Patterns Of Neuronal Connectivity Research Articles

A Deep Learning-based Pipeline for Segmenting the Cerebral Cortex Laminar Structure in Histology Images.

Characterizing the anatomical structure and connectivity between cortical regions is a critical step towards understanding the information processing properties of the brain and will help provide insight into the nature of neurological disorders. A key feature of the mammalian cerebral cortex is its laminar structure. Identifying these layers in neuroimaging data is important for understanding their global structure and to help understand the connectivity patterns of neurons in the brain. We studied Nissl-stained and myelin-stained slice images of the brain of the common marmoset (Callithrix jacchus), which is a new world monkey that is becoming increasingly popular in the neuroscience community as an object of study. We present a novel computational framework that first acquired the cortical labels using AI-based tools followed by a trained deep learning model to segment cerebral cortical layers. We obtained a Euclidean distance of for the cortical labels acquisition, which was in the acceptable range by computing the half Euclidean distance of the average cortex thickness ( ). We compared our cortical layer segmentation pipeline with the pipeline proposed by Wagstyl et al. (PLoS biology, 18(4), e3000678 2020) adapted to 2D data. We obtained a better mean percentile Hausdorff distance (95HD) of . Whereas a mean 95HD of was obtained from Wagstyl et al. We also compared our pipeline's performance against theirs using their dataset (the BigBrain dataset). The results also showed better segmentation quality, Jaccard Index acquired from our pipeline, while was stated in their paper.

Multiscale Functional Connectivity analysis of episodic memory reconstruction

Our ability to share memories constitutes a social foundation of our world. When exposed to another person's memory, individuals can mentally reconstruct the events described, even if they were not present during the related events. However, the extent to which the neuronal connectivity patterns elicited by the mental reconstruction of an event mirror those present in the brains of individuals who experienced the original event remains unclear. Through two independent fMRI experiments, we explore the Functional Connectivity (FC) patterns at different timescales associated with these cognitive processes using the innovative Multiscale Functional Connectivity (MFC) technique. This study aims to shed light on how our brains construct mental representations of scenes in a movie compared to the verbal transmission of the same scenes. Our results demonstrated that the Default Mode Network (DMN) plays a crucial role in these experiments and exhibits unique FC patterns across different timescales, yet remarkably consistent among participants. In addition, we found significant connectivity patterns within the temporal cortex, including significant contributions of the temporal pole and the fusiform gyrus, which exhibited a pivotal role in cooperation with the DMN in both experiments.

Handwriting but not typewriting leads to widespread brain connectivity: a high-density EEG study with implications for the classroom.

As traditional handwriting is progressively being replaced by digital devices, it is essential to investigate the implications for the human brain. Brain electrical activity was recorded in 36 university students as they were handwriting visually presented words using a digital pen and typewriting the words on a keyboard. Connectivity analyses were performed on EEG data recorded with a 256-channel sensor array. When writing by hand, brain connectivity patterns were far more elaborate than when typewriting on a keyboard, as shown by widespread theta/alpha connectivity coherence patterns between network hubs and nodes in parietal and central brain regions. Existing literature indicates that connectivity patterns in these brain areas and at such frequencies are crucial for memory formation and for encoding new information and, therefore, are beneficial for learning. Our findings suggest that the spatiotemporal pattern from visual and proprioceptive information obtained through the precisely controlled hand movements when using a pen, contribute extensively to the brain's connectivity patterns that promote learning. We urge that children, from an early age, must be exposed to handwriting activities in school to establish the neuronal connectivity patterns that provide the brain with optimal conditions for learning. Although it is vital to maintain handwriting practice at school, it is also important to keep up with continuously developing technological advances. Therefore, both teachers and students should be aware of which practice has the best learning effect in what context, for example when taking lecture notes or when writing an essay.

Exploring Frequency Band-Based Biomarkers of EEG Signals for Mild Cognitive Impairment Detection.

Mild Cognitive Impairment (MCI) is often considered a precursor to Alzheimer's disease (AD), with a high likelihood of progression. Accurate and timely diagnosis of MCI is essential for halting the progression of AD and other forms of dementia. Electroencephalography (EEG) is the prevalent method for identifying MCI biomarkers. Frequency band-based EEG biomarkers are crucial for identifying MCI as they capture neuronal activities and connectivity patterns linked to cognitive functions. However, traditional approaches struggle to identify precise frequency band-based biomarkers for MCI diagnosis. To address this challenge, a novel framework has been developed for identifying important frequency sub-bands within EEG signals for MCI detection. In the proposed scheme, the signals are first denoised using a stationary wavelet transformation and segmented into small time frames. Then, four frequency sub-bands are extracted from each segment, and spectrogram images are generated for each sub-band as well as for the full filtered frequency band signal segments. This process produces five different sets of images for five separate frequency bands. Afterwards, a convolutional neural network is used individually on those image sets to perform the classification task. Finally, the obtained results for the tested four sub-bands are compared with the results obtained using the full bandwidth. Our proposed framework was tested on two MCI datasets, and the results indicate that the 16-32 Hz sub-band range has the greatest impact on MCI detection, followed by 4-8 Hz. Furthermore, our framework, utilizing the full frequency band, outperformed existing state-of-the-art methods, indicating its potential for developing diagnostic tools for MCI detection.

Simulation-based inference for efficient identification of generative models in computational connectomics.

Recent advances in connectomics research enable the acquisition of increasing amounts of data about the connectivity patterns of neurons. How can we use this wealth of data to efficiently derive and test hypotheses about the principles underlying these patterns? A common approach is to simulate neuronal networks using a hypothesized wiring rule in a generative model and to compare the resulting synthetic data with empirical data. However, most wiring rules have at least some free parameters, and identifying parameters that reproduce empirical data can be challenging as it often requires manual parameter tuning. Here, we propose to use simulation-based Bayesian inference (SBI) to address this challenge. Rather than optimizing a fixed wiring rule to fit the empirical data, SBI considers many parametrizations of a rule and performs Bayesian inference to identify the parameters that are compatible with the data. It uses simulated data from multiple candidate wiring rule parameters and relies on machine learning methods to estimate a probability distribution (the 'posterior distribution over parameters conditioned on the data') that characterizes all data-compatible parameters. We demonstrate how to apply SBI in computational connectomics by inferring the parameters of wiring rules in an in silico model of the rat barrel cortex, given in vivo connectivity measurements. SBI identifies a wide range of wiring rule parameters that reproduce the measurements. We show how access to the posterior distribution over all data-compatible parameters allows us to analyze their relationship, revealing biologically plausible parameter interactions and enabling experimentally testable predictions. We further show how SBI can be applied to wiring rules at different spatial scales to quantitatively rule out invalid wiring hypotheses. Our approach is applicable to a wide range of generative models used in connectomics, providing a quantitative and efficient way to constrain model parameters with empirical connectivity data.

Clonally related, Notch-differentiated spinal neurons integrate into distinct circuits.

Shared lineage has diverse effects on patterns of neuronal connectivity. In mammalian cortex, excitatory sister neurons assemble into shared microcircuits. In Drosophila, in contrast, sister neurons with different levels of Notch expression (NotchON/NotchOFF) develop distinct identities and diverge into separate circuits. Notch-differentiated sister neurons have been observed in vertebrate spinal cord and cerebellum, but whether they integrate into shared or distinct circuits remains unknown. Here, we evaluate how sister V2a (NotchOFF)/V2b (NotchON) neurons in the zebrafish integrate into spinal circuits. Using an in vivo labeling approach, we identified pairs of sister V2a/b neurons born from individual Vsx1+ progenitors and observed that they have somata in close proximity to each other and similar axonal trajectories. However, paired whole-cell electrophysiology and optogenetics revealed that sister V2a/b neurons receive input from distinct presynaptic sources, do not communicate with each other, and connect to largely distinct targets. These results resemble the divergent connectivity in Drosophila and represent the first evidence of Notch-differentiated circuit integration in a vertebrate system.

Oh, What a Tangled Web Epilepsy Genes May Weave.

Aberrant Neuronal Connectivity in the Cortex Drives Generation of Seizures in Rat Absence Epilepsy Studer F, Jarre G, Pouyatos B, et al. Brain 2022;145(6):1978-1991. doi:10.1093/brain/awab438.Absence epilepsy belongs to genetic epilepsies and is characterized by recurrent generalized seizures that are concomitant with alterations of consciousness and associated with cognitive comorbidities. Little is known about the mechanisms leading to occurrence of epileptic seizures (i.e., epileptogenesis) and, in particular, it remains an open question whether neuronal hypersynchronization, a key feature in seizure initiation, could result from aberrant structural connectivity within neuronal networks endowing them with epileptic properties. In the present study, we addressed this question using a genetic model of absence epilepsy in the rat where seizures initiate in the whisker primary somatosensory cortex. We hypothesized that alterations in structural connectivity of neuronal networks within wS1 contribute to pathological neuronal synchronization responsible for seizures. First, we used rabies virus-mediated retrograde synaptic tracing and evidenced that cortical neurons located in both upper- and deep-layers of whisker primary somatosensory cortex displayed aberrant and significantly increased connectivity the genetic model of absence epilepsy, as highlighted by a higher number of presynaptic partners. Next, we showed at the functional level that disrupting these aberrant whisker primary somatosensory cortex neuronal networks with synchrotron X-ray-mediated cortical microtransections drastically decreased both whisker primary somatosensory cortex neuron synchronization and seizure power, as revealed by in vivo local field potential recordings with multichannel probes. Taken together, our data provide for the first time strong evidence that increased structural connectivity patterns of cortical neurons represent critical pathological substrates for increased neuronal synchronization and generation of absence seizures.

Mushroom body input connections form independently of sensory activity in Drosophila melanogaster

Associative brain centers, such as the insect mushroom body, need to represent sensory information in an efficient manner. In Drosophila melanogaster, the Kenyon cells of the mushroom body integrate inputs from a random set of olfactory projection neurons, but some projection neurons-namely those activated by a few ethologically meaningful odors-connect to Kenyon cells more frequently than others. This biased and random connectivity pattern is conceivably advantageous, as it enables the mushroom body to represent a large number of odors as unique activity patterns while prioritizing the representation of a few specific odors. How this connectivity pattern is established remains largely unknown. Here, we test whether the mechanisms patterning the connections between Kenyon cells and projection neurons depend on sensory activity or whether they are hardwired. We mapped a large number of mushroom body input connections in partially anosmic flies-flies lacking the obligate odorant co-receptor Orco-and in wild-type flies. Statistical analyses of these datasets reveal that the random and biased connectivity pattern observed between Kenyon cells and projection neurons forms normally in the absence of most olfactory sensory activity. This finding supports the idea that even comparatively subtle, population-level patterns of neuronal connectivity can be encoded by fixed genetic programs and are likely to be the result of evolved prioritization of ecologically and ethologically salient stimuli.

A brainstem circuit for nausea suppression.

SUMMARYNausea is a discomforting sensation of gut malaise that remains a major clinical challenge. Several visceral poisons induce nausea through the area postrema, a sensory circumventricular organ that detects blood-borne factors. Here, we use genetic approaches based on an area postrema cell atlas to reveal inhibitory neurons that counteract nausea-associated poison responses. The gut hormone glucose insulinotropic peptide (GIP) activates area postrema inhibitory neurons that project locally and elicit inhibitory currents in nausea-promoting excitatory neurons through γ-aminobutyric acid (GABA) receptors. Moreover, GIP blocks behavioral responses to poisons in wild-type mice, with protection eliminated by targeted area postrema neuron ablation. These findings provide insights into the basic organization of nausea-associated brainstem circuits and reveal that area postrema inhibitory neurons are an effective pharmacological target for nausea intervention.

Aberrant neuronal connectivity in the cortex drives generation of seizures in rat absence epilepsy.

Absence epilepsy belongs to genetic epilepsies and is characterized by recurrent generalized seizures that are concomitant with alterations of consciousness and associated with cognitive comorbidities. Little is known about the mechanisms leading to occurrence of epileptic seizures (i.e. epileptogenesis) and, in particular, it remains an open question as to whether neuronal hypersynchronization, a key feature in seizure initiation, could result from aberrant structural connectivity within neuronal networks endowing them with epileptic properties. In the present study, we addressed this question using a genetic model of absence epilepsy in the rat where seizures initiate in the whisker primary somatosensory cortex (wS1). We hypothesized that alterations in structural connectivity of neuronal networks within wS1 contribute to pathological neuronal synchronization responsible for seizures. First, we used rabies virus-mediated retrograde synaptic tracing and showed that cortical neurons located in both upper- and deep-layers of wS1 displayed aberrant and significantly increased connectivity in the genetic model of absence epilepsy, as highlighted by a higher number of presynaptic partners. Next, we showed at the functional level that disrupting these aberrant wS1 neuronal networks with synchrotron X-ray-mediated cortical microtransections drastically decreased both the synchronization and seizure power of wS1 neurons, as revealed by in vivo local field potential recordings with multichannel probes. Taken together, our data provide for the first time strong evidence that increased structural connectivity patterns of cortical neurons represent critical pathological substrates for increased neuronal synchronization and generation of absence seizures.

Retrotransposons as Drivers of Mammalian Brain Evolution

Retrotransposons, a large and diverse class of transposable elements that are still active in humans, represent a remarkable force of genomic innovation underlying mammalian evolution. Among the features distinguishing mammals from all other vertebrates, the presence of a neocortex with a peculiar neuronal organization, composition and connectivity is perhaps the one that, by affecting the cognitive abilities of mammals, contributed mostly to their evolutionary success. Among mammals, hominids and especially humans display an extraordinarily expanded cortical volume, an enrichment of the repertoire of neural cell types and more elaborate patterns of neuronal connectivity. Retrotransposon-derived sequences have recently been implicated in multiple layers of gene regulation in the brain, from transcriptional and post-transcriptional control to both local and large-scale three-dimensional chromatin organization. Accordingly, an increasing variety of neurodevelopmental and neurodegenerative conditions are being recognized to be associated with retrotransposon dysregulation. We review here a large body of recent studies lending support to the idea that retrotransposon-dependent evolutionary novelties were crucial for the emergence of mammalian, primate and human peculiarities of brain morphology and function.

Spontaneous Afferent Activity Carves Olfactory Circuits.

Electrical activity has a key role in shaping neuronal circuits during development. In most sensory modalities, early in development, internally generated spontaneous activity sculpts the initial layout of neuronal wiring. With the maturation of the sense organs, the system relies more on sensory-evoked electrical activity. Stimuli-driven neuronal discharge is required for the transformation of immature circuits in the specific patterns of neuronal connectivity that subserve normal brain function. The olfactory system (OS) differs from this organizational plan. Despite the important role of odorant receptors (ORs) in shaping olfactory topography, odor-evoked activity does not have a prominent role in refining neuronal wiring. On the contrary, afferent spontaneous discharge is required to achieve and maintain the specific diagram of connectivity that defines the topography of the olfactory bulb (OB). Here, we provide an overview of the development of olfactory topography, with a focus on the role of afferent spontaneous discharge in the formation and maintenance of the specific synaptic contacts that result in the topographic organization of the OB.

Neuron-Oligodendrocyte Communication in Myelination of Cortical GABAergic Cells.

Axonal myelination by oligodendrocytes increases the speed and reliability of action potential propagation, and so plays a pivotal role in cortical information processing. The extent and profile of myelination vary between different cortical layers and groups of neurons. Two subtypes of cortical GABAergic neurons are myelinated: fast-spiking parvalbumin-expressing cells and somatostatin-containing cells. The expression of pre-nodes on the axon of these inhibitory cells before myelination illuminates communication between oligodendrocytes and neurons. We explore the consequences of myelination for action potential propagation, for patterns of neuronal connectivity and for the expression of behavioral plasticity.

In vitro models of spinal motor circuit's development in mammals: achievements and challenges.

The connectivity patterns of neurons sustaining the functionality of spinal locomotor circuits rely on the specification of hundreds of motor neuron and interneuron subtypes precisely arrayed within the embryonic spinal cord. Knowledge acquired by developmental biologists on the molecular mechanisms underpinning this process in vivo has supported the development of 2D and 3D differentiation strategies to generate spinal neuronal diversity from mouse and human pluripotent stem cells (PSCs). Here, we review recent breakthroughs in this field and the perspectives opened up by models of in vitro embryogenesis to approach the mechanisms underlying neuronal diversification and the formation of functional mouse and human locomotor circuits. Beyond serving fundamental investigations, these new approaches should help engineering neuronal circuits differentially impacted in neuromuscular disorders, such as amyotrophic lateral sclerosis or spinal muscular atrophies, and thus open new avenues for disease modeling and drug screenings.

Individual odor hedonic perception is coded in temporal joint network activity

IntroThe human sense of smell is highly individual and characterized by a strong variability in the perception and evaluation of olfactory stimuli, depending on cultural imprint and current physiological conditions. Since this individual perspective has often been neglected in fMRI studies on olfactory hedonic coding, this study focuses on the neuronal activity and connectivity patterns resulting from subject-specific olfactory stimulation. Methods: Thirty-one normosmic participants took part in a fMRI block designed paradigm consisting of three olfactory stimulation sessions. The most pleasant and unpleasant odors were individually specified during a pre-test for each participant and validated in the main experiment. Mean activation and functional connectivity analysis focusing on the right and left piriform cortex were performed for the predefined olfactory regions-of-interest (ROIs) and compared between the three olfactory conditions. Results: Individual unpleasant olfactory stimulation as compared to pleasant or neutral did not alter mean BOLD activation in the predefined olfactory ROIs but led to a change in connectivity pattern in the right piriform cortex. Conclusion: Our data suggests that the individual pleasantness of odors is not detectable by average BOLD magnitude changes in primary or secondary olfactory brain areas, but reflected in temporal patterns of joint activation that create a network between the right piriform cortex, the left insular cortex, the orbitofrontal cortex, and the precentral gyrus. This network may serve the evolutionary defense mechanism of olfaction by preparing goal-directed action.

Mushroom Body Input Connections Form Independently of Sensory Activity in <i>Drosophila melanogaster</i>

Associative brain centers, such as the insect mushroom body, need to represent sensory information in an efficient manner. In Drosophila melanogaster, the Kenyon cells of the mushroom body integrate inputs from a random set of olfactory projection neurons, but some projection neurons — namely those activated by a few ethologically meaningful odors — connect to Kenyon cells more frequently than others. This biased and random connectivity pattern is conceivably advantageous, as it enables the mushroom body to represent a large number of odors as unique activity patterns while prioritizing the representation of a few specific odors. How this connectivity pattern is established remains largely unknown. Here, we test whether the mechanisms patterning the connections between Kenyon cells and projection neurons depend on sensory activity or whether they are hardwired. We mapped a large number of mushroom body input connections in anosmic flies — flies lacking the obligate odorant co-receptor Orco — and in wildtype flies. Statistical analyses of these datasets reveal that the random and biased connectivity pattern observed between Kenyon cells and projection neurons forms normally in the absence of most olfactory sensory activity. This finding supports the idea that even comparatively subtle, population-level patterns of neuronal connectivity can be encoded by fixed genetic programs and are likely to be the result of evolved prioritization of ecologically and ethologically salient stimuli.

Visual Input into the Drosophila melanogaster Mushroom Body

SUMMARYThe patterns of neuronal connectivity underlying multisensory integration, a fundamental property of many brains, remain poorly characterized. The Drosophila melanogaster mushroom body—an associative center—is an ideal system to investigate how different sensory channels converge in higher order brain centers. The neurons connecting the mushroom body to the olfactory system have been described in great detail, but input from other sensory systems remains poorly defined. Here, we use a range of anatomical and genetic techniques to identify two types of input neuron that connect visual processing centers—the lobula and the posterior lateral protocerebrum—to the dorsal accessory calyx of the mushroom body. Together with previous work that described a pathway conveying visual information from the medulla to the ventral accessory calyx of the mushroom body, our study defines a second, parallel pathway that is anatomically poised to convey information from the visual system to the dorsal accessory calyx.

MRI spectroscopic and tractography studies indicate consequences of long-term ketogenic diet

To maintain its functional abilities, the mature brain obtains energy from glucose produced in carbohydrate metabolism. When carbohydrates are eliminated from the diet, the energy comes from the oxidation of fatty acids. In this metabolic state called ketosis, ketone bodies are formed: β-hydroxybutyric acid (bHb), acetone, and acetoacetate as alternative source of energy passing through the blood–brain barrier easily. The ketosis state can be achieved through various strategies like caloric restriction, supplementation with medium-chain triglycerides, intense physical training, or ketogenic diet (KD). Using KD, drug-resistant epilepsy has been successfully treated in children and adults. It can also exert neuroprotective influences in cases of brain damage, glioblastoma multiforme, and Alzheimer's or Parkinson's diseases. Although many possible mechanisms of KD activity have been proposed, newer hypotheses appear with the research progress, mostly characterizing the brain under pathological but not normal conditions. Since different pathological conditions may affect the mechanism of KD action differently, additional research on the normal brain appears reasonable. For this purpose, young adult rats were treated with 4-month-lasting KD. Then, MRI structural measurements, spectroscopy, and tractography were performed. The procedures revealed significant increases in the concentration of glutamine, glutamate, glutathione and NAA, accompanied by changes in the pattern of neuronal connections of the striatum and hippocampal formation. This implies a possible involvement of these structures in the functional changes occurring in the brain after KD application. Thus, the investigations on the normal brain add important details concerning mechanisms underlying KD effects without their possible modification by a pathological status.

The connectome of the Caenorhabditis elegans pharynx.

Detailed anatomical maps of individual organs and entire animals have served as invaluable entry points for ensuing dissection of their evolution, development, and function. The pharynx of the nematode Caenorhabditis elegans is a simple neuromuscular organ with a self-contained, autonomously acting nervous system, composed of 20 neurons that fall into 14 anatomically distinct types. Using serial electron micrograph (EM) reconstruction, we re-evaluate here the connectome of the pharyngeal nervous system, providing a novel and more detailed view of its structure and predicted function. Contrasting the previous classification of pharyngeal neurons into distinct inter- and motor neuron classes, we provide evidence that most pharyngeal neurons are also likely sensory neurons and most, if not all, pharyngeal neurons also classify as motor neurons. Together with the extensive cross-connectivity among pharyngeal neurons, which is more widespread than previously realized, the sensory-motor characteristics of most neurons define a shallow network architecture of the pharyngeal connectome. Network analysis reveals that the patterns of neuronal connections are organized into putative computational modules that reflect the known functional domains of the pharynx. Compared with the somatic nervous system, pharyngeal neurons both physically associate with a larger fraction of their neighbors and create synapses with a greater proportion of their neighbors. We speculate that the overall architecture of the pharyngeal nervous system may be reminiscent of the architecture of ancestral, primitive nervous systems.

Visual Input into The Drosophila Melanogaster Mushroom Body

The ability to integrate input from different sensory systems is a fundamental property of many brains. Yet, the patterns of neuronal connectivity that underlie such multisensory integration remain poorly characterized. The Drosophila melanogaster mushroom body — an associative center required for the formation of olfactory and visual memories — is an ideal system to investigate how different sensory channels converge in higher-order brain centers. The neurons connecting the mushroom body to the olfactory system have been described in great detail, but input from other sensory systems remains poorly defined. Here, we use a range of anatomical and genetic techniques to identify two novel types of mushroom body input neuron that connect visual processing centers — namely the lobula and the posterior lateral protocerebrum — to the dorsal accessory calyx of the mushroom body. Together with previous work that described a pathway conveying visual information from the medulla to the ventral accessory calyx of the mushroom body (Vogt et al., 2016), our study defines a second, parallel pathway that is anatomically poised to convey information from the visual system to the dorsal accessory calyx. This connectivity pattern — the segregation of the visual information into two separate pathways — could be a fundamental feature of the neuronal architecture underlying multisensory integration in associative brain centers.