbólica, aún puede capturarse utilizando las técnicas de computación afectiva. Primero, se formula un marco teórico para la descripción de la experiencia humana que no es accesible para la conciencia consciente. Este marco se basó en el trabajo de Carl Jung, quien introdujo un modelo de psique que incluye tres niveles: la conciencia, el inconsciente personal y el inconsciente colectivo. Habiendo definido nuestro marco teórico, realizamos un experimento en el que se mostraron a los sujetos estímulos visuales y auditivos de bases de datos estandarizadas para la obtención de emociones conscientes. Aparte de los estímulos para las emociones conscientes, los sujetos fueron expuestos a estímulos que representaban el arquetipo del yo. Durante la presentación de los estímulos cardiovasculares se registraron las señales de los sujetos. Los resultados experimentales indicaron que las respuestas de la frecuencia cardíaca de los participantes fueron únicas para cada categoría de estímulos, incluido el arquetípico. Estos hallazgos dieron impulso a realizar otro estudio en el que se examinó un espectro más amplio de experiencias arquetípicas. En nuestro segundo estudio, hicimos un cambio de estímulos visuales y auditivos a estímulos audiovisuales porque se esperaba que los videos fueran más eficientes en la obtención de emociones conscientes y experiencias arquetípicas que las imágenes fijas o los sonidos. La cantidad de arquetipos aumentó y los sujetos en general fueron estimulados a sentir ocho experiencias arquetípicas diferentes. También preparamos estímulos para emociones conscientes. En este experimento, las señales fisiológicas incluyeron actividades cardiovasculares, electrodérmicas, respiratorias y temperatura de la piel. El análisis estadístico sugirió que las experiencias arquetípicas podrían diferenciarse en función de las activaciones fisiológicas. Además, se construyeron varios modelos de predicción basados en los datos fisiológicos recopilados. Estos modelos demostraron la capacidad de clasificar los arquetipos con una precisión que era considerablemente más alta que el nivel de probabilidad. Como los resultados del segundo estudio sugirieron una relación positiva entre las experiencias arquetípicas y las activaciones de señales fisiológicas, parecía razonable realizar otro estudio para confirmar la generalización de nuestros hallazgos. Sin embargo, antes de comenzar un nuevo experimento, se decidió construir una herramienta que pudiera facilitar la recopilación de datos fisiológicos y el reconocimiento de experiencias arquetípicas, así como de emociones conscientes. Tal herramienta nos ayudaría a nosotros y a otros investigadores a realizar experimentos sobre la experiencia humana. Nuestra herramienta funciona en "tablets" y admite la recopilación y el análisis de datos de sensores fisiológicos. El último estudio se realizó utilizando una metodología similar al segundo experimento con varias modificaciones que tenían como objetivo obtener resultados más sólidos. El esfuerzo de realizar este estudio se redujo considerablemente al usar la herramienta desarrollada. Durante el experimento, sólo medimos las actividades cardiovasculares y electrodérmicas de los sujetos porque nuestros experimentos anteriores mostraron que estas dos señales contribuyeron significativamente a la clasificación de las emociones conscientes y las experiencias arquetípicas. El análisis estadístico indicó una relación significativa entre los arquetipos retratados en los videos y las respuestas fisiológicas de los sujetos. Además, utilizando métodos de minería de datos, creamos modelos de predicción que fueron capaces de reconocer las experiencias arquetípicas con una precisión menor que en el segundo estudio, pero todavía considerablemente..

On Sexual Lust as an Emotion

Sexual lust – understood as a feeling of sexual attraction towards another – has traditionally been viewed as a sort of desire or at least as an appetite akin to hunger. I argue here that this view is, at best, significantly incomplete. Further insights can be gained into certain occurrences of lust by noticing how strongly they resemble occurrences of “attitudinal” (“object-directed”) emotion. At least in humans, the analogy between the object-directed appetites and attitudinal emotions goes well beyond their psychological structure to include similar ways in which their occurrence can be introspectively recognized, resulting in similar extensions of their functionality and meaningfulness to the subject. I conclude that although further research is needed, given the strength of the analogy, the ability of lust to satisfy some general requirements for being an emotion, and perhaps certain neurological findings, lust may somewhat uniquely straddle the line between appetite and emotion