Markus Handal Sneve

Pupil size signals mental effort deployed during multiple object tracking and predicts brain activity in the dorsal attention network and the locus coeruleus

Attentional effort relates to the allocation of limited-capacity attentional resources to meet current task demands and involves the activation of top-down attentional systems in the brain. Pupillometry is a sensitive measure of this intensity aspect of top-down attentional control. Studies relate pupillary changes in response to cognitive processing to activity in the locus coeruleus (LC), which is the main hub of the brains noradrenergic system and it is thought to modulate the operations of the brains attentional systems. In the present study, participants performed a visual divided attention task known as multiple object tracking (MOT) while their pupil sizes were recorded by use of an infrared eye tracker and then were tested again with the same paradigm while brain activity was recorded using fMRI. We hypothesized that the individual pupil dilations, as an index of individual differences in mental effort, as originally proposed by Kahneman (1973), would be a better predictor of LC activity than the number of tracked objects during MOT. The current results support our hypothesis, since we observed pupil-related activity in the LC. Moreover, the changes in the pupil correlated with activity in the superior colliculus and the right thalamus, as well as cortical activity in the dorsal attention network, which previous studies have shown to be strongly activated during visual tracking of multiple targets. Follow-up pupillometric analyses of the MOT task in the same individuals also revealed that individual differences to cognitive load can be remarkably stable over a lag of several years. To our knowledge this is the first study using pupil dilations as an index of attentional effort in the MOT task and also relating these to functional changes in the brain that directly implicate the LC-NE system in the allocation of processing resources.

Brain Events Underlying Episodic Memory Changes in Aging: A Longitudinal Investigation of Structural and Functional Connectivity

Episodic memories are established and maintained by close interplay between hippocampus and other cortical regions, but degradation of a fronto-striatal network has been suggested to be a driving force of memory decline in aging. We wanted to directly address how changes in hippocampal-cortical versus striatal-cortical networks over time impact episodic memory with age. We followed 119 healthy participants (20-83 years) for 3.5 years with repeated tests of episodic verbal memory and magnetic resonance imaging for quantification of functional and structural connectivity and regional brain atrophy. While hippocampal-cortical functional connectivity predicted memory change in young, changes in cortico-striatal functional connectivity were related to change in recall in older adults. Within each age group, effects of functional and structural connectivity were anatomically closely aligned. Interestingly, the relationship between functional connectivity and memory was strongest in the age ranges where the rate of reduction of the relevant brain structure was lowest, implying selective impacts of the different brain events on memory. Together, these findings suggest a partly sequential and partly simultaneous model of brain events underlying cognitive changes in aging, where different functional and structural events are more or less important in various time windows, dismissing a simple uni-factorial view on neurocognitive aging.

Visual short-term memory: Activity supporting encoding and maintenance in retinotopic visual cortex

Recent studies have demonstrated that retinotopic cortex maintains information about visual stimuli during retention intervals. However, the process by which transient stimulus-evoked sensory responses are transformed into enduring memory representations is unknown. Here, using fMRI and short-term visual memory tasks optimized for univariate and multivariate analysis approaches, we report differential involvement of human retinotopic areas during memory encoding of the low-level visual feature orientation. All visual areas show weaker responses when memory encoding processes are interrupted, possibly due to effects in orientation-sensitive primary visual cortex (V1) propagating across extrastriate areas. Furthermore, intermediate areas in both dorsal (V3a/b) and ventral (LO1/2) streams are significantly more active during memory encoding compared with non-memory (active and passive) processing of the same stimulus material. These effects in intermediate visual cortex are also observed during memory encoding of a different stimulus feature (spatial frequency), suggesting that these areas are involved in encoding processes on a higher level of representation. Using pattern-classification techniques to probe the representational content in visual cortex during delay periods, we further demonstrate that simply initiating memory encoding is not sufficient to produce long-lasting memory traces. Rather, active maintenance appears to underlie the observed memory-specific patterns of information in retinotopic cortex.

Nicotinic receptor gene CHRNA4 interacts with processing load in attention.

Background Pharmacological studies suggest that cholinergic neurotransmission mediates increases in attentional effort in response to high processing load during attention demanding tasks [1]. Methodology/Principal Findings In the present study we tested whether individual variation in CHRNA4, a gene coding for a subcomponent in α4β2 nicotinic receptors in the human brain, interacted with processing load in multiple-object tracking (MOT) and visual search (VS). We hypothesized that the impact of genotype would increase with greater processing load in the MOT task. Similarly, we predicted that genotype would influence performance under high but not low load in the VS task. Two hundred and two healthy persons (age range = 39–77, Mean = 57.5, SD = 9.4) performed the MOT task in which twelve identical circular objects moved about the display in an independent and unpredictable manner. Two to six objects were designated as targets and the remaining objects were distracters. The same observers also performed a visual search for a target letter (i.e. X or Z) presented together with five non-targets while ignoring centrally presented distracters (i.e. X, Z, or L). Targets differed from non-targets by a unique feature in the low load condition, whereas they shared features in the high load condition. CHRNA4 genotype interacted with processing load in both tasks. Homozygotes for the T allele (N = 62) had better tracking capacity in the MOT task and identified targets faster in the high load trials of the VS task. Conclusion The results support the hypothesis that the cholinergic system modulates attentional effort, and that common genetic variation can be used to study the molecular biology of cognition.

Attentional load modulates large-scale functional brain connectivity beyond the core attention networks

In line with the notion of a continuously active and dynamic brain, functional networks identified during rest correspond with those revealed by task-fMRI. Characterizing the dynamic cross-talk between these network nodes is key to understanding the successful implementation of effortful cognitive processing in healthy individuals and its breakdown in a variety of conditions involving aberrant brain biology and cognitive dysfunction. We employed advanced network modeling on fMRI data collected during a task involving sustained attentive tracking of objects at two load levels and during rest. Using multivariate techniques, we demonstrate that attentional load levels can be significantly discriminated, and from a resting-state condition, the accuracy approaches 100%, by means of estimates of between-node functional connectivity. Several network edges were modulated during task engagement: The dorsal attention network increased connectivity with a visual node, while decreasing connectivity with motor and sensory nodes. Also, we observed a decoupling between left and right hemisphere dorsal visual streams. These results support the notion of dynamic network reconfigurations based on attentional effort. No simple correspondence between node signal amplitude change and node connectivity modulations was found, thus network modeling provides novel information beyond what is revealed by conventional task-fMRI analysis. The current decoding of attentional states confirms that edge connectivity contains highly predictive information about the mental state of the individual, and the approach shows promise for the utilization in clinical contexts.

Top-down modulation from inferior frontal junction to FEFs and intraparietal sulcus during short-term memory for visual features.

Visual STM of simple features is achieved through interactions between retinotopic visual cortex and a set of frontal and parietal regions. In the present fMRI study, we investigated effective connectivity between central nodes in this network during the different task epochs of a modified delayed orientation discrimination task. Our univariate analyses demonstrate that the inferior frontal junction (IFJ) is preferentially involved in memory encoding, whereas activity in the putative FEFs and anterior intraparietal sulcus (aIPS) remains elevated throughout periods of memory maintenance. We have earlier reported, using the same task, that areas in visual cortex sustain information about task-relevant stimulus properties during delay intervals [Sneve, M. H., Alnæs, D., Endestad, T., Greenlee, M. W., & Magnussen, S. Visual short-term memory: Activity supporting encoding and maintenance in retinotopic visual cortex. Neuroimage, 63, 166–178, 2012]. To elucidate the temporal dynamics of the IFJ-FEF-aIPS-visual cortex network during memory operations, we estimated Granger causality effects between these regions with fMRI data representing memory encoding/maintenance as well as during memory retrieval. We also investigated a set of control conditions involving active processing of stimuli not associated with a memory task and passive viewing. In line with the developing understanding of IFJ as a region critical for control processes with a possible initiating role in visual STM operations, we observed influence from IFJ to FEF and aIPS during memory encoding. Furthermore, FEF predicted activity in a set of higher-order visual areas during memory retrieval, a finding consistent with its suggested role in top–down biasing of sensory cortex.

The Disconnected Brain and Executive Function Decline in Aging

Abstract Higher order speeded cognitive abilities depend on efficient coordination of activity across the brain, rendering them vulnerable to age reductions in structural and functional brain connectivity. The concept of “disconnected aging” has been invoked, suggesting that degeneration of connections between distant brain regions cause cognitive reductions. However, it has not been shown that changes in cognitive functions over time can be explained by simultaneous changes in brain connectivity. We followed 119 young and middle‐aged (23‐52 years) and older (63‐86 years) adults for 3.3 years with repeated assessments of structural and functional brain connectivity and executive functions. We found unique age‐related longitudinal reductions in executive function over and above changes in more basic cognitive processes. Intriguingly, 82.5% of the age‐related decline in executive function could be explained by changes in connectivity over time. While both structural and functional connectivity changes were related to longitudinal reductions in executive function, only structural connectivity change could explain the age‐specific decline. This suggests that the major part of the age‐related reductions in executive function can be attributed to micro‐ and macrostructural alterations in brain connectivity. Although correlational in nature, we believe the present results constitute evidence for a “disconnected brain” view on cognitive aging.

Functional connectivity change across multiple cortical networks relates to episodic memory changes in aging

A major task of contemporary cognitive neuroscience of aging is to explain why episodic memory declines. Change in resting-state functional connectivity (rsFC) could be a mechanism accounting for reduced function. We addressed this through 3 studies. In study 1, 119 healthy participants (20-83 years) were followed for 3.5 years with verbal recall testing and magnetic resonance imaging. Independent of atrophy, recall change was related to change in rsFC in anatomically widespread areas. Striking age-effects were observed in that a positive relationship between rsFC and memory characterized older participants while a negative relationship was seen among the younger and middle-aged. This suggests that cognitive consequences of rsFC change are not stable across age. In study 2 and 3, the age-dependent differences in rsFC-memory relationship were replicated by use of a simulation model (study 2) and by a cross-sectional experimental recognition memory task (study 3). In conclusion, memory changes were related to altered rsFC in an age-dependent manner, and future research needs to detail the mechanisms behind age-varying relationships.

Relationship between structural and functional connectivity change across the adult lifespan: A longitudinal investigation.

Extensive efforts are devoted to understand the functional (FC) and structural connections (SC) of the brain. FC is usually measured by functional magnetic resonance imaging (fMRI), and conceptualized as degree of synchronicity in brain activity between different regions. SC is typically indexed by measures of white matter (WM) properties, for example, by diffusion weighted imaging (DWI). FC and SC are intrinsically related, in that coordination of activity across regions ultimately depends on fast and efficient transfer of information made possible by structural connections. Convergence between FC and SC has been shown for specific networks, especially the default mode network (DMN). However, it is not known to what degree FC is constrained by major WM tracts and whether FC and SC change together over time. Here, 120 participants (20–85 years) were tested at two time points, separated by 3.3 years. Resting‐state fMRI was used to measure FC, and DWI to measure WM microstructure as an index of SC. TRACULA, part of FreeSurfer, was used for automated tractography of 18 major WM tracts. Cortical regions with tight structural couplings defined by tractography were only weakly related at the functional level. Certain regions of the DMN showed a modest relationship between change in FC and SC, but for the most part, the two measures changed independently. The main conclusions are that anatomical alignment of SC and FC seems restricted to specific networks and tracts, and that changes in SC and FC are not necessarily strongly correlated. Hum Brain Mapp 38:561–573, 2017.

Short-term retention of visual information: Evidence in support of feature-based attention as an underlying mechanism.

Retention of features in visual short-term memory (VSTM) involves maintenance of sensory traces in early visual cortex. However, the mechanism through which this is accomplished is not known. Here, we formulate specific hypotheses derived from studies on feature-based attention to test the prediction that visual cortex is recruited by attentional mechanisms during VSTM of low-level features. Functional magnetic resonance imaging (fMRI) of human visual areas revealed that neural populations coding for task-irrelevant feature information are suppressed during maintenance of detailed spatial frequency memory representations. The narrow spectral extent of this suppression agrees well with known effects of feature-based attention. Additionally, analyses of effective connectivity during maintenance between retinotopic areas in visual cortex show that the observed highlighting of task-relevant parts of the feature spectrum originates in V4, a visual area strongly connected with higher-level control regions and known to convey top-down influence to earlier visual areas during attentional tasks. In line with this property of V4 during attentional operations, we demonstrate that modulations of earlier visual areas during memory maintenance have behavioral consequences, and that these modulations are a result of influences from V4.