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Borland MS, Buell EP, Riley JR, Carroll AM, Moreno NA, Sharma P, Grasse KM, Buell JM, Kilgard MP, Engineer CT. Precise sound characteristics drive plasticity in the primary auditory cortex with VNS-sound pairing. Front Neurosci 2023; 17:1248936. [PMID: 37732302 PMCID: PMC10508341 DOI: 10.3389/fnins.2023.1248936] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/27/2023] [Accepted: 08/22/2023] [Indexed: 09/22/2023] Open
Abstract
Introduction Repeatedly pairing a tone with vagus nerve stimulation (VNS) alters frequency tuning across the auditory pathway. Pairing VNS with speech sounds selectively enhances the primary auditory cortex response to the paired sounds. It is not yet known how altering the speech sounds paired with VNS alters responses. In this study, we test the hypothesis that the sounds that are presented and paired with VNS will influence the neural plasticity observed following VNS-sound pairing. Methods To explore the relationship between acoustic experience and neural plasticity, responses were recorded from primary auditory cortex (A1) after VNS was repeatedly paired with the speech sounds 'rad' and 'lad' or paired with only the speech sound 'rad' while 'lad' was an unpaired background sound. Results Pairing both sounds with VNS increased the response strength and neural discriminability of the paired sounds in the primary auditory cortex. Surprisingly, pairing only 'rad' with VNS did not alter A1 responses. Discussion These results suggest that the specific acoustic contrasts associated with VNS can powerfully shape neural activity in the auditory pathway. Methods to promote plasticity in the central auditory system represent a new therapeutic avenue to treat auditory processing disorders. Understanding how different sound contrasts and neural activity patterns shape plasticity could have important clinical implications.
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Affiliation(s)
- Michael S. Borland
- Department of Neuroscience, School of Behavioral and Brain Sciences, The University of Texas at Dallas, Richardson, TX, United States
- Texas Biomedical Device Center, The University of Texas at Dallas, Richardson, TX, United States
| | - Elizabeth P. Buell
- Department of Neuroscience, School of Behavioral and Brain Sciences, The University of Texas at Dallas, Richardson, TX, United States
- Texas Biomedical Device Center, The University of Texas at Dallas, Richardson, TX, United States
| | - Jonathan R. Riley
- Department of Neuroscience, School of Behavioral and Brain Sciences, The University of Texas at Dallas, Richardson, TX, United States
- Texas Biomedical Device Center, The University of Texas at Dallas, Richardson, TX, United States
| | - Alan M. Carroll
- Department of Neuroscience, School of Behavioral and Brain Sciences, The University of Texas at Dallas, Richardson, TX, United States
- Texas Biomedical Device Center, The University of Texas at Dallas, Richardson, TX, United States
| | - Nicole A. Moreno
- Department of Neuroscience, School of Behavioral and Brain Sciences, The University of Texas at Dallas, Richardson, TX, United States
- Texas Biomedical Device Center, The University of Texas at Dallas, Richardson, TX, United States
| | - Pryanka Sharma
- Department of Neuroscience, School of Behavioral and Brain Sciences, The University of Texas at Dallas, Richardson, TX, United States
- Texas Biomedical Device Center, The University of Texas at Dallas, Richardson, TX, United States
| | - Katelyn M. Grasse
- Texas Biomedical Device Center, The University of Texas at Dallas, Richardson, TX, United States
- Erik Jonsson School of Engineering and Computer Science, The University of Texas at Dallas, Richardson, TX, United States
| | - John M. Buell
- Department of Neuroscience, School of Behavioral and Brain Sciences, The University of Texas at Dallas, Richardson, TX, United States
- Texas Biomedical Device Center, The University of Texas at Dallas, Richardson, TX, United States
| | - Michael P. Kilgard
- Department of Neuroscience, School of Behavioral and Brain Sciences, The University of Texas at Dallas, Richardson, TX, United States
- Texas Biomedical Device Center, The University of Texas at Dallas, Richardson, TX, United States
| | - Crystal T. Engineer
- Department of Neuroscience, School of Behavioral and Brain Sciences, The University of Texas at Dallas, Richardson, TX, United States
- Texas Biomedical Device Center, The University of Texas at Dallas, Richardson, TX, United States
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Kozma R, Hu S, Sokolov Y, Wanger T, Schulz AL, Woldeit ML, Gonçalves AI, Ruszinkó M, Ohl FW. State Transitions During Discrimination Learning in the Gerbil Auditory Cortex Analyzed by Network Causality Metrics. Front Syst Neurosci 2021; 15:641684. [PMID: 33967706 PMCID: PMC8100519 DOI: 10.3389/fnsys.2021.641684] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2020] [Accepted: 03/16/2021] [Indexed: 12/18/2022] Open
Abstract
This work studies the evolution of cortical networks during the transition from escape strategy to avoidance strategy in auditory discrimination learning in Mongolian gerbils trained by the well-established two-way active avoidance learning paradigm. The animals were implanted with electrode arrays centered on the surface of the primary auditory cortex and electrocorticogram (ECoG) recordings were made during performance of an auditory Go/NoGo discrimination task. Our experiments confirm previous results on a sudden behavioral change from the initial naïve state to an avoidance strategy as learning progresses. We employed two causality metrics using Granger Causality (GC) and New Causality (NC) to quantify changes in the causality flow between ECoG channels as the animals switched to avoidance strategy. We found that the number of channel pairs with inverse causal interaction significantly increased after the animal acquired successful discrimination, which indicates structural changes in the cortical networks as a result of learning. A suitable graph-theoretical model is developed to interpret the findings in terms of cortical networks evolving during cognitive state transitions. Structural changes lead to changes in the dynamics of neural populations, which are described as phase transitions in the network graph model with small-world connections. Overall, our findings underscore the importance of functional reorganization in sensory cortical areas as a possible neural contributor to behavioral changes.
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Affiliation(s)
- Robert Kozma
- Center for Large-Scale Intelligent Optimization and Networks, Department of Mathematics, University of Memphis, Memphis, TN, United States
| | - Sanqing Hu
- College of Computer Science, Hangzhou Dianzi University, Hangzhou, China
| | - Yury Sokolov
- Department of Medicine, University of California, San Diego, La Jolla, CA, United States
| | - Tim Wanger
- Leibniz Institute for Neurobiology (LIN), Magdeburg, Germany
| | | | - Marie L Woldeit
- Leibniz Institute for Neurobiology (LIN), Magdeburg, Germany
| | - Ana I Gonçalves
- Leibniz Institute for Neurobiology (LIN), Magdeburg, Germany
| | - Miklós Ruszinkó
- Alfréd Rényi Institute of Mathematics, Budapest, Hungary.,Faculty of Information Technology and Bionics, Pázmány Péter Catholic University, Budapest, Hungary
| | - Frank W Ohl
- Leibniz Institute for Neurobiology (LIN), Magdeburg, Germany.,Institute of Biology, Otto von Guericke University, Magdeburg, Germany.,Center of Behavioral Brain Science (CBBS), Magdeburg, Germany
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Li Z, Dong Z, Bai X, Liu M. Characterizing the orientation selectivity in V1 and V4 of macaques by quadratic phase coupling. J Neural Eng 2020; 17:036028. [PMID: 32480396 DOI: 10.1088/1741-2552/ab9843] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022]
Abstract
OBJECTIVE Orientation selectivity is one of the significant characteristics of neurons in the primary visual cortex (V1). Some neurons in extrastriate visual cortical areas also exhibit certain orientation selectivity. But it is still not well understood that how the orientation selectivity generates. Most previous studies about the orientation selectivity are based on the spike firing rate. However, the spikes are prone to be biased by the detection and sorting algorithms. Then, in this paper, the local field potential (LFP) is adopted to investigate the mechanism of orientation selectivity. APPROACH We used the quadratic phase coupling (QPC), which was calculated by wavelet bicoherence, to describe the characteristics of orientation selectivity available in V1 and V4. The raw wideband neural signals were recorded by two chronically implanted multi-electrode arrays, which were placed in V1 and V4 respectively in two macaques performing a selective visual attention task. MAIN RESULTS There is a strong correlation between the total bicoherence (TotalBic), which is a quantization for the overall QPC of frequency pairs in gamma band, and the grating orientation. Furthermore, the QPC distribution at the non-preferred orientation is mainly concentrated in the low frequencies (30-40 Hz) of gamma; while the QPC distribution at the preferred orientation concentrates in both the low frequencies and high frequencies (60-80 Hz) of gamma. In addition, the TotalBic of the gamma-band LFP between V1 and V4 varies with the grating orientations, indicating that the QPC is available in the feedforward link and the gamma-band LFP in V1 modulates the QPC in V4. SIGNIFICANCE The QPC reflects the orientations of the sinusoidal grating and describes the interaction of gamma-band LFP between different brain regions. Our results suggest that the QPC is an alternative avenue to explore the mechanism for generating orientation selectivity of visual neurons effectively.
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Affiliation(s)
- Zhaohui Li
- School of Information Science and Engineering, Yanshan University, Qinhuangdao, People's Republic of China. Hebei Key Laboratory of Information Transmission and Signal Processing, Yanshan University, Qinhuangdao, People's Republic of China
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Acoustical Enrichment during Early Development Improves Response Reliability in the Adult Auditory Cortex of the Rat. Neural Plast 2018; 2018:5903720. [PMID: 30002673 PMCID: PMC5998158 DOI: 10.1155/2018/5903720] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/12/2017] [Revised: 04/16/2018] [Accepted: 04/29/2018] [Indexed: 11/18/2022] Open
Abstract
It is well known that auditory experience during early development shapes response properties of auditory cortex (AC) neurons, influencing, for example, tonotopical arrangement, response thresholds and strength, or frequency selectivity. Here, we show that rearing rat pups in a complex acoustically enriched environment leads to an increased reliability of responses of AC neurons, affecting both the rate and the temporal codes. For a repetitive stimulus, the neurons exhibit a lower spike count variance, indicating a more stable rate coding. At the level of individual spikes, the discharge patterns of individual neurons show a higher degree of similarity across stimulus repetitions. Furthermore, the neurons follow more precisely the temporal course of the stimulus, as manifested by improved phase-locking to temporally modulated sounds. The changes are persistent and present up to adulthood. The results document that besides basic alterations of receptive fields presented in our previous study, the acoustic environment during the critical period of postnatal development also leads to a decreased stochasticity and a higher reproducibility of neuronal spiking patterns.
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Leon MI, Miasnikov AA, Wright EJ, Weinberger NM. CS-specific modifications of auditory evoked potentials in the behaviorally conditioned rat. Brain Res 2017; 1670:235-247. [PMID: 28673481 DOI: 10.1016/j.brainres.2017.06.030] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/12/2017] [Revised: 06/27/2017] [Accepted: 06/28/2017] [Indexed: 11/16/2022]
Abstract
The current report provides a detailed analysis of the changes in the first two components of the auditory evoked potential (AEP) that accompany associative learning. AEPs were recorded from the primary auditory cortex before and after training sessions. Experimental subjects underwent one (n=5) or two (n=7) days of conditioning in which a tone, serving as a conditioned stimulus (CS), was paired with mild foot shock. Control subjects received one (n=5) or two (n=7) days of exposure to the same stimuli delivered randomly. Only animals receiving paired CS-US training developed a conditioned tachycardia response to the tone. Our analyses demonstrated that both early components of the AEP recorded from the granular layer of the cortex undergo CS-specific associative changes: (1) the first, negative component (occurring ∼21ms following tone onset) was significantly augmented after one and two days of training while maintaining its latency, and (2) the second, positive component (occurring ∼50ms following tone onset) was augmented after two days of training, and showed a significant reduction in latency after one and two days of training. We view these changes as evidence of increased cortical synchronization, thereby lending new insight into the temporal dynamics of neural network activity related to auditory learning.
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Affiliation(s)
- Matthew I Leon
- Center for the Neurobiology of Learning and Memory, University of California, Irvine, Irvine, CA 92697-3800, United States; Department of Psychology, California State University, Bakersfield, 9001 Stockdale Highway, Bakersfield, CA 93311-1022, United States.
| | - Alexandre A Miasnikov
- Center for the Neurobiology of Learning and Memory, University of California, Irvine, Irvine, CA 92697-3800, United States
| | - Ernest J Wright
- Center for the Neurobiology of Learning and Memory, University of California, Irvine, Irvine, CA 92697-3800, United States
| | - Norman M Weinberger
- Center for the Neurobiology of Learning and Memory, University of California, Irvine, Irvine, CA 92697-3800, United States
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Noda T, Amemiya T, Shiramatsu TI, Takahashi H. Stimulus Phase Locking of Cortical Oscillations for Rhythmic Tone Sequences in Rats. Front Neural Circuits 2017; 11:2. [PMID: 28184188 PMCID: PMC5266736 DOI: 10.3389/fncir.2017.00002] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2016] [Accepted: 01/04/2017] [Indexed: 12/21/2022] Open
Abstract
Humans can rapidly detect regular patterns (i.e., within few cycles) without any special attention to the acoustic environment. This suggests that human sensory systems are equipped with a powerful mechanism for automatically predicting forthcoming stimuli to detect regularity. It has recently been hypothesized that the neural basis of sensory predictions exists for not only what happens (predictive coding) but also when a particular stimulus occurs (predictive timing). Here, we hypothesize that the phases of neural oscillations are critical in predictive timing, and these oscillations are modulated in a band-specific manner when acoustic patterns become predictable, i.e., regular. A high-density microelectrode array (10 × 10 within 4 × 4 mm2) was used to characterize spatial patterns of band-specific oscillations when a random-tone sequence was switched to a regular-tone sequence. Increasing the regularity of the tone sequence enhanced phase locking in a band-specific manner, notwithstanding the type of the regular sound pattern. Gamma-band phase locking increased immediately after the transition from random to regular sequences, while beta-band phase locking gradually evolved with time after the transition. The amplitude of the tone-evoked response, in contrast, increased with frequency separation with respect to the prior tone, suggesting that the evoked-response amplitude encodes sequence information on a local scale, i.e., the local order of tones. The phase locking modulation spread widely over the auditory cortex, while the amplitude modulation was confined around the activation foci. Thus, our data suggest that oscillatory phase plays a more important role than amplitude in the neuronal detection of tone sequence regularity, which is closely related to predictive timing. Furthermore, band-specific contributions may support recent theories that gamma oscillations encode bottom-up prediction errors, whereas beta oscillations are involved in top-down prediction.
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Affiliation(s)
- Takahiro Noda
- Research Center for Advanced Science and Technology, University of TokyoTokyo, Japan; Institute of Neuroscience, Technical University MunichMunich, Germany
| | - Tomoki Amemiya
- Graduate School of Information Science and Technology, University of Tokyo Tokyo, Japan
| | - Tomoyo I Shiramatsu
- Research Center for Advanced Science and Technology, University of Tokyo Tokyo, Japan
| | - Hirokazu Takahashi
- Research Center for Advanced Science and Technology, University of TokyoTokyo, Japan; Graduate School of Information Science and Technology, University of TokyoTokyo, Japan
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Noda T, Takahashi H. Anesthetic effects of isoflurane on the tonotopic map and neuronal population activity in the rat auditory cortex. Eur J Neurosci 2015; 42:2298-311. [PMID: 26118739 DOI: 10.1111/ejn.13007] [Citation(s) in RCA: 32] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/13/2015] [Revised: 06/23/2015] [Accepted: 06/24/2015] [Indexed: 12/01/2022]
Abstract
Since its discovery nearly four decades ago, sequential microelectrode mapping using hundreds of recording sites has been able to reveal a precise tonotopic organization of the auditory cortex. Despite concerns regarding the effects that anesthesia might have on neuronal responses to tones, anesthesia was essential for these experiments because such dense mapping was elaborate and time-consuming. Here, taking an 'all-at-once' approach, we investigated how isoflurane modifies spatiotemporal activities by using a dense microelectrode array. The array covered the entire auditory cortex in rats, including the core and belt cortices. By comparing neuronal activity in the awake state with activity under isoflurane anesthesia, we made four observations. First, isoflurane anesthesia did not modify the tonotopic topography within the auditory cortex. Second, in terms of general response properties, isoflurane anesthesia decreased the number of active single units and increased their response onset latency. Third, in terms of tuning properties, isoflurane anesthesia shifted the response threshold without changing the shape of the frequency response area and decreased the response quality. Fourth, in terms of population activities, isoflurane anesthesia increased the noise correlations in discharges and phase synchrony in local field potential (LFP) oscillations, suggesting that the anesthesia made neuronal activities redundant at both single-unit and LFP levels. Thus, while isoflurane anesthesia had little effect on the tonotopic topography, its profound effects on neuronal activities decreased the encoding capacity of the auditory cortex.
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Affiliation(s)
- Takahiro Noda
- Research Center for Advanced Science and Technology, The University of Tokyo, Komaba 4-6-1, Meguro-ku, Tokyo, 153-8904, Japan
| | - Hirokazu Takahashi
- Research Center for Advanced Science and Technology, The University of Tokyo, Komaba 4-6-1, Meguro-ku, Tokyo, 153-8904, Japan.,PRESTO, JST, Kawaguchi, Saitama, Japan
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