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,
• MeSH
• dospělí MeSH
• elektroencefalografie MeSH
• elektrokortikografie MeSH
• hipokampus * fyziologie   MeSH
• lidé MeSH
• mladý dospělý MeSH
• paměť * fyziologie   MeSH
• spánkový lalok * fyziologie   MeSH
• temenní lalok * fyziologie   MeSH
• zraková percepce * fyziologie   MeSH
• zrakové dráhy * fyziologie   MeSH
• Check Tag
• dospělí MeSH
• lidé MeSH
• mladý dospělý MeSH
• mužské pohlaví MeSH
• ženské pohlaví MeSH
• Publikační typ
• časopisecké články MeSH

Objective. Virtual reality (VR) has become a key tool for researching spatial memory. Virtual environments offer many advantages for research in terms of logistics, neuroimaging compatibility etc. However, it is well established in animal models that the lack of physical movement in VR impairs some neural representations of space, and this is considered likely to be true in humans as well. Furthermore, it is unclear how big the disruptive effect stationary navigation is-how much does physical movement during encoding and recall affect human spatial memory and representations of space? What effect does the fatigue of actually walking during tasks have on participants-will physical movement decrease performance, or increase perception of difficulty?Approach. We utilize Augmented reality (AR) to enable participants to perform a spatial memory task while physically moving in the real world, compared to a matched VR task performed while stationary. Our task was performed by a group of healthy participants, by a group of stationary epilepsy patients, as they represent the population from which invasive human spatial signals are typically collected, and, in a case study, by a mobile epilepsy patient with an investigational chronic neural implant (Medtronic Summit RC + STM) streaming real-time continuous hippocampal local field potential data.Main results. Participants showed good performance in both conditions, but reported that the walking condition was significantly easier, more immersive, and more fun than the stationary condition. Importantly, memory performance was significantly better in walking vs. stationary in all groups, including epilepsy patients. We also found evidence for an increase in the amplitude of the theta oscillations associated with movement during the walking condition.Significance. Our findings highlight the importance of paradigms that include physical movement and suggest that integrating AR with movement in real environments can lead to improved techniques for spatial memory research.

• Klíčová slova
• augmented reality, navigation, physical movement, spatial memory, virtual reality,
• MeSH
• augmentovaná realita MeSH
• chůze fyziologie   MeSH
• dospělí MeSH
• lidé středního věku MeSH
• lidé MeSH
• mladý dospělý MeSH
• prostorová navigace * fyziologie   MeSH
• prostorová paměť * fyziologie   MeSH
• virtuální realita * MeSH
• Check Tag
• dospělí MeSH
• lidé středního věku MeSH
• lidé MeSH
• mladý dospělý MeSH
• mužské pohlaví MeSH
• ženské pohlaví MeSH
• Publikační typ
• časopisecké články MeSH

This study proposes a novel hypothesis exploring the potential relationship between magnetite nanoparticle sizes in the human brain and neural oscillation frequencies. Magnetite, a naturally occurring magnetic material found in brain tissue, has been the subject of increasing scientific interest due to its potential role in brain function and its possible link to neurodegenerative diseases. Concurrently, neural oscillations are known to play crucial roles in various cognitive processes. Our theoretical model, grounded in Néel's theory of superparamagnetism and principles of electromagnetism, suggests a direct physical relationship between specific magnetite grain sizes (19-24 nm) and a wide range of neural oscillation frequency bands (1-1000 Hz). Using computational simulations and statistical analyses, we investigated how the magnetic properties of these nanoparticles might interact with or influence neural activity. Our calculations show that magnetite particles within this size range have magnetic moment fluctuation frequencies that span the range of known neural oscillations, with larger particles corresponding to lower frequencies and smaller particles to higher frequencies, following Néel's relaxation equation. This relationship encompasses the entire spectrum of known neural oscillations, from delta waves to high-frequency oscillations. Of particular interest, we found that magnetite particles within this size range could potentially interact with the 50-60 Hz frequencies of power grid systems, raising intriguing questions about potential interactions between environmental electromagnetic fields and endogenous brain activity. These results suggest potential size-dependent interactions between magnetite particles and neural oscillations, with implications for understanding brain function, aging processes, and the impact of environmental electromagnetic fields. This work provides a theoretical approach for future experimental studies and may offer new perspectives on the complex dynamics of brain physiology and pathology.

• MeSH
• lidé MeSH
• magnetické nanočástice * chemie   MeSH
• mozek * fyziologie   MeSH
• neurony * fyziologie   MeSH
• oxid železnato-železitý * chemie   MeSH
• počítačová simulace MeSH
• velikost částic MeSH
• Check Tag
• lidé MeSH
• Publikační typ
• časopisecké články MeSH
• Názvy látek
• magnetické nanočástice * MeSH
• oxid železnato-železitý * MeSH

Patients with alcohol use disorder (AUD) who seek treatment show highly variable outcomes. A precision medicine approach with biomarkers responsive to new treatments is warranted to overcome this limitation. Promising biomarkers relate to prefrontal control mechanisms that are severely disturbed in AUD. This results in reduced inhibitory control of compulsive behavior and, eventually, relapse. We reasoned here that prefrontal dysfunction, which underlies vulnerability to relapse, is evidenced by altered neuroelectric signatures and should be restored by pharmacological interventions that specifically target prefrontal dysfunction. To test this, we applied our recently developed biocompatible neuroprosthesis to measure prefrontal neural function in a well-established rat model of alcohol addiction and relapse. We monitored neural oscillations and event-related potentials in awake alcohol-dependent rats during abstinence and following treatment with psilocybin or LY379268, agonists of the serotonin 2A receptor (5-HT2AR), and the metabotropic glutamate receptor 2 (mGluR2), that are known to reduce prefrontal dysfunction and relapse. Electrophysiological impairments in alcohol-dependent rats are reduced amplitudes of P1N1 and N1P2 components and attenuated event-related oscillatory activity. Psilocybin and LY379268 were able to restore these impairments. Furthermore, alcohol-dependent animals displayed a dominance in higher beta frequencies indicative of a state of hyperarousal that is prone to relapse, which particularly psilocybin was able to counteract. In summary, we provide prefrontal markers indicative of relapse and treatment response, especially for psychedelic drugs.

• MeSH
• alkoholismus * farmakoterapie   patofyziologie   MeSH
• aminokyseliny MeSH
• bicyklické sloučeniny heterocyklické * farmakologie   MeSH
• biologické markery MeSH
• evokované potenciály účinky léků   MeSH
• krysa rodu Rattus MeSH
• modely nemocí na zvířatech * MeSH
• prefrontální mozková kůra * účinky léků   patofyziologie   metabolismus   MeSH
• psilocybin * farmakologie   MeSH
• receptory metabotropního glutamátu MeSH
• zvířata MeSH
• Check Tag
• krysa rodu Rattus MeSH
• mužské pohlaví MeSH
• zvířata MeSH
• Publikační typ
• časopisecké články MeSH
• Názvy látek
• aminokyseliny MeSH
• bicyklické sloučeniny heterocyklické * MeSH
• biologické markery MeSH
• LY 379268 MeSH Prohlížeč
• metabotropic glutamate receptor 2 MeSH Prohlížeč
• psilocybin * MeSH
• receptory metabotropního glutamátu MeSH

Brain imaging studies in complex regional pain syndrome (CRPS) have found mixed evidence for functional and structural changes in CRPS. In this cross-sectional study, we evaluated two patient cohorts from different centers and examined functional connectivity (rsFC) in 51 CRPS patients and 50 matched controls. rsFC was compared in predefined ROI pairs, but also in non-hypothesis driven analyses. Resting state (rs)fMRI changes in default mode network (DMN) and the degree rank order disruption index (kD) were additionally evaluated. Finally, imaging parameters were correlated with clinical severity and somatosensory function. Among predefined pairs, we found only weakly to moderately lower functional connectivity between the right nucleus accumbens and bilateral ventromedial prefrontal cortex in the infra-slow oscillations (ISO) band. The unconstrained ROI-to-ROI analysis revealed lower rsFC between the periaqueductal gray matter (PAG) and left anterior insula, and higher rsFC between the right sensorimotor thalamus and nucleus accumbens. In the correlation analysis, pain was positively associated with insulo-prefrontal rsFC, whereas sensorimotor thalamo-cortical rsFC was positively associated with tactile spatial resolution of the affected side. In contrast to previous reports, we found no group differences for kD or rsFC in the DMN, but detected overall lower data quality in patients. In summary, while some of the previous results were not replicated despite the larger sample size, novel findings from two independent cohorts point to potential down-regulated antinociceptive modulation by the PAG and increased connectivity within the reward system as pathophysiological mechanisms in CRPS. However, in light of the detected systematic differences in data quality between patients and healthy subjects, validity of rsFC abnormalities in CRPS should be carefully scrutinized in future replication studies.

• Klíčová slova
• Biomarker, CRPS, Functional connectivity, Neuropathic pain, Resting-state fMRI,
• MeSH
• default mode network diagnostické zobrazování   patofyziologie   MeSH
• dospělí MeSH
• komplexní regionální syndromy bolesti * patofyziologie   diagnostické zobrazování   MeSH
• konektom metody   MeSH
• lidé středního věku MeSH
• lidé MeSH
• magnetická rezonanční tomografie * MeSH
• mozek patofyziologie   diagnostické zobrazování   MeSH
• nervová síť patofyziologie   diagnostické zobrazování   MeSH
• průřezové studie MeSH
• Check Tag
• dospělí MeSH
• lidé středního věku MeSH
• lidé MeSH
• mužské pohlaví MeSH
• ženské pohlaví MeSH
• Publikační typ
• časopisecké články MeSH
• multicentrická studie MeSH

Antagonistic activity of brain networks likely plays a fundamental role in how the brain optimizes its performance by efficient allocation of computational resources. A prominent example involves externally/internally oriented attention tasks, implicating two anticorrelated, intrinsic brain networks: the default mode network (DMN) and the dorsal attention network (DAN). To elucidate electrophysiological underpinnings and causal interplay during attention switching, we recorded intracranial EEG (iEEG) from 25 epilepsy patients with electrode contacts localized in the DMN and DAN. We show antagonistic network dynamics of activation-related changes in high-frequency (> 50 Hz) and low-frequency (< 30 Hz) power. The temporal profile of information flow between the networks estimated by functional connectivity suggests that the activated network inhibits the other one, gating its activity by increasing the amplitude of the low-frequency oscillations. Insights about inter-network communication may have profound implications for various brain disorders in which these dynamics are compromised.

• MeSH
• dospělí MeSH
• elektroencefalografie MeSH
• elektrofyziologické jevy MeSH
• epilepsie patofyziologie   MeSH
• lidé středního věku MeSH
• lidé MeSH
• mladý dospělý MeSH
• mozek * fyziologie   patofyziologie   MeSH
• nervová síť * fyziologie   MeSH
• pozornost * fyziologie   MeSH
• Check Tag
• dospělí MeSH
• lidé středního věku MeSH
• lidé MeSH
• mladý dospělý MeSH
• mužské pohlaví MeSH
• ženské pohlaví MeSH
• Publikační typ
• časopisecké články MeSH
• práce podpořená grantem MeSH

Despite advances in understanding the cellular and molecular processes underlying memory and cognition, and recent successful modulation of cognitive performance in brain disorders, the neurophysiological mechanisms remain underexplored. High frequency oscillations beyond the classic electroencephalogram spectrum have emerged as a potential neural correlate of fundamental cognitive processes. High frequency oscillations are detected in the human mesial temporal lobe and neocortical intracranial recordings spanning gamma/epsilon (60-150 Hz), ripple (80-250 Hz) and higher frequency ranges. Separate from other non-oscillatory activities, these brief electrophysiological oscillations of distinct duration, frequency and amplitude are thought to be generated by coordinated spiking of neuronal ensembles within volumes as small as a single cortical column. Although the exact origins, mechanisms and physiological roles in health and disease remain elusive, they have been associated with human memory consolidation and cognitive processing. Recent studies suggest their involvement in encoding and recall of episodic memory with a possible role in the formation and reactivation of memory traces. High frequency oscillations are detected during encoding, throughout maintenance, and right before recall of remembered items, meeting a basic definition for an engram activity. The temporal coordination of high frequency oscillations reactivated across cortical and subcortical neural networks is ideally suited for integrating multimodal memory representations, which can be replayed and consolidated during states of wakefulness and sleep. High frequency oscillations have been shown to reflect coordinated bursts of neuronal assembly firing and offer a promising substrate for tracking and modulation of the hypothetical electrophysiological engram.

• Klíčová slova
• cognition, intracranial EEG, local field potential, memory consolidation, network oscillations, sharp-wave ripples,
• MeSH
• elektroencefalografie MeSH
• kognice * fyziologie   MeSH
• lidé MeSH
• mozek fyziologie   MeSH
• mozkové vlny fyziologie   MeSH
• paměť fyziologie   MeSH
• Check Tag
• lidé MeSH
• Publikační typ
• časopisecké články MeSH
• přehledy MeSH

Understanding the function of sleep and its associated neural rhythms is an important goal in neuroscience. While many theoretical models of neural dynamics during sleep exist, few include the effects of neuromodulators on sleep oscillations and describe transitions between sleep and wake states or different sleep stages. Here, we started with a C++-based thalamocortical network model that describes characteristic thalamic and cortical oscillations specific to sleep. This model, which includes a biophysically realistic description of intrinsic and synaptic channels, allows for testing the effects of different neuromodulators, intrinsic cell properties, and synaptic connectivity on neural dynamics during sleep. We present a complete reimplementation of this previously-published sleep model in the standardized NEURON/Python framework, making it more accessible to the wider scientific community.

• Klíčová slova
• Computational neuroscience, NEURON, Neuromodulation, Sleep,
• Publikační typ
• časopisecké články MeSH

Numerous insect species living in temperate regions survive adverse conditions, such as winter, in a state of developmental arrest. The most reliable cue for anticipating seasonal changes is the day-to-night ratio, the photoperiod. The molecular mechanism of the photoperiodic timer in insects is mostly unclear. Multiple pieces of evidence suggest the involvement of circadian clock genes, however, their role might be independent of their well-established role in the daily oscillation of the circadian clock. Furthermore, reproductive diapause is preferentially studied in females, whereas males are usually used for circadian clock research. Given the idiosyncrasies of male and female physiology, we decided to test male reproductive diapause in a strongly photoperiodic species, the linden bug Pyrrhocoris apterus. The data indicate that reproduction is not under circadian control, whereas the photoperiod strongly determines males' mating capacity. Clock mutants in pigment dispersing factor and cryptochrome-m genes are reproductive even in short photoperiod. Thus, we provide additional evidence of the participation of circadian clock genes in the photoperiodic time measurement in insects.

• Klíčová slova
• Circadian clock, Cryptochrome, Photoperiodism, Pigment dispersing factor, Reproductive diapause,
• MeSH
• cirkadiánní hodiny * genetika   fyziologie   MeSH
• cirkadiánní rytmus fyziologie   genetika   MeSH
• diapauza hmyzu genetika   fyziologie   MeSH
• fotoperioda * MeSH
• Heteroptera * genetika   fyziologie   MeSH
• hmyzí proteiny genetika   metabolismus   MeSH
• kryptochromy * genetika   metabolismus   MeSH
• mutace * MeSH
• rozmnožování fyziologie   genetika   MeSH
• sexuální chování zvířat fyziologie   MeSH
• zvířata MeSH
• Check Tag
• mužské pohlaví MeSH
• ženské pohlaví MeSH
• zvířata MeSH
• Publikační typ
• časopisecké články MeSH
• Názvy látek
• hmyzí proteiny MeSH
• kryptochromy * MeSH

Small data learning problems are characterized by a significant discrepancy between the limited number of response variable observations and the large feature space dimension. In this setting, the common learning tools struggle to identify the features important for the classification task from those that bear no relevant information and cannot derive an appropriate learning rule that allows discriminating among different classes. As a potential solution to this problem, here we exploit the idea of reducing and rotating the feature space in a lower-dimensional gauge and propose the gauge-optimal approximate learning (GOAL) algorithm, which provides an analytically tractable joint solution to the dimension reduction, feature segmentation, and classification problems for small data learning problems. We prove that the optimal solution of the GOAL algorithm consists in piecewise-linear functions in the Euclidean space and that it can be approximated through a monotonically convergent algorithm that presents-under the assumption of a discrete segmentation of the feature space-a closed-form solution for each optimization substep and an overall linear iteration cost scaling. The GOAL algorithm has been compared to other state-of-the-art machine learning tools on both synthetic data and challenging real-world applications from climate science and bioinformatics (i.e., prediction of the El Niño Southern Oscillation and inference of epigenetically induced gene-activity networks from limited experimental data). The experimental results show that the proposed algorithm outperforms the reported best competitors for these problems in both learning performance and computational cost.

• Publikační typ
• časopisecké články MeSH