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Neural systems have evolved to process sensory stimuli in a way that allows for efficient and adaptive behavior in a complex environment. Recent technological advances enable us to investigate sensory processing in animal models by simultaneously recording the activity of large populations of neurons with singlecell resolution, yielding high-dimensional datasets. In this review, we discuss concepts and approaches for assessing the population-level representation of sensory stimuli in the form of a representational map. In such a map, not only are the identities of stimuli distinctly represented, but their relational similarity is also mapped onto the space of neuronal activity. We highlight example studies in which the structure of representational maps in the brain are estimated from recordings in humans as well as animals and compare their methodological approaches. Finally, we integrate these aspects and provide an outlook for how the concept of representational maps could be applied to various fields in basic and clinical neuroscience. [ABSTRACT FROM AUTHOR]

The scientific interest in boredom is growing over the past decades. Boredom has not only been linked to symptoms of psychopathology, but also shows a remarkable effect on individual behavior under healthy conditions. Current characterizations of boredom in humans mostly rely on self-report assessments which proved to faithfully reflect boredom in a vast range of experimental environments. Two of the most commonly used and prominent self-report scales in order to assess boredom are the Multidimensional State Boredom Scale (MSBS) and the Boredom Proneness Scale (BPS). Here, we present the German translations of both questionnaires and their validation. We obtained and analyzed psychometric data from more than 800 healthy individuals. We find that the German MSBS and BPS show vast congruence with their originals in respect to item statistics, internal reliability and validity. In particular, we find remarkable associations of state boredom and trait boredom with indicators of mental burden. Testing the factor structure of both questionnaires, we find supporting evidence for a 5-factor model of the MSBS, whereas the BPS in line with its original shows an irregular, inconsistent factor structure. Thus, we validate the German versions of MSBS and BPS and set a starting point for further studies of boredom in German-speaking collectives. [ABSTRACT FROM AUTHOR]

Boredom is an aversive mental state that is typically evoked by monotony and drives individuals to seek novel information. Despite this effect on individual behavior, the consequences of boredom for collective behavior remain elusive. Here, we introduce an agent-based model of collective fashion behavior in which simplified agents interact randomly and repeatedly choose alternatives from a circular space of color variants. Agents are endowed with a memory of past experiences and a boredom parameter, promoting avoidance of monotony. Simulating collective color trends with this model captures aspects of real trends observed in fashion magazines. We manipulate the two parameters and observe that the boredom parameter is essential for perpetuating fashion dynamics in our model. Furthermore, highly bored agents lead future population trends, when acting coherently or being highly popular. Taken together, our study illustrates that highly bored individuals can guide collective dynamics of a population to continuously explore different variants of behavior. [ABSTRACT FROM AUTHOR]

Dendritic spines are considered a morphological proxy for excitatory synapses, rendering them a target of many different lines of research. Over recent years, it has become possible to simultaneously image large numbers of dendritic spines in 3D volumes of neural tissue. In contrast, currently no automated method for 3D spine detection exists that comes close to the detection performance reached by human experts. However, exploiting such datasets requires new tools for the fully automated detection and analysis of large numbers of spines. Here, we developed an efficient analysis pipeline to detect large numbers of dendritic spines in volumetric fluorescence imaging data acquired by two-photon imaging in vivo. The core of our pipeline is a deep convolutional neural network that was pretrained on a general-purpose image library and then optimized on the spine detection task. This transfer learning approach is data efficient while achieving a high detection precision. To train and validate the model we generated a labeled dataset using five human expert annotators to account for the variability in human spine detection. The pipeline enables fully automated dendritic spine detection reaching a performance slightly below that of the human experts. Our method for spine detection is fast, accurate and robust, and thus well suited for large-scale datasets with thousands of spines. The code is easily applicable to new datasets, achieving high detection performance, even without any retraining or adjustment of model parameters. [ABSTRACT FROM AUTHOR]

Enhancers are important cis-regulatory elements controlling cell-type specific expression patterns of genes. Furthermore, combinations of enhancers and minimal promoters are utilized to construct small, artificial promoters for gene delivery vectors. Large-scale functional screening methodology to construct genomic maps of enhancer activities has been successfully established in cultured cell lines, however, not yet applied to terminally differentiated cells and tissues in a living animal. Here, we transposed the Self-Transcribing Active Regulatory Region Sequencing (STARR-seq) technique to the mouse brain using adeno-associated-viruses (AAV) for the delivery of a highly complex screening library tiling entire genomic regions and covering in total 3 Mb of the mouse genome. We identified 483 sequences with enhancer activity, including sequences that were not predicted by DNA accessibility or histone marks. Characterizing the expression patterns of fluorescent reporters controlled by nine candidate sequences, we observed differential expression patterns also in sparse cell types. Together, our study provides an entry point for the unbiased study of enhancer activities in organisms during health and disease. [ABSTRACT FROM AUTHOR]

Boredom has been defined as an aversive mental state that is induced by the disability to engage in satisfying activity, most often experienced in monotonous environments. However, current understanding of the situational factors inducing boredom and driving subsequent behavior remains incomplete. Here, we introduce a two-alternative forced-choice task coupled with sensory stimulation of different degrees of monotony. We find that human subjects develop a bias in decision-making, avoiding the more monotonous alternative that is correlated with self-reported state boredom. This finding was replicated in independent laboratory and online experiments and proved to be specific for the induction of boredom rather than curiosity. Furthermore, using theoretical modeling we show that the entropy in the sequence of individually experienced stimuli, a measure of information gain, serves as a major determinant to predict choice behavior in the task. With this, we underline the relevance of boredom for driving behavioral responses that ensure a lasting stream of information to the brain. [ABSTRACT FROM AUTHOR]

The interphase nucleus is functionally organized in active and repressed territories defining the transcriptional status of the cell. However, it remains poorly understood how the nuclear architecture of neurons adapts in response to behaviorally relevant stimuli that trigger fast alterations in gene expression patterns. Imaging of fluorescently tagged nucleosomes revealed that pharmacological manipulation of neuronal activity in vitro and auditory cued fear conditioning in vivo induce nucleus-scale restructuring of chromatin within minutes. Furthermore, the acquisition of auditory fear memory is impaired after infusion of a drug into auditory cortex which blocks chromatin reorganization in vitro. We propose that active chromatin movements at the nucleus scale act together with local gene-specific modifications to enable transcriptional adaptations at fast time scales. Introducing a transgenic mouse line for photolabeling of histones, we extend the realm of systems available for imaging of chromatin dynamics to living animals. [ABSTRACT FROM AUTHOR]

When trying to gain intuitions about the computations implemented in neural circuits, we often use comparisons with electronic circuits. However, one fundamental difference to hard-wired electronic circuits is that the structure of neural circuits undergoes constant remodeling. Here, we discuss recent findings highlighting the dynamic nature of neural circuits and the underlying mechanisms. The dynamics of neural circuits follows rules that explain steady state statistics of synaptic properties observed at a single time point. Interestingly, these rules allow the prediction of future network states and extend the insights gained from serial sectioning electron microscopy of brain samples, which inherently provides information from only a single time point. We argue how the connectome's dynamic nature can be reconciled with stable functioning and long-term memory storage and how it may even benefit learning. [ABSTRACT FROM AUTHOR]

Dynamic remodeling of connectivity is a fundamental feature of neocortical circuits. Unraveling the principles underlying these dynamics is essential for the understanding of how neuronal circuits give rise to computations. Moreover, as complete descriptions of the wiring diagram in cortical tissues are becoming available, deciphering the dynamic elements in these diagrams is crucial for relating them to cortical function. Here, we used chronic in vivo two-photon imaging to longitudinally follow a few thousand dendritic spines in the mouse auditory cortex to study the determinants of these spines' lifetimes. We applied nonlinear regression to quantify the independent contribution of spine age and several morphological parameters to the prediction of the future survival of a spine. We show that spine age, size, and geometry are parameters that can provide independent contributions to the prediction of the longevity of a synaptic connection. In addition, we use this framework to emulate a serial sectioning electron microscopy experiment and demonstrate how incorporation of morphological information of dendritic spines from a single time-point allows estimation of future connectivity states. The distinction between predictable and nonpredictable connectivity changes may be used in the future to identify the specific adaptations of neuronal circuits to environmental changes. The full dataset is publicly available for further analysis. [ABSTRACT FROM AUTHOR]

Both in humans and in animals, different individuals may learn the same task with strikingly different speeds; however, the sources of this variability remain elusive. In standard learning models, interindividual variability is often explained by variations of the learning rate, a parameter indicating how much synapses are updated on each learning event. Here, we theoretically show that the initial connectivity between the neurons involved in learning a task is also a strong determinant of how quickly the task is learned, provided that connections are updated in a multiplicative manner. To experimentally test this idea, we trained mice to perform an auditory Go/NoGo discrimination task followed by a reversal to compare learning speed when starting from naive or already trained synaptic connections. All mice learned the initial task, but often displayed sigmoid-like learning curves, with a variable delay period followed by a steep increase in performance, as often observed in operant conditioning. For all mice, learning was much faster in the subsequent reversal training. An accurate fit of all learning curves could be obtained with a reinforcement learning model endowed with a multiplicative learning rule, but not with an additive rule. Surprisingly, the multiplicative model could explain a large fraction of the interindividual variability by variations in the initial synaptic weights. Altogether, these results demonstrate the power of multiplicative learning rules to account for the full dynamics of biological learning and suggest an important role of initial wiring in the brain for predispositions to different tasks. [ABSTRACT FROM AUTHOR]

Long-lasting changes in synaptic connections induced by relevant experiences are believed to represent the physical correlate of memories. Here, we combined chronic in vivo two-photon imaging of dendritic spines with auditory-cued classical conditioning to test if the formation of a fear memory is associated with structural changes of synapses in the mouse auditory cortex. We find that paired conditioning and unpaired conditioning induce a transient increase in spine formation or spine elimination, respectively. A fraction of spines formed during paired conditioning persists and leaves a long-lasting trace in the network. Memory recall triggered by the reexposure of mice to the sound cue did not lead to changes in spine dynamics. Our findings provide a synaptic mechanism for plasticity in sound responses of auditory cortex neurons induced by auditory-cued fear conditioning; they also show that retrieval of an auditory fear memory does not lead to a recapitulation of structural plasticity in the auditory cortex as observed during initial memory consolidation. [ABSTRACT FROM AUTHOR]

Sensory stimuli have long been thought to be represented in the brain as activity patterns of specific neuronal assemblies. However, we still know relatively little about the long-term dynamics of sensory representations. Using chronic in vivo calcium imaging in the mouse auditory cortex, we find that sensory representations undergo continuous recombination, even under behaviorally stable conditions. Auditory cued fear conditioning introduces a bias into these ongoing dynamics, resulting in a long-lasting increase in the number of stimuli activating the same subset of neurons. This plasticity is specific for stimuli sharing representational similarity to the conditioned sound prior to conditioning and predicts behaviorally observed stimulus generalization. Our findings demonstrate that learning-induced plasticity leading to a representational linkage between the conditioned stimulus and non-conditioned stimuli weaves into ongoing dynamics of the brain rather than acting on an otherwise static substrate. [Display omitted] • Chronic in vivo two-photon calcium imaging of >36k neurons in mouse auditory cortex • Drift of auditory representations despite stable environmental conditions • Increased co-activation of neurons by CS+ and nonCS+ sounds after conditioning • Degree of co-activation is predictive of behavioral generalization Using longitudinal calcium imaging of sound-evoked activity patterns in the mouse auditory cortex, Aschauer et al. observe increased formation of associations between sound representations following auditory-cued fear conditioning. The degree of newly formed associations predicted behavioral generalization between conditioned and non-conditioned sounds. [ABSTRACT FROM AUTHOR]

: Evolutionarily conserved, nonvisual opsins appear to endow specific interneurons and motorneurons of the vertebrate brain with light sensitivity, suggesting that environmental light may be able to modulate information processing. [ABSTRACT FROM AUTHOR]

One of the biggest tasks in neuroscience is to explain activity patterns of individual neurons during behavior by their cellular characteristics and their connectivity within the neuronal network. To greatly facilitate linking in vivo experiments with a more detailed molecular or physiological analysis in vitro, we have generated and characterized genetically modified mice expressing photoactivatable GFP (PA-GFP) that allow conditional photolabeling of individual neurons. Repeated photolabeling at the soma reveals basic morphological features due to diffusion of activated PA-GFP into the dendrites. Neurons photolabeled in vivo can be re-identified in acute brain slices and targeted for electrophysiological recordings. We demonstrate the advantages of PA-GFP expressing mice by the correlation of in vivo firing rates of individual neurons with their expression levels of the immediate early gene c-fos. Generally, the mouse models described in this study enable the combination of various analytical approaches to characterize living cells, also beyond the neurosciences. [ABSTRACT FROM AUTHOR]

What fundamental properties of synaptic connectivity in the neocortex stem from the ongoing dynamics of synaptic changes? In this study, we seek to find the rules shaping the stationary distribution of synaptic efficacies in the cortex. To address this question, we combined chronic imaging of hundreds of spines in the auditory cortex of mice in vivo over weeks with modeling techniques to quantitatively study the dynamics of spines, the morphological correlates of excitatory synapses in the neocortex. We found that the stationary distribution of spine sizes of individual neurons can be exceptionally well described by a log-normal function. We furthermore show that spines exhibit substantial volatility in their sizes at timescales that range from days to months. Interestingly, the magnitude of changes in spine sizes is proportional to the size of the spine. Such multiplicative dynamics are in contrast with conventional models of synaptic plasticity, learning, and memory, which typically assume additive dynamics. Moreover, we show that the ongoing dynamics of spine sizes can be captured by a simple phenomenological model that operates at two timescales of days and months. This model converges to a log-normal distribution, bridging the gap between synaptic dynamics and the stationary distribution of synaptic efficacies. [ABSTRACT FROM AUTHOR]

The activity-dependent regulation of α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid (AMPA)-type glutamate receptors and the stabilization of synapses are critical to synaptic development and plasticity. One candidate molecule implicated in maturation, synaptic strengthening, and plasticity is PSD-95. Here we find that acute knockdown of PSD-95 in brain slice cultures by RNAi arrests the normal development of synaptic structure and function that is driven by spontaneous activity. Surprisingly, PSD-95 is not necessary for the induction and early expression of long-term potentiation (LTP). However, knockdown of PSD-95 leads to smaller increases in spine size after chemically induced LTP. Furthermore, although at this age spine turnover is normally low and LTP produces a transient increase, in cells with reduced PSD-95 spine turnover is high and remains increased after LTP. Taken together, our data support a model in which appropriate levels of PSD-95 are required for activity-dependent synapse stabilization after initial phases of synaptic potentiation. [ABSTRACT FROM AUTHOR]

Central glutamatergic synapses are thought to initially form as immature, so-called silent synapses showing exclusively N-methyl-d-aspartate receptor-mediated synaptic transmission. Postsynaptic insertion of alpha-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid receptors during further development leads to a conversion into functional, mature synapses. Here, we tested the hypothesis that, according to the "inside first-outside last" pattern of neocortical layer formation and synaptogenesis, pyramidal cells in the superficial layers might show a higher fraction of silent synapses compared with pyramidal cells in the deep layers. We performed an electrophysiological analysis of glutamatergic synapses in acute rat visual cortex slices during postnatal development. In layer VI pyramidal neurons the incidence of silent synapses was high during the first postnatal week and strongly declined during further development. Surprisingly, in superficial cortical plate pyramidal neurons (immature layers II/III), the fraction of silent synapses was initially very low and increased up to the second postnatal week. Thereafter, a similar decline as found in layer VI pyramidal neurons was observed. Thus the developmental regulation of silent synapses was clearly different in pyramidal neurons from different neocortical layers. The almost complete absence of silent synapses at early stages in layer II/III pyramidal neurons indicates that an initially formed subset of synapses is constitutively functional. This might be important to enable spontaneous activity and latter activity-dependent maturation of synapses. [ABSTRACT FROM AUTHOR]

Abstract Long-term synaptic plasticity is thought to underlie synaptic reorganization phenomena that occur during neocortical development. Recently, it has been proposed, that the functional induction of AMPA receptors at silent glutamatergic synapses is of major importance in activity-dependent, developmental plasticity. To investigate the mechanisms involved in the developmental regulation of silent synapses, we analysed the functional maturation of the thalamocortical projection in culture. A large proportion of the thalamocortical synapses were functionally silent at an early stage in vitro. During further differentiation, the incidence of silent synapses decreased drastically, indicating a conversion of silent into functional synapses. Chronic blockade of spontaneous network activity by addition of tetrodotoxin to the culture medium strongly impaired this developmental maturation. Moreover, the developmental decline in the proportion of silent synapses was dramatically accelerated by chronic addition of the neurotrophic factor, insulin. This effect of insulin was partly dependent on spontaneous activity. Thus, insulin appears to be involved in the modulation of long-term developmental plasticity at immature glutamatergic synapses. [ABSTRACT FROM AUTHOR]

Salience is a broad and widely used concept in neuroscience whose neuronal correlates, however, remain elusive. In behavioral conditioning, salience is used to explain various effects, such as stimulus overshadowing, and refers to how fast and strongly a stimulus can be associated with a conditioned event. Here, we identify sounds of equal intensity and perceptual detectability, which due to their spectro-temporal content recruit different levels of population activity in mouse auditory cortex. When using these sounds as cues in a Go/NoGo discrimination task, the degree of cortical recruitment matches the salience parameter of a reinforcement learning model used to analyze learning speed. We test an essential prediction of this model by training mice to discriminate light-sculpted optogenetic activity patterns in auditory cortex, and verify that cortical recruitment causally determines association or overshadowing of the stimulus components. This demonstrates that cortical recruitment underlies major aspects of stimulus salience during reinforcement learning. Sounds vary in the strength of behavioural conditioning they can evoke, a property attributed to stimulus salience. Here, the authors show that stimulus salience the overall level of neuronal activity recruited in the auditory cortex is strongly related with its reinforcing strength. [ABSTRACT FROM AUTHOR]

Recombinant Adeno-associated virus vectors (rAAV) are widely used for gene delivery and multiple naturally occurring serotypes have been harnessed to target cells in different tissues and organs including the brain. Here, we provide a detailed and quantitative analysis of the transduction profiles of rAAV vectors based on six of the most commonly used serotypes (AAV1, AAV2, AAV5, AAV6, AAV8, AAV9) that allows systematic comparison and selection of the optimal vector for a specific application. In our studies we observed marked differences among serotypes in the efficiency to transduce three different brain regions namely the striatum, hippocampus and neocortex of the mouse. Despite the fact that the analyzed serotypes have the general ability to transduce all major cell types in the brain (neurons, microglia, astrocytes and oligodendrocytes), the expression level of a reporter gene driven from a ubiquitous promoter varies significantly for specific cell type / serotype combinations. For example, rAAV8 is particularly efficient to drive transgene expression in astrocytes while rAAV9 appears well suited for the transduction of cortical neurons. Interestingly, we demonstrate selective retrograde transport of rAAV5 along axons projecting from the ventral part of the entorhinal cortex to the dentate gyrus. Furthermore, we show that self-complementing rAAV can be used to significantly decrease the time required for the onset of transgene expression in the mouse brain. [ABSTRACT FROM AUTHOR]