Kathryn A. Davis

Flexible, foldable, actively multiplexed, high-density electrode array for mapping brain activity in vivo

Arrays of electrodes for recording and stimulating the brain are used throughout clinical medicine and basic neuroscience research, yet are unable to sample large areas of the brain while maintaining high spatial resolution because of the need to individually wire each passive sensor at the electrode-tissue interface. To overcome this constraint, we developed new devices that integrate ultrathin and flexible silicon nanomembrane transistors into the electrode array, enabling new dense arrays of thousands of amplified and multiplexed sensors that are connected using fewer wires. We used this system to record spatial properties of cat brain activity in vivo, including sleep spindles, single-trial visual evoked responses and electrographic seizures. We found that seizures may manifest as recurrent spiral waves that propagate in the neocortex. The developments reported here herald a new generation of diagnostic and therapeutic brain-machine interface devices.

Dynamic Network Drivers of Seizure Generation, Propagation and Termination in Human Neocortical Epilepsy

The epileptic network is characterized by pathologic, seizure-generating ‘foci’ embedded in a web of structural and functional connections. Clinically, seizure foci are considered optimal targets for surgery. However, poor surgical outcome suggests a complex relationship between foci and the surrounding network that drives seizure dynamics. We developed a novel technique to objectively track seizure states from dynamic functional networks constructed from intracranial recordings. Each dynamical state captures unique patterns of network connections that indicate synchronized and desynchronized hubs of neural populations. Our approach suggests that seizures are generated when synchronous relationships near foci work in tandem with rapidly changing desynchronous relationships from the surrounding epileptic network. As seizures progress, topographical and geometrical changes in network connectivity strengthen and tighten synchronous connectivity near foci—a mechanism that may aid seizure termination. Collectively, our observations implicate distributed cortical structures in seizure generation, propagation and termination, and may have practical significance in determining which circuits to modulate with implantable devices.

Virtual Cortical Resection Reveals Push-Pull Network Control Preceding Seizure Evolution

In ∼20 million people with drug-resistant epilepsy, focal seizures originating in dysfunctional brain networks will often evolve and spread to surrounding tissue, disrupting function in otherwise normal brain regions. To identify network control mechanisms that regulate seizure spread, we developed a novel tool for pinpointing brain regions that facilitate synchronization in the epileptic network. Our method measures the impact of virtually resecting putative control regions on synchronization in a validated model of the human epileptic network. By applying our technique to time-varying functional networks, we identified brain regions whose topological role is to synchronize or desynchronize the epileptic network. Our results suggest that greater antagonistic push-pull interaction between synchronizing and desynchronizing brain regions better constrains seizure spread. These methods, while applied here to epilepsy, are generalizable to other brain networks and have wide applicability in isolating and mapping functional drivers of brain dynamics in health and disease.

A novel implanted device to wirelessly record and analyze continuous intracranial canine EEG

We present results from continuous intracranial electroencephalographic (iEEG) monitoring in 6 dogs with naturally occurring epilepsy, a disorder similar to the human condition in its clinical presentation, epidemiology, electrophysiology and response to therapy. Recordings were obtained using a novel implantable device wirelessly linked to an external, portable real-time processing unit. We demonstrate previously uncharacterized intracranial seizure onset patterns in these animals that are strikingly similar in appearance to human partial onset epilepsy. We propose: (1) canine epilepsy as an appropriate model for testing human antiepileptic devices and new approaches to epilepsy surgery, and (2) this new technology as a versatile platform for evaluating seizures and response to therapy in the natural, ambulatory setting.

Theta and High-Frequency Activity Mark Spontaneous Recall of Episodic Memories

Humans possess the remarkable ability to search their memory, allowing specific past episodes to be re-experienced spontaneously. Here, we administered a free recall test to 114 neurosurgical patients and used intracranial theta and high-frequency activity (HFA) to identify the spatiotemporal pattern of neural activity underlying spontaneous episodic retrieval. We found that retrieval evolved in three electrophysiological stages composed of: (1) early theta oscillations in the right temporal cortex, (2) increased HFA in the left hemisphere including the medial temporal lobe (MTL), left inferior frontal gyrus, as well as the ventrolateral temporal cortex, and (3) motor/language activation during vocalization of the retrieved item. Of these responses, increased HFA in the left MTL predicted recall performance. These results suggest that spontaneous recall of verbal episodic memories involves a spatiotemporal pattern of spectral changes across the brain; however, high-frequency activity in the left MTL represents a final common pathway of episodic retrieval.

Glutamate imaging (GluCEST) lateralizes epileptic foci in nonlesional temporal lobe epilepsy

Noninvasive glutamate brain imaging (GluCEST) can localize seizure foci to one hemisphere in patients with temporal lobe epilepsy. Toward visualizing the focus Many seizures, especially those that originate in the brain’s temporal lobe, start at a single spot in the brain. If drugs fail, excision of this region can often provide relief from seizures. A new imaging method that harnesses the power of a 7-T magnet shows promise in locating hard-to-find epileptic foci by visualizing the neurotransmitter glutamate. In a pilot study, the authors used glutamate chemical exchange saturation transfer (GluCEST), a very high resolution magnetic resonance imaging contrast method, to measure how much glutamate was in the hippocampi of four patients with epilepsy. Glutamate is elevated in epileptic foci. The amount of glutamate was clearly higher in one of the hippocampi in all four patients, and confirmatory methods (electroencephalography or magnetic resonance spectra) verified independently that the hippocampus with the elevated glutamate was located in the same hemisphere as the epileptic focus. Although the authors have only taken a first step toward noninvasively finding epileptic foci, their demonstration that GluCEST can localize small brain hot spots of high glutamate is promising. This approach can potentially allow a higher rate of successful surgeries in this difficult disease. When neuroimaging reveals a brain lesion, drug-resistant epilepsy patients show better outcomes after resective surgery than do the one-third of drug-resistant epilepsy patients who have normal brain magnetic resonance imaging (MRI). We applied a glutamate imaging method, GluCEST (glutamate chemical exchange saturation transfer), to patients with nonlesional temporal lobe epilepsy based on conventional MRI. GluCEST correctly lateralized the temporal lobe seizure focus on visual and quantitative analyses in all patients. MR spectra, available for a subset of patients and controls, corroborated the GluCEST findings. Hippocampal volumes were not significantly different between hemispheres. GluCEST allowed high-resolution functional imaging of brain glutamate and has potential to identify the epileptic focus in patients previously deemed nonlesional. This method may lead to improved clinical outcomes for temporal lobe epilepsy as well as other localization-related epilepsies.

Direct Brain Stimulation Modulates Encoding States and Memory Performance in Humans

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.

Universal automated high frequency oscillation detector for real-time, long term EEG.

OBJECTIVE Interictal high frequency oscillations (HFOs) in intracranial EEG are a potential biomarker of epilepsy, but current automated HFO detectors require human review to remove artifacts. Our objective is to automatically redact false HFO detections, facilitating clinical use of interictal HFOs. METHODS Intracranial EEG data from 23 patients were processed with automated detectors of HFOs and artifacts. HFOs not concurrent with artifacts were labeled quality HFOs (qHFOs). Methods were validated by human review on a subset of 2000 events. The correlation of qHFO rates with the seizure onset zone (SOZ) was assessed via (1) a retrospective asymmetry measure and (2) a novel quasi-prospective algorithm to identify SOZ. RESULTS Human review estimated that less than 12% of qHFOs are artifacts, whereas 78.5% of redacted HFOs are artifacts. The qHFO rate was more correlated with SOZ (p=0.020, Wilcoxon signed rank test) and resected volume (p=0.0037) than baseline detections. Using qHFOs, our algorithm was able to determine SOZ in 60% of the ILAE Class I patients, with all algorithmically-determined SOZs fully within the resected volumes. CONCLUSIONS The algorithm reduced false-positive HFO detections, improving the precision of the HFO-biomarker. SIGNIFICANCE These methods provide a feasible strategy for HFO detection in real-time, continuous EEG with minimal human monitoring of data quality.

Sensitivity of quantitative EEG for seizure identification in the intensive care unit

Objective: To evaluate the sensitivity of quantitative EEG (QEEG) for electrographic seizure identification in the intensive care unit (ICU). Methods: Six-hour EEG epochs chosen from 15 patients underwent transformation into QEEG displays. Each epoch was reviewed in 3 formats: raw EEG, QEEG + raw, and QEEG-only. Epochs were also analyzed by a proprietary seizure detection algorithm. Nine neurophysiologists reviewed raw EEGs to identify seizures to serve as the gold standard. Nine other neurophysiologists with experience in QEEG evaluated the epochs in QEEG formats, with and without concomitant raw EEG. Sensitivity and false-positive rates (FPRs) for seizure identification were calculated and median review time assessed. Results: Mean sensitivity for seizure identification ranged from 51% to 67% for QEEG-only and 63%–68% for QEEG + raw. FPRs averaged 1/h for QEEG-only and 0.5/h for QEEG + raw. Mean sensitivity of seizure probability software was 26.2%–26.7%, with FPR of 0.07/h. Epochs with the highest sensitivities contained frequent, intermittent seizures. Lower sensitivities were seen with slow-frequency, low-amplitude seizures and epochs with rhythmic or periodic patterns. Median review times were shorter for QEEG (6 minutes) and QEEG + raw analysis (14.5 minutes) vs raw EEG (19 minutes; p = 0.00003). Conclusions: A panel of QEEG trends can be used by experts to shorten EEG review time for seizure identification with reasonable sensitivity and low FPRs. The prevalence of false detections confirms that raw EEG review must be used in conjunction with QEEG. Studies are needed to identify optimal QEEG trend configurations and the utility of QEEG as a screening tool for non-EEG personnel. Classification of evidence review: This study provides Class II evidence that QEEG + raw interpreted by experts identifies seizures in patients in the ICU with a sensitivity of 63%–68% and FPR of 0.5 seizures per hour.

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

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.Memory lapses can occur due to ineffective encoding, but it is unclear if targeted brain stimulation can improve memory performance. Here, authors use a closed-loop system to decode and stimulate periods of ineffective encoding, showing that stimulation of lateral temporal cortex can enhance memory.