BIOENGINEERING
Dr. Aaron Batista’s research group examines the neural control of visually-guided action. We seek to understand basic principles that underlie the function of the cerebral cortex, ur research is those the discoveries Critical Stability Task (CST), wherein subjects must and to use to improve the function of clinical brain-computer interface vision (BCI) and/or tactile) in order to make corrective actions to maintain a systems as a treatment for paralysis. Here we describe two of the research puter display several seconds. Corrective actions to move the cursor endeavorsfor taking place within the laboratory.
Aaron Batista, PhD Professor
RESEARCH LETTER a
Neural activity BCI mapping
Units
302 Benedum Hall | 3700 sensory-driven O’Hara Street | Pittsburgh, PA 15261 at requires continuous motor interaction with a simplified he taskP:can be scaled in the future to embody more complex interactions. 412-383-5394 redictions about neural responses in sensory and motor areas of the aaron.batista@pitt.edu rt to integrate sensory information for the control of ongoing movements. https://smile.pitt.edu e combine multielectrode neurophysiology with quantitative analysis of organized to inform a computational model of sensory-motor interaction Sensory-Motor Integration Laboratory and Engineering
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d movements, or via BCI control. The CST was originally formulated [31] Neural constraints on learning ynamics governed by the differential equation,
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Unit 1 Unit 2 Unit 3
Intrinsic manifold
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we learn(with new skills? are examiningthe the neural underpinnings of learning using a !novel ! f the cursor x>0 We representing cursor to the right of center), paradigm, brain-computer interface control, which allows us to study the neural basis of generated by the subject, and t=0 indicates the start of the trial. The learning more directly than is possible with arm movements. can directly request of of the parameter, !. Because ! is positive, the cursorWeposition will diverge animals (control that they generate specific patterns of neural across a population sating our actions commands) are issued byactivity the subject [89]. Asof ! 100 or so neurons. We can then observe whether the animals are capable of generating r, and the CST is more challenging. The maximum ! (which has units of the patterns we requested. Mathematical tools drawn from machine learning enable us ntrol the cursor is related to the bandwidth of the stabilized closed-loop to predict which new neural activity patterns (and, corresponding skills) are relatively easy tability value” (CIV) since, beyond that value, the closed-loop system learn effective (a day or so),isand will be more difficult (a week or two), just by examining V, the to more thewhich subject’s sensorimotor control. the pre-existing patterns of neural activity prior to learning. e investigation of motor control that requires sensory feedback, consider This work pursuedfrom along with colleagues Stevesuch Chasethat of Carnegie Mellon d to keep the iscursor drifting, i.e., Byron whatYuisand!(!) the cursor University. It is0) currently supported by an NIHthat R01 grant the National of a into Eq. (1) shows the from subject must Institute generate ion (!"(!) !" = Child Health and Human Development. ual and opposite to the current cursor position: ! ! = −!(!). Thus, st know the state of the cursor. A subject who could issue this perfect 00% accurate) would be able to keep the cursor completely still. and is Multisensory not possibleIntegration becauseinofAction sensorimotor noise and nervous system will continuously and control – keeping it thing fromwith rapidly Our actions aremove, shaped by our maintaining perceptual we see, hear, and feel the which going experience. sensory-guided motor action (Fig. 1). With adequate sensory Consider the fine adjustments we are interacting, and our movements ommand signalmakes that tokeeps cursor about an equilibrium a violinist play thethe correct pitch. centered are adjusted on-the-fly to achieve ourpoint subject’s CIV. A subject’s CIV captures important aspects ofhow their Sensory experience is often multimodal: objectives. We seek to understand peed and accuracy with which he or she can react to sensory input. The ective e CIV s an ure of everal pe of our ensory ), the nts or Fig. 1. Two CST trials. 1st row: d the (schematic of) visual [left] and (spectrogram of) vibrotactile [right] d less nd feedback. 2 row: cursor and hand motor position traces. Bottom left: raster of faster DEPARTMENT OF BIOENGINEERING multichannel neural activity from M1. ity or stablish the CIV for each animal under each of the configurations of
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the brain uses sensory information to guide action, we train animals Intuitiveto perform control space challenging balancing tasks in a virtual environment. We record from motor and Within-manifold perturbation control space sensory areas, in the hope of discovering Un Un it 2 areas communicate to send it 2 how the FR FR FR 3 t i n U detailed sensory information to sculpt the activity of motor neurons. Figure 1 | Using a brain–computer interface to study Unit 1 FR
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Why are some new skills learned relatively quickly, while others take far longer? What
=changes ! ! ! in+ ! ,!!!!!! > 0,!!!! the!brain when we learn, ≥ so 0 that pre-existing abilities are retained even as(1)
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moved the BCI cursor (blue circle) to acquire targets (g This work is pursued along with my Pitt modulating their neural activity. The BCI mapping cons Bioengineering colleague PattoLoughlin. the population neural activity the intrinsic manifold from the intrinsic manifold to cursor Itthen is supported by an NIH R01 grant from kinematics u ThisNational two-stepInstitute procedureofallowed us to perform the Child Health and outside-m (blue arrows) and within-manifold perturbations (red ar Human Development. b, A simplified, conceptual illustration using three electr
(FR) observed on each electrode in a brief epoch define in the neural space. The intrinsic manifold (yellow plan prominent patterns of co-modulation. Neural activity m space (black line) to specify cursor velocity. c, Control s mapping (black arrow), within-manifold perturbation (re manifold perturbation (blue arrow). d, Neural 9 activity ( different cursor velocities (open circles and inset) under Arrow colours as in c.
