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Physical Hazards of Space Exploration and the Biological Bases of Behavioral Health and Performance in Extreme Environments
Published in Lauren Blackwell Landon, Kelley J. Slack, Eduardo Salas, Psychology and Human Performance in Space Programs, 2020
Julia M. Schorn, Peter G. Roma
Although many brain regions are involved in memory, the hippocampus is by far the most important. Hippocampal connections with the amygdala enable emotion to affect encoding and subsequent recall of certain evens (Squire, 1992). Key neurochemicals underlying cognitive processing include acetylcholine, glutamate, epinephrine, opioid peptides, and GABA (McGaugh, 1992). Intrinsic hippocampal circuitry (such as between the dentate gyrus, CA3, CA1, and subiculum regions) and extrinsic circuitry (parahippocampal region and higher cortical areas) contribute to the complex formation of memories. The ventrolateral prefrontal cortex is heavily involved in working memory, whereas the basal ganglia and cerebellum support procedural memory (Awh et al., 1996; Pascual-Leone et al., 1993).
Big Data Era in Magnetic Resonance Imaging of the Human Brain
Published in Ervin Sejdić, Tiago H. Falk, Signal Processing and Machine Learning for Biomedical Big Data, 2018
Xiaoyu Ding, Elisabeth de Castro Caparelli, Thomas J. Ross
SZ, affecting about 24 million people globally, is a chronic and serious mental disorder that interferes with a person’s ability to think clearly, manage emotions, and make decisions. Neuroimaging studies in SZ patients have revealed extensive abnormalities, such as altered structural relationships among regional morphology in the thalamus, frontal, temporal, and parietal cortices [143]; altered structural integrity of white matter in frontal and temporal brain regions [144]; and differences in left superior temporal gyrus (STG)–dorsal lateral prefrontal cortex and STG–ventrolateral prefrontal cortex functional connectivity [145]. Compared to other psychiatric disorders, machine learning techniques have been most commonly applied to SZ due to data availability. Studies have shown that this disorder can be accurately predicted using functional and structural MRI data phenotypes (see Table 3.2 [146]).
Therapeutic Monitoring of Children with Attention Deficit Hyperactivity Disorder Using fNIRS Assessment
Published in Yu Chen, Babak Kateb, Neurophotonics and Brain Mapping, 2017
A go/no-go task was selected as the experimental task for the following reasons. First, response inhibition as measured by go/no-go tasks has emerged as one of the principal paradigms for studying ADHD (Aron and Poldrack 2005). Former fMRI studies successfully elucidated neural substrates for ADHD using motor response inhibition tasks, including go/no-go, stop signal, and Stroop tasks (Bush et al. 1999, Dillo et al. 2010, Durston et al. 2003, Rubia et al. 1999, Vaidya et al. 1998). Second, among these tasks, Stroop task performance matures latest at around 17–19 years of age (Comalli et al. 1962), followed by stop signal tasks at 13–17 years (Williams et al. 1999) and go/no-go tasks at approximately 12 years (Levin et al. 1991). Therefore, a go/no-go task is the primary choice for a study of school-age children. Third, fMRI studies have elucidated the neural substrate for go/no-go tasks, including the bilateral dorsolateral prefrontal cortex (DLPFC), ventrolateral prefrontal cortex (VLPFC), premotor cortex, inferior parietal lobe, lingual gyrus, caudate, and right anterior cingulate (Menon et al. 2001). Among these, the right VLPFC was found most responsible for response inhibition (Rubia et al. 2003), while another similar response inhibition task recruited the right DLPFC (Garavan et al. 1999). Fourth, VLPFC activation during a go/no-go task was replicated in an fNIRS study (Herrmann et al. 2005). An extensive review of functional neuroimaging in healthy adults indicates that widespread regions of the frontal cortex, especially the right inferior frontal gyrus (IFG), are associated with response inhibition (Aron and Poldrack 2005). Structural neuroimaging in ADHD has fairly consistently indicated gray matter density reductions in the striatum and right IFG (Durston et al. 2004). A former fMRI study on ADHD children with an MPH history reported that MPH increased the activation of the frontal cortices and striatum during go/no-go tasks (Vaidya et al. 1998). The specificity of the implicated brain regions in healthy subjects, as well as functional and structural changes to those regions in ADHD patients, suggests that response inhibition is a good neurofunctional biomarker candidate for ADHD (Aron and Poldrack 2005).
How to Provide Feedback? The Role of Robot’s Language and Feedback Framework
Published in International Journal of Human–Computer Interaction, 2023
Hanjing Huang, Pei-Luen Patrick Rau
Uncovering the neural basis of emotion is essential for understanding of the emotional mechanisms. Among emotion-related brain systems, the prefrontal cortex (PFC) is generally considered to be primarily involved in regulating the basic emotional processes occurring in subcortical and brainstem regions (Barbas, 2000; Dixon & Christoff, 2014; Ochsner & Gross, 2014; Sharpe & Schoenbaum, 2016). PFC makes a critical contribution to the flexible regulation of emotional responses and goal-directed behavior. Furthermore, the rostromedial prefrontal cortex (rmPFC) in the PFC is usually involved in studies of emotion (Lindquist et al., 2016) and value-based decision making (Bartra et al., 2013; Clithero & Rangel, 2014; Smith et al., 2010). Previous research has found that rmPFC activation is modulated by the receipt of valenced feedback from others about receivers’ personality (Izuma et al., 2008; Somerville et al., 2010). The ventrolateral prefrontal cortex (VLPFC) in the PFC has also been found to be related to attaching verbal labels to emotions (Lieberman, 2007). In addition, the orbitofrontal cortex (OFC) area in the PFC is known to participate in executive functions and attentional control of emotion (Kuusinen et al., 2018; Rolls et al., 2020).
Neurocognitive feedback: a prospective approach to sustain idea generation during design brainstorming
Published in International Journal of Design Creativity and Innovation, 2022
Mo Hu, Tripp Shealy, Julie Milovanovic, John Gero
The PFC functionally divides into sub-regions, including the medial prefrontal cortex (mPFC), dorsolateral prefrontal cortex (DLPFC), and ventrolateral prefrontal cortex (VLPFC), which contribute to different aspects of creative processing. The mPFC is associated with the retrieval of both short-term and long-term memories (Euston et al., 2012), cognitive empathy and perspective taking (Seitz et al., 2006). Increased activation in the mPFC is associated with an improved ability to simulate future imaginative events (Meyer et al., 2019). The DLPFC is highly active in creative tasks involving visuospatial divergent thinking, making new associations, convergent thinking, and evaluations (Funahashi, 2017). The VLPFC is critical for combining existing information into new ideas (Dietrich, 2004; Wu et al., 2015).
Survey and perspective on social emotions in robotics
Published in Advanced Robotics, 2022
Grecucci et al. summarized the brain regions related to emotional regulation as a mechanistic study of social emotional regulation [58] (Table 2). First, individual emotion regulation (IER) has been reported to be related to the dorsolateral prefrontal cortex (DLPFC), ventrolateral prefrontal cortex (VLPFC), anterior cingulate cortex (ACC), amygdala, striatum, and orbitofrontal cortex (OFC), among others. The DLPFC is generally believed to control attention and working memory. The ACC is involved in monitoring and controlling ongoing processes. The VLPFC appears to be responsible for choosing an appropriate response to a goal and suppressing inappropriate responses. The area of interest for reassessment is the amygdala, which is believed to be an important structure that supports the refinement of external and internal emotional and negative stimuli. In addition, the striatum and insula have little relationship with IER.