Lexicality-Modulated Influence of Auditory Cortex on Subthalamic Nucleus During Motor Planning for Speech.

Speech requires successful information transfer within cortical-basal ganglia loop circuits to produce the desired acoustic output. For this reason, up to 90% of Parkinson's disease patients experience impairments of speech articulation. Deep brain stimulation (DBS) is highly effective in controlling the symptoms of Parkinson's disease, sometimes alongside speech improvement, but subthalamic nucleus (STN) DBS can also lead to decreases in semantic and phonological fluency. This paradox demands better understanding of the interactions between the cortical speech network and the STN, which can be investigated with intracranial EEG recordings collected during DBS implantation surgery. We analyzed the propagation of high-gamma activity between STN, superior temporal gyrus (STG), and ventral sensorimotor cortices during reading aloud via event-related causality, a method that estimates strengths and directionalities of neural activity propagation. We employed a newly developed bivariate smoothing model based on a two-dimensional moving average, which is optimal for reducing random noise while retaining a sharp step response, to ensure precise embedding of statistical significance in the time-frequency space. Sustained and reciprocal neural interactions between STN and ventral sensorimotor cortex were observed. Moreover, high-gamma activity propagated from the STG to the STN prior to speech onset. The strength of this influence was affected by the lexical status of the utterance, with increased activity propagation during word versus pseudoword reading. These unique data suggest a potential role for the STN in the feedforward control of speech.

The dynamics of cortical interactions in visual recognition of object category: living versus nonliving.

Noninvasive brain imaging studies have shown that higher visual processing of objects occurs in neural populations that are separable along broad semantic categories, particularly living versus nonliving objects. However, because of their limited temporal resolution, these studies have not been able to determine whether broad semantic categories are also reflected in the dynamics of neural interactions within cortical networks. We investigated the time course of neural propagation among cortical areas activated during object naming in 12 patients implanted with subdural electrode grids prior to epilepsy surgery, with a special focus on the visual recognition phase of the task. Analysis of event-related causality revealed significantly stronger neural propagation among sites within ventral temporal lobe (VTL) at early latencies, around 250 ms, for living objects compared to nonliving objects. Differences in other features, including familiarity, visual complexity, and age of acquisition, did not significantly change the patterns of neural propagation. Our findings suggest that the visual processing of living objects relies on stronger causal interactions among sites within VTL, perhaps reflecting greater integration of visual feature processing. In turn, this may help explain the fragility of naming living objects in neurological diseases affecting VTL.

Source-sink connectivity: a novel interictal EEG marker for seizure localization.

Over 15 million epilepsy patients worldwide have drug-resistant epilepsy. Successful surgery is a standard of care treatment but can only be achieved through complete resection or disconnection of the epileptogenic zone, the brain region(s) where seizures originate. Surgical success rates vary between 20% and 80%, because no clinically validated biological markers of the epileptogenic zone exist. Localizing the epileptogenic zone is a costly and time-consuming process, which often requires days to weeks of intracranial EEG (iEEG) monitoring. Clinicians visually inspect iEEG data to identify abnormal activity on individual channels occurring immediately before seizures or spikes that occur interictally (i.e. between seizures). In the end, the clinical standard mainly relies on a small proportion of the iEEG data captured to assist in epileptogenic zone localization (minutes of seizure data versus days of recordings), missing opportunities to leverage these largely ignored interictal data to better diagnose and treat patients. IEEG offers a unique opportunity to observe epileptic cortical network dynamics but waiting for seizures increases patient risks associated with invasive monitoring. In this study, we aimed to leverage interictal iEEG data by developing a new network-based interictal iEEG marker of the epileptogenic zone. We hypothesized that when a patient is not clinically seizing, it is because the epileptogenic zone is inhibited by other regions. We developed an algorithm that identifies two groups of nodes from the interictal iEEG network: those that are continuously inhibiting a set of neighbouring nodes ('sources') and the inhibited nodes themselves ('sinks'). Specifically, patient-specific dynamical network models were estimated from minutes of iEEG and their connectivity properties revealed top sources and sinks in the network, with each node being quantified by source-sink metrics. We validated the algorithm in a retrospective analysis of 65 patients. The source-sink metrics identified epileptogenic regions with 73% accuracy and clinicians agreed with the algorithm in 93% of seizure-free patients. The algorithm was further validated by using the metrics of the annotated epileptogenic zone to predict surgical outcomes. The source-sink metrics predicted outcomes with an accuracy of 79% compared to an accuracy of 43% for clinicians' predictions (surgical success rate of this dataset). In failed outcomes, we identified brain regions with high metrics that were untreated. When compared with high frequency oscillations, the most commonly proposed interictal iEEG feature for epileptogenic zone localization, source-sink metrics outperformed in predictive power (by a factor of 1.2), suggesting they may be an interictal iEEG fingerprint of the epileptogenic zone.

Significance of event related causality (ERC) in eloquent neural networks.

Neural activity emerges and propagates swiftly between brain areas. Investigation of these transient large-scale flows requires sophisticated statistical models. We present a method for assessing the statistical confidence of event-related neural propagation. Furthermore, we propose a criterion for statistical model selection, based on both goodness of fit and width of confidence intervals. We show that event-related causality (ERC) with two-dimensional (2D) moving average, is an efficient estimator of task-related neural propagation and that it can be used to determine how different cognitive task demands affect the strength and directionality of neural propagation across human cortical networks. Using electrodes surgically implanted on the surface of the brain for clinical testing prior to epilepsy surgery, we recorded electrocorticographic (ECoG) signals as subjects performed three naming tasks: naming of ambiguous and unambiguous visual objects, and as a contrast, naming to auditory description. ERC revealed robust and statistically significant patterns of high gamma activity propagation, consistent with models of visually and auditorily cued word production. Interestingly, ambiguous visual stimuli elicited more robust propagation from visual to auditory cortices relative to unambiguous stimuli, whereas naming to auditory description elicited propagation in the opposite direction, consistent with recruitment of modalities other than those of the stimulus during object recognition and naming. The new method introduced here is uniquely suitable to both research and clinical applications and can be used to estimate the statistical significance of neural propagation for both cognitive neuroscientific studies and functional brain mapping prior to resective surgery for epilepsy and brain tumors.

Spatial-Temporal Functional Mapping Combined With Cortico-Cortical Evoked Potentials in Predicting Cortical Stimulation Results.

Functional human brain mapping is commonly performed during invasive monitoring with intracranial electroencephalographic (iEEG) electrodes prior to resective surgery for drug- resistant epilepsy. The current gold standard, electrocortical stimulation mapping (ESM), is time -consuming, sometimes elicits pain, and often induces after discharges or seizures. Moreover, there is a risk of overestimating eloquent areas due to propagation of the effects of stimulation to a broader network of language cortex. Passive iEEG spatial-temporal functional mapping (STFM) has recently emerged as a potential alternative to ESM. However, investigators have observed less correspondence between STFM and ESM maps of language than between their maps of motor function. We hypothesized that incongruities between ESM and STFM of language function may arise due to propagation of the effects of ESM to cortical areas having strong effective connectivity with the site of stimulation. We evaluated five patients who underwent invasive monitoring for seizure localization, whose language areas were identified using ESM. All patients performed a battery of language tasks during passive iEEG recordings. To estimate the effective connectivity of stimulation sites with a broader network of task-activated cortical sites, we measured cortico-cortical evoked potentials (CCEPs) elicited across all recording sites by single-pulse electrical stimulation at sites where ESM was performed at other times. With the combination of high gamma power as well as CCEPs results, we trained a logistic regression model to predict ESM results at individual electrode pairs. The average accuracy of the classifier using both STFM and CCEPs results combined was 87.7%, significantly higher than the one using STFM alone (71.8%), indicating that the correspondence between STFM and ESM results is greater when effective connectivity between ESM stimulation sites and task-activated sites is taken into consideration. These findings, though based on a small number of subjects to date, provide preliminary support for the hypothesis that incongruities between ESM and STFM may arise in part from propagation of stimulation effects to a broader network of cortical language sites activated by language tasks, and suggest that more studies, with larger numbers of patients, are needed to understand the utility of both mapping techniques in clinical practice.

LCA and economic study on the local oxygen supply in Central Europe during the COVID-19 pandemic.

Medical oxygen is the key to survival for COVID-19 patients. To meet the pandemic-driven oxygen demand spike, local hospitals began searching for a suitable medical oxygen delivery system. Among the studies published on the impact of COVID-19 on a range of aspects, including the global economy and the environment, no study has been conducted on the environmental impact of medical oxygen supply to hospitals under epidemic conditions. In this paper the authors perform a comparative Life Cycle Assessment (LCA) to evaluate the environmental and economic impact of three scenarios (oxygen cylinders, liquid oxygen in tanks and on-site oxygen production) of local oxygen supply to hospitals in Poland. The LCA was performed according to ISO 14040 -14044 standards requirements, using the SimaPro 9.0 software. Results from the analysis showed that the Global Warming Potential (GWP) and Fine Particulate Matter Formation Potential (FPMFP) indicators for the liquid oxygen in tank scenario are the lowest and equal 265 kg CO2 eq and 0.309 kg PM2.5 eq. respectively. The greatest terrestrial acidification reductions (-1.38 kg SO2 eq) can be achieved when applying the on-site oxygen production scenario. Our findings revealed that the oxygen in cylinders scenario has the most harmful impact on the environment. The economic analysis was performed in order to compare the monthly and annual operational costs of analysed scenarios. The results show that hospitals sustain the lowest annual costs when using the on-site oxygen production scenario.

During vigilance to painful stimuli: slower response rate is related to high trait anxiety, whereas faster response rate is related to high state anxiety.

A pathological increase in vigilance, or hypervigilance, may be related to pain intensity in some clinical pain syndromes and may result from attention bias to salient stimuli mediated by anxiety. During a continuous performance task where subjects discriminated painful target stimuli from painful nontargets, we measured detected targets (hits), nondetected targets (misses), nondetected nontargets (correct rejections), and detected nontargets (false alarms). Using signal detection theory, we calculated response bias, the tendency to endorse a stimulus as a target, and discriminability, the ability to discriminate a target from nontarget. Owing to the relatively slow rate of stimulus presentation, our primary hypothesis was that sustained performance would result in a more conservative response bias reflecting a lower response rate over time on task. We found a more conservative response bias with time on task and no change in discriminability. We predicted that greater state and trait anxiety would lead to a more liberal response bias. A multivariable model provided partial support for our prediction; high trait anxiety related to a more conservative response bias (lower response rate), whereas high state anxiety related to a more liberal bias. This inverse relationship of state and trait anxiety is consistent with reports of effects of state and trait anxiety on reaction times to threatening stimuli. In sum, we report that sustained attention to painful stimuli was associated with a decrease in the tendency of the subject to respond to any stimulus over time on task, whereas the ability to discriminate target from nontarget remains unchanged.NEW & NOTEWORTHY During a series of painful stimuli requiring subjects to respond to targets, we separated response willingness from ability to discriminate targets from nontargets. Response willingness declined during the task, with no change in subjects' ability to discriminate, consistent with previous vigilance studies. High trait anxious subjects were less willing to respond and showed slower reaction times to hits than low anxious subjects. This study reveals an important role of trait anxiety in pain vigilance.

The Dynamics of Language Network Interactions in Lexical Selection: An Intracranial EEG Study.

Speaking in sentences requires selection from contextually determined lexical representations. Although posterior temporal cortex (PTC) and Broca's areas play important roles in storage and selection, respectively, of lexical representations, there has been no direct evidence for physiological interactions between these areas on time scales typical of lexical selection. Using intracranial recordings of cortical population activity indexed by high-gamma power (70-150 Hz) modulations, we studied the causal dynamics of cortical language networks while epilepsy surgery patients performed a sentence completion task in which the number of potential lexical responses was systematically varied. Prior to completion of sentences with more response possibilities, Broca's area was not only more active, but also exhibited more local network interactions with and greater top-down influences on PTC, consistent with activation of, and competition between, more lexical representations. These findings provide the most direct experimental support yet for network dynamics playing a role in lexical selection among competing alternatives during speech production.

Behavioral, Physiological and EEG Activities Associated with Conditioned Fear as Sensors for Fear and Anxiety.

Anxiety disorders impose substantial costs upon public health and productivity in the USA and worldwide. At present, these conditions are quantified by self-report questionnaires that only apply to behaviors that are accessible to consciousness, or by the timing of responses to fear- and anxiety-related words that are indirect since they do not produce fear, e.g., Dot Probe Test and emotional Stroop. We now review the conditioned responses (CRs) to fear produced by a neutral stimulus (conditioned stimulus CS+) when it cues a painful laser unconditioned stimulus (US). These CRs include autonomic (Skin Conductance Response) and ratings of the CS+ unpleasantness, ability to command attention, and the recognition of the association of CS+ with US (expectancy). These CRs are directly related to fear, and some measure behaviors that are minimally accessible to consciousness e.g., economic scales. Fear-related CRs include non-phase-locked phase changes in oscillatory EEG power defined by frequency and time post-stimulus over baseline, and changes in phase-locked visual and laser evoked responses both of which include late potentials reflecting attention or expectancy, like the P300, or contingent negative variation. Increases (ERS) and decreases (ERD) in oscillatory power post-stimulus may be generalizable given their consistency across healthy subjects. ERS and ERD are related to the ratings above as well as to anxious personalities and clinical anxiety and can resolve activity over short time intervals like those for some moods and emotions. These results could be incorporated into an objective instrumented test that measures EEG and CRs of autonomic activity and psychological ratings related to conditioned fear, some of which are subliminal. As in the case of instrumented tests of vigilance, these results could be useful for the direct, objective measurement of multiple aspects of the risk, diagnosis, and monitoring of therapies for anxiety disorders and anxious personalities.

Changes in human brain dynamics during behavioral priming and repetition suppression.

Behavioral responses to a perceptual stimulus are typically faster with repeated exposure to the stimulus (behavioral priming). This implicit learning mechanism is critical for survival but impaired in a variety of neurological disorders, including Alzheimer's disease. Many studies of the neural bases for behavioral priming have encountered an interesting paradox: in spite of faster behavioral responses, repeated stimuli usually elicit weaker neural responses (repetition suppression). Several neurophysiological models have been proposed to resolve this paradox, but noninvasive techniques for human studies have had insufficient spatial-temporal precision for testing their predictions. Here, we used the unparalleled precision of electrocorticography (ECoG) to analyze the timing and magnitude of task-related changes in neural activation and propagation while patients named novel vs repeated visual objects. Stimulus repetition was associated with faster verbal responses and decreased neural activation (repetition suppression) in ventral occipito-temporal cortex (VOTC) and left prefrontal cortex (LPFC). Interestingly, we also observed increased neural activation (repetition enhancement) in LPFC and other recording sites. Moreover, with analysis of high gamma propagation we observed increased top-down propagation from LPFC into VOTC, preceding repetition suppression. The latter results indicate that repetition suppression and behavioral priming are associated with strengthening of top-down network influences on perceptual processing, consistent with predictive coding models of repetition suppression, and they support a central role for changes in large-scale cortical dynamics in achieving more efficient and rapid behavioral responses.

Subthalamic Nucleus Activity Influences Sensory and Motor Cortex during Force Transduction.

The subthalamic nucleus (STN) is proposed to participate in pausing, or alternately, in dynamic scaling of behavioral responses, roles that have conflicting implications for understanding STN function in the context of deep brain stimulation (DBS) therapy. To examine the nature of event-related STN activity and subthalamic-cortical dynamics, we performed primary motor and somatosensory electrocorticography while subjects (n = 10) performed a grip force task during DBS implantation surgery. Phase-locking analyses demonstrated periods of STN-cortical coherence that bracketed force transduction, in both beta and gamma ranges. Event-related causality measures demonstrated that both STN beta and gamma activity predicted motor cortical beta and gamma activity not only during force generation but also prior to movement onset. These findings are consistent with the idea that the STN participates in motor planning, in addition to the modulation of ongoing movement. We also demonstrated bidirectional information flow between the STN and somatosensory cortex in both beta and gamma range frequencies, suggesting robust STN participation in somatosensory integration. In fact, interactions in beta activity between the STN and somatosensory cortex, and not between STN and motor cortex, predicted PD symptom severity. Thus, the STN contributes to multiple aspects of sensorimotor behavior dynamically across time.

Missed targets, reaction times, and arousal are related to trait anxiety and attention to pain during an experimental vigilance task with a painful target.

Although hypervigilance may play a role in some clinical pain syndromes, experimental vigilance toward painful stimuli has been studied infrequently. We evaluated vigilance toward pain by using a continuous performance task (CPT), in which subjects responded to moderately intense painful target stimuli, occurring in a train of mildly painful nontargets. We assessed nondetected targets (misses), reaction times (RTs), and psychological activation (tense arousal). During time on task in CPTs of other sensory modalities, there is an increase in misses and RTs (vigilance decrement). We hypothesized that our CPT would influence vigilance performance related to pain, anxiety, and limitation of attentional resources. The results showed a decrement in vigilance over time as misses increased, although RTs were unchanged. While mind-wandering did not influence vigilance performance, intrinsic attention to pain drove both hit RTs and number of misses. This resulted in pain-focused subjects performing worse on the CPT pain task with slower RTs and more misses per block. During the CPT, the change in stimulus salience was related to the change in pain intensity, while pain unpleasantness correlated with tense arousal. CPT performance during experimental vigilance to pain and psychological activation were related to trait anxiety, as measured by the Spielberger State-Trait Anxiety Inventory and neuroticism, as measured by the NEO five factor inventory. Trait anxiety and neuroticism may play important roles in an individual's predisposition to dwell on pain and interpret pain as threatening.NEW & NOTEWORTHY Subjects detected moderately painful target stimuli in a train of mildly painful nontarget stimuli, which resulted in vigilance performance metrics including missed targets, reaction times, and psychological activation. These performance metrics were related to intrinsic attention to pain and trait anxiety. Subjects with high trait anxiety and neuroticism scores, with a predisposition to attend to pain, had greater tense arousal and poorer vigilance performance, which may be important psychological aspects of vigilance to pain.

The neural tides of sleep and consciousness revealed by single-pulse electrical brain stimulation.

Wakefulness and sleep arise from global changes in brain physiology that may also govern the flow of neural activity between cortical regions responsible for perceptual processing versus planning and action. To test whether and how the sleep/wake cycle affects the overall propagation of neural activity in large-scale brain networks, we applied single-pulse electrical stimulation (SPES) in patients implanted with intracranial EEG electrodes for epilepsy surgery. SPES elicited cortico-cortical spectral responses at high-gamma frequencies (CCSRHG, 80-150 Hz), which indexes changes in neuronal population firing rates. Using event-related causality (ERC) analysis, we found that the overall patterns of neural propagation among sites with CCSRHG were different during wakefulness and different sleep stages. For example, stimulation of frontal lobe elicited greater propagation toward parietal lobe during slow-wave sleep than during wakefulness. During REM sleep, we observed a decrease in propagation within frontal lobe, and an increase in propagation within parietal lobe, elicited by frontal and parietal stimulation, respectively. These biases in the directionality of large-scale cortical network dynamics during REM sleep could potentially account for some of the unique experiential aspects of this sleep stage. Together these findings suggest that the regulation of conscious awareness and sleep is associated with differences in the balance of neural propagation across large-scale frontal-parietal networks.

Cortical Responses to Input From Distant Areas are Modulated by Local Spontaneous Alpha/Beta Oscillations.

Any given area in human cortex may receive input from multiple, functionally heterogeneous areas, potentially representing different processing threads. Alpha (8-13 Hz) and beta oscillations (13-20 Hz) have been hypothesized by other investigators to gate local cortical processing, but their influence on cortical responses to input from other cortical areas is unknown. To study this, we measured the effect of local oscillatory power and phase on cortical responses elicited by single-pulse electrical stimulation (SPES) at distant cortical sites, in awake human subjects implanted with intracranial electrodes for epilepsy surgery. In 4 out of 5 subjects, the amplitudes of corticocortical evoked potentials (CCEPs) elicited by distant SPES were reproducibly modulated by the power, but not the phase, of local oscillations in alpha and beta frequencies. Specifically, CCEP amplitudes were higher when average oscillatory power just before distant SPES (-110 to -10 ms) was high. This effect was observed in only a subset (0-33%) of sites with CCEPs and, like the CCEPs themselves, varied with stimulation at different distant sites. Our results suggest that although alpha and beta oscillations may gate local processing, they may also enhance the responsiveness of cortex to input from distant cortical sites.

Coexistence of asthma and the obesity-hypoventilation syndrome.

OBJECTIVE: Introduction: With the increasing problem of obesity in the world, high prevalence of asthma in obese persons and high prevalence of sleep breathing disorders related to obesity, the number of patients with coexisting asthma and obesity hypoventilation syndrome is likely to increase. The aim: To evaluate long-term effects of obesity hypoventilation syndrome treatment in the patients with concomitant asthma. PATIENTS AND METHODS: Materials and methods: Obesity hypoventilation syndrome was diagnosed in six adult patients with asthma (body mass index 43.2±5.84 kg/m2, diurnal PaCO2 53.8±8.9 mmHg, apnea/hypopnea index 82±12.8/hour, mean SaO2 during sleep 77.7±6.6%). Four patients were treated with continuous positive airway pressure (CPAP) and two patients - with non-invasive ventilation (NIV). The patients were followed-up for 36±19 months. RESULTS: Results: During the follow-up period daytime PaCO2 decreased to normal values, mean SaO2 during sleep increased to 93±3.1%, p<0.001. No asthma exacerbations were observed. In two patients significant reduction of anti-asthmatic treatment was observed, including withdrawal of chronic oral corticosteroid treatment. CONCLUSION: Conclusions: Obese asthmatic patients with chronic respiratory insufficiency should be checked for concomitant obesity hypoventilation syndrome. Positive airway pressure treatment during sleep (CPAP or NIV) in asthmatic patients with obesity hypoventilation syndrome is well tolerated, leads to reversal of chronic respiratory insufficiency and in some patients may contribute to the improvement of asthma control.

Brain network dynamics in the human articulatory loop.

OBJECTIVE: The articulatory loop is a fundamental component of language function, involved in the short-term buffer of auditory information followed by its vocal reproduction. We characterized the network dynamics of the human articulatory loop, using invasive recording and stimulation. METHODS: We measured high-gamma activity70-110 Hz recorded intracranially when patients with epilepsy either only listened to, or listened to and then reproduced two successive tones by humming. We also conducted network analyses, and analyzed behavioral responses to cortical stimulation. RESULTS: Presentation of the initial tone elicited high-gamma augmentation bilaterally in the superior-temporal gyrus (STG) within 40ms, and in the precentral and inferior-frontal gyri (PCG and IFG) within 160ms after sound onset. During presentation of the second tone, high-gamma augmentation was reduced in STG but enhanced in IFG. The task requiring tone reproduction further enhanced high-gamma augmentation in PCG during and after sound presentation. Event-related causality (ERC) analysis revealed dominant flows within STG immediately after sound onset, followed by reciprocal interactions involving PCG and IFG. Measurement of cortico-cortical evoked-potentials (CCEPs) confirmed connectivity between distant high-gamma sites in the articulatory loop. High-frequency stimulation of precentral high-gamma sites in either hemisphere induced speech arrest, inability to control vocalization, or forced vocalization. Vocalization of tones was accompanied by high-gamma augmentation over larger extents of PCG. CONCLUSIONS: Bilateral PCG rapidly and directly receives feed-forward signals from STG, and may promptly initiate motor planning including sub-vocal rehearsal for short-term buffering of auditory stimuli. Enhanced high-gamma augmentation in IFG during presentation of the second tone may reflect high-order processing of the tone sequence. SIGNIFICANCE: The articulatory loop employs sustained reciprocal propagation of neural activity across a network of cortical sites with strong neurophysiological connectivity.

Human Thalamic Somatosensory Nucleus (Ventral Caudal, Vc) as a Locus for Stimulation by INPUTS from Tactile, Noxious and Thermal Sensors on an Active Prosthesis.

The forebrain somatic sensory locus for input from sensors on the surface of an active prosthesis is an important component of the Brain Machine Interface. We now review the neuronal responses to controlled cutaneous stimuli and the sensations produced by Threshold Stimulation at Microampere current levels (TMIS) in such a locus, the human thalamic Ventral Caudal nucleus (Vc). The responses of these neurons to tactile stimuli mirror those for the corresponding class of tactile mechanoreceptor fiber in the peripheral nerve, and TMIS can evoke sensations like those produced by the stimuli that optimally activate each class. These neuronal responses show a somatotopic arrangement from lateral to medial in the sequence: leg, arm, face and intraoral structures. TMIS evoked sensations show a much more detailed organization into anterior posteriorly oriented rods, approximately 300 microns diameter, that represent smaller parts of the body, such as parts of individual digits. Neurons responding to painful and thermal stimuli are most dense around the posterior inferior border of Vc, and TMIS evoked pain sensations occur in one of two patterns: (i) pain evoked regardless of the frequency or number of spikes in a burst of TMIS; and (ii) the description and intensity of the sensation changes with increasing frequencies and numbers. In patients with major injuries leading to loss of somatic sensory input, TMIS often evokes sensations in the representation of parts of the body with loss of sensory input, e.g., the phantom after amputation. Some patients with these injuries have ongoing pain and pain evoked by TMIS of the representation in those parts of the body. Therefore, thalamic TMIS may produce useful patterned somatotopic feedback to the CNS from sensors on an active prosthesis that is sometimes complicated by TMIS evoked pain in the representation of those parts of the body.

Cortical subnetwork dynamics during human language tasks.

Language tasks require the coordinated activation of multiple subnetworks-groups of related cortical interactions involved in specific components of task processing. Although electrocorticography (ECoG) has sufficient temporal and spatial resolution to capture the dynamics of event-related interactions between cortical sites, it is difficult to decompose these complex spatiotemporal patterns into functionally discrete subnetworks without explicit knowledge of each subnetwork's timing. We hypothesized that subnetworks corresponding to distinct components of task-related processing could be identified as groups of interactions with co-varying strengths. In this study, five subjects implanted with ECoG grids over language areas performed word repetition and picture naming. We estimated the interaction strength between each pair of electrodes during each task using a time-varying dynamic Bayesian network (tvDBN) model constructed from the power of high gamma (70-110Hz) activity, a surrogate for population firing rates. We then reduced the dimensionality of this model using principal component analysis (PCA) to identify groups of interactions with co-varying strengths, which we term functional network components (FNCs). This data-driven technique estimates both the weight of each interaction's contribution to a particular subnetwork, and the temporal profile of each subnetwork's activation during the task. We found FNCs with temporal and anatomical features consistent with articulatory preparation in both tasks, and with auditory and visual processing in the word repetition and picture naming tasks, respectively. These FNCs were highly consistent between subjects with similar electrode placement, and were robust enough to be characterized in single trials. Furthermore, the interaction patterns uncovered by FNC analysis correlated well with recent literature suggesting important functional-anatomical distinctions between processing external and self-produced speech. Our results demonstrate that subnetwork decomposition of event-related cortical interactions is a powerful paradigm for interpreting the rich dynamics of large-scale, distributed cortical networks during human cognitive tasks.

Spatial-temporal functional mapping of language at the bedside with electrocorticography.

OBJECTIVE: To investigate the feasibility and clinical utility of using passive electrocorticography (ECoG) for online spatial-temporal functional mapping (STFM) of language cortex in patients being monitored for epilepsy surgery. METHODS: We developed and tested an online system that exploits ECoG's temporal resolution to display the evolution of statistically significant high gamma (70-110 Hz) responses across all recording sites activated by a discrete cognitive task. We illustrate how this spatial-temporal evolution can be used to study the function of individual recording sites engaged during different language tasks, and how this approach can be particularly useful for mapping eloquent cortex. RESULTS: Using electrocortical stimulation mapping (ESM) as the clinical gold standard for localizing language cortex, the average sensitivity and specificity of online STFM across 7 patients were 69.9% and 83.5%, respectively. Moreover, relative to regions of interest where discrete cortical lesions have most reliably caused language impairments in the literature, the sensitivity of STFM was significantly greater than that of ESM, while its specificity was also greater than that of ESM, though not significantly so. CONCLUSIONS: This study supports the feasibility and clinical utility of online STFM for mapping human language function, particularly under clinical circumstances in which time is limited and comprehensive ESM is impractical.