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Leveraging firsthand experience, BRAIN-funded investigators conducting intracranial human neuroscience research propose two fundamental ethical commitments: (1) maintaining the integrity of clinical care and (2) ensuring voluntariness. Principles, practices, and uncertainties related to these commitments are offered for future investigation.

Introduction: For patients with drug-resistant epilepsy, successful localization and surgical treatment of the epileptogenic zone (EZ) can bring seizure freedom. However, surgical success rates vary widely because there are currently no clinically validated biomarkers of the EZ. Highly epileptogenic regions often display increased levels of cortical excitability, which can be probed using single-pulse electrical stimulation (SPES), where brief pulses of electrical current are delivered to brain tissue. It has been shown that high-amplitude responses to SPES can localize EZ regions, indicating a decreased threshold of excitability. However, performing extensive SPES in the epilepsy monitoring unit (EMU) is time-consuming. Thus, we built patient-specific in silico dynamical network models from interictal intracranial EEG (iEEG) to test whether virtual stimulation could reveal information about the underlying network to identify highly excitable brain regions similar to physical stimulation of the brain. Methods: We performed virtual stimulation in 69 patients that were evaluated at five centers and assessed for clinical outcome 1 year post surgery. We further investigated differences in observed SPES iEEG responses of 14 patients stratified by surgical outcome. Results: Clinically-labeled EZ cortical regions exhibited higher excitability from virtual stimulation than non-EZ regions with most significant differences in successful patients and little difference in failure patients. These trends were also observed in responses to extensive SPES performed in the EMU. Finally, when excitability was used to predict whether a channel is in the EZ or not, the classifier achieved an accuracy of 91%. Discussion: This study demonstrates how excitability determined via virtual stimulation can capture valuable information about the EZ from interictal intracranial EEG. [ABSTRACT FROM AUTHOR]

ObjectiveCommon data elements (CDEs) are currently unavailable for mobile health (mHealth) in epilepsy devices and related applications. As a result, despite expansive growth of new digital services for people with epilepsy, information collected is often not interoperable or directly comparable. We aim to correct this problem through development of industry-wide standards for mHealth epilepsy data.MethodsUsing a group of stakeholders from industry, academia, and patient advocacy organizations, we offer a consensus statement for the elements that may facilitate communication among different systems.ResultsA consensus statement is presented for epilepsy mHealth CDEs.SignificanceAlthough it is not exclusive, we believe that the use of a minimal common information denominator, specifically these CDEs, will promote innovation, accelerate scientific discovery, and enhance clinical usage across applications and devices in the epilepsy mHealth space. As a consequence, people with epilepsy will have greater flexibility and ultimately more powerful tools to improve their lives.

How do humans flexibly respond to changing environmental demands on a sub-second temporal scale? Extensive research has highlighted the key role of the prefrontal cortex in flexible decision-making and adaptive behavior, yet the core mechanisms that translate sensory information into behavior remain undefined. Utilizing direct human cortical recordings, we investigated the temporal and spatial evolution of neuronal activity, indexed by the broadband gamma signal, while sixteen participants performed a broad range of self-paced cognitive tasks. Here we describe a robust domain- and modality-independent pattern of persistent stimulus-to-response neural activation that encodes stimulus features and predicts motor output on a trial-by-trial basis with near-perfect accuracy. Observed across a distributed network of brain areas, this persistent neural activation is centered in the prefrontal cortex and is required for successful response implementation, providing a functional substrate for domain-general transformation of perception into action, critical for flexible behavior.

Word retrieval is core to language production and relies on complementary processes: the rapid activation of lexical and conceptual representations and word selection, which chooses the correct word among semantically related competitors. Lexical and conceptual activation is measured by semantic priming. In contrast, word selection is indexed by semantic interference and is hampered in semantically homogeneous (HOM) contexts. We examined the spatiotemporal dynamics of these complementary processes in a picture naming task with blocks of semantically heterogeneous (HET) or HOM stimuli. We used electrocorticography data obtained from frontal and temporal cortices, permitting detailed spatiotemporal analysis of word retrieval processes. A semantic interference effect was observed with naming latencies longer in HOM versus HET blocks. Cortical response strength as indexed by high-frequency band (HFB) activity (70-150 Hz) amplitude revealed effects linked to lexical-semantic activation and word selection observed in widespread regions of the cortical mantle. Depending on the subsecond timing and cortical region, HFB indexed semantic interference (i.e., more activity in HOM than HET blocks) or semantic priming effects (i.e., more activity in HET than HOM blocks). These effects overlapped in time and space in the left posterior inferior temporal gyrus and the left prefrontal cortex. The data do not support a modular view of word retrieval in speech production but rather support substantial overlap of lexical-semantic activation and word selection mechanisms in the brain.

How the human auditory system extracts perceptually relevant acoustic features of speech is unknown. To address this question, we used intracranial recordings from nonprimary auditory cortex in the human superior temporal gyrus to determine what acoustic information in speech sounds can be reconstructed from population neural activity. We found that slow and intermediate temporal fluctuations, such as those corresponding to syllable rate, were accurately reconstructed using a linear model based on the auditory spectrogram. However, reconstruction of fast temporal fluctuations, such as syllable onsets and offsets, required a nonlinear sound representation based on temporal modulation energy. Reconstruction accuracy was highest within the range of spectro-temporal fluctuations that have been found to be critical for speech intelligibility. The decoded speech representations allowed readout and identification of individual words directly from brain activity during single trial sound presentations. These findings reveal neural encoding mechanisms of speech acoustic parameters in higher order human auditory cortex.

Patterns of responses in the cerebral cortex can vary, and are influenced by pre-existing cortical function, but it is not known how rapidly these variations can occur in humans. We investigated how rapidly response patterns to electrical stimulation can vary in intact human brain. We also investigated whether the type of functional change occurring at a given location with stimulation would help predict the distribution of responses elsewhere over the cortex to stimulation at that given location. We did this by studying cortical afterdischarges following electrical stimulation of the cortex in awake humans undergoing evaluations for brain surgery. Response occurrence and location could change within seconds, both nearby to and distant from stimulation sites. Responses might occur at a given location during one trial but not the next. They could occur at electrodes adjacent or not adjacent to those directly stimulated or to other electrodes showing afterdischarges. The likelihood of an afterdischarge at an individual site after stimulation was predicted by spontaneous electroencephalographic activity at that specific site just prior to stimulation, but not by overall cortical activity. When stimulation at a site interrupted motor, sensory or language function, afterdischarges were more likely to occur at other sites where stimulation interrupted similar functions. These results show that widespread dynamic changes in cortical responses can occur in intact cortex within short periods of time, and that the distribution of these responses depends on local brain states and functional brain architecture at the time of stimulation. Similar rapid variations may occur during normal intracortical communication and may underlie changes in the cortical organization of function. Possibly these variations, and the occurrence and distribution of responses to cortical stimulation, could be predicted. If so, interventions such as stimulation might be used to alter spread of epileptogenic activity, accelerate learning or enhance cortical reorganization after brain injury.