AIMC Topic: Parietal Lobe
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Exploring semantic grounding in the posterior parietal cortex.
Brain structure & function
Jun 26, 2025
This study examines the evolving perspective on semantic processing, which has shifted from the traditional view of an isolated semantic memory system to one that recognizes the involvement of dynamic, distributed neural networks. Recent evidence sup...
Temporal spiking generative adversarial networks for heading direction decoding.
Neural networks : the official journal of the International Neural Network Society
Dec 5, 2024
The spike-based neuronal responses within the ventral intraparietal area (VIP) exhibit intricate spatial and temporal dynamics in the posterior parietal cortex, presenting decoding challenges such as limited data availability at the biological popula...
Zero-shot counting with a dual-stream neural network model.
Neuron
Nov 1, 2024
To understand a visual scene, observers need to both recognize objects and encode relational structure. For example, a scene comprising three apples requires the observer to encode concepts of "apple" and "three." In the primate brain, these function...
Convolutional neural networks reveal properties of reach-to-grasp encoding in posterior parietal cortex.
Computers in biology and medicine
Feb 19, 2024
Deep neural networks (DNNs) are widely adopted to decode motor states from both non-invasively and invasively recorded neural signals, e.g., for realizing brain-computer interfaces. However, the neurophysiological interpretation of how DNNs make the ...
Motor decoding from the posterior parietal cortex using deep neural networks.
Journal of neural engineering
May 19, 2023
Motor decoding is crucial to translate the neural activity for brain-computer interfaces (BCIs) and provides information on how motor states are encoded in the brain. Deep neural networks (DNNs) are emerging as promising neural decoders. Nevertheless...
Artificial neural network modelling of the neural population code underlying mathematical operations.
NeuroImage
Feb 26, 2023
Mathematical operations have long been regarded as a sparse, symbolic process in neuroimaging studies. In contrast, advances in artificial neural networks (ANN) have enabled extracting distributed representations of mathematical operations. Recent ne...
Precuneus brain response changes differently during human-robot and human-human dyadic social interaction.
Scientific reports
Aug 30, 2022
Human-human interactions (HHI) and human-robot interactions (HRI) are compared to identify differences between cognitive processes reflecting bonding in social interactions with natural and artificial agents. We capitalize on a unique corpus of neuro...
Organization of areal connectivity in the monkey frontoparietal network.
NeuroImage
Jul 20, 2021
Activity observed in biological neural networks is determined by anatomical connectivity between cortical areas. The monkey frontoparietal network facilitates cognitive functions, but the organization of its connectivity is unknown. Here, a new conne...
Assessing the Accuracy and Reproducibility of PARIETAL: A Deep Learning Brain Extraction Algorithm.
Journal of magnetic resonance imaging : JMRI
Jun 16, 2021
BACKGROUND: Manual brain extraction from magnetic resonance (MR) images is time-consuming and prone to intra- and inter-rater variability. Several automated approaches have been developed to alleviate these constraints, including deep learning pipeli...
How hot is the hot zone? Computational modelling clarifies the role of parietal and frontoparietal connectivity during anaesthetic-induced loss of consciousness.
NeuroImage
Feb 9, 2021
In recent years, specific cortical networks have been proposed to be crucial for sustaining consciousness, including the posterior hot zone and frontoparietal resting state networks (RSN). Here, we computationally evaluate the relative contributions ...
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