Lapses in Attention and Mind-Wandering are Related but Distinct Constructs

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Post by Shireen Parimoo

The takeaway

Lapses in attention are more common in people who are prone to boredom, have poor attentional control, and a tendency to let their mind wander. Mind-wandering, on the other hand, is more strongly related to low motivation and alertness, as well as personality traits like conscientiousness and neuroticism.

What's the science?

We have all experienced days at work where we find it challenging to stay focused on the simplest of tasks. Lapses of attention can occur when we are disengaged from a task or when we let our mind wander, often negatively impacting our performance. The degree to which different causes of attentional lapses are related to each other, as well as to other cognitive abilities and personality traits is unclear. This week in Journal of Experimental Psychology: General, Unsworth and colleagues used latent variable analysis techniques to investigate the underlying causes of lapses in attention and whether individual differences might make some people more prone to experiencing attentional lapses than others.

How did they do it?

Participants were 358 young adults who completed a battery of cognitive tasks that assessed their working memory capacity (e.g., reading span), attentional control abilities (e.g., anti-saccade task), and lapses in attention (e.g., sustained attention to response task – SART). Participants also rated the degree to which they experienced task-unrelated mind-wandering by responding to infrequently presented thought probes during some of the tasks, as well as their level of motivation and alertness. Lastly, they filled out a series of self-report questionnaires assessing aspects of their personality (Big Five Inventory), proneness to boredom, daily cognitive failures including lapses in attention and memory, and sleep habits.

The authors first performed confirmatory factor analyses in which all the measures from the lapses of attention tasks were hypothesized to load onto a single latent factor (i.e., the construct of lapses in attention). In subsequent analyses, they tested whether the lapses of attention measures loaded onto the same factor as mind-wandering thoughts and attentional control or whether those were separable constructs. They then tested how all the cognitive factors were related to each other and to the questionnaire measures. Finally, the authors used structural equation modeling to determine which of the self-reported measures and cognitive factors uniquely contributed to (i) in-lab lapses in attention, (ii) daily cognitive failures, and (ii) task-unrelated mind-wandering, after accounting for the shared contribution of the remaining variables.

What did they find?

Behavioral measures of in-lab attentional lapses loaded onto a single latent factor, which means that those measures do arise from lapses in attention. Importantly, the factor of lapses in attention was distinct from both mind-wandering and attentional control, despite being correlated with them. Reduced attentional control and greater mind-wandering contributed to increased lapses in attention. Moreover, those who were more prone to boredom and lapses in attention in their daily lives were also more likely to experience greater lapses in attention on the cognitive tasks in the lab. In contrast, none of the cognitive factors predicted daily cognitive failures, only boredom proneness, conscientiousness, and neuroticism. These findings demonstrate that although in-lab lapses in attention are associated with boredom proneness, cognitive abilities, and everyday cognitive failures, everyday cognitive failures are primarily driven by personality traits.

Mind-wandering was not only distinct from lapses in attention but also showed a different pattern of correlations with other variables. For example, mind-wandering was associated with greater neuroticism and lower conscientiousness, whereas these personality traits were not related to lapses in attention. Compared to lapses in attention, mind-wandering was weakly related to attentional control and working memory but more strongly correlated with motivation and alertness. Lastly, greater lapses in attention, greater attentional control, and low alertness predicted greater mind-wandering. Thus, cognitive variables and personality traits differentially contribute to every day and in-lab lapses in attention and mind-wandering.

What's the impact?

This study found that lapses in attention and mind-wandering are related but separate constructs that arise from a distinct combination of cognitive abilities and personality traits. These findings provide greater insight into the different reasons why people have difficulty focusing on tasks and pave the way for developing effective interventions for improving task focus and performance.

Access the original scientific publication here.

P.S. This post is a part of our new BrainPost Behavior series. For more posts like this check out BrainPost Behavior.

The Medial Entorhinal Cortex is Necessary for Perception of Time Intervals

Post by Leanna Kalinowski

The takeaway

Connections between two brain regions - the hippocampus and medial entorhinal cortex - are responsible for perceiving and memorizing intervals of time. Neurons in the medial entorhinal cortex play an important role in reproducing these memorized time intervals.

What's the science?

Perceiving and memorizing intervals of time is important for our ability to interact with the changing world. The hippocampus has long been considered important for regulating memory of elapsed time. It receives input from the medial entorhinal cortex (MEC), primarily through the firing of neurons at specific time intervals. The time intervals at which these neurons fire are associated with elapsed time as measured by a clock. However, the specific role of MEC in time perception is still largely unknown. This week in The Journal of Neuroscience, Dias and colleagues examined the role of the MEC in time perception by disrupting MEC activity during a goal-directed timing task.

How did they do it?

To measure rats’ ability to tell time, the authors developed a goal-directed timing task called the Waiting-for-Trajectory (WfT) task. This task took place on a 2.0 m linear testing track: at one end of the track was the rats’ starting area, and at the other end of the track was a delivery pump for a chocolate milk reward. To receive the reward, rats were trained to voluntarily stop and wait at the starting area of the track for 2.5 seconds. If the rats left the waiting area before the 2.5 seconds elapsed, they did not receive a reward.

Once rats were trained on the WfT task, the researchers used a technique called chemogenetics, which is commonly used in neuroscience to directly manipulate the activity of neurons. First, the rats received an injection of a viral vector directly into the MEC. This viral vector then caused the MEC to express DREADDs (“designer receptor exclusively activated by designer drugs”) that “turn off” the neurons when the animals are given a substance called clozapine N-oxide (CNO). This allowed for the researchers to selectively “turn off” cells in the MEC. Following this procedure, rats underwent the WfT task daily for 10 consecutive days. Prior to each testing session, rats received daily alternating injections of either CNO (to “turn off” the MEC) or saline (to keep the MEC “on”), for a total of 5 CNO and 5 saline sessions per rat. The researchers measured the time that rats spent in the waiting area and classified each trial as a “hit” (staying in the waiting area for the full 2.5 seconds) or “miss” (prematurely leaving the waiting area).

What did they find?

First, the researchers found that “turning off” the MEC impaired rats’ ability to successfully complete the WfT task. These rats overestimated the amount of time spent waiting in the designated area, ended their waiting periods prematurely, and did not receive a reward. This suggests that activity in the MEC is necessary for the brain to accurately measure time.

To determine whether the memory of the target waiting time was affected by silencing the MEC, the researchers then used the individual waiting times from each trial to determine whether they would influence performance in subsequent trials. They found that waiting times and performance of any given trial were influenced by up to three of the preceding trials. They also found that “turning off” the MEC increased the number of consecutive misses (trials where rats stopped waiting prematurely). This suggests that decreasing activity in the MEC might influence the effects of trial history on timing behavior.

What's the impact?

Findings from this study reveal an important role of MEC neurons in the accurate reproduction of a memorized time interval. Specifically, these neurons may be responsible for maintaining a reference memory of important time intervals across multiple trials of a goal-directed timing test. These results aid in our understanding of how the brain measures and perceives time.

Memory Reactivation Predicts the Consolidation of Long-Term Cognitive Maps

Post by Andrew Vo

The takeaway

Forming a mental map of our spatial environment involves both active (i.e., exploration) and passive (i.e., rest) processes in the brain. Reactivation of spatial memories occurs during rest and is related to how stable these memories are in the future.

What's the science?

Cognitive maps provide mental representations of our environments. They are encoded during ‘online’ exploratory periods and then consolidated through replay during ‘offline’ resting periods by place cells in the hippocampus. The neural mechanisms by which offline reactivation (i.e. reactivation of memory at rest) of spatial memories strengthen the long-term stability of such representations are still poorly understood. This week in Nature Neuroscience, Grosmark et al. track the activity of hippocampal place cells over 2 weeks to investigate the relationship between offline reactivation and the persistence of spatial memories.

How did they do it?

The authors performed calcium imaging and electrophysiological recordings to measure the activity of cells in the dorsal hippocampus of mice over 12 days. During periods of offline rest, hippocampal activity occurs in short sharp-wave/ripple (SWR) events corresponding to 125-225 Hz oscillations, and these events are thought to support offline reactivation and consolidation of memories. On each day, the mice performed three consecutive sessions, each lasting 15-20 minutes. Their heads were fixed in position to allow recording of hippocampal activity during the behavioral task. During pre- and post-run sessions, the mice would mostly rest on a cue-less treadmill belt. These two sessions were separated by a run session, during which they would run on one of two different 2-m long, cue-rich belts to obtain a spatially fixed reward.

What did they find?

During run sessions, mice spent more time near rewarded versus unrewarded locations on the belt. Recordings from hippocampal place cells revealed pronounced spatial coding and theta oscillations typically associated with online encoding. These spatial representations decayed across days, although those place cells with peak activity occurring closer to reward locations showed greater stability.

During pre- and post-run sessions, increased place cell activity and synchrony coincided with the occurrence of SWR events that are associated with offline reactivation. SWR events were more frequent and longer-lasting during post- than pre-run sessions. This increase in pre to post SWR events was greater for those place cells that coded locations farther away from reward during the run sessions, which the authors argue allows for consolidation of a more comprehensive spatial map of the underlying environment. Ensembles of place cells detected during run sessions were more strongly reactivated during post- than pre-run sessions and coincided with SWR events. Ensemble reactivation remained elevated compared to baseline for at least 24 hours following spatial exploration. Further, this cross-day ensemble reactivation was greater across pairs of days in which the animal ran on the same belt than when they ran on different belts. These findings illustrate the persistence and contextual specificity of offline reactivation across days.

Finally, the authors describe that pre to post-learning changes in SWR recruitment and memory-ensemble participation predicted place cells’ future cross-day spatial coding stability. Notably, the stability-predicting effect of SWRs was specific to the areas of the environment far from the reward. The authors suggest that this is a mechanism by which post-learning reactivation selectively stabilizes the low-salience, under-sampled areas of the cognitive map which are otherwise vulnerable to being forgotten.

What's the impact?

In summary, this study showed that hippocampal offline reactivation predicts the long-term stability of spatial representations and is most prominent for locations farthest from rewards. This process might help to stabilize representations of under-explored or less rewarding parts of the environment that are most vulnerable to memory decay, allowing for a more comprehensive cognitive map of our spatial environment. The findings here reveal a role of offline memory consolidation that is distinct from but complimentary to online learning.