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Results for “Neuroscience”

Search indexed bioRxiv preprints in genomics, neuroscience, cell biology and bioinformatics. Read source abstracts and check manuscript versions; preprints are not peer reviewed.

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At least 613 records · Page 34Linked to original sources

bioRxiv2015

Similarity-based fusion of MEG and fMRI reveals spatio-temporal dynamics in human cortex during visual object recognition

Every human cognitive function, such as visual object recognition, is realized in a complex spatio-temporal activity pattern in the brain. Current brain imaging techniques in isolation cannot resolve the brains spatio-temporal dynamics because they provide either high spatial or temporal resolution but not both. To overcome this limitation, we developed a new integration approach that uses representational similarities to combine measurements from different imaging modalities - magnetoencephalography (MEG) and functional MRI (fMRI) - to yield a spatially and temporally integrated characterization of neuronal activation. Applying this approach to two independent MEG-fMRI data sets, we observed that neural activity first emerged in the occipital pole at 50-80ms, before spreading rapidly and progressively in the anterior direction along the ventral and dorsal visual streams. These results provide a novel and comprehensive, spatio-temporally resolved view of the rapid neural dynamics during the first few hundred milliseconds of object vision. They further demonstrate the feasibility of spatially unbiased representational similarity based fusion of MEG and fMRI, promising new insights into how the brain computes complex cognitive functions.

Neuroscience↗

bioRxiv2015

Expression weighted cell type enrichments reveal genetic and cellular nature of major brain disorders

The cell types that trigger the primary pathology in many brain diseases remain largely unknown. One route to understanding the primary pathological cell type for a particular disease is to identify the cells expressing susceptibility genes. Although this is straightforward for monogenic conditions where the causative mutation may alter expression of a cell type specific marker, methods are required for the common polygenic disorders. We developed the Expression Weighted Cell Type Enrichment (EWCE) method that uses single cell transcriptomes to generate the probability distribution associated with a gene list having an average level of expression within a cell type. Following validation, we applied EWCE to human genetic data from cases of epilepsy, Schizophrenia, Autism, Intellectual Disability, Alzheimers disease, Multiple Sclerosis and anxiety disorders. Genetic susceptibility primarily affected microglia in Alzheimers and Multiple Sclerosis; was shared between interneurons and pyramidal neurons in Autism and Schizophrenia; while intellectual disabilities and epilepsy were attributable to a range of cell-types, with the strongest enrichment in interneurons. We hypothesized that the primary cell type pathology could trigger secondary changes in other cell types and these could be detected by applying EWCE to transcriptome data from diseased tissue. In Autism, Schizophrenia and Alzheimers disease we find evidence of pathological changes in all of the major brain cell types. These findings give novel insight into the cellular origins and progression in common brain disorders. The methods can be applied to any tissue and disorder and have applications in validating mouse models.

Neuroscience↗

bioRxiv2015

Cell-type and state-dependent synchronization among rodent areas S1BF, V1, perirhinal cortex and hippocampus CA1

Beta and gamma rhythms have been hypothesized to be involved in global and local coordination of neuronal activity, respectively. Here, we investigated how cells in rodent area S1BF are entrained by rhythmic fluctuations at various frequencies within the local area and in connected areas, and how this depends on behavioral state and cell type. We performed simultaneous extracellular field and unit recordings in four connected areas of the freely moving rat (S1BF, V1M, perirhinal cortex, CA1). S1BF spiking activity was strongly entrained by both beta and gamma S1BF oscillations, which were associated with deactivations and activations, respectively. We identified multiple classes of fast spiking and excitatory cells in S1BF, which showed prominent differences in rhythmic entrainment and in the extent to which phase locking was modulated by behavioral state. Using an additional dataset acquired by whole-cell recordings in head-fixed mice, these cell classes could be compared with identified phenotypes showing gamma rhythmicity in their membrane potential. We next examined how S1BF cells were entrained by rhythmic fluctuations in connected brain areas. Gamma-synchronization was detected in all four areas, however we did not detect significant gamma coherence among these areas. Instead, we only found long-range coherence in the theta-beta range among these areas. In contrast to local S1BF synchronization, we found long-range S1BF-spike to CA1-LFP synchronization to be homogeneous across inhibitory and excitatory cell types. These findings suggest distinct, cell-type contributions of low and high-frequency synchronization to intra- and inter-areal neuronal interactions.

Neuroscience↗

bioRxiv2015

Automated long-term recording and analysis of neural activity in behaving animals

Addressing how neural circuits underlie behavior is routinely done by measuring electrical activity from single neurons during experimental sessions. While such recordings yield snapshots of neural dynamics during specified tasks, they are ill-suited for tracking single-unit activity over longer timescales relevant for most developmental and learning processes, or for capturing neural dynamics across different behavioral states. Here we describe an automated platform for continuous long-term recordings of neural activity and behavior in freely moving animals. An unsupervised algorithm identifies and tracks the activity of single units over weeks of recording, dramatically simplifying the analysis of large datasets. Months-long recordings from motor cortex and striatum made and analyzed with our system revealed remarkable stability in basic neuronal properties, such as firing rates and inter-spike interval distributions. Interneuronal correlations and the representation of different movements and behaviors were similarly stable. This establishes the feasibility of high-throughput long-term extracellular recordings in behaving animals.\n\nHighlightsO_LIWe record neural activity and behavior in rodents continuously (24/7) over months\nC_LIO_LIAn automated spike-sorting method isolates and tracks single units over many weeks\nC_LIO_LINeural dynamics and motor representations are highly stable over long timescales\nC_LIO_LINeurons cluster into functional groups based on their activity in different states\nC_LI\n\neTOC BlurbDhawale et al. describe experimental infrastructure for recording neural activity and behavior continuously over months in freely moving rodents. A fully automated spike-sorting algorithm allows single units to be tracked over weeks of recording. Recordings from motor cortex and striatum revealed a remarkable long-term stability in both single unit activity and network dynamics.

Neuroscience↗

bioRxiv2015

Multidimensional Heritability Analysis of Neuroanatomical Shape

In the dawning era of large-scale biomedical data, multidimensional phenotype vectors will play an increasing role in examining the genetic underpinnings of brain features, behavior and disease. For example, shape measurements derived from brain MRI scans are multidimensional geometric descriptions of brain structure and provide an alternate class of phenotypes that remains largely unexplored in genetic studies. Here we extend the concept of heritability to multidimensional traits, and present the first comprehensive analysis of the heritability of neuroanatomical shape measurements across an ensemble of brain structures based on genome-wide SNP and MRI data from 1,320 unrelated, young and healthy individuals. We replicate our findings in an extended twin sample from the Human Connectome Project (HCP). Our results demonstrate that neuroanatomical shape can be significantly heritable, above and beyond volume, and can serve as a complementary phenotype to study the genetic determinants and clinical relevance of brain structure.

Neuroscience↗

bioRxiv2015

Flexibility in motor timing constrains the topology and dynamics of pattern generator circuits

Temporally precise movement patterns underlie many motor skills and innate actions, yet the flexibility with which the timing of such stereotyped behaviors can be modified is poorly understood. To probe this, we induced adaptive changes to the temporal structure of birdsong. We find that the duration of specific song segments can be modified without affecting the timing in other parts of the song. We derive formal prescriptions for how neural networks can implement such flexible motor timing. We find that randomly connected recurrent networks, a common approximation for how neocortex is wired, do not generally conform to these, though certain implementations can approximate them. We show that feedforward networks, by virtue of their one-to-one mapping between network activity and time, are better suited. Our study provides general prescriptions for pattern generator networks that implement flexible motor timing, an important aspect of many motor skills, including birdsong and human speech.

Neuroscience↗

bioRxiv2015

Homeostatic activity-dependent tuning of recurrent networks for robust propagation of activity

Developing neuronal networks display spontaneous rhythmic bursts of action potentials that are necessary for circuit organization and tuning. While spontaneous activity has been shown to instruct map formation in sensory circuits, it is unknown whether it plays a role in the organization of motor networks that produce rhythmic output. Using computational modeling we investigate how recurrent networks of excitatory and inhibitory neuronal populations assemble to produce robust patterns of unidirectional and precisely-timed propagating activity during organism locomotion. One example is provided by the motor network in Drosophila larvae, which generates propagating peristaltic waves of muscle contractions during crawling. We examine two activity-dependent models which tune weak network connectivity based on spontaneous activity patterns: a Hebbian model, where coincident activity in neighboring populations strengthens connections between them; and a homeostatic model, where connections are homeostatically regulated to maintain a constant level of excitatory activity based on spontaneous input. The homeostatic model tunes network connectivity to generate robust activity patterns with the appropriate timing relationships between neighboring populations. These timing relationships can be modulated by the properties of spontaneous activity suggesting its instructive role for generating functional variability in network output. In contrast, the Hebbian model fails to produce the tight timing relationships between neighboring populations required for unidirectional activity propagation, even when additional assumptions are imposed to constrain synaptic growth. These results argue that homeostatic mechanisms are more likely than Hebbian mechanisms to tune weak connectivity based on local activity patterns in a recurrent network for rhythm generation and propagation.

Neuroscience↗

bioRxiv2015

Putting value in context: A role for context memory in decisions for reward.

How does experience inform decisions? In episodic sampling, decisions are guided by a few episodic memories of past choices. This process can yield choice patterns similar to model-free Reinforcement Learning (RL); however, samples can vary from trial to trial, causing decisions to vary. Here, we show that context retrieved during episodic sampling can cause choice behavior to deviate sharply from the predictions of RL. Specifically, we show that, when a given memory is sampled, choices (in the present) are influenced by the properties of other decisions made in the same context as the sampled event. This effect is mediated by fMRI measures of context retrieval on each trial, suggesting a mechanism whereby cues trigger retrieval of context, which then triggers retrieval of other decisions from that context. This result establishes a new avenue by which experience can guide choice, and as such has broad implications for the study of decisions.

Neuroscience↗

bioRxiv2015

Linking stimuli and behavior with fast near-whole brain recordings in adult Drosophila

We describe a method to record near-whole brain activity in behaving adult flies. Pan-neuronal calcium and voltage sensors were imaged at high speed with light field microscopy. Functional maps were then extracted by principal component analysis and independent component analysis. Their characteristic shapes match the anatomy of sub-neuropil regions and in some cases a specific neuron type. Responses to light and odor produced activity patterns consistent with previous techniques. Furthermore, the method detected activity linked to behavior as well as a previously uncharacterized pattern of spontaneous activity in the central complex.

Neuroscience↗

bioRxiv2015

Principles of ipsilateral and contralateral cortico-cortical connectivity in the mouse

Structural connectivity among cortical areas provides the substrate for information exchange in the brain and is characterized by the presence or absence of connections between specific areas. What principles govern this cortical wiring diagram? Here, we investigate the relation of physical distance and cytoarchitecture with the connectional architecture of the mouse cortex. Moreover, we examine the relation between patterns of ipsilateral and contralateral connections. Our analysis reveals a mirrored and attenuated organization of contralateral connections when compared to ipsilateral connections. Both spatial proximity and cytoarchitectonic similarity of cortical areas are related to the presence or absence of connections. Notably, our analysis demonstrated that these factors conjointly relate better to cortico-cortical connectivity than each factor in isolation, and that the two factors contribute differently to ipsilateral and contralateral connectivity. Distance is more tightly related to the presence or absence of ipsilateral connections, but its contribution greatly diminishes for contralateral connections, while the contribution of cytoarchitectonic similarity remains stable. Our results, conjointly with similar findings in the cat and macaque cortex, suggest that a common set of principles underlies the macroscale wiring of mammalian brains.

Neuroscience↗

bioRxiv2015

What’s past is present: Reminders of past choices bias decisions for reward in humans

We provide evidence that decisions are made by consulting memories for individual past experiences, and that this process can be biased in favor of past choices using incidental reminders. First, in a standard rewarded choice task, we show that a model that estimates value at decision-time using individual samples of past outcomes fits choices and decision-related neural activity better than a canonical incremental learning model. In a second experiment, we bias this sampling process by incidentally reminding participants of individual past decisions. The next decision after a reminder shows a strong influence of the action taken and value received on the reminded trial. These results provide new empirical support for a decision architecture that relies on samples of individual past choice episodes rather than incrementally averaged rewards in evaluating options, and has suggestive implications for the underlying cognitive and neural mechanisms.

Neuroscience↗

bioRxiv2015

On the relation between face and object recognition in developmental prosopagnosia: Systematic association but no dissociation.

There is an ongoing debate about whether face recognition and object recognition constitute separate domains. Clarification of this issue can have important theoretical implications as face recognition is often used as a prime example of domain-specificity in mind and brain. An important source of input to this debate comes from studies of individuals with developmental prosopagnosia, suggesting that face recognition can be selectively impaired. We put the selectivity-hypothesis to test by assessing the performance of 10 subjects with developmental prosopagnosia on demanding tests of visual object processing involving both regular and degraded drawings. None of the individuals exhibited a dissociation between face and object recognition, and as a group they were significantly more affected by degradation of objects than control participants. Importantly, we also find positive correlations between the severity of the face recognition impairment and the degree of impaired performance with degraded objects. This suggests that the face and object deficits are systematically related rather than coincidental. We conclude that at present, there is no strong evidence in the literature on developmental prosopagnosia supporting domain-specific accounts of face recognition.

Neuroscience↗

bioRxiv2015

Molecular organization of CA1 interneuron classes

GABAergic interneurons are key regulators of hippocampal circuits, but our understanding of the diversity and classification of these cells remains controversial. Here we analyze the organization of interneurons in the CA1 area, using the combinatorial patterns of gene expression revealed by single-cell mRNA sequencing (scRNA-seq). This analysis reveals a 5-level hierarchy of cell classes. Most of the predicted classes correspond closely to known interneuron types, allowing us to predict a large number of novel molecular markers of these classes. In addition we identified a major new interneuron population localized at the border of strata radiatum and lacunosum-moleculare that we term \"R2C2 cells\" after their characteristic combinatorial expression of Rgs12, Reln, Cxcl14, and Cpne5. Several predictions of this classification scheme were verified using in situ hybridization and immunohistochemistry, providing further confidence in the gene expression patterns and novel classes predicted by the single cell data.

Neuroscience↗

bioRxiv2015

Neural oscillations as a signature of efficient coding in the presence of synaptic delays

Cortical networks exhibit \"global oscillations\", in which neural spike times are entrained to an underlying oscillatory rhythm, but where individual neurons fire irregularly, on only a fraction of cycles. While the network dynamics underlying global oscillations have been well characterised, their function is debated. Here, we show that such global oscillations are a direct consequence of optimal efficient coding in spiking networks with synaptic delays. To avoid firing unnecessary spikes, neurons need to share information about the network state. Ideally, membrane potentials should be strongly correlated and reflect a \"prediction error\" while the spikes themselves are uncorrelated and occur rarely. We show that the most efficient representation is achieved when: (i) spike times are entrained to a global Gamma rhythm (implying a consistent representation of the error); but (ii) few neurons fire on each cycle (implying high efficiency), while (iii) excitation and inhibition are tightly balanced. This suggests that cortical networks exhibiting such dynamics are tuned to achieve a maximally efficient population code.

Neuroscience↗

bioRxiv2015

Octopamine release impairs courtship conditioning in Drosophila melanogaster

Octopamine is known to have an appetitive role in odor conditioning paradigms in Drosophila melanogaster. We wanted to test whether octopamine could also act as an appetitive stimulus in courtship conditioning, a paradigm in which training with an unreceptive female (such as a decapitated virgin) causes a subsequent decrease in courtship behavior in male Drosophila. To control octopamine release, we used the Tdc2-Gal4 and UAS-dTRPa1 genes in conjunction to depolarize octopaminergic neurons at 27 C in experimental flies. We hypothesized that inducing octopamine release during courtship training would decrease the aversive impact of training and cause less subsequent suppression of courtship behavior. Our findings confirmed this hypothesis: Tdc2-Gal4/UAS-dTRPa1 flies trained at 27 degrees showed significantly more courtship behavior than controls during testing, and in fact showed no significant effect of courtship training. This confirms that octopamine release counteracts the aversive stimulus of failure to copulate, indicating that octopamine may have an appetitive role in courtship.

Neuroscience↗

bioRxiv2015

Hippocampal circuit abnormalities in MeCP2+/- mouse model of Rett syndrome

Rett syndrome (RTT) has a complex developmental course over childhood and adolescence. Patients with RTT often have a pre-symptomatic period with no or little outward signs of the disorder, followed by developmental arrest and regression. Following regression, the individuals condition is not static, as they often progress into defined stages with unique neurological symptoms. Similarly, the progression of RTT-like symptoms in female mice heterozygous for a null-mutation has a prodromal and symptomatic period. Change in functional local circuit connectivity was studied using hippocampal slices, assaying Schaffer evoked activity in area CA1 using fast voltage sensitive dye imaging. With this technique the local functional interactions between the excitatory and inhibitory components of the circuit can be characterized. The prodromal period was associated with a shift in extent of excitation into the stratum oriens of the hippocampus and reduced sensitivity to changes in divalent cation concentration. These data suggest that hyperexcitability of the hippocampus at the circuit level may contribute to the prodromal reduction in cognitive performance and the onset of developmental regression.

Neuroscience↗

bioRxiv2015

Transition between functional regimes in an integrate-and-fire network model of the thalamus

The thalamus is a key brain element in the processing of sensory information. During the sleep and awake states, this brain area is characterized by the presence of two distinct dynamical regimes: in the sleep state activity is dominated by spindle oscillations (7 - 15 Hz) weakly affected by external stimuli, while in the awake state the activity is primarily driven by external stimuli. Here we develop a simple and computationally efficient model of the thalamus that exhibits two dynamical regimes with different information-processing capabilities, and study the transition between them. The network model includes glutamatergic thalamocortical (TC) relay neurons and gabaergic reticular (RE) neurons described by adaptative integrate-and-fire models in which spikes are induced by either depolarization or hyperpolarization rebound. We found a range of connectivity conditions under which the thalamic network composed by these neurons displays the two aforementioned dynamical regimes. Our results show that TC-RE loops generate spindle-like oscillations and that a critical value of clustering in the RE-RE connections is necessary for the coexistence of the two regimes. We also observe that the transition between the two regimes occurs when the external excitatory input on TC neurons (mimicking sensory stimulation) is large enough to cause a significant fraction of them to switch from hyperpolarization-rebound-driven firing to depolarization-driven firing. Overall, our model gives a novel and clear description of the role that the two types of neurons and their connectivity play in the dynamical regimes observed in the thalamus, and in the transition between them. These results pave the way for the development of efficient models of the transmission of sensory information from periphery to cortex.\n\nAuthor SummaryThe thalamus is known to exhibit two clearly distinct dynamical regimes with different functionalities. During slow-wave sleep the thalamus is dominated by internal activity and is hardly sensitive to external stimuli. In contrast, in the awake state, the thalamus modulates its activity according to the stimuli coming from the periphery. Here we study the conditions regulating the transition between these two states. To that end we implement a simple yet biologically realistic neuronal network model of the thalamus, based on single-neuron models that reproduce the properties of the two prominent types of thalamic neurons, namely thalamocortical relay cells and reticular neurons. We found that when reticular neurons are clustered the network exhibits two distinct dynamical regimes; one dominated by oscillations and insensitive to external stimuli (like sleep) and one sensitive to them (like wake). Moreover we found that the transition between the two regimes is due to the increase of the external excitatory input (corresponding to stronger sensory stimuli).

Neuroscience↗

bioRxiv2015

Pain to remember: a single incidental association with pain leads to increased memory for neutral items one year later

Negative and positive experiences can exert a strong influence on later memory. Our emotional experiences are composed of many different elements - people, place, things - most of them neutral. Do emotional experiences lead to enhanced long-term for these neutral elements as well? Demonstrating a lasting effect of emotion on memory is particularly important if memory for emotional events is to adaptively guide behavior days, weeks, or years later. We thus tested whether aversive experiences modulate very long-term episodic memory in an fMRI experiment. Participants experienced episodes of high or low pain in conjunction with the presentation of incidental, trial-unique neutral object pictures. In a scanned surprise immediate memory test, we found no effect of pain on recognition strength. Critically, in a follow-up memory test one year later we found that pain significantly enhanced memory. Neurally, we provide a novel demonstration of activity predicting memory one year later, whereby greater insula activity and more unique distributed patterns of insular activity in the initial session correlated with memory for pain-associated objects. Generally, our results suggest that pairing episodes with arousing negative stimuli may lead to very long-lasting memory enhancements.

Neuroscience↗