Faculty Bibliography

How do firing patterns in a cortical circuit change when inhibitory neurons are excited? We virally expressed an excitatory designer receptor exclusively activated by a designer drug (Gq-DREADD) in all inhibitory interneuron types of the CA1 region of the hippocampus in the rat. While clozapine N-oxide (CNO) activation of interneurons suppressed firing of pyramidal cells, unexpectedly the majority of interneurons also decreased their activity. CNO-induced inhibition decreased over repeated sessions, which we attribute to long-term synaptic plasticity between interneurons and pyramidal cells. Individual interneurons did not display sustained firing but instead transiently enhanced their activity, interleaved with suppression of others. The power of the local fields in the theta band was unaffected, while power at higher frequencies was attenuated, likely reflecting reduced pyramidal neuron spiking. The incidence of sharp wave ripples decreased but the surviving ripples were associated with stronger population firing compared with the control condition. These findings demonstrate that DREADD activation of interneurons brings about both short-term and long-term circuit reorganization, which should be taken into account in the interpretation of chemogenic effects on behavior.

OBJECTIVE:The combined spatiotemporal dynamics underlying sign language production remains largely unknown. To investigate these dynamics as compared to speech production we utilized intracranial electrocorticography during a battery of language tasks. METHODS:We report a unique case of direct cortical surface recordings obtained from a neurosurgical patient with intact hearing and bilingual in English and American Sign Language. We designed a battery of cognitive tasks to capture multiple modalities of language processing and production. RESULTS:We identified two spatially distinct cortical networks: ventral for speech and dorsal for sign production. Sign production recruited peri-rolandic, parietal and posterior temporal regions, while speech production recruited frontal, peri-sylvian and peri-rolandic regions. Electrical cortical stimulation confirmed this spatial segregation, identifying mouth areas for speech production and limb areas for sign production. The temporal dynamics revealed superior parietal cortex activity immediately before sign production, suggesting its role in planning and producing sign language. CONCLUSIONS:Our findings reveal a distinct network for sign language and detail the temporal propagation supporting sign production.

High frequency oscillations (HFOs) are bursts of neural activity in the range of 80 Hz or higher, recorded from intracranial electrodes during epileptiform discharges. HFOs are a proposed biomarker of epileptic brain tissue and may also be useful for seizure forecasting. Despite such clinical utility of HFOs, the spatial context and neuronal activity underlying these local field potential (LFP) events remains unclear. We sought to further understand the neuronal correlates of ictal high frequency LFPs using multielectrode array recordings in the human neocortex and mesial temporal lobe during rhythmic onset seizures. These multiscale recordings capture single cell, multiunit, and LFP activity from the human brain. We compare features of multiunit firing and high frequency LFP from microelectrodes and macroelectrodes during ictal discharges in both the seizure core and penumbra (spatial seizure domains defined by multiunit activity patterns). We report differences in spectral features, unit-local field potential coupling, and information theoretic characteristics of high frequency LFP before and after local seizure invasion. Furthermore, we tie these time-domain differences to spatial domains of seizures, showing that penumbral discharges are more broadly distributed and less useful for seizure localization. These results describe the neuronal and synaptic correlates of two types of pathological HFOs in humans and have important implications for clinical interpretation of rhythmic onset seizures.

PURPOSE/OBJECTIVE:Surgical planning for people with drug resistant non-lesional focal epilepsy can be challenging. Prior studies focus on cases that are only MRI-negative or MRI-negative with PET-positive imaging, but little is known about outcomes in patients with non-lesional findings on both MRI and PET imaging. In this study, we investigate 5-year surgical outcomes in patients who underwent epilepsy surgery for drug resistant MRI/PET-negative focal epilepsy. METHODS:We collected clinical and testing data on 131 consecutive patients with drug resistant non-lesional epilepsy who were presented at a multidisciplinary epilepsy surgery conference at the New York University Comprehensive Epilepsy Center between 2010 and 2014, and identified those who underwent epilepsy surgery in order to review 5-year surgical outcomes. RESULTS:There were 103 with non-lesional MRI studies, and of these, 22 had corresponding non-lesional PET imaging. 14 MRI/PET-negative patients pursued a surgical treatment option and 9 underwent resections after intracranial EEG. At 5 years, 77.8 % of patients had favorable (ILAE class 1 and 2) outcomes. Most (77.8 %) had focal cortical dysplasia type Ia (FCDIa) on pathology. CONCLUSION/CONCLUSIONS:These findings suggest that with careful planning and patient selection, surgery for patients with drug resistant MRI/PET-negative focal epilepsy can be successful.

The alpha rhythm is the longest-studied brain oscillation and has been theorized to play a key role in cognition. Still, its physiology is poorly understood. In this study, we used microelectrodes and macroelectrodes in surgical epilepsy patients to measure the intracortical and thalamic generators of the alpha rhythm during quiet wakefulness. We first found that alpha in both visual and somatosensory cortex propagates from higher-order to lower-order areas. In posterior cortex, alpha propagates from higher-order anterosuperior areas toward the occipital pole, whereas alpha in somatosensory cortex propagates from associative regions toward primary cortex. Several analyses suggest that this cortical alpha leads pulvinar alpha, complicating prevailing theories of a thalamic pacemaker. Finally, alpha is dominated by currents and firing in supragranular cortical layers. Together, these results suggest that the alpha rhythm likely reflects short-range supragranular feedback, which propagates from higher- to lower-order cortex and cortex to thalamus. These physiological insights suggest how alpha could mediate feedback throughout the thalamocortical system.

Dynamic interactions between remote but functionally specialized brain regions enable complex information processing. This intercortical communication is disrupted in the neural networks of patients with focal epilepsy, and epileptic activity can exert widespread effects within the brain. Using large-scale human intracranial electroencephalography recordings, we show that interictal epileptiform discharges (IEDs) are significantly coupled with spindles in discrete, individualized brain regions outside of the epileptic network. We found that a substantial proportion of these localized spindles travel across the cortical surface. Brain regions that participate in this IED-driven oscillatory coupling express spindles that have a broader spatial extent and higher tendency to propagate than spindles occurring in uncoupled regions. These altered spatiotemporal oscillatory properties identify areas that are shaped by epileptic activity independent of IED or seizure detection. Our findings suggest that IED-spindle coupling may be an important mechanism of interictal global network dysfunction that could be targeted to prevent disruption of normal neural activity.

We studied the relationship between uninstructed, unstructured movements and neural activity in three epilepsy patients with intracranial electroencephalographic (iEEG) recordings. We used a custom system to continuously record high definition video precisely time-aligned to clinical iEEG data. From these video recordings, movement periods were annotated via semi-automatic tracking based on dense optical flow. We found that neural signal features (8--32 Hz and 76--100 Hz power) previously identified from task-based experiments are also modulated before and during a variety of movement behaviors. These movement behaviors are coarsely labeled by time period and movement side (e.g. `Idle' and `Move', `Right' and `Left'); movements within a label can include a wide variety of uninstructed behaviors. A rigorous nested cross-validation framework was used to classify both movement onset and lateralization with statistical significance for all subjects. We demonstrate an evaluation framework to study neural activity related to natural movements not evoked by a task, annotated over hours of video. This work further establishes the feasibility to study neural correlates of unstructured behavior through continuous recording in the epilepsy monitoring unit. The insights gained from such studies may advance our understanding of how the brain naturally controls movement, which may inform the development of more robust and generalizable brain-computer interfaces.

The principles underlying functional asymmetries in cortex remain debated. For example, it is accepted that speech is processed bilaterally in auditory cortex, but a left hemisphere dominance emerges when the input is interpreted linguistically. The mechanisms, however, are contested, such as what sound features or processing principles underlie laterality. Recent findings across species (humans, canines and bats) provide converging evidence that spectrotemporal sound features drive asymmetrical responses. Typically, accounts invoke models wherein the hemispheres differ in time-frequency resolution or integration window size. We develop a framework that builds on and unifies prevailing models, using spectrotemporal modulation space. Using signal processing techniques motivated by neural responses, we test this approach, employing behavioural and neurophysiological measures. We show how psychophysical judgements align with spectrotemporal modulations and then characterize the neural sensitivities to temporal and spectral modulations. We demonstrate differential contributions from both hemispheres, with a left lateralization for temporal modulations and a weaker right lateralization for spectral modulations. We argue that representations in the modulation domain provide a more mechanistic basis to account for lateralization in auditory cortex.

BACKGROUND:Although they form a unitary phenomenon, the relationship between extracranial M/EEG and transmembrane ion flows is understood only as a general principle rather than as a well-articulated and quantified causal chain. METHOD/METHODS:We present an integrated multiscale model, consisting of a neural simulation of thalamus and cortex during stage N2 sleep and a biophysical model projecting cortical current densities to M/EEG fields. Sleep spindles were generated through the interactions of local and distant network connections and intrinsic currents within thalamocortical circuits. 32,652 cortical neurons were mapped onto the cortical surface reconstructed from subjects' MRI, interconnected based on geodesic distances, and scaled-up to current dipole densities based on laminar recordings in humans. MRIs were used to generate a quasi-static electromagnetic model enabling simulated cortical activity to be projected to the M/EEG sensors. RESULTS:The simulated M/EEG spindles were similar in amplitude and topography to empirical examples in the same subjects. Simulated spindles with more core-dominant activity were more MEG weighted. COMPARISON WITH EXISTING METHODS/UNASSIGNED:Previous models lacked either spindle-generating thalamic neural dynamics or whole head biophysical modeling; the framework presented here is the first to simultaneously capture these disparate scales simultaneously. CONCLUSIONS:This multiscale model provides a platform for the principled quantitative integration of existing information relevant to the generation of sleep spindles, and allows the implications of future findings to be explored. It provides a proof of principle for a methodological framework allowing large-scale integrative brain oscillations to be understood in terms of their underlying channels and synapses.