Towards emotionally aligned social robots for dementia: perspectives of care partners and persons with dementia.

BACKGROUND: Persons living with dementia and their care partners place a high value on aging in place and maintaining independence. Socially assistive robots - embodied characters or pets that provide companionship and aid through social interaction - are a promising tool to support these goals. There is a growing commercial market for these devices, with functions including medication reminders, conversation, pet-like behaviours, and even the collection of health data. While potential users generally report positive feelings towards social robots, persons with dementia have been under-included in design and development, leading to a disconnect between robot functions and the real-world needs and desires of end-users. Furthermore, a key element of social and emotional connectedness in human relationships is emotional alignment - a state where all partners have congruent emotional understandings of a situation. Strong emotional alignment between users and robots will be necessary for social robots to provide meaningful companionship, but a computational model of how to achieve this has been absent from the field. To this end, we propose and test Affect Control Theory (ACT) as a framework to improve emotional alignment between older adults and social robotics. METHOD: Using a Canadian online survey, we introduced respondents to three exemplar social robots with older adult-specific functionalities and evaluated their responses around features, emotions, and ethics using standardized and novel measures (n=171 older adults, n=28 care partners, and n=7 persons living with dementia). RESULT: Overall, participants responded positively to the robots. High priority uses included companionship, interaction, and safety. Reasoning around robot use was pragmatic; curiosity and entertainment were motivators to use, while a perceived lack of need and the mechanical appearance of the robots were detractors. Realistic, cute, and cuddly robots were preferred while artificial-looking, creepy, and toy-like robots were disliked. Most importantly, our evidence supported ACT as a viable model of human-robot emotional alignment. CONCLUSION: This work supports the development of emotionally sophisticated, evidence-based, and user-centered social robotics with older adult- and dementia-specific functionality.

Whisker touch sensing guides locomotion in small, quadrupedal mammals.

All small mammals have prominent facial whiskers that they employ as tactile sensors to guide navigation and foraging in complex habitats. Nocturnal, arboreal mammals tend to have the longest and most densely packed whiskers, and semi-aquatic mammals have the most sensitive. Here we present evidence to indicate that many small mammals use their whiskers to tactually guide safe foot positioning. Specifically, in 11, small, non-flying mammal species, we demonstrate that forepaw placement always falls within the ground contact zone of the whisker field and that forepaw width is always smaller than whisker span. We also demonstrate commonalities of whisker scanning movements (whisking) and elements of active control, associated with increasing contact with objects of interest, across multiple small mammal species that have previously only been shown in common laboratory animals. Overall, we propose that guiding locomotion, alongside environment exploration, is a common function of whisker touch sensing in small, quadrupedal mammals.

Whisker touch guides canopy exploration in a nocturnal, arboreal rodent, the Hazel dormouse (Muscardinus avellanarius).

Dormouse numbers are declining in the UK due to habitat loss and fragmentation. We know that dormice are nocturnal, arboreal, and avoid crossing open spaces between habitats, yet how they navigate around their canopy is unknown. As other rodents use whisker touch sensing to navigate and explore their environment, this study investigates whether Hazel dormice (Muscardinus avellanarius) employ their whiskers to cross between habitats. We analysed high-speed video footage of dormice exploring freely in flat and climbing arenas in near darkness and using infrared light illumination. We confirm that, like rats and mice, dormice move their whiskers back and forth continuously (~10 Hz) in a motion called whisking and recruit them to explore small gaps (<10 cm) by increasing the amplitude and frequency of whisking and also the asymmetry of movement between the left and right whisker fields. When gaps between platforms are larger than 10-15 cm, dormice spend more time travelling on the floor. These findings suggest that dormice can actively and purposively move their whiskers to gather relevant information from their canopy at night. As this species is vulnerable to threats on the ground, we also provide evidence that joining habitat patches between dormouse populations is important for promoting natural behaviours and movement between patches.

Whisker movements reveal spatial attention: a unified computational model of active sensing control in the rat.

Spatial attention is most often investigated in the visual modality through measurement of eye movements, with primates, including humans, a widely-studied model. Its study in laboratory rodents, such as mice and rats, requires different techniques, owing to the lack of a visual fovea and the particular ethological relevance of orienting movements of the snout and the whiskers in these animals. In recent years, several reliable relationships have been observed between environmental and behavioural variables and movements of the whiskers, but the function of these responses, as well as how they integrate, remains unclear. Here, we propose a unifying abstract model of whisker movement control that has as its key variable the region of space that is the animal's current focus of attention, and demonstrate, using computer-simulated behavioral experiments, that the model is consistent with a broad range of experimental observations. A core hypothesis is that the rat explicitly decodes the location in space of whisker contacts and that this representation is used to regulate whisker drive signals. This proposition stands in contrast to earlier proposals that the modulation of whisker movement during exploration is mediated primarily by reflex loops. We go on to argue that the superior colliculus is a candidate neural substrate for the siting of a head-centred map guiding whisker movement, in analogy to current models of visual attention. The proposed model has the potential to offer a more complete understanding of whisker control as well as to highlight the potential of the rodent and its whiskers as a tool for the study of mammalian attention.

Simulated Dopamine Modulation of a Neurorobotic Model of the Basal Ganglia.

The vertebrate basal ganglia play an important role in action selection-the resolution of conflicts between alternative motor programs. The effective operation of basal ganglia circuitry is also known to rely on appropriate levels of the neurotransmitter dopamine. We investigated reducing or increasing the tonic level of simulated dopamine in a prior model of the basal ganglia integrated into a robot control architecture engaged in a foraging task inspired by animal behaviour. The main findings were that progressive reductions in the levels of simulated dopamine caused slowed behaviour and, at low levels, an inability to initiate movement. These states were partially relieved by increased salience levels (stronger sensory/motivational input). Conversely, increased simulated dopamine caused distortion of the robot's motor acts through partially expressed motor activity relating to losing actions. This could also lead to an increased frequency of behaviour switching. Levels of simulated dopamine that were either significantly lower or higher than baseline could cause a loss of behavioural integration, sometimes leaving the robot in a 'behavioral trap'. That some analogous traits are observed in animals and humans affected by dopamine dysregulation suggests that robotic models could prove useful in understanding the role of dopamine neurotransmission in basal ganglia function and dysfunction.

The evolution of active vibrissal sensing in mammals: evidence from vibrissal musculature and function in the marsupial opossum Monodelphis domestica.

Facial vibrissae, or whiskers, are found in nearly all extant mammal species and are likely to have been present in early mammalian ancestors. A sub-set of modern mammals, including many rodents, move their long mystacial whiskers back and forth at high speed whilst exploring in a behaviour known as 'whisking'. It is not known whether the vibrissae of early mammals moved in this way. The grey short-tailed opossum, Monodelphis domestica, is considered a useful species from the perspective of tracing the evolution of modern mammals. Interestingly, these marsupials engage in whisking bouts similar to those seen in rodents. To better assess the likelihood that active vibrissal sensing was present in ancestral mammals, we examined the vibrissal musculature of the opossum using digital miscroscopy to see whether this resembles that of rodents. Although opossums have fewer whiskers than rats, our investigation found that they have a similar vibrissal musculature. In particular, in both rats and opossums, the musculature includes both intrinsic and extrinsic muscles with the intrinsic muscles positioned as slings linking pairs of large vibrissae within rows. We identified some differences in the extrinsic musculature which, interestingly, matched with behavioural data obtained through high-speed video recording, and indicated additional degrees of freedom for positioning the vibrissae in rats. These data show that the whisker movements of opossum and rat exploit similar underlying mechanisms. Paired with earlier results suggesting similar patterns of vibrissal movement, this strongly implies that early therian (marsupial and placental) mammals were whisking animals that actively controlled their vibrissae.

Understanding brain functional architecture through robotics.

Robotics is increasingly seen as a useful test bed for computational models of the brain functional architecture underlying animal behavior. We provide an overview of past and current work, focusing on probabilistic and dynamical models, including approaches premised on the free energy principle, situating this endeavor in relation to evidence that the brain constitutes a layered control system. We argue that future neurorobotic models should integrate multiple neurobiological constraints and be hybrid in nature.

Neural computation via neural geometry: a place code for inter-whisker timing in the barrel cortex?

The place theory proposed by Jeffress (1948) is still the dominant model of how the brain represents the movement of sensory stimuli between sensory receptors. According to the place theory, delays in signalling between neurons, dependent on the distances between them, compensate for time differences in the stimulation of sensory receptors. Hence the location of neurons, activated by the coincident arrival of multiple signals, reports the stimulus movement velocity. Despite its generality, most evidence for the place theory has been provided by studies of the auditory system of auditory specialists like the barn owl, but in the study of mammalian auditory systems the evidence is inconclusive. We ask to what extent the somatosensory systems of tactile specialists like rats and mice use distance dependent delays between neurons to compute the motion of tactile stimuli between the facial whiskers (or 'vibrissae'). We present a model in which synaptic inputs evoked by whisker deflections arrive at neurons in layer 2/3 (L2/3) somatosensory 'barrel' cortex at different times. The timing of synaptic inputs to each neuron depends on its location relative to sources of input in layer 4 (L4) that represent stimulation of each whisker. Constrained by the geometry and timing of projections from L4 to L2/3, the model can account for a range of experimentally measured responses to two-whisker stimuli. Consistent with that data, responses of model neurons located between the barrels to paired stimulation of two whiskers are greater than the sum of the responses to either whisker input alone. The model predicts that for neurons located closer to either barrel these supralinear responses are tuned for longer inter-whisker stimulation intervals, yielding a topographic map for the inter-whisker deflection interval across the surface of L2/3. This map constitutes a neural place code for the relative timing of sensory stimuli.

The development of whisker control in rats in relation to locomotion.

Adult rats sweep their large facial whiskers (macrovibrissae) back and forth in a rhythmic pattern known as "whisking". Here we examine how these whisker movements develop in relation to other aspects of exploratory behavior, particularly locomotion. We analyzed 963 high-speed video recordings of neonatal rats, from P1 (Post-natal day 1) to P21, and measured the emergence of whisker control and of head, body, and limb movements. Prior to P11, whisker movements were largely limited to unilateral retractions accompanying head turns. Between P11 and P13 bilateral whisking emerged alongside increased forward locomotion and improved control of the head. Contact-induced modulations of whisking symmetry, synchrony, and whisker spread emerge shortly thereafter but continue to develop until at least P18, coinciding with the emergence of adult-like locomotion patterns such as rearing. Overall, whisking develops alongside increasing locomotor competence indicating that active vibrissal sensing plays an important role in the exploratory behavior of the developing animal.

Scaffolding layered control architectures through constraint closure: insights into brain evolution and development.

The functional organization of the mammalian brain can be considered to form a layered control architecture, but how this complex system has emerged through evolution and is constructed during development remains a puzzle. Here we consider brain organization through the framework of constraint closure, viewed as a general characteristic of living systems, that they are composed of multiple sub-systems that constrain each other at different timescales. We do so by developing a new formalism for constraint closure, inspired by a previous model showing how within-lifetime dynamics can constrain between-lifetime dynamics, and we demonstrate how this interaction can be generalized to multi-layered systems. Through this model, we consider brain organization in the context of two major examples of constraint closure-physiological regulation and visual orienting. Our analysis draws attention to the capacity of layered brain architectures to scaffold themselves across multiple timescales, including the ability of cortical processes to constrain the evolution of sub-cortical processes, and of the latter to constrain the space in which cortical systems self-organize and refine themselves. This article is part of the theme issue 'Systems neuroscience through the lens of evolutionary theory'.

A robotic model of hippocampal reverse replay for reinforcement learning.

Hippocampal reverse replay, a phenomenon in which recently active hippocampal cells reactivate in the reverse order, is thought to contribute to learning, particularly reinforcement learning (RL), in animals. Here, we present a novel computational model which exploits reverse replay to improve stability and performance on a homing task. The model takes inspiration from the hippocampal-striatal network, and learning occurs via a three-factor RL rule. To augment this model with hippocampal reverse replay, we derived a policy gradient learning rule that associates place-cell activity with responses in cells representing actions and a supervised learning rule of the same form, interpreting the replay activity as a 'target' frequency. We evaluated the model using a simulated robot spatial navigation task inspired by the Morris water maze. Results suggest that reverse replay can improve performance stability over multiple trials. Our model exploits reverse reply as an additional source for propagating information about desirable synaptic changes, reducing the requirements for long-time scales in eligibility traces combined with low learning rates. We conclude that reverse replay can positively contribute to RL, although less stable learning is possible in its absence. Analogously, we postulate that reverse replay may enhance RL in the mammalian hippocampal-striatal system rather than provide its core mechanism.

User perspectives on emotionally aligned social robots for older adults and persons living with dementia.

Introduction: Socially assistive robots are devices designed to aid users through social interaction and companionship. Social robotics promise to support cognitive health and aging in place for older adults with and without dementia, as well as their care partners. However, while new and more advanced social robots are entering the commercial market, there are still major barriers to their adoption, including a lack of emotional alignment between users and their robots. Affect Control Theory (ACT) is a framework that allows for the computational modeling of emotional alignment between two partners. Methods: We conducted a Canadian online survey capturing attitudes, emotions, and perspectives surrounding pet-like robots among older adults (n = 171), care partners (n = 28), and persons living with dementia (n = 7). Results: We demonstrate the potential of ACT to model the emotional relationship between older adult users and three exemplar robots. We also capture a rich description of participants' robot attitudes through the lens of the Technology Acceptance Model, as well as the most important ethical concerns around social robot use. Conclusions: Findings from this work will support the development of emotionally aligned, user-centered robots for older adults, care partners, and people living with dementia.

Are friends electric? The benefits and risks of human-robot relationships.

Social robots that can interact and communicate with people are growing in popularity for use at home and in customer-service, education, and healthcare settings. Although growing evidence suggests that co-operative and emotionally aligned social robots could benefit users across the lifespan, controversy continues about the ethical implications of these devices and their potential harms. In this perspective, we explore this balance between benefit and risk through the lens of human-robot relationships. We review the definitions and purposes of social robots, explore their philosophical and psychological status, and relate research on human-human and human-animal relationships to the emerging literature on human-robot relationships. Advocating a relational rather than essentialist view, we consider the balance of benefits and harms that can arise from different types of relationship with social robots and conclude by considering the role of researchers in understanding the ethical and societal impacts of social robotics.

Addressing the Ethics of Telepresence Applications Through End-User Engagement.

Portacolone et al.'s Ethics Review highlights the ethical challenges associated with the implementation of telepresence devices and applications in the context of aging and dementia. In this response, we review ethical considerations as they relate to specific modalities of telepresence, with an emphasis on the continuum of potential interaction agents, from known individuals to fully automated and intelligent interlocutors. We further discuss areas in need of empirical evidence to inform regulatory efforts in telepresence. We close with a call for meaningful end-user engagement at all stages of technology development.

Memory and mental time travel in humans and social robots.

From neuroscience, brain imaging and the psychology of memory, we are beginning to assemble an integrated theory of the brain subsystems and pathways that allow the compression, storage and reconstruction of memories for past events and their use in contextualizing the present and reasoning about the future-mental time travel (MTT). Using computational models, embedded in humanoid robots, we are seeking to test the sufficiency of this theoretical account and to evaluate the usefulness of brain-inspired memory systems for social robots. In this contribution, we describe the use of machine learning techniques-Gaussian process latent variable models-to build a multimodal memory system for the iCub humanoid robot and summarize results of the deployment of this system for human-robot interaction. We also outline the further steps required to create a more complete robotic implementation of human-like autobiographical memory and MTT. We propose that generative memory models, such as those that form the core of our robot memory system, can provide a solution to the symbol grounding problem in embodied artificial intelligence. This article is part of the theme issue 'From social brains to social robots: applying neurocognitive insights to human-robot interaction'.

The Combinatorial Creature: Cortical Phenotypes within and across Lifetimes.

The neocortex is one of the most distinctive structures of the mammalian brain, yet also one of the most varied in terms of both size and organization. Multiple processes have contributed to this variability, including evolutionary mechanisms (i.e., alterations in gene sequence) that alter the size, organization, and connections of neocortex, and activity dependent mechanisms that can also modify these same features. Thus, changes to the neocortex can occur over different time-scales, including within a single generation. This combination of genetic and activity dependent mechanisms that create a given cortical phenotype allows the mammalian neocortex to rapidly and flexibly adjust to different body and environmental contexts, and in humans permits culture to impact brain construction.

iCub-HRI: A Software Framework for Complex Human-Robot Interaction Scenarios on the iCub Humanoid Robot.

Generating complex, human-like behavior in a humanoid robot like the iCub requires the integration of a wide range of open source components and a scalable cognitive architecture. Hence, we present the iCub-HRI library which provides convenience wrappers for components related to perception (object recognition, agent tracking, speech recognition, and touch detection), object manipulation (basic and complex motor actions), and social interaction (speech synthesis and joint attention) exposed as a C++ library with bindings for Java (allowing to use iCub-HRI within Matlab) and Python. In addition to previously integrated components, the library allows for simple extension to new components and rapid prototyping by adapting to changes in interfaces between components. We also provide a set of modules which make use of the library, such as a high-level knowledge acquisition module and an action recognition module. The proposed architecture has been successfully employed for a complex human-robot interaction scenario involving the acquisition of language capabilities, execution of goal-oriented behavior and expression of a verbal narrative of the robot's experience in the world. Accompanying this paper is a tutorial which allows a subset of this interaction to be reproduced. The architecture is aimed at researchers familiarizing themselves with the iCub ecosystem, as well as expert users, and we expect the library to be widely used in the iCub community.

Feedback control in active sensing: rat exploratory whisking is modulated by environmental contact.

Rats sweep their facial whiskers back and forth to generate tactile sensory information through contact with environmental structure. The neural processes operating on the signals arising from these whisker contacts are widely studied as a model of sensing in general, even though detailed knowledge of the natural circumstances under which such signals are generated is lacking. We used digital video tracking and wireless recording of mystacial electromyogram signals to assess the effects of whisker-object contact on whisking in freely moving animals exploring simple environments. Our results show that contact leads to reduced protraction (forward whisker motion) on the side of the animal ipsilateral to an obstruction and increased protraction on the contralateral side. Reduced ipsilateral protraction occurs rapidly and in the same whisk cycle as the initial contact. We conclude that whisker movements are actively controlled so as to increase the likelihood of environmental contacts while constraining such interactions to involve a gentle touch. That whisking pattern generation is under strong feedback control has important implications for understanding the nature of the signals reaching upstream neural processes.

IntelliTable: Inclusively-Designed Furniture with Robotic Capabilities.

IntelliTable is a new proof-of-principle assistive technology system with robotic capabilities in the form of an elegant universal cantilever table able to move around by itself, or under user control. We describe the design and current capabilities of the table and the human-centered design methodology used in its development and initial evaluation. The IntelliTable study has delivered robotic platform programmed by a smartphone that can navigate around a typical home or care environment, avoiding obstacles, and positioning itself at the user's command. It can also be configured to navigate itself to pre-ordained places positions within an environment using ceiling tracking, responsive optical guidance and object-based sonar navigation.

Computational models of the basal ganglia: from robots to membranes.

With the rapid accumulation of neuroscientific data comes a pressing need to develop models that can explain the computational processes performed by the basal ganglia. Relevant biological information spans a range of structural levels, from the activity of neuronal membranes to the role of the basal ganglia in overt behavioural control. This viewpoint presents a framework for understanding the aims, limitations and methods for testing of computational models across all structural levels. We identify distinct modelling strategies that can deliver important and complementary insights into the nature of problems the basal ganglia have evolved to solve, and describe methods that are used to solve them.