Elsevier

NeuroImage

Volume 87, 15 February 2014, Pages 323-331
NeuroImage

Direct, intraoperative observation of ~ 0.1 Hz hemodynamic oscillations in awake human cortex: Implications for fMRI

https://doi.org/10.1016/j.neuroimage.2013.10.044Get rights and content

Highlights

  • Direct observation of ~ 0.1 Hz oscillation in awake human cortex.

  • Oscillation in frequency range of resting state function connectivity analysis.

  • Oscillation delineates vascular networks.

  • ~ 0.1 Hz oscillations are also observed in pre-operative fMRI BOLD signal.

  • Potential novel target for functional diagnosis of neurological disease.

Abstract

An almost sinusoidal, large amplitude ~ 0.1 Hz oscillation in cortical hemodynamics has been repeatedly observed in species ranging from mice to humans. However, the occurrence of ‘slow sinusoidal hemodynamic oscillations’ (SSHOs) in human functional magnetic resonance imaging (fMRI) studies is rarely noted or considered. As a result, little investigation into the cause of SSHOs has been undertaken, and their potential to confound fMRI analysis, as well as their possible value as a functional biomarker has been largely overlooked.

Here, we report direct observation of large-amplitude, sinusoidal ~ 0.1 Hz hemodynamic oscillations in the cortex of an awake human undergoing surgical resection of a brain tumor. Intraoperative multispectral optical intrinsic signal imaging (MS-OISI) revealed that SSHOs were spatially localized to distinct regions of the cortex, exhibited wave-like propagation, and involved oscillations in the diameter of specific pial arterioles, indicating that the effect was not the result of systemic blood pressure oscillations. fMRI data collected from the same subject 4 days prior to surgery demonstrates that ~ 0.1 Hz oscillations in the BOLD signal can be detected around the same region. Intraoperative optical imaging data from a patient undergoing epilepsy surgery, in whom sinusoidal oscillations were not observed, is shown for comparison.

This direct observation of the ‘0.1 Hz wave’ in the awake human brain, using both intraoperative imaging and pre-operative fMRI, confirms that SSHOs occur in the human brain, and can be detected by fMRI. We discuss the possible physiological basis of this oscillation and its potential link to brain pathologies, highlighting its relevance to resting-state fMRI and its potential as a novel target for functional diagnosis and delineation of neurological disease.

Introduction

It is well known that the brain exhibits baseline variations in blood flow with temporal frequencies between ~ 0.01 and 0.15 Hz (Fox and Raichle, 2007). Assumed to have a relatively featureless 1/f-type spectrum, and to be tightly coupled to neuronal activity, these fluctuations are the foundation of so-called ‘resting state functional connectivity mapping’ (RSFC); an increasingly popular approach to functional magnetic resonance imaging (fMRI). The basis of RSFC mapping is the idea that spatially distinct correlations in the time-course of spontaneous hemodynamic fluctuations (detected as changes in the fMRI blood oxygen level dependent signal, BOLD) can be interpreted as maps of large-scale functional network organization. Such mapping has been demonstrated in mice (White et al., 2011), rats (Pawela et al., 2008), non-human primates (Mantini et al., 2011) and humans (Buckner et al., 2008, Fox and Raichle, 2007) and is increasingly being applied to study the difference between normal and diseased brain states including early Alzheimer's disease (Buckner et al., 2009, Sheline and Raichle, 2013), study of motor deficits in brain tumor patients (Otten et al., 2012), predicting surgical outcome of epilepsy (Negishi et al., 2011), traumatic brain injury (Mayer et al., 2011) and schizophrenia (Garrity et al., 2007).

Distinct from these 1/f-type fluctuations, there have also been reports of a so called ~ 0.1 Hz, ‘vasomotor’ or slow sinusoidal hemodynamic oscillation (SSHO) in the brain (Mayhew et al., 1996). These large oscillations, with amplitudes comparable to the hemodynamic response to sensory stimulus, are sporadic, but have been shown to occur in the rat (Golanov et al., 1994, Grosberg et al., 2012, Majeed et al., 2009, Mayhew et al., 1996, Saka et al., 2010), cat (Spitzer et al., 2001), awake rabbit (Hundley et al., 1988) and non-invasively in humans using near-infrared spectroscopy (Elwell et al., 1999, Kolyva et al., 2013, Näsi et al., 2011, Obrig et al., 2000, Sassaroli et al., 2012, Schroeter et al., 2005), and fMRI BOLD (Mitra et al., 1997). In some cases the appearance of SSHOs in the brain has been linked to distinct physiological conditions or states (Näsi et al., 2011). However, a factor that has confused interpretation of these observations is the known occurrence of sinusoidal oscillations in systemic blood pressure, also at around 0.1 Hz, in this case being called ‘Mayer waves’ (Julien, 2006, Mayer, 1876). The possible influence of systemic blood pressure oscillations on measurements of cortical hemodynamics, particularly non-invasive NIRS measurements through the intact scalp, (Kvernmo et al., 1998) has made the true prevalence, cause, mechanisms and neural correlates of SSHOs unclear.

In this study we present the direct observation of a ~ 0.1 Hz, spatially distinct cortical hemodynamic oscillation in an awake human undergoing brain tumor resection, acquired using intraoperative multi-spectral optical intrinsic signal imaging (MS-OISI). Intraoperative imaging data collected on a second subject, who was undergoing epilepsy surgery and did not exhibit SSHOs, is shown for comparison. We characterize the spatiotemporal properties of the SSHOs observed in subject 1, identifying correlated oscillations in the tone of pial arterioles, and demonstrating that the SSHOs exhibit wave-like properties within affected regions of the cortex. We further show that a similar ~ 0.1 Hz oscillation was detected in fMRI BOLD data acquired in the same subject, four days prior to surgery.

We conclude that although only observed here in one subject, SSHOs can occur in the human, awake brain and are measurable via fMRI. We discuss the possible mechanistic underpinnings of SSHOs and their potential importance for diagnostics and RSFC mapping.

Section snippets

Multi-spectral optical intrinsic signal imaging (MS-OISI)

This study utilized MS-OISI, a technique which uses a camera to acquire images while the cortical surface is illuminated with specific wavelengths of light. Changes in measured light intensity correspond to changes in absorption due to changes in the concentrations of oxy- and deoxy-hemoglobin ([HbO] and [HbR] respectively) (Bouchard et al., 2009, Hillman, 2007). MS-OISI images represent a 2D, superficially weighted sum of these hemodynamic signals from the pial vasculature and the deeper

Direct observation of ~ 0.1 Hz oscillation in the awake human cortex

Subject 1 was a 35 year old female undergoing a repeat craniotomy for resection of a right posterior medial frontal lobe oligodendroglioma. During intrasurgical optical imaging, the subject was awake and engaged in performing a hand motor task by pushing a button for the duration of an auditory cue (3 s on, 3 s off). Although the subject was performing a task during MS-OISI acquisition, intrasurgical somatosensory evoked potential monitoring via a strip electrode and pre-operative fMRI data (Fig. 4

Discussion

Slow sinusoidal 0.1 Hz hemodynamic oscillations, or SSHOs in humans have been reported previously using both NIRS and fMRI BOLD (Mitra et al., 1997, Obrig et al., 2000). However, the prevalence and importance of SSHOs have been questioned, particularly in relation to contamination from systemic blood pressure fluctuations (Ferguson, 2003, Kvernmo et al., 1998). Using intraoperative MS-OISI we recorded optical reflectance signals directly from the superficial layers of the awake human cortex,

Acknowledgments

We thank Drs. Catherine Schevon, Angela Lignelli-Dipple, Jack Grinband, Sameer Sheth, John Sheehy, Hani Malone, Daniel Stoyanov, Daniel Chow, Mariel Kozberg and Jason Berwick for helpful discussions; Drs. Michael Sisti and Jeffrey Bruce, Columbia University neurosurgery residents, and neurosurgical operating room staff for their help in collecting the data; Keith Yeager for machining assistance; and members of the Laboratory for Functional Optical Imaging for their support and helpful

References (79)

  • M. Nakai et al.

    Scopolamine-sensitive and resistant components of increase in cerebral cortical blood flow elicited by periaqueductal gray matter of rats

    Neurosci. Lett.

    (1999)
  • H. Obrig et al.

    Spontaneous low frequency oscillations of cerebral hemodynamics and metabolism in human adults

    NeuroImage

    (2000)
  • H. Oishi et al.

    Role of membrane potential in vasomotion of isolated pressurized rat arteries

    Life Sci.

    (2002)
  • N. Prakash et al.

    Current trends in intraoperative optical imaging for functional brain mapping and delineation of lesions of language cortex

    NeuroImage

    (2009)
  • J.A. Schmidt et al.

    Periodic hemodynamics (flow motion) in peripheral arterial occlusive disease

    J. Vasc. Surg.

    (1993)
  • Y.I. Sheline et al.

    Resting state functional connectivity in preclinical Alzheimer's disease

    Biol. Psychiatry

    (2013)
  • C. Aalkjær et al.

    Vasomotion: cellular background for the oscillator and for the synchronization of smooth muscle cells

    Br. J. Pharmacol.

    (2005)
  • C. Aalkjær et al.

    Vasomotion — what is currently thought?

    Acta Physiol.

    (2011)
  • N.A. Anis et al.

    The dissociative anaesthetics, ketamine and phencyclidine, selectively reduce excitation of central mammalian neurones by N-methyl-aspartate

    Br. J. Pharmacol.

    (1983)
  • D. Attwell et al.

    Glial and neuronal control of brain blood flow

    Nature

    (2010)
  • B. Biswal et al.

    Functional connectivity in the motor cortex of resting human brain using echo-planar MRI

    Magn. Reson. Med.

    (1995)
  • M.B. Bouchard et al.

    Ultra-fast multispectral optical imaging of cortical oxygenation, blood flow, and intracellular calcium dynamics

    Opt. Express

    (2009)
  • E. Bouskela et al.

    Spontaneous vasomotion in hamster cheek pouch arterioles in varying experimental conditions

    Am. J. Physiol. Heart Circ. Physiol.

    (1992)
  • R.L. Buckner et al.

    The brain's default network

    Ann. N. Y. Acad. Sci.

    (2008)
  • R.L. Buckner et al.

    Cortical hubs revealed by intrinsic functional connectivity: mapping, assessment of stability, and relation to Alzheimer's disease

    J. Neurosci.

    (2009)
  • P.J. Drew et al.

    Finding coherence in spontaneous oscillations

    Nat. Neurosci.

    (2008)
  • C.E. Elwell et al.

    Oscillations in cerebral haemodynamics. Implications for functional activation studies

    Adv. Exp. Med. Biol.

    (1999)
  • A. Farin et al.

    Transplanted glioma cells migrate and proliferate on host brain vasculature: a dynamic analysis

    Glia

    (2006)
  • M.D. Fox et al.

    Spontaneous fluctuations in brain activity observed with functional magnetic resonance imaging

    Nat. Rev. Neurosci.

    (2007)
  • M.D. Fox et al.

    The human brain is intrinsically organized into dynamic, anticorrelated functional networks

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

    (2005)
  • K. Fujii et al.

    Vasomotion of basilar arteries in vivo

    Am. J. Physiol. Heart Circ. Physiol.

    (1990)
  • A.G. Garrity et al.

    Aberrant “default mode” functional connectivity in schizophrenia

    Am. J. Psychiatr.

    (2007)
  • E.V. Golanov et al.

    Spontaneous waves of cerebral blood flow associated with a pattern of electrocortical activity

    Am. J. Physiol. Regul. Integr. Comp. Physiol.

    (1994)
  • C. Grefkes et al.

    Reorganization of cerebral networks after stroke: new insights from neuroimaging with connectivity approaches

    Brain

    (2011)
  • L.E. Grosberg et al.

    Simultaneous multiplane in vivo nonlinear microscopy using spectral encoding

    Opt. Lett.

    (2012)
  • R.E. Haddock et al.

    Rhythmicity in arterial smooth muscle

    J. Physiol.

    (2005)
  • R.E. Haddock et al.

    Voltage independence of vasomotion in isolated irideal arterioles of the rat

    J. Physiol.

    (2002)
  • M.M. Haglund et al.

    Optical imaging of epileptiform activity in human neocortex

    Epilepsia

    (2004)
  • M.M. Haglund et al.

    Optical imaging of epileptiform and functional activity in human cerebral cortex

    Nature

    (1992)
  • Cited by (62)

    • Multimodal methods to help interpret resting-state fMRI

      2023, Advances in Resting-State Functional MRI: Methods, Interpretation, and Applications
    • Interactions between stimuli-evoked cortical activity and spontaneous low frequency oscillations measured with neuronal calcium

      2020, NeuroImage
      Citation Excerpt :

      They also confirm that the phase of the ongoing activity can impact the level of stimulus-evoked responses, making it possible that the state of the brain can impact detectability and performance in noisy situations. Spontaneous cerebral hemodynamic fluctuations and neuronal oscillations have been observed in BOLD signals (Fransson, 2005), HbO2/HbR/Ca2+ fluctuations (Du et al., 2014; Rayshubskiy et al., 2014) and local field potentials (Buzsaki and Draguhn, 2004; Obrig et al., 2000; Rayshubskiy et al., 2014). It is now widely accepted that cerebral hemodynamic oscillations of ~0.04–0.1 ​Hz reflect underlying neuronal activity (Auer, 2008; Du et al., 2014; Fox and Raichle, 2007; Ma et al., 2016b; Tong and Frederick, 2010; Wright et al., 2017; Xie et al., 2016).

    • Vasomotion as a Driving Force for Paravascular Clearance in the Awake Mouse Brain

      2020, Neuron
      Citation Excerpt :

      Early experimental studies have demonstrated that the rhythmic low-frequency contractile activity of arteries is driven by membrane calcium and potassium conductance and can be modulated (e.g., with nitric oxide, anesthesia) (Osol and Halpern, 1988; Dirnagl et al., 1993). Evidence that vasomotion occurs in humans comes from the observation of ultra-slow hemodynamic oscillations centered at around ∼0.1 Hz in pial surface vessels during brain-exposed surgical interventions (Rayshubskiy et al., 2014; Noordmans et al., 2018). More recently, it has been suggested that spontaneous vasomotion is the underlying principle of the resting-state blood oxygen level-dependent (BOLD) signal in fMRI studies in rodents (Mateo et al., 2017; He et al., 2018).

    View all citing articles on Scopus
    View full text