Neuroscience research articles are provided.
What is neuroscience? Neuroscience is the scientific study of nervous systems. Neuroscience can involve research from many branches of science including those involving neurology, brain science, neurobiology, psychology, computer science, artificial intelligence, statistics, prosthetics, neuroimaging, engineering, medicine, physics, mathematics, pharmacology, electrophysiology, biology, robotics and technology.
– These articles focus mainly on neurology research. – What is neurology? – Definition of neurology: a science involved in the study of the nervous systems, especially of the diseases and disorders affecting them. – Neurology research can include information involving brain research, neurological disorders, medicine, brain cancer, peripheral nervous systems, central nervous systems, nerve damage, brain tumors, seizures, neurosurgery, electrophysiology, BMI, brain injuries, paralysis and spinal cord treatments.
What is Psychology? Definition of Psychology: Psychology is the study of behavior in an individual, or group. Psychology news articles are listed below.
Artificial Intelligence articles involve programming, neural engineering, artificial neural networks, artificial life, a-life, floyds, boids, emergence, machine learning, neuralbots, neuralrobotics, computational neuroscience and more involving A.I. research.
Robotics articles will cover robotics research press releases. Robotics news from universities, labs, researchers, engineers, students, high schools, conventions, competitions and more are posted and welcome.
Genetics articles related to neuroscience research will be listed here.
Neurotechnology research articles deal with robotics, AI, deep learning, machine learning, Brain Computer Interfaces, neuroprosthetics, neural implants and more. Read the latest neurotech news articles below.
Summary: Study reports the ordered structure of brain areas is not only determined by neural connectivity, but also by the total number of neurons.
Source: Max Planck Institute.
Frankfurt researchers find a simple explanation for the typical patterns of nerve cells inside neural maps
The human brain consists of a highly complex network of approximately 85 billion nerve cells, which continually exchange information with each other. In order for this complex network to function efficiently, it is important that the distances between neurons encoding similar properties remain relatively short. In the human visual system and in that of many mammals, the neurons that respond to objects with similar orientation are indeed located near each other. Interestingly, such an ordered structure cannot be found in rodents. Researchers from the Frankfurt Institute for Advanced Studies, the Max-Planck-Institute for Brain Research and the Ernst-Strüngmann Institute for Neuroscience have studied why such differences between these animal species exist using two different computer models. Unexpectedly, the researchers found that the existence of this ordered structure is not only determined by the connectivity in the circuit, but also by the total number of neurons.
Distinct regions of our brain are responsible for different tasks, such as vision, language, and memory. Within these regions, the nerve cells – or neurons – that respond to similar features are also located near each other, forming so-called neural maps. These neurons are strongly interconnected, which enables them to communicate with each other. If similar cells are in close proximity to each other, the paths connecting them are shorter and our brain works more quickly and efficiently. A prominent example of such neural maps is the arrangement of nerve cells with similar orientation preferences. These nerve cells are located in the brain’s visual cortex, and they recognize the orientation of individual objects in our field of vision (vertical, horizontal, diagonal, etc.). The colored visualization of these orientation preferences results in pinwheel-like patterns on the surface of the brain. Interestingly enough, these “pinwheels” exist in many types of mammals, but not in rodents, which instead possess an unstructured neural map.
Neuroscientists have long speculated whether the rodents’ neural circuitry differs from that of other mammals. The Frankfurt research group, led by Hermann Cuntz, has now demonstrated with two radically different models that the structure of neural maps is determined by the number of nerve cells in addition to the underlying neural connectivity. This result is a simple explanation for the observed differences in the neural maps. Rodents, such as mice or rats have a significantly lower number of neurons due to their body size and their relatively lower density of nerve cells compared to other types of mammals.
More neurons, more structure
Indeed, the models show that with an increasing number of neurons, the neural map transitions from unstructured to structured. In addition to a rapid transition from an unstructured to a structured neural map, there is also a gradual increase in the quality of the structure with an increasing number of neurons. Therefore, ferrets or tree shrews display less structure in the neural map of the visual cortex than closely-related species with more neurons in their visual system. “The apparent difference in the neural map of rodents’ visual systems could be caused by the lower number of nerve cells in the examined species – therefore, there is not necessarily any difference in the underlying neural circuitry,” the lead author Marvin Weigand explains. Therefore, the “pinwheels” could exist in the largest species of rodents, the capybaras native to South America.
In order to reveal the dependence of the neural maps’ structural quality on the interconnectivity – in other words, the number of relevant connections per neuron – the research group adopted two models from different scientific disciplines for its own purposes. The first model was based mainly on multidimensional scaling. In this numerical method, objects are sorted spatially according to their similarity – in this case, the similarity of the circuitry of the nerve cells. The second model was a modification of the so-called XY model. This model, which originally came from statistical physics, was also used by David J. Thouless and J. Michael Kosterlitz for examining topological phases of matter, for which they were awarded last year’s Nobel Prize in Physics. Incidentally, the predictions derived from the models apply to all possible neural maps and could possibly lead to a better understanding of the relationship between the number of neurons and the quantity of encoded attributes in the brain.
[divider]About this neuroscience research article[/divider]
Source: Arjan Vink – Max Planck Institute Image Source: NeuroscienceNews.com image is credited to FIAS/ H. Cuntz. Original Research: Abstract for “Universal transition from unstructured to structured neural maps” by Marvin Weigand, Fabio Sartori, and Hermann Cuntz in PNAS. Published online May 3 2017 doi:10.1073/pnas.1616163114 [divider]Cite This NeuroscienceNews.com Article[/divider]
[cbtabs][cbtab title=”MLA”]Max Planck Institute “Cell Number Determines Structure of Neural Maps: Brain Views Immoral Acts As If They Are Impossible.” NeuroscienceNews. NeuroscienceNews, 13 May 2017. <https://neurosciencenews.com/neural-map-neuron-numbers-6667/>.[/cbtab][cbtab title=”APA”]Max Planck Institute (2017, May 13). Cell Number Determines Structure of Neural Maps: Brain Views Immoral Acts As If They Are Impossible. NeuroscienceNew. Retrieved May 13, 2017 from https://neurosciencenews.com/neural-map-neuron-numbers-6667/[/cbtab][cbtab title=”Chicago”]Max Planck Institute “Cell Number Determines Structure of Neural Maps: Brain Views Immoral Acts As If They Are Impossible.” https://neurosciencenews.com/neural-map-neuron-numbers-6667/ (accessed May 13, 2017).[/cbtab][/cbtabs]
Universal transition from unstructured to structured neural maps
Neurons sharing similar features are often selectively connected with a higher probability and should be located in close vicinity to save wiring. Selective connectivity has, therefore, been proposed to be the cause for spatial organization in cortical maps. Interestingly, orientation preference (OP) maps in the visual cortex are found in carnivores, ungulates, and primates but are not found in rodents, indicating fundamental differences in selective connectivity that seem unexpected for closely related species. Here, we investigate this finding by using multidimensional scaling to predict the locations of neurons based on minimizing wiring costs for any given connectivity. Our model shows a transition from an unstructured salt-and-pepper organization to a pinwheel arrangement when increasing the number of neurons, even without changing the selectivity of the connections. Increasing neuronal numbers also leads to the emergence of layers, retinotopy, or ocular dominance columns for the selective connectivity corresponding to each arrangement. We further show that neuron numbers impact overall interconnectivity as the primary reason for the appearance of neural maps, which we link to a known phase transition in an Ising-like model from statistical mechanics. Finally, we curated biological data from the literature to show that neural maps appear as the number of neurons in visual cortex increases over a wide range of mammalian species. Our results provide a simple explanation for the existence of salt-and-pepper arrangements in rodents and pinwheel arrangements in the visual cortex of primates, carnivores, and ungulates without assuming differences in the general visual cortex architecture and connectivity.
“Universal transition from unstructured to structured neural maps” by Marvin Weigand, Fabio Sartori, and Hermann Cuntz in PNAS. Published online May 3 2017 doi:10.1073/pnas.1616163114
[divider]Feel free to share this Neuroscience News.[/divider]