PLDAPS: A Hardware Architecture and Software Toolbox for Neurophysiology Requiring Complex Visual Stimuli and Online Behavioral Control

Neurophysiological studies in awake, behaving primates (both human and non-human) have focused with increasing scrutiny on the temporal relationship between neural signals and behaviors. Consequently, laboratories are often faced with the problem of developing experimental equipment that can support data recording with high temporal precision and also be flexible enough to accommodate a wide variety of experimental paradigms. To this end, we have developed a MATLAB toolbox that integrates several modern pieces of equipment, but still grants experimenters the flexibility of a high-level programming language. Our toolbox takes advantage of three popular and powerful technologies: the Plexon apparatus for neurophysiological recordings (Plexon, Inc., Dallas, TX, USA), a Datapixx peripheral (Vpixx Technologies, Saint-Bruno, QC, Canada) for control of analog, digital, and video input–output signals, and the Psychtoolbox MATLAB toolbox for stimulus generation (Brainard, 1997; Pelli, 1997; Kleiner et al., 2007). The PLDAPS (“Platypus”) system is designed to support the study of the visual systems of awake, behaving primates during multi-electrode neurophysiological recordings, but can be easily applied to other related domains. Despite its wide range of capabilities and support for cutting-edge video displays and neural recording systems, the PLDAPS system is simple enough for someone with basic MATLAB programming skills to design their own experiments

Neural correlates and neural computations in posterior parietal cortex during perceptual decision-making

A recent line of work has found remarkable success in relating perceptual decision-making and the spiking activity in the macaque lateral intraparietal area (LIP). In this review, we focus on questions about the neural computations in LIP that are not answered by demonstrations of neural correlates of psychological processes. We highlight three areas of limitations in our current understanding of the precise neural computations that might underlie neural correlates of decisions: (1) empirical questions not yet answered by existing data; (2) implementation issues related to how neural circuits could actually implement the mechanisms suggested by both extracellular neurophysiology and psychophysics; and (3) ecological constraints related to the use of well-controlled laboratory tasks and whether they provide an accurate window on sensorimotor computation. These issues motivate the adoption of a more general “encoding-decoding framework” that will be fruitful for more detailed contemplation of how neural computations in LIP relate to the formation of perceptual decisions

Neuronal Basis of the Motion Aftereffect Reconsidered

AbstractSeveral fMRI studies have reported MT+ response increases correlated with perception of the motion aftereffect (MAE). However, attention can strongly affect MT+ responses, and subjects may naturally attend more to the MAE than control trials without MAE. We found that requiring subjects to attend to motion on both MAE and control trials produced equal levels of MT+ response, suggesting that attention may have confounded the interpretation of previous experiments; in our data, attention accounts for the entire effect. After eliminating this confound, we observed that direction-selective motion adaptation produced a direction-selective imbalance in MT+ responses (and earlier visual areas), and yielded a corresponding asymmetry in speed discrimination thresholds. These findings provide physiological evidence that population level response imbalances underlie the MAE, and quantify the relative proportions of direction-selective neurons across human visual areas

Neural Circuit Dynamics Underlying Accumulation of Time-Varying Evidence During Perceptual Decision Making

How do neurons in a decision circuit integrate time-varying signals, in favor of or against alternative choice options? To address this question, we used a recurrent neural circuit model to simulate an experiment in which monkeys performed a direction-discrimination task on a visual motion stimulus. In a recent study, it was found that brief pulses of motion perturbed neural activity in the lateral intraparietal area (LIP), and exerted corresponding effects on the monkey's choices and response times. Our model reproduces the behavioral observations and replicates LIP activity which, depending on whether the direction of the pulse is the same or opposite to that of a preferred motion stimulus, increases or decreases persistently over a few hundred milliseconds. Furthermore, our model accounts for the observation that the pulse exerts a weaker influence on LIP neuronal responses when the pulse is late relative to motion stimulus onset. We show that this violation of time-shift invariance (TSI) is consistent with a recurrent circuit mechanism of time integration. We further examine time integration using two consecutive pulses of the same or opposite motion directions. The induced changes in the performance are not additive, and the second of the paired pulses is less effective than its standalone impact, a prediction that is experimentally testable. Taken together, these findings lend further support for an attractor network model of time integration in perceptual decision making

A Model for Transient Oxygen Delivery in Cerebral Cortex

Popular hemodynamic brain imaging methods, such as blood oxygen-level dependent functional magnetic resonance imaging (BOLD fMRI), would benefit from a detailed understanding of the mechanisms by which oxygen is delivered to the cortex in response to brief periods of neural activity. Tissue oxygen responses in visual cortex following brief visual stimulation exhibit rich dynamics, including an early decrease in oxygen concentration, a subsequent large increase in concentration, and substantial late-time oscillations (“ringing”). We introduce a model that explains the full time-course of these observations made by Thompson et al. (2003). The model treats oxygen transport with a set of differential equations that include a combination of flow and diffusion in a three-compartment (intravascular, extravascular, and intracellular) system. Blood flow in this system is modeled using the impulse response of a lumped linear system that includes an inertive element; this provides a simple biophysical mechanism for the ringing. The model system is solved numerically to produce excellent fits to measurements of tissue oxygen. The results give insight into the dynamics of cerebral oxygen transfer, and can serve as the starting point to understand BOLD fMRI measurements

Strong percepts of motion through depth without strong percepts of position in depth

Encoding the motion of objects through three spatial dimensions is a fundamental challenge for the visual system. Two binocular cues could contribute to the perception of motion through depth: changes in horizontal disparity (CD) and interocular velocity differences (IOVD). Although conceptually distinct, both cues are typically present when real objects move. Direct experimental isolation of the putative IOVD cue has remained elusive, and it is therefore unclear to what extent the visual system relies on it. We have found that binocularly anticorrelated stimuli impair position in depth judgments, but motion through depth judgments for the same stimuli are relatively unaffected. This dissociation of direction of motion from position in depth provides strong evidence that percepts of motion through depth are not based exclusively on estimating changes in disparity. Horizontal IOVDs appear to complement the CD cue. Vertical IOVDs fail to yield comparable performance, further implicating a comparison of horizontal interocular velocity and also ruling out explanations of our results based on monocular cues. These results suggest that (1) IOVDs are a robust cue to motion through depth; (2) IOVDs and retinal disparities exhibit similar horizontal/vertical anisotropies, consistent with the geometry of binocular viewing; and (3) binocular anticorrelation provides means to titrate the relative contributions of CD and IOVD cues

A Probabilistic, Distributed, Recursive Mechanism for Decision-making in the Brain

Decision formation recruits many brain regions, but the procedure they jointly execute is unknown. Here we characterize its essential composition, using as a framework a novel recursive Bayesian algorithm that makes decisions based on spike-trains with the statistics of those in sensory cortex (MT). Using it to simulate the random-dot-motion task, we demonstrate it quantitatively replicates the choice behaviour of monkeys, whilst predicting losses of otherwise usable information from MT. Its architecture maps to the recurrent cortico-basal-ganglia-thalamo-cortical loops, whose components are all implicated in decision-making. We show that the dynamics of its mapped computations match those of neural activity in the sensorimotor cortex and striatum during decisions, and forecast those of basal ganglia output and thalamus. This also predicts which aspects of neural dynamics are and are not part of inference. Our single-equation algorithm is probabilistic, distributed, recursive, and parallel. Its success at capturing anatomy, behaviour, and electrophysiology suggests that the mechanism implemented by the brain has these same characteristics

Visual Neuroscience: Retinotopy Meets Percept-otopy?

SummaryIn the mammalian brain, the primary visual cortex forms a systematic spatial map of the visual field. A new study suggests that the representations on this map are affected by visual illusions that alter perceived size. Spatial patterns of activity may thus reflect perceived size

Word, Picture, and Mixed-Condition Reality Decisions and Naming: An Investigation of Concept-Based Category Effects

The effect of category membership on the processing of both words and pictures was investigated,\ud 'vith special regard to the category interference effect discussed in Kroll and Smith (1989).\ud Response latencies for both decision and naming tasks were evaluated using words-only, picturesonly,\ud and mixed words-and-pictures lists. Comparisons were made between a lists of items from\ud the same conceptual category and a list which was non-categorical. Picture decision, word\ud naming, and object naming- the tasks which, theoretically, require access to the conceptual\ud store- all showed faster RTs for categorical lists than non-categorical ones. The results of these\ud unmixed conditions support a model of spreading activation providing a category facilitation effect.\ud However, results from mixed conditions (words-and-pictures-together -naming or -decision) were\ud inconclusive, possibly suggesting a category interference effect