Corrigendum: LeGUI: A Fast and Accurate Graphical User Interface for Automated Detection and Anatomical Localization of Intracranial Electrodes.

[This corrects the article DOI: 10.3389/fnins.2021.769872.].

Electrocorticography to Investigate Age-Related Brain Lateralization on Pediatric Motor Inhibition.

Response inhibition refers to the ability to suppress inappropriate actions that interfere with goal-driven behavior. The inferior frontal gyrus (IFG) is known to be associated with inhibition of a motor response by assuming executive control over motor cortex outputs. This study aimed to evaluate the pediatric development of response inhibition through subdural electrocorticography (ECoG) recording. Subdural ECoG recorded neural activities simultaneously during a Go/No-Go task, which was optimized for children. Different frequency power [theta: 4-8 Hz; beta: 12-40 Hz; high-gamma (HG): 70-200 Hz] was estimated within the IFG and motor cortex. Age-related analysis was computed by each bandpass power ratio between Go and No-Go conditions, and phase-amplitude coupling (PAC) over IFG by using the modulating index metric in two conditions. For all the eight pediatric patients, HG power was more activated in No-Go trials than in Go trials, in either right- or left-side IFG when available. In the IFG region, the power over theta and HG in No-Go conditions was higher than those in Go conditions, with significance over the right side (p < 0.05). The age-related lateralization from both sides to the right side was observed from the ratio of HG power and PAC value between the No-Go and Go trials. In the pediatric population, the role of motor inhibition was observed in both IFG, with age-related lateralization to the right side, which was proved in the previous functional magnetic resonance imaging studies. In this study, the evidence correlation of age and response inhibition was observed directly by the evidence of cortical recordings.

Effects of laser interstitial thermal therapy for mesial temporal lobe epilepsy on the structural connectome and its relationship to seizure freedom.

OBJECTIVE: Laser interstitial thermal therapy (LITT) is a minimally invasive surgery for mesial temporal lobe epilepsy (mTLE), but the effects of individual patient anatomy and location of ablation volumes affect seizure outcomes. The purpose of this study is to see if features of individual patient structural connectomes predict surgical outcomes after LITT for mTLE. METHODS: This is a retrospective analysis of seizure outcomes of LITT for mTLE in 24 patients. We use preoperative diffusion tensor imaging (DTI) to simulate changes in structural connectivity after laser ablation. A two-step machine-learning algorithm is applied to predict seizure outcomes from the change in connectomic features after surgery. RESULTS: Although node-based network features such as clustering coefficient and betweenness centrality have some predictive value, changes in connection strength between mesial temporal regions predict seizure outcomes significantly better. Changes in connection strength between the entorhinal cortex (EC), and the insula, hippocampus, and amygdala, as well as between the temporal pole and hippocampus, predict Engel Class I outcomes with an accuracy of 88%. Analysis of the ablation location, as well as simulated, alternative ablations, reveals that a more medial, anterior, and inferior ablation volume is associated with a greater effect on these connections, and potentially on seizure outcomes. SIGNIFICANCE: Our results indicate (1) that seizure outcomes can be retrospectively predicted with excellent accuracy using changes in structural connectivity, and (2) that favorable connectomic changes are associated with an ablation volume involving relatively mesial, anterior, and inferior locations. These results may provide a framework whereby individual pre-operative structural connectomes can be used to optimize ablation volumes and improve outcomes in LITT for mTLE.

LeGUI: A Fast and Accurate Graphical User Interface for Automated Detection and Anatomical Localization of Intracranial Electrodes.

Accurate anatomical localization of intracranial electrodes is important for identifying the seizure foci in patients with epilepsy and for interpreting effects from cognitive studies employing intracranial electroencephalography. Localization is typically performed by coregistering postimplant computed tomography (CT) with preoperative magnetic resonance imaging (MRI). Electrodes are then detected in the CT, and the corresponding brain region is identified using the MRI. Many existing software packages for electrode localization chain together separate preexisting programs or rely on command line instructions to perform the various localization steps, making them difficult to install and operate for a typical user. Further, many packages provide solutions for some, but not all, of the steps needed for confident localization. We have developed software, Locate electrodes Graphical User Interface (LeGUI), that consists of a single interface to perform all steps needed to localize both surface and depth/penetrating intracranial electrodes, including coregistration of the CT to MRI, normalization of the MRI to the Montreal Neurological Institute template, automated electrode detection for multiple types of electrodes, electrode spacing correction and projection to the brain surface, electrode labeling, and anatomical targeting. The software is written in MATLAB, core image processing is performed using the Statistical Parametric Mapping toolbox, and standalone executable binaries are available for Windows, Mac, and Linux platforms. LeGUI was tested and validated on 51 datasets from two universities. The total user and computational time required to process a single dataset was approximately 1 h. Automatic electrode detection correctly identified 4362 of 4695 surface and depth electrodes with only 71 false positives. Anatomical targeting was verified by comparing electrode locations from LeGUI to locations that were assigned by an experienced neuroanatomist. LeGUI showed a 94% match with the 482 neuroanatomist-assigned locations. LeGUI combines all the features needed for fast and accurate anatomical localization of intracranial electrodes into a single interface, making it a valuable tool for intracranial electrophysiology research.

Intraoperative Characterization of Subthalamic Nucleus-to-Cortex Evoked Potentials in Parkinson's Disease Deep Brain Stimulation.

Deep brain stimulation (DBS) of the subthalamic nucleus (STN) is a clinically effective tool for treating medically refractory Parkinson's disease (PD), but its neural mechanisms remain debated. Previous work has demonstrated that STN DBS results in evoked potentials (EPs) in the primary motor cortex (M1), suggesting that modulation of cortical physiology may be involved in its therapeutic effects. Due to technical challenges presented by high-amplitude DBS artifacts, these EPs are often measured in response to low-frequency stimulation, which is generally ineffective at PD symptom management. This study aims to characterize STN-to-cortex EPs seen during clinically relevant high-frequency STN DBS for PD. Intraoperatively, we applied STN DBS to 6 PD patients while recording electrocorticography (ECoG) from an electrode strip over the ipsilateral central sulcus. Using recently published techniques, we removed large stimulation artifacts to enable quantification of STN-to-cortex EPs. Two cortical EPs were observed - one synchronized with DBS onset and persisting during ongoing stimulation, and one immediately following DBS offset, here termed the "start" and the "end" EPs respectively. The start EP is, to our knowledge, the first long-latency cortical EP reported during ongoing high-frequency DBS. The start and end EPs differ in magnitude (p < 0.05) and latency (p < 0.001), and the end, but not the start, EP magnitude has a significant relationship (p < 0.001, adjusted for random effects of subject) to ongoing high gamma (80-150 Hz) power during the EP. These contrasts may suggest mechanistic or circuit differences in EP production during the two time periods. This represents a potential framework for relating DBS clinical efficacy to the effects of a variety of stimulation parameters on EPs.

Concurrent Deep Brain Stimulation Reduces the Direct Cortical Stimulation Necessary for Motor Output.

BACKGROUND: Converging literatures suggest that deep brain stimulation (DBS) in Parkinson's disease affects multiple circuit mechanisms. One proposed mechanism is the normalization of primary motor cortex (M1) pathophysiology via effects on the hyperdirect pathway. OBJECTIVES: We hypothesized that DBS would reduce the current intensity necessary to modulate motor-evoked potentials from focally applied direct cortical stimulation (DCS). METHODS: Intraoperative subthalamic DBS, DCS, and preoperative diffusion tensor imaging data were acquired in 8 patients with Parkinson's disease. RESULTS: In 7 of 8 patients, DBS significantly reduced the M1 DCS current intensity required to elicit motor-evoked potentials. This neuromodulation was specific to select DBS bipolar configurations. In addition, the volume of activated tissue models of these configurations were significantly associated with overlap of the hyperdirect pathway. CONCLUSIONS: DBS reduces the current necessary to elicit a motor-evoked potential using DCS. This supports a circuit mechanism of DBS effectiveness, potentially involving the hyperdirect pathway that speculatively may underlie reductions in hypokinetic abnormalities in Parkinson's disease. © 2020 International Parkinson and Movement Disorder Society.

Publisher Correction: Direct stimulation of somatosensory cortex results in slower reaction times compared to peripheral touch in humans.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Cortical Topography of Error-Related High-Frequency Potentials During Erroneous Control in a Continuous Control Brain-Computer Interface.

Brain-computer interfaces (BCIs) benefit greatly from performance feedback, but current systems lack automatic, task-independent feedback. Cortical responses elicited from user error have the potential to serve as state-based feedback to BCI decoders. To gain a better understanding of local error potentials, we investigate responsive cortical power underlying error-related potentials (ErrPs) from the human cortex during a one-dimensional center-out BCI task, tracking the topography of high-gamma (70-100 Hz) band power (HBP) specific to BCI error. We measured electrocorticography (ECoG) in three human subjects during dynamic, continuous control over BCI cursor velocity. Subjects used motor imagery and rest to move the cursor toward and subsequently dwell within a target region. We then identified and labeled epochs where the BCI decoder incorrectly moved the cursor in the direction opposite of the subject's expectations (i.e., BCI error). We found increased HBP in various cortical areas 100-500 ms following BCI error with respect to epochs of correct, intended control. Significant responses were noted in primary somatosensory, motor, premotor, and parietal areas and generally regardless of whether the subject was using motor imagery or rest to move the cursor toward the target. Parts of somatosensory, temporal, and parietal areas exclusively had increased HBP when subjects were using motor imagery. In contrast, only part of the parietal cortex near the angular gyrus exclusively had an increase in HBP during rest. This investigation is, to our knowledge, the first to explore cortical fields changes in the context of continuous control in ECoG BCI. We present topographical changes in HBP characteristic specific to the generation of error. By focusing on continuous control, instead of on discrete control for simple selection, we investigate a more naturalistic setting and provide high ecological validity for characterizing error potentials. Such potentials could be considered as design elements for co-adaptive BCIs in the future as task-independent feedback to the decoder, allowing for more robust and individualized BCIs.

Differentiation of epileptic regions from voluntary high-gamma activation via interictal cross-frequency windowed power-power correlation.

OBJECTIVEElectrocorticography is an indispensable tool in identifying the epileptogenic zone in the presurgical evaluation of many epilepsy patients. Traditional electrocorticographic features (spikes, ictal onset changes, and recently high-frequency oscillations [HFOs]) rely on the presence of transient features that occur within or near epileptogenic cortex. Here the authors report on a novel corticography feature of epileptogenic cortex-covariation of high-gamma and beta frequency band power profiles. Band-limited power was measured from each recording site based on native physiological signal differences without relying on clinical ictal or interictal epileptogenic features. In this preliminary analysis, frequency windowed power correlation appears to be a specific marker of the epileptogenic zone. The authors' overall aim was to validate this observation with the location of the eventual resection and outcome.METHODSThe authors conducted a retrospective analysis of 13 adult patients who had undergone electrocorticography for surgical planning at their center. They quantified the correlation of high-gamma (70-200 Hz) and beta (12-18 Hz) band frequency power per electrode site during a cognitive task. They used a sliding window method to correlate the power of smoothed, Hilbert-transformed high-gamma and beta bands. They then compared positive and negative correlations between power in the high-gamma and beta bands in the setting of a hand versus a tongue motor task as well as within the resting state. Significant positive correlations were compared to surgically resected areas and outcomes based on reviewed records.RESULTSPositive high-gamma and beta correlations appeared to predict the area of eventual resection and, preliminarily, surgical outcome independent of spike detection. In general, patients with the best outcomes had well-localized positive correlations (high-gamma and beta activities) to areas of eventual resection, while those with poorer outcomes displayed more diffuse patterns.CONCLUSIONSData in this study suggest that positive high-gamma and beta correlations independent of any behavioral metric may have clinical applicability in surgical decision-making. Further studies are needed to evaluate the clinical potential of this methodology. Additional work is also needed to relate these results to other methods, such as HFO detection or connectivity with other cortical areas.

Context-dependent relationship in high-resolution micro-ECoG studies during finger movements.

OBJECTIVE: The activation of the sensorimotor cortex as measured by electrocorticographic (ECoG) signals has been correlated with contralateral hand movements in humans, as precisely as the level of individual digits. However, the relationship between individual and multiple synergistic finger movements and the neural signal as detected by ECoG has not been fully explored. The authors used intraoperative high-resolution micro-ECoG (µECoG) on the sensorimotor cortex to link neural signals to finger movements across several context-specific motor tasks. METHODS: Three neurosurgical patients with cortical lesions over eloquent regions participated. During awake craniotomy, a sensorimotor cortex area of hand movement was localized by high-frequency responses measured by an 8 × 8 µECoG grid of 3-mm interelectrode spacing. Patients performed a flexion movement of the thumb or index finger, or a pinch movement of both, based on a visual cue. High-gamma (HG; 70-230 Hz) filtered µECoG was used to identify dominant electrodes associated with thumb and index movement. Hand movements were recorded by a dataglove simultaneously with µECoG recording. RESULTS: In all 3 patients, the electrodes controlling thumb and index finger movements were identifiable approximately 3-6-mm apart by the HG-filtered µECoG signal. For HG power of cortical activation measured with µECoG, the thumb and index signals in the pinch movement were similar to those observed during thumb-only and index-only movement, respectively (all p > 0.05). Index finger movements, measured by the dataglove joint angles, were similar in both the index-only and pinch movements (p > 0.05). However, despite similar activation across the conditions, markedly decreased thumb movement was observed in pinch relative to independent thumb-only movement (all p < 0.05). CONCLUSIONS: HG-filtered µECoG signals effectively identify dominant regions associated with thumb and index finger movement. For pinch, the µECoG signal comprises a combination of the signals from individual thumb and index movements. However, while the relationship between the index finger joint angle and HG-filtered signal remains consistent between conditions, there is not a fixed relationship for thumb movement. Although the HG-filtered µECoG signal is similar in both thumb-only and pinch conditions, the actual thumb movement is markedly smaller in the pinch condition than in the thumb-only condition. This implies a nonlinear relationship between the cortical signal and the motor output for some, but importantly not all, movement types. This analysis provides insight into the tuning of the motor cortex toward specific types of motor behaviors.

Spontaneous Variation in Electrocorticographic Resting-State Connectivity.

Prior studies using functional magnetic resonance imaging, electroencephalography, and magnetoencephalography have observed both structured patterns in resting-state functional connectivity and spontaneous longitudinal variation in connectivity patterns independent of a task. In this first study using electrocorticography (ECoG), we characterized spontaneous, intersession variation in resting-state functional connectivity not linked to a task. We evaluated pairwise connectivity between electrodes using three measures (phase locking value [PLV], amplitude correlation, and coherence) for six canonical frequency bands, capturing different characteristics of time-evolving signals. We grouped electrodes into 10 functional regions and used intraclass correlation (ICC) to estimate pairwise longitudinal stability. We found that stronger PLV (PLV ≥0.4) in theta through gamma bands and strong correlation in all bands (R2's ≥0.6) are linked to substantial stability (ICC ≥0.6), but that stability does not imply strong phase locking or amplitude correlation. There was no notable link between strong coherence and high ICC. All within-region PLVs are markedly stable across frequencies. In addition, we highlight interaction patterns across several regions: parahippocampal/entorhinal cortex is characterized by stable, weak functional connectivity except self-connections. Dorsolateral prefrontal cortex connectivity is weak and unstable, except self-connections. Inferior parietal lobule has little stability despite narrow connectivity bounds. We confirm prior studies linking functional connectivity strength and intersession variability, extending into higher frequencies than other modalities, with greater spatial specificity than scalp electrophysiology. We suggest further studies quantitatively compare ECoG to other modalities and/or use these findings as a baseline to capture functional connectivity and dynamics linked to perturbations with a task or disease state.

Direct stimulation of somatosensory cortex results in slower reaction times compared to peripheral touch in humans.

Direct cortical stimulation (DCS) of primary somatosensory cortex (S1) could help restore sensation and provide task-relevant feedback in a neuroprosthesis. However, the psychophysics of S1 DCS is poorly studied, including any comparison to cutaneous haptic stimulation. We compare the response times to DCS of human hand somatosensory cortex through electrocorticographic grids with response times to haptic stimuli delivered to the hand in four subjects. We found that subjects respond significantly slower to S1 DCS than to natural, haptic stimuli for a range of DCS train durations. Median response times for haptic stimulation varied from 198 ms to 313 ms, while median responses to reliably perceived DCS ranged from 254 ms for one subject, all the way to 528 ms for another. We discern no significant impact of learning or habituation through the analysis of blocked trials, and find no significant impact of cortical stimulation train duration on response times. Our results provide a realistic set of expectations for latencies with somatosensory DCS feedback for future neuroprosthetic applications and motivate the study of neural mechanisms underlying human perception of somatosensation via DCS.

Direct Electrophysiological Correlates of Body Ownership in Human Cerebral Cortex.

Over the past decade, numerous neuroimaging studies based on hemodynamic markers of brain activity have examined the feeling of body ownership using perceptual body-illusions in humans. However, the direct electrophysiological correlates of body ownership at the cortical level remain unexplored. To address this, we studied the rubber hand illusion in 5 patients (3 males and 2 females) implanted with intracranial electrodes measuring cortical surface potentials. Increased high-γ (70-200 Hz) activity, an index of neuronal firing rate, in premotor and intraparietal cortices reflected the feeling of ownership. In both areas, high-γ increases were intimately coupled with the subjective illusion onset and sustained both during and in-between touches. However, intraparietal activity was modulated by tactile stimulation to a higher degree than the premotor cortex through effective connectivity with the hand-somatosensory cortex, which suggests different functional roles. These findings constitute the first intracranial electrophysiological characterization of the rubber hand illusion and extend our understanding of the dynamic mechanisms of body ownership.

Electrocorticography and the early maturation of high-frequency suppression within the default mode network.

OBJECTIVE The acquisition and refinement of cognitive and behavioral skills during development is associated with the maturation of various brain oscillatory activities. Most developmental investigations have identified distinct patterns of low-frequency electrophysiological activity that are characteristic of various behavioral milestones. In this investigation, the authors focused on the cross-sectional developmental properties of high-frequency spectral power from the brain's default mode network (DMN) during goal-directed behavior. METHODS The authors contrasted regionally specific, time-evolving high gamma power (HGP) in the lateral DMN cortex between 3 young children (age range 3-6 years) and 3 adults by use of electrocorticography (ECoG) recordings over the left perisylvian cortex during a picture-naming task. RESULTS Across all participants, a nearly identical and consistent response suppression of HGP, which is a functional signature of the DMN, was observed during task performance recordings acquired from ECoG electrodes placed over the lateral DMN cortex. This finding provides evidence of relatively early maturation of the DMN. Furthermore, only HGP relative to evoked alpha and beta band power showed this level of consistency across all participants. CONCLUSIONS Regionally specific, task-evoked suppression of the high-frequency components of the cortical power spectrum is established early in brain development, and this response may reflect the early maturation of specific cognitive and/or computational mechanisms.

Limbic and Basal Ganglia Neuroanatomical Correlates of Gait and Executive Function: Older Adults With Mild Cognitive Impairment and Intact Cognition.

OBJECTIVE: This study aimed to examine differences in spatiotemporal gait parameters between older adults with amnestic mild cognitive impairment and normal cognition and to examine limbic and basal ganglia neural correlates of gait and executive function in older adults without dementia. DESIGN: This was a cross-sectional study of 46 community-dwelling older adults, ages 70-95 yrs, with amnestic mild cognitive impairment (n = 23) and normal cognition (n = 23). Structural magnetic resonance imaging was used to attain volumetric measures of limbic and basal ganglia structures. Quantitative motion analysis was used to measure spatiotemporal parameters of gait. The Trail Making Test was used to assess executive function. RESULTS: During fast-paced walking, older adults with amnestic mild cognitive impairment demonstrated significantly slower gait speed and shorter stride length compared with older adults with normal cognition. Stride length was positively correlated with hippocampal, anterior cingulate, and nucleus accumbens volumes (P < 0.05). Executive function was positively correlated with hippocampal, anterior cingulate, and posterior cingulate volumes (P < 0.05). CONCLUSIONS: Compared with older adults with normal cognition, those with amnestic mild cognitive impairment demonstrated slower gait speed and shorter stride length, during fast-paced walking, and lower executive function. Hippocampal and anterior cingulate volumes demonstrated moderate positive correlation with both gait and executive function, after adjusting for age. TO CLAIM CME CREDITS: Complete the self-assessment activity and evaluation online at http://www.physiatry.org/JournalCME CME OBJECTIVES: Upon completion of this article, the reader should be able to: (1) discuss gait performance and cognitive function in older adults with amnestic mild cognitive impairment versus normal cognition, (2) discuss neurocorrelates of gait and executive function in older adults without dementia, and (3) recognize the importance of assessing gait speed and cognitive function in the clinical management of older adults at risk for dementia. LEVEL: Advanced ACCREDITATION: The Association of Academic Physiatrists is accredited by the Accreditation Council for Continuing Medical Education to provide continuing medical education for physicians.The Association of Academic Physiatrists designates this Journal-based CME activity for a maximum of 0.5 AMA PRA Category 1 Credit(s)™. Physicians should only claim credit commensurate with the extent of their participation in the activity.

BCI Use and Its Relation to Adaptation in Cortical Networks.

Brain-computer interfaces (BCIs) carry great potential in the treatment of motor impairments. As a new motor output, BCIs interface with the native motor system, but acquisition of BCI proficiency requires a degree of learning to integrate this new function. In this review, we discuss how BCI designs often take advantage of the brain's motor system infrastructure as sources of command signals. We highlight a growing body of literature examining how this approach leads to changes in activity across cortex, including beyond motor regions, as a result of learning the new skill of BCI control. We discuss the previous research identifying patterns of neural activity associated with BCI skill acquisition and use that closely resembles those associated with learning traditional native motor tasks. We then discuss recent work in animals probing changes in connectivity of the BCI control site, which were linked to BCI skill acquisition, and use this as a foundation for our original work in humans. We present our novel work showing changes in resting state connectivity across cortex following the BCI learning process. We find substantial, heterogeneous changes in connectivity across regions and frequencies, including interactions that do not involve the BCI control site. We conclude from our review and original work that BCI skill acquisition may potentially lead to significant changes in evoked and resting state connectivity across multiple cortical regions. We recommend that future studies of BCIs look beyond motor regions to fully describe the cortical networks involved and long-term adaptations resulting from BCI skill acquisition.

An interspecies comparative study of invasive electrophysiological functional connectivity.

Introduction: Resting-state connectivity patterns have been observed in humans and other mammal species, and can be recorded using a variety of different technologies. Functional connectivity has been previously compared between species using resting-state fMRI, but not in electrophysiological studies. Methods: We compared connectivity with implanted electrodes in humans (electrocorticography) to macaques and sheep (microelectrocorticography), which are capable of recording neural data at high frequencies with spatial precision. We specifically examined synchrony, implicated in functional integration between regions. Results: We found that connectivity strength was overwhelmingly similar in humans and monkeys for pairs of two different brain regions (prefrontal, motor, premotor, parietal), but differed more often within single brain regions. The two connectivity measures, correlation and phase locking value, were similar in most comparisons. Connectivity strength agreed more often between the species at higher frequencies. Where the species differed, monkey synchrony was stronger than human in all but one case. In contrast, human and sheep connectivity within somatosensory cortex diverged in almost all frequencies, with human connectivity stronger than sheep. Discussion: Our findings imply greater heterogeneity within regions in humans than in monkeys, but comparable functional interactions between regions in the two species. This suggests that monkeys may be effectively used to probe resting-state connectivity in humans, and that such findings can then be validated in humans. Although the discrepancy between humans and sheep is larger, we suggest that findings from sheep in highly invasive studies may be used to provide guidance for studies in other species.

Regional Patterns of Cortical Phase Synchrony in the Resting State.

Synchronized phase estimates between oscillating neuronal signals at the macroscale level reflect coordinated activities between neuronal assemblies. Recent electrophysiological evidence suggests the presence of significant spontaneous phase synchrony within the resting state. The purpose of this study was to investigate phase synchrony, including directional interactions, in resting state subdural electrocorticographic recordings to better characterize patterns of regional phase interactions across the lateral cortical surface during the resting state. We estimated spontaneous phase locking value (PLV) as a measure of functional connectivity, and phase slope index (PSI) as a measure of pseudo-causal phase interactions, across a broad range of canonical frequency bands and the modulation of the amplitude envelope of high gamma (amHG), a band that is believed to best reflect the physiological processes giving rise to the functional magnetic resonance imaging BOLD signal. Long-distance interactions had higher PLVs in slower frequencies (≤theta) than in higher ones (≥beta) with amHG behaving more like slow frequencies, and a general trend of increasing frequency band of significant PLVs when moving across the lateral surface along an anterior-posterior axis. Moreover, there was a strong trend of frontal-to-parietal directional phase synchronization, measured by PSI across multiple frequencies. These findings, which are likely indicative of coordinated and structured spontaneous cortical interactions, are important in the study of time scales and directional nature of resting state functional connectivity, and may ultimately contribute to a better understanding of how spontaneous synchrony is linked to variation in regional architecture across the lateral cortical surface.

Directional patterns of cross frequency phase and amplitude coupling within the resting state mimic patterns of fMRI functional connectivity.

Functional imaging investigations into the brain's resting state interactions have yielded a wealth of insight into the intrinsic and dynamic neural architecture supporting cognition and behavior. Electrophysiological studies however have highlighted the fact that synchrony across large-scale cortical systems is composed of spontaneous interactions occurring at timescales beyond the traditional resolution of fMRI, a feature that limits the capacity of fMRI to draw inference on the true directional relationship between network nodes. To approach the question of directionality in resting state signals, we recorded resting state functional MRI (rsfMRI) and electrocorticography (ECoG) from four human subjects undergoing invasive epilepsy monitoring. Using a seed-point based approach, we employed phase-amplitude coupling (PAC) and biPhase Locking Values (bPLV), two measures of cross-frequency coupling (CFC) to explore both outgoing and incoming connections between the seed and all non-seed, site electrodes. We observed robust PAC between a wide range of low-frequency phase and high frequency amplitude estimates. However, significant bPLV, a CFC measure of phase-phase synchrony, was only observed at specific narrow low and high frequency bandwidths. Furthermore, the spatial patterns of outgoing PAC connectivity were most closely associated with the rsfMRI connectivity maps. Our results support the hypothesis that PAC is relatively ubiquitous phenomenon serving as a mechanism for coordinating high-frequency amplitudes across distant neuronal assemblies even in absence of overt task structure. Additionally, we demonstrate that the spatial distribution of a seed-point rsfMRI sensorimotor network is strikingly similar to specific patterns of directional PAC. Specifically, the high frequency activities of distal patches of cortex owning membership in a rsfMRI sensorimotor network were most likely to be entrained to the phase of a low frequency rhythm engendered from the neural populations at the seed-point, suggestive of greater directional coupling from the seed out to the site electrodes.

Posterior Cingulate Lactate as a Metabolic Biomarker in Amnestic Mild Cognitive Impairment.

Mitochondrial dysfunction represents a central factor within the pathogenesis of the Alzheimer's disease (AD) spectrum. We hypothesized that in vivo measurements of lactate (lac), a by-product of glycolysis, would correlate with functional impairment and measures of brain health in a cohort of 15 amnestic mild cognitive impairment (aMCI) individuals. Lac was quantified from the precuneus/posterior cingulate (PPC) using 2-dimensional J-resolved magnetic resonance spectroscopy (MRS). Additionally, standard behavioral and imaging markers of aMCI disease progression were acquired. PPC lac was negatively correlated with performance on the Wechsler logical memory tests and on the minimental state examination even after accounting for gray matter, cerebral spinal fluid volume, and age. No such relationships were observed between lac and performance on nonmemory tests. Significant negative relationships were also noted between PPC lac and hippocampal volume and PPC functional connectivity. Together, these results reveal that aMCI individuals with a greater disease progression have increased concentrations of PPC lac. Because lac is upregulated as a compensatory response to mitochondrial impairment, we propose that J-resolved MRS of lac is a noninvasive, surrogate biomarker of impaired metabolic function and would provide a useful means of tracking mitochondrial function during therapeutic trials targeting brain metabolism.