NeuroML is an XML-based model description language, which provides a powerful common data format for defining and exchanging models of neurons and neuronal networks. In the latest version of NeuroML, the structure and behavior of ion channel, synapse, cell, and network model descriptions are based on underlying definitions provided in LEMS, a domain-independent language for expressing hierarchical mathematical models of physical entities. While declarative approaches for describing models have led to greater exchange of model elements among software tools in computational neuroscience, a frequent criticism of XML-based languages is that they are difficult to work with directly. Here we describe two Application Programming Interfaces (APIs) written in Python (http://www.python.org), which simplify the process of developing and modifying models expressed in NeuroML and LEMS. The libNeuroML API provides a Python object model with a direct mapping to all NeuroML concepts defined by the NeuroML Schema, which facilitates reading and writing the XML equivalents. In addition, it offers a memory-efficient, array-based internal representation, which is useful for handling large-scale connectomics data. The libNeuroML API also includes support for performing common operations that are required when working with NeuroML documents. Access to the LEMS data model is provided by the PyLEMS API, which provides a Python implementation of the LEMS language, including the ability to simulate most models expressed in LEMS. Together, libNeuroML and PyLEMS provide a comprehensive solution for interacting with NeuroML models in a Python environment.

Illicit psychostimulant addiction remains a significant problem worldwide, despite decades of research into the neural underpinnings and various treatment approaches. The purpose of this review is to provide a succinct overview of the neurocircuitry involved in drug addiction, as well as the acute and chronic effects of cocaine and amphetamines within this circuitry in humans. Investigational pharmacological treatments for illicit psychostimulant addiction are also reviewed. Our current knowledge base clearly demonstrates that illicit psychostimulants produce lasting adaptive neural and behavioral changes that contribute to the progression and maintenance of addiction. However, attempts at generating pharmacological treatments for psychostimulant addiction have historically focused on intervening at the level of the acute effects of these drugs. The lack of approved pharmacological treatments for psychostimulant addiction highlights the need for new treatment strategies, especially those that prevent or ameliorate the adaptive neural, cognitive, and behavioral changes caused by chronic use of this class of illicit drugs.

In several group-living species, individuals' social preferences are thought to be influenced by cooperation. For some societies with fission–fusion dynamics, sex-specific association patterns reflect sex differences in cooperation in within- and between-group contexts. In our study, we investigated this hypothesis further by comparing sex-specific association patterns in two closely related species, chimpanzees and bonobos, which differ in the level of between-group competition and in the degree to which sex and kinship influence dyadic cooperation. Here, we used long-term party composition data collected on five chimpanzee and two bonobo communities and assessed, for each individual of 10 years and older, the sex of its top associate and of all conspecifics with whom it associated more frequently than expected by chance. We found clear species differences in association patterns. While in all chimpanzee communities males and females associated more with same-sex partners, in bonobos males and females tended to associate preferentially with females, but the female association preference for other females is lower than in chimpanzees. Our results also show that, for bonobos (but not for chimpanzees), association patterns were predominantly driven by mother–offspring relationships. These species differences in association patterns reflect the high levels of male–male cooperation in chimpanzees and of mother–son cooperation in bonobos. Finally, female chimpanzees showed intense association with a few other females, and male chimpanzees showed more uniform association across males. In bonobos, the most differentiated associations were from males towards females. Chimpanzee male association patterns mirror fundamental human male social traits and, as in humans, may have evolved as a response to strong between-group competition. The lack of such a pattern in a closely related species with a lower degree of between-group competition further supports this notion.

We recommend using backward design to develop course-based undergraduate research experiences (CUREs). The defining hallmark of CUREs is that students in a formal lab course explore research questions with unknown answers that are broadly relevant outside the course. Because CUREs lead to novel research findings, they represent a unique course design challenge, as the dual nature of these courses requires course designers to consider two distinct, but complementary, sets of goals for the CURE: 1) scientific discovery milestones (i.e., research goals) and 2) student learning in cognitive, psychomotor, and affective domains (i.e., pedagogical goals). As more undergraduate laboratory courses are re-imagined as CUREs, how do we thoughtfully design these courses to effectively meet both sets of goals? In this Perspectives article, we explore this question and outline recommendations for using backward design in CURE development.

The research project entitled “Local Policing in the Context of Immigration” (LPCI) was active from 2007 through 2016. The purposes of the study were to explore and describe the types of local policies and policing practices that local jurisdictions and police agencies throughout the United States were undertaking with regard to police encounters with immigrants (specifically, unauthorized or undocumented immigrants), and to investigate the characteristics of local communities that were associated with these various approaches to immigration policing as well as the potential consequences of local immigration policing for immigrants, communities, and the nation.