Literature DB >> 24972604

Quantitative investigations of axonal and dendritic arbors: development, structure, function, and pathology.

Ruchi Parekh1, Giorgio A Ascoli2.   

Abstract

The branching structures of neurons are a long-standing focus of neuroscience. Axonal and dendritic morphology affect synaptic signaling, integration, and connectivity, and their diversity reflects the computational specialization of neural circuits. Altered neuronal morphology accompanies functional changes during development, experience, aging, and disease. Technological improvements continuously accelerate high-throughput tissue processing, image acquisition, and morphological reconstruction. Digital reconstructions of neuronal morphologies allow for complex quantitative analyses that are unattainable from raw images or two-dimensional tracings. Furthermore, digitized morphologies enable computational modeling of biophysically realistic neuronal dynamics. Additionally, reconstructions generated to address specific scientific questions have the potential for continued investigations beyond the original reason for their acquisition. Facilitating multiple reuse are repositories like NeuroMorpho.Org, which ease the sharing of reconstructions. Here, we review selected scientific literature reporting the reconstruction of axonal or dendritic morphology with diverse goals including establishment of neuronal identity, examination of physiological properties, and quantification of developmental or pathological changes. These reconstructions, deposited in NeuroMorpho.Org, have since been used by other investigators in additional research, of which we highlight representative examples. This cycle of data generation, analysis, sharing, and reuse reveals the vast potential of digital reconstructions in quantitative investigations of neuronal morphology.
© The Author(s) 2014.

Entities:  

Keywords:  data sharing; database; neuron morphology; quantitative analysis; three-dimensional reconstructions

Mesh:

Year:  2014        PMID: 24972604      PMCID: PMC4723268          DOI: 10.1177/1073858414540216

Source DB:  PubMed          Journal:  Neuroscientist        ISSN: 1073-8584            Impact factor:   7.519


  87 in total

1.  Passive electrotonic properties of rat hippocampal CA3 interneurones.

Authors:  R A Chitwood; A Hubbard; D B Jaffe
Journal:  J Physiol       Date:  1999-03-15       Impact factor: 5.182

Review 2.  Successes and rewards in sharing digital reconstructions of neuronal morphology.

Authors:  Giorgio A Ascoli
Journal:  Neuroinformatics       Date:  2007

3.  Determinants of voltage attenuation in neocortical pyramidal neuron dendrites.

Authors:  G Stuart; N Spruston
Journal:  J Neurosci       Date:  1998-05-15       Impact factor: 6.167

4.  Intracellular and computational characterization of the intracortical inhibitory control of synchronized thalamic inputs in vivo.

Authors:  D Contreras; A Destexhe; M Steriade
Journal:  J Neurophysiol       Date:  1997-07       Impact factor: 2.714

5.  Anatomical, physiological, molecular and circuit properties of nest basket cells in the developing somatosensory cortex.

Authors:  Yun Wang; Anirudh Gupta; Maria Toledo-Rodriguez; Cai Zhi Wu; Henry Markram
Journal:  Cereb Cortex       Date:  2002-04       Impact factor: 5.357

6.  Nicotinic α5 subunits drive developmental changes in the activation and morphology of prefrontal cortex layer VI neurons.

Authors:  Craig D C Bailey; Nyresa C Alves; Raad Nashmi; Mariella De Biasi; Evelyn K Lambe
Journal:  Biol Psychiatry       Date:  2011-10-25       Impact factor: 13.382

7.  Evidence of a breakdown of corticostriatal connections in Parkinson's disease.

Authors:  B Stephens; A J Mueller; A F Shering; S H Hood; P Taggart; G W Arbuthnott; J E Bell; L Kilford; A E Kingsbury; S E Daniel; C A Ingham
Journal:  Neuroscience       Date:  2005       Impact factor: 3.590

8.  Total number and ratio of excitatory and inhibitory synapses converging onto single interneurons of different types in the CA1 area of the rat hippocampus.

Authors:  A I Gulyás; M Megías; Z Emri; T F Freund
Journal:  J Neurosci       Date:  1999-11-15       Impact factor: 6.167

9.  Comparative neuronal morphology of the cerebellar cortex in afrotherians, carnivores, cetartiodactyls, and primates.

Authors:  Bob Jacobs; Nicholas L Johnson; Devin Wahl; Matthew Schall; Busisiwe C Maseko; Albert Lewandowski; Mary A Raghanti; Bridget Wicinski; Camilla Butti; William D Hopkins; Mads F Bertelsen; Timothy Walsh; John R Roberts; Roger L Reep; Patrick R Hof; Chet C Sherwood; Paul R Manger
Journal:  Front Neuroanat       Date:  2014-04-23       Impact factor: 3.856

10.  Morphology and physiology of excitatory neurons in layer 6b of the somatosensory rat barrel cortex.

Authors:  Manuel Marx; Dirk Feldmeyer
Journal:  Cereb Cortex       Date:  2012-09-03       Impact factor: 5.357

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  17 in total

1.  Highlights from the Era of Open Source Web-Based Tools.

Authors:  Kristin R Anderson; Julie A Harris; Lydia Ng; Pjotr Prins; Sara Memar; Bengt Ljungquist; Daniel Fürth; Robert W Williams; Giorgio A Ascoli; Dani Dumitriu
Journal:  J Neurosci       Date:  2021-01-20       Impact factor: 6.167

2.  Win-win data sharing in neuroscience.

Authors:  Giorgio A Ascoli; Patricia Maraver; Sumit Nanda; Sridevi Polavaram; Rubén Armañanzas
Journal:  Nat Methods       Date:  2017-01-31       Impact factor: 28.547

3.  Influence of the size and curvedness of neural projections on the orientationally averaged diffusion MR signal.

Authors:  Evren Özarslan; Cem Yolcu; Magnus Herberthson; Hans Knutsson; Carl-Fredrik Westin
Journal:  Front Phys       Date:  2018-03-02

4.  Embryonic and postnatal neurogenesis produce functionally distinct subclasses of dopaminergic neuron.

Authors:  Elisa Galliano; Eleonora Franzoni; Marine Breton; Annisa N Chand; Darren J Byrne; Venkatesh N Murthy; Matthew S Grubb
Journal:  Elife       Date:  2018-04-20       Impact factor: 8.140

5.  Doubling up on the fly: NeuroMorpho.Org Meets Big Data.

Authors:  Sumit Nanda; M Mowafak Allaham; Maurizio Bergamino; Sridevi Polavaram; Rubén Armañanzas; Giorgio A Ascoli; Ruchi Parekh
Journal:  Neuroinformatics       Date:  2015-01

6.  The importance of metadata to assess information content in digital reconstructions of neuronal morphology.

Authors:  Ruchi Parekh; Rubén Armañanzas; Giorgio A Ascoli
Journal:  Cell Tissue Res       Date:  2015-02-05       Impact factor: 5.249

Review 7.  Towards the automatic classification of neurons.

Authors:  Rubén Armañanzas; Giorgio A Ascoli
Journal:  Trends Neurosci       Date:  2015-03-09       Impact factor: 13.837

8.  Efficient metadata mining of web-accessible neural morphologies.

Authors:  Masood A Akram; Bengt Ljungquist; Giorgio A Ascoli
Journal:  Prog Biophys Mol Biol       Date:  2021-05-19       Impact factor: 3.667

9.  Sharing Neuron Data: Carrots, Sticks, and Digital Records.

Authors:  Giorgio A Ascoli
Journal:  PLoS Biol       Date:  2015-10-08       Impact factor: 8.029

10.  Hippocampome.org: a knowledge base of neuron types in the rodent hippocampus.

Authors:  Diek W Wheeler; Charise M White; Christopher L Rees; Alexander O Komendantov; David J Hamilton; Giorgio A Ascoli
Journal:  Elife       Date:  2015-09-24       Impact factor: 8.140

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