Electrical Stimulation 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.

The thalamocortical pathways exhibit neuroplasticity not only during the critical period but also in adulthood. In this study, we investigated how cholecystokinin (CCK) modulates age-dependent thalamocortical plasticity. Our findings demonstrated that CCK is expressed in thalamocortical neurons and that high-frequency stimulation (HFS) of the thalamocortical pathway triggers the release of CCK in auditory cortex (ACx), as detected by a CCK sensor. HFS of the medial geniculate body (MGB) induced thalamocortical long-term potentiation (LTP) in wild-type young adult mice. However, knockdown of CCK expression in MGB neurons or blockade of the CCK-B receptor (CCKBR) in the ACx abolished HFS-induced LTP. Interestingly, this LTP could not be elicited in juvenile (3-week-old) or aged mice (over 18-month-old) due to distinct mechanisms: the absence of CCKBR in juveniles and the inability to release CCK in aged mice. Notably, exogenous administration of CCK into the ACx rescued LTP in aged mice and significantly improved frequency discrimination. These findings highlight the potential of CCK as a therapeutic intervention for ameliorating neuroplasticity deficits associated with thalamocortical connectivity.

Most spinal cord injuries (SCI) spare descending and sublesional circuits that can be targeted through motor cortex and spinal cord stimulation to mitigate locomotor deficits. However, the potential synergy between cortical and spinal stimulation remains unknown. Here, we first investigated the phase-locked electrical stimulation of the motor cortex and lumbar spinal cord at 40 Hz in a rat model of unilateral SCI. Combining cortical and lumbar stimulation around the anticipated lift synergistically enhanced leg movements. When integrated into rehabilitation training, cortical stimulation proved essential for the recovery of skilled locomotion. We next investigated the effects of high-frequency (330 Hz) lumbar and sacral stimulation combined with cortical stimulation. Timely integration during the swing phase showed that cortical and lumbar stimulations enhance the initial and mid-swing phases, while sacral stimulation improves extension velocity in the late swing. These findings indicate that supraspinal and sublesional neuromodulation offer complementary neuroprosthetic effects in targeted SCI gait rehabilitation.

Although control of movement involves many cortical association areas, bidirectional brain-machine interfaces (BMIs) typically decode movement intent from the motor cortex and deliver feedback information to the primary somatosensory cortex (S1). Compared to the S1, the parietal and premotor areas encode more complex information about object properties, hand pre-shaping, and reach trajectories. BMIs therefore might deliver richer information to those cortical association areas than to primary areas. Here, we investigated whether instructions for a center-out task could be delivered via intracortical microstimulation (ICMS) in the anterior intraparietal area (AIP), dorsal posterior parietal cortex (dPPC), or dorsal premotor cortex (PMd) as well as the ventral premotor cortex (PMv) and S1. Two monkeys successfully learned to use AIP, PMv, or S1-ICMS instructions, but neither learned to use dPPC- or PMd-ICMS instructions. The AIP, PMv, and S1 may thus be effective cortical territory for delivering information to the brain, whereas the dPPC or PMd may be comparatively ineffective.

Neurostimulation for cardiovascular control faces challenges due to the lack of predictive modeling for stimulus-driven dynamic responses, which is crucial for precise neuromodulation via quality feedback. We address this by employing a digital twin approach that leverages computational mechanisms underlying neuro-hemodynamic responses during neurostimulation. Our results emphasize the computational role of the nucleus tractus solitarius (NTS) in the brainstem in determining these responses. The intrinsic neural circuit within the NTS harbors collective dynamics residing in a low-dimensional latent space, which effectively captures stimulus-driven hemodynamic perturbations. Building on this, we developed a digital twin framework for individually optimized predictive modeling of neuromodulatory outcomes. This framework potentially enables the design of closed-loop neurostimulation systems for precise hemodynamic control. Consequently, our digital twin based on neural computation mechanisms marks an advancement in the artificial regulation of internal organs, paving the way for precise translational medicine to treat chronic diseases.

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.

High-frequency stimulation (HFS)-induced long–term potentiation (LTP) is generally regarded as a homosynaptic Hebbian-type LTP, where synaptic changes are thought to occur at the synapses that project from the stimulation site and terminate onto the neurons at the recording site. In this study, we first investigated HFS-induced LTP on urethane-anesthetized rats and found that cortical HFS enhances neural responses at the recording site through the strengthening of local connectivity with nearby neurons at the stimulation site rather than through synaptic strengthening at the recording site. This enhanced local connectivity at the stimulation site leads to increased output propagation, resulting in signal potentiation at the recording site. Additionally, we discovered that HFS can also nonspecifically strengthen distant afferent synapses at the HFS site, thereby expanding its impact beyond local neural connections. This form of plasticity exhibits a neo-Hebbian characteristic as it exclusively manifests in the presence of cholecystokinin release, induced by HFS. The cortical HFS-induced local LTP was further supported by a behavioral task, providing additional evidence. Our results unveil a previously overlooked mechanism underlying cortical plasticity: synaptic plasticity is more likely to occur around the soma site of strongly activated cortical neurons rather than solely at their projection terminals.

Long-term potentiation (LTP), which underlies learning and memory, can be induced by high-frequency electrical stimulation (HFS or HFES) and is thought to occur at the synapses of efferent projection. Here, the contralateral connectivity in mice auditory cortex was investigated to reveal the fundamental corticocortical connection properties. After HFES, plasticity was not observed at the terminal synapses at the recording site. The optogenetic HFS at the recording site of the interhemispheric cortical projections could not induce LTP, but HFES at the recording site could induce the interhemispheric cortical LTP. Our subsequent results uncovered that it is the cholecystokinin (CCK) released from the entorhino-neocortical pathway induced by HEFS that modulates the neuroplasticity of the afferent projections, including interhemispheric auditory cortical afferents. Our study illustrates a heterosynaptic mechanism as the basis for cortical plasticity. This regulation might contribute new spots for the understanding and treatment of neurological disorders.

Neural stimulation can alleviate paralysis and sensory deficits. Novel high-density neural interfaces can enable refined and multipronged neurostimulation interventions. To achieve this, it is essential to develop algorithmic frameworks capable of handling optimization in large parameter spaces. Here, we leveraged an algorithmic class, Gaussian-process (GP)-based Bayesian optimization (BO), to solve this problem. We show that GP-BO efficiently explores the neurostimulation space, outperforming other search strategies after testing only a fraction of the possible combinations. Through a series of real-time multi-dimensional neurostimulation experiments, we demonstrate optimization across diverse biological targets (brain, spinal cord), animal models (rats, non-human primates), in healthy subjects, and in neuroprosthetic intervention after injury, for both immediate and continual learning over multiple sessions. GP-BO can embed and improve "prior" expert/clinical knowledge to dramatically enhance its performance. These results advocate for broader establishment of learning agents as structural elements of neuroprosthetic design, enabling personalization and maximization of therapeutic effectiveness.

In humans, the level of consciousness is assessed by quantifying the spatiotemporal complexity of cortical responses using Perturbational Complexity Index (PCI) and related PCIst (st, state transitions). Here we validate PCIst in freely moving rats and mice by showing that it is lower in NREM sleep and slow wave anesthesia than in wake or REM sleep, as in humans. We then show that (1) low PCIst is associated with the occurrence of an OFF period of neuronal silence; (2) stimulation of deep, but not superficial, cortical layers leads to reliable PCIst changes across sleep/wake and anesthesia; (3) consistent PCIst changes are independent of which single area is being stimulated or recorded, except for recordings in mouse prefrontal cortex. These experiments show that PCIst can reliably measure vigilance states in unresponsive animals and support the hypothesis that it is low when an OFF period disrupts causal interactions in cortical networks.

Objective: Intuitive control of conventional prostheses is hampered by their inability to provide the real-time tactile and proprioceptive feedback of natural sensory pathways. The macro-sieve electrode (MSE) is a candidate interface to amputees’ truncated peripheral nerves for introducing sensory feedback from external sensors to facilitate prosthetic control. Its unique geometry enables selective control of the complete nerve cross-section by current steering. Unlike previously studied interfaces that target intact nerve, the MSE’s implantation requires transection and subsequent regeneration of the target nerve. Therefore, a key determinant of the MSE’s suitability for this task is whether it can elicit sensory percepts at low current levels in the face of altered morphology and caliber distribution inherent to axon regeneration. The present in vivo study describes a combined rat sciatic nerve and behavioral model developed to answer this question. Approach: Rats learned a go/no-go detection task using auditory stimuli and then underwent surgery to implant the MSE in the sciatic nerve. After healing, they were trained with monopolar electrical stimuli with one multi-channel and eight single-channel stimulus configurations. Psychometric curves derived by the method of constant stimuli (MCS) were used to calculate 50% detection thresholds and associated psychometric slopes. Thresholds and slopes were calculated at two time points 3 weeks apart. Main Results: For the multi-channel stimulus configuration, the average current required for stimulus detection was 19.37 μA (3.87 nC) per channel. Single-channel thresholds for leads located near the nerve’s center were, on average, half those of leads located near the periphery (54.92 μA vs. 110.71 μA, or 10.98 nC vs. 22.14 nC). Longitudinally, 3 of 5 leads’ thresholds decreased or remained stable over the 3-week span. The remaining two leads’ thresholds increased by 70–74%, possibly due to scarring or device failure. Significance: This work represents an important first step in establishing the MSE’s viability as a sensory feedback interface. It further lays the groundwork for future experiments that will extend this model to the study of other devices, stimulus parameters, and task paradigms.

Mammalian cortex has both local and cross-area connections, suggesting vital roles for both local and cross-area neural population dynamics in cortically-dependent tasks, like movement learning. Prior studies of movement learning have focused on how single-area population dynamics change during short-term adaptation. It is unclear how cross-area dynamics contribute to movement learning, particularly long-term learning and skill acquisition. Using simultaneous recordings of rodent motor (M1) and premotor (M2) cortex and computational methods, we show how cross-area activity patterns evolve during reach-to-grasp learning in rats. The emergence of reach-related modulation in cross-area activity correlates with skill acquisition, and single-trial modulation in cross-area activity predicts reaction time and reach duration. Local M2 neural activity precedes local M1 activity, supporting top–down hierarchy between the regions. M2 inactivation preferentially affects cross-area dynamics and behavior, with minimal disruption of local M1 dynamics. Together, these results indicate that cross-area population dynamics are necessary for learned motor skills.

In rats, forelimb movements are evoked from two cortical regions, the caudal and rostral forelimb areas (CFA and RFA, respectively). These areas are densely interconnected and RFA induces complex and powerful modulations of CFA outputs. CFA and RFA also have interhemispheric connections, and these areas from both hemispheres send projections to common targets along the motor axis, providing multiple potential sites of interactions for movement production. Our objective was to characterize how CFA and RFA in one hemisphere can modulate motor outputs of the opposite hemisphere. To do so, we used paired-pulse protocols with intracortical microstimulation techniques (ICMS), while recording electromyographic (EMG) activity of forelimb muscles in sedated rats. A subthreshold conditioning stimulation was applied in either CFA or RFA in one hemisphere simultaneously or before a suprathreshold test stimulation in either CFA or RFA in the opposite hemisphere. Both CFA and RFA tended to facilitate motor outputs with short (0–2.5 ms) or long (20–35 ms) delays between the conditioning and test stimuli. In contrast, they tended to inhibit motor outputs with intermediate delays, in particular 10 ms. When comparing the two areas, we found that facilitatory effects from RFA were more frequent and powerful than the ones from CFA. In contrast, inhibitory effects from CFA on its homolog were more frequent and powerful than the ones from RFA. Our results demonstrate that interhemispheric modulations from CFA and RFA share some similarities but also have clear differences that could sustain specific functions these cortical areas carry for the generation of forelimb movements. NEW & NOTEWORTHY We show that caudal and rostral forelimb areas (CFA and RFA) have distinct effects on motor outputs from the opposite hemisphere, supporting that they are distinct nodes in the motor network of rats. However, the pattern of interhemispheric modulations from RFA has no clear equivalent among premotor areas in nonhuman primates, suggesting they contribute differently to the generation of ipsilateral hand movements. Understanding these interspecies differences is important given the common use of rodent models in motor control and recovery studies.

Nowadays, the majority of the progress in the development of implantable neuroprostheses has been achieved by improving the knowledge of brain functions so as to restore sensorial impairments. Intracortical microstimulation (ICMS) is a widely used technique to investigate site-specific cortical responses to electrical stimuli. Herein, we investigated the neural modulation induced in the primary auditory cortex (A1) by an acousto-electric transduction of ultrasonic signals using a bio-inspired intracortical microstimulator. The developed electronic system emulates the transduction of ultrasound signals in the cochlea, providing bio-inspired electrical stimuli. Firstly, we identified the receptive fields in the primary auditory cortex devoted to encoding ultrasonic waves at different frequencies, mapping each area with neurophysiological patterns. Subsequently, the activity elicited by bio-inspired ICMS in the previously identified areas, bypassing the sense organ, was investigated. The observed evoked response by microstimulation resulted as highly specific to the stimuli, and the spatiotemporal dynamics of neural oscillatory activity in the alpha, beta, and gamma waves were related to the stimuli preferred by the neurons at the stimulated site. The alpha waves modulated cortical excitability only during the activation of the specific tonotopic neuronal populations, inhibiting neural responses in unrelated areas. Greater neuronal activity in the posterior area of A1 was observed in the beta band, whereas a gamma rhythm was induced in the anterior A1. The results evidence that the proposed bio-inspired acousto-electric ICMS triggers high-frequency oscillations, encoding information about the stimulation sites and involving a large-scale integration in the brain.

We investigated whether visuoauditory association can be artificially implanted in rodents and then retrieved in a behaviorally relevant context. Rats were trained to approach the left or right hole of a behavioral apparatus to retrieve a reward depending on the side of electrical stimulation of the auditory cortex (EAC) they received and mice were fear-conditioned to EAC. Next, an irrelevant visual stimulus (VS) was repeatedly paired with EAC in the presence of cholecystokinin (CCK) or with activation of terminals of entorhinal CCK neurons in the auditory cortex. In subsequent behavioral testing with VS, rats approached the hole associated with reward availability and mice showed a freezing response to the VS. A CCK antagonist blocked the establishment of visuoauditory association, whereas a CCK agonist rescued the deficit of association. Our findings provide a scientific foundation for “memory implantation” and indicate that CCK is the switching chemical for formation of visuoauditory association.