AIMC Topic: Temporal Lobe

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Machine learning algorithm for predicting seizure control after temporal lobe resection using peri-ictal electroencephalography.

Scientific reports
Brain resection is curative for a subset of patients with drug resistant epilepsy but up to half will fail to achieve sustained seizure freedom in the long term. There is a critical need for accurate prediction tools to identify patients likely to ha...

Machine learning quantification of Amyloid-β deposits in the temporal lobe of 131 brain bank cases.

Acta neuropathologica communications
Accurate and scalable quantification of amyloid-β (Aβ) pathology is crucial for deeper disease phenotyping and furthering research in Alzheimer Disease (AD). This multidisciplinary study addresses the current limitations on neuropathology by leveragi...

A deep learning-based method for the prediction of temporal lobe injury in patients with nasopharyngeal carcinoma.

Physica medica : PM : an international journal devoted to the applications of physics to medicine and biology : official journal of the Italian Association of Biomedical Physics (AIFB)
PURPOSE: To establish a deep learning-based model to predict radiotherapy-induced temporal lobe injury (TLI).

DeepFLAIR: A neural network approach to mitigate signal and contrast loss in temporal lobes at 7 Tesla FLAIR images.

Magnetic resonance imaging
BACKGROUND AND PURPOSE: Higher magnetic field strength introduces stronger magnetic field inhomogeneities in the brain, especially within temporal lobes, leading to image artifacts. Particularly, T2-weighted fluid-attenuated inversion recovery (FLAIR...

Consciousness: a neurosurgical perspective.

Acta neurochirurgica
Neurosurgeons are in a unique position to shed light on the neural basis for consciousness, not only by their clinical care of patients with compromised states of consciousness, but also by employing neurostimulation and neuronal recordings through i...

Evidence of a predictive coding hierarchy in the human brain listening to speech.

Nature human behaviour
Considerable progress has recently been made in natural language processing: deep learning algorithms are increasingly able to generate, summarize, translate and classify texts. Yet, these language models still fail to match the language abilities of...

Decoding of human identity by computer vision and neuronal vision.

Scientific reports
Extracting meaning from a dynamic and variable flow of incoming information is a major goal of both natural and artificial intelligence. Computer vision (CV) guided by deep learning (DL) has made significant strides in recognizing a specific identity...

A separable neural code in monkey IT enables perfect CAPTCHA decoding.

Journal of neurophysiology
Reading distorted letters is easy for us but so challenging for the machine vision that it is used on websites as CAPTCHA (Completely Automated Public Turing Test to tell Computers and Humans Apart). How does our brain solve this problem? One solutio...

Abnormal Degree Centrality as a Potential Imaging Biomarker for Right Temporal Lobe Epilepsy: A Resting-state Functional Magnetic Resonance Imaging Study and Support Vector Machine Analysis.

Neuroscience
Previous studies have reported altered neuroimaging features in right temporal lobe epilepsy (rTLE). However, the alterations in degree centrality (DC) as a diagnostic method for rTLE have not been reported. Therefore, we aimed to explore abnormaliti...