Data Science & Informatics

Real-time neural decoding centers on predicting behavior variables based on neural activity data, where the prediction is performed at a pace that reliably keeps up with the speed of the activity that is being monitored. Neuromodulation devices are becoming one of the most powerful tools for the treatment of brain disorders, enhancing neurocognitive performance, and demonstrating causality (Bergmann et al., 2016; Knotkova and Rasche, 2015). A precise neuromodulation system (Figure 1) integrates neural activity monitoring, real-time neural decoding, and neuromodulation.

Collaborating Pis and Consultant United States Pl: Anitha Pasupathy, Dept. of Biological Structure, University of Washington, Seattle, USA Co-Pl: Wyeth Bair, Dept. of Biological Structure, University of Washington, Seattle, USA Japan Pl: lsamu Motoyoshi, Dept.

Dopamine (DA) neurons are fundamental to many aspects of behavior, and dysfunction of the DA system contributes to a wide range of disorders, including drug addiction. How does DA contribute to such a diversity of functions and dysfunctions? Part of the answer may relate to recent discoveries that DA neurons respond to a wide range of behavioral variables - not only to reward and reward-predicting cues, as traditionally examined, but also to other variables including position, movement, and behavioral choices.

There is a fundamental gap in our understanding of the computational principles and neural mechanisms by which neural circuits represent complex objects like faces. This conceptual gap constitutes an important problem because, until it is filled, we will not be able to understand face recognition and the reasons for face blindness. The long-term goal is to understand the computational principles and neural mechanisms of face recognition and create a computer face-recognition system based on these principles.

Humans and other animals can choose their actions using multiple learning algorithms and decision­ making strategies. For example, habitual behaviors adapted to a stable environment can be selected using so-called model-free reinforcement learning algorithms, in which the value of each action is incrementally updated according to the amount of unexpected reward. The underlying neural mechanisms for this type of reinforcement learning have been intensively studied.

The striking spatial correlates of hippocampal place cells and grid cells have provided unique insights into how the brain constructs internal, cognitive representations of the environment and uses these representations to guide behavior. These spatially selective cells are influenced by both self-motion signals and by external sensory landmarks.

A fundamental goal for understanding the brain and mammalian and human intelligence, and to understand how processing goes awry in genetic and developmental diseases, is to understand the principles of operation of cerebral cortex. A key step is to understand "canonical" operations carried out by cortex. Here we will explore the operations of cortical circuitry in experiments guided by a new theory of a candidate canonical circuit operation. Sensory cortex must globally integrate localized sensory input to parse objects and support perception.

Understanding how different parts of the brain communicate is perhaps the most fundamental question of neuroscience because it is at the heart of understanding all brain functions and disorders. It is of clinical importance because numerous brain diseases - autism, schizophrenia, attention deficit disorder, and many others - are thought to be due to impaired communication among regions of the brain, and attention in particular is impaired in every major neurological disorder.

The network of peripheral nerves offers extraordinary potential for modulating and/or monitoring the functioning of internal organs or the brain. The nervous system functions by generating patterns of neural activity. To influence neural activity for desired outcomes, neural interface technology must access the appropriate peripheral nerve tissue, activate it in a focal targeted manner, and alter the patterns of activity.

Different parts of the brain share and transmit Information through long-range connections that connect nerve cells in each part of the brain with nerve cells in other brain areas. These connections form bundles of nerve cells, and these bundles comprise a complex and expansive network within the human brain. Understanding these brain networks and their relation to the way that the brain Implements perception and cognition, and understanding how these networks break down In various brain disorders are major challenges In contemporary neuroscience.