Literature DB >> 16192396

Separate spatial scales determine neural activity-dependent changes in tissue oxygen within central visual pathways.

Jeffrey K Thompson1, Matthew R Peterson, Ralph D Freeman.   

Abstract

The relationship between oxygen levels and neural activity in the brain is fundamental to functional neuroimaging techniques. We have examined this relationship on a fine spatial scale in the lateral geniculate nucleus (LGN) and visual cortex of the cat using a microelectrode sensor that provides simultaneous colocalized measurements of oxygen partial pressure in tissue (tissue oxygen) and multiunit neural activity. In previous work with this sensor, we found that changes in tissue oxygen depend strongly on the location and spatial extent of neural activation. Specifically, focal neural activity near the microelectrode elicited decreases in tissue oxygen, whereas spatially extended activation, outside the field of view of our sensor, yielded mainly increases. In the current study, we report an expanded set of measurements to quantify the spatiotemporal relationship between neural responses and changes in tissue oxygen. For the purpose of data analysis, we develop a quantitative model that assumes that changes in tissue oxygen are composed of two response components (one positive and one negative) with magnitudes determined by neural activity on separate spatial scales. Our measurements from visual cortex and the LGN are consistent with this model and suggest that the positive response spreads over a distance of 1-2 mm, whereas the negative component is confined to a few hundred micrometers. These results are directly relevant to the mechanisms that generate functional brain imaging signals and place limits on their spatial properties.

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Year:  2005        PMID: 16192396      PMCID: PMC6725582          DOI: 10.1523/JNEUROSCI.2127-05.2005

Source DB:  PubMed          Journal:  J Neurosci        ISSN: 0270-6474            Impact factor:   6.167


  26 in total

1.  Neurometabolic coupling in the lateral geniculate nucleus changes with extended age.

Authors:  Baowang Li; Ralph D Freeman
Journal:  J Neurophysiol       Date:  2010-05-12       Impact factor: 2.714

2.  Analysis of oxygen metabolism implies a neural origin for the negative BOLD response in human visual cortex.

Authors:  Brian N Pasley; Ben A Inglis; Ralph D Freeman
Journal:  Neuroimage       Date:  2006-11-16       Impact factor: 6.556

3.  Functional imaging of primary visual cortex using flavoprotein autofluorescence.

Authors:  T Robert Husson; Atul K Mallik; Jing X Zhang; Naoum P Issa
Journal:  J Neurosci       Date:  2007-08-08       Impact factor: 6.167

4.  Coupling between neuronal activity and microcirculation: implications for functional brain imaging.

Authors:  Ivo Vanzetta; Amiram Grinvald
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5.  Independent components in stimulus-related BOLD signals and estimation of the underlying neural responses.

Authors:  C W Tyler; L L Kontsevich; T C Ferree
Journal:  Brain Res       Date:  2008-06-24       Impact factor: 3.252

6.  Quantitative basis for neuroimaging of cortical laminae with calibrated functional MRI.

Authors:  Peter Herman; Basavaraju G Sanganahalli; Hal Blumenfeld; Douglas L Rothman; Fahmeed Hyder
Journal:  Proc Natl Acad Sci U S A       Date:  2013-08-26       Impact factor: 11.205

7.  BOLD and spiking activity.

Authors:  Yuval Nir; Ilan Dinstein; Rafael Malach; David J Heeger
Journal:  Nat Neurosci       Date:  2008-05       Impact factor: 24.884

8.  Neurometabolic coupling differs for suppression within and beyond the classical receptive field in visual cortex.

Authors:  Baowang Li; Ralph D Freeman
Journal:  J Physiol       Date:  2011-05-09       Impact factor: 5.182

9.  Endogenous attention signals evoked by threshold contrast detection in human superior colliculus.

Authors:  Sucharit Katyal; David Ress
Journal:  J Neurosci       Date:  2014-01-15       Impact factor: 6.167

Review 10.  Neural-metabolic coupling in the central visual pathway.

Authors:  Ralph D Freeman; Baowang Li
Journal:  Philos Trans R Soc Lond B Biol Sci       Date:  2016-10-05       Impact factor: 6.237

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