Visual Stimuli Modulate Local Field Potentials But Drive No High-Frequency Activity in Human Auditory Cortex.

Neuroimaging studies suggest cross-sensory visual influences in human auditory cortices (ACs). Whether these influences reflect active visual processing in human ACs, which drives neuronal firing and concurrent broadband high-frequency activity (BHFA; >70 Hz), or whether they merely modulate sound processing is still debatable. Here, we presented auditory, visual, and audiovisual stimuli to 16 participants (7 women, 9 men) with stereo-EEG depth electrodes implanted near ACs for presurgical monitoring. Anatomically normalized group analyses were facilitated by inverse modeling of intracranial source currents. Analyses of intracranial event-related potentials (iERPs) suggested cross-sensory responses to visual stimuli in ACs, which lagged the earliest auditory responses by several tens of milliseconds. Visual stimuli also modulated the phase of intrinsic low-frequency oscillations and triggered 15-30 Hz event-related desynchronization in ACs. However, BHFA, a putative correlate of neuronal firing, was not significantly increased in ACs after visual stimuli, not even when they coincided with auditory stimuli. Intracranial recordings demonstrate cross-sensory modulations, but no indication of active visual processing in human ACs.

Ballistocardiogram suppression in concurrent EEG-MRI by dynamic modeling of heartbeats.

The ballistocardiogram (BCG), the induced electric potentials by the head motion originating from heartbeats, is a prominent source of noise in electroencephalography (EEG) data during magnetic resonance imaging (MRI). Although methods have been proposed to suppress the BCG artifact, more work considering the variability of cardiac cycles and head motion across time and subjects is needed to provide highly robust correction. Here, a method called "dynamic modeling of heartbeats" (DMH) is proposed to reduce BCG artifacts in EEG data recorded inside an MRI system. The DMH method models BCG artifacts by combining EEG points at time instants with similar dynamics. The modeled BCG artifact is then subtracted from the EEG recording to suppress the BCG artifact. Performance of DMH was tested and specifically compared with the Optimal Basis Set (OBS) method on EEG data recorded inside a 3T MRI system with either no MRI acquisition (Inside-MRI), echo-planar imaging (EPI-EEG), or fast MRI acquisition using simultaneous multi-slice and inverse imaging methods (SMS-InI-EEG). In a steady-state visual evoked response (SSVEP) paradigm, the 15-Hz oscillatory neuronal activity at the visual cortex after DMH processing was about 130% of that achieved by OBS processing for Inside-MRI, SMS-InI-EEG, and EPI-EEG conditions. The DMH method is computationally efficient for suppressing BCG artifacts and in the future may help to improve the quality of EEG data recorded in high-field MRI systems for neuroscientific and clinical applications.

Distributed source modeling of intracranial stereoelectro-encephalographic measurements.

Intracranial stereoelectroencephalography (sEEG) provides unsurpassed sensitivity and specificity for human neurophysiology. However, functional mapping of brain functions has been limited because the implantations have sparse coverage and differ greatly across individuals. Here, we developed a distributed, anatomically realistic sEEG source-modeling approach for within- and between-subject analyses. In addition to intracranial event-related potentials (iERP), we estimated the sources of high broadband gamma activity (HBBG), a putative correlate of local neural firing. Our novel approach accounted for a significant portion of the variance of the sEEG measurements in leave-one-out cross-validation. After logarithmic transformations, the sensitivity and signal-to-noise ratio were linearly inversely related to the minimal distance between the brain location and electrode contacts (slope≈-3.6). The signa-to-noise ratio and sensitivity in the thalamus and brain stem were comparable to those locations at the vicinity of electrode contact implantation. The HGGB source estimates were remarkably consistent with analyses of intracranial-contact data. In conclusion, distributed sEEG source modeling provides a powerful neuroimaging tool, which facilitates anatomically-normalized functional mapping of human brain using both iERP and HBBG data.

Concurrent electrophysiological and hemodynamic measurements of evoked neural oscillations in human visual cortex using sparsely interleaved fast fMRI and EEG.

Electroencephalography (EEG) concurrently collected with functional magnetic resonance imaging (fMRI) is heavily distorted by the repetitive gradient coil switching during the fMRI acquisition. The performance of the typical template-based gradient artifact suppression method can be suboptimal because the artifact changes over time. Gradient artifact residuals also impede the subsequent suppression of ballistocardiography artifacts. Here we propose recording continuous EEG with temporally sparse fast fMRI (fast fMRI-EEG) to minimize the EEG artifacts caused by MRI gradient coil switching without significantly compromising the field-of-view and spatiotemporal resolution of fMRI. Using simultaneous multi-slice inverse imaging to achieve whole-brain fMRI with isotropic 5-mm resolution in 0.1 â€‹s, and performing these acquisitions once every 2 â€‹s, we have 95% of the duty cycle available to record EEG with substantially less gradient artifact. We found that the standard deviation of EEG signals over the entire acquisition period in fast fMRI-EEG was reduced to 54% of that in conventional concurrent echo-planar imaging (EPI) and EEG recordings (EPI-EEG) across participants. When measuring 15-Hz steady-state visual evoked potentials (SSVEPs), the baseline-normalized oscillatory neural response in fast fMRI-EEG was 2.5-fold of that in EPI-EEG. The functional MRI responses associated with the SSVEP delineated by EPI and fast fMRI were similar in the spatial distribution, the elicited waveform, and detection power. Sparsely interleaved fast fMRI-EEG provides high-quality EEG without substantially compromising the quality of fMRI in evoked response measurements, and has the potential utility for applications where the onset of the target stimulus cannot be precisely determined, such as epilepsy.

Why Do Irrelevant Alternatives Matter? An fMRI-TMS Study of Context-Dependent Preferences.

Both humans and animals are known to exhibit a violation of rationality known as "decoy effect": introducing an irrelevant option (a decoy) can influence choices among other (relevant) options. Exactly how and why decoys trigger this effect is not known. It may be an example of fast heuristic decision-making, which is adaptive in natural environments, but may lead to biased choices in certain markets or experiments. We used fMRI and transcranial magnetic stimulation to investigate the neural underpinning of the decoy effect of both sexes. The left ventral striatum was more active when the chosen option dominated the decoy. This is consistent with the hypothesis that the presence of a decoy option influences the valuation of other options, making valuation context-dependent even when choices appear fully rational. Consistent with the idea that control is recruited to prevent heuristics from producing biased choices, the right inferior frontal gyrus, often implicated in inhibiting prepotent responses, connected more strongly with the striatum when subjects successfully overrode the decoy effect and made unbiased choices. This is further supported by our transcranial magnetic stimulation experiment: subjects whose right inferior frontal gyrus was temporarily disrupted made biased choices more often than a control group. Our results suggest that the neural basis of the decoy effect could be the context-dependent activation of the valuation area. But the differential connectivity from the frontal area may indicate how deliberate control monitors and corrects errors and biases in decision-making.SIGNIFICANCE STATEMENT Standard theories of rational decision-making assume context-independent valuations of available options. Motivated by the importance of this basic assumption, we used fMRI to study how the human brain assigns values to available options. We found activity in the valuation area to be consistent with the hypothesis that values depend on irrelevant aspects of the environment, even for subjects whose choices appear fully rational. Such context-dependent valuations may lead to biased decision-making. We further found differential connectivity from the frontal area to the valuation area depending on whether biases were successfully overcome. This suggests a mechanism for making rational choices despite the potential bias. Further support was obtained by a transcranial magnetic stimulation experiment, where subjects whose frontal control was temporarily disrupted made biased choices more often than a control group.

Relative latency and temporal variability of hemodynamic responses at the human primary visual cortex.

The blood-oxygen-level-dependent (BOLD) functional MRI (fMRI) signal is a robust surrogate for local neuronal activity. However, it has been shown to vary substantially across subjects, brain regions, and repetitive measurements. This variability represents a limit to the precision of the BOLD response and the ability to reliably discriminate brain hemodynamic responses elicited by external stimuli or behavior that are nearby in time. While the temporal variability of the BOLD signal at human visual cortex has been found in the range of a few hundreds of milliseconds, the spatial distributions of the average and standard deviation of this temporal variability have not been quantitatively characterized. Here we use fMRI measurements with a high sampling rate (10Hz) to map the latency, intra- and inter-subject variability of the evoked BOLD signal in human primary (V1) visual cortices using an event-related fMRI paradigm. The latency relative to the average BOLD signal evoked by 30 stimuli was estimated to be 0.03±0.20s. Within V1, the absolute value of the relative BOLD latency was found correlated to intra- and inter-subject temporal variability. After comparing these measures to retinotopic maps, we found that locations with V1 areas sensitive to smaller eccentricity have later responses and smaller inter-subject variabilities. These correlations were found from data with either short inter-stimulus interval (ISI; average 4s) or long ISI (average 30s). Maps of the relative latency as well as inter-/intra-subject variability were found visually asymmetric between hemispheres. Our results suggest that the latency and variability of regional BOLD signal measured with high spatiotemporal resolution may be used to detect regional differences in hemodynamics to inform fMRI studies. However, the physiological origins of timing index distributions and their hemispheric asymmetry remain to be investigated.

Universal brain signature of proficient reading: Evidence from four contrasting languages.

We propose and test a theoretical perspective in which a universal hallmark of successful literacy acquisition is the convergence of the speech and orthographic processing systems onto a common network of neural structures, regardless of how spoken words are represented orthographically in a writing system. During functional MRI, skilled adult readers of four distinct and highly contrasting languages, Spanish, English, Hebrew, and Chinese, performed an identical semantic categorization task to spoken and written words. Results from three complementary analytic approaches demonstrate limited language variation, with speech-print convergence emerging as a common brain signature of reading proficiency across the wide spectrum of selected languages, whether their writing system is alphabetic or logographic, whether it is opaque or transparent, and regardless of the phonological and morphological structure it represents.

Significant feed-forward connectivity revealed by high frequency components of BOLD fMRI signals.

Granger causality analysis has been suggested as a method of estimating causal modulation without specifying the direction of information flow a priori. Using BOLD-contrast functional MRI (fMRI) data, such analysis has been typically implemented in the time domain. In this study, we used magnetic resonance inverse imaging, a method of fast fMRI enabled by massively parallel detection allowing up to 10 Hz sampling rate, to investigate the causal modulation at different frequencies up to 5 Hz. Using a visuomotor two-choice reaction-time task, both the spectral decomposition of Granger causality and isolated effective coherence revealed that the BOLD signal at frequency up to 3 Hz can still be used to estimate significant dominant directions of information flow consistent with results from the time-domain Granger causality analysis. We showed the specificity of estimated dominant directions of information flow at high frequencies by contrasting causality estimates using data collected during the visuomotor task and resting state. Our data suggest that hemodynamic responses carry physiological information related to inter-regional modulation at frequency higher than what has been commonly considered.

Combining parallel detection of proton echo planar spectroscopic imaging (PEPSI) measurements with a data-consistency constraint improves SNR.

One major challenge of MRSI is the poor signal-to-noise ratio (SNR), which can be improved by using a surface coil array. Here we propose to exploit the spatial sensitivity of different channels of a coil array to enforce the k-space data consistency (DC) in order to suppress noise and consequently to improve MRSI SNR. MRSI data were collected using a proton echo planar spectroscopic imaging (PEPSI) sequence at 3 T using a 32-channel coil array and were averaged with one, two and eight measurements (avg-1, avg-2 and avg-8). The DC constraint was applied using a regularization parameter λ of 1, 2, 3, 5 or 10. Metabolite concentrations were quantified using LCModel. Our results show that the suppression of noise by applying the DC constraint to PEPSI reconstruction yields up to 32% and 27% SNR gain for avg-1 and avg-2 data with λ = 5, respectively. According to the reported Cramer-Rao lower bounds, the improvement in metabolic fitting was significant (p < 0.01) when the DC constraint was applied with λ ≥ 2. Using the DC constraint with λ = 3 or 5 can minimize both root-mean-square errors and spatial variation for all subjects using the avg-8 data set as reference values. Our results suggest that MRSI reconstructed with a DC constraint can save around 70% of scanning time to obtain images and spectra with similar SNRs using λ = 5.

Universal brain systems for recognizing word shapes and handwriting gestures during reading.

Do the neural circuits for reading vary across culture? Reading of visually complex writing systems such as Chinese has been proposed to rely on areas outside the classical left-hemisphere network for alphabetic reading. Here, however, we show that, once potential confounds in cross-cultural comparisons are controlled for by presenting handwritten stimuli to both Chinese and French readers, the underlying network for visual word recognition may be more universal than previously suspected. Using functional magnetic resonance imaging in a semantic task with words written in cursive font, we demonstrate that two universal circuits, a shape recognition system (reading by eye) and a gesture recognition system (reading by hand), are similarly activated and show identical patterns of activation and repetition priming in the two language groups. These activations cover most of the brain regions previously associated with culture-specific tuning. Our results point to an extended reading network that invariably comprises the occipitotemporal visual word-form system, which is sensitive to well-formed static letter strings, and a distinct left premotor region, Exner's area, which is sensitive to the forward or backward direction with which cursive letters are dynamically presented. These findings suggest that cultural effects in reading merely modulate a fixed set of invariant macroscopic brain circuits, depending on surface features of orthographies.

Effects of far-infrared radiation on heart rate variability and central manifestations in healthy subjects: a resting-fMRI study.

The aim of this study was to investigate the autonomic responses and central manifestations by peripheral FIR stimulation. Ten subjects (mean ± SD age 26.2 ± 3.52 years) received FIR stimulation at left median nerve territory for 40 min. Electrocardiograph was continuously recorded and heart rate variability (HRV) were analyzed. By using a 3 T-MRI scanner, three sessions of resting-state functional magnetic resonance images (fMRI) were acquired, namely, before (baseline-FIR), immediately after (IA-FIR) and 15 min after FIR was turned off (Post-FIR). The fractional amplitude of low-frequency (0.01-0.08 Hz) fluctuation (fALFF) of each session to evaluate the intensity of resting-brain activity in each session was analyzed. Our results showed that FIR stimulation induced significant HRV responses such as an increasing trend of nLF and LF/HF ratio, while FIR increased fALFF in right superior front gyrus, middle frontal gyrus and decreased the resting brain activity at fusiform gyrus, extrastriae cortex, inferior temporal gyrus and middle temporal gyrus, especially 15 min after FIR was turned off. We conclude that the central manifestation and the autonomic responses are prominent during and after FIR stimulation, which provide important mechanistic explanation on human disorder treated by such energy medicine.

The modulation of semantic transparency on the recognition memory for two-character Chinese words.

This study demonstrated that semantic transparency as a linguistic property modulates the recognition memory for two-character Chinese words, with opaque words (i.e., words whose meanings cannot be derived from constituent characters-e.g., "[/guang/, light][/gun/, stick]", bachelor) remembered better than transparent words (i.e., words whose meanings can be derived from constituent characters-e.g., "[/cha/, tea][/bei/, cup]", teacup). In Experiment 1, the participants made lexical decisions on transparent words, opaque words, and nonwords in the study and then engaged in an old/new recognition test. Experiment 2 employed a concreteness judgment as the encoding task to ensure equivalent semantic processing for opaque and transparent words. In Experiment 3, the neighborhood size of the two-character words was manipulated together with their semantic transparency. In all three experiments, opaque words were found to be better remembered than transparent words. We concluded that the conceptual incongruence between the meanings of a whole word and its constituent characters made opaque words more distinctive and, hence, better remembered than transparent words.

Distributed source modeling of stereoencephalographic measurements of ictal activity.

OBJECTIVES: Stereoelectroencephalography (SEEG) can define the epileptogenic zone (EZ). However, SEEG is susceptible to the sampling bias, where no SEEG recording is taken within a circumscribed EZ. METHODS: Nine patients with medically refractory epilepsy underwent SEEG recording, and brain resection got positive outcomes. Ictal neuronal currents were estimated by distributed source modeling using the SEEG data and individual's anatomical magnetic resonance imaging. Using a retrospective leave-one-out data sub-sampling, we evaluated the sensitivity and specificity of the current estimates using MRI after surgical resection or radio-frequency ablation. RESULTS: The sensitivity and specificity in detecting the EZ were indistinguishable from either the data from all electrodes or the sub-sampled data (rank sum test: rank sum = 23719, p = 0.13) when at least one remaining electrode contact was no more than 20 mm away. CONCLUSIONS: The distributed neuronal current estimates of ictal SEEG data can mitigate the challenge of delineating the boundary of the EZ in cases of missing an electrode implanted within the EZ and a required second SEEG exploration. SIGNIFICANCE: Distributed source modeling can be a tool for clinicians to infer the EZ by allowing for more flexible planning of the electrode implantation route and minimizing the number of electrodes.

fMRI hemodynamics accurately reflects neuronal timing in the human brain measured by MEG.

Neuronal activation sequence information is essential for understanding brain functions. Extracting such timing information from blood oxygenation level dependent (BOLD) fMRI is confounded by interregional neurovascular differences and poorly understood relations between BOLD and electrophysiological response delays. Here, we recorded whole-head BOLD fMRI at 100 ms resolution and magnetoencephalography (MEG) during a visuomotor reaction-time task. Both methods detected the same activation sequence across five regions, from visual towards motor cortices, with linearly correlated interregional BOLD and MEG response delays. The smallest significant interregional BOLD delay was 100 ms; all delays ≥400 ms were significant. Switching the order of external events reversed the sequence of BOLD activations, indicating that interregional neurovascular differences did not confound the results. This may open new avenues for using fMRI to follow rapid activation sequences in the brain.

Multi-projection magnetic resonance inverse imaging of the human visuomotor system.

Using highly parallel radiofrequency (RF) detection, magnetic resonance inverse imaging (InI) can achieve 100 ms temporal resolution with whole brain coverage. This is achieved by trading off partition encoding steps and thus spatial resolution for a higher acquisition rate. The reduced spatial information is estimated by solving under-determined inverse problems using RF coil sensitivity information. Here we propose multi projection inverse imaging (mInI) to combine different projection images to improve the spatial resolution of InI. Specifically, coronal, sagittal, and transverse projection images were acquired from different runs of the fMRI acquisitions using a 32-channel head coil array. Simulations show that mInI improves the quality of the instantaneous image reconstruction significantly. Going from one projection to three projections, the spatial resolution quantified by the full width at half maximum of the point-spread function (PSF) is improved from 2.6 pixels to 1.4 pixels (4 mm nominal resolution per pixel). Considering the shape of the PSF, the effective spatial resolution is improved from 16.9 pixels to 4.7 pixels. In vivo fMRI experiments using a two-choice reaction time tasks show visual and sensorimotor cortical activities spatially consistent with typical EPI data, yet mInI offers 100 ms temporal resolution with the whole brain coverage. The mInI data with three projections revealed that the sensorimotor cortex was activated 700 ms after the visual cortex. mInI can be applied to BOLD-contrast fMRI experiments to characterize the dynamics of the activated brain areas with a high spatiotemporal resolution.

Ultrafast inverse imaging techniques for fMRI.

Inverse imaging (InI) supercharges the sampling rate of traditional functional MRI 10-100 fold at a cost of a moderate reduction in spatial resolution. The technique is inspired by similarities between multi-sensor magnetoencephalography (MEG) and highly parallel radio-frequency (RF) MRI detector arrays. Using presently available 32-channel head coils at 3T, InI can be sampled at 10 Hz and provides about 5-mm cortical spatial resolution with whole-brain coverage. Here we discuss the present applications of InI, as well as potential future challenges and opportunities in further improving its spatiotemporal resolution and sensitivity. InI may become a helpful tool for clinicians and neuroscientists for revealing the complex dynamics of brain functions during task-related and resting states.

Reconstruction of MRI data encoded by multiple nonbijective curvilinear magnetic fields.

Parallel imaging technique using localized gradients (PatLoc) uses the combination of surface gradient coils generating nonbijective curvilinear magnetic fields for spatial encoding. PatLoc imaging using one pair of multipolar spatial encoding magnetic fields (SEMs) has two major caveats: (1) The direct inversion of the encoding matrix requires exact determination of multiple locations which are ambiguously encoded by the SEMs. (2) Reconstructed images have a prominent loss of spatial resolution at the center of field-of-view using a symmetric coil array for signal detection. This study shows that a PatLoc system actually has a higher degree of freedom in spatial encoding to mitigate the two challenges mentioned above. Specifically, a PatLoc system can generate not only multipolar but also linear SEMs, which can be used to reduce the loss of spatial resolution at the field-of-view center. Here, we present an efficient and generalized image reconstruction method for PatLoc imaging using multiple SEMs without explicitly identifying the locations where SEM encoding is not unique. Reconstructions using simulations and empirical experimental data are compared with those using conventional linear gradients to demonstrate that the general combination of SEMs can improve image reconstructions.

Functional magnetic resonance inverse imaging of human visuomotor systems using eigenspace linearly constrained minimum amplitude (eLCMA) beamformer.

Recently proposed dynamic magnetic resonance (MR) inverse imaging (InI) is a novel parallel imaging reconstruction technique capable of improving the temporal resolution of blood-oxygen level-dependent (BOLD) contrast functional MRI (fMRI) to the order of milliseconds at the cost of moderate spatial resolution. Volumetric InI reconstructs spatial information from projection data by solving ill-posed inverse problems using simultaneous acquisitions from a RF coil array. Previously a spatial filtering technique based on linearly constrained minimum variance (LCMV) beamformer was suggested to localize the hemodynamic changes of dynamic InI data with improved spatial resolution and sensitivity. Here we report an advancement of the spatial filtering method, which combines the eigenspace projection of the measured data and the L1-norm minimization of the spatial filters' output noise amplitude, to further improve the detection power of BOLD contrast fMRI data. Using numerical simulation and in vivo data, we demonstrate that this eigenspace linearly constrained minimum amplitude (eLCMA) beamformer can reconstruct spatiotemporal hemodynamic signals with high statistical significance values and high spatial resolution in event-related two-choice reaction time visuomotor experiments.

Modulating inhibitory control with direct current stimulation of the superior medial frontal cortex.

The executive control of voluntary action involves not only choosing from a range of possible actions but also the inhibition of responses as circumstances demand. Recent studies have demonstrated that many clinical populations, such as people with attention-deficit hyperactivity disorder, exhibit difficulties in inhibitory control. One prefrontal area that has been particularly associated with inhibitory control is the pre-supplementary motor area (Pre-SMA). Here we applied non-invasive transcranial direct current stimulation (tDCS) over Pre-SMA to test its role in this behavior. tDCS allows for current to be applied in two directions to selectively excite or suppress the neural activity of Pre-SMA. Our results showed that anodal tDCS improved efficiency of inhibitory control. Conversely, cathodal tDCS showed a tendency towards impaired inhibitory control. To our knowledge, this is the first demonstration of non-invasive intervention tDCS altering subjects' inhibitory control. These results further our understanding of the neural bases of inhibitory control and suggest a possible therapeutic intervention method for clinical populations.

The neural basis of compound word processing revealed by varying semantic transparency and morphemic neighborhood size.

This study investigated the neural basis of compound word processing by using fMRI and Chinese two-character compounds for lexical decision. Semantic transparency and morphemic neighborhood size were manipulated to augment the processing profile for measurement. The behavioral results disclosed a semantic transparency effect and its interaction with the neighborhood size, which supported existence of a mechanism for compound processing. The fMRI results located a neural substrate in the left inferior prefrontal cortex (BA 45) which reacted in an interactive manner to the two variables. While its activities were lower when their neighborhood size was larger for processing transparent compounds, its activities became higher when their neighborhood size was larger for processing opaque compounds. When scaling to a larger scope, the function of this mechanism fitted well with the theoretical account of unification function of the left inferior frontal cortex for language processing.