Organization Of Neuronal Networks Research Articles

Bone Trauma Causes Massive but Reversible Changes in Spinal Circuitry.

The discovery of enlarged spinal neuronal receptive fields and caudal extension of the representation area of the injured body part, which subsides several weeks after a bone trauma in mice, might give hope to patients of CRPS if-in the future-we are able to translate the rodent recovery mechanisms to post-traumatic humans.

Role of the adhesion molecule F3/Contactin in synaptic plasticity and memory.

Cell adhesion molecules (CAMs) have a pivotal role in building and maintaining synaptic structures during brain development participating in axonal elongation and pathfinding, glial guidance of neuronal migration, as well as myelination. CAMs expression persists in the adult brain particularly in structures undergoing postnatal neurogenesis and involved in synaptic plasticity and memory as the hippocampus. Among the neural CAMs, we have recently focused on F3/Contactin, a glycosylphosphatidyl inositol-anchored glycoprotein belonging to the immunoglobulin superfamily, involved in neuronal development, synaptic maintenance and organization of neuronal networks. Here, we discuss our recent data suggesting that F3/Contactin exerts a role in hippocampal synaptic plasticity and memory in adult and aged mice. In particular, we have studied long-term potentiation (LTP), spatial and object recognition memory, and phosphorylation of the transcription factor cAMP-Responsive-Element Binding protein (CREB) in a transgenic mouse model of F3/Contactin overexpression. We also investigated whether F3/Contactin might influence neuronal apoptosis and the production of amyloid-beta peptide (Aβ), known to be one of the main pathogenetic hallmarks of Alzheimer's disease (AD). In conclusion, a further understanding of F3/Contactin role in synaptic plasticity and memory might have interesting clinical outcomes in cognitive disorders, such as aging and AD, offering innovative therapeutic opportunities.

How the brain analyzes object shape to support grasping behavior.

Reaching out and grasping an object is second nature to us, but this simple task requires various brain regions to analyze visual features, such as the 3-D shape of the object, and use that information to plan and execute actions (Fig. 1). Past studies have shown that neurons in a brain region called the anterior intraparietal area (AIP) respond selectively to 3-D shape and are active during object grasping. But there has been a lack of research on the causal effects of AIP neuronal activity on other brain regions involved in visual analysis and motor planning, limiting knowledge about the organization of neuronal networks that support grasping behavior.

WONOEP appraisal: optogenetic tools to suppress seizures and explore the mechanisms of epileptogenesis.

Optogenetics is a novel technology that combines optics and genetics by optical control of microbial opsins, targeted to living cell membranes. The versatility and the electrophysiologic characteristics of the light-sensitive ion-channels channelrhodopsin-2 (ChR2), halorhodopsin (NpHR), and the light-sensitive proton pump archaerhodopsin-3 (Arch) make these optogenetic tools potent candidates in controlling neuronal firing in models of epilepsy and in providing insights into the physiology and pathology of neuronal network organization and synchronization. Opsins allow selective activation of excitatory neurons and inhibitory interneurons, or subclasses of interneurons, to study their activity patterns in distinct brain-states in vivo and to dissect their role in generation of synchrony and seizures. The influence of gliotransmission on epileptic network function is another topic of great interest that can be further explored by using light-activated Gq protein-coupled opsins for selective activation of astrocytes. The ever-growing optogenetic toolbox can also be combined with emerging techniques that have greatly expanded our ability to record specific subtypes of cortical and hippocampal neurons in awake behaving animals such as juxtacellular recording and two-photon guided whole-cell recording, to identify the specific subtypes of neurons that are altered in epileptic networks. Finally, optogenetic tools allow rapid and reversible suppression of epileptic electroencephalography (EEG) activity upon photoactivation. This review outlines the most recent advances achieved with optogenetic techniques in the field of epilepsy by summarizing the presentations contributed to the 13th ILAE WONOEP meeting held in the Laurentian Mountains, Quebec, in June 2013.

Causes and consequences of gray matter heterotopia.

The objective of this article is to review the pathophysiological bases of gray matter heterotopia and to appreciate their involvement in brain cortical development and functional consequences, namely epilepsy. The development of the cerebral cortex results from complex sequential processes including cell proliferation, cell migration, cortical organization, and formation of neuronal networks. Disruption of these steps yields different types of cortical malformations including gray matter heterotopia, characterized by the ectopic position of neurons along the ventricular walls or in the deep white matter. Cortical malformations are major causes of epilepsy, being responsible for up to 40% of drug-resistant epilepsy, and the cognitive level of affected patients varies from normal to severely impaired. This review reports data from human patients and animal models highlighting the genetic causes for these disorders affecting not only neuronal migration but also the proliferation of cortical progenitors. Therefore, gray matter heterotopias should not be considered as solely due to an abnormal neuronal migration and classifying them as such may be too restrictive. The review will also summarize literature data indicating that besides ectopic neurons, neighbor cortical areas also play a consistent role in epileptogenesis, supporting the notion that plastic changes secondary to the initial malformation are instrumental in the pathophysiology of epilepsy in affected patients.

Developmental and degenerative modulation of brain-derived neurotrophic factor transcript variants in the mouse hippocampus

Brain-derived neurotrophic factor (BDNF) is regarded as an important factor for neurogenesis, synaptic plasticity, and neuronal network organization in brain circuits. However, little is known about the regulation of BDNF transcript variants in the hippocampus during postnatal development and following chemically induced neurotoxicity. In the present study, we examined the expression of individual BDNF transcript variants in the mouse hippocampus on postnatal day (PD) 3, 7, 14, 21, and 56, as well as in the adult hippocampus 1, 2, 4, and 8 days after trimethyltin (TMT) treatment. During postnatal development, the expression levels of common BDNF-coding transcripts and BDNF transcript variants increased gradually in the hippocampus, but the temporal patterns of each exon transcript showed significant differences. In the TMT-treated hippocampus, the levels of common BDNF-coding transcripts and exon I, IIC, III, VII, VIII, and IXA transcripts were significantly increased 1 day post-treatment. These observations suggest that the differential regulation of BDNF exon transcripts may be associated with neuronal and synaptic maturation during postnatal development, and neuronal survival and synaptic plasticity in chemically induced neurodegeneration.

Neurobiologically based interventions for autism spectrum disorders-rationale and new directions

Autism spectrum disorders (ASD) are heterogeneous, neurodevelopmental disorders with early onset, characterized by a triad of impairments in reciprocal interaction and communication as well as repetitive and restricted interests and activities. Though underlying causes still remain largely unknown, there is now evidence for abnormal growth trajectories in the early brain development in ASD during vulnerable periods and subsequent impairment of neuronal organization and differentiation of neuronal networks. A growing number of studies over the last 10 years support the efficacy of behaviorally based interventions in ASD for the improvement of social communication and behavioral functioning. In contrast, research on neurobiologically based therapies for ASD is still at its beginnings. In this article, we will provide a selective overview of novel interventions and trainings based on neurobiological principles. Directions and options for future research on treatment aiming at restoration of normal plasticity in disrupted brain circuits in ASD are discussed.

The interplay between STDP rules and anticipated synchronization in the organization of neuronal networks

Neuronal networks are able to synchronize in phase-locking regimes. Depending on the structural connectivity it is possible to determine the sign of the phase difference between oscillatory nodes. Specially in unidirectionally coupled motifs the relative phase difference is usually positive. However it has been shown that in the presence of dynamical inhibitory loops, unidirectionally coupled neuron models may present both positive or negative phase difference [1]. The unusual regime in which the phase difference is negative is called anticipated synchronization (AS) [2]. It means that two neurons or two neuronal populations coupled in a master-slave configuration can oscillate in such a way that the slave leads the master. These results are important in light of the growing experimental evidence that the synaptic strength between neurons can undergo spike-timing-dependent plasticity (STDP) [3]. In the delayed synchronization regime the master (pre-synaptic) neuron fires a spike before the slave (post-synaptic) neuron, which under STDP rules would facilitate long term potentiation (LTP), whereas in the AS regime the slave neuron fires a spike before the master neuron, contributing to long term depression (LTD) [4]. Since it has been shown previously that a simple 3-neuron motif can undergo a continuous transition from positive to negative values of relative phase via changes in synaptic conductances [1], the interplay between these regimes and STDP mechanisms is likely to play a very significant role in the organization of the system dynamics. Considering that in certain situations the relative potentiation in strong synapses is less intense than in weak synapses, but the depression do not show this dependence [5], we compare the effects of additive, multiplicative and hybrid rules in our motifs. Together with AS regimes in neuronal populations, STDP rules give synaptic weight distributions that are comparable to experiments in cortex [6,7].

Small-world networks in neuronal populations: A computational perspective

The analysis of the brain in terms of integrated neural networks may offer insights on the reciprocal relation between structure and information processing. Even with inherent technical limits, many studies acknowledge neuron spatial arrangements and communication modes as key factors.In this perspective, we investigated the functional organization of neuronal networks by explicitly assuming a specific functional topology, the small-world network. We developed two different computational approaches. Firstly, we asked whether neuronal populations actually express small-world properties during a definite task, such as a learning task. For this purpose we developed the Inductive Conceptual Network (ICN), which is a hierarchical bio-inspired spiking network, capable of learning invariant patterns by using variable-order Markov models implemented in its nodes. As a result, we actually observed small-world topologies during learning in the ICN. Speculating that the expression of small-world networks is not solely related to learning tasks, we then built a de facto network assuming that the information processing in the brain may occur through functional small-world topologies. In this de facto network, synchronous spikes reflected functional small-world network dependencies. In order to verify the consistency of the assumption, we tested the null-hypothesis by replacing the small-world networks with random networks. As a result, only small world networks exhibited functional biomimetic characteristics such as timing and rate codes, conventional coding strategies and neuronal avalanches, which are cascades of bursting activities with a power-law distribution.Our results suggest that small-world functional configurations are liable to underpin brain information processing at neuronal level.

Changes in the Spinal Segmental Motor Output for Stepping during Development from Infant to Adult

Human stepping movements emerge in utero and show several milestones during development to independent walking. Recently, imaging has become an essential tool for investigating the development and function of pattern generation networks in the spinal cord. Here we examine the development of the spinal segmental output by mapping the distribution of motoneuron activity in the lumbosacral spinal cord during stepping in newborns, toddlers, preschoolers, and adults. Newborn stepping is characterized by an alternating bilateral motor output with only two major components that are active at all lumbosacral levels of the spinal cord. This feature was similar across different cycle durations of neonate stepping. The alternating spinal motor output is consistent with a simpler organization of neuronal networks in neonates. Furthermore, a remarkable feature of newborn stepping is a higher overall activation of lumbar versus sacral segments, consistent with a rostrocaudal excitability gradient. In toddlers, the stance-related motor pool activity migrates to the sacral cord segments, while the lumbar motoneurons are separately activated at touchdown. In the adult, the lumbar and sacral patterns become more dissociated with shorter activation times. We conclude that the development of human locomotion from the neonate to the adult starts from a rostrocaudal excitability gradient and involves a gradual functional reorganization of the pattern generation circuitry.

Optical survey of vagus nerve-related neuronal circuits in the embryonic rat brainstem

The multiple-site optical recording technique with a voltage-sensitive dye, NK2761, was used to survey the functional organization of neuronal networks related to the vagus nerve (N.X) in the E16-stage rat brainstem. When we stimulated N.X, in addition to the responses in the vagal sensory nucleus (nucleus of the tractus solitarius (NTS)) on the stimulated side, other response areas were bilaterally detected. Characteristics of the optical signals in these areas suggested that they correspond to neural activity in the second/higher-ordered nucleus of the vagal pathway. The first area was located at the level of the pons. Based upon morphological information, we suggest that this area corresponds to the parabrachial nucleus (PBN), which receives inputs from the NTS. The second area was located between the NTS and the PBN. We suggest that this area is the A5 noradrenergic group. These results suggest that the N.X-related neural networks are established similarly to the adult pattern from an early developmental stage.

Editorial: models of invertebrate neurons in culture

In an attempt to better model the human nervous system, experimental preparations in current neuroscience have become increasingly complex: Advances in recording and imaging techniques as well as in analysis methods, enable the study of the mammalian nervous systems at a greater resolution than ever previously possible (e.g. Baker 2010; Stevenson and Kording 2011), and allows investigation of intricate phenomena in higher vertebrate models. At the same time, however, with the renaissance of the notion of conserved principles in neurobiology (e.g. Ache and Young 2005; Marder and Bucher 2007; Hobert et al. 2010; see Greenspan 2005 and references within), there has been a revival of interest in invertebrate models in neuroscience. There are striking similarities between species in regard to basic neural features, from the nature of relevant proteins, to cellular processes, to the organization of neuronal networks and pathways, through neural computation and dynamic processes leading to behavior (e.g. Godenschwege et al. 2006; Yanay et al. 2008; Humeau et al. 2011; and see Lichtneckert and Reichert 2005; Arendt et al. 2008; Brand and Livesey 2011; for reviews). These common features span a phylogenetically broad array of animals, vertebrate and invertebrate alike, implying both common ancestors and optimal-homologue solutions to similar problems (Clarac and Pearlstein 2007; Humeau et al. 2011; Chittka and Skorupski 2011 and references within). Similarly to the above, a second duality characterizes current research; Together with important breakthroughs in the ability to conduct in vivo studies (e.g. Tsytsarev et al. 2006; Cardin et al. 2010), there is continued interest in the unique advantages offered by in vitro models. The fundamental questions of how a collection of single entities (i.e. neurons and glia), organize to form a complex functional unit—the neural network, and how these building blocks connect and interact to form further elaborate neuronal structures are extremely tractable in two-dimensional in vitro preparations of primary neuronal cultures (e.g. Bulloch and Syed 1992; Jimbo et al. 2000; Shefi et al. 2002; Darya et al. 2009; and see Beadle 2006 for review of insect neural cultures). The in vitro system is simple (relative to any in vivo network), and allows control over as many of its variables as possible. Most importantly, two-dimensional cultures enable a close look at the dynamics of neural growth and network organization (Fig. 1) by offering easy access for non-invasive optical observations. These processes can also be manipulated by various methods, such as genetic treatments (Bai et al. 2009; Tessier and Broadie 2011), pharmacological interventions (Perk and Mercer 2006; Heck et al. 2009), and the use of patterned growth surfaces (Liu et al. 2000; Anava et al. 2009), all of which can affect the neural network development and activity. The experimental results, or the rules discovered in these model systems, can then be translated to theoretical predictions and simple model assumptions, in order for them to be tested and applied to more complex systems. This special issue of the Journal of Molecular Histology combines and builds upon the different trends mentioned above by focusing on in vitro preparations of invertebrate neurons. Neurons of various invertebrates in primary culture have served as the preparation of choice in numerous studies, focusing on nervous system development, form-function interactions, neural pharmacology and many more (e.g. Acklin and Nichlls 1990; Hayashi and Hildebrand 1990; Howes et al. 1991; Kirchhof and Bicker 1992; Lapied et al. A. Ayali (&) Department of Zoology, Tel-Aviv University, 69978 Tel-Aviv, Israel e-mail: ayali@tauex.tau.ac.il

Synthesis and in Vitro Evaluation of a Biotinylated Dextran-Derived Probe for Molecular Imaging

Herein we report the design, synthesis, and in vitro evaluation of a gadolinium-containing biotinylated dextran-derived molecular imaging probe as a prospective neuroanatomical tracer by means of magnetic resonance imaging (MRI). The probe was effectively taken up by cultured differentiated murine neuroblastoma cells and significantly enhanced the contrast in T(1)- and T(2)-weighted MR images of labeled cells under physiological conditions. A significant longitudinal relaxation rate enhancement in the presence of avidin was observed allowing the verification of the results in the end of noninvasive longitudinal MRI connectivity studies by post-mortem histology. The in vitro results indicate that the probe has the potential to be used in vivo to identify the organization of global neuronal networks in the brain with MRI.

Computational investigations of small-worlds networks in neuronal populations

Event Abstract Back to Event Computational investigations of small-worlds networks in neuronal populations Antonio G. Zippo1*, Giuliana Gelsomino1, Sara Nencini1, Gian Carlo Caramenti2, Maurizio Valente1 and Gabriele E. Biella1 1 National Research Council, Institute of Molecular Bioimaging and Physiology, Italy 2 National Research Council, Institute of Biomedical Technologies, Italy The study of the brain as neuronal network allows gaining insights to the analysis of information processing [1]. Network interactions can play a crucial role in this scenario. In fact many studies identify in the modality of neuronal interaction the key of the problem, but limitations in neuronal recordings makes the clear mechanisms elusive [2-4]. In this perspective, we investigated the functional organization of neuronal networks hypothesizing that they work as small-world networks [5]. We developed two different computational approaches: in the first, we asked whether neuronal populations actually express small-world properties during a learning task. To this purpose we developed the Inductive Conceptual Network (ICN), a hierarchical bio-inspired spiking network, able to learn invariant patterns by Variable-order Markov Models implemented in its nodes [6]. We found that the ICN model expressed small-word networks during learning. As control, we exerted the ICN with random binary inputs, where no patterns can be learnt, and we obtained no small-world network functional organization among nodes. Conjecturing that the expression of small-world networks is not only related to learning, in the second part, we built the de facto network assuming that every information process in brain occurs exhibiting functionally a small-world network. In the de facto network the functional dependencies of the small-world networks, were reflected by synchronous spikes. From the analysis of spiking activity, versus the null hypothesis where small-world networks were replaced by random networks, we detected mainly three functional characteristics, observed in biological networks: timing and rate codes, conventional coding strategies [7], and the neuronal avalanches, cascades of bursting activities distributed as a power-law distribution [8]. Interestingly, rate and timing codes are thus allowed to coexist in the same network model yet in nodes at different hierarchical positions. Our results suggest that small-word functional configurations represent a milestone of brain information processing at the level of neurons. In conclusion, accordingly with other theoretical and experimental works, short path length and sparse connectivity may promote simultaneous performance of information segregation (information retention) and integration (generalization) within neuronal systems. Acknowledgements We thank Riccardo Storchi and Jianyi Lin for his helpful suggestions.

ISSLS Prize Winner

Cross-sectional design. To investigate whether recurrent low back pain (LBP) is associated with changes in motor cortical representation of different paraspinal muscle fascicles. Fascicles of the lumbar paraspinal muscles are differentially activated during function. Human studies indicate this may be associated with a spatially separate array of neuronal networks at the motor cortex. Loss of discrete control of paraspinal muscle fascicles in LBP may be because of changes in cortical organization. Data were collected from 9 individuals with recurrent unilateral LBP and compared with 11 healthy participants from an earlier study. Fine-wire electrodes selectively recorded myoelectric activity from short/deep fascicles of deep multifidus (DM) and long/superficial fascicles of longissimus erector spinae (LES), bilaterally. Motor cortical organization was investigated using transcranial magnetic stimulation at different scalp sites to evoke responses in paraspinal muscles. Location of cortical representation (center of gravity; CoG) and motor excitability (map volume) were compared between healthy and LBP groups. Individuals with LBP had a more posterior location of LES center of gravity, which overlapped with that for DM on both hemispheres. In healthy individuals, LES center of gravity was located separately at a more anterior location to that for DM. Map volume was reduced in LBP compared to healthy individual across muscles. The findings highlight that LBP is associated with a loss of discrete cortical organization of inputs to back muscles. Increased overlap in motor cortical representation of DM and LES may underpin loss of differential activation in this group. The results further unravel the neurophysiological mechanisms of motor changes in recurrent LBP and suggest motor rehabilitation that includes training of differential activation of the paraspinal muscles may be required to restore optimal control in LBP.

Gradient based spinal cord axogenesis and locomotor connectome of the hatchling Xenopus tadpole

Understanding the mechanisms underlying the self-assembly and organization of functional neuronal networks is a crucial problem confronting both experimental and theoretical neuroscience alike. Early in development, functional neuronal networks self-assemble with astonishing rapidity. It is, therefore, imperative to investigate and understand how far simple basic mechanisms can allow primary functioning neuronal circuits to develop. To address this ‘structure-function’ issue, we model anatomy and electrophysiology of young hatchling Xenopus tadpole’s spinal cord [1-3]. Our bottom-up approach to modeling of neuronal connectivity is based on developmental process of axon growth – we develop a gradient-based mathematical model for axon growth. It is known that in the developing vertebrate spinal cord, neurons arise from progenitor cells in the neural tube and thereafter the axons grow under influence of chemical morphogenes released from the dorsal roof plate (‘BMP’), ventral floor plate (‘shh’) and hindbrain regions (‘Wnt’). Distribution of these guidance molecules along the spinal cord set up a gradient field which steer the axons in appropriate locations and thus ensure formation of proper connections. We grow axons of spinal neurons and generate synaptic connections similar to biological developmental process based on the data from Professor Alan Roberts Lab at University of Bristol [4]. Using the gradient-based model we were able to grow axons for all seven types of spinal neurons which are believed to be involved in swimming and struggling behavior of tadpole. These spinal neurons include sensory neurons which are responsible for receiving stimulus from environment; interneurons which process the sensory information and pass it onto the motor which translate these signals into appropriate locomotive activities. We successfully modeled both morphologically different types of spinal neurons– firstly commissural neurons grow axons ventrally on the same side of the spinal cord at first and turn longitudinally on the other (contralateral) side of the spinal cord, whereas non-commissural neurons grow their axons on the same (ipsilateral) side of spinal cord. The model incorporates experimental data for somata distribution in the spinal cord, the outgrowth angles, axon lengths, etc. The computer modeling of the axon growth of spinal neurons has enabled both us and our Biology partners to construct and test various hypotheses particularly the roles of the different guidance cues in the axon growth. We also implemented an optimization technique to determine the model parameters for a particular type of neuron based on minimizing a cost function which comprises of the difference between the axon trajectory distribution of the model axons and the corresponding experimental data and also difference between the tortuisities of the model and experimental axons. The complete reconstruction of the spinal cord includes about 2000 neurons. In the reconstruction, both the neurons and the dendrites are randomly distributed along the spinal cord on the ‘left’ and ‘right’ side of the body according to the experimental measurements. Thus, the reconstruction of the connectivity is biologically realistic. To model spiking activity we use Hodgkin-Huxley type conductance model. Parameters of the model are chosen according to the available neurophysiological measurements. Activity dynamics of neural network comprising both the reconstruction model and conductance based spiking neurons demonstrates swimming patterns, i.e., anti-phase oscillations on opposite sides of the body and metachronal wave in longitudinal direction in a wide range of model parameters.

Generating and Imaging Multicolor Brainbow Mice

INTRODUCTIONVisualizing the precise morphology of closely juxtaposed cells and their interactions can be highly informative, particularly when studying the complex organization of neuronal and glial networks in the nervous system. To this end, one can use optical approaches to image-distinct markers that are differentially distributed among the cells of interest, such as fluorescent proteins of various colors (XFPs). The Brainbow strategies use Cre/lox recombination to stochastically express two to four XFPs in a cellular population from a single promoter. Integration of multiple Brainbow transgene copies results in combinatorial expression of these XFPs, creating a wide range of hues. In the nervous system, the multicolor labeling thus generated can be used to distinguish adjacent neuronal or glial cells and to verify the identity of neuronal processes while tracing circuitry. This article describes the generation of Brainbow transgenes and mice as well as their use to image and digitally reconstruct nerve cells and their interactions in fixed samples. This method also holds potential for studies in other tissues and model organisms as well as live imaging in vivo.

Control of neuronal network organization by chemical surface functionalization ofmulti-walled carbon nanotube arrays

Carbon nanotube substrates are promising candidates for biological applications anddevices. Interfacing of these carbon nanotubes with neurons can be controlled by chemicalmodifications. In this study, we investigated how chemical surface functionalization ofmulti-walled carbon nanotube arrays (MWNT-A) influences neuronal adhesion andnetwork organization. Functionalization of MWNT-A dramatically modifies the length ofneurite fascicles, cluster inter-connection success rate, and the percentage of neurites thatescape from the clusters. We propose that chemical functionalization represents a methodof choice for developing applications in which neuronal patterning on MWNT-A substratesis required.

Behavioral Analysis of Genetically Modified Mice Indicates Essential Roles of Neurosteroidal Estrogen

Aromatase in the mouse brain is expressed only in the nerve cells of specific brain regions with a transient peak during the neonatal period when sexual behaviors become organized. The aromatase-knockout (ArKO) mouse, generated to shed light on the physiological functions of estrogen in the brain, exhibited various abnormal behaviors, concomitant with undetectable estrogen and increased androgen in the blood. To further elucidate the effects of neurosteroidal estrogens on behavioral phenotypes, we first prepared an brain-specific aromatase transgenic (bsArTG) mouse by introduction of a human aromatase transgene controlled under a −6.5 kb upstream region of the brain-specific promoter of the mouse aromatase gene into fertilized mouse eggs, because the −6.5 kb promoter region was previously shown to contain the minimal essential element responsible for brain-specific spatiotemporal expression. Then, an ArKO mouse expressing the human aromatase only in the brain was generated by crossing the bsArTG mouse with the ArKO mouse. The resulting mice (ArKO/bsArTG mice) nearly recovered from abnormal sexual, aggressive, and locomotive (exploratory) behaviors, in spite of having almost the same serum levels of estrogen and androgen as the adult ArKO mouse. These results suggest that estrogens locally synthesized in the specific neurons of the perinatal mouse brain directly act on the neurons and play crucial roles in the organization of neuronal networks participating in the control of sexual, aggressive, and locomotive (exploratory) behaviors.

Granger causal influence predicts BOLD activity levels in the default mode network

Although the brain areas in the default-mode network (DMN) act in a coordinated way during rest, the activity levels in the individual areas of the DMN are highly heterogeneous. The relation between the activity levels and the pattern of causal interaction among the DMN areas remains unknown. In the present fMRI study, seven nodes of the DMN were identified and their activity levels were rank-ordered based on a power spectral analysis of the resting blood oxygenation level-dependent (BOLD) signals. Furthermore, the direction of information flow among these DMN nodes was determined using Granger causality analysis and graph-theoretic methods. We found that the activity levels in these seven DMN nodes had a highly consistent hierarchical distribution, with the highest activity level in the posterior cingulate/precuneus cortices, followed by ventral medial prefrontal cortex and dorsal medial prefrontal cortex, and with the lowest level in the left inferior temporal gyrus. Importantly, a significant correlation was found between the activity levels and the In-Out degrees of information flow across the DMN nodes, suggesting that Granger causal influences can be used to predict BOLD activity levels. These findings shed light on the dynamical organization of cortical neuronal networks and may provide the basis for characterizing network disruption by brain disorders.