The Sensory Ecology of Ant Navigation: From Natural Environments to Neural Mechanisms

Understanding the neural mechanisms for sensing environmental information and controlling behavior in natural environments is a principal aim in neuroscience. One approach towards this goal is rebuilding neural systems by simulation. Despite their relatively simple brains compared with those of mammals, insects are capable of processing various sensory signals and generating adaptive behavior. Nevertheless, our global understanding at network system level is limited by experimental constraints. Simulations are very effective for investigating neural mechanisms when integrating both experimental data and hypotheses. However, it is still very difficult to construct a computational model at the whole brain level owing to the enormous number and complexity of the neurons. We focus on a unique behavior of the silkmoth to investigate neural mechanisms of sensory processing and behavioral control. Standard brains are used to consolidate experimental results and generate new insights through integration. In this study, we constructed a silkmoth standard brain and brain image, in which we registered segmented neuropil regions and neurons. Our original software tools for segmentation of neurons from confocal images, KNEWRiTE, and the registration module for segmented data, NeuroRegister, are shown to be very effective in neuronal registration for computational neuroscience studies.

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The Sensory Ecology of Birds

10.1093/oso/9780199694532.001.0001 ◽

2017 ◽

Cited By ~ 40

Author(s):

Graham R. Martin

Keyword(s):

Cognitive Abilities ◽

Environmental Changes ◽

Partial Information ◽

Sensory System ◽

Sensory Ecology ◽

Natural World ◽

Sensory Systems ◽

Natural Environments ◽

Predator Detection ◽

Trade Offs

The natural world contains a huge amount of constantly changing information. Limitations on, and specializations within, sensory systems mean that each species receives only a small part of that information. In essence, information is filtered by sensory systems. Sensory ecology aims to understand the nature and functions of those filters for each species and sensory system. Fluxes of information, and the perceptual challenges posed by different natural environments, are so large that sensory and behavioural specializations have been inevitable. There have been many trade-offs in the evolution of sensory capacities, and trade-offs and complementarity between different sensory capacities within species. Many behavioural tasks may have influenced the evolution of sensory capacities in birds, but the principal drivers have been associated with just two tasksforaging and predator detection. The key task is the control of the position and timing of the approach of the bill towards a target. Other tasks, such as locomotion and reproduction, are achieved within the requirements of foraging and predator detection. Information thatguides behaviours may often be sparse and partial and key behaviours may only be possible because of cognitive abilities which allow adequate interpretation of partial information. Human modifications of natural environments present perceptual challenges that cannot always be met by the information available to particular birds. Mitigations of the negative effects of human intrusions into natural environments must take account of the sensory ecology of the affected species. Effects of environmental changes cannot be understood sufficiently by viewing them through the filters of human sensory systems.

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Neural integration underlying naturalistic prediction flexibly adapts to varying sensory input rate

Nature Communications ◽

10.1038/s41467-021-22632-z ◽

2021 ◽

Vol 12 (1) ◽

Author(s):

Thomas J. Baumgarten ◽

Brian Maniscalco ◽

Jennifer L. Lee ◽

Matthew W. Flounders ◽

Patrice Abry ◽

...

Keyword(s):

Sensory Input ◽

Sensory Information ◽

Fixed Time ◽

Neural Mechanisms ◽

Natural Environments ◽

Input Rate ◽

Dynamic Stimuli ◽

Neural Integration ◽

Statistical Regularities ◽

Natural Settings

AbstractPrediction of future sensory input based on past sensory information is essential for organisms to effectively adapt their behavior in dynamic environments. Humans successfully predict future stimuli in various natural settings. Yet, it remains elusive how the brain achieves effective prediction despite enormous variations in sensory input rate, which directly affect how fast sensory information can accumulate. We presented participants with acoustic sequences capturing temporal statistical regularities prevalent in nature and investigated neural mechanisms underlying predictive computation using MEG. By parametrically manipulating sequence presentation speed, we tested two hypotheses: neural prediction relies on integrating past sensory information over fixed time periods or fixed amounts of information. We demonstrate that across halved and doubled presentation speeds, predictive information in neural activity stems from integration over fixed amounts of information. Our findings reveal the neural mechanisms enabling humans to robustly predict dynamic stimuli in natural environments despite large sensory input rate variations.

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Effect of Iron Limitation on the Ultrastructure of Agmenellum Quadruplicatum

Proceedings, annual meeting, Electron Microscopy Society of America ◽

10.1017/s0424820100098551 ◽

1981 ◽

Vol 39 ◽

pp. 410-411

Author(s):

L. P. Hardie ◽

D. L. Balkwill ◽

S. E. Stevens

Keyword(s):

Growth Medium ◽

Green Alga ◽

Natural Habitat ◽

Iron Limitation ◽

Natural Environments ◽

Blue Green Alga ◽

Marine Cyanobacterium ◽

Natural Systems ◽

Thin Sectioning ◽

Agmenellum Quadruplicatum

Agmenellum quadruplicatum is a unicellular, non-nitrogen-fixing, marine cyanobacterium (blue-green alga). The ultrastructure of this organism, when grown in the laboratory with all necessary nutrients, has been characterized thoroughly. In contrast, little is known of its ultrastructure in the specific nutrient-limiting conditions typical of its natural habitat. Iron is one of the nutrients likely to limit this organism in such natural environments. It is also of great importance metabolically, being required for both photosynthesis and assimilation of nitrate. The purpose of this study was to assess the effects (if any) of iron limitation on the ultrastructure of A. quadruplicatum. It was part of a broader endeavor to elucidate the ultrastructure of cyanobacteria in natural systemsActively growing cells were placed in a growth medium containing 1% of its usual iron. The cultures were then sampled periodically for 10 days and prepared for thin sectioning TEM to assess the effects of iron limitation.

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John Ludbrook APPS Symposium Neural Mechanisms In The Cardiovascular Responses To Acute Central Hypovolaemia

Clinical and Experimental Pharmacology and Physiology ◽

10.1046/j.1440-1681.2001.3473.x ◽

2001 ◽

Vol 28 (5-6) ◽

pp. 479-487

Author(s):

Roger G Evans ◽

Sabatino Ventura ◽

Roger Al Dampney ◽

John Ludbrook

Keyword(s):

Cardiovascular Responses ◽

Neural Mechanisms ◽

Central Hypovolaemia

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Using Personal Cell Phones for Ecological Momentary Assessment

European Psychologist ◽

10.1027/1016-9040/a000127 ◽

2013 ◽

Vol 18 (1) ◽

pp. 3-11 ◽

Cited By ~ 42

Author(s):

Emmanuel Kuntsche ◽

Florian Labhart

Keyword(s):

Data Collection ◽

Ecological Momentary Assessment ◽

Communication Systems ◽

Cell Phones ◽

Personal Digital Assistants ◽

Natural Environments ◽

Mobility Patterns ◽

Standard Data ◽

Ecological Momentary ◽

Momentary Assessment

Ecological Momentary Assessment (EMA) is a way of collecting data in people’s natural environments in real time and has become very popular in social and health sciences. The emergence of personal digital assistants has led to more complex and sophisticated EMA protocols but has also highlighted some important drawbacks. Modern cell phones combine the functionalities of advanced communication systems with those of a handheld computer and offer various additional features to capture and record sound, pictures, locations, and movements. Moreover, most people own a cell phone, are familiar with the different functions, and always carry it with them. This paper describes ways in which cell phones have been used for data collection purposes in the field of social sciences. This includes automated data capture techniques, for example, geolocation for the study of mobility patterns and the use of external sensors for remote health-monitoring research. The paper also describes cell phones as efficient and user-friendly tools for prompt manual data collection, that is, by asking participants to produce or to provide data. This can either be done by means of dedicated applications or by simply using the web browser. We conclude that cell phones offer a variety of advantages and have a great deal of potential for innovative research designs, suggesting they will be among the standard data collection devices for EMA in the coming years.

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