Journal of Neuroscience

Variations in neural circuitry, inherited or acquired, may underlie important individual differences in thought, feeling, and action patterns. Here, we used task-free connectivity analyses to isolate and characterize two distinct networks typically coactivated during functional MRI tasks. We identified a “salience network,” anchored by dorsal anterior cingulate (dACC) and orbital frontoinsular cortices with robust connectivity to subcortical and limbic structures, and an “executive-control network” that links dorsolateral frontal and parietal neocortices. These intrinsic connectivity networks showed dissociable correlations with functions measured outside the scanner. Prescan anxiety ratings correlated with intrinsic functional connectivity of the dACC node of the salience network, but with no region in the executive-control network, whereas executive task performance correlated with lateral parietal nodes of the executive-control network, but with no region in the salience network. Our findings suggest that task-free analysis of intrinsic connectivity networks may help elucidate the neural architectures that support fundamental aspects of human behavior.

The major cell classes of the brain differ in their developmental processes, metabolism, signaling, and function. To better understand the functions and interactions of the cell types that comprise these classes, we acutely purified representative populations of neurons, astrocytes, oligodendrocyte precursor cells, newly formed oligodendrocytes, myelinating oligodendrocytes, microglia, endothelial cells, and pericytes from mouse cerebral cortex. We generated a transcriptome database for these eight cell types by RNA sequencing and used a sensitive algorithm to detect alternative splicing events in each cell type. Bioinformatic analyses identified thousands of new cell type-enriched genes and splicing isoforms that will provide novel markers for cell identification, tools for genetic manipulation, and insights into the biology of the brain. For example, our data provide clues as to how neurons and astrocytes differ in their ability to dynamically regulate glycolytic flux and lactate generation attributable to unique splicing ofPKM2, the gene encoding the glycolytic enzyme pyruvate kinase. This dataset will provide a powerful new resource for understanding the development and function of the brain. To ensure the widespread distribution of these datasets, we have created a user-friendly website (http://web.stanford.edu/group/barres_lab/brain_rnaseq.html) that provides a platform for analyzing and comparing transciption and alternative splicing profiles for various cell classes in the brain.

This paper presents studies of the coordination of voluntary human arm movements. A mathematical model is formulated which is shown to predict both the qualitative features and the quantitative details observed experimentally in planar, multijoint arm movements. Coordination is modeled mathematically by defining an objective function, a measure of performance for any possible movement. The unique trajectory which yields the best performance is determined using dynamic optimization theory. In the work presented here, the objective function is the square of the magnitude of jerk (rate of change of acceleration) of the hand integrated over the entire movement. This is equivalent to assuming that a major goal of motor coordination is the production of the smoothest possible movement of the hand. Experimental observations of human subjects performing voluntary unconstrained movements in a horizontal plane are presented. They confirm the following predictions of the mathematical model: unconstrained point-to-point motions are approximately straight with bell-shaped tangential velocity profiles; curved motions (through an intermediate point or around an obstacle) have portions of low curvature joined by portions of high curvature; at points of high curvature, the tangential velocity is reduced; the durations of the low-curvature portions are approximately equal. The theoretical analysis is based solely on the kinematics of movement independent of the dynamics of the musculoskeletal system and is successful only when formulated in terms of the motion of the hand in extracorporal space. The implications with respect to movement organization are discussed.

The novel neuropeptides called hypocretins (orexins) have recently been identified as being localized exclusively in cell bodies in a subregion of the tuberal part of the hypothalamus. The structure of the hypocretins, their accumulation in vesicles of axon terminals, and their excitatory effect on cultured hypothalamic neurons suggest that the hypocretins function in intercellular communication. To characterize these peptides further and to help understand what physiological functions they may serve, we undertook an immunohistochemical study to examine the distribution of preprohypocretin-immunoreactive neurons and fibers in the rat brain. Preprohypocretin-positive neurons were found in the perifornical nucleus and in the dorsal and lateral hypothalamic areas. These cells were distinct from those that express melanin-concentrating hormone. Although they represent a restricted group of cells, their projections were widely distributed in the brain. We observed labeled fibers throughout the hypothalamus. The densest extrahypothalamic projection was found in the locus coeruleus. Fibers were also seen in the septal nuclei, the bed nucleus of the stria terminalis, the paraventricular and reuniens nuclei of the thalamus, the zona incerta, the subthalamic nucleus, the central gray, the substantia nigra, the raphe nuclei, the parabrachial area, the medullary reticular formation, and the nucleus of the solitary tract. Less prominent projections were found in cortical regions, central and anterior amygdaloid nuclei, and the olfactory bulb. These results suggest that hypocretins are likely to have a role in physiological functions in addition to food intake such as regulation of blood pressure, the neuroendocrine system, body temperature, and the sleep–waking cycle.

Recent studies suggest that stress-induced atrophy and loss of hippocampal neurons may contribute to the pathophysiology of depression. The aim of this study was to investigate the effect of antidepressants on hippocampal neurogenesis in the adult rat, using the thymidine analog bromodeoxyuridine (BrdU) as a marker for dividing cells. Our studies demonstrate that chronic antidepressant treatment significantly increases the number of BrdU-labeled cells in the dentate gyrus and hilus of the hippocampus. Administration of several different classes of antidepressant, but not non-antidepressant, agents was found to increase BrdU-labeled cell number, indicating that this is a common and selective action of antidepressants. In addition, upregulation of the number of BrdU-labeled cells is observed after chronic, but not acute, treatment, consistent with the time course for the therapeutic action of antidepressants. Additional studies demonstrated that antidepressant treatment increases the proliferation of hippocampal cells and that these new cells mature and become neurons, as determined by triple labeling for BrdU and neuronal- or glial-specific markers. These findings raise the possibility that increased cell proliferation and increased neuronal number may be a mechanism by which antidepressant treatment overcomes the stress-induced atrophy and loss of hippocampal neurons and may contribute to the therapeutic actions of antidepressant treatment.

Understanding the cell–cell interactions that control CNS development and function has long been limited by the lack of methods to cleanly separate neural cell types. Here we describe methods for the prospective isolation and purification of astrocytes, neurons, and oligodendrocytes from developing and mature mouse forebrain. We used FACS (fluorescent-activated cell sorting) to isolate astrocytes from transgenic mice that express enhanced green fluorescent protein (EGFP) under the control of an S100β promoter. Using Affymetrix GeneChip Arrays, we then created a transcriptome database of the expression levels of >20,000 genes by gene profiling these three main CNS neural cell types at various postnatal ages between postnatal day 1 (P1) and P30. This database provides a detailed global characterization and comparison of the genes expressed by acutely isolated astrocytes, neurons, and oligodendrocytes. We found that Aldh1L1 is a highly specific antigenic marker for astrocytes with a substantially broader pattern of astrocyte expression than the traditional astrocyte marker GFAP. Astrocytes were enriched in specific metabolic and lipid synthetic pathways, as well as the draper/Megf10 and Mertk/integrin α_vβ₅phagocytic pathways suggesting that astrocytes are professional phagocytes. Our findings call into question the concept of a “glial” cell class as the gene profiles of astrocytes and oligodendrocytes are as dissimilar to each other as they are to neurons. This transcriptome database of acutely isolated purified astrocytes, neurons, and oligodendrocytes provides a resource to the neuroscience community by providing improved cell-type-specific markers and for better understanding of neural development, function, and disease.

The development of stimulus selectivity in the primary sensory cortex of higher vertebrates is considered in a general mathematical framework. A synaptic evolution scheme of a new kind is proposed in which incoming patterns rather than converging afferents compete. The change in the efficacy of a given synapse depends not only on instantaneous pre- and postsynaptic activities but also on a slowly varying time-averaged value of the postsynaptic activity. Assuming an appropriate nonlinear form for this dependence, development of selectivity is obtained under quite general conditions on the sensory environment. One does not require nonlinearity of the neuron's integrative power nor does one need to assume any particular form for intracortical circuitry. This is first illustrated in simple cases, e.g., when the environment consists of only two different stimuli presented alternately in a random manner. The following formal statement then holds: the state of the system converges with probability 1 to points of maximum selectivity in the state space. We next consider the problem of early development of orientation selectivity and binocular interaction in primary visual cortex. Giving the environment an appropriate form, we obtain orientation tuning curves and ocular dominance comparable to what is observed in normally reared adult cats or monkeys. Simulations with binocular input and various types of normal or altered environments show good agreement with the relevant experimental data. Experiments are suggested that could test our theory further.

Mutations in the genes for amyloid precursor protein (APP) and presenilins (PS1, PS2) increase production of β-amyloid 42 (Aβ₄₂) and cause familial Alzheimer's disease (FAD). Transgenic mice that express FAD mutant APP and PS1 overproduce Aβ₄₂and exhibit amyloid plaque pathology similar to that found in AD, but most transgenic models develop plaques slowly. To accelerate plaque development and investigate the effects of very high cerebral Aβ₄₂levels, we generated APP/PS1 double transgenic mice that coexpress five FAD mutations (5XFAD mice) and additively increase Aβ₄₂production. 5XFAD mice generate Aβ₄₂almost exclusively and rapidly accumulate massive cerebral Aβ₄₂levels. Amyloid deposition (and gliosis) begins at 2 months and reaches a very large burden, especially in subiculum and deep cortical layers. Intraneuronal Aβ₄₂accumulates in 5XFAD brain starting at 1.5 months of age (before plaques form), is aggregated (as determined by thioflavin S staining), and occurs within neuron soma and neurites. Some amyloid deposits originate within morphologically abnormal neuron soma that contain intraneuronal Aβ. Synaptic markers synaptophysin, syntaxin, and postsynaptic density-95 decrease with age in 5XFAD brain, and large pyramidal neurons in cortical layer 5 and subiculum are lost. In addition, levels of the activation subunit of cyclin-dependent kinase 5, p25, are elevated significantly at 9 months in 5XFAD brain, although an upward trend is observed by 3 months of age, before significant neurodegeneration or neuron loss. Finally, 5XFAD mice have impaired memory in the Y-maze. Thus, 5XFAD mice rapidly recapitulate major features of AD amyloid pathology and may be useful models of intraneuronal Aβ₄₂-induced neurodegeneration and amyloid plaque formation.

Small-world properties have been demonstrated for many complex networks. Here, we applied the discrete wavelet transform to functional magnetic resonance imaging (fMRI) time series, acquired from healthy volunteers in the resting state, to estimate frequency-dependent correlation matrices characterizing functional connectivity between 90 cortical and subcortical regions. After thresholding the wavelet correlation matrices to create undirected graphs of brain functional networks, we found a small-world topology of sparse connections most salient in the low-frequency interval 0.03–0.06 Hz. Global mean path length (2.49) was approximately equivalent to a comparable random network, whereas clustering (0.53) was two times greater; similar parameters have been reported for the network of anatomical connections in the macaque cortex. The human functional network was dominated by a neocortical core of highly connected hubs and had an exponentially truncated power law degree distribution. Hubs included recently evolved regions of the heteromodal association cortex, with long-distance connections to other regions, and more cliquishly connected regions of the unimodal association and primary cortices; paralimbic and limbic regions were topologically more peripheral. The network was more resilient to targeted attack on its hubs than a comparable scale-free network, but about equally resilient to random error. We conclude that correlated, low-frequency oscillations in human fMRI data have a small-world architecture that probably reflects underlying anatomical connectivity of the cortex. Because the major hubs of this network are critical for cognition, its slow dynamics could provide a physiological substrate for segregated and distributed information processing.

The linear transform model of functional magnetic resonance imaging (fMRI) hypothesizes that fMRI responses are proportional to local average neural activity averaged over a period of time. This work reports results from three empirical tests that support this hypothesis. First, fMRI responses in human primary visual cortex (V1) depend separably on stimulus timing and stimulus contrast. Second, responses to long-duration stimuli can be predicted from responses to shorter duration stimuli. Third, the noise in the fMRI data is independent of stimulus contrast and temporal period. Although these tests can not prove the correctness of the linear transform model, they might have been used to reject the model. Because the linear transform model is consistent with our data, we proceeded to estimate the temporal fMRI impulse–response function and the underlying (presumably neural) contrast–response function of human V1.