scholarly journals An extension of the studyforrest dataset for vision research

2016 ◽  
Author(s):  
Ayan Sengupta ◽  
Falko R. Kaule ◽  
J. Swaroop Guntupalli ◽  
Michael B. Hoffmann ◽  
Christian Häusler ◽  
...  
Keyword(s):  
Visual Processing ◽  
Functional Neuroimaging ◽  
Original Cohort ◽  
Mapping Procedure ◽  
Retinotopic Mapping ◽  
Face Area ◽  
Neuroimaging Data ◽  
Imaging Research ◽  
Higher Visual Areas

AbstractThe studyforrest (http://studyforrest.org) dataset is likely the largest neuroimag-ing dataset on natural language and story processing publicly available today. In this article, along with a companion publication, we present an update of this dataset that extends its scope to vision and multi-sensory research. 15 participants of the original cohort volunteered for a series of additional studies: a clinical examination of visual function, a standard retinotopic mapping procedure, and a localization of higher visual areas — such as the fusiform face area. The combination of this update, the previous data releases for the dataset, and the companion publication, which includes neuroimaging and eye tracking data from natural stimulation with a motion picture, form an extremely versatile and comprehensive resource for brain imaging research — with almost six hours of functional neuroimaging data across five different stimulation paradigms for each participant. Furthermore, we describe employed paradigms and present results that document the quality of the data for the purpose of characterising major properties of participants’ visual processing stream.

scholarly journals Contrasting Cortical Activity Associated with Category Memory and Recognition Memory

1998 ◽  
Vol 5 (6) ◽  
pp. 420-428 ◽  
Author(s):  
Paul J. Reber ◽  
Craig E.L. Stark ◽  
Larry R. Squire
Keyword(s):  
Recognition Memory ◽  
Visual Processing ◽  
Functional Neuroimaging ◽  
Brain Activity ◽  
Recognition Task ◽  
Occipital Cortex ◽  
Fmri Data ◽  
Categorization Task ◽  
Neuroimaging Data ◽  
Familiar Stimuli

We collected functional neuroimaging data while volunteers performed similar categorization and recognition memory tasks. In the categorization task, volunteers first studied a series of 40 dot patterns that were distortions of a nonstudied prototype dot pattern. After a delay, while fMRI data were collected, they categorized 72 novel dot patterns according to whether or not they belonged to the previously studied category. In the recognition task, volunteers first studied five dot patterns eight times each. After a delay, while fMRI data were collected, they judged whether each of 72 dot patterns had been studied earlier. We found strikingly different patterns of brain activity in visual processing areas for the two tasks. During the categorization task, the familiar stimuli were associated with decreased activity in posterior occipital cortex, whereas during the recognition task, the familiar stimuli were associated with increased activity in this area. The findings indicate that these two types of memory have contrasting effects on early visual processing and reinforce the view that declarative and nondeclarative memory operate independently.

scholarly journals The HCP 7T Retinotopy Dataset: Description and pRF Analysis

2018 ◽  
Author(s):  
Noah C. Benson ◽  
Keith W. Jamison ◽  
Michael J. Arcaro ◽  
An Vu ◽  
Matthew F. Glasser ◽  
...  
Keyword(s):  
Visual Processing ◽  
Large Scale ◽  
Individual Variability ◽  
7 Tesla ◽  
Individual Subject ◽  
Retinotopic Mapping ◽  
Human Connectome Project ◽  
The Brain ◽  
Model Based Analysis

AbstractAbout a quarter of human cerebral cortex is dedicated mainly to visual processing. The large-scale organization of visual cortex can be measured with functional magnetic resonance imaging (fMRI) while subjects view spatially modulated visual stimuli, also known as ‘retinotopic mapping’. One of the datasets collected by the Human Connectome Project (HCP) involved ultra-high-field (7 Tesla) fMRI retinotopic mapping in 181 healthy young adults (1.6-mm resolution), yielding the largest freely available collection of retinotopy data. Here, we describe the experimental paradigm and the results of model-based analysis of the fMRI data. These results provide estimates of population receptive field position and size. Our analyses include both results from individual subjects as well as results obtained by averaging fMRI time-series across subjects at each cortical and subcortical location and then fitting models. Both the group-average and individual-subject results reveal robust signals across much of the brain, including occipital, temporal, parietal, and frontal cortex as well as subcortical areas. The group-average results agree well with previously published parcellations of visual areas. In addition, split-half analyses show strong within-subject reliability, further demonstrating the high quality of the data. We make publicly available the analysis results for individual subjects and the group average, as well as associated stimuli and analysis code. These resources provide an opportunity for studying fine-scale individual variability in cortical and subcortical organization and the properties of high-resolution fMRI. In addition, they provide a set of observations that can be compared with other HCP measures acquired in these same participants.

scholarly journals Electrophysiology and brain imaging of biological motion

2003 ◽  
Vol 358 (1431) ◽  
pp. 435-445 ◽  
Author(s):  
Aina Puce ◽  
David Perrett
Keyword(s):  
Visual Processing ◽  
Biological Motion ◽  
Functional Neuroimaging ◽  
Eye Gaze ◽  
Single Cells ◽  
Field Potential ◽  
Neural Responses ◽  
Social Signals ◽  
Facial Movements ◽  
Neuroimaging Data

The movements of the faces and bodies of other conspecifics provide stimuli of considerable interest to the social primate. Studies of single cells, field potential recordings and functional neuroimaging data indicate that specialized visual mechanisms exist in the superior temporal sulcus (STS) of both human and non–human primates that produce selective neural responses to moving natural images of faces and bodies. STS mechanisms also process simplified displays of biological motion involving point lights marking the limb articulations of animate bodies and geometrical shapes whose motion simulates purposeful behaviour. Facial movements such as deviations in eye gaze, important for gauging an individual's social attention, and mouth movements, indicative of potential utterances, generate particularly robust neural responses that differentiate between movement types. Collectively such visual processing can enable the decoding of complex social signals and through its outputs to limbic, frontal and parietal systems the STS may play a part in enabling appropriate affective responses and social behaviour.

scholarly journals Frontal contributions to face processing differences in autism: Evidence from fMRI of inverted face processing

2008 ◽  
Vol 14 (6) ◽  
pp. 922-932 ◽  
Author(s):  
SUSAN Y. BOOKHEIMER ◽  
A. TING WANG ◽  
ASHLEY SCOTT ◽  
MARIAN SIGMAN ◽  
MIRELLA DAPRETTO
Keyword(s):  
Face Processing ◽  
Visual Processing ◽  
Visual Information ◽  
Functional Neuroimaging ◽  
Autism Spectrum ◽  
Fusiform Face Area ◽  
Social Significance ◽  
Inverted Position ◽  
Face Area ◽  
Reduced Activity

AbstractFunctional neuroimaging studies of face processing deficits in autism have typically focused on visual processing regions, such as the fusiform face area (FFA), which have shown reduced activity in autism spectrum disorders (ASD), though inconsistently. We recently reported reduced activity in the inferior frontal region in ASD, implicating impaired mirror-neuron systems during face processing. In the present study, we used fMRI during a face processing task in which subjects had to match faces presented in the upright versus inverted position. Typically developing (TD) children showed a classic behavioral inversion effect, increased reaction time for inverted faces, while this effect was significantly reduced in ASD subjects. The fMRI data showed similar responses in the fusiform face area for ASD and TD children, with both groups demonstrating increased activation for inverted faces. However, the groups did differ in several brain regions implicated in social cognition, particularly prefrontal cortex and amygdala. These data suggest that the behavioral differences in processing upright versus inverted faces for TD children are related not to visual information processing but to the social significance of the stimuli. Our results are consistent with other recent studies implicating frontal and limbic dysfunction during face processing in autism. (JINS, 2008, 14, 922–932.)

scholarly journals Behavioral Change and Its Neural Correlates in Visual Agnosia After Expertise Training

2005 ◽  
Vol 17 (4) ◽  
pp. 554-568 ◽  
Author(s):  
Marlene Behrmann ◽  
Jonathan Marotta ◽  
Isabel Gauthier ◽  
Michael J. Tarr ◽  
Thomas J. McKeeff
Keyword(s):  
Face Recognition ◽  
Functional Neuroimaging ◽  
Neural Substrates ◽  
Visual Object ◽  
Visual Object Recognition ◽  
Visual Agnosia ◽  
Face Area ◽  
Normal Individuals ◽  
Neuroimaging Data ◽  
Neurologically Normal

Agnosia, the impairment in object and face recognition despite intact vision and intelligence, is one of the most intriguing and debilitating neuropsychological deficits. The goal of this study was to determine whether S.M., an individual with longstanding visual agnosia and concomitant prosopagnosia, can be retrained to perform visual object recognition and, if so, what neural substrates mediate this reacquisition. Additionally, of interest is the extent to which training on one type of visual stimulus generalizes to other visual stimuli, as this informs our understanding of the organization of ventral visual cortex. Greebles were chosen as the stimuli for retraining given that, in neurologically normal individuals, these stimuli can engage the fusiform face area. Posttraining, S.M. showed significant improvement in recognizing Greebles, although he did not attain normal levels of performance. He was also able to recognize untrained Greebles and showed improvement in recognizing common objects. Surprisingly, his performance on face recognition, albeit poor initially, was even more impaired following training. A comparison of preand postintervention functional neuroimaging data mirrored the behavioral findings: Face-selective voxels in the fusiform gyrus prior to training were no longer so and were, in fact, more Greeble-selective. The findings indicate potential for experience-dependent dynamic reorganization in agnosia with the possibility that residual neural tissue, with limited capacity, will compete for representations.

Cancer and Cancer Treatment-Related Cognitive Impairment

2019 ◽  
pp. 60-83
Author(s):  
James C.  Root ◽  
Elizabeth Ryan ◽  
Tim A. Ahles
Keyword(s):  
Cancer Survivors ◽  
Cancer Treatment ◽  
Clinical Presentation ◽  
Functional Neuroimaging ◽  
Theoretical Models ◽  
Future Research ◽  
Cognitive Changes ◽  
Central Nervous System Cancer ◽  
Pharmacologic Treatments

As the population of cancer survivors has grown into the millions, there is increasing emphasis on understanding how late effects of treatment impact survivors’ ability return to work/school, ability to function and live independently, and overall quality of life. Cognitive changes are one of the most feared problems among cancer survivors. This chapter describes the growing literature examining cognitive changes associated with non-central nervous system cancer and cancer treatment. Typical elements of cancer treatment are discussed, followed by a description of clinical presentation, self-reported and objectively assessed cognitive findings, and results of structural and functional neuroimaging research. Genetic and other risk factors for cognitive decline following treatment are identified and discussed, together with biomarkers and animal models of treatment-related effects. This is followed by a discussion of behavioral and pharmacologic treatments. Finally, challenges and recommendations for future research are provided to help guide subsequent research and theoretical models.

scholarly journals Caries and Restoration Detection Using Bitewing Film Based on Transfer Learning with CNNs

Sensors ◽  
2021 ◽  
Vol 21 (13) ◽  
pp. 4613
Author(s):  
Yi-Cheng Mao ◽  
Tsung-Yi Chen ◽  
He-Sheng Chou ◽  
Szu-Yin Lin ◽  
Sheng-Yu Liu ◽  
...  
Keyword(s):  
Neural Networks ◽  
Rapid Development ◽  
Radiographic Examination ◽  
Analysis Model ◽  
Common Procedure ◽  
Medical Treatments ◽  
Pass Filter ◽  
Single Tooth ◽  
Imaging Research

Caries is a dental disease caused by bacterial infection. If the cause of the caries is detected early, the treatment will be relatively easy, which in turn prevents caries from spreading. The current common procedure of dentists is to first perform radiographic examination on the patient and mark the lesions manually. However, the work of judging lesions and markings requires professional experience and is very time-consuming and repetitive. Taking advantage of the rapid development of artificial intelligence imaging research and technical methods will help dentists make accurate markings and improve medical treatments. It can also shorten the judgment time of professionals. In addition to the use of Gaussian high-pass filter and Otsu’s threshold image enhancement technology, this research solves the problem that the original cutting technology cannot extract certain single teeth, and it proposes a caries and lesions area analysis model based on convolutional neural networks (CNN), which can identify caries and restorations from the bitewing images. Moreover, it provides dentists with more accurate objective judgment data to achieve the purpose of automatic diagnosis and treatment planning as a technology for assisting precision medicine. A standardized database established following a defined set of steps is also proposed in this study. There are three main steps to generate the image of a single tooth from a bitewing image, which can increase the accuracy of the analysis model. The steps include (1) preprocessing of the dental image to obtain a high-quality binarization, (2) a dental image cropping procedure to obtain individually separated tooth samples, and (3) a dental image masking step which masks the fine broken teeth from the sample and enhances the quality of the training. Among the current four common neural networks, namely, AlexNet, GoogleNet, Vgg19, and ResNet50, experimental results show that the proposed AlexNet model in this study for restoration and caries judgments has an accuracy as high as 95.56% and 90.30%, respectively. These are promising results that lead to the possibility of developing an automatic judgment method of bitewing film.

Database of MNI stereotactic coordinates for deep brain stimulation targets in neuropsychiatric disorders

2011 ◽  
Vol 26 (S2) ◽  
pp. 1149-1149
Author(s):  
U. Moser ◽  
M. Savli ◽  
R. Lanzenberger ◽  
S. Kasper
Keyword(s):  
Deep Brain Stimulation ◽  
Brain Stimulation ◽  
Functional Neuroimaging ◽  
Case Reports ◽  
Three Dimensional ◽  
Compulsive Disorder ◽  
Neuroimaging Data ◽  
Specific Disorders ◽  
Image Position ◽  
Deep Brain

IntroductionDeep brain stimulation (DBS) is a promising therapy option for otherwise treatment-resistant neuropsychiatrie disorders, especially in obsessive-compulsive disorder (OCD), major depression (TRD) and Tourette's Syndrome (TS).ObjectiveThe brain coordinates of the DBS targets are mainly reported using measurements in original, unnormalized brains. In the neuroimaging community stereotactic data are mainly indicated in the standardized Montreal Neurological Institute (MNI) space, i.e. a three-dimensional proportional grid system.AimsImproved comparability between targets in DBS studies and molecular and functional neuroimaging data from PET, SPECT, MRI, fMRI, mostly published with stereotactic data.MethodsA comprehensive and systematic literature search for published DBS case reports or studies in TRD, OCD and TS was performed. We extracted the tip positions of electrode leads as provided in the publications or by the authors, and transferred individual coordinates to the standard brain in the MNI space.Results46 publications fulfilled the inclusion criteria. The main targets for the specific disorders and one or two examples of their calculated MNI coordinates are indicated in the table:[MNI coordinates of the main DBS targets]ConclusionsWe provide DBS data of neuropsychiatrie disorders in the MNI space, improving the comparability to molecular, functional and structural neuroimaging data.

scholarly journals Functional Neuroimaging and Psychology: What Have You Done for Me Lately?

2013 ◽  
Vol 25 (6) ◽  
pp. 834-842 ◽  
Author(s):  
Joseph M. Moran ◽  
Jamil Zaki
Keyword(s):  
Functional Imaging ◽  
Brain Mapping ◽  
Functional Neuroimaging ◽  
Brain Activity ◽  
Psychological Theory ◽  
Quarter Century ◽  
Psychological Phenomena ◽  
Neuroimaging Data ◽  
Subsequent Behavior ◽  
Reverse Inference

Functional imaging has become a primary tool in the study of human psychology but is not without its detractors. Although cognitive neuroscientists have made great strides in understanding the neural instantiation of countless cognitive processes, commentators have sometimes argued that functional imaging provides little or no utility for psychologists. And indeed, myriad studies over the last quarter century have employed the technique of brain mapping—identifying the neural correlates of various psychological phenomena—in ways that bear minimally on psychological theory. How can brain mapping be made more relevant to behavioral scientists broadly? Here, we describe three trends that increase precisely this relevance: (i) the use of neuroimaging data to adjudicate between competing psychological theories through forward inference, (ii) isolating neural markers of information processing steps to better understand complex tasks and psychological phenomena through probabilistic reverse inference, and (iii) using brain activity to predict subsequent behavior. Critically, these new approaches build on the extensive tradition of brain mapping, suggesting that efforts in this area—although not initially maximally relevant to psychology—can indeed be used in ways that constrain and advance psychological theory.

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