Chapter 7 deals with neuroimaging methods for investigating the structural components underlying brain function. Beginning with lesion-symptom mapping (LSM), which identifies relationships between localized brain damage and specific cognitive deficits, the chapter examines how structural abnormalities correlate with functional impairments. Three primary approaches to measuring brain structures with MRI are discussed: structure tracing for hypothesis-driven volumetric analysis, voxel-based morphometry (VBM) for whole-brain comparison of tissue concentration, and surface-based morphometry (SBM) for analyzing the cortical sheet’s unique properties including thickness, curvature, and gyrification. The chapter then explores diffusion tensor imaging (DTI), a technique that visualizes white-matter tracts by measuring the anisotropic diffusion of water molecules along axon bundles. DTI tractography reveals the brain’s “highways,” short, intermediate, and long-range fiber pathways that connect functional modules within and across hemispheres. Together, these complementary techniques provide critical insights into the structural architecture supporting brain networks, offering a more complete understanding of brain organization when combined with functional imaging methods.

Chapter 9 introduces transcranial magnetic stimulation (TMS), a neurostimulation technique that uses rapidly changing magnetic fields to induce electric currents in targeted brain regions. Beginning with its historical roots in 19th-century electromagnetic experiments and evolving through Anthony Barker’s groundbreaking 1985 demonstration, TMS has become a critical tool for establishing causal relationships between brain activity and behavior. Unlike neuroimaging methods that only observe brain activity, TMS can temporarily interrupt or enhance neural processing, enabling researchers to create “virtual lesions” and directly test hypotheses about regional brain function. The chapter examines TMS delivery methods, single-pulse, paired-pulse, and repetitive stimulation, and their differential effects on cortical excitability. It details four primary research applications: virtual lesions for establishing causality, chronometry for determining processing timelines, mapping functional connectivity between brain regions, and tracking neuroplasticity. Clinical applications are discussed, particularly for treating depression and presurgical mapping. The chapter also addresses practical aspects of TMS implementation, localization techniques, and safety considerations, concluding with a brief overview of transcranial direct current stimulation (tDCS) as a milder alternative stimulation approach.

Chapter 2 traces the development of electroencephalography (EEG) from its inception with Richard Caton’s pioneering work in 1875 to its current status as a cornerstone of human neuroimaging. The chapter discusses how EEG captures the electrical signals generated by synchronous activity of pyramidal neurons arranged in open fields perpendicular to the cortical surface. It examines the technical evolution of recording systems, from basic silver-chloride electrodes to modern active electrode arrays with built-in amplification, and explains the standardized 10-20 electrode placement system that enables spatial mapping of brain activity. The chapter addresses the inverse problem that constrains EEG’s spatial resolution while highlighting its exceptional temporal precision for tracking neuronal events in millisecond timescales. Special attention is given to the characteristic oscillatory patterns in different frequency bands (alpha, beta, theta, delta, gamma) and their association with cognitive states ranging from deep sleep to focused attention. The chapter details practical considerations for obtaining clean recordings, including artifact reduction techniques and experimental design. By evaluating EEG’s strengths (temporal precision, direct measurement of neural activity, accessibility) alongside its limitations, the chapter positions EEG as an enduring, versatile tool for both clinical applications and cognitive neuroscience research despite technological advances in other imaging modalities.

This chapter examines intracranial electroencephalography (iEEG), a rare but powerful technique offering unparalleled insights into human brain function by recording electrical activity directly from the brain’s surface. It traces iEEG’s development from pioneering work by Penfield and Jasper in the 1950s to modern applications with up to 1,024 recording channels. The chapter outlines the two primary surgical approaches, stereo EEG with depth electrodes and electrocorticography with surface grids, and explains how these techniques achieve both high temporal (millisecond) and spatial (millimeter) resolution by bypassing the signal-dampening effects of skull and scalp. Particular attention is given to high-gamma-power signals (70–200 Hz), which reflect neuronal firing with exceptional signal-to-noise ratios. The chapter addresses methodological considerations including electrode localization, signal processing, and data interpretation challenges unique to recording from epilepsy patients. It balances discussion of iEEG’s remarkable advantages, such as direct access to neuronal activity across cortical layers and network nodes along with its limitations, including restricted accessibility, sparse sampling, and the clinical constraints that dictate electrode placement. The ethical framework governing this invasive research methodology is emphasized throughout.

Chapter 5 examines functional magnetic resonance imaging (fMRI) as a transformative neuroimaging technique that maps brain activity by detecting changes in blood oxygenation. The chapter traces fMRI’s development from Angelo Mosso’s 19th-century observations of blood-flow changes during neural activity to Seiji Ogawa’s pioneering work with blood oxygenation level-dependent (BOLD) contrast in the 1990s. It discusses the neurophysiological basis of the BOLD signal and how increased neural activity triggers disproportionate increases in cerebral blood flow relative to oxygen metabolism, creating measurable magnetic susceptibility differences. The text analyzes the temporal profile of the hemodynamic response, with its characteristic delay, peak, and undershoot, emphasizing its implications for experimental design. Considerable attention is given to the methodological complexities of fMRI research: preprocessing steps (slice-timing correction, motion correction, coregistration), statistical analysis approaches (including voxel-wise comparisons and region-of-interest analyses), and techniques for examining functional connectivity between brain regions. By evaluating fMRI’s comparative advantages, which is exceptional spatial precision and its noninvasive nature, alongside its limitations in temporal resolution and indirect measurement of neural activity, the chapter discusses fMRI as a powerful, albeit technically demanding, tool that provides unique insights into functional brain organization while requiring rigorous experimental design and statistical analysis.

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.

Chapter 14 allows us a look at the trajectories in brain imaging technology and research while acknowledging the field’s unpredictable evolution. It examines how existing tools are being refined, with functional MRI achieving submillimeter resolution and EEG sampling rates reaching 100,000 Hz, while highlighting the growing influence of private industry through initiatives like Neuralink, Facebook’s Building 8, and Google Brain. The chapter analyzes the scientific value of multimodal imaging approaches that combine complementary techniques such as EEG-fMRI to leverage both high temporal and spatial resolution. It discusses how large-scale collaborative efforts including the Human Connectome Project and Brain Initiative are reshaping our understanding of neural connectivity despite the challenges of modeling the brain’s extraordinary complexity. The emergence of biomarkers receives particular attention, emphasizing how machine learning algorithms are enhancing our ability to detect neurological and psychiatric conditions through brain imaging data. Recent technological innovations are surveyed, including miniaturized MRI scanners, real-time imaging analysis, optically pumped magnetometry, and functional ultrasound imaging, all pointing toward more accessible and sophisticated brain measurement capabilities. The chapter concludes with practical guidance for newcomers to the field and consideration of ethical dimensions, emphasizing that brain imaging technologies should advance human wellbeing rather than enable control or manipulation. Throughout, the chapter maintains that while specific trajectories remain uncertain, the overall direction is toward increasingly precise, accessible, and clinically valuable brain imaging technologies.

Chapter 12 examines the methodological foundations for conducting effective brain imaging research, positioning experimental design as the cornerstone of meaningful neuroscientific inquiry. It outlines a systematic approach to developing experiments, beginning with the essential groundwork of literature review and theoretical development before proceeding to stimulus creation and experimental implementation. The chapter emphasizes the critical balance between simplicity and complexity in design, advocating for well-controlled paradigms that isolate specific cognitive processes while acknowledging the brain’s inherent complexity. Particular attention is given to the technical considerations unique to different imaging modalities, addressing how fMRI’s hemodynamic response requires different design considerations than EEG’s direct measurement of neural activity. The chapter explores the philosophical challenges of constructing appropriate control conditions that effectively isolate the cognitive processes of interest, comparing cognitive subtraction approaches with factorial designs that reveal interaction effects. It emphasizes the importance of piloting experiments to identify potential confounds like expectancy bias and the role of jittered intertrial intervals in minimizing such effects. Throughout, the chapter underscores that experimental design in neuroimaging requires interdisciplinary expertise: understanding of brain anatomy and physiology, mastery of imaging technology, and sophisticated experimental psychology skills to translate abstract cognitive concepts into operationalizable experimental paradigms.

Chapter 6 explores magnetoencephalography (MEG), a neuroimaging technique that measures magnetic fields generated by neural activity with millisecond temporal precision. Starting with MEG’s development by David Cohen in 1967 and the crucial introduction of SQUID sensors, the chapter examines how MEG differs from EEG while measuring activity from the same neural sources. While EEG predominantly detects signals from gyri parallel to the skull, MEG captures perpendicular signals from sulci with superior spatial resolution as magnetic fields pass unimpeded through tissue. The practical aspects of MEG acquisition are covered, including participant preparation, artifact removal, and the importance of structural MRI for anatomical coregistration. The chapter addresses source localization challenges, such as the inverse problem of determining which neuronal sources created the detected signals, and explores solutions ranging from single dipole models to distributed approaches using anatomical constraints. Clinical applications in epilepsy and presurgical mapping are discussed, as is the complementary nature of combining MEG with other imaging modalities, particularly fMRI, to leverage their respective spatial and temporal strengths for comprehensive brain activity visualization.

Chapter 13 discusses the analysis processes that transform raw brain imaging data into meaningful neuroscientific insights. It explains the methodical progression from preprocessing to advanced analytical techniques, emphasizing that analysis is not merely a technical afterthought but a fundamental component of neuroimaging research. The chapter begins by addressing preprocessing steps – quality control, artifact correction, normalization, and smoothing – that prepare data for subsequent analysis while preserving signal integrity. It then explores single-subject processing approaches that aggregate experimental conditions and trials to establish individual response patterns before proceeding to group-level analyses that enable population-level inferences. Statistical considerations receive particular attention, with the chapter explaining how techniques like statistical parametric mapping function as the interpretive lens through which brain activity becomes visible. The problematic issue of multiple comparisons is thoroughly examined, illustrating how whole-brain analyses necessitate statistical correction to prevent false positives in the tens of thousands of simultaneous tests typical in neuroimaging. The chapter extends beyond traditional univariate approaches to cover network analysis methodologies that reveal functional connectivity patterns between brain regions. It concludes by addressing emerging analytical frontiers: real-time analysis for brain–computer interfaces, closed-loop brain stimulation paradigms, and the methodological limitations that necessitate careful interpretation of neuroimaging results. Throughout, the chapter emphasizes that analytical expertise is as essential as technical proficiency with imaging hardware, and that understanding analytical limitations is crucial for responsible interpretation of the neural basis of cognition and behavior.

Chapter 3 explores event-related potentials (ERPs), one of electroencephalography’s most powerful analytical techniques for investigating cognitive processing. The chapter traces ERPs’ evolution from Pauline and Hallowell Davis’s pioneering work in 1939 through its exponential growth as a research methodology. It explains how ERPs extract meaningful neural signals by time-locking and averaging EEG segments surrounding stimulus presentations, thereby revealing characteristic voltage deflections that correspond to specific cognitive processes. The text examines key ERP components, including C1, P1, N1, P2, N2, and P300, detailing their temporal progression, neuroanatomical origins, and functional significance in the processing hierarchy. It evaluates ERPs’ exceptional capacity to discriminate between processing stages occurring within milliseconds of each other, from early sensory encoding through attention allocation to semantic processing. The chapter addresses methodological considerations essential for robust ERP research, including experimental design principles, artifact reduction techniques, and the interpretation of scalp topographies. By analyzing ERPs’ comparative advantages, including millisecond-precise temporal resolution, ability to track covert processing without behavioral responses, and sensitivity to processing stage differences, alongside their limitations in spatial localization and specific experimental contexts, the chapter positions ERPs as a vital methodology for understanding the sequential unfolding of perceptual and cognitive processes in the human brain.

Chapter 10 discusses functional near-infrared spectroscopy (fNIRS), a noninvasive brain imaging technique that utilizes light to measure hemodynamic responses. It traces the evolution of spectroscopy from Newton’s prism experiments to modern neuroimaging applications, explaining how near-infrared light penetrates tissue to detect changes in oxygenated and deoxygenated hemoglobin. The chapter details the physical principles underlying fNIRS, comparing continuous wave, frequency domain, and time domain approaches while examining the instrumentation of modern systems. It addresses practical considerations including optode placement, signal quality optimization, and noise reduction techniques. The relationship between fNIRS signals and neural activity is discussed, highlighting similarities to the BOLD response in fMRI while acknowledging limitations in depth penetration. The chapter covers analytical approaches for fNIRS data processing and emphasizes its unique advantages: portability, relative affordability, and functionality in environments hostile to electromagnetic recordings. Case studies demonstrate fNIRS applications in specialized contexts like underwater environments and space exploration, illustrating why this technique has become an essential tool for specific research questions despite its spatial limitations.