Nuclei-specific thalamic connectivity predicts seizure frequency in drug-resistant medial temporal lobe epilepsy.

BACKGROUND AND OBJECTIVES: We assessed correlations between the resting state functional connectivity (RSFC) of different thalamic nuclei and seizure frequency in patients with drug-resistant medial temporal lobe epilepsy (mTLE). METHODS: Seventeen patients with mTLE and 17 sex-/age-/handedness-matched controls participated. A seed-based correlation method for the resting-state FMRI data was implemented to get RSFC maps of 70 thalamic nuclei seed masks. Group statistics for individual RSFC for subjects and seed masks were performed to obtain within-group characteristics and between-group differences with age covariates. A linear regression was applied to test whether seizure frequency correlated with thalamic nuclear RSFC with the whole brain in mTLE patients. RESULTS: RSFC of thalamic nuclei showed spatially distinguishable connectivity patterns that reflected principal inputs and outputs that were derived from priori anatomical knowledge. We found group differences between normal control and mTLE groups in RSFC for nuclei seeds located in various subdivisions of thalamus. The RSFCs in some of those nuclei were strongly correlated with seizure frequency. CONCLUSIONS: Mediodorsal thalamic nuclei may play important roles in seizure activity or in the regulation of neuronal activity in the limbic system. The RSFC of motor- and sensory-relay nuclei may help elucidate sensory-motor deficits associated with chronic seizure activity. RSFC of the pulvinar nuclei of the thalamus could also be a key reflection of symptom-related functional deficits in mTLE.

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

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.