Gain Modulation of Neuronal Responses by Subtractive and Divisive Mechanisms of Inhibition

2009 ◽  
Vol 101 (2) ◽  
pp. 958-968 ◽  
Author(s):  
Asli Ayaz ◽  
Frances S. Chance
Keyword(s):  
Gain Control ◽  
Synaptic Activity ◽  
Response Threshold ◽  
Gain Modulation ◽  
Neuronal Responses ◽  
Control Effect ◽  
Tuning Curves ◽  
Mechanism Of Inhibition ◽  
Multiplicative Effect ◽  
Input Gain

Gain modulation of neuronal responses is widely observed in the cerebral cortex of both anesthetized and behaving animals. Does this multiplicative effect on neuronal tuning curves require underlying multiplicative mechanisms of integration? We compare the effects of a divisive mechanism of inhibition (noisy excitatory and inhibitory synaptic inputs) with the effects of two subtractive mechanisms (shunting conductance and hyperpolarizing current) on the tuning curves of a model cortical neuron. We find that, although the effects of subtractive inhibition can appear nonlinear, they are accompanied by a change in response threshold and are best described as a vertical shift along the response axis. Increasing noisy synaptic activity divisively scales the model responses, reproducing a response-gain control effect. When mutual inhibition between subpopulations of local neurons is included, the model exhibits a gain modulation effect that is better described as input-gain control. We apply these findings to experimental data by examining how noisy synaptic input may underlie divisive surround suppression and attention-driven gain modulation of neuronal responses in the visual system.

Quantitative comparison of inhibition of visceral and cutaneous spinal nociceptive transmission from the midbrain and medulla in the rat

1987 ◽  
Vol 58 (4) ◽  
pp. 850-865 ◽  
Author(s):  
T. J. Ness ◽  
G. F. Gebhart
Keyword(s):  
Spinal Cord ◽  
Gain Control ◽  
Neuronal Responses ◽  
Spinal Neurons ◽  
Descending Inhibition ◽  
Colorectal Distension ◽  
Mean Intensity ◽  
Nociceptive Transmission ◽  
Plantar Surface ◽  
The Mean

1. The descending inhibition of neuronal responses by focal electrical stimulation or glutamate microinjections in the periaqueductal gray (PAG) or rostral ventromedial medulla (RVM) was quantitatively studied on 61 spinal neurons in halothane-N2O-anesthetized paralyzed rats. Thirty-six neurons were located in the medial L6-S1 spinal cord and were consistently and reproducibly excited by distension of the descending colon and rectum (75 mmHg). Twenty-five other neurons were located in the dorsal horn of spinal segments L3-L5 and were consistently and reproducibly excited by radiant heating (50 degrees C) of the glabrous skin of the plantar surface of the left (ipsilateral) hind foot. 2. The inhibition of neuronal responses to colorectal distension by stimulation in the PAG or RVM differed quantitatively when examined on the same spinal neurons. Inhibition of neuronal responses to distension occurred at a lower mean threshold of stimulation in the RVM than in the PAG. The mean intensity of stimulation in the RVM producing an attenuation to 50% of the control response to colorectal distension (75 mmHg, 20 s) was significantly lower than the mean intensity of stimulation in the PAG producing a 50% attenuation of the same spinal units. The mean magnitude of inhibition produced by stimulation in the RVM was significantly greater than that produced on the same spinal units by the same intensity of stimulation in the PAG. However, stimulation in the RVM and PAG produced the same mean percent change in inhibition per 25-microA increase in the intensity of stimulation. Thus the slopes of the lines of recruitment of descending inhibition from the PAG and RVM as a function of increasing intensities of stimulation are the same; the lines of recruitment of inhibition are parallel. These findings are virtually identical to those found by others in studies of modulation of neuronal responses to noxious heating of the skin. 3. Neuronal intensity coding to both graded heating of the hindfoot and graded colorectal distension was montonus and accelerating and could be expressed as linear stimulus-response functions (SRFs) in the temperature and pressure ranges studied (46-52 degrees C, 25-100 mmHg). Stimulation in the PAG modulated the SRFs differently than did stimulation in the RVM. Stimulation in the PAG decreased the slope of the SRFs without affecting the units' thresholds of response, thus influencing the gain control of both cutaneous and visceral nociception in the spinal cord.(ABSTRACT TRUNCATED AT 400 WORDS)

A Mechanism for Neuronal Gain Control by Descending Pathways

1994 ◽  
Vol 6 (2) ◽  
pp. 242-254 ◽  
Author(s):  
Mark E. Nelson
Keyword(s):  
Gain Control ◽  
Membrane Conductance ◽  
Neural Model ◽  
Adaptive Signal Processing ◽  
Synaptic Activity ◽  
Weakly Electric Fish ◽  
Exact Nature ◽  
Activity Levels ◽  
Descending Pathways ◽  
Target Neuron

Many implementations of adaptive signal processing in the nervous system are likely to require a mechanism for gain control at the single neuron level. To properly adjust the gain of an individual neuron, it may be necessary to use information carried by neurons in other parts of the system. The ability to adjust the gain of neurons in one part of the brain, using control signals arising from another, has been observed in the electrosensory system of weakly electric fish, where descending pathways to a first-order sensory nucleus have been shown to influence the gain of its output neurons. Although the neural circuitry associated with this system is well studied, the exact nature of the gain control mechanism is not fully understood. In this paper, we propose a mechanism based on the regulation of total membrane conductance via synaptic activity on descending pathways. Using a simple neural model, we show how the activity levels of paired excitatory and inhibitory control pathways can regulate the gain and baseline excitation of a target neuron.

scholarly journals Unifying Temporal Phenomena in Human Visual Cortex

2017 ◽  
Author(s):  
Jingyang Zhou ◽  
Noah C. Benson ◽  
Kendrick Kay ◽  
Jonathan Winawer
Keyword(s):  
Visual Cortex ◽  
Receptive Field ◽  
Temporal Dynamics ◽  
Gain Control ◽  
Spatial Vision ◽  
Research Area ◽  
Neuronal Responses ◽  
Stimulus Contrast ◽  
Temporal Properties ◽  
Cortical Responses

AbstractNeuronal responses in visual cortex show a diversity of complex temporal properties. These properties include sub-additive temporal summation, response reduction with repeated or sustained stimuli (adaptation), and slower dynamics at low stimulus contrast. Here, we hypothesize that these seemingly disparate effects can be explained by a single, shared computational mechanism. We propose a model consisting of a linear stage, followed by history-dependent gain control. The model accounts for these various temporal phenomena, tested against an unusually diverse set of measurements - intracranial electrodes in patients, fMRI, and macaque single unit spiking. The model further enables us to uncover a systematic and rich variety of temporal encoding strategies across visual cortex: First, temporal receptive field shape differs both across and within visual field maps. Second, later visual areas show more rapid and pronounced adaptation. Our study provides a new framework to understand the transformation between visual input and dynamical cortical responses.Author SummaryThe nervous system extracts meaning from the distribution of light over space and time. Spatial vision has been a highly successful research area, and the spatial receptive field has served as a fundamental and unifying concept that spans perception, computation, and physiology. While there has also been a large interest in temporal vision, the temporal domain has lagged the spatial domain in terms of quantitative models of how signals are transformed across the visual hierarchy. Here we present a model of temporal dynamics of neuronal responses in human cerebral cortex. We show that the model can accurately predict responses at the millisecond scale using intracortical electrodes in patient volunteers, and that the same model generalizes to multiple types of other measurements, including functional MRI and action potentials from monkey cortex. Further, we show that a single model can account for a variety of temporal phenomena, including short-term adaptation and slower dynamics at low stimulus contrast. By developing a computational model and showing that it successfully generalizes across measurement types, cortical areas, and stimuli, we provide new insights into how time-varying images are encoded and transformed into dynamic cortical responses.

scholarly journals Enhanced representation of natural sound sequences in the ventral auditory midbrain

2019 ◽  
Author(s):  
Eugenia González-Palomares ◽  
Luciana López-Jury ◽  
Francisco García-Rosales ◽  
Julio C. Hechavarria
Keyword(s):  
Mutual Information ◽  
Spectral Composition ◽  
Neuronal Responses ◽  
Auditory Midbrain ◽  
Low Frequencies ◽  
High Frequencies ◽  
Tuning Curves ◽  
Motor Behaviors ◽  
Acoustic Stimuli ◽  
Sensory Map

SummaryThe auditory midbrain (inferior colliculus, IC) plays an important role in sound processing, acting as hub for acoustic information extraction and for the implementation of fast audio-motor behaviors. IC neurons are topographically organized according to their sound frequency preference: dorsal IC regions encode low frequencies while ventral areas respond best to high frequencies, a type of sensory map defined as tonotopy. Tonotopic maps have been studied extensively using artificial stimuli (pure tones) but our knowledge of how these maps represent information about sequences of natural, spectro-temporally rich sounds is sparse. We studied this question by conducting simultaneous extracellular recordings across IC depths in awake bats (Carollia perspicillata) that listened to sequences of natural communication and echolocation sounds. The hypothesis was that information about these two types of sound streams is represented at different IC depths since they exhibit large differences in spectral composition, i.e. echolocation covers the high frequency portion of the bat soundscape (> 45 kHz), while communication sounds are broadband and carry most power at low frequencies (20-25 kHz). Our results showed that mutual information between neuronal responses and acoustic stimuli, as well as response redundancy in pairs of neurons recorded simultaneously, increase exponentially with IC depth. The latter occurs regardless of the sound type presented to the bats (echolocation or communication). Taken together, our results indicate the existence of mutual information and redundancy maps at the midbrain level whose response cannot be predicted based on the frequency composition of natural sounds and classic neuronal tuning curves.

Responses of Neurons in the Rat's Ventral Nucleus of the Lateral Lemniscus to Monaural and Binaural Tone Bursts

2006 ◽  
Vol 95 (4) ◽  
pp. 2501-2512 ◽  
Author(s):  
Huiming Zhang ◽  
Jack B. Kelly
Keyword(s):  
Ampa Receptor ◽  
Frequency Tuning ◽  
Synaptic Activity ◽  
Temporal Response ◽  
Lateral Lemniscus ◽  
Tuning Curves ◽  
Temporal Firing ◽  
Excitatory Responses ◽  
Ventral Nucleus ◽  
Sustained Responses

Responses to monaural and binaural tone bursts were recorded from neurons in the rat's ventral nucleus of the lateral lemniscus (VNLL). Most of the neurons (55%) had V- or U-shaped frequency-tuning curves with a single clearly defined characteristic frequency (CF). However, many neurons had more complex, multipeaked tuning curves (37%), or other patterns (8%). Temporal firing patterns included both onset and sustained responses to contralateral tone bursts. Onset and sustained responses were distributed along the dorsoventral length of VNLL with no indication of segregation into different regions. Onset neurons had shorter average first-spike latencies than neurons with sustained responses (means, 8.3 vs. 14.8 ms). They also had less jitter, as reflected in the SD of first-spike latencies, than neurons with sustained responses (means, 0.59 and 4.2 ms, respectively). The extent of jitter decreased with an increase in stimulus intensity for neurons with sustained responses, but remained unchanged for onset neurons tested over the same range. Many neurons had binaural responses, primarily of the excitatory/inhibitory (EI) type, widely distributed along the dorsoventral extent of VNLL. Local application of the AMPA receptor antagonist NBQX reduced excitatory responses, indicating that responses were dependent on synaptic activity and not recorded from passing fibers. The results show that many neurons in VNLL have a precision of timing that is well suited for processing auditory temporal information. In the rat, these neurons are intermingled among cells with less precise temporal response features and include cells with binaural as well as monaural responses.

scholarly journals Spectral response patterns of auditory cortex neurons to harmonic complex tones in alert monkey (Macaca mulatta)

1990 ◽  
Vol 64 (1) ◽  
pp. 282-298 ◽  
Author(s):  
D. W. Schwarz ◽  
R. W. Tomlinson
Keyword(s):  
Receptive Field ◽  
Auditory Cortex ◽  
Pure Tone ◽  
Response Pattern ◽  
Response Patterns ◽  
Neuronal Responses ◽  
Harmonic Complex ◽  
Tuning Curves ◽  
Complex Tones ◽  
Pure Tones

1. The auditory cortex in the superior temporal region of the alert rhesus monkey was explored for neuronal responses to pure and harmonic complex tones and noise. The monkeys had been previously trained to recognize the similarity between harmonic complex tones with and without fundamentals. Because this suggested that they could preceive the pitch of the lacking fundamental similarly to humans, we searched for neuronal responses relevant to this perception. 2. Combination-sensitive neurons that might explain pitch perception were not found in the surveyed cortical regions. Such neurons would exhibit similar responses to stimuli with similar periodicities but differing spectral compositions. The fact that no neuron with responses to a fundamental frequency responded also to a corresponding harmonic complex missing the fundamental indicates that cochlear distortion products at the fundamental may not have been responsible for missing fundamental-pitch perception in these monkeys. 3. Neuronal responses can be expressed as relatively simple filter functions. Neurons with excitatory response areas (tuning curves) displayed various inhibitory sidebands at lower and/or higher frequencies. Thus responses varied along a continuum of combined excitatory and inhibitory filter functions. 4. Five elementary response classes along this continuum are presented to illustrate the range of response patterns. 5. “Filter (F) neurons” had little or no inhibitory sidebands and responded well when any component of a complex tone entered its pure-tone receptive field. Bandwidths increased with intensity. Filter functions of these neurons were thus similar to cochlear nerve-fiber tuning curves. 6. ”High-resolution filter (HRF) neurons” displayed narrow tuning curves with narrowband widths that displayed little growth with intensity. Such cells were able to resolve up to the lowest seven components of harmonic complex tones as distinct responses. They also responded well to wideband stimuli. 7. “Fundamental (F0) neurons” displayed similar tuning bandwidths for pure tones and corresponding fundamentals of harmonic complexes. This response pattern was due to lower harmonic complexes. This response pattern was due to lower inhibitory sidebands. Thus these cells cannot respond to missing fundamentals of harmonic complexes. Only physically present components in the pure-tone receptive field would excite such neurons. 8. Cells with no or very weak responses to pure tones or other narrowband stimuli responded well to harmonic complexes or wideband noise.(ABSTRACT TRUNCATED AT 400 WORDS)

scholarly journals Using computer simulations to determine the limitations of dynamic clamp stimuli applied at the soma in mimicking distributed conductance sources

2011 ◽  
Vol 105 (5) ◽  
pp. 2610-2624 ◽  
Author(s):  
Risa J. Lin ◽  
Dieter Jaeger
Keyword(s):  
Computer Simulations ◽  
Dendritic Tree ◽  
Cell Types ◽  
Cerebellar Nuclei ◽  
Realistic Model ◽  
Pattern Generation ◽  
Synaptic Activity ◽  
Dynamic Clamp ◽  
Neuronal Responses ◽  
Cell Type

In previous studies we used the technique of dynamic clamp to study how temporal modulation of inhibitory and excitatory inputs control the frequency and precise timing of spikes in neurons of the deep cerebellar nuclei (DCN). Although this technique is now widely used, it is limited to interpreting conductance inputs as being location independent; i.e., all inputs that are biologically distributed across the dendritic tree are applied to the soma. We used computer simulations of a morphologically realistic model of DCN neurons to compare the effects of purely somatic vs. distributed dendritic inputs in this cell type. We applied the same conductance stimuli used in our published experiments to the model. To simulate variability in neuronal responses to repeated stimuli, we added a somatic white current noise to reproduce subthreshold fluctuations in the membrane potential. We were able to replicate our dynamic clamp results with respect to spike rates and spike precision for different patterns of background synaptic activity. We found only minor differences in the spike pattern generation between focal or distributed input in this cell type even when strong inhibitory or excitatory bursts were applied. However, the location dependence of dynamic clamp stimuli is likely to be different for each cell type examined, and the simulation approach developed in the present study will allow a careful assessment of location dependence in all cell types.

scholarly journals Learning to represent continuous variables in heterogeneous neural networks

2021 ◽  
Author(s):  
Ran Darshan ◽  
Alexander Rivkind
Keyword(s):  
Neural Networks ◽  
Complex Geometry ◽  
Continuous Variables ◽  
Neuronal Responses ◽  
Tuning Curves ◽  
Representational Space ◽  
Small Set ◽  
Neuronal Representation ◽  
High Level ◽  
The Brain

Manifold attractors are a key framework for understanding how continuous variables, such as position or head direction, are encoded in the brain. In this framework, the variable is represented along a continuum of persistent neuronal states which forms a manifold attactor. Neural networks with symmetric synaptic connectivity that can implement manifold attractors have become the dominant model in this framework. In addition to a symmetric connectome, these networks imply homogeneity of individual-neuron tuning curves and symmetry of the representational space; these features are largely inconsistent with neurobiological data. Here, we developed a theory for computations based on manifold attractors in trained neural networks and show how these manifolds can cope with diverse neuronal responses, imperfections in the geometry of the manifold and a high level of synaptic heterogeneity. In such heterogeneous trained networks, a continuous representational space emerges from a small set of stimuli used for training. Furthermore, we find that the network response to external inputs depends on the geometry of the representation and on the level of synaptic heterogeneity in an analytically tractable and interpretable way. Finally, we show that a too complex geometry of the neuronal representation impairs the attractiveness of the manifold and may lead to its destabilization. Our framework reveals that continuous features can be represented in the recurrent dynamics of heterogeneous networks without assuming unrealistic symmetry. It suggests that the representational space of putative manifold attractors in the brain dictates the dynamics in their vicinity.

scholarly journals Front-end Weber-Fechner gain control enhances the fidelity of combinatorial odor coding

2018 ◽  
Author(s):  
Nirag Kadakia ◽  
Thierry Emonet
Keyword(s):  
Scaling Law ◽  
Gain Control ◽  
Vital Role ◽  
Biophysical Model ◽  
Natural Environments ◽  
Odor Coding ◽  
Tuning Curves ◽  
Front End ◽  
Receptor Neurons ◽  
Odor Signals

Odor identity is encoded by spatiotemporal patterns of activity in olfactory receptor neurons (ORNs). In natural environments, the intensity and timescales of odor signals can span several orders of magnitude, and odors can mix with one another, potentially scrambling the combinatorial code mapping neural activity to odor identity. Recent studies have shown that inDrosophila melanogasterthe ORNs that express the olfactory co-receptor Orco scale their gain inversely with mean odor concentration according to the Weber-Fechner Law of psychophysics. Here we use a minimal biophysical model of signal transduction, ORN firing, and signal decoding to investigate the implications of this front-end scaling law for the neural representations of odor identity. We find that Weber-Fechner scaling enhances coding capacity and promotes the reconstruction of odor identity from dynamic odor signals, even in the presence of confounding background odors and rapid intensity fluctuations. We show that these enhancements are further aided by downstream transformations in the antennal lobe and mushroom body. Thus, despite the broad overlap between individual ORN tuning curves, a mechanism of front-end adaptation, when endowed with Weber-Fechner scaling, may play a vital role in preserving representations of odor identity in naturalistic odor landscapes.

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