Cognition seminars

I will present field experiments on vervet monkeys testing physical and social cognition, with a focus on social learning. The understanding of the emergence of cultural behaviours in animals has advanced significantly with contributions from complementary approaches: natural observations and controlled field experiments. Experiments with wild vervet monkeys highlight that monkeys are selective about ‘who’ they learn from socially and that they will abandon personal foraging preferences in favour of group norms new to them. The reported findings highlight the feasibility to study cognition under field conditions.

Initial social perceptions are often thought to reflect direct “read outs” of facial features. Instead, we outline a perspective whereby initial perceptions emerge from an automatic yet gradual process of negotiation between the perceptual cues inherent to a person (e.g., facial cues) and top-down social cognitive processes harbored within perceivers. This perspective argues that perceivers’ social-conceptual knowledge in particular can have a fundamental structuring role in perceptions, and thus how we think about social groups, emotions, or personality traits helps determine how we visually perceive them in other people. Integrative evidence from real-time behavioral paradigms (e.g., mouse-tracking), multivariate fMRI, and computational modeling will be discussed. Together, this work shows that the way we use facial cues to categorize other people into social groups (e.g., gender, race), perceive their emotion (e.g., anger), or infer their personality (e.g., trustworthiness) are all fundamentally shaped by prior social-conceptual knowledge and stereotypical assumptions. We find that these top-down impacts on initial perceptions are driven by the interplay of higher-order prefrontal regions involved in top-down predictions and lower-level fusiform regions involved in face processing. We argue that the perception of social categories, emotions, and traits from faces can all be conceived as resulting from an integrated system relying on domain-general cognitive properties. In this system, both visual and social cognitive processes are in a close exchange, and initial social perceptions emerge in part out of the structure of social-conceptual knowledge.

Team work makes sensory streams work: our senses work together, learn from each other, and stand in for one another, the result of which is perception and understanding. Learned associations between stimuli in different sensory modalities can shape the way we perceive these stimuli (Mcgurk and Macdonald, 1976). During audio-visual associative learning, auditory cortex is thought to underlie multi-modal plasticity in visual cortex (McIntosh et al., 1998; Mishra et al., 2007; Zangenehpour and Zatorre, 2010). However, it is not well understood how processing in visual cortex is altered by an auditory stimulus that is predictive of a visual stimulus and what the mechanisms are that mediate such experience-dependent, audio-visual associations in sensory cortex. Here we describe a neural mechanism by which an auditory input can shape visual representations of behaviorally relevant stimuli through direct interactions between auditory and visual cortices. We show that the association of an auditory stimulus with a visual stimulus in a behaviorally relevant context leads to an experience-dependent suppression of visual responses in primary visual cortex (V1). Auditory cortex axons carry a mixture of auditory and retinotopically-matched visual input to V1, and optogenetic stimulation of these axons selectively suppresses V1 neurons responsive to the associated visual stimulus after, but not before, learning. Our results suggest that cross-modal associations can be stored in long-range cortical connections and that with learning these cross-modal connections function to suppress the responses to predictable input.

Studies of neural circuit plasticity focus almost exclusively on functional and structural changes of neuronal synapses. In recent years, however, myelin plasticity has emerged as a potential modulator of neuronal networks. Myelination of previously unmyelinated axons and changes in the structure on already-myelinated axons can have large effects on the function of neuronal networks. Yet myelination has been mostly studied in relation to its functional and metabolic activity. Myelin modifications are increasingly being implicated as a mechanism for sensory-motor learning and unpublished data from our lab indicate that myelination also occurs during cognitive non-motor learning. It is, however, unclear how specific these myelin changes are and even less is known of the underlying mechanisms of learning-evoked myelin plasticity. In this journal club, Dr Giulia Bonetto will provide a general overview on myelin plasticity. Additionally, she will present new data addressing the role of myelin plasticity in cognitive non-motor learning.

I will discuss the mechanisms that determine whether a weak visual stimulus will reach consciousness or not. If the stimulus is simple, early visual cortex acts as a relay station that sends the information to higher visual areas. If the stimulus arrives at a minimal strength, it will be stored in working memory. However, during more complex visual perceptions, which for example depend on the segregation of a figure from the background, early visual cortex’ role goes beyond a simply relay. It now acts as a cognitive blackboard and conscious perception depends on it. Our results also inspire new approaches to create a visual prosthesis for the blind, by creating a direct interface with the visual cortex. I will discuss how high-channel-number interfaces with the visual cortex might be used to restore a rudimentary form of vision in blind individuals.

The COINTOB (conditional intention and integration to bound) model provides a heuristic framework of processes in Libet-style experiments. The model is based on three assumptions. First, brain activation preceding conscious intentions in Libet-style experiments does not reflect an unconscious decision but rather the unfolding of a decision process. Second, the time of conscious decision (W) reflects the moment in time when the decision boundary is crossed. This interpretation of W is consistent with our apparent intuition that we decide in the moment we experience the conscious intention to act. Third, the decision process is configured by conscious intentions that participants form at the beginning of the experiment based on the experimental instruction. Brass and Mele discuss the model, conceptual background for it, and the model’s bearing on free will.

In many learning and decision scenarios, especially sequential settings like mazes or games, it is easy to state an objective function but difficult to compute it, for instance because this can require enumerating many possible future trajectories. This, in turn, motivates a variety of more tractable approximations which then raise resource-rationality questions about whether and when an efficient agent should invest time or resources in computing decision variables more accurately. Previous work has used a simple all-or-nothing version of this reasoning as a framework to explain many phenomena of automaticity, habits, and compulsion in humans and animals. Here, I present a more finegrained theoretical analysis of deliberation, which attempts to address not just whether to deliberate vs. act, but which of many possible actions and trajectories to consider. Empirically, I first motivate and compare this account to nonlocal representations of spatial trajectories in the rodent place cell system, which are thought to be involved in planning. I also consider its implications, in humans, for variation over time and situations in subjective feelings of mental effort, boredom, and cognitive fatigue. Finally, I present results from a new study using magnetoencephalography in humans to measure subjective consideration of possible trajectories during a sequential learning task, and study its relationship to rational prioritization and to choice behavior.

Regulation of information flow in the brain is critical for many forms of behavior. In the process of sensory based decision-making, decisions about future actions are held in memory until enacted, making them potentially vulnerable to distracting sensory input. Therefore, gating of information flow from sensory to motor areas could protect memory from interference during decision-making, but the underlying network mechanisms are not understood. I will present our recent experimental and modeling work describing how information flow from the sensory cortex can be gated by state-dependent frontal cortex dynamics during decision-making in mice. Our results show that communication between brain regions can be regulated via attractor dynamics, which control the degree of commitment to an action, and reveal a novel mechanism of gating of neural information.

Concerns about the impact of social media use on adolescent well-being and mental health are common. While the amount of research in this area has increased rapidly over the last 5 years, most outputs are still marred by a multitude of limitations. These shortcomings have left our understanding of social media effects severely limited, holding back both scientific discovery and policy interventions. This talk discusses how developmental, cognitive and neuroscientific approaches might provide a new and improved way of studying social media effects. It will detail new studies in support of this idea, and raise potential avenues for collaborative work across the Cambridge Neuroscience community. As the digital world now (re)shapes what it means for us to live, communicate and develop, only an interdisciplinary approach will allow us to truly understand its impacts.

Having conscious experience is arguably the most important reason why it matters to us whether we are alive or dead. A powerful paradigm to identify neural correlates of consciousness is binocular rivalry, wherein a constant visual stimulus evokes a varying conscious percept. It has recently been suggested that activity modulations observed during rivalry may represent the act of report rather than the conscious percept itself. Here, we performed single-unit recordings from face patches in macaque inferotemporal (IT) cortex using a novel no-report paradigm in which the animal’s conscious percept was inferred from eye movements. These experiments reveal two new results concerning the neural correlates of consciousness. First, we found that high proportions of IT neurons represented the conscious percept even without active report. Using high-channel recordings, including a new 128-channel Neuropixels-like probe, we were able to decode the conscious percept on single trials. Second, we found that even on single trials, modulation to rivalrous stimuli was weaker than that to unambiguous stimuli, suggesting that cells may encode not only the conscious percept but also the suppressed stimulus. To test this hypothesis, we varied the identity of the suppressed stimulus during binocular rivalry; we found that indeed, we could decode not only the conscious percept but also the suppressed stimulus from neural activity. Moreover, the same cells that were strongly modulated by the conscious percept also tended to be strongly modulated by the suppressed stimulus. Together, our findings indicate that (1) IT cortex possesses a true neural correlate of consciousness even in the absence of report, and (2) this correlate consists of a population code wherein single cells multiplex representation of the conscious percept and veridical physical stimulus, rather than a subset of cells perfectly reflecting consciousness.

Drosophila can learn to associate odours with reward or punishment and the resulting memories direct odour-specific approach or avoidance behaviours. Recent progress has revealed a straightforward model for learning in which reinforcing dopaminergic neurons assign valence to odour representations in the neural ensemble of the mushroom bodies. Dopamine directed synaptic depression alters the route of odour-driven activity through the mushroom body output network. This circuit configuration and influence of internal state guide the expression of appropriate behaviour. Importantly, learned behaviour is flexible and can be updated as the fly accumulates additional experience. Our latest studies demonstrate that well-informed behaviour is guided by combining parallel conflicting and complementary memories of opposite valence.

Join us for a conversation on the science of uncertainty, mind wandering and creativity!

Join us for a conversation on the science of uncertainty, mind wandering and creativity!

Sequential temporal ordering and patterning are key features of natural signals, used by the brain to decode stimuli and perceive them as sensory objects. Touch is one sensory modality where temporal patterning carries key information, and the rodent whisker system is a prominent model for understanding neuronal coding and plasticity underlying touch sensation. Neurons in this system are precise encoders of fluctuations in whisker dynamics down to a timescale of milliseconds, but it is not clear whether they can refine their encoding abilities as a result of learning patterned stimuli. For example, can they enhance temporal integration to become better at distinguishing sequences? To explore how cortical coding plasticity underpins sequence discrimination, we developed a task in which mice distinguished between tactile ‘word’ sequences constructed from distinct vibrations delivered to the whiskers, assembled in different orders. Animals licked to report the presence of the target sequence. Optogenetic inactivation showed that the somatosensory cortex was necessary for sequence discrimination. Two-photon imaging in layer 2/3 of the primary somatosensory “barrel” cortex (S1bf) revealed that, in well-trained animals, neurons had heterogeneous selectivity to multiple task variables including not just sensory input but also the animal’s action decision and the trial outcome (presence or absence of the predicted reward). Many neurons were activated preceding goal-directed licking, thus reflecting the animal’s learnt action in response to the target sequence; these neurons were found as soon as mice learned to associate the rewarded sequence with licking. In contrast, learning evoked smaller changes in sensory response tuning: neurons responding to stimulus features were already found in naïve mice, and training did not generate neurons with enhanced temporal integration or categorical responses. Therefore, in S1bf sequence learning results in neurons whose activity reflects the learnt association between target sequence and licking, rather than a refined representation of sensory features. Taken together with results from other laboratories, our findings suggest that neurons in sensory cortex are involved in task-specific processing and that an animal does not sense the world independently of what it needs to feel in order to guide behaviour.