Example of Brain Topography format
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Example of Brain Topography format Example of Brain Topography format Example of Brain Topography format Example of Brain Topography format Example of Brain Topography format Example of Brain Topography format Example of Brain Topography format Example of Brain Topography format Example of Brain Topography format Example of Brain Topography format Example of Brain Topography format Example of Brain Topography format Example of Brain Topography format Example of Brain Topography format Example of Brain Topography format Example of Brain Topography format Example of Brain Topography format Example of Brain Topography format
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Example of Brain Topography format Example of Brain Topography format Example of Brain Topography format Example of Brain Topography format Example of Brain Topography format Example of Brain Topography format Example of Brain Topography format Example of Brain Topography format Example of Brain Topography format Example of Brain Topography format Example of Brain Topography format Example of Brain Topography format Example of Brain Topography format Example of Brain Topography format Example of Brain Topography format Example of Brain Topography format Example of Brain Topography format Example of Brain Topography format
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open access Open Access

Brain Topography — Template for authors

Publisher: Springer
Categories Rank Trend in last 3 yrs
Radiology, Nuclear Medicine and Imaging #45 of 288 down down by 23 ranks
Anatomy #7 of 37 down down by 3 ranks
Radiological and Ultrasound Technology #11 of 51 down down by 5 ranks
Neurology (clinical) #77 of 343 down down by 31 ranks
Neurology #46 of 156 down down by 14 ranks
journal-quality-icon Journal quality:
High
calendar-icon Last 4 years overview: 274 Published Papers | 1579 Citations
indexed-in-icon Indexed in: Scopus
last-updated-icon Last updated: 15/06/2020
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Related Journals

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Journal Performance & Insights

Impact Factor

CiteRatio

Determines the importance of a journal by taking a measure of frequency with which the average article in a journal has been cited in a particular year.

A measure of average citations received per peer-reviewed paper published in the journal.

2.759

11% from 2018

Impact factor for Brain Topography from 2016 - 2019
Year Value
2019 2.759
2018 3.104
2017 2.703
2016 3.394
graph view Graph view
table view Table view

5.8

9% from 2019

CiteRatio for Brain Topography from 2016 - 2020
Year Value
2020 5.8
2019 5.3
2018 4.9
2017 6.7
2016 6.6
graph view Graph view
table view Table view

insights Insights

  • Impact factor of this journal has decreased by 11% in last year.
  • This journal’s impact factor is in the top 10 percentile category.

insights Insights

  • CiteRatio of this journal has increased by 9% in last years.
  • This journal’s CiteRatio is in the top 10 percentile category.

SCImago Journal Rank (SJR)

Source Normalized Impact per Paper (SNIP)

Measures weighted citations received by the journal. Citation weighting depends on the categories and prestige of the citing journal.

Measures actual citations received relative to citations expected for the journal's category.

1.147

12% from 2019

SJR for Brain Topography from 2016 - 2020
Year Value
2020 1.147
2019 1.028
2018 1.175
2017 1.365
2016 1.752
graph view Graph view
table view Table view

0.995

10% from 2019

SNIP for Brain Topography from 2016 - 2020
Year Value
2020 0.995
2019 0.908
2018 1.006
2017 1.017
2016 1.075
graph view Graph view
table view Table view

insights Insights

  • SJR of this journal has increased by 12% in last years.
  • This journal’s SJR is in the top 10 percentile category.

insights Insights

  • SNIP of this journal has increased by 10% in last years.
  • This journal’s SNIP is in the top 10 percentile category.

Brain Topography

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Springer

Brain Topography

Brain Topography publishes clinical and basic research on cognitive neuroscience and functional neurophysiology using the full range of imaging techniques including EEG, MEG, fMRI, TMS, diffusion imaging, spectroscopy, intracranial recordings, lesion studies, and related metho...... Read More

Medicine

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Last updated on
15 Jun 2020
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ISSN
0896-0267
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Impact Factor
High - 1.147
i
Open Access
No
i
Sherpa RoMEO Archiving Policy
Green faq
i
Plagiarism Check
Available via Turnitin
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Endnote Style
Download Available
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Bibliography Name
SPBASIC
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Citation Type
Author Year
(Blonder et al, 1982)
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Bibliography Example
Beenakker CWJ (2006) Specular andreev reflection in graphene. Phys Rev Lett 97(6):067,007, URL 10.1103/PhysRevLett.97.067007

Top papers written in this journal

open accessOpen access Journal Article DOI: 10.1007/S10548-008-0054-5
Topographic ERP Analyses: A Step-by-Step Tutorial Review
Micah M. Murray1, Denis Brunet, Christoph M. Michel
18 Mar 2008 - Brain Topography

Abstract:

In this tutorial review, we detail both the rationale for as well as the implementation of a set of analyses of surface-recorded event-related potentials (ERPs) that uses the reference-free spatial (i.e. topographic) information available from high-density electrode montages to render statistical information concerning modula... In this tutorial review, we detail both the rationale for as well as the implementation of a set of analyses of surface-recorded event-related potentials (ERPs) that uses the reference-free spatial (i.e. topographic) information available from high-density electrode montages to render statistical information concerning modulations in response strength, latency, and topography both between and within experimental conditions. In these and other ways these topographic analysis methods allow the experimenter to glean additional information and neurophysiologic interpretability beyond what is available from canonical waveform analyses. In this tutorial we present the example of somatosensory evoked potentials (SEPs) in response to stimulation of each hand to illustrate these points. For each step of these analyses, we provide the reader with both a conceptual and mathematical description of how the analysis is carried out, what it yields, and how to interpret its statistical outcome. We show that these topographic analysis methods are intuitive and easy-to-use approaches that can remove much of the guesswork often confronting ERP researchers and also assist in identifying the information contained within high-density ERP datasets. read more read less
View PDF
916 Citations
Journal Article DOI: 10.1023/B:BRAT.0000006333.93597.9D
Using the international 10-20 EEG system for positioning of transcranial magnetic stimulation.
Uwe Herwig1, Peyman Satrapi, Carlos Schönfeldt-Lecuona
01 Jan 2003 - Brain Topography

Abstract:

Background The International 10-20 system for EEG electrode placement is increasingly applied for the positioning of transcranial magnetic stimulation (TMS) in cognitive neuroscience and in psychiatric treatment studies. The crucial issue in TMS studies remains the reliable positioning of the coil above the skull for targetin... Background The International 10-20 system for EEG electrode placement is increasingly applied for the positioning of transcranial magnetic stimulation (TMS) in cognitive neuroscience and in psychiatric treatment studies. The crucial issue in TMS studies remains the reliable positioning of the coil above the skull for targeting a desired cortex region. In order to asses the precision of the 10-20 system for this purpose, we tested its projections onto the underlying cortex by using neuronavigation. Methods In 21 subjects, the 10-20 positions F3, F4, T3, TP3, and P3, as determined by a 10-20 positioning cap, were targeted stereotactically. The corresponding individual anatomical sites were identified in the Talairach atlas. Results The main targeted regions were: for F3 Brodmann areas (BA) 8/9 within the dorsolateral prefrontal cortex, for T3 BA 22/42 on the superior temporal gyrus, for TP3 BA 40/39 in thearea of the supramarginal and angular gyrus, and for P3 BA 7/40 on the inferior parietal lobe. However, in about 10% of the measurements adjacent and possibly functionally distinct BAs were reached. The ranges were mainly below 20 mm. Conclusion Using the 10-20 system for TMS positioning is applicable at low cost and may reach desired cortex regions reliably on a larger scale level. For finer grained positioning, possible interindividual differences, and therefore the application of neuroimaging based methods, are to be considered. read more read less

Topics:

Dorsolateral prefrontal cortex (58%)58% related to the paper, Angular gyrus (56%)56% related to the paper, Transcranial magnetic stimulation (54%)54% related to the paper, Cortex (anatomy) (52%)52% related to the paper, Superior temporal gyrus (51%)51% related to the paper
872 Citations
Journal Article DOI: 10.1023/A:1023437823106
Mu and beta rhythm topographies during motor imagery and actual movements.
Dennis J. McFarland1, Laurie A. Miner1, Theresa M. Vaughan1, Jonathan R. Wolpaw1
01 Jan 2000 - Brain Topography

Abstract:

People can learn to control the 8-12 Hz mu rhythm and/or the 18-25 Hz beta rhythm in the EEG recorded over sensorimotor cortex and use it to control a cursor on a video screen. Subjects often report using motor imagery to control cursor movement, particularly early in training. We compared in untrained subjects the EEG topogr... People can learn to control the 8-12 Hz mu rhythm and/or the 18-25 Hz beta rhythm in the EEG recorded over sensorimotor cortex and use it to control a cursor on a video screen. Subjects often report using motor imagery to control cursor movement, particularly early in training. We compared in untrained subjects the EEG topographies associated with actual hand movement to those associated with imagined hand movement. Sixty-four EEG channels were recorded while each of 33 adults moved left- or right-hand or imagined doing so. Frequency-specific differences between movement or imagery and rest, and between right- and left-hand movement or imagery, were evaluated by scalp topographies of voltage and r spectra, and principal component analysis. Both movement and imagery were associated with mu and beta rhythm desynchronization. The mu topographies showed bilateral foci of desynchronization over sensorimotor cortices, while the beta topographies showed peak desynchronization over the vertex. Both mu and beta rhythm left/right differences showed bilateral central foci that were stronger on the right side. The independence of mu and beta rhythms was demonstrated by differences for movement and imagery for the subjects as a group and by principal components analysis. The results indicated that the effects of imagery were not simply an attenuated version of the effects of movement. They supply evidence that motor imagery could play an important role in EEG-based communication, and suggest that mu and beta rhythms might provide independent control signals. read more read less

Topics:

Beta Rhythm (63%)63% related to the paper, Sensorimotor rhythm (60%)60% related to the paper, Motor imagery (53%)53% related to the paper, Rhythm (50%)50% related to the paper
View PDF
802 Citations
Journal Article DOI: 10.1023/B:BRAT.0000032864.93890.F9
Suppression of interference and artifacts by the Signal Space Separation Method.
Samu Taulu, Matti Kajola, Juha Simola
22 Jan 2003 - Brain Topography

Abstract:

Multichannel measurement with hundreds of channels oversamples a curl-free vector field, like the magnetic field in a volume free of sources. This is based on the constraint caused by the Laplace's equation for the magnetic scalar potential; outside of the source volume the signals are spatially band limited. A functional sol... Multichannel measurement with hundreds of channels oversamples a curl-free vector field, like the magnetic field in a volume free of sources. This is based on the constraint caused by the Laplace's equation for the magnetic scalar potential; outside of the source volume the signals are spatially band limited. A functional solution of Laplace's equation enables one to separate the signals arising from the sphere enclosing the interesting sources, e.g. the currents in the brain, from the magnetic interference. Signal space separation (SSS) is accomplished by calculating individual basis vectors for each term of the functional expansion to create a signal basis covering all measurable signal vectors. Because the SSS basis is linearly independent for all practical sensor arrangements, any signal vector has a unique SSS decomposition with separate coefficients for the interesting signals and signals coming from outside the interesting volume. Thus, SSS basis provides an elegant method to remove external disturbances. The device-independent SSS coefficients can be used in transforming the interesting signals to virtual sensor configurations. This can also be used in compensating for distortions caused by movement of the object by modeling it as movement of the sensor array around a static object. The device-independence of the decomposition also enables physiological DC phenomena to be recorded using voluntary head movements. When used with properly designed sensor array, SSS does not affect the morphology or the signal-to-noise ratio of the interesting signals. read more read less

Topics:

Sensor array (55%)55% related to the paper, Signal (55%)55% related to the paper, Interference (communication) (52%)52% related to the paper, Basis (linear algebra) (52%)52% related to the paper, Signal processing (51%)51% related to the paper
508 Citations
open accessOpen access Journal Article DOI: 10.1007/BF01140588
Phase space topography and the Lyapunov exponent of electrocorticograms in partial seizures
Leonidas D. Iasemidis, J. Chris Sackellares1, Hitten P. Zaveri, William J. Williams
01 Jan 1990 - Brain Topography

Abstract:

Summary: Electrocorticograms (ECoG's) from 16 of 68 chronically implanted subdural electrodes, placed over the right temporal cortex in a patient with a right medial temporal focus, were analyzed using methods from nonlinear dynamics. A time series provides information about a large number of pertinent variables, which may be... Summary: Electrocorticograms (ECoG's) from 16 of 68 chronically implanted subdural electrodes, placed over the right temporal cortex in a patient with a right medial temporal focus, were analyzed using methods from nonlinear dynamics. A time series provides information about a large number of pertinent variables, which may be used to explore and characterize the system's dynamics. These variables and their evolution in time produce the phase portrait of the system. The phase spaces for each of 16 electrodes were constructed and from these the largest average Lyapunov exponents (L's), measures of chaoticity of the system (the larger the L, the more chaotic the system is), were estimated over time for every electrode before, in and after the epileptic seizure for three seizures of the same patient. The start of the seizure corresponds to a simultaneous drop in L values obtained at the electrodes nearest the focus. L values for the rest of the electrodes follow. The mean values of L for all electrodes in the postictal state are larger than the ones in the preictal state, denoting a more chaotic state postictally. The lowest values of L occur during the seizure but they are still positive denoting the presence of a chaotic attractor. Based on the procedure for the estimation of L we were able to develop a methodology for detecting prominent spikes in the ECoG. These measures (L*) calculated over a period of time (10 minutes before to 10 minutes after the seizure outburst) revealed a remarkable coherence of the abrupt transient drops of L* for the electrodes that showed the inital ictal onset. The L* values for the electrodes away from the focus exhibited less abrupt transient drops. These results indicate that the largest average Lyapunov exponent L can be useful in seizure detection as well as a discriminatory factor for focus localization in multielectrode analysis. read more read less

Topics:

Temporal cortex (52%)52% related to the paper, Ictal (51%)51% related to the paper, Lyapunov exponent (50%)50% related to the paper, Epileptic seizure (50%)50% related to the paper
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488 Citations
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Frequently asked questions

1. Can I write Brain Topography in LaTeX?

Absolutely not! Our tool has been designed to help you focus on writing. You can write your entire paper as per the Brain Topography guidelines and auto format it.

2. Do you follow the Brain Topography guidelines?

Yes, the template is compliant with the Brain Topography guidelines. Our experts at SciSpace ensure that. If there are any changes to the journal's guidelines, we'll change our algorithm accordingly.

3. Can I cite my article in multiple styles in Brain Topography?

Of course! We support all the top citation styles, such as APA style, MLA style, Vancouver style, Harvard style, and Chicago style. For example, when you write your paper and hit autoformat, our system will automatically update your article as per the Brain Topography citation style.

4. Can I use the Brain Topography templates for free?

Sign up for our free trial, and you'll be able to use all our features for seven days. You'll see how helpful they are and how inexpensive they are compared to other options, Especially for Brain Topography.

5. Can I use a manuscript in Brain Topography that I have written in MS Word?

Yes. You can choose the right template, copy-paste the contents from the word document, and click on auto-format. Once you're done, you'll have a publish-ready paper Brain Topography that you can download at the end.

6. How long does it usually take you to format my papers in Brain Topography?

It only takes a matter of seconds to edit your manuscript. Besides that, our intuitive editor saves you from writing and formatting it in Brain Topography.

7. Where can I find the template for the Brain Topography?

It is possible to find the Word template for any journal on Google. However, why use a template when you can write your entire manuscript on SciSpace , auto format it as per Brain Topography's guidelines and download the same in Word, PDF and LaTeX formats? Give us a try!.

8. Can I reformat my paper to fit the Brain Topography's guidelines?

Of course! You can do this using our intuitive editor. It's very easy. If you need help, our support team is always ready to assist you.

9. Brain Topography an online tool or is there a desktop version?

SciSpace's Brain Topography is currently available as an online tool. We're developing a desktop version, too. You can request (or upvote) any features that you think would be helpful for you and other researchers in the "feature request" section of your account once you've signed up with us.

10. I cannot find my template in your gallery. Can you create it for me like Brain Topography?

Sure. You can request any template and we'll have it setup within a few days. You can find the request box in Journal Gallery on the right side bar under the heading, "Couldn't find the format you were looking for like Brain Topography?”

11. What is the output that I would get after using Brain Topography?

After writing your paper autoformatting in Brain Topography, you can download it in multiple formats, viz., PDF, Docx, and LaTeX.

12. Is Brain Topography's impact factor high enough that I should try publishing my article there?

To be honest, the answer is no. The impact factor is one of the many elements that determine the quality of a journal. Few of these factors include review board, rejection rates, frequency of inclusion in indexes, and Eigenfactor. You need to assess all these factors before you make your final call.

13. What is Sherpa RoMEO Archiving Policy for Brain Topography?

SHERPA/RoMEO Database

We extracted this data from Sherpa Romeo to help researchers understand the access level of this journal in accordance with the Sherpa Romeo Archiving Policy for Brain Topography. The table below indicates the level of access a journal has as per Sherpa Romeo's archiving policy.

RoMEO Colour Archiving policy
Green Can archive pre-print and post-print or publisher's version/PDF
Blue Can archive post-print (ie final draft post-refereeing) or publisher's version/PDF
Yellow Can archive pre-print (ie pre-refereeing)
White Archiving not formally supported
FYI:
  1. Pre-prints as being the version of the paper before peer review and
  2. Post-prints as being the version of the paper after peer-review, with revisions having been made.

14. What are the most common citation types In Brain Topography?

The 5 most common citation types in order of usage for Brain Topography are:.

S. No. Citation Style Type
1. Author Year
2. Numbered
3. Numbered (Superscripted)
4. Author Year (Cited Pages)
5. Footnote

15. How do I submit my article to the Brain Topography?

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16. Can I download Brain Topography in Endnote format?

Yes, SciSpace provides this functionality. After signing up, you would need to import your existing references from Word or Bib file to SciSpace. Then SciSpace would allow you to download your references in Brain Topography Endnote style according to Elsevier guidelines.

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