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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.

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.

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.

Studying the neural correlates of sleep can lead to revelations in our understanding of sleep and its interplay with different neurological disorders. Sleep research relies on manual annotation of sleep stages based on rules developed for healthy adults. Automating sleep stage annotation can expedite sleep research and enable us to better understand atypical sleep patterns. Our goal was to create a fully unsupervised approach to label sleep and wake states in human electro-corticography (ECoG) data from epilepsy patients. Here, we demonstrate that with continuous data from a single ECoG electrode, hidden semi-Markov models (HSMM) perform best in classifying sleep/wake states without excessive transitions, with a mean accuracy (n=4) of 85.2% compared to using K-means clustering (72.2%) and hidden Markov models (81.5%). Our results confirm that HSMMs produce meaningful labels for ECoG data and establish the groundwork to apply this model to cluster sleep stages and potentially other behavioral states.

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.

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.

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.

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.

OBJECTIVEThe 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.METHODSThe 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.RESULTSAcross 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.CONCLUSIONSRegionally 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.

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.

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 towards 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 towards 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.

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.

Objective The purpose of this study is to determine the relationship between cortical electrophysiological (CE) signals recorded from the surface of the brain (subdural electrocorticography, or ECoG) and signals recorded extracranially from the subgaleal (SG) space. Methods We simultaneously recorded several hours of continuous ECoG and SG signals from 3 human pediatric subjects, and compared power spectra of signals between a differential SG montage and several differential ECoG montages to determine the nature of the transfer function between them. Results We demonstrate the presence of CE signals in the SG montage in the high-gamma range (HG, 70–110 Hz), and the transfer function between 70 and 110 Hz is best characterized as a linear function of frequency. We also test an alternative transfer function, i.e. a single pole filter, to test the hypothesis of frequency dependent attenuation in that range, but find this model to be inferior to the linear model. Conclusions Our findings indicate that SG electrodes are capable of recording HG signals without frequency distortion compared with ECoG electrodes. Significance HG signals could be recorded minimally invasively from outside the skull, which could be important for clinical care or brain–computer interface applications.

Objective. Electrical stimulation of the human brain is commonly used for eliciting and inhibiting neural activity for clinical diagnostics, modifying abnormal neural circuit function for therapeutics, and interrogating cortical connectivity. However, recording electrical signals with concurrent stimulation results in dominant electrical artifacts that mask the neural signals of interest. Here we develop a method to reproducibly and robustly recover neural activity during concurrent stimulation. We concentrate on signal recovery across an array of electrodes without channel-wise fine-tuning of the algorithm. Our goal includes signal recovery with trains of stimulation pulses, since repeated, high-frequency pulses are often required to induce desired effects in both therapeutic and research domains. We have made all of our code and data publicly available. Approach. We developed an algorithm that automatically detects templates of artifacts across many channels of recording, creating a dictionary of learned templates using unsupervised clustering. The artifact template that best matches each individual artifact pulse is subtracted to recover the underlying activity. To assess the success of our method, we focus on whether it extracts physiologically interpretable signals from real recordings. Main results. We demonstrate our signal recovery approach on invasive electrophysiologic recordings from human subjects during stimulation. We show the recovery of meaningful neural signatures in both electrocorticographic (ECoG) arrays and deep brain stimulation (DBS) recordings. In addition, we compared cortical responses induced by the stimulation of primary somatosensory (S1) by natural peripheral touch, as well as motor cortex activity with and without concurrent S1 stimulation. Significance. Our work will enable future advances in neural engineering with simultaneous stimulation and recording.

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.

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.

OBJECTIVEThe 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.METHODSThree 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.RESULTSIn 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).CONCLUSIONSHG-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.

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.

The precise pathogenic mechanisms of Huntington's disease (HD) are unknown but can be tested in vivo using proton magnetic resonance spectroscopy (1H MRS) to measure neurochemical changes. The objective of this study was to evaluate neurochemical differences in HD gene mutation carriers (HGMCs) versus controls and to investigate relationships among function, brain structure, and neurochemistry in HD. Because previous 1H MRS studies have yielded varied conclusions about HD neurochemical changes, an additional goal was to compare two 1H MRS data analysis approaches. HGMCs with premanifest to early HD and controls underwent evaluation of motor function, magnetic resonance imaging, and localized 1H MRS in the caudate and the frontal lobe. Analytical approaches that were tested included absolute quantitation (unsuppressed water signal as an internal reference) and relative quantification (calculating ratios of all neurochemical signals within a voxel). We identified a suite of neurochemicals that were reduced in concentration proportionally to loss of caudate volume in HGMCs. Caudate concentrations of N-acetylaspartate (NAA), creatine, choline, and caudate and frontal lobe concentrations of glutamate plus glutamine (Glx) and glutamate were correlated with caudate volume in HGMCs. The relative, but not the absolute, quantitation approach revealed disease-related differences; the Glx signal was decreased relative to other neurochemicals in the caudate of HGMCs versus controls. This is the first study to demonstrate a correlation among structure, function, and chemical measures in HD brain. Additionally, we demonstrate that a relative quantitation approach may enable the magnification of subtle differences between groups. Observation of decreased Glx suggests that glutamate signaling may be disrupted relatively early in HD, which has important implications for therapeutic approaches. © 2014 International Parkinson and Movement Disorder Society

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The majority of subjects who attempt to learn control of a brain–computer interface (BCI) can do so with adequate training. Much like when one learns to type or ride a bicycle, BCI users report transitioning from a deliberate, cognitively focused mindset to near automatic control as training progresses. What are the neural correlates of this process of BCI skill acquisition? Seven subjects were implanted with electrocorticography (ECoG) electrodes and had multiple opportunities to practice a 1D BCI task. As subjects became proficient, strong initial task-related activation was followed by lessening of activation in prefrontal cortex, premotor cortex, and posterior parietal cortex, areas that have previously been implicated in the cognitive phase of motor sequence learning and abstract task learning. These results demonstrate that, although the use of a BCI only requires modulation of a local population of neurons, a distributed network of cortical areas is involved in the acquisition of BCI proficiency.

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.

Difficulty interpreting facial expressions has been reported in autism spectrum disorders (ASD) and is thought to be associated with amygdala abnormalities. To further explore the neural basis of abnormal emotional face processing in ASD, we conducted an fMRI study of emotional face matching in high-functioning adults with ASD and age, IQ, and gender matched controls. In addition, we investigated whether there was a relationship between self-reported social anxiety and fMRI activation. During fMRI scanning, study participants were instructed to match facial expressions depicting fear or anger. The control condition was a comparable shape - matching task. The control group evidenced significantly increased left prefrontal activation and decreased activation in the occipital lobes compared to the ASD group during emotional face matching. Further, within the ASD group, greater social anxiety was associated with increased activation in right amygdala and left middle temporal gyrus, and decreased activation in the fusiform face area. These results indicate that level of social anxiety mediates the neural response to emotional face perception in ASD.

Neuroimaging-based investigations in humans have established the existence of brain regions that are selectively metabolically active while resting. We report a population-scale neurophysiological measurement of activity in regions of this “default network,” by recording high-frequency power (76–200 Hz) electrical potentials directly from these regions in three human subjects. A selective increase observed during only resting, when compared with activity, firmly establishes a neuronal origin for default network phenomena.

Early onset blindness leads to a dramatic alteration in the way the world is perceived, a change that is detectable in the organization of the brain. Several studies have confirmed that blindness leads to functional alterations in occipital cortices that normally serve visual functions. These reorganized brain regions respond to a variety of tasks and stimuli, but their specific functions are unclear. In sighted individuals, several studies have reported preparatory activity in retinotopic areas, which enhances perceptual sensitivity. “Baseline shifts,” changes in activity associated with a cue predicting an upcoming event, provides a marker for attentional modulation. Here we demonstrate that, in early blind subjects, medial occipital areas produced significant blood oxygenation level-dependent (BOLD) responses to a cue signaling an auditory discrimination trial but not to a cue indicating a no-trial period. Furthermore, the amplitude of the BOLD response in the anterior calcarine sulcus of early blind subjects correlated with their discrimination performance on the auditory backward masking task. Preparatory BOLD responses also were present in auditory cortices, although they were more robust in blind than sighted control subjects. The pattern of response in visual areas is similar to preparatory effects observed during visual selective attention in sighted subjects and consistent with the hypothesis that the mechanisms implicated in visual attention continue to modulate occipital cortex in the early blind. A possible source of this top-down modulation may be the frontoparietal circuits that retain their connectivity with the reorganized occipital cortex and as a result influence processing of nonvisual stimuli in the blind.

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.

For blind individuals, audition provides critical information for interacting with the environment. Individuals blinded early in life (EB) typically show enhanced auditory abilities relative to sighted controls as measured by tasks requiring complex discrimination, attention and memory. In contrast, few deficits have been reported on tasks involving auditory sensory thresholds (e.g., Yates, J.T., Johnson, R.M., Starz, W.J., 1972. Loudness perception of the blind. Audiology 11(5), 368-376; Starlinger, I., Niemeyer, W., 1981. Do the blind hear better? Investigations on auditory processing in congenital or early acquired blindness. I. Peripheral functions. Audiology 20(6), 503-509). A study of gap detection stands at odds with this distinction [Muchnik, C., Efrati, M., Nemeth, E., Malin, M., Hildesheimer, M., 1991. Central auditory skills in blind and sighted subjects. Scand. Audiol. 20(1), 19-23]. In the current investigation we re-examined gap detection abilities in the EB using a single-interval, yes/no method. A group of younger sighted control individuals (SCy) was included in the analysis in addition to EB and sighted age matched control individuals (SCm) in order to examine the effect of age on gap detection performance. Estimates of gap detection thresholds for EB subjects were nearly identical to SCm subjects and slightly poorer relative to the SCy subjects. These results suggest some limits on the extent of auditory temporal advantages in the EB.

High gamma oscillations (70–150 Hz; HG) are rapidly evolving, spatially localized neurophysiological signals that are believed to be the best representative signature of engaged neural populations. The HG band has been best characterized from invasive electrophysiological approaches such as electrocorticography because of the increased signal-to-noise ratio that results when by-passing the scalp and skull. Despite the recent observation that HG activity can be detected non-invasively by electroencephalography (EEG), it is unclear to what extent EEG can accurately resolve the spatial distribution of HG signals during active task engagement. We have overcome some of the limitations inherent to acquiring HG signals across the scalp by utilizing individual head anatomy in combination with an inverse modeling method. We applied a linearly constrained minimum variance (LCMV) beamformer method on EEG data during a motor imagery paradigm to extract a time-frequency spectrogram at every voxel location on the cortex. To confirm spatially distributed patterns of HG responses, we contrasted overlapping maps of the EEG HG signal with blood oxygen level dependence (BOLD) functional magnetic resonance imaging (fMRI) data acquired from the same set of neurologically normal subjects during a separate session. We show that scalp-based HG band activity detected by EEG during motor imagery spatially co-localizes with BOLD fMRI data. Taken together, these results suggest that EEG can accurately resolve spatially specific estimates of local cortical high frequency signals, potentially opening an avenue for non-invasive measurement of HG potentials from diverse sets of neurologically impaired populations for diagnostic and therapeutic purposes.

Due to copyright restrictions, the access to the full text of this article is only available via subscription. Exceptional opportunities exist for researchers and practitioners to invest in conducting innovative and transformative research in data mining and health informatics. This IEEE Intelligent Systems "Trends and Controversies" (T&C) department hopes to raise awareness and highlight recent research to move toward such goals. The introduction, "Healthcare Intelligence: Turning Data into Knowledge," is written by Hui Yang and Erhun Kundakcioglu. Next, "Empowering Excellence of Care by Radiology Informatics" is written by Jing Li, Teresa Wu, J. Ross Mitchell, Amy K. Hara, William Pavlicek, Leland S. Hu, Alvin C. Silva, and Christine M. Zwart. Third, "Opportunities for Operations Research in Medical Decision Making" is written by Sait Tunc, Oguzhan Alagoz, and Elizabeth Burnside. Fourth, "Diagnostic Network Modeling of Neural Connectivity Using Functional Magnetic Resonance Imaging" is written by W. Art Chaovalitwongse, Georgiy Presnyakov, Yulian Cao, Sirirat Sujitnapitsatham, Daehan Won, Tara Madhyastha, Kurt E. Weaver, Paul R. Borghesani, and Thomas J. Grabowski. The final article, "Spatial Clustering in Public Health: Advances and Challenges," is written by Lianjie Shu, Man Ho Ling, Shui-Yee Wong, and Kwok-Leung Tsui. Macau Science and Technology Development Fund ; the Food and Health Bureau ; the Research Grants Council

Early blindness results in occipital cortex neurons responding to a wide range of auditory and tactile stimuli. These changes in tuning properties are accompanied by an extensive reorganization of the occipital cortex that includes alterations in anatomical structure, neurochemical and metabolic pathways. Although it has been established in animal models that neurochemical pathways are heavily affected by early visual deprivation, the effects of blindness on these pathways in humans is still not well characterized. Here, using 1 H magnetic resonance spectroscopy in nine early blind and normally sighted subjects, we find that early blindness is associated with higher levels of creatine, choline and myo -Inositol and indications of lower levels of GABA within the occipital cortex. These results suggest that the cross-modal responses associated with early blindness may, at least in part, be driven by changes within occipital biochemical pathways.

The precise pathogenic mechanisms of Huntington's disease (HD) are unknown but can be tested in vivo using proton magnetic resonance spectroscopy ((1)H MRS) to measure neurochemical changes. The objective of this study was to evaluate neurochemical differences in HD gene mutation carriers (HGMCs) versus controls and to investigate relationships among function, brain structure, and neurochemistry in HD. Because previous (1)H MRS studies have yielded varied conclusions about HD neurochemical changes, an additional goal was to compare two (1)H MRS data analysis approaches. HGMCs with premanifest to early HD and controls underwent evaluation of motor function, magnetic resonance imaging, and localized (1)H MRS in the caudate and the frontal lobe. Analytical approaches that were tested included absolute quantitation (unsuppressed water signal as an internal reference) and relative quantification (calculating ratios of all neurochemical signals within a voxel). We identified a suite of neurochemicals that were reduced in concentration proportionally to loss of caudate volume in HGMCs. Caudate concentrations of N-acetylaspartate (NAA), creatine, choline, and caudate and frontal lobe concentrations of glutamate plus glutamine (Glx) and glutamate were correlated with caudate volume in HGMCs. The relative, but not the absolute, quantitation approach revealed disease-related differences; the Glx signal was decreased relative to other neurochemicals in the caudate of HGMCs versus controls. This is the first study to demonstrate a correlation among structure, function, and chemical measures in HD brain. Additionally, we demonstrate that a relative quantitation approach may enable the magnification of subtle differences between groups. Observation of decreased Glx suggests that glutamate signaling may be disrupted relatively early in HD, which has important implications for therapeutic approaches.

Current electroencephalography (EEG) Brain-Computer Interface (BCI) methods typically use control signals (P300, modulated slow cortical potentials, mu or beta rhythm) that suffer from a slow time scale, low signal to noise ratio, and/or low spatial resolution. High gamma oscillations (70–150 Hz; HG) are rapidly evolving, spatially localized signals and recent studies have shown that EEG can reliably detect task-related HG power changes. In this chapter, we discuss how we capitalize on EEG resolved HG as a control signal for BCI. We use functional magnetic resonance imaging (fMRI) to impose spatial constraints in an effort to improve the signal to noise ratio across the HG band. The overall combination lends itself to a fast-responding, dynamic BCI.

This study examines whether midlife change in episodic memory predicts hippocampal volume in old age. From the Seattle Longitudinal Study we retrospectively identified 84 healthy, cognitively normal individuals, age 52 to 87, whose episodic memory had reliably declined (n = 33), improved (n = 28) or remained stable (n = 23) over a 14-year period in midlife (age 43-63). Midlife memory improvement was associated with 13% larger hippocampal volume (p0.01) in old age (age 66-87), compared with old age individuals whose midlife episodic memory had either declined or remained stable during midlife. Midlife memory change did not predict total hippocampal volume for those currently in late middle age (age 52-65). The pattern of findings was not modified by gender, apolipoprotein ε4 status, education or current memory performance. Change in midlife memory scores over 14 years, but not any single assessment, predicted hippocampal volumes in old age, emphasizing the importance of longitudinal data in examining brain-cognition relationships. These findings suggest that improvement in memory in midlife is associated with sparing of hippocampal volume in later life.

Removal of the anterior temporal lobe (ATL) is an effective surgical treatment for intractable temporal lobe epilepsy but carries a risk of language and verbal memory deficits. Preoperative localization of functional zones in the ATL might help reduce these risks, yet fMRI protocols in current widespread use produce very little activation in this region. Based on recent evidence suggesting a role for the ATL in semantic integration, we designed an fMRI protocol comparing comprehension of brief narratives (Story task) with a semantically shallow control task involving serial arithmetic (Math task). The Story > Math contrast elicited strong activation throughout the ATL, lateral temporal lobe, and medial temporal lobe bilaterally in an initial cohort of 18 healthy participants. The task protocol was then implemented at 6 other imaging centers using identical methods. Data from a second cohort of participants scanned at these centers closely replicated the results from the initial cohort. The Story-Math protocol provides a reliable method for activation of surgical regions of interest in the ATL. The bilateral activation supports previous claims that conceptual processing involves both temporal lobes. Used in combination with language lateralization measures, reliable ATL activation maps may be useful for predicting cognitive outcome in ATL surgery, though the validity of this approach needs to be established in a prospective surgical series.

Recent evidence suggests that a rapid, automatic face detection system is supported by subcortical structures including the amygdala, pulvinar, and superior colliculus. Early-emerging abnormalities in these structures may be related to reduced social orienting in children with autism, and subsequently, to aberrant development of cortical circuits involved in face processing. Our objective was to determine whether functional abnormalities in the subcortical face processing system are present in adults with autism spectrum disorders (ASD) during supraliminal fearful face processing. Participants included twenty-eight individuals with ASD and 25 controls group-matched on age, IQ, and behavioral performance. The ASD group met diagnostic criteria on the ADI-R, ADOS-G, and DSM-IV. Both the ASD and control groups showed significant activation in bilateral fusiform gyri. The control group exhibited additional significant responses in the right amygdala, right pulvinar, and bilateral superior colliculi. In the direct group comparison, the controls showed significantly greater activation in the left amygdala, bilateral fusiform gyrus, right pulvinar, and bilateral superior colliculi. No brain region showed significantly greater activation in the ASD group compared to the controls. Thus, basic rapid face identification mechanisms appear to be functional in ASD. However, individuals with ASD failed to engage the subcortical brain regions involved in face detection and automatic emotional face processing, suggesting a core mechanism for impaired socioemotional processing in ASD. Neural abnormalities in this system may contribute to early-emerging deficits in social orienting and attention, the putative precursors to abnormalities in social cognition and cortical face processing specialization.

Serial diffusion tensor imaging scans were collected at baseline and 1 year follow-up to investigate the neurodegenerative profile of white matter (WM) in seven individuals with the Huntington's Disease (HD) gene mutation and seven control subjects matched on age and gender. In the HD subjects, but not controls, a significant reduction of fractional anisotropy (FA), a measure of WM integrity, between baseline and follow-up was evident throughout the brain. In addition, a DTI scalar associated with the stability of axons, axial diffusivity, showed significant longitudinal decreases from year 1 to year 2 in HD subjects, declines that overlapped to greater degree with FA discrepancies than longitudinal increases in radial diffusivity, a DTI variable sensitive to demylinization. These preliminary results provide the first longitudinal DTI evidence of WM degeneration in HD and support the notion that FA abnormalities in HD may be a result of axonal injury or withdrawal. These results suggest that longitudinal FA changes may serve as a neuropathological biomarker in HD.