Narrow and Broad γ Bands Process Complementary Visual Information in Mouse Primary Visual Cortex

Low-intensity pulsed ultrasound stimulation (LIPUS) modulates microglial activation following intracortical microelectrode implantation

Microglia are important players in surveillance and repair of the brain. Implanting an electrode into the cortex activates microglia, produces an inflammatory cascade, triggers the foreign body response, and opens the blood-brain barrier. These changes can impede intracortical brain-computer interfaces performance. Using two-photon imaging of implanted microelectrodes, we test the hypothesis that low-intensity pulsed ultrasound stimulation can reduce microglia-mediated neuroinflammation following the implantation of microelectrodes. In the first week of treatment, we found that low-intensity pulsed ultrasound stimulation increased microglia migration speed by 128%, enhanced microglia expansion area by 109%, and a reduction in microglial activation by 17%, indicating improved tissue healing and surveillance. Microglial coverage of the microelectrode was reduced by 50% and astrocytic scarring by 36% resulting in an increase in recording performance at chronic time. The data indicate that low-intensity pulsed ultrasound stimulation helps reduce the foreign body response around chronic intracortical microelectrodes.

Dynamic modulation of mouse thalamocortical visual activity by salient sounds

Visual responses of the primary visual cortex (V1) are altered by sound. Sound-driven behavioral arousal suggests that, in addition to direct inputs from the primary auditory cortex (A1), multiple other sources may shape V1 responses to sound. Here, we show in anesthetized mice that sound (white noise, ≥70dB) drives a biphasic modulation of V1 visually driven gamma-band activity, comprising fast-transient inhibitory and slow, prolonged excitatory (A1-independent) arousal-driven components. An analogous yet quicker modulation of the visual response also occurred earlier in the visual pathway, at the level of the dorsolateral geniculate nucleus (dLGN), where sound transiently inhibited the early phasic visual response and subsequently induced a prolonged increase in tonic spiking activity and gamma rhythmicity. Our results demonstrate that sound-driven modulations of visual activity are not exclusive to V1 and suggest that thalamocortical inputs from the dLGN to V1 contribute to shaping V1 visual response to sound.

Rodents' visual gamma as a biomarker of pathological neural conditions

Neural gamma oscillations (indicatively 30-100 Hz) are ubiquitous: they are associated with a broad range of functions in multiple cortical areas and across many animal species. Experimental and computational works established gamma rhythms as a global emergent property of neuronal networks generated by the balanced and coordinated interaction of excitation and inhibition. Coherently, gamma activity is strongly influenced by the alterations of synaptic dynamics which are often associated with pathological neural dysfunctions. We argue therefore that these oscillations are an optimal biomarker for probing the mechanism of cortical dysfunctions. Gamma oscillations are also highly sensitive to external stimuli in sensory cortices, especially the primary visual cortex (V1), where the stimulus dependence of gamma oscillations has been thoroughly investigated. Gamma manipulation by visual stimuli tuning is particularly easy in rodents, which have become a standard animal model for investigating the effects of network alterations on gamma oscillations. Overall, gamma in the rodents' visual cortex offers an accessible probe on dysfunctional information processing in pathological conditions. Beyond vision-related dysfunctions, alterations of gamma oscillations in rodents were indeed also reported in neural deficits such as migraine, epilepsy and neurodegenerative or neuropsychiatric conditions such as Alzheimer's, schizophrenia and autism spectrum disorders. Altogether, the connections between visual cortical gamma activity and physio-pathological conditions in rodent models underscore the potential of gamma oscillations as markers of neuronal (dys)functioning.

Low-intensity pulsed ultrasound stimulation (LIPUS) modulates microglial activation following intracortical microelectrode implantation

Microglia are important players in surveillance and repair of the brain. Their activation mediates neuroinflammation caused by intracortical microelectrode implantation, which impedes the application of intracortical brain-computer interfaces (BCIs). While low-intensity pulsed ultrasound stimulation (LIPUS) can attenuate microglial activation, its potential to modulate the microglia-mediated neuroinflammation and enhance the bio-integration of microelectrodes remains insufficiently explored. We found that LIPUS increased microglia migration speed from 0.59±0.04 to 1.35±0.07 µm/hr on day 1 and enhanced microglia expansion area from 44.50±6.86 to 93.15±8.77 µm 2 /min on day 7, indicating improved tissue healing and surveillance. Furthermore, LIPUS reduced microglial activation by 17% on day 6, vessel-associated microglia ratio from 70.67±6.15 to 40.43±3.87% on day 7, and vessel diameter by 20% on day 28. Additionally, microglial coverage of the microelectrode was reduced by 50% in week 1, indicating better tissue-microelectrode integration. These data reveal that LIPUS helps resolve neuroinflammation around chronic intracortical microelectrodes.

A supervised data-driven spatial filter denoising method for speech artifacts in intracranial electrophysiological recordings

Neurosurgical procedures that enable direct brain recordings in awake patients offer unique opportunities to explore the neurophysiology of human speech. The scarcity of these opportunities and the altruism of participating patients compel us to apply the highest rigor to signal analysis. Intracranial electroencephalography (iEEG) signals recorded during overt speech can contain a speech artifact that tracks the fundamental frequency (F0) of the participant's voice, involving the same high-gamma frequencies that are modulated during speech production and perception. To address this artifact, we developed a spatial-filtering approach to identify and remove acoustic-induced contaminations of the recorded signal. We found that traditional reference schemes jeopardized signal quality, whereas our data-driven method denoised the recordings while preserving underlying neural activity.

Predicting party switching through machine learning and open data

Parliament dynamics might seem erratic at times. Predicting future voting patterns could support policy design based on the simulation of voting scenarios. The availability of open data on legislative activities and machine learning tools might enable such prediction. In our paper, we provide evidence for this statement by developing an algorithm able to predict party switching in the Italian Parliament with over 70% accuracy up to two months in advance. The analysis was based on voting data from the XVII (2013-2018) and XVIII (2018-2022) Italian legislature. We found party switchers exhibited higher participation in secret ballots and showed a progressive decrease in coherence with their party's majority votes up to two months before the actual switch. These results show how machine learning combined with political open data can support predicting and understanding political dynamics.

Over and above frequency: Gamma oscillations as units of neural circuit operations

Gamma oscillations (∼30-150 Hz) are widespread correlates of neural circuit functions. These network activity patterns have been described across multiple animal species, brain structures, and behaviors, and are usually identified based on their spectral peak frequency. Yet, despite intensive investigation, whether gamma oscillations implement causal mechanisms of specific brain functions or represent a general dynamic mode of neural circuit operation remains unclear. In this perspective, we review recent advances in the study of gamma oscillations toward a deeper understanding of their cellular mechanisms, neural pathways, and functional roles. We discuss that a given gamma rhythm does not per se implement any specific cognitive function but rather constitutes an activity motif reporting the cellular substrates, communication channels, and computational operations underlying information processing in its generating brain circuit. Accordingly, we propose shifting the attention from a frequency-based to a circuit-level definition of gamma oscillations.

Narrowband gamma oscillations propagate and synchronize throughout the mouse thalamocortical visual system

Oscillations of neural activity permeate sensory systems. In the visual system, broadband gamma oscillations (30-80 Hz) are thought to act as a communication mechanism underlying perception. However, these oscillations show widely varying frequency and phase, providing constraints for coordinating spike timing across areas. Here, we examined Allen Brain Observatory data and performed causal experiments to show that narrowband gamma (NBG) oscillations (50-70 Hz) propagate and synchronize throughout the awake mouse visual system. Lateral geniculate nucleus (LGN) neurons fired precisely relative to NBG phase in primary visual cortex (V1) and multiple higher visual areas (HVAs). NBG neurons across areas showed a higher likelihood of functional connectivity and stronger visual responses; remarkably, NBG neurons in LGN, preferring bright (ON) versus dark (OFF), fired at distinct NBG phases aligned across the cortical hierarchy. NBG oscillations may thus serve to coordinate spike timing across brain areas and facilitate communication of distinct visual features during perception.

Synaptic alterations in visual cortex reshape contrast-dependent gamma oscillations and inhibition-excitation ratio in a genetic mouse model of migraine

Background

Migraine affects a significant fraction of the world population, yet its etiology is not completely understood. In vitro results highlighted thalamocortical and intra-cortical glutamatergic synaptic gain-of-function associated with a monogenic form of migraine (familial-hemiplegic-migraine-type-1: FHM1). However, how these alterations reverberate on cortical activity remains unclear. As altered responsivity to visual stimuli and abnormal processing of visual sensory information are common hallmarks of migraine, herein we investigated the effects of FHM1-driven synaptic alterations in the visual cortex of awake mice.

Methods

We recorded extracellular field potentials from the primary visual cortex (V1) of head-fixed awake FHM1 knock-in (n = 12) and wild type (n = 12) mice in response to square-wave gratings with different visual contrasts. Additionally, we reproduced in silico the obtained experimental results with a novel spiking neurons network model of mouse V1, by implementing in the model both the synaptic alterations characterizing the FHM1 genetic mouse model adopted.

Results

FHM1 mice displayed similar amplitude but slower temporal evolution of visual evoked potentials. Visual contrast stimuli induced a lower increase of multi-unit activity in FHM1 mice, while the amount of information content about contrast level remained, however, similar to WT.

Spectral analysis of the local field potentials revealed an increase in the β/low γ range of WT mice following the abrupt reversal of contrast gratings. Such frequency range transitioned to the high γ range in FHM1 mice. Despite this change in the encoding channel, these oscillations preserved the amount of information conveyed about visual contrast. The computational model showed how these network effects may arise from a combination of changes in thalamocortical and intra-cortical synaptic transmission, with the former inducing a lower cortical activity and the latter inducing the higher frequencies ɣ oscillations.

Conclusions

Contrast-driven ɣ modulation in V1 activity occurs at a much higher frequency in FHM1. This is likely to play a role in the altered processing of visual information. Computational studies suggest that this shift is specifically due to enhanced cortical excitatory transmission. Our network model can help to shed light on the relationship between cellular and network levels of migraine neural alterations.

Graphical Abstract

Supplementary Information

The online version contains supplementary material available at 10.1186/s10194-022-01495-9.

Disruption of layer-specific visual processing in a model of focal neocortical epilepsy

The epileptic brain is the result of a sequence of events transforming normal neuronal populations into hyperexcitable networks supporting recurrent seizure generation. These modifications are known to induce fundamental alterations of circuit function and, ultimately, of behavior. However, how hyperexcitability affects information processing in cortical sensory circuits is not yet fully understood. Here, we investigated interlaminar alterations in sensory processing of the visual cortex in a mouse model of focal epilepsy. We found three main circuit dynamics alterations in epileptic mice: (i) a spreading of visual contrast-driven gamma modulation across layers, (ii) an increase in firing rate that is layer-unspecific for excitatory units and localized in infragranular layers for inhibitory neurons, and (iii) a strong and contrast-dependent locking of firing units to network activity. Altogether, our data show that epileptic circuits display a functional disruption of layer-specific organization of visual sensory processing, which could account for visual dysfunction observed in epileptic subjects. Understanding these mechanisms paves the way to circuital therapeutic interventions for epilepsy.