Hippocampal-Prefrontal cortex network dynamics predict performance during retrieval in a context-guided object memory task

Remembering life episodes is a complex process that requires the interaction between multiple brain areas. It is thought that contextual information provided by the hippocampus (HPC) can trigger the recall of a past event through the activation of medial prefrontal cortex (mPFC) neuronal ensembles, but the underlying mechanisms remain poorly understood. Indeed, little is known about how the vHPC and mPFC are coordinated during a contextual-guided recall of an object recognition memory. To address this, we performed electrophysiological recordings in behaving rats during the retrieval phase of the object-in-context memory task (OIC). Coherence, phase locking and theta amplitude correlation analysis showed an increase in vHPC-mPFC LFP synchronization in the theta range when animals explore contextually mismatched objects. Moreover, we identified ensembles of putative pyramidal cells in the mPFC that encode specific object-context associations. Interestingly, the increase of vHPC-mPFC synchronization during exploration of the contextually mismatched object and the preference of mPFC incongruent object neurons predicts the animal's performance during the resolution of the OIC task. Altogether, these results identify changes in vHPC-mPFC synchronization and mPFC ensembles encoding specific object-context associations likely involved in the recall of past events.

Phase and amplitude electroencephalography correlations change with disease progression in people with idiopathic rapid eye-movement sleep behavior disorder

Study Objectives Increased phase synchronization in electroencephalography (EEG) bands might reflect the activation of compensatory mechanisms of cognitive decline in people with neurodegenerative diseases. Here, we investigated whether altered large-scale couplings of brain oscillations could be linked to the balancing of cognitive decline in a longitudinal cohort of people with idiopathic rapid eye-movement sleep behavior disorder (iRBD). Methods We analyzed 18 patients (17 males, 69.7 ± 7.5 years) with iRBD undergoing high-density EEG (HD-EEG), presynaptic dopaminergic imaging, and clinical and neuropsychological (NPS) assessments at two time points (time interval 24.2 ± 5.9 months). We thus quantified the HD-EEG power distribution, orthogonalized amplitude correlation, and weighted phase-lag index at both time points and correlated them with clinical, NPS, and imaging data. Results Four patients phenoconverted at follow-up (three cases of parkinsonism and one of dementia). At the group level, NPS scores decreased over time, without reaching statistical significance. However, alpha phase synchronization increased and delta amplitude correlations decreased significantly at follow-up compared to baseline. Both large-scale network connectivity metrics were significantly correlated with NPS scores but not with sleep quality indices or presynaptic dopaminergic imaging data. Conclusions These results suggest that increased alpha phase synchronization and reduced delta amplitude correlation may be considered electrophysiological signs of an active compensatory mechanism of cognitive impairment in people with iRBD. Large-scale functional modifications may be helpful biomarkers in the characterization of prodromal stages of alpha-synucleinopathies.

Phase and amplitude correlations change with disease progression in idiopathic Rapid eye-movement sleep behavior disorder patients

Cognitive decline is a common trait of neurodegenerative diseases of central nervous system and one of the major risk factors associated with faster phenoconversion from prodromal stages. In the transition to full-blown clinical syndromes, increased phase synchronization in the theta, alpha or beta EEG rhythms is thought to reflect the activation of compensatory mechanisms that may counterbalance the cognitive decline of patients affected by Mild Cognitive Impairment (MCI). Patients suffering from idiopathic Rapid eye-movement sleep Behavior Disorder (iRBD) have high risk of developing Parkinson Disease (PD) or Dementia with Lewy Bodies (DLB) and cognitive impairment is among the strongest risk factors together with motor symptoms. Here we wanted to investigate whether altered phase synchronization and amplitude couplings of the brain oscillations could be linked to the balancing of cognitive decline in a longitudinal cohort (N=18) of iRBD patients. We measured high-density Electroencephalographic (HD-EEG) activity at baseline and follow-up and quantified power distribution, orthogonalized amplitude correlation and weighted phase lag index. Despite the overt neurodegenerative progression (three patients converted to PD and one to DLB), cognitive decline was not evident from Mini Mental State Examination (MMSE) or neuropsychological tests. On the other hand, alpha phase synchronization and delta amplitude correlations were significantly different at follow-up compared to baseline. In particular, alpha synchrony was enhanced while delta amplitude coupling was reduced. Those differences were more pronounced among central-posterior channels while frontal channels showed a reduced number of significant edges with respect to surrogates. Both large-scale amplitude and phase coupling significantly correlated with cognitive or neuropsychological scores but not with sleep quality indices. Altogether, these results suggest that increased alpha phase-synchronization and reduced delta amplitude correlation may be considered as electrophysiological signs of an active compensatory mechanism of the cognitive impairment in RDB patients. Large-scale functional modifications could thus be used as significant biomarker in the characterization of prodromal stages of PD.Statement of SignificanceCognitive impairment and RBD emerge much earlier than the better-known motor symptoms distinctive of synucleinopathies. An improved investigation of RBD may constitute an important biomarker for an early diagnosis of the actual neurodegenerative diseases. For the first time, this preliminary study aims to quantify the large-scale network couplings as electrophysiological manifestation of the compensatory mechanism to the cognitive impairment in a longitudinal study of idiopathic RBD patients. Unfortunately, the small number of the subjects limits the generalizability of our observations, but this is only preliminary works in a larger project that aims to investigate advanced electrophysiological markers for an early diagnosis of the synucleinopathies.

Inter-brain amplitude correlation differentiates cooperation from competition in a motion-sensing sports game

Cooperation and competition are two basic modes of human interaction. Their underlying neural mechanisms, especially from an interpersonal perspective, have not been fully explored. Using the electroencephalograph-based hyperscanning technique, the present study investigated the neural correlates of both cooperation and competition within the same ecological paradigm using a classic motion-sensing tennis game. Both the inter-brain coupling (the inter-brain amplitude correlation and inter-brain phase-locking) and the intra-brain spectral power were analyzed. Only the inter-brain amplitude correlation showed a significant difference between cooperation and competition, with different spatial patterns at theta, alpha and beta frequency bands. Further inspection revealed distinct inter-brain coupling patterns for cooperation and competition; cooperation elicited positive inter-brain amplitude correlation at the delta and theta bands in extensive brain regions, while competition was associated with negative occipital inter-brain amplitude correlation at the alpha and beta bands. These findings add to our knowledge of the neural mechanisms of cooperation and competition and suggest the significance of adopting an inter-brain perspective in exploring the neural underpinnings of social interaction in ecological contexts.

Correlation study of relative parameters of intracranial pressure and prognosis of patient with craniocerebral injury

Objective: To analyze the correlation of the relative parameters of intracranial pressure to the prognosis in patients with craniocerebral injury.Methods: The clinical data of 80 patients with closed craniocerebral injury were retrospectively analyzed, and all of these patients underwent conventional examinations of arterial blood pressure and intracranial pressure. Neumatic DCR system was used to monitor relative parameters of intracranial pressure from patients. According to the score of Glasgow outcome scale (GOS) upon discharge, they were divided into favorable prognosis group (GOS III-V, n = 46) and unfavorable prognosis group (GOS I-II, n = 34). The relative parameters of intracranial pressure of two groups were compared so as to analyze the correlation of the prognosis in patients to ICP-related parameters.Results: Pressure reactivity index (PRx) and intracranial pressure (ICP) of favorable prognosis group were significantly higher than those of unfavorable prognosis group (t = 12.27, t = 5.22, p < .05). Meanwhile, cerebral perfusion pressure (CPP) and ICP-ABP wave amplitude correlation (IAAC) of favorable prognosis group were significantly lower than those of unfavorable prognosis group (t = 14.54, t = 14.78, p < .05). The average age, gender, duration of admission to neurosurgical intensive care unit (NICU) and GCS (Glasgow coma scale) score on admission of the two groups were not statistically significant.Conclusions: The prognosis and ICP-related parameters (such as PRx, ICP, CPP, etc.) in patients with craniocerebral injury are risk factors for the prognosis effect. Therefore, to monitor the above-mentioned indicators has an important clinical value for assessing the prognosis of craniocerebral injury.

Intrinsic/extrinsic duality of large-scale neural functional integration in the human brain

Human brain activity is not merely responsive to environmental context but includes intrinsic dynamics, as suggested by the discovery of functionally meaningful neural networks at rest, i.e., even without explicit engagement of the corresponding function. Yet, the neurophysiological coupling mechanisms distinguishing intrinsic (i.e., task-invariant) from extrinsic (i.e., task-dependent) brain networks remain indeterminate. Here, we investigated functional brain integration using magnetoencephalography throughout rest and various tasks recruiting different functional systems and modulating perceptual/cognitive loads. We demonstrated that two distinct modes of neural communication continually operate in parallel: extrinsic coupling supported by phase synchronization and intrinsic integration encoded in amplitude correlation. Intrinsic integration also contributes to phase synchronization, especially over short (second-long) timescales, through modulatory effects of amplitude correlation. Our study establishes the foundations of a novel conceptual framework for human brain function that fundamentally relies on electrophysiological features of functional integration. This framework blurs the boundary between resting-state and task-related neuroimaging.

ACCURACY OF BEARING DETERMINATION IN A THREE-CHANNEL MONOPULSE AMPLITUDE CORRELATION DIRECTION FINDER

In the work, the study of the achievable accuracy of determining the coordinates of the radiating in the radio range of spacecraft using a three‑element amplitude correlation direction finder has been performed. The proposed scheme makes it possible to select single and group low‑power complex signals and simultaneously determine the bearings of several sources, the signals of which can be separated in time‑frequency‑code space. As an example, the radiation pattern of a three‑element antenna system with an orthogonal arrangement of partial diagrams with respect to the equal‑signal direction is considered. The results of statistical modeling of the correlation processing algorithm obtained for a three‑channel monopulse system with a 3.7° pattern width and estimates of the potential accuracy of determining the bearing are presented. Simulation results are given to evaluate the instrumental accuracy of the direction finder. The proposed method of direction finding provides the ability to determine the geodetic coordinates of aerospace objects using the station electronic reconnaissance.

Ghost interactions in MEG/EEG source space: A note of caution on inter-areal coupling measures

When combined with source modeling, magneto‐ (MEG) and electroencephalography (EEG) can be used to study long-range interactions among cortical processes non-invasively. Estimation of such inter-areal connectivity is nevertheless hindered by instantaneous field spread and volume conduction, which artificially introduce linear correlations and impair source separability in cortical current estimates. To overcome the inflating effects of linear source mixing inherent to standard interaction measures, alternative phase‐ and amplitude-correlation based connectivity measures, such as imaginary coherence and orthogonalized amplitude correlation have been proposed. Being by definition insensitive to zero-lag correlations, these techniques have become increasingly popular in the identification of correlations that cannot be attributed to field spread or volume conduction. We show here, however, that while these measures are immune to the direct effects of linear mixing, they may still reveal large numbers of spurious false positive connections through field spread in the vicinity of true interactions. This fundamental problem affects both region-of-interest-based analyses and all-to-all connectome mappings. Most importantly, beyond defining and illustrating the problem of spurious, or “ghost” interactions, we provide a rigorous quantification of this effect through extensive simulations. Additionally, we further show that signal mixing also significantly limits the separability of neuronal phase and amplitude correlations. We conclude that spurious correlations must be carefully considered in connectivity analyses in MEG/EEG source space even when using measures that are immune to zero-lag correlations.Highlights✓Reliable estimation of neuronal coupling with MEG and EEG is challenged by signal mixing✓A number of coupling techniques attempt to overcome this limitation by excluding zero-lag interactions✓Contrary to what is commonly admitted, our simulations illustrate that such interaction metrics will still yield false positives✓Spurious, or “ghost”, interactions are generally detected between sources in the vicinity of true phase-lagged interacting sources✓Signal mixing also severely affects the mutual separability of phase and amplitude correlations