scholarly journals Neural coding and perception of auditory motion direction based on interaural time differences

2019 ◽  
Vol 122 (4) ◽  
pp. 1821-1842 ◽  
Author(s):  
Nathaniel J. Zuk ◽  
Bertrand Delgutte
Keyword(s):  
Neural Coding ◽  
Process Model ◽  
Single Neuron ◽  
Interaural Time Difference ◽  
Direction Selectivity ◽  
Auditory Midbrain ◽  
Motion Direction ◽  
Neural Noise ◽  
Auditory Scene ◽  
Interaural Differences

While motion is important for parsing a complex auditory scene into perceptual objects, how it is encoded in the auditory system is unclear. Perceptual studies suggest that the ability to identify the direction of motion is limited by the duration of the moving sound, yet we can detect changes in interaural differences at even shorter durations. To understand the source of these distinct temporal limits, we recorded from single units in the inferior colliculus (IC) of unanesthetized rabbits in response to noise stimuli containing a brief segment with linearly time-varying interaural time difference (“ITD sweep”) temporally embedded in interaurally uncorrelated noise. We also tested the ability of human listeners to either detect the ITD sweeps or identify the motion direction. Using a point-process model to separate the contributions of stimulus dependence and spiking history to single-neuron responses, we found that the neurons respond primarily by following the instantaneous ITD rather than exhibiting true direction selectivity. Furthermore, using an optimal classifier to decode the single-neuron responses, we found that neural threshold durations of ITD sweeps for both direction identification and detection overlapped with human threshold durations even though the average response of the neurons could track the instantaneous ITD beyond psychophysical limits. Our results suggest that the IC does not explicitly encode motion direction, but internal neural noise may limit the speed at which we can identify the direction of motion. NEW & NOTEWORTHY Recognizing motion and identifying an object’s trajectory are important for parsing a complex auditory scene, but how we do so is unclear. We show that neurons in the auditory midbrain do not exhibit direction selectivity as found in the visual system but instead follow the trajectory of the motion in their temporal firing patterns. Our results suggest that the inherent variability in neural firings may limit our ability to identify motion direction at short durations.

scholarly journals Origins of direction selectivity in the primate retina

2021 ◽  
Author(s):  
Yeon Jin Kim ◽  
Beth Peterson ◽  
Joanna Crook ◽  
Hannah Joo ◽  
Jiajia Wu ◽  
...  
Keyword(s):  
Neural Coding ◽  
Amacrine Cell ◽  
Cell Types ◽  
Macaque Monkey ◽  
Direction Selectivity ◽  
Bipolar Cells ◽  
Motion Processing ◽  
Motion Direction ◽  
Motion Sensitivity ◽  
Starburst Amacrine Cell

Abstract From mouse to primate, there is a striking discontinuity in our current understanding of the neural coding of motion direction. In non-primate mammals, directionally selective cell types and circuits are a signature feature of the retina, situated at the earliest stage of the visual process1,2. In primates, by contrast, direction selectivity is a hallmark of motion processing areas in visual cortex3,4, but has not been found in the retina, despite significant effort5,6. Here we combined functional recordings of light-evoked responses and connectomic reconstruction to identify diverse direction-selective cell types in the macaque monkey retina with distinctive physiological properties and synaptic motifs. This circuitry includes an ON-OFF ganglion cell type, a spiking, ON-OFF poly-axonal amacrine cell and the starburst amacrine cell, all of which show direction selectivity. Moreover, we found unexpectedly that macaque starburst cells possess a strong, non-GABAergic, antagonistic surround mediated by input from excitatory bipolar cells that is critical for the generation of radial motion sensitivity in these cells. Our findings open a new door to investigation of a novel circuitry that computes motion direction in the primate visual system.

scholarly journals Neural selectivity for visual motion in macaque area V3A

2020 ◽  
Author(s):  
Nardin Nakhla ◽  
Yavar Korkian ◽  
Matthew R. Krause ◽  
Christopher C. Pack
Keyword(s):  
Visual Cortex ◽  
Optic Flow ◽  
Functional Role ◽  
Visual Motion ◽  
Flow Patterns ◽  
Brain Regions ◽  
Direction Selectivity ◽  
Motion Processing ◽  
Imaging Studies ◽  
Motion Direction

AbstractThe processing of visual motion is carried out by dedicated pathways in the primate brain. These pathways originate with populations of direction-selective neurons in the primary visual cortex, which project to dorsal structures like the middle temporal (MT) and medial superior temporal (MST) areas. Anatomical and imaging studies have suggested that area V3A might also be specialized for motion processing, but there have been very few studies of single-neuron direction selectivity in this area. We have therefore performed electrophysiological recordings from V3A neurons in two macaque monkeys (one male and one female) and measured responses to a large battery of motion stimuli that includes translation motion, as well as more complex optic flow patterns. For comparison, we simultaneously recorded the responses of MT neurons to the same stimuli. Surprisingly, we find that overall levels of direction selectivity are similar in V3A and MT and moreover that the population of V3A neurons exhibits somewhat greater selectivity for optic flow patterns. These results suggest that V3A should be considered as part of the motion processing machinery of the visual cortex, in both human and non-human primates.Significance statementAlthough area V3A is frequently the target of anatomy and imaging studies, little is known about its functional role in processing visual stimuli. Its contribution to motion processing has been particularly unclear, with different studies yielding different conclusions. We report a detailed study of direction selectivity in V3A. Our results show that single V3A neurons are, on average, as capable of representing motion direction as are neurons in well-known structures like MT. Moreover, we identify a possible specialization for V3A neurons in representing complex optic flow, which has previously been thought to emerge in higher-order brain regions. Thus it appears that V3A is well-suited to a functional role in motion processing.

scholarly journals Weighting neurons by selectivity produces near-optimal population codes

2019 ◽  
Vol 121 (5) ◽  
pp. 1924-1937
Author(s):  
Elizabeth Zavitz ◽  
Nicholas S. C. Price
Keyword(s):  
A Priori ◽  
Maximum Level ◽  
Optimization Methods ◽  
Neuronal Population ◽  
Direction Selectivity ◽  
Motion Direction ◽  
Temporal Area ◽  
Linear Discriminant ◽  
Preferred Direction

Perception is produced by “reading out” the representation of a sensory stimulus contained in the activity of a population of neurons. To examine experimentally how populations code information, a common approach is to decode a linearly weighted sum of the neurons’ spike counts. This approach is popular because of the biological plausibility of weighted, nonlinear integration. For neurons recorded in vivo, weights are highly variable when derived through optimization methods, but it is unclear how the variability affects decoding performance in practice. To address this, we recorded from neurons in the middle temporal area (MT) of anesthetized marmosets ( Callithrix jacchus) viewing stimuli comprising a sheet of dots that moved coherently in 1 of 12 different directions. We found that high peak response and direction selectivity both predicted that a neuron would be weighted more highly in an optimized decoding model. Although learned weights differed markedly from weights chosen according to a priori rules based on a neuron’s tuning profile, decoding performance was only marginally better for the learned weights. In the models with a priori rules, selectivity is the best predictor of weighting, and defining weights according to a neuron’s preferred direction and selectivity improves decoding performance to very near the maximum level possible, as defined by the learned weights. NEW & NOTEWORTHY We examined which aspects of a neuron’s tuning account for its contribution to sensory coding. Strongly direction-selective neurons are weighted most highly by optimal decoders trained to discriminate motion direction. Models with predefined decoding weights demonstrate that this weighting scheme causally improved direction representation by a neuronal population. Optimizing decoders (using a generalized linear model or Fisher’s linear discriminant) led to only marginally better performance than decoders based purely on a neuron’s preferred direction and selectivity.

scholarly journals Specific loss of neural sensitivity to interaural time difference of unmodulated noise stimuli following noise-induced hearing loss

2020 ◽  
Vol 124 (4) ◽  
pp. 1165-1182
Author(s):  
Hariprakash Haragopal ◽  
Ryan Dorkoski ◽  
Austin R. Pollard ◽  
Gareth A. Whaley ◽  
Timothy R. Wohl ◽  
...  
Keyword(s):  
Hearing Loss ◽  
Interaural Time Difference ◽  
Acoustic Trauma ◽  
Sound Level ◽  
Broadband Noise ◽  
Neural Responses ◽  
Auditory Midbrain ◽  
Midbrain Neurons ◽  
Perceptual Abilities ◽  
Encode Time

Sensorineural hearing loss compromises perceptual abilities that arise from hearing with two ears, yet its effects on binaural aspects of neural responses are largely unknown. We found that, following severe hearing loss because of acoustic trauma, auditory midbrain neurons specifically lost the ability to encode time differences between the arrival of a broadband noise stimulus to the two ears, whereas the encoding of sound level differences between the two ears remained uncompromised.

Linking Neuronal Direction Selectivity to Perceptual Decisions About Visual Motion

2020 ◽  
Vol 6 (1) ◽  
pp. 335-362
Author(s):  
Tatiana Pasternak ◽  
Duje Tadin
Keyword(s):  
Prefrontal Cortex ◽  
Visual Processing ◽  
Visual Motion ◽  
Neuronal Response ◽  
Physiological Responses ◽  
Direction Selectivity ◽  
Motion Information ◽  
Motion Direction ◽  
Neurophysiological Studies ◽  
Selective Activity

Psychophysical and neurophysiological studies of responses to visual motion have converged on a consistent set of general principles that characterize visual processing of motion information. Both types of approaches have shown that the direction and speed of target motion are among the most important encoded stimulus properties, revealing many parallels between psychophysical and physiological responses to motion. Motivated by these parallels, this review focuses largely on more direct links between the key feature of the neuronal response to motion, direction selectivity, and its utilization in memory-guided perceptual decisions. These links were established during neuronal recordings in monkeys performing direction discriminations, but also by examining perceptual effects of widespread elimination of cortical direction selectivity produced by motion deprivation during development. Other approaches, such as microstimulation and lesions, have documented the importance of direction-selective activity in the areas that are active during memory-guided direction comparisons, area MT and the prefrontal cortex, revealing their likely interactions during behavioral tasks.

scholarly journals Functional maps within a single neuron

2012 ◽  
Vol 108 (9) ◽  
pp. 2343-2351 ◽  
Author(s):  
Rishikesh Narayanan ◽  
Daniel Johnston
Keyword(s):  
Information Processing ◽  
Ion Channels ◽  
Neural Coding ◽  
Single Neuron ◽  
Expression Profiles ◽  
Information Encoding ◽  
Neuronal Dendrites ◽  
Sensory Maps ◽  
The Face ◽  
Sensory Map

The presence and plasticity of dendritic ion channels are well established. However, the literature is divided on what specific roles these dendritic ion channels play in neuronal information processing, and there is no consensus on why neuronal dendrites should express diverse ion channels with different expression profiles. In this review, we present a case for viewing dendritic information processing through the lens of the sensory map literature, where functional gradients within neurons are considered as maps on the neuronal topograph. Under such a framework, drawing analogies from the sensory map literature, we postulate that the formation of intraneuronal functional maps is driven by the twin objectives of efficiently encoding inputs that impinge along different dendritic locations and of retaining homeostasis in the face of changes that are required in the coding process. In arriving at this postulate, we relate intraneuronal map physiology to the vast literature on sensory maps and argue that such a metaphorical association provides a fresh conceptual framework for analyzing and understanding single-neuron information encoding. We also describe instances where the metaphor presents specific directions for research on intraneuronal maps, derived from analogous pursuits in the sensory map literature. We suggest that this perspective offers a thesis for why neurons should express and alter ion channels in their dendrites and provides a framework under which active dendrites could be related to neural coding, learning theory, and homeostasis.

Wavelet-Like Receptive Fields Emerges by Non-Linear Minimization of Neuron Error

2003 ◽  
Vol 13 (02) ◽  
pp. 87-91
Author(s):  
Allan Kardec Barros ◽  
Andrzej Cichocki ◽  
Noboru Ohnishi
Keyword(s):  
Neural Coding ◽  
Single Neuron ◽  
Receptive Fields ◽  
Natural Images ◽  
Squared Error ◽  
Redundancy Reduction ◽  
One Step ◽  
The One ◽  
Mutually Independent ◽  
Large Research

Redundancy reduction as a form of neural coding has been since the early sixties a topic of large research interest. A number of strategies has been proposed, but the one which is attracting most attention recently assumes that this coding is carried out so that the output signals are mutually independent. In this work we go one step further and suggest an strategy to deal also with non-orthogonal signals (i.e., ''dependent'' signals). Moreover, instead of working with the usual squared error, we design a neuron where the non-linearity is operating on the error. It is computationally more economic and, importantly, the permutation/scaling problem10 is avoided. The framework is given with a biological background, as we avocate throughout the manuscript that the algorithm fits well the single neuron and redundancy reduction doctrine.5 Moreover, we show that wavelet-like receptive fields emerges from natural images processed by this algorithm.

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