Daniel Y. Rubinstein

Revised The left supramarginal gyrus (LSMG) may mediate attention to memory, and gauge memory state and performance. We performed a secondary analysis of 142 verbal delayed free recall experiments, in patients with medically-refractory epilepsy with electrode contacts implanted in the LSMG. In 14 of 142 experiments (in 14 of 113 patients), the cross-validated convolutional neural networks (CNNs) that used 1-dimensional(1-D) pairs of convolved high-gamma and beta tensors, derived from the LSMG recordings, could label recalled words with an area under the receiver operating curve (AUROC) of greater than 60% [range: 60-90%]. These 14 patients were distinguished by: 1) higher amplitudes of high-gamma bursts; 2) distinct electrode placement within the LSMG; and 3) superior performance compared with a CNN that used a 1-D tensor of the broadband recordings in the LSMG. In a pilot study of 7 of these patients, we also cross-validated CNNs using paired 1-D convolved high-gamma and beta tensors, from the LSMG, to: a) distinguish word encoding epochs from free recall epochs [AUC 0.6-1]; and distinguish better performance from poor performance during delayed free recall [AUC 0.5-0.86]. These experiments show that bursts of high-gamma and beta generated in the LSMG are biomarkers of verbal memory state and performance.

Endogenous variation in brain state and stimulus-specific evoked activity can both contribute to successful encoding. Previous studies, however, have not clearly distinguished among these components. We address this question by analysing intracranial EEG recorded from epilepsy patients as they studied and subsequently recalled lists of words. We first trained classifiers to predict recall of either single items or entire lists and found that both classifiers exhibited similar performance. We found that list-level classifier output—a biomarker of successful encoding—tracked item presentation and recall events, despite having no information about the trial structure. Across widespread brain regions, decreased low- and increased high-frequency activity (HFA) marked successful encoding of both items and lists. We found regional differences in the hippocampus and prefrontal cortex, where in the hippocampus HFA correlated more strongly with item recall, whereas, in the prefrontal cortex, HFA correlated more strongly with list performance. Despite subtle differences in item- and list-level features, the similarity in overall classification performance, spectral signatures of successful recall and fluctuations of spectral activity across the encoding period argue for a shared endogenous process that causally impacts the brain’s ability to learn new information.

Objective: How responsive neurostimulation (RNS) decreases seizure frequency is unclear. Stimulation may alter epileptic networks during inter-ictal epochs. Since fast ripples (FR) may be a substrate of the epileptic network, we examined whether stimulation of FR generating networks differed in RNS super- and intermediate-responders. Methods: In 10 patients, we detected FR during sleep from stereo EEG (SEEG) contacts during the pre-surgical evaluation in patients with subsequent RNS placement. The normalized coordinates of the SEEG contacts were compared with that of the eight RNS contacts, and RNS stimulated SEEG contacts were defined as within 1.5 cm ³ of the RNS contacts. We compared the post-RNS placement seizure outcome to 1) the ratio of stimulated SEEG contacts in the seizure-onset zone (SOZ SR); 2) the ratio of FR events on stimulated contacts (FR SR); and 3) the global efficiency of the FR temporal correlational network on stimulated contacts (FR SGe). Results: We found that the SOZ SR (p=0.18) and FR SR (p=0.06) did not differ in the RNS super- and intermediate-responders, but the FR SGe did (p=0.02). In super-responders highly active desynchronous sites of the FR network were stimulated. Significance: RNS that better targets FR networks, as compared to the SOZ, may reduce epileptogenicity more. Short summary: Responsive neurostimulation (RNS) may reduce seizures by altering the epileptic network. Fast ripples (FR) may be a substrate of the epileptic network. We investigated, in 10 patients, if RNS stimulation of FR generating brain differed in RNS super-responders and intermediate-responders. The RNS stimulated brain sites were defined as contacts in the pre-surgical stereo EEG implant within 1.5 cm ³ of the subsequently placed RNS stimulation contacts. FR events were more highly active and temporally desynchronous (p<0.05) on the stimulated contacts in the RNS super-responders. We show RNS that better targets FR networks, as compared to the seizure onset zone, may reduce epileptogenicity more.

Endogenous variation in brain state and stimulus-specific evoked activity can both contribute to successful encoding. Previous studies, however, have not clearly distinguished among these components. We address this question by analyzing intracranial EEG recorded from epilepsy patients as they studied and subsequently recalled lists of words. We first trained classifiers to predict recall of either single items or entire lists and found that both classifiers exhibited similar performance. We found that list-level classifier output—a biomarker of successful encoding—tracked item presentation and recall events, despite having no information about the trial structure. Across widespread brain regions, decreased low- and increased high-frequency activity (HFA) marked successful encoding of both items and lists. We found regional differences in the hippocampus and prefrontal cortex, where in the hippocampus HFA correlated more strongly with item recall, whereas in the prefrontal cortex HFA correlated more strongly with list performance. Despite subtle differences in item- and list-level features, the similarity in overall classification performance, spectral signatures of successful recall, and fluctuations of spectral activity across the encoding period argue for a shared endogenous process that causally impacts the brain’s ability to learn new information.

Standard-of-care biological treatment of schizophrenia remains dependent upon antipsychotic medications, which demonstrate D₂ receptor affinity and elicit variable, partial clinical responses via neural mechanisms that are not entirely understood. In the striatum, where D₂ receptors are abundant, antipsychotic medications may affect neural function in studies of animals, healthy volunteers, and patients, yet the relevance of this to pharmacotherapeutic actions remains unresolved. In this same brain region, some individuals with schizophrenia may demonstrate phenotypes consistent with exaggerated dopaminergic signaling, including alterations in dopamine synthesis capacity; however, the hypothesis that dopamine system characteristics underlie variance in medication-induced regional blood flow changes has not been directly tested. We therefore studied a cohort of 30 individuals with schizophrenia using longitudinal, multi-session [¹⁵O]-water and [¹⁸F]-FDOPA positron emission tomography to determine striatal blood flow during active atypical antipsychotic medication treatment and after at least 3 weeks of placebo treatment, along with presynaptic dopamine synthesis capacity (ie, DOPA decarboxylase activity). Regional striatal blood flow was significantly higher during active treatment than during the placebo condition. Furthermore, medication-related increases in ventral striatal blood flow were associated with more robust amelioration of excited factor symptoms during active medication and with higher dopamine synthesis capacity. These data indicate that atypical medications enact measureable physiological alterations in limbic striatal circuitry that vary as a function of dopaminergic tone and may have relevance to aspects of therapeutic responses.