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Alzheimer's disease (AD) is characterized by extensive, yet selective, neuron death in the cerebral neocortex leading to dramatic decline in cognitive abilities and memory. A more modest disruption of memory occurs frequently in normal aging, in humans and in animal models. Significant neuron death does not appear to be the cause of such age-related memory deficits, but in AD, hippocampal and long association corticocortical circuits are devastated. Evidence from rodent and nonhuman primate models reveals that these same circuits exhibit subtle age-related changes in neurochemical phenotype, dendritic and spine morphology, and synaptic integrity that correlate with impaired function. Molecular alterations of synapses, such as shifts in expression of excitatory receptors, also contribute to these deficits. These brain regions are also responsive to circulating estrogen levels. Interactions between reproductive senescence and brain aging may affect cortical synaptic transmission, implying that certain synaptic alterations in aging may be reversible. As such, integrity of spines and synapses may reflect age-related memory decline, whereas the loss of select cortical circuits is a crucial substrate for functional decline in AD.

Information processing in neurons is critically dependent on dendritic morphology. The overall extent and orientation of dendrites determines the kinds of input a neuron receives. Fine dendritic appendages called spines act as subcellular compartments devoted to processing synaptic information, and the dendritic branching pattern determines the efficacy with which synaptic information is transmitted to the soma. The development of the dendritic tree is influenced by a number of factors. Studies in Drosophila have identified key components of the genetic program that regulates dendritic morphogenesis. Parallel studies in vertebrates have revealed that extracellular signals and neuronal activity exert a major influence on the growth and branching of dendrites and the formation of dendritic spines. The identification of genes that mediate these processes is providing important insight into the molecular mechanisms of dendritic morphogenesis.

Most synapses are made onto dendrites, and most excitatory connections are made onto dendritic spines. Synaptic plasticity is thus an intrinsically dendritic phenomenon, but the functional significance of the structural, electrical, and molecular properties of dendrites for synaptic plasticity is still very poorly understood. Do dendrites have a computational or cell biological role in the modification of synaptic strength that is more than circumstantial? This chapter aims to summarize experimental data and theoretical considerations that may be relevant to the role of dendrites in synaptic plasticity. The focus is on associative Hebbian synaptic plasticity, including spike-timing-dependent forms, mediated by NMDA receptor activation.

Dendrites have both an electrical and a biochemical character, which are closely linked. This chapter discusses dendritic structures as compartments for chemical signals such as concentration changes of ions or other second messengers, which control enzyme activity and signaling cascades. It focuses on the following question: to what extent can these signals be confined to only part of the dendritic tree or to dendritic spines? Such ‘compartmentalization’ is considered the basis of local modifications of dendritic properties, in particular to achieve input-specific changes in synaptic strength. General factors that affect compartmentalization of chemical signals are first discussed, including diffusion, intracellular binding, and removal mechanisms. Examples are given of measurements of dendritic ion and second messenger signaling, with the main focus on calcium signaling, for which the most detailed information is available from imaging studies. Subsequently, in an attempt to define functional units, an overview of the different spatial scales of dendritic compartmentalization is given, spanning a range of three orders of magnitude. Finally, there are examples of how chemical signals are used for dendritic information processing.

This chapter explores our recent advances in our understanding of how estrogens can modulate spinogenesis within the cortex and its relevance for estrogenic-regulation of cognition. It describes how estrogens, including 17β‎-estradiol and estrogen receptor modulators, rapidly modify dendritic spine density concurrently with influencing cognitive behaviors that require cortical processing. Furthermore, it reviews the evidence that these effects are not limited to female animals but may represent a relevant mechanism in the male brain. This chapter will also explore the emerging role for a novel estrogen receptor, G-protein estrogen receptor (GPER), in mediating the rapid effects of estrogens on dendritic spines. Finally, the chapter also reviews the potential molecular mechanisms that underlie rapid estrogenic signaling, linking this signaling to the modulation of spinogenesis, which may ultimately provide a cellular model by which estrogens can produce long-lasting changes in neural circuitry.

This chapter discusses some of the most exciting recent discoveries concerning the mechanisms of spine synapse plasticity and reviews the most intriguing questions which still loom over these tiny cytoplasmic extrusions. It reveals that the sensory experience affects spine motility. This chapter shows that the formation of dendritic spines may be potentiated around sites of high synaptic activity. It supports the hypothesis that spine morphological changes underlie experience-dependent changes in neuronal circuits.

Dendrites, the neuronal processes that receive synaptic inputs, are found in all nervous systems. The great diversity of dendrites, both within individual species and across phylogeny, reflects their adaptation to particular functional roles. This chapter explores this diversity to consider dendrites from an evolutionary perspective. The evidence that dendrites scale across phylogeny to preserve the number of synapses per neuron is reviewed, as well as the architecture of local microcircuits, including the number of neurons in a single neocortical column. Dendritic spines may have originated to form and regulate connections, and later acquired the function of maximizing information storage in densely packed neuropil. These observations are consistent with the unifying principle that dendrites have adapted to keep circuit-level function the same, even though per-gram metabolic rates vary widely. Finally, the chapter considers an emerging area of investigation in normal function and in disease: molecular and developmental mechanisms regulating dendritic form, the targets upon which selection has acted.

This chapter aims to integrate all current knowledge on dendritic spines, and provide information on the important features of the circuits in which they operate. It discusses the various aspects of the biology of the spines. It then presents a brief summary of each chapter on the book, which explores the different physiological functions of the spine.

This chapter reviews the relationship between estrogens, memory, and dendritic spine plasticity. Estrogens, given systemically or directly into the hippocampus, enhance memory consolidation in object recognition and object placement tasks within minutes of application. Dendritic spine density in the CA1 area of the hippocampus and medial prefrontal cortex increases under the same conditions, suggesting that changes in dendritic spine density are an important component of estrogen’s ability to impact memory processes. Possible receptors and signaling pathways mediating the molecular mechanisms in response to estrogen are discussed. Although the precise mechanisms remain to be elucidated, research to date suggests that modulation of dendritic spines by estradiol is a key component in promotion of memory consolidation.

This chapter narrates the discovery of dendritic spines. It begins with Santiago Ramón y Cajal, a Spanish professor of Pathology and Histology, and his work entitled Estractura delos centros nerviosos de la aves (Structure of the Nervous Centers in Birds) and how he discovered the spines using the Golgi technique. Cajal defined “spine” on the spines of a rose bush, as it resembled one when he first investigated it in Purkinje cells.

Research from the past decade has begun to shed light on the neural mechanisms through which the potent estrogen 17β‎-estradiol (E2) regulates the formation of memories. Consolidation is a rapid process which appears to take advantage of the ability of estrogen receptors to quickly trigger cell signaling alterations that increase gene expression, local protein synthesis, and dendritic spinogenesis. This chapter discusses recent advances in understanding how the rapid effects of E2 on the hippocampus influence memory consolidation in female and male rodents and examines new directions for exploring similar mechanisms in other interconnected brain regions.

Although the potent estrogen, 17β‎-estradiol (E2), has long been known to regulate the hippocampal dendritic spine density and synaptic plasticity, the molecular mechanisms through which it does so are less well understood. This chapter discusses the rapid modulation of hippocampal dendritic spine density and synaptic plasticity in male and female rats, with particular attention to studies in hippocampal slices from male rats. Among the mechanisms described are the roles of specific cell-signaling kinases and estrogen receptors in mediating the effects of E2 and progesterone on hippocampal neurons. In addition, dynamic changes of spine structures over time and sex differences in spine regulation are also considered. Finally, the chapter ends by discussing the importance of local hippocampal synthesis of E2 and androgens to hippocampal spine morphology and plasticity.

Learning belongs to a broad principle of biological design: adapt, match, learn, and forget. Organisms respond to changed demands by re-sculpting at all levels to prepare for what will most likely be next. Physical exercise thickens skin and strengthens muscle; mental practice combined with motor practice refines neural circuits and thereby skills. Circuits at early stages, e.g., V1, re-sculpt to match stable changes in bottom-up statistics. Circuits at later stages can, with extended training and practice, radically rewire. For example, an “object” area can re-wire to recognize and store written symbols and words – as it prunes back circuits that recognize and store objects. Because circuits occupy space in a skull of fixed volume, learning couples inescapably to forgetting. Efficient learning involves all the principles of neural design across all spatial and temporal scales: use chemistry; store only what is needed; store only for as long as needed; store and retrieve information without adding wire. Since learning requires practice, efficient design requires a teaching signal to tell the organism what behaviour to repeat. This is the dopamine reward signal that serves as a final common pathway for many learning systems across the whole brain. A similar circuit operates in insects.

Neuroanatomy and dopamine systems explains how sensory signals ascend the central nervous system via a series of nuclei; axons detecting specific elements converge onto higher-order neurons that respond to particular stimulus features. Assemblies of feature-detection cells in the cerebral cortex detect complex stimuli such as faces. These cell assemblies project to motor nuclei of the dorsal and ventral striatum where they terminate on dendritic spines of efferent medium spiny neurons. Dopaminergic projections from ventral mesencephalic nuclei terminate on the same spines. Individual corticostriatal afferents contact relatively few medium spiny neurons and individual dopaminergic neurons contact a far larger number. Stimuli activate specific subsets of corticostriatal synapses. Synaptic activity that is closely followed by a rewarding stimulus, that produces a burst of action potentials in dopaminergic neurons, is modified so that those specific corticostriatal synapses acquire an increased ability to elicit approach and other responses in the future, i.e., incentive learning.

How information circulates in the brain was the subject of a heated debate lasting a decade or more among anatomists in the closing years of the last century. One camp argued that neural tissue consisted of a continuum, a syncytium, with no discernible functional units while the opposing view held that the brain consisted of discrete units, the nerve cells, communicating through point-to-point contacts that Sherrington dubbed synapses. Although in principle both views can be supported, in practice the majority of rapid communication occurs via specific point-to-point contacts, at either chemical and electrical synapses. Ephaptic transmission refers to nonsynaptic, electrical interactions between neurons. While such interactions do occur, for instance, among adjacent, parallel axons across the extracellular space, they are, by their very nature, neither very strong among any one pair of processes nor very specific. Their functional significance—if any—is currently not known, and we will not discuss them here (Traub and Miles, 1991; Jefferys, 1995). In the beginning chapter, we introduced the action of fast, chemical synapses. Given their importance, we will now return to this topic in greater depth. We first overview the pertinent biophysical events underlying chemical synaptic transmission and some of the vital statistics of synapses before we come to the mathematical treatment of synaptic input. In the last section, we will summarize our knowledge of electrical synapses and their computational role. Most typically, a synapse consists of a presynaptic axonal terminal and a postsynaptic process that can be located on a dendritic spine, on the trunk of a dendrite, or on the cell body. Figure 4.1 shows some examples of synapses among cortical cells as seen through a high-powered electron microscope. It is not easy at first to identify the synapses amid all the curved, irregular, and densely packed structures making up the neuronal tissue. In a number of locations, such as the retina or the thalamus, a synaptic connection is made between two dendrites, rather than between an axon and a dendrite. These synapses are called dendrodendritic synapses; they are believed to be relatively rare in the adult cortex. Most synapses are small and highly specialized features of the nervous system. As we will see, a chemical synapse converts a presynaptic electrical signal into a chemical signal and back into a postsynaptic electrical signal.

Intellectual disability is a general term that describes intellectual capacity and adaptive functioning. There are many causes and many co-occurring conditions. To appreciate and respect the uniqueness of each individual and to choose appropriate interventions, it is critical that, if possible, the cause for intellectual disability be identified or the conditions that led to or sustain it be recognized. This chapter begins with an overview followed by an approach to understanding causation, a description of how etiology is determined, consideration of the neurobiological/environmental interface, a discussion of the evaluation process to determine causes and conditions related to diagnoses, and a discussion of risk factors. Intellectual disability is an intellectual, cognitive, and developmental disability that profoundly affects an individual’s functioning and adaptation to everyday life. Intellect refers to mental ability or capacity, the power of thought, and the ability to reason and solve problems. Mental capacity is distinguished from perception, emotions, and feelings. Intelligence refers to facility and quickness in understanding and problem solving. In intellectual disability, there is reduced mental capacity. Cognition refers to the use or handling of knowledge through mental activities associated with thinking, learning, and memory, which are necessary processes to acquire knowledge. In intellectual disability, there are cognitive disabilities that vary depending on the individual syndrome. The extent of intellectual disability varies among syndromes, and there may be variations within a syndrome. Both cognition and intellect are linked to cortical brain function. Intellectual disability is a developmental disability with onset during the developmental period. Thus, there are delays in meeting developmental mile stones in motor, fine motor, language, and psychosocial areas. Finally, there are difficulties in adaptive function and in the mastery of developmental tasks as a result of intellectual, cognitive, and developmental disabilities. A focus on the etiology of intellectual disability is needed for research, clinical, and administrative purposes. This chapter will review the multiple causes of intellectual disability, considering the interface between genetic, neurobiologic, and environmental factors and causation. It emphasizes the importance of a comprehensive evaluation and provides guidelines for conducting an evaluation. Associated mental, emotional, and behavioral disorders are discussed in chapter 6.

In discussions of the mind-body problem, there are two separate issues on which attention is commonly focused: ‘How is it that a material object (a brain) can actually evoke consciousness?’; and, conversely; ‘How is it that a consciousness, by the action of its will, can actually influence the (apparently physically determined) motion of material objects?’ These are the passive and active aspects of the mind-body problem. It appears that we have, in ‘mind’ (or, rather, in ‘consciousness’), a non-material ‘thing’ that is, on the one hand, evoked by the material world and, on the other, can influence it. However, I shall prefer, in my preliminary discussions in this last chapter, to consider a somewhat different and perhaps more scientific question - which has relevance to both the active and passive problems - in the hope that our attempts at an answer may move us a little way towards an improved understanding of these age-old fundamental conundrums of philosophy. My question is: ‘What selective advantage does a consciousness confer on those who actually possess it?’ There are several implicit assumptions involved in phrasing the question in this way. First, there is the belief that consciousness is actually a scientifically describable ‘thing’. There is the assumption that this ‘thing’ actually ‘does something’ - and, moreover, that what it does is helpful to the creature possessing it, so that an otherwise equivalent creature, but without consciousness, would behave in some less effective way. On the other hand, one might believe that consciousness is merely a passive concomitant of the possession of a sufficiently elaborate control system and does not, in itself, actually ‘do’ anything. (This last would presumably be the view of the strong-AI supporters, for example.) Alternatively, perhaps there is some divine or mysterious purpose for the phenomenon of consciousness - possibly a teleological one not yet revealed to us - and any discussion of this phenomenon in terms merely of the ideas of natural selection would miss this ‘purpose’ completely.