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Roeder BM, She X, Dakos AS, Moore B, Wicks RT, Witcher MR, Couture DE, Laxton AW, Clary HM, Popli G, Liu C, Lee B, Heck C, Nune G, Gong H, Shaw S, Marmarelis VZ, Berger TW, Deadwyler SA, Song D, Hampson RE. Developing a hippocampal neural prosthetic to facilitate human memory encoding and recall of stimulus features and categories. Front Comput Neurosci 2024; 18:1263311. [PMID: 38390007 PMCID: PMC10881797 DOI: 10.3389/fncom.2024.1263311] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/19/2023] [Accepted: 01/19/2024] [Indexed: 02/24/2024] Open
Abstract
Objective Here, we demonstrate the first successful use of static neural stimulation patterns for specific information content. These static patterns were derived by a model that was applied to a subject's own hippocampal spatiotemporal neural codes for memory. Approach We constructed a new model of processes by which the hippocampus encodes specific memory items via spatiotemporal firing of neural ensembles that underlie the successful encoding of targeted content into short-term memory. A memory decoding model (MDM) of hippocampal CA3 and CA1 neural firing was computed which derives a stimulation pattern for CA1 and CA3 neurons to be applied during the encoding (sample) phase of a delayed match-to-sample (DMS) human short-term memory task. Main results MDM electrical stimulation delivered to the CA1 and CA3 locations in the hippocampus during the sample phase of DMS trials facilitated memory of images from the DMS task during a delayed recognition (DR) task that also included control images that were not from the DMS task. Across all subjects, the stimulated trials exhibited significant changes in performance in 22.4% of patient and category combinations. Changes in performance were a combination of both increased memory performance and decreased memory performance, with increases in performance occurring at almost 2 to 1 relative to decreases in performance. Across patients with impaired memory that received bilateral stimulation, significant changes in over 37.9% of patient and category combinations was seen with the changes in memory performance show a ratio of increased to decreased performance of over 4 to 1. Modification of memory performance was dependent on whether memory function was intact or impaired, and if stimulation was applied bilaterally or unilaterally, with nearly all increase in performance seen in subjects with impaired memory receiving bilateral stimulation. Significance These results demonstrate that memory encoding in patients with impaired memory function can be facilitated for specific memory content, which offers a stimulation method for a future implantable neural prosthetic to improve human memory.
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Affiliation(s)
- Brent M Roeder
- Wake Forest Baptist Medical Center, Winston-Salem, NC, United States
| | - Xiwei She
- Department of Biomedical Engineering, University of Southern California, Los Angeles, CA, United States
| | - Alexander S Dakos
- Wake Forest Baptist Medical Center, Winston-Salem, NC, United States
| | - Bryan Moore
- Department of Biomedical Engineering, University of Southern California, Los Angeles, CA, United States
| | - Robert T Wicks
- Wake Forest Baptist Medical Center, Winston-Salem, NC, United States
- Johns Hopkins Children's Center, Baltimore, MD, United States
| | - Mark R Witcher
- Wake Forest Baptist Medical Center, Winston-Salem, NC, United States
- Virginia Tech Carilion School of Medicine and Research Institute, Roanoke, VA, United States
| | - Daniel E Couture
- Wake Forest Baptist Medical Center, Winston-Salem, NC, United States
| | - Adrian W Laxton
- Wake Forest Baptist Medical Center, Winston-Salem, NC, United States
| | | | - Gautam Popli
- Wake Forest Baptist Medical Center, Winston-Salem, NC, United States
| | - Charles Liu
- Department of Biomedical Engineering, University of Southern California, Los Angeles, CA, United States
- USC Keck Memorial Hospital, Los Angeles, CA, United States
| | - Brian Lee
- USC Keck Memorial Hospital, Los Angeles, CA, United States
| | - Christianne Heck
- Department of Biomedical Engineering, University of Southern California, Los Angeles, CA, United States
- USC Keck Memorial Hospital, Los Angeles, CA, United States
| | - George Nune
- USC Keck Memorial Hospital, Los Angeles, CA, United States
| | - Hui Gong
- Rancho Los Amigos National Rehabilitation Hospital, Los Angeles, CA, United States
| | - Susan Shaw
- Rancho Los Amigos National Rehabilitation Hospital, Los Angeles, CA, United States
| | - Vasilis Z Marmarelis
- Department of Biomedical Engineering, University of Southern California, Los Angeles, CA, United States
| | - Theodore W Berger
- Department of Biomedical Engineering, University of Southern California, Los Angeles, CA, United States
| | - Sam A Deadwyler
- Wake Forest Baptist Medical Center, Winston-Salem, NC, United States
| | - Dong Song
- Department of Biomedical Engineering, University of Southern California, Los Angeles, CA, United States
| | - Robert E Hampson
- Wake Forest Baptist Medical Center, Winston-Salem, NC, United States
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Chen R, Vakilna YS, Lassers SB, Tang WC, Brewer G. Hippocampal network axons respond to patterned theta burst stimulation with lower activity of initially higher spike train similarity from EC to DG and later similarity of axons from CA1 to EC. J Neural Eng 2023; 20:056004. [PMID: 37666242 DOI: 10.1088/1741-2552/acf68a] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/24/2023] [Accepted: 09/04/2023] [Indexed: 09/06/2023]
Abstract
Objective. Decoding memory functions for each hippocampal subregion involves extensive understanding of how each hippocampal subnetwork processes input stimuli. Theta burst stimulation (TBS) recapitulates natural brain stimuli which potentiates synapses in hippocampal circuits. TBS is typically applied to a bundle of axons to measure the immediate response in a downstream subregion like the cornu ammonis 1 (CA1). Yet little is known about network processing in response to stimulation, especially because individual axonal transmission between subregions is not accessible.Approach. To address these limitations, we reverse engineered the hippocampal network on a micro-electrode array partitioned by a MEMS four-chambered device with interconnecting microfluidic tunnels. The micro tunnels allowed monitoring single axon transmission which is inaccessible in slices orin vivo. The four chambers were plated separately with entorhinal cortex (EC), dentate gyrus (DG), CA1, and CA3 neurons. The patterned TBS was delivered to the EC hippocampal gateway. Evoked spike pattern similarity in each subregions was quantified with Jaccard distance metrics of spike timing.Main results. We found that the network subregion produced unique axonal responses to different stimulation patterns. Single site and multisite stimulations caused distinct information routing of axonal spikes in the network. The most spatially similar output at axons from CA3 to CA1 reflected the auto association within CA3 recurrent networks. Moreover, the spike pattern similarities shifted from high levels for axons to and from DG at 0.2 s repeat stimuli to greater similarity in axons to and from CA1 for repetitions at 10 s intervals. This time-dependent response suggested that CA3 encoded temporal information and axons transmitted the information to CA1.Significance. Our design and interrogation approach provide first insights into differences in information transmission between the four subregions of the structured hippocampal network and the dynamic pattern variations in response to stimulation at the subregional level to achieve probabilistic pattern separation and novelty detection.
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Affiliation(s)
- Ruiyi Chen
- Department of Biomedical Engineering, University of California, Irvine, CA 92697, United States of America
| | - Yash Shashank Vakilna
- Department of Biomedical Engineering, University of California, Irvine, CA 92697, United States of America
- Texas Institute of Restorative Neurotechnologies (TIRN), The University of Texas Health Science Center (UTHealth), Houston, TX 77030, United States of America
| | - Samuel Brandon Lassers
- Department of Biomedical Engineering, University of California, Irvine, CA 92697, United States of America
| | - William C Tang
- Department of Biomedical Engineering, University of California, Irvine, CA 92697, United States of America
- Department of Biomedical Engineering, National Taiwan University, Taipei 106319, Taiwan (ROC)
| | - Gregory Brewer
- Department of Biomedical Engineering, University of California, Irvine, CA 92697, United States of America
- Center for Neuroscience of Learning and Memory & MIND Center, University of California, Irvine, CA 92697, United States of America
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Hwang S, Hwang Y, Kim D, Lee J, Choe HK, Lee J, Kang H, Kung J. ReplaceNet: real-time replacement of a biological neural circuit with a hardware-assisted spiking neural network. Front Neurosci 2023; 17:1161592. [PMID: 37638314 PMCID: PMC10448768 DOI: 10.3389/fnins.2023.1161592] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/08/2023] [Accepted: 07/28/2023] [Indexed: 08/29/2023] Open
Abstract
Recent developments in artificial neural networks and their learning algorithms have enabled new research directions in computer vision, language modeling, and neuroscience. Among various neural network algorithms, spiking neural networks (SNNs) are well-suited for understanding the behavior of biological neural circuits. In this work, we propose to guide the training of a sparse SNN in order to replace a sub-region of a cultured hippocampal network with limited hardware resources. To verify our approach with a realistic experimental setup, we record spikes of cultured hippocampal neurons with a microelectrode array (in vitro). The main focus of this work is to dynamically cut unimportant synapses during SNN training on the fly so that the model can be realized on resource-constrained hardware, e.g., implantable devices. To do so, we adopt a simple STDP learning rule to easily select important synapses that impact the quality of spike timing learning. By combining the STDP rule with online supervised learning, we can precisely predict the spike pattern of the cultured network in real-time. The reduction in the model complexity, i.e., the reduced number of connections, significantly reduces the required hardware resources, which is crucial in developing an implantable chip for the treatment of neurological disorders. In addition to the new learning algorithm, we prototype a sparse SNN hardware on a small FPGA with pipelined execution and parallel computing to verify the possibility of real-time replacement. As a result, we can replace a sub-region of the biological neural circuit within 22 μs using 2.5 × fewer hardware resources, i.e., by allowing 80% sparsity in the SNN model, compared to the fully-connected SNN model. With energy-efficient algorithms and hardware, this work presents an essential step toward real-time neuroprosthetic computation.
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Affiliation(s)
- Sangwoo Hwang
- Department of Electrical Engineering and Computer Science, DGIST, Daegu, Republic of Korea
| | - Yujin Hwang
- Department of Electrical Engineering and Computer Science, DGIST, Daegu, Republic of Korea
| | - Duhee Kim
- Department of Electrical Engineering and Computer Science, DGIST, Daegu, Republic of Korea
| | - Junhee Lee
- Department of Electrical Engineering and Computer Science, DGIST, Daegu, Republic of Korea
| | - Han Kyoung Choe
- Department of Brain Sciences, DGIST, Daegu, Republic of Korea
| | - Junghyup Lee
- Department of Electrical Engineering and Computer Science, DGIST, Daegu, Republic of Korea
| | - Hongki Kang
- Department of Electrical Engineering and Computer Science, DGIST, Daegu, Republic of Korea
| | - Jaeha Kung
- School of Electrical Engineering, Korea University, Seoul, Republic of Korea
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Liu X, Wang F, Ramakrishna S. Hippocampus-guided engineering of memory prosthesis. CURRENT OPINION IN BIOMEDICAL ENGINEERING 2022. [DOI: 10.1016/j.cobme.2022.100415] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
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Roeder BM, Riley MR, She X, Dakos AS, Robinson BS, Moore BJ, Couture DE, Laxton AW, Popli G, Munger Clary HM, Sam M, Heck C, Nune G, Lee B, Liu C, Shaw S, Gong H, Marmarelis VZ, Berger TW, Deadwyler SA, Song D, Hampson RE. Patterned Hippocampal Stimulation Facilitates Memory in Patients With a History of Head Impact and/or Brain Injury. Front Hum Neurosci 2022; 16:933401. [PMID: 35959242 PMCID: PMC9358788 DOI: 10.3389/fnhum.2022.933401] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/30/2022] [Accepted: 06/13/2022] [Indexed: 11/24/2022] Open
Abstract
Rationale: Deep brain stimulation (DBS) of the hippocampus is proposed for enhancement of memory impaired by injury or disease. Many pre-clinical DBS paradigms can be addressed in epilepsy patients undergoing intracranial monitoring for seizure localization, since they already have electrodes implanted in brain areas of interest. Even though epilepsy is usually not a memory disorder targeted by DBS, the studies can nevertheless model other memory-impacting disorders, such as Traumatic Brain Injury (TBI). Methods: Human patients undergoing Phase II invasive monitoring for intractable epilepsy were implanted with depth electrodes capable of recording neurophysiological signals. Subjects performed a delayed-match-to-sample (DMS) memory task while hippocampal ensembles from CA1 and CA3 cell layers were recorded to estimate a multi-input, multi-output (MIMO) model of CA3-to-CA1 neural encoding and a memory decoding model (MDM) to decode memory information from CA3 and CA1 neuronal signals. After model estimation, subjects again performed the DMS task while either MIMO-based or MDM-based patterned stimulation was delivered to CA1 electrode sites during the encoding phase of the DMS trials. Each subject was sorted (post hoc) by prior experience of repeated and/or mild-to-moderate brain injury (RMBI), TBI, or no history (control) and scored for percentage successful delayed recognition (DR) recall on stimulated vs. non-stimulated DMS trials. The subject’s medical history was unknown to the experimenters until after individual subject memory retention results were scored. Results: When examined compared to control subjects, both TBI and RMBI subjects showed increased memory retention in response to both MIMO and MDM-based hippocampal stimulation. Furthermore, effects of stimulation were also greater in subjects who were evaluated as having pre-existing mild-to-moderate memory impairment. Conclusion: These results show that hippocampal stimulation for memory facilitation was more beneficial for subjects who had previously suffered a brain injury (other than epilepsy), compared to control (epilepsy) subjects who had not suffered a brain injury. This study demonstrates that the epilepsy/intracranial recording model can be extended to test the ability of DBS to restore memory function in subjects who previously suffered a brain injury other than epilepsy, and support further investigation into the beneficial effect of DBS in TBI patients.
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Affiliation(s)
- Brent M. Roeder
- Department of Physiology and Pharmacology, Wake Forest School of Medicine, Winston-Salem, NC, United States
| | - Mitchell R. Riley
- Department of Physiology and Pharmacology, Wake Forest School of Medicine, Winston-Salem, NC, United States
| | - Xiwei She
- Department Biomedical Engineering, Viterbi School of Engineering, University of Southern California, Los Angeles, CA, United States
| | - Alexander S. Dakos
- Department of Physiology and Pharmacology, Wake Forest School of Medicine, Winston-Salem, NC, United States
| | - Brian S. Robinson
- Department Biomedical Engineering, Viterbi School of Engineering, University of Southern California, Los Angeles, CA, United States
| | - Bryan J. Moore
- Department Biomedical Engineering, Viterbi School of Engineering, University of Southern California, Los Angeles, CA, United States
| | - Daniel E. Couture
- Department of Neurosurgery, Wake Forest School of Medicine/Atrium Health Wake Forest Baptist, Winston-Salem, NC, United States
| | - Adrian W. Laxton
- Department of Neurosurgery, Wake Forest School of Medicine/Atrium Health Wake Forest Baptist, Winston-Salem, NC, United States
| | - Gautam Popli
- Department of Neurology, Wake Forest School of Medicine/Atrium Health Wake Forest Baptist, Winston-Salem, NC, United States
| | - Heidi M. Munger Clary
- Department of Neurology, Wake Forest School of Medicine/Atrium Health Wake Forest Baptist, Winston-Salem, NC, United States
| | - Maria Sam
- Department of Neurology, Wake Forest School of Medicine/Atrium Health Wake Forest Baptist, Winston-Salem, NC, United States
| | - Christi Heck
- Department of Neurology, W. M. Keck School of Medicine, University of Southern California, Los Angeles, CA, United States
| | - George Nune
- Department of Neurology, W. M. Keck School of Medicine, University of Southern California, Los Angeles, CA, United States
| | - Brian Lee
- Department of Neurosurgery, W. M. Keck School of Medicine, University of Southern California, Los Angeles, CA, United States
| | - Charles Liu
- Department of Neurosurgery, W. M. Keck School of Medicine, University of Southern California, Los Angeles, CA, United States
| | - Susan Shaw
- Department of Neurology, Rancho Los Amigos National Rehabilitation Hospital, Los Angeles, CA, United States
| | - Hui Gong
- Department of Neurology, Rancho Los Amigos National Rehabilitation Hospital, Los Angeles, CA, United States
| | - Vasilis Z. Marmarelis
- Department Biomedical Engineering, Viterbi School of Engineering, University of Southern California, Los Angeles, CA, United States
| | - Theodore W. Berger
- Department Biomedical Engineering, Viterbi School of Engineering, University of Southern California, Los Angeles, CA, United States
| | - Sam A. Deadwyler
- Department of Physiology and Pharmacology, Wake Forest School of Medicine, Winston-Salem, NC, United States
| | - Dong Song
- Department Biomedical Engineering, Viterbi School of Engineering, University of Southern California, Los Angeles, CA, United States
| | - Robert E. Hampson
- Department of Physiology and Pharmacology, Wake Forest School of Medicine, Winston-Salem, NC, United States
- Department of Neurology, Wake Forest School of Medicine/Atrium Health Wake Forest Baptist, Winston-Salem, NC, United States
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