Direct, intraoperative observation of ~ 0.1 Hz hemodynamic oscillations in awake human cortex: Implications for fMRI
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
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2020, NeuroImageCitation 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, NeuronCitation 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).