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Introduction: The human brain is an intricate structure composed of interconnected modular networks, whose organization is known to balance the principles of segregation and integration, enabling rapid information exchange and the generation of coherent brain states. Segregation involves the specialization of brain regions for specific tasks, while integration facilitates communication among these regions, allowing for efficient information flow. Several factors influence this balance, including maturation, aging, and the insurgence of neurological disorders like epilepsy, stroke, or cancer. To gain insights into information processing and connectivity recovery, we devised a controllable in vitro model to mimic and investigate the effects of different segregation and integration ratios over time. Methods: We designed a cross-shaped polymeric mask to initially establish four independent sub-populations of cortical neurons and analyzed how the timing of its removal affected network development. We evaluated the morphological and functional features of the networks from 11 to 18 days in vitro (DIVs) with immunofluorescence techniques and micro-electrode arrays (MEAs). Results: The removal of the mask at different developmental stages of the network lead to strong variations in the degree of intercommunication among the four assemblies (altering the segregation/integration balance), impacting firing and bursting parameters. Early removal (after 5 DIVs) resulted in networks with a level of integration similar to homogeneous controls (without physical constraints). In contrast, late removal (after 15 DIVs) hindered the formation of strong inter-compartment connectivity, leading to more clustered and segregated assemblies. Discussion: A critical balance between segregation and integration was observed when the mask was removed at DIV 10, allowing for the formation of a strong connectivity among the still-separated compartments, thus demonstrating the existence of a time window in network development in which it is possible to achieve a balance between segregation and integration. [ABSTRACT FROM AUTHOR]

The claustrum is an ancient telencephalic subcortical structure displaying extensive, reciprocal connections with much of the cortex and receiving projections from thalamus, amygdala, and hippocampus. This structure has a general role in modulating cortical excitability and is considered to be engaged in different cognitive and motor functions, such as sensory integration and perceptual binding, salience-guided attention, top-down executive functions, as well as in the control of brain states, such as sleep and its interhemispheric integration. The present study is the first to describe in detail a projection from the claustrum to the striatum in the macaque brain. Based on tracer injections in different striatal regions and in different cortical areas, we observed a rough topography of the claustral connectivity, thanks to which a claustral zone projects to both a specific striatal territory and to cortical areas involved in a network projecting to the same striatal territory. The present data add new elements of complexity of the basal ganglia information processing mode in motor and non-motor functions and provide evidence for an influence of the claustrum on both cortical functional domains and cortico-basal ganglia circuits. [ABSTRACT FROM AUTHOR]

IntroductionThe human brain is an intricate structure composed of interconnected modular networks, whose organization is known to balance the principles of segregation and integration, enabling rapid information exchange and the generation of coherent brain states. Segregation involves the specialization of brain regions for specific tasks, while integration facilitates communication among these regions, allowing for efficient information flow. Several factors influence this balance, including maturation, aging, and the insurgence of neurological disorders like epilepsy, stroke, or cancer. To gain insights into information processing and connectivity recovery, we devised a controllable in vitro model to mimic and investigate the effects of different segregation and integration ratios over time.MethodsWe designed a cross-shaped polymeric mask to initially establish four independent sub-populations of cortical neurons and analyzed how the timing of its removal affected network development. We evaluated the morphological and functional features of the networks from 11 to 18 days in vitro (DIVs) with immunofluorescence techniques and micro-electrode arrays (MEAs).ResultsThe removal of the mask at different developmental stages of the network lead to strong variations in the degree of intercommunication among the four assemblies (altering the segregation/integration balance), impacting firing and bursting parameters. Early removal (after 5 DIVs) resulted in networks with a level of integration similar to homogeneous controls (without physical constraints). In contrast, late removal (after 15 DIVs) hindered the formation of strong inter-compartment connectivity, leading to more clustered and segregated assemblies.DiscussionA critical balance between segregation and integration was observed when the mask was removed at DIV 10, allowing for the formation of a strong connectivity among the still-separated compartments, thus demonstrating the existence of a time window in network development in which it is possible to achieve a balance between segregation and integration.

Under what conditions can prefrontal cortex direct the composition of brain states, to generate coherent streams of thoughts? Using a simplified Potts model of cortical dynamics, crudely differentiated into two halves, we show that once activity levels are regulated, so as to disambiguate a single temporal sequence, whether the contents of the sequence are mainly determined by the frontal or by the posterior half, or by neither, depends on statistical parameters that describe its microcircuits. The frontal cortex tends to lead if it has more local attractors, longer lasting and stronger ones, in order of increasing importance. Its guidance is particularly effective to the extent that posterior cortices do not tend to transition from state to state on their own. The result may be related to prefrontal cortex enforcing its temporally-oriented schemata driving coherent sequences of brain states, unlike the atemporal "context" contributed by the hippocampus. Modelling a mild prefrontal (vs. posterior) lesion offers an account of mind-wandering and event construction deficits observed in prefrontal patients. [ABSTRACT FROM AUTHOR]

Objective: Several studies have attributed epileptic activities in temporal lobe epilepsy (TLE) to the hippocampus; however, the participation of nonhippocampal neuronal networks in the development of TLE is often neglected. Here, we sought to understand how these nonhippocampal networks are involved in the pathology that is associated with TLE disease. Methods: A kainic acid (KA) model of temporal lobe epilepsy was induced by injecting KA into dorsal hippocampus of C57BL/6J mice. Network activation after spontaneous seizure was assessed using c‐Fos expression. Protocols to induce seizure using visual or auditory stimulation were developed, and seizure onset zone (SOZ) and frequency of epileptic spikes were evaluated using electrophysiology. The hippocampus was removed to assess seizure recurrence in the absence of hippocampus. Results: Our results showed that cortical and hippocampal epileptic networks are activated during spontaneous seizures. Perturbation of these networks using visual or auditory stimulation readily precipitates seizures in TLE mice; the frequency of the light‐induced or noise‐induced seizures depends on the induction modality adopted during the induction period. Localization of SOZ revealed the existence of cortical and hippocampal SOZ in light‐induced and noise‐induced seizures, and the development of local and remote epileptic spikes in TLE occurs during the early stage of the disease. Importantly, we further discovered that removal of the hippocampi does not stop seizure activities in TLE mice, revealing that seizures in TLE mice can occur independent of the hippocampus. Significance: This study has shown that the network pathology that evolves in TLE is not localized to the hippocampus; rather, remote brain areas are also recruited. The occurrence of light‐induced or noise‐induced seizures and epileptic discharges in epileptic mice is a consequence of the activation of nonhippocampal brain areas. This work therefore demonstrates the fundamental role of nonhippocampal epileptic networks in generating epileptic activities with or without the hippocampus in TLE disease. [ABSTRACT FROM AUTHOR]

Background and Hypothesis Schizophrenia is a multidimensional disease. This study proposes a new research framework that combines multimodal meta-analysis and genetic/molecular architecture to solve the consistency in neuroimaging biomarkers of schizophrenia and whether these link to molecular genetics. Study Design We systematically searched Web of Science, PubMed, and BrainMap for the amplitude of low-frequency fluctuations (ALFF) or fractional ALFF, regional homogeneity, regional cerebral blood flow, and voxel-based morphometry analysis studies investigating schizophrenia. The pooled-modality, single-modality, and illness duration-dependent meta-analyses were performed using the activation likelihood estimation algorithm. Subsequently, Spearman correlation and partial least squares regression analyses were conducted to assess the relationship between identified reliable convergent patterns of multimodality and neurotransmitter/transcriptome, using prior molecular imaging and brain-wide gene expression. Study Results In total, 203 experiments comprising 10 613 patients and 10 461 healthy controls were included. Multimodal meta-analysis showed that brain regions of significant convergence in schizophrenia were mainly distributed in the frontotemporal cortex, anterior cingulate cortex, insula, thalamus, striatum, and hippocampus. Interestingly, the analyses of illness-duration subgroups identified aberrant functional and structural evolutionary patterns: Lines from the striatum to the cortical core networks to extensive cortical and subcortical regions. Subsequently, we found that these robust multimodal neuroimaging abnormalities were associated with multiple neurobiological abnormalities, such as dopaminergic, glutamatergic, serotonergic, and GABAergic systems. Conclusions This work links transcriptome/neurotransmitters with reliable structural and functional signatures of brain abnormalities underlying disease effects in schizophrenia, which provides novel insight into the understanding of schizophrenia pathophysiology and targeted treatments. [ABSTRACT FROM AUTHOR]

Traditional neuroimaging methods have identified alterations in brain activity patterns following mild traumatic brain injury (mTBI), particularly during rest, complex tasks, and normal vision. However, studies using graph theory to examine brain network changes in mTBI have produced varied results, influenced by the specific networks and task demands analyzed. In our study, we employed functional MRI to observe 17 mTBI patients and 54 healthy individuals as they viewed a simple, non-narrative underwater film, simulating everyday visual tasks. This approach revealed significant mTBI-related changes in network connectivity, efficiency, and organization. Specifically, the mTBI group exhibited higher overall connectivity and local network specialization, suggesting enhanced information integration without overwhelming the brain’s processing capabilities. Conversely, these patients showed reduced network segregation, indicating a less compartmentalized brain function compared to healthy controls. These patterns were consistent across various visual cortex subnetworks, except in primary visual areas. Our findings highlight the potential of using naturalistic stimuli in graph-based neuroimaging to understand brain network alterations in mTBI and possibly other conditions affecting brain integration.

Previous studies have found facial emotion recognition (FER) impairments in individuals with epilepsy. While such deficits have been extensively explored in individuals with focal temporal lobe epilepsy, studies on individuals with generalized epilepsies are rare. However, studying FER specifically in individuals with juvenile myoclonic epilepsy (JME) is particularly interesting since they frequently suffer from social and neuropsychological difficulties in addition to epilepsy-specific symptoms. Furthermore, recent brain imaging studies have shown subtle microstructural alterations in individuals with JME. FER is considered a fundamental social skill that relies on a distributed neural network, which could be disturbed by network dysfunction in individuals with JME. This cross-sectional study aimed to examine FER and social adjustment in individuals with JME. It included 27 patients with JME and 27 healthy controls. All subjects underwent an Ekman-60 Faces Task to examine FER and neuropsychological tests to assess social adjustment as well as executive functions, intelligence, depression, and personality traits. Individuals with JME performed worse in global FER and fear and surprise recognition than healthy controls. However, probably due to the small sample size, no significant difference was found between the two groups. A potential FER impairment needs to be confirmed in further studies with larger sample size. If so, patients with JME could benefit from addressing possible deficits in FER and social difficulties when treated. By developing therapeutic strategies to improve FER, patients could be specifically supported with the aim of improving social outcomes and quality of life. [ABSTRACT FROM AUTHOR]

Hippocampus-neocortex interactions during sleep are critical for memory processes: Hippocampally initiated replay contributes to memory consolidation in the neocortex and hippocampal sharp wave/ripples modulate cortical activity. Yet, the spatial and temporal patterns of this interaction are unknown. With voltage imaging, electrocorticography, and laminarly resolved hippocampal potentials, we characterized cortico-hippocampal signaling during anesthesia and nonrapid eye movement sleep. We observed neocortical activation transients, with statistics suggesting a quasi-critical regime, may be helpful for communication across remote brain areas. From activity transients, we identified, in a data-driven fashion, three functional networks. A network overlapping with the default mode network and centered on retrosplenial cortex was the most associated with hippocampal activity. Hippocampal slow gamma rhythms were strongly associated to neocortical transients, even more than ripples. In fact, neocortical activity predicted hippocampal slow gamma and followed ripples, suggesting that consolidation processes rely on bidirectional signaling between hippocampus and neocortex. [ABSTRACT FROM AUTHOR]

• There is a heterogeneous expression of GPCR-mRNA across all cortical regions in mouse, macaque and human brains. • However, the distribution of these GPCR-mRNA shows strong spatial correlations among congregated Gq/11-, Gs-, and Gi/o-linked systems. • Spatial correlation strength increases with age but dropps when randomly removing genes from their corresponding groups. • These findings suggest that the expression patterns of GPCR subtypes and receptor families are intricately intertwined. G-protein coupled receptors (GPCRs) modulate brain function by signaling through heterotrimeric G q/11 , G s , and G i/o protein subtypes. Researchers frequently study neuromodulation via these GPCR-subtypes on a 'cell-by-cell' basis. Although useful to explore a small number of interactions among neuromodulatory systems under controlled settings, this approach fails to account for a global organization of GPCRs in the brain. Furthermore, because multiple receptors and signal transduction pathways are present in single cells, neuromodulation is controlled by groups of GPCRs rather than by individual receptors. Using an integrative approach, the present study examined how large GPCR-subtype communities (ensembles) are expressed in different anatomical regions. Using the Allen Brain Atlas (http://www.brain-map.org/), we analyzed the mRNA expression energy of hundreds of GPCR-subtypes located in mouse, macaque, and human brains. We found that although there was a heterogeneous expression of GPCR-mRNA across all cortical regions, there were strong spatial correlations among congregated G q/11 -, G s -, and G i/o -linked systems. Correlation strength increased with age but dropped when randomly removing genes from their corresponding groups. These findings suggest that the expression patterns of GPCR subtypes and receptor families are intricately intertwined. Well-orchestrated interactions by neuromodulatory-GPCR ensembles could be crucial for the brain to function as a highly integrated complex system. [ABSTRACT FROM AUTHOR]

Humans and other animals learn to extract general concepts from sensory experience without extensive teaching. This ability is thought to be facilitated by offline states like sleep where previous experiences are systemically replayed. However, the characteristic creative nature of dreams suggests that learning semantic representations may go beyond merely replaying previous experiences. We support this hypothesis by implementing a cortical architecture inspired by generative adversarial networks (GANs). Learning in our model is organized across three different global brain states mimicking wakefulness, non-rapid eye movement (NREM), and REM sleep, optimizing different, but complementary, objective functions. We train the model on standard datasets of natural images and evaluate the quality of the learned representations. Our results suggest that generating new, virtual sensory inputs via adversarial dreaming during REM sleep is essential for extracting semantic concepts, while replaying episodic memories via perturbed dreaming during NREM sleep improves the robustness of latent representations. The model provides a new computational perspective on sleep states, memory replay, and dreams, and suggests a cortical implementation of GANs.

Transient propagation of information across neuronal assembles is thought to underlie many cognitive processes. However, the nature of the neural code that is embedded within these transmissions remains uncertain. Much of our understanding of how information is transmitted among these assemblies has been derived from computational models. While these models have been instrumental in understanding these processes they often make simplifying assumptions about the biophysical properties of neurons that may influence the nature and properties expressed. To address this issue we created an in vitro analog of a feed-forward network composed of two small populations (also referred to as assemblies or layers) of living dissociated rat cortical neurons. The populations were separated by, and communicated through, a microelectromechanical systems (MEMS) device containing a strip of microscale tunnels. Delayed culturing of one population in the first layer followed by the second a few days later induced the unidirectional growth of axons through the microtunnels resulting in a primarily feed-forward communication between these two small neural populations. In this study we systematically manipulated the number of tunnels that connected each layer and hence, the number of axons providing communication between those populations. We then assess the effect of reducing the number of tunnels has upon the properties of between-layer communication capacity and fidelity of neural transmission among spike trains transmitted across and within layers. We show evidence based on Victor-Purpura's and van Rossum's spike train similarity metrics supporting the presence of both rate and temporal information embedded within these transmissions whose fidelity increased during communication both between and within layers when the number of tunnels are increased. We also provide evidence reinforcing the role of synchronized activity upon transmission fidelity during the spontaneous synchronized network burst events that propagated between layers and highlight the potential applications of these MEMs devices as a tool for further investigation of structure and functional dynamics among neural populations.

Intracortical inhibition plays a critical role in shaping activity patterns in the mature cortex. However, little is known about the structure of inhibition in early development prior to the onset of sensory experience, a time when spontaneous activity exhibits long-range correlations predictive of mature functional networks. Here, using calcium imaging of GABAergic neurons in the ferret visual cortex, we show that spontaneous activity in inhibitory neurons is already highly organized into distributed modular networks before visual experience. Inhibitory neurons exhibit spatially modular activity with long-range correlations and precise local organization that is in quantitative agreement with excitatory networks. Furthermore, excitatory and inhibitory networks are strongly co-aligned at both millimeter and cellular scales. These results demonstrate a remarkable degree of organization in inhibitory networks early in the developing cortex, providing support for computational models of self-organizing networks and suggesting a mechanism for the emergence of distributed functional networks during development.

Over the past decade extensive research has examined the segregation of the human brain into large-scale functional networks. The resulting network maps, i.e. parcellations, are now commonly used for the a priori identification of functional networks. However, the use of these parcellations, particularly in developmental and clinical samples, hinges on four fundamental assumptions: (1) the various parcellations are equally able to recover the networks of interest; (2) adult-derived parcellations well represent the networks in children's brains; (3) network properties, such as within-network connectivity, are reliably measured across parcellations; and (4) parcellation selection does not impact the results with regard to individual differences in given network properties. In the present study we examined these assumptions using eight common parcellation schemes in two independent developmental samples. We found that the parcellations are equally able to capture networks of interest in both children and adults. However, networks bearing the same name across parcellations (e.g., default network) do not produce reliable within-network measures of functional connectivity. Critically, parcellation selection significantly impacted the magnitude of associations of functional connectivity with age, poverty, and cognitive ability, producing meaningful differences in interpretation of individual differences in functional connectivity based on parcellation choice. Our findings suggest that work employing parcellations may benefit from the use of multiple schemes to confirm the robustness and generalizability of results. Furthermore, researchers looking to gain insight into functional networks may benefit from employing more nuanced network identification approaches such as using densely-sampled data to produce individual-derived network parcellations. A transition towards precision neuroscience will provide new avenues in the characterization of functional brain organization across development and within clinical populations.

Dysfunctional brain networks have been found in patients with major depressive disorder (MDD). In this study, to verify this in a more straightforward way, we investigated the intrinsic organization of brain networks in MDD by leveraging the resting-state functional near-infrared spectroscopy (rs-fNIRS). Thirty-four MDD patients (24 females, 38.41 ± 13.14 years old) and thirty healthy controls (22 females, 34.43 ± 5.03 years old) underwent a 10 min rest while their brain activity was recorded via fNIRS. The results showed that MDD patients and healthy controls exhibited similar resting-state functional connectivity. Moreover, the depression group showed lower small-world Lambda (1.12 ± 0.04 vs. 1.16 ± 0.10, p = 0.04) but higher global efficiency (0.51 ± 0.03 vs. 0.48 ± 0.05, p = 0.03) than the control group. Importantly, MDD patients, as opposed to healthy controls, showed a significantly lower nodal local efficiency at the left middle occipital gyrus (0.56 ± 0.36 vs. 0.81 ± 0.20, pFDR < 0.05), which predicted the level of depression in MDD (r = 0.45, p = 0.01, R2 = 0.15). In sum, we found a more integrated brain network in MDD patients with a lower nodal local efficiency at the occipital hub, which could predict depressive symptoms.

Aberrant cognitive network activity and cognitive deficits are established features of chronic pain. However, the nature of cognitive network alterations associated with chronic pain and their underlying mechanisms require elucidation. Here, we report that the claustrum, a subcortical nucleus implicated in cognitive network modulation, is activated by acute painful stimulation and pain-predictive cues in healthy participants. Moreover, we discover pathological activity of the claustrum and a region near the posterior inferior frontal sulcus of the right dorsolateral prefrontal cortex (piDLPFC) in migraine patients during acute pain and cognitive task performance. Dynamic causal modeling suggests a directional influence of the claustrum on activity in this piDLPFC region, and diffusion weighted imaging verifies their structural connectivity. These findings advance understanding of claustrum function during acute pain and provide evidence of a possible circuit mechanism driving cognitive impairments in chronic pain. [Display omitted] • A region, piDLPFC, aberrantly responds to cognitive load in migraine patients • A claustrum-piDLPFC circuit is activated by pain in healthy subjects • This circuit excessively responds to pain and cognitive load in migraine patients • Connectivity analyses suggest an excitatory claustrum projection to piDLPFC Many people with chronic pain suffer cognitive deficits. Using magnetic resonance imaging (MRI), Stewart et al. discover a pain-sensitive, claustrum-cortex brain circuit active in migraine patients when thinking through a task, even when not in pain. These data reveal a potential mechanism underlying the cortical network and cognitive dysfunction observed in chronic pain. [ABSTRACT FROM AUTHOR]

To understand how neural circuits process information, it is essential to identify the relationship between computation and circuit organization. Rich clubs, highly interconnected sets of neurons, are known to propagate a disproportionate amount of information within cortical circuits. Here, we test the hypothesis that rich clubs also perform a disproportionate amount of computation. To do so, we recorded the spiking activity of on average ∼300 well-isolated individual neurons from organotypic cortical cultures. We then constructed weighted, directed networks reflecting the effective connectivity between the neurons. For each neuron, we quantified the amount of computation it performed based on its inputs. We found that rich-club neurons compute ∼160% more information than neurons outside of the rich club. The amount of computation performed in the rich club was proportional to the amount of information propagation by the same neurons. This suggests that in these circuits, information propagation drives computation. In total, our findings indicate that rich-club organization in effective cortical circuits supports not only information propagation but also neural computation. Here we answer the question of whether rich-club organization in functional networks of cortical circuits supports neural computation. To do so, we combined network analysis with information theoretic tools to analyze the spiking activity of hundreds of neurons recorded from organotypic cultures of mouse somatosensory cortex. We found that neurons in rich clubs computed significantly more than neurons outside of rich clubs, suggesting that rich clubs do support computation in cortical circuits. Indeed, the amount of computation that we found in the rich clubs was proportional to the amount of information they propagate, suggesting that in these circuits, information propagation drives computation.

Successful surgical treatment of patients with focal drug-resistant epilepsy remains challenging, especially in cases for which it is difficult to define the area of cortex from which seizures originate, the seizure onset zone (SOZ). Various diagnostic methods are needed to select surgical candidates and determine the extent of resection. Interictal magnetoencephalography (MEG) with source imaging has proven to be useful for presurgical evaluation, but the use of ictal MEG data remains limited. The purpose of the present study was to determine whether pre-ictal variations of spectral properties of neural activity from ictal MEG recordings are predictive of SOZ location.We performed a 4 h overnight MEG recording in an 8-year-old child with drug-resistant focal epilepsy of suspected right fronto-temporal origin and captured one ~45-s seizure. The patient underwent a right temporal resection from the anterior temporal neocortex and amygdala to the mid-posterior temporal neocortex, sparing the hippocampus proper. She remains seizure-free 21 months postoperatively. The histopathological assessment confirmed frank focal cortical dysplasia (FCD) type IIa in the MEG-defined SOZ, which was based on source imaging of averaged ictal spikes at seizure onset. We investigated temporal changes (inter-ictal, pre-ictal, and ictal periods) together with spatial differences (SOZ vs. control regions) in spectral parameters of background brain activity, namely the aperiodic broadband offset and slope, and assessed how they confounded the interpretation of apparent variations of signal power in typical electrophysiological bands. Our data show that the SOZ was associated with a higher aperiodic offset and exponent during the seizure compared to control regions. Both parameters increased in all regions from 2 min before the seizure onwards. Regions anatomically closer to the SOZ also expressed higher values compared to contralateral regions, potentially indicating ictal spread. We also show that narrow-band power changes were caused by these fluctuations in the aperiodic component of ongoing brain activity. Our results indicate that the broadband aperiodic component of ongoing brain activity cannot be reduced to background noise of no physiological interest, and rather may be indicative of the neuropathophysiology of the SOZ. We believe these findings will inspire future studies of ictal MEG cases and confirm their significance.

Viewing the faces of familiar people selectively activates a distributed network of brain regions implicated in both the perceptual and nonperceptual processing of conspecifics. In this functional magnetic resonance imaging (fMRI) study, we investigate the influence of depth of famous-face processing on this network, comparing a passive incidental face processing to a task that required the extraction of identity and biographic information. We observed that the precuneus, ventromedial prefrontal cortex (vmPFC), anterior temporal face patch (ATFP), and the amygdala exhibit a selective response even during incidental face processing. At the same time, face selectivity was enhanced in the lateral anterior temporal lobe (latATL) and the posterior superior temporal sulcus (pSTS) when identity and information extraction was required. In addition, goal-directed identity and information extraction was associated with a recruitment of inferior frontal gyrus (IFG), whereas this region was deactivated during passive viewing. Collectively, these results show that: 1) in addition to active information extraction, the extended system is recruited by the passive retrieval of person-related knowledge and 2) active access to such knowledge modulates activity in latATL and pSTS, potentially mediated via control circuits in the IFG. NEW & NOTEWORTHY Information is extracted from familiar faces in both automatic and active modes. Using functional MRI, we show: 1) that automatic access results in the selective activation of nonperceptual brain regions, the precuneus, ventromedial prefrontal cortex, and the anterior face patch and amygdala, demonstrating the automaticity of access to information in these regions; 2) selective increases in the activation of the lateral anterior temporal lobe and posterior superior temporal gyrus when biographic information is actively extracted. [ABSTRACT FROM AUTHOR]

Successful surgical treatment of patients with focal drug-resistant epilepsy remains challenging, especially in cases for which it is difficult to define the area of cortex from which seizures originate, the seizure onset zone (SOZ). Various diagnostic methods are needed to select surgical candidates and determine the extent of resection. Interictal magnetoencephalography (MEG) with source imaging has proven to be useful for presurgical evaluation, but the use of ictal MEG data remains limited. The purpose of the present study was to determine whether pre-ictal variations of spectral properties of neural activity from ictal MEG recordings are predictive of SOZ location.We performed a 4 h overnight MEG recording in an 8-year-old child with drug-resistant focal epilepsy of suspected right fronto-temporal origin and captured one ~45-s seizure. The patient underwent a right temporal resection from the anterior temporal neocortex and amygdala to the mid-posterior temporal neocortex, sparing the hippocampus proper. She remains seizure-free 21 months postoperatively. The histopathological assessment confirmed frank focal cortical dysplasia (FCD) type IIa in the MEG-defined SOZ, which was based on source imaging of averaged ictal spikes at seizure onset. We investigated temporal changes (inter-ictal, pre-ictal, and ictal periods) together with spatial differences (SOZ vs. control regions) in spectral parameters of background brain activity, namely the aperiodic broadband offset and slope, and assessed how they confounded the interpretation of apparent variations of signal power in typical electrophysiological bands. Our data show that the SOZ was associated with a higher aperiodic offset and exponent during the seizure compared to control regions. Both parameters increased in all regions from 2 min before the seizure onwards. Regions anatomically closer to the SOZ also expressed higher values compared to contralateral regions, potentially indicating ictal spread. We also show that narrow-band power changes were caused by these fluctuations in the aperiodic component of ongoing brain activity. Our results indicate that the broadband aperiodic component of ongoing brain activity cannot be reduced to background noise of no physiological interest, and rather may be indicative of the neuropathophysiology of the SOZ. We believe these findings will inspire future studies of ictal MEG cases and confirm their significance. [ABSTRACT FROM AUTHOR]

Traditional neuroimaging methods have identified alterations in brain activity patterns following mild traumatic brain injury (mTBI), particularly during rest, complex tasks, and normal vision. However, studies using graph theory to examine brain network changes in mTBI have produced varied results, influenced by the specific networks and task demands analyzed. In our study, we employed functional MRI to observe 17 mTBI patients and 54 healthy individuals as they viewed a simple, non-narrative underwater film, simulating everyday visual tasks. This approach revealed significant mTBI-related changes in network connectivity, efficiency, and organization. Specifically, the mTBI group exhibited higher overall connectivity and local network specialization, suggesting enhanced information integration without overwhelming the brain's processing capabilities. Conversely, these patients showed reduced network segregation, indicating a less compartmentalized brain function compared to healthy controls. These patterns were consistent across various visual cortex subnetworks, except in primary visual areas. Our findings highlight the potential of using naturalistic stimuli in graph-based neuroimaging to understand brain network alterations in mTBI and possibly other conditions affecting brain integration.

Abstract Deep brain stimulation (DBS), a reversible and adjustable treatment for neurological and psychiatric refractory disorders, consists in delivering electrical currents to neuronal populations located in subcortical structures. The targets of DBS are spatially restricted, but connect to many parts of the brain, including the cortex, which might explain the observed clinical benefits in terms of symptomatology. The DBS mechanisms of action at a large scale are however poorly understood, which has motivated several groups to recently conduct many research programs to monitor cortical responses to DBS. Here we review the knowledge gathered from the use of electroencephalography (EEG) in patients treated by DBS. We first focus on the methodology to record and process EEG signals concurrently to DBS. In the second part of the review, we address the clinical and scientific benefits brought by EEG/DBS studies so far.

Multiple sensory signal, such as various visual stimuli, can be simultaneously transmitted and processed through different cortical areas. Using a biologically inspired model, we investigate the mechanism underlying such multiplexing in cortex. The network model is comprised of five feedforward-connected neural population of excitatory (E) and inhibitory (I) spiking neurons, each representing a cortical area. Numerical results indicate that multiple input signals are independently transmitted through feedforward neural networks via stochastic resonance (SR), and the transmission of information between adjacent cortical areas is altered by E-I relation of local cortical circuits. Due to different intrinsic properties of neurons, excitatory population can induce stochastic resonance to respond to low-frequency signal, and inhibitory neurons tend to respond to high-frequency signal through resonance. The E-I coupled neural ensemble shows selectivity for different input signal, which is gated by the gain between excitatory and inhibitory neurons. To be specific, neural network is inclined to gate-on signal with low-frequency when the excitation exceeds inhibition, whereas the high-frequency signal is selected. Moreover, neural signal can be transmitted from area to area only when the input frequency coincides with the inherent frequency of receivers in posterior areas, thus the independent conduction pathway is established through resonance. The transmission efficiency largely depends on the gain between excitatory and inhibitory input. Mean-field theory is further applied to validate the multiplexing in cortical networks and demonstrate the effective transmission of multiple information via SR in cortical networks. [ABSTRACT FROM AUTHOR]

We have characterized the in vitro and in vivo extracellular neural recording and stimulation properties of ruthenium oxide (RuOx) based microelectrodes. Cytotoxicity and functional neurotoxicity assays were carried out to confirm the in vitro biocompatibility of RuOx. Material extract assays, in accordance to ISO protocol "10993-5: Biological evaluation of medical devices", revealed no significant effect on neuronal cell viability or the functional activity of cortical networks. In vitro microelectrode arrays (MEAs), with indium tin oxide (ITO) sites modified with sputtered iridium oxide (IrOx) and RuOx in a single array, were developed for a direct comparison of electrochemical and recording performance of RuOx to ITO and IrOx deposited microelectrode sites. The impedance of the RuOx-coated electrodes measured by electrochemical impedance spectroscopy was notably lower than that of ITO electrodes, resulting in robust extracellular recordings from cortical networks in vitro. We found comparable signal-to-noise ratios (SNRs) for RuOx and IrOx, both significantly higher than the SNR for ITO. RuOx-based MEAs were also fabricated and implanted in the rat motor cortex to demonstrate manufacturability of the RuOx processing and acute recording capabilities in vivo. We observed single-unit extracellular action potentials with a SNR >22, representing a first step for neurophysiological recordings in vivo with RuOx based microelectrodes. A critical challenge in neural interface technology is the development of microelectrodes that have recording and electrical stimulation capabilities suitable for bidirectional communication between the external electronic device and the nervous system. The present study explores the feasibility and functional capabilities of ruthenium oxide microelectrodes as a neural interface. Significant improvement in electrochemical properties and neuronal recordings are reported when compared to commercially available indium tin oxide and was similar to that of iridium oxide electrodes. The data demonstrate the potential for future development of chronic neural interfaces using ruthenium oxide based microelectrodes for recording and stimulation. Image, graphical abstract [ABSTRACT FROM AUTHOR]

Schizophrenia patients have widespread deficits in neurocognitive functioning linked to underlying abnormalities in gamma oscillations that are readily measured by the 40 Hz auditory steady-state response (ASSR). Emerging interventions such as auditory-based targeted cognitive training (TCT) improve neurocognitive function in patients. While acute ASSR changes after 1 hour of TCT predict clinical and cognitive gains after a 30-hour course of TCT, the neural substrates of underlying shortand long-term TCT interventions are unknown. To determine the neural substrates underlying TCT-associated ASSR changes, a novel data analysis method was applied to assess the effective connectivity of gamma-band ASSR among estimated cortical sources. In this study, schizophrenia patients (N = 52) were randomized to receive either a treatment as usual (TAU; N = 22) or TAU augmented with TCT (N = 30). EEG recordings were obtained immediately before (T0) and after 1 hour of either computer games (TAU) or cognitive training (TCT; T1), and at 65 ± 15 days (mean ± SD) post-randomization (T2). Results showed increased connectivity from the left ventral middle cingulate gyrus to the left posterior cingulate gyrus, accompanied by decreased connectivity from the left Rolandic operculum (a region that includes auditory cortex) to the right ventral middle cingulate gyrus after 1 hour of TCT. After 30 hours, decreased connectivity from the frontal cortex to a region near the calcarine sulcus were detected. Auditory-based cognitive training drives shortand long-term plasticity in cortical network functioning in schizophrenia patients. These findings may help us understand the mechanisms underlying cognitive training effects in schizophrenia patients and enhance the development of pro-cognitive therapeutics. [ABSTRACT FROM AUTHOR]

The sensory cortex amplifies relevant features of external stimuli. This sensitivity and selectivity arise through the transformation of inputs by cortical circuitry. We characterize the circuit mechanisms and dynamics of cortical amplification by making large-scale simultaneous measurements of single cells in awake primates and testing computational models. By comparing network activity in both driven and spontaneous states with models, we identify the circuit as operating in a regime of non-normal balanced amplification. Incoming inputs are strongly but transiently amplified by strong recurrent feedback from the disruption of excitatory-inhibitory balance in the network. Strong inhibition rapidly quenches responses, thereby permitting the tracking of time-varying stimuli. • Population dynamics in area MT reveal the mechanisms of cortical amplification • Cortical amplification models can be differentiated using their distinct dynamics • The dynamics of area MT are consistent with a balanced amplification model • Balanced amplification increases sensitivity while maintaining fast dynamics Sensory circuits show high sensitivity to signals of interest even in noisy, changing environments. Pattadkal et al. place constraints on the circuitry for amplification using calcium imaging and electrophysiology in marmoset area MT. Different circuits for amplification are characterized by distinct dynamics. Area MT dynamics match a balanced amplification circuit. [ABSTRACT FROM AUTHOR]

Dissociated cortical neurons in vitro display spontaneously synchronized, low-frequency firing patterns, which can resemble the slow wave oscillations characterizing sleep in vivo. Experiments in humans, rodents, and cortical slices have shown that awakening or the administration of activating neuromodulators decrease slow waves, while increasing the spatio-temporal complexity of responses to perturbations. In this study, we attempted to replicate those findings using in vitro cortical cultures coupled with micro-electrode arrays and chemically treated with carbachol (CCh), to modulate sleep-like activity and suppress slow oscillations. We adapted metrics such as neural complexity (NC) and the perturbational complexity index (PCI), typically employed in animal and human brain studies, to quantify complexity in simplified, unstructured networks, both during resting state and in response to electrical stimulation. After CCh administration, we found a decrease in the amplitude of the initial response and a marked enhancement of the complexity during spontaneous activity. Crucially, unlike in cortical slices and intact brains, PCI in cortical cultures displayed only a moderate increase. This dissociation suggests that PCI, a measure of the complexity of causal interactions, requires more than activating neuromodulation and that additional factors, such as an appropriate circuit architecture, may be necessary. Exploring more structured in vitro networks, characterized by the presence of strong lateral connections, recurrent excitation, and feedback loops, may thus help to identify the features that are more relevant to support causal complexity.

Episodic memories reflect a bound representation of multimodal features that can be reinstated with varying precision. Yet little is known about how brain networks involved in memory, including the hippocampus and posterior-medial (PM) and anterior-temporal (AT) systems, interact to support the quality and content of recollection. Participants learned color, spatial, and emotion associations of objects, later reconstructing the visual features using a continuous color spectrum and 360-degree panorama scenes. Behaviorally, dependencies in memory were observed for the gist but not precision of event associations. Supporting this integration, hippocampus, AT, and PM regions showed increased connectivity and reduced modularity during retrieval compared to encoding. These inter-network connections tracked a multidimensional, objective measure of memory quality. Moreover, distinct patterns of connectivity tracked item color and spatial memory precision. These findings demonstrate how hippocampal-cortical connections reconfigure during episodic retrieval, and how such dynamic interactions might flexibly support the multidimensional quality of remembered events.

Objective: To evaluate brain networks for motor control of voice production in patients with treated unilateral vocal fold paralysis (UVFP).Study Design: Cross-sectional comparison.Methods: Nine UVFP patients treated by type I thyroplasty, and 11 control subjects were compared using magnetoencephalographic imaging to measure beta band (12-30 Hz) neural oscillations during voice production with perturbation of pitch feedback. Differences in beta band power relative to baseline were analyzed to identify cortical areas with abnormal activity within the 400 ms perturbation period and 125 ms beyond, for a total of 525 ms.Results: Whole-brain task-induced beta band activation patterns were qualitatively similar in both treated UVFP patients and healthy controls. Central vocal motor control plasticity in UVFP was expressed within constitutive components of central human communication networks identified in healthy controls. Treated UVFP patients exhibited statistically significant enhancement (P < 0.05) in beta band activity following pitch perturbation onset in left auditory cortex to 525 ms, left premotor cortex to 225 ms, and left and right frontal cortex to 525 ms.Conclusion: This study further corroborates that a peripheral motor impairment of the larynx can affect central cortical networks engaged in auditory feedback processing, vocal motor control, and judgment of voice-as-self. Future research to dissect functional relationships among constitutive cortical networks could reveal neurophysiological bases of central contributions to voice production impairment in UVFP. Those novel insights would motivate innovative treatments to improve voice production and reduce misalignment of voice-quality judgment between clinicians and patients.Level Of Evidence: 3b Laryngoscope, 129:2125-2130, 2019. [ABSTRACT FROM AUTHOR]

Successful episodic memory calls upon a number of different cognitive processes that are supported by the coordination of several large-scale cortical networks. Previous work from our group has demonstrated dissociable anatomic substrates at different stages of memory in patients with dementia due to Alzheimer's disease (AD). The aim of the current study was to extend the understanding of brain-behavior associations underlying a commonly administered neuropsychological assessment of verbal episodic memory (Rey Auditory Verbal Learning Test; RAVLT) by determining the cortical network contributions to the performance at early vs. late stages of list learning, delayed recall, and retention, in 235 very mild biomarker positive (A+/T+/N+) individuals diagnosed with amnestic mild cognitive impairment (aMCI; MMSE = 27.7). We measured cortical atrophy in four large-scale cortical networks impacted by AD: default mode (DMN), dorsal attention (DAN), frontoparietal (FPN), and language (LN) networks. We also evaluated the role of hippocampal atrophy at each stage of memory performance. Partial correlation analyses controlling for age, sex, and education and corrected for multiple comparisons revealed that early learning was most strongly associated with cortical thickness in the DAN, while late learning was most strongly associated with hippocampal volume, but also related to cortical thickness in the DAN, FPN, DMN, and LN. Delayed recall was associated most strongly with hippocampal volume, but was also related to cortical thickness in the FPN and DMN, while retention was associated only with hippocampal volume. These findings are consistent with prior models of the neural substrates of different stages of verbal list learning and retrieval, provide new insights into the cortical networks undergoing neurodegeneration even at very mild stages of prodromal AD, and inform our thinking about the networks and regions being interrogated by this kind of neuropsychological assessment of episodic memory. • Early learning is associated with cortical thickness in the dorsal attention network, and not with hippocampal volume. • Late learning is associated with hippocampal volume, but also to cortical thickness in the distributed cortical networks. • Delayed recall is associated with hippocampal volume and thickness in the frontoparietal and default mode networks. • Retention is associated only with hippocampal volume. • These findings provide new insights into the cortical networks undergoing neurodegeneration in prodromal AD. [ABSTRACT FROM AUTHOR]

Child maltreatment is a major cause of pediatric posttraumatic stress disorder (PTSD). Previous studies have not investigated potential differences in network architecture in maltreated youth with PTSD and those resilient to PTSD. High-resolution magnetic resonance imaging brain scans at 3 T were completed in maltreated youth with PTSD (n = 31), without PTSD (n = 32), and nonmaltreated controls (n = 57). Structural covariance network architecture was derived from between-subject intraregional correlations in measures of cortical thickness in 148 cortical regions (nodes). Interregional positive partial correlations controlling for demographic variables were assessed, and those correlations that exceeded specified thresholds constituted connections in cortical brain networks. Four measures of network centrality characterized topology, and the importance of cortical regions (nodes) within the network architecture were calculated for each group. Permutation testing and principle component analysis method were employed to calculate between-group differences. Principle component analysis is a methodological improvement to methods used in previous brain structural covariance network studies. Differences in centrality were observed between groups. Larger centrality was found in maltreated youth with PTSD in the right posterior cingulate cortex; smaller centrality was detected in the right inferior frontal cortex compared to youth resilient to PTSD and controls, demonstrating network characteristics unique to pediatric maltreatment-related PTSD. Larger centrality was detected in right frontal pole in maltreated youth resilient to PTSD compared to youth with PTSD and controls, demonstrating structural covariance network differences in youth resilience to PTSD following maltreatment. Smaller centrality was found in the left posterior cingulate cortex and in the right inferior frontal cortex in maltreated youth compared to controls, demonstrating attributes of structural covariance network topology that is unique to experiencing maltreatment. This work is the first to identify cortical thickness-based structural covariance network differences between maltreated youth with and without PTSD. We demonstrated network differences in both networks unique to maltreated youth with PTSD and those resilient to PTSD. The networks identified are important for the successful attainment of age-appropriate social cognition, attention, emotional processing, and inhibitory control. Our findings in maltreated youth with PTSD versus those without PTSD suggest vulnerability mechanisms for developing PTSD. [ABSTRACT FROM AUTHOR]

Highlights • Interaction between Extrinsic and Default Mode Networks are perturbed in psychiatric conditions. • Perturbed network interactions underlie cognitive deficits and psychiatric symptoms. • Perturbed network interactions related to excitatory/inhibitory neurotransmitter imbalances. • Childhood trauma can affect excitatory/inhibitory neurotransmitter imbalances. Abstract Over the last three decades there has been an accumulation of Magnetic Resonance Imaging (MRI) studies reporting that aberrant functional networks may underlie cognitive deficits and other symptoms across a range of psychiatric diagnoses. The use of pharmacological MRI and 1H-Magnetic Resonance Spectroscopy (1H-MRS) has allowed researchers to investigate how changes in network dynamics are related to perturbed excitatory and inhibitory neurotransmission in individuals with psychiatric conditions. More recently, changes in functional network dynamics and excitatory/inhibitory (E/I) neurotransmission have been linked to early childhood trauma, a major antecedents for psychiatric illness in adulthood. Here we review studies investigating whether perturbed network dynamics seen across psychiatric conditions are related to changes in E/I neurotransmission, and whether such changes could be linked to childhood trauma. Whilst there is currently a paucity of studies relating early traumatic experiences to altered E/I balance and network function, the research discussed here lead towards a plausible mechanistic hypothesis, linking early traumatic experiences to cognitive dysfunction and symptoms mediated by E/I neurotransmitter imbalances. [ABSTRACT FROM AUTHOR]

Abstract Ageing is associated with widespread alterations to the brain's anatomy and to attendant cortical networks. Yet, few studies to date have indexed anatomical covariance network differences within the age distribution of older adulthood, despite known phenotypic variation. Here, we explored cortical anatomical covariance networks in middle and older age cross-sectionally, using a large sample of community-dwelling older adults from the Irish Longitudinal Study on Ageing (TILDA). We assayed age-related anatomical changes via cortical thickness. Moreover, we explored age-related alterations in small-world and global properties of cortical thickness covariance networks, by targeting analyses towards the elder (ages 75–88; n = 88) and younger (ages 52–64; n = 95) sample members. Age, sex, and chronic disease-adjusted vertex-wise analyses revealed robust reductions in cortical thickness with age. Graph theoretical analyses of cortical thickness covariance networks revealed significantly lower betweenness centrality (i.e., network hub status) at left inferior parietal cortex in the eldest participant group as compared to the youngest. Furthermore, indices of small-worldness revealed greater lambda (i.e., less effective integration) across the right hemisphere of the eldest participant group versus the youngest. Our results are interpreted in the context of mechanisms of cortical atrophy in ageing, functional network organisation, and cognition in ageing. Highlights • We explored anatomical network differences in ageing via cortical thickness. • We examined age-related change in local and global network features with graph theory. • Left inferior parietal cortex's hub status was weaker in the over 75 s versus under 65 s. • Integration across the right hemisphere was lower in the over 75 s versus under 65 s. • Results are interpreted in light of cortical atrophy and functional network organisation. [ABSTRACT FROM AUTHOR]

Brain activity during wakefulness is characterized by rapid fluctuations in neuronal responses. Whether these fluctuations play any role in modulating the accuracy of behavioral responses is poorly understood. Here, we investigated whether and how trial changes in the population response impact sensory coding in monkey V1 and perceptual performance. Although the responses of individual neurons varied widely across trials, many cells tended to covary with the local population. When population activity was in a ‘low’ state, neurons had lower evoked responses and correlated variability, yet higher probability to predict perceptual accuracy. The impact of firing rate fluctuations on network and perceptual accuracy was strongest 200 ms before stimulus presentation, and it greatly diminished when the number of cells used to measure the state of the population was decreased. These findings indicate that enhanced perceptual discrimination occurs when population activity is in a ‘silent’ response mode in which neurons increase information extraction.

Efficient control of principal neuron firing by basket cells is critical for information processing in cortical microcircuits, however, the relative contribution of their perisomatic and dendritic synapses to spike inhibition is still unknown. Using in vitro electrophysiological paired recordings we reveal that in the mouse basal amygdala cholecystokinin- and parvalbumin-containing basket cells provide equally potent control of principal neuron spiking. We performed pharmacological manipulations, light and electron microscopic investigations to show that, although basket cells innervate the entire somato-denditic membrane surface of principal neurons, the spike controlling effect is achieved primarily via the minority of synapses targeting the perisomatic region. As the innervation patterns of individual basket cells on their different postsynaptic partners show high variability, the impact of inhibitory control accomplished by single basket cells is also variable. Our results show that both basket cell types can powerfully regulate the activity in amygdala networks predominantly via their perisomatic synapses.

Brain-computer interfaces (BCIs) carry great potential in the treatment of motor impairments. As a new motor output, BCIs interface with the native motor system, but acquisition of BCI proficiency requires a degree of learning to integrate this new function. In this review, we discuss how BCI designs often take advantage of the brain’s motor system infrastructure as sources of command signals. We highlight a growing body of literature examining how this approach leads to changes in activity across cortex, including beyond motor regions, as a result of learning the new skill of BCI control. We discuss the previous research identifying patterns of neural activity associated with BCI skill acquisition and use that closely resembles those associated with learning traditional native motor tasks. We then discuss recent work in animals probing changes in connectivity of the BCI control site, which were linked to BCI skill acquisition, and use this as a foundation for our original work in humans. We present our novel work showing changes in resting state connectivity across cortex following the BCI learning process. We find substantial, heterogeneous changes in connectivity across regions and frequencies, including interactions that do not involve the BCI control site. We conclude from our review and original work that BCI skill acquisition may potentially lead to significant changes in evoked and resting state connectivity across multiple cortical regions. We recommend that future studies of BCIs look beyond motor regions to fully describe the cortical networks involved and long-term adaptations resulting from BCI skill acquisition. [ABSTRACT FROM AUTHOR]

Theories of consciousness suggest that brain mechanisms underlying transitions into and out of unconsciousness are conserved no matter the context or precipitating conditions. We compared signatures of these mechanisms using intracranial electroencephalography in neurosurgical patients during propofol anesthesia and overnight sleep and found strikingly similar reorganization of human cortical networks. We computed the "effective dimensionality" of the normalized resting state functional connectivity matrix to quantify network complexity. Effective dimensionality decreased during stages of reduced consciousness (anesthesia unresponsiveness, N2 and N3 sleep). These changes were not region-specific, suggesting global network reorganization. When connectivity data were embedded into a low-dimensional space in which proximity represents functional similarity, we observed greater distances between brain regions during stages of reduced consciousness, and individual recording sites became closer to their nearest neighbors. These changes corresponded to decreased differentiation and functional integration and correlated with decreases in effective dimensionality. This network reorganization constitutes a neural signature of states of reduced consciousness that is common to anesthesia and sleep. These results establish a framework for understanding the neural correlates of consciousness and for practical evaluation of loss and recovery of consciousness., (© The Author(s) 2023. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permission@oup.com.)