Beyond the Triplet Code: Context Cues Transform Translation

Context-specific adaptation (Shelhamer M, Clendaniel R. Neurosci Lett 332: 200–204, 2002) explains that reflexive responses can be maintained with different “calibrations” for different situations (contexts). Which context cues are crucial and how they combine to evoke context-specific adaptation is not fully understood. Gaze stabilization in birds is a nice model with which to tackle that question. Previous data showed that when pigeons ( Columba livia) were hung in a harness and subjected to a frontal airstream provoking a flying posture (“flying condition”), the working range of the optokinetic head response [optocollic reflex (OCR)] extended toward higher velocities compared with the “resting condition.” The present study was aimed at identifying which context cues are instrumental in recalibrating the OCR. We investigated that question by using vibrating stimuli delivered during the OCR provoked by rotating the visual surroundings at different velocities. The OCR gain increase and the boost of the fast phase velocity observed during the “flying condition” were mimicked by body vibration. On the other hand, the newly emerged relationship between the fast-phase and slow-phase velocities in the “flying condition” was mimicked by head vibration. Spinal cord lesion at the lumbosacral level decreased the effects of body vibration, whereas lesions of the lumbosacral apparatus had no effect. Our data suggest a major role of muscular proprioception in the context-specific adaptation of the stabilizing behavior, while the vestibular system could contribute to the context-specific adaptation of the orienting behavior. Participation of an efferent copy of the motor command driving the flight cannot be excluded.

Download Full-text

Reinstatement of odour context cues veridical memories but not false memories

Memory ◽

10.1080/09658211.2018.1513041 ◽

2018 ◽

Vol 27 (4) ◽

pp. 575-579 ◽

Cited By ~ 1

Author(s):

Jakke Tamminen ◽

Mariam Mebude

Keyword(s):

False Memories ◽

Context Cues

Download Full-text

Triplet Code

Encyclopedia of Genetics, Genomics, Proteomics and Informatics ◽

10.1007/978-1-4020-6754-9_17486 ◽

2008 ◽

pp. 2031-2031

Keyword(s):

Triplet Code

Download Full-text

A Geometric Framework for Understanding Dynamic Information Integration in Context-Dependent Computation

10.1101/2021.02.09.430498 ◽

2021 ◽

Author(s):

Xiaohan Zhang ◽

Shenquan Liu ◽

Zhe Sage Chen

Keyword(s):

Decision Making ◽

Prefrontal Cortex ◽

Information Integration ◽

Principal Component ◽

Population Coding ◽

Geometric Framework ◽

Context Dependent ◽

Activity State ◽

Low Dimensional ◽

Context Cues

AbstractPrefrontal cortex plays a prominent role in performing flexible cognitive functions and working memory, yet the underlying computational principle remains poorly understood. Here we trained a rate-based recurrent neural network (RNN) to explore how the context rules are encoded, maintained across seconds-long mnemonic delay, and subsequently used in a context-dependent decision-making task. The trained networks emerged key experimentally observed features in the prefrontal cortex (PFC) of rodent and monkey experiments, such as mixed-selectivity, sparse representations, neuronal sequential activity and rotation dynamics. To uncover the high-dimensional neural dynamical system, we further proposed a geometric framework to quantify and visualize population coding and sensory integration in a temporally-defined manner. We employed dynamic epoch-wise principal component analysis (PCA) to define multiple task-specific subspaces and task-related axes, and computed the angles between task-related axes and these subspaces. In low-dimensional neural representations, the trained RNN first encoded the context cues in a cue-specific subspace, and then maintained the cue information with a stable low-activity state persisting during the delay epoch, and further formed line attractors for sensor integration through low-dimensional neural trajectories to guide decision making. We demonstrated via intensive computer simulations that the geometric manifolds encoding the context information were robust to varying degrees of weight perturbation in both space and time. Overall, our analysis framework provides clear geometric interpretations and quantification of information coding, maintenance and integration, yielding new insight into the computational mechanisms of context-dependent computation.

Download Full-text

Astronomical Significance of the 137.035 999 Part of the Inverse Fine-Structure Constant

Applied Physics Research ◽

10.5539/apr.v12n2p42 ◽

2020 ◽

Vol 12 (2) ◽

pp. 42

Author(s):

Mels Sluyser

Keyword(s):

Fine Structure ◽

Structure Constant ◽

Space Time ◽

Fine Structure Constant ◽

M Theory ◽

Triplet Code

The inverse fine-structure constant 1/α= 137.035 satisfies 1/α = 112 + 42 + 0.035 = 121 + 16 + 0.035 = 137.035, with 11 being the 11 dimensions of M-theory, 4 the number of dimensions of Einstein’s space-time, and 0.035 the 3.5 percent visible Universe. Cosmological information appears to be encrypted linearly as a triplet code in 1/α.

Download Full-text

Context-Aware User Modeling and Semantic Interoperability in Smart Home Environments

International Journal of Virtual Communities and Social Networking ◽

10.4018/ijvcsn.2015070102 ◽

2015 ◽

Vol 7 (3) ◽

pp. 17-50

Author(s):

Giorgos Siolas ◽

George Caridakis ◽

Phivos Mylonas ◽

Giorgos Stratogiannis ◽

Stefanos Kollias ◽

...

Keyword(s):

Pervasive Computing ◽

Smart Home ◽

User Modeling ◽

Collective Intelligence ◽

Context Modeling ◽

Home Environments ◽

Computing Systems ◽

Knowledge Based ◽

Context Cues ◽

Smart Home Environments

The current paper provides an overview on how user modeling, context awareness and content adaptation in Smart Home environments may be handled formally in order to capture the semantics that emerge from a newly introduced user experience: SandS is in fact a complete ecosystem of users within a social network, creating and exchanging content in the form of so-called recipes and developing a collective intelligence which adapts its operation through appropriate feedback provided by the user. The authors will approach SandS from the user's perspective and illustrate how users and their relationships can be modeled through a number of fuzzy stereotypical profiles. Additionally, context modeling in pervasive computing systems and especially in the Smart Home paradigm will be examined through appropriate representation of context cues in the overall interaction. Finally, the authors will investigate how users and system services although using languages of different semantic expressiveness can inter-operate successfully thanks to appropriate knowledge-based expert mappings.

Download Full-text