2011
DOI: 10.1073/pnas.1102026108
|View full text |Cite
|
Sign up to set email alerts
|

Evidence for the importance of measuring total brain activity in neuroimaging

Abstract: A principal goal in neuroscience is to understand how neuronal populations across different brain regions process information from the vibrant world, rich in moment-to-moment variations of sight, smell, sound, touch, etc. Traditional inquiries examine how the evoked neuronal responses differ with stimuli (e.g., sound or touch). However, the brain detects stimuli reliably even when ambient (or background) conditions shift owing to external (e.g., light vs. dark) and/or internal (e.g., alert vs. sleepy) factors.… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
1
1
1
1

Citation Types

0
16
0

Year Published

2011
2011
2020
2020

Publication Types

Select...
8
1

Relationship

5
4

Authors

Journals

citations
Cited by 16 publications
(16 citation statements)
references
References 22 publications
0
16
0
Order By: Relevance
“…The magnitude of neuronal signaling in the human brain, and by inference the commensurate energy demand, underscores the functional relevance of resting activity and has profound implications for interpreting fMRI experiments in humans. [12][13][14] Given the rapidly increasing use of resting-state fMRI in mapping networks-defined as a subset of cortical and subcortical gray-matter regions that function together 15,16 -it is important to quantitatively establish if in the resting human the metabolic demand for neuronal signaling is high, as has been established for the rodent, 5,[7][8][9] and to what extent metabolic demand varies across gray-matter regions. 13 C magnetic resonance spectroscopy (MRS) of 13 C-labeled substrates (e.g., glucose and acetate) can measure rates of 13 C label incorporation into cell-specific pools (e.g., glutamate and gamino butyric acid (GABA) are predominantly neuronal and glutamine is predominantly glial) thereby estimating metabolic fluxes 17 of neuronal glucose oxidation (CMR glc(ox),N ) and of total glutamate neurotransmitter cycling (V cyc(tot) ).…”
Section: Introductionmentioning
confidence: 99%
“…The magnitude of neuronal signaling in the human brain, and by inference the commensurate energy demand, underscores the functional relevance of resting activity and has profound implications for interpreting fMRI experiments in humans. [12][13][14] Given the rapidly increasing use of resting-state fMRI in mapping networks-defined as a subset of cortical and subcortical gray-matter regions that function together 15,16 -it is important to quantitatively establish if in the resting human the metabolic demand for neuronal signaling is high, as has been established for the rodent, 5,[7][8][9] and to what extent metabolic demand varies across gray-matter regions. 13 C magnetic resonance spectroscopy (MRS) of 13 C-labeled substrates (e.g., glucose and acetate) can measure rates of 13 C label incorporation into cell-specific pools (e.g., glutamate and gamino butyric acid (GABA) are predominantly neuronal and glutamine is predominantly glial) thereby estimating metabolic fluxes 17 of neuronal glucose oxidation (CMR glc(ox),N ) and of total glutamate neurotransmitter cycling (V cyc(tot) ).…”
Section: Introductionmentioning
confidence: 99%
“…While recent experimental evidence is changing the opinion that spontaneous neuronal activity is simply “noise” (for recent reviews see (Hyder and Rothman, 2011; Northoff et al, 2010; Ringach, 2009; Shulman et al, 2007)), it should be noted that classical studies had raised the importance of spontaneous activity for understanding brain function (Adrian, 1941). Future studies need considerations about properties of the stimulus (e.g., amplitude, contrast, etc.)…”
Section: What Fraction Of Neuronal Ensemble’s Activity Is Needed For mentioning
confidence: 99%
“…The optimal definition of a baseline signal in BOLD data is not straightforward because the brain is never truly at rest (31,32). Here we calculate the mean baseline value for each subject from the average signal in the 24-to 30-s time period, and use this value to convert all single trials to percent signal change.…”
Section: Are the Davis And Baseline Assumptions Correct For Poststimulusmentioning
confidence: 99%