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The brain has limited processing capacities. Attention selection processes are continuously shaping humans’ world perception. Understanding the mechanisms underlying such covert cognitive processes requires the combination of psychophysical and electrophysiological investigation methods. This combination allows researchers to describe how individual neurons and neuronal populations encode attentional function. Direct access to neuronal information through innovative electrophysiological approaches, additionally, allows the tracking of covert attention in real time. These converging approaches capture a comprehensive view of attentional function.

Compared to other animals or to artificial agents, humans are unique in the extent of their abilities to learn and adapt to changing environments. When focusing on skill learning and model-based approaches, learning can be conceived as a progression of increasing, then decreasing, dimensions of representing knowledge. First, initial learning demands exploration of the learning space and the identification of the relevant dimensions for the novel task at hand. Second, intermediate learning requires a refinement of these relevant dimensions of knowledge and behavior to continue improving performance while increasing efficiency. Such improvements utilize chunking or other forms of dimensionality reduction to diminish task complexity. Finally, late learning ensures automatization of behavior through habit formation and expertise development, thereby reducing the need to effortfully control behavior. While automatization greatly increases efficiency, there is also a trade-off with the ability to generalize, with late learning tending to be highly specific to the learned features and contexts. In each of these phases a variety of interacting factors are relevant: Declarative instructions, prior knowledge, attentional deployment, and cognitive fitness have unique roles to play. Neural contributions to processes involved also shift from earlier to later points in learning as effortfulness initially increases and then gives way to automaticity. Interestingly, video games excel at providing uniquely supportive environments to guide the learner through each of these learning stages. This fact makes video games a useful tool for both studying learning, due to their engaging nature and dynamic range of complexity, as well as engendering learning in domains such as education or cognitive training.

The perception of odors exerts powerful influences on moods, decisions, and actions. Indeed, odor perception is a major driving force underlying some of the most important human behaviors. How is it that the simple inhalation of airborne molecules can exert such strong effects on complex aspects of human functions? Certainly, just like in the case of vision and audition, the perception of odors is dictated by the ability to transduce environmental information into an electrical “code” for the brain to use. However, the use of that information, including whether or not the information is used at all, is governed strongly by many emotional and cognitive factors, including learning and experiences, as well as states of arousal and attention. Understanding the manners whereby these factors regulate both the perception of odors and how an individual responds to those percepts are paramount for appreciating the orchestration of behavior.

Crossmodal plasticity occurs when sensory regions of the brain adapt to process sensory inputs from different modalities. This is seen in cases of congenital and early deafness and blindness, where, in the absence of their typical inputs, auditory and visual cortices respond to other sensory information. Crossmodal plasticity in deaf and blind individuals impacts several cognitive processes, including working memory, attention, switching, numerical cognition, and language. Crossmodal plasticity in cognitive domains demonstrates that brain function and cognition are shaped by the interplay between structural connectivity, computational capacities, and early sensory experience.

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.