skip to main content

Explore Research Products in the NSF-PAR

  • NSF Public Access
  • Search Results
  • Beta oscillations in the sensorimotor cortex correlate with disease and remission in benign epilepsy with centrotemporal spikes
Title: Beta oscillations in the sensorimotor cortex correlate with disease and remission in benign epilepsy with centrotemporal spikes
Abstract Introduction

Benign epilepsy with centrotemporal spikes (BECTS) is a common form of childhood epilepsy with the majority of those afflicted remitting during their early teenage years. Seizures arise from the lower half of the sensorimotor cortex of the brain (e.g. seizure onset zone) and the abnormal epileptiform discharges observed increase during NREM sleep. To date no clinical factors reliably predict disease course, making determination of ongoing seizure risk a significant challenge. Prior work in BECTS have shown abnormalities in beta band (14.9–30 Hz) oscillations during movement and rest. Oscillations in this frequency band are modulated by state of consciousness and thought to reflect intrinsic inhibitory mechanisms.

 Methods

We used high density EEG and source localization techniques to examine beta band activity in the seizure onset zone (sensorimotor cortex) in a prospective cohort of children with BECTS and healthy controls during sleep. We hypothesized that beta power in the sensorimotor cortex would be different between patients and healthy controls, and that beta abnormalities would improve with resolution of disease in this self‐limited epilepsy syndrome. We further explored the specificity of our findings and correlation with clinical features. Statistical testing was performed using logistic and standard linear regression models.

 Results

We found that beta band power in the seizure onset zone is different between healthy controls and BECTS patients. We also found that a longer duration of time spent seizure‐free (corresponding to disease remission) correlates with lower beta power in the seizure onset zone. Exploratory spatial analysis suggests this effect is not restricted to the sensorimotor cortex. Exploratory frequency analysis suggests that this phenomenon is also observed in alpha and gamma range activity. We found no relationship between beta power and the presence or rate of epileptiform discharges in the sensorimotor cortex or a test of sensorimotor performance.

 Conclusion

These results provide evidence that cortical beta power in the seizure onset zone may provide a dynamic physiological biomarker of disease in BECTS.

  more » « less
NSF-PAR ID:
10086378
Author(s) / Creator(s):
 ;  ;  ;  ;  ;  ;  ;  ;  ;  
Publisher / Repository:
Wiley Blackwell (John Wiley & Sons)
Date Published:
Journal Name:
Brain and Behavior
Volume:
9
Issue:
3
ISSN:
2162-3279
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
More Like this
  1. ; ; ; ; ; ; ; ; ; ; et al ( , Epilepsia)
    Abstract Objective

    Temporal coordination between oscillations enables intercortical communication and is implicated in cognition. Focal epileptic activity can affect distributed neural networks and interfere with these interactions. Refractory pediatric epilepsies are often accompanied by substantial cognitive comorbidity, but mechanisms and predictors remain mostly unknown. Here, we investigate oscillatory coupling across large‐scale networks in the developing brain.

     Methods

    We analyzed large‐scale intracranial electroencephalographic recordings in children with medically refractory epilepsy undergoing presurgical workup (n = 25, aged 3–21 years). Interictal epileptiform discharges (IEDs), pathologic high‐frequency oscillations (HFOs), and sleep spindles were detected. Spatiotemporal metrics of oscillatory coupling were determined and correlated with age, cognitive function, and postsurgical outcome.

     Results

    Children with epilepsy demonstrated significant temporal coupling of both IEDs and HFOs to sleep spindles in discrete brain regions. HFOs were associated with stronger coupling patterns than IEDs. These interactions involved tissue beyond the clinically identified epileptogenic zone and were ubiquitous across cortical regions. Increased spatial extent of coupling was most prominent in older children. Poor neurocognitive function was significantly correlated with high IED–spindle coupling strength and spatial extent; children with strong pathologic interactions additionally had decreased likelihood of postoperative seizure freedom.

     Significance

    Our findings identify pathologic large‐scale oscillatory coupling patterns in the immature brain. These results suggest that such intercortical interactions could predict risk for adverse neurocognitive and surgical outcomes, with the potential to serve as novel therapeutic targets to restore physiologic development.

     
    more » « less
  2. ; ; ; ; ; ; ; ; ; ; et al ( , Epilepsia)
    Abstract Objective

    Interictal epileptiform discharges (IEDs) were shown to be associated with cognitive impairment in persons with epilepsy. Previous studies indicated that IED rate, location, timing, and spatial relation to the seizure onset zone could predict an IED's impact on memory encoding and retrieval if they occurred in lateral temporal, mesial temporal, or parietal regions. In this study, we explore the influence that other IED properties (e.g., amplitude, duration, white matter classification) have on memory performance. We were specifically interested in investigating the influence that lateral temporal IEDs have on memory encoding.

     Methods

    Two hundred sixty‐one subjects with medication‐refractory epilepsy undergoing intracranial electroencephalographic monitoring performed multiple sessions of a delayed free‐recall task (n = 671). Generalized linear mixed models were utilized to examine the relationship between IED properties and memory performance.

     Results

    We found that increased IED rate, IEDs propagating in white matter, and IEDs localized to the left middle temporal region were associated with poorer memory performance. For lateral temporal IEDs, we observed a significant interaction between IED white matter categorization and amplitude, where IEDs with an increased amplitude and white matter propagation were associated with reduced memory performance. Additionally, changes in alpha power after an IED showed a significant positive correlation with memory performance.

     Significance

    Our results suggest that IED properties may be useful for predicting the impact an IED has on memory encoding. We provide an essential step toward understanding pathological versus potentially beneficial interictal epileptiform activity.

     
    more » « less
  3. ; ; ; ; ; ; ( , Epilepsia)
    Summary Objective

    Identification of patient‐specific epileptogenic networks is critical to designing successful treatment strategies. Multiple noninvasive methods have been used to characterize epileptogenic networks. However, these methods lack the spatiotemporal resolution to allow precise localization of epileptiform activity. We used intracranial recordings, at much higher spatiotemporal resolution, across a cohort of patients with mesial temporal lobe epilepsy (MTLE) to delineate features common to their epileptogenic networks. We used interictal rather than seizure data because interictal spikes occur more frequently, providing us greater power for analyzing variances in the network.

     Methods

    Intracranial recordings from 10 medically refractoryMTLEpatients were analyzed. In each patient, hour‐long recordings were selected for having frequent interictal discharges and no ictal events. For all possible pairs of electrodes, conditional probability of the occurrence of interictal spikes within a 150‐millisecond bin was computed. These probabilities were used to construct a weighted graph between all electrodes, and the node degree was estimated. To assess the relationship of the highly connected regions in this network to the clinically identified seizure network, logistic regression was used to model the regions that were surgically resected using weighted node degree and number of spikes in each channel as factors. Lastly, the conditional spike probability was normalized and averaged across patients to visualize theMTLEnetwork at group level.

     Results

    We generated the first graph of connectivity across a cohort ofMTLEpatients using interictal activity. The most consistent connections were hippocampus to amygdala, anterior fusiform cortex to hippocampus, and parahippocampal gyrus projections to amygdala. Additionally, the weighted node degree and number of spikes modeled the brain regions identified as seizure networks by clinicians.

     Significance

    Apart from identifying interictal measures that can model patient‐specific epileptogenic networks, we also produce a group map of network connectivity from a cohort ofMTLEpatients.

     
    more » « less
  4. ; ; ; ; ; ; ; ; ; ; et al ( , Epilepsia)
    Abstract Objective

    Anterior temporal lobectomy (ATL) is a widely performed and successful intervention for drug‐resistant temporal lobe epilepsy (TLE). However, up to one third of patients experience seizure recurrence within 1 year after ATL. Despite the extensive literature on presurgical electroencephalography (EEG) and magnetic resonance imaging (MRI) abnormalities to prognosticate seizure freedom following ATL, the value of quantitative analysis of visually reviewed normal interictal EEG in such prognostication remains unclear. In this retrospective multicenter study, we investigate whether machine learning analysis of normal interictal scalp EEG studies can inform the prediction of postoperative seizure freedom outcomes in patients who have undergone ATL.

     Methods

    We analyzed normal presurgical scalp EEG recordings from 41 Mayo Clinic (MC) and 23 Cleveland Clinic (CC) patients. We used an unbiased automated algorithm to extract eyes closed awake epochs from scalp EEG studies that were free of any epileptiform activity and then extracted spectral EEG features representing (a) spectral power and (b) interhemispheric spectral coherence in frequencies between 1 and 25 Hz across several brain regions. We analyzed the differences between the seizure‐free and non–seizure‐free patients and employed a Naïve Bayes classifier using multiple spectral features to predict surgery outcomes. We trained the classifier using a leave‐one‐patient‐out cross‐validation scheme within the MC data set and then tested using the out‐of‐sample CC data set. Finally, we compared the predictive performance of normal scalp EEG‐derived features against MRI abnormalities.

     Results

    We found that several spectral power and coherence features showed significant differences correlated with surgical outcomes and that they were most pronounced in the 10–25 Hz range. The Naïve Bayes classification based on those features predicted 1‐year seizure freedom following ATL with area under the curve (AUC) values of 0.78 and 0.76 for the MC and CC data sets, respectively. Subsequent analyses revealed that (a) interhemispheric spectral coherence features in the 10–25 Hz range provided better predictability than other combinations and (b) normal scalp EEG‐derived features provided superior and potentially distinct predictive value when compared with MRI abnormalities (>10% higher F1 score).

     Significance

    These results support that quantitative analysis of even a normal presurgical scalp EEG may help prognosticate seizure freedom following ATL in patients with drug‐resistant TLE. Although the mechanism for this result is not known, the scalp EEG spectral and coherence properties predicting seizure freedom may represent activity arising from the neocortex or the networks responsible for temporal lobe seizure generation within vs outside the margins of an ATL.

     
    more » « less
  5. ; ; ; ; ; ; ; ; ( , Epilepsia)
    Abstract Objective

    Cognitive impairment often impacts quality of life in epilepsy even if seizures are controlled. Word‐finding difficulty is particularly prevalent and often attributed to etiological (static, baseline) circuit alterations. We sought to determine whether interictal discharges convey significant superimposed contributions to word‐finding difficulty in patients, and if so, through which cognitive mechanism(s).

     Methods

    Twenty‐three patients undergoing intracranial monitoring for drug‐resistant epilepsy participated in multiple tasks involving word production (auditory naming, short‐term verbal free recall, repetition) to probe word‐finding difficulty across different cognitive domains. We compared behavioral performance between trials with versus without interictal discharges across six major brain areas and adjusted for intersubject differences using mixed‐effects models. We also evaluated for subjective word‐finding difficulties through retrospective chart review.

     Results

    Subjective word‐finding difficulty was reported by the majority (79%) of studied patients preoperatively. During intracranial recordings, interictal epileptiform discharges (IEDs) in the medial temporal lobe were associated with long‐term lexicosemantic memory impairments as indexed by auditory naming (p = .009), in addition to their established impact on short‐term verbal memory as indexed by free recall (p = .004). Interictal discharges involving the lateral temporal cortex and lateral frontal cortex were associated with delayed reaction time in the auditory naming task (p = .016 andp = .018), as well as phonological working memory impairments as indexed by repetition reaction time (p = .002). Effects of IEDs across anatomical regions were strongly dependent on their precise timing within the task.

     Significance

    IEDs appear to act through multiple cognitive mechanisms to form a convergent basis for the debilitating clinical word‐finding difficulty reported by patients with epilepsy. This was particularly notable for medial temporal spikes, which are quite common in adult focal epilepsy. In parallel with the treatment of seizures, the modulation of interictal discharges through emerging pharmacological means and neurostimulation approaches may be an opportunity to help address devastating memory and language impairments in epilepsy.

     
    more » « less
  • Citation Formats
  • MLA
  • APA
  • Chicago
  • BibTeX
  • Save / Share this Record
  • Send to Email