Biology subjects

Cohen, Y. E.

Publications and source records attributed to Cohen, Y. E..

4 recordsLinked to original sources

bioRxiv2022

Time as a supervisor: temporal regularity and auditory object learning

Sensory systems appear to learn to transform incoming sensory information into perceptual representations, or "objects", that can inform and guide behavior with minimal explicit supervision. Here, we propose that the auditory system can achieve this goal by using time as a supervisor, i.e., by learning features of a stimulus that are temporally regular. We will show that this procedure generates a feature space sufficient to support fundamental computations of auditory perception. In detail, we consider the problem of discriminating between instances of a prototypical class of natural auditory objects, i.e., rhesus macaque vocalizations. We test discrimination in two ethologically relevant tasks: discrimination in a cluttered acoustic background and generalization to discriminate between novel exemplars. We show that an algorithm that learns these temporally regular features affords better or equivalent discrimination and generalization than conventional feature-selection algorithms, i.e., principal component analysis and independent component analysis. Our findings suggest that the slow temporal features of auditory stimuli may be sufficient for parsing auditory scenes and that the auditory brain could utilize these slowly changing temporal features.

neuroscience↗

bioRxiv2022

Laminar Distribution of stimulus- and task-related variables related to auditory streaming in core and belt auditory cortex

Although previous studies have identified neural mechanisms that may underlie auditory scene analysis, the relationship between these mechanisms and behavior remains elusive. To fill these gaps, we recorded multiunit activity (MUA) from the posterior and anterior auditory fields while monkeys participated in an auditory streaming task. We found that MUA magnitude was reduced as the streaming stimulus unfolded over time, and this reduction depended on the frequency difference between the tone bursts comprising the streaming stimulus. We then examined whether this frequency-dependent reduction in activity could be utilized by downstream neurons to read out "one stream" versus "two streams" and found that, as the frequency difference increased, an ideal observer consistently classified neural activity as "two streams". However, because this classification was not modulated by the monkeys choices, it suggests that this activity may not reflect the segregation of stimuli into perceptually distinct auditory streams but may simply reflect bottom-up processes.

neuroscience↗

bioRxiv2021

Rule-based and stimulus-based cues bias auditory decisions via different computational and physiological mechanisms

Expectations, such as those arising from either learned rules or recent stimulus regularities, can bias subsequent auditory perception in diverse ways. However, it is not well understood if and how these diverse effects depend on the source of the expectations. Further, it is unknown whether different sources of bias use the same or different computational and physiological mechanisms. We examined how rule-based and stimulus-based expectations influenced behavior and pupil- linked arousal, a marker of certain forms of expectation-based processing, of human subjects performing an auditory frequency-discrimination task. Rule-based cues consistently biased choices and response times (RTs) toward the more-probable stimulus. In contrast, stimulus-based cues had a complex combination of effects, including choice and RT biases toward and away from the frequency of recently presented stimuli. These different behavioral patterns also had: 1) distinct computational signatures, including different modulations of key components of a novel form of a drift-diffusion decision model and 2) distinct physiological signatures, including substantial bias- dependent modulations of pupil size in response to rule-based but not stimulus-based cues. These results imply that different sources of expectations can modulate auditory processing via distinct mechanisms: one that uses arousal-linked, rule-based information and another that uses arousal- independent, stimulus-based information to bias the speed and accuracy of auditory perceptual decisions. Author summaryPrior information about upcoming stimuli can bias our perception of those stimuli. Whether different sources of prior information bias perception in similar or distinct ways is not well understood. We compared the influence of two kinds of prior information on tone-frequency discrimination: rule-based cues, in the form of explicit information about the most-likely identity of the upcoming tone; and stimulus-based cues, in the form of sequences of tones presented before the to-be-discriminated tone. Although both types of prior information biased auditory decision- making, they demonstrated distinct behavioral, computational, and physiological signatures. Our results suggest that the brain processes prior information in a form-specific manner rather than utilizing a general-purpose prior. Such form-specific processing has implications for understanding decision biases real-world contexts, in which prior information comes from many different sources and modalities.

neuroscience↗

bioRxiv2017

Cortical circuit based lossless neural integrator for perceptual decision-making

The intrinsic uncertainty of sensory information (i.e., evidence) does not necessarily deter an observer from making a reliable decision. Indeed, uncertainty can be reduced by integrating (accumulating) incoming sensory evidence. It is widely thought that this accumulation is instantiated via recurrent rate-code neural networks. Yet, these networks do not fully explain important aspects of perceptual decision-making, such as a subjects ability to retain accumulated evidence during temporal gaps in the sensory evidence. Here, we utilized computational models to show that cortical circuits can switch flexibly between retention and integration modes during perceptual decision-making. Further, we found that, depending on how the sensory evidence was readout, we could simulate stepping and ramping activity patterns, which may be analogous to those seen in different studies of decision-making in the primate parietal cortex. This finding may reconcile these previous empirical studies because it suggests these two activity patterns emerge from the same mechanism.

neuroscience↗