Dissociating refreshing and elaboration and their impacts on memory

Maintenance of information in working memory (WM) is assumed to rely on refreshing and elaboration, but clear mechanistic descriptions of these cognitive processes are lacking, and it is unclear whether they are simply two labels for the same process. This fMRI study investigated the extent to which refreshing, elaboration, and repeating of items in WM are distinct neural processes with dissociable behavioral outcomes in WM and long-term memory (LTM). Multivariate pattern analyses of fMRI data revealed differentiable neural signatures for these processes, which we also replicated in an independent sample of older adults. In some cases, the degree of neural separation within an individual predicted their memory performance. Elaboration improved LTM, but not WM, and this benefit increased as its neural signature became more distinct from repetition. Refreshing had no impact on LTM, but did improve WM, although the neural discrimination of this process was not predictive of the degree of improvement. These results demonstrate that refreshing and elaboration are separate processes that differently contribute to memory performance

Neural evidence for a distinction between short-term memory and the focus of attention

It is widely assumed that the short-term retention of information is accomplished via maintenance of an active neural trace. However, we demonstrate that memory can be preserved across a brief delay despite the apparent loss of sustained representations. Delay period activity may, in fact, reflect the focus of attention, rather than STM. We unconfounded attention and memory by causing external and internal shifts of attention away from items that were being actively retained. Multivariate pattern analysis of fMRI indicated that only items within the focus of attention elicited an active neural trace. Activity corresponding to representations of items outside the focus quickly dropped to baseline. Nevertheless, this information was remembered after a brief delay. Our data also show that refocusing attention toward a previously unattended memory item can reactivate its neural signature. The loss of sustained activity has long been thought to indicate a disruption of STM, but our results suggest that, even for small memory loads not exceeding the capacity limits of STM, the active maintenance of a stimulus representation may not be necessary for its short-term retention

Increased Alpha-Band Power during the Retention of Shapes and Shape-Location Associations in Visual Short-Term Memory

Studies exploring the role of neural oscillations in cognition have revealed sustained increases in alpha-band (~8–14 Hz) power during the delay period of delayed-recognition short-term memory tasks. These increases have been proposed to reflect the inhibition, for example, of cortical areas representing task-irrelevant information, or of potentially interfering representations from previous trials. Another possibility, however, is that elevated delay-period alpha-band power (DPABP) reflects the selection and maintenance of information, rather than, or in addition to, the inhibition of task-irrelevant information. In the present study, we explored these possibilities using a delayed-recognition paradigm in which the presence and task relevance of shape information was systematically manipulated across trial blocks and electroencephalographic was used to measure alpha-band power. In the first trial block, participants remembered locations marked by identical black circles. The second block featured the same instructions, but locations were marked by unique shapes. The third block featured the same stimulus presentation as the second, but with pretrial instructions indicating, on a trial-by-trial basis, whether memory for shape or location was required, the other dimension being irrelevant. In the final block, participants remembered the unique pairing of shape and location for each stimulus. Results revealed minimal DPABP in each of the location-memory conditions, whether locations were marked with identical circles or with unique task-irrelevant shapes. In contrast, alpha-band power increases were observed in both the shape-memory condition, in which location was task irrelevant, and in the critical final condition, in which both shape and location were task relevant. These results provide support for the proposal that alpha-band oscillations reflect the retention of shape information and/or shape–location associations in short-term memory

Consensus on the reporting and experimental design of clinical and cognitive-behavioural neurofeedback studies (CRED-nf checklist)

Neurofeedback has begun to attract the attention and scrutiny of the scientific and medical mainstream. Here, neurofeedback researchers present a consensus-derived checklist that aims to improve the reporting and experimental design standards in the field.</p

Competition between items in working memory leads to forgetting

Switching attention from one thought to the next propels our mental lives forward. However, it is unclear how this thought-juggling affects our ability to remember these thoughts. Here we show that competition between the neural representations of pictures in working memory can impair subsequent recognition of those pictures. We use pattern classifiers to decode functional magnetic resonance imaging (fMRI) data from a retro-cueing task where participants juggle two pictures in working memory. Trial-by-trial fluctuations in neural dynamics are predictive of performance on a surprise recognition memory test: trials that elicit similar levels of classifier evidence for both pictures (indicating close competition) are associated with worse memory performance than trials where participants switch decisively from thinking about one picture to the other. This result is consistent with the non-monotonic plasticity hypothesis, which predicts that close competition can trigger weakening of memories that lose the competition, leading to subsequent forgetting

Neural evidence of the strategic choice between working memory and episodic memory in prospective remembering

Theories of prospective memory (PM) posit that it can be subserved either by working memory (WM) or episodic memory (EM). Testing and refining these multiprocess theories of PM requires a way of tracking participants' reliance on WM versus EM. Here we use multi-voxel pattern analysis (MVPA) to derive a trial-by-trial measure of WM use in prospective memory. We manipulated strategy demands by varying the degree of proactive interference (which impairs EM) and the memory load required to perform the secondary task (which impairs WM). For the condition in which participants were pushed to rely more on WM, our MVPA measures showed 1) greater WM use and 2) a trial-by-trial correlation between WM use and PM behavior. Finally, we also showed that MVPA measures of WM use are not redundant with other behavioral measures: in the condition in which participants were pushed more to rely on WM, using neural and behavioral measures together led to better prediction of PM accuracy than either measure on its own

Self-regulation strategy, feedback timing and hemodynamic properties modulate learning in a simulated fMRI neurofeedback environment.

Direct manipulation of brain activity can be used to investigate causal brain-behavior relationships. Current noninvasive neural stimulation techniques are too coarse to manipulate behaviors that correlate with fine-grained spatial patterns recorded by fMRI. However, these activity patterns can be manipulated by having people learn to self-regulate their own recorded neural activity. This technique, known as fMRI neurofeedback, faces challenges as many participants are unable to self-regulate. The causes of this non-responder effect are not well understood due to the cost and complexity of such investigation in the MRI scanner. Here, we investigated the temporal dynamics of the hemodynamic response measured by fMRI as a potential cause of the non-responder effect. Learning to self-regulate the hemodynamic response involves a difficult temporal credit-assignment problem because this signal is both delayed and blurred over time. Two factors critical to this problem are the prescribed self-regulation strategy (cognitive or automatic) and feedback timing (continuous or intermittent). Here, we sought to evaluate how these factors interact with the temporal dynamics of fMRI without using the MRI scanner. We first examined the role of cognitive strategies by having participants learn to regulate a simulated neurofeedback signal using a unidimensional strategy: pressing one of two buttons to rotate a visual grating that stimulates a model of visual cortex. Under these conditions, continuous feedback led to faster regulation compared to intermittent feedback. Yet, since many neurofeedback studies prescribe implicit self-regulation strategies, we created a computational model of automatic reward-based learning to examine whether this result held true for automatic processing. When feedback was delayed and blurred based on the hemodynamics of fMRI, this model learned more reliably from intermittent feedback compared to continuous feedback. These results suggest that different self-regulation mechanisms prefer different feedback timings, and that these factors can be effectively explored and optimized via simulation prior to deployment in the MRI scanner

Automatic learning of neurofeedback signals.

<p><b>(A)</b> Reinforcement learning is used to shape neural activity in the absence of delay. <b>(B)</b> A simple two-voxel neural model is used to demonstrate how our model of automatic learning can learn a pattern of neural activity associated with a stimulus. <b>(C)</b> Without delays, our model is able to learn the desired pattern of neural activity. The top row shows example data from one trial, while the filled plots on the bottom row show the mean and 50% confidence interval (CI) for each signal at each time point, averaged over 1000 simulated trials. <b>(D)</b> If significant physiological delays exist, then an internal model must exist to hold in memory underlying neural activity before it can be reinforced by the delayed feedback signal. <b>(E)</b> If no internal model exists, learning of neural activity filtered by the HRF does not occur.</p