Different aspects of the face are represented in the dynamic firing rate patterns of macaque temporal cortical neurons

1998 ◽  
Vol 31 ◽  
pp. S184
Author(s):  
Yasuko Sugase ◽  
Sigeru Yamane ◽  
Shoogo Ueno ◽  
Kenji Kawano
Keyword(s):  
Firing Rate ◽  
Cortical Neurons ◽  
The Face

scholarly journals Firing rate homeostasis occurs in the absence of neuronal activity-regulated transcription

2019 ◽  
Author(s):  
Kelsey M. Tyssowski ◽  
Katherine C. Letai ◽  
Samuel D. Rendall ◽  
Anastasia Nizhnik ◽  
Jesse M. Gray
Keyword(s):  
Firing Rate ◽  
Neuronal Activity ◽  
Cortical Neurons ◽  
Molecular Mechanisms ◽  
Neuronal Circuits ◽  
Electrode Arrays ◽  
Knock Out ◽  
Firing Rates ◽  
The Face ◽  
Homeostatic Mechanisms

ABSTRACTDespite dynamic inputs, neuronal circuits maintain relatively stable firing rates over long periods. This maintenance of firing rate, or firing rate homeostasis, is likely mediated by homeostatic mechanisms such as synaptic scaling and regulation of intrinsic excitability. Because some of these homeostatic mechanisms depend on transcription of activity-regulated genes, including Arc and Homer1a, we hypothesized that activity-regulated transcription would be required for firing rate homeostasis. Surprisingly, however, we found that cultured mouse cortical neurons grown on multi-electrode arrays homeostatically adapt their firing rates to persistent pharmacological stimulation even when activity-regulated transcription is disrupted. Specifically, we observed firing rate homeostasis Arc knock-out neurons, as well as knock-out neurons lacking activity-regulated transcription factors, AP1 and SRF. Firing rate homeostasis also occurred normally during acute pharmacological blockade of transcription. Thus, firing rate homeostasis in response to increased neuronal activity can occur in the absence of neuronal-activity-regulated transcription.SIGNIFICANCE STATEMENTNeuronal circuits maintain relatively stable firing rates even in the face of dynamic circuit inputs. Understanding the molecular mechanisms that enable this firing rate homeostasis could potentially provide insight into neuronal diseases that present with an imbalance of excitation and inhibition. However, the molecular mechanisms underlying firing rate homeostasis are largely unknown.It has long been hypothesized that firing rate homeostasis relies upon neuronal activity-regulated transcription. For example, a 2012 review (PMID 22685679) proposed it, and a 2014 modeling approach established that transcription could theoretically both measure and control firing rate (PMID 24853940). Surprisingly, despite this prediction, we found that cortical neurons undergo firing rate homeostasis in the absence of activity-regulated transcription, indicating that firing rate homeostasis is controlled by non-transcriptional mechanisms.

scholarly journals Sparse bursts optimize information transmission in a multiplexed neural code

2018 ◽  
Vol 115 (27) ◽  
pp. E6329-E6338 ◽  
Author(s):  
Richard Naud ◽  
Henning Sprekeler
Keyword(s):  
Firing Rate ◽  
Cortical Neurons ◽  
Neural Code ◽  
Spike Timing ◽  
Neural Ensemble ◽  
Multiple Input ◽  
Cortical Hierarchy ◽  
Connectivity Patterns ◽  
Rate Coding

Many cortical neurons combine the information ascending and descending the cortical hierarchy. In the classical view, this information is combined nonlinearly to give rise to a single firing-rate output, which collapses all input streams into one. We analyze the extent to which neurons can simultaneously represent multiple input streams by using a code that distinguishes spike timing patterns at the level of a neural ensemble. Using computational simulations constrained by experimental data, we show that cortical neurons are well suited to generate such multiplexing. Interestingly, this neural code maximizes information for short and sparse bursts, a regime consistent with in vivo recordings. Neurons can also demultiplex this information, using specific connectivity patterns. The anatomy of the adult mammalian cortex suggests that these connectivity patterns are used by the nervous system to maintain sparse bursting and optimal multiplexing. Contrary to firing-rate coding, our findings indicate that the physiology and anatomy of the cortex may be interpreted as optimizing the transmission of multiple independent signals to different targets.

Possible Effects of Depolarizing GABAA Conductance on the Neuronal Input–Output Relationship: A Modeling Study

2005 ◽  
Vol 93 (6) ◽  
pp. 3504-3523 ◽  
Author(s):  
Kenji Morita ◽  
Kunichika Tsumoto ◽  
Kazuyuki Aihara
Keyword(s):  
Firing Rate ◽  
Cortical Neurons ◽  
Reversal Potential ◽  
Pyramidal Cells ◽  
Resting Potential ◽  
Input Output ◽  
Wide Range ◽  
The Relationship

Recent in vitro experiments revealed that the GABAA reversal potential is about 10 mV higher than the resting potential in mature mammalian neocortical pyramidal cells; thus GABAergic inputs could have facilitatory, rather than inhibitory, effects on action potential generation under certain conditions. However, how the relationship between excitatory input conductances and the output firing rate is modulated by such depolarizing GABAergic inputs under in vivo circumstances has not yet been understood. We examine herewith the input–output relationship in a simple conductance-based model of cortical neurons with the depolarized GABAA reversal potential, and show that a tonic depolarizing GABAergic conductance up to a certain amount does not change the relationship between a tonic glutamatergic driving conductance and the output firing rate, whereas a higher GABAergic conductance prevents spike generation. When the tonic glutamatergic and GABAergic conductances are replaced by in vivo–like highly fluctuating inputs, on the other hand, the effect of depolarizing GABAergic inputs on the input–output relationship critically depends on the degree of coincidence between glutamatergic input events and GABAergic ones. Although a wide range of depolarizing GABAergic inputs hardly changes the firing rate of a neuron driven by noncoincident glutamatergic inputs, a certain range of these inputs considerably decreases the firing rate if a large number of driving glutamatergic inputs are coincident with them. These results raise the possibility that the depolarized GABAA reversal potential is not a paradoxical mystery, but is instead a sophisticated device for discriminative firing rate modulation.

Neural Responses to Facial Expression and Face Identity in the Monkey Amygdala

2007 ◽  
Vol 97 (2) ◽  
pp. 1671-1683 ◽  
Author(s):  
K. M. Gothard ◽  
F. P. Battaglia ◽  
C. A. Erickson ◽  
K. M. Spitler ◽  
D. G. Amaral
Keyword(s):  
Facial Expression ◽  
Firing Rate ◽  
Face Processing ◽  
Neural Responses ◽  
Firing Rates ◽  
Face Identity ◽  
Relative Contribution ◽  
The Face ◽  
Face Stimuli ◽  
Human Faces

The amygdala is purported to play an important role in face processing, yet the specificity of its activation to face stimuli and the relative contribution of identity and expression to its activation are unknown. In the current study, neural activity in the amygdala was recorded as monkeys passively viewed images of monkey faces, human faces, and objects on a computer monitor. Comparable proportions of neurons responded selectively to images from each category. Neural responses to monkey faces were further examined to determine whether face identity or facial expression drove the face-selective responses. The majority of these neurons (64%) responded both to identity and facial expression, suggesting that these parameters are processed jointly in the amygdala. Large fractions of neurons, however, showed pure identity-selective or expression-selective responses. Neurons were selective for a particular facial expression by either increasing or decreasing their firing rate compared with the firing rates elicited by the other expressions. Responses to appeasing faces were often marked by significant decreases of firing rates, whereas responses to threatening faces were strongly associated with increased firing rate. Thus global activation in the amygdala might be larger to threatening faces than to neutral or appeasing faces.

Neuronal responses in cat primary auditory cortex to electrical cochlear stimulation. II. Repetition rate coding

1996 ◽  
Vol 75 (3) ◽  
pp. 1283-1300 ◽  
Author(s):  
C. E. Schreiner ◽  
M. W. Raggio
Keyword(s):  
Electrical Stimulation ◽  
Firing Rate ◽  
Repetition Rate ◽  
Cortical Neurons ◽  
Primary Auditory Cortex ◽  
Acoustic Stimulation ◽  
Electrode Spacing ◽  
Bipolar Electrode ◽  
Cochlear Prosthesis ◽  
Cutoff Frequencies

1. Responses of neurons in primary auditory cortex (AI) of the barbiturate-anesthetized adult cat were studied using cochlear stimulation with electrical and acoustic stimuli. Neuronal responses to acoustic stimulation with brief biphasic clicks of the ear ipsilateral to the studied cortical hemisphere were compared with those evoked by electrical stimulation of the contralateral cochlea with brief biphasic electrical pulses delivered via a feline cochlear prosthesis. The contralateral ear was deafened immediately before implantation of the cochlear prosthesis. The feline cochlear prosthesis consisted of four bipolar electrode pairs and was placed in the scala tympani. Two bipolar electrode conditions were used for stimulation: one near radial pair with electrode spacing of 0.25-0.5 mm, and one longitudinal pair with electrode spacing of approximately 6 mm. 2. The firing rates obtained from single- and multiple-neuron recordings were measured as a function of stimulus repetition rate of electrical and acoustic pulses. From period histograms over a recording interval of 1,000 ms, the driven firing rate to repetition rates from 2 to 38 Hz was obtained and repetition rate transfer functions (RRTFs) were constructed. The RRTFs were characterized as low-pass or band-pass filters and several descriptors were obtained, such as the repetition rate producing the highest driven activity, high and low cutoff frequencies 6 dB below maximum firing rate, and maximum firing rate. 3. For a given neuron, the main characteristics of cortical RRTFs obtained with electrical and acoustic cochlear stimulation were quite similar. However, some small but statistically significant differences in the best repetition rate, cutoff frequencies, and maximum firing rate could be observed between the different stimulation modes. The proportion of band-pass RRTFs was larger for electrical stimulation (57%) than for acoustic stimulation (41%). The high cutoff frequencies for electrical stimulation were slightly but consistently higher than for acoustic RRTFs of the same neuron and the maximum firing rate for electrical stimulation was significantly higher than that evoked by ipsilateral acoustic stimulation. 4. The entrainment of cortical neurons to electrical and acoustic pulses was determined and entrainment profiles were constructed. For a given neuron, electrical entrainment profiles showed higher cutoff frequencies than with acoustic stimulation when judged with a fixed entrainment criterion of 0.25 spikes per event. The maximum entrainment seen for electrical stimulation was approximately 20% higher than seen for the same neuron with acoustic stimulation. 5. Correlation analysis of repetition coding and latency parameters revealed several relationships between these response aspects. Most prominent among them was a significant correlation between measures of the response latency and estimates of the ability to follow temporal repetitions for acoustic as well as electrical conditions. 6. Parametric and comparative evaluations of cortical responses to acoustic and electrical cochlear stimulation support the conclusion that the temporal resolution seen in cortical neurons is largely a consequence of central processing mechanisms based on cell and circuit properties and to a lesser degree a consequence of particular spatial and temporal peripheral excitation patterns. The slightly higher temporal resolution found for the electrical stimulation modes suggests that the temporally highly coherent electrical stimulation appears to engage, in a more effective manner, the excitatory/inhibitory mechanisms contributing to the response in AI than acoustic click stimulation with less temporal coherence. (ABSTRACT TRUNCATED)

Functional properties of single neurons in the face primary motor cortex of the primate. II. Relations with trained orofacial motor behavior

1992 ◽  
Vol 67 (3) ◽  
pp. 759-774 ◽  
Author(s):  
G. M. Murray ◽  
B. J. Sessle
Keyword(s):  
Motor Cortex ◽  
Cortical Neurons ◽  
Primary Motor Cortex ◽  
Motor Behavior ◽  
Afferent Input ◽  
Single Neurons ◽  
Tongue Protrusion ◽  
Input And Output ◽  
The Face ◽  
Tongue Movements

1. The previous paper has described in detail the input and output features of single neurons located at sites within primate face motor cortex from which intracortical microstimulation (ICMS, less than or equal to 20 microA) evoked tongue movements at the lowest threshold ("tongue-MI" sites); for comparative purposes, we also reported on the input and output features of a smaller number of neurons recorded at sites from which ICMS could evoke jaw movements ("jaw-MI" sites), facial movements ("face-MI" sites), or, at a few sites, tongue movements and, at the same threshold intensity, either a jaw movement or a facial movement. 2. Our findings of an extensive and diverse representation of sites within face motor cortex of monkeys for the generation of elemental components of tongue movement, and the relatively few sites from which jaw-closing movements could be evoked, were consistent with our recent observations that reversible, cooling-induced inactivation of the face motor cortex severely impaired the performance by monkeys of a tongue-protrusion task but had only relatively minor effects on the performance of a biting task. In an attempt to establish a neuronal correlate for these different behavioral relations, the present study has documented the task-related activities of those single neurons that were characterized in the previous paper in terms of afferent input and ICMS-defined output features. 3. Each task required the development and maintenance by each monkey of a fixed force level for a minimum period of time to obtain a fruit-juice reward. During one or both of these tasks, we characterized the activities of 231 single face motor cortical neurons that were located at the above-mentioned ICMS-defined sites. Neurons were said to be related to a particular task if they showed statistically significant differences in firing rates during the task in comparison with a control pretrial period (PTP). 4. In tongue-MI, there was a significantly higher proportion of neurons (63% of 156 neurons tested) that were related to the tongue-protrusion task than to the biting task (15% of 65). However, in jaw-MI the proportion of neurons that were biting task-related (63% of 19) was significantly higher than the proportion related to the tongue-protrusion task (11% of 9); the proportion of biting task-related neurons at ICMS-defined jaw-closing sites was also higher than that at jaw-opening sites.(ABSTRACT TRUNCATED AT 400 WORDS)

scholarly journals Computing and Stability in Cortical Networks

2004 ◽  
Vol 16 (7) ◽  
pp. 1385-1412 ◽  
Author(s):  
Peter E. Latham ◽  
Sheila Nirenberg
Keyword(s):  
Cortical Neurons ◽  
Unstable State ◽  
Stable States ◽  
Attractor Networks ◽  
Firing Rates ◽  
The Face ◽  
Multiple Stable States ◽  
Background State ◽  
Do So

Cortical neurons are predominantly excitatory and highly interconnected. In spite of this, the cortex is remarkably stable: normal brains do not exhibit the kind of runaway excitation one might expect of such a system. How does the cortex maintain stability in the face of this massive excitatory feedback? More importantly, how does it do so during computations, which necessarily involve elevated firing rates? Here we address these questions in the context of attractor networks—networks that exhibit multiple stable states, or memories. We find that such networks can be stabilized at the relatively low firing rates observed in vivo if two conditions are met: (1) the background state, where all neurons are firing at low rates, is inhibition dominated, and (2) the fraction of neurons involved in a memory is above some threshold, so that there is sufficient coupling between the memory neurons and the background. This allows “dynamical stabilization” of the attractors, meaning feedback from the pool of background neurons stabilizes what would otherwise be an unstable state. We suggest that dynamical stabilization may be a strategy used for a broad range of computations, not just those involving attractors.

scholarly journals Neuronal firing rates diverge during REM and homogenize during non-REM

2016 ◽  
Author(s):  
Hiroyuki Miyawaki ◽  
Brendon Watson ◽  
Kamran Diba
Keyword(s):  
Firing Rate ◽  
Frontal Cortex ◽  
Rem Sleep ◽  
Cortical Neurons ◽  
Nrem Sleep ◽  
Regression To The Mean ◽  
Firing Rates ◽  
The Mean ◽  
High Firing ◽  
Interneuron Activity

AbstractNeurons fire at highly variable innate rates and recent evidence suggests that low and high firing rate neurons display different plasticity and dynamics. Furthermore, recent publications imply possibly differing rate-dependent effects in hippocampus versus neocortex, but those analyses were carried out separately and with possibly important differences. To more effectively synthesize these questions, we analyzed the firing rate dynamics of populations of neurons in both hippocampal CA1 and frontal cortex under one framework that avoids pitfalls of previous analyses and accounts for regression-to-the-mean. We observed remarkably consistent effects across these regions. While rapid eye movement (REM) sleep was marked by decreased hippocampal firing and increased neocortical firing, in both regions firing rates distributions widened during REM due to differential changes in high-firing versus low-firing cells in parallel with increased interneuron activity. In contrast, upon non-REM (NREM) sleep, firing rate distributions narrowed while interneuron firing decreased. Interestingly, hippocampal interneuron activity closely followed the patterns observed in neocortical principal cells rather than the hippocampal principal cells, suggestive of long-range interactions. Following these undulations in variance, the net effect of sleep was a decrease in firing rates. These decreases were greater in lower-firing hippocampal neurons but higher-firing frontal cortical neurons, suggestive of greater plasticity in these cell groups. Our results across two different regions and with statistical corrections indicate that the hippocampus and neocortex show a mixture of differences and similarities as they cycle between sleep states with a unifying characteristic of homogenization of firing during NREM and diversification during REM.Significance StatementMiyawaki and colleagues analyze firing patterns across low-firing and high-firing neurons in the hippocampus and the frontal cortex throughout sleep in a framework that accounts for regression-to-the-mean. They find that in both regions REM sleep activity is relatively dominated by high-firing neurons and increased inhibition, resulting in a wider distribution of firing rates. On the other hand, NREM sleep produces lower inhibition, and results in a more homogenous distribution of firing rates. Integration of these changes across sleep results in net decrease of firing rates with largest drops in low-firing hippocampal pyramidal neurons and high-firing neocortical principal neurons. These findings provide insights into the effects and functions of different sleep stages on cortical neurons.

scholarly journals KCC2 overexpression prevents the paradoxical seizure-promoting action of somatic inhibition

2018 ◽  
Author(s):  
Vincent Magloire ◽  
Jonathan Cornford ◽  
Andreas Lieb ◽  
Dimitri M. Kullmann ◽  
Ivan Pavlov
Keyword(s):  
Potassium Chloride ◽  
Cortical Neurons ◽  
Closed Loop ◽  
Network Activity ◽  
Intracellular Chloride ◽  
Cortical Interneurons ◽  
The Face ◽  
Somatic Inhibition

AbstractAlthough cortical interneurons are apparently well-placed to suppress seizures, several recent reports have highlighted a paradoxical role of parvalbumin-positive perisomatic-targeting (PV+) interneurons in ictogenesis. Here, we use an acute in vivo model of focal cortical seizures in awake behaving mice, together with closed-loop optogenetic manipulation of PV+ interneurons, to investigate their function during seizures. We show that photo-depolarization of PV+ interneurons rapidly switches from an anti-ictal to a pro-ictal effect within a few seconds of seizure initiation. The pro-ictal effect of delayed photostimulation of PV+ interneurons was not shared with dendrite-targeting somatostatin-positive (SOM+) interneurons. We also show that this switch can be prevented by overexpression of the neuronal potassium-chloride co-transporter KCC2 in principal cortical neurons. These results suggest that strategies aimed at improving the ability of principal neurons to maintain intracellular chloride levels in the face of excessive network activity can prevent interneurons from contributing to seizure perpetuation.

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