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Predictive coding models for pain perception
AbstractPain is a complex, multidimensional experience that involves dynamic interactions between sensory-discriminative and affective-emotional processes. Pain experiences have a high degree of variability depending on their context and prior anticipation. Viewing pain perception as a perceptual inference problem, we propose a predictive coding paradigm to characterize evoked and non-evoked pain. We record the local field potentials (LFPs) from the primary somatosensory cortex (S1) and the anterior cingulate cortex (ACC) of freely behaving rats —two regions known to encode the sensory-discriminative and affective-emotio...
Source: Journal of Computational Neuroscience - February 17, 2021 Category: Neuroscience Source Type: research

Comparison of neuronal responses in primate inferior-temporal cortex and feed-forward deep neural network model with regard to information processing of faces
AbstractFeed-forward deep neural networks have better performance in object categorization tasks than other models of computer vision. To understand the relationship between feed-forward deep networks and the primate brain, we investigated representations of upright and inverted faces in a convolutional deep neural network model and compared them with representations by neurons in the monkey anterior inferior-temporal cortex, area TE. We applied principal component analysis to feature vectors in each model layer to visualize the relationship between the vectors of the upright and inverted faces. The vectors of the upright ...
Source: Journal of Computational Neuroscience - February 17, 2021 Category: Neuroscience Source Type: research

Energetics of stochastic BCM type synaptic plasticity and storing of accurate information
This study investigates the energy requirement of information storing in plastic synapses for an extended version of BCM plasticity with a decay term, stochastic noise, and nonlinear dependence of neuron ’s firing rate on synaptic current (adaptation). It is shown that synaptic weights in this model exhibit bistability. In order to analyze the system analytically, it is reduced to a simple dynamic mean-field for a population averaged plastic synaptic current. Next, using the concepts of nonequilib rium thermodynamics, we derive the energy rate (entropy production rate) for plastic synapses and a corresponding Fisher info...
Source: Journal of Computational Neuroscience - February 2, 2021 Category: Neuroscience Source Type: research

Monosynaptic inference via finely-timed spikes
AbstractObservations of finely-timed spike relationships in population recordings have been used to support partial reconstruction of neural microcircuit diagrams. In this approach, fine-timescale components of paired spike train interactions are isolated and subsequently attributed to synaptic parameters. Recent perturbation studies strengthen the case for such an inference, yet the complete set of measurements needed to calibrate statistical models is unavailable. To address this gap, we study features of pairwise spiking in a large-scalein vivo dataset where presynaptic neurons were explicitly decoupled from network act...
Source: Journal of Computational Neuroscience - January 28, 2021 Category: Neuroscience Source Type: research

Correction to: A modeling study of spinal motoneuron recruitment regulated by ionic channels during fictive locomotion
The authors find several printing errors in the equations in the final versions on line and in print proof. However, there were no such errors in the submitted proof. (Source: Journal of Computational Neuroscience)
Source: Journal of Computational Neuroscience - January 28, 2021 Category: Neuroscience Source Type: research

Effects of subthalamic deep brain stimulation on fixational eye movements in Parkinson ’s disease
AbstractMiniature yoked eye movements, fixational saccades, are critical to counteract visual fading. Fixational saccades are followed by a return saccades forming squarewaves. Present in healthy states, squarewaves, if too many or too big, affect visual stability. Parkinson ’s disease (PD), where visual deficits are not uncommon, is associated with the squarewaves that are excessive in number or size. Our working hypothesis is that the basal ganglia are at the epicenter of the abnormal fixational saccades and squarewaves in PD; the effects are manifested through thei r connections to the superior colliculus (affecting s...
Source: Journal of Computational Neuroscience - January 19, 2021 Category: Neuroscience Source Type: research

Noise induced quiescence of epileptic spike generation in patients with epilepsy
In this study we show that epileptic discharges seen on scalp electroencephalographic recordings and background activity are driven at least partly by a common biological noise. Furthermore, our results indicate noise induced quiescence of spike generation which, in analogy with computational models of spiking, indicate spikes to be generated by transitions between semi-stable states of the brain, similar to the generation of epileptic seizure activity. The deepened physiological understanding of spike generation in epilepsy that this study provides could be useful in the electrophysiological assessment of different therap...
Source: Journal of Computational Neuroscience - January 8, 2021 Category: Neuroscience Source Type: research

Modeling suggests combined-drug treatments for disorders impairing synaptic plasticity via shared signaling pathways
AbstractGenetic disorders such as Rubinstein-Taybi syndrome (RTS) and Coffin-Lowry syndrome (CLS) cause lifelong cognitive disability, including deficits in learning and memory. Can pharmacological therapies be suggested that improve learning and memory in these disorders? To address this question, we simulated drug effects within a computational model describing induction of late long-term potentiation (L-LTP). Biochemical pathways impaired in these and other disorders converge on a common target, histone acetylation by acetyltransferases such as CREB binding protein (CBP), which facilitates gene induction necessary for L...
Source: Journal of Computational Neuroscience - November 11, 2020 Category: Neuroscience Source Type: research

Modeling nucleus accumbens
AbstractNucleus accumbens is part of the neural structures required for reward based learning and cognitive processing of motivation. Understanding its cellular dynamics and its role in basal ganglia circuits is important not only in diagnosing behavioral disorders and psychiatric problems as addiction and depression but also for developing therapeutic treatments for them. Building a computational model would expand our comprehension of nucleus accumbens. In this work, we are focusing on establishing a model of nucleus accumbens which has not been considered as much as dorsal striatum in computational neuroscience. We will...
Source: Journal of Computational Neuroscience - November 9, 2020 Category: Neuroscience Source Type: research

Frontal eye field inactivation alters the readout of superior colliculus activity for saccade generation in a task-dependent manner
AbstractSaccades require a spatiotemporal transformation of activity between the intermediate layers of the superior colliculus (iSC) and downstream brainstem burst generator. The dynamic linear ensemble-coding model (Goossens and Van Opstal2006) proposes that each iSC spike contributes a fixed mini-vector to saccade displacement. Although biologically-plausible, this model assumes cortical areas like the frontal eye fields (FEF) simply provide the saccadic goal to be executed by the iSC and brainstem burst generator. However, the FEF and iSC operate in unison during saccades, and a pathway from the FEF to the brainstem bu...
Source: Journal of Computational Neuroscience - November 8, 2020 Category: Neuroscience Source Type: research

Optimal templates for signal extraction by noisy ideal detectors and human observers
We report a targeted analysis of the theoretical prediction for an experimental protocol that maximizes template-matching on the part of human participants. We find indicative evidence to support the theoretical expectation when internal noise is compared across participants, but not within each participant. Our results indicate that implicit knowledge about internal variability in different individuals is reflected by their detection templates; no implicit knowledge is retained for internal-noise fluctuations experienced by a given participant during data collection. The results also indicate that template encoding is con...
Source: Journal of Computational Neuroscience - October 29, 2020 Category: Neuroscience Source Type: research

Altered neuronal excitability in a Hodgkin-Huxley model incorporating channelopathies of the delayed rectifier potassium channel
AbstractChannelopathies involving acquired or genetic modifications of the delayed rectifier K+ channel Kv1.1 include phenotypes characterized by enhanced neuronal excitability. Affected Kv1.1 channels exhibit combinations of altered expression, voltage sensitivity, and rates of activation and deactivation. Computational modeling and analysis can reveal the potential of particular channelopathies to alter neuronal excitability. A dynamical systems approach was taken to study the excitability and underlying dynamical structure of the Hodgkin-Huxley (HH) model of neural excitation as properties of the delayed rectifier K+ ch...
Source: Journal of Computational Neuroscience - October 15, 2020 Category: Neuroscience Source Type: research

A model for the transfer of control from the brain to the spinal cord through synaptic learning
AbstractThe spinal cord is essential to the control of locomotion in legged animals and humans. However, the actual circuitry of the spinal controller remains only vaguely understood. Here we approach this problem from the viewpoint of learning. More precisely, we assume the circuitry evolves through the transfer of control from the brain to the spinal cord, propose a specific learning mechanism for this transfer based on the error between the cord and brain contributions to muscle control, and study the resulting structure of the spinal controller in a simplified neuromuscular model of human locomotion. The model focuses ...
Source: Journal of Computational Neuroscience - October 1, 2020 Category: Neuroscience Source Type: research

Frontotemporal dementia patients exhibit deficits in predictive saccades
AbstractPrediction and time estimation are all but required for motor function in everyday life. In the context of eye movements, for instance, they allow predictive saccades and eye re-acceleration in anticipation of a target re-appearance. While the neural pathways involved are not fully understood, it is known that the frontal lobe plays an important role. As such, neurological disorders that affect it, such as frontotemporal (FTD) dementia, are likely to induce deficits in such movements. In this work, we study the performances of frontotemporal dementia patients in an oculomotor task designed to elicit predictive sacc...
Source: Journal of Computational Neuroscience - September 17, 2020 Category: Neuroscience Source Type: research

Influence of prior and visual information on eye movements in amblyopic children
This study analyzed the characteristics of pursuit and assessed the influence of prior and visual information on eye velocity and saccades in amblyopic and control children, in comparison to adults. Eye movements of 41 children (21 amblyopes and 20 controls) were compared to eye movements of 55 adults (18 amblyopes and 37 controls). Participants were asked to pursue a target moving at a constant velocity. The target was either a ‘standard’ target, with a uniform color intensity, or a ‘noisy’ target, with blurry edges, to mimic the blurriness of an amblyopic eye. Analysis of pursuit patterns showed that the onset wa...
Source: Journal of Computational Neuroscience - September 7, 2020 Category: Neuroscience Source Type: research