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1

Iqbal, Azlan, Matej Guid, Simon Colton, Jana Krivec, Shazril Azman, and Boshra Haghighi. The Digital Synaptic Neural Substrate. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-28079-0.

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2

Call, Josep, Gordon M. Burghardt, Irene M. Pepperberg, Charles T. Snowdon, and Thomas Zentall, eds. APA handbook of comparative psychology: Basic concepts, methods, neural substrate, and behavior. Washington: American Psychological Association, 2017. http://dx.doi.org/10.1037/0000011-000.

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3

Schmajuk, Nestor A. Latent Inhibition and Its Neural Substrates. Boston, MA: Springer US, 2002. http://dx.doi.org/10.1007/978-1-4615-0841-0.

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4

Schmajuk, Nestor A. Latent inhibition and its neural substrates. Boston: Kluwer Academic Pub., 2002.

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5

Beeson, Pelagie, and Brenda Rapp. Dysgraphia: Cognitive Processes, Remediation, and Neural Substrates. London: Psychology Press, 2024. http://dx.doi.org/10.4324/9781003579458.

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6

Loeb, C., and G. F. Poggio. Neural Substrates of Memory, Affective Functions, and Conscious Experience. Berlin, Heidelberg: Springer Berlin Heidelberg, 2002. http://dx.doi.org/10.1007/978-3-642-59432-8.

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7

Elizabeth, Hillis Argye, ed. New techniques for identifying the neural substrates of language. [Hove, East Sussex: Psychology Press, 2002.

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8

S, Lund Jennifer, Werner Gerhard 1921-, and University of Pittsburgh. Center for Neuroscience., eds. Sensory processing in the mammalian brain: Neural substrates and experimental strategies. New York: Oxford University Press, 1989.

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9

Colvin, Leigh Elizabeth. The Psychological Factors and Neural Substrates Associated with Metacognition among Community-Dwelling and Neurologic Cohorts of Older Adults. [New York, N.Y.?]: [publisher not identified], 2019.

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10

Hendrik, Gispen Willem, and Routtenberg Aryeh, eds. Protein kinase C and its brain substrates: Role in neuronal growth and plasticity : proceedings of the Third International Meeting on Brain Phosphoproteins, held at Zeist (The Netherlands) 24-26 August, 1990. Amsterdam: Elsevier, 1991.

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11

Iqbal, Azlan, Matej Guid, Jana Krivec, Shazril Azman, and Simon Colton. Digital Synaptic Neural Substrate: A New Approach to Computational Creativity. Springer International Publishing AG, 2016.

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12

Iqbal, Azlan, Matej Guid, Jana Krivec, Shazril Azman, and Simon Colton. Digital Synaptic Neural Substrate: A New Approach to Computational Creativity. Springer London, Limited, 2016.

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13

Garvey, Marjorie A. TMS: neurodevelopment and perinatal insults. Edited by Charles M. Epstein, Eric M. Wassermann, and Ulf Ziemann. Oxford University Press, 2012. http://dx.doi.org/10.1093/oxfordhb/9780198568926.013.0022.

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Neural substrate for changes in neuromotor skills of typically developing children involves the complex and organized maturation of underlying brain structures. This article gives an overview of the changes that occur in motor function, as children get older and those aspects of central nervous development which may form the neural substrates of motor function development. It describes those TMS evoked parameters, related to the motor system, that have been studied in both typically developing children and in those who have suffered perinatal insults to the central nervous system. TMS has its limitations and is especially useful when used in combination with other neurophysiological modalities. The focus for future studies should be on correlating TMS evoked parameters with behavioural measures in typically developing children and explanation of the neural substrates of the motor abnormalities in children with perinatal insults and developmental disabilities.
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14

Dienel, Samuel J., and David A. Lewis. Cellular Mechanisms of Psychotic Disorders. Edited by Dennis S. Charney, Eric J. Nestler, Pamela Sklar, and Joseph D. Buxbaum. Oxford University Press, 2017. http://dx.doi.org/10.1093/med/9780190681425.003.0018.

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Cognitive dysfunction in schizophrenia, including disturbances in working memory, is a core feature of the illness and the best predictor of long-term functional outcome. Working memory relies on neural network oscillations in the prefrontal cortex. Gamma-aminobutyric acid (GABA) neurons in the prefrontal cortex, which are crucial for this oscillatory activity, exhibit a number of alterations in individuals diagnosed with schizophrenia. These GABA neuron disturbances may be secondary to upstream alterations in excitatory pyramidal cells in the prefrontal cortex. Together, these findings suggest both a neural substrate for working memory impairments in schizophrenia and therapeutic targets for improving functional outcomes in this patient population.
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15

APA Handbook of Comparative Psychology : Vol. 1 : Basic Concepts, Methods, Neural Substrate, and Behavior Vol. 2: Perception, Learning, and Cognition. American Psychological Association, 2017.

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16

Domhoff, G. William. The Neurocognitive Theory of Dreaming. The MIT Press, 2022. http://dx.doi.org/10.7551/mitpress/14679.001.0001.

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A comprehensive neurocognitive theory of dreaming based on the theories, methodologies, and findings of cognitive neuroscience and the psychological sciences. G. William Domhoff's neurocognitive theory of dreaming is the only theory of dreaming that makes full use of the new neuroimaging findings on all forms of spontaneous thought and shows how well they explain the results of rigorous quantitative studies of dream content. Domhoff identifies five separate issues—neural substrates, cognitive processes, the psychological meaning of dream content, evolutionarily adaptive functions, and historically invented cultural uses—and then explores how they are intertwined. He also discusses the degree to which there is symbolism in dreams, the development of dreaming in children, and the relative frequency of emotions in the dreams of children and adults. During dreaming, the neural substrates that support waking sensory input, task-oriented thinking, and movement are relatively deactivated. Domhoff presents the conditions that have to be fulfilled before dreaming can occur spontaneously. He describes the specific cognitive processes supported by the neural substrate of dreaming and then looks at dream reports of research participants. The “why” of dreaming, he says, may be the most counterintuitive outcome of empirical dream research. Though the question is usually framed in terms of adaptation, there is no positive evidence for an adaptive theory of dreaming. Research by anthropologists, historians, and comparative religion scholars, however, suggests that dreaming has psychological and cultural uses, with the most important of these found in religious ceremonies and healing practices. Finally, he offers suggestions for how future dream studies might take advantage of new technologies, including smart phones.
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17

Campagnola, Luke, and Paul Manis. Patch Clamp Recording in Brain Slices. Oxford University Press, 2015. http://dx.doi.org/10.1093/med/9780199939800.003.0001.

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Patch clamp recording in brain slices allows unparalleled access to neuronal membrane signals in a system that approximates the in-vivo neural substrate while affording greater control of experimental conditions. In this chapter we discuss the theory, methodology, and practical considerations of such experiments including the initial setup, techniques for preparing and handling viable brain slices, and patching and recording signals. A number of practical and technical issues faced by electrophysiologists are also considered, including maintaining slice viability, visualizing and identifying healthy cells, acquiring reliable patch seals, amplifier compensation features, hardware configuration, sources of electrical noise and table vibration, as well as basic data analysis issues and some troubleshooting tips.
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18

Raymont, Vanessa, and Robert D. Stevens. Cognitive Reserve. Oxford University Press, 2014. http://dx.doi.org/10.1093/med/9780199653461.003.0029.

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The cognitive reserve hypothesis suggests that the structure and function of an individual’s brain can modulate the clinical expression of brain damage and illness. This chapter describes passive and active models of reserve, their impact on neurological illness, and how these effects can be assessed. Passive models focus on the protective potential of anatomical features, such as brain size, neural density, and synaptic connectivity, while active models emphasize the connectivity and efficiency of neural networks and active compensation by alternative networks. It is likely that both models represent features of a common biological substrate and could help in the development of strategies to improve outcome following critical illness.
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19

Adolphs, Ralph, and Elina Birmingham. Neural Substrates of Social Perception. Oxford University Press, 2011. http://dx.doi.org/10.1093/oxfordhb/9780199559053.013.0029.

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20

Boraud, Thomas. How the Brain Makes Decisions. Oxford University Press, 2020. http://dx.doi.org/10.1093/oso/9780198824367.001.0001.

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The human decision-making process is tainted with irrationality. To address this issue, this book proposes a ‘bottom-up’ approach of the neural substrate of decision-making, starting from the fundamental question: What are the basic properties that a neural network of decision-making needs to possess? Combining data drawn from phylogeny and physiology, this book provides a general framework of the neurobiology of decision-making in vertebrates and explains how it evolved from the lamprey to the apes. It also addresses the consequences, examining how it impacts our capacity of reasoning and some aspects of the pathophysiology of high brain functions. To conclude, the text opens discussion to more philosophical concepts such as the question of free will.
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21

Schmajuk, Nestor. Latent Inhibition and Its Neural Substrates. Springer, 2002.

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22

Schmajuk, Nestor. Latent Inhibition and Its Neural Substrates. Springer London, Limited, 2012.

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23

Schmajuk, Nestor. Latent Inhibition and Its Neural Substrates. Springer, 2012.

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24

Latent inhibition and its neural substrates. Boston: Kluwer Academic Pub., 2002.

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25

Domhoff, G. William. Dreaming Is an Intensified Form of Mind-Wandering, Based in an Augmented Portion of the Default Network. Edited by Kalina Christoff and Kieran C. R. Fox. Oxford University Press, 2018. http://dx.doi.org/10.1093/oxfordhb/9780190464745.013.7.

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This chapter argues that dreaming is an intensified form of mind-wandering that makes use of embodied simulation. It further hypothesizes that the neural network that enables dreaming is very likely an augmented portion of the default network. This network is activated whenever there is (1) a mature and intact neural substrate that can support the cognitive process of dreaming; (2) an adequate level of cortical activation; (3) an occlusion of external stimuli; (4) a cognitively mature imagination system (a necessity indicated by the virtual lack of dreaming in preschoolers and its relative paucity until ages 8–9); and (5) the loss of conscious self-control, which may be neurologically mediated in the final step in a complex process by the decoupling of the dorsal attentional network from the anterior portions of the default network. If this testable theory proves to be correct, then dreaming may be the quintessential cognitive simulation.
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26

Domhoff, G. William. The Cognitive Neuroscience of Dreaming. Oxford University Press, 2017. http://dx.doi.org/10.1093/oso/9780190673420.003.0006.

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The fifth chapter presents the evidence for the novel idea that the neural substrate that enables dreaming is based in subsystems within the waking default network. The evidence for this hypothesis includes neuroimaging studies of representative samples of children and adults as well as studies of neurological patients who report they have experienced alterations in their dreaming, or even lost the ability to dream, due to their injury or illness. Based on these relatively new findings from many research settings, some as recent as 2015 and 2016, both the developmental trajectory of dreaming and the nature of dream content can be explained by the neurocognitive theory of dreams.
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27

Domhoff, G. William. A Promising Agenda. Oxford University Press, 2017. http://dx.doi.org/10.1093/oso/9780190673420.003.0010.

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The ninth and final chapter returns to the forward-looking orientation of the first five chapters by presenting an agenda for future dream research, which makes use of recent developments in both communications (such as smartphones) and neuroimaging. It suggests how new and better studies can be done of dream recall, dream content, and the development of dreaming in children. It presents a novel way in which the neural substrate that very likely supports dreaming could be studied in greater detail by detecting the brief episodes of dreaming that are now known to occur during extended periods of drifting waking thought (e.g., during mind-wandering and daydreaming).
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28

Rapp, Brenda. Dysgraphia: Cognitive Processes, Remediation, and Neural Substrates. Psychology Press, 2003.

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29

Nutt, David J., and Liam J. Nestor. The glutamate system and addiction. Oxford University Press, 2018. http://dx.doi.org/10.1093/med/9780198797746.003.0009.

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Glutamate is the primary excitatory neurotransmitter in the brain. Glutamate is involved in synaptic plasticity, particularly within dopamine systems of the brain that are involved in reward. Glutamate-dependent plasticity is involved in the development of substance addiction through its actions at NMDA receptors during long-term potentiation (LTP) related learning and memory processes. This plasticity within brain circuitry involved in learning and memory is sustained during substance abstinence and may provide a neural substrate for a vulnerability to addiction relapse. Medications that possess the efficacy to reduce glutamate tone in certain brain circuits may reduce craving, and ultimately, relapse in substance dependence. Further research is required, however, to show that the modulation of glutamate transmission in the brain confers clinical benefits in substance addiction.
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30

Calingasan, Noel Y. Neural substrates of metabolic controls of feeding behavior. 1992.

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31

Westheimer, Gerald. The Shifted-Chessboard Pattern as Paradigm of the Exegesis of Geometrical-Optical Illusions. Oxford University Press, 2017. http://dx.doi.org/10.1093/acprof:oso/9780199794607.003.0036.

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The shifted chessboard or café wall illusion yields to analysis at the two poles of the practice of vision science: bottom-up, pursuing its course from the visual stimulus into the front end of the visual apparatus, and top-down, figuring how the rules governing perception might lead to it. Following the first approach, examination of the effects of light spread in the eye and of nonlinearity and center-surround antagonism in the retina has made some inroads and provided partial explanations; with respect to the second, principles of perspective and of continuity and smoothness of contours can be evoked, and arguments about perception as Bayesian inference can be joined. Insights from these two directions are helping neurophysiologists in their struggle to identify a neural substrate of the phenomenon Münsterberg described in 1897.
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32

Geva, Sharon. Inner Speech and Mental Imagery. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780198796640.003.0005.

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Inner speech has been investigated using neuroscientific techniques since the beginning of the twentieth century. One of the most important finding is that inner and overt speech differ in many respects, not only in the absence/presence of articulatory movements. In addition, studies implicate the involvement of various brain regions in the production and processing of inner speech, including areas involved in phonology and semantics, as well as auditory and motor processing. By looking at parallels between inner speech and other domains of imagery, studies explore two major questions: Are there common types of representations that underlie all types of mental imagery? And, is there a neural substrate for imagery, above and beyond modality? While these questions cannot yet be fully answered, studies of the neuroscience of imagery are bringing us a step towards better understanding of inner speech.
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33

Loeb, C., and G. F. Poggio. Neural Substrates of Memory, Affective Functions, and Conscious Experience. Springer London, Limited, 2012.

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34

Weatherford, Sally Crinean. Neural substrates mediating glucagon-induced suppression of food intake. 1987.

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35

Geary, David C., Daniel B. Berch, and Kathleen Mann Koepke. Development of Mathematical Cognition: Neural Substrates and Genetic Influences. Elsevier Science & Technology Books, 2015.

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36

Geary, David C., Daniel B. Berch, and Kathleen Mann Koepke. Development of Mathematical Cognition: Neural Substrates and Genetic Influences. Elsevier Science & Technology Books, 2015.

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37

Neural Substrates of Memory, Affective Functions, and Conscious Experience. Springer-Verlag, 2002.

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38

Berkowitz, Aaron L. The Cognitive Neuroscience of Improvisation. Edited by George E. Lewis and Benjamin Piekut. Oxford University Press, 2014. http://dx.doi.org/10.1093/oxfordhb/9780195370935.013.004.

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Cognitive neuroscience research has begun to elucidate the neural substrates and cognitive processes that are involved in musical improvisation. In turn, the study of improvisation from the perspective of cognitive neuroscience has provided new insights about the brain and cognition. This chapter reviews brain imaging research studies of improvisation and explores the relevance of this work to musicians, musicologists, music educators, and cognitive neuroscientists with respect to the practice and pedagogy of improvisation, comparisons between music and language cognition, mirror neuron systems, and neural plasticity.
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39

Erdem, Uğur Murat, Nicholas Roy, John J. Leonard, and Michael E. Hasselmo. Spatial and episodic memory. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780199674923.003.0029.

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The neuroscience of spatial memory is one of the most promising areas for developing biomimetic solutions to complex engineering challenges. Grid cells are neurons recorded in the medial entorhinal cortex that fire when rats are in an array of locations in the environment falling on the vertices of tightly packed equilateral triangles. Grid cells suggest an exciting new approach for enhancing robot simultaneous localization and mapping (SLAM) in changing environments and could provide a common map for situational awareness between human and robotic teammates. Current models of grid cells are well suited to robotics, as they utilize input from self-motion and sensory flow similar to inertial sensors and visual odometry in robots. Computational models, supported by in vivo neural activity data, demonstrate how grid cell representations could provide a substrate for goal-directed behavior using hierarchical forward planning that finds novel shortcut trajectories in changing environments.
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40

Hillis, Argye. Aphasiology-New Techniques for Identifying the Neural Substrates of Language. Psychology Press, 2003.

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41

Jaeger, Thomas V. Dissociation of neural substrates underlying morphine's reinforcing and discriminative effects. 1995.

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42

Chae, Younbyoung, Vitaly Napadow, Florian Beissner, Yi-Wen Lin, and Richard E. Harris, eds. Neural Substrates of Acupuncture: from Peripheral to Central Nervous System Mechanisms. Frontiers Media SA, 2020. http://dx.doi.org/10.3389/978-2-88963-505-4.

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43

Lund, Jennifer S. Sensory Processing in the Mammalian Brain: Neural Substrates and Experimental Strategies. Oxford University Press, USA, 1988.

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44

Ladenheim, Ellen Elizabeth. Neural substrates involved in cholecystokinin- and bombesin- induced suppression of food intake. 1989.

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45

Chechlacz, Magdalena, and Glyn Humphreys, eds. The enigma of Bálint’s syndrome: complexity of neural substrates and cognitive deficits. Frontiers Media SA, 2015. http://dx.doi.org/10.3389/978-2-88919-599-2.

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46

Andres, Michael, and Mauro Pesenti. Finger-based representation of mental arithmetic. Edited by Roi Cohen Kadosh and Ann Dowker. Oxford University Press, 2014. http://dx.doi.org/10.1093/oxfordhb/9780199642342.013.028.

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Human beings are permanently required to process the world numerically and, consequently, to perform computations to adapt their behaviour and they have developed various calculation strategies, some of them based on specific manipulations of the fingers. In this chapter, we argue that the way we express physically numerical concepts by raising fingers while counting leads to embodied representations of numbers and calculation procedures in the adult brain. To illustrate this, we focus on number and finger interactions in the context of simple arithmetic operations. We show that the fixed order of fingers on the hand provides human beings with unique facilities to increment numerical changes or represent a cardinal value while solving arithmetic problems. In order to specify the influence of finger representation on mental arithmetic both at the cognitive and neural level, we review past and recent findings from behavioural, electrophysiological, and brain imaging studies. We start with anthropological and developmental data showing the role of fingers in the acquisition of arithmetic knowledge, then address the issue of whether number and finger interactions are also observed in adults solving arithmetic problems mentally. We suggest that arithmetic performance depends on the integrity of finger representations in children and adults. Finally, we overview the results of recent functional magnetic resonance imaging (fMRI) studies showing a common brain substrate for finger and number representations during and after the acquisition of arithmetic skills.
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47

Klimecki, Olga M., and Tania Singer. The Compassionate Brain. Edited by Emma M. Seppälä, Emiliana Simon-Thomas, Stephanie L. Brown, Monica C. Worline, C. Daryl Cameron, and James R. Doty. Oxford University Press, 2017. http://dx.doi.org/10.1093/oxfordhb/9780190464684.013.9.

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This chapter focuses on the neuroscience of compassion and related social emotions such as empathy, empathic concern, or empathic distress. First, we review neuroscientific literature on empathy and relate empathy to similar social emotions. We then turn to neuroscientific research on caregiving and social connection before describing cross-sectional studies on the neural signatures of compassion. To investigate whether training of compassion can change neural functions, the neural “fingerprints” of compassion expertise were studied in both expert and inexperienced meditators. The latter included the comparison between functional plasticity induced by empathy for suffering as opposed to compassion training. These studies show that compassion training changes neural functions, and that the neural substrates related to empathy for suffering differ experientially as well as neuronally. This is in line with the observation of distinct behavioral patterns related to feelings of empathic distress and compassion, described towards the end of the chapter.
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48

Gillett, Grant, and Rom Harré. Discourse and Diseases of the Psyche. Edited by K. W. M. Fulford, Martin Davies, Richard G. T. Gipps, George Graham, John Z. Sadler, Giovanni Stanghellini, and Tim Thornton. Oxford University Press, 2013. http://dx.doi.org/10.1093/oxfordhb/9780199579563.013.0022.

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The discursive approach to psychiatry, taking as it does an ethological approach to the human organism, directs us to rules and story lines that structure our ways of dealing with the challenges thrown up by particular situated positions in our discursive world. For human beings this means engaging with the sense they are making of the world and the words they use to try and communicate that (to themselves and others). Doing things with words is behavior that draws on certain skills attuned to prompts, cues, expectations, and so on, all of which can go seriously awry in any setting where certain features are unfamiliar or where one of the participants is "impaired" or out of step with prevailing norms and assumptions. Discursive competence and the reality of the human psyche as a mode of being-in-relation-with others crucially depends on intact neural function and brain pathways slowly and cumulatively developed throughout life and is vulnerable to disruption of that substrate. Hysteria (or conversion disorder) and dementia represent two very different situations in which the discursive mismatch between an individual and his or her context of being causes the voice (and soul) of a person to be "lost in translation" so that understanding what is happening and then care and restoration demand a great deal of us not just as biomedical scientists but also as human beings who are reaching out to those who suffer and try to endure (patients) so as to help hold them in being.
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49

Domhoff, G. William. The Emergence of Dreaming. Oxford University Press, 2017. http://dx.doi.org/10.1093/oso/9780190673420.001.0001.

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This book presents a new neurocognitive theory of dreams that documents the similarities of dreaming to waking thought, demonstrates that personal psychological meaning can be found in a majority of dream reports, has a strong developmental dimension based on excellent longitudinal and cross-sectional studies carried out in sleep labs with children ages 3–15, locates the neural substrate for dreaming in the same brain network active during mind-wandering and daydreaming, and marshals the evidence that shows it is very unlikely that dreaming has any adaptive function. These claims are based on five different sets of descriptive empirical findings that were developed between the late 1950s and the first sixteen years of the twenty-first century. All of these findings were unanticipated by scientific dream researchers and then resisted to varying degrees by dream theorists for a variety of reasons. The first five chapters spell out the theory and the evidence for it without any discussion or criticism of past theories. The next two chapters present detailed criticisms of two major alternative theories. The penultimate chapter presents evidence that it is very unlikely that dreaming has any adaptive function in the evolutionary sense of the term, although humans have invented uses for dreams in religious and healing rituals. In that regard, dreaming has an emergent function in culture that was invented in the course of history due to human cognitive capacities. The final chapter presents a general agenda for future research using new methodologies to test all of the neurocognitive hypotheses.
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50

Frost, Randy O., and Jessica L. Rasmussen. Phenomenology and Characteristics of Compulsive Hoarding. Edited by Gail Steketee. Oxford University Press, 2012. http://dx.doi.org/10.1093/oxfordhb/9780195376210.013.0020.

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This chapter discusses current understanding of the phenomenology and characteristics of compulsive hoarding. The disorder is conceptualized within a cognitive-behavioral framework that includes excessive acquisition, difficulties with discarding, and clutter/disorganization. Information-processing deficits, emotional attachments, beliefs about possessions, and perfectionism are examined as underlying etiological factors. Characteristics of the disorder such as prevalence, onset and course, demographics and comorbidity are discussed. It is suggested that the distinctive features of compulsive hoarding, including unique neural and genetic substrates, warrant diagnostic classification as a separate disorder. Methodological problems with existing research are identified.
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