Biomedical subjects

Lee Schroeder

Publications and source records attributed to Lee Schroeder.

5 recordsLinked to original sources

PubMed2003

Fuzzy cluster analysis of high-field functional MRI data.

Functional magnetic resonance imaging (fMRI) based on blood-oxygen level dependent (BOLD) contrast today is an established brain research method and quickly gains acceptance for complementary clinical diagnosis. However, neither the basic mechanisms like coupling between neuronal activation and haemodynamic response are known exactly, nor can the various artifacts be predicted or controlled. Thus, modeling functional signal changes is non-trivial and exploratory data analysis (EDA) may be rather useful. In particular, identification and separation of artifacts as well as quantification of expected, i.e. stimulus correlated, and novel information on brain activity is important for both, new insights in neuroscience and future developments in functional MRI of the human brain. After an introduction on fuzzy clustering and very high-field fMRI we present several examples where fuzzy cluster analysis (FCA) of fMRI time series helps to identify and locally separate various artifacts. We also present and discuss applications and limitations of fuzzy cluster analysis in very high-field functional MRI: differentiate temporal patterns in MRI using (a) a test object with static and dynamic parts, (b) artifacts due to gross head motion artifacts. Using a synthetic fMRI data set we quantitatively examine the influences of relevant FCA parameters on clustering results in terms of receiver-operator characteristics (ROC) and compare them with a commonly used model-based correlation analysis (CA) approach. The application of FCA in analyzing in vivo fMRI data is shown for (a) a motor paradigm, (b) data from multi-echo imaging, and (c) a fMRI study using mental rotation of three-dimensional cubes. We found that differentiation of true "neural" from false "vascular" activation is possible based on echo time dependence and specific activation levels, as well as based on their signal time-course. Exploratory data analysis methods in general and fuzzy cluster analysis in particular may help to identify artifacts and add novel and unexpected information valuable for interpretation, classification and characterization of functional MRI data which can be used to design new data acquisition schemes, stimulus presentations, neuro(physio)logical paradigms, as well as to improve quantitative biophysical models.

Artifacts↗

PubMed2002

Brain activation during facial emotion processing.

Functional neuroimaging studies have helped identify neural systems involved in cognitive processing and more recently have indicated limbic activation to emotional stimuli. Some functional magnetic resonance imaging (fMRI) studies have reported increased amygdala response during exposure to emotional stimuli while others have not shown such activation. The present study was designed to test the hypothesis that activation of the amygdala is related to the relevance of the emotional valence of stimuli. Healthy young participants (7 men, 7 women) were studied in a high-field (4 tesla) scanner using blood oxygenation-level dependent (BOLD) signal changes in a blocked "box car" design. They viewed facial displays of happiness, sadness, anger, fear, and disgust as well as neutral faces obtained from professional actors and actresses of diverse ethnicity and age. Their task alternated between emotion discrimination (indicating whether the emotion was positive or negative) and age discrimination (indicating whether the poser was older or younger than 30). Blocks contained the same proportion of emotional and neutral faces. Limbic response was greater during the emotion than during the age discrimination conditions. The response was most pronounced in the amygdala, but was also present in the hippocampus and circumscribed voxels in other limbic regions. These results support the central role of the amygdala in emotion processing, and indicate its sensitivity to the task relevance of the emotional display.

Adult↗

PubMed2002

An fMRI study of facial emotion processing in patients with schizophrenia.

OBJECTIVE: Emotion processing deficits are notable in schizophrenia. The authors evaluated cerebral blood flow response in schizophrenia patients during facial emotion processing to test the hypothesis of diminished limbic activation related to emotional relevance of facial stimuli. METHOD: Fourteen patients with schizophrenia and 14 matched comparison subjects viewed facial displays of happiness, sadness, anger, fear, and disgust as well as neutral faces. Functional magnetic resonance imaging was used to measure blood-oxygen-level-dependent signal changes as the subjects alternated between tasks of discriminating emotional valence (positive versus negative) and age (over 30 versus under 30) of the faces with an interleaved crosshair reference condition. RESULTS: The groups did not differ in performance on either task. For both tasks, healthy participants showed activation in the fusiform gyrus, occipital lobe, and inferior frontal cortex relative to the resting baseline condition. The increase was greater in the amygdala and hippocampus during the emotional valence discrimination task than during the age discrimination task. In the patients with schizophrenia, minimal focal response was observed for all tasks relative to the resting baseline condition. Contrasting patients and comparison subjects on the emotional valence discrimination task revealed voxels in the left amygdala and bilateral hippocampus in which the comparison subjects had significantly greater activation. CONCLUSIONS: Failure to activate limbic regions during emotional valence discrimination may explain emotion processing deficits in patients with schizophrenia. While the lack of limbic recruitment did not significantly impair simple valence discrimination performance in this clinically stable group, it may impact performance of more demanding tasks.

Affect↗

PubMed2002

Working memory for complex figures: an fMRI comparison of letter and fractal n-back tasks.

n-back letter and fractal tasks were administered to 11 participants during functional magnetic resonance imaging to test process specificity theories of prefrontal cortex (PFC) function and assess task validity. Tasks were matched on accuracy, but fractal n-back responses were slower and more conservative. Maintenance (1-back minus 0-back) activated inferior parietal and dorsolateral PFC, with additional activation in right ventrolateral PFC during letter n-back and left lingual gyrus during fractal n-back. Maintenance plus manipulation (2-back minus 0-back) activated inferior parietal, Broca's area, insula, and dorsolateral and ventral PFC, with greater right dorsolateral PFC activation for letter n-back. Manipulation only (2-back minus 1-back) produced additional and equivalent dorsolateral PFC and anterior cingulate activation in both tasks. Results support fractal n-back validity and indicate substantial overlap in working memory functions of dorsal and ventral PFC.

Adult↗

PubMedDate not supplied

Age-related differences in brain activation during emotional face processing.

Advancing age is associated with significant declines on neurobehavioral tasks that demand substantial mental effort. Functional imaging studies of mental abilities indicate that older adults faced with cognitive challenges tend to activate more regions, particularly frontal, than their younger counterparts, and that this recruitment of additional regions may reflect an attempt to compensate for inefficiency in cortical networks. The neural basis of emotion processing in aging has received little attention, and the goal of the present study was to use functional magnetic resonance imaging (fMRI) to examine the influence of age on facial emotion processing and activation in cortical and limbic regions. Participants (eight old and eight young adults) viewed facial displays of happiness, sadness, anger, fear, disgust, and neutrality in alternating blocks of emotion and age discrimination. We predicted that in response to an emotion discrimination task, older adults would demonstrate increased use of frontal regions relative to younger adults, perhaps combined with diminished use of regions recruited by younger adults, such as temporo-limbic regions. During the emotion discrimination task, young participants activated, visual, frontal and limbic regions, whereas older participants activated parietal, temporal and frontal regions. A direct comparison between emotion and age discrimination revealed that while younger adults activated the amygdala and surrounding temporo-limbic regions, older adults activated left frontal regions. The results of this study suggest that older adults may rely on different cortical networks to perceive emotional facial expressions than do their younger counterparts.

Adult↗