Implicit memory refers to a lack of conscious experience or awareness of previously learned information. Section 7.1 considers the brain regions that have been associated with implicit memory, which include the lateral prefrontal cortex and sensory processing regions. In Section 7.2, the frequency bands of activity associated with implicit memory are discussed, which include gamma activity and alpha activity. Section 7.3 details theoretical models of neural activity that underlie implicit memory effects and discusses the ways in which these models can be distinguished from one another. In Section 7.4, evidence is considered that has claimed to link the hippocampus to implicit memory. Section 7.5 focuses on skill learning by evaluating how brain activity changes over time, from the initial stage of learning that depends on long-term memory to a later stage of learning that depends on implicit memory.

This chapter considers the brain regions associated with long-term memory, a type of explicit memory. Long-term memory can be broken down into episodic memory and semantic memory. Episodic memory refers to the detailed retrieval of a previous episode. Semantic memory refers to the retrieval of factual information. The first two sections of the chapter consider the brain regions associated with episodic memory and semantic memory. Section 3.3 considers long-term memory consolidation (i.e., the process of creating more permanent memory representations in the brain). In Section 3.4, the role of sleep in long-term memory consolidation is examined. Long-term memory consolidation requires the interaction between multiple brain regions in which activity oscillates at specific frequencies. Section 3.5 reviews the brain regions associated with memory encoding. In Section 3.6, the brain regions associated with event boundaries (e.g., transitions between scenes in a movie) are discussed, and it is argued that the reported effects reflect the processing of novel information.

This chapter considers the behavioral and brain differences between separate groups of participants during long-term memory. Section 5.1 details differences between females and males (i.e., sex differences). Differences between older adults and younger adults are detailed in Section 5.2. In Section 5.3, the brains of those with superior memory are evaluated, including London taxi drivers and those who compete in World Memory Championships. Although the research on this topic is sparse, there is convergent evidence that having a superior memory does not come without a cost. Section 5.4 discusses the factors that go into determining the minimum number of participants, N, needed in each group to produce valid results that generalize to the population. All the topics of this chapter are important in that they have provided critical insights into the mechanisms mediating long-term memory, yet research on group differences (and N) is unpopular in the field of cognitive neuroscience.

This chapter focuses on the timing of brain activity associated with long-term memory. The chapter begins by introducing ERP activations that have been associated with familiarity and recollection. Familiarity has been associated with activity in frontal brain regions 300–500 milliseconds after stimulus onset, while recollection has been associated with activity in parietal brain regions 500–800 milliseconds after stimulus onset. In Section 4.2, a scientific debate that has focused on the ERP activity associated with familiarity is discussed. In Section 4.3, it is shown that synchronous activity in two different brain regions (i.e., activation time courses that increase and decrease together) indicates that these regions interact. Such synchronous activity between regions during long-term memory typically occurs within the theta frequency band, the alpha frequency band, and the gamma frequency band. Section 4.4 details some intriguing intracranial EEG findings based on recording activity in the hippocampus and the parahippocampal gyrus.

Section 1.1 gives a brief overview of the field of cognitive neuroscience. Section 1.2 details the different types of memory. In Section 1.3, an overview of human brain anatomy is provided. Commonly known anatomic distinctions such as the frontal lobe, the parietal lobe, the temporal lobe, and the occipital lobe are reviewed, and more detailed anatomy is discussed. Section 1.4 highlights the importance of the medial temporal lobe in memory, which was discovered in the 1950s when this region was surgically removed from one individual. In Section 1.5, an overview of brain sensory regions is provided, such as the regions associated with visual perception and auditory perception. In Section 1.6, the regions of the brain that control memory retrieval are considered, which include part of the frontal cortex, the parietal cortex, and the medial temporal lobe. Section 1.7 provides an overview of the organization of this book.

Section 6.1 considers the brain regions associated with typical forgetting, which can be attributed to a lack of attention during encoding. In Section 6.2, the brain mechanisms underlying retrieval-induced forgetting are considered, which is when retrieval of one item (e.g., the word ‘banana’) has an inhibitory effect on related items (e.g., the word ‘orange’) and increases the rate of forgetting for these items. The brain regions associated with a related process called motivated forgetting, which is an increase in the rate of forgetting for items that one intentionally tries to forget, is then considered. In the next two sections of the chapter, two types of memory distortion are considered: false memories (i.e., memories for information that did not occur) and flashbulb memories (i.e., seemingly picture-like memories for very surprising and consequential events). It has been argued that long-term memory failure reflects an adaptive memory system that works well.

Section 2.1 reviews the behavioral measures that allow for the interpretation of brain activation results. Section 2.2 discusses techniques with high spatial resolution, such as fMRI, which is the most popular method. Section 2.3 focuses on techniques with high temporal resolution, such as ERPs. ERPs measure voltages on the scalp that directly reflect the underlying brain activity. In Section 2.4, techniques with excellent spatial resolution and excellent temporal resolution are described, including combined fMRI and ERPs, as well as recording from patients with electrodes implanted in the brain for clinical reasons. Section 2.5 considers evidence from patients with brain lesions and cortical deactivation methods such as TMS. Both methods have limited spatial resolution and poor temporal resolution; however, they can assess whether a brain region is necessary for a given cognitive process. In Section 2.6, the spatial resolution and temporal resolution of the different techniques are compared.

This chapter highlights the cognitive neuroscience techniques that have been employed in the past and the techniques that will be employed in the future. Section 12.1 describes the similarities between fMRI and phrenology, a pseudoscience from about two centuries ago in which protrusions of the skull were associated with behavioral characteristics. In Section 12.2, fMRI is directly compared to ERPs. Section 12.3 discusses research investigating brain region interactions. This type of research has only recently started to be conducted and involves brain activity frequency analysis or modulating one brain region and measuring how that changes activity in another brain region. Section 12.4 provides an overview of the field of cognitive neuroscience in the future. The final section shines a spotlight on the dimension of time. To date, temporal processing in the brain has received less attention than spatial localization. However, time is the future of the cognitive neuroscience of memory.

Over the years, the General Theory has been as controversial as it has been influential. However, many of the controversies have been fanned by misunderstandings of the General Theory. In addition, resolution to the controversies were sometimes delayed because the models used to account for specific phenomena were not yet developed. This chapter addresses these controversies by showing how specific empirical phenomena once thought by some to challenge the General Theory are actually predicted a priori by retrieving effectively from memory (REM) models originally designed to account for forgetting.

An often overlooked, but important, influence on human memory is prior testing. In this chapter, search of associative memory (SAM) and retrieving effectively from memory (REM) models of effects of memory testing are described, as applied to recall and recognition procedures. In addition, problems associated with not taking into account the consequences of testing are illustrated through a discussion of ongoing research on the von Restorff effect.

The formal details of the modeling frameworks that have been most useful in accounting for specific empirical phenomena are presented. At the highest, most abstract level are mathematical models used to describe how the contents of the short-term store are managed. At the middle level, the search of associative memory models (SAM) describe how information is transferred from the short-term store to the long-term store, and how memories in the long-term store are retrieved to the short-term store. At the lowest, most complex level, the retrieving effectively from memory (REM) models are described, which implement multidimensional memory representations and rational decision processes.