The Spatial Structure of Stimuli Shapes the Timescale of Correlations in Population Spiking Activity

Throughout the central nervous system, the timescale over which pairs of neural spike trains are correlated is shaped by stimulus structure and behavioral context. Such shaping is thought to underlie important changes in the neural code, but the neural circuitry responsible is largely unknown. In this study, we investigate a stimulus-induced shaping of pairwise spike train correlations in the electrosensory system of weakly electric fish. Simultaneous single unit recordings of principal electrosensory cells show that an increase in the spatial extent of stimuli increases correlations at short (~10 ms) timescales while simultaneously reducing correlations at long (~100 ms) timescales. A spiking network model of the first two stages of electrosensory processing replicates this correlation shaping, under the assumptions that spatially broad stimuli both saturate feedforward afferent input and recruit an open-loop inhibitory feedback pathway. Our model predictions are experimentally verified using both the natural heterogeneity of the electrosensory system and pharmacological blockade of descending feedback projections. For weak stimuli, linear response analysis of the spiking network shows that the reduction of long timescale correlation for spatially broad stimuli is similar to correlation cancellation mechanisms previously suggested to be operative in mammalian cortex. The mechanism for correlation shaping supports population-level filtering of irrelevant distractor stimuli, thereby enhancing the population response to relevant prey and conspecific communication inputs. © 2012 Litwin-Kumar et al

The cortical states of wakefulness

Cortical neurons process information on a background of spontaneous, ongoing activity with distinct spatiotemporal profiles defining different cortical states. During wakefulness, cortical states alter constantly in relation to behavioral context, attentional level or general motor activity. In this review article, we will discuss our current understanding of cortical states in awake rodents, how they are controlled, their impact on sensory processing, and highlight areas for future research. A common observation in awake rodents is the rapid change in spontaneous cortical activity from high-amplitude, low-frequency (LF) fluctuations, when animals are quiet, to faster and smaller fluctuations when animals are active. This transition is typically thought of as a change in global brain state but recent work has shown variation in cortical states across regions, indicating the presence of a fine spatial scale control system. In sensory areas, the cortical state change is mediated by at least two convergent inputs, one from the thalamus and the other from cholinergic inputs in the basal forebrain. Cortical states have a major impact on the balance of activity between specific subtypes of neurons, on the synchronization between nearby neurons, as well as the functional coupling between distant cortical areas. This reorganization of the activity of cortical networks strongly affects sensory processing. Thus cortical states provide a dynamic control system for the moment-by-moment regulation of cortical processing

Spatial processing of conspecific signals in weakly electric fish: from sensory image to neural population coding

In this dissertation, I examine how an animal’s nervous system encodes spatially realistic conspecific signals in their environment and how the encoding mechanisms support behavioral sensitivity. I begin by modeling changes in the electrosensory signals exchanged by weakly electric fish in a social context. During this behavior, I estimate how the spatial structure of conspecific stimuli influences sensory responses at the electroreceptive periphery. I then quantify how space is represented in the hindbrain, specifically in the primary sensory area called the electrosensory lateral line lobe. I show that behavioral sensitivity is influenced by the heterogeneous properties of the pyramidal cell population. I further demonstrate that this heterogeneity serves to start segregating spatial and temporal information early in the sensory pathway. Lastly, I characterize the accuracy of spatial coding in this network and predict the role of network elements, such as correlated noise and feedback, in shaping the spatial information. My research provides a comprehensive understanding of spatial coding in the first stages of sensory processing in this system and allows us to better understand how network dynamics shape coding accuracy

Effects of Adaptation in a Somatosensory Thalamocortical Circuit

In the mammalian brain, thalamocortical circuits perform the initial stage of processing before information is sent to higher levels of the cerebral cortex. Substantial changes in receptive field properties are produced in the thalamocortical response transformation. In the whisker-to-barrel thalamocortical pathway, the response magnitude of barrel excitatory cells is sensitive to the velocity of whisker deflections, whereas in the thalamus, velocity is only encoded by firing synchrony. The behavior of this circuit can be captured in a model which contains a window of opportunity for thalamic firing synchrony to engage intra-barrel recurrent excitation before being 'damped' by slightly delayed, but strong, local feedforward inhibition. Some remaining aspects of the model that require investigation are: (1) how does adaptation with ongoing and repetitive sensory stimulation affect processing in this circuit and (2) what are the rules governing intra-barrel interactions. By examining sensory processing in thalamic barreloids and cortical barrels, before and after adaptation with repetitive high-frequency whisker stimulation, I have determined that adaptation modifies the operations of the thalamocortical circuit without fundamentally changing it. In the non-adapted state, higher velocities produce larger responses in barrel cells than lower velocities. Similarly, in the adapted barrel, putative excitatory and inhibitory neurons can respond with temporal fidelity to high-frequency whisker deflections if they are of sufficient velocity. Additionally, before and after adaptation, relative to putative excitatory cells, inhibitory cells produce larger responses and are more broadly-tuned for stimulus parameters (e.g., the angle of whisker deflection). In barrel excitatory cells, adaptation is angularly-nonspecific; that is, response suppression is not specific to the angle of the adapting stimulus. The angular tuning of barrel excitatory cells is sharpened and the original angular preference is maintained. This is consistent with intra-barrel interactions being angularly-nonspecific. The maintenance of the original angular preference also suggests that the same thalamocortical inputs determine angular tuning before and after adaptation. In summary, the present findings suggest that adaptation narrows the window of opportunity for synchronous thalamic inputs to engage recurrent excitation so that it can withstand strong, local inhibition. These results from the whisker-to-barrel thalamocortical response transformation are likely to have parallels in other systems

Neural Network Dynamics of Visual Processing in the Higher-Order Visual System

Vision is one of the most important human senses that facilitate rich interaction with the external environment. For example, optimal spatial localization and subsequent motor contact with a specific physical object amongst others requires a combination of visual attention, discrimination, and sensory-motor coordination. The mammalian brain has evolved to elegantly solve this problem of transforming visual input into an efficient motor output to interact with an object of interest. The frontal and parietal cortices are two higher-order (i.e. processes information beyond simple sensory transformations) brain areas that are intimately involved in assessing how an animal’s internal state or prior experiences should influence cognitive-behavioral output. It is well known that activity within each region and functional interactions between both regions are correlated with visual attention, decision-making, and memory performance. Therefore, it is not surprising that impairment in the fronto-parietal circuit is often observed in many psychiatric disorders. Network- and circuit-level fronto-parietal involvement in sensory-based behavior is well studied; however, comparatively less is known about how single neuron activity in each of these areas can give rise to such macroscopic activity. The goal of the studies in this dissertation is to address this gap in knowledge through simultaneous recordings of cellular and population activity during sensory processing and behavioral paradigms. Together, the combined narrative builds on several themes in neuroscience: variability of single cell function, population-level encoding of stimulus properties, and state and context-dependent neural dynamics.Doctor of Philosoph

PRINCIPLES OF INFORMATION PROCESSING IN NEURONAL AVALANCHES

How the brain processes information is poorly understood. It has been suggested that the imbalance of excitation and inhibition (E/I) can significantly affect information processing in the brain. Neuronal avalanches, a type of spontaneous activity recently discovered, have been ubiquitously observed in vitro and in vivo when the cortical network is in the E/I balanced state. In this dissertation, I experimentally demonstrate that several properties regarding information processing in the cortex, i.e. the entropy of spontaneous activity, the information transmission between stimulus and response, the diversity of synchronized states and the discrimination of external stimuli, are optimized when the cortical network is in the E/I balanced state, exhibiting neuronal avalanche dynamics. These experimental studies not only support the hypothesis that the cortex operates in the critical state, but also suggest that criticality is a potential principle of information processing in the cortex. Further, we study the interaction structure in population neuronal dynamics, and discovered a special structure of higher order interactions that are inherent in the neuronal dynamics

Inhibition Controls Asynchronous States of Neuronal Networks

Computations in cortical circuits require action potentials from excitatory and inhibitory neurons. In this mini-review, I first provide a quick overview of findings that indicate that GABAergic neurons play a fundamental role in coordinating spikes and generating synchronized network activity. Next, I argue that these observations helped popularize the notion that network oscillations require a high degree of spike correlations among interneurons which, in turn, produce synchronous inhibition of the local microcircuit. The aim of this text is to discuss some recent experimental and computational findings that support a complementary view: one in which interneurons participate actively in producing asynchronous states in cortical networks. This requires a proper mixture of shared excitation and inhibition leading to asynchronous activity between neighboring cells. Such contribution from interneurons would be extremely important because it would tend to reduce the spike correlation between neighboring pyramidal cells, a drop in redundancy that could enhance the information-processing capacity of neural networks