Leveraging Time Series Data For Mri And Bold ( Blood Oxygen Level Dependent )

A fresh human brain does not resemble the stereotypical fixated human brain typically seen in textbooks or diagrams. Instead, a fresh human brain is rich in vasculature, extending across the entire surface of the brain. The brain, in a sense, is greedy, requiring twenty percent of the oxygen coming from the lungs and twenty percent of the blood pumped by the heart. Recently, the brain’s greediness has led to advances in medical brain imaging technology. The PET scan maps the amount blood flow through specific areas of the brain, allowing researchers to localize particular functions to precise areas of the brain. In the TED talk, Dr. Allen explains the function of the cerebellum, temporal cortex, and frontal lobe – areas of the brain whose functions were determined using PET scan.

Due to this, it has been deemed difficult to determine which deficit is the consequence of which part of a lesion. To overcome this problem, other methods are being used to aid in the visualisation of memory processes in the healthy parts of the brain. These come in the form of functional neuroimaging studies using Positron Emission Tomography (PET) and Functional Magnetic Resonance Imaging (fMRI). These studies have allowed researchers to target specific memory processes using targeted psychological experiments. However, with all psychological experiments, there are limitations to using neuroimaging equipment. PET and fMRI attain their signals from local changes in blood flow or metabolism correlated with neural activity rather than from brain waves (or signals). The local vascular changes affect the distribution of an injected radionuclide (e.g. O15) in PET or magnetic properties that are blood-oxygen level dependent (BOLD) in fMRI. The indirect measure of neural activity limits the temporal and spatial fidelity of activations.

Using Functional MRI helps to visualize the brain functionality through local metabolism. In this technology it allows the researcher to measure and track the brain functions by discovering the correlated changes in blood flow. From this functional Mri when a brain function is acted out the flow of oxygenated rich blood is detected and highlighted on the specific location where the functionality came from on the brain.

Resting-State functional MRI (rsfMRI) has been drawing increased attention (Biswal et al., 2010) and can be divided into two categories (Lee et al., 2013; Song et al., 2011). The first category is Resting-state functional connectivity (RsFC), which is a task-independent metric of brain activity that is primarily based on based on correlations between low-frequency fluctuations of the blood oxygen level dependent (BOLD) signal between disparate brain regions

The Functional magnetic resonance imaging (fMRI) is a functional neuroimaging procedure that used MRI technology to measure our brains activity through blood flow changes and our voxels.

The study demonstrates that functional connectivity profiles from functional magnetic resonance imaging studies can accurately and consistently identify individual subjects between scan sessions and also task and rest conditions. Data from 126 subjects of six fMRI sessions provided by the Human Connectome Project were used for the primary data set. Each subject was scanned over 2 days (3 sessions each day): consisting of a resting-state session, a working-memory task, and a motor task on the first day; costing a resting-state session, a language task, and an emotion task on the second day. Functional connectivity was mapped in a functional brain atlas consisting of 268 nodes covering the brain. Identification was performed across pairs of scans comparing

This quantitative quasi-experimental study will employ a single-factor ex-post facto design. Statistical Parametric Mapping (SPM) is a statistic technique that will be used to examine the differences in brain activity recorded functional neuroimging using the neuroimaging techniques (i.e., PET and MRI). The software created by the Wellcome Department of Imaging Neuroscience will be used to conduct this analysis (Daglish et al., 2008).

Haxby’s model suggests that the OFA projects information to both the FFA and the pSTS-FA. However, recent studies that explored the connections between the face-selective areas, found that the pSTS-FA is only weakly connected to the FFA and OFA, while the FFA and OFA are highly connected to one another (Pyles et al., 2013). Avidan et al recently carried out a functional connection study and reported a higher correlation between the fMRI signal of the OFA and FFA compared to the correlation between these areas and the pSTS-FA (Avidan et al., 2014). Therefore, these findings do not support Haxby’s model and suggest that the OFA and FFA make up one pathway, while the pSTS-FA is part of a separate pathway. Findings from several case studies

For neuroscience to progress, existing investigative techniques must be improved and refined, and new technologies developed. The following discussion explores proposals for enhancing fMRI technology and modifying experimental approaches in animal research in order to advance knowledge in the field.

The MRIs were taken by a method called segmentation, which gave them enough details of the brain

At first, the idea of dissecting a brain excites me but the moment it was there, I was hesitant to hold it first because I was afraid of how it feel to hold a human brain. However, as our examination of the brain parts went along, I finally had the courage to touch it and sense its surfaces. Honestly, being a novice in identifying the parts of the brain was a challenge for me, or for the most of us. My groupmates and I had a difficulty in identifying the specific location of its parts since our reference was from google images and a phone application. In result, for every part that we will identify, it took us almost more than a minute to discover the right place of a certain part. The

In addition, measuring fMRI responses across visual areas ranging from the V1 to fusiform face

2. Functional brain mapping (scanning a person's brain while he or she is performing a certain physical task such as squeezing a ball, or looking at a particular type of picture) is helping researchers better understand how the brain works.

Q1. Discuss the advantages and disadvantages of lesion studies compared to in vivo neuroimaging methods of neuroscience. Lesion studies, which produce data, localize human brain function by studying the correlation between a behavioural disorder and the location of brain injury. They are particularly invasive as it involves removing part of the brain while making comparisons before and after the lesion and consequent deficits are noted. Lesion studies are often carried out when brain surgery is required, for example to remove parts of the brain where epileptic seizures are known to originate.

In this section we evaluated the proposed approach using experiments based on synthetic and real image data. The proposed approach was compared to a public DT registration toolkit DTI-TK [#Zhang2006] using a number of evaluation metrics. DTI-TK is an open source DT image registration package. It is optimized for examining white matter morphometry using DT images. It was consistently ranked the best performing tool in two DT registration evaluation projects [#Wang2011, #Wang2017]. It also has a close relationship with our proposed approach because both methods are piecewise based. The difference is that DTI-TK uses an affine model while we use nonlinear models for registering pieces.