Human Function Representation

A central principle in neuroscience is that neurons within the brain act in concert to produce perception, cognition, and adaptive behavior. Neurons are organized into specialized brain areas, dedicated to different functions to varying extents, and their function relies on distributed circuits to continuously encode relevant environmental and body-state features, enabling other areas to

A comprehensive, computable representation of the functional repertoire of all macromolecules encoded within the human genome is a foundational resource for biology and biomedical research. The

Using a representation learning method previously designed for human participants 16,39, we identified 66 sparse, non-negative dimensions underlying LLMs' similarity judgements that lead to

The three-part brain model is a classic representation of the human brain that divides it into three regions the forebrain, the midbrain, and the hindbrain. This model is commonly used to explain the concept of lateralization of brain function, which is important in neuroscience and psychotherapy.

Functional MRI has been invaluable in understanding brain function, but findings often remain of limited real-world relevance. This Perspective discusses how neuroimaging in more naturalistic environments may reveal crucial insights into human cognition and social interactions in everyday life.

In this paper, we formulate the representation learning of human brain function as an embedding problem. The regularity and variability of brain function across individual brains and at different time points are represented in a general, comparable, and stereotyped embedding space, where the 3D volumes of fMRI data that record functional brain

Then, we introduce a new brain function representation framework for the sampled patches. Each patch has its function description by referring to anchor patches, as well as the position description. Furthermore, we design an adaptive-selection-assisted Transformer network to optimize and integrate the function representations of all sampled

Learning an effective and compact representation of human brain function from high-dimensional fMRI data is crucial for studying the brain's functional organization. Traditional representation methods such as independent component analysis ICA and sparse dictionary learning SDL mainly rely on matrix decomposition which represents the brain

This is the PyTorch implementation for randomizing human brain function representation for brain disease diagnosis. Abstract. We propose a novel randomizing strategy for generating brain function representation to facilitate neural disease diagnosis. Specifically, we randomly sample brain patches, thus avoiding ROI parcellations of the brain atlas.

Based on anatomical and functional criteria, the cortex of the human brain is divided in primary, secondary, and tertiary areas, with anatomical representation predominantly in primary cortex and modality-independent, functional representation in tertiary structures Mesulam, 1987.The primary sensorimotor cortex shows a clear somatotopic representation of body parts Penfield and Boldrey