Epilepsy has been classically seen as a brain disorder resulting from abnormally enhanced neuronal excitability and synchronization. Although it has been described since antiquity, there are still significant challenges achieving the therapeutic goal of seizure freedom. Deep brain stimulation of the anterior nucleus of the thalamus has emerged as a promising therapy for focal drug-resistant epilepsy; the basic mechanism of action, however, remains unclear. Here, we show that desynchronization is a potential mechanism of deep brain stimulation of the anterior nucleus of the thalamus by studying local field potentials recordings from the cortex during high-frequency stimulation (130 Hz) of the anterior nucleus of the thalamus in nine patients with drug-resistant focal epilepsy. We demonstrate that high-frequency stimulation applied to the anterior nucleus of the thalamus desynchronizes ipsilateral hippocampal background electrical activity over a broad frequency range, and reduces pathological epileptic discharges including interictal spikes and high-frequency oscillations. Furthermore, high-frequency stimulation of the anterior nucleus of the thalamus is capable of decoupling large-scale neural activity involving the hippocampus and distributed cortical areas. We found that stimulation frequencies ranging from 15 to 45 Hz were associated with synchronization of hippocampal local field potentials, whereas higher frequencies (>45 Hz) promoted desynchronization of ipsilateral hippocampal activity. Moreover, reciprocal effective connectivity between the anterior nucleus of the thalamus and the hippocampus was demonstrated by hippocampal-thalamic evoked potentials and thalamic-hippocampal evoked potentials. In summary, high-frequency stimulation of the anterior nucleus of the thalamus is shown to desynchronize focal and large-scale epileptic networks, and here is proposed as the mechanism for reducing seizure generation and propagation. Our data also demonstrate position-specific correlation between deep brain stimulation applied to the anterior nucleus of the thalamus and patients with temporal lobe epilepsy and seizure onset zone within the Papaz circuit or limbic system. Our observation may prove useful for guiding electrode implantation to increase clinical efficacy.

BACKGROUND AND PURPOSE:Olfactory dysfunction is commonly associated with IPD. We here report the association of OB volume and OS depth with olfactory function in patients with PD.

Visual short-term memory (VSTM) enables humans to form a stable and coherent representation of the external world. However, the nature and temporal dynamics of the neural representations in VSTM that support this stability are barely understood. Here we combined human intracranial electroencephalography (iEEG) recordings with analyses using deep neural networks and semantic models to probe the representational format and temporal dynamics of information in VSTM. We found clear evidence that VSTM maintenance occurred in two distinct representational formats which originated from different encoding periods. The first format derived from an early encoding period (250 to 770 ms) corresponded to higher-order visual representations. The second format originated from a late encoding period (1,000 to 1,980 ms) and contained abstract semantic representations. These representational formats were overall stable during maintenance, with no consistent transformation across time. Nevertheless, maintenance of both representational formats showed substantial arrhythmic fluctuations, i.e., waxing and waning in irregular intervals. The increases of the maintained representational formats were specific to the phases of hippocampal low-frequency activity. Our results demonstrate that human VSTM simultaneously maintains representations at different levels of processing, from higher-order visual information to abstract semantic representations, which are stably maintained via coupling to hippocampal low-frequency activity.

Memory is often conceived as a dynamic process that involves substantial transformations of mental representations. However, the neural mechanisms underlying these transformations and their role in memory formation and retrieval have only started to be elucidated. Combining intracranial EEG recordings with deep neural network models, we provide a detailed picture of the representational transformations from encoding to short-term memory maintenance and long-term memory retrieval that underlie successful episodic memory. We observed substantial representational transformations during encoding. Critically, more pronounced semantic representational formats predicted better subsequent long-term memory, and this effect was mediated by more consistent item-specific representations across encoding events. The representations were further transformed right after stimulus offset, and the representations during long-term memory retrieval were more similar to those during short-term maintenance than during encoding. Our results suggest that memory representations pass through multiple stages of transformations to achieve successful long-term memory formation and recall.

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