AIMC Topic: Temporal Lobe

Clear Filters Showing 41 to 50 of 71 articles

Evidence that recurrent circuits are critical to the ventral stream's execution of core object recognition behavior.

Nature neuroscience
Non-recurrent deep convolutional neural networks (CNNs) are currently the best at modeling core object recognition, a behavior that is supported by the densely recurrent primate ventral stream, culminating in the inferior temporal (IT) cortex. If rec...

Resting-state anticorrelated networks in Schizophrenia.

Psychiatry research. Neuroimaging
Converging evidences from different lines of research suggest abnormalities in functional brain connectivity in schizophrenia. While positively correlated brain networks have been well researched, anticorrelated functional connectivity remains under ...

Representations of regular and irregular shapes by deep Convolutional Neural Networks, monkey inferotemporal neurons and human judgments.

PLoS computational biology
Recent studies suggest that deep Convolutional Neural Network (CNN) models show higher representational similarity, compared to any other existing object recognition models, with macaque inferior temporal (IT) cortical responses, human ventral stream...

Creatures great and small: Real-world size of animals predicts visual cortex representations beyond taxonomic category.

NeuroImage
Human occipitotemporal cortex contains neural representations for a variety of perceptual and conceptual features. We report a study examining neural representations of real-world size along the visual ventral stream, while carefully accounting for t...

Neuro-cognitive mechanisms of global Gestalt perception in visual quantification.

NeuroImage
Recent neuroimaging studies identified posterior regions in the temporal and parietal lobes as neuro-functional correlates of subitizing and global Gestalt perception. Beyond notable overlap on a neuronal level both mechanisms are remarkably similar ...

Global temporal lobe asymmetry as a semi-quantitative imaging biomarker for temporal lobe epilepsy lateralization: A machine learning classification study.

Hellenic journal of nuclear medicine
OBJECTIVE: The purpose of this study was to evaluate the utility of global semi-quantitative analysis via fluorine-18-flurodeoxyglucose positron emission tomography (F-FDG PET) at lateralizing seizure foci and diagnosing patients with unilateral temp...

Attractor Dynamics in Networks with Learning Rules Inferred from In Vivo Data.

Neuron
The attractor neural network scenario is a popular scenario for memory storage in the association cortex, but there is still a large gap between models based on this scenario and experimental data. We study a recurrent network model in which both lea...

Sub-millimeter ECoG pitch in human enables higher fidelity cognitive neural state estimation.

NeuroImage
Electrocorticography (ECoG), electrophysiological recording from the pial surface of the brain, is a critical measurement technique for clinical neurophysiology, basic neurophysiology studies, and demonstrates great promise for the development of neu...

Relationship between neuronal network architecture and naming performance in temporal lobe epilepsy: A connectome based approach using machine learning.

Brain and language
Impaired confrontation naming is a common symptom of temporal lobe epilepsy (TLE). The neurobiological mechanisms underlying this impairment are poorly understood but may indicate a structural disorganization of broadly distributed neuronal networks ...

Using machine learning and surface reconstruction to accurately differentiate different trajectories of mood and energy dysregulation in youth.

PloS one
Difficulty regulating positive mood and energy is a feature that cuts across different pediatric psychiatric disorders. Yet, little is known regarding the neural mechanisms underlying different developmental trajectories of positive mood and energy r...