The role of cortical beta oscillations in time estimation.

Estimation of time is central to perception, action, and cognition. Human functional magnetic resonance imaging (fMRI) and positron emission topography (PET) have revealed a positive correlation between the estimation of multi-second temporal durations and neuronal activity in a circuit of sensory and motor areas, prefrontal and temporal cortices, basal ganglia, and cerebellum. The systems-level mechanisms coordinating the collective neuronal activity in these areas have remained poorly understood. Synchronized oscillations regulate communication in neuronal networks and could hence serve such coordination, but their role in the estimation and maintenance of multi-second time intervals has remained largely unknown. We used source-reconstructed magnetoencephalography (MEG) to address the functional significance of local neuronal synchronization, as indexed by the amplitudes of cortical oscillations, in time-estimation. MEG was acquired during a working memory (WM) task where the subjects first estimated and then memorized the durations, or in the contrast condition, the colors of dynamic visual stimuli. Time estimation was associated with stronger beta (ß, 14 - 30 Hz) band oscillations than color estimation in sensory regions and attentional cortical structures that earlier have been associated with time processing. In addition, the encoding of duration information was associated with strengthened gamma- (γ, 30 - 120 Hz), and the retrieval and maintenance with alpha- (α, 8 - 14 Hz) band oscillations. These data suggest that ß oscillations may provide a mechanism for estimating short temporal durations, while γ and α oscillations support their encoding, retrieval, and maintenance in memory. Hum Brain Mapp 37:3262-3281, 2016. © 2016 Wiley Periodicals, Inc.

Automatic segmentation of deep intracerebral electrodes in computed tomography scans.

BACKGROUND: Invasive monitoring of brain activity by means of intracerebral electrodes is widely practiced to improve pre-surgical seizure onset zone localization in patients with medically refractory seizures. Stereo-Electroencephalography (SEEG) is mainly used to localize the epileptogenic zone and a precise knowledge of the location of the electrodes is expected to facilitate the recordings interpretation and the planning of resective surgery. However, the localization of intracerebral electrodes on post-implant acquisitions is usually time-consuming (i.e., manual segmentation), it requires advanced 3D visualization tools, and it needs the supervision of trained medical doctors in order to minimize the errors. In this paper we propose an automated segmentation algorithm specifically designed to segment SEEG contacts from a thresholded post-implant Cone-Beam CT volume (0.4 mm, 0.4 mm, 0.8 mm). The algorithm relies on the planned position of target and entry points for each electrode as a first estimation of electrode axis. We implemented the proposed algorithm into DEETO, an open source C++ prototype based on ITK library. RESULTS: We tested our implementation on a cohort of 28 subjects in total. The experimental analysis, carried out over a subset of 12 subjects (35 multilead electrodes; 200 contacts) manually segmented by experts, show that the algorithm: (i) is faster than manual segmentation (i.e., less than 1s/subject versus a few hours) (ii) is reliable, with an error of 0.5 mm ± 0.06 mm, and (iii) it accurately maps SEEG implants to their anatomical regions improving the interpretability of electrophysiological traces for both clinical and research studies. Moreover, using the 28-subject cohort we show here that the algorithm is also robust (error < 0.005 mm) against deep-brain displacements (< 12 mm) of the implanted electrode shaft from those planned before surgery. CONCLUSIONS: Our method represents, to the best of our knowledge, the first automatic algorithm for the segmentation of SEEG electrodes. The method can be used to accurately identify the neuroanatomical loci of SEEG electrode contacts by a non-expert in a fast and reliable manner.