Focus |

Focus on Learning and Memory

Learning new information and skills, storing memories of this knowledge, and retrieving, modifying, or forgetting these memories over time are critical for flexibly responding to a changing environment. How these processes occur has fascinated philosophers, psychologists, and neuroscientists for generations, and continues to inspire research encompassing diverse approaches. In our October 2019 issue, Nature Neuroscience presents a collection of reviews and perspectives that reflects the breadth and vibrancy of this field.

Editorial

Reviews

Memory retrieval involves interactions between internal or external cues and stored engrams. Identification of engrams in mice permits examination of these interactions at the level of neural ensembles. This review highlights emerging findings.

Review Article | | Nature Neuroscience

Perspectives

When crossing the street, you can ignore the color of oncoming cars, but for hailing a taxi color is important. How do we learn what to represent neurally for each task? Here, Niv summarizes a decade of work on representation learning in the brain.

Perspective | | Nature Neuroscience

This paper first reviews the work on brain-machine interfaces (BMIs) for restoring lost motor function and then provides a perspective on how BMIs could extend to the new frontier of restoring lost emotional function in neuropsychiatric disorders.

Perspective | | Nature Neuroscience

A deep network is best understood in terms of components used to design it—objective functions, architecture and learning rules—rather than unit-by-unit computation. Richards et al. argue that this inspires fruitful approaches to systems neuroscience.

Perspective | | Nature Neuroscience

From the archive

The function of rapid eye movement (REM) sleep remains unclear. By examining how REM sleep affects synapses in the mouse cortex, the authors show that REM sleep is fundamental to brain development, learning and memory consolidation by selectively pruning and maintaining newly formed synapses via dendritic calcium spike-dependent mechanisms.

Article | | Nature Neuroscience

The authors address why the use of prior expectations might be compromised in autism, by using computational models and pupillometric markers of the neuromodulator noradrenaline. They show that by estimating the world to be more changeable than it really is, adults with autism have difficulty in learning what to expect.

Article | | Nature Neuroscience

Humans and other mammals are prodigious learners, partly because they also ‘learn how to learn’. Wang and colleagues present a new theory showing how learning to learn may arise from interactions between prefrontal cortex and the dopamine system.

Article | | Nature Neuroscience

Pairing an odor conditioned stimulus (CS) with an unconditioned stimulus (US) induces memory formation. Vetere et al. replace the real CS and US with direct optogenetic stimulation of the brain and create a fully artificial odor memory in mice.

Article | | Nature Neuroscience

Learning to predict reward is thought to be driven by dopaminergic prediction errors, which reflect discrepancies between actual and expected value. Here the authors show that learning to predict neutral events is also driven by prediction errors and that such value-neutral associative learning is also likely mediated by dopaminergic error signals.

Article | | Nature Neuroscience

The authors show how predictive representations are useful for maximizing future reward, particularly in spatial domains. They develop a predictive-map model of hippocampal place cells and entorhinal grid cells that captures a wide variety of effects from human and rodent literature.

Article | | Nature Neuroscience

Learning is ubiquitous in everyday life, yet it is unclear how neurons change their activity together during learning. Golub and colleagues show that short-term learning relies on a fixed neural repertoire, which limits behavioral improvement.

Article | | Nature Neuroscience

Corticospinal cells of the motor cortex act as a direct link between the cortex and movement-generating circuits within the spinal cord. The authors demonstrate that the relationship between activity of these cells and movement changes with time and learning, indicating a flexible cortical output to drive movements.

Article | | Nature Neuroscience

Granule cells constitute half of the cells in the brain, yet their activity during behavior is largely uncharacterized. The authors report that granule cells encode multisensory representations that evolve with learning into a predictive motor signal. This activity may help the cerebellum implement a forward model for action.

Article | | Nature Neuroscience