Biology subjects

Snyder, A. C.

Publications and source records attributed to Snyder, A. C..

6 recordsLinked to original sources

bioRxiv2024

Distractor anticipation during working memory is associated with theta and beta oscillations across spatial scales

Anticipating distractors during working memory maintenance is critical to reduce their disruptive effects. In this study, we aimed to identify the oscillatory correlates of this process across different spatial scales of neural activity. We simultaneously recorded local field potentials (LFP) from the LPFC and electroencephalograms (EEG) from the scalp of monkeys performing a modified memory-guided saccade (MGS) task. The monkeys were required to remember the location of a target visual stimulus while anticipating distracting visual stimulus, flashed at 50% probability during the delay period. We found significant theta-band activity across spatial scales during anticipation of a distractor, closely linked with underlying working memory dynamics, through decoding and cross-temporal generalization analyses. EEG particularly reflected reactivation of memory around the anticipated time of a distractor, even in the absence of stimuli. During this anticipated time, beta-band activity exhibited transiently enhanced intrahemispheric communication between the LPFC and occipitoparietal brain areas. These oscillatory phenomena were observed only when the monkeys successfully performed the task, implicating their possible functional role in mitigating anticipated distractors. Our results demonstrate that distractor anticipation recruits multiple oscillatory processes across the brain during working memory maintenance, with a key activity observed predominantly in the theta and beta bands.

neuroscience↗

bioRxiv2022

Dynamic attention signaling in V4: relation to excitatory/inhibitory cell class and population coupling

Neurons have different roles in attention processing. These roles are determined by a neurons firing properties, neurotransmitter expression, and functional connectivity. Neurons in the visual cortical area, V4, are reliably engaged by selective attention but exhibit differences in firing rate and correlated variability. It remains unclear what specific neuronal properties shape these attention effects. We identified neurons as fast-spiking (FS) (putative inhibitory) and regular-spiking (RS) (putative excitatory) and investigated their role in anticipatory attention and how this related to their functional connectivity. V4 neurons exhibited a continuum of time-varying attention effects ranging from "restless-weak" neurons at one extreme to "quiet-strong" neurons at another. We found an interdependence between neural attention effects (e.g., restless-weak or quiet-strong), neuron type (FS, RS), and functional connectivity. In particular, we found neurons with restless-weak attention effects were more likely to be RS and have greater population coupling, compared to neurons with other types of attention effects. Also, quiet-strong neurons were more likely to be FS and these FS neurons exhibited higher spike synchrony. From this we propose that time-varying attention effects in a neuronal population depends on the relative involvement of neurons that drive stimulus processing and those that are engaged by intrinsic population activity. These results add important information to our understanding of visual attention circuits at the cellular level.

neuroscience↗

bioRxiv2020

Bridging neuronal correlations and dimensionality reduction

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 related. We first established concrete mathematical and empirical relationships between pairwise correlation and metrics of population-wide covariability based on dimensionality reduction. Applying these insights to macaque V4 population recordings, we found that the previously reported decrease in mean pairwise correlation associated with attention stemmed from three distinct changes in population-wide covariability. Overall, our work builds the intuition and formalism to bridge between pairwise correlation and population-wide covariability and presents a cautionary tale about the inferences one can make about population activity by using a single statistic, whether it be mean pairwise correlation or dimensionality.

neuroscience↗

bioRxiv2020

EEG signals index a global signature of arousal embedded in neuronal population recordings

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 to measure brain-wide signals. Here, we combined these techniques while monkeys performed a change detection task and discovered a link between EEG and a signal embedded in spiking responses. This slow drift was associated with arousal: decreases in pre-stimulus power/increases in P1 amplitude were accompanied by :1) increases in pupil size, false alarm rate and saccade velocity; and 2) decreases in microsaccade rate and reaction time. These results show that brain-wide EEG signals can be used to index modes of activity acquired from direct neural recordings, that in turn reflect global changes in brain state that influence perception and behavior.

neuroscience↗

bioRxiv2020

The eyes reflect an internal cognitive state embedded in the population activity of cortical neurons

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 saccadic eye movements. However, precisely because the eyes have been associated with modulation of neural activity across the brain, and many different kinds of measurements of the eyes have been made across studies, it has been difficult to clearly isolate how internal states affect the behavior of the eyes, and vice versa. Recent work in our laboratory identified a latent dimension of neural activity in macaque visual cortex on the timescale of minutes to tens of minutes. This slow drift was associated with perceptual performance on an orientation-change detection task, as well as neural activity in visual and prefrontal cortex (PFC), suggesting it might reflect a shift in a global brain state. This motivated us to ask if the neural signature of this internal state is correlated with the action of the eyes in different behavioral tasks. We recorded from visual cortex (V4) while monkeys performed a change detection task, and the prefrontal cortex, while they performed a memory-guided saccade task. On both tasks, slow drift was associated with a pattern that is indicative of changes in arousal level over time. When pupil size was large, and the subjects were in a heighted state of arousal, microsaccade rate and reaction time decreased while saccade velocity increased. These results show that the action of the eyes is associated with a dominant mode of neural activity that is pervasive and task-independent, and can be accessed in the population activity of neurons across the cortex.

neuroscience↗

bioRxiv2020

Slow drift of neural activity as a signature of impulsivity in macaque visual and prefrontal cortex

An animals 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, over the timescale of tens of minutes during a perceptual decision-making task, animals slowly shifted their likelihood of reporting stimulus changes. They did this unprompted by task conditions. We recorded neural population activity from visual area V4 as well as prefrontal cortex, and found that the activity of both areas slowly drifted together with the behavioral fluctuations. We reasoned that such slow fluctuations in behavior could either be due to slow changes in how the sensory stimulus is processed or due to a process that acts independently of sensory processing. By analyzing the recorded activity in conjunction with models of perceptual decision-making, we found evidence for the slow drift in neural activity acting as an impulsivity signal, overriding sensory evidence to dictate the final decision. Overall, this work uncovers an internal state embedded in the population activity across multiple brain areas, hidden from typical trial-averaged analyses and revealed only when considering the passage of time within each experimental session. Knowledge of this cognitive factor was critical in elucidating how sensory signals and the internal state together contribute to the decision-making process.

neuroscience↗