Is coding a relevant metaphor for building AI?

Brette contends that the neural coding metaphor is an invalid basis for theories of what the brain does. Here, we argue that it is an insufficient guide for building an artificial intelligence that learns to accomplish short- and long-term goals in a complex, changing environment.

Posterior Parietal Cortex Guides Visual Decisions in Rats.

Neurons in putative decision-making structures can reflect both sensory and decision signals, making their causal role in decisions unclear. Here, we tested whether rat posterior parietal cortex (PPC) is causal for processing visual sensory signals or instead for accumulating evidence for decision alternatives. We disrupted PPC activity optogenetically during decision making and compared effects on decisions guided by auditory versus visual evidence. Deficits were largely restricted to visual decisions. To further test for visual dominance in PPC, we evaluated electrophysiological responses after individual sensory events and observed much larger response modulation after visual stimuli than auditory stimuli. Finally, we measured trial-to-trial spike count variability during stimulus presentation and decision formation. Variability decreased sharply, suggesting that the network is stabilized by inputs, unlike what would be expected if sensory signals were locally accumulated. Our findings suggest that PPC plays a causal role in processing visual signals that are accumulated elsewhere.SIGNIFICANCE STATEMENT Defining the neural circuits that support decision making bridges a gap between our understanding of simple sensorimotor reflexes and our understanding of truly complex behavior. However, identifying brain areas that play a causal role in decision making has proved challenging. We tested the causal role of a candidate component of decision circuits, the rat posterior parietal cortex (PPC). Our interpretation of the data benefited from our use of animals trained to make decisions guided by either visual or auditory evidence. Our results suggest that PPC plays a causal role specifically in visual decision making and may support sensory aspects of the decision, such as interpreting the visual signals so that evidence for a decision can be accumulated elsewhere.

A category-free neural population supports evolving demands during decision-making.

The posterior parietal cortex (PPC) receives diverse inputs and is involved in a dizzying array of behaviors. These many behaviors could rely on distinct categories of neurons specialized to represent particular variables or could rely on a single population of PPC neurons that is leveraged in different ways. To distinguish these possibilities, we evaluated rat PPC neurons recorded during multisensory decisions. Newly designed tests revealed that task parameters and temporal response features were distributed randomly across neurons, without evidence of categories. This suggests that PPC neurons constitute a dynamic network that is decoded according to the animal's present needs. To test for an additional signature of a dynamic network, we compared moments when behavioral demands differed: decision and movement. Our new state-space analysis revealed that the network explored different dimensions during decision and movement. These observations suggest that a single network of neurons can support the evolving behavioral demands of decision-making.

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.

Multisensory decision-making in rats and humans.

We report a novel multisensory decision task designed to encourage subjects to combine information across both time and sensory modalities. We presented subjects, humans and rats, with multisensory event streams, consisting of a series of brief auditory and/or visual events. Subjects made judgments about whether the event rate of these streams was high or low. We have three main findings. First, we report that subjects can combine multisensory information over time to improve judgments about whether a fluctuating rate is high or low. Importantly, the improvement we observed was frequently close to, or better than, the statistically optimal prediction. Second, we found that subjects showed a clear multisensory enhancement both when the inputs in each modality were redundant and when they provided independent evidence about the rate. This latter finding suggests a model where event rates are estimated separately for each modality and fused at a later stage. Finally, because a similar multisensory enhancement was observed in both humans and rats, we conclude that the ability to optimally exploit sequentially presented multisensory information is not restricted to a particular species.