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Functional magnetic resonance imaging: Applications, Research & Regions
Functional magnetic resonance imaging or functional MRI (fMRI) measures brain activity by detecting changes associated with blood flow. This technique relies on the fact that cerebral blood flow and neuronal activation are coupled: When an area of the brain is in use, blood flow to that region increases.
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Functional magnetic resonance imaging topic overview
The analysis highlights Applications, Research and Regions as prominent areas in the source structure around Functional magnetic resonance imaging.
Related topics
139
Source areas
13
Connected nodes
152
Extracted relationships
142
Concept neighborhoods
25
Bridge connections
152
What this topic covers Research coverage
Source areas are shown by the number of related topics found in each part of the analysis. Use smaller areas too: they can reveal specialized angles and content gaps.
Overview · 53 topics
BOLD hemodynamic response · 21 topics
Analyzing the data · 16 topics
Issues in fMRI · 9 topics
Matching neural activity to the BOLD signal · 8 topics
Commercial use · 7 topics
Advanced methods · 5 topics
Criticism · 5 topics
Health risks · 5 topics
Medical use · 5 topics
Combining with other methods · 3 topics
Animal research · 1 topics
Textbooks · 1 topics
Smaller areas are not necessarily less important. They contain fewer connections in this analysis and can be useful for finding specialized angles or coverage gaps.
Key facts & relationships
High-confidence facts extracted from structured source data. Use them as anchors for further research.
Purpose
Measures brain activity detecting changes due to blood flow.
Explore all related topics Closing gaps
A structured outline of related entities, concepts and subtopics. Open any item to build a new map centered on it.
Browse the complete topic structure, not only the most central items. Less prominent entities and concepts can reveal missing angles, specialized context and useful research gaps. Each item opens a new analysis centered on that subject.
Deeper signals for content research, entity SEO and topical coverage. The plain-language headings explain what each technical view is useful for.
How Functional magnetic resonance imaging connects Entity context
Entity context groups extracted connections by relationship type. Counts show recurrence in the analyzed source; the examples are research signals, not claims about importance.
The extracted context around Functional magnetic resonance imaging shows recurring relationship patterns in the source. For example, Functional magnetic resonance imaging → An Event-Related Functional Magnetic, Bas, Basic Books, Berend, Brain Activity, Brainwashed, Childress, Colier, Erning, Gur, Henk, Hoefnagels, Human Brain Mapping, ISBN, Jannet, Jansen, Kallen, Langleben, Leon, Lilienfeld Another extracted example is Functional magnetic resonance imaging → Alan Kingstone, Buxton, Cabeza, Cambridge University Press, Cognition, Editors, EMRF/TRTF, Functional Imaging, Functional Neuroimaging, Handbook, Hornak, Introduction, ISBN, Joseph, Magnetic Resonance, Massachusetts, McCarthy, MIT Press, MRI, Peter. Use these groups to spot repeated connection types before inspecting the individual relationships.
Functional magnetic resonance imaging
Top relations
related to Further reading· 47
Functional magnetic resonance imaging → An Event-Related Functional Magnetic, Bas, Basic Books, Berend, Brain Activity, Brainwashed, Childress, Colier, Erning, Gur, Henk, Hoefnagels, Human Brain Mapping, ISBN, Jannet, Jansen, Kallen, Langleben, Leon, Lilienfeld
related to Textbooks· 27
Functional magnetic resonance imaging → Alan Kingstone, Buxton, Cabeza, Cambridge University Press, Cognition, Editors, EMRF/TRTF, Functional Imaging, Functional Neuroimaging, Handbook, Hornak, Introduction, ISBN, Joseph, Magnetic Resonance, Massachusetts, McCarthy, MIT Press, MRI, Peter
Purpose· 1
Functional magnetic resonance imaging → Measures brain activity detecting changes due to blood flow.
Important terminology
Frequent words and multi-word phrases across the lead, headings, infobox and body. Useful for terminology coverage.
Use these terms to understand the vocabulary surrounding the topic, not as a checklist for keyword stuffing.
Functional magnetic resonance imaging relationships Subject–Predicate–Object triples
Relationships are represented as Subject → Predicate → Object triples. Confidence describes extraction strength, not the real-world importance of a relationship; lower-confidence rows may be contextual rather than explicit.
TTTA extracted 142 structured relationships around Functional magnetic resonance imaging. Examples in this analysis include Functional magnetic resonance imaging → Purpose → Measures brain activity detecting changes due to blood flow. and radioactive tracers as in positron emission tomography → instance of → or the ingestion of substances. The table shows each extracted connection, where it came from and its confidence.
Subject
Predicate
Object
Confidence
Src
Functional magnetic resonance imaging
Purpose
Measures brain activity detecting changes due to blood flow.
1.00
infobox
radioactive tracers as in positron emission tomography
instance of
or the ingestion of substances
0.80
text
electroencephalography
instance of
It can complement other measures of brain physiology
0.80
text
lie detectors based on fMRI techniques
instance of
Some companies have developed commercial products
0.80
text
but the research is not believed to be developed enough for widespread commercial use
instance of
Some companies have developed commercial products
0.80
text
the 'signal-to-noise ratio'
instance of
Angelo Mosso investigated several critical variables that are still relevant in modern neuroimaging
0.80
text
the appropriate choice of the experimental paradigm
instance of
Angelo Mosso investigated several critical variables that are still relevant in modern neuroimaging
0.80
text
the need for the simultaneous recording of differing physiological parameters
instance of
Angelo Mosso investigated several critical variables that are still relevant in modern neuroimaging
0.80
text
iron
instance of
though less so than ferromagnetic elements
0.80
text
the amygdala
instance of
Initial results show there is more inflow than consumption of glucose in regions
0.80
text
basal ganglia
instance of
Initial results show there is more inflow than consumption of glucose in regions
0.80
text
thalamus
instance of
Initial results show there is more inflow than consumption of glucose in regions
0.80
text
No triples extracted yet.
Related concept clusters Concept neighborhoods
Concept neighborhoods group terms that sit near one another in the extracted graph. They are useful for discovering adjacent language and context, but proximity does not by itself imply a factual relationship.
The concept neighborhoods around Functional magnetic resonance imaging bring nearby vocabulary together. In this analysis, examples include Field, Imaging and Regions. Use the clusters to find adjacent concepts and terminology that may deserve separate research.
Functional magnetic resonance imaging
Field
Imaging
Regions
Changes
Magnetic
Mri
Using
Brain
Activity
Study
Activation
Fmri
functional magnetic resonance imaging
Field
Imaging
Regions
Changes
Magnetic
Mri
Using
Brain
Study
Techniques
Activity
Signal
blood flow
Flow
Brain
Changes
Use
Neural
Signal
Magnetic
Regions
Bold
Response
Mri
However
brain
Activity
Regions
Fmri
Blood
Flow
Activation
Changes
Functional
Mri
Used
Cognitive
Neural
brain mapping
Activity
Regions
Fmri
Blood
Flow
Activation
Changes
Functional
Mri
Used
Cognitive
Neural
red blood cells
Flow
Brain
Changes
Signal
Neural
Magnetic
Use
Bold
Mri
Response
However
Regions
blood
Flow
Brain
Changes
Signal
Neural
Magnetic
Use
Bold
Mri
Response
However
Regions
cerebral blood volume
Flow
Brain
Changes
Signal
Neural
Magnetic
Use
Bold
Mri
Response
However
Regions
Connections between topic areas Semantic bridges
Semantic bridges connect parts of the graph that would otherwise be more separate. A bridge is a structural signal in this analysis, not a claim that the two topic areas are equivalent.
For Functional magnetic resonance imaging, one of the stronger structural bridges in this analysis connects Functional magnetic resonance imaging with Overview. Bridges highlight paths between different parts of the map and can reveal research angles that are easy to miss in a flat list.
Min side: 3
Functional magnetic resonance imaging — Overview· splits 99 ⟂ 54Functional magnetic resonance imaging — BOLD hemodynamic response· splits 131 ⟂ 22Functional magnetic resonance imaging — Analyzing the data· splits 136 ⟂ 17Functional magnetic resonance imaging — Issues in fMRI· splits 143 ⟂ 10Functional magnetic resonance imaging — Matching neural activity to the BOLD signal· splits 144 ⟂ 9Functional magnetic resonance imaging — Commercial use· splits 145 ⟂ 8Functional magnetic resonance imaging — Medical use· splits 147 ⟂ 6Functional magnetic resonance imaging — Health risks· splits 147 ⟂ 6Functional magnetic resonance imaging — Advanced methods· splits 147 ⟂ 6Functional magnetic resonance imaging — Criticism· splits 147 ⟂ 6Functional magnetic resonance imaging — Combining with other methods· splits 149 ⟂ 4
Map overview Semantic statistics
Number of nodes, edges, triples, density and central hubs. Use it to gauge the size and connectivity of the map.
Functional magnetic resonance imaging
Nodes153
Edges152
Triples142
Avg. degree1.99
Density0.013072
Components1
Source & methodology
TTTA analyzes the structure around Functional magnetic resonance imaging to surface related topics, entities, relationships, concept neighborhoods and bridge connections. Use the map to explore areas such as Applications, Research & Regions, including less central topics that may reveal useful research gaps. Automatically extracted connections are research leads rather than rewritten encyclopedia content.
