A simulation study on the effects of dendritic morphology on layer V prefrontal pyramidal cell firing behaviour

Pyramidal cells, the most abundant neurons in neocortex, exhibit significant structural variability across different brain areas and layers in different species. Moreover, in response to a somatic step current, these cells display a range of firing behaviors, the most common being (1) repetitive action potentials (Regular Spiking—RS), and (2) an initial cluster of 2–5 action potentials with short interspike interval (ISIs) followed by single spikes (Intrinsic Bursting—IB). A correlation between firing behavior and dendritic morphology has recently been reported. In this work we use computational modeling to investigate quantitatively the effects of the basal dendritic tree morphology on the firing behavior of 112 three-dimensional reconstructions of layer V PFC rat pyramidal cells. Particularly, we focus on how different morphological (diameter, total length, volume, and branch number) and passive [Mean Electrotonic Path length (MEP)] features of basal dendritic trees shape somatic firing when the spatial distribution of ionic mechanisms in the basal dendritic trees is uniform or non-uniform. Our results suggest that total length, volume and branch number are the best morphological parameters to discriminate the cells as RS or IB, regardless of the distribution of ionic mechanisms in basal trees. The discriminatory power of total length, volume, and branch number remains high in the presence of different apical dendrites. These results suggest that morphological variations in the basal dendritic trees of layer V pyramidal neurons in the PFC influence their firing patterns in a predictive manner and may in turn influence the information processing capabilities of these neurons

Optically Induced Calcium-Dependent Gene Activation and Labeling of Active Neurons Using CaMPARI and Cal-Light

The advent of optogenetic methods has made it possible to use endogeneously produced molecules to image and manipulate cellular, subcellular, and synaptic activity. It has also led to the development of photoactivatable calcium-dependent indicators that mark active synapses, neurons, and circuits. Furthermore, calcium-dependent photoactivation can be used to trigger gene expression in active neurons. Here we describe two sets of protocols, one using CaMPARI and a second one using Cal-Light. CaMPARI, a calcium-modulated photoactivatable ratiometric integrator, enables rapid network-wide, tunable, all-optical functional circuit mapping. Cal-Light, a photoactivatable calcium sensor, while slower to respond than CaMPARI, has the capacity to trigger the expression of genes, including effectors, activators, indicators, or other constructs. Here we describe the rationale and provide procedures for using these two calcium-dependent constructs (1) in vitro in dissociated primary neuronal cell cultures (CaMPARI & Cal-Light); (2) in vitro in acute brain slices for circuit mapping (CaMPARI); (3) in vivo for triggering photoconversion or gene expression (CaMPARI & Cal-Light); and finally, (4) for recovering photoconverted neurons post-fixation with immunocytochemistry (CaMPARI). The approaches and protocols we describe are examples of the potential uses of both CaMPARI & Cal-Light. The ability to mark and manipulate neurons that are active during specific epochs of behavior has a vast unexplored experimental potential

26th Annual Computational Neuroscience Meeting (CNS*2017): Part 3 - Meeting Abstracts - Antwerp, Belgium. 15–20 July 2017

This work was produced as part of the activities of FAPESP Research,\ud Disseminations and Innovation Center for Neuromathematics (grant\ud 2013/07699-0, S. Paulo Research Foundation). NLK is supported by a\ud FAPESP postdoctoral fellowship (grant 2016/03855-5). ACR is partially\ud supported by a CNPq fellowship (grant 306251/2014-0)

Interplay of dendritic non-linearities and network size mediate persistent activity in a PFC microcircuit model

The ways in which neurons are embedded in a network to support various computations determines the functional output of the cortex. Recently, a number of in vivo studies have shown that dendritic integration in pyramidal neurons shapes neuronal function (Smith et al., 2013; Longordo et al., 2013) and that clusters of few reciprocally connected neurons are co-activated during behavioral tasks (Ko et al., 2011, 2013; Morishima et al., 2011). In the prefrontal cortex (PFC), such microcircuits are linked to persistent activity (prolonged spiking activity that exceeds stimulus presentation), which is the cellular correlate of working memory (Papoutsi et al., 2013). However, the effect of dendritic integration on the functional output of such small microcircuits has remained unexplored. In this work, we investigate the contribution of nonlinear dendritic properties to the induction and coding of upcoming state transitions in PFC microcircuits. Towards this goal we used a heavily constrained biophysical model of a layer 5 PFC microcircuit consisting of 7 pyramidal neurons and 2 interneurons implemented in the NEURON simulation environment. All neuron models are biophysically detailed but morphologically simplified and validated regarding their intrinsic, synaptic and connectivity properties (Papoutsi et al., 2013). Our results show that the non-linear integration of synaptic inputs at the basal dendrites of pyramidal neurons, mediated by the induction of NMDA spikes, is imperative for the emergence of the persistent state in the microcircuit: if synaptic drive is sufficient to induce NMDA spikes, the minimum network size required for persistent activity induction can be reduced down to 2 cells. In addition, slow synaptic mechanisms, such as the NMDA and GABAB currents, determine the ability of a given stimulus to induce persistent firing in the microcircuit model. On the other hand, the necessity for NMDA spikes disappears when persistent activity depends on larger scale networks (of the order of hundreds of neurons) with relaxed conductivity delays. Overall, this study zooms out from dendrites to cell assemblies and suggests that there is a tradeoff between dendritic non-linearities and network properties (size/connectivity) in mediating the short-memory function of the PFC

Προσέγγιση της παραμένουσας δραστηριότητας στον προμετωπιαίο φλοιό με τη χρήση υπολογιστικών μοντέλων

Working memory refers to the temporary storage of information and is strongly associated with the prefrontal cortex (PFC). Persistent activity of cortical neurons, namely the activity that persists beyond the stimulus presentation, is considered the cellular correlate of working memory. Although past studies suggested that this type of activity is characteristic of large scale networks, recent experimental evidence imply that small, tightly interconnected clusters of neurons in the cortex may support similar functionalities. In addition, very little is known about the biophysical mechanisms giving rise to persistent activity in small-sized microcircuits in the PFC. In this work, we developed biophysically detailed microcircuit models of morphologically simplified or detailed layer 5 PFC neurons that incorporated connectivity constraints and were validated against a multitude of experimental data. We used this microcircuit model to study the mechanisms that support persistent activity in a realistic framework. Our results show that PFC microcircuits can serve as tunable modules for persistent activity induction. We show that the underlying mechanisms are different when investigated in large-scaled compared to small-scaled networks: in microcircuits, persistent activity strongly depends on dendritic non-linearities and is shaped by the morphological properties of the basal dendrites, providing a link between dendritic morphology and neuronal function. Overall, this study zooms out from dendrites to cell assemblies and suggests a tight interaction between dendritic non-linearities, morphology and network properties that may facilitate the short-term memory function of the PFC. Our model generates a number of experimentally testable predictions that may lead to a better understanding of the physiological and pathological function of prefrontal cortex.Η μνήμη εργασίας είναι η προσωρινή αποθήκευση και επεξεργασία αισθητηριακής πληροφορίας και σχετίζεται κυρίως με αυξημένη νευρική δραστηριότητα στον προμετωπιαίο φλοιό. Τόσο οι πυραμιδικοί νευρώνες, όσο και οι ενδονευρώνες του προμετωπιαίου φλοιού παρουσιάζουν παραμένουσα δραστηριότητα, δηλαδή δραστηριότητα η οποία παραμένει μετά την απομάκρυνση ενός αισθητηριακού ερεθίσματος. Αν και προηγούμενες έρευνες υποστηρίζουν ότι η παραμένουσα δραστηριότητα είναι χαρακτηριστικό δικτύων μεγάλης κλίμακας, πρόσφατα πειραματικά δεδομένα έδειξαν ότι ο φλοιός εμφανίζει χαρακτηριστική μικρο-αρχιτεκτονική, όπου μικρός αριθμός νευρώνων δημιουργεί ανεξάρτητα αθροίσματα (μικροκυκλώματα) ικανά να υποστηρίξουν διάφορες λειτουργίες. Αν και είναι πειραματικά επιβεβαιωμένη η ύπαρξη αυτών των μικροκυκλωμάτων στον προμετωπιαίο φλοιό, μέχρι τώρα δεν έχει μελετηθεί η λειτουργία τους στην παραμένουσα δραστηριότητα. Στην παρούσα εργασία αναπτύξαμε λεπτομερή βιοφυσικά μοντέλα των αθροισμάτων με απλοποιημένη ή λεπτομερής μορφολογία της στιβάδας 5 του προμετωπιαίου φλοιού, των οποίων οι ιδιότητες (συνδεσμολογία / ηλεκτροφυσιολογικές ιδιότητες) βασίστηκαν εκτενώς σε πειραματικά δεδομένα, με σκοπό να μελετήσουμε την παραμένουσα δραστηριότητα σε ένα βιολογικά ρεαλιστικό πλαίσιο. Τα αποτελέσματά μας δείχνουν ότι τα μικροκυκλώματα του προμετωπιαίου φλοιού μπορούν να υποστηρίξουν παραμένουσα δραστηριότητα με διαφορετικές ιδιότητες. Οι μηχανισμοί που συμμετέχουν σε αυτή την δραστηριότητα είναι διαφορετικοί στα μεγάλης-κλίμακας σε σχέση με τα μικροκυκλώματα: στα μικροκυκλώματα, η παραμένουσα δραστηριότητα εξαρτάται από τη μη-γραμμική ολοκλήρωση των συναπτικών ερεθισμάτων σε δενδρίτες με περίπλοκη μορφολογία. Συνολικά, η μελέτη αυτή προτείνει ότι η στενή αλληλεπίδραση μεταξύ της μορφολογίας, της συναπτικής ολοκλήρωσης και των μικροκυκλωμάτων είναι αναγκαία για τη λειτουργία του προμετωπιαίου φλοιού στη μνήμη εργασίας. Το μοντέλο μας παράγει μια σειρά από πειραματικά ελέγξιμες προβλέψεις που μπορεί να οδηγήσουν σε καλύτερη κατανόηση της φυσιολογικής αλλά και της παθολογικής λειτουργίας του προμετωπιαίου φλοιού