Cortical Models for Movement Control

Defense Advanced Research Projects Agency and Office of Naval Research (N0014-95-l-0409)

Adaptive Neural Models of Queuing and Timing in Fluent Action

Temporal structure in skilled, fluent action exists at several nested levels. At the largest scale considered here, short sequences of actions that are planned collectively in prefrontal cortex appear to be queued for performance by a cyclic competitive process that operates in concert with a parallel analog representation that implicitly specifies the relative priority of elements of the sequence. At an intermediate scale, single acts, like reaching to grasp, depend on coordinated scaling of the rates at which many muscles shorten or lengthen in parallel. To ensure success of acts such as catching an approaching ball, such parallel rate scaling, which appears to be one function of the basal ganglia, must be coupled to perceptual variables, such as time-to-contact. At a fine scale, within each act, desired rate scaling can be realized only if precisely timed muscle activations first accelerate and then decelerate the limbs, to ensure that muscle length changes do not under- or over-shoot the amounts needed for the precise acts. Each context of action may require a much different timed muscle activation pattern than similar contexts. Because context differences that require different treatment cannot be known in advance, a formidable adaptive engine-the cerebellum-is needed to amplify differences within, and continuosly search, a vast parallel signal flow, in order to discover contextual "leading indicators" of when to generate distinctive parallel patterns of analog signals. From some parts of the cerebellum, such signals controls muscles. But a recent model shows how the lateral cerebellum, such signals control muscles. But a recent model shows how the lateral cerebellum may serve the competitive queuing system (in frontal cortex) as a repository of quickly accessed long-term sequence memories. Thus different parts of the cerebellum may use the same adaptive engine system design to serve the lowest and the highest of the three levels of temporal structure treated. If so, no one-to-one mapping exists between levels of temporal structure and major parts of the brain. Finally, recent data cast doubt on network-delay models of cerebellar adaptive timing.National Institute of Mental Health (R01 DC02852

Evaluation of behavior in transgenic mouse models to understand human congenital pain conditions

BACKGROUND: Containing a brain for signal processing and decision making, and a peripheral component for sensation and response, the nervous system provides higher organisms a powerful method of interacting with their environment. The specific neurons involved in pain sensation are known as nociceptors and are the source of normal nociceptive pain signaling to prompt appropriate responses. Though acute hypersensitization can be advantageous by encouraging an organism to allow an injured area to heal, chronic pain conditions can be pathological and can markedly reduce quality of life. While a variety of genes have been associated with congenital pain conditions, two rare cases examined in this study have not had their mutated genes identified. Potassium voltage-gated channel subfamily H member 8, or KCNH8, is involved in regulating action potential production and propagation, and has not been linked with pain processing of any kind to date. Here, a male patient evaluated at Boston Children’s Hospital contains a novel single-base KCNH8 mutation and possesses an extremely low sensitivity to cold temperatures and mechanical pain, but a higher sensitivity to warmer temperatures. A separate protein, intersectin-2, or ITSN2, normally functions in clathrin-mediated endocytosis and exocytosis. A second patient at Boston Children’s Hospital expresses a previously-unseen point mutation in ITSN2 and experiences erythromelalgia, characterized by episodes of intense pain and red, swollen limbs during ambient warm temperatures. Through the use of Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR)/Cas9 genome editing, this study will produce these specific genetic mutations in mouse lines to explore their effects on mammalian behavior. OBJECTIVES: This project employs two transgenic mouse models to study the behavioral phenotypes associated with rare potentially damaging mutations in KCNH8 and ITSN2 exhibited in the human patients. Through these experiments, a greater understanding of neural pain signaling and sensitivity changes can occur. METHODS: The differences in temperature preference of KCNH8 and ITSN2 mutant mice compared to wild type mice lacking these mutations was studied using thermal plates under cold and warm conditions. Direct application of acetone and von Frey filaments to mouse paws was used to study cold and mechanical sensitivity. Further testing of stamina, anxiety, coordination, and strength were also evaluated. RESULTS: A marked decrease in sensitivity to von Frey stimulation (p<0.01) and acetone administration (p<0.05) was observed in KCNH8 mutant mice. Thermal preference testing demonstrated a decreased preference for warmer temperatures as compared to wild type mice. In addition, anxiety levels were also observed to be slightly higher in these mutant KCNH8 mice (p<0.05). The mutant ITSN2 mice spent less time at cooler temperatures, though surprisingly they significantly preferred warmer conditions as compared to their wild type littermates. A full and partial reversal of these temperature preferences was demonstrated in cold and heat thermal conditions respectively after intraperitoneal gabapentin injection, which normalized the mice toward wild type behavior. CONCLUSIONS: Data from the KCNH8 mutant mouse model indicates an aversion to warmer temperatures and a decreased ability to detect cold or mechanical pressure, much like the human patient. The mutant ITSN2 mice were less likely to spend time at cooler temperatures, indicating heightened sensory sensitivity, but their preference for warmer temperatures suggests a possible desensitization of the affected nociceptors. These results often mirror the patient’s phenotype, but the preference for ambient warmer environments appears opposite to the patient. As the ITSN2 mice feel discomfort at cooler temperatures, a proposed desensitization at warmer temperatures would result in a more comfortable environment and could explain the observed preference. The trends toward normal neural firing rates achieved through gabapentin injection suggest that the aberrant responses in mutant ITSN2 mice is due to altered sensitization, but additional examination under these conditions with a larger group of mice is necessary to further unravel these signaling pathways. However, these extremely encouraging data introduce two new molecular targets for acute pain control

From Parallel Sequence Representations to Calligraphic Control: A Conspiracy of Neural Circuits

Calligraphic writing presents a rich set of challenges to the human movement control system. These challenges include: initial learning, and recall from memory, of prescribed stroke sequences; critical timing of stroke onsets and durations; fine control of grip and contact forces; and letter-form invariance under voluntary size scaling, which entails fine control of stroke direction and amplitude during recruitment and derecruitment of musculoskeletal degrees of freedom. Experimental and computational studies in behavioral neuroscience have made rapid progress toward explaining the learning, planning and contTOl exercised in tasks that share features with calligraphic writing and drawing. This article summarizes computational neuroscience models and related neurobiological data that reveal critical operations spanning from parallel sequence representations to fine force control. Part one addresses stroke sequencing. It treats competitive queuing (CQ) models of sequence representation, performance, learning, and recall. Part two addresses letter size scaling and motor equivalence. It treats cursive handwriting models together with models in which sensory-motor tmnsformations are performed by circuits that learn inverse differential kinematic mappings. Part three addresses fine-grained control of timing and transient forces, by treating circuit models that learn to solve inverse dynamics problems.National Institutes of Health (R01 DC02852

A Neural Circuit for Coordinating Reaching with Grasping: Autocompensating Variable Initial Apertures, Perturbations to Target Size, and Perturbations to Target Orientation

A neural network model is presented, that extends principles of the VITE (vector integration to end-point) model [1, 2, 3, 4] of primate reaching to the more complex case of reach-grasp coordination. The main new planning problem addressed by the model is how to simulate human data on temporal coordination between reaching and grasping, while at the same time remaining stable and compensating for altered initial apertures and perturbations of object size and object location/ orientation. Simulations of the model replicate key features of four different experimental protocols with a single set of parameters. The proposed circuit computes reaching to grasp trajectories in real-time, by continuously updating vector positioning commands, and with no precomputation of total or component movement times. The model consists of three generator channels: transport, which generates a reaching trajectory; aperture, which controls distance between thumb and index finger; and orientation, which controls hand orientation vis-a-vis target's orientation.CONACYT of Mexico; Defense Advanced Research Projects Agency and Office of Naval Research (N00014-95-1-0409

Moving in time: simulating how neural circuits enable rhythmic enactment of planned sequences

Many complex actions are mentally pre-composed as plans that specify orderings of simpler actions. To be executed accurately, planned orderings must become active in working memory, and then enacted one-by-one until the sequence is complete. Examples include writing, typing, and speaking. In cases where the planned complex action is musical in nature (e.g. a choreographed dance or a piano melody), it appears to be possible to deploy two learned sequences at the same time, one composed from actions and a second composed from the time intervals between actions. Despite this added complexity, humans readily learn and perform rhythm-based action sequences. Notably, people can learn action sequences and rhythmic sequences separately, and then combine them with little trouble (Ullén & Bengtsson 2003). Related functional MRI data suggest that there are distinct neural regions responsible for the two different sequence types (Bengtsson et al. 2004). Although research on musical rhythm is extensive, few computational models exist to extend and inform our understanding of its neural bases. To that end, this article introduces the TAMSIN (Timing And Motor System Integration Network) model, a systems-level neural network model capable of performing arbitrary item sequences in accord with any rhythmic pattern that can be represented as a sequence of integer multiples of a base interval. In TAMSIN, two Competitive Queuing (CQ) modules operate in parallel. One represents and controls item order (the ORD module) and the second represents and controls the sequence of inter-onset-intervals (IOIs) that define a rhythmic pattern (RHY module). Further circuitry helps these modules coordinate their signal processing to enable performative output consistent with a desired beat and tempo.Accepted manuscrip

A Scalable Model of Cerebellar Adaptive Timing and Sequencing: The Recurrent Slide and Latch (RSL) Model

From the dawn of modern neural network theory, the mammalian cerebellum has been a favored object of mathematical modeling studies. Early studies focused on the fan-out, convergence, thresholding, and learned weighting of perceptual-motor signals within the cerebellar cortex. This led in the proposals of Albus (1971; 1975) and Marr (1969) to the still viable idea that the granule cell stage in the cerebellar cortex performs a sparse expansive recoding of the time-varying input vector. This recoding reveals and emphasizes combinations (of input state variables) in a distributed representation that serves as a basis for the learned, state-dependent control actions engendered by cerebellar outputs to movement related centers. Although well-grounded as such, this perspective seriously underestimates the intelligence of the cerebellar cortex. Context and state information arises asynchronously due to the heterogeneity of sources that contribute signals to compose the cerebellar input vector. These sources include radically different sensory systems - vision, kinesthesia, touch, balance and audition - as well as many stages of the motor output channel. To make optimal use of available signals, the cerebellum must be able to sift the evolving state representation for the most reliable predictors of the need for control actions, and to use those predictors even if they appear only transiently and well in advance of the optimal time for initiating the control action. Such a cerebellar adaptive timing competence has recently been experimentally verified (Perrett, Ruiz, & Mauk, 1993). This paper proposes a modification to prior, population, models for cerebellar adaptive timing and sequencing. Since it replaces a population with a single clement, the proposed Recurrent Slide and Latch (RSL) model is in one sense maximally efficient, and therefore optimal from the perspective of scalability.Defense Advanced Research Projects Agency and the Office of Naval Research (N00014-92-J-1309, N00014-93-1-1364, N00014-95-1-0409)

Neural Network Modeling of Sensory-Motor Control in Animals

National Science Foundation (IRI 90-24877, IRI 87-16960); Air Force Office of Scientific Research (F49620-92-J-0499); Office of Naval Research (N00014-92-J-1309