A rise-to-threshold process for a relative-value decision.

Whereas progress has been made in the identification of neural signals related to rapid, cued decisions1-3, less is known about how brains guide and terminate more ethologically relevant decisions in which an animal's own behaviour governs the options experienced over minutes4-6. Drosophila search for many seconds to minutes for egg-laying sites with high relative value7,8 and have neurons, called oviDNs, whose activity fulfills necessity and sufficiency criteria for initiating the egg-deposition motor programme9. Here we show that oviDNs express a calcium signal that (1) dips when an egg is internally prepared (ovulated), (2) drifts up and down over seconds to minutes-in a manner influenced by the relative value of substrates-as a fly determines whether to lay an egg and (3) reaches a consistent peak level just before the abdomen bend for egg deposition. This signal is apparent in the cell bodies of oviDNs in the brain and it probably reflects a behaviourally relevant rise-to-threshold process in the ventral nerve cord, where the synaptic terminals of oviDNs are located and where their output can influence behaviour. We provide perturbational evidence that the egg-deposition motor programme is initiated once this process hits a threshold and that subthreshold variation in this process regulates the time spent considering options and, ultimately, the choice taken. Finally, we identify a small recurrent circuit that feeds into oviDNs and show that activity in each of its constituent cell types is required for laying an egg. These results argue that a rise-to-threshold process regulates a relative-value, self-paced decision and provide initial insight into the underlying circuit mechanism for building this process.

An RNA-based theory of natural universal computation.

Life is confronted with computation problems in a variety of domains including animal behavior, single-cell behavior, and embryonic development. Yet we currently do not know of a naturally existing biological system that is capable of universal computation, i.e., Turing-equivalent in scope. Generic finite-dimensional dynamical systems (which encompass most models of neural networks, intracellular signaling cascades, and gene regulatory networks) fall short of universal computation, but are assumed to be capable of explaining cognition and development. I present a class of models that bridge two concepts from distant fields: combinatory logic (or, equivalently, lambda calculus) and RNA molecular biology. A set of basic RNA editing rules can make it possible to compute any computable function with identical algorithmic complexity to that of Turing machines. The models do not assume extraordinarily complex molecular machinery or any processes that radically differ from what we already know to occur in cells. Distinct independent enzymes can mediate each of the rules and RNA molecules solve the problem of parenthesis matching through their secondary structure. In the most plausible of these models all of the editing rules can be implemented with merely cleavage and ligation operations at fixed positions relative to predefined motifs. This demonstrates that universal computation is well within the reach of molecular biology. It is therefore reasonable to assume that life has evolved - or possibly began with - a universal computer that yet remains to be discovered. The variety of seemingly unrelated computational problems across many scales can potentially be solved using the same RNA-based computation system. Experimental validation of this theory may immensely impact our understanding of memory, cognition, development, disease, evolution, and the early stages of life.

Global selection of saccadic target features by neurons in area v4.

Psychophysical and neurophysiological studies indicate that during the preparation of saccades, visual processing at the target location is facilitated automatically by the deployment of attention. It has been assumed that the neural mechanisms involved in presaccadic shifts of attention are purely spatial in nature. Saccade preparation modulates the visual responses of neurons within extrastriate area V4, where the responses to targets are enhanced and responses to nontargets are suppressed. We tested whether this effect also engages a nonspatial form of modulation. We measured the responses of area V4 neurons to oriented gratings in two monkeys (Macaca mulatta) making delayed saccades to targets distant from the neuronal receptive field (RF). We varied the orientation of both the RF stimulus and the saccadic target. We found that, in addition to the spatial modulation, saccade preparation involves a feature-dependent modulation of V4 neuronal responses. Specifically, we found that the suppression of area V4 responses to nontarget stimuli during the preparation of saccades depends on the features of the saccadic target. Presaccadic suppression was absent when the features of the saccadic target matched the features preferred by individual V4 neurons. This feature-dependent modulation occurred in the absence of any feature-attention task. We show that our observations are consistent with a computational framework in which feature-based effects automatically emerge from saccade-related feedback signals that are spatial in nature.

An internal expectation guides Drosophila egg-laying decisions.

To better understand how animals make ethologically relevant decisions, we studied egg-laying substrate choice in Drosophila. We found that flies dynamically increase or decrease their egg-laying rates while exploring substrates so as to target eggs to the best, recently visited option. Visiting the best option typically yielded inhibition of egg laying on other substrates for many minutes. Our data support a model in which flies compare the current substrate's value with an internally constructed expectation on the value of available options to regulate the likelihood of laying an egg. We show that dopamine neuron activity is critical for learning and/or expressing this expectation, similar to its role in certain tasks in vertebrates. Integrating sensory experiences over minutes to generate an estimate of the quality of available options allows flies to use a dynamic reference point for judging the current substrate and might be a general way in which decisions are made.

Dissociated sequential activity and stimulus encoding in the dorsomedial striatum during spatial working memory.

Several lines of evidence suggest that the striatum has an important role in spatial working memory. The neural dynamics in the striatum have been described in tasks with short delay periods (1-4 s), but remain largely uncharacterized for tasks with longer delay periods. We collected and analyzed single unit recordings from the dorsomedial striatum of rats performing a spatial working memory task with delays up to 10 s. We found that neurons were activated sequentially, with the sequences spanning the entire delay period. Surprisingly, this sequential activity was dissociated from stimulus encoding activity, which was present in the same neurons, but preferentially appeared towards the onset of the delay period. These observations contrast with descriptions of sequential dynamics during similar tasks in other brains areas, and clarify the contribution of the striatum to spatial working memory.