scholarly journals Central neural coding of sky polarization in insects

2011 ◽  
Vol 366 (1565) ◽  
pp. 680-687 ◽  
Author(s):  
Uwe Homberg ◽  
Stanley Heinze ◽  
Keram Pfeiffer ◽  
Michiyo Kinoshita ◽  
Basil el Jundi
Keyword(s):  
Neural Coding ◽  
Compound Eye ◽  
Optic Lobe ◽  
Brain Area ◽  
Central Complex ◽  
Polarization Sensitivity ◽  
Diurnal Changes ◽  
Polarization Pattern ◽  
Chromatic Contrast ◽  
Brain Areas

Many animals rely on a sun compass for spatial orientation and long-range navigation. In addition to the Sun, insects also exploit the polarization pattern and chromatic gradient of the sky for estimating navigational directions. Analysis of polarization–vision pathways in locusts and crickets has shed first light on brain areas involved in sky compass orientation. Detection of sky polarization relies on specialized photoreceptor cells in a small dorsal rim area of the compound eye. Brain areas involved in polarization processing include parts of the lamina, medulla and lobula of the optic lobe and, in the central brain, the anterior optic tubercle, the lateral accessory lobe and the central complex. In the optic lobe, polarization sensitivity and contrast are enhanced through convergence and opponency. In the anterior optic tubercle, polarized-light signals are integrated with information on the chromatic contrast of the sky. Tubercle neurons combine responses to the UV/green contrast and e-vector orientation of the sky and compensate for diurnal changes of the celestial polarization pattern associated with changes in solar elevation. In the central complex, a topographic representation of e-vector tunings underlies the columnar organization and suggests that this brain area serves as an internal compass coding for spatial directions.

scholarly journals Inferring decoding strategies for multiple correlated neural populations

2017 ◽  
Author(s):  
Kaushik J Lakshminarasimhan ◽  
Alexandre Pouget ◽  
Gregory C DeAngelis ◽  
Dora E Angelaki ◽  
Xaq Pitkow
Keyword(s):  
Neural Coding ◽  
Large Scale ◽  
Brain Area ◽  
Mathematical Framework ◽  
Correlated Noise ◽  
Neural Basis ◽  
Brain Areas ◽  
Precise Knowledge ◽  
Behaving Monkeys

AbstractStudies of neuron-behaviour correlation and causal manipulation have long been used separately to understand the neural basis of perception. Yet these approaches sometimes lead to drastically conflicting conclusions about the functional role of brain areas. Theories that focus only on choice-related neuronal activity cannot reconcile those findings without additional experiments involving large-scale recordings to measure interneuronal correlations. By expanding current theories of neural coding and incorporating results from inactivation experiments, we demonstrate here that it is possible to infer decoding weights of different brain areas without precise knowledge of the correlation structure. We apply this technique to neural data collected from two different cortical areas in macaque monkeys trained to perform a heading discrimination task. We identify two opposing decoding schemes, each consistent with data depending on the nature of correlated noise. Our theory makes specific testable predictions to distinguish these scenarios experimentally without requiring measurement of the underlying noise correlations.Author SummaryThe neocortex is structurally organized into distinct brain areas. The role of specific brain areas in sensory perception is typically studied using two kinds of laboratory experiments: those that measure correlations between neural activity and reported percepts, and those that inactivate a brain region and measure the resulting changes in percepts. The two types of experiments have generally been interpreted in isolation, in part because no theory has been able combine their outcomes. Here, we describe a mathematical framework that synthesizes both kinds of results, giving us a new way to assess how different brain areas contribute to perception. When we apply our framework to experiments on behaving monkeys, we discover two models that can explain the perplexing finding that one brain area can predict an animal’s percepts, even though the percepts are not affected when that brain area is inactivated. The two models ascribe dramatically different efficiencies to brain computation. We show that these two models can be distinguished by an experiment that measures correlations while inactivating different brain areas.

scholarly journals Muscular Movements in Man, and their Evolution in the Infant: a Study of Movement in Man, and its Evolution, together with Inferences as to the Properties of Nerve-Centres and their Modes of Action in expressing Thought

1889 ◽  
Vol 35 (149) ◽  
pp. 23-44 ◽  
Author(s):  
Francis Warner
Keyword(s):  
Brain Area ◽  
Muscular Contraction ◽  
The Body ◽  
Brain Areas ◽  
Modes Of Action ◽  
Central Nerve System ◽  
Nerve System ◽  
The Brain ◽  
Compound Series ◽  
Stimulation Of

(1) Movement in mau has long been a subject of profitable study. Visible movement in the body is produced by muscular contraction following upon stimulation of the muscles by efferent currents passing from the central nerve-system. Modern physiological experiments have demonstrated that when a special brain-area discharges nerve-currents, these are followed by certain visible movements or contraction of certain muscles corresponding. So exact are such reactions, as obtained by experiment upon the brain-areas, that movements similar to those produced by experimental excitation of a certain brain-area may be taken as evidence of action in that area, or as commencing in discharge from that area (see Reinforcement of Movements, 35; Compound Series of Movements, 34).

Light guides in the dorsal eye of the male mayfly

1982 ◽  
Vol 216 (1202) ◽  
pp. 25-51 ◽  
Keyword(s):  
Ultraviolet Light ◽  
Compound Eye ◽  
Lucifer Yellow ◽  
Single Units ◽  
Polarization Sensitivity ◽  
Clear Zone ◽  
Tight Coupling ◽  
Acceptance Angle ◽  
Yellow Light ◽  
Light Guides

(i) The dorsal eyes are sensitive to ultraviolet light, which is focused by the corneal lens into crystalline cones in the region where these taper progressively to columns across the clear zone. The action of these columns as light guides can be observed in fixed eyes embedded in polymerized resin. In life the light guide part of the column is surrounded by watery non-cellular haemolymph. (ii) Shadowing the eye surface with a thin wire (three facets wide) while recording from individual receptor units shows that ultraviolet light reaches each receptor by its own facet as in an apposition eye, and not, as in a superposition eye, by a group of many facets. (iii) As shown by the dye Lucifer Yellow injected from a microelectrode, the electrophysiological unit consists of all seven retinula cells in the rhabdom region. Consistent with this tight coupling of retinula cells there is no polarization sensitivity. The peak spectral sensitivity of all single units is at 345-365 nm in the ultraviolet. The acceptance angle is 2.0–2.5°. The sensitivity at the spectral peak to a point source on the optical axis of the unit is poor compared to that in other insects tested with the same equipment. (iv) The acceptance angles (∆ ρ ) in the dorsal eye are at the theoretical minimum for the facet diameter and wavelength from diffraction theory. Ultraviolet vision, therefore, has made possible a reduction in facet size but the interommatidial angle ∆ ϕ is greater than expected from the optimum sampling theory of the diffraction limited compound eye. In fact ∆ ρ ≈ ∆ ϕ ≈ 2°. (v) The dorsal eye is effectively a foveal region with greater sampling density and narrower receptive fields but less overlap of fields than the lateral eye. (vi) The square cones and yellow screening pigment strongly suggest that there is superposition by reflexion of yellow light that spreads between ommatidia across the clear zone. This yellow light might photoreisomerize the visual pigment. Attempts to prove this theory during the recording from single units have so far failed but no better function for the clear zone has been suggested.

scholarly journals Computational Principles of Supervised Learning in the Cerebellum

2018 ◽  
Vol 41 (1) ◽  
pp. 233-253 ◽  
Author(s):  
Jennifer L. Raymond ◽  
Javier F. Medina
Keyword(s):  
Neural Networks ◽  
Artificial Neural Networks ◽  
Supervised Learning ◽  
Brain Area ◽  
Future Research ◽  
Brain Areas ◽  
Adaptive Mechanisms ◽  
Networks Analysis ◽  
Artificial Neural ◽  
Organizational Principles

Supervised learning plays a key role in the operation of many biological and artificial neural networks. Analysis of the computations underlying supervised learning is facilitated by the relatively simple and uniform architecture of the cerebellum, a brain area that supports numerous motor, sensory, and cognitive functions. We highlight recent discoveries indicating that the cerebellum implements supervised learning using the following organizational principles: ( a) extensive preprocessing of input representations (i.e., feature engineering), ( b) massively recurrent circuit architecture, ( c) linear input–output computations, ( d) sophisticated instructive signals that can be regulated and are predictive, ( e) adaptive mechanisms of plasticity with multiple timescales, and ( f) task-specific hardware specializations. The principles emerging from studies of the cerebellum have striking parallels with those in other brain areas and in artificial neural networks, as well as some notable differences, which can inform future research on supervised learning and inspire next-generation machine-based algorithms.

scholarly journals Region-specific brain area reductions and increased cholecystokinin positive neurons in diabetic OLETF rats: implication for anxiety-like behavior

2020 ◽  
Vol 70 (1) ◽  
Author(s):  
Ryosuke Ochi ◽  
Naoto Fujita ◽  
Natsuki Goto ◽  
Son Tien Nguyen ◽  
Duc Trung Le ◽  
...  
Keyword(s):  
Metabolic Disorders ◽  
Basolateral Amygdala ◽  
Open Field Test ◽  
Brain Area ◽  
Brain Areas ◽  
Oletf Rats ◽  
Cornu Ammonis ◽  
Long Evans ◽  
Type 2 Diabetic

Abstract Metabolic disorders can induce psychiatric comorbidities. Both brain and neuronal composition imbalances reportedly induce an anxiety-like phenotype. We hypothesized that alterations of localized brain areas and cholecystokinin (CCK) and parvalbumin (PV) expression could induce anxiety-like behavior in type 2 diabetic Otsuka Long-Evans Tokushima fatty (OLETF) rats. Twenty-week-old OLETF and non-diabetic Long-Evans Tokushima Otsuka (LETO) rats were used. The areas of corticolimbic regions were smaller in OLETF rats. The densities of CCK positive neurons in the lateral and basolateral amygdala, hippocampal cornu ammonis area 2, and prelimbic cortex were higher in OLETF rats. The densities of PV positive neurons were comparable between OLETF and LETO rats. Locomotion in the center zone in the open field test was lower in OLETF rats. These results suggest that imbalances of specific brain region areas and neuronal compositions in emotion-related areas increase the prevalence of anxiety-like behaviors in OLETF rats.

scholarly journals Characterization of a reduced-eye mutant of the grasshopper, Melanoplus sanguinipes

Development ◽  
1984 ◽  
Vol 83 (1) ◽  
pp. 189-211
Author(s):  
D. J. Emery ◽  
K. A. Bell ◽  
W. Chapco ◽  
J. D. Steeves
Keyword(s):  
Compound Eye ◽  
Optic Lobe ◽  
Compound Eyes ◽  
Movement Detector ◽  
Melanoplus Sanguinipes ◽  
Optic Chiasma ◽  
Morphological Alterations ◽  
Tactile Stimuli ◽  
Normal Manner ◽  
Contralateral Movement

A reduced-eye (re) mutant grasshopper of Melanoplus sanguinipes has been characterized by small flat compound eyes lacking facets, no lateral ocelli and only a remnant of the median ocellus. The re grasshoppers walk, jump, fly and feed in a normal manner, but do not respond to visual and auditory stimuli, suggesting they may be blind and deaf. Extracellular recordings from the ventral nerve cord of re mutants verified the lack of neural activity in response to visual and auditory inputs, yet the mutants detected mechanical and tactile stimuli. Electroretinograms implied that a visual deficit may be within the photoreceptors of the compound eye. Histological examination of the compound eyes and ocelli indicated that the cells of the mutant compound eye incompletely differentiate. The optic lamina underlying the retina is missing, as is the outer optic chiasma. The medulla and lobula of the mutant optic lobe are present, however, the neuropil of the medulla lacks the characteristic axonal projection patterns of wild-type grasshoppers. The re grasshopper also lacks all ocellar nerves. Ocellar nerves are normally formed from processes of second order ocellar neurons (SONs), suggesting that if the mutant SONs are present within the protocerebrum, their morphology is drastically altered. Comparison of embryos and juvenile nymphs supports the suggestion that the alterations in the re visual system are the result of abnormal differentiation during development. Even though there is clear evidence of morphological alterations in second and third order optic lobe interneurons, one higher order visual interneuron of the midbrain, the descending contralateral movement detector (DCMD), has the same morphology as the DCMD in a wildtype brain. In this instance, the complete deprivation of the primary sensory input does not appear to alter cellular development.

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