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1. Cerebellar patients have intact feedback control that can be leveraged to improve reaching

   https://doi.org/10.7554/eLife.53246  

   Zimmet, Amanda M; Cao, Di; Bastian, Amy J; Cowan, Noah J (October 2020, eLife)

   null (Ed.)

   It is thought that the brain does not simply react to sensory feedback, but rather uses an internal model of the body to predict the consequences of motor commands before sensory feedback arrives. Time-delayed sensory feedback can then be used to correct for the unexpected—perturbations, motor noise, or a moving target. The cerebellum has been implicated in this predictive control process. Here, we show that the feedback gain in patients with cerebellar ataxia matches that of healthy subjects, but that patients exhibit substantially more phase lag. This difference is captured by a computational model incorporating a Smith predictor in healthy subjects that is missing in patients, supporting the predictive role of the cerebellum in feedback control. Lastly, we improve cerebellar patients’ movement control by altering (phase advancing) the visual feedback they receive from their own self movement in a simplified virtual reality setup. 

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2. Unconscious Neural Activity Predicts Overt Attention in Visual Search

   https://doi.org/10.1101/2025.02.21.639607  

   Nadra, John G; Bengson, Jesse J; Mangun, George R (February 2025, bioRxiv)

   Abstract Unconscious neural activity has been shown to precede both motor and cognitive acts. In the present study, we investigated the neural antecedents of overt attention during visual search, where subjects make voluntary saccadic eye movements to search a cluttered stimulus array for a target item. Building on studies of both overt self-generated motor actions (Lau et al., 2004, Soon et al., 2008) and self-generated cognitive actions (Bengson et al., 2014, Soon et al., 2013), we hypothesized that brain activity prior to the onset of a search array would predict the direction of the first saccade during unguided visual search. Because both spatial attention and gaze are coordinated during visual search, both cognition and motor actions are coupled during visual search. A well-established finding in fMRI studies of willed action is that neural antecedents of the intention to make a motor act (e.g., reaching) can be identified seconds before the action occurs. Studies of the volitional control ofcovertspatial attention in EEG have shown that predictive brain activity is limited to only a few hundred milliseconds before a voluntary shift of covert spatial attention. In the present study, the visual search task and stimuli were designed so that subjects could not predict the onset of the search array. Perceptual task difficulty was high, such that they could not locate the target using covert attention alone, thus requiring overt shifts of attention (saccades) to carry out the visual search. If the first saccade to the array onset in unguided visual search shares mechanisms with willed shifts of covert attention, we expected predictive EEG alpha-band activity (8-12 Hz) immediately prior to the array onset (within 1 sec) (Bengson et al., 2014; Nadra et al., 2023). Alternatively, if they follow the principles of willed motor actions, predictive neural signals should be reflected in broadband EEG activity (Libet et al., 1983) and would likely emerge earlier (Soon et al., 2008). Applying support vector machine decoding, we found that the direction of the first saccade in an unguided visual search could be predicted up to two seconds preceding the search array’s onset in the broadband but not alpha-band EEG. These findings suggest that self-directed eye movements in visual search emerge from early preparatory neural activity more akin to willed motor actions than to covert willed attention. This highlights a distinct role for unconscious neural dynamics in shaping visual search behavior. 

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3. Multi-modal Interactive Perception in Human Control of Complex Objects

   https://doi.org/10.1109/ICRA48891.2023.10160375  

   Nayeem, Rashida; Bazzi, Salah; Sadeghi, Mohsen; Razavian, Reza Sharif; Sternad, Dagmar (May 2023, IEEE International Conference on Robotics and Automation (ICRA 2023),)

   Tactile sensing has been increasingly utilized in robot control of unknown objects to infer physical properties and optimize manipulation. However, there is limited understanding about the contribution of different sensory modalities during interactive perception in complex interaction both in robots and in humans. This study investigated the effect of visual and haptic information on humans’ exploratory interactions with a ‘cup of coffee’, an object with nonlinear internal dynamics. Subjects were instructed to rhythmically transport a virtual cup with a rolling ball inside between two targets at a specified frequency, using a robotic interface. The cup and targets were displayed on a screen, and force feedback from the cup-andball dynamics was provided via the robotic manipulandum. Subjects were encouraged to explore and prepare the dynamics by “shaking” the cup-and-ball system to find the best initial conditions prior to the task. Two groups of subjects received the full haptic feedback about the cup-and-ball movement during the task; however, for one group the ball movement was visually occluded. Visual information about the ball movement had two distinctive effects on the performance: it reduced preparation time needed to understand the dynamics and, importantly, it led to simpler, more linear input-output interactions between hand and object. The results highlight how visual and haptic information regarding nonlinear internal dynamics have distinct roles for the interactive perception of complex objects. 

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4. EEG-based trial-by-trial texture classification during active touch

   https://doi.org/10.1038/s41598-020-77439-7  

   Eldeeb, Safaa; Weber, Douglas; Ting, Jordyn; Demir, Andac; Erdogmus, Deniz; Akcakaya, Murat (December 2020, Scientific Reports)

   Abstract Trial-by-trial texture classification analysis and identifying salient texture related EEG features during active touch that are minimally influenced by movement type and frequency conditions are the main contributions of this work. A total of twelve healthy subjects were recruited. Each subject was instructed to use the fingertip of their dominant hand’s index finger to rub or tap three textured surfaces (smooth flat, medium rough, and rough) with three levels of movement frequency (approximately 2, 1 and 0.5 Hz). EEG and force data were collected synchronously during each touch condition. A systematic feature selection process was performed to select temporal and spectral EEG features that contribute to texture classification but have low contribution towards movement type and frequency classification. A tenfold cross validation was used to train two 3-class (each for texture and movement frequency classification) and a 2-class (movement type) Support Vector Machine classifiers. Our results showed that the total power in the mu (8–15 Hz) and beta (16–30 Hz) frequency bands showed high accuracy in discriminating among textures with different levels of roughness (average accuracy > 84%) but lower contribution towards movement type (average accuracy < 65%) and frequency (average accuracy < 58%) classification. 

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5. Increase in weighting of vision vs. proprioception associated with force field adaptation

   https://doi.org/10.1038/s41598-019-46625-7  

   Sexton, Brandon M.; Liu, Yang; Block, Hannah J. (July 2019, Scientific Reports)

   Abstract Hand position can be estimated by vision and proprioception (position sense). The brain is thought to weight and integrate these percepts to form a multisensory estimate of hand position with which to guide movement. Force field adaptation, a type of cerebellum-dependent motor learning, is associated with both motor and proprioceptive changes. The cerebellum has connections with multisensory parietal regions; however, it is unknown if force adaptation is associated with changes in multisensory perception. If force adaptation affects all relevant sensory modalities similarly, the brain’s weighting of vision vs. proprioception should be maintained. Alternatively, if force perturbation is interpreted as somatosensory unreliability, vision may be up-weighted relative to proprioception. We assessed visuo-proprioceptive weighting with a perceptual estimation task before and after subjects performed straight-ahead reaches grasping a robotic manipulandum. Each subject performed one session with a clockwise or counter-clockwise velocity-dependent force field, and one session in a null field. Subjects increased their weight of vision vs. proprioception in the force field session relative to the null session, regardless of force field direction, in the straight-ahead dimension (F_1,44 = 5.13, p = 0.029). This suggests that force field adaptation is associated with an increase in the brain’s weighting of vision vs. proprioception. 

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