LFP publications

Objective. Infrared neural stimulation (INS) has emerged as a potent neuromodulation technology, offering safe and focal stimulation with superior spatial recruitment profiles compared to conventional electrical methods. However, the neural dynamics induced by INS stimulation remain poorly understood. Elucidating these dynamics will help develop new INS stimulation paradigms and advance its clinical application. Approach. In this study, we assessed the local network dynamics of INS entrainment in the auditory thalamocortical circuit using the chronically implanted rat model. Our approach focused on measuring INS energy-based local field potential (LFP) recruitment induced by focal thalamocortical stimulation. We further characterized linear and nonlinear oscillatory LFP activity in response to single-pulse and periodic INS and performed spectral decomposition to uncover specific LFP band entrainment to INS. Finally, we examined spike-field transformations across the thalamocortical synapse using spike-LFP coherence coupling measures. Main results. We found that INS significantly increases LFP amplitude as a log-linear function of INS energy per pulse, primarily entraining to LFP β and γ bands with synchrony extending to 200 Hz in some cases. A subset of neurons demonstrated nonlinear, chaotic oscillations linked to information transfer across cortical circuits. Finally, we utilized spike-field coherences to correlate spike coupling to LFP frequency band activity and suggest an energy-dependent model of network activation resulting from INS stimulation. Significance. We show that INS reliably drives robust network activity and can potently modulate cortical field potentials across a wide range of frequencies in a stimulus parameter-dependent manner. Based on these results, we propose design principles for developing full coverage, all-optical thalamocortical auditory neuroprostheses.

Aging disrupts brain network integration and is a significant risk factor for cognitive decline and neurological diseases, yet the circuit-level mechanisms underlying these changes remain unclear. Most previous studies have utilized cross-sectional or acute approaches, limiting insights into the longitudinal dynamics of the neural network. In this study, we chronically recorded laminar electrophysiological activity in both the primary visual cortex (V1) and hippocampal CA1 region of young (2-month-old) and aged (13-month-old) mice over 16 weeks. This approach allowed us to directly assess how aging modulates functional connectivity within hierarchically connected cortical and hippocampal circuits. We found that single-unit spiking activity and the signal-to-noise ratio were largely preserved in aged versus young mice, suggesting intact neuronal firing properties. However, aged mice showed global reductions in local field potential (LFP) power and a selective decrease in coherence across delta, alpha-beta, and gamma frequency bands within and between cortical layers and V1-CA1 pathways, while phase amplitude coupling remained unaffected. Interestingly, population level excitatory activity in CA1 was increased in aged animals. These findings indicate that aging selectively impairs network-level synchrony and temporal coordination in specific frequency bands and regions, with minimal loss of single-neuron function. Our results highlight the necessity of longitudinal, multi-region measurements to uncover the multi-scale vulnerabilities of the aging brain. Understanding the depth- and region-dependent circuit changes will guide strategies to preserve cortical-hippocampal communication and cognitive function in aging, as well as enhance neural interface technologies for older populations. NEW & NOTEWORTHY Aging non-uniformly degrades cortico-hippocampal networks, leading to region- and frequency-specific breakdowns in coordinated activity. While single-neuron activity remains preserved, disruptions in frequency-selective synchrony (delta and alpha-beta) were observed in aged mice, indicating impaired V1-CA1 communication as a marker of aging rather than neuronal degeneration. By separating single-neuron activity and large-scale dynamics, we reveal that aging alters communication between sensory and memory systems, underscoring the need for longitudinal approaches to capture age-related impairments in laminar connectivity.

Closed-loop neural control is a powerful tool for both the scientific exploration of neural function and for mitigating deficiencies found in open-loop deep brain stimulation (DBS). Here, we present a protocol for artificial intelligence-guided neural control in rats using deep reinforcement learning (RL) and infrared neural stimulation (INS). We describe steps for integrating RL closed-loop control into neuroscience and neuromodulation studies. We then detail procedures for using and deploying infrared INS in chronic DBS applications. For complete details on the use and execution of this protocol, please refer to Coventry et al.1 and Coventry and Bartlett.2.

Typical statistical practices in the biological sciences have been increasingly called into question due to difficulties in the replication of an increasing number of studies, many of which are confounded by the relative difficulty of null significance hypothesis testing designs and interpretation of p -values. Bayesian inference, representing a fundamentally different approach to hypothesis testing, is receiving renewed interest as a potential alternative or complement to traditional null significance hypothesis testing due to its ease of interpretation and explicit declarations of prior assumptions. Bayesian models are more mathematically complex than equivalent frequentist approaches, which have historically limited applications to simplified analysis cases. However, the advent of probability distribution sampling tools with exponential increases in computational power now allows for quick and robust inference under any distribution of data. Here we present a practical tutorial on the use of Bayesian inference in the context of neuroscientific studies in both rat electrophysiological and computational modeling data. We first start with an intuitive discussion of Bayes' rule and inference followed by the formulation of Bayesian-based regression and ANOVA models using data from a variety of neuroscientific studies. We show how Bayesian inference leads to easily interpretable analysis of data while providing an open-source toolbox to facilitate the use of Bayesian tools.

The rhizome of Gastrodia elata (GE), a herb medicine, has been used for treatment of neuronal disorders in Eastern Asia for hundreds of years. Parishin C is a major ingredient of GE. In this study, the i.c.v. injection of soluble Aβ 1-42 oligomers model of LTP injury was used. We investigated the effects of parishin C on the improvement of LTP in soluble Aβ 1-42 oligomer-injected rats and the underlying electrophysiological mechanisms. Parishin C (i.p. or i.c.v.) significantly ameliorated LTP impairment induced by i.c.v. injection of soluble Aβ 1-42 oligomers. In cultured hippocampal neurons, soluble Aβ 1-42 oligomers significantly inhibited NMDAR currents while not affecting AMPAR currents and voltage-dependent currents. Pretreatment with parishin C protected NMDA receptor currents from the damage induced by Aβ. In summary, parishin C improved LTP deficits induced by soluble Aβ 1-42 oligomers. The protection by parishin C against Aβ-induced LTP damage might be related to NMDA receptors.

Negative hemodynamic response has been widely reported in blood oxygenation level-dependent (BOLD) functional magnetic resonance imaging studies, however its origin is still controversial. Optical intrinsic signal (OIS) imaging can be used to study brain activity by simultaneously recording hemodynamic signals at different wavelengths with high spatial resolution. In this study, we found transcorneal electrical stimulation (TcES) could elicit both positive OIS response (POR) and negative OIS response (NOR) in cats’ visual cortex. We then investigated the property of this negative response to TcES and its relationship with cerebral blood flow (CBF) and neuronal activity. Results from laser speckle contrast imaging showed decreased CBF in the NOR region while increased CBF in the POR region. Both planar and laminar electrophysiological recordings in the middle (500–700 μm) cortical layers demonstrated that decreased and increased neuronal activities were coexisted in the NOR region. Furthermore, decreased neuronal activity was also detected in the deep cortical layers in the NOR region. This work provides evidence that the negative OIS together with the decreased CBF should be explained by mechanisms of both neuronal inhibition and excitation within middle cortical layers. Our results would be important for interpreting neurophysiological mechanisms underlying the negative BOLD signals.