Kucewicz, Michał T.

Eidetic memory has been reported in children and in patients with synesthesia but is otherwise thought to be a rare phenomenon. Presented herein is a patient with right-sided language dominance, as proven via multiple functional imaging and neuropsychometric methods, who has a seizure onset zone in the right temporo-parietal-occipital cortex. This patient’s medically refractory epilepsy and thus hyperactive cortex could possibly contribute to near eidetic ability with paired-associates learning tasks (in both short-term and long-term retention). There are reports of epilepsy negatively affecting memory, but as far as the authors are aware to date, there is limited evidence of any lesion enhancing cognitive functions (whether through direct lesion or via compensatory mechanism) that would be localized to a seizure onset zone in the dominant temporo-parietal-occipital junction.

Abstract Modulation of cognitive functions supporting human declarative memory is one of the grand challenges of neuroscience, and of vast importance for a variety of neuropsychiatric, neurodegenerative and neurodevelopmental diseases. Despite a recent surge of successful attempts at improving performance in a range of memory tasks, the optimal approaches and parameters for memory enhancement have yet to be determined. On a more fundamental level, it remains elusive as to how delivering electrical current in a given brain area leads to enhanced memory processing. Starting from the local and distal physiological effects on neural populations, the mechanisms of enhanced memory encoding, maintenance, consolidation or recall in response to direct electrical stimulation are only now being unravelled. With the advent of innovative neurotechnologies for concurrent recording and stimulation intracranially in the human brain, it becomes possible to study both acute and chronic effects of stimulation on memory performance and the underlying neural activities. In this review, we summarize the effects of various invasive stimulation approaches for modulating memory functions. We first outline the challenges that were faced in the initial studies of memory enhancement and the lessons learnt. Electrophysiological biomarkers are then reviewed as more objective measures of the stimulation effects than behavioural outcomes. Finally, we classify the various stimulation approaches into continuous and phasic modulation with an open or closed loop for responsive stimulation based on analysis of the recorded neural activities. Although the potential advantage of closed-loop responsive stimulation over the classic open-loop approaches is inconclusive, we foresee the emerging results from ongoing longitudinal studies and clinical trials will shed light on both the mechanisms and optimal strategies for improving declarative memory. Adaptive stimulation based on the biomarker analysis over extended periods of time is proposed as a future direction for obtaining lasting effects on memory functions. Chronic tracking and modulation of neural activities intracranially through adaptive stimulation opens tantalizing new avenues to continually monitor and treat memory and cognitive deficits in a range of brain disorders. Brain co-processors created with machine-learning tools and wireless bi-directional connectivity to seamlessly integrate implanted devices with smartphones and cloud computing are poised to enable real-time automated analysis of large data volumes and adaptively tune electrical stimulation based on electrophysiological biomarkers of behavioural states. Next-generation implantable devices for high-density recording and stimulation of electrophysiological activities, and technologies for distributed brain–computer interfaces are presented as selected future perspectives for modulating human memory and associated mental processes.

The emergence of innovative neurotechnologies in global brain projects has accelerated research and clinical applications of BCIs beyond sensory and motor functions. Both invasive and noninvasive sensors are developed to interface with cognitive functions engaged in thinking, communication, or remembering. The detection of eye movements by a camera offers a particularly attractive external sensor for computer interfaces to monitor, assess, and control these higher brain functions without acquiring signals from the brain. Features of gaze position and pupil dilation can be effectively used to track our attention in healthy mental processes, to enable interaction in disorders of consciousness, or to even predict memory performance in various brain diseases. In this perspective article, we propose the term ‘CyberEye’ to encompass emerging cognitive applications of eye-tracking interfaces for neuroscience research, clinical practice, and the biomedical industry. As CyberEye technologies continue to develop, we expect BCIs to become less dependent on brain activities, to be less invasive, and to thus be more applicable.

Abstract Objective Verbal memory dysfunction is common in focal, drug‐resistant epilepsy (DRE). Unfortunately, surgical removal of seizure‐generating brain tissue can be associated with further memory decline. Therefore, localization of both the circuits generating seizures and those underlying cognitive functions is critical in presurgical evaluations for patients who may be candidates for resective surgery. We used intracranial electroencephalographic (iEEG) recordings during a verbal memory task to investigate word encoding in focal epilepsy. We hypothesized that engagement in a memory task would exaggerate local iEEG feature differences between the seizure onset zone (SOZ) and neighboring tissue as compared to wakeful rest (“nontask”). Methods Ten participants undergoing presurgical iEEG evaluation for DRE performed a free recall verbal memory task. We evaluated three iEEG features in SOZ and non‐SOZ electrodes during successful word encoding and compared them with nontask recordings: interictal epileptiform spike (IES) rates, power in band (PIB), and relative entropy (REN; a functional connectivity measure). Results We found a complex pattern of PIB and REN changes in SOZ and non‐SOZ electrodes during successful word encoding compared to nontask. Successful word encoding was associated with a reduction in local electrographic functional connectivity (increased REN), which was most exaggerated in temporal lobe SOZ. The IES rates were reduced during task, but only in the non‐SOZ electrodes. Compared with nontask, REN features during task yielded marginal improvements in SOZ classification. Significance Previous studies have supported REN as a biomarker for epileptic brain. We show that REN differences between SOZ and non‐SOZ are enhanced during a verbal memory task. We also show that IESs are reduced during task in non‐SOZ, but not in SOZ. These findings support the hypothesis that SOZ and non‐SOZ respond differently to task and warrant further exploration into the use of cognitive tasks to identify functioning memory circuits and localize SOZ.

Abstract 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 34 ± 12 , 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.

SummaryObjectiveLocal 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).MethodsScalp 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).ResultsChanges 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.SignificanceThese 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.