Rationally inattentive intertemporal choice

July 31, 2020

Discounting of future rewards is traditionally interpreted as evidence for an intrinsic preference in favor of sooner rewards. However, temporal discounting can also arise from internal uncertainty in value representations of future events, if one assumes that noisy mental simulations of the future are rationally combined with prior beliefs. Here, we further develop this idea by considering how simulation noise may be adaptively modulated by task demands, based on principles of rational inattention. We show how the optimal allocation of mental effort can give rise to the magnitude effect in intertemporal choice. In a re-analysis of two prior data sets, and in another experiment, we reveal several behavioral signatures of this theoretical account, tying choice stochasticity to the magnitude effect. We conclude that some aspects of temporal discounting may result from a cognitively plausible adaptive response to the costs of information processing.

A Neural Network for Wind-Guided Compass Navigation

July 14, 2020

Spatial maps in the brain are most accurate when they are linked to external sensory cues. Here, we show that the compass in the Drosophila brain is linked to the direction of the wind. Shifting the wind rightward rotates the compass as if the fly were turning leftward, and vice versa. We describe the mechanisms of several computations that integrate wind information into the compass. First, an intensity-invariant representation of wind direction is computed by comparing left-right mechanosensory signals. Then, signals are reformatted to reduce the coding biases inherent in peripheral mechanics, and wind cues are brought into the same circular coordinate system that represents visual cues and self-motion signals. Because the compass incorporates both mechanosensory and visual cues, it should enable navigation under conditions where no single cue is consistently reliable. These results show how local sensory signals can be transformed into a global, multimodal, abstract representation of space.

Origin of perseveration in the trade-off between reward and complexity

July 14, 2020

When humans and other animals make repeated choices, they tend to repeat previously chosen actions independently of their reward history. This paper locates the origin of perseveration in a trade-off between two computational goals: maximizing rewards and minimizing the complexity of the action policy. We develop an information-theoretic formalization of policy complexity and show how optimizing the trade-off leads to perseveration. Analysis of two data sets reveals that people attain close to optimal trade-offs. Parameter estimation and model comparison supports the claim that perseveration quantitatively agrees with the theoretically predicted functional form (a softmax function with a frequency-dependent action bias).

NMDAR-mediated modulation of gap junction circuit regulates olfactory learning in C. elegans

July 10, 2020

Modulation of gap junction-mediated electrical synapses is a common form of neural plasticity. However, the behavioral consequence of the modulation and the underlying molecular cellular mechanisms are not understood. Here, using a C. elegans circuit of interneurons that are connected by gap junctions, we show that modulation of the gap junctions facilitates olfactory learning. Learning experience weakens the gap junctions and induces a repulsive sensory response to the training odorants, which together decouple the responses of the interneurons to the training odorants to generate learned olfactory behavior. The weakening of the gap junctions results from downregulation of the abundance of a gap junction molecule, which is regulated by cell-autonomous function of the worm homologs of a NMDAR subunit and CaMKII. Thus, our findings identify the function of a gap junction modulation in an in vivo model of learning and a conserved regulatory pathway underlying the modulation.

3D Brain Organoids: Studying Brain Development and Disease Outside the Embryo

July 8, 2020

Scientists have been fascinated by the human brain for centuries, yet knowledge of the cellular and molecular events that build the human brain during embryogenesis and of how abnormalities in this process lead to neurological disease remains very superficial. In particular, the lack of experimental models for a process that largely occurs during human in utero development, and is therefore poorly accessible for study, has hindered progress in mechanistic understanding. Advances in stem cell-derived models of human organogenesis, in the form of three-dimensional organoid cultures, and transformative new analytic technologies have opened new experimental pathways for investigation of aspects of development, evolution, and pathology of the human brain. Here, we consider the biology of brain organoids, compared and contrasted with the endogenous human brain, and highlight experimental strategies to use organoids to pioneer new understanding of human brain pathology.