Approaches to Predicting Outcomes in Patients with Acute Kidney Injury.

Despite recognition that Acute Kidney Injury (AKI) leads to substantial increases in morbidity, mortality, and length of stay, accurate prognostication of these clinical events remains difficult. It remains unclear which approaches to variable selection and model building are most robust. We used data from a randomized trial of AKI alerting to develop time-updated prognostic models using stepwise regression compared to more advanced variable selection techniques. We randomly split data into training and validation cohorts. Outcomes of interest were death within 7 days, dialysis within 7 days, and length of stay. Data elements eligible for model-building included lab values, medications and dosages, procedures, and demographics. We assessed model discrimination using the area under the receiver operator characteristic curve and r-squared values. 2241 individuals were available for analysis. Both modeling techniques created viable models with very good discrimination ability, with AUCs exceeding 0.85 for dialysis and 0.8 for death prediction. Model performance was similar across model building strategies, though the strategy employing more advanced variable selection was more parsimonious. Very good to excellent prediction of outcome events is feasible in patients with AKI. More advanced techniques may lead to more parsimonious models, which may facilitate adoption in other settings.

Early planning activity in frontal and parietal cortex in a simplified task.

Cortical planning activity has traditionally been probed with visual targets. However, external sensory signals might obscure early correlates of internally generated plans. We devised a nonspatial decision-making task in which the monkey is encouraged to decide randomly whether to reach or saccade in the absence of sensory stimuli. Neurons in frontal and parietal planning areas (in and around the arcuate and intraparietal sulci) showed responses predictive of the monkey's upcoming movement at early stages during the planning process. Neurons predicted the animal's future movements several seconds beforehand, sometimes before the trial even began. These data cast new light on the role of the cerebral cortex in the action planning process, when the animal is free to decide on his own actions in the absence of extraneous sensory cues.

The parietal reach region selectively anti-synchronizes with dorsal premotor cortex during planning.

Recent reports have indicated that oscillations shared across distant cortical regions can enhance their connectivity, but do coherent oscillations ever diminish connectivity? We investigated oscillatory activity in two distinct reach-related regions in the awake behaving monkey (Macaca mulatta): the parietal reach region (PRR) and the dorsal premotor cortex (PMd). PRR and PMd were found to oscillate at similar frequencies (beta, 15-30 Hz) during periods of fixation and movement planning. At first glance, the stronger oscillator of the two, PRR, would seem to drive the weaker, PMd. However, a more fine-grained measure, the partial spike-field coherence, revealed a different relationship. Relative to global beta-band activity in the brain, action potentials in PRR anti-synchronize with PMd oscillations. These data suggest that, rather than driving PMd during planning, PRR neurons fire in such a way that they are less likely to communicate information to PMd.

A neural model for temporal order judgments and their active recalibration: a common mechanism for space and time?

When observers experience a constant delay between their motor actions and sensory feedback, their perception of the temporal order between actions and sensations adapt (Stetson et al., 2006). We present here a novel neural model that can explain temporal order judgments (TOJs) and their recalibration. Our model employs three ubiquitous features of neural systems: (1) information pooling, (2) opponent processing, and (3) synaptic scaling. Specifically, the model proposes that different populations of neurons encode different delays between motor-sensory events, the outputs of these populations feed into rivaling neural populations (encoding "before" and "after"), and the activity difference between these populations determines the perceptual judgment. As a consequence of synaptic scaling of input weights, motor acts which are consistently followed by delayed sensory feedback will cause the network to recalibrate its point of subjective simultaneity. The structure of our model raises the possibility that recalibration of TOJs is a temporal analog to the motion aftereffect (MAE). In other words, identical neural mechanisms may be used to make perceptual determinations about both space and time. Our model captures behavioral recalibration results for different numbers of adapting trials and different adapting delays. In line with predictions of the model, we additionally demonstrate that temporal recalibration can last through time, in analogy to storage of the MAE.

Ready...go: Amplitude of the FMRI signal encodes expectation of cue arrival time.

What happens when the brain awaits a signal of uncertain arrival time, as when a sprinter waits for the starting pistol? And what happens just after the starting pistol fires? Using functional magnetic resonance imaging (fMRI), we have discovered a novel correlate of temporal expectations in several brain regions, most prominently in the supplementary motor area (SMA). Contrary to expectations, we found little fMRI activity during the waiting period; however, a large signal appears after the "go" signal, the amplitude of which reflects learned expectations about the distribution of possible waiting times. Specifically, the amplitude of the fMRI signal appears to encode a cumulative conditional probability, also known as the cumulative hazard function. The fMRI signal loses its dependence on waiting time in a "countdown" condition in which the arrival time of the go cue is known in advance, suggesting that the signal encodes temporal probabilities rather than simply elapsed time. The dependence of the signal on temporal expectation is present in "no-go" conditions, demonstrating that the effect is not a consequence of motor output. Finally, the encoding is not dependent on modality, operating in the same manner with auditory or visual signals. This finding extends our understanding of the relationship between temporal expectancy and measurable neural signals.

Does time really slow down during a frightening event?

Observers commonly report that time seems to have moved in slow motion during a life-threatening event. It is unknown whether this is a function of increased time resolution during the event, or instead an illusion of remembering an emotionally salient event. Using a hand-held device to measure speed of visual perception, participants experienced free fall for 31 m before landing safely in a net. We found no evidence of increased temporal resolution, in apparent conflict with the fact that participants retrospectively estimated their own fall to last 36% longer than others' falls. The duration dilation during a frightening event, and the lack of concomitant increase in temporal resolution, indicate that subjective time is not a single entity that speeds or slows, but instead is composed of separable subcomponents. Our findings suggest that time-slowing is a function of recollection, not perception: a richer encoding of memory may cause a salient event to appear, retrospectively, as though it lasted longer.

Motor-sensory recalibration leads to an illusory reversal of action and sensation.

To judge causality, organisms must determine the temporal order of their actions and sensations. However, this judgment may be confounded by changing delays in sensory pathways, suggesting the need for dynamic temporal recalibration. To test for such a mechanism, we artificially injected a fixed delay between participants' actions (keypresses) and subsequent sensations (flashes). After participants adapted to this delay, flashes at unexpectedly short delays after the keypress were often perceived as occurring before the keypress, demonstrating a recalibration of motor-sensory temporal order judgments. When participants experienced illusory reversals, fMRI BOLD signals increased in anterior cingulate cortex/medial frontal cortex (ACC/MFC), a brain region previously implicated in conflict monitoring. This illusion-specific activation suggests that the brain maintains not only a recalibrated representation of timing, but also a less-plastic representation against which to compare it.