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PLoS ONE (2)
Journal of cognitive neuroscience (1)
Liu, Xun (3)
Fan, Jin (2)
Guise, Kevin G. (2)
Farley, Alison B. (1)
Fossella, John (1)
Gu, Xiaosi (1)
Joseph, Jane E. (1)
Smith, Charles D. (1)
Steinmetz, Nicholas A. (1)
Wang, Hongbin (1)
Wang, Kai (1)
Year of Publication
Mid-fusiform Activation during Object Discrimination Reflects the Process of Differentiating Structural Descriptions
Steinmetz, Nicholas A.
Farley, Alison B.
Smith, Charles D.
Joseph, Jane E.
Journal of cognitive neuroscience
The present study explored constraints on mid-fusiform activation during object discrimination. In three experiments, participants performed a matching task on simple line configurations, nameable objects, three dimensional (3-D) shapes, and colors. Significant bilateral mid-fusiform activation emerged when participants matched objects and 3-D shapes, as compared to when they matched two-dimensional (2-D) line configurations and colors, indicating that the mid-fusiform is engaged more strongly for processing structural descriptions (e.g., comparing 3-D volumetric shape) than perceptual descriptions (e.g., comparing 2-D or color information). In two of the experiments, the same mid-fusiform regions were also modulated by the degree of structural similarity between stimuli, implicating a role for the mid-fusiform in fine differentiation of similar visual object representations. Importantly, however, this process of fine differentiation occurred at the level of structural, but not perceptual, descriptions. Moreover, mid-fusiform activity was more robust when participants matched shape compared to color information using the identical stimuli, indicating that activity in the mid-fusiform gyrus is not driven by specific stimulus properties, but rather by the process of distinguishing stimuli based on shape information. Taken together, these findings further clarify the nature of object processing in the mid-fusiform gyrus. This region is engaged specifically in structural differentiation, a critical component process of object recognition and categorization.
Alexithymic Trait and Voluntary Control in Healthy Adults
Guise, Kevin G.
Alexithymia is a personality trait characterized by deficiency in understanding, processing, or describing emotions. Recent studies have revealed that alexithymia is associated with less activation of the anterior cingulate cortex, a brain region shown to play a role in cognitive and emotional processing. However, few studies have directly investigated the cognitive domain in relation to alexithymia to examine whether alexithymic trait is related to less efficient voluntary control.
Methodology/ Principal Findings
We examined the relationship between alexithymic trait and voluntary control in a group of healthy volunteers. We used the 20-item Toronto Alexithymia Scale (TAS-20) to measure alexithymic trait. Additionally, we examined state and trait voluntary control using the revised Attention Network Test (ANT-R) and the Adult Temperament Questionnaire (ATQ), respectively. Alexithymic trait was positively correlated with the overall reaction time of the ANT-R, and negatively correlated with the Effortful Control factor of the ATQ.
Our results suggest that alexithymic trait is associated with less efficient voluntary control.
Searching for the Majority: Algorithms of Voluntary Control
Guise, Kevin G.
Voluntary control of information processing is crucial to allocate resources and prioritize the processes that are most important under a given situation; the algorithms underlying such control, however, are often not clear. We investigated possible algorithms of control for the performance of the majority function, in which participants searched for and identified one of two alternative categories (left or right pointing arrows) as composing the majority in each stimulus set. We manipulated the amount (set size of 1, 3, and 5) and content (ratio of left and right pointing arrows within a set) of the inputs to test competing hypotheses regarding mental operations for information processing. Using a novel measure based on computational load, we found that reaction time was best predicted by a grouping search algorithm as compared to alternative algorithms (i.e., exhaustive or self-terminating search). The grouping search algorithm involves sampling and resampling of the inputs before a decision is reached. These findings highlight the importance of investigating the implications of voluntary control via algorithms of mental operations.
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