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Books on the topic 'Brain encoding'

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Published: 7 July 2024
Last updated: 7 July 2024

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1

1955-, Parker Amanda, Wilding Edward L. 1968-, and Bussey Timothy J. 1961-, eds. The cognitive neuroscience of memory: Encoding and retrieval. New York: Psychology Press, 2002.

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2

Cao, Chenglong. Immunological screening of a rat brain cDNA library for genes encoding potential novel glutamate receptors. Ottawa: National Library of Canada, 1993.

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3

Parker, Amanda, Timothy J. Bussey, and Edward L. Wilding. Cognitive Neuroscience of Memory: Encoding and Retrieval. Taylor & Francis Group, 2005.

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4

Parker, Amanda, Timothy J. Bussey, and Edward L. Wilding. Cognitive Neuroscience of Memory: Encoding and Retrieval. Taylor & Francis Group, 2005.

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5

Parker, Amanda, Timothy J. Bussey, and Edward L. Wilding. Cognitive Neuroscience of Memory: Encoding and Retrieval. Taylor & Francis Group, 2014.

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6

Parker, Amanda, Timothy J. Bussey, and Edward L. Wilding. Cognitive Neuroscience of Memory: Encoding and Retrieval. Taylor & Francis Group, 2005.

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7

Parker, Amanda, Timothy J. Bussey, and Edward L. Wilding. Cognitive Neuroscience of Memory: Encoding and Retrieval. Taylor & Francis Group, 2005.

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8

Parker, Amanda, Timothy J. Bussey, and Edward L. Wilding. Cognitive Neuroscience of Memory: Encoding and Retrieval. Taylor & Francis Group, 2005.

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9

Cao, Chenglong. Immunological screening of a rat brain cDNA library for genes encoding potential novel glutamate receptors. 1994.

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10

Roth, Jeffrey Stephen. Isolation and expression of a cDNA clone encoding the catalytic subunit of the rat cAMP-dependent protein kinase. 1987.

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11

Landry, Charles Francis. Expression from the gene encoding the gbs-subunit of the S100 protein during development of the rodent brain. 1992.

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12

Papanicolaou, Andrew C., ed. The Oxford Handbook of Functional Brain Imaging in Neuropsychology and Cognitive Neurosciences. Oxford University Press, 2014. http://dx.doi.org/10.1093/oxfordhb/9780199764228.001.0001.

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A large part of the contemporary literature involves functional neuroimaging. Yet few readers are sufficiently familiar with the various imaging methods, their capabilities and limitations, to appraise it correctly. To fulfill that need is the purpose of this Handbook, which consists of an accessible description of the methods and their clinical and research applications. The Handbook begins with an overview of basic concepts of functional brain imaging, magnetoencephalography and the use of magnetic source imaging (MSI), positron emission tomography (PET), diffusion tensor imaging (DTI), and transcranial magnetic stimulation (TMS). The authors then discuss the various research applications of imaging, such as white matter connectivity; the function of the default mode network; the possibility and the utility of imaging of consciousness; the search for mnemonic traces of concepts the mechanisms of the encoding, consolidation, and retrieval of memories; executive functions and their neuroanatomical mechanisms; voluntary actions, human will and decision-making; motor cognition; language and the mechanisms of affective states and pain. The final chapter discusses the uses of functional neuroimaging in the presurgical mapping of the brain.
13

Mitchell, Karen J. The Cognitive Neuroscience of Source Monitoring. Edited by John Dunlosky and Sarah (Uma) K. Tauber. Oxford University Press, 2015. http://dx.doi.org/10.1093/oxfordhb/9780199336746.013.2.

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Source monitoring is a metamemory function that includes processes for encoding and organizing the content of memories, and processes that selectively revive, cumulate, and evaluate that content in the service of making attributions about the origin of the information (e.g., perception vs imagination). Neuroimaging techniques, especially functional magnetic resonance imaging (fMRI), are encouraging rapid developments in understanding the neural mechanisms supporting source monitoring. This chapter reviews current findings, placing them in historical context. It highlights key issues of particular relevance, including: neural reinstatement—the match between brain activity at encoding and later remembering; the role of lateral parietal cortex in cumulating multiple features and attending to information during remembering; functional specificity of the prefrontal cortex with respect to cognitive control; and identifying functional networks that support source monitoring. Suggestions are made for clarifying the big picture and increasing the specificity of our understanding of source monitoring and its neural architecture.
14

van de Ven, Vincent, Henry Otgaar, and Mark L. Howe. A Neurobiological Account of False Memories. Oxford University Press, 2017. http://dx.doi.org/10.1093/oso/9780190612016.003.0005.

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This chapter discusses human functional neuroimaging findings about how the brain creates true and false memories. These studies have shown that different brain systems contribute to the creation and retrieval of false memories, including systems for sensory perception, executive functioning and cognitive control, and the medial temporal lobe, which has long been associated with episodic and autobiographical memory formation. Many neuroimaging findings provide support for an associative account of false memories, which proposes that false memories arise from associating unrelated mental experiences in memory. At the same time, other neuroimaging findings suggest that false memory creation may depend on states of brain activity during memory encoding. Finally, the chapter briefly provides cautionary notes about using functional neuroimaging as a tool to assess private mental states in individual cases in the courtroom.
15

Papanicolaou, Andrew C., Roozbeh Rezaie, Shalini Narayana, Asim F. Choudhri, James W. Wheless, Eduardo M. Castillo, James E. Baumgartner, and Frederick A. Boop. Clinical Applications of Functional Neuroimaging. Edited by Andrew C. Papanicolaou. Oxford University Press, 2014. http://dx.doi.org/10.1093/oxfordhb/9780199764228.013.004.

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The main clinical application of functional neuroimaging is mapping cortical regions containing part of the circuitry necessary for somatosensory, motor, and language functions and assessing hemispheric dominance for both language and encoding operations of memory prior to several types of brain surgery. Presently, it is used in conjunction with the classical invasive methods of brain mapping. This chapter presents the case for replacing invasive methods with noninvasive ones given the limitations of the invasive methods that render them unjustifiable as “gold standards.” Evidence is presented that the efficacy of the two types of methods in reducing morbidity, facilitating surgical planning, and enhancing surgical outcome is comparable. Additional advantages of noninvasive presurgical brain mapping are also discussed. The chapter concludes that there are no compelling reasons for invasive mapping in most patients whenever noninvasive methods are available.
16

Craik, Fergus I. M. Remembering. Oxford University Press, 2021. http://dx.doi.org/10.1093/oso/9780192895226.001.0001.

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The book sets out Fergus Craik’s view of human memory as a dynamic activity of mind and brain. In this account, remembering is understood as a system of active cognitive processes, similar to the processes underlying attending, perceiving, and thinking. The book therefore extends and elaborates the concept of “levels of processing” proposed by Craik and Lockhart (1972). Thus, encoding processes are essentially the mental activities involved in perceiving and understanding, and retrieval is described as the partial reactivation of these same processes. It is further suggested that “memory traces” are represented by a hierarchically organized system of analyzers, modified, sharpened, and differentiated by encounters with successive events. This account proposes that episodic and semantic memory should be thought of as levels in a continuum of specificity rather than as separate systems of memory. The book also covers Craik’s views on working memory and on changes in memory as a function of aging. In the latter case the losses are attributed largely to a difficulty with the self-initiation of appropriate encoding and retrieval operations, compensated by support from the external environment. There is a short chapter on the cognitive neuroscience of human memory, and a final chapter bringing the ideas together. The book covers the development of these ideas, illustrated substantially by experiments from Craik’s own laboratory, and also by empirical and theoretical contributions from other researchers. The final product is a broad account of current ideas and findings in contemporary memory research but viewed from Craik’s personal theoretical standpoint.
17

Carrión, Victor G., John A. Turner, and Carl F. Weems. Memory. Oxford University Press, 2017. http://dx.doi.org/10.1093/med/9780190201968.003.0002.

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One of the most prominent symptoms of PTSD is the persistence of troubling trauma-memories that appear resistant to extinction. To understand the key role that memory plays in the development of PTSD, the current chapter presents a review of theoretical models for memory encoding, processing, learning, and extinction. The preclinical literature that has informed our understanding of the toxic relationship between chronic elevation of stress hormones such as glucocorticoids and memory is examined. Consideration of cognitive and neuroimaging studies on adults and children illustrates the long-term consequences of traumatic stress on the neurofunctional structures involved in memory, such as the hippocampus and LHPA axis. The variance in these effects, attributable to their timing and context, is discussed, and suggests that stress may preprogram subsequent memory performance when it is experienced during the critical period of brain development.
18

Brigard, Felipe De. Memory and the Intentional Stance. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780199367511.003.0005.

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Despite Dennett’s vast scholarship, he seemed to only have directly addressed the topic of memory in a relatively unknown coauthored article published in a somewhat obscure volume. The current chapter attempts to reconstruct the ideas from this old article, and argues that it offers a viable and coherent view of episodic memory with substantial empirical support. Specifically, the chapter uncovers three empirically supported theses. A functional thesis, according to which our memory system not only processes information about past events but also uses this information to construct useful anticipations of possible future events. A computational thesis, according to which statistical regularities, along with individual limitations and goals, probabilistically constrain the search space examined during memory retrieval. And a metaphysical thesis, according to which memories do not exist as subpersonal-level brain structures encoding particular intentional contents but rather as personal-level psychological phenomena only accessible from the intentional stance.
19

Mundy, Peter. A Neural Networks, Information-Processing Model of Joint Attention and Social-Cognitive Development. Edited by Philip David Zelazo. Oxford University Press, 2013. http://dx.doi.org/10.1093/oxfordhb/9780199958474.013.0010.

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A neural networks approach to the development of joint attention can inform the study of the nature of human social cognition, learning, and symbolic thought process. Joint attention development involves increments in the capacity to engage in simultaneous or parallel processing of information about one’s own attention and the attention of other people. Infant practice with joint attention is both a consequence and an organizer of a distributed and integrated brain network involving frontal and parietal cortical systems. In this chapter I discuss two hypotheses that stem from this model. One is that activation of this distributed network during coordinated attention enhances the depth of information processing and encoding beginning in the first year of life. I also propose that with development joint attention becomes internalized as the capacity to socially coordinate mental attention to internal representations. As this occurs the executive joint attention network makes vital contributions to the development of human social cognition and symbolic thinking.
20

Powell, Craig M. PTEN and Autism With Macrocepaly. Oxford University Press, 2013. http://dx.doi.org/10.1093/med/9780199744312.003.0010.

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Phosphatase and Tensin homolog deleted on chromosome 10 (PTEN) is a gene encoding an intracellular signaling molecule. PTEN was originally discovered as the gene responsible for a subset of familial hamartoma (tumor) syndromes associated with increased risk for certain cancers (Nelen et al., 1997) and as a gene often mutated in human cancers and tumor cell lines (Li et al., 1997; Steck et al., 1997). More recently, mutations in PTEN have been linked genetically to the clinical phenotype of autism or developmental delay with macrocephaly (Boccone et al., 2006; Butler et al., 2005; Buxbaum et al., 2007; Goffin, Hoefsloot, Bosgoed, Swillen, & Fryns, 2001; Herman, Butter, et al., 2007; McBride et al., 2010; Orrico et al., 2009; Stein, Elias, Saenz, Pickler, & Reynolds, 2010; Varga, Pastore, Prior, Herman, & McBride, 2009; Zori, Marsh, Graham, Marliss, & Eng, 1998). This chapter examines the role of PTEN in intracellular signaling, the link between PTEN signaling pathways and other autism-related genes and signaling pathways, the genetic relationship between PTEN and autism, model systems in which effects of Pten deletion on the brain have been studied, and promising preclinical data identifying therapeutic targets for patients with autism/macrocephaly associated with PTEN mutations.
21

Butz, Martin V., and Esther F. Kutter. How the Mind Comes into Being. Oxford University Press, 2017. http://dx.doi.org/10.1093/acprof:oso/9780198739692.001.0001.

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For more than 2000 years Greek philosophers have thought about the puzzling introspectively assessed dichotomy between our physical bodies and our seemingly non-physical minds. How is it that we can think highly abstract thoughts, seemingly fully detached from actual, physical reality? Despite the obvious interactions between mind and body (we get tired, we are hungry, we stay up late despite being tired, etc.), until today it remains puzzling how our mind controls our body, and vice versa, how our body shapes our mind. Despite a big movement towards embodied cognitive science over the last 20 years or so, introductory books with a functional and computational perspective on how human thought and language capabilities may actually have come about – and are coming about over and over again – are missing. This book fills that gap. Starting with a historical background on traditional cognitive science and resulting fundamental challenges that have not been resolved, embodied cognitive science is introduced and its implications for how human minds have come and continue to come into being are detailed. In particular, the book shows that evolution has produced biological bodies that provide “morphologically intelligent” structures, which foster the development of suitable behavioral and cognitive capabilities. While these capabilities can be modified and optimized given positive and negative reward as feedback, to reach abstract cognitive capabilities, evolution has furthermore produced particular anticipatory control-oriented mechanisms, which cause the development of particular types of predictive encodings, modularizations, and abstractions. Coupled with an embodied motivational system, versatile, goal-directed, self-motivated behavior, learning becomes possible. These lines of thought are introduced and detailed from interdisciplinary, evolutionary, ontogenetic, reinforcement learning, and anticipatory predictive encoding perspectives in the first part of the book. A short excursus then provides an introduction to neuroscience, including general knowledge about brain anatomy, and basic neural and brain functionality, as well as the main research methodologies. With reference to this knowledge, the subsequent chapters then focus on how the human brain manages to develop abstract thought and language. Sensory systems, motor systems, and their predictive, control-oriented interactions are detailed from a functional and computational perspective. Bayesian information processing is introduced along these lines as are generative models. Moreover, it is shown how particular modularizations can develop. When control and attention come into play, these structures develop also dependent on the available motor capabilities. Vice versa, the development of more versatile motor capabilities depends on structural development. Event-oriented abstractions enable conceptualizations and behavioral compositions, paving the path towards abstract thought and language. Also evolutionary drives towards social interactions play a crucial role. Based on the developing sensorimotor- and socially-grounded structures, the human mind becomes language ready. The development of language in each human child then further facilitates the self-motivated generation of abstract, compositional, highly flexible thought about the present, past, and future, as well as about others. In conclusion, the book gives an overview over how the human mind comes into being – sketching out a developmental pathway towards the mastery of abstract and reflective thought, while detailing the critical body and neural functionalities, and computational mechanisms, which enable this development.
22

Butz, Martin V., and Esther F. Kutter. Top-Down Predictions Determine Perceptions. Oxford University Press, 2017. http://dx.doi.org/10.1093/acprof:oso/9780198739692.003.0009.

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While bottom-up visual processing is important, the brain integrates this information with top-down, generative expectations from very early on in the visual processing hierarchy. Indeed, our brain should not be viewed as a classification system, but rather as a generative system, which perceives something by integrating sensory evidence with the available, learned, predictive knowledge about that thing. The involved generative models continuously produce expectations over time, across space, and from abstracted encodings to more concrete encodings. Bayesian information processing is the key to understand how information integration must work computationally – at least in approximation – also in the brain. Bayesian networks in the form of graphical models allow the modularization of information and the factorization of interactions, which can strongly improve the efficiency of generative models. The resulting generative models essentially produce state estimations in the form of probability densities, which are very well-suited to integrate multiple sources of information, including top-down and bottom-up ones. A hierarchical neural visual processing architecture illustrates this point even further. Finally, some well-known visual illusions are shown and the perceptions are explained by means of generative, information integrating, perceptual processes, which in all cases combine top-down prior knowledge and expectations about objects and environments with the available, bottom-up visual information.
23

Butz, Martin V., and Esther F. Kutter. Retrospection and future perspectives. Oxford University Press, 2017. http://dx.doi.org/10.1093/acprof:oso/9780198739692.003.0014.

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As the concluding chapter, the story of the book’s content is revisited and summarized. Essentially, our embodied minds come into being due to an evolutionary predisposed cognitive developmental process, which builds progressively more abstract, conceptual, compositional predictive encodings based on actively gathered sensorimotor experiences. The chapter also acknowledges several under-represented, but important topics in cognitive science. Finally, the matter of consciousness is addressed, emphasizing that the mind emerges from a recurrent, self-maintaining, and self-regulating system, that is, our brain–body system. Combined with developing self-referential, social, event-oriented, conceptualizing predictive encodings, self-reflective cognition becomes possible. We conclude that despite pursuing a computational approach to embodied cognitive science, cognitive models in this direction are just at their beginning. Future cognitive modeling efforts promise to shed much further light on the exact details about how our minds come into being and how we may create useful, artificial, cognitive systems in the future.
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