How not to study spontaneous activity

Logothetis, Nikos K.; Murayama, Yusuke; Augath, M; Steffen, Theodor; Werner, Joachim; Oeltermann, A

doi:10.1016/j.neuroimage.2009.01.010

Cited by 112 publications

(99 citation statements)

References 33 publications

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“…However, because neuronal activity in the brain is altered by multiple pathways, most importantly by locally specific neurotransmission and a more diffuse neuromodulation, multiple IRFs might exist. Indeed, as has already been shown by Logothetis et al (2009) in macaque monkeys, the IRF to stimulation rises and decays faster than the IRF to spontaneous activity as assessed using invasive electrophysiology during eyes closed. To test whether this is also true in awake human subjects, we performed an additional experiment recording simultaneously fMRI and EEG data, while the subject was resting in the scanner with eyes closed.…”

Section: Impulse Hemodynamic Response Function: Internally Versus Extsupporting

confidence: 56%

Relationship of the BOLD Signal with VEP for Ultrashort Duration Visual Stimuli (0.1 to 5 ms) in Humans

Yesilyurt

Whittingstall

Uğurbil

et al. 2009

J Cereb Blood Flow Metab

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There is currently a great interest to combine electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) to study brain function. Earlier studies have shown different EEG components to correlate well with the fMRI signal arguing for a complex relationship between both measurements. In this study, using separate EEG and fMRI measurements, we show that (1) 0.1 ms visual stimulation evokes detectable hemodynamic and visual-evoked potential (VEP) responses, (2) the negative VEP deflection at B80 ms (N2) co-varies with stimulus duration/intensity such as with blood oxygenation level-dependent (BOLD) response; the positive deflection at B120 ms (P2) does not, and (3) although the N2 VEP-BOLD relationship is approximately linear, deviation is evident at the limit of zero N2 VEP. The latter finding argues that, although EEG and fMRI measurements can co-vary, they reflect partially independent processes in the brain tissue. Finally, it is shown that the stimulus-induced impulse response function (IRF) at 0.1 ms and the intrinsic IRF during rest have different temporal dynamics, possibly due to predominance of neuromodulation during rest as compared with neurotransmission during stimulation. These results extend earlier findings regarding VEP-BOLD coupling and highlight the component-and context-dependency of the relationship between evoked potentials and hemodynamic responses.

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Section: Impulse Hemodynamic Response Function: Internally Versus Extsupporting

confidence: 56%

Relationship of the BOLD Signal with VEP for Ultrashort Duration Visual Stimuli (0.1 to 5 ms) in Humans

Yesilyurt

Whittingstall

Uğurbil

et al. 2009

J Cereb Blood Flow Metab

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“…Additionally, it has been shown that using remifentanil (an ultra-fast-acting -opioid receptor agonist) has no significant effect on the neurovascular and neural activity of brain areas that do not belong to the pain matrix (Lund et al, 1994;Logothetis et al, 1999Logothetis et al, , 2009Sereno et al, 2002;Zappe et al, 2008a,b). In particular, visual cortex does not bind remifentanil (Jones et al, 1991).…”

Section: Methodsmentioning

confidence: 99%

“…Spontaneous activity was recorded in runs of 4 min, with the monkey sitting in complete darkness with its eyes open and no direct visual stimulation (Logothetis et al, 2009). High-spatiotemporal resolution, multishot (two segments) gradient echo-echoplanar imaging scans were run for the acquisition of spontaneous activity [TR ϭ 250 or 125 ms (two experiments), TE ϭ 20 ms, bandwidth ϭ 100 kHz, flip angle ϭ 20 -25°], yielding an intervolume time of 500 or 250 ms, respectively.…”

Section: Methodsmentioning

confidence: 99%

The Amplitude and Timing of the BOLD Signal Reflects the Relationship between Local Field Potential Power at Different Frequencies

et al. 2012

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There is growing evidence that several components of the mass neural activity contributing to the local field potential (LFP) can be partly separated by decomposing the LFP into nonoverlapping frequency bands. Although the blood oxygen level-dependent (BOLD) signal has been found to correlate preferentially with specific frequency bands of the LFP, it is still unclear whether the BOLD signal relates to the activity expressed by each LFP band independently of the others or if, instead, it also reflects specific relationships among different bands. We investigated these issues by recording, simultaneously and with high spatiotemporal resolution, BOLD signal and LFP during spontaneous activity in early visual cortices of anesthetized monkeys (Macaca mulatta). We used information theory to characterize the statistical dependency between BOLD and LFP. We found that the alpha (8 -12 Hz), beta (18 -30 Hz), and gamma (40 -100 Hz) LFP bands were informative about the BOLD signal. In agreement with previous studies, gamma was the most informative band. Both increases and decreases in BOLD signal reliably followed increases and decreases in gamma power. However, both alpha and beta power signals carried information about BOLD that was largely complementary to that carried by gamma power. In particular, the relationship between alpha and gamma power was reflected in the amplitude of the BOLD signal, while the relationship between beta and gamma bands was reflected in the latency of BOLD with respect to significant changes in gamma power. These results lay the basis for identifying contributions of different neural pathways to cortical processing using fMRI.

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“…Widespread correlations and apparent waves of activity given by correlations between fMRI and discrete LFP recordings have also been noted in the primate brain (16). However, the origin and the physiological meaning of these patterns of neural activity remain controversial (42).…”

Section: Fig 6 Summary Of Hrfs Derived From Multiple Analysis Methomentioning

confidence: 99%

Resting-state hemodynamics are spatiotemporally coupled to synchronized and symmetric neural activity in excitatory neurons

Shaik

Kozberg

et al. 2016

Proc. Natl. Acad. Sci. U.S.A.

305

303

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Brain hemodynamics serve as a proxy for neural activity in a range of noninvasive neuroimaging techniques including functional magnetic resonance imaging (fMRI). In resting-state fMRI, hemodynamic fluctuations have been found to exhibit patterns of bilateral synchrony, with correlated regions inferred to have functional connectivity. However, the relationship between resting-state hemodynamics and underlying neural activity has not been well established, making the neural underpinnings of functional connectivity networks unclear. In this study, neural activity and hemodynamics were recorded simultaneously over the bilateral cortex of awake and anesthetized Thy1-GCaMP mice using wide-field optical mapping. Neural activity was visualized via selective expression of the calcium-sensitive fluorophore GCaMP in layer 2/3 and 5 excitatory neurons. Characteristic patterns of resting-state hemodynamics were accompanied by more rapidly changing bilateral patterns of resting-state neural activity. Spatiotemporal hemodynamics could be modeled by convolving this neural activity with hemodynamic response functions derived through both deconvolution and gamma-variate fitting. Simultaneous imaging and electrophysiology confirmed that Thy1-GCaMP signals are well-predicted by multiunit activity. Neurovascular coupling between resting-state neural activity and hemodynamics was robust and fast in awake animals, whereas coupling in urethane-anesthetized animals was slower, and in some cases included lower-frequency (<0.04 Hz) hemodynamic fluctuations that were not well-predicted by local Thy1-GCaMP recordings. These results support that resting-state hemodynamics in the awake and anesthetized brain are coupled to underlying patterns of excitatory neural activity. The patterns of bilaterally-symmetric spontaneous neural activity revealed by widefield Thy1-GCaMP imaging may depict the neural foundation of functional connectivity networks detected in resting-state fMRI. neurovascular coupling | resting state | GCaMP | optical imaging | neural network activity F unctional magnetic resonance imaging (fMRI) measures local changes in deoxyhemoglobin concentration [HbR] as a surrogate for neural activity. In stimulus-evoked studies, the positive fMRI blood oxygen level-dependent (BOLD) signal corresponds to a decrease in [HbR] caused by a local increase in blood flow leading to over-oxygenation of the region. However, a growing number of studies are now using resting-state functional connectivity fMRI (fc-fMRI) in which spontaneous fluctuations in the BOLD signal are recorded in the absence of a task (1). Spatiotemporal correlations in these hemodynamic signals across the brain have been found to be bilaterally symmetric and synchronized in distant brain regions. This synchrony is interpreted as representing the connectivity of intrinsic neural networks (2-6). Many studies have identified changes in these resting-state networks during brain development (7,8) and in neurological and even psychological disorders (9-11). However, understandin...

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How not to study spontaneous activity

Cited by 112 publications

References 33 publications

Relationship of the BOLD Signal with VEP for Ultrashort Duration Visual Stimuli (0.1 to 5 ms) in Humans

Relationship of the BOLD Signal with VEP for Ultrashort Duration Visual Stimuli (0.1 to 5 ms) in Humans

The Amplitude and Timing of the BOLD Signal Reflects the Relationship between Local Field Potential Power at Different Frequencies

Resting-state hemodynamics are spatiotemporally coupled to synchronized and symmetric neural activity in excitatory neurons

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