Deborah Green | U.S. Department of Veterans Affairs (original) (raw)

Papers by Deborah Green

Brain Research, 2015

Reductions of cerebrospinal fluid (CSF) amyloid-beta (Aβ42) and elevated phosphorylated-tau (p-Ta... more Reductions of cerebrospinal fluid (CSF) amyloid-beta (Aβ42) and elevated phosphorylated-tau (p-Tau) reflect in vivo Alzheimer׳s disease (AD) pathology and show utility in predicting conversion from mild cognitive impairment (MCI) to dementia. We investigated the P50 event-related potential component as a noninvasive biomarker of AD pathology in non-demented elderly. 36 MCI patients were stratified into amyloid positive (MCI-AD, n=17) and negative (MCI-Other, n=19) groups using CSF levels of Aβ42. All amyloid positive patients were also p-Tau positive. P50s were elicited with an auditory oddball paradigm. MCI-AD patients yielded larger P50s than MCI-Other. The best amyloid-status predictor model showed 94.7% sensitivity, 94.1% specificity and 94.4% total accuracy. P50 predicted amyloid status in MCI patients, thereby showing a relationship with AD pathology versus MCI from another etiology. The P50 may have clinical utility for inexpensive pre-screening and assessment of Alzheimer׳s pathology.

2006 IEEE International Conference on Acoustics Speed and Signal Processing Proceedings, 2006

With the rapid increase in the population of elderly individuals affected by Alzheimer's disease,... more With the rapid increase in the population of elderly individuals affected by Alzheimer's disease, the need for an accurate, inexpensive and non-intrusive diagnostic biomarker that can be made available to community healthcare providers presents itself as a major public health concern. The feasibility of EEG as such a biomarker has gained a renewed attention as several recent studies, including our previous efforts, reported promising results. In this paper we present our preliminary results on using wavelet coefficients of event related potentials along with an ensemble of classifiers combined with majority vote and decision templates.

2009 4th International IEEE/EMBS Conference on Neural Engineering, 2009

Conference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual Conference, 2005

We describe an ensemble of classifiers based data fusion approach to combine information from two... more We describe an ensemble of classifiers based data fusion approach to combine information from two sources, believed to contain complimentary information, for early diagnosis of Alzheimer's disease. Specifically, we use the event related potentials recorded from the Pz and Cz electrodes of the EEG, which are further analyzed using multiresolution wavelet analysis. The proposed data fusion approach includes generating multiple classifiers trained with strategically selected subsets of the training data from each source, which are then combined through a weighted majority voting. Several factors set this study apart from similar prior efforts: we use a larger cohort, specifically target early diagnosis of the disease, use an ensemble based approach rather then a single classifier, and most importantly, we combine information from multiple sources, rather then using a single modality. We present promising results obtained from the first 35 (of 80) patients whose data are analyzed th...

Conference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual Conference, 2005

With the number of the elderly population affected by Alzheimer's disease (AD) rising, the ne... more With the number of the elderly population affected by Alzheimer's disease (AD) rising, the need to find an accurate, inexpensive and non-intrusive procedure that can be made available to community healthcare providers for early diagnosis of Alzheimer's disease is becoming more and more urgent as a major health concern. Several recent studies have looked at analyzing electroencephalogram signals through the use of wavelets and neural networks. In this study, multiresolution wavelet analysis, coupled with the ensemble of classifiers based boosting algorithm is used on the P300 component of the event related potentials (ERP) to determine the feasibility of the approach as a diagnostic tool for early diagnosis of AD. The technique and its promising initial results are presented.

Conference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual Conference, 2006

The diagnosis of Alzheimer's disease (AD) at an early stage is a major concern due to growing... more The diagnosis of Alzheimer's disease (AD) at an early stage is a major concern due to growing number of elderly population affected by the disease, as well as the lack of a standard diagnosis procedure available to community clinics. Recent studies have used wavelets and other signal processing methods to analyze EEG signals in an attempt to find a non-invasive biomarker for AD. These studies had varying degrees of success, in part due to small cohort size. In this study, multiresolution wavelet analysis is performed on event related potentials of the EEGs of a relatively larger cohort of 44 patients. Particular emphasis was on diagnosis at the earliest stage and feasibility of implementation in a community health clinic setting. Extracted features were then used to train an ensemble of classifiers based stacked generalization approach. We describe the approach, and present our promising preliminary results.

Conference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual Conference, 2009

As the average life expectancy increases, particularly in developing countries, prevalence of neu... more As the average life expectancy increases, particularly in developing countries, prevalence of neurodegenerative diseases has also increased. This trend is especially alarming for Alzheimer's disease (AD); as there is no cure to stop or reverse the effects of AD. However, recent pharmacological advances can slow the progression of AD, but only if AD is diagnosed at early stages. We have previously introduced an ensemble of classifiers based approach for combining event related potentials obtained from different electrode locations as an effective approach for early diagnosis of AD. We further expand this approach and analyze its robustness and stability in two ways: comparing the diagnostic accuracy on hand selected and cleaned data vs. standard automated preprocessing, but more importantly, comparing the diagnostic accuracy on two different cohorts, whose data are collected under different settings: a research university lab and a community clinic.

2007 International Joint Conference on Neural Networks, 2007

As a natural consequence of steady increase of average population age in developed countries, Alz... more As a natural consequence of steady increase of average population age in developed countries, Alzheimer's disease is becoming an increasingly important public health concern. The financial and emotional toll of the disease is exacerbated with lack of standard diagnostic procedures available at the community clinics and hospitals, where most patients are evaluated. In our recent preliminary results, we have reported that the event related potentials (ERPs) of the electroencephalogram can be used to train an ensemble-based classifier for automated diagnosis of Alzheimer's disease. In this study, we present an updated alternative approach by combining complementary information provided by ERPs obtained from several parietal region electrodes. The results indicate that ERPs obtained from parietal region of the cortex carry substantial complementary diagnostic information. Specifically, the diagnostic ability of such an approach is substantially better, compared to the performance obtained by using data from any of the individual electrodes alone. Furthermore, the diagnostic performance of the proposed approach compares very favorably to that obtained at community clinics and hospitals.

The Clinical Neuropsychologist, 2007

Neuropsychologia, 2008

People can solve problems in more than one way. Two general strategies involve (A) methodical, co... more People can solve problems in more than one way. Two general strategies involve (A) methodical, conscious, search of problem-state transformations, and (B) sudden insight, with abrupt emergence of the solution into consciousness. This study elucidated the influence of initial resting brain-state on subjects' subsequent strategy choices. High-density electroencephalograms (EEGs) were recorded from subjects at rest who were subsequently directed to solve a series of anagrams. Subjects were divided into two groups based on the proportion of anagram solutions derived with self-reported insight versus search. Reaction-time and accuracy results were consistent with different cognitive problem-solving strategies used for solving anagrams with versus without insight. Spectral analyses yielded group differences in resting-state EEG supporting hypotheses concerning insight-related attentional diffusion and right-lateralized hemispheric asymmetry. These results reveal a relationship between resting-state brain activity and problem-solving strategy, and, more generally, a dependence of event-related neural computations on the preceding resting-state.

Journal of Abnormal Psychology, 2009

Restraint theory has been used to model the process that produces binge eating. However, there is... more Restraint theory has been used to model the process that produces binge eating. However, there is no satisfactory explanation for the tendency of restrained eaters (REs) to engage in counterregulatory eating, an ostensible analogue of binge eating. Using functional magnetic resonance imaging (fMRI), the authors investigated brain activation of normal weight REs (N = 9) and unrestrained eaters (UREs; N = 10) when fasted and fed and viewing pictures of highly and moderately palatable foods and neutral objects. When fasted and viewing highly palatable foods, UREs showed widespread bilateral activation in areas associated with hunger and motivation, whereas REs showed activation only in the cerebellum, an area previously implicated in low-level processing of appetitive stimuli. When fed and viewing high palatability foods, UREs showed activation in areas related to satiation and memory, whereas REs showed activation in areas implicated in desire, expectation of reward, and goal-defined behavior. These findings parallel those from behavioral research. The authors propose that the counterintuitive findings from preload studies and the present study are due to the fact that REs are less hungry than UREs when fasted and find palatable food more appealing than UREs when fed.

Information Fusion, 2008

As the number of the elderly population affected by Alzheimer's disease (AD) rises rapidly, the n... more As the number of the elderly population affected by Alzheimer's disease (AD) rises rapidly, the need to find an accurate, inexpensive and non-intrusive diagnostic procedure that can be made available to community healthcare providers is becoming an increasingly urgent public health concern. Several recent studies have looked at analyzing electroencephalogram (EEG) signals through the use of wavelets and neural networks. While showing great promise, the final outcomes of these studies have been largely inconclusive. This is mostly due to inherent difficulty of the problem, but also -perhaps -due to inefficient use of the available information, as many of these studies have used a single EEG channel for the analysis. In this contribution, we describe an ensemble of classifiers based data fusion approach to combine information from two or more sources, believed to contain complementary information, for early diagnosis of Alzheimer's disease. Our emphasis is on sequentially generating an ensemble of classifiers that explicitly seek the most discriminating information from each data source. Specifically, we use the event related potentials recorded from the Pz, Cz, and Fz electrodes of the EEG, decomposed into different frequency bands using multiresolution wavelet analysis. The proposed data fusion approach includes generating multiple classifiers trained with strategically selected subsets of the training data from each source, which are then combined through a modified weighted majority voting procedure. The implementation details and the promising outcomes of this implementation are presented.

Cortex, 2008

Hemispheric asymmetry a b s t r a c t Transliminality reflects individual differences in the thre... more Hemispheric asymmetry a b s t r a c t Transliminality reflects individual differences in the threshold at which unconscious processes or external stimuli enter into consciousness. Individuals high in transliminality possess characteristics such as magical ideation, belief in the paranormal, and creative personality traits, and also report the occurrence of manic/mystic experiences. The goal of the present research was to determine if resting brain activity differs for individuals high versus low in transliminality. We compared baseline EEG recordings (eyes-closed) between individuals high versus low in transliminality, assessed using The Revised Transliminality Scale of Lange et al. (2000). Identifying reliable differences at rest between high-and lowtransliminality individuals would support a predisposition for transliminality-related traits. Individuals high in transliminality exhibited lower alpha, beta, and gamma power than individuals low in transliminality over left posterior association cortex and lower high alpha, low beta, and gamma power over the right superior temporal region. In contrast, when compared to individuals low in transliminality, individuals high in transliminality exhibited greater gamma power over the frontal-midline region. These results are consistent with prior research reporting reductions in left temporal/parietal activity, as well as the desynchronization of right temporal activity in schizotypy and related schizophrenia spectrum disorders. Further, differences between high-and low-transliminality groups extend existing theories linking altered hemispheric asymmetries in brain activity to a predisposition toward schizophrenia, paranormal beliefs, and unusual experiences. (J.I. Fleck). a v a i l a b l e a t w w w . s c i e n c e d i r e c t . c o m j o u r n a l h o m e p a g e : w w w . e l s e v i e r . c o m / l o c a t e / c o r t e x 0010-9452/$ -see front matter ª

Computers in Biology and Medicine, 2007

Early diagnosis of Alzheimer's disease (AD) is becoming an increasingly important healthcare conc... more Early diagnosis of Alzheimer's disease (AD) is becoming an increasingly important healthcare concern. Prior approaches analyzing eventrelated potentials (ERPs) had varying degrees of success, primarily due to smaller study cohorts, and the inherent difficulty of the problem. A new effort using multiresolution analysis of ERPs is described. Distinctions of this study include analyzing a larger cohort, comparing different wavelets and different frequency bands, using ensemble-based decisions and, most importantly, aiming the earliest possible diagnosis of the disease. Surprising yet promising outcomes indicate that ERPs in response to novel sounds of oddball paradigm may be more reliable as a biomarker than the more commonly used responses to target sounds. ᭧

Brain Research, 2009

Semantic richness refers to the amount of semantic information associated with a concept.

Appetite, 2009

Dietary restraint is heavily influenced by affect, which has been independently related to asymme... more Dietary restraint is heavily influenced by affect, which has been independently related to asymmetrical activation in the prefrontal cortex (prefrontal asymmetry) in electroencephalograph (EEG) studies. In normal weight individuals, dietary restraint has been related to prefrontal asymmetry; however, this relationship was not mediated by affect. This study was designed to test the hypotheses that, in an overweight and obese sample, dietary restraint as well as binge eating, disinhibition, hunger, and appetitive responsivity would be related to prefrontal asymmetry independent of affect at the time of assessment. Resting EEG recordings and self-report measures of overeating and affect were collected in 28 overweight and obese adults. Linear regression analyses were used to predict prefrontal asymmetry from appetitive measures while controlling for affect. Cognitive restraint and binge eating were not associated with prefrontal asymmetry. However, disinhibition, hunger, and appetitive responsivity predicted left-, greater than right-, sided prefrontal cortex activation independent of affect. Findings in this study add to a growing literature implicating the prefrontal cortex in the cognitive control of dietary intake. Further research to specify the precise role of prefrontal asymmetry in the motivation toward, and cessation of, feeding in obese individuals is encouraged. ß

Alzheimer's & Dementia, 2006

Brain Research, 2015

Reductions of cerebrospinal fluid (CSF) amyloid-beta (Aβ42) and elevated phosphorylated-tau (p-Ta... more Reductions of cerebrospinal fluid (CSF) amyloid-beta (Aβ42) and elevated phosphorylated-tau (p-Tau) reflect in vivo Alzheimer׳s disease (AD) pathology and show utility in predicting conversion from mild cognitive impairment (MCI) to dementia. We investigated the P50 event-related potential component as a noninvasive biomarker of AD pathology in non-demented elderly. 36 MCI patients were stratified into amyloid positive (MCI-AD, n=17) and negative (MCI-Other, n=19) groups using CSF levels of Aβ42. All amyloid positive patients were also p-Tau positive. P50s were elicited with an auditory oddball paradigm. MCI-AD patients yielded larger P50s than MCI-Other. The best amyloid-status predictor model showed 94.7% sensitivity, 94.1% specificity and 94.4% total accuracy. P50 predicted amyloid status in MCI patients, thereby showing a relationship with AD pathology versus MCI from another etiology. The P50 may have clinical utility for inexpensive pre-screening and assessment of Alzheimer׳s pathology.

2006 IEEE International Conference on Acoustics Speed and Signal Processing Proceedings, 2006

With the rapid increase in the population of elderly individuals affected by Alzheimer's disease,... more With the rapid increase in the population of elderly individuals affected by Alzheimer's disease, the need for an accurate, inexpensive and non-intrusive diagnostic biomarker that can be made available to community healthcare providers presents itself as a major public health concern. The feasibility of EEG as such a biomarker has gained a renewed attention as several recent studies, including our previous efforts, reported promising results. In this paper we present our preliminary results on using wavelet coefficients of event related potentials along with an ensemble of classifiers combined with majority vote and decision templates.

2009 4th International IEEE/EMBS Conference on Neural Engineering, 2009

Conference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual Conference, 2005

We describe an ensemble of classifiers based data fusion approach to combine information from two... more We describe an ensemble of classifiers based data fusion approach to combine information from two sources, believed to contain complimentary information, for early diagnosis of Alzheimer's disease. Specifically, we use the event related potentials recorded from the Pz and Cz electrodes of the EEG, which are further analyzed using multiresolution wavelet analysis. The proposed data fusion approach includes generating multiple classifiers trained with strategically selected subsets of the training data from each source, which are then combined through a weighted majority voting. Several factors set this study apart from similar prior efforts: we use a larger cohort, specifically target early diagnosis of the disease, use an ensemble based approach rather then a single classifier, and most importantly, we combine information from multiple sources, rather then using a single modality. We present promising results obtained from the first 35 (of 80) patients whose data are analyzed th...

Conference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual Conference, 2005

With the number of the elderly population affected by Alzheimer's disease (AD) rising, the ne... more With the number of the elderly population affected by Alzheimer's disease (AD) rising, the need to find an accurate, inexpensive and non-intrusive procedure that can be made available to community healthcare providers for early diagnosis of Alzheimer's disease is becoming more and more urgent as a major health concern. Several recent studies have looked at analyzing electroencephalogram signals through the use of wavelets and neural networks. In this study, multiresolution wavelet analysis, coupled with the ensemble of classifiers based boosting algorithm is used on the P300 component of the event related potentials (ERP) to determine the feasibility of the approach as a diagnostic tool for early diagnosis of AD. The technique and its promising initial results are presented.

Conference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual Conference, 2006

The diagnosis of Alzheimer's disease (AD) at an early stage is a major concern due to growing... more The diagnosis of Alzheimer's disease (AD) at an early stage is a major concern due to growing number of elderly population affected by the disease, as well as the lack of a standard diagnosis procedure available to community clinics. Recent studies have used wavelets and other signal processing methods to analyze EEG signals in an attempt to find a non-invasive biomarker for AD. These studies had varying degrees of success, in part due to small cohort size. In this study, multiresolution wavelet analysis is performed on event related potentials of the EEGs of a relatively larger cohort of 44 patients. Particular emphasis was on diagnosis at the earliest stage and feasibility of implementation in a community health clinic setting. Extracted features were then used to train an ensemble of classifiers based stacked generalization approach. We describe the approach, and present our promising preliminary results.

Conference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual Conference, 2009

As the average life expectancy increases, particularly in developing countries, prevalence of neu... more As the average life expectancy increases, particularly in developing countries, prevalence of neurodegenerative diseases has also increased. This trend is especially alarming for Alzheimer's disease (AD); as there is no cure to stop or reverse the effects of AD. However, recent pharmacological advances can slow the progression of AD, but only if AD is diagnosed at early stages. We have previously introduced an ensemble of classifiers based approach for combining event related potentials obtained from different electrode locations as an effective approach for early diagnosis of AD. We further expand this approach and analyze its robustness and stability in two ways: comparing the diagnostic accuracy on hand selected and cleaned data vs. standard automated preprocessing, but more importantly, comparing the diagnostic accuracy on two different cohorts, whose data are collected under different settings: a research university lab and a community clinic.

2007 International Joint Conference on Neural Networks, 2007

As a natural consequence of steady increase of average population age in developed countries, Alz... more As a natural consequence of steady increase of average population age in developed countries, Alzheimer's disease is becoming an increasingly important public health concern. The financial and emotional toll of the disease is exacerbated with lack of standard diagnostic procedures available at the community clinics and hospitals, where most patients are evaluated. In our recent preliminary results, we have reported that the event related potentials (ERPs) of the electroencephalogram can be used to train an ensemble-based classifier for automated diagnosis of Alzheimer's disease. In this study, we present an updated alternative approach by combining complementary information provided by ERPs obtained from several parietal region electrodes. The results indicate that ERPs obtained from parietal region of the cortex carry substantial complementary diagnostic information. Specifically, the diagnostic ability of such an approach is substantially better, compared to the performance obtained by using data from any of the individual electrodes alone. Furthermore, the diagnostic performance of the proposed approach compares very favorably to that obtained at community clinics and hospitals.

The Clinical Neuropsychologist, 2007

Neuropsychologia, 2008

People can solve problems in more than one way. Two general strategies involve (A) methodical, co... more People can solve problems in more than one way. Two general strategies involve (A) methodical, conscious, search of problem-state transformations, and (B) sudden insight, with abrupt emergence of the solution into consciousness. This study elucidated the influence of initial resting brain-state on subjects' subsequent strategy choices. High-density electroencephalograms (EEGs) were recorded from subjects at rest who were subsequently directed to solve a series of anagrams. Subjects were divided into two groups based on the proportion of anagram solutions derived with self-reported insight versus search. Reaction-time and accuracy results were consistent with different cognitive problem-solving strategies used for solving anagrams with versus without insight. Spectral analyses yielded group differences in resting-state EEG supporting hypotheses concerning insight-related attentional diffusion and right-lateralized hemispheric asymmetry. These results reveal a relationship between resting-state brain activity and problem-solving strategy, and, more generally, a dependence of event-related neural computations on the preceding resting-state.

Journal of Abnormal Psychology, 2009

Restraint theory has been used to model the process that produces binge eating. However, there is... more Restraint theory has been used to model the process that produces binge eating. However, there is no satisfactory explanation for the tendency of restrained eaters (REs) to engage in counterregulatory eating, an ostensible analogue of binge eating. Using functional magnetic resonance imaging (fMRI), the authors investigated brain activation of normal weight REs (N = 9) and unrestrained eaters (UREs; N = 10) when fasted and fed and viewing pictures of highly and moderately palatable foods and neutral objects. When fasted and viewing highly palatable foods, UREs showed widespread bilateral activation in areas associated with hunger and motivation, whereas REs showed activation only in the cerebellum, an area previously implicated in low-level processing of appetitive stimuli. When fed and viewing high palatability foods, UREs showed activation in areas related to satiation and memory, whereas REs showed activation in areas implicated in desire, expectation of reward, and goal-defined behavior. These findings parallel those from behavioral research. The authors propose that the counterintuitive findings from preload studies and the present study are due to the fact that REs are less hungry than UREs when fasted and find palatable food more appealing than UREs when fed.

Information Fusion, 2008

As the number of the elderly population affected by Alzheimer's disease (AD) rises rapidly, the n... more As the number of the elderly population affected by Alzheimer's disease (AD) rises rapidly, the need to find an accurate, inexpensive and non-intrusive diagnostic procedure that can be made available to community healthcare providers is becoming an increasingly urgent public health concern. Several recent studies have looked at analyzing electroencephalogram (EEG) signals through the use of wavelets and neural networks. While showing great promise, the final outcomes of these studies have been largely inconclusive. This is mostly due to inherent difficulty of the problem, but also -perhaps -due to inefficient use of the available information, as many of these studies have used a single EEG channel for the analysis. In this contribution, we describe an ensemble of classifiers based data fusion approach to combine information from two or more sources, believed to contain complementary information, for early diagnosis of Alzheimer's disease. Our emphasis is on sequentially generating an ensemble of classifiers that explicitly seek the most discriminating information from each data source. Specifically, we use the event related potentials recorded from the Pz, Cz, and Fz electrodes of the EEG, decomposed into different frequency bands using multiresolution wavelet analysis. The proposed data fusion approach includes generating multiple classifiers trained with strategically selected subsets of the training data from each source, which are then combined through a modified weighted majority voting procedure. The implementation details and the promising outcomes of this implementation are presented.

Cortex, 2008

Hemispheric asymmetry a b s t r a c t Transliminality reflects individual differences in the thre... more Hemispheric asymmetry a b s t r a c t Transliminality reflects individual differences in the threshold at which unconscious processes or external stimuli enter into consciousness. Individuals high in transliminality possess characteristics such as magical ideation, belief in the paranormal, and creative personality traits, and also report the occurrence of manic/mystic experiences. The goal of the present research was to determine if resting brain activity differs for individuals high versus low in transliminality. We compared baseline EEG recordings (eyes-closed) between individuals high versus low in transliminality, assessed using The Revised Transliminality Scale of Lange et al. (2000). Identifying reliable differences at rest between high-and lowtransliminality individuals would support a predisposition for transliminality-related traits. Individuals high in transliminality exhibited lower alpha, beta, and gamma power than individuals low in transliminality over left posterior association cortex and lower high alpha, low beta, and gamma power over the right superior temporal region. In contrast, when compared to individuals low in transliminality, individuals high in transliminality exhibited greater gamma power over the frontal-midline region. These results are consistent with prior research reporting reductions in left temporal/parietal activity, as well as the desynchronization of right temporal activity in schizotypy and related schizophrenia spectrum disorders. Further, differences between high-and low-transliminality groups extend existing theories linking altered hemispheric asymmetries in brain activity to a predisposition toward schizophrenia, paranormal beliefs, and unusual experiences. (J.I. Fleck). a v a i l a b l e a t w w w . s c i e n c e d i r e c t . c o m j o u r n a l h o m e p a g e : w w w . e l s e v i e r . c o m / l o c a t e / c o r t e x 0010-9452/$ -see front matter ª

Computers in Biology and Medicine, 2007

Early diagnosis of Alzheimer's disease (AD) is becoming an increasingly important healthcare conc... more Early diagnosis of Alzheimer's disease (AD) is becoming an increasingly important healthcare concern. Prior approaches analyzing eventrelated potentials (ERPs) had varying degrees of success, primarily due to smaller study cohorts, and the inherent difficulty of the problem. A new effort using multiresolution analysis of ERPs is described. Distinctions of this study include analyzing a larger cohort, comparing different wavelets and different frequency bands, using ensemble-based decisions and, most importantly, aiming the earliest possible diagnosis of the disease. Surprising yet promising outcomes indicate that ERPs in response to novel sounds of oddball paradigm may be more reliable as a biomarker than the more commonly used responses to target sounds. ᭧

Brain Research, 2009

Semantic richness refers to the amount of semantic information associated with a concept.

Appetite, 2009

Dietary restraint is heavily influenced by affect, which has been independently related to asymme... more Dietary restraint is heavily influenced by affect, which has been independently related to asymmetrical activation in the prefrontal cortex (prefrontal asymmetry) in electroencephalograph (EEG) studies. In normal weight individuals, dietary restraint has been related to prefrontal asymmetry; however, this relationship was not mediated by affect. This study was designed to test the hypotheses that, in an overweight and obese sample, dietary restraint as well as binge eating, disinhibition, hunger, and appetitive responsivity would be related to prefrontal asymmetry independent of affect at the time of assessment. Resting EEG recordings and self-report measures of overeating and affect were collected in 28 overweight and obese adults. Linear regression analyses were used to predict prefrontal asymmetry from appetitive measures while controlling for affect. Cognitive restraint and binge eating were not associated with prefrontal asymmetry. However, disinhibition, hunger, and appetitive responsivity predicted left-, greater than right-, sided prefrontal cortex activation independent of affect. Findings in this study add to a growing literature implicating the prefrontal cortex in the cognitive control of dietary intake. Further research to specify the precise role of prefrontal asymmetry in the motivation toward, and cessation of, feeding in obese individuals is encouraged. ß

Alzheimer's & Dementia, 2006