scholarly journals Spontaneous Plasticity of Multineuronal Activity Patterns in Activated Hippocampal Networks

2008 ◽  
Vol 2008 ◽  
pp. 1-8 ◽  
Author(s):  
Atsushi Usami ◽  
Norio Matsuki ◽  
Yuji Ikegaya
Keyword(s):  
Spontaneous Activity ◽  
Activity Patterns ◽  
Cell Number ◽  
Activity Level ◽  
Correlated Activity ◽  
Activity Frequency ◽  
Level Of Activity ◽  
Multineuronal Activity ◽  
Hippocampal Networks

Using functional multineuron imaging with single-cell resolution, we examined how hippocampal networks by themselves change the spatiotemporal patterns of spontaneous activity during the course of emitting spontaneous activity. When extracellular ionic concentrations were changed to those that mimicked in vivo conditions, spontaneous activity was increased in active cell number and activity frequency. When ionic compositions were restored to the control conditions, the activity level returned to baseline, but the weighted spatial dispersion of active cells, as assessed by entropy-based metrics, did not. Thus, the networks can modify themselves by altering the internal structure of their correlated activity, even though they as a whole maintained the same level of activity in space and time.

scholarly journals Oxytocin shapes spontaneous activity patterns in the developing visual cortex by activating somatostatin interneurons

2019 ◽  
Author(s):  
Paloma P Maldonado ◽  
Alvaro Nuno-Perez ◽  
Jan Kirchner ◽  
Elizabeth Hammock ◽  
Julijana Gjorgjieva ◽  
...  
Keyword(s):  
Visual Cortex ◽  
Spontaneous Activity ◽  
Sensory Processing ◽  
Activity Patterns ◽  
Network Activity ◽  
Synaptic Connections ◽  
Pairwise Correlations ◽  
Early Brain Development

SummarySpontaneous network activity shapes emerging neuronal circuits during early brain development, however how neuromodulation influences this activity is not fully understood. Here, we report that the neuromodulator oxytocin powerfully shapes spontaneous activity patterns. In vivo, oxytocin strongly decreased the frequency and pairwise correlations of spontaneous activity events in visual cortex (V1), but not in somatosensory cortex (S1). This differential effect was a consequence of oxytocin only increasing inhibition in V1 and increasing both inhibition and excitation in S1. The increase in inhibition was mediated by the depolarization and increase in excitability of somatostatin+ (SST) interneurons specifically. Accordingly, silencing SST+ neurons pharmacogenetically fully blocked oxytocin’s effect on inhibition in vitro as well its effect on spontaneous activity patterns in vivo. Thus, oxytocin decreases the excitatory/inhibitory ratio and modulates specific features of V1 spontaneous activity patterns that are crucial for refining developing synaptic connections and sensory processing later in life.

Biophysical basis of brain activity: implications for neuroimaging

2002 ◽  
Vol 35 (3) ◽  
pp. 287-325 ◽  
Author(s):  
Robert G. Shulman ◽  
Fahmeed Hyder ◽  
Douglas L. Rothman
Keyword(s):  
Energy Consumption ◽  
Magnetic Resonance ◽  
Neuronal Activity ◽  
Glucose Oxidation ◽  
Activity Level ◽  
Quantitative Relation ◽  
Cerebral Function ◽  
Level Of Activity ◽  
The Brain

1. Summary 2882. Introduction 2883. Relationship between neuroenergetics and neurotransmitter flux 2944. A model of coupling between neuroenergetics and neurotransmission 2965. Relationship between neuroenergetics and neural spiking frequency 2976. Comparison with previous electrophysiological and fMRI measurements 2987. Contributions of non-oxidative energetics to a primarily oxidative brain 2998. Possible explanation for non-oxidative energetics contributions 3009. A model of total neuronal activity to support cerebral function 30210. Implications for interpretation of fMRI studies 30511. The restless brain 30612. Acknowledgements 31013. Appendix A. CMRO2by13C-MRS 31014. Appendix B.Vcycand test of model 31315. Appendix C. CMRO2by calibrated BOLD 31616. Appendix D. Comparison of spiking activity of a neuronal ensemble with CMRO231817. References 320In vivo13C magnetic resonance spectroscopy (MRS) studies of the brain have quantitatively assessed rates of glutamate–glutamine cycle (Vcyc) and glucose oxidation (CMRGlc(ox)) by detecting 13C label turnover from glucose to glutamate and glutamine. Contrary to expectations from in vitro and ex vivo studies, the in vivo13C-MRS results demonstrate that glutamate recycling is a major metabolic pathway, inseparable from its actions of neurotransmission. Furthermore, both in the awake human and in the anesthetized rat brain, Vcyc and CMRGlc(ox) are stoichiometrically related, where more than two thirds of the energy from glucose oxidation supports events associated with glutamate neurotransmission. The high energy consumption of the brain measured at rest and its quantitative relation to neurotransmission reflects a sizeable activity level for the resting brain. The high activity of the non-stimulated brain, as measured by cerebral metabolic rate of oxygen use (CMRO2), establishes a new neurophysiological basis of cerebral function that leads to reinterpreting functional imaging data because the large baseline signal is commonly discarded in cognitive neuroscience paradigms. Changes in energy consumption (ΔCMRO2%) can also be obtained from magnetic resonance imaging (MRI) experiments, using the blood oxygen level- dependent (BOLD) image contrast, provided that all the separate parameters contributing to the functional MRI (fMRI) signal are measured. The BOLD-derived ΔCMRO2% when compared with alterations in neuronal spiking rate (Δν%) during sensory stimulation in the rat reveals a stoichiometric relationship, in good agreement with 13C-MRS results. Hence fMRI when calibrated so as to provide ΔCMRO2% can provide high spatial resolution evaluation of neuronal activity. Our studies of quantitative measurements of changes in neuroenergetics and neurotransmission reveal that a stimulus does not provoke an arbitrary amount of activity in a localized region, rather a total level of activity is required where the increment is inversely related to the level of activity in the non-stimulated condition. These biophysical experiments have established relationships between energy consumption and neuronal activity that provide novel insights into the nature of brain function and the interpretation of fMRI data.

scholarly journals Quantitative differences in developmental profiles of spontaneous activity in cortical and hippocampal cultures

2014 ◽  
Author(s):  
Paul Charlesworth ◽  
Ellese Cotterill ◽  
Andrew Morton ◽  
Seth Grant ◽  
Stephen Eglen
Keyword(s):  
Spontaneous Activity ◽  
Cortical Neurons ◽  
Activity Patterns ◽  
Machine Learning Techniques ◽  
Multielectrode Arrays ◽  
Cortical Networks ◽  
Hippocampal Cultures ◽  
Hippocampal Networks ◽  
Cultured Networks

Background: Neural circuits can spontaneously generate complex spatiotemporal firing patterns during development. This spontaneous activity is thought to help guide development of the nervous system. In this study, we had two aims. First, to characterise the changes in spontaneous activity in cultures of developing networks of either hippocampal or cortical neurons dissociated from mouse. Second, to assess whether there are any functional differences in the patterns of activity in hippocampal and cortical networks. Results: We used multielectrode arrays to record the development of spontaneous activity in cultured networks of either hippocampal or cortical neurons every two or three days for the first month after plating. Within a few days of culturing, networks exhibited spontaneous activity. This activity strengthened and then stabilised typically around 21 days in vitro. We quantified the activity patterns in hippocampal and cortical networks using eleven features. Three out of eleven features showed striking differences in activity between hippocampal and cortical networks. 1: Interburst intervals are less variable in spike trains from hippocampal cultures. 2: Hippocampal networks have higher correlations. 3: Hippocampal networks generate more robust theta bursting patterns. Machine learning techniques confirmed that these differences in patterning are sufficient to reliably classify recordings at any given age as either hippocampal or cortical networks. Conclusions: Although cultured networks of hippocampal and cortical networks both generate spontaneous activity that changes over time, at any given time we can reliably detect differences in the activity patterns. We anticipate that this quantitative framework could have applications in many areas, including neurotoxicity testing and for characterising phenotype of different mutant mice. All code and data relating to this report are freely available for others to use.

scholarly journals Adaptation of spontaneous activity in the developing visual cortex

eLife ◽  
2021 ◽  
Vol 10 ◽  
Author(s):  
Marina E Wosniack ◽  
Jan H Kirchner ◽  
Ling-Ya Chao ◽  
Nawal Zabouri ◽  
Christian Lohmann ◽  
...  
Keyword(s):  
Visual Cortex ◽  
Spontaneous Activity ◽  
Activity Patterns ◽  
Network Connectivity ◽  
Cortical Activation ◽  
Cortical Input ◽  
Visual Inputs ◽  
Eye Opening ◽  
Global Events

Spontaneous activity drives the establishment of appropriate connectivity in different circuits during brain development. In the mouse primary visual cortex, two distinct patterns of spontaneous activity occur before vision onset: local low-synchronicity events originating in the retina and global high-synchronicity events originating in the cortex. We sought to determine the contribution of these activity patterns to jointly organize network connectivity through different activity-dependent plasticity rules. We postulated that local events shape cortical input selectivity and topography, while global events homeostatically regulate connection strength. However, to generate robust selectivity, we found that global events should adapt their amplitude to the history of preceding cortical activation. We confirmed this prediction by analyzing in vivo spontaneous cortical activity. The predicted adaptation leads to the sparsification of spontaneous activity on a slower timescale during development, demonstrating the remarkable capacity of the developing sensory cortex to acquire sensitivity to visual inputs after eye-opening.

scholarly journals Adaptation of spontaneous activity in the developing visual cortex

2020 ◽  
Author(s):  
Marina E. Wosniack ◽  
Jan H. Kirchner ◽  
Ling-Ya Chao ◽  
Nawal Zabouri ◽  
Christian Lohmann ◽  
...  
Keyword(s):  
Visual Cortex ◽  
Spontaneous Activity ◽  
Activity Patterns ◽  
Network Connectivity ◽  
Cortical Activation ◽  
Cortical Input ◽  
Visual Inputs ◽  
Eye Opening ◽  
Global Events

Spontaneous activity drives the establishment of appropriate connectivity in different circuits during brain development. In the mouse primary visual cortex, two distinct patterns of spontaneous activity occur before vision onset: local low-synchronicity events originating in the retina, and global high-synchronicity events originating in the cortex. We sought to determine the contribution of these activity patterns to jointly organize network connectivity through different activity-dependent plasticity rules. We found that local events shape cortical input selectivity and topography, while global events have a homeostatic role regulating connection strength. To generate robust selectivity, we predicted that global events should adapt their amplitude to the history of preceding cortical activation, and confirmed by analyzing in vivo spontaneous cortical activity. This adaptation led to the sparsification of spontaneous activity on a slower timescale during development, demonstrating the remarkable capacity of the developing sensory cortex to acquire sensitivity to visual inputs after eye-opening.

scholarly journals Robustness of STDP to spike timing jitter

2018 ◽  
Author(s):  
Yihui Cui ◽  
Ilya Prokin ◽  
Alexandre Mendes ◽  
Hugues Berry ◽  
Laurent Venance
Keyword(s):  
Activity Patterns ◽  
Spike Timing ◽  
Differential Sensitivity ◽  
Time Intervals ◽  
Hebbian Plasticity ◽  
Activity Frequency ◽  
Experimental Implementation ◽  
Millisecond Timing ◽  
The Impact

ABSTRACTIn Hebbian plasticity, neural circuits adjust their synaptic weights depending on patterned firing of action potential on either side of the synapse. Spike-timing-dependent plasticity (STDP) is an experimental implementation of Hebb’s postulate that relies on the precise order and the millisecond timing of the paired activities in pre- and postsynaptic neurons. In recent years, STDP has attracted considerable attention in computational and experimental neurosciences. However, canonical STDP is assessed with deterministic (constant) spike timings and time intervals between successive pairings, thus exhibiting a regularity that strongly differs from the biological variability. Hence, the emergence of STDP from noisy neural activity patterns as expected in in vivo-like firing remains unresolved. Here, we used noisy STDP stimulations where the spike timing and/or the interval between successive pairings were jittered. We explored with a combination of experimental neurophysiology and mathematical modeling, the impact of jittering on three distinct forms of STDP at corticostriatal synapses: NMDAR-mediated tLTP, endocannabinoid-mediated tLTD and endocannabinoid-mediated tLTP. As the main result, we found a differential sensitivity to jittered spike timing: NMDAR-tLTP was highly fragile whereas endocannabinoid-plasticity (tLTD and tLTP) appeared more resistant. Moreover, when the frequency or the number of pairings was increased, NMDAR-tLTP became more robust and could be expressed despite strong jittering of the spike timing. Taken together, our results identify endocannabinoid-mediated plasticity as a robust form of STDP while the sensitivity to jitter of NMDAR-tLTP varies with activity frequency. This provides new insights into the mechanisms at play during the different phases of learning and memory and the emergence of Hebbian plasticity in in vivo-like firing.

scholarly journals Long-range order from local interactions: organization and development of distributed cortical networks

2018 ◽  
Author(s):  
Gordon B. Smith ◽  
Bettina Hein ◽  
David E. Whitney ◽  
David Fitzpatrick ◽  
Matthias Kaschube
Keyword(s):  
Visual Cortex ◽  
Spontaneous Activity ◽  
Long Range ◽  
Network Structure ◽  
Large Scale ◽  
Wide Field ◽  
Cortical Networks ◽  
Subsequent Formation ◽  
Correlated Activity

The cortical networks that underlie behavior exhibit an orderly functional organization at local and global scales, which is readily evident in the visual cortex of carnivores and primates1-6. Here, neighboring columns of neurons represent the full range of stimulus orientations and contribute to distributed networks spanning several millimeters2,7-11. However, the principles governing functional interactions that bridge this fine-scale functional architecture and distant network elements are unclear, and the emergence of these network interactions during development remains unexplored. Here, by using in vivo wide-field and 2-photon calcium imaging of spontaneous activity patterns in mature ferret visual cortex, we find widespread and specific modular correlation patterns that accurately predict the local structure of visually-evoked orientation columns from the spontaneous activity of neurons that lie several millimeters away. The large-scale networks revealed by correlated spontaneous activity show abrupt ‘fractures’ in continuity that are in tight register with evoked orientation pinwheels. Chronic in vivo imaging demonstrates that these large-scale modular correlation patterns and fractures are already present at early stages of cortical development and predictive of the mature network structure. Silencing feed-forward drive through either retinal or thalamic blockade does not affect network structure suggesting a cortical origin for this large-scale correlated activity, despite the immaturity of long-range horizontal network connections in the early cortex. Using a circuit model containing only local connections, we demonstrate that such a circuit is sufficient to generate large-scale correlated activity, while also producing correlated networks showing strong fractures, a reduced dimensionality, and an elongated local correlation structure, all in close agreement with our empirical data. These results demonstrate the precise local and global organization of cortical networks revealed through correlated spontaneous activity and suggest that local connections in early cortical circuits may generate structured long-range network correlations that underlie the subsequent formation of visually-evoked distributed functional networks.

scholarly journals Application of YOLOv4 for Detection and Motion Monitoring of Red Foxes

Animals ◽  
2021 ◽  
Vol 11 (6) ◽  
pp. 1723
Author(s):  
Anne K. Schütz ◽  
Verena Schöler  ◽  
E. Tobias Krause  ◽  
Mareike Fischer  ◽  
Thomas Müller  ◽  
...  
Keyword(s):  
Animal Welfare ◽  
Early Recognition ◽  
Activity Patterns ◽  
Automatic Detection ◽  
Animal Husbandry ◽  
Video Data ◽  
Activity Level ◽  
Red Foxes ◽  
Experimental Conditions ◽  
Animal Activity

Animal activity is an indicator for its welfare and manual observation is time and cost intensive. To this end, automatic detection and monitoring of live captive animals is of major importance for assessing animal activity, and, thereby, allowing for early recognition of changes indicative for diseases and animal welfare issues. We demonstrate that machine learning methods can provide a gap-less monitoring of red foxes in an experimental lab-setting, including a classification into activity patterns. Therefore, bounding boxes are used to measure fox movements, and, thus, the activity level of the animals. We use computer vision, being a non-invasive method for the automatic monitoring of foxes. More specifically, we train the existing algorithm ‘you only look once’ version 4 (YOLOv4) to detect foxes, and the trained classifier is applied to video data of an experiment involving foxes. As we show, computer evaluation outperforms other evaluation methods. Application of automatic detection of foxes can be used for detecting different movement patterns. These, in turn, can be used for animal behavioral analysis and, thus, animal welfare monitoring. Once established for a specific animal species, such systems could be used for animal monitoring in real-time under experimental conditions, or other areas of animal husbandry.

scholarly journals EXAMINING WHETHER LIFESTYLE ACTIVITY PATTERNS PREDICT DEMENTIA INCIDENCE AMONG COMMUNITY-DWELLING OLDER ADULTS

2019 ◽  
Vol 3 (Supplement_1) ◽  
pp. S812-S812
Author(s):  
Kyle Moored ◽  
Kyle Moored ◽  
Jeanine Parisi ◽  
Michelle Carlson
Keyword(s):  
Latent Class ◽  
Cox Regression ◽  
Activity Patterns ◽  
Intervention Group ◽  
Community Dwelling ◽  
Activity Frequency ◽  
Incident Dementia ◽  
Dementia Incidence ◽  
Lifestyle Activities ◽  
Community Dwelling Older Adults

Abstract Engagement in lifestyle activities can be neuroprotective, but it remains unclear what aspects of engagement are most beneficial. Examining activity patterns may better characterize both quantitative (e.g., number) and qualitative (e.g., characteristic/motivational) differences in engagement. We used a novel, latent class analysis (LCA) to characterize subgroups with distinct activity patterns and examined whether they have differential risk of incident dementia. We compared these findings to models including standard activity frequency and variety metrics. Using the Ginkgo Evaluation of Memory Study (N=3,069), we fit Cox regressions of each activity metric on time to dementia, adjusting for intervention group and demographics. For the LCA, we derived group/class indicators for Cox regression. Variety predicted incident dementia and will be compared to LCA activity metrics in predicting risk. Activity metrics that are most protective against dementia inform intervention design. Unlike standard activity metrics, LCA may further identify subgroups with common motivations to sustain activity.

scholarly journals Cdx2 regulates immune cell infiltration in the intestine

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Simon Chewchuk ◽  
Sanzida Jahan ◽  
David Lohnes
Keyword(s):  
Intestinal Epithelium ◽  
Target Genes ◽  
Immune Cell ◽  
Cell Number ◽  
Macrophage Infiltration ◽  
Intestinal Homeostasis ◽  
Chronic Inflammatory Response ◽  
Complex Protein ◽  
Inflammatory Phenotype

AbstractThe intestinal epithelium is a unique tissue, serving both as a barrier against pathogens and to conduct the end digestion and adsorption of nutrients. As regards the former, the intestinal epithelium contains a diverse repertoire of immune cells, including a variety of resident lymphocytes, macrophages and dendritic cells. These cells serve a number of roles including mitigation of infection and to stimulate regeneration in response to damage. The transcription factor Cdx2, and to a lesser extent Cdx1, plays essential roles in intestinal homeostasis, and acts as a context-dependent tumour suppressor in colorectal cancer. Deletion of Cdx2 from the murine intestinal epithelium leads to macrophage infiltration resulting in a chronic inflammatory response. However the mechanisms by which Cdx2 loss evokes this response are poorly understood. To better understand this relationship, we used a conditional mouse model lacking all intestinal Cdx function to identify potential target genes which may contribute to this inflammatory phenotype. One such candidate encodes the histocompatability complex protein H2-T3, which functions to regulate intestinal iCD8α lymphocyte activity. We found that Cdx2 occupies the H3-T3 promoter in vivo and directly regulates its expression via a Cdx response element. Loss of Cdx function leads to a rapid and pronounced attenuation of H2-T3, followed by a decrease in iCD8α cell number, an increase in macrophage infiltration and activation of pro-inflammatory cascades. These findings suggest a previously unrecognized role for Cdx in intestinal homeostasis through H2-T3-dependent regulation of iCD8α cells.

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