Example of Cognitive Processing format
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Example of Cognitive Processing format Example of Cognitive Processing format Example of Cognitive Processing format Example of Cognitive Processing format Example of Cognitive Processing format Example of Cognitive Processing format Example of Cognitive Processing format Example of Cognitive Processing format Example of Cognitive Processing format Example of Cognitive Processing format Example of Cognitive Processing format Example of Cognitive Processing format Example of Cognitive Processing format Example of Cognitive Processing format Example of Cognitive Processing format Example of Cognitive Processing format Example of Cognitive Processing format Example of Cognitive Processing format
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Example of Cognitive Processing format Example of Cognitive Processing format Example of Cognitive Processing format Example of Cognitive Processing format Example of Cognitive Processing format Example of Cognitive Processing format Example of Cognitive Processing format Example of Cognitive Processing format Example of Cognitive Processing format Example of Cognitive Processing format Example of Cognitive Processing format Example of Cognitive Processing format Example of Cognitive Processing format Example of Cognitive Processing format Example of Cognitive Processing format Example of Cognitive Processing format Example of Cognitive Processing format Example of Cognitive Processing format
Sample paper formatted on SciSpace - SciSpace
This content is only for preview purposes. The original open access content can be found here.
open access Open Access

Cognitive Processing — Template for authors

Publisher: Springer
Categories Rank Trend in last 3 yrs
Experimental and Cognitive Psychology #83 of 148 down down by 3 ranks
Artificial Intelligence #138 of 227 down down by 48 ranks
Cognitive Neuroscience #66 of 96 down down by 2 ranks
journal-quality-icon Journal quality:
Medium
calendar-icon Last 4 years overview: 200 Published Papers | 507 Citations
indexed-in-icon Indexed in: Scopus
last-updated-icon Last updated: 21/07/2020
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Related Journals

open access Open Access

Elsevier

Quality:  
High
CiteRatio: 6.0
SJR: 0.52
SNIP: 1.569
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SAGE

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SJR: 0.286
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Elsevier

Quality:  
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CiteRatio: 25.5
SJR: 6.857
SNIP: 5.733
open access Open Access
recommended Recommended

Elsevier

Quality:  
High
CiteRatio: 10.9
SJR: 1.396
SNIP: 2.809

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.

0.96

22% from 2018

Impact factor for Cognitive Processing from 2016 - 2019
Year Value
2019 0.96
2018 1.233
2017 1.15
2016 0.974
graph view Graph view
table view Table view

2.5

9% from 2019

CiteRatio for Cognitive Processing from 2016 - 2020
Year Value
2020 2.5
2019 2.3
2018 2.5
2017 2.4
2016 2.3
graph view Graph view
table view Table view

insights Insights

  • Impact factor of this journal has decreased by 22% 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.

0.51

10% from 2019

SJR for Cognitive Processing from 2016 - 2020
Year Value
2020 0.51
2019 0.566
2018 0.6
2017 0.579
2016 0.622
graph view Graph view
table view Table view

0.875

1% from 2019

SNIP for Cognitive Processing from 2016 - 2020
Year Value
2020 0.875
2019 0.886
2018 0.772
2017 0.697
2016 0.585
graph view Graph view
table view Table view

insights Insights

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

insights Insights

  • SNIP of this journal has decreased by 1% in last years.
  • This journal’s SNIP is in the top 10 percentile category.

Cognitive Processing

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Springer

Cognitive Processing

Cognitive Processing - International Quarterly of Cognitive Science is a peer-reviewed international journal that publishes innovative contributions in the multidisciplinary field of cognitive science.Its first aim is to present the latest results obtained in the manifold disc...... Read More

Medicine

i
Last updated on
20 Jul 2020
i
ISSN
1612-4782
i
Impact Factor
Medium - 0.92
i
Open Access
No
i
Sherpa RoMEO Archiving Policy
Green faq
i
Plagiarism Check
Available via Turnitin
i
Endnote Style
Download Available
i
Bibliography Name
SPBASIC
i
Citation Type
Author Year
(Blonder et al, 1982)
i
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/S10339-011-0430-Z
The novel object recognition memory: neurobiology, test procedure, and its modifications.
Marta Coelho Antunes1, Marta Coelho Antunes2, Grazyna Biala1
01 May 2012 - Cognitive Processing

Abstract:

Animal models of memory have been considered as the subject of many scientific publications at least since the beginning of the twentieth century. In humans, memory is often accessed through spoken or written language, while in animals, cognitive functions must be accessed through different kind of behaviors in many specific,... Animal models of memory have been considered as the subject of many scientific publications at least since the beginning of the twentieth century. In humans, memory is often accessed through spoken or written language, while in animals, cognitive functions must be accessed through different kind of behaviors in many specific, experimental models of memory and learning. Among them, the novel object recognition test can be evaluated by the differences in the exploration time of novel and familiar objects. Its application is not limited to a field of research and enables that various issues can be studied, such as the memory and learning, the preference for novelty, the influence of different brain regions in the process of recognition, and even the study of different drugs and their effects. This paper describes the novel object recognition paradigms in animals, as a valuable measure of cognition. The purpose of this work was to review the neurobiology and methodological modifications of the test commonly used in behavioral pharmacology. read more read less

Topics:

Cognition (52%)52% related to the paper, Novelty (51%)51% related to the paper
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1,635 Citations
open accessOpen access Journal Article DOI: 10.1007/S10339-007-0170-2
Predictive coding: an account of the mirror neuron system.
12 Apr 2007 - Cognitive Processing

Abstract:

Is it possible to understand the intentions of other people by simply observing their actions? Many believe that this ability is made possible by the brain’s mirror neuron system through its direct link between action and observation. However, precisely how intentions can be inferred through action observation has provoked mu... Is it possible to understand the intentions of other people by simply observing their actions? Many believe that this ability is made possible by the brain’s mirror neuron system through its direct link between action and observation. However, precisely how intentions can be inferred through action observation has provoked much debate. Here we suggest that the function of the mirror system can be understood within a predictive coding framework that appeals to the statistical approach known as empirical Bayes. Within this scheme the most likely cause of an observed action can be inferred by minimizing the prediction error at all levels of the cortical hierarchy that are engaged during action observation. This account identifies a precise role for the mirror system in our ability to infer intentions from actions and provides the outline of the underlying computational mechanisms. read more read less

Topics:

Action (philosophy) (51%)51% related to the paper, Mirror neuron (50%)50% related to the paper
View PDF
939 Citations
open accessOpen access Journal Article DOI: 10.1007/S10339-004-0013-3
The body schema and multisensory representation(s) of peripersonal space
Nicholas P. Holmes1, Charles Spence1
20 Mar 2004 - Cognitive Processing

Abstract:

To guide the movement of the body through space, the brain must constantly monitor the position and movement of the body in relation to nearby objects. The effective piloting of the body to avoid or manipulate objects in pursuit of behavioural goals requires an integrated neural representation of the body (the ‘body schema’) ... To guide the movement of the body through space, the brain must constantly monitor the position and movement of the body in relation to nearby objects. The effective piloting of the body to avoid or manipulate objects in pursuit of behavioural goals requires an integrated neural representation of the body (the ‘body schema’) and of the space around the body (‘peripersonal space’). In the review that follows, we describe and evaluate recent results from neurophysiology, neuropsychology, and psychophysics in both human and non-human primates that support the existence of an integrated representation of visual, somatosensory, and auditory peripersonal space. Such a representation involves primarily visual, somatosensory, and proprioceptive modalities, operates in body-part-centred reference frames, and demonstrates significant plasticity. Recent research shows that the use of tools, the viewing of one’s body or body parts in mirrors, and in video monitors, may also modulate the visuotactile representation of peripersonal space. read more read less

Topics:

Body schema (65%)65% related to the paper, Body awareness (55%)55% related to the paper, Representation (systemics) (51%)51% related to the paper
View PDF
565 Citations
Journal Article DOI: 10.1007/S10339-011-0404-1
Model learning for robot control: a survey
Duy Nguyen-Tuong1, Jan Peters1
13 Apr 2011 - Cognitive Processing

Abstract:

Models are among the most essential tools in robotics, such as kinematics and dynamics models of the robot’s own body and controllable external objects. It is widely believed that intelligent mammals also rely on internal models in order to generate their actions. However, while classical robotics relies on manually generated... Models are among the most essential tools in robotics, such as kinematics and dynamics models of the robot’s own body and controllable external objects. It is widely believed that intelligent mammals also rely on internal models in order to generate their actions. However, while classical robotics relies on manually generated models that are based on human insights into physics, future autonomous, cognitive robots need to be able to automatically generate models that are based on information which is extracted from the data streams accessible to the robot. In this paper, we survey the progress in model learning with a strong focus on robot control on a kinematic as well as dynamical level. Here, a model describes essential information about the behavior of the environment and the influence of an agent on this environment. In the context of model-based learning control, we view the model from three different perspectives. First, we need to study the different possible model learning architectures for robotics. Second, we discuss what kind of problems these architecture and the domain of robotics imply for the applicable learning methods. From this discussion, we deduce future directions of real-time learning algorithms. Third, we show where these scenarios have been used successfully in several case studies. read more read less

Topics:

Robot learning (73%)73% related to the paper, Evolutionary robotics (63%)63% related to the paper, Social robot (63%)63% related to the paper, Robot control (61%)61% related to the paper, Robot (59%)59% related to the paper
View PDF
506 Citations
open accessOpen access Journal Article DOI: 10.1007/S10339-013-0571-3
Active inference, sensory attenuation and illusions
Harriet R. Brown1, Rick A. Adams1, Isabel Pareés1, Mark J. Edwards1, Karl J. Friston1
07 Jun 2013 - Cognitive Processing

Abstract:

Active inference provides a simple and neurobiologically plausible account of how action and perception are coupled in producing (Bayes) optimal behaviour. This can be seen most easily as minimising prediction error: we can either change our predictions to explain sensory input through perception. Alternatively, we can active... Active inference provides a simple and neurobiologically plausible account of how action and perception are coupled in producing (Bayes) optimal behaviour. This can be seen most easily as minimising prediction error: we can either change our predictions to explain sensory input through perception. Alternatively, we can actively change sensory input to fulfil our predictions. In active inference, this action is mediated by classical reflex arcs that minimise proprioceptive prediction error created by descending proprioceptive predictions. However, this creates a conflict between action and perception; in that, self-generated movements require predictions to override the sensory evidence that one is not actually moving. However, ignoring sensory evidence means that externally generated sensations will not be perceived. Conversely, attending to (proprioceptive and somatosensory) sensations enables the detection of externally generated events but precludes generation of actions. This conflict can be resolved by attenuating the precision of sensory evidence during movement or, equivalently, attending away from the consequences of self-made acts. We propose that this Bayes optimal withdrawal of precise sensory evidence during movement is the cause of psychophysical sensory attenuation. Furthermore, it explains the force-matching illusion and reproduces empirical results almost exactly. Finally, if attenuation is removed, the force-matching illusion disappears and false (delusional) inferences about agency emerge. This is important, given the negative correlation between sensory attenuation and delusional beliefs in normal subjects--and the reduction in the magnitude of the illusion in schizophrenia. Active inference therefore links the neuromodulatory optimisation of precision to sensory attenuation and illusory phenomena during the attribution of agency in normal subjects. It also provides a functional account of deficits in syndromes characterised by false inference and impaired movement--like schizophrenia and Parkinsonism--syndromes that implicate abnormal modulatory neurotransmission. read more read less

Topics:

Illusion (57%)57% related to the paper, Perception (55%)55% related to the paper, Sensory system (52%)52% related to the paper, Inference (50%)50% related to the paper
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351 Citations
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Cognitive Processing format uses SPBASIC citation style.

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Frequently asked questions

1. Can I write Cognitive Processing in LaTeX?

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

2. Do you follow the Cognitive Processing guidelines?

Yes, the template is compliant with the Cognitive Processing 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 Cognitive Processing?

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 Cognitive Processing citation style.

4. Can I use the Cognitive Processing 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 Cognitive Processing.

5. Can I use a manuscript in Cognitive Processing 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 Cognitive Processing that you can download at the end.

6. How long does it usually take you to format my papers in Cognitive Processing?

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

7. Where can I find the template for the Cognitive Processing?

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 Cognitive Processing'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 Cognitive Processing'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. Cognitive Processing an online tool or is there a desktop version?

SciSpace's Cognitive Processing 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 Cognitive Processing?

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 Cognitive Processing?”

11. What is the output that I would get after using Cognitive Processing?

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

12. Is Cognitive Processing'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 Cognitive Processing?

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 Cognitive Processing. 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 Cognitive Processing?

The 5 most common citation types in order of usage for Cognitive Processing 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 Cognitive Processing?

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 Cognitive Processing's guidelines and download the same in Word, PDF and LaTeX formats? Give us a try!.

16. Can I download Cognitive Processing 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 Cognitive Processing Endnote style according to Elsevier guidelines.

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