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Article ; Online: Progress towards a cellularly resolved mouse mesoconnectome is empowered by data fusion and new neuroanatomy techniques.

Timonidis, Nestor / Tiesinga, Paul H E

2021 Volume 128, Page(s) 569–591

Abstract: Over the past decade there has been a rapid improvement in techniques for obtaining large-scale cellular level data related to the mouse brain connectome. However, a detailed mapping of cell-type-specific projection patterns is lacking, which would, for ... ...

Abstract	Over the past decade there has been a rapid improvement in techniques for obtaining large-scale cellular level data related to the mouse brain connectome. However, a detailed mapping of cell-type-specific projection patterns is lacking, which would, for instance, allow us to study the role of circuit motifs in cognitive processes. In this work, we review advanced neuroanatomical and data fusion techniques within the context of a proposed Multimodal Connectomic Integration Framework for augmenting the cellularly resolved mouse mesoconnectome. First, we emphasize the importance of registering data modalities to a common reference atlas. We then review a number of novel experimental techniques that can provide data for characterizing cell-types in the mouse brain. Furthermore, we examine a number of data integration strategies, which involve fine-grained cell-type classification, spatial inference of cell densities, latent variable models for the mesoconnectome and multi-modal factorisation. Finally, we discuss a number of use cases which depend on connectome augmentation techniques, such as model simulations of functional connectivity and generating mechanistic hypotheses for animal disease models.
MeSH term(s)	Animals ; Brain ; Connectome ; Mice ; Neuroanatomy
Language	English
Publishing date	2021-06-10
Publishing country	United States
Document type	Journal Article ; Research Support, Non-U.S. Gov't ; Review
ZDB-ID	282464-4
ISSN	1873-7528 ; 0149-7634
ISSN (online)	1873-7528
ISSN	0149-7634
DOI	10.1016/j.neubiorev.2021.06.016
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Article ; Online: Comprehensive characterization of oscillatory signatures in a model circuit with PV- and SOM-expressing interneurons.

Ter Wal, Marije / Tiesinga, Paul H E

Biological cybernetics

2021 Volume 115, Issue 5, Page(s) 487–517

Abstract: Neural circuits contain a wide variety of interneuron types, which differ in their biophysical properties and connectivity patterns. The two most common interneuron types, parvalbumin-expressing and somatostatin-expressing cells, have been shown to be ... ...

Abstract	Neural circuits contain a wide variety of interneuron types, which differ in their biophysical properties and connectivity patterns. The two most common interneuron types, parvalbumin-expressing and somatostatin-expressing cells, have been shown to be differentially involved in many cognitive functions. These cell types also show different relationships with the power and phase of oscillations in local field potentials. The mechanisms that underlie the emergence of different oscillatory rhythms in neural circuits with more than one interneuron subtype, and the roles specific interneurons play in those mechanisms, are not fully understood. Here, we present a comprehensive analysis of all possible circuit motifs and input regimes that can be achieved in circuits comprised of excitatory cells, PV-like fast-spiking interneurons and SOM-like low-threshold spiking interneurons. We identify 18 unique motifs and simulate their dynamics over a range of input strengths. Using several characteristics, such as oscillation frequency, firing rates, phase of firing and burst fraction, we cluster the resulting circuit dynamics across motifs in order to identify patterns of activity and compare these patterns to behaviors that were generated in circuits with one interneuron type. In addition to the well-known PING and ING gamma oscillations and an asynchronous state, our analysis identified three oscillatory behaviors that were generated by the three-cell-type motifs only: theta-nested gamma oscillations, stable beta oscillations and theta-locked bursting behavior, which have also been observed in experiments. Our characterization provides a map to interpret experimental activity patterns and suggests pharmacological manipulations or optogenetics approaches to validate these conclusions.
MeSH term(s)	Interneurons ; Parvalbumins
Chemical Substances	Parvalbumins
Language	English
Publishing date	2021-10-09
Publishing country	Germany
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	220699-7
ISSN	1432-0770 ; 0340-1200
ISSN (online)	1432-0770
ISSN	0340-1200
DOI	10.1007/s00422-021-00894-6
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Zs.A 1279: Show issues

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Article ; Online: Flexible Frequency Switching in Adult Mouse Visual Cortex Is Mediated by Competition Between Parvalbumin and Somatostatin Expressing Interneurons.

Domhof, Justin W M / Tiesinga, Paul H E

Neural computation

2021 Volume 33, Issue 4, Page(s) 926–966

Abstract: Neuronal networks in rodent primary visual cortex (V1) can generate oscillations in different frequency bands depending on the network state and the level of visual stimulation. High-frequency gamma rhythms, for example, dominate the network's ... ...

Abstract	Neuronal networks in rodent primary visual cortex (V1) can generate oscillations in different frequency bands depending on the network state and the level of visual stimulation. High-frequency gamma rhythms, for example, dominate the network's spontaneous activity in adult mice but are attenuated upon visual stimulation, during which the network switches to the beta band instead. The spontaneous local field potential (LFP) of juvenile mouse V1, however, mainly contains beta rhythms and presenting a stimulus does not elicit drastic changes in network oscillations. We study, in a spiking neuron network model, the mechanism in adult mice allowing for flexible switches between multiple frequency bands and contrast this to the network structure in juvenile mice that lack this flexibility. The model comprises excitatory pyramidal cells (PCs) and two types of interneurons: the parvalbumin-expressing (PV) and the somatostatinexpressing (SOM) interneuron. In accordance with experimental findings, the pyramidal-PV and pyramidal-SOM cell subnetworks are associated with gamma and beta oscillations, respectively. In our model, they are both generated via a pyramidal-interneuron gamma (PING) mechanism, wherein the PCs drive the oscillations. Furthermore, we demonstrate that large but not small visual stimulation activates SOM cells, which shift the frequency of resting-state gamma oscillations produced by the pyramidal-PV cell subnetwork so that beta rhythms emerge. Finally, we show that this behavior is obtained for only a subset of PV and SOM interneuron projection strengths, indicating that their influence on the PCs should be balanced so that they can compete for oscillatory control of the PCs. In sum, we propose a mechanism by which visual beta rhythms can emerge from spontaneous gamma oscillations in a network model of the mouse V1; for this mechanism to reproduce V1 dynamics in adult mice, balance between the effective strengths of PV and SOM cells is required.
Language	English
Publishing date	2021-03-17
Publishing country	United States
Document type	Journal Article
ZDB-ID	1025692-1
ISSN	1530-888X ; 0899-7667
ISSN (online)	1530-888X
ISSN	0899-7667
DOI	10.1162/neco_a_01369
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Article ; Online: Uncovering Statistical Links Between Gene Expression and Structural Connectivity Patterns in the Mouse Brain.

Timonidis, Nestor / Llera, Alberto / Tiesinga, Paul H E

Neuroinformatics

2021 Volume 19, Issue 4, Page(s) 649–667

Abstract: Finding links between genes and structural connectivity is of the utmost importance for unravelling the underlying mechanism of the brain connectome. In this study we identify links between the gene expression and the axonal projection density in the ... ...

Abstract	Finding links between genes and structural connectivity is of the utmost importance for unravelling the underlying mechanism of the brain connectome. In this study we identify links between the gene expression and the axonal projection density in the mouse brain, by applying a modified version of the Linked ICA method to volumetric data from the Allen Institute for Brain Science for identifying independent sources of information that link both modalities at the voxel level. We performed separate analyses on sets of projections from the visual cortex, the caudoputamen and the midbrain reticular nucleus, and we determined those brain areas, injections and genes that were most involved in independent components that link both gene expression and projection density data, while we validated their biological context through enrichment analysis. We identified representative and literature-validated cortico-midbrain and cortico-striatal projections, whose gene subsets were enriched with annotations for neuronal and synaptic function and related developmental and metabolic processes. The results were highly reproducible when including all available projections, as well as consistent with factorisations obtained using the Dictionary Learning and Sparse Coding technique. Hence, Linked ICA yielded reproducible independent components that were preserved under increasing data variance. Taken together, we have developed and validated a novel paradigm for linking gene expression and structural projection patterns in the mouse mesoconnectome, which can power future studies aiming to relate genes to brain function.
MeSH term(s)	Animals ; Axons ; Brain/diagnostic imaging ; Connectome ; Corpus Striatum ; Gene Expression ; Mice
Language	English
Publishing date	2021-03-11
Publishing country	United States
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	2111941-7
ISSN	1559-0089 ; 1539-2791
ISSN (online)	1559-0089
ISSN	1539-2791
DOI	10.1007/s12021-021-09511-0
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Article: Translating single-neuron axonal reconstructions into meso-scale connectivity statistics in the mouse somatosensory thalamus.

Timonidis, Nestor / Bakker, Rembrandt / Rubio-Teves, Mario / Alonso-Martínez, Carmen / Garcia-Amado, Maria / Clascá, Francisco / Tiesinga, Paul H E

Frontiers in neuroinformatics

2023 Volume 17, Page(s) 1272243

Abstract: Characterizing the connectomic and morphological diversity of thalamic neurons is key for better understanding how the thalamus relays sensory inputs to the cortex. The recent public release of complete single-neuron morphological reconstructions enables ...

Abstract	Characterizing the connectomic and morphological diversity of thalamic neurons is key for better understanding how the thalamus relays sensory inputs to the cortex. The recent public release of complete single-neuron morphological reconstructions enables the analysis of previously inaccessible connectivity patterns from individual neurons. Here we focus on the Ventral Posteromedial (VPM) nucleus and characterize the full diversity of 257 VPM neurons, obtained by combining data from the MouseLight and Braintell projects. Neurons were clustered according to their most dominantly targeted cortical area and further subdivided by their jointly targeted areas. We obtained a 2D embedding of morphological diversity using the dissimilarity between all pairs of axonal trees. The curved shape of the embedding allowed us to characterize neurons by a 1-dimensional coordinate. The coordinate values were aligned both with the progression of soma position along the dorsal-ventral and lateral-medial axes and with that of axonal terminals along the posterior-anterior and medial-lateral axes, as well as with an increase in the number of branching points, distance from soma and branching width. Taken together, we have developed a novel workflow for linking three challenging aspects of connectomics, namely the topography, higher order connectivity patterns and morphological diversity, with VPM as a test-case. The workflow is linked to a unified access portal that contains the morphologies and integrated with 2D cortical flatmap and subcortical visualization tools. The workflow and resulting processed data have been made available in Python, and can thus be used for modeling and experimentally validating new hypotheses on thalamocortical connectivity.
Language	English
Publishing date	2023-12-01
Publishing country	Switzerland
Document type	Journal Article
ZDB-ID	2452979-5
ISSN	1662-5196
ISSN	1662-5196
DOI	10.3389/fninf.2023.1272243
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Article ; Online: Motifs in health and disease: the promise of circuit interrogation by optogenetics.

Tiesinga, Paul H E

The European journal of neuroscience

2012 Volume 36, Issue 2, Page(s) 2260–2272

Abstract: Identifying the dominant dynamical motifs in cortical circuits and determining their functional relevance is of the utmost importance to understand the underlying mechanisms of psychiatric diseases and to develop effective therapies. Optogenetics can be ... ...

Abstract	Identifying the dominant dynamical motifs in cortical circuits and determining their functional relevance is of the utmost importance to understand the underlying mechanisms of psychiatric diseases and to develop effective therapies. Optogenetics can be used to interrogate cortical circuits to determine the dominant motif and thereby identify the relevant biophysical time scales that set the oscillation frequency. We review how computational models of cortical networks can help guide optogenetics experiments. We focus our attention on the pyramidal interneuron gamma motif, which is comprised of reciprocally connected excitatory and inhibitory neurons, and determine how the different biophysical time scales of the circuit components are reflected in the resonance of the power in the local field potential at the frequency of stimulation as a function of that frequency. Cardin et al. [J.A. Cardin et al. (2009)Nature, 459, 663-667] find that periodic stimulation of inhibitory cells leads to a resonance at gamma frequencies (30-80 Hz), but that stimulation of excitatory cells does not lead to a resonance. We can account for these results when the pyramidal cells are endowed with an intrinsic frequency preference due to a slow hyperpolarizing current. Furthermore, when fast α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid (AMPA)-mediated excitatory currents are replaced by slow N-methyl-d-aspartate (NMDA)-mediated ones in inhibitory cells, the gamma frequency resonance is reduced; however, when the same replacement is made in excitatory cells, gamma oscillations are enhanced. The results are relevant to schizophrenia, because there is evidence that NMDA receptors on parvalbumin-positive cells are primarily affected and that the regulation of gamma oscillations is impaired.
MeSH term(s)	Brain Waves/physiology ; Cerebral Cortex/physiology ; Evoked Potentials/physiology ; Humans ; Models, Neurological ; Neural Inhibition/physiology ; Photic Stimulation/methods ; Schizophrenia/physiopathology
Language	English
Publishing date	2012-07
Publishing country	France
Document type	Journal Article ; Research Support, Non-U.S. Gov't ; Review
ZDB-ID	645180-9
ISSN	1460-9568 ; 0953-816X
ISSN (online)	1460-9568
ISSN	0953-816X
DOI	10.1111/j.1460-9568.2012.08186.x
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Article ; Online: Multiple Midfrontal Thetas Revealed by Source Separation of Simultaneous MEG and EEG.

Zuure, Marrit B / Hinkley, Leighton B / Tiesinga, Paul H E / Nagarajan, Srikantan S / Cohen, Michael X

The Journal of neuroscience : the official journal of the Society for Neuroscience

2020 Volume 40, Issue 40, Page(s) 7702–7713

Abstract: Theta-band (∼6 Hz) rhythmic activity within and over the medial PFC ("midfrontal theta") has been identified as a distinctive signature of "response conflict," the competition between multiple actions when only one action is goal-relevant. Midfrontal ... ...

Abstract	Theta-band (∼6 Hz) rhythmic activity within and over the medial PFC ("midfrontal theta") has been identified as a distinctive signature of "response conflict," the competition between multiple actions when only one action is goal-relevant. Midfrontal theta is traditionally conceptualized and analyzed under the assumption that it is a unitary signature of conflict that can be uniquely identified at one electrode (typically FCz). Here we recorded simultaneous MEG and EEG (total of 328 sensors) in 9 human subjects (7 female) and applied a feature-guided multivariate source-separation decomposition to determine whether conflict-related midfrontal theta is a unitary or multidimensional feature of the data. For each subject, a generalized eigendecomposition yielded spatial filters (components) that maximized the ratio between theta and broadband activity. Components were retained based on significance thresholding and midfrontal EEG topography. All of the subjects individually exhibited multiple (mean 5.89, SD 2.47) midfrontal components that contributed to sensor-level midfrontal theta power during the task. Component signals were temporally uncorrelated and asynchronous, suggesting that each midfrontal theta component was unique. Our findings call into question the dominant notion that midfrontal theta represents a unitary process. Instead, we suggest that midfrontal theta spans a multidimensional space, indicating multiple origins, but can manifest as a single feature at the sensor level because of signal mixing.
MeSH term(s)	Adult ; Conflict, Psychological ; Female ; Frontal Lobe/physiology ; Humans ; Magnetoencephalography/methods ; Male ; Theta Rhythm
Language	English
Publishing date	2020-09-08
Publishing country	United States
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	604637-x
ISSN	1529-2401 ; 0270-6474
ISSN (online)	1529-2401
ISSN	0270-6474
DOI	10.1523/JNEUROSCI.0321-20.2020
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Article: Phase Difference between Model Cortical Areas Determines Level of Information Transfer.

Ter Wal, Marije / Tiesinga, Paul H

Frontiers in computational neuroscience

2017 Volume 11, Page(s) 6

Abstract: Communication between cortical sites is mediated by long-range synaptic connections. However, these connections are relatively static, while everyday cognitive tasks demand a fast and flexible routing of information in the brain. Synchronization of ... ...

Abstract	Communication between cortical sites is mediated by long-range synaptic connections. However, these connections are relatively static, while everyday cognitive tasks demand a fast and flexible routing of information in the brain. Synchronization of activity between distant cortical sites has been proposed as the mechanism underlying such a dynamic communication structure. Here, we study how oscillatory activity affects the excitability and input-output relation of local cortical circuits and how it alters the transmission of information between cortical circuits. To this end, we develop model circuits showing fast oscillations by the PING mechanism, of which the oscillatory characteristics can be altered. We identify conditions for synchronization between two brain circuits and show that the level of intercircuit coherence and the phase difference is set by the frequency difference between the intrinsic oscillations. We show that the susceptibility of the circuits to inputs, i.e., the degree of change in circuit output following input pulses, is not uniform throughout the oscillation period and that both firing rate, frequency and power are differentially modulated by inputs arriving at different phases. As a result, an appropriate phase difference between the circuits is critical for the susceptibility windows of the circuits in the network to align and for information to be efficiently transferred. We demonstrate that changes in synchrony and phase difference can be used to set up or abolish information transfer in a network of cortical circuits.
Language	English
Publishing date	2017-02-09
Publishing country	Switzerland
Document type	Journal Article
ZDB-ID	2452964-3
ISSN	1662-5188
ISSN	1662-5188
DOI	10.3389/fncom.2017.00006
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Article: Connectomic Analysis of Brain Networks: Novel Techniques and Future Directions.

Cazemier, J Leonie / Clascá, Francisco / Tiesinga, Paul H E

Frontiers in neuroanatomy

2016 Volume 10, Page(s) 110

Abstract: Brain networks, localized or brain-wide, exist only at the cellular level, i.e., between specific pre- and post-synaptic neurons, which are connected through functionally diverse synapses located at specific points of their cell membranes. "Connectomics" ...

Abstract	Brain networks, localized or brain-wide, exist only at the cellular level, i.e., between specific pre- and post-synaptic neurons, which are connected through functionally diverse synapses located at specific points of their cell membranes. "Connectomics" is the emerging subfield of neuroanatomy explicitly aimed at elucidating the wiring of brain networks with cellular resolution and a quantified accuracy. Such data are indispensable for realistic modeling of brain circuitry and function. A connectomic analysis, therefore, needs to identify and measure the soma, dendrites, axonal path, and branching patterns together with the synapses and gap junctions of the neurons involved in any given brain circuit or network. However, because of the submicron caliber, 3D complexity, and high packing density of most such structures, as well as the fact that axons frequently extend over long distances to make synapses in remote brain regions, creating connectomic maps is technically challenging and requires multi-scale approaches, Such approaches involve the combination of the most sensitive cell labeling and analysis methods available, as well as the development of new ones able to resolve individual cells and synapses with increasing high-throughput. In this review, we provide an overview of recently introduced high-resolution methods, which researchers wanting to enter the field of connectomics may consider. It includes several molecular labeling tools, some of which specifically label synapses, and covers a number of novel imaging tools such as brain clearing protocols and microscopy approaches. Apart from describing the tools, we also provide an assessment of their qualities. The criteria we use assess the qualities that tools need in order to contribute to deciphering the key levels of circuit organization. We conclude with a brief future outlook for neuroanatomic research, computational methods, and network modeling, where we also point out several outstanding issues like structure-function relations and the complexity of neural models.
Language	English
Publishing date	2016-11-09
Publishing country	Switzerland
Document type	Review ; Journal Article
ZDB-ID	2452969-2
ISSN	1662-5129
ISSN	1662-5129
DOI	10.3389/fnana.2016.00110
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Article ; Online: Sensitivity to Stimulus Irregularity Is Inherent in Neural Networks.

van Gils, Teun / Tiesinga, Paul H E / Englitz, Bernhard / Martens, Marijn B

Neural computation

2019 Volume 31, Issue 9, Page(s) 1789–1824

Abstract: Behavior is controlled by complex neural networks in which neurons process thousands of inputs. However, even short spike trains evoked in a single cortical neuron were demonstrated to be sufficient to influence behavior in vivo. Specifically, irregular ... ...

Abstract	Behavior is controlled by complex neural networks in which neurons process thousands of inputs. However, even short spike trains evoked in a single cortical neuron were demonstrated to be sufficient to influence behavior in vivo. Specifically, irregular sequences of interspike intervals (ISIs) had a more reliable influence on behavior despite their resemblance to stochastic activity. Similarly, irregular tactile stimulation led to higher rates of behavioral responses. In this study, we identify the mechanisms enabling this sensitivity to stimulus irregularity (SSI) on the neuronal and network levels using simulated spiking neural networks. Matching in vivo experiments, we find that irregular stimulation elicits more detectable network events (bursts) than regular stimulation. Dissecting the stimuli, we identify short ISIs-occurring more frequently in irregular stimulations-as the main drivers of SSI rather than complex irregularity per se. In addition, we find that short-term plasticity modulates SSI. We subsequently eliminate the different mechanisms in turn to assess their role in generating SSI. Removing inhibitory interneurons, we find that SSI is retained, suggesting that SSI is not dependent on inhibition. Removing recurrency, we find that SSI is retained due to the ability of individual neurons to integrate activity over short timescales ("cell memory"). Removing single-neuron dynamics, we find that SSI is retained based on the short-term retention of activity within the recurrent network structure ("network memory"). Finally, using a further simplified probabilistic model, we find that local network structure is not required for SSI. Hence, SSI is identified as a general property that we hypothesize to be ubiquitous in neural networks with different structures and biophysical properties. Irregular sequences contain shorter ISIs, which are the main drivers underlying SSI. The experimentally observed SSI should thus generalize to other systems, suggesting a functional role for irregular activity in cortex.
MeSH term(s)	Action Potentials/physiology ; Animals ; Nerve Net/cytology ; Nerve Net/physiology ; Neural Networks, Computer ; Neurons/physiology ; Somatosensory Cortex/cytology ; Somatosensory Cortex/physiology ; Synapses/physiology
Language	English
Publishing date	2019-07-23
Publishing country	United States
Document type	Letter ; Research Support, Non-U.S. Gov't
ZDB-ID	1025692-1
ISSN	1530-888X ; 0899-7667
ISSN (online)	1530-888X
ISSN	0899-7667
DOI	10.1162/neco_a_01215
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