Decoding oscillatory representations and mechanisms in memory

Jafarpour, Anna; Horner, Aidan J.; Fuentemilla, Lluís; Penny, Will D.; Düzel, Emrah

doi:10.1016/j.neuropsychologia.2012.04.002

Cited by 34 publications

(33 citation statements)

References 52 publications

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“…Moreover, they found that the combination of power and phase was better than either measure alone (Figure 1C), indicating a multiplexed coding scheme (discussed below). Together, these and other studies [30,31] confirm that content-specific representations can be decoded from aggregated neural activity.…”

Section: Independent Contributions Of Lfp Power and Phase To Neural Rsupporting

confidence: 79%

More than spikes: common oscillatory mechanisms for content specific neural representations during perception and memory

Watrous

Fell

Ekstrom

et al. 2015

Current Opinion in Neurobiology

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Although previous research into the mechanisms underlying sensory and episodic representations has primarily focused on changes in neural firing rate, more recent evidence suggests that neural oscillations also contribute to these representations. Here, we argue that multiplexed oscillatory power and phase contribute to neural representations at the mesoscopic scale, complementary to neuronal firing. Reviewing recent studies which used oscillatory activity to decipher content-specific neural representations, we identify oscillatory mechanisms common to both sensory and episodic memory representations and incorporate these into a model of episodic encoding and retrieval. This model advances the idea that oscillations provide a reference frame for phase-coded item representations during memory encoding and that shifts in oscillatory frequency and phase coordinate ensemble activity during memory retrieval.

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Section: Independent Contributions Of Lfp Power and Phase To Neural Rsupporting

confidence: 79%

More than spikes: common oscillatory mechanisms for content specific neural representations during perception and memory

Watrous

Fell

Ekstrom

et al. 2015

Current Opinion in Neurobiology

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show abstract

“…Therefore, we sought to replicate the important features of the Lewis-Peacock et al (2012) study while assaying neural activity with EEG, a technique sensitive to neural oscillations. This study was also notable for its attempt to decode stimulus information from delay-period oscillatory neural activity, a challenging design which is only slowly being adopted (for a recent review, see Jafarpour et al, 2013). The classifiers used in this study were trained and tested on frequency-transformed EEG data, allowing us to assay the information present in patterns of oscillatory signals.…”

Section: Neural Activation and Representational States In Short-term mentioning

confidence: 99%

Multiple neural states of representation in short-term memory? It’s a matter of attention

LaRocque

Lewis-Peacock

Postle

2014

Front. Hum. Neurosci.

157

138

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Short-term memory (STM) refers to the capacity-limited retention of information over a brief period of time, and working memory (WM) refers to the manipulation and use of that information to guide behavior. In recent years it has become apparent that STM and WM interact and overlap with other cognitive processes, including attention (the selection of a subset of information for further processing) and long-term memory (LTM—the encoding and retention of an effectively unlimited amount of information for a much longer period of time). Broadly speaking, there have been two classes of memory models: systems models, which posit distinct stores for STM and LTM (Atkinson and Shiffrin, 1968; Baddeley and Hitch, 1974); and state-based models, which posit a common store with different activation states corresponding to STM and LTM (Cowan, 1995; McElree, 1996; Oberauer, 2002). In this paper, we will focus on state-based accounts of STM. First, we will consider several theoretical models that postulate, based on considerable behavioral evidence, that information in STM can exist in multiple representational states. We will then consider how neural data from recent studies of STM can inform and constrain these theoretical models. In the process we will highlight the inferential advantage of multivariate, information-based analyses of neuroimaging data (fMRI and electroencephalography (EEG)) over conventional activation-based analysis approaches (Postle, in press). We will conclude by addressing lingering questions regarding the fractionation of STM, highlighting differences between the attention to information vs. the retention of information during brief memory delays.

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“…Offline, the data were downsampled to 512 Hz, and divided into epochs of 4 s, from -1.5 to 2.5 s relative to both the onset of the word cue and target image in the study phase and relative to the word cue in the test phase. The data were transformed to a linked-mastoid reference, and a baseline correction was applied (subtraction by the average amplitude of the epoch; as in Jafarpour et al, 2013, 2014). Bipolar EOG was computed using the FP1 and the electrodes placed vertically and horizontally around the eyes.…”

Section: Methodsmentioning

confidence: 99%

“…Thus, for each classifier, there were 6510 possible features (31 channels × 42 frequencies × five time points). No additional baseline correction was performed on the TFR and instead the power at each timepoint, frequency, and channel was normalized across trials (as in Jafarpour et al, 2013, 2014). Each classification used a ten-fold cross validation, that is, the data were randomized and partitioned into ten rough equal-sized subsets, over which ten training-test iterations were performed.…”

Section: Methodsmentioning

confidence: 99%

Neural Pattern Classification Tracks Transfer-Appropriate Processing in Episodic Memory

Bramão

Johansson

2018

eNeuro

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The transfer-appropriate processing (TAP) account holds that episodic memory depends on the overlap between encoding and retrieval processing. In the current study, we employed multivariate pattern analysis (MVPA) of electroencephalography to examine the relevance of spontaneously engaged visual processing during encoding for later retrieval. Human participants encoded word-picture associations, where the picture could be a famous face, a landmark, or an object. At test, we manipulated the retrieval demands by asking participants to retrieve either visual or verbal information about the pictures. MVPA revealed classification between picture categories during early perceptual stages of encoding (∼170 ms). Importantly, these visual category-specific neural patterns were predictive of later episodic remembering, but the direction of the relationship was contingent on the particular retrieval demand of the memory task: a benefit for the visual and a cost for the verbal. A reinstatement of the category-specific neural patterns established during encoding was observed during retrieval, and again the relationship with behavior varied with retrieval demands. Reactivation of visual representations during retrieval was associated with better memory in the visual task, but with lower performance in the verbal task. Our findings support and extend the TAP account by demonstrating that processing of particular aspects during memory formation can also have detrimental effects on later episodic remembering when other aspects of the event are called-for and shed new light on encoding and retrieval interactions in episodic memory.

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Decoding oscillatory representations and mechanisms in memory

Cited by 34 publications

References 52 publications

More than spikes: common oscillatory mechanisms for content specific neural representations during perception and memory

More than spikes: common oscillatory mechanisms for content specific neural representations during perception and memory

Multiple neural states of representation in short-term memory? It’s a matter of attention

Neural Pattern Classification Tracks Transfer-Appropriate Processing in Episodic Memory

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