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Rodríguez-Cattáneo A, Pereira AC, Aguilera PA, Caputi ÁA. Packet information encoding in a cerebellum-like circuit. PLoS One 2024; 19:e0308146. [PMID: 39302961 DOI: 10.1371/journal.pone.0308146] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/22/2023] [Accepted: 07/16/2024] [Indexed: 09/22/2024] Open
Abstract
Packet information encoding of neural signals was proposed for vision about 50 years ago and has recently been revived as a plausible strategy generalizable to natural and artificial sensory systems. It involves discrete image segmentation controlled by feedback and the ability to store and compare packets of information. This article shows that neurons of the cerebellum-like electrosensory lobe (EL) of the electric fish Gymnotus omarorum use spike-count and spike-timing distribution as constitutive variables of packets of information that encode one-by-one the electrosensory images generated by a self-timed series of electric organ discharges (EODs). To evaluate this hypothesis, extracellular unitary activity was recorded from the centro-medial map of the EL. Units recorded in high-decerebrate preparations were classified into six types using hierarchical cluster analysis of post-EOD spiking histograms. Cross-correlation analysis indicated that each EOD strongly influences the unit firing probability within the next inter-EOD interval. Units of the same type were similarly located in the laminar organization of the EL and showed similar stimulus-specific changes in spike count and spike timing after the EOD when a metal object was moved close by, along the fish's body parallel to the skin, or when the longitudinal impedance of a static cylindrical probe placed at the center of the receptive field was incremented in a stepwise manner in repetitive trials. These last experiments showed that spike-counts and the relative entropy, expressing a comparative measure of information before and after the step, were systematically increased with respect to a control in all unit types. The post-EOD spike-timing probability distribution and the relatively independent contribution of spike-timing and number to the content of information in the transmitted packet suggest that these are the constitutive image-encoding variables of the packets. Comparative analysis suggests that packet information transmission is a general principle for processing superposition images in cerebellum-like networks.
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Affiliation(s)
- Alejo Rodríguez-Cattáneo
- Departamento de Neurociencias Integrativas y Computacionales, Instituto de Investigaciones Biológicas Clemente Estable, Montevideo, Uruguay
| | - Ana Carolina Pereira
- Departamento de Neurociencias Integrativas y Computacionales, Instituto de Investigaciones Biológicas Clemente Estable, Montevideo, Uruguay
| | - Pedro Anibal Aguilera
- Departamento de Neurociencias Integrativas y Computacionales, Instituto de Investigaciones Biológicas Clemente Estable, Montevideo, Uruguay
| | - Ángel Ariel Caputi
- Departamento de Neurociencias Integrativas y Computacionales, Instituto de Investigaciones Biológicas Clemente Estable, Montevideo, Uruguay
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Tye KM, Miller EK, Taschbach FH, Benna MK, Rigotti M, Fusi S. Mixed selectivity: Cellular computations for complexity. Neuron 2024; 112:2289-2303. [PMID: 38729151 PMCID: PMC11257803 DOI: 10.1016/j.neuron.2024.04.017] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/11/2023] [Revised: 03/08/2024] [Accepted: 04/12/2024] [Indexed: 05/12/2024]
Abstract
The property of mixed selectivity has been discussed at a computational level and offers a strategy to maximize computational power by adding versatility to the functional role of each neuron. Here, we offer a biologically grounded implementational-level mechanistic explanation for mixed selectivity in neural circuits. We define pure, linear, and nonlinear mixed selectivity and discuss how these response properties can be obtained in simple neural circuits. Neurons that respond to multiple, statistically independent variables display mixed selectivity. If their activity can be expressed as a weighted sum, then they exhibit linear mixed selectivity; otherwise, they exhibit nonlinear mixed selectivity. Neural representations based on diverse nonlinear mixed selectivity are high dimensional; hence, they confer enormous flexibility to a simple downstream readout neural circuit. However, a simple neural circuit cannot possibly encode all possible mixtures of variables simultaneously, as this would require a combinatorially large number of mixed selectivity neurons. Gating mechanisms like oscillations and neuromodulation can solve this problem by dynamically selecting which variables are mixed and transmitted to the readout.
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Affiliation(s)
- Kay M Tye
- Salk Institute for Biological Studies, La Jolla, CA, USA; Howard Hughes Medical Institute, La Jolla, CA; Department of Neurobiology, School of Biological Sciences, University of California, San Diego, La Jolla, CA 92093, USA; Kavli Institute for Brain and Mind, San Diego, CA, USA.
| | - Earl K Miller
- The Picower Institute for Learning and Memory, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139, USA.
| | - Felix H Taschbach
- Salk Institute for Biological Studies, La Jolla, CA, USA; Biological Science Graduate Program, University of California, San Diego, La Jolla, CA 92093, USA; Department of Neurobiology, School of Biological Sciences, University of California, San Diego, La Jolla, CA 92093, USA.
| | - Marcus K Benna
- Department of Neurobiology, School of Biological Sciences, University of California, San Diego, La Jolla, CA 92093, USA.
| | | | - Stefano Fusi
- Center for Theoretical Neuroscience, Columbia University, New York, NY, USA; Zuckerman Mind Brain Behavior Institute, Columbia University, New York, NY, USA; Department of Neuroscience, Columbia University, New York, NY, USA; Kavli Institute for Brain Science, Columbia University, New York, NY, USA.
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Girard C. The tri-flow adaptiveness of codes in major evolutionary transitions. Biosystems 2024; 237:105133. [PMID: 38336225 DOI: 10.1016/j.biosystems.2024.105133] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/17/2023] [Revised: 01/26/2024] [Accepted: 01/27/2024] [Indexed: 02/12/2024]
Abstract
Life codes increase in both number and variety with biological complexity. Although our knowledge of codes is constantly expanding, the evolutionary progression of organic, neural, and cultural codes in response to selection pressure remains poorly understood. Greater clarification of the selective mechanisms is achieved by investigating how major evolutionary transitions reduce spatiotemporal and energetic constraints on transmitting heritable code to offspring. Evolution toward less constrained flows is integral to enduring flow architecture everywhere, in both engineered and natural flow systems. Beginning approximately 4 billion years ago, the most basic level for transmitting genetic material to offspring was initiated by protocell division. Evidence from ribosomes suggests that protocells transmitted comma-free or circular codes, preceding the evolution of standard genetic code. This rudimentary information flow within protocells is likely to have first emerged within the geo-energetic and geospatial constraints of hydrothermal vents. A broad-gauged hypothesis is that major evolutionary transitions overcame such constraints with tri-flow adaptations. The interconnected triple flows incorporated energy-converting, spatiotemporal, and code-based informational dynamics. Such tri-flow adaptations stacked sequence splicing code on top of protein-DNA recognition code in eukaryotes, prefiguring the transition to sexual reproduction. Sex overcame the spatiotemporal-energetic constraints of binary fission with further code stacking. Examples are tubulin code and transcription initiation code in vertebrates. In a later evolutionary transition, language reduced metabolic-spatiotemporal constraints on inheritance by stacking phonetic, phonological, and orthographic codes. In organisms that reproduce sexually, each major evolutionary transition is shown to be a tri-flow adaptation that adds new levels of code-based informational exchange. Evolving biological complexity is also shown to increase the nongenetic transmissibility of code.
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Affiliation(s)
- Chris Girard
- Department of Global and Sociocultural Studies, Florida International University, Miami, FL 33199, United States.
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Abstract
The electric organ discharges (EODs) produced by weakly electric fish have long been a source of scientific intrigue and inspiration. The study of these species has contributed to our understanding of the organization of fixed action patterns, as well as enriching general imaging theory by unveiling the dual impact of an agent's actions on the environment and its own sensory system during the imaging process. This Centenary Review firstly compares how weakly electric fish generate species- and sex-specific stereotyped electric fields by considering: (1) peripheral mechanisms, including the geometry, channel repertoire and innervation of the electrogenic units; (2) the organization of the electric organs (EOs); and (3) neural coordination mechanisms. Secondly, the Review discusses the threefold function of the fish-centered electric fields: (1) to generate electric signals that encode the material, geometry and distance of nearby objects, serving as a short-range sensory modality or 'electric touch'; (2) to mark emitter identity and location; and (3) to convey social messages encoded in stereotypical modulations of the electric field that might be considered as species-specific communication symbols. Finally, this Review considers a range of potential research directions that are likely to be productive in the future.
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Affiliation(s)
- Angel Ariel Caputi
- Sistema Nacional de Investigadores - Uruguay, Av. Wilson Ferreira Aldunate 1219, Pando, PC 15600, Uruguay
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Barayeu A, Schäfer R, Grewe J, Benda J. Beat encoding at mistuned octaves within single electrosensory neurons. iScience 2023; 26:106840. [PMID: 37434697 PMCID: PMC10331418 DOI: 10.1016/j.isci.2023.106840] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/18/2022] [Revised: 11/28/2022] [Accepted: 05/04/2023] [Indexed: 07/13/2023] Open
Abstract
Beats are slow periodic amplitude modulations resulting from the superposition of two spectrally close periodic signals. The difference frequency between the signals sets the frequency of the beat. A field study in the electric fish Apteronotus rostratus showed the behavioral relevance of very high difference frequencies. Contrary to expectations from previous studies, our electrophysiological data show strong responses of p-type electroreceptor afferents whenever the difference frequency approaches integer multiples (mistuned octaves) of the fish's own electric field frequency (carrier). Mathematical reasoning and simulations show that common approaches to extract amplitude modulations, such as Hilbert transform or half-wave rectification, are not sufficient to explain the responses at carrier octaves. Instead, half-wave rectification needs to be smoothed out, for example by a cubic function. Because electroreceptive afferents share many properties with auditory nerve fibers, these mechanisms may underly the human perception of beats at mistuned octaves as described by Ohm and Helmholtz.
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Affiliation(s)
- Alexandra Barayeu
- Neuroethology, Institute for Neurobiology, Eberhard Karls University, 72076 Tübingen, Germany
| | - Ramona Schäfer
- Neuroethology, Institute for Neurobiology, Eberhard Karls University, 72076 Tübingen, Germany
| | - Jan Grewe
- Neuroethology, Institute for Neurobiology, Eberhard Karls University, 72076 Tübingen, Germany
| | - Jan Benda
- Neuroethology, Institute for Neurobiology, Eberhard Karls University, 72076 Tübingen, Germany
- Bernstein Center for Computational Neuroscience Tübingen, 72076 Tübingen, Germany
- Werner Reichardt Centre for Integrative Neuroscience, 72076 Tübingen, Germany
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Talley J, Pusdekar S, Feltenberger A, Ketner N, Evers J, Liu M, Gosh A, Palmer SE, Wardill TJ, Gonzalez-Bellido PT. Predictive saccades and decision making in the beetle-predating saffron robber fly. Curr Biol 2023:S0960-9822(23)00770-4. [PMID: 37379842 DOI: 10.1016/j.cub.2023.06.019] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/11/2022] [Revised: 04/28/2023] [Accepted: 06/06/2023] [Indexed: 06/30/2023]
Abstract
Internal predictions about the sensory consequences of self-motion, encoded by corollary discharge, are ubiquitous in the animal kingdom, including for fruit flies, dragonflies, and humans. In contrast, predicting the future location of an independently moving external target requires an internal model. With the use of internal models for predictive gaze control, vertebrate predatory species compensate for their sluggish visual systems and long sensorimotor latencies. This ability is crucial for the timely and accurate decisions that underpin a successful attack. Here, we directly demonstrate that the robber fly Laphria saffrana, a specialized beetle predator, also uses predictive gaze control when head tracking potential prey. Laphria uses this predictive ability to perform the difficult categorization and perceptual decision task of differentiating a beetle from other flying insects with a low spatial resolution retina. Specifically, we show that (1) this predictive behavior is part of a saccade-and-fixate strategy, (2) the relative target angular position and velocity, acquired during fixation, inform the subsequent predictive saccade, and (3) the predictive saccade provides Laphria with additional fixation time to sample the frequency of the prey's specular wing reflections. We also demonstrate that Laphria uses such wing reflections as a proxy for the wingbeat frequency of the potential prey and that consecutively flashing LEDs to produce apparent motion elicits attacks when the LED flicker frequency matches that of the beetle's wingbeat cycle.
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Affiliation(s)
- Jennifer Talley
- Air Force Research Laboratory, Munitions Directorate, Eglin AFB, FL 32542, USA.
| | - Siddhant Pusdekar
- Department of Ecology, Evolution and Behavior, University of Minnesota, Saint Paul, MN 55108, USA
| | - Aaron Feltenberger
- Air Force Research Laboratory, Munitions Directorate, Eglin AFB, FL 32542, USA
| | - Natalie Ketner
- Air Force Research Laboratory, Munitions Directorate, Eglin AFB, FL 32542, USA
| | - Johnny Evers
- Air Force Research Laboratory, Munitions Directorate, Eglin AFB, FL 32542, USA
| | - Molly Liu
- Department of Ecology, Evolution and Behavior, University of Minnesota, Saint Paul, MN 55108, USA
| | - Atishya Gosh
- Department of Ecology, Evolution and Behavior, University of Minnesota, Saint Paul, MN 55108, USA; Department of Biomedical Informatics and Computational Biology, University of Minnesota, Minneapolis, MN 55455, USA
| | - Stephanie E Palmer
- Department of Organismal Biology and Anatomy, The University of Chicago, Chicago, IL 60637, USA
| | - Trevor J Wardill
- Department of Ecology, Evolution and Behavior, University of Minnesota, Saint Paul, MN 55108, USA; Department of Biomedical Informatics and Computational Biology, University of Minnesota, Minneapolis, MN 55455, USA
| | - Paloma T Gonzalez-Bellido
- Department of Ecology, Evolution and Behavior, University of Minnesota, Saint Paul, MN 55108, USA; Department of Biomedical Informatics and Computational Biology, University of Minnesota, Minneapolis, MN 55455, USA.
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Salazar V, Silva A. Neural processing: Cracking the code to extract relevant social information. Curr Biol 2022; 32:R32-R34. [PMID: 35015991 DOI: 10.1016/j.cub.2021.11.011] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
Abstract
How does the brain decode sensory features from social signals? A new study in electric fish provides an elegant model where mixed selectivity coding and corollary discharges at the thalamic level can guide decision making in social behavior.
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Affiliation(s)
- Vielka Salazar
- Department of Biology, Cape Breton University, 1250 Grand Lake Road, Sydney, NS B1P 6L2, Canada
| | - Ana Silva
- Laboratorio de Neurociencias, Facultad de Ciencias, Universidad de la República, Iguá 4225, 11400 Montevideo, Uruguay.
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