Biology subjects

Tokdar, S. T.

Publications and source records attributed to Tokdar, S. T..

5 recordsLinked to original sources

bioRxiv2025

Multiplexing of visual-auditory signals in a predominantly auditory brain region

A recently proposed theory of neural representation postulates that when more than one stimulus is to be encoded, neurons in that representation may fluctuate between encoding each item. To date, such work has considered only cases in which both stimuli are of the same sensory modality, such as how two sounds are encoded in an auditory brain region. Here, we consider the influence of sensory modality on this process, asking whether stimuli of a non-dominant sensory modality can evoke or influence the fluctuating activity patterns observed for combinations of stimuli of a dominant sensory modality. Specifically, we investigated the impact of combining visual and auditory stimuli on single-unit activity in the inferior colliculus, a predominantly auditory structure, in monkeys performing a behavioral task involving reporting all stimulus locations in a given trial. We found that fluctuating activity is evident when a single sound and a single visual stimulus are paired at the same spatial location, indicating that fluctuating activity can be induced when one item is not from a brain areas preferred modality, and even when only a single spatial location is involved and spatial attention is directed to only one place. Fluctuating activity was also identified when visual stimuli were paired with sounds presented at two spatial locations. The IC appeared to maintain a representation of all stimuli, regardless of the sequence in which the monkey localized the targets (although in one monkey there was a bias toward greater representation of the second reported location). Together, these results indicate that fluctuating activity occurs in response to multimodal stimuli in a predominantly unimodal brain structure and is geared toward preservation of all sensory information rather than attentional filtering. Impact StatementWe found that when visual stimuli are paired with sounds, they can induce fluctuating activity in neurons that are primarily sensitive to sound alone. Such activity fluctuations may permit the representation of both the visual and auditory stimuli in an overlapping population of neurons.

neuroscience↗

bioRxiv2024

Spike Count Analysis for MultiPlexing Inference (SCAMPI)

Understanding how neurons encode multiple simultaneous stimuli is a fundamental question in neuroscience. We have previously introduced a novel theory of stochastic encoding patterns wherein a neurons spiking activity dynamically switches among its constituent single-stimulus activity patterns when presented with multiple stimuli (Groh et al., 2024). Here, we present an enhanced, comprehensive statistical testing framework for such "multiplexing" or "code juggling". Our new approach evaluates whether dual-stimulus responses can be accounted for as mixtures of Poissons either anchored to or bounded by single-stimulus benchmarks. Our enhanced framework improves upon previous methods in two key ways. First, it introduces a stronger set of foils for multiplexing, including an "overreaching" category that captures overdispersed activity patterns unrelated to the single-stimulus benchmarks, reducing false detection of multiplexing/code-juggling. Second, it detects faster fluctuations - i.e. at sub-trial timescales - that would have been overlooked before. We utilize a Bayesian inference framework, considering the hypothesis with the highest posterior probability as the winner, and employ predictive recursion marginal likelihood method for the involving nonparametric density estimation. Reanalysis of previous findings confirms the general observation of "code juggling" and indicates that such juggling may well occur on faster timescales than previously suggested. We further confirm that juggling is more prevalent in (a) the inferotemporal face patch system for combinations of face stimuli than for faces and non-face objects; and (b) the primary visual cortex for distinct vs fused objects.

neuroscience↗

bioRxiv2023

Multiple objects evoke fluctuating responses in several regions of the visual pathway

How neural representations preserve information about multiple stimuli is mysterious. Because tuning of individual neurons is coarse (for example, visual receptive field diameters can exceed perceptual resolution), the populations of neurons potentially responsive to each individual stimulus can overlap, raising the question of how information about each item might be segregated and preserved in the population. We recently reported evidence for a potential solution to this problem: when two stimuli were present, some neurons in the macaque visual cortical areas V1 and V4 exhibited fluctuating firing patterns, as if they responded to only one individual stimulus at a time (Jun et al., 2022). However, whether such an information encoding strategy is ubiquitous in the visual pathway and thus could constitute a general phenomenon remains unknown. Here we provide new evidence that such fluctuating activity is also evoked by multiple stimuli in visual areas responsible for processing visual motion (middle temporal visual area, MT), and faces (middle fundus and anterolateral face patches in inferotemporal cortex - areas MF and AL), thus extending the scope of circumstances in which fluctuating activity is observed. Furthermore, consistent with our previous results in the early visual area V1, MT exhibits fluctuations between the representations of two stimuli when these form distinguishable objects but not when they fuse into one perceived object, suggesting that fluctuating activity patterns may underlie visual object formation. Taken together, these findings point toward an updated model of how the brain preserves sensory information about multiple stimuli for subsequent processing and behavioral action. Impact StatementNeural fluctuations in multiple areas along the visual cortical hierarchy could allow the brain to represent distinct co-occurring visual stimuli.

neuroscience↗

bioRxiv2019

Patterns of neural correlations in V1 vary with the number of objects

Sensory receptive fields are large enough that they can contain more than one perceptible stimulus. How, then, can the brain encode information about each of the stimuli that may be present at a given moment? We recently showed that when more than one stimulus is present, single neurons can fluctuate between coding one vs. the other(s) across some time period, suggesting a form of neural multiplexing of different stimuli (Caruso et al., 2018). Here we investigate (a) whether such coding fluctuations occur in early visual cortical areas; (b) how coding fluctuations are coordinated across the neural population; and (c) how coordinated coding fluctuations depend on the parsing of stimuli into separate vs. fused objects. We found coding fluctuations do occur in macaque V1 but only when the two stimuli form separate objects. Such separate objects evoked a novel pattern of V1 spike count ("noise") correlations involving distinct distributions of positive and negative values. This bimodal correlation pattern was most pronounced among pairs of neurons showing the strongest evidence for coding fluctuations or multiplexing. Whether a given pair of neurons exhibited positive or negative correlations depended on whether the two neurons both responded better to the same object or had different object preferences. Distinct distributions of spike count correlations based on stimulus preferences were also seen in V4 for separate objects but not when two stimuli fused to form one object. These findings suggest multiple objects evoke different response dynamics than those evoked by single stimuli, lending support to the multiplexing hypothesis and suggesting a means by which information about multiple objects can be preserved despite the apparent coarseness of sensory coding. Significance StatementHow the brain separates information about multiple objects despite overlap in the neurons responsive to each item is not well understood. Here we show that some neurons in V1 exhibit coding fluctuations in response to two objects, and that these coding fluctuations are coordinated at the population level in ways that are not observed for single objects. Broadly similar results were obtained in V4. These response dynamics lend support to the hypothesis that information about individual objects may be multiplexed across the neural population, preserving information about each item despite the coarseness of sensory coding.

neuroscience↗

bioRxiv2019

Sensitivity and specificity of a Bayesian single trial analysis for time varying neural signals

We recently reported the existence of fluctuations in neural signals that may permit neurons to code multiple simultaneous stimuli sequentially across time1. This required deploying a novel statistical approach to permit investigation of neural activity at the scale of individual trials. Here we present tests using synthetic data to assess the sensitivity and specificity of this analysis. We fabricated datasets to match each of several potential response patterns derived from single-stimulus response distributions. In particular, we simulated dual stimulus trial spike counts that reflected fluctuating mixtures of the single stimulus spike counts, stable intermediate averages, single stimulus winner-take-all, or response distributions that were outside the range defined by the single stimulus responses (such as summation or suppression). We then assessed how well the analysis recovered the correct response pattern as a function of the number of simulated trials and the difference between the simulated responses to each \"stimulus\" alone. We found excellent recovery of the mixture, intermediate, and outside categories (>97% correct), and good recovery of the single/winner-take-all category (>90% correct) when the number of trials was >20 and the single-stimulus response rates were 50Hz and 20Hz respectively. Both larger numbers of trials and greater separation between the single stimulus firing rates improved categorization accuracy. These results provide a benchmark, and guidelines for data collection, for use of this method to investigate coding of multiple items at the individual-trial time scale.

neuroscience↗