Research on dance interventions (DIs) in the elderly has shown promising benefits to physical and cognitive outcomes. The effect of DIs on resting-state functional connectivity (rs-FC) varies, which is possibly due to individual variability. In this study, we assessed the moderation effects of residual cognitive reserve (CR) on DI-induced changes in dynamic rs-FC and their association on cognitive outcomes. Dynamic rs-FC (rs-dFC) and cognitive functions were evaluated in non-demented elderly subjects before and after a 6-month DI (n = 36) and a control group, referred to as the life-as-usual (LAU) group (n = 32). Using linear mixed models and moderation, we examined the interaction effect of DIs and CR on changes in the dwell time and coverage of rs-dFC. Cognitive reserve was calculated as the residual difference between the observed memory performance and the performance predicted by brain state. Partial correlations accounting for CR evaluated the unique association between changes in rs-dFC and cognition in the DI group. In subjects with lower residual CR, we observed DI-induced increases in dwell time [t(58) = -2.14, p = 0.036] and coverage [t(58) = -2.22, p = 0.030] of a rs-dFC state, which was implicated in bottom-up information processing. Increased dwell time was also correlated with a DI-induced improvement in Symbol Search (r = 0.42, p = 0.02). In subjects with higher residual CR, we observed a DI-induced increase in coverage [t(58) = 2.11, p = 0.039] of another rs-dFC state, which was implicated in top-down information processing. The study showed that DIs have a differential and behaviorally relevant effect on dynamic rs-dFC, but these benefits depend on the current CR level.

• Klíčová slova
• attention, bottom-up processing, cognitive reserve, coverage, dance intervention, dwell time, dynamic resting-state functional connectivity, top-down processing,
• Publikační typ
• časopisecké články MeSH

To identify the neurocognitive mechanisms underpinning the social difficulties that characterize autism, we performed functional magnetic resonance imaging on pairs of autistic and non-autistic adults simultaneously whilst they interacted with one another on the iterated Ultimatum Game (iUG)-an interactive task that emulates the reciprocal characteristic of naturalistic interpersonal exchanges. Two age-matched sets of male-male dyads were investigated: 16 comprised an autistic Responder and a non-autistic Proposer, and 19 comprised non-autistic pairs of Responder and Proposer. Players' round-by-round behavior on the iUG was modeled as reciprocal choices, and dynamic functional connectivity (dFC) was measured to identify the neural mechanisms underpinning reciprocal behaviors. Behavioral expressions of reciprocity were significantly reduced in autistic compared with non-autistic Responders, yet no such differences were observed between the non-autistic Proposers in either set of dyads. Furthermore, we identified latent dFC states with temporal properties associated with reciprocity. Autistic interactants spent less time in brain states characterized by dynamic inter-network integration and segregation among the Default Mode Network and cognitive control networks, suggesting that their reduced expressions of social-emotional reciprocity reflect less efficient reconfigurations among brain networks supporting flexible cognition and behavior. These findings advance our mechanistic understanding of the social difficulties characterizing autism.

• Klíčová slova
• autism, dynamic functional connectivity, reciprocity, social interaction,
• MeSH
• autistická porucha * patofyziologie   psychologie   diagnostické zobrazování   MeSH
• dospělí MeSH
• emoce * fyziologie   MeSH
• interpersonální vztahy * MeSH
• lidé MeSH
• magnetická rezonanční tomografie MeSH
• mladý dospělý MeSH
• mozek * patofyziologie   diagnostické zobrazování   MeSH
• sociální chování * MeSH
• sociální interakce * MeSH
• Check Tag
• dospělí MeSH
• lidé MeSH
• mladý dospělý MeSH
• mužské pohlaví MeSH
• Publikační typ
• časopisecké články MeSH
• práce podpořená grantem MeSH

We spend much our lives interacting with others in various social contexts. Although we deal with this myriad of interpersonal exchanges with apparent ease, each one relies upon a broad array of sophisticated cognitive processes. Recent research suggests that the cognitive operations supporting interactive behaviour are themselves underpinned by several canonical functional brain networks (CFNs) that integrate dynamically with one another in response to changing situational demands. Dynamic integrations among these CFNs should therefore play a pivotal role in coordinating interpersonal behaviour. Further, different types of interaction should present different demands on cognitive systems, thereby eliciting distinct patterns of dynamism among these CFNs. To investigate this, the present study performed functional magnetic resonance imaging (fMRI) on 30 individuals while they interacted with one another cooperatively or competitively. By applying a novel combination of analytical techniques to these brain imaging data, we identify six states of dynamic functional connectivity characterised by distinct patterns of integration and segregation among specific CFNs that differ systematically between these opposing types of interaction. Moreover, applying these same states to fMRI data acquired from an independent sample engaged in the same kinds of interaction, we were able to classify interpersonal exchanges as cooperative or competitive. These results provide the first direct evidence for the systematic involvement of CFNs during social interactions, which should guide neurocognitive models of interactive behaviour and investigations into biomarkers for the interpersonal dysfunction characterizing many neurological and psychiatric disorders.

• Klíčová slova
• Canonical brain networks, Competition, Cooperation, Dynamic functional connectivity, Social interaction,
• MeSH
• duševní poruchy * MeSH
• lidé MeSH
• magnetická rezonanční tomografie metody   MeSH
• mapování mozku MeSH
• mozek fyziologie   MeSH
• sociální interakce * MeSH
• Check Tag
• lidé MeSH
• Publikační typ
• časopisecké články MeSH
• práce podpořená grantem MeSH

BACKGROUND: Posttraumatic stress disorder (PTSD) and mild traumatic brain injury (mTBI) are associated with alterations in the functional connectome, specifically in canonical resting state networks including the default mode (DMN), central executive (CEN), and salience networks (SN). Comorbid PTSD+mTBI is linked to worse functional outcomes, but little is known about effects on the functional connectome. METHODS: We investigated brain phenotypes from resting-state fMRI associated with PTSD (n=326), mTBI (n=448), and comorbid PTSD+mTBI (n=289) in military veterans and civilians (n=1526) from ENIGMA-TBI and -PTSD. We examined static functional connectivity (SFC) and dynamic functional connectivity (DFC), quantified both as variability in FC (VFC) over time and as dwell time in recurring FC states identified through clustering. ANCOVA was followed by post-hoc linear regression to test main and interaction effects of diagnosis on FC metrics. RESULTS: We found a significant (pFDR<0.05) interaction of diagnosis by age on VFC. Older comorbid subjects had greater VFC within SN, between SN-to-CEN and SN-to-DMN than older controls. Comorbid relative to control subjects had significantly greater dwell time in an externally focused state. Comorbid and mTBI groups, relative to control subjects, had greater dwell time in a moderate connectivity transition state. CONCLUSIONS: DFC related to the SN revealed distinct brain network patterns across diagnostic groups, with comorbid PTSD+mTBI showing age- and anxiety-related effects. Older comorbid subjects had heightened hypervigilance and reduced network segregation. PTSD and anxiety may synergistically worsen network instability, while mTBI reflects more rigid, disconnected states, highlighting DFC as a sensitive marker of neuropsychiatric comorbidity.

• Klíčová slova
• Canonical Networks, Comorbid PTSD and mTBI, Dynamic Functional Connectivity, Military Veterans, PTSD, Resting-state fMRI, Static Functional Connectivity, mTBI,
• Publikační typ
• časopisecké články MeSH

BACKGROUND: Cannabis, and specifically one of its active compounds delta-9-tetrahydrocannabinol in recreational doses, has a variety of effects on cognitive processes. Most studies employ resting state functional magnetic resonance imaging techniques to assess the stationary effects of cannabis and to-date one report addressed the impact of delta-9-tetrahydrocannabinol on the dynamics of whole-brain functional connectivity. METHODS: Using a repeated-measures, within-subjects design, 19 healthy occasional cannabis users (smoking cannabis ⩽2 per week) underwent resting state functional magnetic resonance imaging scans. Each subject underwent two scans: in the intoxicated condition, shortly after smoking a cannabis cigarette, and in the non-intoxicated condition, with the subject being free from cannabinoids for at least one week before. All sessions were randomized and performed in a four-week interval. Data were analysed employing a standard independent component analysis approach with subsequent tracking of the functional connectivity dynamics, which allowed six connectivity clusters (states) to be individuated. RESULTS: Using standard independent component analysis in resting state functional connectivity, a group effect was found in the precuneus connectivity. With a dynamic independent component analysis approach, we identified one transient connectivity state, characterized by high connectivity within and between auditory and somato-motor cortices and anti-correlation with subcortical structures and the cerebellum that was only found during the intoxicated condition. Behavioural measures of the subjective experiences of changed perceptions and tetrahydrocannabinol plasma levels during intoxication were associated with this state. CONCLUSIONS: With the help of the dynamic connectivity approach we could elucidate neural correlates of the transitory perceptual changes induced by delta-9-tetrahydrocannabinol in cannabis users, and possibly identify a biomarker of cannabis intoxication.

• Klíčová slova
• Cannabis, altered states of consciousness, dynamic functional connectivity, resting state networks, tetrahydrocannabinol,
• MeSH
• dospělí MeSH
• halucinogeny farmakologie   MeSH
• kouření marihuany psychologie   MeSH
• lidé MeSH
• magnetická rezonanční tomografie MeSH
• mladý dospělý MeSH
• mozek diagnostické zobrazování   účinky léků   MeSH
• tetrahydrokanabinol farmakologie   MeSH
• Check Tag
• dospělí MeSH
• lidé MeSH
• mladý dospělý MeSH
• mužské pohlaví MeSH
• ženské pohlaví MeSH
• Publikační typ
• časopisecké články MeSH
• práce podpořená grantem MeSH
• randomizované kontrolované studie MeSH
• Research Support, N.I.H., Extramural MeSH
• Názvy látek
• halucinogeny MeSH
• tetrahydrokanabinol MeSH

Increasing interest in understanding dynamic interactions of brain neural networks leads to formulation of sophisticated connectivity analysis methods. Recent studies have applied Granger causality based on standard multivariate autoregressive (MAR) modeling to assess the brain connectivity. Nevertheless, one important flaw of this commonly proposed method is that it requires the analyzed time series to be stationary, whereas such assumption is mostly violated due to the weakly nonstationary nature of functional magnetic resonance imaging (fMRI) time series. Therefore, we propose an approach to dynamic Granger causality in the frequency domain for evaluating functional network connectivity in fMRI data. The effectiveness and robustness of the dynamic approach was significantly improved by combining a forward and backward Kalman filter that improved estimates compared to the standard time-invariant MAR modeling. In our method, the functional networks were first detected by independent component analysis (ICA), a computational method for separating a multivariate signal into maximally independent components. Then the measure of Granger causality was evaluated using generalized partial directed coherence that is suitable for bivariate as well as multivariate data. Moreover, this metric provides identification of causal relation in frequency domain, which allows one to distinguish the frequency components related to the experimental paradigm. The procedure of evaluating Granger causality via dynamic MAR was demonstrated on simulated time series as well as on two sets of group fMRI data collected during an auditory sensorimotor (SM) or auditory oddball discrimination (AOD) tasks. Finally, a comparison with the results obtained from a standard time-invariant MAR model was provided.

• MeSH
• algoritmy * MeSH
• dospělí MeSH
• interpretace obrazu počítačem metody   MeSH
• lidé MeSH
• magnetická rezonanční tomografie metody   MeSH
• nervová síť fyziologie   MeSH
• počítačové zpracování signálu MeSH
• reprodukovatelnost výsledků MeSH
• senzitivita a specificita MeSH
• sluchová percepce fyziologie   MeSH
• sluchové evokované potenciály fyziologie   MeSH
• sluchové korové centrum fyziologie   MeSH
• vylepšení obrazu metody   MeSH
• Check Tag
• dospělí MeSH
• lidé MeSH
• mužské pohlaví MeSH
• ženské pohlaví MeSH
• Publikační typ
• časopisecké články MeSH
• Research Support, N.I.H., Extramural MeSH

Transcranial direct current stimulation (tDCS) has the potential to modulate cognitive training in healthy aging; however, results from various studies have been inconsistent. We hypothesized that inter-individual differences in baseline brain state may contribute to the varied results. We aimed to explore whether baseline resting-state dynamic functional connectivity (rs-dFC) and/or conventional resting-state static functional connectivity (rs-sFC) may be related to the magnitude of cognitive aftereffects of tDCS. To achieve this aim, we used data from our double-blind randomized sham-controlled cross-over tDCS trial in 25 healthy seniors in which bifrontal tDCS combined with cognitive training had induced significant behavioral aftereffects. We performed a backward regression analysis including rs-sFC/rs-dFC measures to explain the variability in the magnitude of tDCS-induced improvements in visual object-matching task (VOMT) accuracy. Rs-dFC analysis revealed four rs-dFC states. The occurrence rate of a rs-dFC state 4, characterized by a high correlation between the left fronto-parietal control network and the language network, was significantly associated with tDCS-induced VOMT accuracy changes. The rs-sFC measure was not significantly associated with the cognitive outcome. We show that flexibility of the brain state representing readiness for top-down control of object identification implicated in the studied task is linked to the tDCS-enhanced task accuracy.

• MeSH
• individualita MeSH
• kognice MeSH
• lidé MeSH
• mozek MeSH
• přímá transkraniální stimulace mozku * MeSH
• progrese nemoci MeSH
• Check Tag
• lidé MeSH
• Publikační typ
• časopisecké články MeSH
• práce podpořená grantem MeSH
• randomizované kontrolované studie MeSH

OBJECTIVE: Growing interest in the examination of large-scale brain network functional connectivity dynamics is accompanied by an effort to find the electrophysiological correlates. The commonly used constraints applied to spatial and spectral domains during electroencephalogram (EEG) data analysis may leave part of the neural activity unrecognized. We propose an approach that blindly reveals multimodal EEG spectral patterns that are related to the dynamics of the BOLD functional network connectivity. APPROACH: The blind decomposition of EEG spectrogram by parallel factor analysis has been shown to be a useful technique for uncovering patterns of neural activity. The simultaneously acquired BOLD fMRI data were decomposed by independent component analysis. Dynamic functional connectivity was computed on the component's time series using a sliding window correlation, and between-network connectivity states were then defined based on the values of the correlation coefficients. ANOVA tests were performed to assess the relationships between the dynamics of between-network connectivity states and the fluctuations of EEG spectral patterns. MAIN RESULTS: We found three patterns related to the dynamics of between-network connectivity states. The first pattern has dominant peaks in the alpha, beta, and gamma bands and is related to the dynamics between the auditory, sensorimotor, and attentional networks. The second pattern, with dominant peaks in the theta and low alpha bands, is related to the visual and default mode network. The third pattern, also with peaks in the theta and low alpha bands, is related to the auditory and frontal network. SIGNIFICANCE: Our previous findings revealed a relationship between EEG spectral pattern fluctuations and the hemodynamics of large-scale brain networks. In this study, we suggest that the relationship also exists at the level of functional connectivity dynamics among large-scale brain networks when no standard spatial and spectral constraints are applied on the EEG data.

• MeSH
• časové faktory MeSH
• dospělí MeSH
• elektroencefalografie metody   MeSH
• lidé MeSH
• magnetická rezonanční tomografie metody   MeSH
• mladý dospělý MeSH
• mozek diagnostické zobrazování   fyziologie   MeSH
• nervová síť diagnostické zobrazování   fyziologie   MeSH
• Check Tag
• dospělí MeSH
• lidé MeSH
• mladý dospělý MeSH
• mužské pohlaví MeSH
• ženské pohlaví MeSH
• Publikační typ
• časopisecké články MeSH
• práce podpořená grantem MeSH

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
• mapování mozku metody   MeSH
• mladiství MeSH
• mladý dospělý MeSH
• mozek * patofyziologie   MeSH
• nervová síť * patofyziologie   MeSH
• nervové dráhy patofyziologie   MeSH
• odpočinek MeSH
• průřezové studie MeSH
• schizofrenie * patofyziologie   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

Hippocampus stores spatial representations, or maps, which are recalled each time a subject is placed in the corresponding environment. Across different environments of similar geometry, these representations show strong orthogonality in CA3 of hippocampus, whereas in the CA1 subfield a considerable overlap between the maps can be seen. The lower orthogonality decreases reliability of various decoders developed in an attempt to identify which of the stored maps is active at the moment. Especially, the problem with decoding emerges with a need to analyze data at high temporal resolution. Here, we introduce a functional-connectivity-based decoder, which accounts for the pairwise correlations between the spiking activities of neurons in each map and does not require any positional information, i.e. any knowledge about place fields. We first show, on recordings of hippocampal activity in constant environmental conditions, that our decoder outperforms existing decoding methods in CA1. Our decoder is then applied to data from teleportation experiments, in which an instantaneous switch between the environment identity triggers a recall of the corresponding spatial representation . We test the sensitivity of our approach on the transition dynamics between the respective memory states (maps). We find that the rate of spontaneous state shifts (flickering) after a teleportation event is increased not only within the first few seconds as already reported, but this instability is sustained across much longer (> 1 min.) periods.

• Klíčová slova
• Bayesian inference, CA1, Decoding, Functional connectivity, Graphical models, Hippocampus, Spatial representation,
• MeSH
• hipokampální oblast CA1 fyziologie   MeSH
• hipokampus MeSH
• lidé MeSH
• modely neurologické * MeSH
• neurony fyziologie   MeSH
• paměť * MeSH
• reprodukovatelnost výsledků MeSH
• Check Tag
• lidé MeSH
• Publikační typ
• časopisecké články MeSH