The what, where and how of delay activity

Abstract

Working memory is characterized by neural activity that persists during the retention interval of delay tasks. Despite the ubiquity of this delay activity across tasks, species and experimental techniques, our understanding of this phenomenon remains incomplete. Although initially there was a narrow focus on sustained activation in a small number of brain regions, methodological and analytical advances have allowed researchers to uncover previously unobserved forms of delay activity various parts of the brain. In light of these new findings, this Review reconsiders what delay activity is, where in the brain it is found, what roles it serves and how it may be generated.

Fig. 1 |. Schematic examples of different types of delay activity.

Here we use schematics to highlight two properties of delay activity. First, delay activity can be stable in time (top row), or it can be temporally irregular or dynamic (bottom row). Second, delay activity can be measured within or averaged over individual neurons, voxels or electrodes (left column), or measured as the combined response across populations of neurons/voxels/electrodes (right column). a | Temporally stable delay activity in individual neurons or blood-oxygen-level-dependent (BOLD) response averaged over functional MRI voxels. Activity remains elevated above baseline throughout the delay period, signifying the sustained representation of information. b | Temporally irregular responses in individual neurons or electrodes. Individual neurons can display spiking activity that varies over the course of the delay (schematicized at the top of this panel). Recent results demonstrate intermittent bursts in the LFP signal throughout the delay (schematicized at the bottom). c | Stable population coding. WM information (for example, WM content, task rules or planned responses) can be decoded from the combined activity of populations of neurons or voxels. A pattern classifier can be trained and tested on independent data sets recorded during a WM task. Above-chance classification accuracy indicates that a representation of the information being classified exists in those neurons or voxels. The classifier can be trained on data from a specific time (for example, during the early delay) in the trial, and tested (on independent data) from the same time point or different time points, allowing one to measure the stability of the representation over the course of WM maintenance. In stable population codes, the pattern of activity that encodes specific information at any given time point is the same as the pattern of activity that encodes that same information at any other time point; thus, a classifier trained at one time point will be more accurate than chance at other time points throughout the trial. This is indicated by above chance classification at each time point regardless of which time point or period (for example, those represented in light blue, red or green) the classifier is trained on. d | Dynamic population coding. In contrast to stable population coding, information encoded in the population activity at a certain time point is encoded in different forms of activity at other time points. A classifier trained on a time point will therefore perform successfully at that time point, but not at other time points in the trial. This time-dependent classification is indicated by above-chance classification accuracy along the diagonal of the training-by-testing matrix (top; compare to the matrix in c), but chance classification elsewhere in the matrix, and above-chance classification accuracy that is limited to brief periods of time for classifiers trained on the sample, delay and response periods (bottom; light blue, red and green, respectively).

Fig. 2 |. Schematic depictions of the properties of delay activity in different brain regions.

In each panel, simplified schematic diagrams are provided to illustrate the type of information represented by delay activity in different parts of the brain. Note that not all of the findings were shown in humans, but the regions have been depicted on a human brain for illustrative purposes. a | Delay activity in the lateral prefrontal cortex (lPFC) represents task rules. Population analyses involving pattern classification approaches have demonstrated that classification of the task rule (for example, which feature of a memorandum is relevant for response) is above chance during the memory delay, suggesting that lPFC delay activity represents aspects of task rules. b | lPFC delay activity represents working memory (WM) content. Neurons in the lPFC of non-human primates (NHPs) exhibit delay-period activity that varies in spike frequency with the properties of the memory stimulus, such as vibrotactile frequency. c | Electroencephalogram (EEG) electrodes over PPC reveal delay activity that increases in magnitude and oscillatory power with WM load, and plateaus at an individual’s WM capacity. This is consistent with the notions that PPC delay activity encodes WM content and that PPC delay activity represents internal attention directed to items in WM. Challenges in localizing EEG activity make it unclear where in the brain these signals originate. d | Basal ganglia (BG) delay activity is associated with the upcoming behavioural response. BG delay activity is greater in magnitude when participants can anticipate the upcoming response (prospective representation) than when they cannot (retrospective representation). e | Neurons in motor association cortex show preference for specific response rules. Tasks that require NHPs to maintain response rules (for example, which memory item to indicate first with a behavioural response), suggest that this region encodes the anticipation of specific planned responses. f | Population activity in visual sensory regions is tuned to features of WM content. Functional MRI studies can identify meso-scale responses to features (such as orientation) of memory items, and have found that populations that represent features of WM content are preferentially active during the delay. g | Delay activity in the medial temporal lobe (MTL) may be involved in storing complex information in WM. The magnitude of MTL delay activity is larger for novel items than for familiar items, and MTL delay activity is often observed during WM for complex items. h | The thalamus exhibits delay activity that seems to drive delay responses in PFC. Experimental disruption of thalamic delay activity in mice resulted in reduced or abolished delay activity in PFC^,.