Whole-brain Activity Research Articles

Whole-brain responses to visual and auditory stimuli in anesthetized and minimally restrained awake mice using quiet zero echo time fMRI

Abstract Functional MRI (fMRI) is a flexible tool for sensory perception studies in animal models. However, animal fMRI studies are generally performed under anesthesia. Unfortunately, anesthesia affects brain function and sensory processing, complicating the interpretation of the findings. Since there is a growing need for fMRI protocols applicable for awake animals, we optimized a zero echo time Multi-Band Sweep Imaging with a Fourier Transformation (MB-SWIFT) fMRI approach for imaging awake mice. We implemented a 14-day habituation protocol that resulted in merely moderate motion of the mice while being head-fixed with the animals’ body and limbs being free-to-move. The sensory responsiveness between different states of consciousness was compared by imaging mice with visual and auditory stimulation schemes in the awake state and under ketamine-xylazine anesthesia. In awake mice, we observed a robust whole-brain activation of the ascending auditory and visual pathways, as well as higher sensory processing areas. Under ketamine-xylazine anesthesia, auditory responses were suppressed, and the temporal shapes of fMRI responses were different from those obtained in awake mice. Our results suggest that the quiet and motion-tolerant zero echo time MB-SWIFT approach allows complex behavioral fMRI designs in the awake state that promise to improve our understanding of the underlying mechanisms of perception.

The recurrent temporal restricted Boltzmann machine captures neural assembly dynamics in whole-brain activity

Animal behaviour alternates between stochastic exploration and goal-directed actions, which are generated by the underlying neural dynamics. Previously, we demonstrated that the compositional Restricted Boltzmann Machine (cRBM) can decompose whole-brain activity of larval zebrafish data at the neural level into a small number (∼100-200) of assemblies that can account for the stochasticity of the neural activity (van der Plas et al., eLife, 2023). Here, we advance this representation by extending to a combined stochastic-dynamical representation to account for both aspects using the recurrent temporal RBM (RTRBM) and transfer-learning based on the cRBM estimate. We demonstrate that the functional advantage of the RTRBM is captured in the temporal weights on the hidden units, representing neural assemblies, for both simulated and experimental data. Our results show that the temporal expansion outperforms the stochastic-only cRBM in terms of generalization error and achieves a more accurate representation of the moments in time. Lastly, we demonstrate that we can identify the original time-scale of assembly dynamics by estimating multiple RTRBMs at different temporal resolutions. Together, we propose that RTRBMs are a valuable tool for capturing the combined stochastic and time-predictive dynamics of large-scale data sets.

The recurrent temporal restricted Boltzmann machine captures neural assembly dynamics in whole-brain activity.

Animal behaviour alternates between stochastic exploration and goal-directed actions, which are generated by the underlying neural dynamics. Previously, we demonstrated that the compositional Restricted Boltzmann Machine (cRBM) can decompose whole-brain activity of larval zebrafish data at the neural level into a small number (∼100-200) of assemblies that can account for the stochasticity of the neural activity (van der Plas et al., eLife, 2023). Here, we advance this representation by extending to a combined stochastic-dynamical representation to account for both aspects using the recurrent temporal RBM (RTRBM) and transfer-learning based on the cRBM estimate. We demonstrate that the functional advantage of the RTRBM is captured in the temporal weights on the hidden units, representing neural assemblies, for both simulated and experimental data. Our results show that the temporal expansion outperforms the stochastic-only cRBM in terms of generalization error and achieves a more accurate representation of the moments in time. Lastly, we demonstrate that we can identify the original time-scale of assembly dynamics by estimating multiple RTRBMs at different temporal resolutions. Together, we propose that RTRBMs are a valuable tool for capturing the combined stochastic and time-predictive dynamics of large-scale data sets.

An anterior hypothalamic circuit gates stress vulnerability.

Prior adversity increases susceptibility to subsequent stressful events, but the causal underlying changes in brain circuitry are poorly understood. We harnessed unbiased whole-brain activity mapping to identify circuits that are functionally remodeled by prior adversity. This revealed that the anterior hypothalamic nucleus (AHN) displays heightened stress reactivity in previously stressed mice. This was accompanied by increased functional connectivity between the AHN and a threat-related limbic network. Using in vivo Miniscope imaging, we found that neuronal activity in the AHN encodes stressor valence. Moreover, stimulating AHN neurons enhanced, and inhibiting their activity mitigated, reactivity to stressful events. Lastly, silencing amygdala inputs to the AHN abolished the ability of prior adversity to increase stress sensitivity. These findings define a key role of the AHN in gating stress vulnerability by scaling valence signals from the amygdala.

Oxytocin moderates fMRI connectivity and response to implicit threat processing in cocaine use disorder

Stressful social experiences play an important role in increasing vulnerability to substance use, including cocaine. Oxytocin (OXT), known for its anxiolytic properties and involvement in social functioning, has been suggested as a potential therapeutic for cocaine use disorder (CUD). However, limited research has explored OXT’s influence on social stress in CUD, and no study has examined its effects on neural response to subconscious (implicit) social threat cues in this population. To address this gap, the present study administered intranasal OXT (24 IU) or placebo (PBO) to participants with CUD (CUD+, N = 76) or without CUD (CUD-, N = 61) in a randomized parallel design. Participants then completed a functional magnetic resonance imaging (fMRI) task involving briefly presented facial fear and anger (i.e., threat) cues, followed by neutral face stimuli. Whole-brain activation and amygdala functional connectivity (using psychophysiological interaction modeling) were examined in response to the facial threat cues. OXT reduced activation in the thalamus and pontine reticular formation in response to fear cues, and in the supplementary motor area for both fear and anger cues, regardless of CUD status. Additionally, under PBO, amygdala-medial prefrontal cortex connectivity to fear stimuli was negative for the CUD+ group, but under OXT, this coupling was positive, similar to the positive coupling observed for the CUD- group under both PBO and OXT administration. The finding of OXT-mediated reversal of amygdala-prefrontal coupling was specific to CUD+ and suggests that OXT alters circuitry related to threat surveillance and implicit emotion regulation in CUD. However, additional research is needed to determine whether these alterations due to OXT have clinical significance in CUD.

Mental rotation-related neural interactions between gender and cognitive strategy

Abstract A long-standing history of research has focused on the differences between men and women in cognitive tasks, including that men would be more accurate and faster than women in mental rotation (MR). This advantage suggests that men would use an object-based cognitive strategy (OBS) to perform MR, whereas women would rely more on an effector-based cognitive strategy (EBS). To test this hypothesis, participants in the present study performed MR using OBS and EBS (plus a control condition) while their brain activity was recorded using fMRI. As sex hormones have often been reported to influence spatial ability, we also assessed the relationship between MR and testosterone levels and digit ratio. Behavioral results showed that (1) men performed faster MR than women in the OBS and control conditions, (2) men were more accurate than women in the OBS condition, and (3) women performed better in OBS than the other two conditions. No relationship was found between MR and testosterone or digit ratio. fMRI data showed that women in the OBS condition had greater activation than men in the inferior frontal and somatosensory cortices. Salivary testosterone levels had no effect on whole-brain activity. Combining behavioral and brain imaging data, these findings suggest that the additional somatosensory activation found in women during OBS somehow affects their MR, preventing the use of a purely spatial strategy and promoting the use of body-based sensorimotor processing, which would result in lower accuracy. These results support that gender differences in MR would be better explained by considering their relationship with the cognitive strategies used to perform MR.

Repetitive Transcranial Magnetic Stimulation (rTMS) Treatment Reduces Variability in Brain Function in Schizophrenia: Data From a Double-Blind, Randomized, Sham-Controlled Trial.

There is increasing awareness of interindividual variability in brain function, with potentially major implications for repetitive transcranial magnetic stimulation (rTMS) efficacy. We perform a secondary analysis using data from a double-blind randomized controlled 4-week trial of 20 Hz active versus sham rTMS to dorsolateral prefrontal cortex (DLPFC) during a working memory task in participants with schizophrenia. We hypothesized that rTMS would change local functional activity and variability in the active group compared with sham. 83 participants were randomized in the original trial, and offered neuroimaging pre- and post-treatment. Of those who successfully completed both scans (n = 57), rigorous quality control left n = 42 (active/sham: n = 19/23), who were included in this analysis. Working memory-evoked activity during an N-Back (3-Back vs 1-Back) task was contrasted. Changes in local brain activity were examined from an 8mm ROI around the rTMS coordinates. Individual variability was examined as the mean correlational distance (MCD) in brain activity pattern from each participant to others within the same group. We observed an increase in task-evoked left DLPFC activity in the active group compared with sham (F1,36 = 5.83, False Discovery Rate (FDR))-corrected P = .04). Although whole-brain activation patterns were similar in both groups, active rTMS reduced the MCD in activation pattern compared with sham (F1,36 = 32.57, P < .0001). Reduction in MCD was associated with improvements in attention performance (F1,16 = 14.82, P = .0014, uncorrected). Active rTMS to DLPFC reduces individual variability of brain function in people with schizophrenia. Given that individual variability is typically higher in schizophrenia patients compared with controls, such reduction may "normalize" brain function during higher-order cognitive processing.

Action expectancy modulates activity in the mirror neuron system and mentalizing system

Action understanding involves two distinct processing levels that engage separate neural mechanisms: perception of concrete kinematic information and recognition of abstract action intentions. The mirror neuron system and the mentalizing system have both been linked to concrete action and abstract information processing, but their specific roles remain debatable. Here, we conducted a functional magnetic resonance imaging study with 26 participants who passively observed expected and unexpected actions. We performed whole-brain activation, region of interest, and effective connectivity analyses to investigate the neural correlates of these actions. Whole-brain activation analyses revealed that expected actions were associated with increased activation in the left medial superior frontal gyrus, while unexpected actions were linked to heightened activity in the left supramarginal gyrus, left superior parietal lobule, right inferior temporal gyrus, and left middle frontal gyrus. Region of interest analyses demonstrated that the left ventral premotor cortex exhibited greater activation during the observation of expected actions compared to unexpected actions, while the left inferior frontal gyrus, left superior parietal lobule, and left precuneus showed stronger activation during the observation of unexpected actions. Effective connectivity was observed between the left ventral premotor cortex and the left angular gyrus, left intraparietal sulcus, left dorsal premotor cortex, and left ventromedial prefrontal cortex with the middle frontal gyrus when observing unexpected, but not expected, actions. These findings suggest that expected actions are primarily processed by the mirror neuron system, whereas unexpected actions engage both the mirror neuron system and the mentalizing system, with these systems playing complementary roles in the understanding of unexpected actions.

Spontaneous Brain Activity Emerges from Pairwise Interactions in the Larval Zebrafish Brain

Brain activity is characterized by brainwide spatiotemporal patterns that emerge from synapse-mediated interactions between individual neurons. Calcium imaging provides access to recordings of whole-brain activity at single-neuron resolution and, therefore, allows the study of how large-scale brain dynamics emerge from local activity. In this study, we use a statistical mechanics approach—the pairwise maximum entropy model—to infer microscopic network features from collective patterns of activity in the larval zebrafish brain and relate these features to the emergence of observed whole-brain dynamics. Our findings indicate that the pairwise interactions between neural populations and their intrinsic activity states are sufficient to explain observed whole-brain dynamics. In fact, the pairwise relationships between neuronal populations estimated with the maximum entropy model strongly correspond to observed structural connectivity patterns. Model simulations also demonstrated how tuning pairwise neuronal interactions drives transitions between observed physiological regimes and pathologically hyperexcitable whole-brain regimes. Finally, we use virtual resection to identify the brain structures that are important for maintaining the brain in a physiological dynamic regime. Together, our results indicate that whole-brain activity emerges from a complex dynamical system that transitions between basins of attraction whose strength and topology depend on the connectivity between brain areas. Published by the American Physical Society 2024

Age-related neural changes underlying long-term recognition of musical sequences

Aging is often associated with decline in brain processing power and neural predictive capabilities. To challenge this notion, we used magnetoencephalography (MEG) and magnetic resonance imaging (MRI) to record the whole-brain activity of 39 older adults (over 60 years old) and 37 young adults (aged 18–25 years) during recognition of previously memorised and varied musical sequences. Results reveal that when recognising memorised sequences, the brain of older compared to young adults reshapes its functional organisation. In fact, it shows increased early activity in sensory regions such as the left auditory cortex (100 ms and 250 ms after each note), and only moderate decreased activity (350 ms) in medial temporal lobe and prefrontal regions. When processing the varied sequences, older adults show a marked reduction of the fast-scale functionality (250 ms after each note) of higher-order brain regions including hippocampus, ventromedial prefrontal and inferior temporal cortices, while no differences are observed in the auditory cortex. Accordingly, young outperform older adults in the recognition of novel sequences, while no behavioural differences are observed with regards to memorised ones. Our findings show age-related neural changes in predictive and memory processes, integrating existing theories on compensatory neural mechanisms in non-pathological aging.

Bed nucleus of the stria terminalis network responses to unpredictable threat in early alcohol abstinence.

Anxiety during early alcohol abstinence, likely resulting from neural changes caused by chronic alcohol use, contributes to high relapse rates. Studies in rodents show heightened activation during early abstinence in the bed nucleus of the stria terminalis (BNST)-a neural hub for anxiety-and its extended anxiety-related corticolimbic network. Despite the clinical importance of early abstinence, few studies investigate the underlying neural mechanisms. To address this gap, we investigated brain function in early alcohol abstinence (EA = 20, 9 women) relative to controls (HC = 20, 11 women) using an unpredictable threat task shown to engage the BNST and corticolimbic brain regions involved in anxiety and alcohol use disorder (AUD). Group, anxiety, and sex were predictors used to determine whole-brain activation and BNST functional connectivity. We found widespread interactions of group × anxiety and group × anxiety × sex for both activation and BNST connectivity during unpredictable threat. In the EA group, higher anxiety was correlated with activation in the BNST, rostral anterior cingulate cortex (ACC), insula (men only), and dorsal ACC (men only). In the HC group, higher anxiety was negatively correlated with activation in the BNST, nucleus accumbens, thalamus, and insula (men only). For connectivity, anxiety was positively correlated in EA and negatively correlated in HC, between the BNST and the amygdala, ventromedial prefrontal cortex (PFC), and dorsomedial PFC; EA men showed stronger BNST-vmPFC connectivity than HC men. These novel findings provide preliminary evidence for alterations in the BNST and anxiety-related corticolimbic brain regions in early alcohol abstinence, adding to growing literature in humans supporting the BNST's role in anxiety and sex-dependent effects of chronic alcohol use.

Personalized whole-brain activity patterns predict human corticospinal tract activation in real-time.

Transcranial magnetic stimulation (TMS) interventions could feasibly treat stroke-related motor impairments, but their effects are highly variable. Brain state-dependent TMS approaches are a promising solution to this problem, but inter-individual variation in lesion location and oscillatory dynamics can make translating them to the poststroke brain challenging. Personalized brain state-dependent approaches specifically designed to address these challenges are therefore needed. As a first step towards this goal, we tested a novel machine learning-based EEG-TMS system that identifies personalized brain activity patterns reflecting strong and weak corticospinal tract (CST) output (strong and weak CST states) in healthy adults in real-time. Participants completed a single-session study that included the acquisition of a TMS-EEG-EMG training dataset, personalized classifier training, and real-time EEG-informed single pulse TMS during classifier-predicted personalized CST states. MEP amplitudes elicited in real-time during personalized strong CST states were significantly larger than those elicited during personalized weak and random CST states. MEP amplitudes elicited in real-time during personalized strong CST states were also significantly less variable than those elicited during personalized weak CST states. Personalized CST states lasted for ~1-2 seconds at a time and ~1 second elapsed between consecutive similar states. Individual participants exhibited unique differences in spectro-spatial EEG patterns between personalized strong and weak CST states. Our results show for the first time that personalized whole-brain EEG activity patterns predict CST activation in real-time in healthy humans. These findings represent a pivotal step towards using personalized brain state-dependent TMS interventions to promote poststroke CST function.

Whole-brain mapping in adult zebrafish and identification of a novel tank test functional connectome.

Identifying general principles of brain function requires the study of structure-function relationships in a variety of species. Zebrafish have recently gained prominence as a model organism in neuroscience, yielding important insights into vertebrate brain function. Although methods have been developed for mapping neural activity in larval animals, we lack similar techniques for adult zebrafish that have the advantage of a fully developed neuroanatomy and larger behavioral repertoire. Here, we describe a pipeline built around open-source tools for whole-brain activity mapping in freely swimming adult zebrafish. Our pipeline combines recent advances in histology, microscopy, and machine learning to capture cfos activity across the entirety of the adult brain. Images captured using light-sheet microscopy are registered to the recently created adult zebrafish brain atlas (AZBA) for automated segmentation using advanced normalization tools (ANTs). We used our pipeline to measure brain activity after zebrafish were subject to the novel tank test. We found that cfos levels peaked 15 minutes following behavior and that several regions containing serotoninergic, dopaminergic, noradrenergic, and cholinergic neurons were active during exploration. Finally, we generated a novel tank test functional connectome. Functional network analysis revealed that several regions of the medial ventral telencephalon form a cohesive sub-network during exploration. We also found that the anterior portion of the parvocellular preoptic nucleus (PPa) serves as a key connection between the ventral telencephalon and many other parts of the brain. Taken together, our work enables whole-brain activity mapping in adult zebrafish for the first time while providing insight into neural basis for the novel tank test.

Examining the relationship between psychosocial adversity and inhibitory control: an fMRI study of children growing up in extreme poverty.

Exposure to psychosocial adversity (PA) is associated with poor behavioral, physical, and mental health outcomes in adulthood. As these outcomes are related to alterations in developmental processes, growing evidence suggests that deficits in executive functions-inhibitory control in particular-may, in part, explain this relationship. However, literature examining the development of inhibitory control has been based on children in higher resource environments, and little is known how low resource settings might exacerbate the link between inhibitory control and health outcomes. In this context, we collected fMRI data during a Go/No-Go inhibitory control task and PA variables for 68 children 5 to 7 years of age living in Dhaka, Bangladesh, an area with a high prevalence of PA. The children's mothers completed behavioral questionnaires to assess the child's PA and their own PA. Whole-brain activation underlying inhibitory control was examined using the No-Go versus Go contrast, and associations with PA variables were assessed using whole-brain regressions. Childhood neglect was associated with weaker activation in the right posterior cingulate, whereas greater family conflict, economic stress, and maternal PA factors were associated with greater activation in the left medial frontal gyrus, right superior and middle frontal gyri, and left cingulate gyrus. These data suggest that neural networks supporting inhibitory control processes may vary as a function of exposure to different types of PA, particularly between those related to threat and deprivation. Furthermore, increased activation in children with greater PA may serve as a compensatory mechanism, allowing them to maintain similar behavioral task performance.

Spatiotemporal whole-brain activity and functional connectivity of melodies recognition.

Music is a non-verbal human language, built on logical, hierarchical structures, that offers excellent opportunities to explore how the brain processes complex spatiotemporal auditory sequences. Using the high temporal resolution of magnetoencephalography, we investigated the unfolding brain dynamics of 70 participants during the recognition of previously memorized musical sequences compared to novel sequences matched in terms of entropy and information content. Measures of both whole-brain activity and functional connectivity revealed a widespread brain network underlying the recognition of the memorized auditory sequences, which comprised primary auditory cortex, superior temporal gyrus, insula, frontal operculum, cingulate gyrus, orbitofrontal cortex, basal ganglia, thalamus, and hippocampus. Furthermore, while the auditory cortex responded mainly to the first tones of the sequences, the activity of higher-order brain areas such as the cingulate gyrus, frontal operculum, hippocampus, and orbitofrontal cortex largely increased over time during the recognition of the memorized versus novel musical sequences. In conclusion, using a wide range of analytical techniques spanning from decoding to functional connectivity and building on previous works, our study provided new insights into the spatiotemporal whole-brain mechanisms for conscious recognition of auditory sequences.

Cortical Face-Selective Responses Emerge Early in Human Infancy.

In human adults, multiple cortical regions respond robustly to faces, including the occipital face area (OFA) and fusiform face area (FFA), implicated in face perception, and the superior temporal sulcus (STS) and medial prefrontal cortex (MPFC), implicated in higher-level social functions. When in development, does face selectivity arise in each of these regions? Here, we combined two awake infant functional magnetic resonance imaging (fMRI) datasets to create a sample size twice the size of previous reports (n = 65 infants; 2.6-9.6 months). Infants watched movies of faces, bodies, objects, and scenes, while fMRI data were collected. Despite variable amounts of data from each infant, individual subject whole-brain activation maps revealed responses to faces compared to nonface visual categories in the approximate location of OFA, FFA, STS, and MPFC. To determine the strength and nature of face selectivity in these regions, we used cross-validated functional region of interest analyses. Across this larger sample size, face responses in OFA, FFA, STS, and MPFC were significantly greater than responses to bodies, objects, and scenes. Even the youngest infants (2-5 months) showed significantly face-selective responses in FFA, STS, and MPFC, but not OFA. These results demonstrate that face selectivity is present in multiple cortical regions within months of birth, providing powerful constraints on theories of cortical development.

Quantitative Activity-Induced Manganese-Enhanced Magnetic Resonance Imaging: Principles, Applications, and Limitations

Accurate identification of regions that show activity changes in response to functional expression is necessary to understand the mechanisms underlying functional expression in the brain. Quantitative activity-induced manganese-enhanced magnetic resonance imaging (qAIM-MRI) is a noninvasive whole-brain activity history imaging method used for this purpose. Notably, qAIM-MRI is a pseudo-Ca2+ imaging method that uses Mn2+ as a surrogate marker for Ca2+. In this paper, I describe the principles, applications, and limitations of qAIM-MRI.

Multivariate sharp-wave ripples in schizophrenia during awake state.

Schizophrenia (SZ) is a brain disorder characterized by psychotic symptoms and cognitive dysfunction. Recently, irregularities in sharp-wave ripples (SPW-Rs) have been reported in SZ. As SPW-Rs play a critical role in memory, their irregularities can cause psychotic symptoms and cognitive dysfunction in patients with SZ. In this study, we investigated the SPW-Rs in human SZ. We measured whole-brain activity using magnetoencephalography (MEG) in patients with SZ (n = 20) and sex- and age-matched healthy participants (n = 20) during open-eye rest. We identified SPW-Rs and analyzed their occurrence and time-frequency traits. Furthermore, we developed a novel multivariate analysis method, termed "ripple-gedMEG" to extract the global features of SPW-Rs. We also examined the association between SPW-Rs and brain state transitions. The outcomes of these analyses were modeled to predict the positive and negative syndrome scale (PANSS) scores of SZ. We found that SPW-Rs in the SZ (1) occurred more frequently, (2) the delay of the coupling phase (3) appeared in different brain areas, (4) consisted of a less organized spatiotemporal pattern, and (5) were less involved in brain state transitions. Finally, some of the neural features associated with the SPW-Rs were found to be PANSS-positive, a pathological indicator of SZ. These results suggest that widespread but disorganized SPW-Rs underlies the symptoms of SZ. We identified irregularities in SPW-Rs in SZ and confirmed that their alternations were strongly associated with SZ neuropathology. These results suggest a new direction for human SZ research.

A master regulator of opioid reward in the ventral prefrontal cortex.

In addition to their intrinsic rewarding properties, opioids can also evoke aversive reactions that protect against misuse. Cellular mechanisms that govern the interplay between opioid reward and aversion are poorly understood. We used whole-brain activity mapping in mice to show that neurons in the dorsal peduncular nucleus (DPn) are highly responsive to the opioid oxycodone. Connectomic profiling revealed that DPn neurons innervate the parabrachial nucleus (PBn). Spatial and single-nuclei transcriptomics resolved a population of PBn-projecting pyramidal neurons in the DPn that express μ-opioid receptors (μORs). Disrupting μOR signaling in the DPn switched oxycodone from rewarding to aversive and exacerbated the severity of opioid withdrawal. These findings identify the DPn as a key substrate for the abuse liability of opioids.

Long-Term Bridge Training Induces Functional Plasticity Changes in the Brain of Early-Adult Individuals.

The aim of this study was to investigate the impact of extended bridge expertise on rapid perceptual processing and brain functional plasticity in early adulthood, utilizing functional magnetic resonance imaging (fMRI). In this investigation, we compared 6 high-level college bridge players with 25 college students lacking bridge experience, assessing their intelligence and working memory. Additionally, we scrutinized behavioral performance and whole-brain activation patterns during an image perceptual judgment task. Findings indicated significant group and interaction effects at the behavioral level. Bridge players exhibited prolonged reaction times and enhanced accuracy on card tasks. At the neural level, the activation level of bridge players in the occipital lobe exceeded that of ordinary college students, with more pronounced group effects in the motor area and inferior parietal lobule during card tasks. This implies that bridge expertise in early adulthood induces functional plasticity changes in regions associated with visual processing and automated mathematical computation.