Let’s image we are driving home and, suddenly, road signs alert us that we are reaching a dangerous crossroads. This will trigger our attention, orienting it in a certain direction, enhancing the elaboration of forthcoming stimuli, and, eventually, resulting in anticipatory deceleration or faster reaction to avoid a potential car accident. This trivial example illustrates how the capacity to generate prediction by using either explicit or implicit environmental clues is fundamental for our survival. Predicting when, what or where events are most probable to occur allows all biological systems to build up inner models of external reality, resulting in the possibility of anticipating a forthcoming event. This, in turn, translates into a fine-grained adaptation of cognitive, emotional and motor resources and therefore to dynamically optimize behavior over time. Indeed, predicted stimuli require less energy to be elaborated, and this can result in a better (i.e., faster and more accurate) response implementation.
Flexible behavioral adaptation has been traditionally considered a top-down process requiring volition and attention to down-regulate behavior. However, a recent theoretical framework posits that this can be successfully driven by simple bottom-up, implicit learning processes, rather than necessarily requiring effortful ones. However, the neurocognitive mechanisms involved in the interplay between prediction and adaptation still need additional investigation. Particularly, how the proficiency of the implicit/explicit flexible adaptation of the behavior dynamically changes across ages needs to be clarified.
In addition, a dysfunction in flexibly adapting the behavior in a proactive way may have a cascade effect on multiple cognitive domains as memory, attention and executive control. This is particularly relevant in neuropsychological and neurological disorders impacting directly cognitive functioning, as well as in aging, which is often characterized by cognitive performance reduction. In this scenario, the understanding of how the prediction-adaptation relationship changes across typical and atypical development, as well as in healthy adults and clinical populations is a pivotal open question.
The general goal of the present research topic is to encourage researchers to contribute to the understanding of the mechanisms involved in prediction-based proactive adaptation of human behavior. Particular attention will be devoted to the core neuropsychological functions involved, including but not limited to attention, cognitive control, memory, language, perception, emotion, motor control, etc.
The topic can be investigated in healthy adults, typical and atypical development, as well as aging populations, taking a lifespan perspective. A part of the topic will be also dedicated to those works investigating possible dysfunctions in neuropsychological and neurological disorders. However, in this latter case, the clinical works should emphasize a neurocognitive approach. The methodology can include clinical, behavioral and neuroimaging measures (e.g., M/EEG, fMRI, fNIRS, etc.) as well as neurostimulation techniques (e.g., TMS, tDCS, etc.).
Let’s image we are driving home and, suddenly, road signs alert us that we are reaching a dangerous crossroads. This will trigger our attention, orienting it in a certain direction, enhancing the elaboration of forthcoming stimuli, and, eventually, resulting in anticipatory deceleration or faster reaction to avoid a potential car accident. This trivial example illustrates how the capacity to generate prediction by using either explicit or implicit environmental clues is fundamental for our survival. Predicting when, what or where events are most probable to occur allows all biological systems to build up inner models of external reality, resulting in the possibility of anticipating a forthcoming event. This, in turn, translates into a fine-grained adaptation of cognitive, emotional and motor resources and therefore to dynamically optimize behavior over time. Indeed, predicted stimuli require less energy to be elaborated, and this can result in a better (i.e., faster and more accurate) response implementation.
Flexible behavioral adaptation has been traditionally considered a top-down process requiring volition and attention to down-regulate behavior. However, a recent theoretical framework posits that this can be successfully driven by simple bottom-up, implicit learning processes, rather than necessarily requiring effortful ones. However, the neurocognitive mechanisms involved in the interplay between prediction and adaptation still need additional investigation. Particularly, how the proficiency of the implicit/explicit flexible adaptation of the behavior dynamically changes across ages needs to be clarified.
In addition, a dysfunction in flexibly adapting the behavior in a proactive way may have a cascade effect on multiple cognitive domains as memory, attention and executive control. This is particularly relevant in neuropsychological and neurological disorders impacting directly cognitive functioning, as well as in aging, which is often characterized by cognitive performance reduction. In this scenario, the understanding of how the prediction-adaptation relationship changes across typical and atypical development, as well as in healthy adults and clinical populations is a pivotal open question.
The general goal of the present research topic is to encourage researchers to contribute to the understanding of the mechanisms involved in prediction-based proactive adaptation of human behavior. Particular attention will be devoted to the core neuropsychological functions involved, including but not limited to attention, cognitive control, memory, language, perception, emotion, motor control, etc.
The topic can be investigated in healthy adults, typical and atypical development, as well as aging populations, taking a lifespan perspective. A part of the topic will be also dedicated to those works investigating possible dysfunctions in neuropsychological and neurological disorders. However, in this latter case, the clinical works should emphasize a neurocognitive approach. The methodology can include clinical, behavioral and neuroimaging measures (e.g., M/EEG, fMRI, fNIRS, etc.) as well as neurostimulation techniques (e.g., TMS, tDCS, etc.).
