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A Large Lateral Craniotomy Procedure for Mesoscale Wide-field Optical Imaging of Brain Activity

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Second order blind identification on the cerebral cortex.

David Wheland¹, Dimitrios Pantazis²

¹Signal & Image Processing Institute, University of Southern California, Los Angeles, CA, USA.

Journal of Neuroscience Methods

|December 10, 2013

Summary

This summary is machine-generated.

Related Concept Videos

Motor and Sensory Areas of the Cortex

Motor and Sensory Areas of the Cortex

The cerebral cortex, the brain's outermost layer, is pivotal in processing complex cognitive tasks, emotions, and various sensory inputs and executing voluntary motor activities. This intricate structure is divided into three primary functional areas: the motor areas, sensory areas, and association areas.
Motor Areas
The motor areas located in the frontal lobe are central to controlling voluntary movements. This region is further subdivided into the primary motor cortex and the premotor cortex....

Association Areas of the Cortex

Association Areas of the Cortex

Association areas are regions of the cerebral cortex that do not have a specific sensory or motor function. Instead, they integrate and interpret information from various sources to enable higher cognitive processes such as memory, learning, and decision-making. Some key association areas include the following:
Prefrontal Association Area: This area is located in the frontal lobe and is involved in planning, decision-making, and moderating social behavior. It connects with primary motor areas,...

Somatosensory, Motor, and Association Cortex

Somatosensory, Motor, and Association Cortex

The somatosensory cortex in the parietal lobes is crucial for interpreting sensory data such as touch, temperature, and proprioception. The somatosensory cortex, situated in the parietal lobes, plays a vital role in interpreting sensory information like touch, temperature, and proprioception—awareness of body position. This specialized brain region features an organized structure wherein neurons at the top primarily process sensations originating from the lower body. In contrast, those at...

Parallel Processing

Parallel Processing

The brain processes sensory information rapidly due to parallel processing, which involves sending data across multiple neural pathways at the same time. This method allows the brain to manage various sensory qualities, such as shapes, colors, movements, and locations, all concurrently. For instance, when observing a forest landscape, the brain simultaneously processes the movement of leaves, the shapes of trees, the depth between them, and the various shades of green. This enables a quick and...

Vision

Vision

Vision is the result of light being detected and transduced into neural signals by the retina of the eye. This information is then further analyzed and interpreted by the brain. First, light enters the front of the eye and is focused by the cornea and lens onto the retina—a thin sheet of neural tissue lining the back of the eye. Because of refraction through the convex lens of the eye, images are projected onto the retina upside-down and reversed.

Lobes of the Cerebrum

Lobes of the Cerebrum

The cerebral cortex, a critical structure of the brain, is intricately divided into two hemispheres, each consisting of four distinct lobes: occipital, temporal, frontal, and parietal. These lobes function cooperatively to regulate various cognitive and sensory functions, forming the basis of our complex neural capabilities.
Frontal lobe
The frontal lobes, located behind the forehead, are the command center of our brain, controlling personality, intelligence, and voluntary muscle movements....

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Blind source separation (BSS) methods offer new insights into brain structure. A novel spatial BSS approach, based on second-order blind identification (SOBI), effectively reveals cortical networks from thickness and folding patterns.

Area of Science:

Neuroimaging
Computational Neuroscience
Brain Imaging Analysis

Background:

Blind source separation (BSS) methods are standard for brain imaging analysis, primarily for artifact removal and component extraction.
Limited application of BSS methods exists for analyzing cortical morphometry, such as thickness and folding patterns.
Understanding the relationship between cortical morphometry, brain development, and neurological disorders is crucial.

Purpose of the Study:

To introduce a novel spatial BSS method specifically designed for analyzing cerebral cortical data.
To evaluate the performance of the proposed method against existing BSS techniques like regular second-order blind identification (SOBI) and FastICA.
To explore the potential of BSS in uncovering structural brain networks from morphometric data.

Main Methods:

Keywords:

Blind source separation (BSS)Cerebral cortex Gray matter thickness Independent component analysis (ICA)Second order blind identification (SOBI)Sulcal folding pattern

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Development of a novel spatial BSS algorithm tailored for cortical surface data.
Utilized the second-order blind identification (SOBI) framework as the basis for the new method.
Compared the proposed method with standard SOBI and FastICA using simulated data.

Main Results:

The proposed spatial BSS method demonstrated superior performance compared to regular SOBI and FastICA on simulation data.
Application of the method to cortical thickness and curvature maps from healthy controls identified novel structural networks.
The findings suggest BSS is a valuable tool for investigating cortical morphometry.

Conclusions:

The novel spatial BSS method is effective for analyzing cortical morphometry.
This approach advances the application of BSS in neuroimaging for exploring brain structure.
The study highlights the potential of BSS in revealing intricate structural networks within the brain.