Subset Of Brain Regions Research Articles

A subset of brain regions within adult functional connectivity networks demonstrates high reliability across early development.

The human cerebral cortex contains groups of areas that support sensory, motor, cognitive, and affective functions, often categorized into functional networks. These networks show stronger internal and weaker external functional connectivity (FC), with FC profiles more similar within the same network. Previous studies have shown these networks develop from nascent forms before birth to their mature, adult-like structures in childhood. However, these analyses often rely on adult functional network definitions. This study assesses the potential misidentification of infant functional networks when using adult models and explores the consequences and possible solutions to this problem. Our findings suggest that although adult networks only marginally describe infant FC organization better than chance, misidentification is primarily driven by specific areas. Restricting functional networks to areas with adult-like network clustering revealed consistent within-network FC across scans and throughout development. These areas are also near locations with low network identity variability. Our results highlight the implications of using adult networks for infants and offer guidance for selecting and utilizing functional network models based on research questions and scenarios.

The dynamic brain-network model of PTSD

The brain is a highly complex system whose functioning is critical for our interaction with the world. Neural elements, from single cells to brain systems, constantly fluctuate in their dynamics, accompanying the plethora of possible exchanges between our environment and ourselves. However, sometimes things go awry. An unfortunate example is post-traumatic stress disorder (PTSD), a debilitating clinical condition that can appear after exposure to a threatening life event. In this work, using complexity as a framework, we aim to introduce the dynamic brain network model of PTSD. We hope this model will allow the generation of novel specific hypotheses concerning brain organization and dynamics in PTSD research. We first introduce how the network framework complements the localizationist approach centered in specific brain regions or subsets of brain regions, with a whole brain approach considering brain regions' dynamic relationships. Then, we review key concepts in network neuroscience, focusing on the importance of the network topology and dynamics to understand the organizational principles of the brain, that is, functional segregation and integration. In the third part, we apply this knowledge to describe the possible trajectories conducting a brain system to present PTSD alterations. Accordingly, we introduce the Dynamic Brain Network Model (DBNM) of PTSD, a concrete framework built on the network approach and resilience theory to study the transition of a brain network from state 1 (e.g., before the traumatic event) to state 2 (e.g., after the traumatic event). To conclude, we provide a summary of metrics for quantifying elements on the DBNM and its potential use in computational models of PTSD.

Learning Active Multimodal Subspaces in the Brain.

Here we introduce a multimodal framework to identify subspaces in the human brain that are defined by collective changes in structural and functional measures and are actively linked to demographic, biological and cognitive indicators in a population. We determine the multimodal subspaces using principles of active subspace learning (ASL) and demonstrate its application on a sample learning task (biological ageing) on a schizophrenia dataset. The proposed multimodal ASL method successfully identifies latent brain representations as subsets of brain regions and connections forming covarying subspaces in association with biological age. We show that schizophrenia is characterized by different subspace patterns compared to those in a cognitively normal brain. The multimodal features generated by projecting structural and functional MRI components onto these active subspaces perform better than several PCA-based transformations and equally well when compared to non-transformed features on the studied learning task. In essence, the proposed method successfully learns active brain subspaces associated with a specific brain condition but inferred from the brain imaging data along with the biological/cognitive traits of interest. Clinical relevance- The work introduces a novel way to create multimodal brain biomarkers based on subspaces computed in association with cognitive or biological traits of interest. These subspaces collectively covary maximally in association with a given trait and successfully retain predictive information.

Distributed and Multifaceted Effects of Threat and Safety.

In the present fMRI study, we examined how anxious apprehension is processed in the human brain. A central goal of the study was to test the prediction that a subset of brain regions would exhibit sustained response profiles during threat periods, including the anterior insula, a region implicated in anxiety disorders. A second important goal was to evaluate the responses in the amygdala and the bed nucleus of the stria terminals, regions that have been suggested to be involved in more transient and sustained threat, respectively. A total of 109 participants performed an experiment in which they encountered "threat" or "safe" trials lasting approximately 16 sec. During the former, they experienced zero to three highly unpleasant electrical stimulations, whereas in the latter, they experienced zero to three benign electrical stimulations (not perceived as unpleasant). The timing of the stimulation during trials was randomized, and as some trials contained no stimulation, stimulation delivery was uncertain. We contrasted responses during threat and safe trials that did not contain electrical stimulation, but only the potential that unpleasant (threat) or benign (safe) stimulation could occur. We employed Bayesian multilevel analysis to contrast responses to threat and safe trials in 85 brain regions implicated in threat processing. Our results revealed that the effect of anxious apprehension is distributed across the brain and that the temporal evolution of the responses is quite varied, including more transient and more sustained profiles, as well as signal increases and decreases with threat.

Uncovering Active Structural Subspaces Associated with Changes in Indicators for Alzheimer's Disease.

We present a framework for identifying subspaces in the brain that are associated with changes in biological and cognitive indicators for a given disorder. By employing a method called active subspace learning (ASL) on structural MRI features from an Alzheimer's disease dataset, we identify subsets of regions that form co-varying subspaces in association with biological age and mini-mental state exam (MMSE) scores. Features generated by projecting structural MRI components onto these subspaces performed equally well on regression tasks when compared to non-transformed features as well as PCA-based transformations. Thus, without compromising on predictive performance, we present a way to extract sparse subspaces in the brain which are associated with a particular disorder but inferred only from the neuroimaging data along with relevant biological and cognitive test measures.Clinical relevance-This work provides a way to identify active structural subspaces in the brain, i.e. subsets of brain regions which collectively change the most, in association with changes in the indicators of a given disorder.

Learning Clique Subgraphs in Structural Brain Network Classification with Application to Crystallized Cognition

Structural brain networks constructed from diffusion MRI are important biomarkers for understanding human brain structure and its relation to cognitive functioning. There is increasing interest in learning differences in structural brain networks between groups of subjects in neuroimaging studies, leading to a variable selection problem in network classification. Traditional methods often use independent edgewise tests or unstructured generalized linear model (GLM) with regularization on vectorized networks to select edges distinguishing the groups, which ignore the network structure and make the results hard to interpret. In this paper, we develop a symmetric bilinear logistic regression (SBLR) with elastic-net penalty to identify a set of small clique subgraphs in network classification. Clique subgraphs, consisting of all the interconnections among a subset of brain regions, have appealing neurological interpretations as they may correspond to some anatomical circuits in the brain related to the outcome. We apply this method to study differences in the structural connectome between adolescents with high and low crystallized cognitive ability, using the crystallized cognition composite score, picture vocabulary and oral reading recognition tests from NIH Toolbox. A few clique subgraphs containing several small sets of brain regions are identified between different levels of functioning, indicating their importance in crystallized cognition.

Evidence of early vasogenic edema following minor head impact that can be reduced with a vasopressin V1a receptor antagonist

BackgroundDoes minor head impact without signs of structural brain damage cause short-term changes in vasogenic edema as measured by an increase apparent diffusion coefficient (ADC) using diffusion weighted imaging? If so, could the increase in vasogenic edema be treated with a vasopressin V1a receptor antagonist? We hypothesized that SRX251, a highly selective V1a antagonist, would reduce vasogenic edema in response to a single minor head impact. MethodsLightly anesthetized male rats were subjected to a sham procedure or a single hit to the forehead using a closed skull, momentum exchange model. Animals recovered in five min and were injected with saline vehicle (n = 8) or SRX251 (n = 8) at 15 min post head impact and again 7−8 hrs later. At 2 h, 6 h, and 24 h post injury, rats were anesthetized and scanned for increases in ADC, a neurological measure of vasogenic edema. Sham rats (n = 6) were exposed to anesthesia and scanned at all time points but were not hit or treated. Images were registered to and analyzed using a 3D MRI rat atlas providing site-specific data on 150 different brain areas. These brain areas were parsed into 11 major brain regions. ResultsUntreated rats with brain injury showed a significant increase in global brain vasogenic edema as compared to sham and SRX251 treated rats. Edema peaked at 6 h in injured, untreated rats in three brain regions where changes in ADC were observed, but returned to sham levels by 24 h. There were regional variations in the time course of vasogenic edema and drug efficacy. Edema was significantly reduced in cerebellum and thalamus with SRX251 treatment while the basal ganglia did not show a response to treatment. ConclusionA single minor impact to the forehead causes regional increases in vasogenic edema that peak at 6 h but return to baseline within a day in a subset of brain regions. Treatment with a selective V1a receptor antagonist can reduce much of the edema.

Lorcaserin Alters Serotonin and Noradrenaline Tissue Content and Their Interaction With Dopamine in the Rat Brain.

Lorcaserin is a preferential serotonin2C receptor (5-HT2CR) agonist effective to treat obesity that has also recently been proposed to treat addiction and epilepsy. Central dopamine (DA) mechanisms are likely involved in the lorcaserin mechanism of action, but other monoamines 5-HT and noradrenaline (NA) contents or their interaction with DA might account for its effects. Here we showed that lorcaserin at 3, but not 0.3 mg/kg enhanced 5-HT content in the insular cortex, the core of the nucleus accumbens, and ventral hypothalamus. Without affecting the metabolite 5-hydroxy indole acetic acid, lorcaserin reduced the indirect index of 5-HT turnover in the hippocampus, substantia nigra, and habenula. Lorcaserin at 3 mg/kg increased NA content in the orbitofrontal cortex, the central amygdala (also at 0.3 mg/kg), the ventral hypothalamus, and the shell of the nucleus accumbens. A correlative analysis of the tissue contents between pairs of brain regions revealed that 0.3 mg/kg lorcaserin enhanced the number of correlations for 5-HT, its metabolism, and NA to a lower extent. The correlation profiles were very different between saline, 0.3 and 3 mg/kg lorcaserin. Lorcaserin enhanced the correlations established between NA or 5-HT at 0.3 and 3 mg/kg and reduced the number of correlations established between the index of the turnover for DA and 5-HT. These results show that lorcaserin modulates the biochemistry of NA and 5-HT systems in a subset of brain regions. Qualitatively, they reveal, oppositely to the DA changes, that lorcaserin at 0.3, but not 3 mg/kg, enhanced the number of correlations of 5-HT content between brain regions.

Spatial modeling of brain connectivity data via latent distance models with nodes clustering

Brain network data—measuring structural interconnections among brain regions of interest—are increasingly collected for multiple individuals. Moreover, recent analyses provide additional information on the brain regions under study. These predictors typically include the three‐dimensional anatomical coordinates of the regions, and their membership to hemispheres and lobes. Although recent studies have explored the spatial effects underlying brain networks, there is still a lack of statistical analyses on the net connectivity structure which is not explained by the physical proximity of the brain regions. We answer this question via a predictor‐dependent latent space model for replicated brain network data which provides a meaningful representation for the net connectivity architecture via a set of latent positions having a mixture of Gaussians prior. This model allows for flexible inference on brain network patterns which are not explained by the anatomical structure, and facilitates clustering among brain regions according to local similarities in the latent space. Our findings offer novel insights on wiring mechanisms among subsets of brain regions which interestingly departs from the anatomical proximity structure.

Local Slow Waves in Superficial Layers of Primary Cortical Areas during REM Sleep

Sleep is traditionally constituted of two global behavioral states, non-rapid eye movement (NREM) and rapid eye movement (REM), characterized by quiescence and reduced responsiveness to sensory stimuli [1]. NREM sleep is distinguished by slow waves and spindles throughout the cerebral cortex and REM sleep by an "activated," low-voltage fast electroencephalogram (EEG) paradoxically similar to that of wake, accompanied by rapid eye movements and muscle atonia. However, recent evidence has shown that cortical activity patterns during wake and NREM sleep are not as global as previously thought. Local slow waves can appear in various cortical regions in both awake humans [2] and rodents [3-5]. Intracranial recordings in humans [6] and rodents [4, 7] have shown that NREM sleep slow waves most often involve only a subset of brain regions that varies from wave to wave rather than occurring near synchronously across all cortical areas. Moreover, some cortical areas can transiently "wake up" [8] in an otherwise sleeping brain. Yet until now, cortical activity during REM sleep was thought to be homogenously wake-like. We show here, using local laminar recordings in freely moving mice, that slow waves occur regularly during REM sleep, but only in primary sensory and motor areas and mostly in layer 4, the main target of relay thalamic inputs, and layer 3. This finding may help explain why, during REM sleep, we remain disconnected from the environment even though the bulk of the cortex shows wake-like, paradoxical activation.

Brain regions and molecular pathways responding to food reward type and value in honey bees.

The ability of honey bees to evaluate differences in food type and value is crucial for colony success, but these assessments are made by individuals who bring food to the hive, eating little, if any, of it themselves. We tested the hypothesis that responses to food type (pollen or nectar) and value involve different subsets of brain regions, and genes responsive to food. mRNA in situ hybridization of c-jun revealed that brain regions responsive to differences in food type were mostly different from regions responsive to differences in food value, except those dorsal and lateral to the mushroom body calyces, which responded to all three. Transcriptomic profiles of the mushroom bodies generated by RNA sequencing gave the following results: (1) responses to differences in food type or value included a subset of molecular pathways involved in the response to food reward; (2) genes responsive to food reward, food type and food value were enriched for (the Gene Ontology categories) mitochondrial and endoplasmic reticulum activity; (3) genes responsive to only food and food type were enriched for regulation of transcription and translation; and (4) genes responsive to only food and food value were enriched for regulation of neuronal signaling. These results reveal how activities necessary for colony survival are channeled through the reward system of individual honey bees.

Task-Driven Activity Reduces the Cortical Activity Space of the Brain: Experiment and Whole-Brain Modeling.

How a stimulus or a task alters the spontaneous dynamics of the brain remains a fundamental open question in neuroscience. One of the most robust hallmarks of task/stimulus-driven brain dynamics is the decrease of variability with respect to the spontaneous level, an effect seen across multiple experimental conditions and in brain signals observed at different spatiotemporal scales. Recently, it was observed that the trial-to-trial variability and temporal variance of functional magnetic resonance imaging (fMRI) signals decrease in the task-driven activity. Here we examined the dynamics of a large-scale model of the human cortex to provide a mechanistic understanding of these observations. The model allows computing the statistics of synaptic activity in the spontaneous condition and in putative tasks determined by external inputs to a given subset of brain regions. We demonstrated that external inputs decrease the variance, increase the covariances, and decrease the autocovariance of synaptic activity as a consequence of single node and large-scale network dynamics. Altogether, these changes in network statistics imply a reduction of entropy, meaning that the spontaneous synaptic activity outlines a larger multidimensional activity space than does the task-driven activity. We tested this model’s prediction on fMRI signals from healthy humans acquired during rest and task conditions and found a significant decrease of entropy in the stimulus-driven activity. Altogether, our study proposes a mechanism for increasing the information capacity of brain networks by enlarging the volume of possible activity configurations at rest and reliably settling into a confined stimulus-driven state to allow better transmission of stimulus-related information.

Developmental pattern of diacylglycerol lipase-α (DAGLα) immunoreactivity in brain regions important for song learning and control in the zebra finch (Taeniopygia guttata)

Zebra finch song is a learned behavior dependent upon successful progress through a sensitive period of late-postnatal development. This learning is associated with maturation of distinct brain nuclei and the fiber tract interconnections between them. We have previously found remarkably distinct and dense CB1 cannabinoid receptor expression within many of these song control brain regions, implying a normal role for endocannabinoid signaling in vocal learning. Activation of CB1 receptors via daily treatments with exogenous agonist during sensorimotor stages of song learning (but not in adulthood) results in persistent alteration of song patterns. Now we are working to understand physiological changes responsible for this cannabinoid-altered vocal learning. We have found that song-altering developmental treatments are associated with changes in expression of endocannabinoid signaling elements, including CB1 receptors and the principal CNS endogenous agonist, 2-AG. Within CNS, 2-AG is produced largely through activity of the α isoform of the enzyme diacylglycerol lipase (DAGLα). To better appreciate the role of 2-AG production in normal vocal development we have determined the spatial distribution of DAGLα expression within zebra finch CNS during vocal development. Early during vocal development at 25 days, DAGLα staining is typically light and of fibroid processes. Staining peaks late in the sensorimotor stage of song learning at 75 days and is characterized by fiber, neuropil and some staining of both small and large cell somata. Results provide insight to the normal role for endocannabinoid signaling in the maturation of brain regions responsible for song learning and vocal-motor output, and suggest mechanisms by which exogenous cannabinoid exposure alters acquisition of this form of vocal communication.

Chemotherapy effects on brain glucose metabolism at rest

Abstract Background: A growing number of studies reports that chemotherapy may impair brain functions inducing cognitive changes which can persist in a subset of cancer survivors.Aims: To investigate the neural basis of the chemotherapy-induced neurobehavioral changes by means of metabolic imaging and voxel-based statistical parametric mapping analyses. Methods: We studied the resting brain [18]FDG-PET/CT images of 43 adult cancer patients with solid (n=12, 28%) or hematologic malignancies (n=31, 72%); 12 patients were studied prior to chemotherapy (No chemotherapy) while treated patients were divided into two matched subgroups: Early High (<9 months after chemotherapy, >6 chemotherapy cycles, n=10), and Late Low (>9 months after chemotherapy, <6 chemotherapy cycles, n=21). Findings: Compared to No chemotherapy, the Early High subgroup showed a significant bilateral (p<0.05) lower regional cerebral metabolic rate of glucose metabolism in both the prefrontal cortices and white matter, cerebellum, posterior medial cortices and limbic regions. A similar pattern emerged in the Early High versus Low Late comparison, while no significant result was obtained in the Low Late versus No chemotherapy comparison. The number of cycles and the post-chemotherapy time were negatively and positively correlated, respectively, with a set of these same brain regions. Interpretation: The present study shows that chemotherapy induces significant transient changes in the glucose metabolism of multiple cerebral cortical and white matter regions with a prevailing involvement of the prefrontal cortex. The severity of these changes are significantly related with the number of chemotherapy cycles and a subset of brain regions seems to present longer lasting, but more subtle, metabolic changes.

Experiential, autonomic, and neural responses during threat anticipation vary as a function of threat intensity and neuroticism

Anticipatory emotional responses play a crucial role in preparing individuals for impending challenges. They do this by triggering a coordinated set of changes in behavioral, autonomic, and neural response systems. In the present study, we examined the biobehavioral impact of varying levels of anticipatory anxiety, using a shock anticipation task in which unpredictable electric shocks were threatened and delivered to the wrist at variable intervals and intensities (safe, medium, strong). This permitted investigation of a dynamic range of anticipatory anxiety responses. In two studies, 95 and 51 healthy female participants, respectively, underwent this shock anticipation task while providing continuous ratings of anxiety experience and electrodermal responding (Study 1) and during fMRI BOLD neuroimaging (Study 2). Results indicated a step-wise pattern of responding in anxiety experience and electrodermal responses. Several brain regions showed robust responses to shock anticipation relative to safe trials, including the hypothalamus, periaqueductal gray, caudate, precentral gyrus, thalamus, insula, ventrolateral PFC, dorsomedial PFC, and ACC. A subset of these regions demonstrated a linear pattern of increased responding from safe to medium to strong trials, including the bilateral insula, ACC, and inferior frontal gyrus. These responses were modulated by individual differences in neuroticism, such that those high in neuroticism showed exaggerated anxiety experience across the entire task, and reduced brain activation from medium to strong trials in a subset of brain regions. These findings suggest that individual differences in neuroticism may influence sensitivity to anticipatory threat and provide new insights into the mechanism through which neuroticism may confer risk for developing anxiety disorders via dysregulated anticipatory responses.

Statistical Parametric Mapping reveals ligand and region-specific activation of G-proteins by CB1 receptors and non-CB1 sites in the 3D reconstructed mouse brain

CB1 receptors mediate the CNS effects of Δ9-tetrahydrocannabinol and synthetic cannabinoids. Previous studies have investigated cannabinoid-mediated G-protein activity in a subset of brain regions thought to mediate the behavioral effects of cannabinoids, but a detailed regional comparison of the effects of multiple ligands has not been conducted. This study used a novel approach, Statistical Parametric Mapping (SPM), to analyze 3D reconstructed brain images derived from agonist-stimulated [35S]GTPγS autoradiography in a whole-brain unbiased manner. SPM analysis demonstrated regional differences in the relative efficacies of cannabinoid agonists methanandamide (M-AEA), CP55,940 (CP) and WIN55,212-2 (WIN) in CB1+/+ mouse brains. To assess the potential contribution of novel cannabinoid binding sites, experiments were performed in CB1−/− mouse brains. SPM analysis revealed that the aminoalkylindole WIN, but not the bicyclic cannabinoid CP or the endocannabinoid analogue M-AEA, stimulated [35S]GTPγS binding in cortex, hippocampus, hypothalamus, amygdala, cerebellum and certain brainstem areas (dorsal tegmental complex and locus coeruleus). No differences between WIN-stimulated G-protein activity and basal activity were found in basal ganglia. Pharmacological experiments using the CB1 antagonist SR141716A in CB1+/+ mice showed that SR141716A blocked WIN-stimulated G-protein activity in all brain regions, suggesting that it binds to both CB1 and putative non-CB1 sites. These studies show ligand and region-specific cannabinoid-mediated G-protein activity at both CB1 and non-CB1 sites and demonstrate that SPM is a powerful approach for the analysis of reconstructed brain imaging data derived from agonist-stimulated [35S]GTPγS autoradiography.

Nicotine increases FosB expression within a subset of reward- and memory-related brain regions during both peri- and post-adolescence

Periadolescent nicotine exposure is associated with increased consumption and rewarding properties of abused drugs. In the case of peri- but not post-adolescent animals, these effects are persistent and last to adulthood, suggesting that early nicotine treatment may alter postnatal CNS development in ways that contribute to long-term problems with drug abuse. To begin to identify brain regions that may be altered by developmental nicotine exposure, we have measured expression of a transcription factor, FosB, within a series of reward- and memory-related brain regions of Sprague-Dawley rats. FosB expression is known to acutely and cumulatively increase within a subset of brain regions, particularly nucleus accumbens, after exposure to many classes of abused drugs. Our results demonstrate that FosB is increased within nucleus accumbens and also the granule cell layer of hippocampal dentate gyrus after both peri- and post-adolescent nicotine exposure (0.4 mg kg(-1) day(-1) from days 34 to 43 and 60 to 69, respectively). In periadolescents, expression increases were detected 2 days after nicotine exposure, and persisted for weeks, through at least early adulthood at 80 days of age. In post-adolescents, expression increases persisted for at least 11 days to postnatal day 80. These findings demonstrate that nicotine treatment during both peri- and post-adolescence persistently alters activity of brain regions involved in reward and memory. Because this altered gene expression occurs after both peri- and post-adolescent treatment, it cannot be directly responsible for increased consumption and rewarding properties of abused drugs previously established to be distinctly associated with periadolescent nicotine exposure.

The Drosophila trio plays an essential role in patterning of axons by regulating their directional extension.

We identified the Drosophila trio gene, which encodes a Dbl family protein carrying two Dbl homology (DH) domains, each of which potentially activates Rho family GTPases. Trio was distributed along axons in the central nervous system (CNS) of embryos and was strongly expressed in subsets of brain regions, including the mushroom body (MB). Loss-of-function trio mutations resulted in the misdirection or stall of axons in embryos and also caused malformation of the MB. The MB phenotypes were attributed to alteration in the intrinsic nature of neurites, as revealed by clonal analyses. Thus, Trio is essential in order for neurites to faithfully extend on the correct pathways. In addition, the localization of Trio in the adult brain suggests its postdevelopmental role in neurite terminals.

Airpuff Startle Stress Elicited Fos Expression in Brain Cardiovascular Areas of Young Shr and Wky Rats

Prior studies comparing Fos expression in adult Wistar Kyoto (WKY) and Spontaneously Hypertensive rats (SHR) identified more Fos-positive neurons in a subset of brain regions following two stressors: placement in a startle chamber and presentation of an airpuff startle stimulus. The present study assessed Fos expression in five week old SHR and WKY rats in those same brain areas. Like adults, young SHR expressed more Fos-positive neurons than WKY in response to the startle chamber alone. Unlike adults,

Restrictive clonal allocation in the chimeric mouse brain.

Whether, and to what extent, lineage restriction contributes to the organization of the mammalian brain remains unclear. Here we address this issue by examining the distribution of clonally related cells in chimeric mice generated by injecting genetically tagged embryonic stem (ES) cells into blastocyst embryos. Our examination of postnatal chimeric brains revealed that the vast majority of labeled ES cell descendents were confined within a different subset of brain regions in each animal. Moreover, the deployment of labeled cells in different brain regions was distinctive. The pattern of ordered and binomial colonization suggested that early diversified founder cells may constrain the fates of their descendants through a restriction of dispersion. In addition, the symmetrical distribution of ES cell descendants suggests that bilaterally corresponding structures may arise from a common set of progenitor cells. Finally, clones of cells formed a continuous band within the deep strata of the neocortex. This later finding in conjunction with the radial distribution of clones in remaining layers observed in previous studies indicates that the cerebral neocortex may derive from two groups of founder cells, which is consistent with the hypothesis of dual phylogenetic origins of the mammalian cerebral cortex.