The first line, Eq. (3.1), is the Dirac Lagrangian for free fermions. The second line, Eq. (3.2), is the electromagnetic current. I will take it that these two terms are already known (I discussed them briefly in Chapter 1).

Many of the psychological topics we have discussed have focused on the mind of the individual, but humans are a fundamentally social species. Recently, the nature of our social interactions has transformed, through our new abilities to connect with people online. This chapter discusses psychological principles of social networks, and how to quantify social networks via graph theory. The chapter examines the small-world phenomenon and the role of social ties via these graph theory measures. We then look at the case of online social networks, what can be learned about you from your profile, and how their use impacts psychological measures. The chapter concludes by showcasing findings on social network representations in the brain, and touching on ethical questions related to social media privacy concerns and AI-based social interactions.

This chapter provides an overview of some of the key practice strategies that social workers use to try to challenge and arrest the massive social inequalities we explored in the previous chapters. The theory and practices of critical social work help us to devise creative and effective ways to contest and resist the harms created by oppressive social forces. Developing our capacity for critical analysis is an important first step that underpins all other practices outlined in this chapter: social policy analysis and development; social activism, allyship and participation in social movements; critical practice in organisations; and undertaking social research. These practices connect practitioners with discretionary spaces in which they can work towards social justice and emancipatory aims.

Exploration of planetary bodies beyond Earth is occurring at an ever-increasing rate. What used to be points of light in the night sky are now amazing, complicated, and intriguing objects of geologic study. For extraterrestrial bodies with solid surfaces – such as rocky planets, asteroids, and icy bodies – the study of planetary bodies as geologic objects includes careful scrutiny of their surfaces. Planetary exploration is an examination of geomorphology, as our interpretations of other planetary surfaces are largely guided by geomorphic studies done on Earth. At the same time, planetary landforms developed in different geologic conditions than on Earth – such as under different gravities, in different materials (like ice instead of rock), and beneath different atmospheric pressures or compositions.

This chapter illustrates that various geomorphic processes observed on Earth occur on other planets as well, and also how the resultant landforms contrast with those found on Earth.

As noted in Chapter 1, since writing the last edition of this text in 2019, the world has undergone rapid changes and continues to transform at an accelerated pace. Social work, often informed by social movements and community experience, aims to anticipate and respond to emerging social issues. Perhaps this is one of the defining hallmarks of the social work profession – its capacity to evolve to address new challenges and opportunities. Throughout this book, and especially in Chapter 2, we explore some of the global social forces and discourses that characterise the rapidly changing contexts in which social work operates. These changes have created new challenges that require critical responses, in some cases generating new fields of practice. In this chapter, our major focus will be on: (1) the increasing urgency of climate change, threats to the planet (and humanity) and the implications of climate change for social work; (2) global pandemics and their impacts for people and service delivery; and (3) increasing wealth inequality and associated poverty and homelessness.

We begin with a case study of a traditional small-scale face memory experiment. The chapter deconstructs the elements that prevent this experiment from being generalizable, and poses potential ways in which we can expand this experiment into a "Big Data" experiment. The chapter discusses the replication crisis in psychology as an important motivator for broadening psychological experiments, as well as common issues with data fishing or "p-hacking." At the same time, there are limitations to our ability to run perfect Big Data experiments. The chapter describes the beneficial relationship of hypothesis-driven research and data-driven research in psychology, presenting the pros and cons of each. Finally, the chapter discusses different formats of Big Data – wide, deep, and long data.

Computational neuroimaging is defined broadly as the use of neuroimaging to investigate the localization and representation of parameters in formal mathematical models. We focus upon models of behavior and neural processing that have been adopted widely in behavioral sciences and cognitive neuroscience, including reinforcement learning, predictive coding, decision theory (drift diffusion and evidence accumulation), population receptive field models, and encoding models (including artificial neural networks). The aim is not to explain all the technical details of the various models, but illustrate and discuss the added value of combining such models with neuroimaging.

Chapter 11 introduces basic EEG and MEG data analysis methods. It begins with an explanation of the noise components in EEG and MEG signals and discusses various methods of noise reduction, including filtering and independent component analysis (ICA). Spectral analysis, event-related response (ERR) analysis, and steady-state evoked response (ssER) analysis are then introduced. Each method is explained in plain language, followed by more detailed explanations to meet the different needs of beginners and advanced readers. Relevant statistical methods and data presentation formats are also introduced, using various data analysis platforms.

We present the main methods that are used to modulate brain activity directly. These methods are often used in combination or following up on neuroimaging experiments, in a means to test causal hypotheses. We include microstimulation, deep brain stimulation, focused ultrasound stimulation (FUS), transcranial magnetic stimulation (TMS) and its sub-types like single- and double-pulse and repetitive TMS. We end with transcranial current stimulation (TCS), also known as trancranial electric stimulation (TES), which comes in several variants such as transcranial direct current stimulation (TDCS) and transcranial alternating current stimulation (TACS).