Information Coding through Adaptive Gating of Synchronized Thalamic Bursting

Abstract

Summary It has been posited that the regulation of burst/tonic firing in the thalamus could function as a mechanism for controlling not only how much, but what kind of information is conveyed to downstream cortical targets. Yet how this gating mechanism is adaptively modulated on fast time scales by ongoing sensory inputs in rich sensory environments remains unknown. Using single unit recordings in the rat vibrissa thalamus (VPm), we found that the degree of bottom-up adaptation modulated thalamic burst/tonic firing as well as the synchronization of bursting across the thalamic population along a continuum for which the extremes facilitate detection or discrimination of sensory inputs. Optogenetic control of baseline membrane potential in thalamus further suggests that this regulation may result from an interplay between adaptive changes in thalamic membrane potential and synaptic drive from inputs to thalamus, setting the stage for an intricate control strategy upon which cortical computation is built.

The role of the supplementary motor area for speech and language processing

“…In general, the thalamus serves as a preprocessor for sensory input and, furthermore, as a kind of gating mechanism by synchronizing neuronal activity (Whitmire et al, 2016). Some aspects of the speech-related function of the "thalamic hub", linking basal ganglia and cerebellum to frontal cortex, were considered in Barbas et al (2013).…”

Rapid Sensory Adaptation Redux: A Circuit Perspective

“…The difference between the state of the brain during most neurophysiological recordings and the state of the brain during conscious perception of adaptation may suggest potential differences in encoding (Castro-Alamancos, 2004). While the absolute neural responses likely vary with state, there is significant evidence to suggest that many of the neural adaptation effects, such as reductions in neural activity levels (Ollerenshaw et al, 2014; Stoelzel et al, 2015), shifts in encoding states (Whitmire et al, 2016), and changes in population coding (Gutnisky and Dragoi, 2008), seen in the anesthetized animal are also present in the awake animal. The qualitative ability to rapidly adapt neural properties appears to be a conserved mechanism across brain states.…”

“…Adaptation modulates not only temporal precision within neurons, but also synchronous firing across neurons (Wang et al, 2010b). Furthermore, transitions in the coding properties of the pathway in response to adaptation also extend to state-related firing such as burst-tonic firing in the thalamus (Lesica and Stanley, 2004; Lesica et al, 2006; Whitmire et al, 2016), that could underlie the shift in information processing modes (Ollerenshaw et al, 2014). …”

Taller Peaks: an improved spike detection algorithm that simultaneously reduces type I and type II errors for Wave{\_}clus

“…Whereas the simultaneous use of positive and negative thresholds reduces the number of misses by about a factor of two, it increases the number of false positives by about a factor of eight in the present data set (results not shown). Perhaps because of this reason, either the positive or the negative threshold alone is used in virtually all studies that use Wave clus for spike sorting [6,13,24]. Because a positive threshold may be used instead of a negative one simply by using the negative of x as the input data, the algorithms considered here will be explained under the assumption that the positive threshold is used for spike detection.…”

“…Among this wide collection of tools and algorithms, Wave clus has been used as an open source spike sorting tool in dozens of experimental [13][14][15][16][17][18][19] and methodological studies [20], and also as a benchmark for new spike sorting algorithms [7,8,11,12,21]. Considered as a state-of-the-art spike sorting algorithm [11], Wave clus has been reported to be the second most highly cited spike sorting algorithm in the literature [21].…”