scholarly journals Behavioral prioritization enhances working memory precision and neural population gain

2021 ◽  
Author(s):  
Aspen H. Yoo ◽  
Alfredo Bolaños ◽  
Grace E. Hallenbeck ◽  
Masih Rahmati ◽  
Thomas C. Sprague ◽  
...  
Keyword(s):  
Working Memory ◽  
Brain Area ◽  
Brain Regions ◽  
Delay Period ◽  
Common Finding ◽  
Neural Population ◽  
Association Cortex ◽  
Absolute Amount ◽  
Neural Populations ◽  
Memory Precision

ABSTRACTHumans allocate visual working memory (WM) resource according to behavioral relevance, resulting in more precise memories for more important items. Theoretically, items may be maintained by feature-tuned neural populations, where the relative gain of the populations encoding each item determines precision. To test this hypothesis, we compared the amplitudes of delay-period activity in the different parts of retinotopic maps representing each of several WM items, predicting amplitude would track with behavioral priority. Using fMRI, we scanned participants while they remembered the location of multiple items over a WM delay, then reported the location of one probed item using a memory-guided saccade. Importantly, items were not equally probable to be probed (0.6, 0.3, 0.1, 0.0), which was indicated with a pre-cue. We analyzed fMRI activity in ten visual field maps in occipital, parietal, and frontal cortex known to be important for visual WM. In early visual cortex, but not association cortex, the amplitude of BOLD activation within voxels corresponding to the retinotopic location of visual WM items increased with the priority of the item. Interestingly, these results were contrasted with a common finding that higher-level brain regions had greater delay-period activity, demonstrating a dissociation between the absolute amount of activity in a brain area, and the activity of different spatially-selective populations within it. These results suggest that the distribution of WM resources according to priority sculpts the relative gains of neural populations that encode items, offering a neural mechanism for how prioritization impacts memory precision.

scholarly journals Behavioral Prioritization Enhances Working Memory Precision and Neural Population Gain

2021 ◽  
pp. 1-14
Author(s):  
Aspen H. Yoo ◽  
Alfredo Bolaños ◽  
Grace E. Hallenbeck ◽  
Masih Rahmati ◽  
Thomas C. Sprague ◽  
...  
Keyword(s):  
Working Memory ◽  
Brain Area ◽  
Brain Regions ◽  
Delay Period ◽  
Common Finding ◽  
Neural Population ◽  
Association Cortex ◽  
Absolute Amount ◽  
Neural Populations ◽  
Memory Precision

Abstract Humans allocate visual working memory (WM) resource according to behavioral relevance, resulting in more precise memories for more important items. Theoretically, items may be maintained by feature-tuned neural populations, where the relative gain of the populations encoding each item determines precision. To test this hypothesis, we compared the amplitudes of delay period activity in the different parts of retinotopic maps representing each of several WM items, predicting the amplitudes would track behavioral priority. Using fMRI, we scanned participants while they remembered the location of multiple items over a WM delay and then reported the location of one probed item using a memory-guided saccade. Importantly, items were not equally probable to be probed (0.6, 0.3, 0.1, 0.0), which was indicated with a precue. We analyzed fMRI activity in 10 visual field maps in occipital, parietal, and frontal cortex known to be important for visual WM. In early visual cortex, but not association cortex, the amplitude of BOLD activation within voxels corresponding to the retinotopic location of visual WM items increased with the priority of the item. Interestingly, these results were contrasted with a common finding that higher-level brain regions had greater delay period activity, demonstrating a dissociation between the absolute amount of activity in a brain area and the activity of different spatially selective populations within it. These results suggest that the distribution of WM resources according to priority sculpts the relative gains of neural populations that encode items, offering a neural mechanism for how prioritization impacts memory precision.

scholarly journals Interhemispheric Connectivity Supports Load-Dependent Working Memory Maintenance for Complex Visual Stimuli

2021 ◽  
Author(s):  
Chelsea Reichert Plaska ◽  
Jefferson Ortega ◽  
Bernard A. Gomes ◽  
Timothy M. Ellmore
Keyword(s):  
Working Memory ◽  
Phase Locking ◽  
Visual Stimuli ◽  
Load Condition ◽  
Brain Regions ◽  
Delay Period ◽  
Temporal Region ◽  
Verbal Rehearsal ◽  
Complex Stimuli ◽  
Low Load

AbstractAn open question in the working memory (WM) field is how information is kept online during the WM delay period. Maintenance of simple stimuli in WM is supported by connectivity between frontal and parietal brain regions. How does delay period activity and connectivity support WM of complex stimuli? Twenty-two participants completed a modified Sternberg WM task with complex stimuli and were told to remember either 2 (low-load) or 5 (high-load) scenes while 32- channel scalp EEG was recorded. During the 6-sec delay period 6 phase-scrambled scenes were presented, which served as interference. While increasing the WM load, particularly with complex stimuli, places a greater demand on attentional resources, interfering stimuli may hijack the available resources. This was confirmed in the examination of theta and alpha amplitude, as amplitude was reduced for the high WM load as compared with the low WM load across frontal, central, and parietal regions. Delay period connectivity was assessed with phase-locking value (PLV). We identified 3 supporting networks that facilitated performance for the low-load condition: 1) increased PLV between left frontal and right posterior temporal in the theta and alpha bands; 2) increased PLV between right anterior temporal and left central in the alpha and lower beta bands; and 3) increased PLV between left anterior temporal and left posterior temporal in theta, alpha, and lower beta bands for the low-load condition. These results suggest that these brain networks facilitated the low-load WM by filtering of interference and the use of verbal rehearsal during the delay period.Impact StatementAlthough, studies of working memory maintenance with simple stimuli have suggested a role of frontal-parietal networks in supporting maintenance, the current study suggests that maintenance of complex visual stimuli with interference present is supported by interhemispheric frontal-posterior temporal and intrahemispheric left temporal region connectivity. These networks support maintenance by filtering of the interfering stimuli, which facilitates the use of verbal rehearsal strategies during the delay period.

scholarly journals Finger representations in primary somatosensory cortex are modulated during vibrotactile working memory

2021 ◽  
Author(s):  
Finn Rabe ◽  
Sanne Kikkert ◽  
Nicole Wenderoth
Keyword(s):  
Working Memory ◽  
Somatosensory Cortex ◽  
Pattern Analysis ◽  
Blood Oxygen Level Dependent ◽  
Brain Regions ◽  
Delay Period ◽  
Blood Oxygen Level ◽  
Secondary Somatosensory Cortex ◽  
Analysis Technique ◽  
Hand Area

It is well-established that vibrotactile stimulations elicit Blood-oxygen-level-dependent (BOLD) responses in somatotopically organized brain regions. Whether these somatotopic maps are modulated by working memory (WM) is still unknown. In our WM experiment, participants had to compare frequencies that were separated by a delay period. Vibrotactile stimuli were sequentially applied to either their right index or little finger. Using functional MRI, we investigated whether vibrotactile WM modulated neural activity in primary somatosensory (S1), an area that is known to contain individual finger representations. Our mass-univariate results revealed the well-described network of brain regions involved in WM. Interestingly, our mass-univariate results did not demonstrate S1 to be part of this network. However, when we parametrically modulated the time-binned regressors in our GLM we found that the delay activity in S1 and secondary somatosensory cortex (S2) was reflected in a U-shaped manner. Using multi-voxel pattern analysis (MVPA), an analysis technique that is more sensitive to subtle activity differences, we found finger-specific patterns of activation in the S1 hand area during the WM delay period. These results indicate that processes underlying WM modulate finger-specific representations during our discrimination task.

scholarly journals Prioritization affects working memory precision and neural population gain

2019 ◽  
Vol 19 (10) ◽  
pp. 204d
Author(s):  
Aspen H Yoo ◽  
Alfredo Bolaños ◽  
Grace E Hallenbeck ◽  
Masih Rahmati ◽  
Thomas C Sprague ◽  
...  
Keyword(s):  
Working Memory ◽  
Neural Population ◽  
Memory Precision

scholarly journals A neural population mechanism for rapid learning

2017 ◽  
Author(s):  
Matthew G. Perich ◽  
Juan A. Gallego ◽  
Lee E. Miller
Keyword(s):  
Brain Area ◽  
Population Level ◽  
Neural Population ◽  
Reaching Movement ◽  
Neural Populations ◽  
Show Evidence ◽  
Preparatory Activity ◽  
Plastic Changes ◽  
The Brain

AbstractLong-term learning of language, mathematics, and motor skills likely requires plastic changes in the cortex, but behavior often requires faster changes, sometimes based even on single errors. Here, we show evidence of one mechanism by which the brain can rapidly develop new motor output, seemingly without altering the functional connectivity between or within cortical areas. We recorded simultaneously from hundreds of neurons in the premotor (PMd) and primary motor (M1) cortices, and computed models relating these neural populations throughout adaptation to reaching movement perturbations. We found a signature of learning in the “null subspace” of PMd with respect to M1. Earlier experiments have shown that null subspace activity allows the motor cortex to alter preparatory activity without directly influencing M1. In our experiments, the null subspace planning activity evolved with the adaptation, yet the “potent” mapping that captures information sent to M1 was preserved. Our results illustrate a population-level mechanism within the motor cortices to adjust the output from one brain area to its downstream structures that could be exploited throughout the brain for rapid, online behavioral adaptation.

scholarly journals Oscillatory correlates of auditory working memory examined with human electrocorticography

2020 ◽  
Author(s):  
Sukhbinder Kumar ◽  
Phillip E. Gander ◽  
Joel I. Berger ◽  
Alexander J. Billig ◽  
Kirill V. Nourski ◽  
...  
Keyword(s):  
Working Memory ◽  
Auditory Cortex ◽  
Frontal Cortex ◽  
Low Frequency ◽  
Brain Regions ◽  
Delay Period ◽  
Blood Oxygenation ◽  
Oscillatory Activity ◽  
Frequency Bands ◽  
Inferior Frontal Cortex

AbstractThis work examines how sounds are held in auditory working memory (AWM) in humans by examining oscillatory local field potentials (LFPs) in candidate brain regions. Previous fMRI studies by our group demonstrated blood oxygenation level-dependent (BOLD) response increases during maintenance in auditory cortex, inferior frontal cortex and the hippocampus using a paradigm with a delay period greater than 10s. The relationship between such BOLD changes and ensemble activity in different frequency bands is complex, and the long delay period raised the possibility that long-term memory mechanisms were engaged. Here we assessed LFPs in different frequency bands in six subjects with recordings from all candidate brain regions using a paradigm with a short delay period of 3 s. Sustained delay activity was demonstrated in all areas, with different patterns in the different areas. Enhancement in low frequency (delta) power and suppression across higher frequencies (beta/gamma) were demonstrated in primary auditory cortex in medial Heschl’s gyrus (HG) whilst non-primary cortex showed patterns of enhancement and suppression that altered at different levels of the auditory hierarchy from lateral HG to superior- and middle-temporal gyrus. Inferior frontal cortex showed increasing suppression with increasing frequency. The hippocampus and parahippocampal gyrus showed low frequency increases and high frequency decreases in oscillatory activity. The work demonstrates sustained activity patterns that can only be explained by AWM maintenance, with prominent low-frequency increases in medial temporal lobe regions.

scholarly journals Delay-period activity in frontal, parietal, and occipital cortex tracks different attractor dynamics in visual working memory

2020 ◽  
Author(s):  
Qing Yu ◽  
Matthew F. Panichello ◽  
Ying Cai ◽  
Bradley R. Postle ◽  
Timothy J. Buschman
Keyword(s):  
Working Memory ◽  
Parietal Cortex ◽  
Memory Load ◽  
Internal Noise ◽  
Occipital Cortex ◽  
Delay Period ◽  
Attractor Dynamics ◽  
Attractor Model ◽  
New Interpretation ◽  
Memory Precision

AbstractOne important neural hallmark of working memory is persistent elevated delay-period activity in frontal and parietal cortex. In human fMRI, delay-period BOLD activity in frontal and parietal cortex increases monotonically with memory load and asymptotes at an individual’s capacity. Previous work has demonstrated that frontal and parietal delay-period activity correlates with the decline in behavioral memory precision observed with increasing memory load. However, because memory precision can be influenced by a variety of factors, it remains unclear what cognitive processes underlie persistent activity in frontal and parietal cortex. Recent psychophysical work has shown that attractor dynamics bias memory representations toward a few stable representations and reduce the effects of internal noise. From this perspective, imprecision in memory results from both drift towards stable attractor states and random diffusion. Here we asked whether delay-period BOLD activity in frontal and parietal cortex might be explained, in part, by these attractor dynamics. We analyzed data from an existing experiment in which subjects performed delayed recall for line orientation, at different loads, during fMRI scanning. We modeled subjects’ behavior using a discrete attractor model, and calculated within-subject correlation between frontal and parietal delay-period activity and estimated sources of memory error (drift and diffusion). We found that although increases in frontal and parietal activity were associated with increases in both diffusion and drift, diffusion explained the most variance in frontal and parietal delay-period activity. In comparison, a subsequent whole-brain regression analysis showed that drift rather than diffusion explained the most variance in delay-period activity in lateral occipital cortex. These results provide a new interpretation for the function of frontal, parietal, and occipital delay-period activity in working memory.

Retrospective prioritization of multiple items during working memory storage

2019 ◽  
Author(s):  
Ashley DiPuma ◽  
Kelly Rivera ◽  
Edward Ester
Keyword(s):  
Working Memory ◽  
Memory Performance ◽  
Memory Item ◽  
Neutral Condition ◽  
Memory Storage ◽  
Single Item ◽  
Incorrect Item ◽  
Memory Precision ◽  
Neutral Conditions ◽  
Directing Attention

Working memory (WM) performance can be improved by an informative cue presented during storage. This effect, termed a retro-cue benefit, can be used to explore mechanisms of attentional prioritization in WM. Directing attention to a single item stored in memory is known to increase memory precision while decreasing the likelihood of incorrect item reports and random guesses, but it is unclear whether similar benefits manifest when participants direct attention to multiple items stored in memory. We tested this possibility by quantifying memory performance when participants were cued to prioritize one or two items stored in working memory. Consistent with prior work, cueing participants to prioritize a single memory item yielded higher recall precision, fewer swap errors, and fewer guesses relative to a neutral cue condition. Conversely, cueing participants to prioritize two memory items yielded fewer swap errors relative to a neutral condition, but no differences in recall precision or guess rates. Although swap rates were less likely during the cue-two vs. neutral conditions, planned comparisons revealed that when participants made swap errors during cue-two trials they were far more likely to confuse two prioritized stimuli than they were to confuse a prioritized stimulus vs. a non-prioritized stimulus. Our results suggest that it is possible to prioritize multiple items stored in memory, with the caveat that doing so may increase the probability of confusing prioritized items.

The Costs of Ignoring High-Order Correlations in Populations of Model Neurons

2006 ◽  
Vol 18 (3) ◽  
pp. 660-682 ◽  
Author(s):  
Melchi M. Michel ◽  
Robert A. Jacobs
Keyword(s):  
Model Neuron ◽  
Joint Probability ◽  
High Order ◽  
Neural Population ◽  
Neural Responses ◽  
Significant Information ◽  
Statistical Correlations ◽  
Neural Populations ◽  
Simulation Results ◽  
Dependence Tree

Investigators debate the extent to which neural populations use pairwise and higher-order statistical dependencies among neural responses to represent information about a visual stimulus. To study this issue, three statistical decoders were used to extract the information in the responses of model neurons about the binocular disparities present in simulated pairs of left-eye and right-eye images: (1) the full joint probability decoder considered all possible statistical relations among neural responses as potentially important; (2) the dependence tree decoder also considered all possible relations as potentially important, but it approximated high-order statistical correlations using a computationally tractable procedure; and (3) the independent response decoder, which assumed that neural responses are statistically independent, meaning that all correlations should be zero and thus can be ignored. Simulation results indicate that high-order correlations among model neuron responses contain significant information about binocular disparities and that the amount of this high-order information increases rapidly as a function of neural population size. Furthermore, the results highlight the potential importance of the dependence tree decoder to neuroscientists as a powerful but still practical way of approximating high-order correlations among neural responses.

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