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Local Field Potential (LFP), despite its name, often reflects remote activity. Depending on the orientation and synchrony of their sources, both oscillations and more complex waves may passively spread in brain tissue over long distances and be falsely interpreted as local activity at such distant recording sites. Here we show that the whisker-evoked potentials in the thalamic nuclei are of local origin up to around 6 ms post stimulus, but the later (7-15 ms) wave is overshadowed by a negative component reaching from cortex. This component can be analytically removed and local thalamic LFP can be recovered reliably using Current Source Density analysis. We used model-based kernel CSD (kCSD) method which allowed us to study the contribution of local and distant currents to LFP from rat thalamic nuclei and barrel cortex recorded with multiple, non-linear and non-regular multichannel probes. Importantly, we verified that concurrent recordings from the cortex are not essential for reliable thalamic CSD estimation. The proposed framework can be used to analyze LFP from other brain areas and has consequences for general LFP interpretation and analysis., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2024 Średniawa et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Interdisciplinary approaches are needed to understand the relationship between genetic factors and brain structure and function. Here we describe a database that includes genetic data on apolipoprotein E (APOE) and phosphatidylinositol binding clathrin assembly protein (PICALM) genes, both of which are known to increase the risk of late-onset Alzheimer's disease, paired with psychometric (memory, intelligence, mood, personality, stress coping strategies), basic demographic and health data on a cohort of 192 healthy middle-aged (50-63) individuals. Part of the database (~79 participants) also includes blood tests (blood counts, lipid profile, HSV virus) and functional neuroimaging data (EEG/fMRI) recorded with a resting-state protocol (eyes open and eyes closed) and two cognitive tasks (multi-source interference task, MSIT; and Sternberg's memory task). The data were validated and showed overall good quality. This open-science dataset is well suited not only for research relating to susceptibility to Alzheimer's disease but also for more general questions on brain aging or can be used as part of meta-analytical multi-disciplinary projects., (© 2024. The Author(s).)

The ability to identify and resolve conflicts between standard, well-trained behaviors and behaviors required by the current context is an essential feature of cognitive control. To date, no consensus has been reached on the brain mechanisms involved in exerting such control: while some studies identified diverse patterns of activity across different conflicts, other studies reported common resources across conflict tasks or even across simple tasks devoid of the conflict component. The latter reports attributed the entire activity observed in the presence of conflict to longer time spent on the task (i.e., to the so-called time-on-task effects). Here, we used an extended Multi-Source Interference Task (MSIT) which combines Simon and flanker types of interference to determine shared and conflict-specific mechanisms of conflict resolution in fMRI and their separability from the time-on-task effects. Large portions of the activity in the dorsal attention network and decreases of activity in the default mode network were shared across the tasks and scaled in parallel with increasing reaction times. Importantly, the activity in the sensory and sensorimotor cortices, as well as in the posterior medial frontal cortex (pMFC) - a key region implicated in conflict processing - could not be exhaustively explained by the time-on-task effects., (© 2024 The Authors. Human Brain Mapping published by Wiley Periodicals LLC.)

In neuroscience, the acquisition of neural signals from the brain cortex is crucial to analyze brain processes, detect neurological disorders, and offer therapeutic brain-computer interfaces. The design of neural interfaces conformable to the brain tissue is one of today's major challenges since the insufficient biocompatibility of those systems provokes a fibrotic encapsulation response, leading to an inaccurate signal recording and tissue damage precluding long-term/permanent implants. The design and production of a novel soft neural biointerface made of polyacrylamide hydrogels loaded with plasmonic silver nanocubes are reported herein. Hydrogels are surrounded by a silicon-based template as a supporting element for guaranteeing an intimate neural-hydrogel contact while making possible stable recordings from specific sites in the brain cortex. The nanostructured hydrogels show superior electroconductivity while mimicking the mechanical characteristics of the brain tissue. Furthermore, in vitro biological tests performed by culturing neural progenitor cells demonstrate the biocompatibility of hydrogels along with neuronal differentiation. In vivo chronic neuroinflammation tests on a mouse model show no adverse immune response toward the nanostructured hydrogel-based neural interface. Additionally, electrocorticography acquisitions indicate that the proposed platform permits long-term efficient recordings of neural signals, revealing the suitability of the system as a chronic neural biointerface.

APOE‑ε4 genotype (apolipoprotein E, epsilon 4) is the strongest genetic risk factor for Alzheimer's disease (AD). Despite years of research, it is still not known how it contributes to dementia development. APOE has been implicated in many AD pathology mechanisms, like Aβ clearance, brain metabolism, changes within microglia and other glial functions and inflammatory processes. In fact, immunological/inflammatory processes are recently discussed as an important factor in Alzheimer's development and granulocyte profiles changes are reported in patients. However, the exact link between the immune system and risk‑genes is unknown. In particular, it is not known whether and how they interact throughout the lifetime, before the disease onset. The aim of the study was to investigate the relationship between granulocyte count and the APOE/PICALM genes in healthy individuals with an increased genetic risk of AD. An exploratory analysis regarding other blood cells was also conducted. Blood samples were collected from 77 healthy middle‑aged (50-63 years old) participants, who were also asked to complete a health and life‑style questionnaires. Groups with different AD risk‑genes were compared. Differences in granulocyte profiles were found in healthy carriers of AD risk‑genes who had slightly elevated eosinophil levels as compared to non-risk carriers. An exploratory analysis showed some alteration in mean corpuscular hemoglobin content and concentration (MCH/MCHC) levels between risk‑carriers subgroups and non-risk carriers. No other differences in blood count or lipoprotein profile were found between healthy APOE/PICALM risk‑carriers and non-risk carriers. Longitudinal studies will reveal if and how those changes contribute to the development of AD pathology.

Background: One of the goals of neuropsychology is to understand the brain mechanisms underlying aspects of attention and cognitive control. Several tasks have been developed as a part of this body of research, however their results are not always consistent. A reliable comparison of the data and a synthesis of study conclusions has been precluded by multiple methodological differences. Here, we describe a publicly available, high-density electroencephalography (EEG) dataset obtained from 42 healthy young adults while they performed 3 cognitive tasks: (i) an extended multi-source interference task; (ii) a 3-stimuli oddball task; (iii) a control, simple reaction task; and (iv) a resting-state protocol. Demographic and psychometric information are included within the dataset., Dataset Validation: First, data validation confirmed acceptable quality of the obtained EEG signals. Typical event-related potential (ERP) waveforms were obtained, as expected for attention and cognitive control tasks (i.e., N200, P300, N450). Behavioral results showed the expected progression of reaction times and error rates, which confirmed the effectiveness of the applied paradigms., Conclusions: This dataset is well suited for neuropsychological research regarding common and distinct mechanisms involved in different cognitive tasks. Using this dataset, researchers can compare a wide range of classical EEG/ERP features across tasks for any selected subset of electrodes. At the same time, 128-channel EEG recording allows for source localization and detailed connectivity studies. Neurophysiological measures can be correlated with additional psychometric data obtained from the same participants. This dataset can also be used to develop and verify novel analytical and classification approaches that can advance the field of deep/machine learning algorithms, recognition of single-trial ERP responses to different task conditions, and detection of EEG/ERP features for use in brain-computer interface applications., (© The Author(s) 2022. Published by Oxford University Press GigaScience.)

In this paper, we present a modular Data Acquisition (DAQ) system for simultaneous electrical stimulation and recording of brain activity. The DAQ system is designed to work with custom-designed Application Specific Integrated Circuit (ASIC) called Neurostim-3 and a variety of commercially available Multi-Electrode Arrays (MEAs). The system can control simultaneously up to 512 independent bidirectional i.e., input-output channels. We present in-depth insight into both hardware and software architectures and discuss relationships between cooperating parts of that system. The particular focus of this study was the exploration of efficient software design so that it could perform all its tasks in real-time using a standard Personal Computer (PC) without the need for data precomputation even for the most demanding experiment scenarios. Not only do we show bare performance metrics, but we also used this software to characterise signal processing capabilities of Neurostim-3 (e.g., gain linearity, transmission band) so that to obtain information on how well it can handle neural signals in real-world applications. The results indicate that each Neurostim-3 channel exhibits signal gain linearity in a wide range of input signal amplitudes. Moreover, their high-pass cut-off frequency gets close to 0.6Hz making it suitable for recording both Local Field Potential (LFP) and spiking brain activity signals. Additionally, the current stimulation circuitry was checked in terms of the ability to reproduce complex patterns. Finally, we present data acquired using our system from the experiments on a living rat's brain, which proved we obtained physiological data from non-stimulated and stimulated tissue. The presented results lead us to conclude that our hardware and software can work efficiently and effectively in tandem giving valuable insights into how information is being processed by the brain.

Animals display a rich repertoire of defensive responses adequate to the threat proximity. In social species, these reactions can be additionally influenced by the behavior of fearful conspecifics. However, the majority of neuroscientific studies on socially triggered defensive responses focuses on one type of behavior, freezing. To study a broader range of socially triggered reactions and underlying mechanisms, we directly compared two experimental paradigms, mimicking occurrence of the imminent versus remote threat. Observation of a partner currently experiencing aversive stimulation evokes passive defensive responses in the observer rats. Similar interaction with a partner that has just undergone the aversive stimulation prompts animals to increase active exploration. Although the observers display behaviors similar to those of the aversively stimulated demonstrators, their reactions are not synchronized in time, suggesting that observers' responses are caused by the change in their affective state rather than mimicry. Using opsins targeted to behaviorally activated neurons, we tagged central amygdala (CeA) cells implicated in observers' responses to either imminent or remote threat and reactivated them during the exploration of a novel environment. The manipulation revealed that the two populations of CeA cells promote passive or active defensive responses, respectively. Further experiments confirmed that the two populations of cells at least partially differ in expression of molecular markers (protein kinase C-δ [PKC-δ] and corticotropin-releasing factor [CRF]) and connectivity patterns (receiving input from the basolateral amygdala or from the anterior insula). The results are consistent with the literature on single subjects' fear conditioning, suggesting that similar neuronal circuits control defensive responses in social and non-social contexts., Competing Interests: Declaration of interests The authors declare no competing interests., (Copyright © 2021 Elsevier Inc. All rights reserved.)

Extracellular recording is an accessible technique used in animals and humans to study the brain physiology and pathology. As the number of recording channels and their density grows it is natural to ask how much improvement the additional channels bring in and how we can optimally use the new capabilities for monitoring the brain. Here we show that for any given distribution of electrodes we can establish exactly what information about current sources in the brain can be recovered and what information is strictly unobservable. We demonstrate this in the general setting of previously proposed kernel Current Source Density method and illustrate it with simplified examples as well as using evoked potentials from the barrel cortex obtained with a Neuropixels probe and with compatible model data. We show that with conceptual separation of the estimation space from experimental setup one can recover sources not accessible to standard methods., Competing Interests: The authors have declared that no competing interests exist.

Cholinergic and noradrenergic neuromodulation of the synaptic transmission from cortical layer 6 of the primary somatosensory cortex to neurons in the posteromedial thalamic nucleus (PoM) was studied using an in vitro slice preparation from young rats. Cholinergic agonist carbachol substantially decreased the amplitudes of consecutive excitatory postsynaptic potentials (EPSPs) evoked by a 20 Hz five pulse train. The decreased amplitude effect was counteracted by a parallel increase of synaptic frequency-dependent facilitation. We found this modulation to be mediated by muscarinic acetylcholine receptors. In the presence of carbachol the amplitudes of the postsynaptic potentials showed a higher trial-to-trial coefficient of variation (CV), which suggested a presynaptic site of action for the modulation. To substantiate this finding, we measured the failure rate of the excitatory postsynaptic currents in PoM cells evoked by "pseudominimal" stimulation of corticothalamic input. A higher failure-rate in the presence of carbachol indicated decreased probability of transmitter release at the synapse. Activation of the noradrenergic modulatory system that was mimicked by application of norepinephrine did not affect the amplitude of the first EPSP evoked in the five-pulse train, but later EPSPs were diminished. This indicated a decrease of the synaptic frequency-dependent facilitation. Treatment with noradrenergic α-2 agonist clonidine, α-1 agonist phenylephrine, or β-receptor agonist isoproterenol showed that the modulation may partly rely on α-2 adrenergic receptors. CV analysis did not suggest a presynaptic action of norepinephrine. We conclude that cholinergic and noradrenergic modulation act as different variable dynamic controls for the corticothalamic mechanism of the frequency-dependent facilitation in PoM., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2021 Nersisyan, Bekisz, Kublik, Granseth and Wróbel.)

Wake-related ketamine-dependent high frequency oscillations (HFO) can be recorded in local field potentials (LFP) from cortical and subcortical regions in rodents. The mechanisms underlying their generation and occurrence in higher mammals are unclear. Unfortunately, anesthetic doses of pure ketamine attenuate HFO, which has precluded their investigation under anesthesia. Here, we show ketamine-xylazine (KX) anesthesia is associated with a prominent 80-130 Hz rhythm in the olfactory bulb (OB) of rats, whereas 30-65 Hz gamma power is diminished. Simultaneous LFP and thermocouple recordings revealed the 80-130 Hz rhythm was dependent on nasal respiration. This rhythm persisted despite surgical excision of the piriform cortex. Silicon probes spanning the dorsoventral aspect of the OB revealed this rhythm was strongest in ventral areas and associated with microcurrent sources about the mitral layer. Pharmacological microinfusion studies revealed dependency on excitatory-inhibitory synaptic activity, but not gap junctions. Finally, a similar rhythm occurred in the OB of KX-anesthetized cats, which shared key features with our rodent studies. We conclude that the activity we report here is driven by nasal airflow, local excitatory-inhibitory interactions, and conserved in higher mammals. Additionally, KX anesthesia is a convenient model to investigate further the mechanisms underlying wake-related ketamine-dependent HFO.

Mounting evidence indicates that resting-state EEG activity is related to various cognitive functions. To trace physiological underpinnings of this relationship, we investigated EEG and behavioral performance of 36 healthy adults recorded at rest and during visual attention tasks: visual search and gun shooting. All measures were repeated two months later to determine stability of the results. Correlation analyses revealed that within the range of 2-45 Hz, at rest, beta-2 band power correlated with the strength of frontoparietal connectivity and behavioral performance in both sessions. Participants with lower global beta-2 resting-state power (gB2rest) showed weaker frontoparietal connectivity and greater capacity for its modifications, as indicated by changes in phase correlations of the EEG signals. At the same time shorter reaction times and improved shooting accuracy were found, in both test and retest, in participants with low gB2rest compared to higher gB2rest values. We posit that weak frontoparietal connectivity permits flexible network reconfigurations required for improved performance in everyday tasks.

The frequency-function relation of various EEG bands has inspired EEG-neurofeedback procedures intending to improve cognitive abilities in numerous clinical groups. In this study, we administered EEG-neurofeedback (EEG-NFB) to a healthy population to determine the efficacy of this procedure. We evaluated feedback manipulation in the beta band (12-22Hz), known to be involved in visual attention processing. Two groups of healthy adults were trained to either up- or down-regulate beta band activity, thus providing mutual control. Up-regulation training induced increases in beta and alpha band (8-12Hz) amplitudes during the first three sessions. Group-independent increases in the activity of both bands were observed in the later phase of training. EEG changes were not matched by measured behavioural indices of attention. Parallel changes in the two bands challenge the idea of frequency-specific EEG-NFB protocols and suggest their interdependence. Our study exposes the possibility (i) that the alpha band is more prone to manipulation, and (ii) that changes in the bands' amplitudes are independent from specified training. We therefore encourage a more comprehensive approach to EEG-neurofeedback training embracing physiological and/or operational relations among various EEG bands., (Copyright © 2017 Elsevier Ltd. All rights reserved.)

EEG-neurofeedback (NFB) became a very popular method aimed at improving cognitive and behavioral performance. However, the EMG frequency spectrum overlies the higher EEG oscillations and the NFB trainings focusing on these frequencies is hindered by the problem of EMG load in the information fed back to the subjects. In such a complex signal, it is highly probable that the most controllable component will form the basis for operant conditioning. This might cause different effects in the case of various training protocols and therefore needs to be carefully assessed before designing training protocols and algorithms. In the current experiment a group of healthy adults ( n = 14) was trained by professional trainers to up-regulate their beta1 (15-22 Hz) band for eight sessions. The control group ( n = 18) underwent the same training regime but without rewards for increasing beta. In half of the participants trained to up-regulate beta1 band ( n = 7) a systematic increase in tonic EMG activity was identified offline, implying that muscle activity became a foundation for reinforcement in the trainings. The remaining participants did not present any specific increase of the trained beta1 band amplitude. The training was perceived effective by both trainers and the trainees in all groups. These results indicate the necessity of proper control of muscle activity as a requirement for the genuine EEG-NFB training, especially in protocols that do not aim at the participants' relaxation. The specificity of the information fed back to the participants should be of highest interest to all therapists and researchers, as it might irreversibly alter the results of the training.

In rat barrel cortex, evoked potentials (EPs) to vibrissa stimulation can be divided into two distinct classes according to the relative contribution of their principal components. Our experiments support the notion that these components can be attributed to activation of two pyramidal cell populations: supra- and infragranular. With well-habituated stimuli EPs are dominated by a component related to the supragranular cells (class 1). However, the first reinforcement of vibrissa stimulation in the classical aversive paradigm favours the appearance of EPs dominated by a component characteristic of infragranular cells which matches with activation in the surround zone of the barrel field (class 2). Similar dynamic changes of the relative occurrence of the two EP classes follow other aversive stimuli, including pressing the animal’s ear and restraining a whisker. We hypothesize that neuromodulatory action elicited by contextual stimulation activates all neurons in the principal barrel column, including those providing an output to the surrounding barrels. In the classical conditioning paradigm this mechanism may lead to experience-dependent changes within the intracortical network. [ABSTRACT FROM AUTHOR]

The goal of EEG neurofeedback (EEG-NFB) training is to induce changes in the power of targeted EEG bands to produce beneficial changes in cognitive or motor function. The effectiveness of different EEG-NFB protocols can be measured using two dependent variables: (1) changes in EEG activity and (2) behavioral changes of a targeted function (for therapeutic applications the desired changes should be long-lasting). To firmly establish a causal link between these variables and the selected protocol, similar changes should not be observed when appropriate control paradigms are used. The main objective of this review is to evaluate the evidence, reported in the scientific literature, which supports the validity of various EEG-NFB protocols. Our primary concern is to highlight the role that uncontrolled nonspecific factors can play in the results generated from EEG-NFB studies. Nonspecific factors are often ignored in EEG-NFB designs or the data are not presented, which means conclusions should be interpreted cautiously. As an outcome of this review we present a do's and don'ts list, which can be used to develop future EEG-NFB methodologies, based on the small set of experiments in which the proper control groups have excluded non-EEG-NFB related effects. We found two features which positively correlated with the expected changes in power of the trained EEG band(s): (1) protocols which focused on training a smaller number of frequency bands and (2) a bigger number of electrodes used for neurofeedback training. However, we did not find evidence in support of the positive relationship between power changes of a trained frequency band(s) and specific behavioral effects.

Selective attention can be focused either volitionally, by top-down signals derived from task demands, or automatically, by bottom-up signals from salient stimuli. Because the brain mechanisms that underlie these two attention processes are poorly understood, we recorded local field potentials (LFPs) from primary visual cortical areas of cats as they performed stimulus-driven and anticipatory discrimination tasks. Consistent with our previous observations, in both tasks, we found enhanced beta activity, which we have postulated may serve as an attention carrier. We characterized the functional organization of task-related beta activity by (i) cortical responses (EPs) evoked by electrical stimulation of the optic chiasm and (ii) intracortical LFP correlations. During the anticipatory task, peripheral stimulation that was preceded by high-amplitude beta oscillations evoked large-amplitude EPs compared with EPs that followed low-amplitude beta. In contrast, during the stimulus-driven task, cortical EPs preceded by high-amplitude beta oscillations were, on average, smaller than those preceded by low-amplitude beta. Analysis of the correlations between the different recording sites revealed that beta activation maps were heterogeneous during the bottom-up task and homogeneous for the top-down task. We conclude that bottom-up attention activates cortical visual areas in a mosaic-like pattern, whereas top-down attentional modulation results in spatially homogeneous excitation.

Behavioural reactions to sensory stimuli vary with the level of arousal, but little is known about the underlying reorganization of neuronal networks. In this study, we use chronic recordings from the somatosensory regions of the thalamus and cortex of behaving rats together with a novel analysis of functional connectivity to show that during low arousal tactile signals are transmitted via the ventral posteromedial thalamic nucleus (VPM), a first-order thalamic relay, to the primary somatosensory (barrel) cortex and then from the cortex to the posterior medial thalamic nucleus (PoM), which plays a role of a higher-order thalamic relay. By contrast, during high arousal this network scheme is modified and both VPM and PoM transmit peripheral input to the barrel cortex acting as first-order relays. We also show that in urethane anaesthesia PoM is largely excluded from the thalamo-cortical loop. We thus demonstrate a way in which the thalamo-cortical system, despite its fixed anatomy, is capable of dynamically reconfiguring the transmission route of a sensory signal in concert with the behavioural state of an animal., (© 2015 Federation of European Neuroscience Societies and John Wiley & Sons Ltd.)

The local field potential (LFP), the low-frequency part of the extracellular potential, reflects transmembrane currents in the vicinity of the recording electrode. Thought mainly to stem from currents caused by synaptic input, it provides information about neural activity complementary to that of spikes, the output of neurons. However, the many neural sources contributing to the LFP, and likewise the derived current source density (CSD), can often make it challenging to interpret. Efforts to improve its interpretability have included the application of statistical decomposition tools like principal component analysis (PCA) and independent component analysis (ICA) to disentangle the contributions from different neural sources. However, their underlying assumptions of, respectively, orthogonality and statistical independence are not always valid for the various processes or pathways generating LFP. Here, we expand upon and validate a decomposition algorithm named Laminar Population Analysis (LPA), which is based on physiological rather than statistical assumptions. LPA utilizes the multiunit activity (MUA) and LFP jointly to uncover the contributions of different populations to the LFP. To perform the validation of LPA, we used data simulated with the large-scale, biophysically detailed model of mouse V1 developed by the Allen Institute. We find that LPA can identify laminar positions within V1 and the temporal profiles of laminar population firing rates from the MUA. We also find that LPA can estimate the salient current sinks and sources generated by feedforward input from the lateral geniculate nucleus (LGN), recurrent activity in V1, and feedback input from the lateromedial (LM) area of visual cortex. LPA identifies and distinguishes these contributions with a greater accuracy than the alternative statistical decomposition methods, PCA and ICA. The contributions from different cortical layers within V1 could however not be robustly separated and identified with LPA. This is likely due to substantial synchrony in population firing rates across layers, which may be reduced with other stimulus protocols in the future. Lastly, we also demonstrate the application of LPA on experimentally recorded MUA and LFP from 24 animals in the publicly available Visual Coding dataset. Our results suggest that LPA can be used both as a method to estimate positions of laminar populations and to uncover salient features in LFP/CSD contributions from different populations. Author summary: To make the best use of all the data collected in neuroscientific experiments, we need to develop appropriate analysis tools. In extracellular electrophysiological recordings, that is, measurements of electrical signals outside of cells produced by neural activity, the low-frequency part of the signal referred to as the local field potential (LFP) is often difficult to interpret due to the many neurons and biophysical processes contributing to this signal. Statistical tools have been used to decompose the recorded LFP with the aim of disentangling contributions from different neural populations and pathways. However, these methods are based on assumptions that can be invalid for LFP in the structure of interest. In this study, we extend and validate a method called laminar population analysis (LPA), which is based on physiological rather than statistical assumptions. We tested, developed, and validated LPA using simulated data from a large-scale, biophysically detailed model of mouse primary visual cortex. We found that LPA is able to tease apart several of the most salient contributions from different external inputs as well as the total contribution from recurrent activity within the primary visual cortex. We also demonstrate the application of LPA on experimentally recorded LFP. [ABSTRACT FROM AUTHOR]

The diagnosis, treatment, and management of dementia provide significant challenges due to its chronic cognitive impairment. The complexity of this condition is further highlighted by the impact of gene-environment interactions. A recent strategy combines advanced genomics and precision medicine methods to explore the complex genetic foundations of dementia. Utilizing the most recent research in the field of neurogenetics, the importance of precise genetic data in explaining the variation seen in dementia patients can be investigated. Gene-environment interactions are important because they influence genetic susceptibilities and aid in the development and progression of dementia. Modified to each patient's genetic profile, precision medicine has the potential to detect groups at risk and make previously unheard-of predictions about the course of diseases. Precision medicine techniques have the potential to completely transform treatment and diagnosis methods. Targeted medications that target genetic abnormalities will probably appear, providing the possibility for more efficient and customized medical interventions. Investigating the relationship between genes and the environment may lead to preventive measures that would enable people to change their surroundings and minimize the risk of dementia, leading to the improved lifestyle of affected people. This paper provides a comprehensive overview of the genomic insights into dementia, emphasizing the pivotal role of precision medicine, and gene-environment interactions. [ABSTRACT FROM AUTHOR]

One of the challenges of modern neuroscience is integrating voluminous data of diferent modalities derived from a variety of specimens. This task requires a common spatial framework that can be provided by brain atlases. The first atlases were limited to two-dimentional presentation of structural data. Recently, attempts at creating 3D atlases have been made to offer navigation within non-standard anatomical planes and improve capability of localization of different types of data within the brain volume. The 3D atlases available so far have been created using frameworks which make it difficult for other researchers to replicate the results. To facilitate reproducible research and data sharing in the field we propose an SVG-based Common Atlas Format (CAF) to store 2D atlas delineations or other compatible data and 3D Brain Atlas Reconstructor (3dBAR), software dedicated to automated reconstruction of three-dimensional brain structures from 2D atlas data. The basic functionality is provided by (1) a set of parsers which translate various atlases from a number of formats into the CAF, and (2) a module generating 3D models from CAF datasets. The whole reconstruction process is reproducible and can easily be configured, tracked and reviewed, which facilitates fixing errors. Manual corrections can be made when automatic reconstruction is not sufficient. The software was designed to simplify interoperability with other neuroinformatics tools by using open file formats. The content can easily be exchanged at any stage of data processing. The framework allows for the addition of new public or proprietary content.

The second order somatosensory thalamic nucleus (posteromedial nucleus, PoM) receives excitatory projection from layer VI of somatosensory cortex. While it is known that layer VI cortical input to first order, ventrobasal nucleus (VB) is modulated by cholinergic projections from the brainstem, no such data exists concerning the PoM nucleus. In order to study if layer VI corticothalamic transmission to PoM is also modulated we used patch-clamp recording in thalamocortical slices from the rat's brain. Excitatory postsynaptic potentials (EPSPs) were evoked in PoM cells by trains of 5 electrical pulses at 20 Hz frequency applied to corticothalamic fibers. After carbachol was applied to mimic activation of the cholinergic neuromodulatory system corticothalamic EPSP amplitudes were reduced, while facilitation of EPSP amplitudes was enhanced for each next pulse in the series. Such cholinergic control of layer VI corticothalamic synapses in PoM may be used as gain modulator for the transfer of the peripheral sensory information to the cortex.

Impact of meditation on emotional processing, and its clinical applications, has recently drawn significant interest. In this visual event-related potential (ERP) study we investigated whether long-term meditation practitioners exhibit different ERP responses to the emotional load of stimuli (IAPS pictures) than control subjects with no experience in meditation. Differences were observed in the late positive potential (LPP). LPP amplitude is typically greater in ERPs evoked by emotionally arousing scenes, specifically negative images, compared to neutral scenes. This effect was also replicated in our study, but not in case of meditators' frontal scalp regions, who differed significantly in this respect from control subjects. Our findings provide support for different emotional processing in meditation practitioners: at high levels of processing meditators are less affected by stimuli with adverse emotional load, while processing of positive stimuli remains unaltered. To further confirm this observation, a long-term longitudinal random assignment study would be desirable., (Copyright © 2011 Elsevier Ireland Ltd and the Japan Neuroscience Society. All rights reserved.)

The vibrissa-barrel system of rodents has become one of the dominant models for studying sensory information processing. Fast oscillations (>200 Hz) have been shown to play an important role in cortical integration of inputs from several whiskers. The mechanism subserving such integration remains, however, unknown. To address this issue, we examined the influence of the gap junction blocker (carbenoxolone, CBX) topically applied on the cortical surface on the high frequency component evoked by multiple-whisker stimulation. The magnitude of the fast oscillatory response to simultaneous stimulation of three whiskers was shown to be higher compared to its linear prediction (defined as the sum of corresponding single whisker responses). Application of CBX eliminated this supra-linear enhancement of fast oscillations. These results indicate that gap junctions are involved in the synchronization of cortical high frequency oscillations and integration of multiple whisker responses., (Copyright © 2011 Elsevier Inc. All rights reserved.)

Objective: 5-12 Hz oscillations, observed in cortical LFP of awake rats during quiet immobility, were proposed to be either (i) epileptic events or (ii) physiological alpha-like oscillations, manifesting an idling state of the cortex. We aimed to test this controversy., Methods: We recorded LFP from the barrel cortex of awake Wistar rats, while applying weak tactile (whisker) and stronger arousing (electrical) stimuli., Results: We observed a mean effect of desynchronization of the 5-12 Hz rhythm by the weak tactile stimulation. Arousal reduced the incidence of the 5-12 Hz oscillations and increased the desynchronizing power of tactile stimuli., Conclusions: Oscillations that can be disrupted by weak, purely tactile stimulation, and whose incidence is reduced by increased arousal, should be interpreted as a physiological phenomenon typical for behavioral idling while the cerebral cortex maintains sensory sensitivity., Significance: Our results contradict the view that the 5-12 Hz oscillatory activity, often observed in fronto-parietal cortical regions of Wistar rats, represents epileptic discharges. Rather, this activity provides a model for studying the physiology of alpha/mu oscillations., (Copyright © 2010 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.)

Local field potentials have good temporal resolution but are blurred due to the slow spatial decay of the electric field. For simultaneous recordings on regular grids one can reconstruct efficiently the current sources (CSD) using the inverse Current Source Density method (iCSD). It is possible to decompose the resultant spatiotemporal information about the current dynamics into functional components using Independent Component Analysis (ICA). We show on test data modeling recordings of evoked potentials on a grid of 4 × 5 × 7 points that meaningful results are obtained with spatial ICA decomposition of reconstructed CSD. The components obtained through decomposition of CSD are better defined and allow easier physiological interpretation than the results of similar analysis of corresponding evoked potentials in the thalamus. We show that spatiotemporal ICA decompositions can perform better for certain types of sources but it does not seem to be the case for the experimental data studied. Having found the appropriate approach to decomposing neural dynamics into functional components we use the technique to study the somatosensory evoked potentials recorded on a grid spanning a large part of the forebrain. We discuss two example components associated with the first waves of activation of the somatosensory thalamus. We show that the proposed method brings up new, more detailed information on the time and spatial location of specific activity conveyed through various parts of the somatosensory thalamus in the rat.

We describe a computational method for assessing functional connectivity in sensory neuronal networks. The method, which we term cross-trial correlation, can be applied to signals representing local field potentials (LFPs) evoked by sensory stimulations and utilizes their trial-to-trial variability. A set of single trial samples of a given post-stimulus latency from consecutive evoked potentials (EPs) recorded at a given site is correlated with such sets for all other latencies and recording sites. The results of this computation reveal how neuronal activities at various sites and latencies correspond to activation of other sites at other latencies. The method was used to investigate the functional connectivity of thalamo-cortical network of somatosensory system in behaving rats at two levels of alertness: habituated and aroused. We analyzed potentials evoked by vibrissal deflections recorded simultaneously from the ventrobasal thalamus and barrel cortex. The cross-trial correlation analysis applied to the early post-stimulus period (<25 ms) showed that the magnitude of the population spike recorded in the thalamus at 5 ms post-stimulus correlated with the cortical activation at 6-13 ms post-stimulus. This correlation value was reduced at 6-9 ms, i.e. at early postsynaptic cortical response, with increased level of the animals' arousal. Similarly, the aroused state diminished positive thalamo-cortical correlation for subsequent early EP waves, whereas the efficacy of an indirect cortico-fugal inhibition (over 15 ms) did not change significantly. Thus we were able to characterize the state related changes of functional connections within the thalamo-cortical network of behaving animals.

Estimation of the continuous current-source density in bulk tissue from a finite set of electrode measurements is a daunting task. Here we present a methodology which allows such a reconstruction by generalizing the one-dimensional inverse CSD method. The idea is to assume a particular plausible form of CSD within a class described by a number of parameters which can be estimated from available data, for example a set of cubic splines in 3D spanned on a fixed grid of the same size as the set of measurements. To avoid specificity of particular choice of reconstruction grid we add random jitter to the points positions and show that it leads to a correct reconstruction. We propose different ways of improving the quality of reconstruction which take into account the sources located outside the recording region through appropriate boundary treatment. The efficiency of the traditional CSD and variants of inverse CSD methods is compared using several fidelity measures on different test data to investigate when one of the methods is superior to the others. The methods are illustrated with reconstructions of CSD from potentials evoked by stimulation of a bunch of whiskers recorded in a slab of the rat forebrain on a grid of 4x5x7 positions.

Depressive states in both healthy individuals and those with major depressive disorder exhibit differences primarily in symptom severity rather than symptom type, suggesting that there is a spectrum of depressive symptoms. The increasing prevalence of mild depression carries lifelong implications, emphasizing its clinical and social significance, which parallels that of moderate depression. Early intervention and psychotherapy have shown effective outcomes in subthreshold depression. Electroencephalography serves as a non-invasive, powerful tool in depression research, with many studies employing it to discover biomarkers and explore underlying mechanisms for the identification and diagnosis of depression. However, the efficacy of these biomarkers in distinguishing various depressive states in healthy individuals and in understanding the associated mechanisms remains uncertain. In our study, we examined the power spectrum density and the region-based phase-locking value in healthy individuals with various depressive states during their resting state. We found significant differences in neural activity, even among healthy individuals. Participants were categorized into high, middle, and low depressive state groups based on their response to a questionnaire, and eyes-open resting-state electroencephalography was conducted. We observed significant differences among the different depressive state groups in theta- and betaband power, as well as correlations in the theta–beta ratio in the frontal lobe and phase-locking connections in the frontal, parietal, and temporal lobes. Standardized low-resolution electromagnetic tomography analysis for source localization comparing the differences in resting-state networks among the three depressive state groups showed significant differences in the frontal and temporal lobes. We anticipate that our study will contribute to the development of effective biomarkers for the early detection and prevention of depression. [ABSTRACT FROM AUTHOR]

Alterations in functional connectivity (FC) have been observed in individuals with Alzheimer's disease (AD) with elevated amyloid (Aβ) and tau. However, it is not yet known whether directed FC is already influenced by Aβ and tau load in cognitively healthy (CH) individuals. A 21-channel electroencephalogram (EEG) was used from 46 CHs classified based on cerebrospinal fluid (CSF) Aβ tau ratio: pathological (CH-PAT) or normal (CH-NAT). Directed FC was estimated with Partial Directed Coherence in frontal, temporal, parietal, central, and occipital regions. We also examined the correlations between directed FC and various functional metrics, including neuropsychology, cognitive reserve, MRI volumetrics, and heart rate variability between both groups. Compared to CH-NATs, the CH-PATs showed decreased FC from the temporal regions, indicating a loss of relative functional importance of the temporal regions. In addition, frontal regions showed enhanced FC in the CH-PATs compared to CH-NATs, suggesting neural compensation for the damage caused by the pathology. Moreover, CH-PATs showed greater FC in the frontal and occipital regions than CH-NATs. Our findings provide a useful and non-invasive method for EEG-based analysis to identify alterations in brain connectivity in CHs with a pathological versus normal CSF Aβ/tau. This study reveals disrupted brain functional connectivity as an early biomarker in cognitively healthy individuals with pathological CSF amyloid/tau, aiding early Alzheimer's detection. [ABSTRACT FROM AUTHOR]

Our understanding of human brain function can be greatly aided by studying analogous brain structures in other organisms. One brain structure with neurochemical and anatomical homology throughout vertebrate species is the locus coeruleus (LC), a small collection of norepinephrine (NE)-containing neurons in the brainstem that project throughout the central nervous system. The LC is involved in nearly every aspect of brain function, including arousal and learning, which has been extensively examined in rats and nonhuman primates using single-unit recordings. Recent work has expanded into putative LC single-unit electrophysiological recordings in a nonmodel species, the zebra finch. Given the importance of correctly identifying analogous structures as research efforts expand to other vertebrates, we suggest adoption of consensus anatomical and electrophysiological guidelines for identifying LC neurons across species when evaluating brainstem single-unit spiking or calcium imaging. Such consensus criteria will allow for confident cross-species understanding of the roles of the LC in brain function and behavior. [ABSTRACT FROM AUTHOR]

Dynamic states of the brain determine the way information is processed in local neural networks. We have applied classical conditioning paradigm in order to study whether habituated and aroused states can be differentiated in single barrel column of rat's somatosensory cortex by means of analysis of field potentials evoked by stimulation of a single vibrissa. A new method using local classifiers is presented which allows for reliable and meaningful classification of single evoked potentials which might be consequently attributed to different functional states of the cortical column.

In order to understand the processing of sensory information in different behavioral situations we recorded evoked potentials (EP) to stimulation of a single vibrissa in the barrel cortex of non-anesthetized rat. We attributed the two principal components of the first negative wave (N1) of the cortical EP to the activation of two pyramidal cell populations (supra- and infragranular) of the central barrel-column. A positive wave of longer latency (P2) reflected the activation of the neighboring columns of the barrel cortex. The EPs recorded continuously throughout the experiment could be sorted into two classes dominated by the activity of either infra- or supragranular pyramidal cells. The introduction of an aversive contextual stimuli increased the amplitude of the second component of the N1 wave, which is built up by activation of infragranular cells, and the amplitude of the P2 wave representing excitation of neighboring columns. We hypothesize that increased activity of infragranular cells activates a cortico-thalamo-cortical loop going through the POm nucleus, which finally excites wider areas of primary somatosensory cortex. This spread of activity enables the comparison of information from neighboring vibrissae at the mystacial pad. The general cortical activation caused by the introduction of the contextual stimuli might be induced by noradrenergic and/or cholinergic systems. Prolonged contextual stimulation causes habituation processes, which return the cortical network to an idle state.

Evoked potentials (EPs) recorded within the primary sensory cortex of non-anesthetized rats vary considerably with each peripheral stimulation. We have previously shown that most of this variance reflects the shift of cortical activation between habituated and aroused states. Here we show that a method of matching the potential's course by wavelet functions can reliably differentiate single EPs and may therefore, be used as a probe for indicating the current activation state of the cortex.