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This letter proposes a new negative correlation (NC) learning method that is both easy to implement and has the advantages that: 1) it requires much lesser communication overhead than the standard NC method and 2) it is applicable to ensembles of heterogenous networks.
In everyday life, we reach, grasp, and manipulate a variety of different objects all with their own dynamic properties. This degree of adaptability is essential for a brain-controlled prosthetic arm to work in the real world. In this study, rats were trained to make reaching movements while holding a torque manipulandum working against two distinct loads. Neural recordings obtained from arrays of 32 microelectrodes spanning the motor cortex were used to predict several movement related variables. In this paper, we demonstrate that a simple linear regression model can translate neural activity into endpoint position of a robotic manipulandum even while the animal controlling it works against different loads. A second regression model can predict, with 100% accuracy, which of the two loads is being manipulated by the animal. Finally, a third model predicts the work needed to move the manipulandum endpoint. This prediction is significantly better than that for position. In each case, the regression model uses a single set of weights. Thus, the neural ensemble is capable of providing the information necessary to compensate for at least two distinct load conditions.
Sensory feedback is required by biological motor control systems to maintain stability, respond to perturbations, and adapt. Similarly, motor neuroprostheses require feedback to provide natural and complete restoration of motor functions. In this paper, we show that ensemble firing rates from the body's mechanoreceptors can provide a natural source of kinematic state feedback and could be useful for prosthetic control. Single unit recordings from multiple primary afferent neurons were obtained during walking using multichannel electrode arrays implanted chronically in the L7 dorsal root ganglia of three cats. We typically recorded simultaneously from over 20-30 neurons during the first 7-14 days after surgery, but recordings gradually worsened thereafter. Histology indicates that a ring of inflammatory and connective tissues (100 microm thick) develops around each microelectrode and likely contributes to the degradation in recording quality. Accurate estimates of the hindlimb trajectory were made using a linear filter with inputs from only a few neurons highly correlated with limb kinematics. The coefficients for the linear filter were identified in a least-squares fit with 5-10 s of walking data (model training stage). The estimated and actual trajectories of separate walking data generally match well for walking at a range of speeds accounting for 63 +/- 22% (mean +/- S.D. for hip, knee, and ankle) of the variance in joint angle and 72 +/- 4% of the variance in joint angular velocities. These results indicate that a neural interface with primary sensory neurons in the dorsal root ganglion can provide accurate kinematic state information that may be useful for closed loop control of a neuroprosthesis.
In this study, we examined single-unit activity in the amygdala before and after a rat had acquired an inhibitory avoidance task. Long-Evans rats with microwires chronically implanted into the central nucleus (CeA) or basolateral complex (BLC) of the amygdala were acclimatized to the apparatus of a step-through inhibitory avoidance task for three sessions. On the fourth session, rats in the experimental group received an inescapable footshock (3 mA, 1 s) as they stepped from the lit side into the dark side of the task apparatus, whereas rats in the control group received the same amount of shock on a different apparatus. All rats were tested for retention in the task apparatus 1 day after shock training. The experimental rats showed better retention than the controls as they stayed longer in the lit side. Ensemble unit activities were recorded in the amygdala nuclei from the indwelling wire bundles during the acclimation and test sessions. The data collected from well-isolated amygdala units showed that neuronal discharge habituated from the first to the third acclimation session. In the test session, the experimental group, but not the control group, showed elevated firing rates in the CeA or BLC neurons located on either side of the brain. These findings provide the first piece of evidence showing that learning of an inhibitory avoidance task leads to an increase in amygdala neuronal discharges during a retention test.
Previous studies have shown that systemic administration of cocaine transiently alters stimulus-evoked responses of ventral posteromedial (VPM) thalamic neurons. Results from these single-unit electrophysiological studies revealed that cocaine was equally likely to augment or attenuate the magnitude of sensory evoked responses following threshold level stimulation of peripheral receptive fields. In an attempt to clarify the impact of cocaine administration on sensory signal processing, we examined the drug's effects on responses of individual neurons and ensembles of VPM thalamic neurons to sensory stimuli, and performance of subjects in a sensory detection behavioural task. Extracellular responses of single (n = 1 cell/rat) or multiple VPM thalamic neurons (n = 10-40 cells/rat) were monitored before and after cumulative doses of cocaine (0.25-2.0 mg/kg i.v.). Neuronal responses were characterized by assessing the response profile to a range of peri-threshold-level deflections of the optimal whisker on the contralateral face. Drug effects on stimulus-response curves, determined from quantitative analysis of spike train data, indicated that whereas cocaine elicits variable effects at the single cell level, the stimulus-evoked response of the recorded population was likely to increase following lower (0.25-1.0 mg/kg i.v.) doses of cocaine. Furthermore, cocaine preferentially enhanced responses to smaller magnitude deflections of vibrissa, altering the response profile from a mode that accurately conveyed stimulus strength to one that increased detection at the expense of discrimination. Finally, a similar pattern emerged in a behavioural paradigm involving rats trained to detect variable amplitude whisker pad stimulation, suggesting a common action of cocaine that may contribute to the drug's addictive properties.
1. The aim of this work was to compare the ability of several mathematical models to predict the firing characteristics of muscle spindle primary afferents recorded chronically during normal stepping in cats. 2. Ensemble firing profiles of nine hamstring spindle primary (presumed group Ia) afferents were compiled from stored data from 132 step cycles. Three sets of profiles corresponding to slow, medium and fast steps were generated by averaging groups of step cycles aligned to peak muscle length in each cycle. 3. Five models obtained from the literature were compared. Each of these models was used to predict the spindle firing profiles from the averaged muscle length signals. The models were also used in the reverse direction, namely to predict muscle length from the firing profiles. A sixth model incorporating some key aspects of the other models was also included in the comparisons. 4. Five of the models predicted spindle firing well, with root mean square (r.m.s.) errors lower than 14 % of the modulation depth of the target profiles. The key variable in achieving good predictions was muscle velocity, the best fits being obtained with power-law functions of velocity, with an exponent of 0.5 or 0.6 (i.e. spindle firing rate is approximately proportional to the square root of muscle velocity). The fits were slightly improved by adding small components of EMG signal to mimic fusimotor action linked to muscle activation. The modest relative size of EMG-linked fusimotor action may be related to the fact that hamstring muscles are not strongly recruited in stepping. 5. Length was predicted very accurately from firing profiles with the inverse of the above models, indicating that the nervous system could in principle process spindle firing in a relatively simple way to give accurate information on muscle length. 6. The responses of the models to standard ramp-and-hold displacements at 10 mm s-1 were also studied (i.e. velocities that were an order of magnitude lower than that during stepping). In these cases components of spindle primary response related to length as well as velocity were needed for good fits. Because these length-related components detracted from rather than improved predictions of the step cycle data, an attenuation of length dependence at high muscle velocities emerged as a possibility. 7. We conclude that in this study we have identified models and parameters that may be used to predict spindle afferent firing from the time course of muscle length in the cat step cycle.
1. A general approach to the analysis of ensemble currents of ligand-gated channels is presented, with a variety of examples that include single and multiple agonist binding steps, desensitization and several blocking pathways. 2. The use of matrix methods to describe model reaction schemes leads to a simplification if the reaction scheme is irreversible: the product of the exponential relaxation rate constants is exactly equal to the product of the forward reaction steps. 3. This method of analysis applied to the bovine adrenal nicotinic receptor suggests that in the range of acetylcholine concentrations from 1 microM to 2 mM, a model with a single kinetically relevant agonist binding step is appropriate. 4. Complex models, to explain the presence of two desensitizing components in currents recorded from whole cells, may be discounted in favour of two distinct receptor types. 5. A simple model of open channel block is discounted, and desensitization of the blocked state proposed.
A series of recent studies have indicated that ensembles of neurones, distributed within the neural structures that form the primary thalamocortical loop (TCL) of the trigeminal component of the rat somatosensory system, change the way they respond to similar tactile stimuli, according to both the behavioural strategy employed by animals to gather information and the animal's internal brain states. These findings suggest that top-down influences, which are more likely to play a role during active discrimination than during passive whisker stimulation, may alter the pattern of neuronal firing within both the distinct layers of the primary somatosensory cortex (S1) and the ventral posterior medial nucleus (VPM). We propose that through this physiological process, which involves concurrent dynamic modulations at both cellular and circuit levels in the TCL, rats can either optimize the detection of novel or hard to sense stimuli or they can analyse complex patterns of multi-whisker stimulation, during natural exploration of their surrounding environment.
In this paper, we describe a new technique to identify rapidly time-varying Hammerstein systems from ensembles of input-output realizations. The technique involves two steps. A correlation approach is first used to obtain initial estimates of the linear subsystem parameters for every sampling time. An iterative optimization algorithm is then employed to produce final estimates of the system parameters. The input does not need to be white. The technique was tested on simulated data and was found to produce excellent results under realistic conditions.
The recording of neural ensembles in awake, behaving rats has been an extremely successful experimental paradigm, providing demonstrable scientific advances. Dynamic control of the position of the implanted electrodes is of key importance as mobile electrodes provide a better signal-to-noise ratio and a better cell/ electrode yield than nonmobile electrodes. Here we describe the use of low cost, soon to be commercially available dc motors to successfully control the depth of electrodes. The prototype designed is approximately 30 mm in diameter and 50 mm in length and weighed about 30 gms. This paper presents the results of linear displacements of electrodes achievable with this motorized microdrive.
Deformable shape models (DSMs) comprise a general approach that shows great promise for automatic image segmentation. Published studies by others and our own research results strongly suggest that segmentation of a normal or near-normal object from 3D medical images will be most successful when the DSM approach uses (1) knowledge of the geometry of not only the target anatomic object but also the ensemble of objects providing context for the target object and (2) knowledge of the image intensities to be expected relative to the geometry of the target and contextual objects. The segmentation will be most efficient when the deformation operates at multiple object-related scales and uses deformations that include not just local translations but the biologically important transformations of bending and twisting, i.e., local rotation, and local magnification. In computer vision an important class of DSM methods uses explicit geometric models in a Bayesian statistical framework to provide a priori information used in posterior optimization to match the DSM against a target image. In this approach a DSM of the object to be segmented is placed in the target image data and undergoes a series of rigid and nonrigid transformations that deform the model to closely match the target object. The deformation process is driven by optimizing an objective function that has terms for the geometric typicality and model-to-image match for each instance of the deformed model. The success of this approach depends strongly on the object representation, i.e., the structural details and parameter set for the DSM, which in turn determines the analytic form of the objective function. This paper describes a form of DSM called m-reps that has or allows these properties, and a method of segmentation consisting of large to small scale posterior optimization of m-reps. Segmentation by deformable m-reps, together with the appropriate data representations, visualizations, and user interface, has been implemented in software that accomplishes 3D segmentations in a few minutes. Software for building and training models has also been developed. The methods underlying this software and its abilities are the subject of this paper.
A correcting formula for the estimation of harmonics-to-noise ratios (HNR) based on ensemble-averaging techniques is derived. The original method yields a biased approximation which is more accurate as the number of averaged pulses (N) increases. However, the method treats gradual waveform changes incorrectly as noise, which is worsened for large values of N. The obtained formula allows the use of as few averaged pulses as desired, while allowing the complete removal of the bias from the estimate of HNR.
The frequency spectra of transmission coefficients for ultrasound passing through a sheet of gas-filled micropores have been measured using incident waves with amplitudes up to 2.4 x 10(4) Pa. It is found that as the amplitude of the incident wave is increased, the peak frequency of transmission loss through the two-dimensional trapped-bubble ensemble shifts to lower values by as much as 47%. The experiments indicate that the shifting is caused by the net displacements of air-water-membrane triple-phase lines and the air loss of the trapped bubble, which are due to the radiation force and microbubble production produced by the incident wave. Results of the experiments and possible theoretical explanations are discussed.
Experiments in coherent magnetic resonance, microwave, and optical spectroscopy control quantum-mechanical ensembles by guiding them from initial states toward target states by unitary transformation. Often, the coherences detected as signals are represented by a non-Hermitian operator. Hence, spectroscopic experiments, such as those used in nuclear magnetic resonance, correspond to unitary transformations between operators that in general are not Hermitian. A gradient-based systematic procedure for optimizing these transformations is described that finds the largest projection of a transformed initial operator onto the target operator and, thus, the maximum spectroscopic signal. This method can also be used in applied mathematics and control theory.
Simultaneous recordings were made from large ensembles of hippocampal "place cells" in three rats during spatial behavioral tasks and in slow-wave sleep preceding and following these behaviors. Cells that fired together when the animal occupied particular locations in the environment exhibited an increased tendency to fire together during subsequent sleep, in comparison to sleep episodes preceding the behavioral tasks. Cells that were inactive during behavior, or that were active but had non-overlapping spatial firing, did not show this increase. This effect, which declined gradually during each post-behavior sleep session, may result from synaptic modification during waking experience. Information acquired during active behavior is thus re-expressed in hippocampal circuits during sleep, as postulated by some theories of memory consolidation.
The recent report by T. Murillo, L. E. Enrique Chaves-González, S. Temmam, S. Bermúdez, et al. (Microbiol Spectr 14:e04078-25, 2026, https://doi.org/10.1128/spectrum.04078-25) expands the known geographic and ecological range of Jingmen tick virus (JMTV) by detecting the virus in Amblyomma mixtum ticks collected from horses in Costa Rica. This is an important finding because A. mixtum can feed on wildlife, domestic animals, and humans, creating a possible interface for virus movement across various hosts. The study also places the Costa Rican virus in a wider phylogenetic context, linking it to JMTV diversity reported from other regions. However, the detection of viral RNA in ticks should not be interpreted as proof of local disease, human infection, or active transmission, especially in the absence of supporting results. Instead, it reflects an important signal for careful viral surveillance. Here, I discuss how JMTV illustrates the need for ensemble approaches that combine field sampling, phylogeny, segment-level genome analysis, serology, experimental validation, and data-driven virus discovery tools.
We present a study of homogeneous and heterogeneous nucleation in polymer crystallisation. In bulk samples the crystallization is typically dominated by nucleation from defects (heterogeneous nucleation), and consequently studies must rely on sample preparation to minimize this effect. We present a study of nucleation within discrete droplets of poly(ethylene oxide) that are formed by the dewetting of a thin film on an unfavourable substrate. The samples provide an ensemble of impurity-free droplets, with length scales that can easily be measured. We show that the data for heterogeneous and homogeneous nucleation is qualitatively different, and that the data mirrors the fundamental differences in the underlying mechanisms for the two nucleation processes. The experiments presented here provide a simple method that can be used to study heterogeneous and homogeneous nucleation in great detail.
Computer simulations offer critical insights into the reaction of biological macromolecules, especially when the molecular shapes are too complex to be amenable to analytical solution. In this work, the Weighted-Ensemble Brownian (WEB) Dynamics simulation algorithm is adapted to a reaction of two unlike biological molecules, with the interaction modeled by a two-parameter system: a spherical molecular depositing on a target region of an infinite cylinder with a periodic boundary conditions. The original algorithm of Huber and Kim is streamlined for this class of reactive models. The reaction rate constant is calculated as a function of relative sizes of the reactive to non-reactive regions of the cylindrical molecule. An analytical expression for the rate constant is also obtained from the solution of the diffusion equation for the special case of a constant-flux boundary condition. Good agreement between analytical and simulation results validates the applicability of WEB Dynamics to a reaction of molecules of complicated shape. On the other hand, the simple form of our analytical expression is useful as a testing case for other simulation and numerical techniques.