Prospective multicenter study of continuous tonic-clonic seizure monitoring on Apple Watch in epilepsy monitoring units and ambulatory environments.

OBJECTIVE: Evaluate the performance of a custom application developed for tonic-clonic seizure (TCS) monitoring on a consumer-wearable (Apple Watch) device. METHODS: Participants with a history of convulsive epileptic seizures were recruited for either Epilepsy Monitoring Unit (EMU) or ambulatory (AMB) monitoring; participants without epilepsy (normal controls [NC]) were also enrolled in the AMB group. Both EMU and AMB participants wore an Apple Watch with a research app that continuously recorded accelerometer and photoplethysmography (PPG) signals, and ran a fixed-and-frozen tonic-clonic seizure detection algorithm during the testing period. This algorithm had been previously developed and validated using a separate training dataset. All EMU convulsive events were validated by video-electroencephalography (video-EEG); AMB events were validated by caregiver reporting and follow-ups. Device performance was characterized and compared to prior monitoring devices through sensitivity, false alarm rate (FAR; false-alarms per 24 h), precision, and detection delay (latency). RESULTS: The EMU group had 85 participants (4,279 h, 19 TCS from 15 participants) enrolled across four EMUs; the AMB group had 21 participants (13 outpatient, 8 NC, 6,735 h, 10 TCS from 3 participants). All but one AMB participant completed the study. Device performance in the EMU group included a sensitivity of 100 % [95 % confidence interval (CI) 79-100 %]; an FAR of 0.05 [0.02, 0.08] per 24 h; a precision of 68 % [48 %, 83 %]; and a latency of 32.07 s [standard deviation (std) 10.22 s]. The AMB group had a sensitivity of 100 % [66-100 %]; an FAR of 0.13 [0.08, 0.24] per 24 h; a precision of 22 % [11 %, 37 %]; and a latency of 37.38 s [13.24 s]. Notably, a single AMB participant was responsible for 8 of 31 false alarms. The AMB FAR excluding this participant was 0.10 [0.07, 0.14] per 24 h. DISCUSSION: This study demonstrates the practicability of TCS monitoring on a popular consumer wearable (Apple Watch) in daily use for people with epilepsy. The monitoring app had a high sensitivity and a substantially lower FAR than previously reported in both EMU and AMB environments.

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.

Stimulating native seizures with neural resonance: a new approach to localize the seizure onset zone.

Successful outcomes in epilepsy surgery rely on the accurate localization of the seizure onset zone. Localizing the seizure onset zone is often a costly and time-consuming process wherein a patient undergoes intracranial EEG monitoring, and a team of clinicians wait for seizures to occur. Clinicians then analyse the intracranial EEG before each seizure onset to identify the seizure onset zone and localization accuracy increases when more seizures are captured. In this study, we develop a new approach to guide clinicians to actively elicit seizures with electrical stimulation. We propose that a brain region belongs to the seizure onset zone if a periodic stimulation at a particular frequency produces large amplitude oscillations in the intracranial EEG network that propagate seizure activity. Such responses occur when there is 'resonance' in the intracranial EEG network, and the resonant frequency can be detected by observing a sharp peak in the magnitude versus frequency response curve, called a Bode plot. To test our hypothesis, we analysed single-pulse electrical stimulation response data in 32 epilepsy patients undergoing intracranial EEG monitoring. For each patient and each stimulated brain region, we constructed a Bode plot by estimating a transfer function model from the intracranial EEG 'impulse' or single-pulse electrical stimulation response. The Bode plots were then analysed for evidence of resonance. First, we showed that when Bode plot features were used as a marker of the seizure onset zone, it distinguished successful from failed surgical outcomes with an area under the curve of 0.83, an accuracy that surpassed current methods of analysis with cortico-cortical evoked potential amplitude and cortico-cortical spectral responses. Then, we retrospectively showed that three out of five native seizures accidentally triggered in four patients during routine periodic stimulation at a given frequency corresponded to a resonant peak in the Bode plot. Last, we prospectively stimulated peak resonant frequencies gleaned from the Bode plots to elicit seizures in six patients, and this resulted in an induction of three seizures and three auras in these patients. These findings suggest neural resonance as a new biomarker of the seizure onset zone that can guide clinicians in eliciting native seizures to more quickly and accurately localize the seizure onset zone.

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.

Seizure triggers identified postictally using a smart watch reporting system.

Persons with epilepsy (PWE) often report that seizure triggers can influence the occurrence and timing of seizures. Some previous studies of seizure triggers have relied on retrospective daily seizure diaries or surveys pertaining to all past seizures, recent and/or remote, in respondents. To assess the characteristics of seizure triggers at the granularity of individual seizures, we used a seizure-tracking app, called EpiWatch, on a smart watch system (Apple Watch and iPhone) in a national study of PWE. Participants tracked seizures during a 16-month study period using the EpiWatch app. Seizure tracking was initiated during a pre-ictal state or as the seizure was occurring and included collection of biosensor data, responsiveness testing, and completion of an immediate post-seizure survey. The survey evaluated seizure types, auras or warning symptoms, loss of awareness, use of rescue medication, and seizure triggers for each tracked seizure. Two hundred and thirty four participants tracked 2493 seizures. Ninety six participants reported triggers in 650 seizures: stress (65.8%), lack of sleep (30.5%), menstrual cycle (19.7%), and overexertion (18%) were the most common. Participants often reported having multiple combined triggers, frequent stress with lack of sleep, overexertion, or menses. Participants who reported triggers were more likely to be taking 3 or more anti-seizure medications compared to participants who did not report triggers. Participants were able to interact with the app and use mobile technology in this national study to record seizures and report common seizure triggers. These findings demonstrate the promise of longitudinal, self-reported data to improve our understanding of epilepsy and its related comorbidities.

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.

Graph theoretical analysis of evoked potentials shows network influence of epileptogenic mesial temporal region.

It is now widely accepted that seizures arise from the coordinated activity of epileptic networks, and as a result, traditional methods of analyzing seizures have been augmented by techniques like single-pulse electrical stimulation (SPES) that estimate effective connectivity in brain networks. We used SPES and graph analytics in 18 patients undergoing intracranial EEG monitoring to investigate effective connectivity between recording sites within and outside mesial temporal structures. We compared evoked potential amplitude, network density, and centrality measures inside and outside the mesial temporal region (MTR) across three patient groups: focal epileptogenic MTR, multifocal epileptogenic MTR, and non-epileptogenic MTR. Effective connectivity within the MTR had significantly greater magnitude (evoked potential amplitude) and network density, regardless of epileptogenicity. However, effective connectivity between MTR and surrounding non-epileptogenic regions was of greater magnitude and density in patients with focal epileptogenic MTR compared to patients with multifocal epileptogenic MTR and those with non-epileptogenic MTR. Moreover, electrodes within focal epileptogenic MTR had significantly greater outward network centrality compared to electrodes outside non-epileptogenic regions and to multifocal and non-epileptogenic MTR. Our results indicate that the MTR is a robustly connected subnetwork that can exert an overall elevated propagative influence over other brain regions when it is epileptogenic. Understanding the underlying effective connectivity and roles of epileptogenic regions within the larger network may provide insights that eventually lead to improved surgical outcomes.

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.

Increased mirror overflow movements in ADHD are associated with altered EEG alpha/beta band desynchronization.

Children with ADHD show developmentally abnormal levels of mirror overflow-unintentional movements occurring symmetrically opposite of intentional movements. Because mirror overflow correlates with ADHD behavioral symptoms, the study of disinhibition in motor control may shed light on physiologic mechanisms underlying impaired behavioral/cognitive control. This is a case-controlled study of EEG recording from 25 children with ADHD and 25 typically developing (TD) controls performing unilateral sequential finger tapping, with overflow movements measured using electronic goniometers. Consistent with previously published findings, children with ADHD showed increased mirror overflow as compared with TD peers. EEG findings revealed less lateralized alpha modulation (event-related desynchronization; ERD) and decreased magnitude of beta ERD in ADHD; both alpha and beta ERD reflect cortical activation. Moderation analysis revealed a significant association between beta ERD and overflow, independent of diagnosis; and an equivocal (p = .08) effect of diagnosis on the relationship between alpha ERD and overflow, with a significant effect in children with ADHD but not TD children. These results suggest two mechanisms involved with mirror overflow: one reflected in beta ipsilateral to the intentional movement and relevant to both children with ADHD and controls, and the other seemingly more specific to ADHD (alpha, contralateral to movement).

Antiepileptic drug withdrawal and seizure severity in the epilepsy monitoring unit.

OBJECTIVE: The goal of this study was to identify a strategy for antiepileptic drug (AED) reduction to allow efficient recording of focal seizures (FS) in patients undergoing video-electroencephalography (EEG) in an epilepsy monitoring unit (EMU) while avoiding the risk of complications associated with more severe seizure types. METHODS: We retrospectively reviewed consecutive patients admitted to our institution's EMU from July 1, 2016 to December 31, 2017. We included 114 presurgical patients who had AEDs reduced and at least one seizure during the admission. We compared AED dosages at which FS versus focal to bilateral tonic-clonic seizures (f-BTCS), seizure clusters, and lorazepam administration occurred. We also examined rate of AED reduction and seizure types. We used a receiver-operating characteristic (ROC) curve to identify a dose maximizing FS and minimizing other seizure types. RESULTS: Antiepileptic drug withdrawal rates ranged from 0 to 100% in the first 24 h (mean: 20%, standard deviation: 20%). Focal to bilateral tonic-clonic seizures and lorazepam administration occurred at a lower median AED dose than did FS (0%, 7.2%, and 43.8%, respectively, expressed as a percentage of the patient's outpatient daily AED dose; p < 0.001). A daily EMU-administered dose of one-third of the patient's outpatient AED dose allowed 55.0% of FS to occur while avoiding 82.0% of more severe seizure types. The seizure types had no difference in rate of AED withdrawal in the first 24 h of EMU stay. CONCLUSIONS: Focal seizures occurred at a higher AED dose than did f-BTCS. This may imply that a low minimally effective dose of AED could allow FS to be recorded while providing protection against f-BTCS. This strategy could improve efficacy and safety in the EMU.

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.

Spatiotemporal dynamics of word retrieval in speech production revealed by cortical high-frequency band activity.

Word retrieval is core to language production and relies on complementary processes: the rapid activation of lexical and conceptual representations and word selection, which chooses the correct word among semantically related competitors. Lexical and conceptual activation is measured by semantic priming. In contrast, word selection is indexed by semantic interference and is hampered in semantically homogeneous (HOM) contexts. We examined the spatiotemporal dynamics of these complementary processes in a picture naming task with blocks of semantically heterogeneous (HET) or HOM stimuli. We used electrocorticography data obtained from frontal and temporal cortices, permitting detailed spatiotemporal analysis of word retrieval processes. A semantic interference effect was observed with naming latencies longer in HOM versus HET blocks. Cortical response strength as indexed by high-frequency band (HFB) activity (70-150 Hz) amplitude revealed effects linked to lexical-semantic activation and word selection observed in widespread regions of the cortical mantle. Depending on the subsecond timing and cortical region, HFB indexed semantic interference (i.e., more activity in HOM than HET blocks) or semantic priming effects (i.e., more activity in HET than HOM blocks). These effects overlapped in time and space in the left posterior inferior temporal gyrus and the left prefrontal cortex. The data do not support a modular view of word retrieval in speech production but rather support substantial overlap of lexical-semantic activation and word selection mechanisms in the brain.

Strategies for non-EEG seizure detection and timing for alerting and interventions with tonic-clonic seizures.

Sudden unexpected death in epilepsy (SUDEP) is a common cause of death in epilepsy and frequently occurs following generalized tonic-clonic seizures (GTCS). Non-electroencephalography (EEG) seizure detection systems using mobile sensor devices permit caregivers to assist patients during seizures and may reduce risks for complications of seizures such as injuries and SUDEP. We review changes in accelerometry, electrodermal activity, and heart rate associated with tonic-clonic seizures and their use in detection systems, including multimodal detectors. We reviewed current and past publications reporting data on linkage between GTCS, post-ictal generalized EEG suppression (PGES), and ventilatory dysfunction. The timing and duration of postictal immobility and respiratory dysfunction associated with convulsions help identify which patients might benefit the most from seizure monitoring and from benchmarks for the timing of seizure detection, caregiver alerting, and interventions.

Electrocorticographic high-gamma modulation with passive listening paradigm for pediatric extraoperative language mapping.

OBJECTIVE: This prospective study compared the topography of high-gamma modulation (HGM) during a story-listening task requiring negligible patient cooperation, with the conventional electrical stimulation mapping (ESM) using a picture-naming task, for presurgical language localization in pediatric drug-resistant epilepsy. METHODS: Patients undergoing extraoperative monitoring with subdural electrodes were included. Electrocorticographic signals were recorded during quiet baseline and a story-listening task. The likelihood of 70- to 150-Hz power modulation during the listening task relative to the baseline was estimated for each electrode and plotted on a cortical surface model. Sensitivity, specificity, accuracy, and diagnostic odds ratio (DOR) were estimated compared to ESM, using a meta-analytic framework. RESULTS: Nineteen patients (10 with left hemisphere electrodes) aged 4-19 years were analyzed. HGM during story listening was observed in bilateral posterior superior temporal, angular, supramarginal, and inferior frontal gyri, along with anatomically defined language association areas. Compared to either cognitive or both cognitive and orofacial sensorimotor interference with naming during ESM, left hemisphere HGM showed high specificity (0.82-0.84), good accuracy (0.66-0.70), and DOR of 2.23 and 3.24, respectively. HGM was a better classifier of ESM language sites in the left temporoparietal cortex compared to the frontal lobe. Incorporating visual naming with the story-listening task substantially improved the accuracy (0.80) and DOR (13.61) of HGM mapping, while the high specificity (0.85) was retained. In the right hemisphere, no ESM sites for aphasia were seen, and the results of HGM and ESM comparisons were not significant. SIGNIFICANCE: HGM associated with story listening is a specific determinant of left hemisphere ESM language sites. It can be used for presurgical language mapping in children who cannot cooperate with conventional language tasks requiring active engagement. Incorporation of additional language tasks, if feasible, can further improve the diagnostic accuracy of language localization with HGM.

Common data elements for epilepsy mobile health systems.

OBJECTIVE: Common data elements (CDEs) are currently unavailable for mobile health (mHealth) in epilepsy devices and related applications. As a result, despite expansive growth of new digital services for people with epilepsy, information collected is often not interoperable or directly comparable. We aim to correct this problem through development of industry-wide standards for mHealth epilepsy data. METHODS: Using a group of stakeholders from industry, academia, and patient advocacy organizations, we offer a consensus statement for the elements that may facilitate communication among different systems. RESULTS: A consensus statement is presented for epilepsy mHealth CDEs. SIGNIFICANCE: Although it is not exclusive, we believe that the use of a minimal common information denominator, specifically these CDEs, will promote innovation, accelerate scientific discovery, and enhance clinical usage across applications and devices in the epilepsy mHealth space. As a consequence, people with epilepsy will have greater flexibility and ultimately more powerful tools to improve their lives.

ECoG high-gamma modulation versus electrical stimulation for presurgical language mapping.

OBJECTIVE: This meta-analysis compared diagnostic validity of electrocorticographic (ECoG) high-γ modulation (HGM) with electrical stimulation mapping (ESM) for presurgical language localization. METHODS: From a structured literature search, studies with electrode level data comparing ECoG HGM and ESM for language localization were included in the meta-analysis. Outcomes included global measures of diagnostic validity: area under the summary receiver operating characteristic (SROC) curve (AUC), and diagnostic odds ratio (DOR); as well as pooled estimates of sensitivity and specificity. Clinical and technical determinants of sensitivity/specificity were explored. RESULTS: Fifteen studies were included in qualitative synthesis, and 10 studies included in the meta-analysis (number of patients 1-17, mean age 10.3-53.6years). Overt picture naming was the most commonly used task for language mapping with either method. Electrocorticographic high-γ modulation was analyzed at 50-400Hz with different bandwidths in individual studies. For ESM, pulse duration, train duration, and maximum current varied greatly among studies. Sensitivity (0.23-0.99), specificity (0.48-0.96), and DOR (1.45-376.28) varied widely across studies. The pooled estimates are: sensitivity 0.61 (95% CI 0.44, 0.76), specificity 0.79 (95% CI 0.68, 0.88), and DOR 6.44 (95% CI 3.47, 11.94). Area under the SROC curve was 0.77. Results of bivariate meta-regression were limited by small samples for individual variables. CONCLUSION: Electrocorticographic high-γ modulation is a specific but not sensitive method for language localization compared with gold-standard ESM. Given the pooled DOR of 6.44 and AUC of 0.77, ECoG HGM can fairly reliably ascertain electrodes overlying ESM cortical language sites.

Bottom-of-sulcus focal cortical dysplasia presenting as epilepsia partialis continua multimodality characterization including 7T MRI.

INTRODUCTION: Bottom-of-sulcus focal cortical dysplasias are an under recognized, surgically treatable cause of focal epilepsy. Resection can dramatically reduce the seizure burden for children with refractory epilepsy, or eliminate seizures altogether. MATERIAL AND METHODS: We report the case and present the results of multimodality evaluation of a 15-year-old young man who presented with long-standing partial epilepsy affecting his right leg, which over the years became refractory to therapy. RESULTS: High-resolution 3T MRI images acquired as a dedicated epilepsyprotocol were initially interpreted as unremarkable. On further review by an experienced specialist aware of clinical and electroencephalographic findings, a subtle focal cortical dysplasia was identified at the bottom of a sulcus near the medial aspect of the left precentral gyrus. After confirmation of the extent of the lesion with PET and ultra-high field 7T MRI, the patient underwent cortical mapping and focal resection and remains free of seizures. COCLUSIONS: This case emphasizes the need for a multidisciplinary approach to the evaluation of refractory focal epilepsy in children and highlights the potential role of ultra-high field 7T MRI in identifying the often subtle causative anatomic abnormalities.

Redefining the role of Broca's area in speech.

For over a century neuroscientists have debated the dynamics by which human cortical language networks allow words to be spoken. Although it is widely accepted that Broca's area in the left inferior frontal gyrus plays an important role in this process, it was not possible, until recently, to detail the timing of its recruitment relative to other language areas, nor how it interacts with these areas during word production. Using direct cortical surface recordings in neurosurgical patients, we studied the evolution of activity in cortical neuronal populations, as well as the Granger causal interactions between them. We found that, during the cued production of words, a temporal cascade of neural activity proceeds from sensory representations of words in temporal cortex to their corresponding articulatory gestures in motor cortex. Broca's area mediates this cascade through reciprocal interactions with temporal and frontal motor regions. Contrary to classic notions of the role of Broca's area in speech, while motor cortex is activated during spoken responses, Broca's area is surprisingly silent. Moreover, when novel strings of articulatory gestures must be produced in response to nonword stimuli, neural activity is enhanced in Broca's area, but not in motor cortex. These unique data provide evidence that Broca's area coordinates the transformation of information across large-scale cortical networks involved in spoken word production. In this role, Broca's area formulates an appropriate articulatory code to be implemented by motor cortex.

Semantic attributes are encoded in human electrocorticographic signals during visual object recognition.

Non-invasive neuroimaging studies have shown that semantic category and attribute information are encoded in neural population activity. Electrocorticography (ECoG) offers several advantages over non-invasive approaches, but the degree to which semantic attribute information is encoded in ECoG responses is not known. We recorded ECoG while patients named objects from 12 semantic categories and then trained high-dimensional encoding models to map semantic attributes to spectral-temporal features of the task-related neural responses. Using these semantic attribute encoding models, untrained objects were decoded with accuracies comparable to whole-brain functional Magnetic Resonance Imaging (fMRI), and we observed that high-gamma activity (70-110Hz) at basal occipitotemporal electrodes was associated with specific semantic dimensions (manmade-animate, canonically large-small, and places-tools). Individual patient results were in close agreement with reports from other imaging modalities on the time course and functional organization of semantic processing along the ventral visual pathway during object recognition. The semantic attribute encoding model approach is critical for decoding objects absent from a training set, as well as for studying complex semantic encodings without artificially restricting stimuli to a small number of semantic categories.