Michael W. Cole

Multi-task connectivity reveals flexible hubs for adaptive task control

Extensive evidence suggests that the human ability to adaptively implement a wide variety of tasks is preferentially a result of the operation of a fronto-parietal brain network (FPN). We hypothesized that this networks adaptability is made possible by flexible hubs: brain regions that rapidly update their pattern of global functional connectivity according to task demands. Using recent advances in characterizing brain network organization and dynamics, we identified mechanisms consistent with the flexible hub theory. We found that the FPNs brain-wide functional connectivity pattern shifted more than those of other networks across a variety of task states and that these connectivity patterns could be used to identify the current task. Furthermore, these patterns were consistent across practiced and novel tasks, suggesting that reuse of flexible hub connectivity patterns facilitates adaptive (novel) task performance. Together, these findings support a central role for fronto-parietal flexible hubs in cognitive control and adaptive implementation of task demands.

The role of default network deactivation in cognition and disease

A considerable body of evidence has accumulated over recent years on the functions of the default-mode network (DMN)--a set of brain regions whose activity is high when the mind is not engaged in specific behavioral tasks and low during focused attention on the external environment. In this review, we focus on DMN suppression and its functional role in health and disease, summarizing evidence that spans several disciplines, including cognitive neuroscience, pharmacological neuroimaging, clinical neuroscience, and theoretical neuroscience. Collectively, this research highlights the functional relevance of DMN suppression for goal-directed cognition, possibly by reducing goal-irrelevant functions supported by the DMN (e.g., mind-wandering), and illustrates the functional significance of DMN suppression deficits in severe mental illness.

Global Connectivity of Prefrontal Cortex Predicts Cognitive Control and Intelligence

Control of thought and behavior is fundamental to human intelligence. Evidence suggests a frontoparietal brain network implements such cognitive control across diverse contexts. We identify a mechanism—global connectivity—by which components of this network might coordinate control of other networks. A lateral prefrontal cortex (LPFC) regions activity was found to predict performance in a high control demand working memory task and also to exhibit high global connectivity. Critically, global connectivity in this LPFC region, involving connections both within and outside the frontoparietal network, showed a highly selective relationship with individual differences in fluid intelligence. These findings suggest LPFC is a global hub with a brainwide influence that facilitates the ability to implement control processes central to human intelligence.

Characterizing Thalamo-Cortical Disturbances in Schizophrenia and Bipolar Illness

Schizophrenia is a devastating neuropsychiatric syndrome associated with distributed brain dysconnectivity that may involve large-scale thalamo-cortical systems. Incomplete characterization of thalamic connectivity in schizophrenia limits our understanding of its relationship to symptoms and to diagnoses with shared clinical presentation, such as bipolar illness, which may exist on a spectrum. Using resting-state functional magnetic resonance imaging, we characterized thalamic connectivity in 90 schizophrenia patients versus 90 matched controls via: (1) Subject-specific anatomically defined thalamic seeds; (2) anatomical and data-driven clustering to assay within-thalamus dysconnectivity; and (3) machine learning to classify diagnostic membership via thalamic connectivity for schizophrenia and for 47 bipolar patients and 47 matched controls. Schizophrenia analyses revealed functionally related disturbances: Thalamic over-connectivity with bilateral sensory-motor cortices, which predicted symptoms, but thalamic under-connectivity with prefrontal-striatal-cerebellar regions relative to controls, possibly reflective of sensory gating and top-down control disturbances. Clustering revealed that this dysconnectivity was prominent for thalamic nuclei densely connected with the prefrontal cortex. Classification and cross-diagnostic results suggest that thalamic dysconnectivity may be a neural marker for disturbances across diagnoses. Present findings, using one of the largest schizophrenia and bipolar neuroimaging samples to date, inform basic understanding of large-scale thalamo-cortical systems and provide vital clues about the complex nature of its disturbances in severe mental illness.

Altered global brain signal in schizophrenia

Significance This study identified elevated global brain signal variability in schizophrenia, but not bipolar illness. This variability was related to schizophrenia symptoms. A commonly used analytic procedure in neuroimaging, global signal regression, attenuated clinical effects and altered inferences. Furthermore, local voxel-wise variance was increased in schizophrenia, independent of global signal regression. Finally, neurobiologically grounded computational modeling suggests a putative mechanism, whereby altered overall connection strength in schizophrenia may underlie observed empirical results. Neuropsychiatric conditions like schizophrenia display a complex neurobiology, which has long been associated with distributed brain dysfunction. However, no investigation has tested whether schizophrenia shows alterations in global brain signal (GS), a signal derived from functional MRI and often discarded as a meaningless baseline in many studies. To evaluate GS alterations associated with schizophrenia, we studied two large chronic patient samples (n = 90, n = 71), comparing them to healthy subjects (n = 220) and patients diagnosed with bipolar disorder (n = 73). We identified and replicated increased cortical power and variance in schizophrenia, an effect predictive of symptoms yet obscured by GS removal. Voxel-wise signal variance was also increased in schizophrenia, independent of GS effects. Both findings were absent in bipolar patients, confirming diagnostic specificity. Biologically informed computational modeling of shared and nonshared signal propagation through the brain suggests that these findings may be explained by altered net strength of overall brain connectivity in schizophrenia.

Global prefrontal and fronto-amygdala dysconnectivity in bipolar I disorder with psychosis history.

BACKGROUND Pathophysiological models of bipolar disorder postulate that mood dysregulation arises from fronto-limbic dysfunction, marked by reduced prefrontal cortex (PFC) inhibitory control. This might occur due to both disruptions within PFC networks and abnormal inhibition over subcortical structures involved in emotional processing. However, no study has examined global PFC dysconnectivity in bipolar disorder and tested whether regions with within-PFC dysconnectivity also exhibit fronto-limbic connectivity deficits. Furthermore, no study has investigated whether such connectivity disruptions differ for bipolar patients with psychosis history, who might exhibit a more severe clinical course. METHODS We collected resting-state functional magnetic resonance imaging at 3T in 68 remitted bipolar I patients (34 with psychosis history) and 51 demographically matched healthy participants. We employed a recently developed global brain connectivity method, restricted to PFC (rGBC). We also independently tested connectivity between anatomically defined amygdala and PFC. RESULTS Bipolar patients exhibited reduced medial prefrontal cortex (mPFC) rGBC, increased amygdala-mPFC connectivity, and reduced connectivity between amygdala and dorsolateral PFC. All effects were driven by psychosis history. Moreover, the magnitude of observed effects was significantly associated with lifetime psychotic symptom severity. CONCLUSIONS This convergence between rGBC, seed-based amygdala findings, and symptom severity analyses highlights that mPFC, a core emotion regulation region, exhibits both within-PFC dysconnectivity and connectivity abnormalities with limbic structures in bipolar illness. Furthermore, lateral PFC dysconnectivity in patients with psychosis history converges with published work in schizophrenia, indicating possible shared risk factors. Observed dysconnectivity in remitted patients suggests a bipolar trait characteristic and might constitute a risk factor for phasic features of the disorder.

The Frontoparietal Control System A Central Role in Mental Health

Recent findings suggest the existence of a frontoparietal control system consisting of flexible hubs that regulate distributed systems (e.g., visual, limbic, motor) according to current task goals. A growing number of studies are reporting alterations of this control system across a striking range of mental diseases. We suggest this may reflect a critical role for the control system in promoting and maintaining mental health. Specifically, we propose that this system implements feedback control to regulate symptoms as they arise (e.g., excessive anxiety reduced via regulation of amygdala), such that an intact control system is protective against a variety of mental illnesses. Consistent with this possibility, recent results indicate that several major mental illnesses involve altered brain-wide connectivity of the control system, likely altering its ability to regulate symptoms. These results suggest that this “immune system of the mind” may be an especially important target for future basic and clinical research.

Global resting-state functional magnetic resonance imaging analysis identifies frontal cortex, striatal, and cerebellar dysconnectivity in obsessive-compulsive disorder.

BACKGROUND Obsessive-compulsive disorder (OCD) is associated with regional hyperactivity in cortico-striatal circuits. However, the large-scale patterns of abnormal neural connectivity remain uncharacterized. Resting-state functional connectivity studies have shown altered connectivity within the implicated circuitry, but they have used seed-driven approaches wherein a circuit of interest is defined a priori. This limits their ability to identify network abnormalities beyond the prevailing framework. This limitation is particularly problematic within the prefrontal cortex (PFC), which is large and heterogeneous and where a priori specification of seeds is therefore difficult. A hypothesis-neutral, data-driven approach to the analysis of connectivity is vital. METHODS We analyzed resting-state functional connectivity data collected at 3T in 27 OCD patients and 66 matched control subjects with a recently developed data-driven global brain connectivity (GBC) method, both within the PFC and across the whole brain. RESULTS We found clusters of decreased connectivity in the left lateral PFC in both whole-brain and PFC-restricted analyses. Increased GBC was found in the right putamen and left cerebellar cortex. Within regions of interest in the basal ganglia and thalamus, we identified increased GBC in dorsal striatum and anterior thalamus, which was reduced in patients on medication. The ventral striatum/nucleus accumbens exhibited decreased global connectivity but increased connectivity specifically with the ventral anterior cingulate cortex in subjects with OCD. CONCLUSIONS These findings identify previously uncharacterized PFC and basal ganglia dysconnectivity in OCD and reveal differentially altered GBC in dorsal and ventral striatum. Results highlight complex disturbances in PFC networks, which could contribute to disrupted cortical-striatal-cerebellar circuits in OCD.

Cingulate cortex: Diverging data from humans and monkeys

Cognitive neuroscience research relies, in part, on homologies between the brains of human and non-human primates. A quandary therefore arises when presumed anatomical homologues exhibit different functional properties. Such a situation has recently arisen in the case of the anterior cingulate cortex (ACC). In humans, numerous studies suggest a role for ACC in detecting conflicts in information processing. Studies of macaque monkey ACC, in contrast, have failed to find conflict-related responses. We consider several interpretations of this discrepancy, including differences in research methodology and cross-species differences in functional neuroanatomy. New directions for future research are outlined, emphasizing the importance of distinguishing illusory cross-species differences from the true evolutionary differences that make our species unique.

Prefrontal Dynamics Underlying Rapid Instructed Task Learning Reverse with Practice

The ability to rapidly reconfigure our minds to perform novel tasks is important for adapting to an ever-changing world, yet little is understood about its basis in the brain. Furthermore, it is unclear how this kind of task preparation changes with practice. Previous research suggests that prefrontal cortex (PFC) is essential when preparing to perform either novel or practiced tasks. Building upon recent evidence that PFC is organized in an anterior-to-posterior hierarchy, we postulated that novel and practiced task preparation would differentiate hierarchically distinct regions within PFC across time. Specifically, we hypothesized and confirmed using functional magnetic resonance imaging and magnetoencephalography with humans that novel task preparation is a bottom-up process that involves lower-level rule representations in dorsolateral PFC (DLPFC) before a higher-level rule-integrating task representation in anterior PFC (aPFC). In contrast, we identified a complete reversal of this activity pattern during practiced task preparation. Specifically, we found that practiced task preparation is a top-down process that involves a higher-level rule-integrating task representation (recalled from long-term memory) in aPFC before lower-level rule representations in DLPFC. These findings reveal two distinct yet highly inter-related mechanisms for task preparation, one involving task set formation from instructions during rapid instructed task learning and the other involving task set retrieval from long-term memory to facilitate familiar task performance. These two mechanisms demonstrate the exceptional flexibility of human PFC as it rapidly reconfigures cognitive brain networks to implement a wide variety of possible tasks.