AIMC Topic: Temporal Lobe

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Machine learning algorithm accurately detects fMRI signature of vulnerability to major depression.

Psychiatry research
Standard functional magnetic resonance imaging (fMRI) analyses cannot assess the potential of a neuroimaging signature as a biomarker to predict individual vulnerability to major depression (MD). Here, we use machine learning for the first time to ad...

A Model of Emergent Category-specific Activation in the Posterior Fusiform Gyrus of Sighted and Congenitally Blind Populations.

Journal of cognitive neuroscience
Theories about the neural bases of semantic knowledge tend between two poles, one proposing that distinct brain regions are innately dedicated to different conceptual domains and the other suggesting that all concepts are encoded within a single netw...

Discrimination of schizophrenia auditory hallucinators by machine learning of resting-state functional MRI.

International journal of neural systems
Auditory hallucinations (AH) are a symptom that is most often associated with schizophrenia, but patients with other neuropsychiatric conditions, and even a small percentage of healthy individuals, may also experience AH. Elucidating the neural mecha...

Exploring the diagnostic potential of EEG theta power and interhemispheric correlation of temporal lobe activities in Alzheimer's Disease through random forest analysis.

Computers in biology and medicine
BACKGROUND: Considering the prevalence of Alzheimer's Disease (AD) among the aging population and the limited means of treatment, early detection emerges as a crucial focus area whereas electroencephalography (EEG) provides a promising diagnostic too...

fNIRS experimental study on the impact of AI-synthesized familiar voices on brain neural responses.

Scientific reports
With the advancement of artificial intelligence (AI) speech synthesis technology, its application in personalized voice services and its potential role in emotional comfort have become research focal points. This study aims to explore the impact of A...

Perception and memory in the medial temporal lobe: Deep learning offers a new lens on an old debate.

Neuron
In this issue of Neuron, Bonnen et al. (2021) use artificial neural networks to resolve a long-standing controversy surrounding the neurocognitive dichotomy between memory and perception. They show that the perirhinal cortex supports performance on t...

Diverse Deep Neural Networks All Predict Human Inferior Temporal Cortex Well, After Training and Fitting.

Journal of cognitive neuroscience
Deep neural networks (DNNs) trained on object recognition provide the best current models of high-level visual cortex. What remains unclear is how strongly experimental choices, such as network architecture, training, and fitting to brain data, contr...

How multisensory neurons solve causal inference.

Proceedings of the National Academy of Sciences of the United States of America
Sitting in a static railway carriage can produce illusory self-motion if the train on an adjoining track moves off. While our visual system registers motion, vestibular signals indicate that we are stationary. The brain is faced with a difficult chal...

Machine learning approach to identify a resting-state functional connectivity pattern serving as an endophenotype of autism spectrum disorder.

Brain imaging and behavior
Endophenotype refers to a measurable and heritable component between genetics and diagnosis, and the same endophenotype is present in both individuals with a diagnosis and their unaffected siblings. Determination of the neural correlates of an endoph...

Machine learning technique reveals intrinsic characteristics of schizophrenia: an alternative method.

Brain imaging and behavior
Machine learning technique has long been utilized to assist disease diagnosis, increasing clinical physicians' confidence in their decision and expediting the process of diagnosis. In this case, machine learning technique serves as a tool for disting...