Adam C Snyder

University of Rochester | UR · Brain and Cognitive Sciences / Neuroscience

Understanding brain function is facilitated by constructing computational models that accurately reproduce aspects of brain activity. Networks of spiking neurons capture the underlying biophysics of neuronal circuits, yet the dependence of their activity on model parameters is notoriously complex. As a result, heuristic methods have been used to co...

Electroencephalography (EEG) has long been used to index brain states, from early studies describing activity in the presence and absence of visual stimulation to modern work employing complex perceptual tasks. These studies have shed light on brain-wide signals but often lack explanatory power at the single neuron level. Similarly, single neuron r...

Decades of research have shown that global brain states such as arousal can be indexed by measuring the properties of the eyes. The spiking responses of neurons throughout the brain have been associated with the pupil, small fixational saccades, and vigor in eye movements, but it has been difficult to isolate how internal states affect the eyes, an...

Attention often requires maintaining a stable mental state over time while simultaneously improving perceptual sensitivity. These requirements place conflicting demands on neural populations, as sensitivity implies robust response to perturbation by incoming stimuli, which is antithetical to stability. Functional specialization of cortical areas pr...

Two commonly used approaches to study interactions among neurons are spike count correlation, which describes pairs of neurons, and dimensionality reduction, applied to a population of neurons. Although both approaches have been used to study trial-to-trial neuronal variability correlated among neurons, they are often used in isolation and have not...

Two commonly used approaches to study interactions among neurons are spike count correlation, which describes pairs of neurons, and dimensionality reduction, applied to a population of neurons. While both approaches have been used to study trial-to-trial correlated neuronal variability, they are often used in isolation and have not been directly re...

Electroencephalography (EEG) has long been used to index brain states, from early studies describing activity during visual stimulation to modern work employing complex perceptual tasks. These studies shed light on brain-wide signals but lacked explanatory power at the single neuron level. Similarly, single neuron studies can suffer from inability...

An animal’s decision depends not only on incoming sensory evidence but also on its fluctuating internal state. This state embodies multiple cognitive factors, such as arousal and fatigue, but it is unclear how these factors influence the neural processes that encode sensory stimuli and form a decision. We discovered that, unprompted by task conditi...

Decades of research have shown that global brain states such as arousal can be indexed by measuring the properties of the eyes. Neural signals from individual neurons, populations of neurons, and field potentials measured throughout much of the brain have been associated with the size of the pupil, small fixational eye movements, and vigor in sacca...

An animal's decision depends not only on incoming sensory evidence but also on its fluctuating internal state. This internal state is a product of cognitive factors, such as fatigue, motivation, and arousal, but it is unclear how these factors influence the neural processes that encode the sensory stimulus and form a decision. We discovered that, o...

The sequence of events leading to an eye movement to a target begins the moment visual information has reached the brain, well in advance of the eye movement itself. The process by which visual information is encoded and used to generate a motor plan has been the focus of substantial interest partly because of the rapid and reproducible nature of s...

Visual neurons respond more vigorously to an attended stimulus than an unattended one. How the brain prepares for response gain in anticipation of that stimulus is not well understood. One prominent proposal is that anticipation is characterized by gain-like modulations of spontaneous activity similar to gains in stimulus responses. Here we test an...

The problem of multiple testing arises in many contexts, including testing for pairwise interaction among a large number of neurons. Recently a method was developed to control false positives when covariate information, such as distances between pairs of neurons, is available. This method, however, relies on computationally-intensive Markov Chain M...

Long-range interactions between cortical areas are undoubtedly key to the computational power of the brain. For healthy human subjects the premier method for measuring brain activity on fast timescales is EEG, and coherence between EEG signals is often used to assay functional connectivity between different brain regions. However, the nature of the...

Purpose of review: The computational power of the brain arises from the complex interactions between neurons. One straightforward method to quantify the strength of neuronal interactions is by measuring correlation and coherence. Efforts to measure correlation have been advancing rapidly of late, spurred by the development of advanced recording te...

Many studies use population analysis approaches, such as dimensionality reduction, to characterize the activity of large groups of neurons. To date, these methods have treated each neuron equally, without taking into account whether neurons are excitatory or inhibitory. We studied population activity structure as a function of neuron type by applyi...

Timescale of neuronal correlations. Autocorrelation of excitatory and inhibitory neurons using a 10 ms spike count window. Curves were averaged across neurons and have a maximum of one at zero time lag. (A) Clustered network: autocorrelation of excitatory neurons (red), inhibitory neurons (blue), and excitatory neurons broken down by cluster (orang...

Modes of shared activity for V1 recordings. (A) Modes for broad-spiking neurons. The columns of the heatmap represent the eigenvectors of the shared covariance matrix, ordered by the amount of shared variance explained. (B) Same conventions as A for narrow-spiking neurons. (C) Percent of total shared variance of broad-spiking (red) and narrow-spiki...

Mixed neuron type samplings using 100 ms spike count windows. Same analysis as shown in Fig 5 using a 100 ms spike count window. The same neurons and trials of the clustered and non-clustered networks were used. Spike counts were taken in the first 100 ms of the original one second trials. (EPS)

Relationship of percent shared variance to pairwise spike count correlation. To study the relationship of the width of a zero-mean spike count correlation distribution to shared variance, we generated simulated spike counts with near-zero mean spike count correlation distributions of various widths using the method described in [44]. We began by dr...

Excitatory and inhibitory population activity structure using 100 ms spike count windows. Same analysis as shown in Fig 3 using a 100 ms spike count window. The same neurons and trials of the clustered and non-clustered networks were used. Spike counts were taken in the first 100 ms of the original one second trial. (EPS)

Neuron type classification. (A) Normalized average waveforms of neurons with average firing rates greater than one spike per second. Each waveform corresponds to one neuron and is colored by the probability that it belongs to the broad-spiking class (toward red) or the narrow-spiking class (toward blue). (B) Posterior probability of neurons belongi...

The problem of large scale multiple testing arises in many contexts, including testing for pairwise interaction among large numbers of neurons. With advances in technologies, it has become common to record from hundreds of neurons simultaneously, and this number is growing quickly, so that the number of pairwise tests can be very large. It is impor...

Inhibition and excitation form two fundamental modes of neuronal interaction, yet we understand relatively little about their distinct roles in service of perceptual and cognitive processes. We developed a multidimensional waveform analysis to identify fast-spiking (putative inhibitory) and regular-spiking (putative excitatory) neurons in vivo and...

Pairs of active neurons frequently fire action potentials or “spikes” nearly synchronously (i.e., within 5 ms of each other). This spike synchrony may occur by chance, based solely on the neurons’ fluctuating firing patterns, or it may occur too frequently to be explicable by chance alone. When spike synchrony above chances levels is present, it ma...

The development and refinement of non-invasive techniques for imaging neural activity is of paramount importance for human neuroscience. Currently, the most accessible and popular technique is electroencephalography (EEG). However, nearly all of what we know about the neural events that underlie EEG signals is based on inference, due to a dearth of...

A central neuroscientific pursuit is understanding neuronal interactions that support computations underlying cognition and behavior. Although neurons interact across disparate scales, from cortical columns to whole-brain networks, research has been restricted to one scale at a time. We measured local interactions through multi-neuronal recordings...

The trial-to-trial response variability of nearby cortical neurons is correlated. These correlations may strongly influence population coding performance. Numerous studies have shown that correlations can be dynamically modified by attention, adaptation, learning, and potent stimulus drive. However, the mechanisms that influence correlation strengt...

Correlated variability in the spiking responses of pairs of neurons, also known as spike count correlation, is a key indicator of functional connectivity and a critical factor in population coding. Underscoring the importance of correlation as a measure for cognitive neuroscience research is the observation that spike count correlations are not fix...

Functional networks are comprised of neuronal ensembles bound through synchronization across multiple intrinsic oscillatory frequencies. Various coupled interactions between brain oscillators have been described (e.g., phase-amplitude coupling), but with little evidence that these interactions actually influence perceptual sensitivity. Here, electr...

Our own work, as well as that of others, has demonstrated the oscillatory nature of visual perception. For example, the phase of ongoing cortical oscillations influences the likelihood of visual-target detection, such that a near-threshold stimulus is more likely to be detected if it occurs during a high-excitability state. Debate persists, however...

The present study investigated the feasibility of acquiring high-density event-related brain potential (ERP) recordings during treadmill walking in human subjects. The work builds upon recent studies testing the applicability of real-world tasks while obtaining electroencephalographic (EEG) recordings. Participants performed a response inhibition G...

To reveal the fundamental processes underlying the different stages of visual object perception, most studies have manipulated relatively complex images, such as photographs, line drawings of natural objects, or perceptual illusions. Here, rather than starting from complex images and working backward to infer simpler processes, we investigated how...

Humans have limited cognitive resources to process the nearly limitless information available in the environment. Endogenous, or 'top-down', selective attention to basic visual features such as color or motion is a common strategy for biasing resources in favor of the most relevant information sources in a given context. Opposing this top-down sepa...

The visual system can automatically interpolate or "fill-in" the boundaries of objects when inputs are fragmented or incomplete. A canonical class of visual stimuli known as illusory-contour (IC) stimuli has been extensively used to study this contour interpolation process. Visual evoked potential (VEP) studies have identified a neural signature of...

The present study investigated the feasibility of acquiring high-density event-related brain potential (ERP) recordings during treadmill walking in human subjects. The work builds upon recent studies testing the applicability of real-world tasks while obtaining electroencephalographic (EEG) recordings. Participants performed a response inhibition G...

Functional networks are comprised of neuronal ensembles bound through synchronization across multiple intrinsic oscillatory frequencies. Various coupled interactions between brain oscillators have been described (e.g., phase–amplitude coupling), but with little evidence that these interactions actually influence perceptual sensitivity. Here, electr...

Oscillatory alpha-band activity (8-15 Hz) over parieto-occipital cortex in humans plays an important role in suppression of processing for inputs at to-be-ignored regions of space, with increased alpha-band power observed over cortex contralateral to locations expected to contain distractors. It is unclear whether similar processes operate during d...

The simultaneous presentation of a stimulus in one sensory modality often enhances target detection in another sensory modality, but the neural mechanisms that govern these effects are still under investigation. Here, we test a hypothesis proposed in the neurophysiological literature: that auditory facilitation of visual-target detection operates t...

Evidence has amassed from both animal intracranial recordings and human electrophysiology that neural oscillatory mechanisms play a critical role in a number of cognitive functions such as learning, memory, feature binding and sensory gating. The wide availability of high-density electrical and magnetic recordings (64-256 channels) over the past tw...

The neural processing of biological motion (BM) is of profound experimental interest since it is often through the movement of another that we interpret their immediate intentions. Neuroimaging points to a specialized cortical network for processing biological motion. Here, high-density electrical mapping and source-analysis techniques were employe...

The N1 component of the auditory evoked potential (AEP) is a robust and easily recorded metric of auditory sensory-perceptual processing. In patients with schizophrenia, a diminution in the amplitude of this component is a near-ubiquitous finding. A pair of recent studies has also shown this N1 deficit in first-degree relatives of schizophrenia pro...

Retinotopically specific increases in alpha-band ( approximately 10 Hz) oscillatory power have been strongly implicated in the suppression of processing for irrelevant parts of the visual field during the deployment of visuospatial attention. Here, we asked whether this alpha suppression mechanism also plays a role in the nonspatial anticipatory bi...

Background: As well as the obvious clinical behavioral manifestations of Autism, it is now apparent that differences in very basic sensory-perceptual processing of environmental inputs may also be a core feature of Autistic Spectrum Disorder (ASD). For instance, early visual processing of object boundaries in late teens and young adults with ASD...