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Brain imaging genetics is an emerging research field to explore the underlying genetic architecture of brain structure and function measured by different imaging modalities. However, not all the changes in the brain are a consequential result of ...

Recently, linear formulations and convex optimization methods have been proposed to predict diffusion-weighted Magnetic Resonance Imaging (dMRI) data given estimates of brain connections generated using tractography algorithms. The size of the linear ...

Visualization plays an important role in helping neuroscientist understanding human brain data. Most publicly available software focuses on visualizing a specific brain imaging modality. Here we present an extensible visualization platform, BECA, ...

Crucial to understanding how the brain works is connectivity, and the centerpiece of brain connectivity is the connectome, a comprehensive description of how neurons and brain regions are connected. The human brain is a network of extraordinary ...

Over the last decade, the study of complex networks has expanded across diverse scientific fields. Increasingly, science is concerned with the structure, behavior, and evolution of complex systems ranging from cells to ecosystems. Modern network ...

Much progress has been made in our understanding of the structure and function of brain networks. Recent evidence indicates that such networks contain specific structural patterns and motifs and that these structural attributes facilitate complex neural ...

In this chapter, we discuss the new research field brain-like intelligence and introduce and relate the contributions to this volume to each other.

Embodied artificial intelligence is based on the notion that cognition and action emerge from interactions between brain, body and environment. This chapter sketches a set of foundational principles that might be useful for understanding the emergence ("...

Embodied intelligent systems are naturally subject to physical constraints, such as forces and torques (due to gravity and friction), energy requirements for propulsion, and eventual damage and degeneration. But embodiment implies far more than just a ...

The prefrontal cortex (PFC) is crucially involved in the executive component of working memory, representation of task state, and behavior selection. This article presents a large-scale computational model of the PFC and associated brain regions ...

Brain networks are uniquely capable of generating and integrating information collected from multiple sources in real time. The application of structural and information theoretical measures to such networks has begun to unravel the crucial ingredients ...

In this paper, we implement a computational model of a neuromodulatory system in an autonomous robot. The model is based on a set of anatomical and physiological properties of the mammalian dopamine system, one of several diffuse ascending systems of ...

We describe and discuss a neural network model of the dopaminergic system based on observed anatomical and physiological properties of the primate midbrain. The model relies on value-dependent synaptic modification to acquire ...

In this paper we implement a computational model of a neuromodulatory system in an autonomous robot. The output of the neuromodulatory system acts as a value signal, modulating widely distributed synaptic changes. The model is based on anatomical and ...