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Measuring brain beats: cardiac-aligned fast fMRI signals [article]

Dora Hermes, Hua Wu, Adam B Kerr, Brian Wandell
2022 bioRxiv   pre-print
Blood and cerebrospinal fluid (CSF) pulse and flow throughout the brain, driven by the cardiac cycle. These fluid dynamics, which are essential to healthy brain function, are characterized by several noninvasive magnetic resonance imaging (MRI) methods. Recent developments in fast MRI, specifically simultaneous multislice (SMS) acquisition methods, provide a new opportunity to rapidly and broadly assess cardiac-driven flow, including CSF spaces, surface vessels and parenchymal vessels. We use
more » ... ese techniques to assess blood and CSF flow dynamics in brief (3.5 minute) scans on a conventional 3T MRI scanner. Cardiac pulses are measured with a photoplethysmograph (PPG) on the index finger, along with fMRI signals in the brain. We retrospectively analyze the fMRI signals gated to the heart beat. Highly reliable cardiac-gated fMRI temporal signals are observed in CSF and blood on the timescale of one heartbeat (test-retest reliability within subjects R2>0.50). Cardiac pulsations with a local minimum following systole are observed in blood vessels, with earlier extrema in the carotid and basilar arteries and in branches of the anterior, posterior and middle cerebral arteries and extrema ~200 ms later in the superior sagittal, transverse and straight sinuses. CSF spaces in the ventricles and subarachnoid space showed cardiac pulsations with a local maximum following systole instead. Similar responses are observed, with less temporal detail, in slower resting state scans with slice timing retrospectively aligned to the cardiac pulse in the same manner. The SMS measurements rapidly, noninvasively and reliably sample brain-wide fMRI signal pulsations aligned to the heartbeat. The measurements estimate the amplitude and phase of cardiac driven fMRI pulsations in the CSF relative to those in the arteries, which is thought to be an estimate of the local intracranial impedance. Cardiac aligned fMRI signals can provide new insights about fluid dynamics or diagnostics for diseases where these dynamics are important.
doi:10.1101/2022.02.18.480957 fatcat:5w2m4q2rnfcofa2i2lfib6laam

Gamma oscillations and photosensitive epilepsy

Dora Hermes, Dorothée G.A. Kasteleijn-Nolst Trenité, Jonathan Winawer
2017 Current Biology  
Hermes et al.  ... 
doi:10.1016/j.cub.2017.03.076 pmid:28486114 pmcid:PMC5438467 fatcat:wdldrmiwifeqro737ywbo76iwm

An image-computable model for the stimulus selectivity of gamma oscillations [article]

Dora Hermes, Natalia Petridou, Kendrick Kay, Jonathan Winawer
2019 bioRxiv   pre-print
( Butler et al., 2017; 520 Hermes et al., 2017b; Krusienski et al., 2011; Winawer et al., 2013).  ...  Some images of scenes 62 and objects cause large reliable gamma oscillations while others do not (Brunet et 63 al., 2015; Hermes et al., 2015).  ... 
doi:10.1101/583567 fatcat:bdmaz4ygmbcynlbcdetgguihrq

Neuronal synchrony and the relation between the BOLD response and the local field potential [article]

Dora Hermes, Mai Nguyen, Jonathan Winawer
2016 bioRxiv   pre-print
The most widespread measures of human brain activity are the blood oxygen level dependent (BOLD) signal and surface field potential. Prior studies report a variety of relationships between these signals. To develop an understanding of how to interpret these signals and the relationship between them, we developed a model of (a) neuronal population responses, and (b) transformations from neuronal responses into the fMRI BOLD signal and electrocorticographic (ECoG) field potential. Rather than
more » ... ing a transformation between the two measures directly, this approach interprets each measure with respect to the underlying neuronal population responses. This model accounts for the relationship between BOLD and ECoG data from human visual cortex in V1-V3, with the model predictions and data matching in three ways: Across stimuli, the BOLD amplitude and ECoG broadband power were positively correlated, the BOLD amplitude and alpha power (8-13 Hz) were negatively correlated, and the BOLD amplitude and narrowband gamma power (30-80 Hz) were uncorrelated. The two measures provide complementary information about human brain activity and we infer that features of the field potential that are uncorrelated with BOLD arise largely from changes in synchrony, rather than level, of neuronal activity.
doi:10.1101/083840 fatcat:wm2pqyqqbzc63etwgjxjm7xhmy

Gamma Power Is Phase-Locked to Posterior Alpha Activity

Daria Osipova, Dora Hermes, Ole Jensen, Aldo Rustichini
2008 PLoS ONE  
Neuronal oscillations in various frequency bands have been reported in numerous studies in both humans and animals. While it is obvious that these oscillations play an important role in cognitive processing, it remains unclear how oscillations in various frequency bands interact. In this study we have investigated phase to power locking in MEG activity of healthy human subjects at rest with their eyes closed. To examine cross-frequency coupling, we have computed coherence between the time
more » ... of the power in a given frequency band and the signal itself within every channel. The time-course of the power was calculated using a sliding tapered time window followed by a Fourier transform. Our findings show that high-frequency gamma power (30-70 Hz) is phase-locked to alpha oscillations (8-13 Hz) in the ongoing MEG signals. The topography of the coupling was similar to the topography of the alpha power and was strongest over occipital areas. Interestingly, gamma activity per se was not evident in the power spectra and only became detectable when studied in relation to the alpha phase. Intracranial data from an epileptic subject confirmed these findings albeit there was slowing in both the alpha and gamma band. A tentative explanation for this phenomenon is that the visual system is inhibited during most of the alpha cycle whereas a burst of gamma activity at a specific alpha phase (e.g. at troughs) reflects a window of excitability.
doi:10.1371/journal.pone.0003990 pmid:19098986 pmcid:PMC2602598 fatcat:vpvwb7og6zg57ar7ic6rffk6oy

The current state of electrocorticography-based brain–computer interfaces

Kai J. Miller, Dora Hermes, Nathan P. Staff
2020 Neurosurgical Focus  
Brain–computer interfaces (BCIs) provide a way for the brain to interface directly with a computer. Many different brain signals can be used to control a device, varying in ease of recording, reliability, stability, temporal and spatial resolution, and noise. Electrocorticography (ECoG) electrodes provide a highly reliable signal from the human brain surface, and these signals have been used to decode movements, vision, and speech. ECoG-based BCIs are being developed to provide increased
more » ... for treatment and assistive devices for patients who have functional limitations. Decoding ECoG signals in real time provides direct feedback to the patient and can be used to control a cursor on a computer or an exoskeleton. In this review, the authors describe the current state of ECoG-based BCIs that are approaching clinical viability for restoring lost communication and motor function in patients with amyotrophic lateral sclerosis or tetraplegia. These studies provide a proof of principle and the possibility that ECoG-based BCI technology may also be useful in the future for assisting in the cortical rehabilitation of patients who have suffered a stroke.
doi:10.3171/2020.4.focus20185 pmid:32610290 fatcat:bujpqgcuonektenv7jcydmke5y

An image-computable model for the stimulus selectivity of gamma oscillations

Dora Hermes, Natalia Petridou, Kendrick N Kay, Jonathan Winawer
2019 eLife  
., 2015; Hermes et al., 2015) .  ...  Code to reproduce this figure can be found on GitHub (Hermes, 2019) . (Hermes et al., 2015; Kayser et al., 2003) .  ... 
doi:10.7554/elife.47035 pmid:31702552 pmcid:PMC6839904 fatcat:lxv3rcyx6veohhsqoysfwv6jri

Basis profile curve identification to understand electrical stimulation effects in human brain networks [article]

Kai Joshua Miller, Klaus-Robert M&uumlller, Dora Hermes
2021 bioRxiv   pre-print
Brain networks can be explored by delivering brief pulses of electrical current in one area while measuring voltage responses in other areas. We propose a convergent paradigm to study brain dynamics, focusing on a single brain site to observe the average effect of stimulating each of many other brain sites. Viewed in this manner, visually-apparent motifs in the temporal response shape emerge from adjacent stimulation sites. This work constructs and illustrates a data-driven approach to
more » ... characteristic spatiotemporal structure in these response shapes, summarized by a set of unique "basis profile curves" (BPCs). Each BPC may be mapped back to underlying anatomy in a natural way, quantifying projection strength from each stimulation site using simple metrics. Our technique is demonstrated for an array of implanted brain surface electrodes in a human patient. This framework enables straightforward interpretation of single-pulse brain stimulation data, and can be applied generically to explore the diverse milieu of interactions that comprise the connectome.
doi:10.1101/2021.01.24.428020 fatcat:vqejs6tntfbspdww2tnzciplyy

Face percept formation in human ventral temporal cortex

Kai J. Miller, Dora Hermes, Franco Pestilli, Gagan S. Wig, Jeffrey G. Ojemann
2017 Journal of Neurophysiology  
Hermes), and NIMH ULTTR001108 (F. Pestilli) and National Science Foundation (NSF) Awards EEC-1028725 (Center for Sensorimotor Neural Engineering), IIS-1636893 (F. Pestilli), and BCS-1734853 (F.  ...  Electrode positions were calculated with respect to the structural MRI from postoperative CT using the CTMR package and FreeSurfer-rendered cortical reconstructions (Dale et al. 1999; Hermes et al. 2010  ... 
doi:10.1152/jn.00113.2017 pmid:28814631 fatcat:pgnqznzmqbgmbl4mtsyzfyyrnq

Gamma oscillations in visual cortex: the stimulus matters

Dora Hermes, Kai J. Miller, Brian A. Wandell, Jonathan Winawer
2015 Trends in Cognitive Sciences  
doi:10.1016/j.tics.2014.12.009 pmid:25575448 pmcid:PMC4395850 fatcat:s27yqn3qnfawpoeewrcjtrgf7i

A practical workflow for organizing clinical intraoperative and long-term iEEG data in BIDS [article]

Matteo Demuru, Dorien van Blooijs, Willemiek Zweiphenning, Dora Hermes, Frans Leijten, Maeike Zijlmans
2020 medRxiv   pre-print
The code ( ) to do this was adapted from Hermes et al. 15 and Branco et al. 16 .  ... 
doi:10.1101/2020.12.07.20245290 fatcat:jn6x33qh6jggpmh2ar25wj62ne

Functional MRI based simulations of ECoG grid configurations for optimal measurement of spatially distributed hand-gesture information [article]

Max A van den Boom, Kai J. Miller, Nick F. Ramsey, Dora Hermes
2020 bioRxiv   pre-print
power increase across conditions (Winawer et al. 2013; Jacques et al. 2016; Hermes et al. 2017) .  ...  Recent research has shown that the ECoG HFB signal correlates well with the BOLD response at the standard clinical scale (Hermes et al. 2012) , that the millimeter scale finger representations found in  ... 
doi:10.1101/2020.12.27.424363 fatcat:dabfwt5yabe6baiiokbymxrwba

Basis profile curve identification to understand electrical stimulation effects in human brain networks

Kai J. Miller, Klaus-Robert Müller, Dora Hermes, Marieke Karlijn van Vugt
2021 PLoS Computational Biology  
Miller, Klaus-Robert Müller, Dora Hermes. 1 . 1 First, elements of H are individually scaled according to: H qm 7 !H qm ðW > ΞÞ qm ðW > WHÞ qm 2.  ... 
doi:10.1371/journal.pcbi.1008710 pmid:34473701 pmcid:PMC8412306 fatcat:bb7a6sef6ze5pnacpydkihdk6y

Late Repair of Abductor Avulsion After the Transgluteal Approach for Hip Arthroplasty

Hermes H. Miozzari, Claudio Dora, John M. Clark, Hubert P. Nötzli
2010 Journal of Arthroplasty  
The Journal of Arthroplasty Vol. 25 No. 3 2010 Late Repair of Abductor Avulsion After the Transgluteal Approach for Hip Arthroplasty Hermes H. Miozzari, MD,* Claudio Dora, MD, } John M.  ... 
doi:10.1016/j.arth.2008.12.010 pmid:19282140 fatcat:tfil7qrngbg47p7y2hfpfaabku

Electrophysiological Responses in the Ventral Temporal Cortex During Reading of Numerals and Calculation

Dora Hermes, Vinitha Rangarajan, Brett L. Foster, Jean-Remi King, Itir Kasikci, Kai J. Miller, Josef Parvizi
2015 Cerebral Cortex  
Electrodes were localized from the CT scan and visualized on the MRI with an accuracy of ±5 mm (median 2.6 mm) as described previously (Hermes et al. 2010) .  ...  ECoG signal is tightly coupled to the population firing rate (Manning et al. 2009; Miller et al. 2009; Ray and Maunsell 2011) and fMRI BOLD responses (Logothetis et al. 2001; Lachaux et al. 2007; Hermes  ... 
doi:10.1093/cercor/bhv250 pmid:26503267 pmcid:PMC5939218 fatcat:xg56ddiapzewtlxwjwmvhekdfi
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