Single-Neuron Correlates of Visual Object Representation in the Human Brain: Effects of Attention, Memory, and Choice

Neurons in the medial temporal lobe (amygdala and hippocampus) are known to respond selectively to specific object categories, such as faces. This dissertation investigates two novel extensions of this work: (1) how are such neuronal responses influenced by where we attend; (2) how is category information used by the brain to make decisions. The first question evaluated the representation of faces in the primate amygdala during naturalistic conditions, by recording from both human and macaque amygdala neurons during free viewing of arrays of images with concurrent eye tracking. We found that category-selective responses were very strongly modulated by where people, or monkeys, fixated (overt attention). Subsequent experiments in humans only further demonstrated that this effect holds even when people allocate visual attention while keeping central fixation (covert attention). In both monkeys and humans, the majority of face-selective neurons preferred faces of conspecifics, a bias also seen behaviorally in first fixation preferences. Response latencies, relative to fixation onset, were shortest for conspecific-selective neurons. Response latencies were also notably shorter in monkeys than in humans. To answer the second question, we investigated how visual representations in the medial temporal lobe are subsequently used to make two types of decisions: a recognition memory choice ("have you seen this image before?"), and a stimulus categorization choice ("Is this a face?"). We show that (i) there are distinct populations of cells in the medial frontal cortex (including anterior cingulate cortex, and supplementary motor cortex) encoding recognition memory or categorization-based choices; (ii) category-selective cells in the medial temporal lobe are insensitive to such task conditions; and (iii) spike-field coherence between field potentials in the medial temporal lobe and action potentials in the medial frontal cortex is enhanced during recognition memory choices. This suggests that inter-areal communication between these two brain regions may be facilitated selectively in tasks that rely on recognition memory-based information. Taken together these two components of this dissertation provide novel insights into how visual object representations in the human brain are gated by attention, and how they are used in decisions. This work thus for the first time provides a comprehensive characterization of how single neurons in the human brain participate in the cycle from perception to action.</p

Musical preferences predict personality: evidence from active listening and Facebook likes

Research over the past decade has shown that various personality traits are communicated through musical preferences. One limitation of that research is external validity, as most studies have assessed individual differences in musical preferences using self-reports of music-genre preferences. Are personality traits communicated through behavioral manifestations of musical preferences? We addressed this question in two large-scale online studies with demographically diverse populations. Study 1 (N = 22,252) shows that reactions to unfamiliar musical excerpts predicted individual differences in personality—most notably, openness and extraversion—above and beyond demographic characteristics. Moreover, these personality traits were differentially associated with particular music-preference dimensions. The results from Study 2 (N = 21,929) replicated and extended these findings by showing that an active measure of naturally occurring behavior, Facebook Likes for musical artists, also predicted individual differences in personality. In general, our findings establish the robustness and external validity of the links between musical preferences and personality

A cognitive neuroprosthetic that uses cortical stimulation for somatosensory feedback

Present day cortical brain–machine interfaces (BMIs) have made impressive advances using decoded brain signals to control extracorporeal devices. Although BMIs are used in a closed-loop fashion, sensory feedback typically is visual only. However medical case studies have shown that the loss of somesthesis in a limb greatly reduces the agility of the limb even when visual feedback is available. Approach. To overcome this limitation, this study tested a closed-loop BMI that utilizes intracortical microstimulation to provide 'tactile' sensation to a non-human primate. Main result. Using stimulation electrodes in Brodmann area 1 of somatosensory cortex (BA1) and recording electrodes in the anterior intraparietal area, the parietal reach region and dorsal area 5 (area 5d), it was found that this form of feedback can be used in BMI tasks. Significance. Providing somatosensory feedback has the poyential to greatly improve the performance of cognitive neuroprostheses especially for fine control and object manipulation. Adding stimulation to a BMI system could therefore improve the quality of life for severely paralyzed patients

Flexible recruitment of memory-based choice representations by human medial-frontal cortex

Flexibly switching between different tasks is a fundamental human cognitive ability that allows us to make selective use of only the information needed for a given decision. Minxha et al. used single-neuron recordings from patients to understand how the human brain retrieves memories on demand when needed for making a decision and how retrieved memories are dynamically routed in the brain from the temporal to the frontal lobe. When memory was not needed, only medial frontal cortex neural activity was correlated with the task. However, when outcome choices required memory retrieval, frontal cortex neurons were phase-locked to field potentials recorded in the medial temporal lobe. Therefore, depending on demands of the task, neurons in different regions can flexibly engage and disengage their activity patterns

Value-related neuronal responses in the human amygdala during observational learning

The amygdala plays an important role in many aspects of social cognition and reward learning. Here, we aimed to determine whether human amygdala neurons are involved in the computations necessary to implement learning through observation. We performed single-neuron recordings from the amygdalae of human neurosurgical patients (male and female) while they learned about the value of stimuli through observing the outcomes experienced by another agent interacting with those stimuli. We used a detailed computational modeling approach to describe patients' behavior in the task. We found a significant proportion of amygdala neurons whose activity correlated with both expected rewards for oneself and others, and in tracking outcome values received by oneself or other agents. Additionally, a population decoding analysis suggests the presence of information for both observed and experiential outcomes in the amygdala. Encoding and decoding analyses suggested observational value coding in amygdala neurons occurred in a different subset of neurons than experiential value coding. Collectively, these findings support a key role for the human amygdala in the computations underlying the capacity for learning through observation

Fixations Gate Species-Specific Responses to Free Viewing of Faces in the Human and Macaque Amygdala

Neurons in the primate amygdala respond prominently to faces. This implicates the amygdala in the processing of socially significant stimuli, yet its contribution to social perception remains poorly understood. We evaluated the representation of faces in the primate amygdala during naturalistic conditions by recording from both human and macaque amygdala neurons during free viewing of identical arrays of images with concurrent eye tracking. Neurons responded to faces only when they were fixated, suggesting that neuronal activity was gated by visual attention. Further experiments in humans utilizing covert attention confirmed this hypothesis. In both species, the majority of face-selective neurons preferred faces of conspecifics, a bias also seen behaviorally in first fixation preferences. Response latencies, relative to fixation onset, were shortest for conspecific-selective neurons and were ∼100 ms shorter in monkeys compared to humans. This argues that attention to faces gates amygdala responses, which in turn prioritize species-typical information for further processing

Inferring brain-wide interactions using data-constrained recurrent neural network models

Behavior arises from the coordinated activity of numerous anatomically and functionally distinct brain regions. Modern experimental tools allow unprecedented access to large neural populations spanning many interacting regions brain-wide. Yet, understanding such large-scale datasets necessitates both scalable computational models to extract meaningful features of inter-region communication and principled theories to interpret those features. Here, we introduce Current-Based Decomposition (CURBD), an approach for inferring brain-wide interactions using data-constrained recurrent neural network models that directly reproduce experimentally-obtained neural data. CURBD leverages the functional interactions inferred by such models to reveal directional currents between multiple brain regions. We first show that CURBD accurately isolates inter-region currents in simulated networks with known dynamics. We then apply CURBD to multi-region neural recordings obtained from mice during running, macaques during Pavlovian conditioning, and humans during memory retrieval to demonstrate the widespread applicability of CURBD to untangle brain-wide interactions underlying behavior from a variety of neural datasets

Value-related neuronal responses in the human amygdala during observational learning

The amygdala plays an important role in many aspects of social cognition and reward learning. Here, we aimed to determine whether human amygdala neurons are involved in the computations necessary to implement learning through observation. We performed single-neuron recordings from the amygdalae of human neurosurgical patients (male and female) while they learned about the value of stimuli through observing the outcomes experienced by another agent interacting with those stimuli. We used a detailed computational modeling approach to describe patients' behavior in the task. We found a significant proportion of amygdala neurons whose activity correlated with both expected rewards for oneself and others, and in tracking outcome values received by oneself or other agents. Additionally, a population decoding analysis suggests the presence of information for both observed and experiential outcomes in the amygdala. Encoding and decoding analyses suggested observational value coding in amygdala neurons occurred in a different subset of neurons than experiential value coding. Collectively, these findings support a key role for the human amygdala in the computations underlying the capacity for learning through observation

Making Decisions Based on Autobiographical Memories

A new human intracranial study by Foster et al. (2015) sheds light on the electrophysiological correlates of intrinsic and task-evoked functional connectivity in lateral and medial parietal cortex