Biology subjects

Jones, S. R.

Publications and source records attributed to Jones, S. R..

23 records · Page 2Linked to original sources

bioRxiv2020

Taxonomy of neural oscillation events in primate auditory cortex

Electrophysiological oscillations in the brain have been shown to occur as multi-cycle events, with onset and offset dependent on behavioral and cognitive state. To provide a baseline for state-related and task-related events, we quantified oscillation features in resting-state recordings. We used two invasively-recorded electrophysiology datasets: one from human, and one from non-human primate auditory system. After removing incidentally occuring event related potentials, we used a wavelet transform based method to quantify oscillation features. We identified about 2 million oscillation events, classified within traditional frequency bands: delta, theta, alpha, beta, low gamma, gamma, high gamma. Oscillation events of 1-44 cycles were present in at least one frequency band in 90% of the time in human and non-human primate recordings. Individual oscillation events were characterized by non-constant frequency and amplitude. This result naturally contrasts with prior studies which assumed such constancy, but is consistent with evidence from event-associated oscillations. We measured oscillation event duration, frequency span, and waveform shape. Oscillations tended to exhibit multiple cycles per event, verifiable by comparing filtered to unfiltered waveforms. In addition to the clear intra-event rhythmicity, there was also evidence of inter-event rhythmicity within bands, demonstrated by finding that coefficient of variation of interval distributions and Fano Factor measures differed significantly from a Poisson distribution assumption. Overall, our study demonstrates that rhythmic, multi-cycle oscillation events dominate auditory cortical dynamics.

neuroscience↗

bioRxiv2019

A supragranular nexus for the effects of neocortical beta events on human tactile perception

Transient neocortical events with high spectral power in the 15-29Hz beta band are among the most reliable predictors of sensory perception: High prestimulus beta event rates in primary somatosensory lead to sensory suppression, most effective at 100-300ms prestimulus latency. However, the synaptic and neuronal mechanisms inducing betas perceptual effects have not been completely localized. We combined human MEG with neural modeling designed to account for these macroscale signals to interpret the cellular and circuit mechanisms that underlie the influence of beta on tactile detection. Extending prior studies, we modeled the hypothesis that higher-order thalamic bursts, sufficient for beta event generation in cortex, recruit supragranular GABAB inhibition acting on a 300ms time scale to suppress sensory information. Consistency between model and MEG data supported this hypothesis and led to a further prediction, validated in our data, that stimuli are perceived when beta events occur simultaneously with tactile stimulation. The post-event suppressive mechanism explains an array of studies that associate beta with decreased processing, while the during-event mechanism may demand a reinterpretation of the role of beta events in the context of coincident timing.\n\nSignificance statementSomatosensory beta events - transient 15-29Hz oscillations in electromagnetic recordings - are thought to be generated when \"top-down\" bursts of spikes presumably originating in higher-order thalamus arrive in upper layers of somatosensory cortex. Physiological evidence had shown that the immediate action of these top-down projections should be excitatory; however, after a beta event, sensory perception is noticeably inhibited for approximately 300ms. The source of this post-event sensory suppression, in particular, had been unresolved. Using a detailed computational model of somatosensory cortex, we find evidence for the hypothesis that these bursts couple indirectly to GABAB inhibition in upper layers of cortex, and that beta events first briefly disinhibit sensory relay before a longer period of inhibition.

neuroscience↗

bioRxiv2019

Human Neocortical Neurosolver (HNN): A new software tool for interpreting the cellular and network origin of human MEG/EEG data

Magneto- and electro-encephalography (MEG/EEG) non-invasively record human brain activity with millisecond resolution providing reliable markers of healthy and disease states. Relating these macroscopic signals to underlying cellular- and circuit-level generators is a limitation that constrains using MEG/EEG to reveal novel principles of information processing or to translate findings into new therapies for neuropathology. To address this problem, we built Human Neocortical Neurosolver (HNN, https://hnn.brown.edu) software. HNN has a graphical user interface designed to help researchers and clinicians interpret the neural origins of MEG/EEG. HNNs core is a neocortical circuit model that accounts for biophysical origins of electrical currents generating MEG/EEG. Data can be directly compared to simulated signals and parameters easily manipulated to develop/test hypotheses on a signals origin. Tutorials teach users to simulate commonly measured signals, including event related potentials and brain rhythms. HNNs ability to associate signals across scales makes it a unique tool for translational neuroscience research.

neuroscience↗

bioRxiv2018

Stress-induced alterations of norepinephrine release in the bed nucleus of the stria terminalis of mice

Stress can drive adaptive changes to maintain survival during threatening stimuli. Chronic stress exposure, however, may result in pathological adaptations. A key neurotransmitter involved in stress signaling is norepinephrine. Previous studies show that stress elevates norepinephrine levels in the bed nucleus of the stria terminalis (BNST), a critical node regulating anxiety and upstream of stress responses. Here, we use mice expressing channelrhodopsin in norepinephrine neurons to selectively activate terminals in the BNST, and measure norepinephrine release with fast-scan cyclic voltammetry. Mice exposed to a single restraint session show an identical norepinephrine release profile compared to that of unexposed mice. Mice experiencing five days of restraint stress, however, show elevated noradrenergic release across multiple stimulation parameters, and reduced sensitivity to the 2-adrenergic receptor antagonist idazoxan. These data are the first to examine norepinephrine release in the BNST to tonic and phasic stimulation frequencies, and confirm that repeated stress alters autoreceptor sensitivity.\n\nO_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=122 SRC=\"FIGDIR/small/335653_ufig1.gif\" ALT=\"Figure 1\">\nView larger version (28K):\norg.highwire.dtl.DTLVardef@75ef4aorg.highwire.dtl.DTLVardef@b0fd27org.highwire.dtl.DTLVardef@1bc3afborg.highwire.dtl.DTLVardef@c469f1_HPS_FORMAT_FIGEXP M_FIG C_FIG

neuroscience↗

bioRxiv2017

The rate of transient beta frequency events predicts impaired function across tasks and species

Beta frequency oscillations (15-29Hz) are among the most prominent signatures of brain activity. Beta power is predictive of many healthy and abnormal behaviors, including perception, attention and motor action. Recent evidence shows that in non-averaged signals, beta can emerge as transient high-power \"events\". As such, functionally relevant differences in averaged power across time and trials can reflect accumulated changes in the number, power, duration, and/or frequency span of the events. We show for the first time that functionally relevant differences in averaged prestimulus beta power in human sensory neocortex reflects a difference in the number of high-power beta events per trial, i.e., the rate of events. Further, high power beta events close to the time of the stimulus were more likely to impair perception. This result is consistent across detection and attention tasks in human magnetoencephalography (MEG) and is conserved in local field potential (LFP) recordings of mice performing a detection task. Our findings suggest transient brain rhythms are best viewed as a \"rate metric\" in their impact on function, and provides a new framework for understanding and manipulating functionally relevant rhythmic events.

neuroscience↗