scholarly journals Neuronal networks in the developing brain are adversely modulated by early psychosocial neglect

2017 ◽  
Vol 118 (4) ◽  
pp. 2275-2288 ◽  
Author(s):  
Catherine Stamoulis ◽  
Ross E. Vanderwert ◽  
Charles H. Zeanah ◽  
Nathan A. Fox ◽  
Charles A. Nelson
Keyword(s):  
Early Intervention ◽  
Cognitive Processing ◽  
Brain Networks ◽  
Neural Circuitry ◽  
Developing Brain ◽  
Cognitive Domains ◽  
Institutionalized Children ◽  
Neural Information ◽  
Neural Information Processing ◽  
Early Intervention Project

The brain’s neural circuitry plays a ubiquitous role across domains in cognitive processing and undergoes extensive reorganization during the course of development in part as a result of experience. In this study we investigated the effects of profound early psychosocial neglect associated with institutional rearing on the development of task-independent brain networks, estimated from longitudinally acquired electroencephalographic (EEG) data from <30 to 96 mo, in three cohorts of children from the Bucharest Early Intervention Project (BEIP), including abandoned children reared in institutions who were randomly assigned either to a foster care intervention or to remain in care as usual and never-institutionalized children. Two aberrantly connected brain networks were identified in children that had been reared in institutions: 1) a hyperconnected parieto-occipital network, which included cortical hubs and connections that may partially overlap with default-mode network, and 2) a hypoconnected network between left temporal and distributed bilateral regions, both of which were aberrantly connected across neural oscillations. This study provides the first evidence of the adverse effects of early psychosocial neglect on the wiring of the developing brain. Given these networks' potentially significant role in various cognitive processes, including memory, learning, social communication, and language, these findings suggest that institutionalization in early life may profoundly impact the neural correlates underlying multiple cognitive domains, in ways that may not be fully reversible in the short term. NEW & NOTEWORTHY This paper provides first evidence that early psychosocial neglect associated with institutional rearing profoundly affects the development of the brain’s neural circuitry. Using longitudinally acquired electrophysiological data from the Bucharest Early Intervention Project (BEIP), the paper identifies multiple task-independent networks that are abnormally connected (hyper- or hypoconnected) in children reared in institutions compared with never-institutionalized children. These networks involve spatially distributed brain areas and their abnormal connections may adversely impact neural information processing across cognitive domains.

Neural Information Processing

1967 ◽  
Vol 12 (11) ◽  
pp. 558-559
Author(s):  
STEPHAN L. CHOROVER
Keyword(s):  
Information Processing ◽  
Neural Information ◽  
Neural Information Processing

scholarly journals Cortical response to naturalistic stimuli is largely predictable with deep neural networks

2021 ◽  
Vol 7 (22) ◽  
pp. eabe7547
Author(s):  
Meenakshi Khosla ◽  
Gia H. Ngo ◽  
Keith Jamison ◽  
Amy Kuceyeski ◽  
Mert R. Sabuncu
Keyword(s):  
Brain Function ◽  
Deep Neural Networks ◽  
Neural Responses ◽  
Dynamic Interactions ◽  
Hierarchical Processing ◽  
Human Connectome Project ◽  
Neural Information ◽  
Neural Information Processing ◽  
Visual Interactions ◽  
High Level

Naturalistic stimuli, such as movies, activate a substantial portion of the human brain, invoking a response shared across individuals. Encoding models that predict neural responses to arbitrary stimuli can be very useful for studying brain function. However, existing models focus on limited aspects of naturalistic stimuli, ignoring the dynamic interactions of modalities in this inherently context-rich paradigm. Using movie-watching data from the Human Connectome Project, we build group-level models of neural activity that incorporate several inductive biases about neural information processing, including hierarchical processing, temporal assimilation, and auditory-visual interactions. We demonstrate how incorporating these biases leads to remarkable prediction performance across large areas of the cortex, beyond the sensory-specific cortices into multisensory sites and frontal cortex. Furthermore, we illustrate that encoding models learn high-level concepts that generalize to task-bound paradigms. Together, our findings underscore the potential of encoding models as powerful tools for studying brain function in ecologically valid conditions.

scholarly journals Consciousness, decision making, and volition: freedom beyond chance and necessity

2021 ◽  
Author(s):  
Hans Liljenström
Keyword(s):  
Decision Making ◽  
Free Will ◽  
Brain Activity ◽  
Brain Structures ◽  
Complex Process ◽  
Neural Information ◽  
Neural Information Processing ◽  
Stochastic Population Model ◽  
The Brain

AbstractWhat is the role of consciousness in volition and decision-making? Are our actions fully determined by brain activity preceding our decisions to act, or can consciousness instead affect the brain activity leading to action? This has been much debated in philosophy, but also in science since the famous experiments by Libet in the 1980s, where the current most common interpretation is that conscious free will is an illusion. It seems that the brain knows, up to several seconds in advance what “you” decide to do. These studies have, however, been criticized, and alternative interpretations of the experiments can be given, some of which are discussed in this paper. In an attempt to elucidate the processes involved in decision-making (DM), as an essential part of volition, we have developed a computational model of relevant brain structures and their neurodynamics. While DM is a complex process, we have particularly focused on the amygdala and orbitofrontal cortex (OFC) for its emotional, and the lateral prefrontal cortex (LPFC) for its cognitive aspects. In this paper, we present a stochastic population model representing the neural information processing of DM. Simulation results seem to confirm the notion that if decisions have to be made fast, emotional processes and aspects dominate, while rational processes are more time consuming and may result in a delayed decision. Finally, some limitations of current science and computational modeling will be discussed, hinting at a future development of science, where consciousness and free will may add to chance and necessity as explanation for what happens in the world.

scholarly journals Developing brain networks of attention

2016 ◽  
Vol 28 (6) ◽  
pp. 720-724 ◽  
Author(s):  
Michael I. Posner ◽  
Mary K. Rothbart ◽  
Pascale Voelker
Keyword(s):  
Brain Networks ◽  
Developing Brain
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