Protocol to examine the neural basis of symbolic and non-symbolic quantity processing in human brain with fMRI.

Number perception is among the basic cognitive abilities necessary to understand our environment. Here, we present a protocol to examine the neural underpinnings of numerosity comparison regarding symbolic and non-symbolic stimuli using functional magnetic resonance imaging (fMRI). This protocol gives instructions for screening participants, followed by steps to perform an event-related fMRI experiment and data analysis with SPM12.

Children With Dyscalculia Show Hippocampal Hyperactivity During Symbolic Number Perception.

Dyscalculia is a learning disability affecting the acquisition of arithmetical skills in children with normal intelligence and age-appropriate education. Two hypotheses attempt to explain the main cause of dyscalculia. The first hypothesis suggests that a problem with the core mechanisms of perceiving (non-symbolic) quantities is the cause of dyscalculia (core deficit hypothesis), while the alternative hypothesis suggests that dyscalculics have problems only with the processing of numerical symbols (access deficit hypothesis).

Amygdala-prefrontal cortex connectivity increased during face discrimination but not time perception.

Time sensitivity is affected by emotional stimuli such as fearful faces. The effect of threatening stimuli on time perception depends on numerous factors, including task type and duration range. We applied a two-interval forced-choice task using face stimuli to healthy volunteers to evaluate time perception and emotion interaction using functional magnetic resonance imaging.

Integrated assessment of visual perception abnormalities in psychotic disorders and relationship with clinical characteristics.

Background: The visual system is recognized as an important site of pathology and dysfunction in schizophrenia. In this study, we evaluated different visual perceptual functions in patients with psychotic disorders using a potentially clinically applicable task battery and assessed their relationship with symptom severity in patients, and with schizotypal features in healthy participants.

Methods: Five different areas of visual functioning were evaluated in patients with schizophrenia and schizoaffective disorder (n = 28) and healthy control subjects (n = 31) using a battery that included visuospatial working memory (VSWM), velocity discrimination (VD), contour integration, visual context processing, and backward masking tasks.

Neural Mechanisms Underlying Time Perception and Reward Anticipation.

Findings suggest that the physiological mechanisms involved in the reward anticipation and time perception partially overlap. But the systematic investigation of a potential interaction between time and reward systems using neuroimaging is lacking. Eighteen healthy volunteers (all right-handed) participated in an event-related functional magnetic resonance imaging (fMRI) experiment that employs a visual paradigm that consists monetary reward to assess whether the functional neural representations of time perception and reward prospection are shared or distinct.

Neural Networks for Time Perception and Working Memory.

Time is an important concept which determines most human behaviors, however questions remain about how time is perceived and which areas of the brain are responsible for time perception. The aim of this study was to evaluate the relationship between time perception and working memory in healthy adults. Functional magnetic resonance imaging (fMRI) was used during the application of a visual paradigm.

Automatic segmentation of human facial tissue by MRI-CT fusion: a feasibility study.

The aim of this study was to develop automatic image segmentation methods to segment human facial tissue which contains very thin anatomic structures. The segmentation output can be used to construct a more realistic human face model for a variety of purposes like surgery planning, patient specific prosthesis design and facial expression simulation. Segmentation methods developed were based on Bayesian and Level Set frameworks, which were applied on three image types: magnetic resonance imaging (MRI), computerized tomography (CT) and fusion, in which case information from both modalities were utilized maximally for every tissue type.