Your browser doesn't support javascript.
loading
Mostrar: 20 | 50 | 100
Resultados 1 - 20 de 215
Filtrar
1.
Annu Int Conf IEEE Eng Med Biol Soc ; 2022: 2933-2936, 2022 Jul.
Artigo em Inglês | MEDLINE | ID: mdl-36086368

RESUMO

Seizure termination has received significantly less attention than initiation and propagation and consequently, remains a poorly understood phase of seizure evolution. Yet, its study may have a significant impact on the development of efficient interventional approaches, i.e., it may be critical for the design of treatments that induce or reproduce termination mechanisms that are triggered in self-terminating seizures. In this work, we aim to study temporal and spectral features of intracranial EEG (iEEG) during epileptic seizures to find time-frequency signatures that can predict the termination patterns. We propose a deep learning model for classification of multi channel iEEG epileptic seizure termination pattern into burst suppression and continuous bursting. We decompose the raw time series seizure data into time-frequency maps using Morlet Wavelet Transform. A Convolution Neural Network (CNN) is then trained on cross-patient time-frequency maps to classify the seizure termination patterns. For evaluation of classification performance, we compared the proposed method with k-Nearest Neighbour (k-NN). The CNN is shown to achieve an accuracy of 90 % and precision of 92 % as compared to 70% and 72% accuracy and precision achieved with the k-NN respectively. The proposed model is thus able to capture the temporal and spatial patterns which results in high performance of the classifier. This method of classification can be used to predict how a particular seizure will end and can potentially inform seizure management and treatment. Clinical relevance- This method establishes a model that can be used to classify seizure termination patterns with an accuracy of 90 % which can assist in better treatment of epilepsy patients.


Assuntos
Aprendizado Profundo , Epilepsia , Eletrocorticografia , Eletroencefalografia/métodos , Epilepsia/diagnóstico , Humanos , Convulsões/diagnóstico
2.
Annu Int Conf IEEE Eng Med Biol Soc ; 2022: 2937-2940, 2022 Jul.
Artigo em Inglês | MEDLINE | ID: mdl-36086466

RESUMO

Cognitive control, the ability to rapidly shift one's attention and behavioral strategy in response to environmental changes, is often compromised across psychiatric disorders. One of the well-validated behavioral paradigms for tapping into the cognitive control circuits is a cognitive interference task, where subjects must suppress a natural response to follow a less intuitive rule. Slower response times on these tasks indicate difficulty exerting control to overcome response conflict. Conflict evokes robust electrophysiological signatures, such as theta (4-8 Hz) oscillations in the prefrontal cortex (PFC). However, the underlying neural mechanisms of conflict-evoked theta oscillations in the PFC are not clear. The objective of this work is to use a neural mass model (NMM) to find feasible cortical networks generating theta oscillations during conflict processing in human subjects. We used intracranial EEG (iEEG) recorded from dorsolateral PFC (dIPFC) and lateral temporal lobe (LTL) of human subjects with intractable epilepsy undergoing invasive monitoring, while they performed a multi-source interference task (MSIT). We used a dynamic causal modeling (DCM) framework to simulate dIPFC-LTL theta using a Jansen-Rit NMM. We found significant evidence for an LTL input into the dlPFC during the initial 500 ms of conflict processing compared to a bidirectional connection between the dlPFC and LTL. We conclude that a neural mass modeling framework can be used to elucidate candidate mechanisms of neural oscillations underlying conflict resolution in human subjects. Clinical Relevance- This can be used to find feasible target mechanisms for designing therapy in patients with compromised cognitive control. This framework can also be expanded to serve as an in-silico test bed for designing and testing neuromodulatory interventions such as electrical stimulation for improving cognitive control in mood/anxiety disorders.


Assuntos
Atenção , Córtex Pré-Frontal , Cognição/fisiologia , Humanos , Tempo de Reação/fisiologia , Sujeitos da Pesquisa
3.
J Neurosci ; 2022 Aug 30.
Artigo em Inglês | MEDLINE | ID: mdl-36041852

RESUMO

Hippocampal ripples index the reconstruction of spatiotemporal neuronal firing patterns essential for the consolidation of memories in the cortex during non-rapid eye movement sleep (NREM). Recently, cortical ripples in humans have been shown to enfold the replay of neuron firing patterns during cued recall. Here, using intracranial recordings from 18 patients (12 female), we show that cortical ripples also occur during NREM in humans, with similar density, oscillation frequency (∼90 Hz), duration, and amplitude to waking. Ripples occurred in all cortical regions with similar characteristics, unrelated to putative hippocampal connectivity, and were less dense and robust in higher association areas. Putative pyramidal and interneuron spiking phase-locked to cortical ripples during NREM, with phase delays consistent with ripple generation through pyramidal-interneuron feedback. Cortical ripples were smaller in amplitude than hippocampal ripples, but were similar in density, frequency, and duration. Cortical ripples during NREM typically occurred just prior to the upstate peak, often during spindles. Upstates and spindles have previously been associated with memory consolidation, and we found that cortical ripples grouped co-firing between units within the window of spike-timing-dependent plasticity. Thus, human NREM cortical ripples are: ubiquitous and stereotyped with a tightly focused oscillation frequency; similar to hippocampal ripples; associated with upstates and spindles; and associated with unit co-firing. These properties are consistent with cortical ripples possibly contributing to memory consolidation and other functions during NREM in humans.SIGNIFICANCE STATEMENT:In rodents, hippocampal ripples organize replay during sleep to promote memory consolidation in the cortex, where ripples also occur. However, evidence for cortical ripples in human sleep is limited, and their anatomical distribution and physiological properties are unexplored. Here, using human intracranial recordings, we demonstrate that ripples occur throughout the cortex during waking and sleep with highly stereotyped characteristics. During sleep, cortical ripples tend to occur during spindles on the down-to-upstate transition, and thus participate in a sequence of sleep waves that is important for consolidation. Furthermore, cortical ripples organize single unit spiking with timing optimal to facilitate plasticity. Therefore, cortical ripples in humans possess essential physiological properties to support memory and other cognitive functions.

4.
Sleep Breath ; 2022 Aug 16.
Artigo em Inglês | MEDLINE | ID: mdl-35971023

RESUMO

PURPOSE: Sleep-disordered breathing may be induced by, exacerbate, or complicate recovery from critical illness. Disordered breathing during sleep, which itself is often fragmented, can go unrecognized in the intensive care unit (ICU). The objective of this study was to investigate the prevalence, severity, and risk factors of sleep-disordered breathing in ICU patients using a single respiratory belt and oxygen saturation signals. METHODS: Patients in three ICUs at Massachusetts General Hospital wore a thoracic respiratory effort belt as part of a clinical trial for up to 7 days and nights. Using a previously developed machine learning algorithm, we processed respiratory and oximetry signals to measure the 3% apnea-hypopnea index (AHI) and estimate AH-specific hypoxic burden and periodic breathing. We trained models to predict AHI categories for 12-h segments from risk factors, including admission variables and bio-signals data, available at the start of these segments. RESULTS: Of 129 patients, 68% had an AHI ≥ 5; 40% an AHI > 15, and 19% had an AHI > 30 while critically ill. Median [interquartile range] hypoxic burden was 2.8 [0.5, 9.8] at night and 4.2 [1.0, 13.7] %min/h during the day. Of patients with AHI ≥ 5, 26% had periodic breathing. Performance of predicting AHI-categories from risk factors was poor. CONCLUSIONS: Sleep-disordered breathing and sleep apnea events while in the ICU are common and are associated with substantial burden of hypoxia and periodic breathing. Detection is feasible using limited bio-signals, such as respiratory effort and SpO2 signals, while risk factors were insufficient to predict AHI severity.

5.
Proc Natl Acad Sci U S A ; 119(28): e2107797119, 2022 07 12.
Artigo em Inglês | MEDLINE | ID: mdl-35867767

RESUMO

Declarative memory encoding, consolidation, and retrieval require the integration of elements encoded in widespread cortical locations. The mechanism whereby such "binding" of different components of mental events into unified representations occurs is unknown. The "binding-by-synchrony" theory proposes that distributed encoding areas are bound by synchronous oscillations enabling enhanced communication. However, evidence for such oscillations is sparse. Brief high-frequency oscillations ("ripples") occur in the hippocampus and cortex and help organize memory recall and consolidation. Here, using intracranial recordings in humans, we report that these ∼70-ms-duration, 90-Hz ripples often couple (within ±500 ms), co-occur (≥ 25-ms overlap), and, crucially, phase-lock (have consistent phase lags) between widely distributed focal cortical locations during both sleep and waking, even between hemispheres. Cortical ripple co-occurrence is facilitated through activation across multiple sites, and phase locking increases with more cortical sites corippling. Ripples in all cortical areas co-occur with hippocampal ripples but do not phase-lock with them, further suggesting that cortico-cortical synchrony is mediated by cortico-cortical connections. Ripple phase lags vary across sleep nights, consistent with participation in different networks. During waking, we show that hippocampo-cortical and cortico-cortical coripples increase preceding successful delayed memory recall, when binding between the cue and response is essential. Ripples increase and phase-modulate unit firing, and coripples increase high-frequency correlations between areas, suggesting synchronized unit spiking facilitating information exchange. co-occurrence, phase synchrony, and high-frequency correlation are maintained with little decrement over very long distances (25 cm). Hippocampo-cortico-cortical coripples appear to possess the essential properties necessary to support binding by synchrony during memory retrieval and perhaps generally in cognition.


Assuntos
Córtex Cerebral , Hipocampo , Consolidação da Memória , Rememoração Mental , Sono , Vigília , Córtex Cerebral/fisiologia , Eletrocorticografia , Hipocampo/fisiologia , Humanos , Consolidação da Memória/fisiologia , Rememoração Mental/fisiologia , Sono/fisiologia , Vigília/fisiologia
6.
J Neurosci ; 2022 Jul 29.
Artigo em Inglês | MEDLINE | ID: mdl-35906069

RESUMO

During human seizures organized waves of voltage activity rapidly sweep across the cortex. Two contradictory theories describe the source of these fast traveling waves: either a slowly advancing narrow region of multiunit activity (an ictal wavefront) or a fixed cortical location. Limited observations and different analyses prevent resolution of these incompatible theories. Here we address this disagreement by combining the methods and microelectrode array recordings (N=11 patients, 2 females, N=31 seizures) from previous human studies to analyze the traveling wave source. We find - inconsistent with both existing theories - a transient relationship between the ictal wavefront and traveling waves, and multiple stable directions of traveling waves in many seizures. Using a computational model that combines elements of both existing theories, we show that interactions between an ictal wavefront and fixed source reproduce the traveling wave dynamics observed in vivo We conclude that combining both existing theories can generate the diversity of ictal traveling waves.Significance StatementThe source of voltage discharges that propagate across cortex during human seizures remains unknown. Two candidate theories exist, each proposing a different discharge source. Support for each theory consists of observations from a small number of human subject recordings, analyzed with separately developed methods. How the different, limited data and different analysis methods impact the evidence for each theory is unclear. To resolve these differences, we combine the unique, human microelectrode array recordings collected separately for each theory and analyze these combined data with a unified approach. We show that neither existing theory adequately describes the data. We then propose a new theory that unifies existing proposals and successfully reproduces the voltage discharge dynamics observed in vivo.

7.
IEEE Open J Circuits Syst ; 3: 82-96, 2022.
Artigo em Inglês | MEDLINE | ID: mdl-35647555

RESUMO

This paper reviews and analyses the design of popular radio frequency energy harvesting systems and proposes a method to qualitatively and quantitatively analyze their circuit architectures using new square-wave approximation method. This approach helps in simplifying design analysis. Using this analysis, we can establish no load output voltage characteristics, upper limit on rectifier efficiency, and maximum power characteristics of a rectifier. This paper will help guide the design of RF energy harvesting rectifier circuits for radio frequency identification (RFIDs), the Internet of Things (IoTs), wearable, and implantable medical device applications. Different application scenarios are explained in the context of design challenges, and corresponding design considerations are discussed in order to evaluate their performance. The pros and cons of different rectifier topologies are also investigated. In addition to presenting the popular rectifier topologies, new measurement results of these energy harvester topologies, fabricated in 65nm, 130nm and 180nm CMOS technologies are also presented.

9.
J Neurosci ; 42(25): 5007-5020, 2022 06 22.
Artigo em Inglês | MEDLINE | ID: mdl-35589391

RESUMO

Consolidation of memory is believed to involve offline replay of neural activity. While amply demonstrated in rodents, evidence for replay in humans, particularly regarding motor memory, is less compelling. To determine whether replay occurs after motor learning, we sought to record from motor cortex during a novel motor task and subsequent overnight sleep. A 36-year-old man with tetraplegia secondary to cervical spinal cord injury enrolled in the ongoing BrainGate brain-computer interface pilot clinical trial had two 96-channel intracortical microelectrode arrays placed chronically into left precentral gyrus. Single- and multi-unit activity was recorded while he played a color/sound sequence matching memory game. Intended movements were decoded from motor cortical neuronal activity by a real-time steady-state Kalman filter that allowed the participant to control a neurally driven cursor on the screen. Intracortical neural activity from precentral gyrus and 2-lead scalp EEG were recorded overnight as he slept. When decoded using the same steady-state Kalman filter parameters, intracortical neural signals recorded overnight replayed the target sequence from the memory game at intervals throughout at a frequency significantly greater than expected by chance. Replay events occurred at speeds ranging from 1 to 4 times as fast as initial task execution and were most frequently observed during slow-wave sleep. These results demonstrate that recent visuomotor skill acquisition in humans may be accompanied by replay of the corresponding motor cortex neural activity during sleep.SIGNIFICANCE STATEMENT Within cortex, the acquisition of information is often followed by the offline recapitulation of specific sequences of neural firing. Replay of recent activity is enriched during sleep and may support the consolidation of learning and memory. Using an intracortical brain-computer interface, we recorded and decoded activity from motor cortex as a human research participant performed a novel motor task. By decoding neural activity throughout subsequent sleep, we find that neural sequences underlying the recently practiced motor task are repeated throughout the night, providing direct evidence of replay in human motor cortex during sleep. This approach, using an optimized brain-computer interface decoder to characterize neural activity during sleep, provides a framework for future studies exploring replay, learning, and memory.


Assuntos
Aprendizagem/fisiologia , Córtex Motor/fisiologia , Sono/fisiologia , Adulto , Interfaces Cérebro-Computador , Vértebras Cervicais , Eletroencefalografia/métodos , Humanos , Masculino , Projetos Piloto , Quadriplegia/etiologia , Quadriplegia/fisiopatologia , Traumatismos da Medula Espinal/complicações , Traumatismos da Medula Espinal/fisiopatologia
10.
JAMA Neurol ; 79(6): 614-622, 2022 06 01.
Artigo em Inglês | MEDLINE | ID: mdl-35499837

RESUMO

Importance: The hippocampus is a highly epileptogenic brain region, yet over 90% of hippocampal epileptiform activity (HEA) cannot be identified on scalp electroencephalogram (EEG) by human experts. Currently, detection of HEA requires intracranial electrodes, which limits our understanding of the role of HEA in brain diseases. Objective: To develop and validate a machine learning algorithm that accurately detects HEA from a standard scalp EEG, without the need for intracranial electrodes. Design, Setting, and Participants: In this diagnostic study, conducted from 2008 to 2021, EEG data were used from patients with temporal lobe epilepsy (TLE) and healthy controls (HCs) to train and validate a deep neural network, HEAnet, to detect HEA on scalp EEG. Participants were evaluated at tertiary-level epilepsy centers at 2 academic hospitals: Massachusetts General Hospital (MGH) or Brigham and Women's Hospital (BWH). Included in the study were patients aged 12 to 78 years with a clinical diagnosis of TLE and HCs without epilepsy. Patients with TLE and HCs with a history of intracranial surgery were excluded from the study. Exposures: Simultaneous intracranial EEG and/or scalp EEG. Main Outcomes and Measures: Performance was assessed using cross-validated areas under the receiver operating characteristic curve (AUC ROC) and precision-recall curve (AUC PR) and additional clinically relevant metrics. Results: HEAnet was trained and validated using data sets that were derived from a convenience sample of 141 eligible participants (97 with TLE and 44 HCs without epilepsy) whose retrospective EEG data were readily available. Data set 1 included the simultaneous scalp EEG and intracranial electrode recordings of 51 patients with TLE (mean [SD] age, 40.7 [15.9] years; 30 men [59%]) at MGH. An automatically generated training data set with 972 095 positive HEA examples was created, in addition to a held-out expert-annotated testing data set with 22 762 positive HEA examples. HEAnet's performance was validated on 2 independent scalp EEG data sets: (1) data set 2 (at MGH; 24 patients with TLE and 20 HCs; mean [SD] age, 42.3 [16.2] years; 17 men [39%]) and (2) data set 3 (at BWH; 22 patients with TLE and 24 HCs; mean [SD] age, 43.0 [14.4] years; 20 men [43%]). For single-event detection of HEA on data set 1, HEAnet achieved a mean (SD) AUC ROC of 0.89 (0.01) and a mean (SD) AUC PR of 0.39 (0.03). On external validation with data sets 2 and 3, HEAnet accurately distinguished TLE from HC (AUC ROC of 0.88 and 0.95, respectively) and predicted epilepsy lateralization with 100% and 92% accuracy, respectively. HEAnet tracked dynamic changes in HEA in response to seizure medication adjustments and performed comparably with human experts in diagnosing TLE from 1-hour scalp EEG recordings, diagnosing TLE in several individuals that experts missed. Without reducing specificity, addition of HEAnet to human expert EEG review increased sensitivity for diagnosing TLE in humans from 50% to 58% to 63% to 67%. Conclusions and Relevance: Results of this diagnostic study suggest that HEAnet provides a novel, noninvasive, quantitative, and clinically relevant biomarker of hippocampal hyperexcitability in humans.


Assuntos
Epilepsia do Lobo Temporal , Epilepsia , Adulto , Eletroencefalografia/métodos , Epilepsia do Lobo Temporal/diagnóstico , Feminino , Hipocampo , Humanos , Masculino , Estudos Retrospectivos , Couro Cabeludo
11.
Brain Stimul ; 15(2): 491-508, 2022.
Artigo em Inglês | MEDLINE | ID: mdl-35247646

RESUMO

BACKGROUND: Electrical neuromodulation via direct electrical stimulation (DES) is an increasingly common therapy for a wide variety of neuropsychiatric diseases. Unfortunately, therapeutic efficacy is inconsistent, likely due to our limited understanding of the relationship between the massive stimulation parameter space and brain tissue responses. OBJECTIVE: To better understand how different parameters induce varied neural responses, we systematically examined single pulse-induced cortico-cortico evoked potentials (CCEP) as a function of stimulation amplitude, duration, brain region, and whether grey or white matter was stimulated. METHODS: We measured voltage peak amplitudes and area under the curve (AUC) of intracranially recorded stimulation responses as a function of distance from the stimulation site, pulse width, current injected, location relative to grey and white matter, and brain region stimulated (N = 52, n = 719 stimulation sites). RESULTS: Increasing stimulation pulse width increased responses near the stimulation location. Increasing stimulation amplitude (current) increased both evoked amplitudes and AUC nonlinearly. Locally (<15 mm), stimulation at the boundary between grey and white matter induced larger responses. In contrast, for distant sites (>15 mm), white matter stimulation consistently produced larger responses than stimulation in or near grey matter. The stimulation location-response curves followed different trends for cingulate, lateral frontal, and lateral temporal cortical stimulation. CONCLUSION: These results demonstrate that a stronger local response may require stimulation in the grey-white boundary while stimulation in the white matter could be needed for network activation. Thus, stimulation parameters tailored for a specific anatomical-functional outcome may be key to advancing neuromodulatory therapy.


Assuntos
Córtex Cerebral , Substância Branca , Encéfalo , Córtex Cerebral/fisiologia , Estimulação Elétrica/métodos , Potenciais Evocados/fisiologia , Humanos
12.
Neural Comput ; 34(5): 1100-1135, 2022 04 15.
Artigo em Inglês | MEDLINE | ID: mdl-35344988

RESUMO

With the accelerated development of neural recording technology over the past few decades, research in integrative neuroscience has become increasingly reliant on data analysis methods that are scalable to high-dimensional recordings and computationally tractable. Latent process models have shown promising results in estimating the dynamics of cognitive processes using individual models for each neuron's receptive field. However, scaling these models to work on high-dimensional neural recordings remains challenging. Not only is it impractical to build receptive field models for individual neurons of a large neural population, but most neural data analyses based on individual receptive field models discard the local history of neural activity, which has been shown to be critical in the accurate inference of the underlying cognitive processes. Here, we propose a novel, scalable latent process model that can directly estimate cognitive process dynamics without requiring precise receptive field models of individual neurons or brain nodes. We call this the direct discriminative decoder (DDD) model. The DDD model consists of (1) a discriminative process that characterizes the conditional distribution of the signal to be estimated, or state, as a function of both the current neural activity and its local history, and (2) a state transition model that characterizes the evolution of the state over a longer time period. While this modeling framework inherits advantages of existing latent process modeling methods, its computational cost is tractable. More important, the solution can incorporate any information from the history of neural activity at any timescale in computing the estimate of the state process. There are many choices in building the discriminative process, including deep neural networks or gaussian processes, which adds to the flexibility of the framework. We argue that these attributes of the proposed methodology, along with its applicability to different modalities of neural data, make it a powerful tool for high-dimensional neural data analysis. We also introduce an extension of these methods, called the discriminative-generative decoder (DGD). The DGD includes both discriminative and generative processes in characterizing observed data. As a result, we can combine physiological correlates like behavior with neural data to better estimate underlying cognitive processes. We illustrate the methods, including steps for inference and model identification, and demonstrate applications to multiple data analysis problems with high-dimensional neural recordings. The modeling results demonstrate the computational and modeling advantages of the DDD and DGD methods.


Assuntos
Redes Neurais de Computação , Neurônios , Encéfalo/fisiologia , Neurônios/fisiologia , Distribuição Normal
13.
World Neurosurg ; 161: e199-e209, 2022 05.
Artigo em Inglês | MEDLINE | ID: mdl-35108645

RESUMO

OBJECTIVE: Temporal lobe epilepsy (TLE) is one of the most common causes of medically refractory focal epilepsy. Anterior temporal lobectomy (ATL) leads to improved seizure control in patients with medically refractory TLE. Various auras are associated with TLE; however, the relationships between aura type and outcome after ATL are poorly understood. Our objective was to investigate the associations among clinical features, aura type, and seizure outcome after ATL. METHODS: The records of patients who underwent ATL between 1993 and 2016 at a single institution (N = 174) were retrospectively reviewed. Demographic and clinical variables were compared among aura types using analysis of variance and logistic regression analysis. A multiple regression analysis was conducted to determine whether aura type predicted seizure outcome after ATL. RESULTS: Mesial temporal sclerosis (MTS) on magnetic resonance imaging inversely correlated with cephalic auras (P = 0.0090). Affective auras (P = 0.014) and somatosensory auras (P = 0.021) were correlated with findings of MTS on pathology, whereas this finding was inversely correlated with the presence of auditory auras (P = 0.0056). On multiple regression analysis, predictors of worse seizure outcome after ATL were cephalic auras (P = 0.0048), gustatory auras (P = 0.029), visual auras (P = 0.049), and tonic-clonic seizures (P = 0.047). Fewer preoperative antiepileptic medications (P = 0.0032), and presence of multiple auras (P = 0.011) were associated with better outcome. CONCLUSIONS: Cephalic auras, gustatory auras, and visual auras were associated with worse seizure outcome after ATL.


Assuntos
Epilepsia Resistente a Medicamentos , Epilepsia do Lobo Temporal , Lobectomia Temporal Anterior , Anticonvulsivantes , Epilepsia Resistente a Medicamentos/diagnóstico por imagem , Epilepsia Resistente a Medicamentos/cirurgia , Epilepsia do Lobo Temporal/cirurgia , Humanos , Estudos Retrospectivos , Convulsões/cirurgia
14.
Nat Neurosci ; 25(2): 252-263, 2022 02.
Artigo em Inglês | MEDLINE | ID: mdl-35102333

RESUMO

Recent advances in multi-electrode array technology have made it possible to monitor large neuronal ensembles at cellular resolution in animal models. In humans, however, current approaches restrict recordings to a few neurons per penetrating electrode or combine the signals of thousands of neurons in local field potential (LFP) recordings. Here we describe a new probe variant and set of techniques that enable simultaneous recording from over 200 well-isolated cortical single units in human participants during intraoperative neurosurgical procedures using silicon Neuropixels probes. We characterized a diversity of extracellular waveforms with eight separable single-unit classes, with differing firing rates, locations along the length of the electrode array, waveform spatial spread and modulation by LFP events such as inter-ictal discharges and burst suppression. Although some challenges remain in creating a turnkey recording system, high-density silicon arrays provide a path for studying human-specific cognitive processes and their dysfunction at unprecedented spatiotemporal resolution.


Assuntos
Córtex Cerebral , Neurônios , Animais , Eletrodos , Humanos , Neurônios/fisiologia , Silício
15.
Neurobiol Dis ; 165: 105645, 2022 04.
Artigo em Inglês | MEDLINE | ID: mdl-35104646

RESUMO

OBJECTIVE: Despite their possible importance in the design of novel neuromodulatory approaches and in understanding status epilepticus, the dynamics and mechanisms of seizure termination are not well studied. We examined intracranial recordings from patients with epilepsy to differentiate seizure termination patterns and investigated whether these patterns are indicative of different underlying mechanisms. METHODS: Seizures were classified into one of two termination patterns: (a) those that end simultaneously across the brain (synchronous), and (b) those whose termination is piecemeal across the cortex (asynchronous). Both types ended with either a burst suppression pattern, or continuous seizure activity. These patterns were quantified and compared using burst suppression ratio, absolute energy, and network connectivity. RESULTS: Seizures with electrographic generalization showed burst suppression patterns in 90% of cases, compared with only 60% of seizures which remained focal. Interestingly, we found similar absolute energy and burst suppression ratios in seizures with synchronous and asynchronous termination, while seizures with continuous seizure activity were found to be different from seizures with burst suppression, showing lower energy during seizure and lower burst suppression ratio at the start and end of seizure. Finally, network density was observed to increase with seizure progression, with significantly lower densities in seizures with continuous seizure activity compared to seizures with burst suppression. SIGNIFICANCE: Based on this spatiotemporal classification scheme, we suggest that there are a limited number of seizure termination patterns and dynamics. If this bears out, it would imply that the number of mechanisms underlying seizure termination is also constrained. Seizures with different termination patterns exhibit different dynamics even before their start. This may provide useful clues about how seizures may be managed, which in turn may lead to more targeted modes of therapy for seizure control.


Assuntos
Ondas Encefálicas , Epilepsia , Encéfalo , Eletroencefalografia , Humanos , Convulsões
16.
Sleep ; 45(4)2022 04 11.
Artigo em Inglês | MEDLINE | ID: mdl-34984446

RESUMO

STUDY OBJECTIVES: Alterations in sleep spindles have been linked to cognitive impairment. This finding has contributed to a growing interest in identifying sleep-based biomarkers of cognition and neurodegeneration, including sleep spindles. However, flexibility surrounding spindle definitions and algorithm parameter settings present a methodological challenge. The aim of this study was to characterize how spindle detection parameter settings influence the association between spindle features and cognition and to identify parameters with the strongest association with cognition. METHODS: Adult patients (n = 167, 49 ± 18 years) completed the NIH Toolbox Cognition Battery after undergoing overnight diagnostic polysomnography recordings for suspected sleep disorders. We explored 1000 combinations across seven parameters in Luna, an open-source spindle detector, and used four features of detected spindles (amplitude, density, duration, and peak frequency) to fit linear multiple regression models to predict cognitive scores. RESULTS: Spindle features (amplitude, density, duration, and mean frequency) were associated with the ability to predict raw fluid cognition scores (r = 0.503) and age-adjusted fluid cognition scores (r = 0.315) with the best spindle parameters. Fast spindle features generally showed better performance relative to slow spindle features. Spindle features weakly predicted total cognition and poorly predicted crystallized cognition regardless of parameter settings. CONCLUSIONS: Our exploration of spindle detection parameters identified optimal parameters for studies of fluid cognition and revealed the role of parameter interactions for both slow and fast spindles. Our findings support sleep spindles as a sleep-based biomarker of fluid cognition.


Assuntos
Eletroencefalografia , Transtornos do Sono-Vigília , Adulto , Cognição , Humanos , Polissonografia , Sono , Fases do Sono
17.
Nature ; 600(7888): 274-278, 2021 12.
Artigo em Inglês | MEDLINE | ID: mdl-34759318

RESUMO

The biophysical properties of neurons are the foundation for computation in the brain. Neuronal size is a key determinant of single neuron input-output features and varies substantially across species1-3. However, it is unknown whether different species adapt neuronal properties to conserve how single neurons process information4-7. Here we characterize layer 5 cortical pyramidal neurons across 10 mammalian species to identify the allometric relationships that govern how neuronal biophysics change with cell size. In 9 of the 10 species, we observe conserved rules that control the conductance of voltage-gated potassium and HCN channels. Species with larger neurons, and therefore a decreased surface-to-volume ratio, exhibit higher membrane ionic conductances. This relationship produces a conserved conductance per unit brain volume. These size-dependent rules result in large but predictable changes in somatic and dendritic integrative properties. Human neurons do not follow these allometric relationships, exhibiting much lower voltage-gated potassium and HCN conductances. Together, our results in layer 5 neurons identify conserved evolutionary principles for neuronal biophysics in mammals as well as notable features of the human cortex.


Assuntos
Biofísica , Tamanho Celular , Córtex Cerebral/citologia , Mamíferos , Células Piramidais/citologia , Células Piramidais/fisiologia , Animais , Córtex Cerebral/anatomia & histologia , Córtex Cerebral/fisiologia , Dendritos/fisiologia , Condutividade Elétrica , Humanos , Canais Disparados por Nucleotídeos Cíclicos Ativados por Hiperpolarização/metabolismo , Masculino , Canais de Potássio de Abertura Dependente da Tensão da Membrana/metabolismo , Especificidade da Espécie
18.
Nat Biomed Eng ; 2021 Nov 01.
Artigo em Inglês | MEDLINE | ID: mdl-34725508

RESUMO

Deficits in cognitive control-that is, in the ability to withhold a default pre-potent response in favour of a more adaptive choice-are common in depression, anxiety, addiction and other mental disorders. Here we report proof-of-concept evidence that, in participants undergoing intracranial epilepsy monitoring, closed-loop direct stimulation of the internal capsule or striatum, especially the dorsal sites, enhances the participants' cognitive control during a conflict task. We also show that closed-loop stimulation upon the detection of lapses in cognitive control produced larger behavioural changes than open-loop stimulation, and that task performance for single trials can be directly decoded from the activity of a small number of electrodes via neural features that are compatible with existing closed-loop brain implants. Closed-loop enhancement of cognitive control might remediate underlying cognitive deficits and aid the treatment of severe mental disorders.

19.
Chaos ; 31(10): 103108, 2021 Oct.
Artigo em Inglês | MEDLINE | ID: mdl-34717330

RESUMO

Determining synchronization, causality, and dynamical similarity in highly complex nonlinear systems like brains is challenging. Although distinct, these measures are related by the unknown deterministic structure of the underlying dynamical system. For two systems that are not independent on each other, either because they result from a common process or they are already synchronized, causality measures typically fail. Here, we introduce dynamical ergodicity to assess dynamical similarity between time series and then combine this new measure with cross-dynamical delay differential analysis to estimate causal interactions between time series. We first tested this approach on simulated data from coupled Rössler systems where ground truth was known. We then applied it to intracranial electroencephalographic data from patients with epilepsy and found distinct dynamical states that were highly predictive of epileptic seizures.


Assuntos
Eletroencefalografia , Epilepsia , Encéfalo , DDT/análogos & derivados , Humanos , Dinâmica não Linear
20.
Clin Neurophysiol ; 132(11): 2916-2931, 2021 11.
Artigo em Inglês | MEDLINE | ID: mdl-34419344

RESUMO

OBJECTIVE: Interictal discharges (IIDs) and high frequency oscillations (HFOs) are established neurophysiologic biomarkers of epilepsy, while microseizures are less well studied. We used custom poly(3,4-ethylenedioxythiophene) polystyrene sulfonate (PEDOT:PSS) microelectrodes to better understand these markers' microscale spatial dynamics. METHODS: Electrodes with spatial resolution down to 50 µm were used to record intraoperatively in 30 subjects. IIDs' degree of spread and spatiotemporal paths were generated by peak-tracking followed by clustering. Repeating HFO patterns were delineated by clustering similar time windows. Multi-unit activity (MUA) was analyzed in relation to IID and HFO timing. RESULTS: We detected IIDs encompassing the entire array in 93% of subjects, while localized IIDs, observed across < 50% of channels, were seen in 53%. IIDs traveled along specific paths. HFOs appeared in small, repeated spatiotemporal patterns. Finally, we identified microseizure events that spanned 50-100 µm. HFOs covaried with MUA, but not with IIDs. CONCLUSIONS: Overall, these data suggest that irritable cortex micro-domains may form part of an underlying pathologic architecture which could contribute to the seizure network. SIGNIFICANCE: These results, supporting the possibility that epileptogenic cortex comprises a mosaic of irritable domains, suggests that microscale approaches might be an important perspective in devising novel seizure control therapies.


Assuntos
Mapeamento Encefálico/métodos , Encéfalo/fisiopatologia , Eletroencefalografia/métodos , Epilepsia/fisiopatologia , Monitorização Neurofisiológica Intraoperatória/métodos , Microeletrodos , Adulto , Encéfalo/cirurgia , Eletroencefalografia/instrumentação , Epilepsia/diagnóstico , Epilepsia/cirurgia , Feminino , Humanos , Monitorização Neurofisiológica Intraoperatória/instrumentação , Masculino , Pessoa de Meia-Idade , Adulto Jovem
SELEÇÃO DE REFERÊNCIAS
DETALHE DA PESQUISA
...