Sensory Flow as a Basis for a Novel Distance Cue in Freely Behaving Electric Fish

Hofmann, Volker; Sanguinetti-Scheck, Juan Ignacio; Gómez-Sena, Leonel; Engelmann, Jacob

doi:10.1523/jneurosci.1361-16.2016

Cited by 28 publications

(24 citation statements)

References 77 publications

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“…During prey capture ( Nelson and MacIver, 1999 ), animals detect and localize (i.e., “electrolocation”) small prey items that cause weak and spatially localized AMs of the EOD (Figure 2A ). Several studies have shown that the resulting pattern of stimulation carries important information about the distance, size, and conductivity of an object and the relative speed and angle of the motion between object and fish ( Rasnow, 1996 ; Nelson and MacIver, 1999 ; Nelson et al, 2002 ; Babineau et al, 2006 ; Hofmann et al, 2017 ; Pedraja et al, 2018 ).…”

Section: Electrosensory Stimuli: Electrolocation and Social Interactimentioning

confidence: 99%

“…While many of the above discussed assessments of neuronal encoding are based on recordings from immobilized animals, it is important to note that weakly electric fish, on top of being able to display electrical behaviors when immobilized, show elaborate behaviors and astonishing cognitive abilities and are getting more and more attention for the study of various aspects of active sensing behaviors ( Nelson and MacIver, 2006 ; Engelmann et al, 2008 ; von der Emde et al, 2010 ; Hofmann et al, 2013 , 2017 ; Pedraja et al, 2018 ). Recent technological advances such as electrophysiological recordings from freely moving aquatic animals are rapidly evolving ( Fotowat et al, 2013 ; Vinepinsky et al, 2017 ).…”

Section: Future Directionsmentioning

confidence: 99%

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Population Coding and Correlated Variability in Electrosensory Pathways

Hofmann

Chacron

2018

Front. Integr. Neurosci.

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The fact that perception and behavior depend on the simultaneous and coordinated activity of neural populations is well established. Understanding encoding through neuronal population activity is however complicated by the statistical dependencies between the activities of neurons, which can be present in terms of both their mean (signal correlations) and their response variability (noise correlations). Here, we review the state of knowledge regarding population coding and the influence of correlated variability in the electrosensory pathways of the weakly electric fish Apteronotus leptorhynchus. We summarize known population coding strategies at the peripheral level, which are largely unaffected by noise correlations. We then move on to the hindbrain, where existing data from the electrosensory lateral line lobe (ELL) shows the presence of noise correlations. We summarize the current knowledge regarding the mechanistic origins of noise correlations and known mechanisms of stimulus dependent correlation shaping in ELL. We finish by considering future directions for understanding population coding in the electrosensory pathways of weakly electric fish, highlighting the benefits of this model system for understanding the origins and impact of noise correlations on population coding.

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Section: Electrosensory Stimuli: Electrolocation and Social Interactimentioning

confidence: 99%

Section: Future Directionsmentioning

confidence: 99%

Population Coding and Correlated Variability in Electrosensory Pathways

Hofmann

Chacron

2018

Front. Integr. Neurosci.

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“…Electric images were computed with the software originally developed by Rother (2003). This approach was verified and utilized in previous studies (Rother et al, 2003;Migliaro et al, 2005;Sanguinetti-Scheck et al, 2011;Hofmann et al, 2013Hofmann et al, , 2017Pedraja et al, 2014). The model estimates the transcutaneous current density for each of the points on the surface of the animal and is based on the following assumptions:…”

Section: Modeling the Eismentioning

confidence: 94%

The Use of Supervised Learning Models in Studying Agonistic Behavior and Communication in Weakly Electric Fish

Pedraja

Herzog

Engelmann

et al. 2021

Front. Behav. Neurosci.

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Despite considerable advances, studying electrocommunication of weakly electric fish, particularly in pulse-type species, is challenging as very short signal epochs at variable intervals from a few hertz up to more than 100 Hz need to be assigned to individuals. In this study, we show that supervised learning approaches offer a promising tool to automate or semiautomate the workflow, and thereby allowing the analysis of much longer episodes of behavior in a reasonable amount of time. We provide a detailed workflow mainly based on open resource software. We demonstrate the usefulness by applying the approach to the analysis of dyadic interactions of Gnathonemus petersii. Coupling of the proposed methods with a boundary element modeling approach, we are thereby able to model the information gained and provided during agonistic encounters. The data indicate that the passive electrosensory input, in particular, provides sufficient information to localize a contender during the pre-contest phase, fish did not use or rely on the theoretically also available sensory information of the contest outcome-determining size difference between contenders before engaging in agonistic behavior.

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“…Nonetheless, animals in general and weakly electric fish in particular are known to display a rich repertoire of sensory-related behaviors termed “active sensing movements” (for review, see e.g., Schroeder et al, 2010; Wachowiak, 2011; Hofmann et al, 2013; Grant et al, 2014). It was shown that active control of the re-afferent sensory input can enhance (Stamper et al, 2012; Hofmann et al, 2017) or even generate sensory information (Biswas et al, 2018; Hofmann and Chacron, 2018a; Pedraja et al, 2018). Recent technological advances made it possible to record neuronal activity in freely moving animals (Fotowat et al, 2019) and thus to investigate the role of feedback under active conditions.…”

Section: Summary and Future Directionsmentioning

confidence: 99%

Novel Functions of Feedback in Electrosensory Processing

Hofmann

Chacron

2019

Front. Integr. Neurosci.

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Environmental signals act as input and are processed across successive stages in the brain to generate a meaningful behavioral output. However, a ubiquitous observation is that descending feedback projections from more central to more peripheral brain areas vastly outnumber ascending feedforward projections. Such projections generally act to modify how sensory neurons respond to afferent signals. Recent studies in the electrosensory system of weakly electric fish have revealed novel functions for feedback pathways in that their transformation of the afferent input generates neural firing rate responses to sensory signals mediating perception and behavior. In this review, we focus on summarizing these novel and recently uncovered functions and put them into context by describing the more “classical” functions of feedback in the electrosensory system. We further highlight the parallels between the electrosensory system and other systems as well as outline interesting future directions.

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Sensory Flow as a Basis for a Novel Distance Cue in Freely Behaving Electric Fish

Cited by 28 publications

References 77 publications

Population Coding and Correlated Variability in Electrosensory Pathways

Population Coding and Correlated Variability in Electrosensory Pathways

The Use of Supervised Learning Models in Studying Agonistic Behavior and Communication in Weakly Electric Fish

Novel Functions of Feedback in Electrosensory Processing

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