1
|
Searching for the principles of a less artificial A.I. INFORMATICS IN MEDICINE UNLOCKED 2022. [DOI: 10.1016/j.imu.2022.101018] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022] Open
|
2
|
Batta I, Yao Q, Sabrin KM, Dovrolis C. A weighted network analysis framework for the hourglass effect-And its application in the C. elegans connectome. PLoS One 2021; 16:e0249846. [PMID: 34705821 PMCID: PMC8550382 DOI: 10.1371/journal.pone.0249846] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/05/2021] [Accepted: 09/09/2021] [Indexed: 11/18/2022] Open
Abstract
Understanding hierarchy and modularity in natural as well as technological networks is of utmost importance. A major aspect of such analysis involves identifying the nodes that are crucial to the overall processing structure of the network. More recently, the approach of hourglass analysis has been developed for the purpose of quantitatively analyzing whether only a few intermediate nodes mediate the information processing between a large number of inputs and outputs of a network. We develop a new framework for hourglass analysis that takes network weights into account while identifying the core nodes and the extent of hourglass effect in a given weighted network. We use this framework to study the structural connectome of the C. elegans and identify intermediate neurons that form the core of sensori-motor pathways in the organism. Our results show that the neurons forming the core of the connectome show significant differences across the male and hermaphrodite sexes, with most core nodes in the male concentrated in sex-organs while they are located in the head for the hermaphrodite. Our work demonstrates that taking weights into account for network analysis framework leads to emergence of different network patterns in terms of identification of core nodes and hourglass structure in the network, which otherwise would be missed by unweighted approaches.
Collapse
Affiliation(s)
- Ishaan Batta
- School of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, Georgia, United States of America
| | - Qihang Yao
- School of Computer Science, Georgia Institute of Technology, Atlanta, Georgia, United States of America
| | - Kaeser M. Sabrin
- School of Computer Science, Georgia Institute of Technology, Atlanta, Georgia, United States of America
| | - Constantine Dovrolis
- School of Computer Science, Georgia Institute of Technology, Atlanta, Georgia, United States of America
| |
Collapse
|
3
|
Güntürkün O, von Eugen K, Packheiser J, Pusch R. Avian pallial circuits and cognition: A comparison to mammals. Curr Opin Neurobiol 2021; 71:29-36. [PMID: 34562800 DOI: 10.1016/j.conb.2021.08.007] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/07/2021] [Revised: 08/23/2021] [Accepted: 08/25/2021] [Indexed: 12/27/2022]
Abstract
Cognitive functions are similar in birds and mammals. So, are therefore pallial cellular circuits and neuronal computations also alike? In search of answers, we move in from bird's pallial connectomes, to cortex-like sensory canonical circuits and connections, to forebrain micro-circuitries and finally to the avian "prefrontal" area. This voyage from macro- to micro-scale networks and areas reveals that both birds and mammals evolved similar neural and computational properties in either convergent or parallel manner, based upon circuitries inherited from common ancestry. Thus, these two vertebrate classes evolved separately within 315 million years with highly similar pallial architectures that produce comparable cognitive functions.
Collapse
Affiliation(s)
- Onur Güntürkün
- Department of Biopsychology, Institute of Cognitive Neuroscience, Faculty of Psychology, Ruhr University Bochum, Universitätsstraße 150, 44801, Bochum, Germany.
| | - Kaya von Eugen
- Department of Biopsychology, Institute of Cognitive Neuroscience, Faculty of Psychology, Ruhr University Bochum, Universitätsstraße 150, 44801, Bochum, Germany
| | - Julian Packheiser
- Department of Biopsychology, Institute of Cognitive Neuroscience, Faculty of Psychology, Ruhr University Bochum, Universitätsstraße 150, 44801, Bochum, Germany
| | - Roland Pusch
- Department of Biopsychology, Institute of Cognitive Neuroscience, Faculty of Psychology, Ruhr University Bochum, Universitätsstraße 150, 44801, Bochum, Germany
| |
Collapse
|
4
|
Sando SR, Bhatla N, Lee EL, Horvitz HR. An hourglass circuit motif transforms a motor program via subcellularly localized muscle calcium signaling and contraction. eLife 2021; 10:59341. [PMID: 34212858 PMCID: PMC8331187 DOI: 10.7554/elife.59341] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/26/2020] [Accepted: 06/26/2021] [Indexed: 12/27/2022] Open
Abstract
Neural control of muscle function is fundamental to animal behavior. Many muscles can generate multiple distinct behaviors. Nonetheless, individual muscle cells are generally regarded as the smallest units of motor control. We report that muscle cells can alter behavior by contracting subcellularly. We previously discovered that noxious tastes reverse the net flow of particles through the C. elegans pharynx, a neuromuscular pump, resulting in spitting. We now show that spitting results from the subcellular contraction of the anterior region of the pm3 muscle cell. Subcellularly localized calcium increases accompany this contraction. Spitting is controlled by an ‘hourglass’ circuit motif: parallel neural pathways converge onto a single motor neuron that differentially controls multiple muscles and the critical subcellular muscle compartment. We conclude that subcellular muscle units enable modulatory motor control and propose that subcellular muscle contraction is a fundamental mechanism by which neurons can reshape behavior.
Collapse
Affiliation(s)
- Steven R Sando
- Howard Hughes Medical Institute, Department of Biology, McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, United States
| | - Nikhil Bhatla
- Howard Hughes Medical Institute, Department of Biology, McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, United States.,Miller Institute, Helen Wills Neuroscience Institute, Department of Molecular and Cellular Biology, University of California, Berkeley, Berkeley, United States.,Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, United States
| | - Eugene Lq Lee
- Howard Hughes Medical Institute, Department of Biology, McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, United States.,Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, United States
| | - H Robert Horvitz
- Howard Hughes Medical Institute, Department of Biology, McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, United States
| |
Collapse
|
5
|
Batta I, Yao Q, Sabrin KM, Dovrolis C. A Weighted Network Analysis Framework for the Hourglass Effect — and its Application in the C. Elegans Connectome.. [DOI: 10.1101/2021.03.19.436224] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/27/2023]
Abstract
ABSTRACTUnderstanding hierarchy and modularity in natural as well as technological networks is of utmost importance. A major aspect of such analysis involves identifying the nodes that are crucial to the overall processing structure of the network. More recently, the approach of hourglass analysis has been developed for the purpose of quantitatively analyzing whether only a few intermediate nodes mediate the information processing between a large number of inputs and outputs of a network. We develop a new framework for hourglass analysis that takes network weights into account while identifying the core nodes and the extent of hourglass effect in a given weighted network. We use this framework to study the structural connectome of theC. elegansand identify intermediate neurons that form the core of sensori-motor pathways in the organism. Our results show that the neurons forming the core of the connectome show significant differences across the male and hermaphrodite sexes, with most core nodes in the male concentrated in sex-organs while they are located in the head for the hermaphrodite. Our work demonstrates that taking weights into account for network analysis framework leads to emergence of different network patterns in terms of identification of core nodes and hourglass structure in the network, which otherwise would be missed by unweighted approaches.
Collapse
|
6
|
George VK, Puppo F, Silva GA. Computing Temporal Sequences Associated With Dynamic Patterns on the C. elegans Connectome. Front Syst Neurosci 2021; 15:564124. [PMID: 33767613 PMCID: PMC7985353 DOI: 10.3389/fnsys.2021.564124] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/20/2020] [Accepted: 02/04/2021] [Indexed: 12/03/2022] Open
Abstract
Understanding how the structural connectivity and spatial geometry of a network constrains the dynamics it is able to support is an active and open area of research. We simulated the plausible dynamics resulting from the known C. elegans connectome using a recent model and theoretical analysis that computes the dynamics of neurobiological networks by focusing on how local interactions among connected neurons give rise to the global dynamics in an emergent way. We studied the dynamics which resulted from stimulating a chemosensory neuron (ASEL) in a known feeding circuit, both in isolation and embedded in the full connectome. We show that contralateral motorneuron activations in ventral (VB) and dorsal (DB) classes of motorneurons emerged from the simulations, which are qualitatively similar to rhythmic motorneuron firing pattern associated with locomotion of the worm. One interpretation of these results is that there is an inherent-and we propose-purposeful structural wiring to the C. elegans connectome that has evolved to serve specific behavioral functions. To study network signaling pathways responsible for the dynamics we developed an analytic framework that constructs Temporal Sequences (TSeq), time-ordered walks of signals on graphs. We found that only 5% of TSeq are preserved between the isolated feeding network relative to its embedded counterpart. The remaining 95% of signaling pathways computed in the isolated network are not present in the embedded network. This suggests a cautionary note for computational studies of isolated neurobiological circuits and networks.
Collapse
Affiliation(s)
- Vivek Kurien George
- Department of Bioengineering, University of California, San Diego, San Diego, CA, United States
- Center for Engineered Natural Intelligence, University of California, San Diego, San Diego, CA, United States
| | - Francesca Puppo
- Department of Bioengineering, University of California, San Diego, San Diego, CA, United States
- Center for Engineered Natural Intelligence, University of California, San Diego, San Diego, CA, United States
- BioCircuits Institute, University of California, San Diego, San Diego, CA, United States
| | - Gabriel A. Silva
- Department of Bioengineering, University of California, San Diego, San Diego, CA, United States
- Center for Engineered Natural Intelligence, University of California, San Diego, San Diego, CA, United States
- BioCircuits Institute, University of California, San Diego, San Diego, CA, United States
- Department of Neurosciences, University of California, San Diego, San Diego, CA, United States
| |
Collapse
|
7
|
Structural and developmental principles of neuropil assembly in C. elegans. Nature 2021; 591:99-104. [PMID: 33627875 PMCID: PMC8385650 DOI: 10.1038/s41586-020-03169-5] [Citation(s) in RCA: 44] [Impact Index Per Article: 14.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/21/2020] [Accepted: 11/12/2020] [Indexed: 01/31/2023]
Abstract
Neuropil is a fundamental form of tissue organization within the brain1, in which densely packed neurons synaptically interconnect into precise circuit architecture2,3. However, the structural and developmental principles that govern this nanoscale precision remain largely unknown4,5. Here we use an iterative data coarse-graining algorithm termed 'diffusion condensation'6 to identify nested circuit structures within the Caenorhabditis elegans neuropil, which is known as the nerve ring. We show that the nerve ring neuropil is largely organized into four strata that are composed of related behavioural circuits. The stratified architecture of the neuropil is a geometrical representation of the functional segregation of sensory information and motor outputs, with specific sensory organs and muscle quadrants mapping onto particular neuropil strata. We identify groups of neurons with unique morphologies that integrate information across strata and that create neural structures that cage the strata within the nerve ring. We use high resolution light-sheet microscopy7,8 coupled with lineage-tracing and cell-tracking algorithms9,10 to resolve the developmental sequence and reveal principles of cell position, migration and outgrowth that guide stratified neuropil organization. Our results uncover conserved structural design principles that underlie the architecture and function of the nerve ring neuropil, and reveal a temporal progression of outgrowth-based on pioneer neurons-that guides the hierarchical development of the layered neuropil. Our findings provide a systematic blueprint for using structural and developmental approaches to understand neuropil organization within the brain.
Collapse
|
8
|
Shadi K, Dyer E, Dovrolis C. Multisensory integration in the mouse cortical connectome using a network diffusion model. Netw Neurosci 2020; 4:1030-1054. [PMID: 33195947 PMCID: PMC7655044 DOI: 10.1162/netn_a_00164] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/18/2019] [Accepted: 08/03/2020] [Indexed: 01/05/2023] Open
Abstract
Having a structural network representation of connectivity in the brain is instrumental in analyzing communication dynamics and neural information processing. In this work, we make steps towards understanding multisensory information flow and integration using a network diffusion approach. In particular, we model the flow of evoked activity, initiated by stimuli at primary sensory regions, using the asynchronous linear threshold (ALT) diffusion model. The ALT model captures how evoked activity that originates at a given region of the cortex “ripples through” other brain regions (referred to as an activation cascade). We find that a small number of brain regions–the claustrum and the parietal temporal cortex being at the top of the list–are involved in almost all cortical sensory streams. This suggests that the cortex relies on an hourglass architecture to first integrate and compress multisensory information from multiple sensory regions, before utilizing that lower dimensionality representation in higher level association regions and more complex cognitive tasks. Having a structural network representation of connectivity in the brain is instrumental in analyzing communication dynamics and neural information processing. In this work, we make steps towards understanding multisensory information flow and integration using a network diffusion approach. In particular, we model the flow of evoked activity, initiated by stimuli at primary sensory regions, using the asynchronous linear threshold (ALT) diffusion model. The ALT model captures how evoked activity that originates at a given region of the cortex “ripples through” other brain regions (referred to as an activation cascade). We apply the ALT model to the mouse connectome provided by the Allen Institute for Brain Science. A first result, using functional datasets based on voltage-sensitive dye (VSD) imaging, is that the ALT model, despite its simplicity, predicts the temporal ordering of each sensory activation cascade quite accurately. We further apply this model to study multisensory integration and find that a small number of brain regionsthe claustrum and the parietal temporal cortex being at the top of the listare involved in almost all cortical sensory streams. This suggests that the cortex relies on an hourglass architecture to first integrate and compress multisensory information from multiple sensory regions, before utilizing that lower dimensionality representation in higher level association regions and more complex cognitive tasks.
Collapse
Affiliation(s)
- Kamal Shadi
- School of Computer Science, Georgia Institute of Technology, Atlanta, GA, USA
| | - Eva Dyer
- Department of Biomedical Engineering, Georgia Institute of Technology, Atlanta, GA, USA
| | | |
Collapse
|