1
|
Gelperin A, Ambrosini AE. Quantitative Characterization of Output from the Directionally Selective Visual Interneuron H1 in the Grey Flesh Fly Sarcophaga bullata. JOURNAL OF UNDERGRADUATE NEUROSCIENCE EDUCATION : JUNE : A PUBLICATION OF FUN, FACULTY FOR UNDERGRADUATE NEUROSCIENCE 2021; 20:A88-A99. [PMID: 35540945 PMCID: PMC9053427] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Subscribe] [Scholar Register] [Received: 06/08/2021] [Revised: 08/31/2021] [Accepted: 09/20/2021] [Indexed: 06/14/2023]
Abstract
H1, a very well-studied insect visual interneuron, has a panoramic receptive field and is directionally selective in responding to optic flow. The synaptic basis for the directional selectivity of the H1 neuron has been studied using both theoretical and cellular approaches. Extracellular single-unit recordings are readily obtained by beginning students using commercially available adults of the grey flesh fly Sarcophaga bullata. We describe an apparatus which allows students to present a series of moving visual stimuli to the eye of the restrained, minimally dissected adult Sarcophaga, while recording both the single unit responses of the H1 neuron and the position and velocity of the moving stimulus. Students obtain quantitative and reproducible responses of H1, probing the response properties of the neuron by modulating stimulus parameters such as: direction and speed of movement, visual contrast, spatial wavelength, or the extent of the visual field occupied. Students learn to perform quantitative analysis of their data and to generate graphical representations of their results characterizing the tuning and receptive field of this neuron. This exercise demonstrates the utility of single unit recording of an identified interneuron in an awake restrained insect and promotes interpretation of these results in terms of the visual stimuli normally encountered by freely flying flies in their natural environment.
Collapse
Affiliation(s)
- Alan Gelperin
- Princeton Neuroscience Institute, Princeton University, Princeton, NJ 08544
| | | |
Collapse
|
2
|
Carter O, van Swinderen B, Leopold DA, Collin S, Maier A. Perceptual rivalry across animal species. J Comp Neurol 2020; 528:3123-3133. [PMID: 32361986 PMCID: PMC7541519 DOI: 10.1002/cne.24939] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/15/2020] [Revised: 04/18/2020] [Accepted: 04/20/2020] [Indexed: 01/10/2023]
Abstract
This review in memoriam of Jack Pettigrew provides an overview of past and current research into the phenomenon of multistable perception across multiple animal species. Multistable perception is characterized by two or more perceptual interpretations spontaneously alternating, or rivaling, when animals are exposed to stimuli with inherent sensory ambiguity. There is a wide array of ambiguous stimuli across sensory modalities, ranging from the configural changes observed in simple line drawings, such as the famous Necker cube, to the alternating perception of entire visual scenes that can be instigated by interocular conflict. The latter phenomenon, called binocular rivalry, in particular caught the attention of the late Jack Pettigrew, who combined his interest in the neuronal basis of perception with a unique comparative biological approach that considered ambiguous sensation as a fundamental problem of sensory systems that has shaped the brain throughout evolution. Here, we examine the research findings on visual perceptual alternation and suppression in a wide variety of species including insects, fish, reptiles, and primates. We highlight several interesting commonalities across species and behavioral indicators of perceptual alternation. In addition, we show how the comparative approach provides new avenues for understanding how the brain suppresses opposing sensory signals and generates alternations in perceptual dominance.
Collapse
Affiliation(s)
- Olivia Carter
- Melbourne School of Psychological Sciences, University of Melbourne, Parkville, VIC, AUS
| | | | | | - Shaun Collin
- School of Life Sciences, La Trobe University, Melbourne, VIC, AUS
| | - Alex Maier
- Department of Psychology, Vanderbilt University, Nashville, TN, USA
| |
Collapse
|
3
|
Kaushik PK, Olsson SB. Using virtual worlds to understand insect navigation for bio-inspired systems. CURRENT OPINION IN INSECT SCIENCE 2020; 42:97-104. [PMID: 33010476 DOI: 10.1016/j.cois.2020.09.010] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/14/2020] [Revised: 09/18/2020] [Accepted: 09/22/2020] [Indexed: 06/11/2023]
Abstract
Insects perform a wide array of intricate behaviors over large spatial and temporal scales in complex natural environments. A mechanistic understanding of insect cognition has direct implications on how brains integrate multimodal information and can inspire bio-based solutions for autonomous robots. Virtual Reality (VR) offers an opportunity assess insect neuroethology while presenting complex, yet controlled, stimuli. Here, we discuss the use of insects as inspiration for artificial systems, recent advances in different VR technologies, current knowledge gaps, and the potential for application of insect VR research to bio-inspired robots. Finally, we advocate the need to diversify our model organisms, behavioral paradigms, and embrace the complexity of the natural world. This will help us to uncover the proximate and ultimate basis of brain and behavior and extract general principles for common challenging problems.
Collapse
Affiliation(s)
- Pavan Kumar Kaushik
- National Centre for Biological Sciences, Tata Institute of Fundamental Research, GKVK Campus, Bellary Road, Bengaluru, 560064, India.
| | - Shannon B Olsson
- National Centre for Biological Sciences, Tata Institute of Fundamental Research, GKVK Campus, Bellary Road, Bengaluru, 560064, India.
| |
Collapse
|
4
|
Zhao F, Zeng Y, Guo A, Su H, Xu B. A neural algorithm for Drosophila linear and nonlinear decision-making. Sci Rep 2020; 10:18660. [PMID: 33122701 PMCID: PMC7596070 DOI: 10.1038/s41598-020-75628-y] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/08/2020] [Accepted: 10/16/2020] [Indexed: 11/15/2022] Open
Abstract
It has been evidenced that vision-based decision-making in Drosophila consists of both simple perceptual (linear) decision and value-based (non-linear) decision. This paper proposes a general computational spiking neural network (SNN) model to explore how different brain areas are connected contributing to Drosophila linear and nonlinear decision-making behavior. First, our SNN model could successfully describe all the experimental findings in fly visual reinforcement learning and action selection among multiple conflicting choices as well. Second, our computational modeling shows that dopaminergic neuron-GABAergic neuron-mushroom body (DA-GABA-MB) works in a recurrent loop providing a key circuit for gain and gating mechanism of nonlinear decision making. Compared with existing models, our model shows more biologically plausible on the network design and working mechanism, and could amplify the small differences between two conflicting cues more clearly. Finally, based on the proposed model, the UAV could quickly learn to make clear-cut decisions among multiple visual choices and flexible reversal learning resembling to real fly. Compared with linear and uniform decision-making methods, the DA-GABA-MB mechanism helps UAV complete the decision-making task with fewer steps.
Collapse
Affiliation(s)
- Feifei Zhao
- Research Center for Brain-inspired Intelligence, Institute of Automation, Chinese Academy of Sciences, Beijing, 100190, China
| | - Yi Zeng
- Research Center for Brain-inspired Intelligence, Institute of Automation, Chinese Academy of Sciences, Beijing, 100190, China. .,Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Shanghai, 200031, China. .,National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, 100190, China. .,University of Chinese Academy of Sciences, Beijing, 100049, China.
| | - Aike Guo
- Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Shanghai, 200031, China. .,University of Chinese Academy of Sciences, Beijing, 100049, China. .,Institute of Neuroscience and State Key Laboratory of Neuroscience, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai, 200031, China. .,State Key Laboratory of Brain and Cognitive Science, Institute of Biophysics, Chinese Academy of Sciences, Beijing, 100101, China. .,Shanghai Institute of Microsystem and Information Technology, Shanghai, 200050, China.
| | - Haifeng Su
- Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Shanghai, 200031, China.,Institute of Neuroscience and State Key Laboratory of Neuroscience, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai, 200031, China.,Laboratory of Molecular Neural Biology, School of Life Sciences, Shanghai University, Shanghai, 200444, China
| | - Bo Xu
- Research Center for Brain-inspired Intelligence, Institute of Automation, Chinese Academy of Sciences, Beijing, 100190, China.,Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Shanghai, 200031, China.,University of Chinese Academy of Sciences, Beijing, 100049, China
| |
Collapse
|
5
|
Pack CC, Theobald JC. Fruit flies are multistable geniuses. PLoS Biol 2018; 16:e2005429. [PMID: 29444072 PMCID: PMC5828447 DOI: 10.1371/journal.pbio.2005429] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Revised: 02/27/2018] [Indexed: 11/18/2022] Open
Abstract
Our sensory systems have evolved to provide us with information about the external world. Such information is useful only insofar as it leads to actions that enhance fitness, and thus, the link between sensation and action has been thoroughly studied in many species. In insects, for example, specific visual stimuli lead to highly stereotyped responses. In contrast, humans can exhibit a wide range of responses to the same stimulus, as occurs most notably in the phenomenon of multistable perception. On this basis, one might think that humans have a fundamentally different way of generating actions from sensory inputs, but Toepfer et al. show that flies show evidence of multistable perception as well. Specifically, when confronted with a sensory stimulus that can yield different motor responses, flies switch from one response to another with temporal dynamics that are similar to those of humans and other animals. This suggests that the mechanisms that give rise to the rich repertoire of sensory experience in humans have correlates in much simpler nervous systems.
Collapse
Affiliation(s)
- Christopher C. Pack
- Department of Neurology & Neurosurgery, McGill University, Montreal, Quebec, Canada
- * E-mail:
| | - Jamie C. Theobald
- Department of Biological Sciences, Florida International University, Miami, Florida, United States of America
| |
Collapse
|