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This chapter examines the nature of memory causation. This involves identifying the vehicle of memory causation, specifying the strength of the causal relation constitutive of memory, and ruling out deviant causal chains. It is argued that the causal chains connecting the past and present representation must consist in a persisting memory trace. Memory traces are either dispositional beliefs or subdoxastic states. For a memory trace to give rise to a genuine memory it must at least be an INUS condition for one's present state of seeming to remember. If the memory trace is an independently sufficient condition for the state of seeming to remember, it may not be preempted by another independently sufficient condition. The dependence of memory states on past representations must support counterfactuals of the form: if the subject hadn't represented a particular proposition in the past he wouldn't represent it now. This chapter discusses, among other things, the possibility of trace transplants, connectionism, the Gettier problem, hypnosis, and suggestibility.

This part presents four chapters on the concept of consolidation. The first chapter presents a personal view of memory consolidation that illustrates the growing ambivalence towards this enormously influential idea. The second focuses on molecular consolidation and its implications for what memory is at the biological level. The third argues that the notion of a fixed memory trace, and its strengthening during consolidation, stands as a barrier to further progress in understanding the nature and underlying bases of memory. The fourth chapter presents a synthesis of the chapters in this part.

This part presents four chapters on the concept of coding and representation. The first chapter focuses on the online coding and representation of information by means of neuronal activity. The second argues that the ability of the brain to segregate and integrate information, to make use of population and predictive coding, makes for a system that is specialized for memory. The third discusses the concept of memory trace. The fourth chapter presents a synthesis of the chapters in this part.

Descartes explains memory and imagination, as ideas, by patterns in the flow of animal spirits through the brain that are caused by traces of former sensations (memory) or by other bodily conditions that are more active when we sleep or daydream. Despite the contrast with intuition, imagination constructs reliable images of perceptual phenomena, by synthesizing incoming signals from different senses.

This chapter reviews the theoretical considerations for why the brain might require an active reprocessing of memories during periods when it is relatively ‘disconnected’ from external input. It summarizes the current understanding of the phenomenon based on neurophysiological investigations in animals.

This chapter begins with a discussion of a two-stage model of memory trace formation. It then discusses the similarity of long-term firing rates and co-activation in the waking and sleeping brain, the impact of experience in a novel environment on firing patterns in subsequent sleep, homeostatic maintenance of firing rates, and downstream effects of cortical activity during sleep.

This chapter develops an interpretation of the working memory span task as reflecting the rapid switching of a single, limited capacity attentional resource between the processing element and rehearsal of the items for recall. It argues that memory trace is subject to decay over time and demonstrates that when attention is captured by demanding processing tasks that prevent time for rehearsal, the result is poorer memory performance. This view then is of a system in which capacity is limited by time and by attention.

This chapter discusses post-Nietzschean philosophers and other forms of the anachronous. One of these forms is within memory, which is seen as always productive of the traumatic event. It studies the sense of catastrophe that is outside chronology. This chapter also studies anachronoristics, the structure of language anachronistic, the use of flashbacks in the film 2046, and trauma.

Evidence supports the view that ‘memory traces’ are formed in the hippocampus and in the cerebellum in classical conditioning of discrete behavioural responses. In the hippocampus learning results in long-lasting increases in excitability of pyramidal neurons that resemble the phenomenon of long-term potentiation. Although it plays a role in certain aspects of conditioning, the hippocampus is not necessary for learning and memory of the basic conditioned responses. The cerebellum and its associated brain-stem circuitry, on the other hand, does appear to be essential (necessary and sufficient) for learning and memory of the conditioned response.

This chapter lays the conceptual and mathematical foundations of dynamic field theory (DFT). It first discusses continua of possible percepts and of possible motor actions and proposes activation fields defined over relevant feature dimensions as the universal format of the neural representations on which perceptual, motor, and cognitive processes are based. The neural dynamics introduced in Chapter 1 are lifted to a dynamics of these activation fields. Self-excitation, discussed in Chapter 1, becomes local excitatory interaction within an activation field. Mutual inhibitory coupling, also discussed in Chapter 1, becomes global inhibitory interaction within a field. Self-stabilized peaks of activation become the new attractor states, which are the fundamental units of representation in DFT. A set of instabilities is examined that peaks emerge from or disappear in. The last element of DFT introduced is the memory trace, a simple mechanism of learning from the activation history of a field.

This chapter applies dynamic field theory to word learning. The use of one-dimensional neural fields to represent labels and the combination of these with a feature dimension are introduced. These label-feature fields keep a record of prior feature-label associations via the memory trace mechanism. Using a robotic instantiation, the chapter show how individual features of objects, represented in multiple feature-label fields, can be bound via a shared label dimension. The result is a dynamic field model that can 1) learn robust novel label-object mappings after only a few presentations of the label and/or the object, 2) demonstrate emergent categories, 3) fill in missing information, and 4) distinguish between two different objects that share a value on one feature dimension but not others. An expanded version of this model includes two feature-label and two feature-space fields, which enable the model to overcome referential ambiguity by binding names to objects across a shared spatial dimension. This model can capture multiple word-learning behaviors, thus pointing to a critical innovation of this work—the integration of timescales.

Infants are said to habituate to a stimulus as their looking to it declines over the course of a task. As infants look and look away from a stimulus, they form lasting long-term memories for it. With age, infants habituate more quickly and can discriminate between highly similar familiar and novel stimuli. This chapter extends the concepts of recognition and change detection in the three-layer model to infant habituation by adding a memory trace and fixation system to the model. This model provides an account of a wide array of looking behaviors infants exhibit in habituation tasks, including the interdependence between looking and memory formation. To account for developmental change in looking and discrimination, the spatial precision hypothesis is generalized from the domain of spatial working memory to infant habituation. The chapter concludes with a set of simulations testing whether the dynamic field model can autonomously create developmental change in looking and memory formation through the slow accumulation of a memory trace across an entire feature dimension.

This chapter presents a neurocognitive study of musical material by showing research investigating musical information in short-term and working memory. It is illustrated here how short-term memory of musical material suffers from interference due to additional information and from forgetting over time. Memory traces of music can improve, however, and become more precise over time as evidenced by an investigation of short-term memory for musical material during the continuous listening of an ongoing musical piece. Even nonmusicians possess knowledge about the musical system of their culture. This chapter also considers listeners' long-term knowledge about specific familiar melodies, also referred to as the “musical lexicon.” Drawing from multiple findings, this chapter presents the specific feature of musical memory and its neural correlates and compares them to memory in language and other domains.

Learning can be considered as a stimulus- and, hence, activity-dependent neuronal process that leads to a lasting change of stimulus-response relationships. The formation of a memory trace may thus be considered as a modification of the neuronal program that specifies input-output functions. This program is contained in the architecture of neuronal connectivity and in the transfer functions of these connections. Thus, any activity-dependent process that modifies, in a sufficiently stable and long-lasting way, the interactions between pairs of neurones could serve as a mechanism of learning.