Measuring the dynamic relationship between neuromodulators, such as dopamine, and neuronal action potentials is imperative to understand how these fundamental modes of neural signaling interact to mediate behavior. We developed methods to measure concurrently dopamine and extracellular action potentials (i.e., spikes) in monkeys. Standard fast-scan cyclic voltammetric (FSCV) electrochemical (EChem) and electrophysiological (EPhys) recording systems are combined and used to collect spike and dopamine signals, respectively, from an array of carbon fiber (CF) sensors implanted in the monkey striatum. FSCV requires the application of small voltages at the implanted sensors to measure redox currents generated from target molecules, such as dopamine. These applied voltages create artifacts at neighboring EPhys measurement sensors which may lead to misclassification of these signals as physiological spikes. Therefore, simple automated temporal interpolation algorithms were designed to remove these artifacts and e...

Typical statistical practices in the biological sciences have been increasingly called into question due to difficulties in the replication of an increasing number of studies, many of which are confounded by the relative difficulty of null significance hypothesis testing designs and interpretation of p -values. Bayesian inference, representing a fundamentally different approach to hypothesis testing, is receiving renewed interest as a potential alternative or complement to traditional null significance hypothesis testing due to its ease of interpretation and explicit declarations of prior assumptions. Bayesian models are more mathematically complex than equivalent frequentist approaches, which have historically limited applications to simplified analysis cases. However, the advent of probability distribution sampling tools with exponential increases in computational power now allows for quick and robust inference under any distribution of data. Here we present a practical tutorial on the use of Bayesian in...

Acetylcholine (ACh) neurons in the central nervous system are required for the coordination of neural network activity during higher brain functions, such as attention, learning, and memory, as well as locomotion. Disturbed cholinergic signaling has been described in many neurodevelopmental and neurodegenerative disorders. Furthermore, cotransmission of other signaling molecules, such as glutamate and GABA, with ACh has been associated with essential roles in brain function or disease. However, it is unknown when ACh neurons become cholinergic during development. Thus, understanding the timeline of how the cholinergic system develops and becomes active in the healthy brain is a crucial part of understanding brain development. To study this, we used transgenic mice to selectively label ACh neurons with tdTomato. We imaged serial sectioned brains and generated whole-brain reconstructions at different time points during pre- and postnatal development. We found three crucial time windows—two in the prenatal an...

CRISPR/Cas9 gene editing represents an exciting avenue to study genes of unknown function and can be combined with genetically encoded tools such as fluorescent proteins, channelrhodopsins, DREADDs, and various biosensors to more deeply probe the function of these genes in different cell types. However, current strategies to also manipulate or visualize edited cells are challenging due to the large size of Cas9 proteins and the limited packaging capacity of adeno-associated viruses (AAVs). To overcome these constraints, we developed an alternative gene editing strategy using a single AAV vector and mouse lines that express Cre-dependent Cas9 to achieve efficient cell-type specific editing across the nervous system. Expressing Cre-dependent Cas9 from a genomic locus affords space to package guide RNAs for gene editing together with Cre-dependent, genetically encoded tools to manipulate, map, or monitor neurons using a single virus. We validated this strategy with three common tools in neuroscience: ChRonos,...

The role of gamma rhythm (30–80 Hz) in visual processing is debated; stimuli like gratings and hue patches generate strong gamma, but many natural images do not. Could image gamma responses be predicted by approximating images as gratings or hue patches? Surprisingly, this question remains unanswered, since the joint dependence of gamma on multiple features is poorly understood. We recorded local field potentials and electrocorticogram from two female monkeys while presenting natural images and parametric stimuli varying along several feature dimensions. Gamma responses to different grating/hue features were separable, allowing for a multiplicative model based on individual features. By fitting a hue patch to the image around the receptive field, this simple model could predict gamma responses to chromatic images across scales with reasonably high accuracy. Our results provide a simple “baseline” model to predict gamma from local image properties, against which more complex models of natural vision can be ...

Midbrain dopamine neurons receive convergent synaptic input from multiple brain areas, which perturbs rhythmic pacemaking to produce the complex firing patterns observed in vivo. This study investigated the impact of single and multiple inhibitory inputs on ventral tegmental area (VTA) dopamine neuron firing in mice of both sexes using novel experimental measurements and modeling. We first measured unitary inhibitory postsynaptic currents produced by single axons using both minimal electrical stimulation and minimal optical stimulation of rostromedial tegmental nucleus and ventral pallidum afferents. We next determined the phase resetting curve, the reversal potential for GABAA receptor-mediated inhibitory postsynaptic currents (IPSCs), and the average interspike membrane potential trajectory during pacemaking. We combined these data in a phase oscillator model of a VTA dopamine neuron, simulating the effects of unitary inhibitory postsynaptic conductances (uIPSGs) on spike timing and rate. The effect of a...

Ghrelin is a stomach-derived hormone that increases feeding and is elevated in response to chronic psychosocial stressors. The effects of ghrelin on feeding are mediated by the binding of ghrelin to the growth hormone secretagogue receptor (GHSR), a receptor located in hypothalamic and extrahypothalamic regions important for regulating food intake and metabolic rate. The ability of ghrelin to enter the brain, however, seems to be restricted to circumventricular organs like the median eminence and the brainstem area postrema, whereas ghrelin does not readily enter other GHSR-expressing regions like the ventral tegmental area (VTA). Interestingly, social stressors result in increased blood–brain barrier permeability, and this could therefore facilitate the entry of ghrelin into the brain. To investigate this, we exposed mice to social defeat stress for 21 d and then peripherally injected a Cy5-labelled biologically active ghrelin analog. The results demonstrate that chronically stressed mice exhibit higher C...

Brain activity implies the orchestrated functioning of interconnected brain regions. Typical in vitro models aim to mimic the brain using single human pluripotent stem cell-derived neuronal networks. However, the field is constantly evolving to model brain functions more accurately through the use of new paradigms, e.g., brain-on-a-chip models with compartmentalized structures and integrated sensors. These methods create novel data requiring more complex analysis approaches. The previously introduced circular tripartite network concept models the connectivity between spatially diverse neuronal structures. The model consists of a microfluidic device allowing axonal connectivity between separated neuronal networks with an embedded microelectrode array to record both local and global electrophysiological activity patterns in the closed circuitry. The existing tools are suboptimal for the analysis of the data produced with this model. Here, we introduce advanced tools for synchronization and functional connect...

Quantifying and analyzing licking behavior can offer valuable insights into fundamental neurobiological mechanisms controlling animal consummatory behaviors. Lickometers are typically based on electrical properties, a strategy that comes with limitations, including susceptibility to electrical interference and generation of electrical disturbances in electrophysiological measurements. While optical lickometers offer an alternative method to measure licks and quantify fluid intake in animals, they are prone to false readings and susceptibility to outside light sources. To overcome this problem, we propose a low-cost open-source lickometer that combines a restricted infrared beam defined by optical fibers, with a poke design that allows easy access to the tongue while limiting access of other body parts and external light sources. This device also includes features for detecting nose pokes and presenting visual cues during behavioral tasks. We provide validation experiments that demonstrate the optical licko...

In the article, “The Impact of Spectral and Temporal Degradation on Vocoded Speech Recognition in Early-Blind Individuals,” by Hyo Jung Choi, Jeong-Sug Kyong, Jae …