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1.
bioRxiv ; 2023 Apr 18.
Artigo em Inglês | MEDLINE | ID: mdl-37131710

RESUMO

The brain consists of many cell classes yet in vivo electrophysiology recordings are typically unable to identify and monitor their activity in the behaving animal. Here, we employed a systematic approach to link cellular, multi-modal in vitro properties from experiments with in vivo recorded units via computational modeling and optotagging experiments. We found two one-channel and six multi-channel clusters in mouse visual cortex with distinct in vivo properties in terms of activity, cortical depth, and behavior. We used biophysical models to map the two one- and the six multi-channel clusters to specific in vitro classes with unique morphology, excitability and conductance properties that explain their distinct extracellular signatures and functional characteristics. These concepts were tested in ground-truth optotagging experiments with two inhibitory classes unveiling distinct in vivo properties. This multi-modal approach presents a powerful way to separate in vivo clusters and infer their cellular properties from first principles.

2.
Nat Commun ; 14(1): 2344, 2023 04 24.
Artigo em Inglês | MEDLINE | ID: mdl-37095130

RESUMO

The brain consists of many cell classes yet in vivo electrophysiology recordings are typically unable to identify and monitor their activity in the behaving animal. Here, we employed a systematic approach to link cellular, multi-modal in vitro properties from experiments with in vivo recorded units via computational modeling and optotagging experiments. We found two one-channel and six multi-channel clusters in mouse visual cortex with distinct in vivo properties in terms of activity, cortical depth, and behavior. We used biophysical models to map the two one- and the six multi-channel clusters to specific in vitro classes with unique morphology, excitability and conductance properties that explain their distinct extracellular signatures and functional characteristics. These concepts were tested in ground-truth optotagging experiments with two inhibitory classes unveiling distinct in vivo properties. This multi-modal approach presents a powerful way to separate in vivo clusters and infer their cellular properties from first principles.


Assuntos
Encéfalo , Córtex Visual Primário , Camundongos , Animais , Encéfalo/fisiologia , Biofísica
3.
Cell Rep ; 41(13): 111873, 2022 12 27.
Artigo em Inglês | MEDLINE | ID: mdl-36577383

RESUMO

Temporal lobe epilepsy is the fourth most common neurological disorder, with about 40% of patients not responding to pharmacological treatment. Increased cellular loss is linked to disease severity and pathological phenotypes such as heightened seizure propensity. While the hippocampus is the target of therapeutic interventions, the impact of the disease at the cellular level remains unclear. Here, we show that hippocampal granule cells change with disease progression as measured in living, resected hippocampal tissue excised from patients with epilepsy. We show that granule cells increase excitability and shorten response latency while also enlarging in cellular volume and spine density. Single-nucleus RNA sequencing combined with simulations ascribes the changes to three conductances: BK, Cav2.2, and Kir2.1. In a network model, we show that these changes related to disease progression bring the circuit into a more excitable state, while reversing them produces a less excitable, "early-disease-like" state.


Assuntos
Epilepsia do Lobo Temporal , Epilepsia , Humanos , Hipocampo/patologia , Epilepsia/patologia , Neurônios/fisiologia , Epilepsia do Lobo Temporal/patologia , Simulação por Computador
5.
Cell Rep ; 40(6): 111176, 2022 08 09.
Artigo em Inglês | MEDLINE | ID: mdl-35947954

RESUMO

Which cell types constitute brain circuits is a fundamental question, but establishing the correspondence across cellular data modalities is challenging. Bio-realistic models allow probing cause-and-effect and linking seemingly disparate modalities. Here, we introduce a computational optimization workflow to generate 9,200 single-neuron models with active conductances. These models are based on 230 in vitro electrophysiological experiments followed by morphological reconstruction from the mouse visual cortex. We show that, in contrast to current belief, the generated models are robust representations of individual experiments and cortical cell types as defined via cellular electrophysiology or transcriptomics. Next, we show that differences in specific conductances predicted from the models reflect differences in gene expression supported by single-cell transcriptomics. The differences in model conductances, in turn, explain electrophysiological differences observed between the cortical subclasses. Our computational effort reconciles single-cell modalities that define cell types and enables causal relationships to be examined.


Assuntos
Transcriptoma , Córtex Visual , Animais , Fenômenos Eletrofisiológicos , Eletrofisiologia , Camundongos , Modelos Neurológicos , Neurônios/fisiologia , Transcriptoma/genética , Córtex Visual/fisiologia
6.
Elife ; 102021 12 01.
Artigo em Inglês | MEDLINE | ID: mdl-34851292

RESUMO

Inhibitory neurons in mammalian cortex exhibit diverse physiological, morphological, molecular, and connectivity signatures. While considerable work has measured the average connectivity of several interneuron classes, there remains a fundamental lack of understanding of the connectivity distribution of distinct inhibitory cell types with synaptic resolution, how it relates to properties of target cells, and how it affects function. Here, we used large-scale electron microscopy and functional imaging to address these questions for chandelier cells in layer 2/3 of the mouse visual cortex. With dense reconstructions from electron microscopy, we mapped the complete chandelier input onto 153 pyramidal neurons. We found that synapse number is highly variable across the population and is correlated with several structural features of the target neuron. This variability in the number of axo-axonic ChC synapses is higher than the variability seen in perisomatic inhibition. Biophysical simulations show that the observed pattern of axo-axonic inhibition is particularly effective in controlling excitatory output when excitation and inhibition are co-active. Finally, we measured chandelier cell activity in awake animals using a cell-type-specific calcium imaging approach and saw highly correlated activity across chandelier cells. In the same experiments, in vivo chandelier population activity correlated with pupil dilation, a proxy for arousal. Together, these results suggest that chandelier cells provide a circuit-wide signal whose strength is adjusted relative to the properties of target neurons.


Assuntos
Células Piramidais/ultraestrutura , Sinapses/ultraestrutura , Córtex Visual/ultraestrutura , Animais , Feminino , Masculino , Camundongos , Microscopia Eletrônica de Transmissão
7.
J Neurosci ; 40(17): 3408-3423, 2020 04 22.
Artigo em Inglês | MEDLINE | ID: mdl-32165416

RESUMO

We consider the question of how sensory networks enable the detection of sensory stimuli in a combinatorial coding space. We are specifically interested in the olfactory system, wherein recent experimental studies have reported the existence of rich, enigmatic response patterns associated with stimulus onset and offset. This study aims to identify the functional relevance of such response patterns (i.e., what benefits does such neural activity provide in the context of detecting stimuli in a natural environment). We study this problem through the lens of normative, optimization-based modeling. Here, we define the notion of a low-dimensional latent representation of stimulus identity, which is generated through action of the sensory network. The objective of our optimization framework is to ensure high-fidelity tracking of a nominal representation in this latent space in an energy-efficient manner. It turns out that the optimal motifs emerging from this framework possess morphologic similarity with prototypical onset and offset responses observed in vivo in locusts (Schistocerca americana) of either sex. Furthermore, this objective can be exactly achieved by a network with reciprocal excitatory-inhibitory competitive dynamics, similar to interactions between projection neurons and local neurons in the early olfactory system of insects. The derived model also makes several predictions regarding maintenance of robust latent representations in the presence of confounding background information and trade-offs between the energy of sensory activity and resultant behavioral measures such as speed and accuracy of stimulus detection.SIGNIFICANCE STATEMENT A key area of study in olfactory coding involves understanding the transformation from high-dimensional sensory stimulus to low-dimensional decoded representation. Here, we examine not only the dimensionality reduction of this mapping but also its temporal dynamics, with specific focus on stimuli that are temporally continuous. Through optimization-based synthesis, we examine how sensory networks can track representations without prior assumption of discrete trial structure. We show that such tracking can be achieved by canonical network architectures and dynamics, and that the resulting responses resemble observations from neurons in the insect olfactory system. Thus, our results provide hypotheses regarding the functional role of olfactory circuit activity at both single neuronal and population scales.


Assuntos
Modelos Neurológicos , Rede Nervosa/fisiologia , Neurônios/fisiologia , Condutos Olfatórios/fisiologia , Potenciais de Ação/fisiologia , Animais , Feminino , Gafanhotos , Masculino
8.
Cell Rep ; 30(10): 3536-3551.e6, 2020 03 10.
Artigo em Inglês | MEDLINE | ID: mdl-32160555

RESUMO

Determining cell types is critical for understanding neural circuits but remains elusive in the living human brain. Current approaches discriminate units into putative cell classes using features of the extracellular action potential (EAP); in absence of ground truth data, this remains a problematic procedure. We find that EAPs in deep structures of the brain exhibit robust and systematic variability during the cardiac cycle. These cardiac-related features refine neural classification. We use these features to link bio-realistic models generated from in vitro human whole-cell recordings of morphologically classified neurons to in vivo recordings. We differentiate aspiny inhibitory and spiny excitatory human hippocampal neurons and, in a second stage, demonstrate that cardiac-motion features reveal two types of spiny neurons with distinct intrinsic electrophysiological properties and phase-locking characteristics to endogenous oscillations. This multi-modal approach markedly improves cell classification in humans, offers interpretable cell classes, and is applicable to other brain areas and species.


Assuntos
Potenciais de Ação/fisiologia , Encéfalo/fisiologia , Espaço Extracelular/fisiologia , Frequência Cardíaca/fisiologia , Fenômenos Biofísicos , Simulação por Computador , Eletrodos , Fenômenos Eletrofisiológicos , Coração/fisiologia , Humanos , Modelos Neurológicos , Movimento (Física) , Neurônios/fisiologia
9.
Neuron ; 100(5): 1194-1208.e5, 2018 12 05.
Artigo em Inglês | MEDLINE | ID: mdl-30392798

RESUMO

Gene expression studies suggest that differential ion channel expression contributes to differences in rodent versus human neuronal physiology. We tested whether h-channels more prominently contribute to the physiological properties of human compared to mouse supragranular pyramidal neurons. Single-cell/nucleus RNA sequencing revealed ubiquitous HCN1-subunit expression in excitatory neurons in human, but not mouse, supragranular layers. Using patch-clamp recordings, we found stronger h-channel-related membrane properties in supragranular pyramidal neurons in human temporal cortex, compared to mouse supragranular pyramidal neurons in temporal association area. The magnitude of these differences depended upon cortical depth and was largest in pyramidal neurons in deep L3. Additionally, pharmacologically blocking h-channels produced a larger change in membrane properties in human compared to mouse neurons. Finally, using biophysical modeling, we provide evidence that h-channels promote the transfer of theta frequencies from dendrite-to-soma in human L3 pyramidal neurons. Thus, h-channels contribute to between-species differences in a fundamental neuronal property.


Assuntos
Córtex Cerebral/fisiologia , Canais Disparados por Nucleotídeos Cíclicos Ativados por Hiperpolarização/fisiologia , Potenciais da Membrana , Canais de Potássio/fisiologia , Células Piramidais/fisiologia , Adulto , Animais , Membrana Celular/fisiologia , Córtex Cerebral/metabolismo , Feminino , Humanos , Canais Disparados por Nucleotídeos Cíclicos Ativados por Hiperpolarização/metabolismo , Masculino , Camundongos Endogâmicos C57BL , Camundongos Transgênicos , Modelos Neurológicos , Canais de Potássio/metabolismo , Células Piramidais/metabolismo , Especificidade da Espécie
10.
IEEE Trans Control Netw Syst ; 5(3): 1146-1156, 2018 Sep.
Artigo em Inglês | MEDLINE | ID: mdl-30984793

RESUMO

A popular approach to characterizing activity in neuronal networks is the use of statistical models that describe neurons in terms of their firing rates (i.e., the number of spikes produced per unit time). The output realization of a statistical model is, in essence, an n-dimensional binary time series, or pattern. While such models are commonly fit to data, they can also be postulated de novo, as a theoretical description of a given spiking network. More generally, they can model any network producing binary events as a function of time. In this paper, we rigorously develop a set of analyses that may be used to assay the controllability of a particular statistical spiking model, the point-process generalized linear model (PPGLM). Our analysis quantifies the ease or difficulty of inducing desired spiking patterns via an extrinsic input signal, thus providing a framework for basic network analysis, as well as for emerging applications such as neurostimulation design.

12.
Neural Netw ; 83: 11-20, 2016 Nov.
Artigo em Inglês | MEDLINE | ID: mdl-27541050

RESUMO

In this paper, we study how the dynamics of recurrent networks, formulated as general dynamical systems, mediate the recovery of sparse, time-varying signals. Our formulation resembles the well-described problem of compressed sensing, but in a dynamic setting. We specifically consider the problem of recovering a high-dimensional network input, over time, from observation of only a subset of the network states (i.e., the network output). Our goal is to ascertain how the network dynamics may enable recovery, even if classical methods fail at each time instant. We are particularly interested in understanding performance in scenarios where both the input and output are corrupted by disturbance and noise, respectively. Our main results consist of the development of analytical conditions, including a generalized observability criterion, that ensure exact and stable input recovery in a dynamic, recurrent network setting.


Assuntos
Redes Neurais de Computação , Compressão de Dados/métodos , Tempo
13.
J Anal Methods Chem ; 2014: 413616, 2014.
Artigo em Inglês | MEDLINE | ID: mdl-25057428

RESUMO

Six Sigma methodology has been successfully applied to daily operations by several leading global private firms including GE and Motorola, to leverage their net profits. Comparatively, limited studies have been conducted to find out whether this highly successful methodology can be applied to research and development (R&D). In the current study, we have reviewed and proposed a process for a probable integration of Six Sigma methodology to large-scale production of Penicillin G and its subsequent conversion to 6-aminopenicillanic acid (6-APA). It is anticipated that the important aspects of quality control and quality assurance will highly benefit from the integration of Six Sigma methodology in mass production of Penicillin G and/or its conversion to 6-APA.

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