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

Encoding of continuous perceptual choices in human early visual cortex

Introduction

Research on the neural mechanisms of perceptual decision-making has typically focused on simple categorical choices, say between two alternative motion directions. Studies on such discrete alternatives have often suggested that choices are encoded either in a motor-based or in an abstract, categorical format in regions beyond sensory cortex.

Methods

In this study, we used motion stimuli that could vary anywhere between 0° and 360° to assess how the brain encodes choices for features that span the full sensory continuum. We employed a combination of neuroimaging and encoding models based on Gaussian process regression to assess how either stimuli or choices were encoded in brain responses.

Results

We found that single-voxel tuning patterns could be used to reconstruct the trial-by-trial physical direction of motion as well as the participants' continuous choices. Importantly, these continuous choice signals were primarily observed in early visual areas. The tuning properties in this region generalized between choice encoding and stimulus encoding, even for reports that reflected pure guessing.

Discussion

We found only little information related to the decision outcome in regions beyond visual cortex, such as parietal cortex, possibly because our task did not involve differential motor preparation. This could suggest that decisions for continuous stimuli take can place already in sensory brain regions, potentially using similar mechanisms to the sensory recruitment in visual working memory.

Transient neuronal suppression for exploitation of new sensory evidence

In noisy but stationary environments, decisions should be based on the temporal integration of sequentially sampled evidence. This strategy has been supported by many behavioral studies and is qualitatively consistent with neural activity in multiple brain areas. By contrast, decision-making in the face of non-stationary sensory evidence remains poorly understood. Here, we trained monkeys to identify and respond via saccade to the dominant color of a dynamically refreshed bicolor patch that becomes informative after a variable delay. Animals’ behavioral responses were briefly suppressed after evidence changes, and many neurons in the frontal eye field displayed a corresponding dip in activity at this time, similar to that frequently observed after stimulus onset but sensitive to stimulus strength. Generalized drift-diffusion models revealed consistency of behavior and neural activity with brief suppression of motor output, but not with pausing or resetting of evidence accumulation. These results suggest that momentary arrest of motor preparation is important for dynamic perceptual decision making.

While evidence is constantly changing during real-world decisions, little is known about how the brain deals with such changes. Here, the authors show that the brain strategically suppresses motor output via the frontal eye fields in response to stimulus changes.

Neuroanatomical substrates accounting for the effect of present hedonistic time perspective on risk preference: the mediating role of right posterior parietal cortex

The preference for taking risk troubles people across multiple domains including health, economics, and social well-being. Prior research has demonstrated that risk preference can be influenced by time perspective (TP). However, little is known about the neural substrates underlying the effect of TP on risk preference. Here, we used a voxel-based morphometry (VBM) method across two samples to address this question. In Sample 1, the behavioral results showed a positive correlation between present hedonistic TP (PHTP) and gambling rate (the index of risk preference), indicating the higher PHTP, the greater the preference for risk. Subsequently, the whole-brain VBM results found that gambling rate was negatively correlated with the gray matter (GM) volume of a cluster in the right posterior parietal cortex (rPPC). The PHTP score was also negatively related to the GM volume of another cluster in the rPPC. We then examined an overlapping region in the rPPC using a conjunction analysis method. The GM volume of this overlapping brain region was related to both PHTP score and gambling rate. Finally, the mediation analysis found that the GM volume of overlapping region in rPPC played a role in explaining the effect of PHTP on risk preference. This result was also reproduced and validated in another independent sample. Taken together, our findings manifest that the structural variation of rPPC can account for the influence that PHTP has upon the risk preference.

Mechanisms of competitive selection: A canonical neural circuit framework

Competitive selection, the transformation of multiple competing sensory inputs and internal states into a unitary choice, is a fundamental component of animal behavior. Selection behaviors have been studied under several intersecting umbrellas including decision-making, action selection, perceptual categorization, and attentional selection. Neural correlates of these behaviors and computational models have been investigated extensively. However, specific, identifiable neural circuit mechanisms underlying the implementation of selection remain elusive. Here, we employ a first principles approach to map competitive selection explicitly onto neural circuit elements. We decompose selection into six computational primitives, identify demands that their execution places on neural circuit design, and propose a canonical neural circuit framework. The resulting framework has several links to neural literature, indicating its biological feasibility, and has several common elements with prominent computational models, suggesting its generality. We propose that this framework can help catalyze experimental discovery of the neural circuit underpinnings of competitive selection.

Difference in Cortical Modulation of Walking between Persons with Multiple Sclerosis and Healthy Controls: An EEG pilot study

The overall goal of this study is to investigate the role of parietal cortex in the control of walking in persons with Multiple Sclerosis (pwMS). We examined within-brain connectivity and cortico-muscular connectivity as pwMS and healthy control (HC) participants walked on an instrumented treadmill. Cortical activity was collected using EEG, muscle activity was collected using wireless EMG modules, and gait data were obtained by using the instrumented treadmill. Results show significant activation of sensorimotor and posterior parietal cortex during walking in both groups. Connectivity between parietal (posterior cingulate cortex PCC) and premotor regions (pars opercularis), and between PCC and contralateral muscles were higher in the healthy control group. Higher connectivity correlated with higher walking speed.

Directional Limits on Motion Transparency Assessed Through Colour-Motion Binding

Motion-defined transparency is the perception of two or more distinct moving surfaces at the same retinal location. We explored the limits of motion transparency using superimposed surfaces of randomly positioned dots defined by differences in motion direction and colour. In one experiment, dots were red or green and we varied the proportion of dots of a single colour that moved in a single direction ('colour-motion coherence') and measured the threshold direction difference for discriminating between two directions. When colour-motion coherences were high (e.g., 90% of red dots moving in one direction), a smaller direction difference was required to correctly bind colour with direction than at low coherences. In another experiment, we varied the direction difference between the surfaces and measured the threshold colour-motion coherence required to discriminate between them. Generally, colour-motion coherence thresholds decreased with increasing direction differences, stabilising at direction differences around 45°. Different stimulus durations were compared, and thresholds were higher at the shortest (150 ms) compared with the longest (1,000 ms) duration. These results highlight different yet interrelated aspects of the task and the fundamental limits of the mechanisms involved: the resolution of narrowly separated directions in motion processing and the local sampling of dot colours from each surface.

Power Spectral Density Analysis of Electrocorticogram Recordings during Cerebral Hypothermia in Neonatal Seizures

BACKGROUND

Neonatal seizures (NS) are the most common form of neurological dysfunction observed in newborns.

PURPOSE

The purpose of this study in newborn piglets was to determine the effect of cerebral hypothermia (CH) on neural activity during pharmacologically induced NS. We hypothesized that the neuroprotective effects of CH would preserve higher frequencies observed in electrocorticogram (ECoG) recordings.

METHODS

Power spectral density was employed to determine the levels of brain activity in ECoGs to quantitatively assess the power of each frequency observed in neurological brain states of delta, theta, alpha, and beta-gamma frequencies.

RESULT

The most significant reduction of power occurs in the lower frequency band of delta-theta-alpha of CH cohorts, while t score probabilities imply that high-frequency brain activity in the beta-gamma range is preserved in the CH population.

CONCLUSION

While the overall power density decreases over time in both groups, the decrease is to a lesser degree in the CH population.

Neurofunctional correlates of ethical, food-related decision-making

For consumers today, the perceived ethicality of a food’s production method can be as important a purchasing consideration as its price. Still, few studies have examined how, neurofunctionally, consumers are making ethical, food-related decisions. We examined how consumers’ ethical concern about a food’s production method may relate to how, neurofunctionally, they make decisions whether to purchase that food. Forty-six participants completed a measure of the extent to which they took ethical concern into consideration when making food-related decisions. They then underwent a series of functional magnetic resonance imaging (fMRI) scans while performing a food-related decision-making (FRDM) task. During this task, they made 56 decisions whether to purchase a food based on either its price (i.e., high or low, the “price condition”) or production method (i.e., with or without the use of cages, the “production method condition”), but not both. For 23 randomly selected participants, we performed an exploratory, whole-brain correlation between ethical concern and differential neurofunctional activity in the price and production method conditions. Ethical concern correlated negatively and significantly with differential neurofunctional activity in the left dorsolateral prefrontal cortex (dlPFC). For the remaining 23 participants, we performed a confirmatory, region-of-interest (ROI) correlation between the same variables, using an 8-mm3 volume situated in the left dlPFC. Again, the variables correlated negatively and significantly. This suggests, when making ethical, food-related decisions, the more consumers take ethical concern into consideration, the less they may rely on neurofunctional activity in the left dlPFC, possibly because making these decisions is more routine for them, and therefore a more perfunctory process requiring fewer cognitive resources.

Encoding and decoding in parietal cortex during sensorimotor decision-making

The lateral intraparietal area (LIP) of macaques has been asserted to play a fundamental role in sensorimotor decision-making. Here we dissect the neural code in LIP at the level of individual trial spike trains using a statistical approach based on generalized linear models. We show that LIP responses reflect a combination of temporally-overlapping task and decision-related signals. Our model accounts for the detailed statistics of LIP spike trains, and accurately predicts spike trains from task events on single trials. Moreover, we derive an optimal decoder for heterogeneous, multiplexed LIP responses that could be implemented in biologically plausible circuits. In contrast to interpretations of LIP as providing an instantaneous code for decision variables, we show that optimal decoding requires integrating LIP spikes over two timescales. These analyses provide a detailed understanding of the neural code in LIP, and a framework for studying the coding of multiplexed signals in higher brain areas.

What are the neural origins of choice variability?

Two recent studies examine neural activity predictive of upcoming choices during value-guided choice. Their results may be cast in light of a competitive winner-take-all decision network. This viewpoint places certain decision variables not as features of the environment to be encoded, but as emergent properties of network activity.

Context-dependent computation by recurrent dynamics in prefrontal cortex

Prefrontal cortex is thought to have a fundamental role in flexible, context-dependent behaviour, but the exact nature of the computations underlying this role remains largely unknown. In particular, individual prefrontal neurons often generate remarkably complex responses that defy deep understanding of their contribution to behaviour. Here we study prefrontal cortex activity in macaque monkeys trained to flexibly select and integrate noisy sensory inputs towards a choice. We find that the observed complexity and functional roles of single neurons are readily understood in the framework of a dynamical process unfolding at the level of the population. The population dynamics can be reproduced by a trained recurrent neural network, which suggests a previously unknown mechanism for selection and integration of task-relevant inputs. This mechanism indicates that selection and integration are two aspects of a single dynamical process unfolding within the same prefrontal circuits, and potentially provides a novel, general framework for understanding context-dependent computations.

Dynamic weighting of multisensory stimuli shapes decision-making in rats and humans

Stimuli that animals encounter in the natural world are frequently time-varying and activate multiple sensory systems together. Such stimuli pose a major challenge for the brain: Successful multisensory integration requires subjects to estimate the reliability of each modality and use these estimates to weight each signal appropriately. Here, we examined whether humans and rats can estimate the reliability of time-varying multisensory stimuli when stimulus reliability changes unpredictably from trial to trial. Using an existing multisensory decision task that features time-varying audiovisual stimuli, we independently manipulated the signal-to-noise ratios of each modality and measured subjects' decisions on single- and multi-sensory trials. We report three main findings: (a) Sensory reliability influences how subjects weight multisensory evidence even for time-varying, stochastic stimuli. (b) The ability to exploit sensory reliability extends beyond human and nonhuman primates: Rodents and humans both weight incoming sensory information in a reliability-dependent manner. (c) Regardless of sensory reliability, most subjects are disinclined to make "snap judgments" and instead base decisions on evidence presented over the majority of the trial duration. Rare departures from this trend highlight the importance of using time-varying stimuli that permit this analysis. Taken together, these results suggest that the brain's ability to use stimulus reliability to guide decision-making likely relies on computations that are conserved across species and operate over a wide range of stimulus conditions.