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Sabine Kastner and Timothy J. Buschman

Natural scenes are cluttered and contain many objects that cannot all be processed simultaneously. Due to this limited processing capacity, neural mechanisms are needed to selectively enhance the information that is most relevant to one’s current behavior and to filter unwanted information. We refer to these mechanisms as “selective attention.” Attention has been studied extensively at the behavioral level in a variety of paradigms, most notably, Treisman’s visual search and Posner’s paradigm. These paradigms have also provided the basis for studies directed at understanding the neural mechanisms underlying attentional selection, both in the form of neuroimaging studies in humans and intracranial electrophysiology in non-human primates. The selection of behaviorally relevant information is mediated by a large-scale network that includes regions in all major lobes as well as subcortical structures. Attending to a visual stimulus modulates processing across the visual processing hierarchy with stronger effects in higher-order areas. Current research is aimed at characterizing the functions of the different network nodes as well as the dynamics of their functional connectivity.

Article

The title “Scientific Approaches to Mysticism” reveals half the task and belies the other half—namely, which of the sciences and whose mysticism are to be considered. Is it Capra’s tao of physics, Bohm’s holomovement of undivided wholeness, or Saver/Rabin’s limbic correlates of mystical ecstasy? Is it Freud’s psychoanalytic oneness of nursing at the breast, or Goodall’s evolutionary biology of mystical wonder? Numerous mystics have presented us with a cornucopia of mystical experiences, and many sciences have been employed to analyze mysticism. Any effort to create a singular scientific approach to an “imagined singular mysticism” is doomed to vagueness. Specifics matter, and they matter in the scientific approaches to mysticism. A scientific study of mysticism must first clarify what mysticism means—namely, a conscious experience in which one feels that the normal subject-object boundaries manifest in waking consciousness are altered, presenting a state of unity, union, or interrelationship. This definition of mysticism is broad enough to encompass nature mysticism, theistic I–Thou mysticism, and various forms of non-dualistic mysticisms ranging from experiences of the oneness of Being to the awareness of the emptiness of becoming. Each of these broad categories of mysticism must be refined by examining the particular tradition in which it manifests. As such, the scientific study of mysticism cannot assume, for example, that all Christian mystics, proclaiming the ultimacy of a personal communion with the Trinitarian god, are uttering the same thing, nor that non-dualistic mystics from different traditions, such as Christianity and Hinduism, are saying different things. The scientific study of mysticism must immediately confront the threat of reductionism, in which “mystical experience” is reduced to some elemental explanation such as, “it is only one’s brain.” This threat of scientific reductionism has long been elicited by the knowledge, for example, that the intake of drugs is correlated with mystical experience; more recently, this threat of reductionism has been intensified by the knowledge that we have machines that measure the neural patterns associated with individuals having mystical experiences, and we have machines that can allegedly induce mystical experiences. Stepping beyond the psychological, cognitive, and neuropsychological approaches to mysticism, the connections between mystical experience and physics have also been drawn. Relativity and quantum theories have become the hermeneutical tools to analyze and interpret the declarations of all sorts of mystical experiences. These studies of mysticism tend to present parallel explanations of the world. Evolutionary theory and biology also offer different angles of approach to the study of mysticism proposing explanations, for example, which relate mystical experience to the evolutionary chain of being or to techniques for transcending present limitations.

Article

Jessica R. Andrews-Hanna, Matthew D. Grilli, and Muireann Irish

The brain’s default network (DN) has received considerable interest in the context of so-called “normal” and pathological aging. Findings have generally been couched in support of a pessimistic view of brain aging, marked by substantial loss of structural brain integrity accompanied by a host of impairments in brain and cognitive function. A critical look at the literature, however, reveals that the standard loss of integrity, loss of function (LILF) view in normal aging may not necessarily hold with respect to the DN and the internally guided functions it supports. Many internally guided processes subserved by the DN are preserved or enhanced in cognitively healthy older adults. Moreover, differences in motivational, contextual, and physiological factors between young and older adults likely influence the extant neuroimaging and cognitive findings. Accordingly, normal aging can be viewed as a series of possibly adaptive cognitive and DN-related alterations that bolster cognitive function and promote socioemotional well-being and stability in a stage of life noted for change. On the other hand, the available evidence reveals strong support for the LILF view of the DN in neurodegenerative disorders, whereby syndromes such as Alzheimer’s disease (AD) and semantic dementia (SD), characterized by progressive atrophy to distinct DN subsystems, display distinct aberrations in autobiographical and semantic cognition. Taken together, these findings call for more naturalistic, age-appropriate, and longitudinal paradigms when investigating neurocognitive changes in aging and to adequately assess and control for differences in non-neural factors that may obscure “true” effects of normal and pathological aging. A shift in the framework with which age-related alterations in internally guided cognition are interpreted may shed important light on the neurocognitive mechanisms differentiating healthy and pathological aging, leading to a more complete picture of the aging brain in all its complexity.

Article

Sequences permeate daily life. They can be defined as a discrete series of items or states that occur in a specific order with a beginning and end. The brain supports the perception and execution of sequences. Perceptual sequences involve tracking regularities in incoming stimuli, such as the series of sounds that make up a word in language. Executed sequences range from the series of muscle activations used by a frog to catch a fly to a chess master mapping her next moves. How the brain controls sequences must therefore scale to multiple levels of control. Investigating how the brain functions to accomplish this task spans from the study of individual cells in the brain to human cognition. Understanding the neural systems that underlie sequential control is necessary to approach the mechanistic underpinnings of complex conditions such as addiction, which may be rooted in difficult-to-extinguish sequential behaviors. Current research focuses on studies in both animal and human models and spans the levels of complexity of sequential control and the brain systems that support it.

Article

Cognitive neuroimaging studies often report that older adults display more activation of neural networks relative to younger adults, referred to as overactivation. Greater or more widespread activity frequently involves bilateral recruitment of both cerebral hemispheres, especially the frontal cortex. In many reports, overactivation has been associated with superior cognitive performance, suggesting that this activity may reflect compensatory processes that offset age-related decline and maintain behavior. Several theories have been proposed to account for age differences in brain activation, including the Hemispheric Asymmetry Reduction in Older Adults (HAROLD) model, the Posterior-Anterior Shift in Aging (PASA) theory, the Compensation-Related Utilization of Neural Circuits Hypothesis (CRUNCH), and the Scaffolding Theory of Aging and Cognition (STAC and STAC-r). Each model has a different explanatory scope with regard to compensatory processes, and each has been highly influential in the field. HAROLD contrasts the general pattern of bilateral prefrontal activation in older adults with that of more unilateral activation in younger adults. PASA describes both anterior (e.g., frontal) overactivation and posterior (e.g., occipital) underactivation in older adults relative to younger adults. CRUNCH emphasizes that the level or extent of brain activity can change in response to the level of task demand at any age. Finally, STAC and STAC-r take the broadest perspective to incorporate individual differences in brain structure, the capacity to implement functional scaffolding, and life-course neural enrichment and depletion factors to predict cognition and cognitive change across the lifespan. Extant empirical work has documented that compensatory overactivation can be observed in regions beyond the prefrontal cortex, that variations in task difficulty influence the degree of brain activation, and that younger adults can show compensatory overactivation under high mental demands. Additional research utilizing experimental designs (e.g., transcranial magnetic stimulation), longitudinal assessments, greater regional precision, both verbal and nonverbal material, and measures of individual difference factors will continue to refine our understanding of age-related activation differences and adjudicate among these various accounts of neurocognitive aging.

Article

Neurolinguistic approaches to morphology include the main theories of morphological representation and processing in the human mind, such as full-listing, full-parsing, and hybrid dual-route models, and how the experimental evidence that has been acquired to support these theories uses different neurolinguistic paradigms (visual and auditory priming, violation, long-lag priming, picture-word interference, etc.) and methods (electroencephalography [EEG]/event-related brain potential [ERP], functional magnetic resonance imaging [fMRI], neuropsychology, and so forth).