scholarly journals The Retina: A Window into the Brain

Cells ◽  
2021 ◽  
Vol 10 (12) ◽  
pp. 3269
Author(s):  
Maurice Ptito ◽  
Maxime Bleau ◽  
Joseph Bouskila
Keyword(s):  
Sensory Systems ◽  
The Brain

In the course of evolution, animals have obtained the capacity to perceive and encode their environment via the development of sensory systems such as touch, olfaction, audition, and vision [...]

A Few More Thoughts About Feelings

2014 ◽  
Author(s):  
A. D. (Bud) Craig
Keyword(s):  
Brain Structures ◽  
Sensory Systems ◽  
The Brain

This concluding chapter addresses some of the larger issues relevant to the ideas presented in this book. These issues include the purpose of feelings, the brain structures required in order to experience feelings and which species have them, the kinds of feelings that other species might experience, why feelings seem to propel behavior, and whether Watson—the computer that won the Jeopardy game—might ever experience feelings. The chapter then examines the concept of graded sentience. This concept seems to provide the basis for graded feelings of interoceptive conditions, depending on the level of refinement of the homeostatic motor and sensory systems.

scholarly journals Neuropod Cells: The Emerging Biology of Gut-Brain Sensory Transduction

2020 ◽  
Vol 43 (1) ◽  
pp. 337-353 ◽  
Author(s):  
Melanie Maya Kaelberer ◽  
Laura E. Rupprecht ◽  
Winston W. Liu ◽  
Peter Weng ◽  
Diego V. Bohórquez
Keyword(s):  
Epithelial Cells ◽  
Vagus Nerve ◽  
Nutritional Value ◽  
Sensory Systems ◽  
Enteroendocrine Cells ◽  
Sensory Transduction ◽  
Sensory Signals ◽  
Passive Release ◽  
The Brain

Guided by sight, scent, texture, and taste, animals ingest food. Once ingested, it is up to the gut to make sense of the food's nutritional value. Classic sensory systems rely on neuroepithelial circuits to convert stimuli into signals that guide behavior. However, sensation of the gut milieu was thought to be mediated only by the passive release of hormones until the discovery of synapses in enteroendocrine cells. These are gut sensory epithelial cells, and those that form synapses are referred to as neuropod cells. Neuropod cells provide the foundation for the gut to transduce sensory signals from the intestinal milieu to the brain through fast neurotransmission onto neurons, including those of the vagus nerve. These findings have sparked a new field of exploration in sensory neurobiology—that of gut-brain sensory transduction.

Phantom Limbs

2017 ◽  
Author(s):  
Stephen Gaukroger
Keyword(s):  
Parietal Cortex ◽  
Limbic System ◽  
Brain Activity ◽  
Sensory Systems ◽  
The Body ◽  
Philosophical Problem ◽  
Nerve Endings ◽  
Spinal Chord ◽  
Phantom Limbs ◽  
The Brain

Phantom limbs pose a philosophical problem about the location of pains. The work of Descartes first used them to make a philosophical point about the brain in relation to the body. They have traditionally been thought of as being due to nerve endings on the pathway to the original limb being activated. However, it was subsequently discovered that the phenomenon occurs even when the spinal chord is severed, suggesting that it is rather a question of brain activity, part of a neurosignature through which the brain indicates the body is one’s own. More recent resarch suggests involvement not only of the sensory systems but also the parietal cortex and the limbic system, which is concerned with emotion and motivation.

scholarly journals Conscious and Unconscious Sensory Inflows Allow Effective Control of the Functions of the Human Brain and Heart at the Initial Ageing Stage

2006 ◽  
Vol 9 (2) ◽  
pp. 201-218
Author(s):  
Anatolij T. Bykov ◽  
Tatyana N. Malyarenko ◽  
Yurij E. Malyarenko ◽  
Vladimir P. Terentjev ◽  
Alexandr A. Dyuzhikov
Keyword(s):  
Visual Information ◽  
Heart Rhythm ◽  
Sensory Systems ◽  
Effective Control ◽  
Human Organism ◽  
Vital Functions ◽  
Cardiac Functions ◽  
Sensory Activation ◽  
The Brain ◽  
Systemic Responses

The authors of the present article based their assumption on the concept that the sensory systems are the “windows to the brain” through which various functions of the human organism can be controlled. Comprehension of the fundamental mechanisms of the optimization of the sensory systems, brain, and cardiac functions has increased based on the prolonged sensory flows using conscious and unconscious aromatherapy and multimodal sensory activation. Sensory flow evoked stable systemic responses, including adaptive alteration of psycho-emotional state, attention, memory, sensorimotor reactions, inter-sensory interaction, visual information processing, statokinetic stability, and autonomic heart rhythm control. The efficacy and expediency of the use of sensory flow for non-medicinal correction of vital functions of the human organism at the initial stages of ageing was revealed.

The Thyroid Hormone ReceptorβGene: Structure and Functions in the Brain and Sensory Systems

Thyroid ◽  
2003 ◽  
Vol 13 (11) ◽  
pp. 1057-1068 ◽  
Author(s):  
Iwan Jones ◽  
Maya Srinivas ◽  
Lily Ng ◽  
Douglas Forrest
Keyword(s):  
Thyroid Hormone ◽  
Sensory Systems ◽  
The Brain ◽  
Structure And Functions

scholarly journals Generalized Regressive Motion: a Visual Cue to Collision

2015 ◽  
Author(s):  
Krzysztof Chalupka ◽  
Michael Dickinson ◽  
Pietro Perona
Keyword(s):  
Geometric Analysis ◽  
Sensory Systems ◽  
Fruit Flies ◽  
Agent Based Modeling ◽  
Neural Mechanisms ◽  
Alternative Strategy ◽  
Visual Cue ◽  
Agent Based ◽  
Stationary Obstacles ◽  
The Brain

Brains and sensory systems evolved to guide motion. Central to this task is controlling the approach to stationary obstacles and detecting moving organisms. Looming has been proposed as the main monocular visual cue for detecting the approach of other animals and avoiding collisions with stationary obstacles. Elegant neural mechanisms for looming detection have been found in the brain of insects and vertebrates. However, looming has not been analyzed in the context of collisions between two moving animals. We propose an alternative strategy, Generalized Regressive Motion (GRM), which is consistent with recently observed behavior in fruit flies. Geometric analysis proves that GRM is a reliable cue to collision among conspecifics, whereas agent-based modeling suggests that GRM is a better cue than looming as a means to detect approach, prevent collisions and maintain mobility.

scholarly journals Variance adaptation in navigational decision making

eLife ◽  
2018 ◽  
Vol 7 ◽  
Author(s):  
Ruben Gepner ◽  
Jason Wolk ◽  
Digvijay Shivaji Wadekar ◽  
Sophie Dvali ◽  
Marc Gershow
Keyword(s):  
Sensory Input ◽  
Variance Estimation ◽  
Temporal Dynamics ◽  
Sensory Systems ◽  
Redundant Information ◽  
Environmental Variance ◽  
Mean And Variance ◽  
The Mean ◽  
Light Signals ◽  
The Brain

Sensory systems relay information about the world to the brain, which enacts behaviors through motor outputs. To maximize information transmission, sensory systems discard redundant information through adaptation to the mean and variance of the environment. The behavioral consequences of sensory adaptation to environmental variance have been largely unexplored. Here, we study how larval fruit flies adapt sensory-motor computations underlying navigation to changes in the variance of visual and olfactory inputs. We show that variance adaptation can be characterized by rescaling of the sensory input and that for both visual and olfactory inputs, the temporal dynamics of adaptation are consistent with optimal variance estimation. In multisensory contexts, larvae adapt independently to variance in each sense, and portions of the navigational pathway encoding mixed odor and light signals are also capable of variance adaptation. Our results suggest multiplication as a mechanism for odor-light integration.

scholarly journals Contribution of linear and nonlinear mechanisms to predictive motion estimation

2021 ◽  
Author(s):  
Belle Liu ◽  
Arthur Hong ◽  
Fred Rieke ◽  
Michael B. Manookin
Keyword(s):  
Neural Circuits ◽  
Sensory Systems ◽  
Neural Systems ◽  
Sparse Signal ◽  
Response Suppression ◽  
Delayed Response ◽  
Signal Integration ◽  
Linear And Nonlinear ◽  
Successful Behavior ◽  
The Brain

Successful behavior relies on the ability to use information obtained from past experience to predict what is likely to occur in the future. A salient example of predictive encoding comes from the vertebrate retina, where neural circuits encode information that can be used to estimate the trajectory of a moving object. Predictive computations should be a general property of sensory systems, but the features needed to identify these computations across neural systems are not well understood. Here, we identify several properties of predictive computations in the primate retina that likely generalize across sensory systems. These features include calculating the derivative of incoming signals, sparse signal integration, and delayed response suppression. These findings provide a deeper understanding of how the brain carries out predictive computations and identify features that can be used to recognize these computations throughout the brain.

scholarly journals Sensory system evolution at the origin of craniates

2000 ◽  
Vol 355 (1401) ◽  
pp. 1309-1313 ◽  
Author(s):  
Ann B. Butler
Keyword(s):  
Visual System ◽  
Neural Crest ◽  
Sensory System ◽  
Sensory Systems ◽  
Visual Pathways ◽  
Circumstantial Evidence ◽  
System Evolution ◽  
Multiple Events ◽  
Restricted Distribution ◽  
The Brain

The multiple events at the transition from non–craniate invertebrate ancestors to craniates included the gain and/or elaboration of migratory neural crest and neurogenic placodes. These tissues give rise to the peripherally located, bipolar neurons of all non–visual sensory systems. The brain was also elaborated at or about this same time. Were the peripheral and central events simultaneous or sequential? A serial transformation hypothesis postulates that paired eyes and an enlarged brain evolved before the elaboration of migratory neural crest–placodal sensory systems. Circumstantial evidence for this scenario is derived from the independent occurrence of the combination of large, paired eyes plus a large, elaborated brain in at least three taxa (cephalochordates, arthropods and craniates) and partly from the exclusivity of the diencephalon for visual system–related distal sensory components versus the restricted distribution of migratory neural crest–placodal sensory systems to the remaining parts of the neuraxis. This scenario accounts for the similarity of all central sensory system pathways due to the primary establishment of descending visual pathways via the diencephalon and midbrain tectum to brainstem motor regions and the subsequent exploitation of the same central beachhead by the migratory neural crest–placodal systems as a template for their organization.

scholarly journals Sensorimotor adaptation changes the neural coding of somatosensory stimuli

2013 ◽  
Vol 109 (8) ◽  
pp. 2077-2085 ◽  
Author(s):  
Sazzad M. Nasir ◽  
Mohammad Darainy ◽  
David J. Ostry
Keyword(s):  
Motor Learning ◽  
Somatosensory Evoked Potentials ◽  
Neural Coding ◽  
Functional Organization ◽  
Sensory Systems ◽  
Sensorimotor Adaptation ◽  
Robotic Device ◽  
Somatosensory Stimuli ◽  
The Brain ◽  
Somatosensory Areas

Motor learning is reflected in changes to the brain's functional organization as a result of experience. We show here that these changes are not limited to motor areas of the brain and indeed that motor learning also changes sensory systems. We test for plasticity in sensory systems using somatosensory evoked potentials (SEPs). A robotic device is used to elicit somatosensory inputs by displacing the arm in the direction of applied force during learning. We observe that following learning there are short latency changes to the response in somatosensory areas of the brain that are reliably correlated with the magnitude of motor learning: subjects who learn more show greater changes in SEP magnitude. The effects we observe are tied to motor learning. When the limb is displaced passively, such that subjects experience similar movements but without experiencing learning, no changes in the evoked response are observed. Sensorimotor adaptation thus alters the neural coding of somatosensory stimuli.

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