Ralph Adolphs

All animals exhibit complex behaviours that share features with those that in humans we call ‘emotional expressions’. Sidestepping contentious issues about the conscious experience of emotion, their expression across species provides a wealth of detail about their emergence in evolution, the shared features that distinguish them from reflexes, and principles for their neural control. This paper provides a high-level survey of this vast field. This article is part of the theme issue ‘Mechanisms, development, phylogeny and functions of emotional expressions’.

Amygdala responses are widely reported in BOLD fMRI studies of human emotions and mood disorders. Although modern acquisition methods have improved image quality, the hemodynamic nature of the BOLD signal continues to complicate interpretation of amygdala responses. Across an array of both visual and auditory tasks, we here show that apparent amygdala BOLD signal is substantially confounded by signal from nearby deep veins, including the basal vein of Rosenthal. In contrast to prior work, we show that when the amygdala is engaged, it is the leading but not exclusive contributor to this venous signal. Across the tested conditions, however, this signal was sensitive to, but not specific for, amygdala engagement. This confound mislocalizes apparent activation and prevents reliable attribution of signal to amygdala subnuclei with conventional BOLD fMRI. We further show that spatial smoothing exacerbates this mislocalization by merging peri-amygdalar venous signal with the anatomical amygdala. We reproduce our findings from precision imaging in a larger sample obtained from the Human Connectome Project. While broad conclusions about amygdala engagement remain largely valid when based on unsmoothed signal within the anatomical amygdala, further conclusions about subnuclear function drawn from conventional fMRI alone warrant considerable caution.

Pursuing longer-term goals relies on representations of task context that can be maintained over long periods of time and switched flexibly when goals change. Little is known about the neural substrate for maintaining context representations on the minute-timescale on which human behaviour frequently persists. Utilizing recordings in neurosurgical patients (total n = 25), we examined how neurons in the human medial frontal cortex and hippocampus persistently represent context. When cued explicitly, context was encoded in both brain areas and changed rapidly at task boundaries. The hippocampus exhibited a temporally dynamic code with fast decorrelation over time, preventing cross-temporal generalization. Medial frontal cortex exhibited a static code that decorrelated slowly, allowing generalization across time. When context needed to be inferred as a latent variable, the hippocampus encoded context with a static code. These findings reveal two formats for encoding minute-timescale context representations that were differentially engaged based on task demands.

People use hundreds of words to describe emotions and related mental states. Yet a large psychological literature and our own intuition argue for a simpler structure that underlies these attributions, since most of the words are antonyms or synonyms that map onto a few basic dimensions or categories. However, there is surprisingly little agreement on their number or interpretation: core affect is generally thought to be two-dimensional; emotion categories vary from six to over twenty; and according to some theories emotion concepts are much higher dimensional since they flexibly incorporate context. Although many of these debates originate in theoretical disagreements, we here focus on methodological sources: how stimuli are selected, tasks are chosen, and dimensionality reduction algorithms are used. We provide a survey of popular methods, their advantages and limitations, and recommendations for best practices.

The surge of online psychological assessments have brought the autism research community both opportunities and challenges: while they enable rapid large-scale data collection and more power to characterize individual differences, they also bring concerns about data quality, generalizability beyond online samples, and whether autistic traits can be reliably characterized with self-report measures administered online. Here we tackle these concerns by providing a systematic characterization of the autistic traits variability across individuals in a large cross-sectional dataset (N = 2826) as well as its temporal reliability within individuals in a test-retest dataset (N = 247), with both online and in-lab samples. We measured autistic traits using the Social Responsiveness Scale, 2nd version, Adult Self Report (SRS-2-ASR) – a tool that quantifies individual differences in autistic traits along a continuum for the general adult population. Across individuals, we found elevated SRS scores in online samples and were able to trace this effect to specific subsets of SRS items. SRS scores also covaried with internalizing symptoms, decreased with age, and were lower in women compared to other genders. Within individuals, we find moderate-to-good test-retest reliability of SRS scores over long intervals, with no difference between online and in-lab samples, suggesting robust temporal stability. We conclude that there are systematic differences in autistic traits between online and in-lab samples that are partly explained by systematic population-level differences in internalizing symptoms, particularly social anxiety. Future studies that sample across different populations should measure, control for, or stratify with respect to these factors.

Inferring the intentions and emotions of others from behavior is crucial for social cognition. While neuroimaging studies have identified brain regions involved in social inference, it remains unknown whether performing social inference is an abstract computation that generalizes across different stimulus categories or is specific to certain stimulus domain. We recorded single-neuron activity from the medial temporal lobe (MTL) and the medial frontal cortex (MFC) in neurosurgical patients performing different types of inferences from images of faces, hands, and natural scenes. Our findings indicate distinct neuron populations in both regions encoding inference type for social (faces, hands) and nonsocial (scenes) stimuli, while stimulus category was itself represented in a task-general manner. Uniquely in the MTL, social inference type was represented by separate subsets of neurons for faces and hands, suggesting a domain-specific representation. These results reveal evidence for specialized social inference processes in the MTL, in which inference representations were entangled with stimulus type as expected from a domain-specific process.

People form impressions of one another in a split second from faces. However, people also infer others’ momentary mental states on the basis of context—for example, one might infer that somebody feels encouraged from the fact that they are receiving constructive feedback. How do trait judgements of faces influence these context-based mental state inferences? In this Registered Report, we asked participants to infer the mental states of unfamiliar people, identified by their neutral faces, under specific contexts. To increase generalizability, we representatively sampled all stimuli from inclusive sets using computational methods. We tested four hypotheses: that trait impressions of faces (1) are correlated with subsequent mental state inferences in a range of contexts, (2) alter the dimensional space that underlies mental state inferences, (3) are associated with specific mental state dimensions in this space and (4) causally influence mental state inferences. We found evidence in support of all hypotheses.

We present a multimodal dataset of intracranial recordings, fMRI, and eye tracking in 20 participants during movie watching. Recordings consist of single neurons, local field potential, and intracranial EEG activity acquired from depth electrodes targeting the amygdala, hippocampus, and medial frontal cortex implanted for monitoring of epileptic seizures. Participants watched an 8-min long excerpt from the video “Bang! You’re Dead” and performed a recognition memory test for movie content. 3 T fMRI activity was recorded prior to surgery in 11 of these participants while performing the same task. This NWB- and BIDS-formatted dataset includes spike times, field potential activity, behavior, eye tracking, electrode locations, demographics, and functional and structural MRI scans. For technical validation, we provide signal quality metrics, assess eye tracking quality, behavior, the tuning of cells and high-frequency broadband power field potentials to familiarity and event boundaries, and show brain-wide inter-subject correlations for fMRI. This dataset will facilitate the investigation of brain activity during movie watching, recognition memory, and the neural basis of the fMRI-BOLD signal.