Interval timing in the seconds-to-minutes range is believed to underlie a variety of complex behaviors in humans and other animals. One of the more interesting problems in interval timing is trying to understand how the brain times events lasting for minutes with millisecond-based neural processes. Timing models proposing the use of coincidence-detection mechanisms (e.g., the detection of simultaneous activity across multiple neural inputs) appear to be the most compatible with known neural mechanisms. From an evolutionary perspective, coincidence detection of neuronal activity may be a fundamental mechanism of timing that is expressed across a wide variety of species. BioEssays 22:94-103, 2000.

Neuropsychological mechanisms of interval timing behavior.

Theoretical and psychophysical studies have suggested that humans learn to make reaching movements in novel dynamic environments by building specific internal models (IMs). Here we have found electromyographic correlates of internal model formation. We recorded EMG from four muscles as subjects learned to move a manipulandum that created systematic forces (a “force field”). We also simulated a biomechanical controller, which generated movements based on an adaptive IM of the inverse dynamics of the human arm and the manipulandum. The simulation defined two metrics of muscle activation. The first metric measured the component of the EMG of each muscle that counteracted the force field. We found that early in training, the field-appropriate EMG was driven by an error feedback signal. As subjects practiced, the peak of the field-appropriate EMG shifted temporally to earlier in the movement, becoming a feedforward command. The gradual temporal shift suggests that the CNS may use the delayed error‐ feedback response, which was likely to have been generated through spinal reflex circuits, as a template to learn a predictive feedforward response. The second metric quantified formation of the IM through changes in the directional bias of each muscle’s spatial EMG function, i.e., EMG as a function of movement direction. As subjects practiced, co-activation decreased, and the directional bias of each muscle’s EMG function gradually rotated by an amount that was specific to the field being learned. This demonstrates that formation of an IM can be represented through rotations in the spatial tuning of muscle EMG functions. Combined with other recent work linking spatial tunings of EMG and motor cortical cells, these results suggest that rotations in motor cortical tuning functions could underlie representation of internal models in the CNS.

/pdf/electromyographic-correlates-of-learning-an-internal-model-21pxnxc7y0.pdf

Electromyographic correlates of learning an internal model of reaching movements.

Initial investigations of the cerebellar microcircuit inspired the Marr-Albus theoretical framework of cerebellar function. We review recent developments in the experimental understanding of cerebellar microcircuit characteristics and in the computational analysis of Marr-Albus models. We conclude that many Marr-Albus models are in effect adaptive filters, and that evidence for symmetrical long-term potentiation and long-term depression, interneuron plasticity, silent parallel fibre synapses and recurrent mossy fibre connectivity is strikingly congruent with predictions from adaptive-filter models of cerebellar function. This congruence suggests that insights from adaptive-filter theory might help to address outstanding issues of cerebellar function, including both microcircuit processing and extra-cerebellar connectivity.

The cerebellar microcircuit as an adaptive filter: experimental and computational evidence

In recent years, an increasing number of research projects investigated whether the central nervous system employs internal models in motor control. While inverse models in the control loop can be identified more readily in both motor behavior and the firing of single neurons, providing direct evidence for the existence of forward models is more complicated. In this paper, we will discuss such an identification of forward models in the context of the visuomotor control of an unstable dynamic system, the balancing of a pole on a finger. Pole balancing imposes stringent constraints on the biological controller, as it needs to cope with the large delays of visual information processing while keeping the pole at an unstable equilibrium. We hypothesize various model-based and non-model-based control schemes of how visuomotor control can be accomplished in this task, including Smith Predictors, predictors with Kalman filters, tapped-delay line control, and delay-uncompensated control. Behavioral experiments with human participants allow exclusion of most of the hypothesized control schemes. In the end, our data support the existence of a forward model in the sensory preprocessing loop of control. As an important part of our research, we will provide a discussion of when and how forward models can be identified and also the possible pitfalls in the search for forward models in control.

Forward models in visuomotor control.

http://cel.huji.ac.il/courses/structureandprocesses/Bibliography/Booth_2007.pdf

The role of the basal ganglia and cerebellum in language processing

A simplified model of the cerebellum was developed to explore its potential for adaptive, predictive control based on delayed feedback information. An abstract representation of a single Purkinje cell with multistable properties was interfaced, using a formalized premotor network, with a simulated single degree-of-freedom limb. The limb actuator was a nonlinear spring-mass system based on the nonlinear velocity dependence of the stretch reflex. By including realistic mossy fiber signals, as well as realistic conduction delays in afferent and efferent pathways, the model allowed the investigation of timing and predictive processes relevant to cerebellar involvement in the control of movement. The model regulates movement by learning to react in an anticipatory fashion to sensory feedback. Learning depends on training information generated from corrective movements and uses a temporally asymmetric form of plasticity for the parallel fiber synapses on Purkinje cells.

/pdf/a-cerebellar-model-of-timing-and-prediction-in-the-control-413b7cyy9k.pdf

Nathan Sitkoff

Papers

A cerebellar model of timing and prediction in the control of reaching