A Fluctuation-Driven Mechanism for Slow Decision Processes in Reverberant Networks

The spike activity of cells in some cortical areas has been found to be correlated with reaction times and behavioral responses during two-choice decision tasks. These experimental findings have motivated the study of biologically plausible winner-take-all network models, in which strong recurrent excitation and feedback inhibition allow the network to form a categorical choice upon stimulation. Choice formation corresponds in these models to the transition from the spontaneous state of the network to a state where neurons selective for one of the choices fire at a high rate and inhibit the activity of the other neurons. This transition has been traditionally induced by an increase in the external input that destabilizes the spontaneous state of the network and forces its relaxation to a decision state. Here we explore a different mechanism by which the system can undergo such transitions while keeping the spontaneous state stable, based on an escape induced by finite-size noise from the spontaneous state. This decision mechanism naturally arises for low stimulus strengths and leads to exponentially distributed decision times when the amount of noise in the system is small. Furthermore, we show using numerical simulations that mean decision times follow in this regime an exponential dependence on the amplitude of noise. The escape mechanism provides thus a dynamical basis for the wide range and variability of decision times observed experimentally

Retinotopic Maps, Spatial Tuning, and Locations of Human Visual Areas in Surface Coordinates Characterized with Multifocal and Blocked fMRI Designs

The localization of visual areas in the human cortex is typically based on mapping the retinotopic organization with functional magnetic resonance imaging (fMRI). The most common approach is to encode the response phase for a slowly moving visual stimulus and to present the result on an individual's reconstructed cortical surface. The main aims of this study were to develop complementary general linear model (GLM)-based retinotopic mapping methods and to characterize the inter-individual variability of the visual area positions on the cortical surface. We studied 15 subjects with two methods: a 24-region multifocal checkerboard stimulus and a blocked presentation of object stimuli at different visual field locations. The retinotopic maps were based on weighted averaging of the GLM parameter estimates for the stimulus regions. In addition to localizing visual areas, both methods could be used to localize multiple retinotopic regions-of-interest. The two methods yielded consistent retinotopic maps in the visual areas V1, V2, V3, hV4, and V3AB. In the higher-level areas IPS0, VO1, LO1, LO2, TO1, and TO2, retinotopy could only be mapped with the blocked stimulus presentation. The gradual widening of spatial tuning and an increase in the responses to stimuli in the ipsilateral visual field along the hierarchy of visual areas likely reflected the increase in the average receptive field size. Finally, after registration to Freesurfer's surface-based atlas of the human cerebral cortex, we calculated the mean and variability of the visual area positions in the spherical surface-based coordinate system and generated probability maps of the visual areas on the average cortical surface. The inter-individual variability in the area locations decreased when the midpoints were calculated along the spherical cortical surface compared with volumetric coordinates. These results can facilitate both analysis of individual functional anatomy and comparisons of visual cortex topology across studies

Changing Human Visual Field Organization from Early Visual to Extra-Occipital Cortex

BACKGROUND: The early visual areas have a clear topographic organization, such that adjacent parts of the cortical surface represent distinct yet adjacent parts of the contralateral visual field. We examined whether cortical regions outside occipital cortex show a similar organization. METHODOLOGY/PRINCIPAL FINDINGS: The BOLD responses to discrete visual field locations that varied in both polar angle and eccentricity were measured using two different tasks. As described previously, numerous occipital regions are both selective for the contralateral visual field and show topographic organization within that field. Extra-occipital regions are also selective for the contralateral visual field, but possess little (or no) topographic organization. A regional analysis demonstrates that this weak topography is not due to increased receptive field size in extra-occipital areas. CONCLUSIONS/SIGNIFICANCE: A number of extra-occipital areas are identified that are sensitive to visual field location. Neurons in these areas corresponding to different locations in the contralateral visual field do not demonstrate any regular or robust topographic organization, but appear instead to be intermixed on the cortical surface. This suggests a shift from processing that is predominately local in visual space, in occipital areas, to global, in extra-occipital areas. Global processing fits with a role for these extra-occipital areas in selecting a spatial locus for attention and/or eye-movements

Modelling fast forms of visual neural plasticity using a modified second-order motion energy model

The Adelson-Bergen motion energy sensor is well established as the leading model of low-level visual motion sensing in human vision. However, the standard model cannot predict adaptation effects in motion perception. A previous paper Pavan et al.(Journal of Vision 10:1-17, 2013) presented an extension to the model which uses a first-order RC gain-control circuit (leaky integrator) to implement adaptation effects which can span many seconds, and showed that the extended model's output is consistent with psychophysical data on the classic motion after-effect. Recent psychophysical research has reported adaptation over much shorter time periods, spanning just a few hundred milliseconds. The present paper further extends the sensor model to implement rapid adaptation, by adding a second-order RC circuit which causes the sensor to require a finite amount of time to react to a sudden change in stimulation. The output of the new sensor accounts accurately for psychophysical data on rapid forms of facilitation (rapid visual motion priming, rVMP) and suppression (rapid motion after-effect, rMAE). Changes in natural scene content occur over multiple time scales, and multi-stage leaky integrators of the kind proposed here offer a computational scheme for modelling adaptation over multiple time scales. © 2014 Springer Science+Business Media New York

Neurobiological Models of Two-Choice Decision Making Can Be Reduced to a One-Dimensional Nonlinear Diffusion Equation

The response behaviors in many two-alternative choice tasks are well described by so-called sequential sampling models. In these models, the evidence for each one of the two alternatives accumulates over time until it reaches a threshold, at which point a response is made. At the neurophysiological level, single neuron data recorded while monkeys are engaged in two-alternative choice tasks are well described by winner-take-all network models in which the two choices are represented in the firing rates of separate populations of neurons. Here, we show that such nonlinear network models can generally be reduced to a one-dimensional nonlinear diffusion equation, which bears functional resemblance to standard sequential sampling models of behavior. This reduction gives the functional dependence of performance and reaction-times on external inputs in the original system, irrespective of the system details. What is more, the nonlinear diffusion equation can provide excellent fits to behavioral data from two-choice decision making tasks by varying these external inputs. This suggests that changes in behavior under various experimental conditions, e.g. changes in stimulus coherence or response deadline, are driven by internal modulation of afferent inputs to putative decision making circuits in the brain. For certain model systems one can analytically derive the nonlinear diffusion equation, thereby mapping the original system parameters onto the diffusion equation coefficients. Here, we illustrate this with three model systems including coupled rate equations and a network of spiking neurons

Failure of dual radius hydroxyapatite-coated acetabular cups

<p>Abstract</p> <p>Introduction</p> <p>Many kind of hydroxyapatite-coated cups were used, with favorable results in short term studies; it was supposed that its use could improve osteointegration of the cup, enhancing thus stability and survivorship. The purpose of this study is to analyze the long term behavior of the hemispheric HA coated, Dual Radius Osteonics cup and to discuss the way of failure through the exam of the revised components and of both periacetabular and osteolysis tissue.</p> <p>Materials and Methods</p> <p>Between 1994 and 1997, at the Department of Orthopedic Sciences of the Insubria University, using the posterolateral approach, were implanted 276 Dual Radius Osteonics^®in 256 patients, with mean age of 63 years.</p> <p>Results</p> <p>At a mean follow-up of 10 years (range 8–12 years), 183 cups in 165 patients, were available for clinical and radiographical evaluation. 22 Cups among the 183 were revised (11%). The cause of revision was aseptic loosening in 17 cases, septic loosening in one case, periprosthetic fracture in another case, osteolysis and polyethylene wear in two cases and, finally, recurrent dislocations in the last one. In the remaining patients, mean HHS increased from a preoperative value of 50,15 to a postoperative value of 92,69. The mean polyethylene wear was 1,25 mm (min. 0,08, max. 3,9 mm), with a mean annual wear of 0,17 mm. The mean acetabular migration on the two axis was 1,6 mm and 1,8 mm. Peri-acetabular osteolysis were recorded in 89% of the implants (163 cases). The cumulative survivorship (revision as endpoint) at the time was 88,9%.</p> <p>Conclusion</p> <p>Our study confirms the bad behavior of this type of cup probably related to the design, to the method of HA fixation. The observations carried out on the revised cup confirm these hypotheses but did not clarify if the third body wear could be a further problem. Another interesting aspect is the high incidence of osteolysis, which are often asymptomatic becoming a problem for the surgeon as the patient refuses the possibility of a revision.</p

Neural Correlates of Visual Motion Prediction

Predicting the trajectories of moving objects in our surroundings is important for many life scenarios, such as driving, walking, reaching, hunting and combat. We determined human subjects’ performance and task-related brain activity in a motion trajectory prediction task. The task required spatial and motion working memory as well as the ability to extrapolate motion information in time to predict future object locations. We showed that the neural circuits associated with motion prediction included frontal, parietal and insular cortex, as well as the thalamus and the visual cortex. Interestingly, deactivation of many of these regions seemed to be more closely related to task performance. The differential activity during motion prediction vs. direct observation was also correlated with task performance. The neural networks involved in our visual motion prediction task are significantly different from those that underlie visual motion memory and imagery. Our results set the stage for the examination of the effects of deficiencies in these networks, such as those caused by aging and mental disorders, on visual motion prediction and its consequences on mobility related daily activities

Spatio-Temporal Brain Mapping of Motion-Onset VEPs Combined with fMRI and Retinotopic Maps

Neuroimaging studies have identified several motion-sensitive visual areas in the human brain, but the time course of their activation cannot be measured with these techniques. In the present study, we combined electrophysiological and neuroimaging methods (including retinotopic brain mapping) to determine the spatio-temporal profile of motion-onset visual evoked potentials for slow and fast motion stimuli and to localize its neural generators. We found that cortical activity initiates in the primary visual area (V1) for slow stimuli, peaking 100 ms after the onset of motion. Subsequently, activity in the mid-temporal motion-sensitive areas, MT+, peaked at 120 ms, followed by peaks in activity in the more dorsal area, V3A, at 160 ms and the lateral occipital complex at 180 ms. Approximately 250 ms after stimulus onset, activity fast motion stimuli was predominant in area V6 along the parieto-occipital sulcus. Finally, at 350 ms (100 ms after the motion offset) brain activity was visible again in area V1. For fast motion stimuli, the spatio-temporal brain pattern was similar, except that the first activity was detected at 70 ms in area MT+. Comparing functional magnetic resonance data for slow vs. fast motion, we found signs of slow-fast motion stimulus topography along the posterior brain in at least three cortical regions (MT+, V3A and LOR)

A Common Cortical Circuit Mechanism for Perceptual Categorical Discrimination and Veridical Judgment

Perception involves two types of decisions about the sensory world: identification of stimulus features as analog quantities, or discrimination of the same stimulus features among a set of discrete alternatives. Veridical judgment and categorical discrimination have traditionally been conceptualized as two distinct computational problems. Here, we found that these two types of decision making can be subserved by a shared cortical circuit mechanism. We used a continuous recurrent network model to simulate two monkey experiments in which subjects were required to make either a two-alternative forced choice or a veridical judgment about the direction of random-dot motion. The model network is endowed with a continuum of bell-shaped population activity patterns, each representing a possible motion direction. Slow recurrent excitation underlies accumulation of sensory evidence, and its interplay with strong recurrent inhibition leads to decision behaviors. The model reproduced the monkey's performance as well as single-neuron activity in the categorical discrimination task. Furthermore, we examined how direction identification is determined by a combination of sensory stimulation and microstimulation. Using a population-vector measure, we found that direction judgments instantiate winner-take-all (with the population vector coinciding with either the coherent motion direction or the electrically elicited motion direction) when two stimuli are far apart, or vector averaging (with the population vector falling between the two directions) when two stimuli are close to each other. Interestingly, for a broad range of intermediate angular distances between the two stimuli, the network displays a mixed strategy in the sense that direction estimates are stochastically produced by winner-take-all on some trials and by vector averaging on the other trials, a model prediction that is experimentally testable. This work thus lends support to a common neurodynamic framework for both veridical judgment and categorical discrimination in perceptual decision making

The interactions of Cobalt(II) with mitochondria from rat liver

The interactions of Co2+ with mitochondria have been investigated. The results indicate that Co2+ inhibits ATP synthesis. Further investigations into ATP synthesis mechanisms indicated that inhibition is due to the opening of a transmembrane pore. The opening of this pore causes the collapse of the high-energy intermediate where, under a pH and a potential gradient, the energy is stored and subsequently utilized to form ATP from ADP