SUMMARY Production of new neurons in the adult hippocampus decreases with age; this decline may underlie age-related cognitive impairment. Here we show that continuous depletion of the neural stem cell pool as a consequence of their division may contribute to the age-related decrease in hippocampal neurogenesis. Our results indicate that adult hippocampal stem cells, upon exiting their quiescent state, rapidly undergo a series of asymmetric divisions to produce dividing progeny destined to become neurons and subsequently convert into mature astrocytes. Thus, the decrease in the number of neural stem cells is a division-coupled process and is directly related to their production of new neurons. We present a scheme of the neurogenesis cascade in the adult hippocampus that includes a proposed “disposable stem cell” model and accounts for the disappearance of hippocampal neural stem cells, the appearance of new astrocytes, and the age-related decline in the production of new neurons.
Responses of mitral cells represent the results of the first stage of odor processing in the olfactory bulb. Most of our knowledge about mitral cell activity has been obtained from recordings in anesthetized animals. We compared odor-elicited changes in firing rate of mitral cells in awake behaving mice and in anesthetized mice. We show that odor-elicited changes in mitral cell firing rate were larger and more frequently observed in the anesthetized than in the awake condition. Only 27% of mitral cells that showed a response to odors in the anesthetized state were also odor responsive in the awake state. The amplitude of their response in the awake state was smaller, and some of the responses changed sign compared with their responses in the anesthetized state. The odor representation in the olfactory bulb is therefore sparser in awake behaving mice than in anesthetized preparations. A qualitative explanation of the mechanism responsible for this phenomenon is proposed.
We studied the spatial organization of directionally selective neurons in the cortical middle temporal visual area (area MT) of the Cebus monkey. We recorded neuronal activity from multielectrode arrays as they were stepped through area MT. The set of recording sites in each array penetration described a plane parallel to the cortical layers. At each recording site, we determined the preferred direction of motion. Responses recorded at successive locations from the same electrode in the array revealed gradual changes in preferred direction, along with occasional directional reversals. Comparisons of responses from adjacent electrodes at successive locations enabled electrophysiological imaging of the two-dimensional pattern of preferred directions across the cortex. Our results demonstrate a systematic organization for directionality in area MT of the New World Cebus monkey, which is similar to that known to exist in the Old World macaque. In addition, our results provide electrophysiological confirmation of map features that have been documented in other cortical areas and primate species by optical imaging. Specifically, the tangential organization of directional selectivity is characterized by slow continuous changes in directional preference, as well as lines (fractures) and points (singularities) that fragment continuous regions into patches. These electrophysiological methods also allowed a direct investigation of neuronal selectivities that give rise to map features. In particular, our results suggest that inhibitory mechanisms may be involved in the generation of fractures and singularities.
Table of contentsA1 Functional advantages of cell-type heterogeneity in neural circuitsTatyana O. SharpeeA2 Mesoscopic modeling of propagating waves in visual cortexAlain DestexheA3 Dynamics and biomarkers of mental disordersMitsuo KawatoF1 Precise recruitment of spiking output at theta frequencies requires dendritic h-channels in multi-compartment models of oriens-lacunosum/moleculare hippocampal interneuronsVladislav Sekulić, Frances K. SkinnerF2 Kernel methods in reconstruction of current sources from extracellular potentials for single cells and the whole brainsDaniel K. Wójcik, Chaitanya Chintaluri, Dorottya Cserpán, Zoltán SomogyváriF3 The synchronized periods depend on intracellular transcriptional repression mechanisms in circadian clocks.Jae Kyoung Kim, Zachary P. Kilpatrick, Matthew R. Bennett, Kresimir JosićO1 Assessing irregularity and coordination of spiking-bursting rhythms in central pattern generatorsIrene Elices, David Arroyo, Rafael Levi, Francisco B. Rodriguez, Pablo VaronaO2 Regulation of top-down processing by cortically-projecting parvalbumin positive neurons in basal forebrainEunjin Hwang, Bowon Kim, Hio-Been Han, Tae Kim, James T. McKenna, Ritchie E. Brown, Robert W. McCarley, Jee Hyun ChoiO3 Modeling auditory stream segregation, build-up and bistabilityJames Rankin, Pamela Osborn Popp, John RinzelO4 Strong competition between tonotopic neural ensembles explains pitch-related dynamics of auditory cortex evoked fieldsAlejandro Tabas, André Rupp, Emili Balaguer-BallesterO5 A simple model of retinal response to multi-electrode stimulationMatias I. Maturana, David B. Grayden, Shaun L. Cloherty, Tatiana Kameneva, Michael R. Ibbotson, Hamish MeffinO6 Noise correlations in V4 area correlate with behavioral performance in visual discrimination taskVeronika Koren, Timm Lochmann, Valentin Dragoi, Klaus ObermayerO7 Input-location dependent gain modulation in cerebellar nucleus neuronsMaria Psarrou, Maria Schilstra, Neil Davey, Benjamin Torben-Nielsen, Volker SteuberO8 Analytic solution of cable energy function for cortical axons and dendritesHuiwen Ju, Jiao Yu, Michael L. Hines, Liang Chen, Yuguo YuO9 C. elegans interactome: interactive visualization of Caenorhabditis elegans worm neuronal networkJimin Kim, Will Leahy, Eli ShlizermanO10 Is the model any good? Objective criteria for computational neuroscience model selectionJustas Birgiolas, Richard C. Gerkin, Sharon M. CrookO11 Cooperation and competition of gamma oscillation mechanismsAtthaphon Viriyopase, Raoul-Martin Memmesheimer, Stan GielenO12 A discrete structure of the brain wavesYuri Dabaghian, Justin DeVito, Luca PerottiO13 Direction-specific silencing of the Drosophila gaze stabilization systemAnmo J. Kim, Lisa M. Fenk, Cheng Lyu, Gaby MaimonO14 What does the fruit fly think about values? A model of olfactory associative learningChang Zhao, Yves Widmer, Simon Sprecher,Walter SennO15 Effects of ionic diffusion on power spectra of local field potentials (LFP)Geir Halnes, Tuomo Mäki-Marttunen, Daniel Keller, Klas H. Pettersen,Ole A. Andreassen...
Directionally selective neurons strongly fire when presented with a preferred direction of motion of a bar and only weakly respond otherwise. Intuition suggests these "specialist" neurons would be better suited to report this stimulus feature to higher visual centers than "generalist" neurons, neurons that broadly modulate their activity to the feature. However, as stimuli are encoded not by one cell but by large neural ensembles, we have studied the role of single-cell receptive field properties in stimulus representation. Using regression error statistics, we compared the performance of direction-of-motion estimators, using ensembles of neurons selectively responding to direction of motion and estimators using ensembles not specializing to direction. We found that direction-selective ensembles were no better at representing a bar's direction of motion than nonselective ensembles. Quite the opposite, the nonselective unit ensembles provided a better estimate of the direction (standard deviation of the error of 33 degrees) than the direction-selective ensembles (standard deviation of the error of 42 degrees). The nonselective neurons provided information through a latency code that is apparent only when a neuron's activity is considered in the context of the responses of neighboring neurons. These results suggest that models utilizing both generalist and specialist neurons may better reflect the encoding mechanisms that take place in sensory pathways.
There is growing excitement in determining the complete connectivity diagram of the brain—the "connectome". So far, the complete connectome has been established for only one organism, C. elegans, with 302 neurons connected by about 7000 synapses—and even this was a heroic task, requiring over 50 person-years of labor. Like all current approaches, this reconstruction was based on microscopy. Unfortunately, microscopy is poorly suited to the study of neural connectivity because brains are macroscopic structures, whereas synapses are microscopic. Nevertheless, there are several large-scale projects underway to scale up high-throughput microscopic approaches to the connectome.Here we present a completely novel method for determining the brain's wiring diagram based on high-throughput DNA sequencing technology, which has not previously been applied in the context of neural connectivity. The appeal of using sequencing is that it is getting faster and cheaper exponentially: it will soon be routine to sequence an entire human genome (~3B nucleotides) within one day for $1000.Our approach has three main components. First, we express a unique sequence of nucleotides—a DNA "barcode"—in individual neurons. A barcode consisting of a random string of even 30 nucleotides can uniquely label 10^{18} neurons, far more than the number of neurons in a mouse brain (fewer than 100 million). Second, we use a specially engineered transsynaptic virus to transport “host” barcodes from one neuron to synaptically coupled partners; after transsynaptic spread, each neuron contains copies of "invader" barcodes from other synaptically coupled neurons, as well its own "host" barcode. Third, we join pairs of host and invader barcodes into single pieces of DNA suitable for high-throughput sequencing.Modern sequencing technology could in principle yield the connectivity diagram of the entire mouse brain. Similar approaches can be applied to Drosophila and C. elegans.
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