Navegando por Autor "Souza, Bryan C."
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Artigo Asymmetry of the temporal code for space by hippocampal place cells(2017-08-17) Souza, Bryan C.; Tort, Adriano Bretanha LopesHippocampal place cells convey spatial information through spike frequency (“rate coding”) and spike timing relative to the theta phase (“temporal coding”). Whether rate and temporal coding are due to independent or related mechanisms has been the subject of wide debate. Here we show that the spike timing of place cells couples to theta phase before major increases in firing rate, anticipating the animal’s entrance into the classical, rate-based place field. In contrast, spikes rapidly decouple from theta as the animal leaves the place field and firing rate decreases. Therefore, temporal coding has strong asymmetry around the place field center. We further show that the dynamics of temporal coding along space evolves in three stages as the animal traverses the place field: phase coupling, sharp precession and phase decoupling. These results suggest that independent mechanisms may govern rate and temporal coding.Artigo Dream characteristics in a Brazilian sample: an online survey focusing on lucid dreaming(2013-12) Rolim, Sérgio A. Mota; Targino, Zé H.; Souza, Bryan C.; Blanco, Wilfredo; Araujo, John F.; Ribeiro, SidartaDuring sleep, humans experience the offline images and sensations that we call dreams, which are typically emotional and lacking in rational judgment of their bizarreness. However, during lucid dreaming (LD), subjects know that they are dreaming, and may control oneiric content. Dreaming and LD features have been studied in North Americans, Europeans and Asians, but not among Brazilians, the largest population in Latin America. Here we investigated dreams and LD characteristics in a Brazilian sample (n = 3,427; median age = 25 years) through an online survey. The subjects reported recalling dreams at least once a week (76%), and that dreams typically depicted actions (93%), known people (92%), sounds/voices (78%), and colored images (76%). The oneiric content was associated with plans for the upcoming days (37%), memories of the previous day (13%), or unrelated to the dreamer (30%). Nightmares usually depicted anxiety/fear (65%), being stalked (48%), or other unpleasant sensations (47%). These data corroborate Freudian notion of day residue in dreams, and suggest that dreams and nightmares are simulations of life situations that are related to our psychobiological integrity. Regarding LD, we observed that 77% of the subjects experienced LD at least once in life (44% up to 10 episodes ever), and for 48% LD subjectively lasted less than 1 min. LD frequency correlated weakly with dream recall frequency (r = 0.20, p < 0.01), and LD control was rare (29%). LD occurrence was facilitated when subjects did not need to wake up early (38%), a situation that increases rapid eye movement sleep (REMS) duration, or when subjects were under stress (30%), which increases REMS transitions into waking. These results indicate that LD is relatively ubiquitous but rare, unstable, difficult to control, and facilitated by increases in REMS duration and transitions to wake state. Together with LD incidence in USA, Europe and Asia, our data from Latin America strengthen the notion that LD is a general phenomenon of the human species.Artigo Dream characteristics in a Brazilian sample: an online survey focusing on lucid dreaming(Frontiers in Human Neuroscience, 2013-12-10) Mota-Rolim, Sérgio A.; Targino, Zé H.; Souza, Bryan C.; Blanco, Wilfredo; Araujo, John F.; Ribeiro, Sidarta Tollendal GomesArtigo Implementação de classificador de tarefas mentais baseado em EEG(Sociedade Brasileira de Redes Neurais, 2009-10) Medeiros, Adelardo Adelino Dantas de; Barbosa, André Freitas; Souza, Bryan C.; Pereira Júnior, AntônioArtigo On information metrics for spatial coding(2018-04-01) Souza, Bryan C.; Pavão, Rodrigo; Belchior, Hindiael; Tort, Adriano Bretanha LopesThe hippocampal formation is involved in navigation, and its neuronal activity exhibits a variety of spatial correlates (e.g., place cells, grid cells). The quantification of the information encoded by spikes has been standard procedure to identify which cells have spatial correlates. For place cells, most of the established metrics derive from Shannon's mutual information (Shannon, 1948), and convey information rate in bits/s or bits/spike (Skaggs et al., 1993, 1996). Despite their widespread use, the performance of these metrics in relation to the original mutual information metric has never been investigated. In this work, using simulated and real data, we find that the current information metrics correlate less with the accuracy of spatial decoding than the original mutual information metric. We also find that the top informative cells may differ among metrics, and show a surrogate-based normalization that yields comparable spatial information estimates. Since different information metrics may identify different neuronal populations, we discuss current and alternative definitions of spatially informative cells, which affect the metric choice.Artigo Spike sorting with Gaussian mixture models(2019-03-06) Souza, Bryan C.; Lopes-dos-Santos, Vítor; Bacelo, João; Tort, Adriano Bretanha LopesThe shape of extracellularly recorded action potentials is a product of several variables, such as the biophysical and anatomical properties of the neuron and the relative position of the electrode. This allows isolating spikes of different neurons recorded in the same channel into clusters based on waveform features. However, correctly classifying spike waveforms into their underlying neuronal sources remains a challenge. This process, called spike sorting, typically consists of two steps: (1) extracting relevant waveform features (e.g., height, width), and (2) clustering them into non-overlapping groups believed to correspond to different neurons. In this study, we explored the performance of Gaussian mixture models (GMMs) in these two steps. We extracted relevant features using a combination of common techniques (e.g., principal components, wavelets) and GMM fitting parameters (e.g., Gaussian distances). Then, we developed an approach to perform unsupervised clustering using GMMs, estimating cluster properties in a data-driven way. We found the proposed GMM-based framework outperforms previously established methods in simulated and real extracellular recordings. We also discuss potentially better techniques for feature extraction than the widely used principal components. Finally, we provide a friendly graphical user interface to run our algorithm, which allows manual adjustments.Artigo Theta-associated high-frequency oscillations (110–160 Hz) in the hippocampus and neocortex(2013) Tort, Adriano Bretanha Lopes; Scheffer-Teixeira, Robson; Souza, Bryan C.; Draguhn, Andreas; Brankacˇk, JurijArtigo Theta-phase modulates different high-frequency oscillations in the CA1 region of the hippocampus during both waking and rapid-eye movement sleep.(2010-09) Teixeira, Robson Scheffer; Souza, Bryan C.; Belchior, Hindiael; Ribeiro, Sidarta Tollendal Gomes; Tort, Adriano Bretanha LopesRecent evidence suggests that not only the brain rhythms per se, but also the interactions among them are involved in the execution of cognitive tasks, mainly those requiring selective attention, information transmission and memory consolidation. However, still little is known about the general characteristics of cross-frequency coupling (CFC) in several brain regions. In the present work, we aimed to characterize phase-amplitude CFC in the CA1 region of rats (n=9) during different stages of the sleep-wake cycle: wake (WK), slow-wave sleep (SWS), and rapid-eye movement sleep (REM). Local field potentials were recorded using multielectrode arrays implanted in the dorsal hippocampus for chronic neural recordings. Electrode positioning was verified by histological analysis of cresyl-stained brain sections. Phase-amplitude coupling was assessed by means of the comodulogram analysis, a CFC tool we have recently developed. Our results show that (1) each sleep-wake state contains characteristic patterns of phase-amplitude CFC that are robust across all animals studied. (2) The CFC patterns obtained during WK and REM are similar and characterized by theta-phase (5 – 10 Hz) modulation of multiple higher frequencies; on the other hand, comodulograms from SWS period exhibited a distinct pattern, characterized by the modulation of very fast oscillations (> 100 Hz) by delta-phase (0 – 4 Hz), consistent with the occurrence of sharp wave-ripple complexes. All these patterns were stable across electrodes and days. Interestingly, during WK and REM, our results indicate that (3) theta-phase modulation comprises two non-overlapping, circumscribed higher frequency ranges: oscillations in the high-gamma (HG, 60 – 100 Hz) frequency range and oscillations between 120 – 160 Hz, which were defined as high-frequency oscillations (HFO). Moreover, (4) theta-phase preferentially modulated more HG or HFO depending on the spatial position of the electrode, with a clear switching between one and another as a function of electrode location, which was also stable across days. Further analyses indicated that (5) electrodes exhibiting HG or HFO modulation during WK and REM can also be differentiated by other electrophysiological features, such as power spectrum, phase-relations, and SWS comodulograms. We argue that the HFO we observed, though presenting overlapping frequency range with ripple oscillations, are distinct from the latter, which only appear in periods of rest and sleep associated to sharp-wave complexes. Therefore, while characterizing the patterns of rhythmic interactions in different cognitive states, the present work also reveals novel hippocampal oscillations that could only be detected by the use of the new CFC tools. We speculate that the different amplitude-modulated bands correspond to different biophysical processes occurring in CA1: HFO would result from entorhinal synaptic inputs to CA1, and HG from CA3 inputs.