UNLABELLED: Schizophrenia is a complex disorder characterized by altered brain functional connectivity, detectable during both task and resting state conditions using different neuroimaging methods. To this day, electroencephalography (EEG) studies have reported inconsistent results, showing both hyper- and hypo-connectivity with diverse topographical distributions. Interpretation of these findings is complicated by volume-conduction effects, where local brain activity fluctuations project simultaneously to distant scalp regions (zero-phase lag), inducing spurious inter-electrode correlations. AIM: In the present study, we explored the network dynamics of schizophrenia using a novel functional connectivity metric-corrected imaginary phase locking value (ciPLV)-which is insensitive to changes in amplitude as well as interactions at zero-phase lag. This method, which is less prone to volume conduction effects, provides a more reliable estimate of sensor-space functional network connectivity in schizophrenia. METHODS: We employed a cross-sectional design, utilizing resting state EEG recordings from two adult groups: individuals diagnosed with chronic schizophrenia (n = 30) and a control group of healthy participants (n = 30), all aged between 18 and 55 years old. RESULTS: Our observations revealed that schizophrenia is characterized by a prevalence of excess theta (4-8 Hz) power localized to centroparietal electrodes. This was accompanied by significant alterations in inter- and intra-hemispheric functional network connectivity patterns, mainly between frontotemporal regions within the theta band and frontoparietal regions within beta/gamma bands. CONCLUSIONS: Our findings suggest that patients with schizophrenia demonstrate long-range electrophysiological connectivity abnormalities that are independent of spectral power (i.e., volume conduction). Overall, distinct hemispheric differences were present in frontotemporo-parietal networks in theta and beta/gamma bands. While preliminary, these alterations could be promising new candidate biomarkers of chronic schizophrenia.

• Klíčová slova
• EEG, functional connectivity, phase locking value, power spectrum, resting‐state, schizophrenia,
• MeSH
• chronická nemoc MeSH
• dospělí MeSH
• elektroencefalografie * metody   MeSH
• lidé středního věku MeSH
• lidé MeSH
• mladiství MeSH
• mladý dospělý MeSH
• mozek patofyziologie   diagnostické zobrazování   MeSH
• nervová síť patofyziologie   diagnostické zobrazování   MeSH
• odpočinek fyziologie   MeSH
• průřezové studie MeSH
• schizofrenie * patofyziologie   diagnostické zobrazování   MeSH
• Check Tag
• dospělí MeSH
• lidé středního věku MeSH
• lidé MeSH
• mladiství MeSH
• mladý dospělý MeSH
• mužské pohlaví MeSH
• ženské pohlaví MeSH
• Publikační typ
• časopisecké články MeSH

In driven nonlinear systems, phase locking is an intriguing effect leading to robust stationary states that are stable over extended ranges of control parameters. Recent experiments allow for exploring microscopic mechanisms underlying such phenomena in collective dynamics of micro- and nanoparticles. Here, we show that phase-locked dynamics of hardcore-interacting microparticles in a densely populated periodic potential under time-periodic driving arises from running solitary cluster waves. We explain how values of phase-locked currents are related to soliton velocities and why collective particle dynamics synchronize with the driving for certain particle diameters only. Our analysis is based on an effective potential for the solitary wave propagation and a unit displacement law, which states that the total average shift of all particle positions per soliton period equals one wavelength of the periodic potential.

• Publikační typ
• časopisecké články MeSH

INTRODUCTION: Intracranial EEG (iEEG) data is a powerful way to map brain function, characterized by high temporal and spatial resolution, allowing the study of interactions among neuronal populations that orchestrate cognitive processing. However, the statistical inference and analysis of brain networks using iEEG data faces many challenges related to its sparse brain coverage, and its inhomogeneity across patients. METHODS: We review these challenges and develop a methodological pipeline for estimation of network structure not obtainable from any single patient, illustrated on the inference of the interaction among visual streams using a dataset of 27 human iEEG recordings from a visual experiment employing visual scene stimuli. 100 ms sliding window and multiple band-pass filtered signals are used to provide temporal and spectral resolution. For the connectivity analysis we showcase two connectivity measures reflecting different types of interaction between regions of interest (ROI): Phase Locking Value as a symmetric measure of synchrony, and Directed Transfer Function-asymmetric measure describing causal interaction. For each two channels, initial uncorrected significance testing at p < 0.05 for every time-frequency point is carried out by comparison of the data-derived connectivity to a baseline surrogate-based null distribution, providing a binary time-frequency connectivity map. For each ROI pair, a connectivity density map is obtained by averaging across all pairs of channels spanning them, effectively agglomerating data across relevant channels and subjects. Finally, the difference of the mean map value after and before the stimulation is compared to the same statistic in surrogate data to assess link significance. RESULTS: The analysis confirmed the function of the parieto-medial temporal pathway, mediating visuospatial information between dorsal and ventral visual streams during visual scene analysis. Moreover, we observed the anterior hippocampal connectivity with more posterior areas in the medial temporal lobe, and found the reciprocal information flow between early processing areas and medial place area. DISCUSSION: To summarize, we developed an approach for estimating network connectivity, dealing with the challenge of sparse individual coverage of intracranial EEG electrodes. Its application provided new insights into the interaction between the dorsal and ventral visual streams, one of the iconic dualities in human cognition.

• Klíčová slova
• Directed Transfer Function, Phase Locking Value, connectivity analysis, dorsal visual stream, information flow, intracranial EEG, ventral visual stream, visual pathways,
• Publikační typ
• časopisecké články MeSH

The dorsal and ventral visual streams have been considered to play distinct roles in visual processing for action: the dorsal stream is assumed to support real-time actions, while the ventral stream facilitates memory-guided actions. However, recent evidence suggests a more integrated function of these streams. We investigated the neural dynamics and functional connectivity between them during memory-guided actions using intracranial EEG. We tracked neural activity in the inferior parietal lobule in the dorsal stream, and the ventral temporal cortex in the ventral stream as well as the hippocampus during a delayed action task involving object identity and location memory. We found increased alpha power in both streams during the delay, indicating their role in maintaining spatial visual information. In addition, we recorded increased alpha power in the hippocampus during the delay, but only when both object identity and location needed to be remembered. We also recorded an increase in theta band phase synchronization between the inferior parietal lobule and ventral temporal cortex and between the inferior parietal lobule and hippocampus during the encoding and delay. Granger causality analysis indicated dynamic and frequency-specific directional interactions among the inferior parietal lobule, ventral temporal cortex, and hippocampus that varied across task phases. Our study provides unique electrophysiological evidence for close interactions between dorsal and ventral streams, supporting an integrated processing model in which both streams contribute to memory-guided actions.

• Klíčová slova
• Alpha oscillations, Dorsal visual stream, Granger causality analysis, Intracranial EEG, Memory-guided actions, Phase-locking value, Theta oscillations, Ventral visual stream,
• Publikační typ
• časopisecké články MeSH

Comb Coherence Transfer (CCT) uses a feed-forward frequency correction to transfer the optical phase of a frequency comb to the beam of a free-running diode laser. This allows the amplification of a selected comb tooth by 50 dB while adding agile and accurate frequency tuning. In the present work, SI-traceable frequency calibration and comb tooth narrowing down to 20 kHz is additionally provided by comb frequency locking to an ultrastable optical frequency reference distributed from Paris to Grenoble through the RENATER optical fiber network [Lisdat et al., Nat. Commun., 2016, 7, 12443]. We apply this CCT broadly tunable source for saturated cavity ring-down spectroscopy of ro-vibrational R0 to R10 multiplets in the 2ν3 band of 12CH4 (from 6015 to 6115 cm-1). Indeed, efficient cavity injection with large intra-cavity power build-up induces saturation of the ro-vibrational transitions at low pressure and Doppler-free Lamb dips are observed with high signal/noise. kHz-accurate transition frequencies are derived improving by three orders of magnitude previous values from spectra in the Doppler regime, which are strongly affected by line blending. While previous saturation spectroscopy investigations addressed specific 2ν3 multiplets (R6 or R9), the CCT approach allowed for a rapid coverage of the entire R0-R10 series. Measured transition frequencies are compared with experimental and theoretical line lists available in the literature.

• Publikační typ
• časopisecké články MeSH