Faculty Bibliography

High-density microelectrode arrays have opened new possibilities for systems neuroscience, but brain motion relative to the array poses challenges for downstream analyses. We introduce DREDge (Decentralized Registration of Electrophysiology Data), a robust algorithm for the registration of noisy, nonstationary extracellular electrophysiology recordings. In addition to estimating motion from action potential data, DREDge enables automated, high-temporal-resolution motion tracking in local field potential data. In human intraoperative recordings, DREDge's local field potential-based tracking reliably recovered evoked potentials and single-unit spike sorting. In recordings of deep probe insertions in nonhuman primates, DREDge tracked motion across centimeters of tissue and several brain regions while mapping single-unit electrophysiological features. DREDge reliably improved motion correction in acute mouse recordings, especially in those made with a recent ultrahigh-density probe. Applying DREDge to recordings from chronic implantations in mice yielded stable motion tracking despite changes in neural activity between experimental sessions. These advances enable automated, scalable registration of electrophysiological data across species, probes and drift types, providing a foundation for downstream analyses of these rich datasets.

While visual responses to familiar and novel stimuli have been extensively studied, it is unknown how neuronal representations of familiar stimuli are affected when they are interleaved with novel images. We examined a large-scale dataset from mice performing a visual go/no-go change detection task. After training with eight images, six novel images were interleaved with two familiar ones. Unexpectedly, we found that the behavioral performance in response to familiar images was impaired when they were mixed with novel images. When familiar images were interleaved with novel ones, the dimensionality of their representation increased, indicating a perturbation of their neuronal responses. Furthermore, responses to familiar images in the primary visual cortex were less predictive of responses in higher-order areas, indicating less efficient communication. Spontaneous correlations between neurons were predictive of responses to novel images, but less so to familiar ones. Our study demonstrates the modification of representations of familiar images by novelty.

Most single units recorded from macaque secondary visual cortex (V2) respond with higher firing rates to synthetic texture images containing "naturalistic" higher-order statistics than to spectrally matched "noise" images lacking these statistics. In contrast, few single units in V1 show this property. We explored how the strength and dynamics of response vary across the different layers of visual cortex by recording multiunit (defined as high-frequency power in the local field potential) and gamma-band activity evoked by brief presentations of naturalistic and noise images in V1 and V2 of anesthetized macaque monkeys of both sexes. As previously reported, recordings in V2 showed consistently stronger responses to naturalistic texture than to spectrally matched noise. In contrast to single-unit recordings, V1 multiunit activity showed a preference for images with naturalistic statistics, and in gamma-band activity this preference was comparable across V1 and V2. Sensitivity to naturalistic image structure was strongest in the supragranular and infragranular layers of V1, but weak in granular layers, suggesting that it might reflect feedback from V2. Response timing was consistent with this idea. Visual responses appeared first in V1, followed by V2. Sensitivity to naturalistic texture emerged first in V2, followed by the supragranular and infragranular layers of V1, and finally in the granular layers of V1. Our results demonstrate laminar differences in the encoding of higher-order statistics of natural texture, and suggest that this sensitivity first arises in V2 and is fed back to modulate activity in V1.SIGNIFICANCE STATEMENT The circuit mechanisms responsible for visual representations of intermediate complexity are largely unknown. We used a well validated set of synthetic texture stimuli to probe the temporal and laminar profile of sensitivity to the higher-order statistical structure of natural images. We found that this sensitivity emerges first and most strongly in V2 but soon after in V1. However, sensitivity in V1 is higher in the laminae (extragranular) and recording modalities (local field potential) most likely affected by V2 connections, suggesting a feedback origin. Our results show how sensitivity to naturalistic image structure emerges across time and circuitry in the early visual cortex.

Amblyopia, a disorder in which vision through one of the eyes is degraded, arises because of defective processing of information by the visual system. Amblyopia often develops in humans after early misalignment of the eyes (strabismus), and can be simulated in macaque monkeys by artificially inducing strabismus. In such amblyopic animals, single-unit responses in primary visual cortex (V1) are appreciably reduced when evoked by the amblyopic eye compared to the other (fellow) eye. However, this degradation in single V1 neuron responsivity is not commensurate with the marked losses in visual sensitivity and resolution measured behaviorally. Here we explored the idea that changes in patterns of coordinated activity across populations of V1 neurons may contribute to degraded visual representations in amblyopia, potentially making it more difficult to read out evoked activity to support perceptual decisions. We studied the visually-evoked activity of V1 neuronal populations in three macaques (M. nemestrina) with strabismic amblyopia and in one control. Activity driven through the amblyopic eye was diminished, and these responses also showed more interneuronal correlation at all stimulus contrasts than responses driven through the fellow eye or responses in the control. A decoding analysis showed that responses driven through the amblyopic eye carried less visual information than other responses.Our results suggest that part of the reduced visual capacity of amblyopes may be due to changes in the patterns of functional interaction among neurons in V1.

Response properties of MT neurons are often studied with "bikinetic" plaid stimuli, which consist of two superimposed sine wave gratings moving in different directions. Oculomotor studies using "unikinetic plaids" in which only one of the two superimposed gratings moves suggest that the eyes first move reflexively in the direction of the moving grating and only later converge on the perceived direction of the moving pattern. MT has been implicated as the source of visual signals that drives these responses. We wanted to know whether stationary gratings, which have little effect on MT cells when presented alone, would influence MT responses when paired with a moving grating. We recorded extracellularly from neurons in area MT and measured responses to stationary and moving gratings, and to their sums: bikinetic and unikinetic plaids. As expected, stationary gratings presented alone had a very modest influence on the activity of MT neurons. Responses to moving gratings and bikinetic plaids were similar to those previously reported and revealed cells selective for the motion of plaid patterns and of their components (pattern and component cells). When these neurons were probed with unikinetic plaids, pattern cells shifted their direction preferences in a way that revealed the influence of the static grating. Component cell preferences shifted little or not at all. These results support the notion that pattern-selective neurons in area MT integrate component motions that differ widely in speed, and that they do so in a way that is consistent with an intersection-of-constraints model.NEW & NOTEWORTHY Human perceptual and eye movement responses to moving gratings are influenced by adding a second, static grating to create a "unikinetic" plaid. Cells in MT do not respond to static gratings, but those gratings still influence the direction selectivity of some MT cells. The cells influenced by static gratings are those tuned for the motion of global patterns, but not those tuned only for the individual components of moving targets.

We are sad to report that Professor Jacob (Jack) Nachmias passed away on March 2, 2019. Nachmias was born in Athens, Greece, on June 9, 1928. To escape the Nazis, he and his family came to the United States in 1939. He received his undergraduate degree from Cornell University and then an MA from Swarthmore College, where he worked with Hans Wallach and Wolfgang Kohler; his PhD in Psychology was from Harvard University. Nachmias spent the majority of his career as a Professor of Psychology at the University of Pennsylvania. He made fundamental contributions to our understanding of vision, most notably through the study of eye movements, the development of signal detection theory and forced-choice psychophysical methods, and the psychophysical characterization of spatial-frequency-selective visual channels. Nachmias' work was recognized by his election to the National Academy of Sciences and receipt of the Optical Society's Tillyer Award.

Motion selectivity in primary visual cortex (V1) is approximately separable in orientation, spatial frequency, and temporal frequency ("frequency-separable"). Models for area MT neurons posit that their selectivity arises by combining direction-selective V1 afferents whose tuning is organized around a tilted plane in the frequency domain, specifying a particular direction and speed ("velocity-separable"). This construction explains "pattern direction selective" MT neurons, which are velocity-selective but relatively invariant to spatial structure, including spatial frequency, texture and shape. We designed a set of experiments to distinguish frequency- and velocity-separable models and executed them with single-unit recordings in macaque V1 and MT. Surprisingly, when tested with single drifting gratings, most MT neurons' responses are fit equally well by models with either form of separability. However, responses to plaids (sums of two moving gratings) tend to be better described as velocity-separable, especially for pattern neurons. We conclude that direction selectivity in MT is primarily computed by summing V1 afferents, but pattern-invariant velocity tuning for complex stimuli may arise from local, recurrent interactions.Significance Statement How do sensory systems build representations of complex features from simpler ones? Visual motion representation in cortex is a well-studied example: the direction and speed of moving objects, regardless of shape or texture, is computed from the local motion of oriented edges. Here we quantify tuning properties based on single-unit recordings in primate area MT, then fit a novel, generalized model of motion computation. The model reveals two core properties of MT neurons - speed tuning and invariance to local edge orientation - result from a single organizing principle: each MT neuron combines afferents that represent edge motions consistent with a common velocity, much as V1 simple cells combine thalamic inputs consistent with a common orientation.

The stimulus selectivity of neurons in V1 is well known, as is the finding that their responses can be affected by visual input to areas outside of the classical receptive field. Less well understood are the ways selectivity is modified as signals propagate to visual areas beyond V1, such as V2. We recently proposed a role for V2 neurons in representing the higher order statistical dependencies found in images of naturally occurring visual texture. V2 neurons, but not V1 neurons, respond more vigorously to "naturalistic" images that contain these dependencies than to "noise" images that lack them. In this work, we examine the dependency of these effects on stimulus size. For most V2 neurons, the preference for naturalistic over noise stimuli was modest when presented in small patches and gradually strengthened with increasing size, suggesting that the mechanisms responsible for this enhanced sensitivity operate over regions of the visual field that are larger than the classical receptive field. Indeed, we found that surround suppression was stronger for noise than for naturalistic stimuli and that the preference for large naturalistic stimuli developed over a delayed time course consistent with lateral or feedback connections. These findings are compatible with a spatially broad facilitatory mechanism that is absent in V1 and suggest that a distinct role for the receptive field surround emerges in V2 along with sensitivity for more complex image structure. NEW & NOTEWORTHY The responses of neurons in visual cortex are often affected by visual input delivered to regions of the visual field outside of the conventionally defined receptive field, but the significance of such contextual modulations are not well understood outside of area V1. We studied the importance of regions beyond the receptive field in establishing a novel form of selectivity for the statistical dependencies contained in natural visual textures that first emerges in area V2.

Sensory neurons represent stimulus information with sequences of action potentials that differ across repeated measurements. This variability limits the information that can be extracted from momentary observations of a neuron's response. It is often assumed that integrating responses over time mitigates this limitation. However, temporal response correlations can reduce the benefits of temporal integration. We examined responses of individual orientation-selective neurons in the primary visual cortex of two macaque monkeys performing an orientation-discrimination task. The signal-to-noise ratio of temporally integrated responses increased for durations up to a few hundred milliseconds but saturated for longer durations. This was true even when cells exhibited little or no adaptation in their response levels. These observations are well explained by a statistical response model in which spikes arise from a Poisson process whose stimulus-dependent rate is modulated by slow, stimulus-independent fluctuations in gain. The response variability arising from the Poisson process is reduced by temporal integration, but the slow modulatory nature of variability due to gain fluctuations is not. Slow gain fluctuations therefore impose a fundamental limit on the benefits of temporal integration.