Publications by authors named "Michal T Kucewicz"

22 Publications

  • Page 1 of 1

Contribution of Ictal Source Imaging for Localizing Seizure Onset Zone in Patients With Focal Epilepsy.

Neurology 2021 01 23;96(3):e366-e375. Epub 2020 Oct 23.

From the Department of Biomedical Engineering (S.Y., A.S., B.H.), Carnegie Mellon University, Pittsburgh, PA; Department of Biomedical Engineering (L.Y., Y.L.), University of Minnesota, Minneapolis; Mayo Clinic (M.T.K., B.B., C.N., G.A.W.), Rochester, MN.

Objective: To determine whether seizure onset zone (SOZ) can be localized accurately prior to surgical planning in patients with focal epilepsy, we performed noninvasive EEG recordings and source localization analyses on 39 patients.

Methods: In 39 patients with focal epilepsy, we recorded and extracted 138 seizures and 1,325 interictal epileptic discharges using high-density EEG. We investigated a novel approach for directly imaging sources of seizures and interictal spikes from high-density EEG recordings, and rigorously validated it for noninvasive localization of SOZ determined from intracranial EEG findings and surgical resection volume. Conventional source imaging analyses were also performed for comparison.

Results: Ictal source imaging showed a concordance rate of 95% when compared to intracranial EEG or resection results. The average distance from estimation to seizure onset (intracranial) electrodes is 1.35 cm in patients with concordant results, and 0.74 cm to surgical resection boundary in patients with successful surgery. About 41% of the patients were found to have multiple types of interictal activities; coincidentally, a lower concordance rate and a significantly worse performance in localizing SOZ were observed in these patients.

Conclusion: Noninvasive ictal source imaging with high-density EEG recording can provide highly concordant results with clinical decisions obtained by invasive monitoring or confirmed by resective surgery. By means of direct seizure imaging using high-density scalp EEG recordings, the added value of ictal source imaging is particularly high in patients with complex interictal activity patterns, who may represent the most challenging cases with poor prognosis.
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http://dx.doi.org/10.1212/WNL.0000000000011109DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7884986PMC
January 2021

Unsupervised machine-learning classification of electrophysiologically active electrodes during human cognitive task performance.

Sci Rep 2019 11 22;9(1):17390. Epub 2019 Nov 22.

Mayo Clinic, Dept. of Neurology, Rochester, MN, USA.

Identification of active electrodes that record task-relevant neurophysiological activity is needed for clinical and industrial applications as well as for investigating brain functions. We developed an unsupervised, fully automated approach to classify active electrodes showing event-related intracranial EEG (iEEG) responses from 115 patients performing a free recall verbal memory task. Our approach employed new interpretable metrics that quantify spectral characteristics of the normalized iEEG signal based on power-in-band and synchrony measures. Unsupervised clustering of the metrics identified distinct sets of active electrodes across different subjects. In the total population of 11,869 electrodes, our method achieved 97% sensitivity and 92.9% specificity with the most efficient metric. We validated our results with anatomical localization revealing significantly greater distribution of active electrodes in brain regions that support verbal memory processing. We propose our machine-learning framework for objective and efficient classification and interpretation of electrophysiological signals of brain activities supporting memory and cognition.
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http://dx.doi.org/10.1038/s41598-019-53925-5DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6874617PMC
November 2019

Author Correction: Pupil size reflects successful encoding and recall of memory in humans.

Sci Rep 2019 Nov 6;9(1):16404. Epub 2019 Nov 6.

Department of Neurology, Mayo Clinic, Rochester, MN, USA.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.
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http://dx.doi.org/10.1038/s41598-019-53308-wDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6834848PMC
November 2019

Human Verbal Memory Encoding Is Hierarchically Distributed in a Continuous Processing Stream.

eNeuro 2019 Jan-Feb;6(1). Epub 2019 Mar 4.

Department of Neurology, Mayo Clinic, Rochester, MN 55905.

Processing of memory is supported by coordinated activity in a network of sensory, association, and motor brain regions. It remains a major challenge to determine where memory is encoded for later retrieval. Here, we used direct intracranial brain recordings from epilepsy patients performing free recall tasks to determine the temporal pattern and anatomical distribution of verbal memory encoding across the entire human cortex. High γ frequency activity (65-115 Hz) showed consistent power responses during encoding of subsequently recalled and forgotten words on a subset of electrodes localized in 16 distinct cortical areas activated in the tasks. More of the high γ power during word encoding, and less power before and after the word presentation, was characteristic of successful recall and observed across multiple brain regions. Latencies of the induced power changes and this subsequent memory effect (SME) between the recalled and forgotten words followed an anatomical sequence from visual to prefrontal cortical areas. Finally, the magnitude of the memory effect was unexpectedly found to be the largest in selected brain regions both at the top and at the bottom of the processing stream. These included the language processing areas of the prefrontal cortex and the early visual areas at the junction of the occipital and temporal lobes. Our results provide evidence for distributed encoding of verbal memory organized along a hierarchical posterior-to-anterior processing stream.
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http://dx.doi.org/10.1523/ENEURO.0214-18.2018DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6402539PMC
May 2019

Human Computer Interface for Tracking Eye Movements Improves Assessment and Diagnosis of Patients With Acquired Brain Injuries.

Front Neurol 2019 23;10. Epub 2019 Jan 23.

Multimedia Systems Department, Faculty of Electronics, Telecommunication and Informatics, Gdansk University of Technology, Gdańsk, Poland.

One of the first clinical signs differentiating the minimally conscious state from the vegetative state is the presence of smooth pursuit eye movements occurring in direct response to moving salient stimuli. Glasgow Coma Scale (GCS) is one of the most commonly used diagnostic tools for acute phase assessment of the level of consciousness, together with a neurological examination. These classic measures are limited to qualitative neurological examination without more quantitative measures provided from e.g., tasks with tracking position of the gaze. Among this and other limitations, it is prone to a relatively high rate of misdiagnosis. Here, we developed an interface for gaze tracking to enhance the assessment of consciousness in 10 patients with acquired brain injuries. According to the acute phase GCS assessment, nine of them were considered unaware and below the minimally conscious state. Chronic neurological examination confirmed six of them below the minimally conscious state. Our new Human Computer Interface (HCI) revealed that six patients were conscious enough to complete at least one of the gaze tracking tasks. Among these six patients, one was originally diagnosed as remaining in a vegetative state and one in coma. The patient diagnosed as remaining in a chronic vegetative state scored six GCS points acutely. Following assessment with our HCI the patient was re-diagnosed with a possible locked-in syndrome. Our HCI method provides a new complementary tool for clinical assessment of patients suffering from disorders of consciousness.
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http://dx.doi.org/10.3389/fneur.2019.00006DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6351480PMC
January 2019

Pupil size reflects successful encoding and recall of memory in humans.

Sci Rep 2018 03 21;8(1):4949. Epub 2018 Mar 21.

Department of Neurology, Mayo Clinic, Rochester, MN, USA.

Pupil responses are known to indicate brain processes involved in perception, attention and decision-making. They can provide an accessible biomarker of human memory performance and cognitive states in general. Here we investigated changes in the pupil size during encoding and recall of word lists. Consistent patterns in the pupil response were found across and within distinct phases of the free recall task. The pupil was most constricted in the initial fixation phase and was gradually more dilated through the subsequent encoding, distractor and recall phases of the task, as the word items were maintained in memory. Within the final recall phase, retrieving memory for individual words was associated with pupil dilation in absence of visual stimulation. Words that were successfully recalled showed significant differences in pupil response during their encoding compared to those that were forgotten - the pupil was more constricted before and more dilated after the onset of word presentation. Our results suggest pupil size as a potential biomarker for probing and modulation of memory processing.
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http://dx.doi.org/10.1038/s41598-018-23197-6DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5862978PMC
March 2018

Closed-loop stimulation of temporal cortex rescues functional networks and improves memory.

Nat Commun 2018 02 6;9(1):365. Epub 2018 Feb 6.

Department of Psychology, University of Pennsylvania, 433 South University Avenue, Philadelphia, PA, 19104, USA.

Memory failures are frustrating and often the result of ineffective encoding. One approach to improving memory outcomes is through direct modulation of brain activity with electrical stimulation. Previous efforts, however, have reported inconsistent effects when using open-loop stimulation and often target the hippocampus and medial temporal lobes. Here we use a closed-loop system to monitor and decode neural activity from direct brain recordings in humans. We apply targeted stimulation to lateral temporal cortex and report that this stimulation rescues periods of poor memory encoding. This system also improves later recall, revealing that the lateral temporal cortex is a reliable target for memory enhancement. Taken together, our results suggest that such systems may provide a therapeutic approach for treating memory dysfunction.
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http://dx.doi.org/10.1038/s41467-017-02753-0DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5802791PMC
February 2018

Electrical Stimulation Modulates High γ Activity and Human Memory Performance.

eNeuro 2018 Jan-Feb;5(1). Epub 2018 Feb 2.

Department of Neurology, Mayo Clinic, Rochester, MN 55905.

Direct electrical stimulation of the brain has emerged as a powerful treatment for multiple neurological diseases, and as a potential technique to enhance human cognition. Despite its application in a range of brain disorders, it remains unclear how stimulation of discrete brain areas affects memory performance and the underlying electrophysiological activities. Here, we investigated the effect of direct electrical stimulation in four brain regions known to support declarative memory: hippocampus (HP), parahippocampal region (PH) neocortex, prefrontal cortex (PF), and lateral temporal cortex (TC). Intracranial EEG recordings with stimulation were collected from 22 patients during performance of verbal memory tasks. We found that high γ (62-118 Hz) activity induced by word presentation was modulated by electrical stimulation. This modulatory effect was greatest for trials with "poor" memory encoding. The high γ modulation correlated with the behavioral effect of stimulation in a given brain region: it was negative, i.e., the induced high γ activity was decreased, in the regions where stimulation decreased memory performance, and positive in the lateral TC where memory enhancement was observed. Our results suggest that the effect of electrical stimulation on high γ activity induced by word presentation may be a useful biomarker for mapping memory networks and guiding therapeutic brain stimulation.
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http://dx.doi.org/10.1523/ENEURO.0369-17.2018DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5797477PMC
January 2019

Evidence for verbal memory enhancement with electrical brain stimulation in the lateral temporal cortex.

Brain 2018 04;141(4):971-978

Mayo Clinic, Department of Neurology, Rochester MN, USA.

Direct electrical stimulation of the human brain can elicit sensory and motor perceptions as well as recall of memories. Stimulating higher order association areas of the lateral temporal cortex in particular was reported to activate visual and auditory memory representations of past experiences (Penfield and Perot, 1963). We hypothesized that this effect could be used to modulate memory processing. Recent attempts at memory enhancement in the human brain have been focused on the hippocampus and other mesial temporal lobe structures, with a few reports of memory improvement in small studies of individual brain regions. Here, we investigated the effect of stimulation in four brain regions known to support declarative memory: hippocampus, parahippocampal neocortex, prefrontal cortex and temporal cortex. Intracranial electrode recordings with stimulation were used to assess verbal memory performance in a group of 22 patients (nine males). We show enhanced performance with electrical stimulation in the lateral temporal cortex (paired t-test, P = 0.0067), but not in the other brain regions tested. This selective enhancement was observed both on the group level, and for two of the four individual subjects stimulated in the temporal cortex. This study shows that electrical stimulation in specific brain areas can enhance verbal memory performance in humans.awx373media15704855796001.
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http://dx.doi.org/10.1093/brain/awx373DOI Listing
April 2018

Direct Brain Stimulation Modulates Encoding States and Memory Performance in Humans.

Curr Biol 2017 May 20;27(9):1251-1258. Epub 2017 Apr 20.

Department of Psychology, University of Pennsylvania, Philadelphia, PA 19104, USA. Electronic address:

People often forget information because they fail to effectively encode it. Here, we test the hypothesis that targeted electrical stimulation can modulate neural encoding states and subsequent memory outcomes. Using recordings from neurosurgical epilepsy patients with intracranially implanted electrodes, we trained multivariate classifiers to discriminate spectral activity during learning that predicted remembering from forgetting, then decoded neural activity in later sessions in which we applied stimulation during learning. Stimulation increased encoding-state estimates and recall if delivered when the classifier indicated low encoding efficiency but had the reverse effect if stimulation was delivered when the classifier indicated high encoding efficiency. Higher encoding-state estimates from stimulation were associated with greater evidence of neural activity linked to contextual memory encoding. In identifying the conditions under which stimulation modulates memory, the data suggest strategies for therapeutically treating memory dysfunction.
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http://dx.doi.org/10.1016/j.cub.2017.03.028DOI Listing
May 2017

Dissecting gamma frequency activity during human memory processing.

Brain 2017 May;140(5):1337-1350

Mayo Clinic, Department of Neurology, Mayo Systems Electrophysiology Laboratory (MSEL), Rochester MN, USA.

Gamma frequency activity (30-150 Hz) is induced in cognitive tasks and is thought to reflect underlying neural processes. Gamma frequency activity can be recorded directly from the human brain using intracranial electrodes implanted in patients undergoing treatment for drug-resistant epilepsy. Previous studies have independently explored narrowband oscillations in the local field potential and broadband power increases. It is not clear, however, which processes contribute to human brain gamma frequency activity, or their dynamics and roles during memory processing. Here a large dataset of intracranial recordings obtained during encoding of words from 101 patients was used to detect, characterize and compare induced gamma frequency activity events. Individual bursts of gamma frequency activity were isolated in the time-frequency domain to determine their spectral features, including peak frequency, amplitude, frequency span, and duration. We found two distinct types of gamma frequency activity events that showed either narrowband or broadband frequency spans revealing characteristic spectral properties. Narrowband events, the predominant type, were induced by word presentations following an initial induction of broadband events, which were temporally separated and selectively correlated with evoked response potentials, suggesting that they reflect different neural activities and play different roles during memory encoding. The two gamma frequency activity types were differentially modulated during encoding of subsequently recalled and forgotten words. In conclusion, we found evidence for two distinct activity types induced in the gamma frequency range during cognitive processing. Separating these two gamma frequency activity components contributes to the current understanding of electrophysiological biomarkers, and may prove useful for emerging neurotechnologies targeting, mapping and modulating distinct neurophysiological processes in normal and epileptogenic brain.
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http://dx.doi.org/10.1093/brain/awx043DOI Listing
May 2017

Behavioral state classification in epileptic brain using intracranial electrophysiology.

J Neural Eng 2017 04 4;14(2):026001. Epub 2017 Jan 4.

Department of Neurology, Mayo Systems Electrophysiology Laboratory, Mayo Clinic, 200 First St SW, Rochester, MN 55905, USA. Czech Institute of Informatics, Robotics and Cybernetics, Czech Technical University in Prague, Zikova street 1903/4, 166 36 Prague 6, Czech Republic. Department of Physiology and Biomedical Engineering, Mayo Clinic, 200 First St SW, Rochester, MN 55905, USA.

Objective: Automated behavioral state classification can benefit next generation implantable epilepsy devices. In this study we explored the feasibility of automated awake (AW) and slow wave sleep (SWS) classification using wide bandwidth intracranial EEG (iEEG) in patients undergoing evaluation for epilepsy surgery.

Approach: Data from seven patients (age [Formula: see text], 4 women) who underwent intracranial depth electrode implantation for iEEG monitoring were included. Spectral power features (0.1-600 Hz) spanning several frequency bands from a single electrode were used to train and test a support vector machine classifier.

Main Results: Classification accuracy of 97.8  ±  0.3% (normal tissue) and 89.4  ±  0.8% (epileptic tissue) across seven subjects using multiple spectral power features from a single electrode was achieved. Spectral power features from electrodes placed in normal temporal neocortex were found to be more useful (accuracy 90.8  ±  0.8%) for sleep-wake state classification than electrodes located in normal hippocampus (87.1  ±  1.6%). Spectral power in high frequency band features (Ripple (80-250 Hz), Fast Ripple (250-600 Hz)) showed comparable performance for AW and SWS classification as the best performing Berger bands (Alpha, Beta, low Gamma) with accuracy  ⩾90% using a single electrode contact and single spectral feature.

Significance: Automated classification of wake and SWS should prove useful for future implantable epilepsy devices with limited computational power, memory, and number of electrodes. Applications include quantifying patient sleep patterns and behavioral state dependent detection, prediction, and electrical stimulation therapies.
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http://dx.doi.org/10.1088/1741-2552/aa5688DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5460075PMC
April 2017

Reactivation of seizure-related changes to interictal spike shape and synchrony during postseizure sleep in patients.

Epilepsia 2017 01 18;58(1):94-104. Epub 2016 Nov 18.

Department of Neurology, Mayo Clinic, Rochester, Minnesota, U.S.A.

Objective: Local field potentials (LFPs) arise from synchronous activation of millions of neurons, producing seemingly consistent waveform shapes and relative synchrony across electrodes. Interictal spikes (IISs) are LFPs associated with epilepsy that are commonly used to guide surgical resection. Recently, changes in neuronal firing patterns observed in the minutes preceding seizure onset were found to be reactivated during postseizure sleep, a process called seizure-related consolidation (SRC), due to similarities with learning-related consolidation. Because IISs arise from summed neural activity, we hypothesized that changes in IIS shape and relative synchrony would be observed in the minutes preceding seizure onset and would be reactivated preferentially during postseizure slow-wave sleep (SWS).

Methods: Scalp and intracranial recordings were obtained continuously across multiple days from clinical macroelectrodes implanted in patients undergoing treatment for intractable epilepsy. Data from scalp electrodes were used to stage sleep. Data from intracranial electrodes were used to detect IISs using a previously established algorithm. Partial correlations were computed for sleep and wake periods before and after seizures as a function of correlations observed in the minutes preceding seizures. Magnetic resonance imaging (MRI) and computed tomography (CT) scans were co-registered with electroencephalography (EEG) to determine the location of the seizure-onset zone (SOZ).

Results: Changes in IIS shape and relative synchrony were observed on a subset of macroelectrodes minutes before seizure onset, and these changes were reactivated preferentially during postseizure SWS. Changes in synchrony were greatest for pairs of electrodes where at least one electrode was located in the SOZ.

Significance: These data suggest preseizure changes in neural activity and their subsequent reactivation occur across a broad spatiotemporal scale: from single neurons to LFPs, both within and outside the SOZ. The preferential reactivation of seizure-related changes in IISs during postseizure SWS adds to a growing body of literature suggesting that pathologic neural processes may utilize physiologic mechanisms of synaptic plasticity.
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http://dx.doi.org/10.1111/epi.13614DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5358812PMC
January 2017

Interictal high-frequency oscillations in focal human epilepsy.

Curr Opin Neurol 2016 Apr;29(2):175-81

aMayo Systems Electrophysiology Laboratory, Department of NeurologybDepartment of Biomedical Engineering and Physiology, Mayo Clinic, Rochester, Minnesota, USAcInternational Clinical Research Center, St. Anne's University Hospital, Brno, Czech Republic.

Purpose Of Review: Localization of focal epileptic brain is critical for successful epilepsy surgery and focal brain stimulation. Despite significant progress, roughly half of all patients undergoing focal surgical resection, and most patients receiving focal electrical stimulation, are not seizure free. There is intense interest in high-frequency oscillations (HFOs) recorded with intracranial electroencephalography as potential biomarkers to improve epileptogenic brain localization, resective surgery, and focal electrical stimulation. The present review examines the evidence that HFOs are clinically useful biomarkers.

Recent Findings: Performing the PubMed search 'High-Frequency Oscillations and Epilepsy' for 2013-2015 identifies 308 articles exploring HFO characteristics, physiological significance, and potential clinical applications.

Summary: There is strong evidence that HFOs are spatially associated with epileptic brain. There remain, however, significant challenges for clinical translation of HFOs as epileptogenic brain biomarkers: Differentiating true HFO from the high-frequency power changes associated with increased neuronal firing and bandpass filtering sharp transients. Distinguishing pathological HFO from normal physiological HFO. Classifying tissue under individual electrodes as normal or pathological. Sharing data and algorithms so research results can be reproduced across laboratories. Multicenter prospective trials to provide definitive evidence of clinical utility.
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http://dx.doi.org/10.1097/WCO.0000000000000302DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4941960PMC
April 2016

Combined Single Neuron Unit Activity and Local Field Potential Oscillations in a Human Visual Recognition Memory Task.

IEEE Trans Biomed Eng 2016 Jan 1;63(1):67-75. Epub 2015 Jul 1.

Goal: Activities of neuronal networks range from action potential firing of individual neurons, coordinated oscillations of local neuronal assemblies, and distributed neural populations. Here, we describe recordings using hybrid electrodes, containing both micro- and clinical macroelectrodes, to simultaneously sample both large-scale network oscillations and single neuron spiking activity in the medial temporal lobe structures of human subjects during a visual recognition memory task. We quantify and compare single neuron unit activity (SUA) with high-frequency macrofield oscillations (HFOs) for decoding visual images.

Results: SUA and HFOs were recorded using hybrid electrodes containing both micro and macroelectrode contacts, implanted in patients with focal epilepsy. Decoding of image properties in different task trials was performed, analyzing SUA and HFO as point processes to capture the dynamics of neurons and their assemblies at different spatiotemporal scales, ranging from submillisecond discharges of single units to fast oscillations across large neuronal populations. Results highlight the limitations and potential complementary use of SUA and HFOs for decoding of general image properties.

Conclusion: The dynamics of SUA and HFOs can be used to explore a wide range of neuronal assembly activities engaged in human memory processing.

Significance: Hybrid electrodes provide a technological bridge for exploring multiscale activity, spanning individual neurons, their assemblies, and large-scale population activity reflected in local field potentials. Analysis of SUA and HFO dynamics as point processes provides a potentially useful signal processing method for exploring the neuronal correlates operating at different spatial scales.
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http://dx.doi.org/10.1109/TBME.2015.2451596DOI Listing
January 2016

Evidence for consolidation of neuronal assemblies after seizures in humans.

J Neurosci 2015 Jan;35(3):999-1010

Department of Neurology, Division of Clinical Neurophysiology and Epilepsy, Mayo Systems Electrophysiology Laboratory, and.

The establishment of memories involves reactivation of waking neuronal activity patterns and strengthening of associated neural circuits during slow-wave sleep (SWS), a process known as "cellular consolidation" (Dudai and Morris, 2013). Reactivation of neural activity patterns during waking behaviors that occurs on a timescale of seconds to minutes is thought to constitute memory recall (O'Keefe and Nadel, 1978), whereas consolidation of memory traces may be revealed and served by correlated firing (reactivation) that appears during sleep under conditions suitable for synaptic modification (Buhry et al., 2011). Although reactivation has been observed in human neuronal recordings (Gelbard-Sagiv et al., 2008; Miller et al., 2013), reactivation during sleep has not, likely because data are difficult to obtain and the effect is subtle. Seizures, however, provide intense and synchronous, yet sparse activation (Bower et al., 2012) that could produce a stronger consolidation effect if seizures activate learning-related mechanisms similar to those activated by learned tasks. Continuous wide-bandwidth recordings from patients undergoing intracranial monitoring for drug-resistant epilepsy revealed reactivation of seizure-related neuronal activity during subsequent SWS, but not wakefulness. Those neuronal assemblies that were most strongly activated during seizures showed the largest correlation changes, suggesting that consolidation selectively strengthened neuronal circuits activated by seizures. These results suggest that seizures "hijack" physiological learning mechanisms and also suggest a novel epilepsy therapy targeting neuronal dynamics during post-seizure sleep.
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http://dx.doi.org/10.1523/JNEUROSCI.3019-14.2015DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4300336PMC
January 2015

Gamma oscillations precede interictal epileptiform spikes in the seizure onset zone.

Neurology 2015 Feb 14;84(6):602-8. Epub 2015 Jan 14.

From the Mayo Systems Electrophysiology Laboratory, Department of Neurology (L.R., M.T.K., J.C., J.Y.M., B.H.B., W.H., S.M.S., G.A.W.), and Department of Neurosurgery (W.R.M., F.B.M.), Mayo Clinic, Rochester, MN; Department of Neurology (L.R.), China-Japan Friendship Hospital, Beijing, China; and International Clinical Research Center (J.C.), St. Anne's University Hospital, Brno, Czech Republic.

Objective: To investigate the generation, spectral characteristics, and potential clinical significance of brain activity preceding interictal epileptiform spike discharges (IEDs) recorded with intracranial EEG.

Methods: Seventeen adult patients with drug-resistant temporal lobe epilepsy were implanted with intracranial electrodes as part of their evaluation for epilepsy surgery. IEDs detected on clinical macro- and research microelectrodes were analyzed using time-frequency spectral analysis.

Results: Gamma frequency oscillations (30-100 Hz) often preceded IEDs in spatially confined brain areas. The gamma-IEDs were consistently observed 35 to 190 milliseconds before the epileptiform spike waveforms on individual macro- and microelectrodes. The gamma oscillations associated with IEDs had longer duration (p < 0.001) and slightly higher frequency (p = 0.045) when recorded on microelectrodes compared with clinical macroelectrodes. Although gamma-IEDs comprised only a subset of IEDs, they were strongly associated with electrodes in the seizure onset zone (SOZ) compared with the surrounding brain regions (p = 0.004), in sharp contrast to IEDs without preceding gamma oscillations that were often also detected outside of the SOZ. Similar to prior studies, isolated pathologic high-frequency oscillations in the gamma (30-100 Hz) and higher (100-600 Hz) frequency range, not associated with an IED, were also found to be associated with SOZ.

Conclusions: The occurrence of locally generated gamma oscillations preceding IEDs suggests a mechanistic role for gamma in pathologic network activity generating IEDs. The results show a strong association between SOZ and gamma-IEDs. The potential clinical application of gamma-IEDs for mapping pathologic brain regions is intriguing, but will require future prospective studies.
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http://dx.doi.org/10.1212/WNL.0000000000001234DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4335986PMC
February 2015

High frequency oscillations are associated with cognitive processing in human recognition memory.

Brain 2014 Aug 11;137(Pt 8):2231-44. Epub 2014 Jun 11.

1 Department of Neurology, Mayo Clinic, 200 First St SW, Rochester MN, 55905, USA

High frequency oscillations are associated with normal brain function, but also increasingly recognized as potential biomarkers of the epileptogenic brain. Their role in human cognition has been predominantly studied in classical gamma frequencies (30-100 Hz), which reflect neuronal network coordination involved in attention, learning and memory. Invasive brain recordings in animals and humans demonstrate that physiological oscillations extend beyond the gamma frequency range, but their function in human cognitive processing has not been fully elucidated. Here we investigate high frequency oscillations spanning the high gamma (50-125 Hz), ripple (125-250 Hz) and fast ripple (250-500 Hz) frequency bands using intracranial recordings from 12 patients (five males and seven females, age 21-63 years) during memory encoding and recall of a series of affectively charged images. Presentation of the images induced high frequency oscillations in all three studied bands within the primary visual, limbic and higher order cortical regions in a sequence consistent with the visual processing stream. These induced oscillations were detected on individual electrodes localized in the amygdala, hippocampus and specific neocortical areas, revealing discrete oscillations of characteristic frequency, duration and latency from image presentation. Memory encoding and recall significantly modulated the number of induced high gamma, ripple and fast ripple detections in the studied structures, which was greater in the primary sensory areas during the encoding (Wilcoxon rank sum test, P = 0.002) and in the higher-order cortical association areas during the recall (Wilcoxon rank sum test, P = 0.001) of memorized images. Furthermore, the induced high gamma, ripple and fast ripple responses discriminated the encoded and the affectively charged images. In summary, our results show that high frequency oscillations, spanning a wide range of frequencies, are associated with memory processing and generated along distributed cortical and limbic brain regions. These findings support an important role for fast network synchronization in human cognition and extend our understanding of normal physiological brain activity during memory processing.
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http://dx.doi.org/10.1093/brain/awu149DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4107742PMC
August 2014

Pathological and physiological high-frequency oscillations in focal human epilepsy.

J Neurophysiol 2013 Oct 7;110(8):1958-64. Epub 2013 Aug 7.

Department of Neurology, Mayo Systems Electrophysiology Laboratory, Mayo Clinic, Rochester, Minnesota; and.

High-frequency oscillations (HFO; gamma: 40-100 Hz, ripples: 100-200 Hz, and fast ripples: 250-500 Hz) have been widely studied in health and disease. These phenomena may serve as biomarkers for epileptic brain; however, a means of differentiating between pathological and normal physiological HFO is essential. We categorized task-induced physiological HFO during periods of HFO induced by a visual or motor task by measuring frequency, duration, and spectral amplitude of each event in single trial time-frequency spectra and compared them to pathological HFO similarly measured. Pathological HFO had higher mean spectral amplitude, longer mean duration, and lower mean frequency than physiological-induced HFO. In individual patients, support vector machine analysis correctly classified pathological HFO with sensitivities ranging from 70-98% and specificities >90% in all but one patient. In this patient, infrequent high-amplitude HFO were observed in the motor cortex just before movement onset in the motor task. This finding raises the possibility that in epileptic brain physiological-induced gamma can assume higher spectral amplitudes similar to those seen in pathologic HFO. This method if automated and validated could provide a step towards differentiating physiological HFO from pathological HFO and improving localization of epileptogenic brain.
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http://dx.doi.org/10.1152/jn.00341.2013DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3798937PMC
October 2013

Network oscillations modulate interictal epileptiform spike rate during human memory.

Brain 2013 Aug 25;136(Pt 8):2444-56. Epub 2013 Jun 25.

Mayo Systems Electrophysiology Laboratory, Department of Neurology, Mayo Clinic, Rochester, MN 55905, USA.

Eleven patients being evaluated with intracranial electroencephalography for medically resistant temporal lobe epilepsy participated in a visual recognition memory task. Interictal epileptiform spikes were manually marked and their rate of occurrence compared between baseline and three 2 s periods spanning a 6 s viewing period. During successful, but not unsuccessful, encoding of the images there was a significant reduction in interictal epileptiform spike rate in the amygdala, hippocampus, and temporal cortex. During the earliest encoding period (0-2000 ms after image presentation) in these trials there was a widespread decrease in the power of theta, alpha and beta band local field potential oscillations that coincided with emergent focal gamma frequency activity. Interictal epileptiform spike rate correlated with spectral band power changes and broadband (4-150 Hz) desynchronization, which predicted significant reduction in interictal epileptiform spike rate. Spike-triggered averaging of the field potential power spectrum detected a burst of low frequency synchronization 200 ms before the interictal epileptiform spikes that arose during this period of encoding. We conclude that interictal epileptiform spikes are modulated by the patterns of network oscillatory activity that accompany human memory offering a new mechanistic insight into the interplay of cognitive processing, local field potential dynamics and interictal epileptiform spike generation.
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http://dx.doi.org/10.1093/brain/awt159DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3722348PMC
August 2013

Dysfunctional prefrontal cortical network activity and interactions following cannabinoid receptor activation.

J Neurosci 2011 Oct;31(43):15560-8

MRC Centre for Synaptic Plasticity, School of Physiology and Pharmacology, University of Bristol, BS8 1TD Bristol, United Kingdom.

Coordinated activity spanning anatomically distributed neuronal networks underpins cognition and mediates limbic-cortical interactions during learning, memory, and decision-making. We used CP55940, a potent agonist of brain cannabinoid receptors known to disrupt coordinated activity in hippocampus, to investigate the roles of network oscillations during hippocampal and medial prefrontal cortical (mPFC) interactions in rats. During quiet wakefulness and rest, CP55940 dose-dependently reduced 0.1-30 Hz local field potential power in CA1 of the hippocampus while concurrently decreasing 30-100 Hz power in mPFC; these contrasting population-level effects were paralleled by differential effects on underlying single-unit activity in the two structures. During decision-making phases of a spatial working memory task, CP5540-induced deficits in hippocampal theta and prefrontal gamma oscillations were observed alongside disrupted theta-frequency coherence between the two structures. These changes in coordinated limbic-cortical network activities correlated with (1) reduced accuracy of task performance, (2) impaired phase-locking of prefrontal single-unit spiking to the local gamma and hippocampal theta rhythms, and (3) impaired task-dependent activity in a subset of mPFC units. In addition to highlighting the importance of CA1-mPFC network oscillations for cognition, these results implicate disrupted theta-frequency coordination of CA1-mPFC activity in the cognitive deficits caused by exogenous activation of brain cannabinoid receptors.
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http://dx.doi.org/10.1523/JNEUROSCI.2970-11.2011DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6703515PMC
October 2011