Lineup identification in young and older witnesses: does describing the criminal help or hinder?

The world population is getting older and, as a result, the number of older victims of crime is expected to increase. It is therefore essential to understand how ageing affects eyewitness identification, so procedures can be developed that enable victims of crime of all ages to provide evidence as accurately and reliably as possible. In criminal investigations, witnesses often provide a description of the perpetrator of the crime before later making an identification. While describing the perpetrator prior to making a lineup identification can have a detrimental effect on identification in younger adults, referred to as verbal overshadowing, it is unclear whether older adults are affected in the same way. Our study compared lineup identification of a group of young adults and a group of older adults using the procedure that has consistently revealed verbal overshadowing in young adults. Participants watched a video of a mock crime. Following a 20-min filled delay, they either described the perpetrator or completed a control task. Immediately afterwards, they identified the perpetrator from a lineup, or indicated that the perpetrator was not present, and rated their confidence. We found that describing the perpetrator decreased subsequent correct identification of the perpetrator in both young and older adults. This effect of verbal overshadowing was not explained by a change in discrimination but was consistent with participants adopting a more conservative criterion. Confidence and response time were both found to predict identification accuracy for young and older groups, particularly in the control condition.

Regional anesthesia and the acute pain service: compliance and controversies.

PURPOSE OF REVIEW: The aims of this article are three-fold: first, to describe the necessary elements that result in accurate and compliant billing practice; second, to discuss billing in the context of new blocks and liposomal bupivacaine; and third, to gain a better understanding of compliance law. RECENT FINDINGS: Regional anesthesia techniques provide an appealing alternative to opioid medication for pain management. However, these techniques also increase the cost of care. As new peripheral and fascial plane blocks emerge, proper coding has become more complex. SUMMARY: Familiarity with documentation, billing, and compliance requirements can help maintain proper reimbursement rates, as well as limit potential downstream consequences. Most importantly this can help increase the viability and success of an acute pain service.

Stereoscopic depth adaptation from binocularly correlated versus anti-correlated noise: Test of an efficient coding theory of stereopsis.

Stereoscopic, or "3D" vision in humans is mediated by neurons sensitive to the disparities in the positions of objects in the two eyes' views. A disparity-sensitive neuron is typically characterized by its responses to left- and right-eye monocular signals, SL and SR, respectively. However, it can alternatively be characterized by sensitivity to the sum of the two eyes' inputs, S+ = SL + SR, and the difference, S- = SL - SR. Li and Atick's theory of efficient binocular encoding proposes that the S+ and S- signals can be separately weighted to maximize the efficiency with which binocular information is encoded. This adaptation changes each neuron's sensitivity and preferred binocular disparity, resulting in predicted effects on the perceived stereoscopic depth of objects. To test these predictions, we measured the apparent depth of a random-dot stereogram with an 'in-front' target following adaptation to binocularly correlated or anti-correlated horizontally-oriented grating stimuli, which reduce sensitivity to the S+ and S- signals, respectively, but which contain no conventional stereo-depth signals. The anti-correlated noise adaptation made the target appear relatively closer to the background than the correlated noise adaptation, with differences of up to 60%. We show how this finding can be accommodated by a standard model of binocular disparity processing, modified to incorporate the binocular adaptation suggested by Li and Atick's theory.

Face perception inherits low-level binocular adaptation.

In previous work (May & Zhaoping, 2016; May, Zhaoping, & Hibbard, 2012), we have provided evidence that the visual system efficiently encodes binocular information using separately adaptable binocular summation and differencing channels. In that work, binocular test stimuli delivered different grating patterns to the two binocular channels; selective adaptation of one of the binocular channels made participants more likely to see the other channel's grating pattern. In the current study, we extend this paradigm to face perception. Our test stimuli delivered different face images to the two binocular channels, and we found that selective adaptation of one binocular channel biased the observer to perceive the other channel's face image. We show that the perceived identity, gender, emotional expression, or direction of 3-D rotation of a facial test image can be influenced by pre-exposure to binocular random-noise patterns that contain no meaningful spatial structure. Our results provide compelling evidence that face-processing mechanisms can inherit adaptation from low-level sites. Our adaptation paradigm targets the low-level mechanisms in such a way that any response bias or inadvertent adaptation of high-level mechanisms selective for face categories would reduce, rather than produce, the measured effects of adaptation.

Efficient Coding Theory Predicts a Tilt Aftereffect from Viewing Untilted Patterns.

The brain is bombarded with a continuous stream of sensory information, but biological limitations on the data-transmission rate require this information to be encoded very efficiently [1]. Li and Atick [2] proposed that the two eyes' signals are coded efficiently in the brain using mutually decorrelated binocular summation and differencing channels; when a channel is strongly stimulated by the visual input, such that sensory noise is negligible, the channel should undergo temporary desensitization (known as adaptation). To date, the evidence for this theory has been limited [3, 4], and the binocular differencing channel is missing from many models of binocular integration [5-10]. Li and Atick's theory makes the remarkable prediction that perceived direction of tilt (clockwise or counterclockwise) of a test pattern can be controlled by pre-exposing observers to visual adaptation patterns that are untilted or even have no orientation signal. Here, we confirm this prediction. Each test pattern consisted of different images presented to the two eyes such that the binocular summation and difference signals were tilted in opposite directions, to give ambiguous information about tilt; by selectively desensitizing one or other of the binocular channels using untilted or non-oriented binocular adaptation patterns, we controlled the perceived tilt of the test pattern. Our results provide compelling evidence that the brain contains binocular summation and differencing channels that adapt to the prevailing binocular statistics.

Inefficiency of orientation averaging: Evidence for hybrid serial/parallel temporal integration.

Intuition suggests that increased viewing time should allow for the accumulation of more visual information, but scant support for this idea has been found in studies of voluntary averaging, where observers are asked to make decisions based on perceived average size. In this paper we examine the dynamics of information accrual in an orientation-averaging task. With orientation (unlike intensive dimensions such as size), it is relatively safe to use an item's physical value as an approximation for its average perceived value. We displayed arrays containing eight iso-eccentric Gabor patterns, and asked six trained psychophysical observers to compare their average orientation with that of probe stimuli that were visible before, during, or only after the presentation of the Gabor array. From the relationship between orientation variance and human performance, we obtained estimates of effective set size, i.e., the number of items that an ideal observer would need to assess in order to estimate average orientation as well as our human observers did. We found that display duration had only a modest influence on effective set size. It rose from an average of ∼2 for 0.1-s displays to an average of ∼3 for 3.3-s displays. These results suggest that the visual computation is neither purely serial nor purely parallel. Computations of this nature can be made with a hybrid process that takes a series of subsamples of a few elements at a time.

Connecting psychophysical performance to neuronal response properties I: Discrimination of suprathreshold stimuli.

One of the major goals of sensory neuroscience is to understand how an organism's perceptual abilities relate to the underlying physiology. To this end, we derived equations to estimate the best possible psychophysical discrimination performance, given the properties of the neurons carrying the sensory code.We set up a generic sensory coding model with neurons characterized by their tuning function to the stimulus and the random process that generates spikes. The tuning function was a Gaussian function or a sigmoid (Naka-Rushton) function.Spikes were generated using Poisson spiking processes whose rates were modulated by a multiplicative, gamma-distributed gain signal that was shared between neurons. This doubly stochastic process generates realistic levels of neuronal variability and a realistic correlation structure within the population. Using Fisher information as a close approximation of the model's decoding precision, we derived equations to predict the model's discrimination performance from the neuronal parameters. We then verified the accuracy of our equations using Monte Carlo simulations. Our work has two major benefits. Firstly, we can quickly calculate the performance of physiologically plausible population-coding models by evaluating simple equations, which makes it easy to fit the model to psychophysical data. Secondly, the equations revealed some remarkably straightforward relationships between psychophysical discrimination performance and the parameters of the neuronal population, giving deep insights into the relationships between an organism's perceptual abilities and the properties of the neurons on which those abilities depend.

Connecting psychophysical performance to neuronal response properties II: Contrast decoding and detection.

The purpose of this article is to provide mathematical insights into the results of some Monte Carlo simulations published by Tolhurst and colleagues (Clatworthy, Chirimuuta, Lauritzen, & Tolhurst, 2003; Chirimuuta & Tolhurst, 2005a). In these simulations, the contrast of a visual stimulus was encoded by a model spiking neuron or a set of such neurons. The mean spike count of each neuron was given by a sigmoidal function of contrast, the Naka-Rushton function. The actual number of spikes generated on each trial was determined by a doubly stochastic Poisson process. The spike counts were decoded using a Bayesian decoder to give an estimate of the stimulus contrast. Tolhurst and colleagues used the estimated contrast values to assess the model's performance in a number of ways, and they uncovered several relationships between properties of the neurons and characteristics of performance. Although this work made a substantial contribution to our understanding of the links between physiology and perceptual performance, the Monte Carlo simulations provided little insight into why the obtained patterns of results arose or how general they are. We overcame these problems by deriving equations that predict the model's performance. We derived an approximation of the model's decoding precision using Fisher information. We also analyzed the model's contrast detection performance and discovered a previously unknown theoretical connection between the Naka-Rushton contrast-response function and the Weibull psychometric function. Our equations give many insights into the theoretical relationships between physiology and perceptual performance reported by Tolhurst and colleagues, explaining how they arise and how they generalize across the neuronal parameter space.

One "shape" fits all: the orientation bandwidth of contour integration.

The ability of human participants to integrate fragmented stimulus elements into perceived coherent contours (amidst a field of distracter elements) has been intensively studied across a large number of contour element parameters, ranging from luminance contrast and chromaticity to motion and stereo. The evidence suggests that contour integration performance depends on the low-level Fourier properties of the stimuli. Thus, to understand contour integration, it would be advantageous to understand the properties of the low-level filters that the visual system uses to process contour stimuli. We addressed this issue by examining the role of stimulus element orientation bandwidth in contour integration, a previously unexplored area. We carried out three psychophysical experiments, and then simulated all of the experiments using a recently developed two-stage filter-overlap model whereby the contour grouping occurs by virtue of the overlap between the filter responses to different elements. The first stage of the model responds to the elements, while the second stage integrates the responses along the contour. We found that the first stage had to be fairly broadly tuned for orientation to account for our results. The model showed a very good fit to a large data set with relatively few free parameters, suggesting that this class of model may have an important role to play in helping us to better understand the mechanisms of contour integration.

Contour extracting networks in early extrastriate cortex.

Neurons in the visual cortex process a local region of visual space, but in order to adequately analyze natural images, neurons need to interact. The notion of an ''association field'' proposes that neurons interact to extract extended contours. Here, we identify the site and properties of contour integration mechanisms. We used functional magnetic resonance imaging (fMRI) and population receptive field (pRF) analyses. We devised pRF mapping stimuli consisting of contours. We isolated the contribution of contour integration mechanisms to the pRF by manipulating the contour content. This stimulus manipulation led to systematic changes in pRF size. Whereas a bank of Gabor filters quantitatively explains pRF size changes in V1, only V2/V3 pRF sizes match the predictions of the association field. pRF size changes in later visual field maps, hV4, LO-1, and LO-2 do not follow either prediction and are probably driven by distinct classical receptive field properties or other extraclassical integration mechanisms. These pRF changes do not follow conventional fMRI signal strength measures. Therefore, analyses of pRF changes provide a novel computational neuroimaging approach to investigating neural interactions. We interpreted these results as evidence for neural interactions along cooriented, cocircular receptive fields in the early extrastriate visual cortex (V2/V3), consistent with the notion of a contour association field.

Four theorems on the psychometric function.

In a 2-alternative forced-choice (2AFC) discrimination task, observers choose which of two stimuli has the higher value. The psychometric function for this task gives the probability of a correct response for a given stimulus difference, Δx. This paper proves four theorems about the psychometric function. Assuming the observer applies a transducer and adds noise, Theorem 1 derives a convenient general expression for the psychometric function. Discrimination data are often fitted with a Weibull function. Theorem 2 proves that the Weibull "slope" parameter, ß, can be approximated by ß(Noise) x ß(Transducer), where ß(Noise) is the ß of the Weibull function that fits best to the cumulative noise distribution, and ß(Transducer) depends on the transducer. We derive general expressions for ß(Noise) and ß(Transducer), from which we derive expressions for specific cases. One case that follows naturally from our general analysis is Pelli's finding that, when d' ∝ (Δx)(b), ß ≈ ß(Noise) x b. We also consider two limiting cases. Theorem 3 proves that, as sensitivity improves, 2AFC performance will usually approach that for a linear transducer, whatever the actual transducer; we show that this does not apply at signal levels where the transducer gradient is zero, which explains why it does not apply to contrast detection. Theorem 4 proves that, when the exponent of a power-function transducer approaches zero, 2AFC performance approaches that of a logarithmic transducer. We show that the power-function exponents of 0.4-0.5 fitted to suprathreshold contrast discrimination data are close enough to zero for the fitted psychometric function to be practically indistinguishable from that of a log transducer. Finally, Weibull ß reflects the shape of the noise distribution, and we used our results to assess the recent claim that internal noise has higher kurtosis than a Gaussian. Our analysis of ß for contrast discrimination suggests that, if internal noise is stimulus-independent, it has lower kurtosis than a Gaussian.

Optimal edge filters explain human blur detection.

Edges are important visual features, providing many cues to the three-dimensional structure of the world. One of these cues is edge blur. Sharp edges tend to be caused by object boundaries, while blurred edges indicate shadows, surface curvature, or defocus due to relative depth. Edge blur also drives accommodation and may be implicated in the correct development of the eye's optical power. Here we use classification image techniques to reveal the mechanisms underlying blur detection in human vision. Observers were shown a sharp and a blurred edge in white noise and had to identify the blurred edge. The resultant smoothed classification image derived from these experiments was similar to a derivative of a Gaussian filter. We also fitted a number of edge detection models (MIRAGE, N(1), and N(3)(+)) and the ideal observer to observer responses, but none performed as well as the classification image. However, observer responses were well fitted by a recently developed optimal edge detector model, coupled with a Bayesian prior on the expected blurs in the stimulus. This model outperformed the classification image when performance was measured by the Akaike Information Criterion. This result strongly suggests that humans use optimal edge detection filters to detect edges and encode their blur.

Pattern masking: the importance of remote spatial frequencies and their phase alignment.

To assess the effects of spatial frequency and phase alignment of mask components in pattern masking, target threshold vs. mask contrast (TvC) functions for a sine-wave grating (S) target were measured for five types of mask: a sine-wave grating (S), a square-wave grating (Q), a missing fundamental square-wave grating (M), harmonic complexes consisting of phase-scrambled harmonics of a square wave (Qp), and harmonic complexes consisting of phase-scrambled harmonics of a missing fundamental square wave (Mp). Target and masks had the same fundamental frequency (0.46 cpd) and the target was added in phase with the fundamental frequency component of the mask. Under monocular viewing conditions, the strength of masking depends on phase relationships among mask spatial frequencies far removed from that of the target, at least 3 times the target frequency, only when there are common target and mask spatial frequencies. Under dichoptic viewing conditions, S and Q masks produced similar masking to each other and the phase-scrambled masks (Qp and Mp) produced less masking. The results suggest that pattern masking is spatial frequency broadband in nature and sensitive to the phase alignments of spatial components.

Perceived direction of motion determined by adaptation to static binocular images.

In Li and Atick's [1, 2] theory of efficient stereo coding, the two eyes' signals are transformed into uncorrelated binocular summation and difference signals, and gain control is applied to the summation and differencing channels to optimize their sensitivities. In natural vision, the optimal channel sensitivities vary from moment to moment, depending on the strengths of the summation and difference signals; these channels should therefore be separately adaptable, whereby a channel's sensitivity is reduced following overexposure to adaptation stimuli that selectively stimulate that channel. This predicts a remarkable effect of binocular adaptation on perceived direction of a dichoptic motion stimulus [3]. For this stimulus, the summation and difference signals move in opposite directions, so perceived motion direction (upward or downward) should depend on which of the two binocular channels is most strongly adapted, even if the adaptation stimuli are completely static. We confirmed this prediction: a single static dichoptic adaptation stimulus presented for less than 1 s can control perceived direction of a subsequently presented dichoptic motion stimulus. This is not predicted by any current model of motion perception and suggests that the visual cortex quickly adapts to the prevailing binocular image statistics to maximize information-coding efficiency.