Role of AI and AI-Derived Techniques in Brain and Behavior Computing

2021 ◽  
pp. 35-55
Author(s):  
Om Prakash Yadav ◽  
Yojana Yadav ◽  
Shashwati Ray
2020 ◽  
Author(s):  
Sara Ruth Westbrook ◽  
Lauren Carrica ◽  
Asia Banks ◽  
Joshua Michael Gulley

Adolescent use of amphetamine and its closely related, methylated version methamphetamine, is alarmingly high in those who use drugs for nonmedical purposes. This raises serious concerns about the potential for this drug use to have a long-lasting, detrimental impact on the normal development of the brain and behavior that is ongoing during adolescence. In this review, we explore recent findings from both human and laboratory animal studies that investigate the consequences of amphetamine and methamphetamine exposure during this stage of life. We highlight studies that assess sex differences in adolescence, as well as those that are designed specifically to address the potential unique effects of adolescent exposure by including groups at other life stages (typically young adulthood). We consider epidemiological studies on age and sex as vulnerability factors for developing problems with the use of amphetamines, as well as human and animal laboratory studies that tap into age differences in use, its short-term effects on behavior, and the long-lasting consequences of this exposure on cognition. We also focus on studies of drug effects in the prefrontal cortex, which is known to be critically important for cognition and is among the later maturing brain regions. Finally, we discuss important issues that should be addressed in future studies so that the field can further our understanding of the mechanisms underlying adolescent use of amphetamines and its outcomes on the developing brain and behavior.


2020 ◽  
Author(s):  
Francisco J. Parada ◽  
Alejandra Rossi

Recent technological advancements encompassed under the Mobile Brain/Body Imaging (MoBI) framework, have produced exciting new experimental results linking mind, brain, and behavior. The main goal of the MoBI approach is to model brain and body dynamics during every-day, natural, real-life situations. However, even though considerable advances have been made in both hardware and software, technical and analytical conditions are not yet optimal. The MoBI approach is based on attaching synchronized, small, and lightweight neurobehavioral sensors to and around participants during behaviorally-measured structured, semi-structured, and unstructured settings. These sensors have yet to become fully unobtrusive or transparent. Even though a considerable technical and analytical gap still exists, acquisition of brain/body dynamics during real-world situations as well as in virtual, modified, and/or extended laboratory settings has been -in many cases- successful. Nevertheless, even if the technical/analytical gap is breached, novel hypotheses, measures, and experimental paradigms are needed in order to tackle MoBI’s ultimate goal: to model and understand cognition, behavior, and experience as it emerges and unfolds unto and from the world. Such a goal is not completely novel or unique to the MoBI framework; it is at the core of a long-standing scientific and philosophical challenge. The present work starts by briefly reviewing the historical origins of complexity in order to identify three “waves and ripples of complexity” derived from naturalist accounts to the historical brain/body problem. We furthermore argue for a current 4th wave. Finally, we offer the reader what we consider to be the main objective for the MoBI+4E framework in its quest for understanding the functional role of brain/body/world couplings in the emergence of cognition.


2014 ◽  
Vol 16 (3) ◽  
pp. 307-320 ◽  

Obesity is now epidemic worldwide. Beyond associated diseases such as diabetes, obesity is linked to neuropsychiatric disorders such as depression. Alarmingly maternal obesity and high-fat diet consumption during gestation/lactation may "program" offspring longterm for increased obesity themselves, along with increased vulnerability to mood disorders. We review the evidence that programming of brain and behavior by perinatal diet is propagated by inflammatory mechanisms, as obesity and high-fat diets are independently associated with exaggerated systemic levels of inflammatory mediators. Due to the recognized dual role of these immune molecules (eg, interleukin [IL]-6, 11-1β) in placental function and brain development, any disruption of their delicate balance with growth factors or neurotransmitters (eg, serotonin) by inflammation early in life can permanently alter the trajectory of fetal brain development. Finally, epigenetic regulation of inflammatory pathways is a likely candidate for persistent changes in metabolic and brain function as a consequence of the perinatal environment.


2020 ◽  
Author(s):  
Milena Rmus ◽  
Samuel McDougle ◽  
Anne Collins

Reinforcement learning (RL) models have advanced our understanding of how animals learn and make decisions, and how the brain supports some aspects of learning. However, the neural computations that are explained by RL algorithms fall short of explaining many sophisticated aspects of human decision making, including the generalization of learned information, one-shot learning, and the synthesis of task information in complex environments. Instead, these aspects of instrumental behavior are assumed to be supported by the brain’s executive functions (EF). We review recent findings that highlight the importance of EF in learning. Specifically, we advance the theory that EF sets the stage for canonical RL computations in the brain, providing inputs that broaden their flexibility and applicability. Our theory has important implications for how to interpret RL computations in the brain and behavior.


2015 ◽  
Vol 27 (2) ◽  
pp. 587-613 ◽  
Author(s):  
Luke W. Hyde

AbstractThe emerging field of neurogenetics seeks to model the complex pathways from gene to brain to behavior. This field has focused on imaging genetics techniques that examine how variability in common genetic polymorphisms predict differences in brain structure and function. These studies are informed by other complimentary techniques (e.g., animal models and multimodal imaging) and have recently begun to incorporate the environment through examination of Imaging Gene × Environment interactions. Though neurogenetics has the potential to inform our understanding of the development of psychopathology, there has been little integration between principles of neurogenetics and developmental psychopathology. The paper describes a neurogenetics and Imaging Gene × Environment approach and how these approaches have been usefully applied to the study of psychopathology. Six tenets of developmental psychopathology (the structure of phenotypes, the importance of exploring mechanisms, the conditional nature of risk, the complexity of multilevel pathways, the role of development, and the importance of who is studied) are identified, and how these principles can further neurogenetics applications to understanding the development of psychopathology is discussed. A major issue of this piece is how neurogenetics and current imaging and molecular genetics approaches can be incorporated into developmental psychopathology perspectives with a goal of providing models for better understanding pathways from among genes, environments, the brain, and behavior.


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