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Animacy perception, the ability to discern living from non-living entities, is crucial for survival and social interaction, as it includes recognizing abstract concepts such as movement, purpose, and intentions. This process involves interpreting cues that may suggest the intentions or actions of others. It engages the temporal cortex (TC), particularly the superior temporal sulcus (STS) and the adjacent region of the inferior temporal cortex (ITC), as well as the dorsomedial prefrontal cortex (dmPFC). However, it remains unclear how animacy is dynamically encoded over time in these brain areas and whether its processing is distributed or localized. In this study, we addressed these questions by employing a symbolic categorization task involving animate and inanimate objects using natural movie stimuli. Simultaneously, electrocorticography were conducted in both the TC and dmPFC. Time-frequency analysis revealed region-specific frequency representations throughout the observation of the movies. Spatial searchlight decoding analysis demonstrated that animacy processing is represented in a distributed manner. Regions encoding animacy information were found to be dispersed across the fundus and lip of the STS, as well as in the ITC. Next, we examined whether these dispersed regions form functional networks. Independent component analysis revealed that the spatial distribution of the component with the most significant animacy information corresponded with the dispersed regions identified by the spatial decoding analysis. Furthermore, Granger causality analysis indicated that these regions exhibit frequency-specific directional functional connectivity, with a general trend of causal influence from the ITC to STS across multiple frequency bands. Notably, a prominent feedback flow in the alpha band from the ITC to both the ventral bank and fundus of the STS was identified. These findings suggest a distributed and functionally interconnected neural substrate for animacy processing across the STS and ITC. [ABSTRACT FROM AUTHOR]

Introduction: Sleep disorders are common in the general population, necessitating the search for new strategies to address this public health challenge. The study aims to describe the electrocorticographic and behavioral changes in sleep deprived Wistar rats exposed to varying doses of camphor, to assess its effects on sleep and its potential as a sleep-inducing drug. Materials and Methods: For the electrocorticographic evaluation, seventy-two rats were randomly assigned to distinct groups: a control group, a sleep-deprived group, three sleep-deprived groups receiving 10, 20, and 30 mg/kg i.p. of camphor respectively, and three groups that received these doses without sleep deprivation. For the behavioral analysis, twenty-seven rats were divided into three groups, each receiving the same doses as the previous test. Results and Discussion: Our results showed that there was a decrease in the frequency of brain oscillatory patterns when camphor was administered at 10 mg/kg i.p. whereas there was a dose-dependent increase in the spectral power and distribution following the administration of 20 and 30 mg/kg i.p., with the emergence of Delta, Theta, Alpha, and Beta waves. As for the behavioral analysis, it was demonstrated that testicular relaxation, decreased motility, and light sleep induction also occurred in a dose-dependent manner. Thus, we conclude that camphor administration intensifies occipital electrocorticographic patterns in sleep-deprived rats, and its electrocorticographic and behavioral analysis could indicate a potential as a supporting agent in the insomnia treatment. [ABSTRACT FROM AUTHOR]

Animacy perception, the ability to discern living from non-living entities, is crucial for survival and social interaction, as it includes recognizing abstract concepts such as movement, purpose, and intentions. This process involves interpreting cues that may suggest the intentions or actions of others. It engages the temporal cortex (TC), particularly the superior temporal sulcus (STS) and the adjacent region of the inferior temporal cortex (ITC), as well as the dorsomedial prefrontal cortex (dmPFC). However, it remains unclear how animacy is dynamically encoded over time in these brain areas and whether its processing is distributed or localized. In this study, we addressed these questions by employing a symbolic categorization task involving animate and inanimate objects using natural movie stimuli. Simultaneously, electrocorticography were conducted in both the TC and dmPFC. Time-frequency analysis revealed region-specific frequency representations throughout the observation of the movies. Spatial searchlight decoding analysis demonstrated that animacy processing is represented in a distributed manner. Regions encoding animacy information were found to be dispersed across the fundus and lip of the STS, as well as in the ITC. Next, we examined whether these dispersed regions form functional networks. Independent component analysis revealed that the spatial distribution of the component with the most significant animacy information corresponded with the dispersed regions identified by the spatial decoding analysis. Furthermore, Granger causality analysis indicated that these regions exhibit frequency-specific directional functional connectivity, with a general trend of causal influence from the ITC to STS across multiple frequency bands. Notably, a prominent feedback flow in the alpha band from the ITC to both the ventral bank and fundus of the STS was identified. These findings suggest a distributed and functionally interconnected neural substrate for animacy processing across the STS and ITC.

IntroductionSleep disorders are common in the general population, necessitating the search for new strategies to address this public health challenge. The study aims to describe the electrocorticographic and behavioral changes in sleep deprived Wistar rats exposed to varying doses of camphor, to assess its effects on sleep and its potential as a sleep-inducing drug.Materials and MethodsFor the electrocorticographic evaluation, seventy-two rats were randomly assigned to distinct groups: a control group, a sleep-deprived group, three sleep-deprived groups receiving 10, 20, and 30 mg/kg i.p. of camphor respectively, and three groups that received these doses without sleep deprivation. For the behavioral analysis, twenty-seven rats were divided into three groups, each receiving the same doses as the previous test.Results and DiscussionOur results showed that there was a decrease in the frequency of brain oscillatory patterns when camphor was administered at 10 mg/kg i.p. whereas there was a dose-dependent increase in the spectral power and distribution following the administration of 20 and 30 mg/kg i.p., with the emergence of Delta, Theta, Alpha, and Beta waves. As for the behavioral analysis, it was demonstrated that testicular relaxation, decreased motility, and light sleep induction also occurred in a dose-dependent manner. Thus, we conclude that camphor administration intensifies occipital electrocorticographic patterns in sleep-deprived rats, and its electrocorticographic and behavioral analysis could indicate a potential as a supporting agent in the insomnia treatment.

Background: Subdural electrocorticography (ECoG) signals have been proposed as a stable, good-quality source for brain-machine interfaces (BMIs), with a higher spatial and temporal resolution than electroencephalography (EEG). However, long-term implantation may lead to chronic inflammatory reactions and connective tissue encapsulation, resulting in a decline in signal recording quality. However, no study has reported the effects of the surrounding tissue on signal recording and device functionality thus far. Methods: In this study, we implanted a wireless recording device with a customized 32-electrode-ECoG array subdurally in two nonhuman primates for 15 months. We evaluated the neural activities recorded from and wirelessly transmitted to the devices and the chronic tissue reactions around the electrodes. In addition, we measured the gain factor of the newly formed ventral fibrous tissue in vivo. Results: Time-frequency analyses of the acute and chronic phases showed similar signal features. The average root mean square voltage and power spectral density showed relatively stable signal quality after chronic implantation. Histological examination revealed thickening of the reactive tissue around the electrode array; however, no evident inflammation in the cortex. From gain factor analysis, we found that tissue proliferation under electrodes reduced the amplitude power of signals. Conclusion: This study suggests that subdural ECoG may provide chronic signal recordings for future clinical applications and neuroscience research. This study also highlights the need to reduce proliferation of reactive tissue ventral to the electrodes to enhance long-term stability. [ABSTRACT FROM AUTHOR]

Introduction: Electrocorticographic (ECoG) high-gamma activity (HGA) is a widely recognized and robust neural correlate of cognition and behavior. However, fundamental signal properties of HGA, such as the high-gamma frequency band or temporal dynamics of HGA, have never been systematically characterized. As a result, HGA estimators are often poorly adjusted, such that they miss valuable physiological information. Methods: To address these issues, we conducted a thorough qualitative and quantitative characterization of HGA in ECoG signals. Our study is based on ECoG signals recorded from 18 epilepsy patients while performing motor control, listening, and visual perception tasks. In this study, we first categorize HGA into HGA types based on the cognitive/behavioral task. For each HGA type, we then systematically quantify three fundamental signal properties of HGA: the high-gamma frequency band, the HGA bandwidth, and the temporal dynamics of HGA. Results: The high-gamma frequency band strongly varies across subjects and across cognitive/behavioral tasks. In addition, HGA time courses have lowpass character, with transients limited to 10 Hz. The task-related rise time and duration of these HGA time courses depend on the individual subject and cognitive/behavioral task. Task-related HGA amplitudes are comparable across the investigated tasks. Discussion: This study is of high practical relevance because it provides a systematic basis for optimizing experiment design, ECoG acquisition and processing, and HGA estimation. Our results reveal previously unknown characteristics of HGA, the physiological principles of which need to be investigated in further studies. [ABSTRACT FROM AUTHOR]

The vocal tract continuously employs tonic muscle activity in the maintenance of postural configurations. Gamma-band activity in the sensorimotor cortex underlies transientmovements during speech production, yet little is known about the neural control of postural states in the vocal tract. Simultaneously, there is evidence that sensorimotor beta-band activations contribute to a system of inhibition and state maintenance that is integral to postural control in the body. Here we use electrocorticography to assess the contribution of sensorimotor beta-band activity during speech articulation and postural maintenance, and demonstrate that beta-band activity corresponds to the inhibition of discrete speech movements and the maintenance of tonic postural states in the vocal tract. Our findings identify consistencies between the neural control of posture in speech and what is previously reported in grossmotor contexts, providing support for a unified theory of postural control across gross and fine motor skills. [ABSTRACT FROM AUTHOR]

Introduction: Stepping and arm swing are stereotyped movements that require coordination across multiple muscle groups. It is not known whether the encoding of these stereotyped movements in the human primary motor cortex is confined to the limbs' respective somatotopy. Methods: We recorded subdural electrocorticography activities from the hand/arm area in the primary motor cortex of 6 subjects undergoing deep brain stimulation surgery for essential tremor and Parkinson's disease who performed stepping (all patients) and arm swing (n = 3 patients) tasks. Results: We show stepping-related low frequency oscillations over the arm area. Furthermore, we show that this oscillatory activity is separable, both in frequency and spatial domains, from gamma band activity changes that occur during arm swing. Discussion: Our study contributes to the growing body of evidence that lower extremity movement may be more broadly represented in the motor cortex, and suggest that it may represent a way to coordinate stereotyped movements across the upper and lower extremities. [ABSTRACT FROM AUTHOR]

In recent years, a paradigm shift in neuroscience has been occurring from "localizationism," or the idea that the brain is organized into separately functioning modules, toward "connectomics," or the idea that interconnected nodes form networks as the underlying substrates of behavior and thought. Accordingly, our understanding of mechanisms of neurological function, dysfunction, and recovery has evolved to include connections, disconnections, and reconnections. Brain tumors provide a unique opportunity to probe large-scale neural networks with focal and sometimes reversible lesions, allowing neuroscientists the unique opportunity to directly test newly formed hypotheses about underlying brain structural-functional relationships and network properties. Moreover, if a more complete model of neurological dysfunction is to be defined as a "disconnectome," potential avenues for recovery might be mapped through a "reconnectome." Such insight may open the door to novel therapeutic approaches where previous attempts have failed. In this review, we briefly delve into the most clinically relevant neural networks and brain mapping techniques, and we examine how they are being applied to modern neurosurgical brain tumor practices. We then explore how brain tumors might teach us more about mechanisms of global brain dysfunction and recovery through pre- and postoperative longitudinal connectomic and behavioral analyses. [ABSTRACT FROM AUTHOR]

IntroductionStepping and arm swing are stereotyped movements that require coordination across multiple muscle groups. It is not known whether the encoding of these stereotyped movements in the human primary motor cortex is confined to the limbs’ respective somatotopy.MethodsWe recorded subdural electrocorticography activities from the hand/arm area in the primary motor cortex of 6 subjects undergoing deep brain stimulation surgery for essential tremor and Parkinson’s disease who performed stepping (all patients) and arm swing (n = 3 patients) tasks.ResultsWe show stepping-related low frequency oscillations over the arm area. Furthermore, we show that this oscillatory activity is separable, both in frequency and spatial domains, from gamma band activity changes that occur during arm swing.DiscussionOur study contributes to the growing body of evidence that lower extremity movement may be more broadly represented in the motor cortex, and suggest that it may represent a way to coordinate stereotyped movements across the upper and lower extremities.

IntroductionElectrocorticographic (ECoG) high-gamma activity (HGA) is a widely recognized and robust neural correlate of cognition and behavior. However, fundamental signal properties of HGA, such as the high-gamma frequency band or temporal dynamics of HGA, have never been systematically characterized. As a result, HGA estimators are often poorly adjusted, such that they miss valuable physiological information.MethodsTo address these issues, we conducted a thorough qualitative and quantitative characterization of HGA in ECoG signals. Our study is based on ECoG signals recorded from 18 epilepsy patients while performing motor control, listening, and visual perception tasks. In this study, we first categorize HGA into HGA types based on the cognitive/behavioral task. For each HGA type, we then systematically quantify three fundamental signal properties of HGA: the high-gamma frequency band, the HGA bandwidth, and the temporal dynamics of HGA.ResultsThe high-gamma frequency band strongly varies across subjects and across cognitive/behavioral tasks. In addition, HGA time courses have lowpass character, with transients limited to 10 Hz. The task-related rise time and duration of these HGA time courses depend on the individual subject and cognitive/behavioral task. Task-related HGA amplitudes are comparable across the investigated tasks.DiscussionThis study is of high practical relevance because it provides a systematic basis for optimizing experiment design, ECoG acquisition and processing, and HGA estimation. Our results reveal previously unknown characteristics of HGA, the physiological principles of which need to be investigated in further studies.

Introduction: Clustering is usually the first exploratory analysis step in empirical data. When the data set comprises graphs, the most common approaches focus on clustering its vertices. In this work, we are interested in grouping networks with similar connectivity structures together instead of grouping vertices of the graph. We could apply this approach to functional brain networks (FBNs) for identifying subgroups of people presenting similar functional connectivity, such as studying a mental disorder. The main problem is that real-world networks present natural fluctuations, which we should consider. Methods: In this context, spectral density is an exciting feature because graphs generated by different models present distinct spectral densities, thus presenting different connectivity structures. We introduce two clustering methods: k-means for graphs of the same size and gCEM, a model-based approach for graphs of different sizes. We evaluated their performance in toy models. Finally, we applied themto FBNs of monkeys under anesthesia and a dataset of chemical compounds. Results: We show that our methods work well in both toy models and real-world data. They present good results for clustering graphs presenting different connectivity structures even when they present the same number of edges, vertices, and degree of centrality. Discussion: We recommend using k-means-based clustering for graphs when graphs present the same number of vertices and the gCEM method when graphs present a different number of vertices. [ABSTRACT FROM AUTHOR]

IntroductionClustering is usually the first exploratory analysis step in empirical data. When the data set comprises graphs, the most common approaches focus on clustering its vertices. In this work, we are interested in grouping networks with similar connectivity structures together instead of grouping vertices of the graph. We could apply this approach to functional brain networks (FBNs) for identifying subgroups of people presenting similar functional connectivity, such as studying a mental disorder. The main problem is that real-world networks present natural fluctuations, which we should consider.MethodsIn this context, spectral density is an exciting feature because graphs generated by different models present distinct spectral densities, thus presenting different connectivity structures. We introduce two clustering methods: k-means for graphs of the same size and gCEM, a model-based approach for graphs of different sizes. We evaluated their performance in toy models. Finally, we applied them to FBNs of monkeys under anesthesia and a dataset of chemical compounds.ResultsWe show that our methods work well in both toy models and real-world data. They present good results for clustering graphs presenting different connectivity structures even when they present the same number of edges, vertices, and degree of centrality.DiscussionWe recommend using k-means-based clustering for graphs when graphs present the same number of vertices and the gCEM method when graphs present a different number of vertices.

Introduction: Most spinal cord injuries (SCI) result in lower extremities paralysis, thus diminishing ambulation. Using brain-computer interfaces (BCI), patients may regain leg control using neural signals that actuate assistive devices. Here, we present a case of a subject with cervical SCI with an implanted electrocorticography (ECoG) device and determined whether the system is capable of motor-imagery-initiated walking in an assistive ambulator. Methods: A 24-year-old male subject with cervical SCI (C5 ASIA A) was implanted before the study with an ECoG sensing device over the sensorimotor hand region of the brain. The subject used motor-imagery (MI) to train decoders to classify sensorimotor rhythms. Fifteen sessions of closed-loop trials followed in which the subject ambulated for one hour on a robotic-assisted weight-supported treadmill one to three times per week. We evaluated the stability of the best-performing decoder over time to initiate walking on the treadmill by decoding upper-limb (UL) MI. Results: An online bagged trees classifier performed best with an accuracy of 84.15% averaged across 9 weeks. Decoder accuracy remained stable following throughout closed-loop data collection. Discussion: These results demonstrate that decoding UL MI is a feasible control signal for use in lower-limb motor control. Invasive BCI systems designed for upper-extremity motor control can be extended for controlling systems beyond upper extremity control alone. Importantly, the decoders used were able to use the invasive signal over several weeks to accurately classify MI from the invasive signal. More work is needed to determine the long-term consequence between UL MI and the resulting lower-limb control. [ABSTRACT FROM AUTHOR]

Introduction: Wyler-strip electrodes for subdural electrocorticography (ECoG) are the gold standard for continuous bed-side monitoring of pathological cortical network events, such as spreading depolarizations (SD) and electrographic seizures. Recently, SD associated parameters were shown to be (1) a marker of early brain damage after aneurysmal subarachnoid hemorrhage (aSAH), (2) the strongest real-time predictor of delayed cerebral ischemia currently known, and (3) the second strongest predictor of patient outcome at 7months. The strongest predictor of patient outcome at 7months was focal brain damage segmented on neuroimaging 2 weeks after the initial hemorrhage, whereas the initial focal brain damage was inferior to the SD variables as a predictor for patient outcome. However, the implantation of Wyler-strip electrodes typically requires either a craniotomy or an enlarged burr hole. Neuromonitoring via an enlarged burr hole has been performed in only about 10% of the total patients monitored. Methods: In the present pilot study, we investigated the feasibility of ECoG monitoring via a less invasive burrhole approach using a Spencer- type electrode array, which was implanted subdurally rather than in the depth of the parenchyma. Seven aSAH patients requiring extraventricular drainage (EVD) were included. For electrode placement, the burr hole over which the EVD was simultaneously placed, was used in all cases. After electrode implantation, continuous, direct current (DC)/alternating current (AC)-ECoG monitoring was performed at bedside in our Neurointensive Care unit. ECoGs were analyzed following the recommendations of the Co-Operative Studies on Brain Injury Depolarizations (COSBID). Results: Subdural Spencer-type electrode arrays permitted high-quality ECoG recording. During a cumulative monitoring period of 1,194.5 hours and a medianmonitoring period of 201.3 (interquartile range: 126.1-209.4) hours per patient, 84 SDs were identified. Numbers of SDs, isoelectric SDs and clustered SDs per recording day, and peak total SD-induced depression duration of a recording day were not significantly different from the previously reported results of the prospective, observational,multicenter, cohort, diagnostic phase III trial, DISCHARGE-1. No adverse events related to electrode implantation were noted. Discussion: In conclusion, our findings support the safety and feasibility of less-invasive subdural electrode implantation for reliable SD-monitoring. [ABSTRACT FROM AUTHOR]

Introduction: Most spinal cord injuries (SCI) result in lower extremities paralysis, thus diminishing ambulation. Using brain-computer interfaces (BCI), patients may regain leg control using neural signals that actuate assistive devices. Here, we present a case of a subject with cervical SCI with an implanted electrocorticography (ECoG) device and determined whether the system is capable of motor-imagery-initiated walking in an assistive ambulator.Methods: A 24-year-old male subject with cervical SCI (C5 ASIA A) was implanted before the study with an ECoG sensing device over the sensorimotor hand region of the brain. The subject used motor-imagery (MI) to train decoders to classify sensorimotor rhythms. Fifteen sessions of closed-loop trials followed in which the subject ambulated for one hour on a robotic-assisted weight-supported treadmill one to three times per week. We evaluated the stability of the best-performing decoder over time to initiate walking on the treadmill by decoding upper-limb (UL) MI.Results: An online bagged trees classifier performed best with an accuracy of 84.15% averaged across 9 weeks. Decoder accuracy remained stable following throughout closed-loop data collection.Discussion: These results demonstrate that decoding UL MI is a feasible control signal for use in lower-limb motor control. Invasive BCI systems designed for upper-extremity motor control can be extended for controlling systems beyond upper extremity control alone. Importantly, the decoders used were able to use the invasive signal over several weeks to accurately classify MI from the invasive signal. More work is needed to determine the long-term consequence between UL MI and the resulting lower-limb control.

IntroductionWyler-strip electrodes for subdural electrocorticography (ECoG) are the gold standard for continuous bed-side monitoring of pathological cortical network events, such as spreading depolarizations (SD) and electrographic seizures. Recently, SD associated parameters were shown to be (1) a marker of early brain damage after aneurysmal subarachnoid hemorrhage (aSAH), (2) the strongest real-time predictor of delayed cerebral ischemia currently known, and (3) the second strongest predictor of patient outcome at 7 months. The strongest predictor of patient outcome at 7 months was focal brain damage segmented on neuroimaging 2 weeks after the initial hemorrhage, whereas the initial focal brain damage was inferior to the SD variables as a predictor for patient outcome. However, the implantation of Wyler-strip electrodes typically requires either a craniotomy or an enlarged burr hole. Neuromonitoring via an enlarged burr hole has been performed in only about 10% of the total patients monitored.MethodsIn the present pilot study, we investigated the feasibility of ECoG monitoring via a less invasive burrhole approach using a Spencer-type electrode array, which was implanted subdurally rather than in the depth of the parenchyma. Seven aSAH patients requiring extraventricular drainage (EVD) were included. For electrode placement, the burr hole over which the EVD was simultaneously placed, was used in all cases. After electrode implantation, continuous, direct current (DC)/alternating current (AC)-ECoG monitoring was performed at bedside in our Neurointensive Care unit. ECoGs were analyzed following the recommendations of the Co-Operative Studies on Brain Injury Depolarizations (COSBID).ResultsSubdural Spencer-type electrode arrays permitted high-quality ECoG recording. During a cumulative monitoring period of 1,194.5 hours and a median monitoring period of 201.3 (interquartile range: 126.1–209.4) hours per patient, 84 SDs were identified. Numbers of SDs, isoelectric SDs and clustered SDs per recording day, and peak total SD-induced depression duration of a recording day were not significantly different from the previously reported results of the prospective, observational, multicenter, cohort, diagnostic phase III trial, DISCHARGE-1. No adverse events related to electrode implantation were noted.DiscussionIn conclusion, our findings support the safety and feasibility of less-invasive subdural electrode implantation for reliable SD-monitoring.

Cortical stimulation via electrocorticography (ECoG) may be an effective method for inducing artificial sensation in bi-directional brain-computer interfaces (BD-BCIs). However, strong electrical artifacts caused by electrostimulation may significantly degrade or obscure neural information. A detailed understanding of stimulation artifact propagation through relevant tissues may improve existing artifact suppression techniques or inspire the development of novel artifact mitigation strategies. Our work thus seeks to comprehensively characterize and model the propagation of artifacts in subdural ECoG stimulation. To this end, we collected and analyzed data from eloquent cortex mapping procedures of four subjects with epilepsy who were implanted with subdural ECoG electrodes. From this data, we observed that artifacts exhibited phase-locking and ratcheting characteristics in the time domain across all subjects. In the frequency domain, stimulation caused broadband power increases, as well as power bursts at the fundamental stimulation frequency and its super-harmonics. The spatial distribution of artifacts followed the potential distribution of an electric dipole with a median goodness-of-fit of R2 = 0.80 across all subjects and stimulation channels. Artifacts as large as ±1,100 µV appeared anywhere from 4.43 to 38.34 mm from the stimulation channel. These temporal, spectral and spatial characteristics can be utilized to improve existing artifact suppression techniques, inspire new strategies for artifact mitigation, and aid in the development of novel cortical stimulation protocols. Taken together, these findings deepen our understanding of cortical electrostimulation and provide critical design specifications for future BD-BCI systems. [ABSTRACT FROM AUTHOR]

Cortical stimulation via electrocorticography (ECoG) may be an effective method for inducing artificial sensation in bi-directional brain-computer interfaces (BD-BCIs). However, strong electrical artifacts caused by electrostimulation may significantly degrade or obscure neural information. A detailed understanding of stimulation artifact propagation through relevant tissues may improve existing artifact suppression techniques or inspire the development of novel artifact mitigation strategies. Our work thus seeks to comprehensively characterize and model the propagation of artifacts in subdural ECoG stimulation. To this end, we collected and analyzed data from eloquent cortex mapping procedures of four subjects with epilepsy who were implanted with subdural ECoG electrodes. From this data, we observed that artifacts exhibited phase-locking and ratcheting characteristics in the time domain across all subjects. In the frequency domain, stimulation caused broadband power increases, as well as power bursts at the fundamental stimulation frequency and its super-harmonics. The spatial distribution of artifacts followed the potential distribution of an electric dipole with a median goodness-of-fit of R2 = 0.80 across all subjects and stimulation channels. Artifacts as large as ±1,100 μV appeared anywhere from 4.43 to 38.34 mm from the stimulation channel. These temporal, spectral and spatial characteristics can be utilized to improve existing artifact suppression techniques, inspire new strategies for artifact mitigation, and aid in the development of novel cortical stimulation protocols. Taken together, these findings deepen our understanding of cortical electrostimulation and provide critical design specifications for future BD-BCI systems.

Background: Regarding brain tumor-related epilepsy (BTRE), there is an increasing number of evidence about a relationship between epileptogenesis and oncogenesis. A recent study suggests a role of post-surgery seizure outcome on the survival of patients with low-grade glioma (LGG), underlying the need for a targeted and aggressive epilepsy treatment. Objective: This study aims at investigating the possible correlation between pre- and post-surgical seizure control and tumor progression in patients who underwent surgery for LGG. Methods: We performed a retrospective analysis of patients affected by LGGs and BTRE, in a single high-volume neurosurgical center. Seizure control was assessed before surgery and at 3 years of follow-up. Patients with histological progression in high-grade glioma (HGG) have been evaluated. Clinical features, pre-surgical electroencephalograms (EEGs), and electrocorticography (ECoG) have been analyzed. Results: Among 154 subjects, we collected 32 patients who presented a tumor progression in HGG during the follow-up period. The majority had poor seizure control both pre- and post-surgery, never being in Engel class Ia throughout the whole history of their disease. Almost all patients with poor seizure control had pathological ECoG recording. Clinical features of seizures did not correlate with seizure outcome. On the univariate analysis, the age, the post-operative Engel class, and the extent of resection (EOR) were the prognostic factors significantly associated with oncological outcome; nevertheless, on multivariate analysis, Engel class significance was not confirmed, and the only predicting factor were age and EOR. Conclusions: Although not confirmed on multivariate analysis, post-surgical seizure control could be a relevant factor to consider during follow-up of BRTE, in particular, when gross total resection is not achieved. Pathological findings on the ECoG may suggest a "hidden" propensity to malignant progression, strictly related to the persistent neuronal hyper-excitability. Further studies with longer follow-up period are needed to confirm our observations. [ABSTRACT FROM AUTHOR]

BackgroundRegarding brain tumor-related epilepsy (BTRE), there is an increasing number of evidence about a relationship between epileptogenesis and oncogenesis. A recent study suggests a role of post-surgery seizure outcome on the survival of patients with low-grade glioma (LGG), underlying the need for a targeted and aggressive epilepsy treatment.ObjectiveThis study aims at investigating the possible correlation between pre- and post-surgical seizure control and tumor progression in patients who underwent surgery for LGG.MethodsWe performed a retrospective analysis of patients affected by LGGs and BTRE, in a single high-volume neurosurgical center. Seizure control was assessed before surgery and at 3 years of follow-up. Patients with histological progression in high-grade glioma (HGG) have been evaluated. Clinical features, pre-surgical electroencephalograms (EEGs), and electrocorticography (ECoG) have been analyzed.ResultsAmong 154 subjects, we collected 32 patients who presented a tumor progression in HGG during the follow-up period. The majority had poor seizure control both pre- and post-surgery, never being in Engel class Ia throughout the whole history of their disease. Almost all patients with poor seizure control had pathological ECoG recording. Clinical features of seizures did not correlate with seizure outcome. On the univariate analysis, the age, the post-operative Engel class, and the extent of resection (EOR) were the prognostic factors significantly associated with oncological outcome; nevertheless, on multivariate analysis, Engel class significance was not confirmed, and the only predicting factor were age and EOR.ConclusionsAlthough not confirmed on multivariate analysis, post-surgical seizure control could be a relevant factor to consider during follow-up of BRTE, in particular, when gross total resection is not achieved. Pathological findings on the ECoG may suggest a “hidden” propensity to malignant progression, strictly related to the persistent neuronal hyper-excitability. Further studies with longer follow-up period are needed to confirm our observations.

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. [ABSTRACT FROM AUTHOR]

Epilepsy affects more than three million people in the United States. In approximately one-third of this population, anti-seizure medications do not control seizures. Many patients pursue surgical treatment that can include a procedure involving the implantation of electrodes for intracranial monitoring of seizure activity. For these cases, accurate mapping of the implanted electrodes on a patient’s brain is crucial in planning the ultimate surgical treatment. Traditionally, electrode mapping results are presented in static figures that do not allow for dynamic interactions and visualizations. In collaboration with a clinical research team at a Level 4 Epilepsy Center, we developed N-Tools-Browser, a web-based software using WebGL and the X-Toolkit (XTK), to help clinicians interactively visualize the location and functional properties of implanted intracranial electrodes in 3D. Our software allows the user to visualize the seizure focus location accurately and simultaneously display functional characteristics (e.g., results from electrical stimulation mapping). Different visualization modes enable the analysis of multiple electrode groups or individual anatomical locations. We deployed a prototype of N-Tools-Browser for our collaborators at the New York University Grossman School of Medicine Comprehensive Epilepsy Center. Then, we evaluated its usefulness with domain experts on clinical cases.

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.

Objective: Anxiety and depression are prominent non-motor symptoms of Parkinson’s disease (PD), but their pathophysiology remains unclear. We sought to understand their neurophysiological correlates from chronic invasive recordings of the prefrontal cortex (PFC).Methods: We studied four patients undergoing deep brain stimulation (DBS) for their motor signs, who had comorbid mild to moderate anxiety and/or depressive symptoms. In addition to their basal ganglia leads, we placed a permanent prefrontal subdural 4-contact lead. These electrodes were attached to an investigational pulse generator with the capability to sense and store field potential signals, as well as deliver therapeutic neurostimulation. At regular intervals over 3–5 months, participants paired brief invasive neural recordings with self-ratings of symptoms related to depression and anxiety.Results: Mean age was 61 ± 7 years, mean disease duration was 11 ± 8 years and a mean Unified Parkinson’s Disease Rating Scale, with part III (UPDRS-III) off medication score of 37 ± 13. Mean Beck Depression Inventory (BDI) score was 14 ± 5 and Beck Anxiety Index was 16.5 ± 5. Prefrontal cortex spectral power in the beta band correlated with patient self-ratings of symptoms of depression and anxiety, with r-values between 0.31 and 0.48. Mood scores showed negative correlation with beta spectral power in lateral locations, and positive correlation with beta spectral power in a mesial recording location, consistent with the dichotomous organization of reward networks in PFC.Interpretation: These findings suggest a physiological basis for anxiety and depression in PD, which may be useful in the development of neurostimulation paradigms for these non-motor disease features.

Objective: This study aimed to explore the characteristics of phase-amplitude coupling in patients with frontal epilepsy based on their electrocorticography data, in order to identify the localization of epileptic regions and further guide clinical resection surgery.Methods: We adopted the modulation index based on the Kullback-Leibler distance, phase-amplitude coupling co-modulogram, and time-varying phase-amplitude modulogram to explore the temporal-spatial patterns and characterization of PAC strength during the period from inter- seizure to post-seizure. Taking the resected area as the gold standard, the epileptogenic zone was located based on MI values of 7 different seizure periods, and the accuracy of localization was measured by the area under the receiver operating curve.Results: (1) The PAC in the inter- and pre-seizure periods was weak and paroxysmal, but strong PAC channels were confined more to the seizure-onset zone and resection region. PAC during the seizure period was intense and persistent, but gradually deviated from the seizure-onset zone. (2) The characteristics of coupling strength of the inter- and pre-seizure EEG can be used to accurately locate the epileptogenic zone, which is better than that in periods after the beginning of a seizure. (3) In an epileptic seizure, the preferred phases of coupling were usually in the rising branches at the pre- and early-seizure stages, while those in the middle- and terminal-seizure were usually in the falling branch. We thus speculate that the coupling occurred in the rising branch can promote the recruitment of abnormal discharge, while the coupling occurred in the falling branch can inhibit the abnormal discharge.Conclusion: The findings suggest that the phase-amplitude coupling during inter- and pre-seizure is a promising marker of epileptic focus location. The preferred phase of coupling changed regularly with the time of epileptic seizure, suggesting that the surge and suppression of abnormal discharges are related to different phases.

Direct electrocortical stimulation (DECS) with electrocorticography electrodes is an established therapy for epilepsy and an emerging application for stroke rehabilitation and brain-computer interfaces. However, the electrophysiological mechanisms that result in a therapeutic effect remain unclear. Patient-specific computational models are promising tools to predict the voltages in the brain and better understand the neural and clinical response to DECS, but the accuracy of such models has not been directly validated in humans. A key hurdle to modeling DECS is accurately locating the electrodes on the cortical surface due to brain shift after electrode implantation. Despite the inherent uncertainty introduced by brain shift, the effects of electrode localization parameters have not been investigated. The goal of this study was to validate patient-specific computational models of DECS against in vivo voltage recordings obtained during DECS and quantify the effects of electrode localization parameters on simulated voltages on the cortical surface. We measured intracranial voltages in six epilepsy patients during DECS and investigated the following electrode localization parameters: principal axis, Hermes, and Dykstra electrode projection methods combined with 0, 1, and 2 mm of cerebral spinal fluid (CSF) below the electrodes. Greater CSF depth between the electrode and cortical surface increased model errors and decreased predicted voltage accuracy. The electrode localization parameters that best estimated the recorded voltages across six patients with varying amounts of brain shift were the Hermes projection method and a CSF depth of 0 mm (r = 0.92 and linear regression slope = 1.21). These results are the first to quantify the effects of electrode localization parameters with in vivo intracranial recordings and may serve as the basis for future studies investigating the neuronal and clinical effects of DECS for epilepsy, stroke, and other emerging closed-loop applications.

Objective: Anxiety and depression are prominent non-motor symptoms of Parkinson's disease (PD), but their pathophysiology remains unclear. We sought to understand their neurophysiological correlates from chronic invasive recordings of the prefrontal cortex (PFC). Methods: We studied four patients undergoing deep brain stimulation (DBS) for their motor signs, who had comorbid mild to moderate anxiety and/or depressive symptoms. In addition to their basal ganglia leads, we placed a permanent prefrontal subdural 4-contact lead. These electrodes were attached to an investigational pulse generator with the capability to sense and store field potential signals, as well as deliver therapeutic neurostimulation. At regular intervals over 3–5 months, participants paired brief invasive neural recordings with self-ratings of symptoms related to depression and anxiety. Results: Mean age was 61 ± 7 years, mean disease duration was 11 ± 8 years and a mean Unified Parkinson's Disease Rating Scale, with part III (UPDRS-III) off medication score of 37 ± 13. Mean Beck Depression Inventory (BDI) score was 14 ± 5 and Beck Anxiety Index was 16.5 ± 5. Prefrontal cortex spectral power in the beta band correlated with patient self-ratings of symptoms of depression and anxiety, with r -values between 0.31 and 0.48. Mood scores showed negative correlation with beta spectral power in lateral locations, and positive correlation with beta spectral power in a mesial recording location, consistent with the dichotomous organization of reward networks in PFC. Interpretation: These findings suggest a physiological basis for anxiety and depression in PD, which may be useful in the development of neurostimulation paradigms for these non-motor disease features. [ABSTRACT FROM AUTHOR]

Objective: This study aimed to explore the characteristics of phase-amplitude coupling in patients with frontal epilepsy based on their electrocorticography data, in order to identify the localization of epileptic regions and further guide clinical resection surgery. Methods: We adopted the modulation index based on the Kullback-Leibler distance, phase-amplitude coupling co-modulogram, and time-varying phase-amplitude modulogram to explore the temporal-spatial patterns and characterization of PAC strength during the period from inter- seizure to post-seizure. Taking the resected area as the gold standard, the epileptogenic zone was located based on MI values of 7 different seizure periods, and the accuracy of localization was measured by the area under the receiver operating curve. Results: (1) The PAC in the inter- and pre-seizure periods was weak and paroxysmal, but strong PAC channels were confined more to the seizure-onset zone and resection region. PAC during the seizure period was intense and persistent, but gradually deviated from the seizure-onset zone. (2) The characteristics of coupling strength of the inter- and pre-seizure EEG can be used to accurately locate the epileptogenic zone, which is better than that in periods after the beginning of a seizure. (3) In an epileptic seizure, the preferred phases of coupling were usually in the rising branches at the pre- and early-seizure stages, while those in the middle- and terminal-seizure were usually in the falling branch. We thus speculate that the coupling occurred in the rising branch can promote the recruitment of abnormal discharge, while the coupling occurred in the falling branch can inhibit the abnormal discharge. Conclusion: The findings suggest that the phase-amplitude coupling during inter- and pre-seizure is a promising marker of epileptic focus location. The preferred phase of coupling changed regularly with the time of epileptic seizure, suggesting that the surge and suppression of abnormal discharges are related to different phases. [ABSTRACT FROM AUTHOR]

Direct electrocortical stimulation (DECS) with electrocorticography electrodes is an established therapy for epilepsy and an emerging application for stroke rehabilitation and brain-computer interfaces. However, the electrophysiological mechanisms that result in a therapeutic effect remain unclear. Patient-specific computational models are promising tools to predict the voltages in the brain and better understand the neural and clinical response to DECS, but the accuracy of such models has not been directly validated in humans. A key hurdle to modeling DECS is accurately locating the electrodes on the cortical surface due to brain shift after electrode implantation. Despite the inherent uncertainty introduced by brain shift, the effects of electrode localization parameters have not been investigated. The goal of this study was to validate patient-specific computational models of DECS against in vivo voltage recordings obtained during DECS and quantify the effects of electrode localization parameters on simulated voltages on the cortical surface. We measured intracranial voltages in six epilepsy patients during DECS and investigated the following electrode localization parameters: principal axis, Hermes, and Dykstra electrode projection methods combined with 0, 1, and 2 mm of cerebral spinal fluid (CSF) below the electrodes. Greater CSF depth between the electrode and cortical surface increased model errors and decreased predicted voltage accuracy. The electrode localization parameters that best estimated the recorded voltages across six patients with varying amounts of brain shift were the Hermes projection method and a CSF depth of 0 mm (r = 0.92 and linear regression slope = 1.21). These results are the first to quantify the effects of electrode localization parameters with in vivo intracranial recordings and may serve as the basis for future studies investigating the neuronal and clinical effects of DECS for epilepsy, stroke, and other emerging closed-loop applications. [ABSTRACT FROM AUTHOR]

Prediction of successful memory encoding is important for learning. High-frequency activity (HFA), such as gamma frequency activity (30–150 Hz) of cortical oscillations, is induced during memory tasks and is thought to reflect underlying neuronal processes. Previous studies have demonstrated that medio-temporal electrophysiological characteristics are related to memory formation, but the effects of neocortical neural activity remain underexplored. The main aim of the present study was to evaluate the ability of gamma activity in human electrocorticography (ECoG) signals to differentiate memory processes into remembered and forgotten memories. A support vector machine (SVM) was employed, and ECoG recordings were collected from six subjects during verbal memory recognition task performance. Two-class classification using an SVM was performed to predict subsequently remembered vs. forgotten trials based on individually selected frequencies (low gamma, 30–60 Hz; high gamma, 60–150 Hz) at time points during pre- and during stimulus intervals. The SVM classifier distinguished memory performance between remembered and forgotten trials with a mean maximum accuracy of 87.5% using temporal cortical gamma activity during the 0- to 1-s interval. Our results support the functional relevance of ECoG for memory formation and suggest that lateral temporal cortical HFA may be utilized for memory prediction.

Prediction of successful memory encoding is important for learning. High-frequency activity (HFA), such as gamma frequency activity (30–150 Hz) of cortical oscillations, is induced during memory tasks and is thought to reflect underlying neuronal processes. Previous studies have demonstrated that medio-temporal electrophysiological characteristics are related to memory formation, but the effects of neocortical neural activity remain underexplored. The main aim of the present study was to evaluate the ability of gamma activity in human electrocorticography (ECoG) signals to differentiate memory processes into remembered and forgotten memories. A support vector machine (SVM) was employed, and ECoG recordings were collected from six subjects during verbal memory recognition task performance. Two-class classification using an SVM was performed to predict subsequently remembered vs. forgotten trials based on individually selected frequencies (low gamma, 30–60 Hz; high gamma, 60–150 Hz) at time points during pre- and during stimulus intervals. The SVM classifier distinguished memory performance between remembered and forgotten trials with a mean maximum accuracy of 87.5% using temporal cortical gamma activity during the 0- to 1-s interval. Our results support the functional relevance of ECoG for memory formation and suggest that lateral temporal cortical HFA may be utilized for memory prediction. [ABSTRACT FROM AUTHOR]

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.

Learning of new auditory stimuli often requires repetitive exposure to the stimulus. Fast and implicit learning of sounds presented at random times enables efficient auditory perception. However, it is unclear how such sensory encoding is processed on a neural level. We investigated neural responses that are developed from a passive, repetitive exposure to a specific sound in the auditory cortex of anesthetized rats, using electrocorticography. We presented a series of random sequences that are generated afresh each time, except for a specific reference sequence that remains constant and re-appears at random times across trials. We compared induced activity amplitudes between reference and fresh sequences. Neural responses from both primary and non-primary auditory cortical regions showed significantly decreased induced activity amplitudes for reference sequences compared to fresh sequences, especially in the beta band. This is the first study showing that neural correlates of auditory pattern learning can be evoked even in anesthetized, passive listening animal models.

Face recognition is impaired in patients with prosopagnosia, which may occur as a side effect of neurosurgical procedures. Face selective regions on the ventral temporal cortex have been localized with electrical cortical stimulation (ECS), electrocorticography (ECoG), and functional magnetic resonance imagining (fMRI). This is the first group study using within-patient comparisons to validate face selective regions mapping, utilizing the aforementioned modalities. Five patients underwent surgical treatment of intractable epilepsy and joined the study. Subdural grid electrodes were implanted on their ventral temporal cortices to localize seizure foci and face selective regions as part of the functional mapping protocol. Face selective regions were identified in all patients with fMRI, four patients with ECoG, and two patients with ECS. From 177 tested electrode locations in the region of interest (ROI), which is defined by the fusiform gyrus and the inferior temporal gyrus, 54 face locations were identified by at least one modality in all patients. fMRI mapping showed the highest detection rate, revealing 70.4% for face selective locations, whereas ECoG and ECS identified 64.8 and 31.5%, respectively. Thus, 28 face locations were co-localized by at least two modalities, with detection rates of 89.3% for fMRI, 85.7% for ECoG and 53.6 % for ECS. All five patients had no face recognition deficits after surgery, even though five of the face selective locations, one obtained by ECoG and the other four by fMRI, were within 10 mm to the resected volumes. Moreover, fMRI included a quite large volume artifact on the ventral temporal cortex in the ROI from the anatomical structures of the temporal base. In conclusion, ECS was not sensitive in several patients, whereas ECoG and fMRI even showed activation within 10 mm to the resected volumes. Considering the potential signal drop-out in fMRI makes ECoG the most reliable tool to identify face selective locations in this study. A multimodal approach can improve the specificity of ECoG and fMRI, while simultaneously minimizing the number of required ECS sessions. Hence, all modalities should be considered in a clinical mapping protocol entailing combined results of co-localized face selective locations.

BackgroundElectrocorticography (ECoG) has been utilized in many epilepsy cases however, the use of this technique for evaluating electrophysiological changes within tumoral zones is spare. Nonetheless, epileptic activities seem to arise from the neocortex surrounding the gliomas suggesting a link between epileptogenesis and glioma cell infiltration in the peritumoral area. The purpose of this study was to implement novel scale-free measures to assess how cortical physiology is altered by the presence of an invasive brain tumor.MethodsTwelve patients undergoing an awake craniotomy for resection of a supratentorial glioma were included. ECoG data over the main tumor and the exposed surroundings was acquired intra-operatively just prior to tumor resection. Six of the patients presented with seizures and had data acquired both in the awake and anesthetic state. The corresponding anatomical location of each electrode in relation to the macroscopically-detectable tumor was recorded using the neuronavigation system based on structural anatomical images obtained pre-operatively. The electrodes were classified into tumoral, healthy or peritumoral based on the macroscopically detectable tumoral tissue from the pre-operative structural MRI.ResultsThe electrodes overlying the tumoral tissue revealed higher power law exponent (PLE) values across tumoral area compared to the surrounding tissues. The difference between the awake and anesthetic states was significant in the tumoral and healthy tissue (p < 0.05) but not in the peritumoral tissue. The absence of a significant PLE reduction in the peritumoral tissue from the anesthetic to the awake state could be considered as an index of the presence or absence of infiltration of tumor cells into the peritumoral tissue.ConclusionsThe current study portrays for the first time distinct power law exponent features in the tumoral tissue, which could provide a potential novel electrophysiological marker in the future. The distinct features seen in the peritumoral tissue of gliomas seem to indicate the area where both the onset of epileptiform activity and the tumor infiltration take place.

Face recognition is impaired in patients with prosopagnosia, which may occur as a side effect of neurosurgical procedures. Face selective regions on the ventral temporal cortex have been localized with electrical cortical stimulation (ECS), electrocorticography (ECoG), and functional magnetic resonance imagining (fMRI). This is the first group study using within-patient comparisons to validate face selective regions mapping, utilizing the aforementioned modalities. Five patients underwent surgical treatment of intractable epilepsy and joined the study. Subdural grid electrodes were implanted on their ventral temporal cortices to localize seizure foci and face selective regions as part of the functional mapping protocol. Face selective regions were identified in all patients with fMRI, four patients with ECoG, and two patients with ECS. From 177 tested electrode locations in the region of interest (ROI), which is defined by the fusiform gyrus and the inferior temporal gyrus, 54 face locations were identified by at least one modality in all patients. fMRI mapping showed the highest detection rate, revealing 70.4% for face selective locations, whereas ECoG and ECS identified 64.8 and 31.5%, respectively. Thus, 28 face locations were co-localized by at least two modalities, with detection rates of 89.3% for fMRI, 85.7% for ECoG and 53.6 % for ECS. All five patients had no face recognition deficits after surgery, even though five of the face selective locations, one obtained by ECoG and the other four by fMRI, were within 10 mm to the resected volumes. Moreover, fMRI included a quite large volume artifact on the ventral temporal cortex in the ROI from the anatomical structures of the temporal base. In conclusion, ECS was not sensitive in several patients, whereas ECoG and fMRI even showed activation within 10 mm to the resected volumes. Considering the potential signal drop-out in fMRI makes ECoG the most reliable tool to identify face selective locations in this study. A multimodal approach can improve the specificity of ECoG and fMRI, while simultaneously minimizing the number of required ECS sessions. Hence, all modalities should be considered in a clinical mapping protocol entailing combined results of co-localized face selective locations. [ABSTRACT FROM AUTHOR]

Learning of new auditory stimuli often requires repetitive exposure to the stimulus. Fast and implicit learning of sounds presented at random times enables efficient auditory perception. However, it is unclear how such sensory encoding is processed on a neural level. We investigated neural responses that are developed from a passive, repetitive exposure to a specific sound in the auditory cortex of anesthetized rats, using electrocorticography. We presented a series of random sequences that are generated afresh each time, except for a specific reference sequence that remains constant and re-appears at random times across trials. We compared induced activity amplitudes between reference and fresh sequences. Neural responses from both primary and non-primary auditory cortical regions showed significantly decreased induced activity amplitudes for reference sequences compared to fresh sequences, especially in the beta band. This is the first study showing that neural correlates of auditory pattern learning can be evoked even in anesthetized, passive listening animal models. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Background: Electrocorticography (ECoG) has been utilized in many epilepsy cases however, the use of this technique for evaluating electrophysiological changes within tumoral zones is spare. Nonetheless, epileptic activities seem to arise from the neocortex surrounding the gliomas suggesting a link between epileptogenesis and glioma cell infiltration in the peritumoral area. The purpose of this study was to implement novel scale-free measures to assess how cortical physiology is altered by the presence of an invasive brain tumor. Methods: Twelve patients undergoing an awake craniotomy for resection of a supratentorial glioma were included. ECoG data over the main tumor and the exposed surroundings was acquired intra-operatively just prior to tumor resection. Six of the patients presented with seizures and had data acquired both in the awake and anesthetic state. The corresponding anatomical location of each electrode in relation to the macroscopically-detectable tumor was recorded using the neuronavigation system based on structural anatomical images obtained pre-operatively. The electrodes were classified into tumoral, healthy or peritumoral based on the macroscopically detectable tumoral tissue from the pre-operative structural MRI. Results: The electrodes overlying the tumoral tissue revealed higher power law exponent (PLE) values across tumoral area compared to the surrounding tissues. The difference between the awake and anesthetic states was significant in the tumoral and healthy tissue (p < 0.05) but not in the peritumoral tissue. The absence of a significant PLE reduction in the peritumoral tissue from the anesthetic to the awake state could be considered as an index of the presence or absence of infiltration of tumor cells into the peritumoral tissue. Conclusions: The current study portrays for the first time distinct power law exponent features in the tumoral tissue, which could provide a potential novel electrophysiological marker in the future. The distinct features seen in the peritumoral tissue of gliomas seem to indicate the area where both the onset of epileptiform activity and the tumor infiltration take place. [ABSTRACT FROM AUTHOR]

Ketamine, an N-methyl-D-aspartate (NMDA) receptor antagonist, exerts broad effects on consciousness and perception. Since NMDA receptor antagonists induce cognitive impairments, ketamine has been used for translational research on several psychiatric diseases, such as schizophrenia. Whereas the effects of ketamine on cognitive functions have been extensively studied, studies on the effects of ketamine on simple sensory information processing remain limited. In this study, we investigated the cortex-wide effects of ketamine administration on auditory information processing in nonhuman primates using whole-cortical electrocorticography (ECoG). We first recorded ECoG from awake monkeys on presenting auditory stimuli of different frequencies or different durations. We observed auditory evoked responses (AERs) across the cortex, including in frontal, parietal, and temporal areas, while feature-specific responses were obtained around the temporal sulcus. Next, we examined the effects of ketamine on cortical auditory information processing. We conducted ECoG recordings from monkeys that had been administered anesthetic doses of ketamine from 10 to 180 min following administration. We observed significant changes in stimulus feature-specific responses. Electrodes showing a frequency preference or offset responses were altered following ketamine administration, while those of the AERs were not strongly influenced. However, the frequency preference of a selected electrode was not significantly altered by ketamine administration over time following administration, while the imbalances in the onset and offset persisted over the course of 150 min following ketamine administration in all three monkeys. These results suggest that ketamine affects the ability to distinguish between sound frequency and duration in different ways. In conclusion, future research on the NMDA sensitivity of cortical wide sensory information processing may provide a new perspective into the development of nonhuman primate models of psychiatric disorders.

The success of surgical resection in epilepsy patients depends on preserving functionally critical brain regions, while removing pathological tissues. Being the gold standard, electro-cortical stimulation mapping (ESM) helps surgeons in localizing the function of eloquent cortex through electrical stimulation of electrodes placed directly on the cortical brain surface. Due to the potential hazards of ESM, including increased risk of provoked seizures, electrocorticography based functional mapping (ECoG-FM) was introduced as a safer alternative approach. However, ECoG-FM has a low success rate when compared to the ESM. In this study, we address this critical limitation by developing a new algorithm based on deep learning for ECoG-FM and thereby we achieve an accuracy comparable to ESM in identifying eloquent language cortex. In our experiments, with 11 epilepsy patients who underwent presurgical evaluation (through deep learning-based signal analysis on 637 electrodes), our proposed algorithm obtained an accuracy of 83.05% in identifying language regions, an exceptional 23% improvement with respect to the conventional ECoG-FM analysis (∼60%). Our findings have demonstrated, for the first time, that deep learning powered ECoG-FM can serve as a stand-alone modality and avoid likely hazards of the ESM in epilepsy surgery. Hence, reducing the potential for developing post-surgical morbidity in the language function.

Stereotactic electroencephalogaphy (sEEG) utilizes localized, penetrating depth electrodes to measure electrophysiological brain activity. It is most commonly used in the identification of epileptogenic zones in cases of refractory epilepsy. The implanted electrodes generally provide a sparse sampling of a unique set of brain regions including deeper brain structures such as hippocampus, amygdala and insula that cannot be captured by superficial measurement modalities such as electrocorticography (ECoG). Despite the overlapping clinical application and recent progress in decoding of ECoG for Brain-Computer Interfaces (BCIs), sEEG has thus far received comparatively little attention for BCI decoding. Additionally, the success of the related deep-brain stimulation (DBS) implants bodes well for the potential for chronic sEEG applications. This article provides an overview of sEEG technology, BCI-related research, and prospective future directions of sEEG for long-term BCI applications.

Normal and pathological networks related to seizure propagation have got attention to elucide complex seizure semiology and contribute to diagnosis and surgical monitoring in epilepsy treatment. Since focal and generalized epileptogenic syndromes abnormalities might involve multiple foci and large-scale networks, we applied electrophysiolpgy (cortco-cortico evoked potential; CCEP), and tractography to make detailed diagnosis for complex syndrome. All 14 epilepsy patients with no or little abnormality on images investigations underwent subdural grid implantation for epilepsy diagnosis. To perform quick network analysis, we recorded and analyzed high gamma activity (HGA) of epileptogenic activity and CCEPs to identify pathological activity distribution and network connectivity. [Results] Pathological CCEPs showed two negative deflections consisting of early (>40 ms) and late (>150 ms) components in electrically stable circumstance at bed side and early CCEPs appeared in 57% of the patients. On the basis of the CCEP findings, tractography detected anatomical connections. Early components of pathological CCEPs diminished after complete disconnection of tractoography-based fibers between the foci in seven of eight cases. One case with residual pathological CCEPs showed poorer outcome. Thirteen (92.8%) patients with or without CCEPs who underwent network surgery had favorable prognosis except for a case with wide traumatic epilepsy. Intraoperative CCEP measurements and HGA mapping enabled visualization of pathological networks and clinical impotence as a biomarker to improve functional prognosis. HGA/CCEP recording should shed light on pathological and complex propagation for epilepsy surgery.

Ketamine, an N-methyl-D-aspartate (NMDA) receptor antagonist, exerts broad effects on consciousness and perception. Since NMDA receptor antagonists induce cognitive impairments, ketamine has been used for translational research on several psychiatric diseases, such as schizophrenia. Whereas the effects of ketamine on cognitive functions have been extensively studied, studies on the effects of ketamine on simple sensory information processing remain limited. In this study, we investigated the cortex-wide effects of ketamine administration on auditory information processing in nonhuman primates using whole-cortical electrocorticography (ECoG). We first recorded ECoG from awake monkeys on presenting auditory stimuli of different frequencies or different durations. We observed auditory evoked responses (AERs) across the cortex, including in frontal, parietal, and temporal areas, while feature-specific responses were obtained around the temporal sulcus. Next, we examined the effects of ketamine on cortical auditory information processing. We conducted ECoG recordings from monkeys that had been administered anesthetic doses of ketamine from 10 to 180 min following administration. We observed significant changes in stimulus feature-specific responses. Electrodes showing a frequency preference or offset responses were altered following ketamine administration, while those of the AERs were not strongly influenced. However, the frequency preference of a selected electrode was not significantly altered by ketamine administration over time following administration, while the imbalances in the onset and offset persisted over the course of 150 min following ketamine administration in all three monkeys. These results suggest that ketamine affects the ability to distinguish between sound frequency and duration in different ways. In conclusion, future research on the NMDA sensitivity of cortical wide sensory information processing may provide a new perspective into the development of nonhuman primate models of psychiatric disorders. [ABSTRACT FROM AUTHOR]

The success of surgical resection in epilepsy patients depends on preserving functionally critical brain regions, while removing pathological tissues. Being the gold standard, electro-cortical stimulation mapping (ESM) helps surgeons in localizing the function of eloquent cortex through electrical stimulation of electrodes placed directly on the cortical brain surface. Due to the potential hazards of ESM, including increased risk of provoked seizures, electrocorticography based functional mapping (ECoG-FM) was introduced as a safer alternative approach. However, ECoG-FM has a low success rate when compared to the ESM. In this study, we address this critical limitation by developing a new algorithm based on deep learning for ECoG-FM and thereby we achieve an accuracy comparable to ESM in identifying eloquent language cortex. In our experiments, with 11 epilepsy patients who underwent presurgical evaluation (through deep learning-based signal analysis on 637 electrodes), our proposed algorithm obtained an accuracy of 83.05% in identifying language regions, an exceptional 23% improvement with respect to the conventional ECoG-FM analysis (∼60%). Our findings have demonstrated, for the first time, that deep learning powered ECoG-FM can serve as a stand-alone modality and avoid likely hazards of the ESM in epilepsy surgery. Hence, reducing the potential for developing post-surgical morbidity in the language function. [ABSTRACT FROM AUTHOR]

Stereotactic electroencephalogaphy (sEEG) utilizes localized, penetrating depth electrodes to measure electrophysiological brain activity. It is most commonly used in the identification of epileptogenic zones in cases of refractory epilepsy. The implanted electrodes generally provide a sparse sampling of a unique set of brain regions including deeper brain structures such as hippocampus, amygdala and insula that cannot be captured by superficial measurement modalities such as electrocorticography (ECoG). Despite the overlapping clinical application and recent progress in decoding of ECoG for Brain-Computer Interfaces (BCIs), sEEG has thus far received comparatively little attention for BCI decoding. Additionally, the success of the related deep-brain stimulation (DBS) implants bodes well for the potential for chronic sEEG applications. This article provides an overview of sEEG technology, BCI-related research, and prospective future directions of sEEG for long-term BCI applications. [ABSTRACT FROM AUTHOR]

Normal and pathological networks related to seizure propagation have got attention to elucide complex seizure semiology and contribute to diagnosis and surgical monitoring in epilepsy treatment. Since focal and generalized epileptogenic syndromes abnormalities might involve multiple foci and large-scale networks, we applied electrophysiolpgy (cortco-cortico evoked potential; CCEP), and tractography to make detailed diagnosis for complex syndrome. All 14 epilepsy patients with no or little abnormality on images investigations underwent subdural grid implantation for epilepsy diagnosis. To perform quick network analysis, we recorded and analyzed high gamma activity (HGA) of epileptogenic activity and CCEPs to identify pathological activity distribution and network connectivity. [Results] Pathological CCEPs showed two negative deflections consisting of early (>40 ms) and late (>150 ms) components in electrically stable circumstance at bed side and early CCEPs appeared in 57% of the patients. On the basis of the CCEP findings, tractography detected anatomical connections. Early components of pathological CCEPs diminished after complete disconnection of tractoography-based fibers between the foci in seven of eight cases. One case with residual pathological CCEPs showed poorer outcome. Thirteen (92.8%) patients with or without CCEPs who underwent network surgery had favorable prognosis except for a case with wide traumatic epilepsy. Intraoperative CCEP measurements and HGA mapping enabled visualization of pathological networks and clinical impotence as a biomarker to improve functional prognosis. HGA/CCEP recording should shed light on pathological and complex propagation for epilepsy surgery. [ABSTRACT FROM AUTHOR]

Electrocorticography (ECoG) holds promise to provide efficient neuroprosthetic solutions for people suffering from neurological disabilities. This recording technique combines adequate temporal and spatial resolution with the lower risks of medical complications compared to the other invasive methods. ECoG is routinely used in clinical practice for preoperative cortical mapping in epileptic patients. During the last two decades, research utilizing ECoG has considerably grown, including the paradigms where behaviorally relevant information is extracted from ECoG activity with decoding algorithms of different complexity. Several research groups have advanced toward the development of assistive devices driven by brain-computer interfaces (BCIs) that decode motor commands from multichannel ECoG recordings. Here we review the evolution of this field and its recent tendencies, and discuss the potential areas for future development.