Modeling neural mechanisms of vertebrate habituation: Locus specificity and pattern discrimination

Wang, DeLiang

doi:10.1007/bf00961877

Cited by 3 publications

(3 citation statements)

References 37 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…These models take an input in the form of one or multiple stimuli repeatedly applied to a system and generate an output in the form of a response function which decays from a high to a stable level with the decrease in novelty of the stimuli. The input is transferred to output response through differential equations [12–15], neural networks [16,17,40], and network circuits [18,19]. For example, a model proposed in Ref.…”

Section: Discussionmentioning

confidence: 99%

See 1 more Smart Citation

Modeling novelty habituation during exploratory activity in Drosophila

Soibam

Shah

Gunaratne

et al. 2013

Behavioural Processes

View full text Add to dashboard Cite

Habituation is a common form of non-associative learning in which the organism gradually decreases its response to repeated stimuli. The decrease in exploratory activity of many animal species during exposure to a novel open field arena is a widely studied habituation paradigm. However, a theoretical framework to quantify how the novelty of the arena is learned during habituation is currently missing. Drosophila melanogaster display a high mean absolute activity and a high probability for directional persistence when first introduced to a novel arena. Both measures decrease during habituation to the arena. Here, we propose a phenomenological model of habituation for Drosophila exploration based on two principles: Drosophila form a spatial representation of the arena edge as a set of connected local patches, and repeated exposure to these patches is essential for the habituation of the novelty. The level of exposure depends on the number of visitations and is quantified by a variable referred to as “coverage.” This model was tested by comparing predictions against the experimentally measured behavior of wild type Drosophila. The novelty habituation of wild type Canton-S depends on coverage and is specifically independent of the arena radius. Our model describes the time dependent locomotor activity, ΔD, of Canton-S using an experimentally established stochastic process Pn(ΔD) which depends on the coverage. The quantitative measures of exploration and habituation were further applied to three mutant genotypes. Consistent with a requirement for vision in novelty habituation, blind no receptor potential A7 mutants display a failure in the decay of probability for directional persistence and mean absolute activity. The rutabaga2080 habituation mutant also shows defects in these measures. The kurtz1 non-visual arrestin mutant demonstrates a rapid decay in these measures, implying reduced motivation. The model and the habituation measures offer a powerful framework for understanding mechanisms associated with open field habituation.

show abstract

Section: Discussionmentioning

confidence: 99%

“…For example, a model proposed in Ref. [40] describes habituation to two stimuli using neural networks representing different physiological layers. This model requires information about the stimuli such as intensity and frequency of the stimuli.…”

Section: Discussionmentioning

confidence: 99%

Modeling novelty habituation during exploratory activity in Drosophila

Soibam

Shah

Gunaratne

et al. 2013

Behavioural Processes

View full text Add to dashboard Cite

show abstract

“…In addition, habituation is also locus specific [6,20] and depends on the stimulus modality, the modality's field width, neuron properties and the complexity of the circuit involved. Habituation can also be obtained from different concomitant input modalities and multiple stimuli [21].…”

Section: Introductionmentioning

confidence: 99%

Habituation: a non-associative learning rule design for spiking neurons and an autonomous mobile robots implementation

Cyr

Boukadoum²

2013

Bioinspir. Biomim.

View full text Add to dashboard Cite

This paper presents a novel bio-inspired habituation function for robots under control by an artificial spiking neural network. This non-associative learning rule is modelled at the synaptic level and validated through robotic behaviours in reaction to different stimuli patterns in a dynamical virtual 3D world. Habituation is minimally represented to show an attenuated response after exposure to and perception of persistent external stimuli. Based on current neurosciences research, the originality of this rule includes modulated response to variable frequencies of the captured stimuli. Filtering out repetitive data from the natural habituation mechanism has been demonstrated to be a key factor in the attention phenomenon, and inserting such a rule operating at multiple temporal dimensions of stimuli increases a robot's adaptive behaviours by ignoring broader contextual irrelevant information.

show abstract