scholarly journals Multivariate sensitivity to voice during auditory categorization

2015 ◽  
Vol 114 (3) ◽  
pp. 1819-1826 ◽  
Author(s):  
Yune Sang Lee ◽  
Jonathan E. Peelle ◽  
David Kraemer ◽  
Samuel Lloyd ◽  
Richard Granger
Keyword(s):  
Brain Activity ◽  
Temporal Cortex ◽  
Neural Representation ◽  
Current Evidence ◽  
General Role ◽  
Object Categories ◽  
Novel Approach ◽  
Auditory Object ◽  
Mri Study ◽  
Multivariate Pattern

Past neuroimaging studies have documented discrete regions of human temporal cortex that are more strongly activated by conspecific voice sounds than by nonvoice sounds. However, the mechanisms underlying this voice sensitivity remain unclear. In the present functional MRI study, we took a novel approach to examining voice sensitivity, in which we applied a signal detection paradigm to the assessment of multivariate pattern classification among several living and nonliving categories of auditory stimuli. Within this framework, voice sensitivity can be interpreted as a distinct neural representation of brain activity that correctly distinguishes human vocalizations from other auditory object categories. Across a series of auditory categorization tests, we found that bilateral superior and middle temporal cortex consistently exhibited robust sensitivity to human vocal sounds. Although the strongest categorization was in distinguishing human voice from other categories, subsets of these regions were also able to distinguish reliably between nonhuman categories, suggesting a general role in auditory object categorization. Our findings complement the current evidence of cortical sensitivity to human vocal sounds by revealing that the greatest sensitivity during categorization tasks is devoted to distinguishing voice from nonvoice categories within human temporal cortex.

scholarly journals Separated and overlapping neural coding of face and body identity

2021 ◽  
Author(s):  
Celia Foster ◽  
Mintao Zhao ◽  
Timo Bolkart ◽  
Michael J. Black ◽  
Andreas Bartels ◽  
...  
Keyword(s):  
Neural Coding ◽  
Brain Activity ◽  
Temporal Cortex ◽  
Occipital Cortex ◽  
Visual Input ◽  
Neural Representation ◽  
Body Images ◽  
General Role ◽  
Low Level ◽  
Person Identity

AbstractRecognising a person’s identity often relies on face and body information, and is tolerant to changes in low-level visual input (e.g. viewpoint changes). Previous studies have suggested that face identity is disentangled from low-level visual input in the anterior face-responsive regions. It remains unclear which regions disentangle body identity from variations in viewpoint, and whether face and body identity are encoded separately or combined into a coherent person identity representation. We trained participants to recognize three identities, and then recorded their brain activity using fMRI while they viewed face and body images of the three identities from different viewpoints. Participants’ task was to respond to either the stimulus identity or viewpoint. We found consistent decoding of body identity across viewpoint in the fusiform body area, right anterior temporal cortex, middle frontal gyrus and right insula. This finding demonstrates a similar function of fusiform and anterior temporal cortex for bodies as has previously been shown for faces, suggesting these regions may play a general role in extracting high-level identity information. Moreover, we could decode identity across neural activity evoked by faces and bodies in the early visual cortex, right inferior occipital cortex, right parahippocampal cortex and right superior parietal cortex, revealing a distributed network that encodes person identity abstractly. Lastly, identity decoding was consistently better when participants attended to identity, indicating that attention to identity enhances its neural representation. These results offer new insights into how the brain develops an abstract neural coding of person identity, shared by faces and bodies.

Partially Distributed Representations of Objects and Faces in Ventral Temporal Cortex

2005 ◽  
Vol 17 (4) ◽  
pp. 580-590 ◽  
Author(s):  
Alice J. O'Toole ◽  
Fang Jiang ◽  
Hervé Abdi ◽  
James V. Haxby
Keyword(s):  
Functional Neuroimaging ◽  
Brain Activity ◽  
Temporal Cortex ◽  
High Spatial Frequency ◽  
Object Classification ◽  
Classification Model ◽  
Neural Structure ◽  
Line Drawings ◽  
Object Categories ◽  
Ventral Temporal Cortex

Object and face representations in ventral temporal (VT) cortex were investigated by combining object confusability data from a computational model of object classification with neural response confusability data from a functional neuroimaging experiment. A pattern-based classification algorithm learned to categorize individual brain maps according to the object category being viewed by the subject. An identical algorithm learned to classify an image-based, view-dependent representation of the stimuli. High correlations were found between the confusability of object categories and the confusability of brain activity maps. This occurred even with the inclusion of multiple views of objects, and when the object classification model was tested with high spatial frequency “line drawings” of the stimuli. Consistent with a distributed representation of objects in VT cortex, the data indicate that object categories with shared image-based attributes have shared neural structure.

Intraoperative localization of spatially and spectrally distinct resting-state networks in Parkinson’s disease

2020 ◽  
Vol 132 (4) ◽  
pp. 1234-1242 ◽  
Author(s):  
Paolo Belardinelli ◽  
Ramin Azodi-Avval ◽  
Erick Ortiz ◽  
Georgios Naros ◽  
Florian Grimm ◽  
...  
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Network Effects ◽  
Brain Activity ◽  
Dynamic Imaging ◽  
Oscillatory Activity ◽  
Network Information ◽  
Novel Approach ◽  
Electrophysiological Recordings ◽  
Intraoperative Localization

Deep brain stimulation (DBS) of the subthalamic nucleus (STN) is an effective treatment for symptomatic Parkinson’s disease (PD); the clinical benefit may not only mirror modulation of local STN activity but also reflect consecutive network effects on cortical oscillatory activity. Moreover, STN-DBS selectively suppresses spatially and spectrally distinct patterns of synchronous oscillatory activity within cortical-subcortical loops. These STN-cortical circuits have been described in PD patients using magnetoencephalography after surgery. This network information, however, is currently not available during surgery to inform the implantation strategy.The authors recorded spontaneous brain activity in 3 awake patients with PD (mean age 67 ± 14 years; mean disease duration 13 ± 7 years) during implantation of DBS electrodes into the STN after overnight withdrawal of dopaminergic medication. Intraoperative propofol was discontinued at least 30 minutes prior to the electrophysiological recordings. The authors used a novel approach for performing simultaneous recordings of STN local field potentials (LFPs) and multichannel electroencephalography (EEG) at rest. Coherent oscillations between LFP and EEG sensors were computed, and subsequent dynamic imaging of coherent sources was performed.The authors identified coherent activity in the upper beta range (21–35 Hz) between the STN and the ipsilateral mesial (pre)motor area. Coherence in the theta range (4–6 Hz) was detected in the ipsilateral prefrontal area.These findings demonstrate the feasibility of detecting frequency-specific and spatially distinct synchronization between the STN and cortex during DBS surgery. Mapping the STN with this technique may disentangle different functional loops relevant for refined targeting during DBS implantation.

scholarly journals Neural alignment predicts learning outcomes in students taking an introduction to computer science course

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Meir Meshulam ◽  
Liat Hasenfratz ◽  
Hanna Hillman ◽  
Yun-Fei Liu ◽  
Mai Nguyen ◽  
...  
Keyword(s):  
Computer Science ◽  
Learning Outcomes ◽  
Brain Activity ◽  
Activity Patterns ◽  
Real Life ◽  
Final Exam ◽  
Neural Representations ◽  
Real Life Setting ◽  
The Right ◽  
Mri Study

AbstractDespite major advances in measuring human brain activity during and after educational experiences, it is unclear how learners internalize new content, especially in real-life and online settings. In this work, we introduce a neural approach to predicting and assessing learning outcomes in a real-life setting. Our approach hinges on the idea that successful learning involves forming the right set of neural representations, which are captured in canonical activity patterns shared across individuals. Specifically, we hypothesized that learning is mirrored in neural alignment: the degree to which an individual learner’s neural representations match those of experts, as well as those of other learners. We tested this hypothesis in a longitudinal functional MRI study that regularly scanned college students enrolled in an introduction to computer science course. We additionally scanned graduate student experts in computer science. We show that alignment among students successfully predicts overall performance in a final exam. Furthermore, within individual students, we find better learning outcomes for concepts that evoke better alignment with experts and with other students, revealing neural patterns associated with specific learned concepts in individuals.

Brain reactivity to humorous films is affected by insomnia

SLEEP ◽  
2021 ◽  
Author(s):  
Ernesto Sanz-Arigita ◽  
Yannick Daviaux ◽  
Marc Joliot ◽  
Bixente Dilharreguy ◽  
Jean-Arthur Micoulaud-Franchi ◽  
...  
Keyword(s):  
Emotional Reactivity ◽  
Brain Activity ◽  
Brain Network ◽  
Anterior Cingulate ◽  
Neural Representation ◽  
Cingulate Gyrus ◽  
Anterior Cingulate Gyrus ◽  
Left Caudate ◽  
Neural Reactivity ◽  
The Right

Abstract Study objectives Emotional reactivity to negative stimuli has been investigated in insomnia, but little is known about emotional reactivity to positive stimuli and its neural representation. Methods We used 3T fMRI to determine neural reactivity during the presentation of standardized short, 10-40-s, humorous films in insomnia patients (n=20, 18 females, aged 27.7 +/- 8.6 years) and age-matched individuals without insomnia (n=20, 19 females, aged 26.7 +/- 7.0 years), and assessed humour ratings through a visual analogue scale (VAS). Seed-based functional connectivity was analysed for left and right amygdala networks: group-level mixed-effects analysis (FLAME; FSL) was used to compare amygdala connectivity maps between groups. Results fMRI seed-based analysis of the amygdala revealed stronger neural reactivity in insomnia patients than in controls in several brain network clusters within the reward brain network, without humour rating differences between groups (p = 0.6). For left amygdala connectivity, cluster maxima were in the left caudate (Z=3.88), left putamen (Z=3.79) and left anterior cingulate gyrus (Z=4.11), while for right amygdala connectivity, cluster maxima were in the left caudate (Z=4.05), right insula (Z=3.83) and left anterior cingulate gyrus (Z=4.29). Cluster maxima of the right amygdala network were correlated with hyperarousal scores in insomnia patients only. Conclusions Presentation of humorous films leads to increased brain activity in the neural reward network for insomnia patients compared to controls, related to hyperarousal features in insomnia patients, in the absence of humor rating group differences. These novel findings may benefit insomnia treatment interventions.

scholarly journals Brain Activation During Reading in Deep Dyslexia: An MEG Study

2000 ◽  
Vol 12 (4) ◽  
pp. 622-634 ◽  
Author(s):  
Matti Laine ◽  
Riitta Salmelin ◽  
Päivi Helenius ◽  
Reijo Marttila
Keyword(s):  
Semantic Processing ◽  
Semantic Analysis ◽  
Right Hemisphere ◽  
Word Reading ◽  
Brain Activity ◽  
Temporal Cortex ◽  
Single Word ◽  
Lexical Semantic ◽  
Deep Dyslexia ◽  
Single Word Reading

Magnetoencephalographic (MEG) changes in cortical activity were studied in a chronic Finnish-speaking deep dyslexic patient during single-word and sentence reading. It has been hypothesized that in deep dyslexia, written word recognition and its lexical-semantic analysis are subserved by the intact right hemisphere. However, in our patient, as well as in most nonimpaired readers, lexical-semantic processing as measured by sentence-final semantic-incongruency detection was related to the left superior-temporal cortex activation. Activations around this same cortical area could be identified in single-word reading as well. Another factor relevant to deep dyslexic reading, the morphological complexity of the presented words, was also studied. The effect of morphology was observed only during the preparation for oral output. By performing repeated recordings 1 year apart, we were able to document significant variability in both the spontaneous activity and the evoked responses in the lesioned left hemisphere even though at the behavioural level, the patient's performance was stable. The observed variability emphasizes the importance of estimating consistency of brain activity both within and between measurements in brain-damaged individuals.

scholarly journals Preparatory Activity in Posterior Temporal Cortex Causally Contributes to Object Detection in Scenes

2015 ◽  
Vol 27 (11) ◽  
pp. 2117-2125 ◽  
Author(s):  
Reshanne R. Reeder ◽  
Francesca Perini ◽  
Marius V. Peelen
Keyword(s):  
Visual Cortex ◽  
Object Detection ◽  
Activity Patterns ◽  
Temporal Cortex ◽  
Relevant Information ◽  
Visual Selective Attention ◽  
Object Categories ◽  
Preparatory Attention ◽  
Preparatory Activity ◽  
Early Visual Cortex

Theories of visual selective attention propose that top–down preparatory attention signals mediate the selection of task-relevant information in cluttered scenes. Neuroimaging and electrophysiology studies have provided correlative evidence for this hypothesis, finding increased activity in target-selective neural populations in visual cortex in the period between a search cue and target onset. In this study, we used online TMS to test whether preparatory neural activity in visual cortex is causally involved in naturalistic object detection. In two experiments, participants detected the presence of object categories (cars, people) in a diverse set of photographs of real-world scenes. TMS was applied over a region in posterior temporal cortex identified by fMRI as carrying category-specific preparatory activity patterns. Results showed that TMS applied over posterior temporal cortex before scene onset (−200 and −100 msec) impaired the detection of object categories in subsequently presented scenes, relative to vertex and early visual cortex stimulation. This effect was specific to category level detection and was related to the type of attentional template participants adopted, with the strongest effects observed in participants adopting category level templates. These results provide evidence for a causal role of preparatory attention in mediating the detection of objects in cluttered daily-life environments.

The Optimum Power Load: A Simple and Powerful Tool for Testing and Training

2021 ◽  
pp. 1-9
Author(s):  
Irineu Loturco ◽  
Antonio Dello Iacono ◽  
Fábio Y. Nakamura ◽  
Tomás T. Freitas ◽  
Daniel Boullosa ◽  
...  
Keyword(s):  
Strong Support ◽  
Current Evidence ◽  
Novel Approach ◽  
Power Load ◽  
Velocity Relationship ◽  
Potential Applications ◽  
Bar Velocity ◽  
Acute And Chronic Effects ◽  
Testing Protocols ◽  
And Training

Purpose: The optimal power load is defined as the load that maximizes power output in a given exercise. This load can be determined through the use of various instruments, under different testing protocols. Specifically, the “optimum power load” (OPL) is derived from the load–velocity relationship, using only bar force and bar velocity in the power computation. The OPL is easily assessed using a simple incremental testing protocol, based on relative percentages of body mass. To date, several studies have examined the associations between the OPL and different sport-specific measures, as well as its acute and chronic effects on athletic performance. The aim of this brief review is to present and summarize the current evidence regarding the OPL, highlighting the main lines of research on this topic and discussing the potential applications of this novel approach for testing and training. Conclusions: The validity and simplicity of OPL-based schemes provide strong support for their use as an alternative to more traditional strength–power training strategies. The OPL method can be effectively used by coaches and sport scientists in different sports and populations, with different purposes and configurations.

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