A Neural Signature Encoding Decisions under Perceptual Ambiguity

Prioritized neural processing of social threats during perceptual decision-making

Emotional signals, notably those signaling threat, benefit from prioritized processing in the human brain. Yet, it remains unclear whether perceptual decisions about the emotional, threat-related aspects of stimuli involve specific or similar neural computations compared to decisions about their non-threatening/non-emotional components. We developed a novel behavioral paradigm in which participants performed two different detection tasks (emotion vs. color) on the same, two-dimensional visual stimuli. First, electroencephalographic (EEG) activity in a cluster of central electrodes reflected the amount of perceptual evidence around 100 ms following stimulus onset, when the decision concerned emotion, not color. Second, participants' choice could be predicted earlier for emotion (240 ms) than for color (380 ms) by the mu (10 Hz) rhythm, which reflects motor preparation. Taken together, these findings indicate that perceptual decisions about threat-signaling dimensions of facial displays are associated with prioritized neural coding in action-related brain regions, supporting the motivational value of socially relevant signals.

An EEG Dataset of Neural Signatures in a Competitive Two-Player Game Encouraging Deceptive Behavior

Studying deception is vital for understanding decision-making and social dynamics. Recent EEG research has deepened insights into the brain mechanisms behind deception. Standard methods in this field often rely on memory, are vulnerable to countermeasures, yield false positives, and lack real-world relevance. Here, we present a comprehensive dataset from an EEG-monitored competitive, two-player card game designed to elicit authentic deception behavior. Our extensive dataset contains EEG data from 12 pairs (N = 24 participants with role switching), controlled for age, gender, and risk-taking, with detailed labels and annotations. The dataset combines standard event-related potential and microstate analyses with state-of-the-art decoding approaches of four scenarios: spontaneous/instructed truth-telling and lying. This demonstrates game-based methods' efficacy in studying deception and sets a benchmark for future research. Overall, our dataset represents a unique resource with applications in cognitive neuroscience and related fields for studying deception, competitive behavior, decision-making, inter-brain synchrony, and benchmarking of decoding frameworks in a difficult, high-level cognitive task.

A uniform human multimodal dataset for emotion perception and judgment

Face perception is a fundamental aspect of human social interaction, yet most research on this topic has focused on single modalities and specific aspects of face perception. Here, we present a comprehensive multimodal dataset for examining facial emotion perception and judgment. This dataset includes EEG data from 97 unique neurotypical participants across 8 experiments, fMRI data from 19 neurotypical participants, single-neuron data from 16 neurosurgical patients (22 sessions), eye tracking data from 24 neurotypical participants, behavioral and eye tracking data from 18 participants with ASD and 15 matched controls, and behavioral data from 3 rare patients with focal bilateral amygdala lesions. Notably, participants from all modalities performed the same task. Overall, this multimodal dataset provides a comprehensive exploration of facial emotion perception, emphasizing the importance of integrating multiple modalities to gain a holistic understanding of this complex cognitive process. This dataset serves as a key missing link between human neuroimaging and neurophysiology literature, and facilitates the study of neuropsychiatric populations.

Functional connectivity between the amygdala and prefrontal cortex underlies processing of emotion ambiguity

Processing facial expressions of emotion draws on a distributed brain network. In particular, judging ambiguous facial emotions involves coordination between multiple brain areas. Here, we applied multimodal functional connectivity analysis to achieve network-level understanding of the neural mechanisms underlying perceptual ambiguity in facial expressions. We found directional effective connectivity between the amygdala, dorsomedial prefrontal cortex (dmPFC), and ventromedial PFC, supporting both bottom-up affective processes for ambiguity representation/perception and top-down cognitive processes for ambiguity resolution/decision. Direct recordings from the human neurosurgical patients showed that the responses of amygdala and dmPFC neurons were modulated by the level of emotion ambiguity, and amygdala neurons responded earlier than dmPFC neurons, reflecting the bottom-up process for ambiguity processing. We further found parietal-frontal coherence and delta-alpha cross-frequency coupling involved in encoding emotion ambiguity. We replicated the EEG coherence result using independent experiments and further showed modulation of the coherence. EEG source connectivity revealed that the dmPFC top-down regulated the activities in other brain regions. Lastly, we showed altered behavioral responses in neuropsychiatric patients who may have dysfunctions in amygdala-PFC functional connectivity. Together, using multimodal experimental and analytical approaches, we have delineated a neural network that underlies processing of emotion ambiguity.

Task Modulation of Single-Neuron Activity in the Human Amygdala and Hippocampus

The human amygdala and hippocampus are critically involved in various processes in face perception. However, it remains unclear how task demands or evaluative contexts modulate processes underlying face perception. In this study, we employed two task instructions when participants viewed the same faces and recorded single-neuron activity from the human amygdala and hippocampus. We comprehensively analyzed task modulation for three key aspects of face processing and we found that neurons in the amygdala and hippocampus (1) encoded high-level social traits such as perceived facial trustworthiness and dominance and this response was modulated by task instructions; (2) encoded low-level facial features and demonstrated region-based feature coding, which was not modulated by task instructions; and (3) encoded fixations on salient face parts such as the eyes and mouth, which was not modulated by task instructions. Together, our results provide a comprehensive survey of task modulation of neural processes underlying face perception at the single-neuron level in the human amygdala and hippocampus.

Trustworthiness and electrocortical processing of emotionally ambiguous faces in student police officers

Perceptions of emotional facial expressions and trustworthiness of others guides behavior and has considerable implications for individuals who work in fields that require rapid decision making, such as law enforcement. This is particularly complicated for more ambiguous expressions, such as 'neutral' faces. We examined behavioral and electrocortical responses to facial expressions in 22 student police officers (18 males; 23.2 ± 3.63 years). Participants completed an emotional face appraisal task that involved viewing three expressions (fearful, neutral, happy) and were asked to identify the emotion and rate the trustworthiness of each face. The late positive potential (LPP), an event-related potential that tracks emotional intensity and/or salience of a stimulus, was measured during the task. Overall, participants rated neutral faces similarly to fearful faces and responded fastest to these expressions. Neutral faces also elicited a robust late LPP response that did not differ from LPP to fearful or happy faces, and there was substantial individual variation in trustworthiness ratings for neutral faces. Together, 'neutral' facial expressions elicited similar trustworthiness ratings to negatively-valenced stimuli. Brain and behavioral responses to neutral faces also varied across student officers; thus, encounters with ambiguous faces in the field may promote increased perceived threat in some officers, which may have real-world consequences (e.g., decision to shoot, risk of psychopathology).

The neural basis of feedback-guided behavioral adjustment

Given feedback on the outcomes of our choices, humans can then make adjustments to future decisions. This is how we learn. However, how knowing the outcome of one's decisions influences behavioral changes, and especially the neural basis of those behavioral changes, still remains unclear. To investigate these questions, we employed a simple gambling task, in which participants chose between two alternative cards and received trial-by-trial feedback of their choices. In different sessions, we emphasized either utility (win or loss) or performance (whether the choice was correct [better than the alternative] or incorrect), making one of the two aspects more salient to participants. We found that trial-by-trial feedback and the saliency of the feedback modulated behavioral adjustments and subjective evaluations of the outcomes. With simultaneous electroencephalogram (EEG) recording, we found that the feedback-related negativity (FRN), P300, and late positive potential (LPP) served as the neural substrates for behavioral decision switching. Together, our findings reveal the neural basis of behavioral adjustment based on outcome evaluation and highlight the key role of feedback evaluation in future action selection and flexible adaptation.

A Flexible Neural Representation of Faces in the Human Brain

An important question in human face perception research is to understand whether the neural representation of faces is dynamically modulated by context. In particular, although there is a plethora of neuroimaging literature that has probed the neural representation of faces, few studies have investigated what low-level structural and textural facial features parametrically drive neural responses to faces and whether the representation of these features is modulated by the task. To answer these questions, we employed 2 task instructions when participants viewed the same faces. We first identified brain regions that parametrically encoded high-level social traits such as perceived facial trustworthiness and dominance, and we showed that these brain regions were modulated by task instructions. We then employed a data-driven computational face model with parametrically generated faces and identified brain regions that encoded low-level variation in the faces (shape and skin texture) that drove neural responses. We further analyzed the evolution of the neural feature vectors along the visual processing stream and visualized and explained these feature vectors. Together, our results showed a flexible neural representation of faces for both low-level features and high-level social traits in the human brain.

The Drosophila melanogaster as Genetic Model System to Dissect the Mechanisms of Disease that Lead to Neurodegeneration in Adrenoleukodystrophy

Drosophila melanogaster is the most successful genetic model organism to study different human disease with a recent increased popularity to study neurological disorders. Drosophila melanogaster has a complex yet well-defined brain with defined anatomical regions with specific functions. The neuronal network in the adult brain has a structural organization highly similar to human neurons, but in a brain that is much more amenable for complex analyses. The availability of sophisticated genetic tools to study neurons permits to examine neuronal functions at the single cell level in the whole brain by confocal imaging, which does not require sections. Thus, Drosophila has been used to successfully study many neurological disorders such as Parkinson's disease and has been recently adopted to understand the complex networks leading to neurological disorders with metabolic origins such as Leigh disease and X-linked adrenoleukodystrophy (X-ALD).In this review, we will describe the genetic tools available to study neuronal structures and functions and also illustrate some limitations of the system. Finally, we will report the experimental efforts that in the past 10 years have established Drosophila melanogaster as an excellent model organism to study neurodegenerative disorders focusing on X-ALD.

Having More Choices Changes How Human Observers Weight Stable Sensory Evidence

Decision-making becomes slower when more choices are available. Existing models attribute this slowing to poor sensory processing, to attenuated rates of sensory evidence accumulation, or to increases in the amount of evidence required before committing to a decision (a higher decision threshold). However, studies have not isolated the effects of having more choices on sensory and decision-related processes from changes in task difficulty and divided attention. Here, we controlled task difficulty while independently manipulating the distribution of attention and the number of choices available to male and female human observers. We used EEG to measure steady-state visually evoked potentials (SSVEPs) and a frontal late positive deflection (LPD), EEG markers of sensory and postsensory decision-related processes, respectively. We found that dividing attention decreased SSVEP and LPD amplitudes, consistent with dampened sensory responses and slower rates of evidence accumulation, respectively. In contrast, having more choices did not alter SSVEP amplitude and led to a larger LPD. These results suggest that having more options largely spares early sensory processing and slows down decision-making via a selective increase in decision thresholds.SIGNIFICANCE STATEMENT When more choices are available, decision-making becomes slower. We tested whether this phenomenon is due to poor sensory processing, to reduced rates of evidence accumulation, or to increases in the amount of evidence required before committing to a decision (a higher decision threshold). We measured choice modulations of sensory and decision-related neural responses using EEG. We also minimized potential confounds from changes in the distribution of attention and task difficulty, which often covary with having more choices. Dividing attention reduced the activity levels of both sensory and decision-related responses. However, having more choices did not change sensory processing and led to larger decision-related responses. These results suggest that having more choices spares sensory processing and selectively increases decision thresholds.