Relatively little is known about how the human brain identifies movement of objects while the obs... more Relatively little is known about how the human brain identifies movement of objects while the observer is also moving in the environment. This is, ecologically, one of the most fundamental motion processing problems, critical for survival. To study this problem, we used a task which involved nine textured spheres moving in depth, eight simulating the observer's forward motion while the ninth, the target, moved independently with a different speed towards or away from the observer. Capitalizing on the high temporal resolution of magnetoencephalography (MEG) we trained a Support Vector Classifier (SVC) using the sensor-level data to identify correct and incorrect responses. Using the same MEG data, we addressed the dynamics of cortical processes involved in the detection of the independently moving object and investigated whether we could obtain confirmatory evidence for the brain activity patterns used by the classifier. Our findings indicate that response correctness could be reliably predicted by the SVC, with the highest accuracy during the blank period after motion and preceding the response. The spatial distribution of the areas critical for the correct prediction was similar but not exclusive to areas underlying the evoked activity. Importantly, SVC identified frontal areas otherwise not detected with evoked activity that seem to be important for the successful performance in the task. Dynamic connectivity further supported the involvement of frontal and occipital-temporal areas during the task periods. This is the first study to dynamically map cortical areas using a fully data-driven approach in order to investigate the neural mechanisms involved in the detection of moving objects during observer's self-motion.
The everyday environment brings to our sensory systems competing inputs from different modalities... more The everyday environment brings to our sensory systems competing inputs from different modalities. The ability to filter these multisensory inputs in order to identify and efficiently utilize useful spatial cues is necessary to detect and process the relevant information. In the present study, we investigate how feature-based attention affects the detection of motion across sensory modalities. We were interested to determine how subjects use intramodal, cross-modal auditory, and combined audiovisual motion cues to attend to specific visual motion signals. The results showed that in most cases, both the visual and the auditory cues enhance feature-based orienting to a transparent visual motion pattern presented among distractor motion patterns. Whereas previous studies have shown cross-modal effects of spatial attention, our results demonstrate a spread of cross-modal feature-based attention cues, which have been matched for the detection threshold of the visual target. These effects...
Magnetoencephalography (MEG) captures the magnetic fields generated by neuronal current sources w... more Magnetoencephalography (MEG) captures the magnetic fields generated by neuronal current sources with sensors outside the head. In MEG analysis these current sources are estimated from the measured data to identify the locations and time courses of neural activity. Since there is no unique solution to this so-called inverse problem, multiple source estimation techniques have been developed. The nulling beamformer (NB), a modified form of the linearly constrained minimum variance (LCMV) beamformer, is specifically used in the process of inferring interregional interactions and is designed to eliminate shared signal contributions, or cross-talk, between regions of interest (ROIs) that would otherwise interfere with the connectivity analyses. The nulling beamformer applies the truncated singular value decomposition (TSVD) to remove small signal contributions from a ROI to the sensor signals. However, ROIs with strong crosstalk will have high separating power in the weaker components, wh...
The functional significance of resting state networks and their abnormal manifestations in psychi... more The functional significance of resting state networks and their abnormal manifestations in psychiatric disorders are firmly established, as is the importance of the cortical rhythms in mediating these networks. Resting state networks are known to undergo substantial reorganization from childhood to adulthood, but whether distinct cortical rhythms, which are generated by separable neural mechanisms and are often manifested abnormally in psychiatric conditions, mediate maturation differentially, remains unknown. Using magnetoencephalography (MEG) to map frequency band specific maturation of resting state networks from age 7 to 29 in 162 participants (31 independent), we found significant changes with age in networks mediated by the beta (13-30 Hz) and gamma (31-80 Hz) bands. More specifically, gamma band mediated networks followed an expected asymptotic trajectory, but beta band mediated networks followed a linear trajectory. Network integration increased with age in gamma band mediat...
Amyloid positron emission tomography (PET) imaging is a valuable tool for research and diagnosis ... more Amyloid positron emission tomography (PET) imaging is a valuable tool for research and diagnosis in Alzheimer's disease (AD). Partial volume effects caused by the limited spatial resolution of PET scanners degrades the quantitative accuracy of PET image. In this study, we have applied a method to evaluate the impact of a joint-entropy based partial volume correction (PVC) technique on brain networks learned from a clinical dataset of AV-45 PET image and compare network properties of both uncorrected and corrected image-based brain networks. We also analyzed the region-wise SUVRs of both uncorrected and corrected images. We further performed classification tests on different groups using the same set of algorithms with same parameter settings. PVC has sometimes been avoided due to increased noise sensitivity in image registration and segmentation, however, our results indicate that appropriate PVC may enhance the brain network structure analysis for AD progression and improve cla...
Extracting functional connectivity patterns among cortical regions in fMRI datasets is a challeng... more Extracting functional connectivity patterns among cortical regions in fMRI datasets is a challenge stimulating the development of effective data-driven or model based techniques. Here, we present a novel data-driven method for the extraction of significantly connected functional ROIs directly from the preprocessed fMRI data without relying on a priori knowledge of the expected activations. This method finds spatially compact groups of voxels which show a homogeneous pattern of significant connectivity with other regions in the brain. The method, called Select and Cluster (S&C), consists of two steps: first, a dimensionality reduction step based on a blind multiresolution pairwise correlation by which the subset of all cortical voxels with significant mutual correlation is selected and the second step in which the selected voxels are grouped into spatially compact and functionally homogeneous ROIs by means of a Support Vector Clustering (SVC) algorithm. The S&C method is described in...
Medical science monitor : international medical journal of experimental and clinical research, Jan 27, 2016
BACKGROUND Understanding the dynamics of our surrounding environments is a task usually attribute... more BACKGROUND Understanding the dynamics of our surrounding environments is a task usually attributed to the detection of motion based on changes in luminance across space. Yet a number of other cues, both dynamic and static, have been shown to provide useful information about how we are moving and how objects around us move. One such cue, based on changes in spatial frequency, or scale, over time has been shown to be useful in conveying motion in depth even in the absence of a coherent, motion-defined flow field (optic flow). MATERIAL AND METHODS 16 right handed healthy observers (ages 18-28) participated in the behavioral experiments described in this study. Using analytical behavioral methods we investigate the functional specificity of this cue by measuring the ability of observers to perform tasks of heading (direction of self-motion) and 3D trajectory discrimination on the basis of scale changes and optic flow. RESULTS Statistical analyses of performance on the test-experiments i...
This paper examines the perception of first- and second-order motion in human vision. In an exten... more This paper examines the perception of first- and second-order motion in human vision. In an extension of previous work by Boulton w . and Baker J.B. Boulton, C.L. Baker, Motion detection is dependent on spatial frequency not size, Vision Res., 31 1991 77-87; J.B. . Boulton, C.L. Baker, Different parameters control motion perception above and below a critical density, Vision
Page 1. SYNTHESE LIBRARY/VOLUME 324 OPTIC FLOW AND BEYOND Edited by Lucia M. Vaina, Scott A. Bear... more Page 1. SYNTHESE LIBRARY/VOLUME 324 OPTIC FLOW AND BEYOND Edited by Lucia M. Vaina, Scott A. Beardsley and Simon K. Rushton KLUWER ACADEMIC PUBLISHERS Page 2. Page 3. Page 4. Page 5. OPTIC FLOW AND BEYOND This One CNT6-K5S-27LH Page 6 ...
Relatively little is known about how the human brain identifies movement of objects while the obs... more Relatively little is known about how the human brain identifies movement of objects while the observer is also moving in the environment. This is, ecologically, one of the most fundamental motion processing problems, critical for survival. To study this problem, we used a task which involved nine textured spheres moving in depth, eight simulating the observer's forward motion while the ninth, the target, moved independently with a different speed towards or away from the observer. Capitalizing on the high temporal resolution of magnetoencephalography (MEG) we trained a Support Vector Classifier (SVC) using the sensor-level data to identify correct and incorrect responses. Using the same MEG data, we addressed the dynamics of cortical processes involved in the detection of the independently moving object and investigated whether we could obtain confirmatory evidence for the brain activity patterns used by the classifier. Our findings indicate that response correctness could be reliably predicted by the SVC, with the highest accuracy during the blank period after motion and preceding the response. The spatial distribution of the areas critical for the correct prediction was similar but not exclusive to areas underlying the evoked activity. Importantly, SVC identified frontal areas otherwise not detected with evoked activity that seem to be important for the successful performance in the task. Dynamic connectivity further supported the involvement of frontal and occipital-temporal areas during the task periods. This is the first study to dynamically map cortical areas using a fully data-driven approach in order to investigate the neural mechanisms involved in the detection of moving objects during observer's self-motion.
The everyday environment brings to our sensory systems competing inputs from different modalities... more The everyday environment brings to our sensory systems competing inputs from different modalities. The ability to filter these multisensory inputs in order to identify and efficiently utilize useful spatial cues is necessary to detect and process the relevant information. In the present study, we investigate how feature-based attention affects the detection of motion across sensory modalities. We were interested to determine how subjects use intramodal, cross-modal auditory, and combined audiovisual motion cues to attend to specific visual motion signals. The results showed that in most cases, both the visual and the auditory cues enhance feature-based orienting to a transparent visual motion pattern presented among distractor motion patterns. Whereas previous studies have shown cross-modal effects of spatial attention, our results demonstrate a spread of cross-modal feature-based attention cues, which have been matched for the detection threshold of the visual target. These effects...
Magnetoencephalography (MEG) captures the magnetic fields generated by neuronal current sources w... more Magnetoencephalography (MEG) captures the magnetic fields generated by neuronal current sources with sensors outside the head. In MEG analysis these current sources are estimated from the measured data to identify the locations and time courses of neural activity. Since there is no unique solution to this so-called inverse problem, multiple source estimation techniques have been developed. The nulling beamformer (NB), a modified form of the linearly constrained minimum variance (LCMV) beamformer, is specifically used in the process of inferring interregional interactions and is designed to eliminate shared signal contributions, or cross-talk, between regions of interest (ROIs) that would otherwise interfere with the connectivity analyses. The nulling beamformer applies the truncated singular value decomposition (TSVD) to remove small signal contributions from a ROI to the sensor signals. However, ROIs with strong crosstalk will have high separating power in the weaker components, wh...
The functional significance of resting state networks and their abnormal manifestations in psychi... more The functional significance of resting state networks and their abnormal manifestations in psychiatric disorders are firmly established, as is the importance of the cortical rhythms in mediating these networks. Resting state networks are known to undergo substantial reorganization from childhood to adulthood, but whether distinct cortical rhythms, which are generated by separable neural mechanisms and are often manifested abnormally in psychiatric conditions, mediate maturation differentially, remains unknown. Using magnetoencephalography (MEG) to map frequency band specific maturation of resting state networks from age 7 to 29 in 162 participants (31 independent), we found significant changes with age in networks mediated by the beta (13-30 Hz) and gamma (31-80 Hz) bands. More specifically, gamma band mediated networks followed an expected asymptotic trajectory, but beta band mediated networks followed a linear trajectory. Network integration increased with age in gamma band mediat...
Amyloid positron emission tomography (PET) imaging is a valuable tool for research and diagnosis ... more Amyloid positron emission tomography (PET) imaging is a valuable tool for research and diagnosis in Alzheimer's disease (AD). Partial volume effects caused by the limited spatial resolution of PET scanners degrades the quantitative accuracy of PET image. In this study, we have applied a method to evaluate the impact of a joint-entropy based partial volume correction (PVC) technique on brain networks learned from a clinical dataset of AV-45 PET image and compare network properties of both uncorrected and corrected image-based brain networks. We also analyzed the region-wise SUVRs of both uncorrected and corrected images. We further performed classification tests on different groups using the same set of algorithms with same parameter settings. PVC has sometimes been avoided due to increased noise sensitivity in image registration and segmentation, however, our results indicate that appropriate PVC may enhance the brain network structure analysis for AD progression and improve cla...
Extracting functional connectivity patterns among cortical regions in fMRI datasets is a challeng... more Extracting functional connectivity patterns among cortical regions in fMRI datasets is a challenge stimulating the development of effective data-driven or model based techniques. Here, we present a novel data-driven method for the extraction of significantly connected functional ROIs directly from the preprocessed fMRI data without relying on a priori knowledge of the expected activations. This method finds spatially compact groups of voxels which show a homogeneous pattern of significant connectivity with other regions in the brain. The method, called Select and Cluster (S&C), consists of two steps: first, a dimensionality reduction step based on a blind multiresolution pairwise correlation by which the subset of all cortical voxels with significant mutual correlation is selected and the second step in which the selected voxels are grouped into spatially compact and functionally homogeneous ROIs by means of a Support Vector Clustering (SVC) algorithm. The S&C method is described in...
Medical science monitor : international medical journal of experimental and clinical research, Jan 27, 2016
BACKGROUND Understanding the dynamics of our surrounding environments is a task usually attribute... more BACKGROUND Understanding the dynamics of our surrounding environments is a task usually attributed to the detection of motion based on changes in luminance across space. Yet a number of other cues, both dynamic and static, have been shown to provide useful information about how we are moving and how objects around us move. One such cue, based on changes in spatial frequency, or scale, over time has been shown to be useful in conveying motion in depth even in the absence of a coherent, motion-defined flow field (optic flow). MATERIAL AND METHODS 16 right handed healthy observers (ages 18-28) participated in the behavioral experiments described in this study. Using analytical behavioral methods we investigate the functional specificity of this cue by measuring the ability of observers to perform tasks of heading (direction of self-motion) and 3D trajectory discrimination on the basis of scale changes and optic flow. RESULTS Statistical analyses of performance on the test-experiments i...
This paper examines the perception of first- and second-order motion in human vision. In an exten... more This paper examines the perception of first- and second-order motion in human vision. In an extension of previous work by Boulton w . and Baker J.B. Boulton, C.L. Baker, Motion detection is dependent on spatial frequency not size, Vision Res., 31 1991 77-87; J.B. . Boulton, C.L. Baker, Different parameters control motion perception above and below a critical density, Vision
Page 1. SYNTHESE LIBRARY/VOLUME 324 OPTIC FLOW AND BEYOND Edited by Lucia M. Vaina, Scott A. Bear... more Page 1. SYNTHESE LIBRARY/VOLUME 324 OPTIC FLOW AND BEYOND Edited by Lucia M. Vaina, Scott A. Beardsley and Simon K. Rushton KLUWER ACADEMIC PUBLISHERS Page 2. Page 3. Page 4. Page 5. OPTIC FLOW AND BEYOND This One CNT6-K5S-27LH Page 6 ...
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