For more than two decades, research focusing on both clinical and non-clinical populations has suggested a key role for specific regions in the regulation of self-conscious emotions. It is speculated that both the expression and the interpretation of self-conscious emotions are critical in humans for action planning and response, communication, learning, parenting, and most social encounters. Empathy, Guilt, Jealousy, Shame, and Pride are all categorized as self-conscious emotions, all of which are crucial components to one’s sense of self. There has been an abundance of evidence pointing to the right Fronto-Temporal involvement in the integration of cognitive processes underlying the expression of these emotions. Numerous regions within the right hemisphere have been identified including the right temporal parietal junction (rTPJ), the orbitofrontal cortex (OFC), and the inferior parietal lobule (IPL). In this review, we aim to investigate patient cases, in addition to clinical and non-clinical studies. We also aim to highlight these specific brain regions pivotal to the right hemispheric dominance observed in the neural correlates of such self-conscious emotions and provide the potential role that self-conscious emotions play in evolution.
more »
« less
An ERP measure of non‐conscious memory reveals dissociable implicit processes in human recognition using an open‐source automated analytic pipeline
Abstract Non‐conscious processing of human memory has traditionally been difficult to objectively measure and thus understand. A prior study on a group of hippocampal amnesia (N= 3) patients and healthy controls (N= 6) used a novel procedure for capturing neural correlates of implicit memory using event‐related potentials (ERPs): old and new items were equated for varying levels of memory awareness, with ERP differences observed from 400 to 800 ms in bilateral parietal regions that were hippocampal‐dependent. The current investigation sought to address the limitations of that study by increasing the sample of healthy subjects (N = 54), applying new controls for construct validity, and developing an improved, open‐source tool for automated analysis of the procedure used for equating levels of memory awareness. Results faithfully reproduced prior ERP findings of parietal effects that a series of systematic control analyses validated were not contributed to nor contaminated by explicit memory. Implicit memory effects extended from 600 to 1000 ms, localized to right parietal sites. These ERP effects were found to be behaviorally relevant and specific in predicting implicit memory response times, and were topographically dissociable from other traditional ERP measures of implicit memory (miss vs. correct rejections) that instead occurred in left parietal regions. Results suggest first that equating for reported awareness of memory strength is a valid, powerful new method for revealing neural correlates of non‐conscious human memory, and second, behavioral correlations suggest that these implicit effects reflect a pure form of priming, whereas misses represent fluency leading to the subjective experience of familiarity.
more »
« less
- Award ID(s):
- 2124252
- PAR ID:
- 10421084
- Publisher / Repository:
- Wiley-Blackwell
- Date Published:
- Journal Name:
- Psychophysiology
- ISSN:
- 0048-5772
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
More Like this
-
-
Global Functional Connectivity at Rest Is Associated with Attention: An Arterial Spin Labeling StudyNeural markers of attention, including those frequently linked to the event-related potential P3 (P300) or P3b component, vary widely within and across participants. Understanding the neural mechanisms of attention that contribute to the P3 is crucial for better understanding attention-related brain disorders. All ten participants were scanned twice with a resting-state PCASL perfusion MRI and an ERP with a visual oddball task to measure brain resting-state functional connectivity (rsFC) and P3 parameters (P3 amplitudes and P3 latencies). Global rsFC (average rsFC across the entire brain) was associated with both P3 amplitudes (r = 0.57, p = 0.011) and P3 onset latencies (r = −0.56, p = 0.012). The observed P3 parameters were correlated with predicted P3 amplitude from the global rsFC (amplitude: r = +0.48, p = 0.037; latency: r = +0.40, p = 0.088) but not correlated with the rsFC over the most significant individual edge. P3 onset latency was primarily related to long-range connections between the prefrontal and parietal/limbic regions, while P3 amplitudes were related to connections between prefrontal and parietal/occipital, between sensorimotor and subcortical, and between limbic/subcortical and parietal/occipital regions. These results demonstrated the power of resting-state PCASL and P3 correlation with brain global functional connectivity.more » « less
-
Does sensory information reach conscious awareness in a discrete, all-or-nothing manner or a gradual, continuous manner? To answer this question, we examined behavioral performance across four different paradigms that manipulate visual awareness: the attentional blink, backward masking, the Sperling iconic memory paradigm, and retro-cuing. We then asked how well we could account for participants’ ( N = 112 adults) behavior using a signal detection framework that factors in psychophysical scaling to model participants’ responses along a single continuum. We found that this model easily accounted for the data from each of these diverse paradigms. Moreover, we reanalyzed the data from prior studies that had posited a discrete view of perceptual awareness and found that our continuous signal detection model outperformed the models that had been used to support an all-or-nothing view of consciousness. This set of data is consistent with the idea that conscious awareness occurs along a graded continuum.more » « less
-
The ability to prioritize valuable information is critical for the efficient use of memory in daily life. When information is important, we engage more effective encoding mechanisms that can better support retrieval. Here, we describe a dual-mechanism framework of value-directed remembering in which both strategic and automatic processes lead to differential encoding of valuable information. Strategic processes rely on metacognitive awareness of effective deep encoding strategies that allow younger and healthy older adults to selectively remember important information. In contrast, some high-value information may also be encoded automatically in the absence of intention to remember, but this may be more impaired in older age. These different mechanisms are subserved by different neural substrates, with left-hemisphere semantic processing regions active during the strategic encoding of high-value items, and automatic enhancement of encoding of high-value items may be supported by activation of midbrain dopaminergic projections to the hippocampal region.more » « less
-
Abstract Previous work using logistic regression suggests that cognitive control‐related frontoparietal activation in early psychosis can predict symptomatic improvement after 1 year of coordinated specialty care with 66% accuracy. Here, we evaluated the ability of six machine learning (ML) algorithms and deep learning (DL) to predict “Improver” status (>20% improvement on Brief Psychiatric Rating Scale [BPRS] total score at 1‐year follow‐up vs. baseline) and continuous change in BPRS score using the same functional magnetic resonance imaging‐based features (frontoparietal activations during the AX‐continuous performance task) in the same sample (individuals with either schizophrenia (n =65, 49M/16F, mean age 20.8 years) or Type I bipolar disorder (n= 17, 9M/8F, mean age 21.6 years)). 138 healthy controls were included as a reference group. “Shallow” ML methods included Naive Bayes, support vector machine, K Star, AdaBoost, J48 decision tree, and random forest. DL included an explainable artificial intelligence (XAI) procedure for understanding results. The best overall performances (70% accuracy for the binary outcome and root mean square error = 9.47 for the continuous outcome) were achieved using DL. XAI revealed left DLPFC activation was the strongest feature used to make binary classification decisions, with a classification activation threshold (adjusted beta = .017) intermediate to the healthy control mean (adjusted beta = .15, 95% CI = −0.02 to 0.31) and patient mean (adjusted beta = −.13, 95% CI = −0.37 to 0.11). Our results suggest DL is more powerful than shallow ML methods for predicting symptomatic improvement. The left DLPFC may be a functional target for future biomarker development as its activation was particularly important for predicting improvement.more » « less
An official website of the United States government
