What Can Sensory Substitution Tell Us about the Organization of the Brain?

Author(s):  
Sarah Hillenbrand ◽  
Dina Raveh ◽  
Amir Amedi

We discuss how sensory substitution devices (SSDs) can be used to study the organization of the brain. To do so we look at the use of SSDs in the blind and how SSDs can be used to identify sensory-dependent and sensory-independent brain function. Cross-modal interactions may represent new patterns of connectivity or the unmasking of pre-existing associations. We show how the blind brain can be a window into cross-modal plasticity and can dissociate intrinsic and experience-dependent brain functions. We argue that the brain is a sensory-independent task machine and explain the implications for the rehabilitation of blind people.

2015 ◽  
Vol 370 (1668) ◽  
pp. 20140172 ◽  
Author(s):  
Marcus E. Raichle

Traditionally studies of brain function have focused on task-evoked responses. By their very nature such experiments tacitly encourage a reflexive view of brain function. While such an approach has been remarkably productive at all levels of neuroscience, it ignores the alternative possibility that brain functions are mainly intrinsic and ongoing, involving information processing for interpreting, responding to and predicting environmental demands. I suggest that the latter view best captures the essence of brain function, a position that accords well with the allocation of the brain's energy resources, its limited access to sensory information and a dynamic, intrinsic functional organization. The nature of this intrinsic activity, which exhibits a surprising level of organization with dimensions of both space and time, is revealed in the ongoing activity of the brain and its metabolism. As we look to the future, understanding the nature of this intrinsic activity will require integrating knowledge from cognitive and systems neuroscience with cellular and molecular neuroscience where ion channels, receptors, components of signal transduction and metabolic pathways are all in a constant state of flux. The reward for doing so will be a much better understanding of human behaviour in health and disease.


2020 ◽  
Author(s):  
Sreejan Kumar ◽  
Cameron T. Ellis ◽  
Thomas O’Connell ◽  
Marvin M Chun ◽  
Nicholas B. Turk-Browne

AbstractThe extent to which brain functions are localized or distributed is a foundational question in neuroscience. In the human brain, common fMRI methods such as cluster correction, atlas parcellation, and anatomical searchlight are biased by design toward finding localized representations. Here we introduce the functional searchlight approach as an alternative to anatomical searchlight analysis, the most commonly used exploratory multivariate fMRI technique. Functional searchlight removes any anatomical bias by grouping voxels based only on functional similarity and ignoring anatomical proximity. We report evidence that visual and auditory features from deep neural networks and semantic features from a natural language processing model are more widely distributed across the brain than previously acknowledged. This approach provides a new way to evaluate and constrain computational models with brain activity and pushes our understanding of human brain function further along the spectrum from strict modularity toward distributed representation.


EMJ Neurology ◽  
2020 ◽  
pp. 68-79
Author(s):  
Varruchi Sharma ◽  
Atul Sankhyan ◽  
Anshika Varshney ◽  
Renuka Choudhary ◽  
Anil K. Sharma

It has been suggested that an intricate communication link exists between the gut microbiota and the brain and its ability to modulate behaviour of an individual governing homeostasis. Metabolic activity of the microbiota is considered to be relatively constant in healthy individuals, despite differences in the composition of microbiota. The metabolites produced by gut microbiota and their homeostatic balance is often perturbed as a result of neurological complications. Therefore, it is of paramount importance to explore the link between gut microbiota and brain function and behaviour through neural, endocrine, and immune pathways. This current review focusses on the impact of altered gut microbiota on brain functions and how microbiome modulation by use of probiotics, prebiotics, and synbiotics might prove beneficial in the prevention and/or treatment of neurological disorders. It is important to carefully understand the complex mechanisms underlying the gut–brain axis so as to use the gut microbiota as a therapeutic intervention strategy for neurological disorders.


e-Neuroforum ◽  
2015 ◽  
Vol 21 (3) ◽  
Author(s):  
Daniela C. Dieterich ◽  
Moritz J. Rossner

AbstractNeuronal as well as glial cells contribute to higher order brain functions. Many observations show that neurons and glial cells are not only physically highly intermingled but are physiologically tightly connected and mutually depend at various levels on each other. Moreover, macroglia classes like astrocytes, NG2 cells and oligodendrocytes are not at all homogenous cell populations but do possess a markedly heterogeneity in various aspects similar to neurons. The diversity of differences in morphology, functionality and, cellular activity has been acknowledged recently and will be integrated into a concept of brain function that pictures a neural rather than a puristical neuronal world. With the recent progress in “omic” technologies, an unbiased and exploratory approach toward an enhanced understanding of glial heterogeneity has become possible. Here, we provide an overview on current technical transcriptomic and proteomic approaches used to dissect glial heterogeneity of the brain.


2016 ◽  
Vol 12 (3) ◽  
Author(s):  
Piotr Prokopowicz ◽  
Dariusz Mikołajewski

AbstractResearch on the computational models of the brain constitutes an important part of the current challenges within computational neuroscience. The current results are not satisfying. Despite the continuous efforts of scientists and clinicians, it is hard to fully explain all the mechanisms of a brain function. Computational models of the brain based on fuzzy logic, including ordered fuzzy numbers, may constitute another breakthrough in the aforementioned area, offering a completing position to the current state of the art. The aim of this paper is to assess the extent to which possible opportunities concerning computational brain models based on fuzzy logic techniques may be exploited both in the area of theoretical and experimental computational neuroscience and in clinical applications, including our own concept. The proposed approach can open a family of novel methods for a more effective and (neuro)biologically reliable brain simulation based on fuzzy logic techniques useful in both basic sciences and applied sciences.


2018 ◽  
Vol 38 (6) ◽  
pp. 935-949 ◽  
Author(s):  
Christine Marie ◽  
Martin Pedard ◽  
Aurore Quirié ◽  
Anne Tessier ◽  
Philippe Garnier ◽  
...  

Low cerebral levels of brain-derived neurotrophic factor (BDNF), which plays a critical role in many brain functions, have been implicated in neurodegenerative, neurological and psychiatric diseases. Thus, increasing BDNF levels in the brain is considered an attractive possibility for the prevention/treatment of various brain diseases. To date, BDNF-based therapies have largely focused on neurons. However, given the cross-talk between endothelial cells and neurons and recent evidence that BDNF expressed by the cerebral endothelium largely accounts for BDNF levels present in the brain, it is likely that BDNF-based therapies would be most effective if they also targeted the cerebral endothelium. In this review, we summarize the available knowledge about the biology and actions of BDNF derived from endothelial cells of the cerebral microvasculature and we emphasize the remaining gaps and shortcomings.


2021 ◽  
Author(s):  
Bernard Marius 't Hart ◽  
Titipat Achakulvisut ◽  
Gunnar Blohm ◽  
Konrad Kording ◽  
Megan A. K. Peters ◽  
...  

Neuromatch Academy (https://neuromatch.io/academy) was designed as an online summer school to cover the basics of computational neuroscience in three weeks. The materials cover dominant and emerging computational neuroscience tools, how they complement one another, and specifically focus on how they can help us to better understand how the brain functions. An original component of the materials is its focus on modeling choices, i.e. how do we choose the right approach, how do we build models, and how can we evaluate models to determine if they provide real (meaningful) insight. This meta-modeling component of the instructional materials asks what questions can be answered by different techniques, and how to apply them meaningfully to get insight about brain function.


Author(s):  
Eyitayo Adeyemi Oyindamola ◽  
Maxwell Kwadwo Agyemang ◽  
Joseph Owusu-Sarfo ◽  
Oduro Kofi Yeboah ◽  
Newman Osafo

Microglia are important in the regulation of the inflammatory response in regulating the release of proinflammatory mediators in the brain. Through their phagocytic actions, microglia are significant in the CNS when it comes to the body's response to physiological insults by promoting repair of impaired brain function. They do so by engulfing and degrading microbes as well as brain-derived debris and proteins such as myelin and axonal fragments, amyloid-beta, and apoptotic cells. This mitophagic activity of microglia is of importance in neurodegeneration. In most neurodegenerative disorders, mitophagy is impaired with resultant accumulation of dysfunctional mitochondria as well as processes such as lysosomal fusion and autophagosomes. In Parkinson's and Alzheimer's for example, impaired mitophagy accounts for the build-up of α-synuclein and amyloid respectively in affected individuals. The chapter discusses extensively the link between microglia mitophagy and neurodegeration and how dysfunctional mitophagy increases the likelihood of their occurrence.


Author(s):  
Seyed Amir Hossein Batouli

Memory is probably one of the most complex cognitive functions of the human, and in many years, thousands of studies have helped us to better recognize this brain function. One of the reference textbooks in neuroscience, which has also elaborated on the memory function, is written by Prof. Kandel and his colleagues. In this book, I encountered a number of ambiguities when it was explaining the memory system. Here, I am sharing those points, either to find an answer for them, or to let them be a suggestion for our future works. Prof. Kandel has spent most of his meritorious lifetime on studying the memory system; however, the brain is extremely complex, and as a result, we still have many years to comprehensively understand the neural mechanisms of brain functions.


2018 ◽  
Vol 2018 ◽  
pp. 1-8 ◽  
Author(s):  
Jisu Elsa Jacob ◽  
Ajith Cherian ◽  
K. Gopakumar ◽  
Thomas Iype ◽  
Doris George Yohannan ◽  
...  

Chaotic analysis is a relatively novel area in the study of physiological signals. Chaotic features of electroencephalogram have been analyzed in various disease states like epilepsy, Alzheimer’s disease, sleep disorders, and depression. All these diseases have primary involvement of the brain. Our study examines the chaotic parameters in metabolic encephalopathy, where the brain functions are involved secondary to a metabolic disturbance. Our analysis clearly showed significant lower values for chaotic parameters, correlation dimension, and largest Lyapunov exponent for EEG in patients with metabolic encephalopathy compared to normal EEG. The chaotic features of EEG have been shown in previous studies to be an indicator of the complexity of brain dynamics. The smaller values of chaotic features for encephalopathy suggest that normal complexity of brain function is reduced in encephalopathy. To the best knowledge of the authors, no similar work has been reported on metabolic encephalopathy. This finding may be useful to understand the neurobiological phenomena in encephalopathy. These chaotic features are then utilized as feature sets for Support Vector Machine classifier to identify cases of encephalopathy from normal healthy subjects yielding high values of accuracy. Thus, we infer that chaotic measures are EEG parameters sensitive to functional alterations of the brain, caused by encephalopathy.


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