Are you interested in learning how your brain constructs emotions? Then you should read "How Emotions are Made" by psychologist and neuroscientist Lisa Feldman Barrett. This book challenges the stimulus-response view of emotions and proposes that emotions are not fixed responses to stimuli, but are rather constructed by the brain through predictions and past experiences. Emotions arise from predictions within the interoceptive network. This network consists of (1) a set of brain regions that send predictions to the body to control its internal environment (heart rhythm, breathing, cortisol, glucose metabolization, etc.) and (2) a region that represents sensations inside the body (the primary interoceptive cortex.
The brain constructs the world and experiences
Feldman Barrett describes how the brain constructs the world and experiences through predictions. The brain is constantly making predictions about sensory input based on past experiences. These predictions are represented by billions of prediction loops formed by networks of neurons at various levels. When a prediction matches the sensory input, the simulation becomes the person's experience. If a prediction doesn't match the sensory input, the brain must resolve the error. The brain's predictions are crucial to understanding how emotions are made, as they allow the brain to prepare for an action, such as catching a ball, well before it consciously sees the ball. When a prediction is correct, it leads to a successful outcome, but when it's incorrect, the brain adjusts its earlier predictions to correct the error.
Affective realism refers to the perception of an object or event in the outside world as inherently positive or negative, regardless of our own personal experience. For example, photographs of kittens are typically deemed pleasant while photographs of rotting corpses are unpleasant, even though these images do not have inherent affective properties. Affective realism influences our daily lives, as we use affect as information to create affective responses. However, affective realism can also shape harmful attitudes, such as blaming victims for their own experiences.
Goal-based concepts are purely mental and can include diverse instances that share no perceptual features but are associated with a common goal. Feldman Barrett suggests that categorization is not just about observing the world and finding similarities but also involves the brain's goals and context. Infants actively learn and estimate probabilities based on patterns they observe. They learn statistically to predict outcomes to maximize desired outcomes. Infants can infer other people's goals statistically and guess the goal behind another person's actions. Statistical learning alone does not equip humans to learn purely mental goal-based concepts, though. To build purely mental concepts, humans need words. From infancy, human brains have an affinity for processing speech signals, and the sounds of words introduce statistical regularity that speeds concept learning. Infants learn concepts such as "Anger" by constructing experiences with it and creating commonalities with all the other instances of "Anger" already in their brain. This helps them give meaning to other people's movements and vocalizations, such as smiles, shrugs, shouts, whispers, tightened jaws, widened eyes, and even motionlessness, to construct perceptions of anger.
This all shows that our experiences are not fixed or objective but are constantly shaped by the brain's predictions, our personal biases, and our goals and context.
Feldman Barrett, L. (2017), How Emotions are Made, London: Pan Macmillan.
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