Shared synaptic mechanism for Alzheimer's and Parkinson’s disease unlocks new treatment possibilities

Study reveals common mechanism affecting brain signaling, identifying a shared cause for neurodegenerative disease symptoms.

JNeurosci Town Hall

Prior Movement of One Arm Facilitates Motor Adaptation in the Other

Many movements in daily life are embedded in motion sequences that involve more than one limb, demanding the motor system to monitor and control different body parts in quick succession. During such movements, systematic changes in the environment or the body might require motor adaptation of specific segments. However, previous motor adaptation research has focused primarily on motion sequences produced by a single limb, or on simultaneous movements of several limbs. For example, adaptation to opposing force fields is possible in unimanual reaching tasks when the direction of a prior or subsequent movement is predictive of force field direction. It is unclear, however, whether multilimb sequences can support motor adaptation processes in a similar way. In the present study (38 females, 38 males), we investigated whether reaches can be adapted to different force fields in a bimanual motor sequence when the information about the perturbation is associated with the prior movement direction of the other arm. In addition, we examined whether prior perceptual (visual or proprioceptive) feedback of the opposite arm contributes to force field-specific motor adaptation. Our key finding is that only active participation in the bimanual sequential task supports pronounced adaptation. This result suggests that active segments in bimanual motion sequences are linked across limbs. If there is a consistent association between movement kinematics of the linked and goal movement, the learning process of the goal movement can be facilitated. More generally, if motion sequences are repeated often, prior segments can evoke specific adjustments of subsequent movements. SIGNIFICANCE STATEMENT Movements in a limb's motion sequence can be adjusted based on linked movements. A prerequisite is that kinematics of the linked movements correctly predict which adjustments are needed. We show that use of kinematic information to improve performance is even possible when a prior linked movement is performed with a different limb. For example, a skilled juggler might have learned how to correctly adjust his catching movement of the left hand when the right hand performed a throwing action in a specific way. Linkage is possibly a key mechanism of the human motor system for learning complex bimanual skills. Our study emphasizes that learning of specific movements should not be studied in isolation but within their motor sequence context.

Undermatching Is a Consequence of Policy Compression

The matching law describes the tendency of agents to match the ratio of choices allocated to the ratio of rewards received when choosing among multiple options ([Herrnstein, 1961][1]). Perfect matching, however, is infrequently observed. Instead, agents tend to undermatch or bias choices toward the poorer option. Overmatching, or the tendency to bias choices toward the richer option, is rarely observed. Despite the ubiquity of undermatching, it has received an inadequate normative justification. Here, we assume agents not only seek to maximize reward, but also seek to minimize cognitive cost, which we formalize as policy complexity (the mutual information between actions and states of the environment). Policy complexity measures the extent to which the policy of an agent is state dependent. Our theory states that capacity-constrained agents (i.e., agents that must compress their policies to reduce complexity) can only undermatch or perfectly match, but not overmatch, consistent with the empirical evidence. Moreover, using mouse behavioral data (male), we validate a novel prediction about which task conditions exaggerate undermatching. Finally, in patients with Parkinson's disease (male and female), we argue that a reduction in undermatching with higher dopamine levels is consistent with an increased policy complexity. SIGNIFICANCE STATEMENT The matching law describes the tendency of agents to match the ratio of choices allocated to different options to the ratio of reward received. For example, if option a yields twice as much reward as option b, matching states that agents will choose option a twice as much. However, agents typically undermatch: they choose the poorer option more frequently than expected. Here, we assume that agents seek to simultaneously maximize reward and minimize the complexity of their action policies. We show that this theory explains when and why undermatching occurs. Neurally, we show that policy complexity, and by extension undermatching, is controlled by tonic dopamine, consistent with other evidence that dopamine plays an important role in cognitive resource allocation. [1]: #ref-21

Johannes Singer on Twitter

“Very happy to share that the first paper of my PhD in #JNeurosci is now online 🥳 Together with Radek Cichy and @martin_hebart we asked whether the recognition of line drawings relies on similar neural mechanisms as those used for recognizing natural objects. 🧵1/7”

Updating Contextual Sensory Expectations for Adaptive Behavior

The brain has the extraordinary capacity to construct predictive models of the environment by internalizing statistical regularities in the sensory inputs. The resulting sensory expectations shape how we perceive and react to the world; at the neural level, this relates to decreased neural responses to expected than unexpected stimuli (“expectation suppression”). Crucially, expectations may need revision as context changes. However, existing research has often neglected this issue. Further, it is unclear whether contextual revisions apply selectively to expectations relevant to the task at hand, hence serving adaptive behavior. The present fMRI study examined how contextual visual expectations spread throughout the cortical hierarchy as we update our beliefs. We created a volatile environment: two alternating contexts contained different sequences of object images, thereby producing context-dependent expectations that needed revision when the context changed. Human participants of both sexes attended a training session before scanning to learn the contextual sequences. The fMRI experiment then tested for the emergence of contextual expectation suppression in two separate tasks, respectively, with task-relevant and task-irrelevant expectations. Effects of contextual expectation emerged progressively across the cortical hierarchy as participants attuned themselves to the context: expectation suppression appeared first in the insula, inferior frontal gyrus, and posterior parietal cortex, followed by the ventral visual stream, up to early visual cortex. This applied selectively to task-relevant expectations. Together, the present results suggest that an insular and frontoparietal executive control network may guide the flexible deployment of contextual sensory expectations for adaptive behavior in our complex and dynamic world. SIGNIFICANCE STATEMENT The world is structured by statistical regularities, which we use to predict the future. This is often accompanied by suppressed neural responses to expected compared with unexpected events (“expectation suppression”). Crucially, the world is also highly volatile and context-dependent: expected events may become unexpected when the context changes, thus raising the crucial need for belief updating. However, this issue has generally been neglected. By setting up a volatile environment, we show that expectation suppression emerges first in executive control regions, followed by relevant sensory areas, only when observers use their expectations to optimize behavior. This provides surprising yet clear evidence on how the brain controls the updating of sensory expectations for adaptive behavior in our ever-changing world.

Rewiring cortico-muscular control in the healthy and post-stroke human brain with proprioceptive beta-band neurofeedback

In severely affected stroke survivors, cortico-muscular control is disturbed and volitional upper limb movements often absent. Mental rehearsal of the impaired movement in conjunction with sensory feedback provision are suggested as promising rehabilitation exercises. Knowledge about the underlying neural processes, however, remains vague. In male and female chronic stroke patients with hand paralysis, a brain-computer interface controlled a robotic orthosis and turned sensorimotor beta-band desynchronization during motor imagery (MI) of finger extension into contingent hand opening. Healthy control subjects performed the same task and received the same proprioceptive feedback with a robotic orthosis or visual feedback only. Only when proprioceptive feedback was provided, cortico-muscular coherence (CMC) increased with a predominant information flow from the sensorimotor cortex to the finger extensors. This effect (i) was specific to the beta frequency-band, (ii) transferred to a motor task, (iii) was proportional to subsequent corticospinal excitability and correlated with behavioral changes in the (iv) healthy and (v) post-stroke condition; notably, MI-related enhancement of beta-band CMC in the ipsilesional premotor cortex correlated with motor improvements after the intervention. In the healthy and injured human nervous system, synchronized activation of motor-related cortical and spinal neural pools facilitates, in accordance with the communication-through-coherence hypothesis, cortico-spinal communication and may, thereby, be therapeutically relevant for functional restoration after stroke, when voluntary movements are no longer possible. Significance statement: This study provides insights into the neural processes that transfer effects of brain-computer interface neurofeedback to subsequent motor behavior. Specifically, volitional control of cortical oscillations and proprioceptive feedback enhances both cortical activity and behaviorally relevant connectivity to the periphery in a topographically circumscribed and frequency-specific way. This enhanced cortico-muscular control can be induced in the healthy and post-stroke brain. Thereby, activating the motor cortex with mental rehearsal of the impaired movement and closing the loop by robot-assisted feedback synchronizes ipsilesional premotor cortex and spinal neural pools in the beta-frequency band. This facilitates, in accordance with the communication-through-coherence hypothesis, cortico-spinal communication and may, thereby, be therapeutically relevant for functional restoration after stroke, when voluntary movements are no longer possible.