Perinatal brain injury is a significant contributor to cerebral palsy, epilepsy, and other neurological disorders, occurring from 20 weeks’ gestation to 28 days postnatally. Approximately 40% of cases are associated with premature birth, whereas 11% result from acute intrapartum hypoxia–ischemia (HI). Despite improvements in neonatal care, the incidence remains stable, underscoring the need for better early detection methods. There is a critical “window of opportunity” for therapeutic intervention postinsult, with therapeutic hypothermia being the only established neuroprotective therapy for term infants. However, its efficacy is limited, as many infants continue to suffer disabilities despite treatment. The development of robust biomarkers is essential to identify infants at risk for significant brain injury and to evaluate the effectiveness of treatments. This chapter explores existing and novel biomarkers for assessing injury, determining treatability, and predicting long-term outcomes after HI, ultimately aiming to enhance management strategies for affected infants and improve prognostic abilities in clinical practice.

This chapter focuses on the different types of intracranial hemorrhage that affect preterm and full-term infants. The most common type of intracranial hemorrhage in preterm infants is germinal matrix hemorrhage–intraventricular hemorrhage, whereas full-term infants are more likely to suffer from choroid plexus hemorrhage, subpial hemorrhage, and extra-axial hemorrhages. Advances in neonatal brain imaging, from the limited use of cranial ultrasound (cUS) and computed tomography (CT) in the early 1980s to the widespread application of magnetic resonance imaging (MRI) nowadays, have enabled a more precise diagnosis of smaller and subtler hemorrhagic lesions, as well as white matter injury and punctate cerebellar hemorrhages that are more prevalent in very preterm infants. This chapter also discusses the incidence, risk factors, and management of intracranial hemorrhage, including preventive strategies.

Disciplines grow at their boundaries. The interdisciplinary topics considered here fall into three groups. One is mainly concerned with liquids: paramagnetic liquids, ferrofluids, magnetic levitation and confinement, and magnetoelectrochemistry. The second relates to life sciences: magnetism in biology and medicine, magnetic imaging and magnetically aided diagnostics. Finally there is planetary and stellar magnetism, covering the magnetism of rocks and the Earth’s magnetic field, as well as and those of other planets, the Sun and stars.

Chapter 4 examines magnetic resonance imaging (MRI) as a cornerstone technology for visualizing brain structure with remarkable precision. The chapter traces MRI’s development from Wolfgang Pauli’s discovery of nuclear spin properties through Nobel Prize-winning innovations by Bloch, Purcell, Lauterbur, and Mansfield that enabled spatial encoding of magnetic resonance signals. It explains the physical principles underlying MRI and how powerful magnetic fields align hydrogen atoms in tissue, followed by precisely tuned radiofrequency pulses that excite these atoms, resulting in detectable signals that vary by tissue composition. The text explores technical considerations essential for high-quality image acquisition, including magnetic field strength, head coil design, and pulse sequence parameters that determine tissue contrast in T1, T2, and FLAIR imaging. Considerable attention is given to image processing methods, distortion correction, registration, normalization, segmentation, and smoothing that prepare brain images for meaningful analysis. By assessing MRI’s comparative advantages over other structural imaging modalities, including its non-ionizing radiation profile and superior tissue differentiation, alongside practical considerations of safety protocols and experimental design, the chapter discusses MRI’s foundational role in modern neuroimaging while acknowledging the tradeoffs between spatial resolution, acquisition time, and signal quality that researchers must navigate when designing studies.

As we think and act, the brain is constantly producing Big Data in the firing of its neurons and in the connections that are strengthened and weakened. This chapter discusses how we can study the brain and the Big Data that it creates. First, we discuss how clever behavioral tasks, looking at development and other species, and natural variation across people are our first tools for understanding the brain. Next, we delve into describing several popular brain imaging methods – direct recording, electroencephalography, magnetoencephalography, magnetic resonance imaging, and a few others. We discuss how to interpret the Big Data shown by brain maps, and some Big Data methods like multiple comparisons correction to consider when viewing this data. Finally, we end the chapter discussing the ethical question of whether such neuroimaging allows mindreading.

This chapter focuses on how recent advances in neuroimaging methods have increased our understanding of a key treatment for bipolar disorder, lithium. Structural magnetic resonance imaging (sMRI) studies suggest that lithium normalises both global and regional reductions in grey matter volume associated with bipolar disorder, while diffusion-weighted imaging (dMRI) studies have shed light on lithium’s potential to rectify abnormalities in white matter integrity. We describe the advent of direct imaging of lithium distribution in the brain using multinuclear MRI techniques (7Li-MRI) which is the first report of noninvasive imaging of a psychoactive drug in its target organ. The spatially heterogenous distribution of the 7Li-MR signal may suggest that lithium directly influences brain structure and function based on lithium tissue concentrations and initial work combining 7Li-MRI and dMRI support this hypothesis. Future directions of research are discussed, including harnessing the potential of multi-modal imaging and longitudinal study designs to develop combined biomarkers or biosignatures of response to treatment. Using lithium as an example, technological and scientific advances in brain imaging can facilitate treatment development and a personalised medicine approach in bipolar disorder.

A growing body of evidence suggests a strong link between how individuals maintain an enriched social network and their brain health. Both the quantity and quality of social networks provide abundant social connections. Through persistent social interactions, individuals’ neurocognitive health appears to benefit from cognitively stimulating activity as well as social support. By utilizing various neuroimaging methods, researchers have found that maintaining an enriched social network is likely to lead to better neural functioning that could delay or counter the effects of neuropathological progression in late life. This chapter reviews studies examining the relationship between social network characteristics and neurocognitive health. The studies highlight that social connectedness and brain functioning have reciprocal effects. It also discusses whether larger and cohesively connected social networks lead to a healthier brain and better cognitive function, as well as the moderators of this association.

Trying to assess the way sex differences in behavior are reflected in the brain, neuroscience reports produced diverse results triggering hot discussions on whether such differences exist and/or are worth considering in further studies. This chapter summarizes recent progress in the study of sex/gender effect on the brain as viewed from the perspective of (1) anatomy, which is based on the description of various global and local morphometric features of male and female brain structures; and (2) connections, which conceptualizes the brain as a large-scale network of structures interconnected within the human connectome which subserves the transmission and integration of information at both global and local levels. It is argued that the key to understanding the behavioral differentiation of the two sexes might lie in the differences in the architecture of their networks rather than in morphometric measures of particular structures and tissues.

Neuroimaging visualizes and quantifies age-related changes in brain structure, function, cerebral blood flow, and cerebral metabolic health. MRI studies show reductions in both overall and regional brain volumes, but to a lesser extent than in Alzheimer’s disease. Those aging non-pathologically tend to have relative preservation of mesial temporal and enthorhinal brain areas. White matter changes are also common as shown by hyperintensities on fluid attenuated inversion recovery and other T2 MRI images, presumably as a result of co-morbities that increasingly occur with age. Diffusion tensor imaging shows reductions in white matter integrity, including white matter fiber counts and overall white matter volume, beginning in mid- to late life. The neural response during both rest and task performance also shows reduced activation of core task-related networks but expansion to include other region activation. Reduced cerebral blood volume and flow also occur, likely reflecting alterations in hemodynamic function due to cerebrovascular and cardiovascular changes. Cerebral metabolic changes on MR spectroscopy occur with reduced concentrations of GABA and other neurotransmitters, as well as markers of neuronal integrity. Myoinositol, a marker of glial activation, may be elevated, indicating neuroinflammation, though this effect is likely not ubiquitous in successful aging.