Pavlovian conditioning paradigms have been a stalwart of animal research on fear learning for over a century. Recent advances in cognitive neuroscience research have led to new insights into the neural mechanisms of how humans learn to associate cues with threats, how these representations become bound to contextual features of the environment, and how they generalize to stimuli that are perceptually or conceptually related. By integrating information gleaned from patients with brain lesions, scalp electrophysiology, neuroimaging, and intracranial recordings, researchers are assembling a dynamic view of the distributed brain activity that generates conditioned fear responses. Innovative virtual reality technology, computational modeling, and multivariate analysis tools have further refined a scientific understanding of the component processes involved, which can inform future clinical interventions for treating fear- and anxiety-related disorders.

What makes music an enduring art that has withstood the test of time across so many cultural contexts? Here we review the literature on emotion and reward as it relates to music, grounding our review on multiple methodological traditions in neuroscience, as well as newer work that combines these tools with music technology and sound design. Key to these disparate lines of research is the idea that the reward system is functionally and structurally connected to the auditory system, giving rise to individual differences in the sensitivity and felt emotion for music. We conclude with implications of this research for the design and implementation of music-based interventions for improving cognitive and brain health, especially for those with neurodegenerative diseases.

A common feature of all existing organisms is their ability to adapt, survive, and even thrive in the face of danger. Evolution has endowed organisms with a myriad of defensive mechanisms, from bodily phenotypes and sensory apparatus to learning mechanisms. Humans are no different, and a wide variety of defensive mechanisms has allowed us to adapt to changing landscapes and threats. Yet, we are unique in our capacity to predict the future, to learn from others through many streams of communication vicariously, and to experience emotions consciously. In this chapter, we briefly go through the evolutionary history of defensive behaviors and how they are guided by a canonical set of ecological conditions, by the characteristics of the threat, and by the organisms’ repertoire of cognitive and sensory abilities. We explore the converging mechanisms across species and highlight the uniqueness of humans, including the rich internal representations of the dangers that allow us to experience a large array of emotions.

The current understanding of posttraumatic stress disorder (PTSD) is unique relative to other psychiatric disorders in that there are very clear links between basic affective neuroscience and the diagnostic criteria and treatment of the disorder. Current theories of the causes of PTSD, and gold-standard cognitive behavioral treatments, are grounded in foundational knowledge of fear learning and extinction, emotion regulation, attention, memory, and executive functioning. This conceptual alignment allows for clear translational links from molecular biology to systems neuroscience to healthy human studies and, finally, to the clinic. This chapter will outline a number of such translational links, giving a general overview of how affective neuroscience has informed the current understanding of PTSD and the emerging benefits of these insights.

Over the last thirty years, affective neuroscience has become a royal road to our understanding of emotion and other affective phenomena, being both a core discipline of the affective sciences, and an engine for the rise of affectivism. After a brief discussion of the role of human affective neuroscience in affectivism, the chapter addresses some terminological and taxonomy-related issues before suggesting a consensual definition of emotion. Next, five major families of theories of emotions are presented in relation to five components of emotion. This review illustrates the fact that different families of theories typically focus on different components – even if each family also often considers some of the other components to a lesser extent. Whereas expression is central to basic emotion theory, action tendencies are central to motivational theories, autonomic reaction is central to bodily/interoceptive theories, feeling is central to constructionist theories, and the role of cognition in emotion-elicitation is central to appraisal theories.

The ability to express and perceive vocal emotions plays an important role in social interactions. Notably, the encoding and decoding of emotions often occur in social interactions of persons of different ages, where speaker and listener characteristics dynamically shape the perception of emotion expressed in the voice. However, existing models of (emotional) voice processing have primarily focused on stimulus quality while accounting sparsely for person characteristics, such as speaker and listener age. Consequently, systematic research on the expression and perception of emotion in the voice across the lifespan is needed. Here, we provide a synopsis of how the perception and specifically the recognition of vocal emotions is modulated by the age of both speakers and listeners. First, we summarize what we currently know about human vocal tract development and age-related variations in voice acoustics. We then synthesize evidence on age-related changes in the expression and perception of vocal emotions. We conclude that the perception of emotion expressed in the voice is not only a matter of how one speaks but also of who speaks and who listens. A broader perspective on how the voice communicates emotions should be reflected in existing models and guide future research.

This chapter highlights the pivotal role of animal models in unraveling the intricate biological mechanisms and complex neural networks associated with emotional processing and psychiatric disorders, including anxiety, depression, and addiction. These models contribute significantly to understanding distinct brain circuits governing specific emotional behaviors and uncovering potential alterations in pathological conditions. Exploring inter-individual variability and sex differences in emotional behaviors using these models is crucial for advancing our knowledge of emotional processing and dysregulation. This chapter emphasizes the importance of extending the time window analyzed, as well as the importance of using computational tools such as machine learning. Integrating cutting-edge computational tools will enable a finer understanding of the neurobiology of emotions, fostering improved interpretability of both preclinical and clinical results. Ultimately, preclinical models play a vital role in comprehending the neurobiology underlying emotional dysregulation, contributing essential insights for the development of effective treatment strategies for mental disorders.

Pain is a complex experience that includes physical sensations and emotional responses. Research has shown that the central nervous system plays a significant role in how we experience pain. In this chapter, we review the current understanding of the neuroscience of pain, with a particular emphasis on pain processing in the brain. We cover early theories that emphasized the brain’s role in integrating and modulating pain, as well as modern approaches that view pain as distributed processing in the brain. We also introduce functional and computational frameworks for understanding the sensory and motivational aspects of pain and discuss various factors that contribute to the multidimensional nature of pain. The future direction of the study of pain neuroscience includes a deep sampling of subjective pain experience and the use of generative models.

The aim of this chapter is to offer an approachable introduction to the questions, goals, and techniques of affective neuroscience research in nonhuman animals. Rather than providing a detailed literature review, we attempt to outline the overarching principles of the neuroscience of emotion and highlight some areas of special interest. We begin by describing a broad conceptual framework for understanding emotion states that is relied upon by many affective neuroscientists working with nonhuman animals today. We then explore representative examples of work from especially instructive domains of emotion research in other animals, focusing on mice. We discuss each example in detail, introducing the relevant methods and highlighting their strengths and weaknesses, to convey the overall logic of affective neuroscience research in other animals and demonstrate its utility and potential for mechanistic insights into how emotions are manifested by the brain.