Context-dependent Coding Research Articles

Context-independent scaling of neural responses to task difficulty in the multiple-demand network.

The multiple-demand (MD) network is sensitive to many aspects of cognitive demand, showing increased activation with more difficult tasks. However, it is currently unknown whether the MD network is modulated by the context in which task difficulty is experienced. Using functional magnetic resonance imaging, we examined MD network responses to low, medium, and high difficulty arithmetic problems within 2 cued contexts, an easy versus a hard set. The results showed that MD activity varied reliably with the absolute difficulty of a problem, independent of the context in which the problem was presented. Similarly, MD activity during task execution was independent of the difficulty of the previous trial. Representational similarity analysis further supported that representational distances in the MD network were consistent with a context-independent code. Finally, we identified several regions outside the MD network that showed context-dependent coding, including the inferior parietal lobule, paracentral lobule, posterior insula, and large areas of the visual cortex. In sum, a cognitive effort is processed by the MD network in a context-independent manner. We suggest that this absolute coding of cognitive demand in the MD network reflects the limited range of task difficulty that can be supported by the cognitive apparatus.

Quantitative model suggests both intrinsic and contextual features contribute to the transcript coding ability determination in cells.

Gene transcription and protein translation are two key steps of the 'central dogma.' It is still a major challenge to quantitatively deconvolute factors contributing to the coding ability of transcripts in mammals. Here, we propose ribosome calculator (RiboCalc) for quantitatively modeling the coding ability of RNAs in human genome. In addition to effectively predicting the experimentally confirmed coding abundance via sequence and transcription features with high accuracy, RiboCalc provides interpretable parameters with biological information. Large-scale analysis further revealed a number of transcripts with a variety of coding ability for distinct types of cells (i.e. context-dependent coding transcripts), suggesting that, contrary to conventional wisdom, a transcript's coding ability should be modeled as a continuous spectrum with a context-dependent nature.

Barking up the right tree: Univariate and multivariate fMRI analyses of homonym comprehension

Homonyms are a critical test case for investigating how the brain resolves ambiguity in language and, more generally, how context influences semantic processing. Previous neuroimaging studies have associated processing of homonyms with greater engagement of regions involved in executive control of semantic processing. However, the precise role of these areas and the involvement of semantic representational regions in homonym comprehension remain elusive. We addressed this by combining univariate and multivariate fMRI analyses of homonym processing. We tested whether multi-voxel activation patterns could discriminate between presentations of the same homonym in different contexts (e.g., bark following tree vs. bark following dog). The ventral anterior temporal lobe, implicated in semantic representation but not previously in homonym comprehension, showed this meaning-specific coding, despite not showing increased mean activation for homonyms. Within inferior frontal gyrus (IFG), a key site for semantic control, there was a dissociation between pars orbitalis, which also showed meaning-specific coding, and pars triangularis, which discriminated more generally between semantically related and unrelated word pairs. IFG effects were goal-dependent, only occurring when the task required semantic decisions, in line with a top-down control function. Finally, posterior middle temporal cortex showed a hybrid pattern of responses, supporting the idea that it acts as an interface between semantic representations and the control system. The study provides new evidence for context-dependent coding in the semantic system and clarifies the role of control regions in processing ambiguity. It also highlights the importance of combining univariate and multivariate neuroimaging data to fully elucidate the role of a brain region in semantic cognition.

Neuromodulation in circuits of aversive emotional learning.

Emotional learning and memory are functionally and dysfunctionally regulated by the neuromodulatory state of the brain. While the role of excitatory and inhibitory neural circuits mediating emotional learning and its control have been the focus of much research, we are only now beginning to understand the more diffuse role of neuromodulation in these processes. Recent experimental studies of the acetylcholine, noradrenaline and dopamine systems in fear learning and extinction of fear responding provide surprising answers to key questions in neuromodulation. One area of research has revealed how modular organization, coupled with context-dependent coding modes, allows for flexible brain-wide or targeted neuromodulation. Other work has shown how these neuromodulators act in downstream targets to enhance signal-to-noise ratios and gain, as well as to bind distributed circuits through neuronal oscillations. These studies elucidate how different neuromodulatory systems regulate aversive emotional processing and reveal fundamental principles of neuromodulatory function.

Context-Dependence and Context-Invariance in the Neural Coding of Intentional Action.

Maintaining intentions over time is fundamental to goal-directed action, and previous research demonstrated that intentions are encoded and maintained in a fronto-parietal network including e.g., the dlPFC and IPS. Yet, intention maintenance is highly challenging in the constantly changing environments we experience every day. While we might have formed an intention under specific conditions, this context can change rapidly and unexpectedly. Some suggested that intentions representations in the fronto-parietal cortex change flexibly when external demands change (context-dependent coding). Others suggested that these representations are encoded in an abstract format that is not affected by changes in external demands (context-invariant coding). Here, I will first outline an analysis approach using multivariate pattern analysis of fMRI data to comprehensively assess the context-dependence / invariance of intention representations in the fronto-parietal cortex. I will then highlight some research following the proposed analysis strategy. Results to date are mixed, showing context-dependence in some, but context-invariance in other cases. In an attempt to synthesize these somewhat divergent results, I will argue that depending on characteristics of the intentions as well as the environment, intentions can either be encoded in a context-dependent or a context-invariant format. This enables us to achieve both stability and flexibility of behavior under constantly changing external demands.

Context-dependent coding and gain control in the auditory system of crickets.

Sensory systems process stimuli that greatly vary in intensity and complexity. To maintain efficient information transmission, neural systems need to adjust their properties to these different sensory contexts, yielding adaptive or stimulus-dependent codes. Here, we demonstrated adaptive spectrotemporal tuning in a small neural network, i.e. the peripheral auditory system of the cricket. We found that tuning of cricket auditory neurons was sharper for complex multi-band than for simple single-band stimuli. Information theoretical considerations revealed that this sharpening improved information transmission by separating the neural representations of individual stimulus components. A network model inspired by the structure of the cricket auditory system suggested two putative mechanisms underlying this adaptive tuning: a saturating peripheral nonlinearity could change the spectral tuning, whereas broad feed-forward inhibition was able to reproduce the observed adaptive sharpening of temporal tuning. Our study revealed a surprisingly dynamic code usually found in more complex nervous systems and suggested that stimulus-dependent codes could be implemented using common neural computations.

Mixing metaphors in the cerebral hemispheres: What happens when careers collide?

Are processes of figurative comparison and figurative categorization different? An experiment combining alternative-sense and matched-sense metaphor priming with a divided visual field assessment technique sought to isolate processes of comparison and categorization in the 2 cerebral hemispheres. For target metaphors presented in the right visual field/left cerebral hemisphere (RVF/LH), only matched-sense primes were facilitative. Literal primes and alternative-sense primes had no effect on comprehension time compared to the unprimed baseline. The effects of matched-sense primes were additive with the rated conventionality of the targets. For target metaphors presented to the left visual field/right cerebral hemisphere (LVF/RH), matched-sense primes were again additively facilitative. However, alternative-sense primes, though facilitative overall, seemed to eliminate the preexisting advantages of conventional target metaphor senses in the LVF/RH in favor of metaphoric senses similar to those of the primes. These findings are consistent with tightly controlled categorical coding in the LH and coarse, flexible, context-dependent coding in the RH.

Context-Dependent DNA Coding With Redundancy and Introns

Deoxyribonucleic acid (DNA) coding methods determine the meaning of a certain character in individual chromosomes by the characters surrounding it. The meaning of each character is context dependent, not position dependent. Although position-dependent coding is most commonly used in genetic algorithms (GAs), a context-dependent coding formation is in fact more closer to the natural DNA chromosome. With the context dependency, the DNA coding methods allow intron parts, redundancy, and variable string length in encoded strings while remaining compatible with the standard genetic operations. This paper tries to explicitly explore the influence of those special features of the DNA coding scheme. Two fundamental DNA coding methods (with and without the use of introns) are constructed and compared with the integer coding method, which lacks the features of interest. The performance of the proposed DNA coding methods is analyzed through the robot soccer role assignment problem. The context-dependent coding exhibits the advantages in handling the negative effect of epistasis. The redundancy and intron parts are helpful in preventing useful schemata from disruption and in increasing the population diversity. The variable length of the individual string enables GAs to evolve both the size and the structure of the fuzzy rule base.

A comparison of context-dependent hippocampal place codes in 1-layer and 2-layer recurrent networks

Recently, it has been suggested that attractor networks may provide a mechanism for context-dependence in hippocampal place codes. We have proposed that context may be coded by “latent attractors” — mutually competitive and internally cooperative cell groups which channel the system's response to afferent stimuli. We have also argued that it is the disynaptically recurrent dentate gyrus–hilus (DGH) system which embodies these latent attractors in the hippocampus. Others have suggested the CA3 network — with its monosynaptic recurrence — is the site. While latent attractors (and, thus, context-dependent coding) can be implemented by a 1-layer or 2-layer recurrent network, we show that a 2-layer recurrent network can implement a sparse context-dependent place-code using latent attractors much more flexibly than a 1-layer network.

New techniques for genetic development of a class of fuzzy controllers

Presents three novel techniques for enhancing the power of a genetic algorithm (GA) used to design fuzzy systems: a new context-dependent coding (CDC) technique, a simple chromosome reordering operator to maximize efficiency, and the coevolution of controller set tests to force competence in all areas of state space. These measures are shown to lead to a considerable improvement over conventional GAs when used to design controllers for a standard problem, such as the cart-pole problem. We use an analysis of GAs by L. Altenberg (1994) to determine a performance measure that demonstrates that our coding scheme and reordering operator improve the ability of the GA to organize itself and evolve chromosomal structures that not only produce high scores, but improve the search efficiency of the genetic operators. We investigate the algorithm in a controller to provide parallel parking maneuvers for mobile robots. It is shown that the controllers developed are robust to the systematic errors that inevitably arise when controllers are transferred from a simulated environment to the real world.

Adaptive pattern classification and universal recoding: II. Feedback, expectation, olfaction, illusions.

Part I of this paper describes a model for the parallel development and adult coding of neural feature detectors. It shows how any set of arbitrary spatial patterns can be recoded, or transformed, into any other spatial patterns (universal recoding), if there are sufficiently many cells in the network's cortex. This code is, however, unstable through time if arbitrarily many patterns can perturb a fixed number of cortical cells. This paper shows how to stabilize the code in the general case using feedback between cellular sites. A biochemically defined critical period is not necessary to stabilize the code, nor is it sufficient to ensure useful coding properties. We ask how short term memory can be reset in response to temporal sequences of spatial patterns. This leads to a context-dependent code in which no feature detector need uniquely characterize an input pattern; yet unique classification by the pattern of activity across feature detectors is possible. This property uses learned expectation mechanisms whereby unexpected patterns are temporarily suppressed and/or activate nonspecific arousal. The simplest case describes reciprocal interactions via trainable synaptic pathways (long term memory traces) between two recurrent on-center off-surround networks undergoing mass action (shunting) interactions. This unit can establish an adaptive resonance, or reverberation, between two regions if their coded patterns match, and can suppress the reverberation if their patterns do not match. This concept yields a model of olfactory coding within the olfactory bulb and prepyriform cortex. The resonance idea also includes the establishment of reverberation between conditioned reinforcers and generators of contingent negative variation if presently avialable sensory cues are compatible with the network's drive requirements at that time; and a search and lock mechanism whereby the disparity between two patterns can be minimized and the minimal disparity images locked into position. Stabilizing the code uses attentional mechanisms, in particular nonspecific arousal as a tuning and search device. We suggest that arousal is gated by a chemical transmitter system--for example, norepinephrine--whose relative states of accumulation at antagonistic pairs of on-cells and off-cells through time can shift the spatial pattern of STM activity across a field of feature detectors. For example, a sudden arousal increment in response to an un-expected pattern can reverse, or rebound, these relative activities, thereby suppressing incorrectly classified populations. The rebound mechanism has formal properties analogous to negative afterimages and spatial frequency adaptation.