scholarly journals Spatial and Temporal Organization of Composite Receptive Fields in the Songbird Auditory Forebrain

2021 ◽  
Author(s):  
Nasim Winchester Vahidi
Keyword(s):  
Vocal Communication ◽  
Receptive Fields ◽  
Temporal Organization ◽  
Quadratic Model ◽  
Bird Songs ◽  
Communication Signals ◽  
Complete Representation ◽  
Auditory Forebrain ◽  
Neuron Populations ◽  
Classical Models

The mechanisms underlying how single auditory neurons and neuron populations encode natural and acoustically complex vocal signals, such as human speech or bird songs, are not well understood. Classical models focus on individual neurons, whose spike rates vary systematically as a function of change in a small number of simple acoustic dimensions. However, neurons in the caudal medial nidopallium (NCM), an auditory forebrain region in songbirds that is analogous to the secondary auditory cortex in mammals, have composite receptive fields (CRFs) that comprise multiple acoustic features tied to both increases and decreases in firing rates. Here, we investigated the anatomical organization and temporal activation patterns of auditory CRFs in European starlings exposed to natural vocal communication signals (songs). We recorded extracellular electrophysiological responses to various bird songs at auditory NCM sites, including both single and multiple neurons, and we then applied a quadratic model to extract large sets of CRF features that were tied to excitatory and suppressive responses at each measurement site. We found that the superset of CRF features yielded spatially and temporally distributed, generalizable representations of a conspecific song. Individual sites responded to acoustically diverse features, as there was no discernable organization of features across anatomically ordered sites. The CRF features at each site yielded broad, temporally distributed responses that spanned the entire duration of many starling songs, which can last for 50 s or more. Based on these results, we estimated that a nearly complete representation of any conspecific song, regardless of length, can be obtained by evaluating populations as small as 100 neurons. We conclude that natural acoustic communication signals drive a distributed yet highly redundant representation across the songbird auditory forebrain, in which adjacent neurons contribute to the encoding of multiple diverse and time-varying spectro-temporal features.

scholarly journals Anatomical and Functional Organization of Inhibitory Circuits in the Songbird Auditory Forebrain

2009 ◽  
Vol 2 ◽  
pp. 117906950900200 ◽  
Author(s):  
Jin Kwon Jeong ◽  
Liisa A. Tremere ◽  
Michael J. Ryave ◽  
Victor C. Vuong ◽  
Raphael Pinaud
Keyword(s):  
Functional Organization ◽  
Large Fraction ◽  
Vocal Learning ◽  
Temporal Organization ◽  
Individual Identification ◽  
Association Cortex ◽  
Strong Impact ◽  
Communication Signals ◽  
Auditory Forebrain ◽  
Auditory Association Cortex

Recent studies on the anatomical and functional organization of GABAergic networks in central auditory circuits of the zebra finch have highlighted the strong impact of inhibitory mechanisms on both the central encoding and processing of acoustic information in a vocal learning species. Most of this work has focused on the caudomedial nidopallium (NCM), a forebrain area postulated to be the songbird analogue of the mammalian auditory association cortex. NCM houses neurons with selective responses to conspecific songs and is a site thought to house auditory memories required for vocal learning and, likely, individual identification. Here we review our recent work on the anatomical distribution of GABAergic cells in NCM, their engagement in response to song and the roles for inhibitory transmission in the physiology of NCM at rest and during the processing of natural communication signals. GABAergic cells are highly abundant in the songbird auditory forebrain and account for nearly half of the overall neuronal population in NCM with a large fraction of these neurons activated by song in freely-behaving animals. GABAergic synapses provide considerable local, tonic inhibition to NCM neurons at rest and, during sound processing, may contain the spread of excitation away from un-activated or quiescent parts of the network. Finally, we review our work showing that GABAA-mediated inhibition directly regulates the temporal organization of song-driven responses in awake songbirds, and appears to enhance the reliability of auditory encoding in NCM.

TUTORIAL ON NEUROBIOLOGY: FROM SINGLE NEURONS TO BRAIN CHAOS

1992 ◽  
Vol 02 (03) ◽  
pp. 451-482 ◽  
Author(s):  
WALTER J. FREEMAN
Keyword(s):  
Dynamic Range ◽  
Basins Of Attraction ◽  
State Transitions ◽  
State Variables ◽  
Dynamic Range Compression ◽  
The Core ◽  
Neuron Populations ◽  
Classical Models ◽  
Sigmoid Curve ◽  
Trigger Zone

Those classical models are reviewed that are most widely used by neurobiologists to explain the dynamics of neurons and neuron populations, and by modelers to implement artificial neural networks. Each neuron has input fibers called dendrites that integrate and an axon that transmits the output. The differing fiber architectures reflect these dissimilar dynamic operations. The basic tools to describe them are the RC model of the membrane, the core conductor model of the fibers, the Hodgkin–Huxley model of the trigger zone, and the modifiable synapse. Populations additionally require description of macroscopic state variables, the types of nonlinearity (most importantly the sigmoid curve and the dynamic range compression at the input to the cortex), and the types and strengths of connections. The properties of these neural masses can be characterized with the tools of nonlinear dynamics. These include description of point, limit cycle, and chaotic attractors for the cerebal cortex, as well as the types and mechanisms for the state transitions between basins of attraction during learning and perception.

From Perception to Action: The Role of Auditory Input in Shaping Vocal Communication and Social Behaviors in Birds

2019 ◽  
Vol 94 (Suppl. 1-4) ◽  
pp. 51-60
Author(s):  
Julie E. Elie ◽  
Susanne Hoffmann ◽  
Jeffery L. Dunning ◽  
Melissa J. Coleman ◽  
Eric S. Fortune ◽  
...  
Keyword(s):  
Feedback Loop ◽  
Vocal Communication ◽  
Neural Mechanisms ◽  
Communication Process ◽  
Auditory Input ◽  
Research Focus ◽  
Vocal Production ◽  
Active Participant ◽  
Communication Signals

Acoustic communication signals are typically generated to influence the behavior of conspecific receivers. In songbirds, for instance, such cues are routinely used by males to influence the behavior of females and rival males. There is remarkable diversity in vocalizations across songbird species, and the mechanisms of vocal production have been studied extensively, yet there has been comparatively little emphasis on how the receiver perceives those signals and uses that information to direct subsequent actions. Here, we emphasize the receiver as an active participant in the communication process. The roles of sender and receiver can alternate between individuals, resulting in an emergent feedback loop that governs the behavior of both. We describe three lines of research that are beginning to reveal the neural mechanisms that underlie the reciprocal exchange of information in communication. These lines of research focus on the perception of the repertoire of songbird vocalizations, evaluation of vocalizations in mate choice, and the coordination of duet singing.

scholarly journals Forebrain circuits underlying the social modulation of vocal communication signals

2015 ◽  
Vol 76 (1) ◽  
pp. 47-63 ◽  
Author(s):  
Laura E. Matheson ◽  
Herie Sun ◽  
Jon T. Sakata
Keyword(s):  
Vocal Communication ◽  
Communication Signals ◽  
Social Modulation ◽  
The Social

scholarly journals Toward a Computational Neuroethology of Vocal Communication: From Bioacoustics to Neurophysiology, Emerging Tools and Future Directions

2021 ◽  
Vol 15 ◽  
Author(s):  
Tim Sainburg ◽  
Timothy Q. Gentner
Keyword(s):  
Signal Processing ◽  
Computational Methods ◽  
Large Scale ◽  
Vocal Communication ◽  
Communication Behavior ◽  
Model Species ◽  
Future Directions ◽  
Communication Signals ◽  
Brain Behavior ◽  
Computational Neuroethology

Recently developed methods in computational neuroethology have enabled increasingly detailed and comprehensive quantification of animal movements and behavioral kinematics. Vocal communication behavior is well poised for application of similar large-scale quantification methods in the service of physiological and ethological studies. This review describes emerging techniques that can be applied to acoustic and vocal communication signals with the goal of enabling study beyond a small number of model species. We review a range of modern computational methods for bioacoustics, signal processing, and brain-behavior mapping. Along with a discussion of recent advances and techniques, we include challenges and broader goals in establishing a framework for the computational neuroethology of vocal communication.

scholarly journals Song Recognition Learning and Stimulus-Specific Weakening of Neural Responses in the Avian Auditory Forebrain

2010 ◽  
Vol 103 (4) ◽  
pp. 1785-1797 ◽  
Author(s):  
Jason V. Thompson ◽  
Timothy Q. Gentner
Keyword(s):  
Associative Learning ◽  
Discharge Rate ◽  
Spontaneous Discharge ◽  
Neural Responses ◽  
Communication Signals ◽  
Dependent Plasticity ◽  
Natural Stimuli ◽  
Auditory Forebrain ◽  
Caudomedial Nidopallium ◽  
Excitatory Responses

Learning typically increases the strength of responses and the number of neurons that respond to training stimuli. Few studies have explored representational plasticity using natural stimuli, however, leaving unknown the changes that accompany learning under more realistic conditions. Here, we examine experience-dependent plasticity in European starlings, a songbird with rich acoustic communication signals tied to robust, natural recognition behaviors. We trained starlings to recognize conspecific songs and recorded the extracellular spiking activity of single neurons in the caudomedial nidopallium (NCM), a secondary auditory forebrain region analogous to mammalian auditory cortex. Training induced a stimulus-specific weakening of the neural responses (lower spike rates) to the learned songs, whereas the population continued to respond robustly to unfamiliar songs. Additional experiments rule out stimulus-specific adaptation and general biases for novel stimuli as explanations of these effects. Instead, the results indicate that associative learning leads to single neuron responses in which both irrelevant and unfamiliar stimuli elicit more robust responses than behaviorally relevant natural stimuli. Detailed analyses of these effects at a finer temporal scale point to changes in the number of motifs eliciting excitatory responses above a neuron's spontaneous discharge rate. These results show a novel form of experience-dependent plasticity in the auditory forebrain that is tied to associative learning and in which the overall strength of responses is inversely related to learned behavioral significance.

Sex differences in discrimination of vocal communication signals in a songbird

2001 ◽  
Vol 61 (4) ◽  
pp. 805-817 ◽  
Author(s):  
David S. Vicario ◽  
Nasir H. Naqvi ◽  
Jonathan N. Raksin
Keyword(s):  
Sex Differences ◽  
Vocal Communication ◽  
Communication Signals

scholarly journals HDAC3 Inhibitor RGFP966 Modulates Neuronal Memory for Vocal Communication Signals in a Songbird Model

2017 ◽  
Vol 11 ◽  
Author(s):  
Mimi L. Phan ◽  
Mark M. Gergues ◽  
Shafali Mahidadia ◽  
Jorge Jimenez-Castillo ◽  
David S. Vicario ◽  
...  
Keyword(s):  
Vocal Communication ◽  
Communication Signals

Catecholaminergic contributions to vocal communication signals

2015 ◽  
Vol 41 (9) ◽  
pp. 1180-1194 ◽  
Author(s):  
Laura E. Matheson ◽  
Jon T. Sakata
Keyword(s):  
Vocal Communication ◽  
Communication Signals

scholarly journals Latent space visualization, characterization, and generation of diverse vocal communication signals

2019 ◽  
Author(s):  
Tim Sainburg ◽  
Marvin Thielk ◽  
Timothy Q Gentner
Keyword(s):  
Latent Variables ◽  
Vocal Communication ◽  
Animal Communication ◽  
Temporal Structure ◽  
Systematic Sampling ◽  
Acoustic Feature ◽  
Communication Signals ◽  
Animal Vocalizations ◽  
Complex Features ◽  
Low Dimensional

ABSTRACTAnimals produce vocalizations that range in complexity from a single repeated call to hundreds of unique vocal elements patterned in sequences unfolding over hours. Characterizing complex vocalizations can require considerable effort and a deep intuition about each species’ vocal behavior. Even with a great deal of experience, human characterizations of animal communication can be affected by human perceptual biases. We present here a set of computational methods that center around projecting animal vocalizations into low dimensional latent representational spaces that are directly learned from data. We apply these methods to diverse datasets from over 20 species, including humans, bats, songbirds, mice, cetaceans, and nonhuman primates, enabling high-powered comparative analyses of unbiased acoustic features in the communicative repertoires across species. Latent projections uncover complex features of data in visually intuitive and quantifiable ways. We introduce methods for analyzing vocalizations as both discrete sequences and as continuous latent variables. Each method can be used to disentangle complex spectro-temporal structure and observe long-timescale organization in communication. Finally, we show how systematic sampling from latent representational spaces of vocalizations enables comprehensive investigations of perceptual and neural representations of complex and ecologically relevant acoustic feature spaces.

Sign in / Sign up

Export Citation Format

Share Document