The impact of closed-loop intracortical stimulation on neural activity in brain-injured, anesthetized animals

Carè, Marta; Averna, Alberto; Barban, Federico; Semprini, Marianna; Michieli, Lorenzo De; Nudo, Randolph J.; Guggenmos, David J.; Chiappalone, Michela

doi:10.1186/s42234-022-00086-y

Cited by 7 publications

(8 citation statements)

References 25 publications

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“…After filtering, spikes were detected using a smoothed nonlinear energy operator (SNEO) [27], with a smoothing width of 5 samples and a minimum amplitude threshold of 15-μV. This detection method captured the physiological response of multi-unit activity in a manner that was consistent with previously reported results [28, 29], indicating its acceptability as a proxy for neural excitation and inhibition in response to the peripheral sensory stimulus. For all trials, any absolute deviation greater than 450 µV was considered artifact and spikes 4 ms before or after the artifact were discarded.…”

Section: Methodsmentioning

confidence: 78%

Post-Ischemic Reorganization of Sensory Responses in Cerebral Cortex

Hayley

Tuchek

Dalla

et al. 2023

Preprint

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Sensorimotor integration is critical for generating skilled, volitional movements. While stroke tends to impact motor function, there are also often associated sensory deficits that contribute to overall behavioral deficits. Because many of the cortico-cortical projections participating in the generation of volitional movement either target or pass-through primary motor cortex (in rats, caudal forelimb area; CFA), any damage to CFA can lead to a subsequent disruption in information flow. As a result, the loss of sensory feedback is thought to contribute to motor dysfunction even when sensory areas are spared from injury. Previous research has suggested that the restoration of sensorimotor integration through reorganization or de novo neuronal connections is important for restoring function. Our goal was to determine if there was crosstalk between sensorimotor cortical areas with recovery from a primary motor cortex injury. First, we investigated if peripheral sensory stimulation would evoke responses in the rostral forelimb area (RFA), a rodent homologue to premotor cortex. We then sought to identify whether intracortical microstimulation-evoked activity in RFA would reciprocally modify the sensory response. We used seven rats with an ischemic lesion of CFA. Four weeks after injury, the rats' forepaw was mechanically stimulated under anesthesia and neural activity was recorded in the cortex. In a subset of trials, a small intracortical stimulation pulse was delivered in RFA either individually or paired with peripheral sensory stimulation. Our results point to post-ischemic connectivity between premotor and sensory cortex that may be related to functional recovery. Premotor recruitment during the sensory response was seen with a peak in spiking within RFA after the peripheral solenoid stimulation despite the damage to CFA. Furthermore, stimulation evoked activity in RFA modulated and disrupted the sensory response in sensory cortex, providing additional evidence for the transmission of premotor activity to sensory cortex and the sensitivity of sensory cortex to premotor cortex's influence. The strength of the modulatory effect may be related to the extent of the injury and the subsequent reshaping of cortical connections in response to network disruption.

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Section: Methodsmentioning

confidence: 78%

Post-Ischemic Reorganization of Sensory Responses in Cerebral Cortex

Hayley

Tuchek

Dalla

et al. 2023

Preprint

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“…Especially, our implementation of the Nested Particle Filter can be applied to any state-space system, even time-varying ones. Moreover, as the Nested Particle Filter is robust to time-varying parameters and model uncertainties [ 13 ], we believe that our proposed solution will be especially relevant for neurophysiology experiments and for clinical applications, such as the optimization of Deep Brain Stimulation (DBS) for the treatment of Parkinson’s Disease [ 32 , 33 ].…”

Section: Discussionmentioning

confidence: 99%

Efficient sampling-based Bayesian Active Learning for synaptic characterization

Gontier,

Surace,

Delvendahl

et al. 2023

PLoS Comput Biol

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Bayesian Active Learning (BAL) is an efficient framework for learning the parameters of a model, in which input stimuli are selected to maximize the mutual information between the observations and the unknown parameters. However, the applicability of BAL to experiments is limited as it requires performing high-dimensional integrations and optimizations in real time. Current methods are either too time consuming, or only applicable to specific models. Here, we propose an Efficient Sampling-Based Bayesian Active Learning (ESB-BAL) framework, which is efficient enough to be used in real-time biological experiments. We apply our method to the problem of estimating the parameters of a chemical synapse from the postsynaptic responses to evoked presynaptic action potentials. Using synthetic data and synaptic whole-cell patch-clamp recordings, we show that our method can improve the precision of model-based inferences, thereby paving the way towards more systematic and efficient experimental designs in physiology.

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“…To better understand the mechanistic properties of ADS for modulating activity, other studies investigated its effect on neuronal firing patterns in rats with focal ischemic lesion in the motor cortex (i.e., M1 or CFA). Their findings suggest that ADS can rapidly alter intrinsic neural activity after an injury, which could be effective for modulating activity in the acute periods after injury ( Averna et al, 2022 ; Carè et al, 2022 ). Additional evidence supporting the use of ADS as a viable therapeutic method also after a spinal cord injury (i.e., SCI) were shown in Borrell et al (2020) , after demonstration that it could enhance synaptic efficacy in remaining pathways between the motor cortex and spinal cord.…”

Section: The Importance Of Closing the Loopmentioning

confidence: 99%

Personalized strategies of neurostimulation: from static biomarkers to dynamic closed-loop assessment of neural function

Carè,

Chiappalone,

Cota

2024

Front. Neurosci.

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Despite considerable advancement of first choice treatment (pharmacological, physical therapy, etc.) over many decades, neurological disorders still represent a major portion of the worldwide disease burden. Particularly concerning, the trend is that this scenario will worsen given an ever expanding and aging population. The many different methods of brain stimulation (electrical, magnetic, etc.) are, on the other hand, one of the most promising alternatives to mitigate the suffering of patients and families when conventional treatment fall short of delivering efficacious treatment. With applications in virtually all neurological conditions, neurostimulation has seen considerable success in providing relief of symptoms. On the other hand, a large variability of therapeutic outcomes has also been observed, particularly in the usage of non-invasive brain stimulation (NIBS) modalities. Borrowing inspiration and concepts from its pharmacological counterpart and empowered by unprecedented neurotechnological advancement, the neurostimulation field has seen in recent years a widespread of methods aimed at the personalization of its parameters, based on biomarkers of the individuals being treated. The rationale is that, by taking into account important factors influencing the outcome, personalized stimulation can yield a much-improved therapy. Here, we review the literature to delineate the state-of-the-art of personalized stimulation, while also considering the important aspects of the type of informing parameter (anatomy, function, hybrid), invasiveness, and level of development (pre-clinical experimentation versus clinical trials). Moreover, by reviewing relevant literature on closed loop neuroengineering solutions in general and on activity dependent stimulation method in particular, we put forward the idea that improved personalization may be achieved when the method is able to track in real time brain dynamics and adjust its stimulation parameters accordingly. We conclude that such approaches have great potential of promoting the recovery of lost functions and enhance the quality of life for patients.

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The impact of closed-loop intracortical stimulation on neural activity in brain-injured, anesthetized animals

Cited by 7 publications

References 25 publications

Post-Ischemic Reorganization of Sensory Responses in Cerebral Cortex

Post-Ischemic Reorganization of Sensory Responses in Cerebral Cortex

Efficient sampling-based Bayesian Active Learning for synaptic characterization

Personalized strategies of neurostimulation: from static biomarkers to dynamic closed-loop assessment of neural function

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