Responses to Pattern-Violating Visual Stimuli Evolve Differently Over Days in Somata and Distal Apical Dendrites.

Scientists have long conjectured that the neocortex learns patterns in sensory data to generate top-down predictions of upcoming stimuli. In line with this conjecture, different responses to pattern-matching vs pattern-violating visual stimuli have been observed in both spiking and somatic calcium imaging data. However, it remains unknown whether these pattern-violation signals are different between the distal apical dendrites, which are heavily targeted by top-down signals, and the somata, where bottom-up information is primarily integrated. Furthermore, it is unknown how responses to pattern-violating stimuli evolve over time as an animal gains more experience with them. Here, we address these unanswered questions by analyzing responses of individual somata and dendritic branches of layer 2/3 and layer 5 pyramidal neurons tracked over multiple days in primary visual cortex of awake, behaving female and male mice. We use sequences of Gabor patches with patterns in their orientations to create pattern-matching and pattern-violating stimuli, and two-photon calcium imaging to record neuronal responses. Many neurons in both layers show large differences between their responses to pattern-matching and pattern-violating stimuli. Interestingly, these responses evolve in opposite directions in the somata and distal apical dendrites, with somata becoming less sensitive to pattern-violating stimuli and distal apical dendrites more sensitive. These differences between the somata and distal apical dendrites may be important for hierarchical computation of sensory predictions and learning, since these two compartments tend to receive bottom-up and top-down information, respectively.

Stimulus information guides the emergence of behavior-related signals in primary somatosensory cortex during learning.

Neurons in the primary cortex carry sensory- and behavior-related information, but it remains an open question how this information emerges and intersects together during learning. Current evidence points to two possible learning-related changes: sensory information increases in the primary cortex or sensory information remains stable, but its readout efficiency in association cortices increases. We investigated this question by imaging neuronal activity in mouse primary somatosensory cortex before, during, and after learning of an object localization task. We quantified sensory- and behavior-related information and estimated how much sensory information was used to instruct perceptual choices as learning progressed. We find that sensory information increases from the start of training, while choice information is mostly present in the later stages of learning. Additionally, the readout of sensory information becomes more efficient with learning as early as in the primary sensory cortex. Together, our results highlight the importance of primary cortical neurons in perceptual learning.

Responses of pyramidal cell somata and apical dendrites in mouse visual cortex over multiple days.

The apical dendrites of pyramidal neurons in sensory cortex receive primarily top-down signals from associative and motor regions, while cell bodies and nearby dendrites are heavily targeted by locally recurrent or bottom-up inputs from the sensory periphery. Based on these differences, a number of theories in computational neuroscience postulate a unique role for apical dendrites in learning. However, due to technical challenges in data collection, little data is available for comparing the responses of apical dendrites to cell bodies over multiple days. Here we present a dataset collected through the Allen Institute Mindscope's OpenScope program that addresses this need. This dataset comprises high-quality two-photon calcium imaging from the apical dendrites and the cell bodies of visual cortical pyramidal neurons, acquired over multiple days in awake, behaving mice that were presented with visual stimuli. Many of the cell bodies and dendrite segments were tracked over days, enabling analyses of how their responses change over time. This dataset allows neuroscientists to explore the differences between apical and somatic processing and plasticity.

A deep learning framework for neuroscience.

Systems neuroscience seeks explanations for how the brain implements a wide variety of perceptual, cognitive and motor tasks. Conversely, artificial intelligence attempts to design computational systems based on the tasks they will have to solve. In artificial neural networks, the three components specified by design are the objective functions, the learning rules and the architectures. With the growing success of deep learning, which utilizes brain-inspired architectures, these three designed components have increasingly become central to how we model, engineer and optimize complex artificial learning systems. Here we argue that a greater focus on these components would also benefit systems neuroscience. We give examples of how this optimization-based framework can drive theoretical and experimental progress in neuroscience. We contend that this principled perspective on systems neuroscience will help to generate more rapid progress.

The Role of The RNA Demethylase FTO (Fat Mass and Obesity-Associated) and mRNA Methylation in Hippocampal Memory Formation.

The formation of long-lasting memories requires coordinated changes in gene expression and protein synthesis. Although many studies implicate DNA modifications (DNA methylation, histone modifications) in memory formation, the contributions of RNA modifications remain largely unexplored. Here we investigated the role of mRNA methylation in hippocampal-dependent memory formation in mice. RNA modifications are highly dynamic and readily reversible. Methyltransferases add a methyl group to mRNA while demethylases remove methyl groups. Here we focused on examining the role of the best characterized RNA demethylase, FTO (fat mass and obesity-associated) in memory. We observed that FTO is expressed in the nuclei, dendrites and near dendritic spines of mouse dorsal hippocampal CA1 neurons. Next, we found that contextual fear conditioning transiently (0.5 h) decreased Fto levels in these neurons, with the largest decrease in FTO observed near synapses. The decrease in FTO observed shortly after contextual fear conditioning suggests that FTO normally constrains memory formation. To directly test this, we artificially decreased FTO levels in dorsal hippocampus of otherwise normal (wild-type) mice by microinjecting before training a single herpes simplex virus (HSV) vector expressing either CRISPR/Cas9 or shRNA targeted against Fto. Decreasing FTO using either method specifically enhanced contextual fear memory. Together, these results show the importance of FTO during memory formation and, furthermore, implicate mRNA modification and epi-transcriptomics as novel regulators of memory formation.

Adult NG2-Glia Are Required for Median Eminence-Mediated Leptin Sensing and Body Weight Control.

While leptin is a well-known regulator of body fat mass, it remains unclear how circulating leptin is sensed centrally to maintain energy homeostasis. Here we show that genetic and pharmacological ablation of adult NG2-glia (also known as oligodendrocyte precursors), but not microglia, leads to primary leptin resistance and obesity in mice. We reveal that NG2-glia contact the dendritic processes of arcuate nucleus leptin receptor (LepR) neurons in the median eminence (ME) and that these processes degenerate upon NG2-glia elimination, which explains the consequential attenuation of these neurons' molecular and electrical responses to leptin. Our data therefore indicate that LepR dendrites in the ME represent the principal conduits of leptin's anorexigenic action and that NG2-glia are essential for their maintenance. Given that ME-directed X-irradiation confirmed the pharmacological and genetically mediated ablation effects on body weight, our findings provide a rationale for the known obesity risk associated with cranial radiation therapy.

Advanced In vivo Use of CRISPR/Cas9 and Anti-sense DNA Inhibition for Gene Manipulation in the Brain.

Gene editing tools are essential for uncovering how genes mediate normal brain-behavior relationships and contribute to neurodegenerative and neuropsychiatric disorders. Recent progress in gene editing technology now allows neuroscientists unprecedented access to edit the genome efficiently. Although many important tools have been developed, here we focus on approaches that allow for rapid gene editing in the adult nervous system, particularly CRISPR/Cas9 and anti-sense nucleotide-based techniques. CRISPR/Cas9 is a flexible gene editing tool, allowing the genome to be manipulated in diverse ways. For instance, CRISPR/Cas9 has been successfully used to knockout genes, knock-in mutations, overexpress or inhibit gene activity, and provide scaffolding for recruiting specific epigenetic regulators to individual genes and gene regions. Moreover, the CRISPR/Cas9 system may be modified to target multiple genes at one time, affording simultaneous inhibition and overexpression of distinct genetic targets. Although many of the more advanced applications of CRISPR/Cas9 have not been applied to the nervous system, the toolbox is widely accessible, such that it is poised to help advance neuroscience. Anti-sense nucleotide-based technologies can be used to rapidly knockdown genes in the brain. The main advantage of anti-sense based tools is their simplicity, allowing for rapid gene delivery with minimal technical expertise. Here, we describe the main applications and functions of each of these systems with an emphasis on their many potential applications in neuroscience laboratories.