Sleep waves in a large-scale corticothalamic model constrained by activities intrinsic to neocortical networks and single thalamic neurons.

AIM: Many biophysical and non-biophysical models have been able to reproduce the corticothalamic activities underlying different EEG sleep rhythms but none of them included the known ability of neocortical networks and single thalamic neurons to generate some of these waves intrinsically. METHODS: We built a large-scale corticothalamic model with a high fidelity in anatomical connectivity consisting of a single cortical column and first- and higher-order thalamic nuclei. The model is constrained by different neocortical excitatory and inhibitory neuronal populations eliciting slow (<1 Hz) oscillations and by thalamic neurons generating sleep waves when isolated from the neocortex. RESULTS: Our model faithfully reproduces all EEG sleep waves and the transition from a desynchronized EEG to spindles, slow (<1 Hz) oscillations, and delta waves by progressively increasing neuronal membrane hyperpolarization as it occurs in the intact brain. Moreover, our model shows that slow (<1 Hz) waves most often start in a small assembly of thalamocortical neurons though they can also originate in cortical layer 5. Moreover, the input of thalamocortical neurons increases the frequency of EEG slow (<1 Hz) waves compared to those generated by isolated cortical networks. CONCLUSION: Our simulations challenge current mechanistic understanding of the temporal dynamics of sleep wave generation and suggest testable predictions.

Spike-and-wave discharges of absence seizures in a sleep waves-constrained corticothalamic model.

AIMS: Recurrent network activity in corticothalamic circuits generates physiological and pathological EEG waves. Many computer models have simulated spike-and-wave discharges (SWDs), the EEG hallmark of absence seizures (ASs). However, these models either provided detailed simulated activity only in a selected territory (i.e., cortical or thalamic) or did not test whether their corticothalamic networks could reproduce the physiological activities that are generated by these circuits. METHODS: Using a biophysical large-scale corticothalamic model that reproduces the full extent of EEG sleep waves, including sleep spindles, delta, and slow (<1 Hz) waves, here we investigated how single abnormalities in voltage- or transmitter-gated channels in the neocortex or thalamus led to SWDs. RESULTS: We found that a selective increase in the tonic γ-aminobutyric acid type A receptor (GABA-A) inhibition of first-order thalamocortical (TC) neurons or a selective decrease in cortical phasic GABA-A inhibition is sufficient to generate ~4 Hz SWDs (as in humans) that invariably start in neocortical territories. Decreasing the leak conductance of higher-order TC neurons leads to ~7 Hz SWDs (as in rodent models) while maintaining sleep spindles at 7-14 Hz. CONCLUSION: By challenging key features of current mechanistic views, this simulated ictal corticothalamic activity provides novel understanding of ASs and makes key testable predictions.

Brain state transitions primarily impact the spontaneous rate of slow-firing neurons.

The spontaneous firing of neurons is modulated by brain state. Here, we examine how such modulation impacts the overall distribution of firing rates in neuronal populations of neocortical, hippocampal, and thalamic areas across natural and pharmacologically driven brain state transitions. We report that across all the examined combinations of brain area and state transition category, the structure of rate modulation is similar, with almost all fast-firing neurons experiencing proportionally weak modulation, while slow-firing neurons exhibit high inter-neuron variability in the modulation magnitude, leading to a stronger modulation on average. We further demonstrate that this modulation structure is linked to the left-skewed distribution of firing rates on the logarithmic scale and is recapitulated by bivariate log-gamma, but not Gaussian, distributions. Our findings indicate that a preconfigured log-rate distribution with rigid fast-firing neurons and a long left tail of malleable slow-firing neurons is a generic property of forebrain neuronal circuits.

Distinct Structure of Cortical Population Activity on Fast and Infraslow Timescales.

Cortical activity is organized across multiple spatial and temporal scales. Most research on the dynamics of neuronal spiking is concerned with timescales of 1 ms-1 s, and little is known about spiking dynamics on timescales of tens of seconds and minutes. Here, we used frequency domain analyses to study the structure of individual neurons' spiking activity and its coupling to local population rate and to arousal level across 0.01-100 Hz frequency range. In mouse medial prefrontal cortex, the spiking dynamics of individual neurons could be quantitatively captured by a combination of interspike interval and firing rate power spectrum distributions. The relative strength of coherence with local population often differed across timescales: a neuron strongly coupled to population rate on fast timescales could be weakly coupled on slow timescales, and vice versa. On slow but not fast timescales, a substantial proportion of neurons showed firing anticorrelated with the population. Infraslow firing rate changes were largely determined by arousal rather than by local factors, which could explain the timescale dependence of individual neurons' population coupling strength. These observations demonstrate how neurons simultaneously partake in fast local dynamics, and slow brain-wide dynamics, extending our understanding of infraslow cortical activity beyond the mesoscale resolution of fMRI.

The Predictive Nature of Pseudoneglect for Visual Neglect: Evidence from Parietal Theta Burst Stimulation.

Following parietal damage most patients with visual neglect bisect horizontal lines significantly away from the true centre. Neurologically intact individuals also misbisect lines; a phenomenon referred to as 'pseudoneglect'. In this study we examined the relationship between neglect and pseudoneglect by testing how patterns of pre-existing visuospatial asymmetry predict asymmetry caused by parietal interference. Twenty-four participants completed line bisection and Landmark tasks before receiving continuous theta burst stimulation to the left or right angular gyrus. Results showed that a pre-existing pattern of left pseudoneglect (i.e. right bias), but not right pseudoneglect, predicts left neglect-like behaviour during line bisection following right parietal cTBS. This correlation is consistent with the view that neglect and pseudoneglect arise via a common or linked neural mechanism.

Comparative incidence rates of mild adverse effects to transcranial magnetic stimulation.

OBJECTIVES: Past research has largely neglected to investigate mild adverse effects (MAEs) to transcranial magnetic stimulation (TMS), including headache and nausea. Here we explored the relationship between MAEs, participant characteristics (age and gender) and protocol parameters, including mode of application, coil geometry, stimulated brain region, TMS frequency, TMS intensity, and active vs. sham stimulation. METHODS: Data from 1270 standard post-monitoring forms was obtained from 113 healthy participants. Analyses aimed to identify the risk factors associated with MAE reports and specific symptoms. RESULTS: The overall rate of MAEs across TMS sessions was ∼5%, with ∼78% of symptoms occurring post-session. Initial TMS sessions were followed by a higher MAE incidence rate relative to later testing sessions. No associations between participant characteristics, TMS frequency, or intensity were observed. CONCLUSIONS: TMS-related MAEs are relatively common and may be exacerbated by initial expectations or anxieties of participants. A significant proportion of MAEs may reflect reporting of coincidental phenomena that are unrelated to TMS. Recommendations for future safety studies are proposed and monitoring documentation is provided. SIGNIFICANCE: Our findings illustrate the importance of standardized monitoring of MAEs. Such research aids our understanding of how MAEs arise and may lead to interventions for reducing their incidence.

Biophysical determinants of transcranial magnetic stimulation: effects of excitability and depth of targeted area.

Safe and effective transcranial magnetic stimulation (TMS) requires accurate intensity calibration. Output is typically calibrated to individual motor cortex excitability and applied to nonmotor brain areas, assuming that it captures a site nonspecific factor of excitability. We tested this assumption by correlating the effect of TMS at motor and visual cortex. In 30 participants, we measured motor threshold (MT) and phosphene threshold (PT) at the scalp surface and at coil-scalp distances of 3.17, 5.63, and 9.03 mm. We also modeled the effect of TMS in a simple head model to test the effect of distance. Four independent tests confirmed a significant correlation between PT and MT. We also found similar effects of distance in motor and visual areas, which did not correlate across participants. Computational modeling suggests that the relationship between the effect of distance and the induced electric field is effectively linear within the range of distances that have been explored empirically. We conclude that MT-guided calibration is valid for nonmotor brain areas if coil-cortex distance is taken into account. For standard figure-of-eight TMS coils connected to biphasic stimulators, the effect of cortical distance should be adjusted using a general correction factor of 2.7% stimulator output per millimeter.

Critical time course of right frontoparietal involvement in mental number space.

Neuropsychological, neurophysiological, and neuroimaging studies suggest that right frontoparietal circuits may be necessary for the processing of mental number space, also known as the mental number line (MNL). Here we sought to specify the critical time course of three nodes that have previously been related to MNL processing: right posterior parietal cortex (rPPC), right FEF (rFEF), and right inferior frontal gyrus (rIFG). The effects of single-pulse TMS delivered at 120% distance-adjusted individual motor threshold were investigated in 21 participants, within a window of 0-400 msec (sampling interval = 33 msec) from the onset of a central digit (1-9, 5 excluded). Pulses were delivered in a random order and with equal probability at each time point, intermixed with noTMS trials. To analyze whether and when TMS interfered with MNL processing, we fitted bimodal Gaussian functions to the observed data and measured effects on changes in the Spatial-Numerical Association of Response Codes (SNARC) effect (i.e., an advantage for left- over right-key responses to small numbers and right- over left-key responses to large numbers) and in overall performance efficiency. We found that, during magnitude judgment with unimanual key-press responses, TMS reduced the SNARC effect in the earlier period of the fitted functions (∼25-60 msec) when delivered over rFEF (small and large numbers) and rIFG (small numbers); TMS further reduced the SNARC effect for small numbers in a later period when delivered to rFEF (∼200 msec). In contrast, TMS of rPPC did not interfere with the SNARC effect but generally reduced performance for small numbers and enhanced it for large numbers, thus producing a pattern reminiscent of "neglect" in mental number space. Our results confirm the causal role of an intact right frontoparietal network in the processing of mental number space. They also indicate that rPPC is specifically tied to explicit number magnitude processing and that rFEF and rIFG contribute to interfacing mental visuospatial codes with lateralized response codes. Overall, our findings suggest that both ventral and dorsal frontoparietal circuits are causally involved and functionally connected in the mapping of numbers to space.