scholarly journals Simple models of quantitative firing phenotypes in hippocampal neurons: comprehensive coverage of intrinsic diversity

2019 ◽  
Author(s):  
Siva Venkadesh ◽  
Alexander O. Komendantov ◽  
Diek W. Wheeler ◽  
David J. Hamilton ◽  
Giorgio A. Ascoli
Keyword(s):  
Hippocampal Neurons ◽  
Hippocampal Neuron ◽  
Activity Patterns ◽  
Model Space ◽  
Brain Regions ◽  
Intrinsic Activity ◽  
Neuron Models ◽  
Neuronal Modeling ◽  
Compartment Models ◽  
Network Simulations

AbstractPatterns of periodic voltage spikes elicited by a neuron help define its dynamical identity. Experimentally recorded spike trains from various neurons show qualitatively distinguishable features such as delayed spiking, spiking with/without frequency adaptation, and intrinsic bursting. Moreover, the input-dependent responses of a neuron not only show different quantitative features, such as higher spike frequency for a stronger input current injection, but can also exhibit qualitatively different responses, such as spiking and bursting under different input conditions, thus forming a complex phenotype of responses. In a previous work, Hippocampome.org, a comprehensive knowledgebase of hippocampal neuron types, systematically characterized various spike pattern phenotypes experimentally identified from 120 neuron types/subtypes. In this paper, we present a comprehensive set of simple phenomenological models that quantitatively reproduce the diverse and complex phenotypes of hippocampal neurons. In addition to point-neuron models, we created compact multi-compartment models with up to four compartments, which will allow spatial segregation of synaptic integration in network simulations. Electrotonic compartmentalization observed in our compact multi-compartment models is qualitatively consistent with experimental observations. Furthermore, we observed that adding dendritic compartments to point-neuron models, in general, allowed soma to reproduce features of bursting patterns and abrupt non-linearities in some frequency adapting patterns slightly more accurately. This work maps 120 neuron types/subtypes in the rodent hippocampus to a low-dimensional model space and adds another dimension to the knowledge accumulated in Hippocampome.org. Computationally efficient representations of intrinsic dynamics, along with other pieces of knowledge available in Hippocampome.org, provide a biologically realistic platform to explore the dynamical interactions of various types at the mesoscopic level.Author SummaryThe neurons in the hippocampus show enormous diversity in their intrinsic activity patterns. A comprehensive characterization of various intrinsic types using a neuronal modeling system is necessary to simulate biologically realistic networks of brain regions. Morphologically detailed neuronal modeling frameworks often limit the scalability of such network simulations due to the specification of hundreds of rules governing each neuron’s intrinsic dynamics. In this work, we have accomplished a comprehensive mapping of experimentally identified intrinsic dynamics in a simple modeling system with only two governing rules. We have created over a hundred point-neuron models that reflect the intrinsic differences among the hippocampal neuron types both qualitatively and quantitatively. In addition, we compactly extended our point-neurons to include up to four compartments, which will allow anatomically finer-grained connections among the neurons in a network. Our compact model representations, which are freely available in Hippocampome.org, will allow future researchers to investigate dynamical interactions among various intrinsic types and emergent integrative properties using scalable, yet biologically realistic network simulations.

scholarly journals Relationship between individual neuron and network spontaneous activity in developing mouse cortex

2014 ◽  
Vol 112 (12) ◽  
pp. 3033-3045 ◽  
Author(s):  
Heather M. Barnett ◽  
Julijana Gjorgjieva ◽  
Keiko Weir ◽  
Cara Comfort ◽  
Adrienne L. Fairhall ◽  
...  
Keyword(s):  
Normal Development ◽  
Activity Patterns ◽  
Piriform Cortex ◽  
Intrinsic Excitability ◽  
Intrinsic Activity ◽  
Dorsal Cortex ◽  
Synchronous Activity ◽  
Mouse Cortex ◽  
Propagating Waves ◽  
Autonomous Activity

Spontaneous synchronous activity (SSA) that propagates as electrical waves is found in numerous central nervous system structures and is critical for normal development, but the mechanisms of generation of such activity are not clear. In previous work, we showed that the ventrolateral piriform cortex is uniquely able to initiate SSA in contrast to the dorsal neocortex, which participates in, but does not initiate, SSA (Lischalk JW, Easton CR, Moody WJ. Dev Neurobiol 69: 407–414, 2009). In this study, we used Ca2+ imaging of cultured embryonic day 18 to postnatal day 2 coronal slices (embryonic day 17 + 1–4 days in culture) of the mouse cortex to investigate the different activity patterns of individual neurons in these regions. In the piriform cortex where SSA is initiated, a higher proportion of neurons was active asynchronously between waves, and a larger number of groups of coactive cells was present compared with the dorsal cortex. When we applied GABA and glutamate synaptic antagonists, asynchronous activity and cellular clusters remained, while synchronous activity was eliminated, indicating that asynchronous activity is a result of cell-intrinsic properties that differ between these regions. To test the hypothesis that higher levels of cell-autonomous activity in the piriform cortex underlie its ability to initiate waves, we constructed a conductance-based network model in which three layers differed only in the proportion of neurons able to intrinsically generate bursting behavior. Simulations using this model demonstrated that a gradient of intrinsic excitability was sufficient to produce directionally propagating waves that replicated key experimental features, indicating that the higher level of cell-intrinsic activity in the piriform cortex may provide a substrate for SSA generation.

scholarly journals Spatially structured inhibition defined by polarized parvalbumin interneuron axons promotes head direction tuning

2021 ◽  
Vol 7 (25) ◽  
pp. eabg4693
Author(s):  
Yangfan Peng ◽  
Federico J. Barreda Tomas ◽  
Paul Pfeiffer ◽  
Moritz Drangmeister ◽  
Susanne Schreiber ◽  
...  
Keyword(s):  
Spatial Organization ◽  
Pyramidal Cells ◽  
Brain Regions ◽  
Head Direction ◽  
Spatial Connectivity ◽  
Parvalbumin Interneurons ◽  
Parvalbumin Interneuron ◽  
Network Simulations ◽  
Fast Spiking ◽  
Direction Tuning

In cortical microcircuits, it is generally assumed that fast-spiking parvalbumin interneurons mediate dense and nonselective inhibition. Some reports indicate sparse and structured inhibitory connectivity, but the computational relevance and the underlying spatial organization remain unresolved. In the rat superficial presubiculum, we find that inhibition by fast-spiking interneurons is organized in the form of a dominant super-reciprocal microcircuit motif where multiple pyramidal cells recurrently inhibit each other via a single interneuron. Multineuron recordings and subsequent 3D reconstructions and analysis further show that this nonrandom connectivity arises from an asymmetric, polarized morphology of fast-spiking interneuron axons, which individually cover different directions in the same volume. Network simulations assuming topographically organized input demonstrate that such polarized inhibition can improve head direction tuning of pyramidal cells in comparison to a “blanket of inhibition.” We propose that structured inhibition based on asymmetrical axons is an overarching spatial connectivity principle for tailored computation across brain regions.

Exact Subthreshold Integration with Continuous Spike Times in Discrete-Time Neural Network Simulations

2007 ◽  
Vol 19 (1) ◽  
pp. 47-79 ◽  
Author(s):  
Abigail Morrison ◽  
Sirko Straube ◽  
Hans Ekkehard Plesser ◽  
Markus Diesmann
Keyword(s):  
Grid Point ◽  
Propagation Delay ◽  
Integration Scheme ◽  
The Novel ◽  
Neuron Models ◽  
Exact Integration ◽  
Wide Range ◽  
Network Simulations ◽  
Adequate Representation ◽  
Grid Points

Very large networks of spiking neurons can be simulated efficiently in parallel under the constraint that spike times are bound to an equidistant time grid. Within this scheme, the subthreshold dynamics of a wide class of integrate-and-fire-type neuron models can be integrated exactly from one grid point to the next. However, the loss in accuracy caused by restricting spike times to the grid can have undesirable consequences, which has led to interest in interpolating spike times between the grid points to retrieve an adequate representation of network dynamics. We demonstrate that the exact integration scheme can be combined naturally with off-grid spike events found by interpolation. We show that by exploiting the existence of a minimal synaptic propagation delay, the need for a central event queue is removed, so that the precision of event-driven simulation on the level of single neurons is combined with the efficiency of time-driven global scheduling. Further, for neuron models with linear subthreshold dynamics, even local event queuing can be avoided, resulting in much greater efficiency on the single-neuron level. These ideas are exemplified by two implementations of a widely used neuron model. We present a measure for the efficiency of network simulations in terms of their integration error and show that for a wide range of input spike rates, the novel techniques we present are both more accurate and faster than standard techniques.

Individual Differences in Mental Imagery Modulate Effective Connectivity of Scene-Selective Regions During Resting State

2021 ◽  
Author(s):  
Maria Giulia Tullo ◽  
Hannes Almgren ◽  
Frederik Van de Steen ◽  
Valentina Sulpizio ◽  
Daniele Marinazzo ◽  
...  
Keyword(s):  
Individual Differences ◽  
Mental Imagery ◽  
Resting State ◽  
Effective Connectivity ◽  
Relevant Information ◽  
Brain Regions ◽  
Intrinsic Activity ◽  
Inhibitory Influence ◽  
Cortical Regions ◽  
Intrinsic Fluctuation

Abstract Successful navigation relies on the ability to identify, perceive, and correctly process the spatial structure of a scene. It is well known that visual mental imagery plays a crucial role in navigation. Indeed, cortical regions encoding navigationally relevant information are also active during mental imagery of navigational scenes. However, it remains unknown whether their intrinsic activity and connectivity reflect the individuals’ ability to imagine a scene. Here, we primarily investigated the intrinsic causal interactions among scene-selective brain regions such as Parahipoccampal Place Area (PPA), Retrosplenial Complex (RSC), and Occipital Place Area (OPA) using Dynamic Causal Modelling (DCM) for resting-state functional magnetic resonance (rs-fMRI) data. Second, we tested whether resting-state effective connectivity parameters among scene-selective regions could reflect individual differences in mental imagery in our sample, as assessed by the self-reported Vividness of Visual Imagery Questionnaire (VVIQ). We found an inhibitory influence of occipito-medial on temporal regions, and an excitatory influence of more anterior on more medial and posterior brain regions. Moreover, we found that a key role in imagery is played by the connection strength from OPA to PPA, especially in the left hemisphere, since the influence of the signal between these scene-selective regions positively correlated with good mental imagery ability. Our investigation contributes to the understanding of the complexity of the causal interaction among brain regions involved in navigation and provides new insight in understanding how an essential ability, such as mental imagery, can be explained by the intrinsic fluctuation of brain signal.

scholarly journals A dynamical model for the basal ganglia-thalamo-cortical oscillatory activity and its implications in Parkinson’s disease

2020 ◽  
Author(s):  
Eva M. Navarro-López ◽  
Utku Çelikok ◽  
Neslihan S. Şengör
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Basal Ganglia ◽  
Activity Patterns ◽  
Dynamical Model ◽  
Substantia Nigra Pars Compacta ◽  
Oscillatory Activity ◽  
Subcortical Structures ◽  
Neuron Models ◽  
Neuronal Patterns

AbstractWe propose to investigate brain electrophysiological alterations associated with Parkinson’s disease through a novel adaptive dynamical model of the network of the basal ganglia, the cortex and the thalamus. The model uniquely unifies the influence of dopamine in the regulation of the activity of all basal ganglia nuclei, the self-organised neuronal interdependent activity of basal ganglia-thalamo-cortical circuits and the generation of subcortical background oscillations. Variations in the amount of dopamine produced in the neurons of the substantia nigra pars compacta are key both in the onset of Parkinson’s disease and in the basal ganglia action selection. We model these dopamine-induced relationships, and Parkinsonian states are interpreted as spontaneous emergent behaviours associated with different rhythms of oscillatory activity patterns of the basal ganglia-thalamo-cortical network. These results are significant because: (1) the neural populations are built upon single-neuron models that have been robustly designed to have eletrophysiologically-realistic responses, and (2) our model distinctively links changes in the oscillatory activity in subcortical structures, dopamine levels in the basal ganglia and pathological synchronisation neuronal patterns compatible with Parkinsonian states, this still remains an open problem and is crucial to better understand the progression of the disease.

scholarly journals Prestimulus feedback connectivity biases the content of visual experiences

2019 ◽  
Vol 116 (32) ◽  
pp. 16056-16061 ◽  
Author(s):  
Elie Rassi ◽  
Andreas Wutz ◽  
Nadia Müller-Voggel ◽  
Nathan Weisz
Keyword(s):  
Neural Activity ◽  
Activity Patterns ◽  
Low Frequency ◽  
Brain Regions ◽  
Stimulus Onset ◽  
Neural Excitability ◽  
Gamma Frequency ◽  
Face Area ◽  
Oscillatory Power ◽  
The Impact

Ongoing fluctuations in neural excitability and in networkwide activity patterns before stimulus onset have been proposed to underlie variability in near-threshold stimulus detection paradigms—that is, whether or not an object is perceived. Here, we investigated the impact of prestimulus neural fluctuations on the content of perception—that is, whether one or another object is perceived. We recorded neural activity with magnetoencephalography (MEG) before and while participants briefly viewed an ambiguous image, the Rubin face/vase illusion, and required them to report their perceived interpretation in each trial. Using multivariate pattern analysis, we showed robust decoding of the perceptual report during the poststimulus period. Applying source localization to the classifier weights suggested early recruitment of primary visual cortex (V1) and ∼160-ms recruitment of the category-sensitive fusiform face area (FFA). These poststimulus effects were accompanied by stronger oscillatory power in the gamma frequency band for face vs. vase reports. In prestimulus intervals, we found no differences in oscillatory power between face vs. vase reports in V1 or in FFA, indicating similar levels of neural excitability. Despite this, we found stronger connectivity between V1 and FFA before face reports for low-frequency oscillations. Specifically, the strength of prestimulus feedback connectivity (i.e., Granger causality) from FFA to V1 predicted not only the category of the upcoming percept but also the strength of poststimulus neural activity associated with the percept. Our work shows that prestimulus network states can help shape future processing in category-sensitive brain regions and in this way bias the content of visual experiences.

scholarly journals Leptin Controls Glutamatergic Synaptogenesis and NMDA-Receptor Trafficking via Fyn Kinase Regulation of NR2B

Endocrinology ◽  
2019 ◽  
Vol 161 (2) ◽  
Author(s):  
Tyler Bland ◽  
Mingyan Zhu ◽  
Crystal Dillon ◽  
Gulcan Semra Sahin ◽  
Jose Luis Rodriguez-Llamas ◽  
...  
Keyword(s):  
Nmda Receptor ◽  
Hippocampal Neurons ◽  
Leptin Receptor ◽  
Kinase Inhibitor ◽  
Phosphorylation Site ◽  
Surface Expression ◽  
Brain Regions ◽  
Dominant Negative ◽  
Nmda Receptor Function ◽  
The Central Nervous System

Abstract Activation of the leptin receptor, LepRb, by the adipocytokine/neurotrophic factor leptin in the central nervous system has procognitive and antidepressive effects. Leptin has been shown to increase glutamatergic synaptogenesis in multiple brain regions. In contrast, mice that have a mutation in the LepRb gene show abnormal synapse development in the hippocampus as well as deficits in cognition and increased depressive-like symptoms. Leptin increases glutamatergic synaptogenesis, in part, through enhancement of N-methyl-D-aspartic acid (NMDA) receptor function; yet the underlying signaling pathway is not known. In this study, we examine how leptin regulates surface expression of NR2B-containing NMDA receptors in hippocampal neurons. Leptin stimulation increases NR2BY1472 phosphorylation, which is inhibited by the Src family kinase inhibitor, PP1. Moreover, we show that Fyn, a member of the Src family kinases, is required for leptin-stimulated NR2BY1472 phosphorylation. Furthermore, inhibiting Y1472 phosphorylation with either a dominant negative Fyn mutant or an NR2B mutant that lacks the phosphorylation site (NR2BY1472F) blocks leptin-stimulated synaptogenesis. Additionally, we show that LepRb forms a complex with NR2B and Fyn. Taken together, these findings expand our knowledge of the LepRb interactome and the mechanisms by which leptin stimulates glutamatergic synaptogenesis in the developing hippocampus. Comprehending these mechanisms is key for understanding dendritic spine development and synaptogenesis, alterations of which are associated with many neurological disorders.

scholarly journals Operant Conditioning of Synaptic and Spiking Activity Patterns in Single Hippocampal Neurons

2014 ◽  
Vol 34 (14) ◽  
pp. 5044-5053 ◽  
Author(s):  
Daisuke Ishikawa ◽  
Nobuyoshi Matsumoto ◽  
Tetsuya Sakaguchi ◽  
Norio Matsuki ◽  
Yuji Ikegaya
Keyword(s):  
Operant Conditioning ◽  
Hippocampal Neurons ◽  
Activity Patterns ◽  
Spiking Activity

scholarly journals MmTX1 and MmTX2 from coral snake venom potently modulate GABAA receptor activity

2015 ◽  
Vol 112 (8) ◽  
pp. E891-E900 ◽  
Author(s):  
Jean-Pierre Rosso ◽  
Jürgen R. Schwarz ◽  
Marcelo Diaz-Bustamante ◽  
Brigitte Céard ◽  
José M. Gutiérrez ◽  
...  
Keyword(s):  
Cell Membrane ◽  
Synaptic Transmission ◽  
Snake Venom ◽  
Hippocampal Neurons ◽  
Hippocampal Neuron ◽  
Costa Rican ◽  
Coral Snake ◽  
Receptor Sensitivity ◽  
Common Receptor ◽  
Receptor Family

GABAA receptors shape synaptic transmission by modulating Cl− conductance across the cell membrane. Remarkably, animal toxins that specifically target GABAA receptors have not been identified. Here, we report the discovery of micrurotoxin1 (MmTX1) and MmTX2, two toxins present in Costa Rican coral snake venom that tightly bind to GABAA receptors at subnanomolar concentrations. Studies with recombinant and synthetic toxin variants on hippocampal neurons and cells expressing common receptor compositions suggest that MmTX1 and MmTX2 allosterically increase GABAA receptor susceptibility to agonist, thereby potentiating receptor opening as well as desensitization, possibly by interacting with the α+/β− interface. Moreover, hippocampal neuron excitability measurements reveal toxin-induced transitory network inhibition, followed by an increase in spontaneous activity. In concert, toxin injections into mouse brain result in reduced basal activity between intense seizures. Altogether, we characterized two animal toxins that enhance GABAA receptor sensitivity to agonist, thereby establishing a previously unidentified class of tools to study this receptor family.

Perceptual Representations and the Vividness of Stimulus-Triggered and Stimulus-Independent Experiences

2020 ◽  
Vol 15 (5) ◽  
pp. 1200-1213 ◽  
Author(s):  
Peter Fazekas ◽  
Georgina Nemeth ◽  
Morten Overgaard
Keyword(s):  
Working Memory ◽  
Mental Imagery ◽  
Information Exchange ◽  
Activity Patterns ◽  
Mind Wandering ◽  
Brain Regions ◽  
Neural Basis ◽  
Fine Grained ◽  
Common Framework ◽  
Cortical Regions

In recent years, researchers from independent subfields have begun to engage with the idea that the same cortical regions that contribute to on-line perception are recruited during and underlie off-line activities such as information maintenance in working memory, mental imagery, hallucinations, dreaming, and mind wandering. Accumulating evidence suggests that in all of these cases the activity of posterior brain regions provides the contents of experiences. This article is intended to move one step further by exploring specific links between the vividness of experiences, which is a characteristic feature of consciousness regardless of its actual content, and certain properties of the content-specific neural-activity patterns. Investigating the mechanisms that underlie mental imagery and its relation to working memory and the processes responsible for mind wandering and its similarities to dreaming form two clusters of research that are in the forefront of the recent scientific study of mental phenomena, yet communication between these two clusters has been surprisingly sparse. Here our aim is to foster such information exchange by articulating a hypothesis about the fine-grained phenomenological structure determining subjective vividness and its possible neural basis that allows us to shed new light on these mental phenomena by bringing them under a common framework.

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