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Stine, G. M.

Publications and source records attributed to Stine, G. M..

5 recordsLinked to original sources

OpenDrive: An Open-Source Microdrive for Large-Scale Neurophysiology

Neuropixels-NHP probes have ushered in a new era of high-density neurophysiology recording in large animal models. Here, we present OpenDrive, an open-source microdrive system designed specifically for acute insertion of Neuropixels-NHPs. OpenDrive combines a custom motorized microdrive, six-drive control console, and software platform. Compared with commercially available options, OpenDrive offers (1) low cost, (2) precise, accurate, and stable probe movement, (3) scalability to many-probe recording, and (4) open-source hardware designs and software. In our experiments, OpenDrive has already supported recordings from thousands of neurons across a variety of cortical and subcortical structures. By lowering technical barriers and enabling community-driven development with OpenDrive, we aim to accelerate Neuropixels recording in large animal models.

neuroscience↗

Neuronal and behavioral responses to naturalistic texture images in macaque monkeys

The visual world is richly adorned with texture, which can serve to delineate important elements of natural scenes. In anesthetized macaque monkeys, selectivity for the statistical features of natural texture is weak in V1, but substantial in V2, suggesting that neuronal activity in V2 might directly support texture perception. To test this, we investigated the relation between single cell activity in macaque V1 and V2 and simultaneously measured behavioral judgments of texture. We generated stimuli along a continuum between naturalistic texture and phase-randomized noise and trained two macaque monkeys to judge whether a sample texture more closely resembled one or the other extreme. Analysis of responses revealed that individual V1 and V2 neurons carried much less information about texture naturalness than behavioral reports. However, the sensitivity of V2 neurons, especially those preferring naturalistic textures, was significantly closer to that of behavior compared with V1. The firing of both V1 and V2 neurons predicted perceptual choices in response to repeated presentations of the same ambiguous stimulus in one monkey, despite low individual neural sensitivity. However, neither population predicted choice in the second monkey. We conclude that neural responses supporting texture perception likely continue to develop downstream of V2. Further, combined with neural data recorded while the same two monkeys performed an orientation discrimination task, our results demonstrate that choice-correlated neural activity in early sensory cortex is unstable across observers and tasks, untethered from neuronal sensitivity, and thus unlikely to reflect a critical aspect of the formation of perceptual decisions. Significance statementAs visual signals propagate along the cortical hierarchy, they encode increasingly complex aspects of the sensory environment and likely have a more direct relationship with perceptual experience. We replicate and extend previous results from anesthetized monkeys differentiating the selectivity of neurons along the first step in cortical vision from area V1 to V2. However, our results further complicate efforts to establish neural signatures that reveal the relationship between perception and the neuronal activity of sensory populations. We find that choice-correlated activity in V1 and V2 is unstable across different observers and tasks, and also untethered from neuronal sensitivity and other features of nonsensory response modulation.

neuroscience↗

Direct observation of the neural computations underlying a single decision

Neurobiological investigations of perceptual decision-making have furnished the first glimpse of a flexible cognitive process at the level of single neurons (Shadlen and Newsome, 1996; Shadlen and Kiani, 2013). Neurons in the parietal and prefrontal cortex (Kim and Shadlen, 1999; Romo et al., 2004; Hernandez et al., 2002; Ding and Gold, 2012) are thought to represent the accumulation of noisy evidence, acquired over time, leading to a decision. Neural recordings averaged over many decisions have provided support for the deterministic rise in activity to a termination bound (Roitman and Shadlen, 2002). Critically, it is the unobserved stochastic component that is thought to confer variability in both choice and decision time (Gold and Shadlen, 2007). Here, we elucidate this drift-diffusion signal on individual decisions. We recorded simultaneously from hundreds of neurons in the lateral intraparietal cortex (LIP) of monkeys while they made decisions about the direction of random dot motion. We show that a single scalar quantity, derived from the weighted sum of the population activity, represents a combination of deterministic drift and stochastic diffusion. Moreover, we provide direct support for the hypothesis that this drift-diffusion signal approximates the quantity responsible for the variability in choice and reaction times. The population-derived signals rely on a small subset of neurons with response fields that overlap the choice targets. These neurons represent the integral of noisy evidence. Another subset of direction-selective neurons with response fields that overlap the motion stimulus appear to represent the integrand. This parsimonious architecture would escape detection by state-space analyses, absent a clear hypothesis.

neuroscience↗

A neural mechanism for terminating decisions

The brain makes decisions by accumulating evidence until there is enough to stop and choose. Neural mechanisms of evidence accumulation are well established in association cortex, but the site and mechanism of termination is unknown. Here, we elucidate a mechanism for termination by neurons in the primate superior colliculus. We recorded simultaneously from neurons in lateral intraparietal cortex (LIP) and the superior colliculus (SC) while monkeys made perceptual decisions, reported by eye-movements. Single-trial analyses revealed distinct dynamics: LIP tracked the accumulation of evidence on each decision, and SC generated one burst at the end of the decision, occasionally preceded by smaller bursts. We hypothesized that the bursts manifest a threshold mechanism applied to LIP activity to terminate the decision. Focal inactivation of SC produced behavioral effects diagnostic of an impaired threshold sensor, requiring a stronger LIP signal to terminate a decision. The results reveal the transformation from deliberation to commitment.

neuroscience↗

Differentiating between integration and non-integration strategies in perceptual decision making

Many tasks used to study decision-making encourage subjects to integrate evidence over time. Such tasks are useful to understand how the brain operates on multiple samples of information over prolonged timescales, but only if subjects actually integrate evidence to form their decisions. We explored the behavioral observations that corroborate evidence-integration in a number of task-designs. Several commonly accepted signs of integration were also predicted by non-integration strategies. Furthermore, an integration model could fit data generated by non-integration models. We identified the features of non-integration models that allowed them to mimic integration and used these insights to design a motion discrimination task that disentangled the models. In human subjects performing the task, we falsified a non-integration strategy in each and confirmed prolonged integration in all but one subject. The findings illustrate the difficulty of identifying a decision-makers strategy and support solutions to achieve this goal.

neuroscience↗