Epilepsy Surgery: Special Circumstances.

Epilepsy surgery has proven to be very effective in treating refractory focal epilepsies in children, producing seizure freedom or partial seizure control well beyond any other medical or dietary therapies. While surgery is mostly utilized in certain clinical phenotypes, either based on the location such as temporal lobe epilepsy, or based on the presence of known epileptogenic lesions such as focal cortical dysplasia, tumors or hemimegalencephaly, there is a growing body of evidence to support the role of surgery in other patients' cohorts that were classically not thought of as surgical candidates. These include patients with rare genetic disorders, electrical status epilepticus in sleep, status epilepticus and the very young patients. Furthermore, epilepsy surgery is not considered as a "last resort" as seizure and cognitive outcomes of surgery are considerably better when done earlier rather than later in relation to the time of onset of epilepsy and age of surgery especially in the context of known focal cortical dysplasia. This article examines the accumulating evidence of the utility of epilepsy surgery in these special circumstances.

Computing Functional Brain Connectivity in Neurological Disorders: Efficient Processing and Retrieval of Electrophysiological Signal Data.

Brain functional network connectivity is an important measure for characterizing changes in a variety of neurological disorders, for example Alzheimer's Disease, Parkinson Disease, and Epilepsy. Epilepsy is a serious neurological disorder affecting more than 50 million persons worldwide with severe impact on the quality of life of patients and their family members due to recurrent seizures. More than 30% of epilepsy patients are refractive to pharmacotherapy and are considered for resection to disrupt epilepsy seizure networks. However, 20-50% of these patients continue to have seizures after surgery. Therefore, there is a critical need to gain new insights into the characteristics of epilepsy seizure networks involving one of more brain regions and accurately delineate epileptogenic zone as a target for surgery. Although there is growing availability of large volume of high resolution stereotactic electroencephalogram (SEEG) data recorded from intracranial electrodes during presurgical evaluation of patients, there are significant informatics challenges associated with processing and analyzing this large signal dataset for characterizing epilepsy seizure networks. In this paper, we describe the development and application of a high-performance indexing structure for efficient retrieval of large-scale SEEG signal data to compute seizure network patterns corresponding to brain functional connectivity networks. This novel Neuro-Integrative Connectivity (NIC) search and retrieval method has been developed by extending the red-black tree index model together with an efficient lookup algorithm. We systematically perform a comparative evaluation of the proposed NIC index using de-identified SEEG data from a patient with temporal lobe epilepsy to retrieve segments of signal data corresponding to multiple seizure events and demonstrate the significant advantages of the NIC index as compared to existing methods. This new NIC Index enables faster computation of brain functional connectivity measures in epilepsy patients for large-scale network analysis and potentially provide new insights into the organization as well as evolution of seizure networks in epilepsy patients.

Incidence, Recurrence, and Risk Factors for Peri-ictal Central Apnea and Sudden Unexpected Death in Epilepsy.

Introduction: Peri-ictal breathing dysfunction was proposed as a potential mechanism for SUDEP. We examined the incidence and risk factors for both ictal (ICA) and post-convulsive central apnea (PCCA) and their relationship with potential seizure severity biomarkers (i. e., post-ictal generalized EEG suppression (PGES) and recurrence. Methods: Prospective, multi-center seizure monitoring study of autonomic, and breathing biomarkers of SUDEP in adults with intractable epilepsy and monitored seizures. Video EEG, thoraco-abdominal excursions, capillary oxygen saturation, and electrocardiography were analyzed. A subgroup analysis determined the incidences of recurrent ICA and PCCA in patients with ≥2 recorded seizures. We excluded status epilepticus and obscured/unavailable video. Central apnea (absence of thoracic-abdominal breathing movements) was defined as ≥1 missed breath, and ≥5 s. ICA referred to apnea preceding or occurring along with non-convulsive seizures (NCS) or apnea before generalized convulsive seizures (GCS). Results: We analyzed 558 seizures in 218 patients (130 female); 321 seizures were NCS and 237 were GCS. ICA occurred in 180/487 (36.9%) seizures in 83/192 (43.2%) patients, all with focal epilepsy. Sleep state was related to presence of ICA [RR 1.33, CI 95% (1.08-1.64), p = 0.008] whereas extratemporal epilepsy was related to lower incidence of ICA [RR 0.58, CI 95% (0.37-0.90), p = 0.015]. ICA recurred in 45/60 (75%) patients. PCCA occurred in 41/228 (18%) of GCS in 30/134 (22.4%) patients, regardless of epilepsy type. Female sex [RR 11.30, CI 95% (4.50-28.34), p < 0.001] and ICA duration [RR 1.14 CI 95% (1.05-1.25), p = 0.001] were related to PCCA presence, whereas absence of PGES was related to absence of PCCA [0.27, CI 95% (0.16-0.47), p < 0.001]. PCCA duration was longer in males [HR 1.84, CI 95% (1.06-3.19), p = 0.003]. In 9/17 (52.9%) patients, PCCA was recurrent. Conclusion: ICA incidence is almost twice the incidence of PCCA and is only seen in focal epilepsies, as opposed to PCCA, suggesting different pathophysiologies. ICA is likely to be a recurrent semiological phenomenon of cortical seizure discharge, whereas PCCA may be a reflection of brainstem dysfunction after GCS. Prolonged ICA or PCCA may, respectively, contribute to SUDEP, as evidenced by two cases we report. Further prospective cohort studies are needed to validate these hypotheses.

Postconvulsive central apnea as a biomarker for sudden unexpected death in epilepsy (SUDEP).

OBJECTIVE: To characterize peri-ictal apnea and postictal asystole in generalized convulsive seizures (GCS) of intractable epilepsy. METHODS: This was a prospective, multicenter epilepsy monitoring study of autonomic and breathing biomarkers of sudden unexpected death in epilepsy (SUDEP) in patients ≥18 years old with intractable epilepsy and monitored GCS. Video-EEG, thoracoabdominal excursions, nasal airflow, capillary oxygen saturation, and ECG were analyzed. RESULTS: We studied 148 GCS in 87 patients. Nineteen patients had generalized epilepsy; 65 had focal epilepsy; 1 had both; and the epileptogenic zone was unknown in 2. Ictal central apnea (ICA) preceded GCS in 49 of 121 (40.4%) seizures in 23 patients, all with focal epilepsy. Postconvulsive central apnea (PCCA) occurred in 31 of 140 (22.1%) seizures in 22 patients, with generalized, focal, or unknown epileptogenic zones. In 2 patients, PCCA occurred concurrently with asystole (near-SUDEP), with an incidence rate of 10.2 per 1,000 patient-years. One patient with PCCA died of probable SUDEP during follow-up, suggesting a SUDEP incidence rate 5.1 per 1,000 patient-years. No cases of laryngospasm were detected. Rhythmic muscle artifact synchronous with breathing was present in 75 of 147 seizures and related to stertorous breathing (odds ratio 3.856, 95% confidence interval 1.395-10.663, p = 0.009). CONCLUSIONS: PCCA occurred in both focal and generalized epilepsies, suggesting a different pathophysiology from ICA, which occurred only in focal epilepsy. PCCA was seen in 2 near-SUDEP cases and 1 probable SUDEP case, suggesting that this phenomenon may serve as a clinical biomarker of SUDEP. Larger studies are needed to validate this observation. Rhythmic postictal muscle artifact is suggestive of post-GCS breathing effort rather than a specific biomarker of laryngospasm.

Sleep-related hypermotor epilepsy and peri-ictal hypotension in a patient with syntaxin-1B mutation.

STX1B is a gene that encodes syntaxin-1B. STX1B mutations have recently been implicated in fever-associated epilepsy syndromes. However, these have not previously been reported in sleep-related hypermotor epilepsy. A 20-year-old man with a strong family history of epilepsy was investigated in our epilepsy monitoring unit due to uncontrolled epilepsy, compatible with sleep-related hypermotor epilepsy. Electroclinical and polygraphic physiological recordings revealed left frontal epileptiform discharges and prominent peri-ictal hypotension. Normal MRI using an epilepsy protocol prompted a search for a genetic epilepsy, which revealed a likely pathogenic mutation in the STX1B gene. The patient remained seizure-free after treatment optimization with carbamazepine. This case suggests that a sleep-related hypermotor epilepsy phenotype can be associated with syntaxin-1B gene mutation, and testing for this gene should be considered in such patients. Furthermore, it may also be concluded that autonomic dysfunction, characterized by peri-ictal hypotension, can also occur in this discorder. [Published with video sequences on www.epilepticdisorders.com].

Serum serotonin levels in patients with epileptic seizures.

Profound cardiovascular and/or respiratory dysfunction is part of the terminal cascade in sudden unexpected death in epilepsy (SUDEP). Central control of ventilation is mediated by brainstem rhythm generators, which are influenced by a variety of inputs, many of which use the modulatory neurotransmitter serotonin to mediate important inputs for breathing. The aim of this study was to investigate epileptic seizure-induced changes in serum serotonin levels and whether there are potential implications for SUDEP. Forty-one epileptic patients were pooled into 2 groups based on seizure type as (1) generalized tonic-clonic seizures (GTCS) of genetic generalized epilepsy and focal to bilateral tonic-clonic seizures (FBTCS; n = 19) and (2) focal seizures (n = 26) based on clinical signs using surface video-electroencephalography. Postictal serotonin levels were statistically significantly higher after GTCS and FBTCS compared to interictal levels (P = .002) but not focal seizures (P = .941). The change in serotonin (postictal-interictal) was inversely associated with a shorter duration of tonic phase of generalized seizures. The interictal serotonin level was inversely associated with a shorter period of postictal generalized electroencephalographic suppression. These data suggest that peripheral serum serotonin levels may play a role in seizure features and earlier postseizure recovery; these findings merit further study.

Automated Detection of Postictal Generalized EEG Suppression.

Although there is no strict consensus, some studies have reported that Postictal generalized EEG suppression (PGES) is a potential electroencephalographic (EEG) biomarker for risk of sudden unexpected death in epilepsy (SUDEP). PGES is an epoch of EEG inactivity after a seizure, and the detection of PGES in clinical data is extremely difficult due to artifacts from breathing, movement and muscle activity that can adversely affect the quality of the recorded EEG data. Even clinical experts visually interpreting the EEG will have diverse opinions on the start and end of PGES for a given patient. The development of an automated EEG suppression detection tool can assist clinical personnel in the review and annotation of seizure files, and can also provide a standard for quantifying PGES in large patient cohorts, possibly leading to further clarification of the role of PGES as a biomarker of SUDEP risk. In this paper, we develop an automated system that can detect the start and end of PGES using frequency domain features in combination with boosting classification algorithms. The average power for different frequency ranges of EEG signals are extracted from the prefiltered recorded signal using the fast fourier transform and are used as the feature set for the classification algorithm. The underlying classifiers for the boosting algorithm are linear classifiers using a logistic regression model. The tool is developed using 12 seizures annotated by an expert then tested and evaluated on another 20 seizures that were annotated by 11 experts.

The incidence and significance of periictal apnea in epileptic seizures.

OBJECTIVE: The aim of this study was to investigate periictal central apnea as a seizure semiological feature, its localizing value, and possible relationship with sudden unexpected death in epilepsy (SUDEP) pathomechanisms. METHODS: We prospectively studied polygraphic physiological responses, including inductance plethysmography, peripheral capillary oxygen saturation (SpO2 ), electrocardiography, and video electroencephalography (VEEG) in 473 patients in a multicenter study of SUDEP. Seizures were classified according to the International League Against Epilepsy (ILAE) 2017 seizure classification based on the most prominent clinical signs during VEEG. The putative epileptogenic zone was defined based on clinical history, seizure semiology, neuroimaging, and EEG. RESULTS: Complete datasets were available in 126 patients in 312 seizures. Ictal central apnea (ICA) occurred exclusively in focal epilepsy (51/109 patients [47%] and 103/312 seizures [36.5%]) (P < .001). ICA was the only clinical manifestation in 16/103 (16.5%) seizures, and preceded EEG seizure onset by 8 ± 4.9 s, in 56/103 (54.3%) seizures. ICA ≥60 s was associated with severe hypoxemia (SpO2 <75%). Focal onset impaired awareness (FOIA) motor onset with automatisms and FOA nonmotor onset semiologies were associated with ICA presence (P < .001), ICA duration (P = .002), and moderate/severe hypoxemia (P = .04). Temporal lobe epilepsy was highly associated with ICA in comparison to extratemporal epilepsy (P = .001) and frontal lobe epilepsy (P = .001). Isolated postictal central apnea was not seen; in 3/103 seizures (3%), ICA persisted into the postictal period. SIGNIFICANCE: ICA is a frequent, self-limiting semiological feature of focal epilepsy, often starting before surface EEG onset, and may be the only clinical manifestation of focal seizures. However, prolonged ICA (≥60 s) is associated with severe hypoxemia and may be a potential SUDEP biomarker. ICA is more frequently seen in temporal than extratemporal seizures, and in typical temporal seizure semiologies. ICA rarely persists after seizure end. ICA agnosia is typical, and thus it may remain unrecognized without polygraphic measurements that include breathing parameters.

Cortical Structures Associated With Human Blood Pressure Control.

Importance: A better understanding of the role of cortical structures in blood pressure control may help us understand cardiovascular collapse that may lead to sudden unexpected death in epilepsy (SUDEP). Objective: To identify cortical control sites for human blood pressure regulation. Design, Setting, and Participants: Patients with intractable epilepsy undergoing intracranial electrode implantation as a prelude to epilepsy surgery in the Epilepsy Monitoring Unit at University Hospitals Cleveland Medical Center were potential candidates for this study. Inclusion criteria were patients 18 years or older who had electrodes implanted in one or more of the regions of interest and in whom deep brain electrical stimulation was indicated for mapping of ictal onset or eloquent cortex as a part of the presurgical evaluation. Twelve consecutive patients were included in this prospective case series from June 1, 2015, to February 28, 2017. Main Outcomes and Measures: Changes in continuous, noninvasive, beat-by-beat blood pressure parameter responses from amygdala, hippocampal, insular, orbitofrontal, temporal, cingulate, and subcallosal stimulation. Electrocardiogram, arterial oxygen saturation, end-tidal carbon dioxide, nasal airflow, and abdominal and thoracic plethysmography were monitored. Results: Among 12 patients (7 female; mean [SD] age, 44.25 [12.55] years), 9 electrodes (7 left and 2 right) all in Brodmann area 25 (subcallosal neocortex) in 4 patients produced striking systolic hypotensive changes. Well-maintained diastolic arterial blood pressure and narrowed pulse pressure indicated stimulation-induced reduction in sympathetic drive and consequent probable reduction in cardiac output rather than bradycardia or peripheral vasodilation-induced hypotension. Frequency-domain analysis of heart rate and blood pressure variability showed a mixed picture. No other stimulated structure produced significant blood pressure changes. Conclusions and Relevance: These findings suggest that Brodmann area 25 has a role in lowering systolic blood pressure in humans. It is a potential symptomatogenic zone for peri-ictal hypotension in patients with epilepsy.

Amygdala and hippocampus are symptomatogenic zones for central apneic seizures.

OBJECTIVE: To identify limbic sites of respiratory control in the human brain, and by extension, the symptomatogenic zone for central apnea. METHODS: We used direct stimulation of anatomically, precisely placed stereotactic EEG electrodes to analyze breathing responses. We prospectively studied 3 patients who were explored with stereotactically implanted depth electrodes. The amygdala and hippocampus, as well as extralimbic sites (orbitofrontal, temporal tip, and temporal neocortex), were investigated. RESULTS: Individual stimulation of the amygdala and hippocampal head consistently elicited central apnea in the expiratory phase, as did exquisitely focal hippocampal seizures. CONCLUSIONS: These findings confirm that hippocampus and amygdala are limbic breathing control sites in humans, as well as the symptomatogenic zone for central apneic seizures.

NeuroPigPen: A Scalable Toolkit for Processing Electrophysiological Signal Data in Neuroscience Applications Using Apache Pig.

The recent advances in neurological imaging and sensing technologies have led to rapid increase in the volume, rate of data generation, and variety of neuroscience data. This "neuroscience Big data" represents a significant opportunity for the biomedical research community to design experiments using data with greater timescale, large number of attributes, and statistically significant data size. The results from these new data-driven research techniques can advance our understanding of complex neurological disorders, help model long-term effects of brain injuries, and provide new insights into dynamics of brain networks. However, many existing neuroinformatics data processing and analysis tools were not built to manage large volume of data, which makes it difficult for researchers to effectively leverage this available data to advance their research. We introduce a new toolkit called NeuroPigPen that was developed using Apache Hadoop and Pig data flow language to address the challenges posed by large-scale electrophysiological signal data. NeuroPigPen is a modular toolkit that can process large volumes of electrophysiological signal data, such as Electroencephalogram (EEG), Electrocardiogram (ECG), and blood oxygen levels (SpO2), using a new distributed storage model called Cloudwave Signal Format (CSF) that supports easy partitioning and storage of signal data on commodity hardware. NeuroPigPen was developed with three design principles: (a) Scalability-the ability to efficiently process increasing volumes of data; (b) Adaptability-the toolkit can be deployed across different computing configurations; and (c) Ease of programming-the toolkit can be easily used to compose multi-step data processing pipelines using high-level programming constructs. The NeuroPigPen toolkit was evaluated using 750 GB of electrophysiological signal data over a variety of Hadoop cluster configurations ranging from 3 to 30 Data nodes. The evaluation results demonstrate that the toolkit is highly scalable and adaptable, which makes it suitable for use in neuroscience applications as a scalable data processing toolkit. As part of the ongoing extension of NeuroPigPen, we are developing new modules to support statistical functions to analyze signal data for brain connectivity research. In addition, the toolkit is being extended to allow integration with scientific workflow systems. NeuroPigPen is released under BSD license at: https://sites.google.com/a/case.edu/neuropigpen/.

Nonseizure SUDEP: Sudden unexpected death in epilepsy without preceding epileptic seizures.

OBJECTIVE: To describe the phenomenology of monitored sudden unexpected death in epilepsy (SUDEP) occurring in the interictal period where death occurs without a seizure preceding it. METHODS: We report a case series of monitored definite and probable SUDEP where no electroclinical evidence of underlying seizures was found preceding death. RESULTS: Three patients (two definite and one probable) had SUDEP. They had a typical high SUDEP risk profile with longstanding intractable epilepsy and frequent generalized tonic-clonic seizures (GTCS). All patients had varying patterns of respiratory and bradyarrhythmic cardiac dysfunction with profound electroencephalography (EEG) suppression. In two patients, patterns of cardiorespiratory failure were similar to those seen in some patients in the Mortality in Epilepsy Monitoring Units Study (MORTEMUS). SIGNIFICANCE: SUDEP almost always occur postictally, after GTCS and less commonly after a partial seizure. Monitored SUDEP or near-SUDEP cases without a seizure have not yet been reported in literature. When nonmonitored SUDEP occurs in an ambulatory setting without an overt seizure, the absence of EEG information prevents the exclusion of a subtle seizure. These cases confirm the existence of nonseizure SUDEP; such deaths may not be prevented by seizure detection-based devices. SUDEP risk in patients with epilepsy may constitute a spectrum of susceptibility wherein some are relatively immune, death occurs in others with frequent GTCS with one episode of seizure ultimately proving fatal, while in others still, death may occur even in the absence of a seizure. We emphasize the heterogeneity of SUDEP phenomena.

Left-insular damage, autonomic instability, and sudden unexpected death in epilepsy.

We analyzed the only two sudden unexpected death in epilepsy (SUDEP) cases from 320 prospectively recruited patients in the three-year Prevention and Risk Identification of SUDEP Mortality (PRISM) project. Both patients had surgically refractory epilepsy, evidence of left insular damage following previous temporal/temporo-insular resections, and progressive changes in heart rate variability (HRV) in monitored evaluations prior to death. Insular damage is known to cause autonomic dysfunction and increased mortality in acute stroke. This report suggests a possible role for the insula in the pathogenesis of SUDEP. The presence of intrinsic insular lesions or acquired insular damage in patients with refractory epilepsy may be an additional risk factor for SUDEP.

Homotopic reciprocal functional connectivity between anterior human insulae.

The aim of this study was to investigate functional connectivity between right and left insulae in the human brain. We studied a patient with implanted depth electrodes for epilepsy surgery evaluation with stereotactically placed symmetric depth electrodes in both insulae. Bipolar 1 Hz electrical stimulation of the right and left posterior short gyri in the anterior insula evoked responses in the contralateral insular structures. These responses showed a latency of 8-24 ms. This report demonstrates for the first time bi-directional homotopic and heterotopic functional connectivity between right and left anterior insulae. The short latency of the evoked responses suggests mono- or oligo-synaptic connections, most likely via the corpus callosum.

NHash: Randomized N-Gram Hashing for Distributed Generation of Validatable Unique Study Identifiers in Multicenter Research.

BACKGROUND: A unique study identifier serves as a key for linking research data about a study subject without revealing protected health information in the identifier. While sufficient for single-site and limited-scale studies, the use of common unique study identifiers has several drawbacks for large multicenter studies, where thousands of research participants may be recruited from multiple sites. An important property of study identifiers is error tolerance (or validatable), in that inadvertent editing mistakes during their transmission and use will most likely result in invalid study identifiers. OBJECTIVE: This paper introduces a novel method called "Randomized N-gram Hashing (NHash)," for generating unique study identifiers in a distributed and validatable fashion, in multicenter research. NHash has a unique set of properties: (1) it is a pseudonym serving the purpose of linking research data about a study participant for research purposes; (2) it can be generated automatically in a completely distributed fashion with virtually no risk for identifier collision; (3) it incorporates a set of cryptographic hash functions based on N-grams, with a combination of additional encryption techniques such as a shift cipher; (d) it is validatable (error tolerant) in the sense that inadvertent edit errors will mostly result in invalid identifiers. METHODS: NHash consists of 2 phases. First, an intermediate string using randomized N-gram hashing is generated. This string consists of a collection of N-gram hashes f1, f2, ..., fk. The input for each function fi has 3 components: a random number r, an integer n, and input data m. The result, fi(r, n, m), is an n-gram of m with a starting position s, which is computed as (r mod |m|), where |m| represents the length of m. The output for Step 1 is the concatenation of the sequence f1(r1, n1, m1), f2(r2, n2, m2), ..., fk(rk, nk, mk). In the second phase, the intermediate string generated in Phase 1 is encrypted using techniques such as shift cipher. The result of the encryption, concatenated with the random number r, is the final NHash study identifier. RESULTS: We performed experiments using a large synthesized dataset comparing NHash with random strings, and demonstrated neglegible probability for collision. We implemented NHash for the Center for SUDEP Research (CSR), a National Institute for Neurological Disorders and Stroke-funded Center Without Walls for Collaborative Research in the Epilepsies. This multicenter collaboration involves 14 institutions across the United States and Europe, bringing together extensive and diverse expertise to understand sudden unexpected death in epilepsy patients (SUDEP). CONCLUSIONS: The CSR Data Repository has successfully used NHash to link deidentified multimodal clinical data collected in participating CSR institutions, meeting all desired objectives of NHash.

Lesion-negative anterior cingulate epilepsy.

MRI-negative anterior cingulate epilepsy is a rare entity. Herein, we describe a case of MRI and functional imaging-negative intractable frontal lobe epilepsy in which, initially, secondary bilateral synchrony of surface and intracranial EEG and non-lateralizing semiology rendered identification of the epileptogenic zone difficult. A staged bilateral stereotactic EEG exploration revealed a very focal, putative ictal onset zone in the right anterior cingulate gyrus, as evidenced by interictal and ictal high-frequency oscillations (at 250Hz) and induction of seizures from the same electrode contacts by 50-Hz low-intensity cortical stimulation. This was subsequently confirmed by ILAE class 1 outcome following resection of the ictal onset and irritative zones. Histopathological examination revealed focal cortical dysplasia type 1b (ILAE Commission, 2011) as the cause of epilepsy. The importance of anatomo-electro-clinical correlation is illustrated in this case in which semiological and electrophysiological features pointed to the anatomical localization of a challenging, MRI-negative epilepsy.

A scalable neuroinformatics data flow for electrophysiological signals using MapReduce.

Data-driven neuroscience research is providing new insights in progression of neurological disorders and supporting the development of improved treatment approaches. However, the volume, velocity, and variety of neuroscience data generated from sophisticated recording instruments and acquisition methods have exacerbated the limited scalability of existing neuroinformatics tools. This makes it difficult for neuroscience researchers to effectively leverage the growing multi-modal neuroscience data to advance research in serious neurological disorders, such as epilepsy. We describe the development of the Cloudwave data flow that uses new data partitioning techniques to store and analyze electrophysiological signal in distributed computing infrastructure. The Cloudwave data flow uses MapReduce parallel programming algorithm to implement an integrated signal data processing pipeline that scales with large volume of data generated at high velocity. Using an epilepsy domain ontology together with an epilepsy focused extensible data representation format called Cloudwave Signal Format (CSF), the data flow addresses the challenge of data heterogeneity and is interoperable with existing neuroinformatics data representation formats, such as HDF5. The scalability of the Cloudwave data flow is evaluated using a 30-node cluster installed with the open source Hadoop software stack. The results demonstrate that the Cloudwave data flow can process increasing volume of signal data by leveraging Hadoop Data Nodes to reduce the total data processing time. The Cloudwave data flow is a template for developing highly scalable neuroscience data processing pipelines using MapReduce algorithms to support a variety of user applications.

Functional connectivity between right and left mesial temporal structures.

The aim of this study is to investigate functional connectivity between right and left mesial temporal structures using cerebrocerebral evoked potentials. We studied seven patients with drug-resistant focal epilepsy who were explored with stereotactically implanted depth electrodes in bilateral hippocampi. In all patients cerebrocerebral evoked potentials evoked by stimulation of the fornix were evaluated as part of a research project assessing fornix stimulation for control of hippocampal seizures. Stimulation of the fornix elicited responses in the ipsilateral hippocampus in all patients with a mean latency of 4.6 ms (range 2-7 ms). Two patients (29 %) also had contralateral hippocampus responses with a mean latency of 7.5 ms (range 5-12 ms) and without involvement of the contralateral temporal neocortex or amygdala. This study confirms the existence of connections between bilateral mesial temporal structures in some patients and explains seizure discharge spreading between homotopic mesial temporal structures without neocortical involvement.