Regular ArticleAnalysis of fMRI Time-Series Revisited
Abstract
This paper presents a general approach to the analysis of functional MRI time-series from one or more subjects. The approach is predicated on an extension of the general linear model that allows for correlations between error terms due to physiological noise or correlations that ensue after temporal smoothing. This extension uses the effective degrees of freedom associated with the error term. The effective degrees of freedom are a simple function of the number of scans and the temporal autocorrelation function. A specific form for the latter can be assumed if the data are smoothed, in time, to accentuate hemodynamic responses with a neural basis. This assumption leads to an expedient implementation of a flexible statistical framework. The importance of this small extension is that, in contradistinction to our previous approach, any parametric statistical analysis can be implemented. We demonstrate this point using a multiple regression analysis that tests for effects of interest (activations due to word generation), while taking explicit account of some obvious confounds.
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FMRI correlates of autobiographical memory: Comparing silent retrieval with narrated retrieval
2024, NeuropsychologiaFMRI studies of autobiographical memory (AM) retrieval typically ask subjects to retrieve memories silently to avoid speech-related motion artifacts. Recently, some fMRI studies have started to use overt (spoken) retrieval to probe moment-to-moment retrieved content. However, the extent to which the overt retrieval method alters fMRI activations during retrieval is unknown. Here we examined this question by eliciting unrehearsed AMs during fMRI scanning either overtly or silently, in the same subjects, in different runs. Differences between retrieval modality (silent vs. narrated) included greater activation for silent retrieval in the anterior hippocampus, left angular gyrus, PCC, and superior PFC, and greater activation for narrated retrieval in speech production regions, posterior hippocampus, and the DLPFC. To probe temporal dynamics, we divided each retrieval period into an initial search phase and a later elaboration phase. The activations during the search and elaboration phases were broadly similar regardless of modality, and these activations were in line with previous fMRI studies of AM temporal dynamics employing silent retrieval. For both retrieval modalities, search activated the hippocampus, mPFC, ACC, and PCC, and elaboration activated the left DLPFC and middle temporal gyri. To examine content-specific reactivation during retrieval, the timecourse of narrated memory content was transcribed and modeled. We observed dynamic activation associated with object content in the lateral occipital complex, and activation associated with scene content in the retrosplenial cortex. The current findings show that both silent and narrated AMs activate a broadly similar memory network, with some key differences, and add to current knowledge regarding the content-specific dynamics of AM retrieval. However, these observed differences between retrieval modality suggest that studies using overt retrieval should carefully consider this method's possible effects on cognitive and neural processing.
The effects of cocaine use severity and abstinence on behavioral performance and neural processes of response inhibition
2023, Psychiatry Research - NeuroimagingPrevious studies identified cerebral markers of response inhibition dysfunction in cocaine dependence. However, whether deficits in response inhibition vary with the severity of cocaine use or ameliorate during abstinence remain unclear. This study aimed to address these issues and the neural mechanisms supporting the individual variation. We examined the data of 67 individuals with cocaine dependence (CD) and 84 healthy controls (HC) who underwent functional magnetic resonance imaging during a stop-signal task (SST). The stop-signal reaction time (SSRT) was computed using the integration method, with a longer SSRT indicating poorer response inhibition. The results showed that, while CD and HC did not differ significantly in SSRT, years of cocaine use (YOC) and days of abstinence (DOA) were each positively and negatively correlated with the SSRT in CD. Whole-brain regressions of stop minus go success trials on SSRT revealed correlates in bilateral superior temporal gyrus (STG) in response inhibition across CD and HC. Further, mediation and path analyses revealed that YOC and DOA affected SSRT through the STG activities in CD. Together, the findings characterized the contrasting effects of cocaine use severity and abstinence on response inhibition as well as the neural processes that support these effects in cocaine dependence.
Logging tools used for underground oil and gas resource exploration often operate at temperatures above 200 °C, and their internal electronics are highly susceptible to burnout. In order to prevent over-temperature failure of the electronics due to prolonged operation, we avert the risk of over-temperature failure by predicting the real-time temperature with the physical model-based machine learning method. First, based on the transient heat transfer equation of the logging tools, the temperature of the electronic device is determined by the combination of its own historical temperature, the historical temperatures of the surrounding devices, and the physical parameters. Therefore, the impact of surrounding devices on the temperature of the electronic device is considered. Furthermore, we obtain the new ERD (Ensemble Recurrent Neural Network and Deep Neural Network) model with physically meaningful linear assumption, which benefits the reduction of complicated formula calculations. Compared with other machine learning methods, prediction error of ERD model can be reduced by 2 °C, and ERD model also shows good prediction when predicting temperature over a longer period of time. The real-time prediction will expand the application of oil and gas resource exploration techniques in deeper, hotter wells.
Beyond sense-specific processing: decoding texture in the brain from touch and sonified movement
2023, iScienceTexture, a fundamental object attribute, is perceived through multisensory information including touch and auditory cues. Coherent perceptions may rely on shared texture representations across different senses in the brain. To test this hypothesis, we delivered haptic textures coupled with a sound synthesizer to generate real-time textural sounds. Participants completed roughness estimation tasks with haptic, auditory, or bimodal cues in an MRI scanner. Somatosensory, auditory, and visual cortices were all activated during haptic and auditory exploration, challenging the traditional view that primary sensory cortices are sense-specific. Furthermore, audio-tactile integration was found in secondary somatosensory (S2) and primary auditory cortices. Multivariate analyses revealed shared spatial activity patterns in primary motor and somatosensory cortices, for discriminating texture across both modalities. This study indicates that primary areas and S2 have a versatile representation of multisensory textures, which has significant implications for how the brain processes multisensory cues to interact more efficiently with our environment.
Dimensional emotions are represented by distinct topographical brain networks
2023, International Journal of Clinical and Health PsychologyThe ability to recognize others’ facial emotions has become increasingly important after the COVID-19 pandemic, which causes stressful situations in emotion regulation. Considering the importance of emotion in maintaining a social life, emotion knowledge to perceive and label emotions of oneself and others requires an understanding of affective dimensions, such as emotional valence and emotional arousal. However, limited information is available about whether the behavioral representation of affective dimensions is similar to their neural representation. To explore the relationship between the brain and behavior in the representational geometries of affective dimensions, we constructed a behavioral paradigm in which emotional faces were categorized into geometric spaces along the valence, arousal, and valence and arousal dimensions. Moreover, we compared such representations to neural representations of the faces acquired by functional magnetic resonance imaging. We found that affective dimensions were similarly represented in the behavior and brain. Specifically, behavioral and neural representations of valence were less similar to those of arousal. We also found that valence was represented in the dorsolateral prefrontal cortex, frontal eye fields, precuneus, and early visual cortex, whereas arousal was represented in the cingulate gyrus, middle frontal gyrus, orbitofrontal cortex, fusiform gyrus, and early visual cortex. In conclusion, the current study suggests that dimensional emotions are similarly represented in the behavior and brain and are presented with differential topographical organizations in the brain.
An autonomic mode of brain activity
2023, Progress in NeurobiologyThe relevance of interactions between autonomic and central nervous systems remains unclear for human brain function and health, particularly when both systems are challenged under sleep deprivation (SD). We measured brain activity (with fMRI), pulse and respiratory signals, and baseline brain amyloid beta burden (with PET) in healthy participants. We found that SD relative to rested wakefulness (RW) resulted in a significant increase in synchronized low frequency (LF, < 0.1 Hz) activity in an autonomically-related network (AN), including dorsal attention, visual, and sensorimotor regions, which we previously found to have consistent temporal coupling with LF pulse signal changes (regulated by sympathetic tone). SD resulted in a significant phase coherence between the LF component of the pulse signal and a medial network with peak effects in the midbrain reticular formation, and between LF component of the respiratory variations (regulated by respiratory motor output) and a cerebellar network. The LF power of AN during SD was significantly and independently correlated with pulse-medial network and respiratory-cerebellar network phase coherences (total adjusted R2 = 0.78). Higher LF power of AN during SD (but not RW) was associated with lower amyloid beta burden (Cohen’s d = 0.8). In sum, SD triggered an autonomic mode of synchronized brain activity that was associated with distinct autonomic-central interactions. Findings highlight the direct relevance of global cortical synchronization to brain clearance mechanisms.