Dataset Information

The adaptive trade-off between detection and discrimination in cortical representations and behavior.

ABSTRACT: It has long been posited that detectability of sensory inputs can be sacrificed in favor of improved discriminability and that sensory adaptation may mediate this trade-off. The extent to which this trade-off exists behaviorally and the complete picture of the underlying neural representations that likely subserve the phenomenon remain unclear. In the rodent vibrissa system, an ideal observer analysis of cortical activity measured using voltage-sensitive dye imaging in anesthetized animals was combined with behavioral detection and discrimination tasks, thalamic recordings from awake animals, and computational modeling to show that spatial discrimination performance was improved following adaptation, but at the expense of the ability to detect weak stimuli. Together, these results provide direct behavioral evidence for the trade-off between detectability and discriminability, that this trade-off can be modulated through bottom-up sensory adaptation, and that these effects correspond to important changes in thalamocortical coding properties.

SUBMITTER: Ollerenshaw DR

PROVIDER: S-EPMC4026261 | biostudies-literature | 2014 Mar

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

The adaptive trade-off between detection and discrimination in cortical representations and behavior.

Ollerenshaw Douglas R DR Zheng He J V HJV Millard Daniel C DC Wang Qi Q Stanley Garrett B GB

Neuron 20140301 5

It has long been posited that detectability of sensory inputs can be sacrificed in favor of improved discriminability and that sensory adaptation may mediate this trade-off. The extent to which this trade-off exists behaviorally and the complete picture of the underlying neural representations that likely subserve the phenomenon remain unclear. In the rodent vibrissa system, an ideal observer analysis of cortical activity measured using voltage-sensitive dye imaging in anesthetized animals was c ...[more]

PMID: 24607233

Similar Datasets

Project description:Brain-Computer Interfaces (BCI) aim to bypass the peripheral nervous system to link the brain to external devices via successful modeling of decoding mechanisms. BCI based on electrocorticogram or ECoG represent a viable compromise between clinical practicality, spatial resolution, and signal quality when it comes to extracellular electrical potentials from local neuronal assemblies. Classic analysis of ECoG traces usually falls under the umbrella of Time-Frequency decompositions with adaptations from Fourier analysis and wavelets as its most prominent variants. However, analyzing such high-dimensional, multivariate time series demands for specialized signal processing and neurophysiological principles. We propose a generative model for single-channel ECoGs that is able to fully characterize reoccurring rhythm-specific neuromodulations as weighted activations of prototypical templates over time. The set of timings, weights and indexes comprise a temporal marked point process (TMPP) that accesses a set of bases from vector spaces of different dimensions-a dictionary. The shallow nature of the model admits the equivalence between latent variables and representations. In this way, learning the model parameters is a case of unsupervised representation learning. We exploit principles of Minimum Description Length (MDL) encoding to effectively yield a data-driven framework where prototypical neuromodulations (not restricted to a particular duration) can be estimated alongside the timings and features of the TMPP. We validate the proposed methodology on discrimination of movement-related tasks utilizing 32-electrode grids implanted in the frontal cortex of six epileptic subjects. We show that the learned representations from the high-gamma band (85-145 Hz) are not only interpretable, but also discriminant in a lower dimensional space. The results also underscore the practicality of our algorithm, i.e., 2 main hyperparameters that can be readily set via neurophysiology, and emphasize the need of principled and interpretable representation learning in order to model encoding mechanisms in the brain.

Project description:ObjectivesTo build an item response theory-based computer adaptive test (CAT) for balance from 3 traditional, fixed-form balance measures: Berg Balance Scale (BBS), Performance-Oriented Mobility Assessment (POMA), and dynamic gait index (DGI); and to examine whether the CAT's psychometric performance exceeded that of individual measures.DesignSecondary analysis combining 2 existing datasets.SettingCommunity based.ParticipantsCommunity-dwelling older adults (N=187) who were aged ≥65 years (mean age, 75.2±6.8y, 69% women).InterventionsNot applicable.Main outcome measuresThe BBS, POMA, and DGI items were compiled into an initial 38-item bank. The Rasch partial credit model was used for final item bank calibration. CAT simulations were conducted to identify the ideal CAT. CAT score accuracy, reliability, floor and ceiling effects, and validity were examined. Floor and ceiling effects and validity of the CAT and individual measures were compared.ResultsA 23-item bank met model expectations. A 10-item CAT was selected, showing a very strong association with full item bank scores (r=.97) and good overall reliability (.78). Reliability was better in low- to midbalance ranges as a result of better item targeting to balance ability when compared with the highest balance ranges. No floor effect was noted. The CAT ceiling effect (11.2%) was significantly lower than the POMA (40.1%) and DGI (40.3%) ceiling effects (P<.001 per comparison). The CAT outperformed individual measures, being the only test to discriminate between fallers and nonfallers (P=.007), and being the strongest predictor of self-reported function.ConclusionsThe balance CAT showed excellent accuracy, good overall reliability, and excellent validity compared with individual measures, being the only measure to discriminate between fallers and nonfallers. Prospective examination, particularly in low-functioning older adults and clinical populations with balance deficits, is recommended. Development of an improved CAT based on an expanded item bank containing higher difficulty items is also recommended.

Dataset Information

The adaptive trade-off between detection and discrimination in cortical representations and behavior.

Publications

The adaptive trade-off between detection and discrimination in cortical representations and behavior.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets