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Results for “animal behavior and cognition”

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 Read source abstracts and check manuscript versions; preprints are not peer reviewed.

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bioRxiv2016

Cell fusion proteins can rejuvenate adult dendritic trees

The aging brain undergoes structural changes, affecting brain homeostasis, neuronal function and consequently cognition. The complex architecture of dendritic arbors poses a challenge to understanding age-dependent morphological alterations, behavioral plasticity and remodeling following brain injury. Here, we use the PVD polymodal neurons of C. elegans as a model to study how aging affects neuronal plasticity. Using confocal live imaging of C. elegans PVD neurons, we demonstrate age-related progressive morphological alterations of intricate dendritic arbors. We show that insulin/IGF-1 receptor mutations (daf-2) fail to inhibit the progressive morphological aging of dendrites and do not prevent the minor decline in response to harsh touch during aging. We uncovered that PVD aging is characterized by a major decline in regenerative potential of dendrites following experimental laser dendrotomy. Furthermore, the remodeling of transected dendritic trees via AFF-1-mediated self-fusion can be restored in old animals by DAF-2 insulin/IGF-1 receptor mutations, and can be differentially reestablished by ectopic expression of AFF-1 fusion protein (fusogen). Thus, AFF-1 fusogen ectopically expressed in the PVD and mutations in DAF-2/IGF-1R, differentially rejuvenate some aspects of dendritic regeneration following injury.\n\nSummary statementEctopic expression of AFF-1 fusogen or low activity of IGF-1R/DAF-2 rejuvenate the regeneration potential of dendrites following injury in aging C. elegans

Neuroscience↗

bioRxiv2015

An integrated homeostatic reinforcement learning theory of motivation explains the transition to cocaine addiction

Drugs of abuse implicate both reward learning and homeostatic regulation mechanisms of the brain. Theories of addiction, thus, have mostly depicted this phenomenon as pathology in either habit-based learning system or homeostatic mechanisms. Showing the limits of those accounts, we hypothesize that compulsive drug seeking arises from drugs hijacking a system that integrates homeostatic regulation mechanism with goal-directed action/behavior. Building upon a recently developed homeostatic reinforcement learning theory, we present a computational theory proposing that cocaine reinforces goal-directed drug-seeking due to its rapid homeostatic corrective effect, whereas its chronic use induces slow and long-lasting changes in homeostatic setpoint. Our theory accounts for key behavioral and neurobiological features of addiction, most notably, escalation of cocaine use, drug-primed craving and relapse, and individual differences underlying susceptibility to addiction. The theory also generates unique predictions about the mechanisms of cocaine-intake regulation and about cocaine-primed craving and relapse that are confirmed by new experiments.\n\nSignificanceChronic use of addictive drugs renders increased motivation in planning to obtain and consume the drugs, despite their adverse social, occupational, and health consequences. It is as if addicts gradually develop a strong need for the drug and use their cognitive abilities and the knowledge of their environment in order to fulfil that need. In this paper, we build a mathematical model of this conception of addiction and show through quantitative simulations that such a model actually behaves in the same way that human addicts or laboratory animals that are exposed to cocaine behave. For example, the model shows gradually increasing motivation for drugs, relapse after long periods of abstinence, and individual differences in susceptibility to addiction.

Neuroscience↗

bioRxiv2017

A Neural Mechanism for the Opportunity Cost of Time

Recent interest has focused on a class of decision problems in which subjects encounter options serially and must decide when to leave an option in search of a better one, rather than directly comparing simultaneously presented options. Although such problems have a rich history in animal foraging and economics, relatively little is known about their neural substrates. Suggestively, however, a separate literature has argued that the key decision variable in these tasks - the opportunity cost of time, given by the average reward rate - may also govern behavioral vigor and may be reported by tonic dopamine (DA).\n\nIn this study, we test whether this putative dopaminergic opportunity cost signal plays an analogous role in serial decisions by examining the behavior of patients with Parkinsons disease (PD), on and off their DA replacement medication, in a patch-foraging task. In these tasks, subjects decisions about when to leave a depleting resource implicitly reflect their beliefs about the opportunity cost of time spent harvesting that resource. Consistent with the opportunity cost hypothesis, umedicated patients harvested longer than matched controls, and medication remediated this deficit. These effects were not explained by motor perseveration. Our results suggest a functional role for DA, and an associated cognitive deficit in PD, in a type of decision process that may be distinct from (but related to) the neuromodulators well studied roles in behavioral invigoration and learning from rewards.\n\nSignificance StatementThis study addresses two important questions whose answers are, unexpectedly, linked. First, what is the scope of cognitive functions of the neuromodulator dopamine, whose contributions - for instance, as assessed by both the motoric and more subtle cognitive deficits of patients with PD, which depletes dopamine - range from movement to reward and decision-making? Second, what are the neural mechanisms supporting an important but understudied class of problems, in which, rather than choose among a set of alternatives (like apples and oranges), one makes serial decisions about whether to stick with an option (like a job, or a mate) or seek another? We demonstrate a novel cognitive deficit in PD that integrates this function into the web of DAs contributions.

neuroscience↗

bioRxiv2016

Ventral tegmental area neurons use an ensemble code for representing information about ongoing actions

Multiple and unpredictable numbers of actions are often required to achieve a goal. In order to organize behavior and allocate effort so that optimal behavioral policies can be selected, it is necessary to continually monitor ongoing actions. Real-time processing of information related to actions and outcomes is typically assigned to the prefrontal cortex and basal ganglia, but also depends on midbrain regions, especially the ventral tegmental area (VTA). We were interested in how individual VTA neurons, as well as networks within the VTA, encode salient events when an unpredictable number of serial actions are required to obtain a reward. We recorded from ensembles of putative dopamine and non-dopamine neurons in the VTA as animals performed multiple cued trials in a recording session where, in each trial, serial actions were randomly rewarded. While averaging population activity did not reveal a response pattern, we observed that different neurons selectively tuned to low, medium, or high numbered actions in a trial. This preferential tuning of putative dopamine and non-dopamine VTA neurons to different subsets of actions in a trial allowed information about binned action number to be decoded from the ensemble activity. At the network level, tuning curve similarity was positively associated with action-evoked noise correlations, suggesting that action number selectivity reflects functional connectivity within these networks. Analysis of phasic responses to cue and reward revealed that the requirement to execute multiple and uncertain numbers of actions weakens both cue-evoked responses and cue-reward response correlation. The functional connectivity and ensemble coding scheme that we observe here may allow VTA neurons to cooperatively provide a real-time account of ongoing behavior. These computations may be critical to cognitive and motivational functions that have long been associated with VTA dopamine neurons.

neuroscience↗

bioRxiv2018

Stress matters: a double-blind, randomized controlled trial on the effects of a multispecies probiotic on neurocognition

Probiotics are microorganisms that can provide health benefits when consumed. Recent animal studies have demonstrated that probiotics can reverse gut microbiome-related alterations in anxiety and depression-like symptoms, in hormonal responses to stress, and in cognition. However, in humans, the effects of probiotics on neurocognition remain poorly understood and a causal understanding of the gut-brain link in emotion and cognition is lacking. We aimed to fill this gap by studying the effects of a probiotics intervention versus placebo on neurocognition in healthy human volunteers.\n\nWe set out to investigate the effects of a multispecies probiotic (Ecologic(R)Barrier) on specific neurocognitive measures of emotion reactivity, emotion regulation, and cognitive control using fMRI. Critically, we also tested whether the use of probiotics can buffer against the detrimental effects of acute stress on working memory. In a double blind, randomized, placebo-controlled, between-subjects intervention study, 58 healthy participants were tested twice, once before and once after 28 days of intervention with probiotics or placebo.\n\nProbiotics versus placebo did not affect emotion reactivity, emotion regulation, and cognitive control processes at brain or behavioral level, neither related self-report measures. However, relative to the placebo group, the probiotics group did show a significant stress-related increase in working memory performance after versus before supplementation (digit span backward, p=0.039, {eta}p2=.07). Interestingly, this change was associated with intervention-related neural changes in frontal cortex during cognitive control in the probiotics group, but not in the placebo group. Overall, our results show that neurocognitive effects of supplementation with a multispecies probiotic in healthy women become visible under challenging (stress) situations. Probiotics buffered against the detrimental effects of stress in terms of cognition, especially in those individuals with probiotics-induced changes in frontal brain regions during cognitive control.\n\nHighlightsO_LIWe ran a randomized placebo-controlled fMRI study with a multispecies probiotic\nC_LIO_LIProbiotics did not affect neurocognitive measures of emotion and cognitive control\nC_LIO_LIProbiotics did affect stress-related working memory and neural correlates\nC_LIO_LIProbiotics in healthy individuals can support cognition under stress\nC_LI

neuroscience↗

bioRxiv2018

Multichannel Silicon Probes for Laminar Cortical and Hippocampal Recordings in Large Animals.

Decoding laminar information across deep brain structures and cortical regions is necessary in order to understand the spatiotemporal ensembles that represent cognition and memory. Large animal models are essential for translational research due to their gyrencephalic neuroanatomy and significant white matter composition. One of the major obstacles to applying the approaches currently utilized in lower order animals are technical limitations in silicon probes, specifically a lack of long-length probes with appropriate stiffness to penetrate to deeper structures with minimal damage to the neural interface. We tested various solutions and designs of multichannel silicon probes developed for large animal electrophysiology by recording neurophysiological signals from deep laminar structures in an acute preparation and in chronically implanted awake behaving Yucatan pigs. Electrophysiological parameters of single units and local field potentials were analyzed to evaluate performance over time of given silicon probes in chronic implantations. The cross-sectional area of silicon probes was found to be a crucial determinant of silicon probes single unit performance over time, potentially due to reduction of damage to the neural interface. EDGE-style probes had the highest yields during intra-hippocampal recordings in pigs, making them the most suitable for chronic implantations and awake behavioral experimentation. Novel CAMB 64-channel EDGE-style probes with linear and poly-2 site arrangement tested acutely had optimal single unit separation and a denser sampling of the laminar structure, identifying them as potential candidates for chronic implantations with less cortical damage above the active portion of the probe. This study provides an analysis of multichannel silicon probes designed for large animal laminar electrophysiology of deep brain structures, and suggests that current designs are reaching the physical thresholds necessary for long-term (~ 1 month) recordings from laminar deep structures with single-unit resolution.

neuroscience↗

bioRxiv2018

A Framework for Intelligence and Cortical Function Based on Grid Cells in the Neocortex

How the neocortex works is a mystery. In this paper we propose a novel framework for understanding its function. Grid cells are neurons in the entorhinal cortex that represent the location of an animal in its environment. Recent evidence suggests that grid cell-like neurons may also be present in the neocortex. We propose that grid cells exist throughout the neocortex, in every region and in every cortical column. They define a location-based framework for how the neocortex functions. Whereas grid cells in the entorhinal cortex represent the location of one thing, the body relative to its environment, we propose that cortical grid cells simultaneously represent the location of many things. Cortical columns in somatosensory cortex track the location of tactile features relative to the object being touched and cortical columns in visual cortex track the location of visual features relative to the object being viewed. We propose that mechanisms in the entorhinal cortex and hippocampus that evolved for learning the structure of environments are now used by the neocortex to learn the structure of objects. Having a representation of location in each cortical column suggests mechanisms for how the neocortex represents object compositionality and object behaviors. It leads to the hypothesis that every part of the neocortex learns complete models of objects and that there are many models of each object distributed throughout the neocortex. The similarity of circuitry observed in all cortical regions is strong evidence that even high-level cognitive tasks are learned and represented in a location-based framework.

neuroscience↗

bioRxiv2018

Integration and multiplexing of positional and contextual information by the hippocampal network

The hippocampus is known to store cognitive representations, or maps, that encode both positional and contextual information, critical for episodic memories and functional behavior. How path integration and contextual cues are dynamically combined and processed by the hippocampus to maintain these representations accurate over time remains unclear. To answer this question, we propose a two-way data analysis and modeling approach to CA3 multi-electrode recordings of a moving rat submitted to rapid changes of contextual (light) cues, triggering back-and-forth instabitilies between two cognitive representations (Jezek et al, Nature 478, p 246 (2011)). We develop a dual neural activity decoder, capable of independently identifying the recalled cognitive map at high temporal resolution (comparable to theta cycle) and the position of the rodent given a map. Remarkably, position can be reconstructed at any time with an accuracy comparable to fixed-context periods, even during highly unstable periods. These findings provide evidence for the capability of the hippocampal neural activity to maintain an accurate encoding of spatial and contextual variables, while one of these variables undergoes rapid changes independently of the other. To explain this result we introduce an attractor neural network model for the hippocampal activity that process inputs from external cues and the path integrator. Our model allows us to make predictions on the frequency of the cognitive map instability, its duration, and the detailed nature of the place-cell population activity, which are validated by a further analysis of the data. Our work therefore sheds light on the mechanisms by which the hippocampal network achieves and updates multi-dimensional neural representations from various input streams.\n\nAuthor summaryAs an animal moves in space and receives external sensory inputs, it must dynamically maintain the representations of its position and environment at all times. How the hippocampus, the brain area crucial for spatial representations, achieves this task, and manages possible conflicts between different inputs remains unclear. We propose here a comprehensive attractor neural network-based model of the hippocampus and of its multiple input streams (including self-motion). We show that this model is capable of maintaining faithful representations of positional and contextual information, and resolves conflicts by adapting internal representations to match external cues. Model predictions are confirmed by the detailed analysis of hippocampal recordings of a rat submitted to quickly varying and conflicting contextual inputs.

neuroscience↗

bioRxiv2018

AMPK signaling linked to the schizophrenia-associated 1q21.1 deletion is required for neuronal and sleep maintenance

The human 1q21.1 deletion of ten genes is associated with increased risk schizophrenia. The deletion involves the {beta}-subunit of the AMP-activated protein kinase (AMPK) complex, a key energy sensor in the cell. Although neurons have a high demand for energy and low capacity to store nutrients, the role of AMPK in neuronal physiology is poorly defined. Here we show that AMPK is important in the nervous system for maintaining neuronal integrity and for stress survival and longevity in Drosophila. To understand its impact on behavior and potential contribution to the 1q21.1 deletion syndrome, we focused on sleep, as its main role is proposed to be to reestablish neuronal energy levels that are diminished during energy-demanding wakefulness. Sleep disturbances are one of the most common problems affecting individuals with psychiatric disorders. We show that AMPK is required to maintain proper sleep architecture and for sleep recovery following sleep deprivation. Neuronal AMPK{beta} loss specifically leads to sleep fragmentation and causes dysregulation of genes believed to play a role in sleep homeostasis. Our data also suggest that AMPK{beta} loss may contribute to the increased risk of developing mental disorders and sleep disturbances associated with the human 1q21.1 deletion. Sleep is regulated by circadian and homeostatic processes. While the circadian clock is well studied, the molecular mechanism underlying homeostasis remains largely unknown. Our data suggest that AMPK is required for sleep maintenance and may be involved in the homeostatic process of sleep regulation.\n\nAuthor SummaryThe human 1q21.1 chromosomal deletion is associated with increased risk of schizophrenia. Because this deletion affects only a small number of genes, it provides a unique opportunity to identify the specific disease-causing gene(s) using animal models. Here, we report the use of a Drosophila model to identify the potential contribution of one gene affected by the 1q21.1 deletion - PRKAB2 - to the pathology of the 1q21.1 deletion syndrome. PRKAB2 encodes a subunit of the AMP-activated protein kinase (AMPK) complex, the main cellular energy sensor. We show that AMPK deficiency reduces lifespan and causes structural abnormalities in neuronal dendritic structures, a phenotype which has been linked to schizophrenia. Furthermore, cognitive impairment and altered sleep patterning are some of the most common symptoms of schizophrenia. Therefore, to understand the potential contribution of PRKAB2 to the 1q21.1 syndrome, we tested whether AMPK alterations would cause defects in learning and sleep. Our study shows that lack of PRKAB2 and AMPK-complex activity, in the nervous system leads to reduced learning and to dramatic sleep disturbances. Thus, our data links a single 1q21.1-related gene with phenotypes that resemble common symptoms of schizophrenia, suggesting that this gene, PRKAB2, may contribute to the risk of developing schizophrenia.

neuroscience↗