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Cardon G, Cate M, Cordingley S, Bown B. Auditory Brainstem Response in Autistic Children: Implications for Sensory Processing. HEARING, BALANCE AND COMMUNICATION 2023; 21:224-232. [PMID: 38223460 PMCID: PMC10786617 DOI: 10.1080/21695717.2023.2181558] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/17/2023]
Abstract
Purpose Autistic individuals frequently experience sensory processing difficulties. Such difficulties can significantly impact important functions and quality of life. We are only beginning to understand the neural mechanisms of atypical sensory processing. However, one established way to measure aspects of auditory function is the auditory brainstem response (ABR). While ABR has been primarily hypothesized thus far as a means of early detection/diagnosis in autism, it has the potential to aid in examining sensory processing in this population. Method Thus, we investigated standard ABR waveform characteristics in age-matched groups of autistic and typically developing children during various stimulus and intensity conditions. We also examined within ear waveform cross correlations and inter-aural cross correlations (IACC) to assess replicability and synchrony of participants' ABRs, which was a novel approach to ABR analysis in this population. Results We observed longer peak latencies (esp. wave III and V) and interpeak latencies in the autism and typically developing groups in different conditions. There were no statistically significant results in cross correlation or IACC. Conclusions These results suggest that brainstem auditory function may differ slightly, but is mostly similar, between autistic and typically developing children. We discuss these findings in terms of their implications for sensory processing and future utility.
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Affiliation(s)
- Garrett Cardon
- Brigham Young University, Department of Communication Disorders, Provo, UT
| | - Madelyn Cate
- Brigham Young University, Department of Communication Disorders, Provo, UT
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2
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Abstract
Brain state fluctuates throughout the course of the day. Whether and how these fluctuations impact signal propagation in the brain remains unknown. Here, we used optogenetic stimulation during different brain states to show that the coupling between neurons modulates the spread of signals across cortical circuits in a state-dependent manner. Our results indicate that brain state influences how far electrical signals travel in neocortex and suggest a revision of computational models relying on robust signal propagation across neural networks. Our perception of the environment relies on the efficient propagation of neural signals across cortical networks. During the time course of a day, neural responses fluctuate dramatically as the state of the brain changes to possibly influence how electrical signals propagate across neural circuits. Despite the importance of this issue, how patterns of spiking activity propagate within neuronal circuits in different brain states remains unknown. Here, we used multielectrode laminar arrays to reveal that brain state strongly modulates the propagation of neural activity across the layers of early visual cortex (V1). We optogenetically induced synchronized state transitions within a group of neurons and examined how far electrical signals travel during wakefulness and rest. Although optogenetic stimulation elicits stronger neural responses during wakefulness relative to rest, signals propagate only weakly across the cortical column during wakefulness, and the extent of spread is inversely related to arousal level. In contrast, the light-induced population activity vigorously propagates throughout the entire cortical column during rest, even when neurons are in a desynchronized wake-like state prior to light stimulation. Mechanistically, the influence of global brain state on the propagation of spiking activity across laminar circuits can be explained by state-dependent changes in the coupling between neurons. Our results impose constraints on the conclusions of causal manipulation studies attempting to influence neural function and behavior, as well as on previous computational models of perception assuming robust signal propagation across cortical layers and areas.
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Ma L, Patel M. Mechanism of carbachol-induced 40 Hz gamma oscillations and the effects of NMDA activation on oscillatory dynamics in a model of the CA3 subfield of the hippocampus. J Theor Biol 2022; 548:111200. [PMID: 35716721 DOI: 10.1016/j.jtbi.2022.111200] [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: 03/12/2022] [Revised: 05/26/2022] [Accepted: 06/08/2022] [Indexed: 11/26/2022]
Abstract
Gamma oscillations are a prominent feature of various neural systems, including the CA3 subfield of the hippocampus. In CA3, in vitro carbachol application induces ∼40 Hz gamma oscillations in the network of glutamatergic excitatory pyramidal neurons (PNs) and local GABAergic inhibitory neurons (INs). Activation of NMDA receptors within CA3 leads to an increase in the frequency of carbachol-induced oscillations to ∼60 Hz, a broadening of the distribution of individual oscillation cycle frequencies, and a decrease in the time lag between PN and IN spike bursts. In this work, we develop a biophysical integrate-and-fire model of the CA3 subfield, we show that the dynamics of our model are in concordance with physiological observations, and we provide computational support for the hypothesis that the 'E-I' mechanism is responsible for the emergence of ∼40 Hz gamma oscillations in the absence of NMDA activation. We then incorporate NMDA receptors into our CA3 model, and we show that our model exhibits the increase in gamma oscillation frequency, broadening of the cycle frequency distribution, and decrease in the time lag between PN and IN spike bursts observed experimentally. Remarkably, we find an inverse relationship in our model between the net NMDA current delivered to PNs and INs in an oscillation cycle and cycle frequency. Furthermore, we find a disparate effect of NMDA receptors on PNs versus INs - we show that NMDA receptors on INs tend to increase oscillation frequency, while NMDA receptors on PNs tend to slightly decrease or not affect oscillation frequency. We find that these observations can be explained if NMDA activity above a threshold level causes a shift in the mechanism underlying gamma oscillations; in the absence of NMDA receptors, the 'E-I' mechanism is primarily responsible for the generation of gamma oscillations (at 40 Hz), while when NMDA receptors are active, the mechanism of gamma oscillations shifts to the 'I-I' mechanism, and we argue that within the 'I-I' regime (which displays a higher baseline oscillation frequency of ∼60 Hz), slight changes in the level of NMDA activity are inversely related to cycle frequency.
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Affiliation(s)
- Linda Ma
- Department of Mathematics, William & Mary, United States.
| | - Mainak Patel
- Department of Mathematics, William & Mary, United States.
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4
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Ma L, Patel M. A model of lateral interactions as the origin of multiwhisker receptive fields in rat barrel cortex. J Comput Neurosci 2021; 50:181-201. [PMID: 34854018 DOI: 10.1007/s10827-021-00804-6] [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: 06/25/2021] [Revised: 09/03/2021] [Accepted: 11/10/2021] [Indexed: 11/30/2022]
Abstract
While cells within barrel cortex respond primarily to deflections of their principal whisker (PW), they also exhibit responses to non-principal, or adjacent, whiskers (AWs), albeit responses with diminished amplitudes and longer latencies. The origin of multiwhisker receptive fields of barrel cells remains a point of controversy within the experimental literature, with three contending possibilities: (i) barrel cells inherit their AW responses from the AW responses of thalamocortical (TC) cells within their aligned barreloid; (ii) the axons of TC cells within a barreloid ramify to innervate multiple barrels, rather than only terminating within their aligned barrel; (iii) lateral intracortical transmission between barrels conveys AW responsivity to barrel cells. In this work, we develop a detailed, biologically plausible model of multiple barrels in order to examine possibility (iii); in order to isolate the dynamics that possibility (iii) entails, we incorporate lateral connections between barrels while assuming that TC cells respond only to their PW and that TC cell axons are confined to their home barrel. We show that our model is capable of capturing a broad swath of experimental observations on multiwhisker receptive field dynamics within barrels, and we compare and contrast the dynamics of this model with model dynamics from prior work in which employ a similar general modeling strategy to examine possibility (i).
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Affiliation(s)
- Linda Ma
- Department of Mathematics, 200 Ukrop Way, Jones Hall, William & Mary, Williamsburg, 23185, VA, USA
| | - Mainak Patel
- Department of Mathematics, 200 Ukrop Way, Jones Hall, William & Mary, Williamsburg, 23185, VA, USA.
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Orkan Olcay B, Özgören M, Karaçalı B. On the characterization of cognitive tasks using activity-specific short-lived synchronization between electroencephalography channels. Neural Netw 2021; 143:452-474. [PMID: 34273721 DOI: 10.1016/j.neunet.2021.06.022] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/12/2021] [Revised: 05/04/2021] [Accepted: 06/18/2021] [Indexed: 10/21/2022]
Abstract
Accurate characterization of brain activity during a cognitive task is challenging due to the dynamically changing and the complex nature of the brain. The majority of the proposed approaches assume stationarity in brain activity and disregard the systematic timing organization among brain regions during cognitive tasks. In this study, we propose a novel cognitive activity recognition method that captures the activity-specific timing parameters from training data that elicits maximal average short-lived pairwise synchronization between electroencephalography signals. We evaluated the characterization power of the activity-specific timing parameter triplets in a motor imagery activity recognition framework. The activity-specific timing parameter triplets consist of latency of the maximally synchronized signal segments from activity onset Δt, the time lag between maximally synchronized signal segments τ, and the duration of the maximally synchronized signal segments w. We used cosine-based similarity, wavelet bi-coherence, phase-locking value, phase coherence value, linearized mutual information, and cross-correntropy to calculate the channel synchronizations at the specific timing parameters. Recognition performances as well as statistical analyses on both BCI Competition-III dataset IVa and PhysioNet Motor Movement/Imagery dataset, indicate that the inter-channel short-lived synchronization calculated using activity-specific timing parameter triplets elicit significantly distinct synchronization profiles for different motor imagery tasks and can thus reliably be used for cognitive task recognition purposes.
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Affiliation(s)
- B Orkan Olcay
- Department of Electrical and Electronics Engineering, Izmir Institute of Technology, 35430, Urla, Izmir, Turkey.
| | - Murat Özgören
- Department of Biophysics, Faculty of Medicine, Near East University, 99138, Nicosia, Cyprus.
| | - Bilge Karaçalı
- Department of Electrical and Electronics Engineering, Izmir Institute of Technology, 35430, Urla, Izmir, Turkey.
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Olfactory encoding within the insect antennal lobe: The emergence and role of higher order temporal correlations in the dynamics of antennal lobe spiking activity. J Theor Biol 2021; 522:110700. [PMID: 33819477 DOI: 10.1016/j.jtbi.2021.110700] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/26/2020] [Revised: 03/20/2021] [Accepted: 03/23/2021] [Indexed: 11/22/2022]
Abstract
In this review, we focus on the antennal lobe (AL) of three insect species - the fruit fly, sphinx moth, and locust. We first review the experimentally elucidated anatomy and physiology of the early olfactory system of each species; empirical studies of AL activity, however, often focus on assessing firing rates (averaged over time scales of about 100 ms), and hence the AL odor code is often analyzed in terms of a temporally evolving vector of firing rates. However, such a perspective necessarily misses the possibility of higher order temporal correlations in spiking activity within a single cell and across multiple cells over shorter time scales (of about 10 ms). Hence, we then review our prior theoretical work, where we constructed biophysically detailed, species-specific AL models within the fly, moth, and locust, finding that in each case higher order temporal correlations in spiking naturally emerge from model dynamics (i.e., without a prioriincorporation of elements designed to produce correlated activity). We therefore use our theoretical work to argue the perspective that temporal correlations in spiking over short time scales, which have received little experimental attention to-date, may provide valuable coding dimensions (complementing the coding dimensions provided by the vector of firing rates) that nature has exploited in the encoding of odors within the AL. We further argue that, if the AL does indeed utilize temporally correlated activity to represent odor information, such an odor code could be naturally and easily deciphered within the Mushroom Body.
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Analysis of feedforward mechanisms of multiwhisker receptive field generation in a model of the rat barrel cortex. J Theor Biol 2019; 477:51-62. [PMID: 31201881 DOI: 10.1016/j.jtbi.2019.06.008] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/27/2019] [Revised: 04/16/2019] [Accepted: 06/11/2019] [Indexed: 11/23/2022]
Abstract
There is substantial anatomical segregation in the organization of the rodent barrel system - each whisker on the mystacial pad sends input to TC cells within a dedicated thalamic barreloid, which in turn innervates a corresponding cortical barrel, and RS cells within a barrel respond primarily to deflections of the corresponding whisker at the beginning of the dedicated transmission line (the principal whisker, PW). However, it is also well-established that barrel cells exhibit multiwhisker receptive fields (RFs), and display lower amplitude, longer latency responses to deflections of non-PWs (or adjacent whiskers, AWs). There is considerable controversy regarding the origin of such multiwhisker RFs; three possibilities include: (i) TC cells within a barreloid respond to multiple whiskers, and barrel RS cells simply inherit multiwhisker responses from their aligned barreloid; (ii) TC cells respond only to the PW, but individual barreloids innervate multiple barrels; (iii) multiwhisker responses of barrel cells arise from lateral corticocortical (barrel-to-barrel) synaptic transmission. Ablation studies attempting to pinpoint the source of RS cell AW responses are often contradictory (though experimental work tends to suggest possibilities (i) or (iii) to be most plausible), and hence it is important to carefully evaluate these hypotheses in terms of available physiological data on barreloid and barrel response dynamics. In this work, I employ a biologically detailed model of the rat barrel cortex to evaluate possibility (i), and I show that, within the model, hypothesis (i) is capable of explaining a broad range of the available physiological data on responses to single (PW or AW) deflections and paired whisker deflections (AW deflection followed by PW deflection), as well as the dependence of such responses on the angular direction of whisker deflection. In particular, the model shows that barrel RS cells can exhibit AW direction tuning despite the fact that barreloid to barrel wiring has no systematic dependence on the AW direction preference of TC cells. Future modeling work will examine the other possibilities for the generation of multiwhisker RS cell RFs, and compare and contrast the different possible mechanisms within the context of available experimental data.
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Negrello M, Warnaar P, Romano V, Owens CB, Lindeman S, Iavarone E, Spanke JK, Bosman LWJ, De Zeeuw CI. Quasiperiodic rhythms of the inferior olive. PLoS Comput Biol 2019; 15:e1006475. [PMID: 31059498 PMCID: PMC6538185 DOI: 10.1371/journal.pcbi.1006475] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/29/2018] [Revised: 05/28/2019] [Accepted: 04/16/2019] [Indexed: 12/13/2022] Open
Abstract
Inferior olivary activity causes both short-term and long-term changes in cerebellar output underlying motor performance and motor learning. Many of its neurons engage in coherent subthreshold oscillations and are extensively coupled via gap junctions. Studies in reduced preparations suggest that these properties promote rhythmic, synchronized output. However, the interaction of these properties with torrential synaptic inputs in awake behaving animals is not well understood. Here we combine electrophysiological recordings in awake mice with a realistic tissue-scale computational model of the inferior olive to study the relative impact of intrinsic and extrinsic mechanisms governing its activity. Our data and model suggest that if subthreshold oscillations are present in the awake state, the period of these oscillations will be transient and variable. Accordingly, by using different temporal patterns of sensory stimulation, we found that complex spike rhythmicity was readily evoked but limited to short intervals of no more than a few hundred milliseconds and that the periodicity of this rhythmic activity was not fixed but dynamically related to the synaptic input to the inferior olive as well as to motor output. In contrast, in the long-term, the average olivary spiking activity was not affected by the strength and duration of the sensory stimulation, while the level of gap junctional coupling determined the stiffness of the rhythmic activity in the olivary network during its dynamic response to sensory modulation. Thus, interactions between intrinsic properties and extrinsic inputs can explain the variations of spiking activity of olivary neurons, providing a temporal framework for the creation of both the short-term and long-term changes in cerebellar output. Activity of the inferior olive, transmitted via climbing fibers to the cerebellum, regulates initiation and amplitude of movements, signals unexpected sensory feedback, and directs cerebellar learning. It is characterized by widespread subthreshold oscillations and synchronization promoted by strong electrotonic coupling. In brain slices, subthreshold oscillations gate which inputs can be transmitted by inferior olivary neurons and which will not—dependent on the phase of the oscillation. We tested whether the subthreshold oscillations had a measurable impact on temporal patterning of climbing fiber activity in intact, awake mice. We did so by recording neural activity of the postsynaptic Purkinje cells, in which complex spike firing faithfully represents climbing fiber activity. For short intervals (<300 ms) many Purkinje cells showed spontaneously rhythmic complex spike activity. However, our experiments designed to evoke conditional responses indicated that complex spikes are not predominantly predicated on stimulus history. Our realistic network model of the inferior olive explains the experimental observations via continuous phase modulations of the subthreshold oscillations under the influence of synaptic fluctuations. We conclude that complex spike activity emerges from a quasiperiodic rhythm that is stabilized by electrotonic coupling between its dendrites, yet dynamically influenced by the status of their synaptic inputs.
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Affiliation(s)
- Mario Negrello
- Department of Neuroscience, Erasmus MC, Rotterdam, the Netherlands
- * E-mail: (MN); (LWJB); (CIDZ)
| | - Pascal Warnaar
- Department of Neuroscience, Erasmus MC, Rotterdam, the Netherlands
| | - Vincenzo Romano
- Department of Neuroscience, Erasmus MC, Rotterdam, the Netherlands
| | - Cullen B. Owens
- Department of Neuroscience, Erasmus MC, Rotterdam, the Netherlands
| | - Sander Lindeman
- Department of Neuroscience, Erasmus MC, Rotterdam, the Netherlands
| | | | - Jochen K. Spanke
- Department of Neuroscience, Erasmus MC, Rotterdam, the Netherlands
| | - Laurens W. J. Bosman
- Department of Neuroscience, Erasmus MC, Rotterdam, the Netherlands
- * E-mail: (MN); (LWJB); (CIDZ)
| | - Chris I. De Zeeuw
- Department of Neuroscience, Erasmus MC, Rotterdam, the Netherlands
- Netherlands Institute for Neuroscience, Royal Academy of Arts and Sciences, Amsterdam, the Netherlands
- * E-mail: (MN); (LWJB); (CIDZ)
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Abstract
The nervous system processes phenomenal amounts of information. This processing must be conducted efficiently. In telecommunications systems, efficiency is increased by transmitting multiple signals through a single communication channel, or multiplexing. Neurons also multiplex. Here, we demonstrate a strategy for multiplexing different features of aperiodic stimuli: Cortical neurons use the rate of asynchronous spiking to encode stimulus intensity while using the timing of synchronous spikes to encode abrupt changes in stimulus intensity. This is possible because high-contrast features (e.g., edges) evoke spikes that transiently synchronize across neurons, whereas low-contrast features evoke sustained asynchronous spiking whose rate is proportional to stimulus intensity. Differentially synchronized spiking evoked in the same neurons by different stimulus features enables the formation of multiplexed representations. Multiplexing refers to the simultaneous encoding of two or more signals. Neurons have been shown to multiplex, but different stimuli require different multiplexing strategies. Whereas the frequency and amplitude of periodic stimuli can be encoded by the timing and rate of the same spikes, natural scenes, which comprise areas over which intensity varies gradually and sparse edges where intensity changes abruptly, require a different multiplexing strategy. Recording in vivo from neurons in primary somatosensory cortex during tactile stimulation, we found that stimulus onset and offset (edges) evoked highly synchronized spiking, whereas other spikes in the same neurons occurred asynchronously. Stimulus intensity modulated the rate of asynchronous spiking, but did not affect the timing of synchronous spikes. From this, we hypothesized that spikes driven by high- and low-contrast stimulus features can be distinguished on the basis of their synchronization, and that differentially synchronized spiking can thus be used to form multiplexed representations. Applying a Bayesian decoding method, we verified that information about high- and low-contrast features can be recovered from an ensemble of model neurons receiving common input. Equally good decoding was achieved by distinguishing synchronous from asynchronous spikes and applying reverse correlation methods separately to each spike type. This result, which we verified with patch clamp recordings in vitro, demonstrates that neurons receiving common input can use the rate of asynchronous spiking to encode the intensity of low-contrast features while using the timing of synchronous spikes to encode the occurrence of high-contrast features. We refer to this strategy as synchrony-division multiplexing.
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Patel MJ. Effects of Adaptation on Discrimination of Whisker Deflection Velocity and Angular Direction in a Model of the Barrel Cortex. Front Comput Neurosci 2018; 12:45. [PMID: 29946250 PMCID: PMC6006271 DOI: 10.3389/fncom.2018.00045] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/13/2017] [Accepted: 05/25/2018] [Indexed: 11/17/2022] Open
Abstract
Two important stimulus features represented within the rodent barrel cortex are velocity and angular direction of whisker deflection. Each cortical barrel receives information from thalamocortical (TC) cells that relay information from a single whisker, and TC input is decoded by barrel regular-spiking (RS) cells through a feedforward inhibitory architecture (with inhibition delivered by cortical fast-spiking or FS cells). TC cells encode deflection velocity through population synchrony, while deflection direction is encoded through the distribution of spike counts across the TC population. Barrel RS cells encode both deflection direction and velocity with spike rate, and are divided into functional domains by direction preference. Following repetitive whisker stimulation, system adaptation causes a weakening of synaptic inputs to RS cells and diminishes RS cell spike responses, though evidence suggests that stimulus discrimination may improve following adaptation. In this work, I construct a model of the TC, FS, and RS cells comprising a single barrel system—the model incorporates realistic synaptic connectivity and dynamics and simulates both angular direction (through the spatial pattern of TC activation) and velocity (through synchrony of the TC population spikes) of a deflection of the primary whisker, and I use the model to examine direction and velocity selectivity of barrel RS cells before and after adaptation. I find that velocity and direction selectivity of individual RS cells (measured over multiple trials) sharpens following adaptation, but stimulus discrimination using a simple linear classifier by the RS population response during a single trial (a more biologically meaningful measure than single cell discrimination over multiple trials) exhibits strikingly different behavior—velocity discrimination is similar both before and after adaptation, while direction classification improves substantially following adaptation. This is the first model, to my knowledge, that simulates both whisker deflection velocity and angular direction and examines the ability of the RS population response to pinpoint both stimulus features within the context of adaptation.
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Affiliation(s)
- Mainak J Patel
- Department of Mathematics, College of William and Mary, Williamsburg, VA, United States
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Spiking and Excitatory/Inhibitory Input Dynamics of Barrel Cells in Response to Whisker Deflections of Varying Velocity and Angular Direction. Neuroscience 2018; 369:15-28. [PMID: 29122591 DOI: 10.1016/j.neuroscience.2017.10.044] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/05/2017] [Revised: 10/29/2017] [Accepted: 10/30/2017] [Indexed: 11/20/2022]
Abstract
The spiking of barrel regular-spiking (RS) cells is tuned for both whisker deflection direction and velocity. Velocity tuning arises due to thalamocortical (TC) synchrony (but not spike quantity) varying with deflection velocity, coupled with feedforward inhibition, while direction selectivity is not fully understood, though may be due partly to direction tuning of TC spiking. Data show that as deflection direction deviates from the preferred direction of an RS cell, excitatory input to the RS cell diminishes minimally, but temporally shifts to coincide with the time-lagged inhibitory input. This work constructs a realistic large-scale model of a barrel; model RS cells exhibit velocity and direction selectivity due to TC input dynamics, with the experimentally observed sharpening of direction tuning with decreasing velocity. The model puts forth the novel proposal that RS→RS synapses can naturally and simply account for the unexplained direction dependence of RS cell inputs - as deflection direction deviates from the preferred direction of an RS cell, and TC input declines, RS→RS synaptic transmission buffers the decline in total excitatory input and causes a shift in timing of the excitatory input peak from the peak in TC input to the delayed peak in RS input. The model also provides several experimentally testable predictions on the velocity dependence of RS cell inputs. This model is the first, to my knowledge, to study the interaction of direction and velocity and propose physiological mechanisms for the stimulus dependence in the timing and amplitude of RS cell inputs.
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Gupta N, Singh SS, Stopfer M. Oscillatory integration windows in neurons. Nat Commun 2016; 7:13808. [PMID: 27976720 PMCID: PMC5171764 DOI: 10.1038/ncomms13808] [Citation(s) in RCA: 22] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/08/2016] [Accepted: 11/02/2016] [Indexed: 11/09/2022] Open
Abstract
Oscillatory synchrony among neurons occurs in many species and brain areas, and has been proposed to help neural circuits process information. One hypothesis states that oscillatory input creates cyclic integration windows: specific times in each oscillatory cycle when postsynaptic neurons become especially responsive to inputs. With paired local field potential (LFP) and intracellular recordings and controlled stimulus manipulations we directly test this idea in the locust olfactory system. We find that inputs arriving in Kenyon cells (KCs) sum most effectively in a preferred window of the oscillation cycle. With a computational model, we show that the non-uniform structure of noise in the membrane potential helps mediate this process. Further experiments performed in vivo demonstrate that integration windows can form in the absence of inhibition and at a broad range of oscillation frequencies. Our results reveal how a fundamental coincidence-detection mechanism in a neural circuit functions to decode temporally organized spiking.
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Affiliation(s)
- Nitin Gupta
- National Institute of Child Health and Human Development, National Institutes of Health, Bethesda, Maryland 20892, USA.,Department of Biological Sciences and Bioengineering, Indian Institute of Technology Kanpur, Kanpur 208016, India
| | - Swikriti Saran Singh
- Department of Biological Sciences and Bioengineering, Indian Institute of Technology Kanpur, Kanpur 208016, India
| | - Mark Stopfer
- National Institute of Child Health and Human Development, National Institutes of Health, Bethesda, Maryland 20892, USA
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Liu R, Patel M, Joshi B. Encoding whisker deflection velocity within the rodent barrel cortex using phase-delayed inhibition. J Comput Neurosci 2014; 37:387-401. [DOI: 10.1007/s10827-014-0535-3] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/24/2014] [Revised: 09/23/2014] [Accepted: 09/26/2014] [Indexed: 11/30/2022]
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Dynamic circuit motifs underlying rhythmic gain control, gating and integration. Nat Neurosci 2014; 17:1031-9. [DOI: 10.1038/nn.3764] [Citation(s) in RCA: 251] [Impact Index Per Article: 25.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/20/2014] [Accepted: 06/16/2014] [Indexed: 12/12/2022]
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