Biomedical subjects

T W Troyer

Publications and source records attributed to T W Troyer.

6 recordsLinked to original sources

PubMed2001

Birdsong: models and mechanisms.

Recent studies have provided important information concerning the neural signals that subserve vocal learning in songbirds: advanced signal processing techniques are beginning to clarify the behavioral trajectories followed by developing birds; single-unit physiology in behaving animals is providing important clues about sensory and motor representations during learning; in vitro whole-cell recordings are revealing patterns of synaptic communication; and experimental alterations in song behavior have advanced our understanding of specific structure-function relationships. The construction of theoretical and computational models will be crucial in integrating such disparate experimental results.

Animals↗

PubMed2000

An associational model of birdsong sensorimotor learning I. Efference copy and the learning of song syllables.

Birdsong learning provides an ideal model system for studying temporally complex motor behavior. Guided by the well-characterized functional anatomy of the song system, we have constructed a computational model of the sensorimotor phase of song learning. Our model uses simple Hebbian and reinforcement learning rules and demonstrates the plausibility of a detailed set of hypotheses concerning sensory-motor interactions during song learning. The model focuses on the motor nuclei HVc and robust nucleus of the archistriatum (RA) of zebra finches and incorporates the long-standing hypothesis that a series of song nuclei, the Anterior Forebrain Pathway (AFP), plays an important role in comparing the bird's own vocalizations with a previously memorized song, or "template." This "AFP comparison hypothesis" is challenged by the significant delay that would be experienced by presumptive auditory feedback signals processed in the AFP. We propose that the AFP does not directly evaluate auditory feedback, but instead, receives an internally generated prediction of the feedback signal corresponding to each vocal gesture, or song "syllable." This prediction, or "efference copy," is learned in HVc by associating premotor activity in RA-projecting HVc neurons with the resulting auditory feedback registered within AFP-projecting HVc neurons. We also demonstrate how negative feedback "adaptation" can be used to separate sensory and motor signals within HVc. The model predicts that motor signals recorded in the AFP during singing carry sensory information and that the primary role for auditory feedback during song learning is to maintain an accurate efference copy. The simplicity of the model suggests that associational efference copy learning may be a common strategy for overcoming feedback delay during sensorimotor learning.

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PubMed2000

An associational model of birdsong sensorimotor learning II. Temporal hierarchies and the learning of song sequence.

Understanding the neural mechanisms underlying serially ordered behavior is a fundamental problem in motor learning. We present a computational model of sensorimotor learning in songbirds that is constrained by the known functional anatomy of the song circuit. The model subsumes our companion model for learning individual song "syllables" and relies on the same underlying assumptions. The extended model addresses the problem of learning to produce syllables in the correct sequence. Central to our approach is the hypothesis that the Anterior Forebrain Pathway (AFP) produces signals related to the comparison of the bird's own vocalizations and a previously memorized "template." This "AFP comparison hypothesis" is challenged by the lack of a direct projection from the AFP to the song nucleus HVc, a candidate site for the generator of song sequence. We propose that sequence generation in HVc results from an associative chain of motor and sensory representations (motor --> sensory --> next motor. ) encoded within the two known populations of HVc projection neurons. The sensory link in the chain is provided, not by auditory feedback, but by a centrally generated efference copy that serves as an internal prediction of this feedback. The use of efference copy as a substitute for the sensory signal explains the ability of adult birds to produce normal song immediately after deafening. We also predict that the AFP guides sequence learning by biasing motor activity in nucleus RA, the premotor nucleus downstream of HVc. Associative learning then remaps the output of the HVc sequence generator. By altering the motor pathway in RA, the AFP alters the correspondence between HVc motor commands and the resulting sensory feedback and triggers renewed efference copy learning in HVc. Thus, auditory feedback-mediated efference copy learning provides an indirect pathway by which the AFP can influence sequence generation in HVc. The model makes predictions concerning the role played by specific neural populations during the sensorimotor phase of song learning and demonstrates how simple rules of associational plasticity can contribute to the learning of a complex behavior on multiple time scales.

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PubMed1998

Contrast-invariant orientation tuning in cat visual cortex: thalamocortical input tuning and correlation-based intracortical connectivity.

The origin of orientation selectivity in visual cortical responses is a central problem for understanding cerebral cortical circuitry. In cats, many experiments suggest that orientation selectivity arises from the arrangement of lateral geniculate nucleus (LGN) afferents to layer 4 simple cells. However, this explanation is not sufficient to account for the contrast invariance of orientation tuning. To understand contrast invariance, we first characterize the input to cat simple cells generated by the oriented arrangement of LGN afferents. We demonstrate that it has two components: a spatial-phase-specific component (i.e., one that depends on receptive field spatial phase), which is tuned for orientation, and a phase-nonspecific component, which is untuned. Both components grow with contrast. Second, we show that a correlation-based intracortical circuit, in which connectivity between cell pairs is determined by the correlation of their LGN inputs, is sufficient to achieve well tuned, contrast-invariant orientation tuning. This circuit generates both spatially opponent, "antiphase" inhibition ("push-pull"), and spatially matched, "same-phase" excitation. The inhibition, if sufficiently strong, suppresses the untuned input component and sharpens responses to the tuned component at all contrasts. The excitation amplifies tuned responses. This circuit agrees with experimental evidence showing spatial opponency between, and similar orientation tuning of, the excitatory and inhibitory inputs received by a simple cell. Orientation tuning is primarily input driven, accounting for the observed invariance of tuning width after removal of intracortical synaptic input, as well as for the dependence of orientation tuning on stimulus spatial frequency. The model differs from previous push-pull models in requiring dominant rather than balanced inhibition and in predicting that a population of layer 4 inhibitory neurons should respond in a contrast-dependent manner to stimuli of all orientations, although their tuning width may be similar to that of excitatory neurons. The model demonstrates that fundamental response properties of cortical layer 4 can be explained by circuitry expected to develop under correlation-based rules of synaptic plasticity, and shows how such circuitry allows the cortex to distinguish stimulus intensity from stimulus form.

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PubMed1997

Physiological gain leads to high ISI variability in a simple model of a cortical regular spiking cell.

To understand the interspike interval (ISI) variability displayed by visual cortical neurons (Softky & Koch, 1993), it is critical to examine the dynamics of their neuronal integration, as well as the variability in their synaptic input current. Most previous models have focused on the latter factor. We match a simple integrate-and-fire model to the experimentally measured integrative properties of cortical regular spiking cells (McCormick, Connors, Lighthall, & Prince, 1985). After setting RC parameters, the post-spike voltage reset is set to match experimental measurements of neuronal gain (obtained from in vitro plots of firing frequency versus injected current). Examination of the resulting model leads to an intuitive picture of neuronal integration that unifies the seemingly contradictory 1/square root of N and random walk pictures that have previously been proposed. When ISIs are dominated by postspike recovery, 1/square root of N arguments hold and spiking is regular; after the "memory" of the last spike becomes negligible, spike threshold crossing is caused by input variance around a steady state and spiking is Poisson. In integrate-and-fire neurons matched to cortical cell physiology, steady-state behavior is predominant, and ISIs are highly variable at all physiological firing rates and for a wide range of inhibitory and excitatory inputs.

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PubMed1994

Construction and analysis of a database representing a neural map.

We describe the development and analysis of a quantitative database representing the global structural and functional organization of an entire sensory map. The database was derived from measurements of anatomical characteristics of a statistical sample of typical mechanosensory afferents in the cricket cercal sensory system. Anatomical characteristics of the neurons were measured quantitatively in three dimensions using a computer reconstruction system. The reconstructions of all neurons were aligned and scaled to a common standard set of dimensions, according to a highly reproducible set of intrinsic fiducial marks. The database therefore preserves accurate information about spatial relationships between the neurons within the ensemble. Algorithms were implemented to allow the integration of electrophysiological data about the stimulus/response characteristics of the reconstructed neurons into the database. The algorithms essentially map a physiological function onto a "field" representing the continuous distribution of synaptic terminals throughout the neural structure. Subsequent analysis allowed quantitative predictions of several important functional characteristics of the sensory map that emerge from its global organization. First, quantitative and testable predictions were made about ensemble response patterns within the map. The predicted patterns are presented as graphical images, similar to images that might be observed with activity-dependent dyes in the real neural system. Second, the synaptic innervation patterns from the sensory afferent map onto the dendrites of a postsynaptic target interneuron were predicted by calculating the overlap between the interneuron's dendrites with the afferent map. By doing so, several aspects of the stimulus/response properties of the interneuron were accurately predicted.

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