We describe an integrated theory of olfactory systems operation that incorporates experimental findings across scales, stages, and methods of analysis into a common framework. In particular, we consider the multiple stages of olfactory signal processing as a collective system, in which each stage samples selectively from its antecedents. We propose that, following the signal conditioning operations of the nasal epithelium and glomerular-layer circuitry, the plastic external plexiform layer of the olfactory bulb effects a process of category learning-the basis for extracting meaningful, quasi-discrete odor representations from the metric space of undifferentiated olfactory quality. Moreover, this early categorization process also resolves the foundational problem of how odors of interest can be recognized in the presence of strong competitive interference from simultaneously encountered background odorants. This problem is fundamentally constraining on early-stage olfactory encoding strategies and must be resolved if these strategies and their underlying mechanisms are to be understood. Multiscale general theories of olfactory systems operation are essential in order to leverage the analytical advantages of engineered approaches together with our expanding capacity to interrogate biological systems.The amount of visual information projected from the retina to the brain exceeds the information processing capacity of the latter. Attention, therefore, functions as a filter to highlight important information at multiple stages of the visual pathway that requires further and more detailed analysis. Among other functions, this determines where to fixate since only the fovea allows for high resolution imaging. Visual saliency modeling, i.e. understanding how the brain selects important information to analyze further and to determine where to fixate next, is an important research topic in computational neuroscience and computer vision. Most existing bottom-up saliency models use low-level features such as intensity and color, while some models employ high-level features, like faces. However, little consideration has been given to mid-level features, such as texture, for visual saliency models. In this paper, we extend a biologically plausible proto-object based saliency model by adding simple texture channels which employ nonlinear operations that mimic the processing performed by primate visual cortex. The extended model shows statistically significant improved performance in predicting human fixations compared to the previous model. Comparing the performance of our model with others on publicly available benchmarking datasets, we find that our biologically plausible model matches the performance of other models, even though those were designed entirely for maximal performance with little regard to biological realism.Even the simplest cognitive processes involve interactions between cortical regions. To study these processes, we usually rely on averaging across several repetitions of a task or across long segments of data to reach a statistically valid conclusion. Neuronal oscillations reflect synchronized excitability fluctuations in ensembles of neurons and can be observed in electrophysiological recordings in the presence or absence of an external stimulus. Oscillatory brain activity has been viewed as sustained increase in power at specific frequency bands. However, this perspective has been challenged in recent years by the notion that oscillations may occur as transient burst-like events that occur in individual trials and may only appear as sustained activity when multiple trials are averaged together. In this review, we examine the idea that oscillatory activity can manifest as a transient burst as well as a sustained increase in power. We discuss the technical challenges involved in the detection and characterization of transient events at the single trial level, the mechanisms that might generate them and the features that can be extracted from these events to study single-trial dynamics of neuronal ensemble activity.Neuroplasticity is a complex process of structural and functional reorganization of brain tissue. In the fetal period, neuroplasticity plays an important role in the emergence and development of white matter tracts. Here, we aimed to study the architecture of normal fetal brains by way of Klingler’s dissection. Ten normal brains were collected from in utero deceased fetuses aged between 13 and 35 gestational weeks (GW). During this period, we observed modifications in volume, shape, and sulci configuration. Our findings indicate that the major white matter tracts follow four waves of development. The first wave (13 GW) involves the corpus callosum, the fornix, the anterior commissure, and the uncinate fasciculus. In the second one (14 GW), the superior and inferior longitudinal fasciculi and the cingulum could be identified. The third wave (17 GW) concerns the internal capsule and in the fourth wave (20 GW) all the major tracts, including the inferior-occipital fasciculus, were depicted. Our results suggest an earlier development of the white matter tracts than estimated by DTI tractography studies. Correlating anatomical dissection with tractography data is of great interest for further research in the field of fetal brain mapping.The major catecholamines-dopamine (DA) and norepinephrine (NE)-are not only involved in synaptic communication but also act as important trophic factors and might ultimately be involved in mammalian brain development. The catecholaminergic innervation of neurogenic regions of the developing brain and its putative relationship to neurogenesis is thus of pivotal interest. We here determined DA and NE innervation around the ventricular/subventricular zone (VZ/SVZ) bordering the whole ventricular system of the developing mouse brain from embryonic day 14.5 (E14.5), E16.5, and E19.5 until postnatal day zero (P0) by histological evaluation and HPLC with electrochemical detection. We correlated these data with the proliferation capacity of the respective regions by quantification of MCM2+ cells. During development, VZ/SVZ catecholamine levels dramatically increased between E16.5 and P0 with DA levels increasing in forebrain VZ/SVZ bordering the lateral ventricles and NE levels raising in midbrain/hindbrain VZ/SVZ bordering the third ventricle, the aqueduct, and the fourth ventricle. Conversely, proliferating MCM2+ cell counts dropped between E16.5 and E19.5 with a special focus on all VZ/SVZs outside the lateral ventricles. We detected an inverse strong negative correlation of the proliferation capacity in the periventricular neurogenic regions (log-transformed MCM2+ cell counts) with their NE levels (r = -0.932; p less then 0.001), but not their DA levels (r = 0.440; p = 0.051) suggesting putative inhibitory effects of NE on cell proliferation within the periventricular regions during mouse brain development. Our data provide the first framework for further demandable studies on the functional importance of catecholamines, particularly NE, in regulating neural stem/progenitor cell proliferation and differentiation during mammalian brain development.The brainstem, a structure of vital importance in mammals, is currently becoming a principal focus in cognitive, affective, and clinical neuroscience. Midbrain, pontine and medullary structures serve as the conduit for signals between the forebrain and spinal cord, are the epicenter of cranial nerve-circuits and systems, and subserve such integrative functions as consciousness, emotional processing, pain, and motivation. In this study, we parcellated the nuclear masses and the principal fiber pathways that were visible in a high-resolution T2-weighted MRI dataset of 50-micron isotropic voxels of a postmortem human brainstem. Based on this analysis, we generated a detailed map of the human brainstem. To assess the validity of our maps, we compared our observations with histological maps of traditional human brainstem atlases. Given the unique capability of MRI-based morphometric analysis in generating and preserving the morphology of 3D objects from individual 2D sections, we reconstructed the motor, sensory and integrative neural systems of the brainstem and rendered them in 3D representations. We anticipate the utilization of these maps by the neuroimaging community for applications in basic neuroscience as well as in neurology, psychiatry, and neurosurgery, due to their versatile computational nature in 2D and 3D representations in a publicly available capacity.Brain function depends on the flexible and dynamic coordination of functional subsystems within distributed neural networks operating on multiple scales. Recent progress has been made in the characterization of functional connectivity (FC) at the whole-brain scale from a dynamic, rather than static, perspective, but its validity for cognitive sciences remains under debate. Here, we analyzed brain activity recorded with functional Magnetic Resonance Imaging from 71 healthy participants evaluated for depressive symptoms after a relationship breakup based on the conventional Major Depression Inventory (MDI). We compared both static and dynamic FC patterns between participants reporting high and low depressive symptoms. Between-group differences in static FC were estimated using a standard pipeline for network-based statistic (NBS). Additionally, FC was analyzed from a dynamic perspective by characterizing the occupancy, lifetime, and transition profiles of recurrent FC patterns. Recurrent FC patterns were definection can only be gleaned if the temporal dynamics of FC is included.As the most important organ in our bodies, the brain plays a critical role in deciding sex-related differential features; however, the underlying neural circuitry basis remains unclear. Here, we used a cell-type-specific rabies virus-mediated monosynaptic tracing system to generate a sex differences-related whole-brain input atlas of locus coeruleus noradrenaline (LC-NE) neurons. We developed custom pipelines for brain-wide comparisons of input sources in both sexes with the registration of the whole-brain data set to the Allen Mouse Brain Reference Atlas. Among 257 distinct anatomical regions, we demonstrated the differential proportions of inputs to LC-NE neurons in male and female mice at different levels. Locus coeruleus noradrenaline neurons of two sexes showed general similarity in the input patterns, but with differentiated input proportions quantitatively from major brain regions and diverse sub-regions. For instance, inputs to male LC-NE neurons were found mainly in the cerebrum, interbrain, and cerebellum, whereas inputs to female LC-NE neurons were found in the midbrain and hindbrain. We further found that specific subsets of nuclei nested within sub-regions contributed to overall sex-related differences in the input circuitry. Furthermore, among the totaled 123 anatomical regions with proportion of inputs >0.1%, we also identified 11 sub-regions with significant statistical differences of total inputs between male and female mice, and seven of them also showed such differences in ipsilateral hemispheres. Our study not only provides a structural basis to facilitate our understanding of sex differences at a circuitry level but also provides clues for future sexually differentiated functional studies related to LC-NE neurons.