Teacher-student neural coupling during teaching and learning.

Human communication is remarkably versatile, enabling teachers to share highly abstracted and novel information with their students. What neural processes enable such transfer of information across brains during naturalistic teaching and learning? Here, a teacher was scanned in functional magnetic resonance imaging while giving an oral lecture with slides on a scientific topic followed by a review lecture. Students were then scanned while watching either the intact Lecture and Review (N = 20) or a temporally scrambled version of the lecture (N = 20). Using intersubject correlation, we observed widespread Teacher-Student neural coupling spanning sensory cortex and language regions along the superior temporal sulcus as well as higher-level regions including posterior medial cortex (PMC), superior parietal lobule, and dorsolateral and dorsomedial prefrontal cortex. Teacher-student alignment in higher-level areas was not observed when learning was disrupted by temporally scrambling the lecture. Moreover, teacher-student coupling in PMC was significantly correlated with learning: the more closely the student's brain mirrored the teacher's brain, the more the student improved their learning score. Together, these results suggest that the alignment of neural responses between teacher and students may reflect effective communication of complex information across brains in classroom settings.

Neural alignment predicts learning outcomes in students taking an introduction to computer science course.

Despite major advances in measuring human brain activity during and after educational experiences, it is unclear how learners internalize new content, especially in real-life and online settings. In this work, we introduce a neural approach to predicting and assessing learning outcomes in a real-life setting. Our approach hinges on the idea that successful learning involves forming the right set of neural representations, which are captured in canonical activity patterns shared across individuals. Specifically, we hypothesized that learning is mirrored in neural alignment: the degree to which an individual learner's neural representations match those of experts, as well as those of other learners. We tested this hypothesis in a longitudinal functional MRI study that regularly scanned college students enrolled in an introduction to computer science course. We additionally scanned graduate student experts in computer science. We show that alignment among students successfully predicts overall performance in a final exam. Furthermore, within individual students, we find better learning outcomes for concepts that evoke better alignment with experts and with other students, revealing neural patterns associated with specific learned concepts in individuals.

Increasing suppression of saccade-related transients along the human visual hierarchy.

A key hallmark of visual perceptual awareness is robustness to instabilities arising from unnoticeable eye and eyelid movements. In previous human intracranial (iEEG) work (Golan et al., 2016) we found that excitatory broadband high-frequency activity transients, driven by eye blinks, are suppressed in higher-level but not early visual cortex. Here, we utilized the broad anatomical coverage of iEEG recordings in 12 eye-tracked neurosurgical patients to test whether a similar stabilizing mechanism operates following small saccades. We compared saccades (1.3°-3.7°) initiated during inspection of large individual visual objects with similarly-sized external stimulus displacements. Early visual cortex sites responded with positive transients to both conditions. In contrast, in both dorsal and ventral higher-level sites the response to saccades (but not to external displacements) was suppressed. These findings indicate that early visual cortex is highly unstable compared to higher-level visual regions which apparently constitute the main target of stabilizing extra-retinal oculomotor influences.

Trained to silence: Progressive signal inhibition during short visuo-motor training.

Short training is often sufficient for human individuals to become adept at performing a complex new task. However, the precise nature of the changes in cortical activity during short-term training of under an hour is still not fully understood. In this study, we have examined the effects of such short training in a visual recognition task on cortical activity using functional imaging (BOLD fMRI). Participants performed a gender/age discrimination task on face images for 28min, preceded and followed by resting state scans. Our results reveal a consistent and progressive signal reduction during stimuli presentation compared to a fixation baseline, which was reflected in participant's subjective experience as evaluated by post-scan questionnaires. The BOLD reduction surprisingly included both task-positive and task-negative regions. While higher order face-selective regions showed a reduced positive peak response, negatively-responding areas - including the peripheral visual representations as well as the Default Mode Network - showed deeper negative BOLD responses during the visual stimulation periods. Interestingly, these training effects have left significant traces in the spontaneous resting-state fluctuations following the training period in areas that partially correspond to those that showed response changes during task performance. The results reveal the widespread cortical changes underlying short-term training.

Human intracranial recordings link suppressed transients rather than 'filling-in' to perceptual continuity across blinks.

We hardly notice our eye blinks, yet an externally generated retinal interruption of a similar duration is perceptually salient. We examined the neural correlates of this perceptual distinction using intracranially measured ECoG signals from the human visual cortex in 14 patients. In early visual areas (V1 and V2), the disappearance of the stimulus due to either invisible blinks or salient blank video frames ('gaps') led to a similar drop in activity level, followed by a positive overshoot beyond baseline, triggered by stimulus reappearance. Ascending the visual hierarchy, the reappearance-related overshoot gradually subsided for blinks but not for gaps. By contrast, the disappearance-related drop did not follow the perceptual distinction - it was actually slightly more pronounced for blinks than for gaps. These findings suggest that blinks' limited visibility compared with gaps is correlated with suppression of blink-related visual activity transients, rather than with "filling-in" of the occluded content during blinks.

Selectivity of audiovisual ECoG responses revealed under naturalistic stimuli in the human cortex.

A fundamental debate in the study of cortical sensory systems concerns the scale of functional selectivity in cortical networks. Brain imaging studies have repeatedly demonstrated functional selectivity in entire cortical areas and networks using predetermined stimuli. However, it is not clear to what extent these networks are heterogeneous, i.e., whether the selectivity profiles in subregions within each sensory network show significant dissimilarity. Here, we studied local functional selectivity in the human cortex using naturalistic movie clips shown to 12 patients implanted with intracranial electrocorticography electrodes (590 in total), providing extensive cortical coverage. We examined the similarity of response profiles (40- to 80-Hz gamma-power modulations) across electrodes using a novel data driven approach without assuming any predefined category. Our results show that the functional selectivity of each highly responsive electrode was different from that of all other electrodes across the sensory cortex. Thus most responsive electrodes showed an activation profile that was unique in each patient and was similar to that of only 0.3% (1-2) of all other electrodes across all patients. Functional similarity between electrodes was linked to anatomical proximity. While in most electrodes the source of selectivity was complex, a small subset showed the well-documented selectivity to faces and actions. Our results indicate that the human sensory cortex is organized as a mosaic of functionally unique subregions in which each site manifests its own special response profile.

Rational emotions.

We present here the concept of rational emotions: Emotions may be directly controlled and utilized in a conscious, analytic fashion, enabling an individual to size up a situation, to determine that a certain "mental state" is strategically advantageous and adjust accordingly. Building on the growing body of literature recognizing the vital role of emotions in determining decisions, we explore the complementary role of rational choice in choosing emotional states. Participants played the role of "recipient" in the dictator game, in which an anonymous "dictator" decides how to split an amount of money between himself and the recipient. A subset of recipients was given a monetary incentive to be angry at low-split offers. That subset demonstrated increased physiological arousal at low offers relative to high offers as well as more anger than other participants. These results provide a fresh outlook on human decision-making and contribute to the continuing effort to build more complete models of rational behavior.

Three-dimensional distribution patterns of newborn neurons in the adult olfactory bulb.

We present a new method to study the three-dimensional (3D) spatial distribution patterns of newborn neurons in the mouse olfactory bulb (OB). Newborn neurons were transduced, in vivo, using lentiviruses to express green fluorescent protein (GFP). Two-photon (2P) microscopy was used to image thick OB slices (approximately 250 microm) at single cell resolution. Image-stacks were captured semi-automatically, and concatenated offline, to create larger image-stacks containing the positional information of all the labeled neurons. Serial reconstruction of the large image-stacks resulted in a three-dimensional virtual model, containing the exact position of all the labeled newborn neurons within large volumes of the OB. The feasibility of this method was demonstrated by analyzing the cell distributions of thousands of GFP labeled newborn neurons. This analysis identified 3D clusters in which the newborn cells' density is significantly higher than the mean density. We show that our method reveals information that is overlooked when sampling only a small fraction of the tissue in 2D. This method may serve as a valuable tool, not only for analyzing newborn neurons in the OB, but also for other neuronal types as well as for other brain regions.