A Novel, Cardiac-Derived Algorithm for Uterine Activity Monitoring in a Wearable Remote Device.

Background: Uterine activity (UA) monitoring is an essential element of pregnancy management. The gold-standard intrauterine pressure catheter (IUPC) is invasive and requires ruptured membranes, while the standard-of-care, external tocodynamometry (TOCO)'s accuracy is hampered by obesity, maternal movements, and belt positioning. There is an urgent need to develop telehealth tools enabling patients to remotely access care. Here, we describe and demonstrate a novel algorithm enabling remote, non-invasive detection and monitoring of UA by analyzing the modulation of the maternal electrocardiographic and phonocardiographic signals. The algorithm was designed and implemented as part of a wireless, FDA-cleared device designed for remote pregnancy monitoring. Two separate prospective, comparative, open-label, multi-center studies were conducted to test this algorithm. Methods: In the intrapartum study, 41 laboring women were simultaneously monitored with IUPC and the remote pregnancy monitoring device. Ten patients were also monitored with TOCO. In the antepartum study, 147 pregnant women were simultaneously monitored with TOCO and the remote pregnancy monitoring device. Results: In the intrapartum study, the remote pregnancy monitoring device and TOCO had sensitivities of 89.8 and 38.5%, respectively, and false discovery rates (FDRs) of 8.6 and 1.9%, respectively. In the antepartum study, a direct comparison of the remote pregnancy monitoring device to TOCO yielded a sensitivity of 94% and FDR of 31.1%. This high FDR is likely related to the low sensitivity of TOCO. Conclusion: UA monitoring via the new algorithm embedded in the remote pregnancy monitoring device is accurate and reliable and more precise than TOCO standard of care. Together with the previously reported remote fetal heart rate monitoring capabilities, this novel method for UA detection expands the remote pregnancy monitoring device's capabilities to include surveillance, such as non-stress tests, greatly benefiting women and providers seeking telehealth solutions for pregnancy care.

Non-Sinusoidal Activity Can Produce Cross-Frequency Coupling in Cortical Signals in the Absence of Functional Interaction between Neural Sources.

The analysis of cross-frequency coupling (CFC) has become popular in studies involving intracranial and scalp EEG recordings in humans. It has been argued that some cases where CFC is mathematically present may not reflect an interaction of two distinct yet functionally coupled neural sources with different frequencies. Here we provide two empirical examples from intracranial recordings where CFC can be shown to be driven by the shape of a periodic waveform rather than by a functional interaction between distinct sources. Using simulations, we also present a generalized and realistic scenario where such coupling may arise. This scenario, which we term waveform-dependent CFC, arises when sharp waveforms (e.g., cortical potentials) occur throughout parts of the data, in particular if they occur rhythmically. Since the waveforms contain both low- and high-frequency components, these components can be inherently phase-aligned as long as the waveforms are spaced with appropriate intervals. We submit that such behavior of the data, which seems to be present in various cortical signals, cannot be interpreted as reflecting functional modulation between distinct neural sources without additional evidence. In addition, we show that even low amplitude periodic potentials that cannot be readily observed or controlled for, are sufficient for significant CFC to occur.

Extracting visual evoked potentials from EEG data recorded during fMRI-guided transcranial magnetic stimulation.

Transcranial Magnetic Stimulation (TMS) is an effective method for establishing a causal link between a cortical area and cognitive/neurophysiological effects. Specifically, by creating a transient interference with the normal activity of a target region and measuring changes in an electrophysiological signal, we can establish a causal link between the stimulated brain area or network and the electrophysiological signal that we record. If target brain areas are functionally defined with prior fMRI scan, TMS could be used to link the fMRI activations with evoked potentials recorded. However, conducting such experiments presents significant technical challenges given the high amplitude artifacts introduced into the EEG signal by the magnetic pulse, and the difficulty to successfully target areas that were functionally defined by fMRI. Here we describe a methodology for combining these three common tools: TMS, EEG, and fMRI. We explain how to guide the stimulator's coil to the desired target area using anatomical or functional MRI data, how to record EEG during concurrent TMS, how to design an ERP study suitable for EEG-TMS combination and how to extract reliable ERP from the recorded data. We will provide representative results from a previously published study, in which fMRI-guided TMS was used concurrently with EEG to show that the face-selective N1 and the body-selective N1 component of the ERP are associated with distinct neural networks in extrastriate cortex. This method allows us to combine the high spatial resolution of fMRI with the high temporal resolution of TMS and EEG and therefore obtain a comprehensive understanding of the neural basis of various cognitive processes.

An integrated face-body representation in the fusiform gyrus but not the lateral occipital cortex.

Faces and bodies are processed by distinct category-selective brain areas. Neuroimaging studies have so far presented isolated faces and headless bodies, and therefore little is known on whether and where faces and headless bodies are grouped together to one object, as they appear in the real world. The current study examined whether a face presented above a body are represented as two separate images or as an integrated face-body representation in face and body-selective brain areas by employing a fMRI competition paradigm. This paradigm has been shown to reveal higher fMRI response to sequential than simultaneous presentation of multiple stimuli (i.e., the competition effect), indicating competitive interactions among simultaneously presented multiple stimuli. We therefore hypothesized that if a face above a body is integrated to an image of a person whereas a body above a face is represented as two separate objects, the competition effect will be larger for the latter than the former. Consistent with our hypothesis, our findings reveal a competition effect when a body is presented above a face, but not when a face is presented above a body, suggesting that a body above a face is represented as two separate objects whereas a face above a body is represented as an integrated image of a person. Interestingly, this integration of a face and a body to an image of a person was found in the fusiform, but not the lateral-occipital face and body areas. We conclude that faces and bodies are processed separately at early stages and are integrated to a unified image of a person at mid-level stages of object processing.

Stimulation of category-selective brain areas modulates ERP to their preferred categories.

Neural selectivity to specific object categories has been demonstrated in extrastriate cortex with both functional MRI [1-3] and event-related potential (ERP) [4, 5]. Here we tested for a causal relationship between the activation of category-selective areas and ERP to their preferred categories. Electroencephalogram (EEG) was recorded while participants observed faces and headless bodies. Concurrently with EEG recording, we delivered two pulses of transcranial magnetic stimulation (TMS) over the right occipital face area (OFA) or extrastriate body area (EBA) at 60 and 100 ms after stimulus onset. Results showed a clear dissociation between the stimulated site and the stimulus category on ERP modulation: stimulation of the OFA significantly increased the N1 amplitude to faces but not to bodies, whereas stimulation of the EBA significantly increased the N1 amplitude to bodies but not to faces. These findings provide the first evidence for a specific and causal link between activity in category-selective networks and scalp-recorded ERP to their preferred categories. This result also demonstrates that the face and body N1 reflects several nonoverlapping neural sources, rather than changes in face-selective mechanisms alone. Lastly, because early stimulation (60-100 ms) affected selectivity of a later ERP component (150-200 ms), the results could imply a feed-forward connection between occipital and temporal category-selective areas.

Why is the N170 enhanced for inverted faces? An ERP competition experiment.

The amplitude of the ERP component N170 is larger in response to inverted than to upright faces. The current study tested two main hypotheses that have been suggested to explain this effect: according to the first hypothesis inverted faces lead to augmentation of activity of the same neural populations used for the processing of upright faces due to the increased processing difficulty that these stimuli impose; according to the second hypothesis the processing of inverted faces involves recruitment of additional neural mechanisms to those used for upright face processing. We employed an ERP competition paradigm in which the effect of a context stimulus on the ERP to a simultaneously presented target stimulus is measured. In Experiment 1, an upright target face was paired with an upright face, inverted face or a non-face context stimulus. ERPs time-locked to the presentation of the target showed reduced N170 amplitude when the context was an upright face more than in non-face context trials, replicating the ERP competition effect for faces. Interestingly, in contrast to the hypothesis that inverted faces recruit mechanisms used for upright faces to a greater extent, competition effects were similar in the context of inverted and upright faces. In Experiment 2, the target stimuli were inverted faces. This time, competition effect was larger in inverted than in upright face context. Taken together, these findings correspond with the hypothesis that inversion of the face leads to recruitment of additional mechanisms as early as at the N170 time-window.

Event-related potential and functional MRI measures of face-selectivity are highly correlated: a simultaneous ERP-fMRI investigation.

A face-selective neural signal is reliably found in humans with functional MRI and event-related potential (ERP) measures, which provide complementary information about the spatial and temporal properties of the neural response. However, because most neuroimaging studies so far have studied ERP and fMRI face-selective markers separately, the relationship between them is still unknown. Here we simultaneously recorded fMRI and ERP responses to faces and chairs to examine the correlations across subjects between the magnitudes of fMRI and ERP face-selectivity measures. Findings show that the face-selective responses in the temporal lobe (i.e., fusiform gyrus--FFA) and superior temporal sulcus (fSTS), but not the face-selective response in the occipital cortex (OFA), were highly correlated with the face-selective N170 component. In contrast, the OFA was correlated with earlier ERPs at about 110 ms after stimulus-onset. Importantly, these correlations reveal a temporal dissociation between the face-selective area in the occipital lobe and face-selective areas in the temporal lobe. Despite the very different time-scale of the fMRI and EEG signals, our data show that a correlation analysis across subjects may be informative with respect to the latency in which different brain regions process information.

The validity of the face-selective ERP N170 component during simultaneous recording with functional MRI.

Despite the wide interest in the neural mechanisms of face processing and numerous event-related potential (ERP) and functional MRI (fMRI) studies of face-selective neural responses, no study, to date, has collected these two measures simultaneously. The main reason for the absence of such an investigation is that MRI data acquisition generates major artifacts, which completely conceals the EEG signal. Recently, artifact removal algorithms have been developed. Our goal was to examine the validity of the face-selective ERP component N170 and its functional effects such as category selectivity and hemispherical laterality, when recorded simultaneously with functional MRI. In our experiment, half of the scans were collected during fMRI acquisition and half without fMRI acquisition. The validity of the N170 was then measured for its amplitude, latency, face selectivity (the difference between the amplitude to faces and objects), laterality (the difference between the amplitude to faces over the right and the left hemispheres) and the laterality of the face selectivity effect, by correlating these measures across subjects between data collected without fMRI and with fMRI data acquisition, after applying artifact removal procedures. We found high validity coefficients for all N170 measures. Furthermore, ERP data collected outside the scanner on a different day were highly correlated with data collected during MR acquisition for the N170 amplitude, latency, and selectivity index but moderate for laterality indices. Our study demonstrates that face-selective ERP effects are preserved in simultaneous recording with fMRI. These findings will hopefully encourage researchers to combine the two complementary neuroimaging techniques in future research.