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PubMed2006

Getting into shape: optimal ligand gradients for axonal guidance.

During neural development, neurons from downstream, presynaptic regions of the nervous system (such as the retina) send spatially patterned axonal projections to upstream, target regions (the tectum or superior colliculus). A servomechanism model has been proposed to explain the pattern and time-course of axonal growth between these two regions [Honda, H., 1998. Topographic mapping in the retinotectal projection by means of complementary ligand and receptor gradients: a computer simulation study. J. Theor. Biol., 192, 235-246]. Here, we show that a modification of this model incorporating a different criterion for axonal decision-making, called the local optimum rule, is guaranteed to converge to a topographic map under a wide range of conditions encountered during neural development. A theoretical investigation of these conditions leads to new hypotheses regarding map formation.

Animals↗
PubMed2006

Reducing topological defects in self-organizing maps using multiple scale neighborhood functions.

In this paper, we propose a method of reducing topological defects in self-organizing maps (SOMs) using multiple scale neighborhood functions. The multiple scale neighborhood functions are inspired by multiple scale channels in the human visual system. To evaluate the proposed method, we applied it to the traveling salesman problem (TSP), and examined two indexes: the tour length of the solution and the number of kinks in the solution. Consequently, the two indexes are lower for the proposed method. These results indicate that our proposed method has the ability to reduce topological defects.

Algorithms↗
PubMed2006

Symbols are not uniquely human.

Modern semiotics is a branch of logics that formally defines symbol-based communication. In recent years, the semiotic classification of signs has been invoked to support the notion that symbols are uniquely human. Here we show that alarm-calls such as those used by African vervet monkeys (Cercopithecus aethiops), logically satisfy the semiotic definition of symbol. We also show that the acquisition of vocal symbols in vervet monkeys can be successfully simulated by a computer program based on minimal semiotic and neurobiological constraints. The simulations indicate that learning depends on the tutor-predator ratio, and that apprentice-generated auditory mistakes in vocal symbol interpretation have little effect on the learning rates of apprentices (up to 80% of mistakes are tolerated). In contrast, just 10% of apprentice-generated visual mistakes in predator identification will prevent any vocal symbol to be correctly associated with a predator call in a stable manner. Tutor unreliability was also deleterious to vocal symbol learning: a mere 5% of "lying" tutors were able to completely disrupt symbol learning, invariably leading to the acquisition of incorrect associations by apprentices. Our investigation corroborates the existence of vocal symbols in a non-human species, and indicates that symbolic competence emerges spontaneously from classical associative learning mechanisms when the conditioned stimuli are self-generated, arbitrary and socially efficacious. We propose that more exclusive properties of human language, such as syntax, may derive from the evolution of higher-order domains for neural association, more removed from both the sensory input and the motor output, able to support the gradual complexification of grammatical categories into syntax.

Animals↗
PubMed2006

Phantom reflexes: muscle contractions at a frequency not physically present in the input stimuli.

In the motor system, the periodic stimulation of one Ia-afferent input produces reflex muscle contractions at the input frequency. However, we observed that when two Ia monosynaptic reflex-afferent inputs are involved the periodic muscle contractions may occur at a frequency physically not present in the afferent inputs even when these inputs are sub-threshold. How can the muscles respond with such phantom reflex contractions at a frequency physically absent in the sub-threshold Ia-afferent input stimuli? Here we provide an explanation for this phenomenon in the cat spinal cord, that we termed "ghost motor response". We recorded monosynaptic reflexes in the L7 ventral root, intracellular potentials in the motoneurons, and the associated muscular contractions elicited by stimulation of the lateral and medial gastrocnemius nerves. By stimulating with periodic pulses of sub-threshold intensities and distinct frequencies of 2 and 3 Hz the lateral and medial gastrocnemius nerves, respectively, we observed monosynaptic responses and phantom reflex muscle contractions occurring at the fundamental frequency (1 Hz), which was absent in the input stimuli. Thus we observed a reflex ghost motor response at a frequency not physically present in the inputs. We additionally studied the inharmonic case for sub-threshold stimuli and observed muscular contractions occurring at much lower frequencies, which were also conspicuously absent in the inputs. This is the first experimental evidence of a phantom reflex response in the nervous system. The observed behavior was modeled by numerical simulations of a pool of neurons subjected to two different input pulses.

Animals↗
PubMed2006

Reproducing bursting interspike interval statistics of the gustatory cortex.

Cortical neurons in vivo generate highly irregular spike sequences. Recently, it was experimentally found that the local variation of interspike intervals, LV, is nearly constant for every spike sequence for the same neurons. On the contrary, the coefficient of variation, CV, varies over different spike sequences. Here, we first show that these characteristic features are also applicable in bursting spike sequences that are obtained from the rat gustatory cortex. Next, we show that the conventional leaky integrate-and-fire model does not fully account for reproducing these statistical features in data of real bursting spike sequences. We resolve this difficulty by proposing an alternative neuron model which is a reduction of the bursting neuron model involving the persistent sodium current. Our study implies that (1) the characteristic features of CV and LV are the results of the endogenous bursting and (2) the bursting behavior in the gustatory cortex is caused mainly by the persistent sodium current.

Animals↗
PubMed2005

On the estimation of the number of dipole sources in EEG source localization.

OBJECTIVE: The purpose of the present study was to determine the number of the equivalent dipole sources corresponding to the scalp EEG using the information criterion method based on the instantaneous-state modeling. METHODS: A three-concentric-spheres head model was used to represent the head volume conductor. The Powell algorithm was used to solve the inverse problem of estimating the equivalent dipoles from the scalp EEG. The information criterion with different penalty functions was used to determine the dipole number. Computer simulations were conducted to evaluate effects of various parameters on the estimation of dipole number. RESULTS: The present results suggest that the present method is able to estimate the number of equivalent current dipoles (ECDs) from instantaneous scalp EEG measurements, and that increase in the electrode number can improve the accuracy of estimation of the ECD number. For two ECDs, the best performance of estimation with 20% white noise were 85%, 92% and 94%, when 64, 128 and 256 electrodes are used, respectively. When there are 3 ECDs, the present results suggest that using 256 electrodes gave up to 82% estimation accuracy. The present simulation results also indicate that the accuracies of identification are similar when the minimum distance between dipoles is either 1 or 2 cm, which was used in the simulation. It was also found that the different penalty functions used in the information criterion method could have substantial influence on the estimation accuracy. CONCLUSIONS: The present method can estimate the number of ECDs from instantaneous scalp EEG distribution for up to three dipoles. SIGNIFICANCE: The successful estimation of the number of ECDs will play an important role in expanding the applicability of dipole source localization to multiple sources.

Algorithms↗
PubMed2005

Tissue and electrode capacitance reduce neural activation volumes during deep brain stimulation.

OBJECTIVE: The growing clinical acceptance of neurostimulation technology has highlighted the need to accurately predict neural activation as a function of stimulation parameters and electrode design. In this study we evaluate the effects of the tissue and electrode capacitance on the volume of tissue activated (VTA) during deep brain stimulation (DBS). METHODS: We use a Fourier finite element method (Fourier FEM) to calculate the potential distribution in the tissue medium as a function of time and space simultaneously for a range of stimulus waveforms. The extracellular voltages are then applied to detailed multi-compartment cable models of myelinated axons to determine neural activation. Neural activation volumes are calculated as a function of the stimulation parameters and magnitude of the capacitive components of the electrode-tissue interface. RESULTS: Inclusion of either electrode or tissue capacitance reduces the VTA compared to electrostatic simulations in a manner dependent on the capacitance magnitude and the stimulation parameters (amplitude and pulse width). Electrostatic simulations with typical DBS parameter settings (-3 V or -3 mA, 90 micros, 130 Hz) overestimate the VTA by approximately 20% for voltage- or current-controlled stimulation. In addition, strength-duration time constants decrease and more closely match clinical measurements when explicitly accounting for the effects of voltage-controlled stimulation. CONCLUSIONS: Attempts to quantify the VTA from clinical neurostimulation devices should account for the effects of electrode and tissue capacitance. SIGNIFICANCE: DBS has rapidly emerged as an effective treatment for movement disorders; however, little is known about the VTA during therapeutic stimulation. In addition, the influence of tissue and electrode capacitance has been largely ignored in previous models of neural stimulation. The results and methodology of this study provide the foundation for the quantitative analysis of the VTA during clinical neurostimulation.

Algorithms↗
PubMed2005

Differences in potentials and excitability properties in simulated cases of demyelinating neuropathies. Part III. Paranodal internodal demyelination.

OBJECTIVE: The aim of this study is to investigate the potentials (intracellular, extracellular, electrotonic) and excitability properties (strength-duration and charge-duration curves, strength-duration time constants, rheobasic currents, recovery cycles) in progressively greater degrees of uniform reduction (20, 50 and 70%) of the paranodal seal resistance and myelin lamellae along the fibre length. METHODS: Three paranodally internodally systematically demyelinated cases (termed as PISD1, PISD2 and PISD3, respectively) are simulated using our previous double cable model of human motor nerve fibres. RESULTS: The results conform that in the more severely demyelinated cases, the intracellular potentials are with significantly reduced amplitude, prolonged duration and slowed conduction velocity, whereas the electrotonic potentials show abnormally greater increase in the early part of the hyperpolarizing responses. The extracellular potentials indicate increased polyphasia in the PISD3 case. The strength-duration time constants are shorter and the rheobasic currents higher in the demyelinated cases. In the recovery cycles, the demyelinated cases have less refractoriness, greater supernormality and less late subnormality than the normal case. CONCLUSIONS: The uniform reduction of the paranodal seal resistance and myelin thickness along the fibre length has significant effects on the potentials and excitability properties of the simulated demyelinated human motor fibres. Unexpectedly, the PISD fibres behave like paranodally demyelinated ones, since the myelin reduction increases slightly the effect of the paranodal demyelination on the nerve membrane properties. The study shows that the excitability properties in demyelinating neuropathies are much more largely determined by the paranodal changes than by the internodal changes. SIGNIFICANCE: The study provides new and important information about the pathophysiology of human demyelinating neuropathies.

Axons↗
PubMed2005

Entropies for detection of epilepsy in EEG.

The electroencephalogram (EEG) is a representative signal containing information about the condition of the brain. The shape of the wave may contain useful information about the state of the brain. However, the human observer cannot directly monitor these subtle details. Besides, since bio-signals are highly subjective, the symptoms may appear at random in the time scale. Therefore, the EEG signal parameters, extracted and analyzed using computers, are highly useful in diagnostics. The aim of this work is to compare the different entropy estimators when applied to EEG data from normal and epileptic subjects. The results obtained indicate that entropy estimators can distinguish normal and epileptic EEG data with more than 95% confidence (using t-test). The classification ability of the entropy measures is tested using ANFIS classifier. The results are promising and a classification accuracy of about 90% is achieved.

Algorithms↗
PubMed2004

Cortico-striatal circuits and interval timing: coincidence detection of oscillatory processes.

Humans and other animals demonstrate the ability to perceive and respond to temporally relevant information with characteristic behavioral properties. For example, the response time distributions in peak-interval timing tasks are well described by Gaussian functions, and superimpose when scaled by the criterion duration. This superimposition has been referred to as the scalar property and results from the fact that the standard deviation of a temporal estimate is proportional to the duration being timed. Various psychological models have been proposed to account for such responding. These models vary in their success in predicting the temporal control of behavior as well as in the neurobiological feasibility of the mechanisms they postulate. A review of the major interval timing models reveals that no current model is successful on both counts. The neurobiological properties of the basal ganglia, an area known to be necessary for interval timing and motor control, suggests that this set of structures act as a coincidence detector of cortical and thalamic input. The hypothesized functioning of the basal ganglia is similar to the mechanisms proposed in the beat frequency timing model [R.C. Miall, Neural Computation 1 (1989) 359-371], leading to a reevaluation of its capabilities in terms of behavioral prediction. By implementing a probabilistic firing rule, a dynamic response threshold, and adding variance to a number of its components, simulations of the striatal beat frequency model were able to produce output that is functionally equivalent to the expected behavioral response form of peak-interval timing procedures.

Animals↗
PubMed2005

Risky decision making and the anterior cingulate cortex in abstinent drug abusers and nonusers.

Risky decision making is a hallmark behavioral phenotype of drug abuse; thus, an understanding of its biological bases may inform efforts to develop therapies for addictive disorders. A neurocognitive task that measures this function (Rogers Decision-Making Task; RDMT) was paired with measures of regional cerebral perfusion to identify brain regions that may underlie deficits in risky decision making in drug abusers. Subjects were abstinent drug abusers (> or =3 months) and healthy controls who underwent positron emission tomography scans with H(2)(15)O. Drug abusers showed greater risk taking and heightened sensitivity to rewards than control subjects. Both drug abusers and controls exhibited significant activations in a widespread network of brain regions, primarily in the frontal cortex, previously implicated in decision-making tasks. The only significant group difference in brain activation, however, was found in the left pregenual anterior cingulate cortex, with drug abusers exhibiting less task-related activation than control subjects. There were no significant correlations between neural activity and task performance within the control group. In the drug abuse group, on the other hand, increased risky choices on the RDMT negatively correlated with activation in the right hippocampus, left anterior cingulate gyrus, left medial orbitofrontal cortex, and left parietal lobule, and positively correlated with activation in the right insula. Drug abuse severity was related positively to right medial orbitofrontal activity. Attenuated activation of the pregenual ACC in the drug abusers relative to the controls during performance on the RDMT may underlie the abusers' tendency to choose risky outcomes.

Adult↗
PubMed2006

Direction selectivity of simple cells in the primary visual cortex: comparison of two alternative mathematical models. I: response to drifting gratings.

Two models of a single hypercolumn in the primary visual cortex are presented, and used for the analysis of direction selectivity in simple cells. The two models differ as to the arrangement of inhibitory connections: in the first ("antiphase model") inhibition is in phase opposition with excitation, but with a similar orientation tuning; in the second ("in-phase model"), inhibition is in phase with excitation, but with broader orientation tuning. Simulation results, performed by using drifting gratings with different orientations, and different spatial and temporal frequencies, show that both models are able to explain the origin of direction preference of simple cells.

Computer Simulation↗
PubMed2005

Geometric diffusions for the analysis of data from sensor networks.

Harmonic analysis on manifolds and graphs has recently led to mathematical developments in the field of data analysis. The resulting new tools can be used to compress and analyze large and complex data sets, such as those derived from sensor networks or neuronal activity datasets, obtained in the laboratory or through computer modeling. The nature of the algorithms (based on diffusion maps and connectivity strengths on graphs) possesses a certain analogy with neural information processing, and has the potential to provide inspiration for modeling and understanding biological organization in perception and memory formation.

Algorithms↗
PubMed2005

A cognitive architecture that combines internal simulation with a global workspace.

This paper proposes a brain-inspired cognitive architecture that incorporates approximations to the concepts of consciousness, imagination, and emotion. To emulate the empirically established cognitive efficacy of conscious as opposed to non-conscious information processing in the mammalian brain, the architecture adopts a model of information flow from global workspace theory. Cognitive functions such as anticipation and planning are realised through internal simulation of interaction with the environment. Action selection, in both actual and internally simulated interaction with the environment, is mediated by affect. An implementation of the architecture is described which is based on weightless neurons and is used to control a simulated robot.

Brain↗
PubMed2005

Anticipating epileptic seizures: from mathematics to clinical applications.

The study of dynamical changes in the neural activity preceding an epileptic seizure allows the characterization of a preictal state several minutes prior to seizure onset. This opens new perspectives for studying the mechanisms of ictogenesis as well as for possible therapeutic interventions that represent a major breakthrough. In this review we present and discuss the results from our group in this domain using nonlinear analysis of brain signals, as well as its limitation and open questions.

Animals↗
PubMed2004

Does past pain influence current pain: biological and psychosocial models of sex differences.

Previous studies have generally indicated sizeable sex differences for both laboratory pain reactivity and clinical pain reports. Numerous biological and psychosocial models have been invoked to account for these findings, but the laboratory and clinical findings have generally been examined in isolation. This paper reviews data which show a relationship between past clinical pain experiences and current responses to experimentally induced pain. Individuals with a greater pain history tend to show lower pain tolerance. Since women often have high pain experience levels and lower pain tolerance, one might ask whether the two factors are related. We review several models, based upon concepts of neonatal differences in pain reactivity, hypervigilance following early pain experiences, and concepts of peripheral and central sensitization or plasticity which might help to bridge the gap between clinical and experimental findings.

Age Factors↗
PubMed2005

Alcohol dependence and gene x environment interaction in emotion regulation: Is serotonin the link?

Alcohol dependence is characterized by frequent, compulsive and uncontrolled consumption of alcohol associated with behavior of maladaption and destruction. It is an etiologically and clinically heterogeneous syndrome, moderately to highly heritable, and caused by interaction of genes and environment. Alcohol dependence is related to other psychiatric diseases by common neurobiological pathways, including those that modulate reward, behavioral control as well as anxiety and stress response. Alcohol induces adaptive changes in brain function providing the basis for tolerance, craving, withdrawal, and emotional disturbance. The differentiation of psychobiological traits of addictive behavior reflecting neurobiological processes is therefore of particular importance for the dissection of the complex genetic susceptibility to alcohol dependence. A central serotonin (5-HT) deficit is thought to be involved in the pathogenesis of alcohol dependence by modulating motivational behavior, neuroadaptive processes, and resulting emotional disturbance. 5-HT-related impulsive, aggressive, and suicidal behavior has been linked to a primordial personality that is susceptible to alcohol dependence. Although variations in many of the genes that encode receptors, enzymes, and transporters of the 5-HT system have been tested as risk factors for alcohol dependence, genetic analyses of 5-HT signaling in alcohol dependence have mainly been focused on the 5-HT transporter (5-HTT) gene. Due to its central role in the fine-tuning serotonergic neurotransmission, a regulatory variant of the 5-HTT, which is associated with anxiety related traits, is not only a key player in the neurobiological mechanism of gene x environment interaction in the etiology of depression, but also contributes to the risk to develop alcohol dependence with antisocial behavior and suicidality. Evidence for a modulatory effect of allelic variation of 5-HTT function on limbic circuit responses to emotional stimuli suggests that genotype-endophenotype correlations may be accessible to molecular functional imaging of the brain. These new developments have broad implications for our understanding how genetic vulnerability to alcohol dependence is manifested in the brain's response to emotional stimuli.

Alcoholism↗
PubMed2004

Generalization as a behavioral window to the neural mechanisms of learning internal models.

In generating motor commands, the brain seems to rely on internal models that predict physical dynamics of the limb and the external world. How does the brain compute an internal model? Which neural structures are involved? We consider a task where a force field is applied to the hand, altering the physical dynamics of reaching. Behavioral measures suggest that as the brain adapts to the field, it maps desired sensory states of the arm into estimates of force. If this neural computation is performed via a population code, i.e., via a set of bases, then activity fields of the bases dictate a generalization function that uses errors experienced in a given state to influence performance in any other state. The patterns of generalization suggest that the bases have activity fields that are directionally tuned, but directional tuning may be bimodal. Limb positions as well as contextual cues multiplicatively modulate the gain of tuning. These properties are consistent with the activity fields of cells in the motor cortex and the cerebellum. We suggest that activity fields of cells in these motor regions dictate the way we represent internal models of limb dynamics.

Biomechanical Phenomena↗