Working memory, a core function underlying many higher-level cognitive processes, requires cooperation of multiple brain regions. White matter refers to myelinated axons, which are critical to interregional brain communication. Past studies on the association between white-matter integrity and working memory have yielded mixed findings. Using voxelwise tract-based spatial statistics analysis, we investigated this relationship in a sample of 328 healthy adults from 25 to 80 years of age. Given the important role of dopamine (DA) in working-memory functioning and white matter, we also analyzed the effects of dopamine-related genes on them. There were associations between white-matter integrity and working memory in multiple tracts, indicating that working-memory functioning relies on global connections between different brain areas across the adult life span. Moreover, a mediation analysis suggested that white-matter integrity contributes to age-related differences in working memory. Finally, there was an ef...

Survival for vertebrate animals is dependent on the ability to successfully find food, locate a mate, and avoid predation. Each of these behaviors requires motor control, which is set by a combination of kinematic properties. For example, the frequency and amplitude of motor output combine in a multiplicative manner to determine features of locomotion such as distance traveled, speed, force (thrust), and vigor. Although there is a good understanding of how different populations of excitatory spinal interneurons establish locomotor frequency, there is a less thorough mechanistic understanding for how locomotor amplitude is established. Recent evidence indicates that locomotor amplitude is regulated in part by a subset of functionally and morphologically distinct V2a excitatory spinal interneurons (Type II, nonbursting) in larval and adult zebrafish. Here, we provide direct evidence that most V3 interneurons (V3-INs), which are a developmentally and genetically defined population of ventromedial glutamatergi...

Learning associations between cues and rewards require the mesolimbic dopamine system. The dopamine response to cues signals differences in reward value in well trained animals. However, these value-related dopamine responses are absent during early training sessions when cues signal differences in the reward rate. These findings suggest cue-evoked dopamine release conveys differences between outcomes only after extensive training, though it is unclear whether this is unique to when cues signal differences in reward rate, or whether this is also evident when cues signal differences in other value-related parameters such as reward size. To address this, we used a Pavlovian conditioning task in which one audio cue was associated with a small reward (one pellet) and another audio cue was associated with a large reward (three pellets). We performed fast-scan cyclic voltammetry to record changes in dopamine release in the nucleus accumbens of male and female rats throughout learning. While female rats exhibited...

Single-brain neuroimaging studies have shown that human cooperation is associated with neural activity in frontal and temporoparietal regions. However, it remains unclear whether single-brain studies are informative about cooperation in real life, where people interact dynamically. Such dynamic interactions have become the focus of interbrain studies. An advantageous technique in this regard is functional near-infrared spectroscopy (fNIRS) because it is less susceptible to movement artifacts than more conventional techniques like electroencephalography (EEG) or functional magnetic resonance imaging (fMRI). We conducted a systematic review and the first quantitative meta-analysis of fNIRS hyperscanning of cooperation, based on thirteen studies with 890 human participants. Overall, the meta-analysis revealed evidence of statistically significant interbrain synchrony while people were cooperating, with large overall effect sizes in both frontal and temporoparietal areas. All thirteen studies observed signific...

Responsible science has three components: doing science, the validity of the discoveries themselves, and the consequences of these discoveries. These three components are nondissociable, because science does not exist by and for itself: it exists within a societal context. Society and Science always interact with each other. Doing science has direct societal consequences, which can be positive, including novel therapeutic solutions and general advancement of knowledge, and negative, including using planet resources, producing waste, and contributing to global warming (with travel, for example). I shall not develop the latter components here; I shall develop the validity of the discoveries and their consequences in the present context of the immediacy of information and “selfie” science. An idealistic and naive depiction of a scientist is someone concerned only with the internal content of their scientific work and not with their external repercussions. A scientist is but one part of the complex organism t...

The marble burying test is a commonly used paradigm to describe phenotypes in mouse models of neurodevelopmental and psychiatric disorders. The current methodological approach relies predominantly on reporting the number of buried marbles at the end of the test. By measuring the proxy of the behavior (buried marbles), many important characteristics regarding the temporal aspect of this assay are lost. Here, we introduce a novel, automated method to quantify mouse behavior during the marble burying test with the focus on the burying bouts and movement dynamics. Using open-source software packages, we trained a supervised machine learning algorithm (the “classifier”) to distinguish burying behavior in freely moving mice. In order to confirm the classifier’s accuracy and characterize burying events in high detail, we performed the marble burying test in three mouse models: Ube3am-/p+ [Angelman syndrome (AS) model], Shank2 −/− (autism model), and Sapap3 −/− [obsessive-compulsive disorder (OCD) model] mice. The...

Dynamic functional connectivity within brain circuits requires coordination of intercellular signaling and intracellular signal transduction. Critical roles for cAMP-dependent protein kinase A (PKA) signaling are well established in the Drosophila mushroom body (MB) learning and memory circuitry, but local PKA activity within this well-mapped neuronal network is uncharacterized. Here, we use an in vivo PKA activity sensor (PKA-SPARK) to test spatiotemporal regulatory requirements in the MB axon lobes. We find immature animals have little detectable PKA activity, whereas postcritical period adults show high field-selective activation primarily in just 3/16 defined output regions. In addition to the age-dependent PKA activity in distinct α’/β’ lobe nodes, females show sex-dependent elevation compared with males in these same restricted regions. Loss of neural cell body Fragile X mental retardation protein (FMRP) and Rugose [human Neurobeachin (NBEA)] suppresses localized PKA activity, whereas overexpression ...

Hypothalamic melanin-concentrating hormone (MCH) neurons are important regulators of multiple physiological processes, such as sleep, feeding, and memory. Despite the increasing interest in their neuronal functions, the molecular mechanism underlying MCH neuron development remains poorly understood. We report that a three-dimensional culture of mouse embryonic stem cells (mESCs) can generate hypothalamic-like tissues containing MCH-positive neurons, which reproduce morphologic maturation, neuronal connectivity, and neuropeptide/neurotransmitter phenotype of native MCH neurons. Using this in vitro system, we demonstrate that Hedgehog (Hh) signaling serves to produce major neurochemical subtypes of MCH neurons characterized by the presence or absence of cocaine- and amphetamine-regulated transcript (CART). Without exogenous Hh signals, mESCs initially differentiated into dorsal hypothalamic/prethalamic progenitors and finally into MCH+CART+ neurons through a specific intermediate progenitor state. Conversely...

In the article, “Automated Detection and Localization of Synaptic Vesicles in Electron Microscopy Images,” by Barbara Imbrosci, Dietmar …

Understanding the human brain is a “Grand Challenge” for 21st century research. Computational approaches enable large and complex datasets to be addressed efficiently, supported by artificial neural networks, modeling and simulation. Dynamic generative multiscale models, which enable the investigation of causation across scales and are guided by principles and theories of brain function, are instrumental for linking brain structure and function. An example of a resource enabling such an integrated approach to neuroscientific discovery is the BigBrain, which spatially anchors tissue models and data across different scales and ensures that multiscale models are supported by the data, making the bridge to both basic neuroscience and medicine. Research at the intersection of neuroscience, computing and robotics has the potential to advance neuro-inspired technologies by taking advantage of a growing body of insights into perception, plasticity and learning. To render data, tools and methods, theories, basic pr...