Effective Visual Working Memory Capacity: An Emergent Effect from the Neural Dynamics in an Attractor Network

PubMed Central

Dempere-Marco, Laura; Melcher, David P.; Deco, Gustavo

2012-01-01

The study of working memory capacity is of outmost importance in cognitive psychology as working memory is at the basis of general cognitive function. Although the working memory capacity limit has been thoroughly studied, its origin still remains a matter of strong debate. Only recently has the role of visual saliency in modulating working memory storage capacity been assessed experimentally and proved to provide valuable insights into working memory function. In the computational arena, attractor networks have successfully accounted for psychophysical and neurophysiological data in numerous working memory tasks given their ability to produce a sustained elevated firing rate during a delay period. Here we investigate the mechanisms underlying working memory capacity by means of a biophysically-realistic attractor network with spiking neurons while accounting for two recent experimental observations: 1) the presence of a visually salient item reduces the number of items that can be held in working memory, and 2) visually salient items are commonly kept in memory at the cost of not keeping as many non-salient items. Our model suggests that working memory capacity is determined by two fundamental processes: encoding of visual items into working memory and maintenance of the encoded items upon their removal from the visual display. While maintenance critically depends on the constraints that lateral inhibition imposes to the mnemonic activity, encoding is limited by the ability of the stimulated neural assemblies to reach a sufficiently high level of excitation, a process governed by the dynamics of competition and cooperation among neuronal pools. Encoding is therefore contingent upon the visual working memory task and has led us to introduce the concept of effective working memory capacity (eWMC) in contrast to the maximal upper capacity limit only reached under ideal conditions. PMID:22952608

Dopamine modulation of GABAergic function enables network stability and input selectivity for sustaining working memory in a computational model of the prefrontal cortex.

PubMed

Lew, Sergio E; Tseng, Kuei Y

2014-12-01

Dopamine modulation of GABAergic transmission in the prefrontal cortex (PFC) is thought to be critical for sustaining cognitive processes such as working memory and decision-making. Here, we developed a neurocomputational model of the PFC that includes physiological features of the facilitatory action of dopamine on fast-spiking interneurons to assess how a GABAergic dysregulation impacts on the prefrontal network stability and working memory. We found that a particular non-linear relationship between dopamine transmission and GABA function is required to enable input selectivity in the PFC for the formation and retention of working memory. Either degradation of the dopamine signal or the GABAergic function is sufficient to elicit hyperexcitability in pyramidal neurons and working memory impairments. The simulations also revealed an inverted U-shape relationship between working memory and dopamine, a function that is maintained even at high levels of GABA degradation. In fact, the working memory deficits resulting from reduced GABAergic transmission can be rescued by increasing dopamine tone and vice versa. We also examined the role of this dopamine-GABA interaction for the termination of working memory and found that the extent of GABAergic excitation needed to reset the PFC network begins to occur when the activity of fast-spiking interneurons surpasses 40 Hz. Together, these results indicate that the capability of the PFC to sustain working memory and network stability depends on a robust interplay of compensatory mechanisms between dopamine tone and the activity of local GABAergic interneurons.

Endogenous-cue prospective memory involving incremental updating of working memory: an fMRI study.

PubMed

Halahalli, Harsha N; John, John P; Lukose, Ammu; Jain, Sanjeev; Kutty, Bindu M

2015-11-01

Prospective memory paradigms are conventionally classified on the basis of event-, time-, or activity-based intention retrieval. In the vast majority of such paradigms, intention retrieval is provoked by some kind of external event. However, prospective memory retrieval cues that prompt intention retrieval in everyday life are commonly endogenous, i.e., linked to a specific imagined retrieval context. We describe herein a novel prospective memory paradigm wherein the endogenous cue is generated by incremental updating of working memory, and investigated the hemodynamic correlates of this task. Eighteen healthy adult volunteers underwent functional magnetic resonance imaging while they performed a prospective memory task where the delayed intention was triggered by an endogenous cue generated by incremental updating of working memory. Working memory and ongoing task control conditions were also administered. The 'endogenous-cue prospective memory condition' with incremental working memory updating was associated with maximum activations in the right rostral prefrontal cortex, and additional activations in the brain regions that constitute the bilateral fronto-parietal network, central and dorsal salience networks as well as cerebellum. In the working memory control condition, maximal activations were noted in the left dorsal anterior insula. Activation of the bilateral dorsal anterior insula, a component of the central salience network, was found to be unique to this 'endogenous-cue prospective memory task' in comparison to previously reported exogenous- and endogenous-cue prospective memory tasks without incremental working memory updating. Thus, the findings of the present study highlight the important role played by the dorsal anterior insula in incremental working memory updating that is integral to our endogenous-cue prospective memory task.

Structural correlates of impaired working memory in hippocampal sclerosis.

PubMed

Winston, Gavin P; Stretton, Jason; Sidhu, Meneka K; Symms, Mark R; Thompson, Pamela J; Duncan, John S

2013-07-01

Temporal lobe epilepsy (TLE) has been considered to impair long-term memory, whilst not affecting working memory, but recent evidence suggests that working memory is compromised. Functional MRI (fMRI) studies demonstrate that working memory involves a bilateral frontoparietal network the activation of which is disrupted in hippocampal sclerosis (HS). A specific role of the hippocampus to deactivate during working memory has been proposed with this mechanism faulty in patients with HS. Structural correlates of disrupted working memory in HS have not been explored. We studied 54 individuals with medically refractory TLE and unilateral HS (29 left) and 28 healthy controls. Subjects underwent 3T structural MRI, a visuospatial n-back fMRI paradigm and diffusion tensor imaging (DTI). Working memory capacity assessed by three span tasks (digit span backwards, gesture span, motor sequences) was combined with performance in the visuospatial paradigm to give a global working memory measure. Gray and white matter changes were investigated using voxel-based morphometry and voxel-based analysis of DTI, respectively. Individuals with left or right HS performed less well than healthy controls on all measures of working memory. fMRI demonstrated a bilateral frontoparietal network during the working memory task with reduced activation of the right parietal lobe in both patient groups. In left HS, gray matter loss was seen in the ipsilateral hippocampus and parietal lobe, with maintenance of the gray matter volume of the contralateral parietal lobe associated with better performance. White matter integrity within the frontoparietal network, in particular the superior longitudinal fasciculus and cingulum, and the contralateral temporal lobe, was associated with working memory performance. In right HS, gray matter loss was also seen in the ipsilateral hippocampus and parietal lobe. Working memory performance correlated with the gray matter volume of both frontal lobes and white matter integrity within the frontoparietal network and contralateral temporal lobe. Our data provide further evidence that working memory is disrupted in HS and impaired integrity of both gray and white matter is seen in functionally relevant areas. We suggest this forms the structural basis of the impairment of working memory, indicating widespread and functionally significant structural changes in patients with apparently isolated HS. Wiley Periodicals, Inc. © 2013 International League Against Epilepsy.

Structural correlates of impaired working memory in hippocampal sclerosis

PubMed Central

Winston, Gavin P; Stretton, Jason; Sidhu, Meneka K; Symms, Mark R; Thompson, Pamela J; Duncan, John S

2013-01-01

Purpose: Temporal lobe epilepsy (TLE) has been considered to impair long-term memory, whilst not affecting working memory, but recent evidence suggests that working memory is compromised. Functional MRI (fMRI) studies demonstrate that working memory involves a bilateral frontoparietal network the activation of which is disrupted in hippocampal sclerosis (HS). A specific role of the hippocampus to deactivate during working memory has been proposed with this mechanism faulty in patients with HS. Structural correlates of disrupted working memory in HS have not been explored. Methods: We studied 54 individuals with medically refractory TLE and unilateral HS (29 left) and 28 healthy controls. Subjects underwent 3T structural MRI, a visuospatial n-back fMRI paradigm and diffusion tensor imaging (DTI). Working memory capacity assessed by three span tasks (digit span backwards, gesture span, motor sequences) was combined with performance in the visuospatial paradigm to give a global working memory measure. Gray and white matter changes were investigated using voxel-based morphometry and voxel-based analysis of DTI, respectively. Key Findings: Individuals with left or right HS performed less well than healthy controls on all measures of working memory. fMRI demonstrated a bilateral frontoparietal network during the working memory task with reduced activation of the right parietal lobe in both patient groups. In left HS, gray matter loss was seen in the ipsilateral hippocampus and parietal lobe, with maintenance of the gray matter volume of the contralateral parietal lobe associated with better performance. White matter integrity within the frontoparietal network, in particular the superior longitudinal fasciculus and cingulum, and the contralateral temporal lobe, was associated with working memory performance. In right HS, gray matter loss was also seen in the ipsilateral hippocampus and parietal lobe. Working memory performance correlated with the gray matter volume of both frontal lobes and white matter integrity within the frontoparietal network and contralateral temporal lobe. Significance: Our data provide further evidence that working memory is disrupted in HS and impaired integrity of both gray and white matter is seen in functionally relevant areas. We suggest this forms the structural basis of the impairment of working memory, indicating widespread and functionally significant structural changes in patients with apparently isolated HS. PMID:23614459

Recurrent Network models of sequence generation and memory

PubMed Central

Rajan, Kanaka; Harvey, Christopher D; Tank, David W

2016-01-01

SUMMARY Sequential activation of neurons is a common feature of network activity during a variety of behaviors, including working memory and decision making. Previous network models for sequences and memory emphasized specialized architectures in which a principled mechanism is pre-wired into their connectivity. Here, we demonstrate that starting from random connectivity and modifying a small fraction of connections, a largely disordered recurrent network can produce sequences and implement working memory efficiently. We use this process, called Partial In-Network training (PINning), to model and match cellular-resolution imaging data from the posterior parietal cortex during a virtual memory-guided two-alternative forced choice task [Harvey, Coen and Tank, 2012]. Analysis of the connectivity reveals that sequences propagate by the cooperation between recurrent synaptic interactions and external inputs, rather than through feedforward or asymmetric connections. Together our results suggest that neural sequences may emerge through learning from largely unstructured network architectures. PMID:26971945

Training of Attentional Filtering, but Not of Memory Storage, Enhances Working Memory Efficiency by Strengthening the Neuronal Gatekeeper Network.

PubMed

Schmicker, Marlen; Schwefel, Melanie; Vellage, Anne-Katrin; Müller, Notger G

2016-04-01

Memory training (MT) in older adults with memory deficits often leads to frustration and, therefore, is usually not recommended. Here, we pursued an alternative approach and looked for transfer effects of 1-week attentional filter training (FT) on working memory performance and its neuronal correlates in young healthy humans. The FT effects were compared with pure MT, which lacked the necessity to filter out irrelevant information. Before and after training, all participants performed an fMRI experiment that included a combined task in which stimuli had to be both filtered based on color and stored in memory. We found that training induced processing changes by biasing either filtering or storage. FT induced larger transfer effects on the untrained cognitive function than MT. FT increased neuronal activity in frontal parts of the neuronal gatekeeper network, which is proposed to hinder irrelevant information from being unnecessarily stored in memory. MT decreased neuronal activity in the BG part of the gatekeeper network but enhanced activity in the parietal storage node. We take these findings as evidence that FT renders working memory more efficient by strengthening the BG-prefrontal gatekeeper network. MT, on the other hand, simply stimulates storage of any kind of information. These findings illustrate a tight connection between working memory and attention, and they may open up new avenues for ameliorating memory deficits in patients with cognitive impairments.

Cerebrocerebellar networks during articulatory rehearsal and verbal working memory tasks.

PubMed

Chen, S H Annabel; Desmond, John E

2005-01-15

Converging evidence has implicated the cerebellum in verbal working memory. The current fMRI study sought to further characterize cerebrocerebellar participation in this cognitive process by revealing regions of activation common to a verbal working task and an articulatory control task, as well as regions that are uniquely activated by working memory. Consistent with our model's predictions, load-dependent activations were observed in Broca's area (BA 44/6) and the superior cerebellar hemisphere (VI/CrusI) for both working memory and motoric rehearsal. In contrast, activations unique to verbal working memory were found in the inferior parietal lobule (BA 40) and the right inferior cerebellum hemisphere (VIIB). These findings provide evidence for two cerebrocerebellar networks for verbal working memory: a frontal/superior cerebellar articulatory control system and a parietal/inferior cerebellar phonological storage system.

Generalized memory associativity in a network model for the neuroses

NASA Astrophysics Data System (ADS)

Wedemann, Roseli S.; Donangelo, Raul; de Carvalho, Luís A. V.

2009-03-01

We review concepts introduced in earlier work, where a neural network mechanism describes some mental processes in neurotic pathology and psychoanalytic working-through, as associative memory functioning, according to the findings of Freud. We developed a complex network model, where modules corresponding to sensorial and symbolic memories interact, representing unconscious and conscious mental processes. The model illustrates Freud's idea that consciousness is related to symbolic and linguistic memory activity in the brain. We have introduced a generalization of the Boltzmann machine to model memory associativity. Model behavior is illustrated with simulations and some of its properties are analyzed with methods from statistical mechanics.

Task positive and default mode networks during a working memory in children with primary monosymptomatic nocturnal enuresis and healthy controls.

PubMed

Zhang, Kaihua; Ma, Jun; Lei, Du; Wang, Mengxing; Zhang, Jilei; Du, Xiaoxia

2015-10-01

Nocturnal enuresis is a common developmental disorder in children, and primary monosymptomatic nocturnal enuresis (PMNE) is the dominant subtype. This study investigated brain functional abnormalities that are specifically related to working memory in children with PMNE using function magnetic resonance imaging (fMRI) in combination with an n-back task. Twenty children with PMNE and 20 healthy children, group-matched for age and sex, participated in this experiment. Several brain regions exhibited reduced activation during the n-back task in children with PMNE, including the right precentral gyrus and the right inferior parietal lobule extending to the postcentral gyrus. Children with PMNE exhibited decreased cerebral activation in the task-positive network, increased task-related cerebral deactivation during a working memory task, and longer response times. Patients exhibited different brain response patterns to different levels of working memory and tended to compensate by greater default mode network deactivation to sustain normal working memory function. Our results suggest that children with PMNE have potential working memory dysfunction.

Gender differences in working memory networks: A BrainMap meta-analysis

PubMed Central

Hill, Ashley C.; Laird, Angela R.; Robinson, Jennifer L.

2014-01-01

Gender differences in psychological processes have been of great interest in a variety of fields. While the majority of research in this area has focused on specific differences in relation to test performance, this study sought to determine the underlying neurofunctional differences observed during working memory, a pivotal cognitive process shown to be predictive of academic achievement and intelligence. Using the BrainMap database, we performed a meta-analysis and applied activation likelihood estimation to our search set. Our results demonstrate consistent working memory networks across genders, but also provide evidence for gender-specific networks whereby females consistently activate more limbic (e.g., amygdala and hippocampus) and prefrontal structures (e.g., right inferior frontal gyrus), and males activate a distributed network inclusive of more parietal regions. These data provide a framework for future investigation using functional or effective connectivity methods to elucidate the underpinnings of gender differences in neural network recruitment during working memory tasks. PMID:25042764

Gender differences in working memory networks: a BrainMap meta-analysis.

PubMed

Hill, Ashley C; Laird, Angela R; Robinson, Jennifer L

2014-10-01

Gender differences in psychological processes have been of great interest in a variety of fields. While the majority of research in this area has focused on specific differences in relation to test performance, this study sought to determine the underlying neurofunctional differences observed during working memory, a pivotal cognitive process shown to be predictive of academic achievement and intelligence. Using the BrainMap database, we performed a meta-analysis and applied activation likelihood estimation to our search set. Our results demonstrate consistent working memory networks across genders, but also provide evidence for gender-specific networks whereby females consistently activate more limbic (e.g., amygdala and hippocampus) and prefrontal structures (e.g., right inferior frontal gyrus), and males activate a distributed network inclusive of more parietal regions. These data provide a framework for future investigations using functional or effective connectivity methods to elucidate the underpinnings of gender differences in neural network recruitment during working memory tasks. Copyright © 2014 Elsevier B.V. All rights reserved.

A Balanced Memory Network

PubMed Central

Roudi, Yasser; Latham, Peter E

2007-01-01

A fundamental problem in neuroscience is understanding how working memory—the ability to store information at intermediate timescales, like tens of seconds—is implemented in realistic neuronal networks. The most likely candidate mechanism is the attractor network, and a great deal of effort has gone toward investigating it theoretically. Yet, despite almost a quarter century of intense work, attractor networks are not fully understood. In particular, there are still two unanswered questions. First, how is it that attractor networks exhibit irregular firing, as is observed experimentally during working memory tasks? And second, how many memories can be stored under biologically realistic conditions? Here we answer both questions by studying an attractor neural network in which inhibition and excitation balance each other. Using mean-field analysis, we derive a three-variable description of attractor networks. From this description it follows that irregular firing can exist only if the number of neurons involved in a memory is large. The same mean-field analysis also shows that the number of memories that can be stored in a network scales with the number of excitatory connections, a result that has been suggested for simple models but never shown for realistic ones. Both of these predictions are verified using simulations with large networks of spiking neurons. PMID:17845070

Working Memory: Maintenance, Updating, and the Realization of Intentions

PubMed Central

Nyberg, Lars; Eriksson, Johan

2016-01-01

“Working memory” refers to a vast set of mnemonic processes and associated brain networks, relates to basic intellectual abilities, and underlies many real-world functions. Working-memory maintenance involves frontoparietal regions and distributed representational areas, and can be based on persistent activity in reentrant loops, synchronous oscillations, or changes in synaptic strength. Manipulation of content of working memory depends on the dorsofrontal cortex, and updating is realized by a frontostriatal ‘“gating” function. Goals and intentions are represented as cognitive and motivational contexts in the rostrofrontal cortex. Different working-memory networks are linked via associative reinforcement-learning mechanisms into a self-organizing system. Normal capacity variation, as well as working-memory deficits, can largely be accounted for by the effectiveness and integrity of the basal ganglia and dopaminergic neurotransmission. PMID:26637287

Intrahemispheric theta rhythm desynchronization impairs working memory.

PubMed

Alekseichuk, Ivan; Pabel, Stefanie Corinna; Antal, Andrea; Paulus, Walter

2017-01-01

There is a growing interest in large-scale connectivity as one of the crucial factors in working memory. Correlative evidence has revealed the anatomical and electrophysiological players in the working memory network, but understanding of the effective role of their connectivity remains elusive. In this double-blind, placebo-controlled study we aimed to identify the causal role of theta phase connectivity in visual-spatial working memory. The frontoparietal network was over- or de-synchronized in the anterior-posterior direction by multi-electrode, 6 Hz transcranial alternating current stimulation (tACS). A decrease in memory performance and increase in reaction time was caused by frontoparietal intrahemispheric desynchronization. According to the diffusion drift model, this originated in a lower signal-to-noise ratio, known as the drift rate index, in the memory system. The EEG analysis revealed a corresponding decrease in phase connectivity between prefrontal and parietal areas after tACS-driven desynchronization. The over-synchronization did not result in any changes in either the behavioral or electrophysiological levels in healthy participants. Taken together, we demonstrate the feasibility of manipulating multi-site large-scale networks in humans, and the disruptive effect of frontoparietal desynchronization on theta phase connectivity and visual-spatial working memory.

Attentional networks and visuospatial working memory capacity in social anxiety.

PubMed

Moriya, Jun

2018-02-01

Social anxiety is associated with attentional bias and working memory for emotional stimuli; however, the ways in which social anxiety affects cognitive functions involving non-emotional stimuli remains unclear. The present study focused on the role of attentional networks (i.e. alerting, orienting, and executive control networks) and visuospatial working memory capacity (WMC) for non-emotional stimuli in the context of social anxiety. One hundred and seventeen undergraduates completed questionnaires on social anxiety. They then performed an attentional network test and a change detection task to measure visuospatial WMC. Orienting network and visuospatial WMC were positively correlated with social anxiety. A multiple regression analysis showed significant positive associations of alerting, orienting, and visuospatial WMC with social anxiety. Alerting, orienting networks, and high visuospatial WMC for non-emotional stimuli may predict degree of social anxiety.

Levels of processing and language modality specificity in working memory.

PubMed

Rudner, Mary; Karlsson, Thomas; Gunnarsson, Johan; Rönnberg, Jerker

2013-03-01

Neural networks underpinning working memory demonstrate sign language specific components possibly related to differences in temporary storage mechanisms. A processing approach to memory systems suggests that the organisation of memory storage is related to type of memory processing as well. In the present study, we investigated for the first time semantic, phonological and orthographic processing in working memory for sign- and speech-based language. During fMRI we administered a picture-based 2-back working memory task with Semantic, Phonological, Orthographic and Baseline conditions to 11 deaf signers and 20 hearing non-signers. Behavioural data showed poorer and slower performance for both groups in Phonological and Orthographic conditions than in the Semantic condition, in line with depth-of-processing theory. An exclusive masking procedure revealed distinct sign-specific neural networks supporting working memory components at all three levels of processing. The overall pattern of sign-specific activations may reflect a relative intermodality difference in the relationship between phonology and semantics influencing working memory storage and processing. Copyright © 2012 Elsevier Ltd. All rights reserved.

Towards a Quantum Memory assisted MDI-QKD node

NASA Astrophysics Data System (ADS)

Namazi, Mehdi; Vallone, Giuseppe; Jordaan, Bertus; Goham, Connor; Shahrokhshahi, Reihaneh; Villoresi, Paolo; Figueroa, Eden

2017-04-01

The creation of large quantum network that permits the communication of quantum states and the secure distribution of cryptographic keys requires multiple operational quantum memories. In this work we present our progress towards building a prototypical quantum network that performs the memory-assisted measurement device independent QKD protocol. Currently our network combines the quantum part of the BB84 protocol with room-temperature quantum memory operation, while still maintaining relevant quantum bit error rates for single-photon level operation. We will also discuss our efforts to use a network of two room temperature quantum memories, receiving, storing and transforming randomly polarized photons in order to realize Bell state measurements. The work was supported by the US-Navy Office of Naval Research, Grant Number N00141410801, the National Science Foundation, Grant Number PHY-1404398 and the Simons Foundation, Grant Number SBF241180.

Properties of a memory network in psychology

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wedemann, Roseli S.; Donangelo, Raul; Carvalho, Luis A. V. de

We have previously described neurotic psychopathology and psychoanalytic working-through by an associative memory mechanism, based on a neural network model, where memory was modelled by a Boltzmann machine (BM). Since brain neural topology is selectively structured, we simulated known microscopic mechanisms that control synaptic properties, showing that the network self-organizes to a hierarchical, clustered structure. Here, we show some statistical mechanical properties of the complex networks which result from this self-organization. They indicate that a generalization of the BM may be necessary to model memory.

Properties of a memory network in psychology

NASA Astrophysics Data System (ADS)

Wedemann, Roseli S.; Donangelo, Raul; de Carvalho, Luís A. V.

2007-12-01

We have previously described neurotic psychopathology and psychoanalytic working-through by an associative memory mechanism, based on a neural network model, where memory was modelled by a Boltzmann machine (BM). Since brain neural topology is selectively structured, we simulated known microscopic mechanisms that control synaptic properties, showing that the network self-organizes to a hierarchical, clustered structure. Here, we show some statistical mechanical properties of the complex networks which result from this self-organization. They indicate that a generalization of the BM may be necessary to model memory.

Balanced Cortical Microcircuitry for Spatial Working Memory Based on Corrective Feedback Control

PubMed Central

2014-01-01

A hallmark of working memory is the ability to maintain graded representations of both the spatial location and amplitude of a memorized stimulus. Previous work has identified a neural correlate of spatial working memory in the persistent maintenance of spatially specific patterns of neural activity. How such activity is maintained by neocortical circuits remains unknown. Traditional models of working memory maintain analog representations of either the spatial location or the amplitude of a stimulus, but not both. Furthermore, although most previous models require local excitation and lateral inhibition to maintain spatially localized persistent activity stably, the substrate for lateral inhibitory feedback pathways is unclear. Here, we suggest an alternative model for spatial working memory that is capable of maintaining analog representations of both the spatial location and amplitude of a stimulus, and that does not rely on long-range feedback inhibition. The model consists of a functionally columnar network of recurrently connected excitatory and inhibitory neural populations. When excitation and inhibition are balanced in strength but offset in time, drifts in activity trigger spatially specific negative feedback that corrects memory decay. The resulting networks can temporally integrate inputs at any spatial location, are robust against many commonly considered perturbations in network parameters, and, when implemented in a spiking model, generate irregular neural firing characteristic of that observed experimentally during persistent activity. This work suggests balanced excitatory–inhibitory memory circuits implementing corrective negative feedback as a substrate for spatial working memory. PMID:24828633

Errors on interrupter tasks presented during spatial and verbal working memory performance are linearly linked to large-scale functional network connectivity in high temporal resolution resting state fMRI.

PubMed

Magnuson, Matthew Evan; Thompson, Garth John; Schwarb, Hillary; Pan, Wen-Ju; McKinley, Andy; Schumacher, Eric H; Keilholz, Shella Dawn

2015-12-01

The brain is organized into networks composed of spatially separated anatomical regions exhibiting coherent functional activity over time. Two of these networks (the default mode network, DMN, and the task positive network, TPN) have been implicated in the performance of a number of cognitive tasks. To directly examine the stable relationship between network connectivity and behavioral performance, high temporal resolution functional magnetic resonance imaging (fMRI) data were collected during the resting state, and behavioral data were collected from 15 subjects on different days, exploring verbal working memory, spatial working memory, and fluid intelligence. Sustained attention performance was also evaluated in a task interleaved between resting state scans. Functional connectivity within and between the DMN and TPN was related to performance on these tasks. Decreased TPN resting state connectivity was found to significantly correlate with fewer errors on an interrupter task presented during a spatial working memory paradigm and decreased DMN/TPN anti-correlation was significantly correlated with fewer errors on an interrupter task presented during a verbal working memory paradigm. A trend for increased DMN resting state connectivity to correlate to measures of fluid intelligence was also observed. These results provide additional evidence of the relationship between resting state networks and behavioral performance, and show that such results can be observed with high temporal resolution fMRI. Because cognitive scores and functional connectivity were collected on nonconsecutive days, these results highlight the stability of functional connectivity/cognitive performance coupling.

Cortical networks dynamically emerge with the interplay of slow and fast oscillations for memory of a natural scene.

PubMed

Mizuhara, Hiroaki; Sato, Naoyuki; Yamaguchi, Yoko

2015-05-01

Neural oscillations are crucial for revealing dynamic cortical networks and for serving as a possible mechanism of inter-cortical communication, especially in association with mnemonic function. The interplay of the slow and fast oscillations might dynamically coordinate the mnemonic cortical circuits to rehearse stored items during working memory retention. We recorded simultaneous EEG-fMRI during a working memory task involving a natural scene to verify whether the cortical networks emerge with the neural oscillations for memory of the natural scene. The slow EEG power was enhanced in association with the better accuracy of working memory retention, and accompanied cortical activities in the mnemonic circuits for the natural scene. Fast oscillation showed a phase-amplitude coupling to the slow oscillation, and its power was tightly coupled with the cortical activities for representing the visual images of natural scenes. The mnemonic cortical circuit with the slow neural oscillations would rehearse the distributed natural scene representations with the fast oscillation for working memory retention. The coincidence of the natural scene representations could be obtained by the slow oscillation phase to create a coherent whole of the natural scene in the working memory. Copyright © 2015 Elsevier Inc. All rights reserved.

The Effect of Binaural Beats on Visuospatial Working Memory and Cortical Connectivity.

PubMed

Beauchene, Christine; Abaid, Nicole; Moran, Rosalyn; Diana, Rachel A; Leonessa, Alexander

2016-01-01

Binaural beats utilize a phenomenon that occurs within the cortex when two different frequencies are presented separately to each ear. This procedure produces a third phantom binaural beat, whose frequency is equal to the difference of the two presented tones and which can be manipulated for non-invasive brain stimulation. The effects of binaural beats on working memory, the system in control of temporary retention and online organization of thoughts for successful goal directed behavior, have not been well studied. Furthermore, no studies have evaluated the effects of binaural beats on brain connectivity during working memory tasks. In this study, we determined the effects of different acoustic stimulation conditions on participant response accuracy and cortical network topology, as measured by EEG recordings, during a visuospatial working memory task. Three acoustic stimulation control conditions and three binaural beat stimulation conditions were used: None, Pure Tone, Classical Music, 5Hz binaural beats, 10Hz binaural beats, and 15Hz binaural beats. We found that listening to 15Hz binaural beats during a visuospatial working memory task not only increased the response accuracy, but also modified the strengths of the cortical networks during the task. The three auditory control conditions and the 5Hz and 10Hz binaural beats all decreased accuracy. Based on graphical network analyses, the cortical activity during 15Hz binaural beats produced networks characteristic of high information transfer with consistent connection strengths throughout the visuospatial working memory task.

The Effect of Binaural Beats on Visuospatial Working Memory and Cortical Connectivity

PubMed Central

Abaid, Nicole; Moran, Rosalyn; Diana, Rachel A.; Leonessa, Alexander

2016-01-01

Binaural beats utilize a phenomenon that occurs within the cortex when two different frequencies are presented separately to each ear. This procedure produces a third phantom binaural beat, whose frequency is equal to the difference of the two presented tones and which can be manipulated for non-invasive brain stimulation. The effects of binaural beats on working memory, the system in control of temporary retention and online organization of thoughts for successful goal directed behavior, have not been well studied. Furthermore, no studies have evaluated the effects of binaural beats on brain connectivity during working memory tasks. In this study, we determined the effects of different acoustic stimulation conditions on participant response accuracy and cortical network topology, as measured by EEG recordings, during a visuospatial working memory task. Three acoustic stimulation control conditions and three binaural beat stimulation conditions were used: None, Pure Tone, Classical Music, 5Hz binaural beats, 10Hz binaural beats, and 15Hz binaural beats. We found that listening to 15Hz binaural beats during a visuospatial working memory task not only increased the response accuracy, but also modified the strengths of the cortical networks during the task. The three auditory control conditions and the 5Hz and 10Hz binaural beats all decreased accuracy. Based on graphical network analyses, the cortical activity during 15Hz binaural beats produced networks characteristic of high information transfer with consistent connection strengths throughout the visuospatial working memory task. PMID:27893766

As Working Memory Grows: A Developmental Account of Neural Bases of Working Memory Capacity in 5- to 8-Year Old Children and Adults.

PubMed

Kharitonova, Maria; Winter, Warren; Sheridan, Margaret A

2015-09-01

Working memory develops slowly: Even by age 8, children are able to maintain only half the number of items that adults can remember. Neural substrates that support performance on working memory tasks also have a slow developmental trajectory and typically activate to a lesser extent in children, relative to adults. Little is known about why younger participants elicit less neural activation. This may be due to maturational differences, differences in behavioral performance, or both. Here we investigate the neural correlates of working memory capacity in children (ages 5-8) and adults using a visual working memory task with parametrically increasing loads (from one to four items) using fMRI. This task allowed us to estimate working memory capacity limit for each group. We found that both age groups increased the activation of frontoparietal networks with increasing working memory loads, until working memory capacity was reached. Because children's working memory capacity limit was half of that for adults, the plateau occurred at lower loads for children. Had a parametric increase in load not been used, this would have given an impression of less activation overall and less load-dependent activation for children relative to adults. Our findings suggest that young children and adults recruit similar frontoparietal networks at working memory loads that do not exceed capacity and highlight the need to consider behavioral performance differences when interpreting developmental differences in neural activation.

Balanced cortical microcircuitry for spatial working memory based on corrective feedback control.

PubMed

Lim, Sukbin; Goldman, Mark S

2014-05-14

A hallmark of working memory is the ability to maintain graded representations of both the spatial location and amplitude of a memorized stimulus. Previous work has identified a neural correlate of spatial working memory in the persistent maintenance of spatially specific patterns of neural activity. How such activity is maintained by neocortical circuits remains unknown. Traditional models of working memory maintain analog representations of either the spatial location or the amplitude of a stimulus, but not both. Furthermore, although most previous models require local excitation and lateral inhibition to maintain spatially localized persistent activity stably, the substrate for lateral inhibitory feedback pathways is unclear. Here, we suggest an alternative model for spatial working memory that is capable of maintaining analog representations of both the spatial location and amplitude of a stimulus, and that does not rely on long-range feedback inhibition. The model consists of a functionally columnar network of recurrently connected excitatory and inhibitory neural populations. When excitation and inhibition are balanced in strength but offset in time, drifts in activity trigger spatially specific negative feedback that corrects memory decay. The resulting networks can temporally integrate inputs at any spatial location, are robust against many commonly considered perturbations in network parameters, and, when implemented in a spiking model, generate irregular neural firing characteristic of that observed experimentally during persistent activity. This work suggests balanced excitatory-inhibitory memory circuits implementing corrective negative feedback as a substrate for spatial working memory. Copyright © 2014 the authors 0270-6474/14/346790-17$15.00/0.

The effect of binaural beats on verbal working memory and cortical connectivity.

PubMed

Beauchene, Christine; Abaid, Nicole; Moran, Rosalyn; Diana, Rachel A; Leonessa, Alexander

2017-04-01

Synchronization in activated regions of cortical networks affect the brain's frequency response, which has been associated with a wide range of states and abilities, including memory. A non-invasive method for manipulating cortical synchronization is binaural beats. Binaural beats take advantage of the brain's response to two pure tones, delivered independently to each ear, when those tones have a small frequency mismatch. The mismatch between the tones is interpreted as a beat frequency, which may act to synchronize cortical oscillations. Neural synchrony is particularly important for working memory processes, the system controlling online organization and retention of information for successful goal-directed behavior. Therefore, manipulation of synchrony via binaural beats provides a unique window into working memory and associated connectivity of cortical networks. In this study, we examined the effects of different acoustic stimulation conditions during an N-back working memory task, and we measured participant response accuracy and cortical network topology via EEG recordings. Six acoustic stimulation conditions were used: None, Pure Tone, Classical Music, 5 Hz binaural beats, 10 Hz binaural beats, and 15 Hz binaural beats. We determined that listening to 15 Hz binaural beats during an N-Back working memory task increased the individual participant's accuracy, modulated the cortical frequency response, and changed the cortical network connection strengths during the task. Only the 15 Hz binaural beats produced significant change in relative accuracy compared to the None condition. Listening to 15 Hz binaural beats during the N-back task activated salient frequency bands and produced networks characterized by higher information transfer as compared to other auditory stimulation conditions.

Working memory for braille is shaped by experience.

PubMed

Cohen, Henri; Scherzer, Peter; Viau, Robert; Voss, Patrice; Lepore, Franco

2011-03-01

Tactile working memory was found to be more developed in completely blind (congenital and acquired) than in semi-sighted subjects, indicating that experience plays a crucial role in shaping working memory. A model of working memory, adapted from the classical model proposed by Baddeley and Hitch1 and Baddeley2 is presented where the connection strengths of a highly cross-modal network are altered through experience.

The modeling and simulation of visuospatial working memory

PubMed Central

Liang, Lina; Zhang, Zhikang

2010-01-01

Camperi and Wang (Comput Neurosci 5:383–405, 1998) presented a network model for working memory that combines intrinsic cellular bistability with the recurrent network architecture of the neocortex. While Fall and Rinzel (Comput Neurosci 20:97–107, 2006) replaced this intrinsic bistability with a biological mechanism-Ca2+ release subsystem. In this study, we aim to further expand the above work. We integrate the traditional firing-rate network with Ca2+ subsystem-induced bistability, amend the synaptic weights and suggest that Ca2+ concentration only increase the efficacy of synaptic input but has nothing to do with the external input for the transient cue. We found that our network model maintained the persistent activity in response to a brief transient stimulus like that of the previous two models and the working memory performance was resistant to noise and distraction stimulus if Ca2+ subsystem was tuned to be bistable. PMID:22132045

Effective connectivity within the frontoparietal control network differentiates cognitive control and working memory.

PubMed

Harding, Ian H; Yücel, Murat; Harrison, Ben J; Pantelis, Christos; Breakspear, Michael

2015-02-01

Cognitive control and working memory rely upon a common fronto-parietal network that includes the inferior frontal junction (IFJ), dorsolateral prefrontal cortex (dlPFC), pre-supplementary motor area/dorsal anterior cingulate cortex (pSMA/dACC), and intraparietal sulcus (IPS). This network is able to flexibly adapt its function in response to changing behavioral goals, mediating a wide range of cognitive demands. Here we apply dynamic causal modeling to functional magnetic resonance imaging data to characterize task-related alterations in the strength of network interactions across distinct cognitive processes. Evidence in favor of task-related connectivity dynamics was accrued across a very large space of possible network structures. Cognitive control and working memory demands were manipulated using a factorial combination of the multi-source interference task and a verbal 2-back working memory task, respectively. Both were found to alter the sensitivity of the IFJ to perceptual information, and to increase IFJ-to-pSMA/dACC connectivity. In contrast, increased connectivity from the pSMA/dACC to the IPS, as well as from the dlPFC to the IFJ, was uniquely driven by cognitive control demands; a task-induced negative influence of the dlPFC on the pSMA/dACC was specific to working memory demands. These results reflect a system of both shared and unique context-dependent dynamics within the fronto-parietal network. Mechanisms supporting cognitive engagement, response selection, and action evaluation may be shared across cognitive domains, while dynamic updating of task and context representations within this network are potentially specific to changing demands on cognitive control. Copyright © 2014 Elsevier Inc. All rights reserved.

Load Modulation of BOLD Response and Connectivity Predicts Working Memory Performance in Younger and Older Adults

ERIC Educational Resources Information Center

Nagel, Irene E.; Preuschhof, Claudia; Li, Shu-Chen; Nyberg, Lars; Backman, Lars; Lindenberger, Ulman; Heekeren, Hauke R.

2011-01-01

Individual differences in working memory (WM) performance have rarely been related to individual differences in the functional responsivity of the WM brain network. By neglecting person-to-person variation, comparisons of network activity between younger and older adults using functional imaging techniques often confound differences in activity…

Team performance in networked supervisory control of unmanned air vehicles: effects of automation, working memory, and communication content.

PubMed

McKendrick, Ryan; Shaw, Tyler; de Visser, Ewart; Saqer, Haneen; Kidwell, Brian; Parasuraman, Raja

2014-05-01

Assess team performance within a net-worked supervisory control setting while manipulating automated decision aids and monitoring team communication and working memory ability. Networked systems such as multi-unmanned air vehicle (UAV) supervision have complex properties that make prediction of human-system performance difficult. Automated decision aid can provide valuable information to operators, individual abilities can limit or facilitate team performance, and team communication patterns can alter how effectively individuals work together. We hypothesized that reliable automation, higher working memory capacity, and increased communication rates of task-relevant information would offset performance decrements attributed to high task load. Two-person teams performed a simulated air defense task with two levels of task load and three levels of automated aid reliability. Teams communicated and received decision aid messages via chat window text messages. Task Load x Automation effects were significant across all performance measures. Reliable automation limited the decline in team performance with increasing task load. Average team spatial working memory was a stronger predictor than other measures of team working memory. Frequency of team rapport and enemy location communications positively related to team performance, and word count was negatively related to team performance. Reliable decision aiding mitigated team performance decline during increased task load during multi-UAV supervisory control. Team spatial working memory, communication of spatial information, and team rapport predicted team success. An automated decision aid can improve team performance under high task load. Assessment of spatial working memory and the communication of task-relevant information can help in operator and team selection in supervisory control systems.

Social Transmission of False Memory in Small Groups and Large Networks.

PubMed

Maswood, Raeya; Rajaram, Suparna

2018-05-21

Sharing information and memories is a key feature of social interactions, making social contexts important for developing and transmitting accurate memories and also false memories. False memory transmission can have wide-ranging effects, including shaping personal memories of individuals as well as collective memories of a network of people. This paper reviews a collection of key findings and explanations in cognitive research on the transmission of false memories in small groups. It also reviews the emerging experimental work on larger networks and collective false memories. Given the reconstructive nature of memory, the abundance of misinformation in everyday life, and the variety of social structures in which people interact, an understanding of transmission of false memories has both scientific and societal implications. © 2018 Cognitive Science Society, Inc.

Persistently active neurons in human medial frontal and medial temporal lobe support working memory

PubMed Central

Kamiński, J; Sullivan, S; Chung, JM; Ross, IB; Mamelak, AN; Rutishauser, U

2017-01-01

Persistent neural activity is a putative mechanism for the maintenance of working memories. Persistent activity relies on the activity of a distributed network of areas, but the differential contribution of each area remains unclear. We recorded single neurons in the human medial frontal cortex and the medial temporal lobe while subjects held up to three items in memory. We found persistently active neurons in both areas. Persistent activity of hippocampal and amygdala neurons was stimulus-specific, formed stable attractors, and was predictive of memory content. Medial frontal cortex persistent activity, on the other hand, was modulated by memory load and task set but was not stimulus-specific. Trial-by-trial variability in persistent activity in both areas was related to memory strength, because it predicted the speed and accuracy by which stimuli were remembered. This work reveals, in humans, direct evidence for a distributed network of persistently active neurons supporting working memory maintenance. PMID:28218914

Reactivation in Working Memory: An Attractor Network Model of Free Recall

PubMed Central

Lansner, Anders; Marklund, Petter; Sikström, Sverker; Nilsson, Lars-Göran

2013-01-01

The dynamic nature of human working memory, the general-purpose system for processing continuous input, while keeping no longer externally available information active in the background, is well captured in immediate free recall of supraspan word-lists. Free recall tasks produce several benchmark memory phenomena, like the U-shaped serial position curve, reflecting enhanced memory for early and late list items. To account for empirical data, including primacy and recency as well as contiguity effects, we propose here a neurobiologically based neural network model that unifies short- and long-term forms of memory and challenges both the standard view of working memory as persistent activity and dual-store accounts of free recall. Rapidly expressed and volatile synaptic plasticity, modulated intrinsic excitability, and spike-frequency adaptation are suggested as key cellular mechanisms underlying working memory encoding, reactivation and recall. Recent findings on the synaptic and molecular mechanisms behind early LTP and on spiking activity during delayed-match-to-sample tasks support this view. PMID:24023690

Reactivation in working memory: an attractor network model of free recall.

PubMed

Lansner, Anders; Marklund, Petter; Sikström, Sverker; Nilsson, Lars-Göran

2013-01-01

The dynamic nature of human working memory, the general-purpose system for processing continuous input, while keeping no longer externally available information active in the background, is well captured in immediate free recall of supraspan word-lists. Free recall tasks produce several benchmark memory phenomena, like the U-shaped serial position curve, reflecting enhanced memory for early and late list items. To account for empirical data, including primacy and recency as well as contiguity effects, we propose here a neurobiologically based neural network model that unifies short- and long-term forms of memory and challenges both the standard view of working memory as persistent activity and dual-store accounts of free recall. Rapidly expressed and volatile synaptic plasticity, modulated intrinsic excitability, and spike-frequency adaptation are suggested as key cellular mechanisms underlying working memory encoding, reactivation and recall. Recent findings on the synaptic and molecular mechanisms behind early LTP and on spiking activity during delayed-match-to-sample tasks support this view.

Working memory for braille is shaped by experience

PubMed Central

Scherzer, Peter; Viau, Robert; Voss, Patrice; Lepore, Franco

2011-01-01

Tactile working memory was found to be more developed in completely blind (congenital and acquired) than in semi-sighted subjects, indicating that experience plays a crucial role in shaping working memory. A model of working memory, adapted from the classical model proposed by Baddeley and Hitch1 and Baddeley2 is presented where the connection strengths of a highly cross-modal network are altered through experience. PMID:21655448

Modelling neural correlates of working memory: A coordinate-based meta-analysis

PubMed Central

Rottschy, C.; Langner, R.; Dogan, I.; Reetz, K.; Laird, A.R.; Schulz, J.B.; Fox, P.T.; Eickhoff, S.B.

2011-01-01

Working memory subsumes the capability to memorize, retrieve and utilize information for a limited period of time which is essential to many human behaviours. Moreover, impairments of working memory functions may be found in nearly all neurological and psychiatric diseases. To examine what brain regions are commonly and differently active during various working memory tasks, we performed a coordinate-based meta-analysis over 189 fMRI experiments on healthy subjects. The main effect yielded a widespread bilateral fronto-parietal network. Further meta-analyses revealed that several regions were sensitive to specific task components, e.g. Broca’s region was selectively active during verbal tasks or ventral and dorsal premotor cortex were preferentially involved in memory for object identity and location, respectively. Moreover, the lateral prefrontal cortex showed a division in a rostral and a caudal part based on differential involvement in task-set and load effects. Nevertheless, a consistent but more restricted “core” network emerged from conjunctions across analyses of specific task designs and contrasts. This “core” network appears to comprise the quintessence of regions, which are necessary during working memory tasks. It may be argued that the core regions form a distributed executive network with potentially generalized functions for focusing on competing representations in the brain. The present study demonstrates that meta-analyses are a powerful tool to integrate the data of functional imaging studies on a (broader) psychological construct, probing the consistency across various paradigms as well as the differential effects of different experimental implementations. PMID:22178808

Soft-error tolerance and energy consumption evaluation of embedded computer with magnetic random access memory in practical systems using computer simulations

NASA Astrophysics Data System (ADS)

Nebashi, Ryusuke; Sakimura, Noboru; Sugibayashi, Tadahiko

2017-08-01

We evaluated the soft-error tolerance and energy consumption of an embedded computer with magnetic random access memory (MRAM) using two computer simulators. One is a central processing unit (CPU) simulator of a typical embedded computer system. We simulated the radiation-induced single-event-upset (SEU) probability in a spin-transfer-torque MRAM cell and also the failure rate of a typical embedded computer due to its main memory SEU error. The other is a delay tolerant network (DTN) system simulator. It simulates the power dissipation of wireless sensor network nodes of the system using a revised CPU simulator and a network simulator. We demonstrated that the SEU effect on the embedded computer with 1 Gbit MRAM-based working memory is less than 1 failure in time (FIT). We also demonstrated that the energy consumption of the DTN sensor node with MRAM-based working memory can be reduced to 1/11. These results indicate that MRAM-based working memory enhances the disaster tolerance of embedded computers.

The effect of binaural beats on verbal working memory and cortical connectivity

NASA Astrophysics Data System (ADS)

Beauchene, Christine; Abaid, Nicole; Moran, Rosalyn; Diana, Rachel A.; Leonessa, Alexander

2017-04-01

Objective. Synchronization in activated regions of cortical networks affect the brain’s frequency response, which has been associated with a wide range of states and abilities, including memory. A non-invasive method for manipulating cortical synchronization is binaural beats. Binaural beats take advantage of the brain’s response to two pure tones, delivered independently to each ear, when those tones have a small frequency mismatch. The mismatch between the tones is interpreted as a beat frequency, which may act to synchronize cortical oscillations. Neural synchrony is particularly important for working memory processes, the system controlling online organization and retention of information for successful goal-directed behavior. Therefore, manipulation of synchrony via binaural beats provides a unique window into working memory and associated connectivity of cortical networks. Approach. In this study, we examined the effects of different acoustic stimulation conditions during an N-back working memory task, and we measured participant response accuracy and cortical network topology via EEG recordings. Six acoustic stimulation conditions were used: None, Pure Tone, Classical Music, 5 Hz binaural beats, 10 Hz binaural beats, and 15 Hz binaural beats. Main results. We determined that listening to 15 Hz binaural beats during an N-Back working memory task increased the individual participant’s accuracy, modulated the cortical frequency response, and changed the cortical network connection strengths during the task. Only the 15 Hz binaural beats produced significant change in relative accuracy compared to the None condition. Significance. Listening to 15 Hz binaural beats during the N-back task activated salient frequency bands and produced networks characterized by higher information transfer as compared to other auditory stimulation conditions.

Memory and betweenness preference in temporal networks induced from time series

NASA Astrophysics Data System (ADS)

Weng, Tongfeng; Zhang, Jie; Small, Michael; Zheng, Rui; Hui, Pan

2017-02-01

We construct temporal networks from time series via unfolding the temporal information into an additional topological dimension of the networks. Thus, we are able to introduce memory entropy analysis to unravel the memory effect within the considered signal. We find distinct patterns in the entropy growth rate of the aggregate network at different memory scales for time series with different dynamics ranging from white noise, 1/f noise, autoregressive process, periodic to chaotic dynamics. Interestingly, for a chaotic time series, an exponential scaling emerges in the memory entropy analysis. We demonstrate that the memory exponent can successfully characterize bifurcation phenomenon, and differentiate the human cardiac system in healthy and pathological states. Moreover, we show that the betweenness preference analysis of these temporal networks can further characterize dynamical systems and separate distinct electrocardiogram recordings. Our work explores the memory effect and betweenness preference in temporal networks constructed from time series data, providing a new perspective to understand the underlying dynamical systems.

Robust sequential working memory recall in heterogeneous cognitive networks

PubMed Central

Rabinovich, Mikhail I.; Sokolov, Yury; Kozma, Robert

2014-01-01

Psychiatric disorders are often caused by partial heterogeneous disinhibition in cognitive networks, controlling sequential and spatial working memory (SWM). Such dynamic connectivity changes suggest that the normal relationship between the neuronal components within the network deteriorates. As a result, competitive network dynamics is qualitatively altered. This dynamics defines the robust recall of the sequential information from memory and, thus, the SWM capacity. To understand pathological and non-pathological bifurcations of the sequential memory dynamics, here we investigate the model of recurrent inhibitory-excitatory networks with heterogeneous inhibition. We consider the ensemble of units with all-to-all inhibitory connections, in which the connection strengths are monotonically distributed at some interval. Based on computer experiments and studying the Lyapunov exponents, we observed and analyzed the new phenomenon—clustered sequential dynamics. The results are interpreted in the context of the winnerless competition principle. Accordingly, clustered sequential dynamics is represented in the phase space of the model by two weakly interacting quasi-attractors. One of them is similar to the sequential heteroclinic chain—the regular image of SWM, while the other is a quasi-chaotic attractor. Coexistence of these quasi-attractors means that the recall of the normal information sequence is intermittently interrupted by episodes with chaotic dynamics. We indicate potential dynamic ways for augmenting damaged working memory and other cognitive functions. PMID:25452717

Angular default mode network connectivity across working memory load.

PubMed

Vatansever, D; Manktelow, A E; Sahakian, B J; Menon, D K; Stamatakis, E A

2017-01-01

Initially identified during no-task, baseline conditions, it has now been suggested that the default mode network (DMN) engages during a variety of working memory paradigms through its flexible interactions with other large-scale brain networks. Nevertheless, its contribution to whole-brain connectivity dynamics across increasing working memory load has not been explicitly assessed. The aim of our study was to determine which DMN hubs relate to working memory task performance during an fMRI-based n-back paradigm with parametric increases in difficulty. Using a voxel-wise metric, termed the intrinsic connectivity contrast (ICC), we found that the bilateral angular gyri (core DMN hubs) displayed the greatest change in global connectivity across three levels of n-back task load. Subsequent seed-based functional connectivity analysis revealed that the angular DMN regions robustly interact with other large-scale brain networks, suggesting a potential involvement in the global integration of information. Further support for this hypothesis comes from the significant correlations we found between angular gyri connectivity and reaction times to correct responses. The implication from our study is that the DMN is actively involved during the n-back task and thus plays an important role related to working memory, with its core angular regions contributing to the changes in global brain connectivity in response to increasing environmental demands. Hum Brain Mapp 38:41-52, 2017. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Statistical modelling of networked human-automation performance using working memory capacity.

PubMed

Ahmed, Nisar; de Visser, Ewart; Shaw, Tyler; Mohamed-Ameen, Amira; Campbell, Mark; Parasuraman, Raja

2014-01-01

This study examines the challenging problem of modelling the interaction between individual attentional limitations and decision-making performance in networked human-automation system tasks. Analysis of real experimental data from a task involving networked supervision of multiple unmanned aerial vehicles by human participants shows that both task load and network message quality affect performance, but that these effects are modulated by individual differences in working memory (WM) capacity. These insights were used to assess three statistical approaches for modelling and making predictions with real experimental networked supervisory performance data: classical linear regression, non-parametric Gaussian processes and probabilistic Bayesian networks. It is shown that each of these approaches can help designers of networked human-automated systems cope with various uncertainties in order to accommodate future users by linking expected operating conditions and performance from real experimental data to observable cognitive traits like WM capacity. Practitioner Summary: Working memory (WM) capacity helps account for inter-individual variability in operator performance in networked unmanned aerial vehicle supervisory tasks. This is useful for reliable performance prediction near experimental conditions via linear models; robust statistical prediction beyond experimental conditions via Gaussian process models and probabilistic inference about unknown task conditions/WM capacities via Bayesian network models.

Optical interconnection network for parallel access to multi-rank memory in future computing systems.

PubMed

Wang, Kang; Gu, Huaxi; Yang, Yintang; Wang, Kun

2015-08-10

With the number of cores increasing, there is an emerging need for a high-bandwidth low-latency interconnection network, serving core-to-memory communication. In this paper, aiming at the goal of simultaneous access to multi-rank memory, we propose an optical interconnection network for core-to-memory communication. In the proposed network, the wavelength usage is delicately arranged so that cores can communicate with different ranks at the same time and broadcast for flow control can be achieved. A distributed memory controller architecture that works in a pipeline mode is also designed for efficient optical communication and transaction address processes. The scaling method and wavelength assignment for the proposed network are investigated. Compared with traditional electronic bus-based core-to-memory communication, the simulation results based on the PARSEC benchmark show that the bandwidth enhancement and latency reduction are apparent.

A Recurrent Network Model of Somatosensory Parametric Working Memory in the Prefrontal Cortex

PubMed Central

Miller, Paul; Brody, Carlos D; Romo, Ranulfo; Wang, Xiao-Jing

2015-01-01

A parametric working memory network stores the information of an analog stimulus in the form of persistent neural activity that is monotonically tuned to the stimulus. The family of persistent firing patterns with a continuous range of firing rates must all be realizable under exactly the same external conditions (during the delay when the transient stimulus is withdrawn). How this can be accomplished by neural mechanisms remains an unresolved question. Here we present a recurrent cortical network model of irregularly spiking neurons that was designed to simulate a somatosensory working memory experiment with behaving monkeys. Our model reproduces the observed positively and negatively monotonic persistent activity, and heterogeneous tuning curves of memory activity. We show that fine-tuning mathematically corresponds to a precise alignment of cusps in the bifurcation diagram of the network. Moreover, we show that the fine-tuned network can integrate stimulus inputs over several seconds. Assuming that such time integration occurs in neural populations downstream from a tonically persistent neural population, our model is able to account for the slow ramping-up and ramping-down behaviors of neurons observed in prefrontal cortex. PMID:14576212

Working Memory after Traumatic Brain Injury: The Neural Basis of Improved Performance with Methylphenidate.

PubMed

Manktelow, Anne E; Menon, David K; Sahakian, Barbara J; Stamatakis, Emmanuel A

2017-01-01

Traumatic brain injury (TBI) often results in cognitive impairments for patients. The aim of this proof of concept study was to establish the nature of abnormalities, in terms of activity and connectivity, in the working memory network of TBI patients and how these relate to compromised behavioral outcomes. Further, this study examined the neural correlates of working memory improvement following the administration of methylphenidate. We report behavioral, functional and structural MRI data from a group of 15 Healthy Controls (HC) and a group of 15 TBI patients, acquired during the execution of the N-back task. The patients were studied on two occasions after the administration of either placebo or 30 mg of methylphenidate. Between group tests revealed a significant difference in performance when HCs were compared to TBI patients on placebo [ F (1, 28) = 4.426, p < 0.05, η p 2 = 0.136]. This difference disappeared when the patients took methylphenidate [ F (1, 28) = 3.665, p = 0.66]. Patients in the middle range of baseline performance demonstrated the most benefit from methylphenidate. Changes in the TBI patient activation levels in the Left Cerebellum significantly and positively correlated with changes in performance ( r = 0.509, df = 13, p = 0.05). Whole-brain connectivity analysis using the Left Cerebellum as a seed revealed widespread negative interactions between the Left Cerebellum and parietal and frontal cortices as well as subcortical areas. Neither the TBI group on methylphenidate nor the HC group demonstrated any significant negative interactions. Our findings indicate that (a) TBI significantly reduces the levels of activation and connectivity strength between key areas of the working memory network and (b) Methylphenidate improves the cognitive outcomes on a working memory task. Therefore, we conclude that methylphenidate may render the working memory network in a TBI group more consistent with that of an intact working memory network.

A Tradeoff Between Accuracy and Flexibility in a Working Memory Circuit Endowed with Slow Feedback Mechanisms

PubMed Central

Pereira, Jacinto; Wang, Xiao-Jing

2015-01-01

Recent studies have shown that reverberation underlying mnemonic persistent activity must be slow, to ensure the stability of a working memory system and to give rise to long neural transients capable of accumulation of information over time. Is the slower the underlying process, the better? To address this question, we investigated 3 slow biophysical mechanisms that are activity-dependent and prominently present in the prefrontal cortex: Depolarization-induced suppression of inhibition (DSI), calcium-dependent nonspecific cationic current (ICAN), and short-term facilitation. Using a spiking network model for spatial working memory, we found that these processes enhance the memory accuracy by counteracting noise-induced drifts, heterogeneity-induced biases, and distractors. Furthermore, the incorporation of DSI and ICAN enlarges the range of network's parameter values required for working memory function. However, when a progressively slower process dominates the network, it becomes increasingly more difficult to erase a memory trace. We demonstrate this accuracy–flexibility tradeoff quantitatively and interpret it using a state-space analysis. Our results supports the scenario where N-methyl-d-aspartate receptor-dependent recurrent excitation is the workhorse for the maintenance of persistent activity, whereas slow synaptic or cellular processes contribute to the robustness of mnemonic function in a tradeoff that potentially can be adjusted according to behavioral demands. PMID:25253801

A revised limbic system model for memory, emotion and behaviour.

PubMed

Catani, Marco; Dell'acqua, Flavio; Thiebaut de Schotten, Michel

2013-09-01

Emotion, memories and behaviour emerge from the coordinated activities of regions connected by the limbic system. Here, we propose an update of the limbic model based on the seminal work of Papez, Yakovlev and MacLean. In the revised model we identify three distinct but partially overlapping networks: (i) the Hippocampal-diencephalic and parahippocampal-retrosplenial network dedicated to memory and spatial orientation; (ii) The temporo-amygdala-orbitofrontal network for the integration of visceral sensation and emotion with semantic memory and behaviour; (iii) the default-mode network involved in autobiographical memories and introspective self-directed thinking. The three networks share cortical nodes that are emerging as principal hubs in connectomic analysis. This revised network model of the limbic system reconciles recent functional imaging findings with anatomical accounts of clinical disorders commonly associated with limbic pathology. Copyright © 2013 Elsevier Ltd. All rights reserved.

Dynamic reconfiguration of frontal brain networks during executive cognition in humans

PubMed Central

Braun, Urs; Schäfer, Axel; Walter, Henrik; Erk, Susanne; Romanczuk-Seiferth, Nina; Haddad, Leila; Schweiger, Janina I.; Grimm, Oliver; Heinz, Andreas; Tost, Heike; Meyer-Lindenberg, Andreas; Bassett, Danielle S.

2015-01-01

The brain is an inherently dynamic system, and executive cognition requires dynamically reconfiguring, highly evolving networks of brain regions that interact in complex and transient communication patterns. However, a precise characterization of these reconfiguration processes during cognitive function in humans remains elusive. Here, we use a series of techniques developed in the field of “dynamic network neuroscience” to investigate the dynamics of functional brain networks in 344 healthy subjects during a working-memory challenge (the “n-back” task). In contrast to a control condition, in which dynamic changes in cortical networks were spread evenly across systems, the effortful working-memory condition was characterized by a reconfiguration of frontoparietal and frontotemporal networks. This reconfiguration, which characterizes “network flexibility,” employs transient and heterogeneous connectivity between frontal systems, which we refer to as “integration.” Frontal integration predicted neuropsychological measures requiring working memory and executive cognition, suggesting that dynamic network reconfiguration between frontal systems supports those functions. Our results characterize dynamic reconfiguration of large-scale distributed neural circuits during executive cognition in humans and have implications for understanding impaired cognitive function in disorders affecting connectivity, such as schizophrenia or dementia. PMID:26324898

The Future of Memory: Remembering, Imagining, and the Brain

PubMed Central

Schacter, Daniel L.; Addis, Donna Rose; Hassabis, Demis; Martin, Victoria C.; Spreng, R. Nathan; Szpunar, Karl K.

2013-01-01

During the past few years, there has been a dramatic increase in research examining the role of memory in imagination and future thinking. This work has revealed striking similarities between remembering the past and imagining or simulating the future, including the finding that a common brain network underlies both memory and imagination. Here we discuss a number of key points that have emerged during recent years, focusing in particular on the importance of distinguishing between temporal and non-temporal factors in analyses of memory and imagination, the nature of differences between remembering the past and imagining the future, the identification of component processes that comprise the default network supporting memory-based simulations, and the finding that this network can couple flexibly with other networks to support complex goal-directed simulations. This growing area of research has broadened our conception of memory by highlighting the many ways in which memory supports adaptive functioning. PMID:23177955

Cooperation in memory-based prisoner's dilemma game on interdependent networks

NASA Astrophysics Data System (ADS)

Luo, Chao; Zhang, Xiaolin; Liu, Hong; Shao, Rui

2016-05-01

Memory or so-called experience normally plays the important role to guide the human behaviors in real world, that is essential for rational decisions made by individuals. Hence, when the evolutionary behaviors of players with bounded rationality are investigated, it is reasonable to make an assumption that players in system are with limited memory. Besides, in order to unravel the intricate variability of complex systems in real world and make a highly integrative understanding of their dynamics, in recent years, interdependent networks as a comprehensive network structure have obtained more attention in this community. In this article, the evolution of cooperation in memory-based prisoner's dilemma game (PDG) on interdependent networks composed by two coupled square lattices is studied. Herein, all or part of players are endowed with finite memory ability, and we focus on the mutual influence of memory effect and interdependent network reciprocity on cooperation of spatial PDG. We show that the density of cooperation can be significantly promoted within an optimal region of memory length and interdependent strength. Furthermore, distinguished by whether having memory ability/external links or not, each kind of players on networks would have distinct evolutionary behaviors. Our work could be helpful to understand the emergence and maintenance of cooperation under the evolution of memory-based players on interdependent networks.

Interaction of multiple networks modulated by the working memory training based on real-time fMRI

NASA Astrophysics Data System (ADS)

Shen, Jiahui; Zhang, Gaoyan; Zhu, Chaozhe; Yao, Li; Zhao, Xiaojie

2015-03-01

Neuroimaging studies of working memory training have identified the alteration of brain activity as well as the regional interactions within the functional networks such as central executive network (CEN) and default mode network (DMN). However, how the interaction within and between these multiple networks is modulated by the training remains unclear. In this paper, we examined the interaction of three training-induced brain networks during working memory training based on real-time functional magnetic resonance imaging (rtfMRI). Thirty subjects assigned to the experimental and control group respectively participated in two times training separated by seven days. Three networks including silence network (SN), CEN and DMN were identified by the training data with the calculated function connections within each network. Structural equation modeling (SEM) approach was used to construct the directional connectivity patterns. The results showed that the causal influences from the percent signal changes of target ROI to the SN were positively changed in both two groups, as well as the causal influence from the SN to CEN was positively changed in experimental group but negatively changed in control group from the SN to DMN. Further correlation analysis of the changes in each network with the behavioral improvements showed that the changes in SN were stronger positively correlated with the behavioral improvement of letter memory task. These findings indicated that the SN was not only a switch between the target ROI and the other networks in the feedback training but also an essential factor to the behavioral improvement.

Constructing Neuronal Network Models in Massively Parallel Environments.

PubMed

Ippen, Tammo; Eppler, Jochen M; Plesser, Hans E; Diesmann, Markus

2017-01-01

Recent advances in the development of data structures to represent spiking neuron network models enable us to exploit the complete memory of petascale computers for a single brain-scale network simulation. In this work, we investigate how well we can exploit the computing power of such supercomputers for the creation of neuronal networks. Using an established benchmark, we divide the runtime of simulation code into the phase of network construction and the phase during which the dynamical state is advanced in time. We find that on multi-core compute nodes network creation scales well with process-parallel code but exhibits a prohibitively large memory consumption. Thread-parallel network creation, in contrast, exhibits speedup only up to a small number of threads but has little overhead in terms of memory. We further observe that the algorithms creating instances of model neurons and their connections scale well for networks of ten thousand neurons, but do not show the same speedup for networks of millions of neurons. Our work uncovers that the lack of scaling of thread-parallel network creation is due to inadequate memory allocation strategies and demonstrates that thread-optimized memory allocators recover excellent scaling. An analysis of the loop order used for network construction reveals that more complex tests on the locality of operations significantly improve scaling and reduce runtime by allowing construction algorithms to step through large networks more efficiently than in existing code. The combination of these techniques increases performance by an order of magnitude and harnesses the increasingly parallel compute power of the compute nodes in high-performance clusters and supercomputers.

Constructing Neuronal Network Models in Massively Parallel Environments

PubMed Central

Ippen, Tammo; Eppler, Jochen M.; Plesser, Hans E.; Diesmann, Markus

2017-01-01

Recent advances in the development of data structures to represent spiking neuron network models enable us to exploit the complete memory of petascale computers for a single brain-scale network simulation. In this work, we investigate how well we can exploit the computing power of such supercomputers for the creation of neuronal networks. Using an established benchmark, we divide the runtime of simulation code into the phase of network construction and the phase during which the dynamical state is advanced in time. We find that on multi-core compute nodes network creation scales well with process-parallel code but exhibits a prohibitively large memory consumption. Thread-parallel network creation, in contrast, exhibits speedup only up to a small number of threads but has little overhead in terms of memory. We further observe that the algorithms creating instances of model neurons and their connections scale well for networks of ten thousand neurons, but do not show the same speedup for networks of millions of neurons. Our work uncovers that the lack of scaling of thread-parallel network creation is due to inadequate memory allocation strategies and demonstrates that thread-optimized memory allocators recover excellent scaling. An analysis of the loop order used for network construction reveals that more complex tests on the locality of operations significantly improve scaling and reduce runtime by allowing construction algorithms to step through large networks more efficiently than in existing code. The combination of these techniques increases performance by an order of magnitude and harnesses the increasingly parallel compute power of the compute nodes in high-performance clusters and supercomputers. PMID:28559808

The effects of refreshing and elaboration on working memory performance, and their contributions to long-term memory formation.

PubMed

Bartsch, Lea M; Singmann, Henrik; Oberauer, Klaus

2018-03-19

Refreshing and elaboration are cognitive processes assumed to underlie verbal working-memory maintenance and assumed to support long-term memory formation. Whereas refreshing refers to the attentional focussing on representations, elaboration refers to linking representations in working memory into existing semantic networks. We measured the impact of instructed refreshing and elaboration on working and long-term memory separately, and investigated to what extent both processes are distinct in their contributions to working as well as long-term memory. Compared with a no-processing baseline, immediate memory was improved by repeating the items, but not by refreshing them. There was no credible effect of elaboration on working memory, except when items were repeated at the same time. Long-term memory benefited from elaboration, but not from refreshing the words. The results replicate the long-term memory benefit for elaboration, but do not support its beneficial role for working memory. Further, refreshing preserves immediate memory, but does not improve it beyond the level achieved without any processing.

Different Roles of Direct and Indirect Frontoparietal Pathways for Individual Working Memory Capacity.

PubMed

Ekman, Matthias; Fiebach, Christian J; Melzer, Corina; Tittgemeyer, Marc; Derrfuss, Jan

2016-03-09

The ability to temporarily store and manipulate information in working memory is a hallmark of human intelligence and differs considerably across individuals, but the structural brain correlates underlying these differences in working memory capacity (WMC) are only poorly understood. In two separate studies, diffusion MRI data and WMC scores were collected for 70 and 109 healthy individuals. Using a combination of probabilistic tractography and network analysis of the white matter tracts, we examined whether structural brain network properties were predictive of individual WMC. Converging evidence from both studies showed that lateral prefrontal cortex and posterior parietal cortex of high-capacity individuals are more densely connected compared with low-capacity individuals. Importantly, our network approach was further able to dissociate putative functional roles associated with two different pathways connecting frontal and parietal regions: a corticocortical pathway and a subcortical pathway. In Study 1, where participants were required to maintain and update working memory items, the connectivity of the direct and indirect pathway was predictive of WMC. In contrast, in Study 2, where participants were required to maintain working memory items without updating, only the connectivity of the direct pathway was predictive of individual WMC. Our results suggest an important dissociation in the circuitry connecting frontal and parietal regions, where direct frontoparietal connections might support storage and maintenance, whereas subcortically mediated connections support the flexible updating of working memory content. Copyright © 2016 the authors 0270-6474/16/362894-10$15.00/0.

Sequence memory based on coherent spin-interaction neural networks.

PubMed

Xia, Min; Wong, W K; Wang, Zhijie

2014-12-01

Sequence information processing, for instance, the sequence memory, plays an important role on many functions of brain. In the workings of the human brain, the steady-state period is alterable. However, in the existing sequence memory models using heteroassociations, the steady-state period cannot be changed in the sequence recall. In this work, a novel neural network model for sequence memory with controllable steady-state period based on coherent spininteraction is proposed. In the proposed model, neurons fire collectively in a phase-coherent manner, which lets a neuron group respond differently to different patterns and also lets different neuron groups respond differently to one pattern. The simulation results demonstrating the performance of the sequence memory are presented. By introducing a new coherent spin-interaction sequence memory model, the steady-state period can be controlled by dimension parameters and the overlap between the input pattern and the stored patterns. The sequence storage capacity is enlarged by coherent spin interaction compared with the existing sequence memory models. Furthermore, the sequence storage capacity has an exponential relationship to the dimension of the neural network.

Slot-like capacity and resource-like coding in a neural model of multiple-item working memory.

PubMed

Standage, Dominic; Pare, Martin

2018-06-27

For the past decade, research on the storage limitations of working memory has been dominated by two fundamentally different hypotheses. On the one hand, the contents of working memory may be stored in a limited number of `slots', each with a fixed resolution. On the other hand, any number of items may be stored, but with decreasing resolution. These two hypotheses have been invaluable in characterizing the computational structure of working memory, but neither provides a complete account of the available experimental data, nor speaks to the neural basis of the limitations it characterizes. To address these shortcomings, we simulated a multiple-item working memory task with a cortical network model, the cellular resolution of which allowed us to quantify the coding fidelity of memoranda as a function of memory load, as measured by the discriminability, regularity and reliability of simulated neural spiking. Our simulations account for a wealth of neural and behavioural data from human and non-human primate studies, and they demonstrate that feedback inhibition lowers both capacity and coding fidelity. Because the strength of inhibition scales with the number of items stored by the network, increasing this number progressively lowers fidelity until capacity is reached. Crucially, the model makes specific, testable predictions for neural activity on multiple-item working memory tasks.

Brain-Based Devices for Neuromorphic Computer Systems

DTIC Science & Technology

2013-07-01

and Deco, G. (2012). Effective Visual Working Memory Capacity: An Emergent Effect from the Neural Dynamics in an Attractor Network. PLoS ONE 7, e42719...models, apply them to a recognition task, and to demonstrate a working memory . In the course of this work a new analytical method for spiking data was...4 3.4 Spiking Neural Model Simulation of Working Memory ..................................... 5 3.5 A Novel Method for Analysis

Using Spatial Multiple Regression to Identify Intrinsic Connectivity Networks Involved in Working Memory Performance

PubMed Central

Gordon, Evan M.; Stollstorff, Melanie; Vaidya, Chandan J.

2012-01-01

Many researchers have noted that the functional architecture of the human brain is relatively invariant during task performance and the resting state. Indeed, intrinsic connectivity networks (ICNs) revealed by resting-state functional connectivity analyses are spatially similar to regions activated during cognitive tasks. This suggests that patterns of task-related activation in individual subjects may result from the engagement of one or more of these ICNs; however, this has not been tested. We used a novel analysis, spatial multiple regression, to test whether the patterns of activation during an N-back working memory task could be well described by a linear combination of ICNs delineated using Independent Components Analysis at rest. We found that across subjects, the cingulo-opercular Set Maintenance ICN, as well as right and left Frontoparietal Control ICNs, were reliably activated during working memory, while Default Mode and Visual ICNs were reliably deactivated. Further, involvement of Set Maintenance, Frontoparietal Control, and Dorsal Attention ICNs was sensitive to varying working memory load. Finally, the degree of left Frontoparietal Control network activation predicted response speed, while activation in both left Frontoparietal Control and Dorsal Attention networks predicted task accuracy. These results suggest that a close relationship between resting-state networks and task-evoked activation is functionally relevant for behavior, and that spatial multiple regression analysis is a suitable method for revealing that relationship. PMID:21761505

Functional Connectivity of Cognitive Brain Networks in Schizophrenia during a Working Memory Task

PubMed Central

Godwin, Douglass; Ji, Andrew; Kandala, Sridhar; Mamah, Daniel

2017-01-01

Task-based connectivity studies facilitate the understanding of how the brain functions during cognition, which is commonly impaired in schizophrenia (SZ). Our aim was to investigate functional connectivity during a working memory task in SZ. We hypothesized that the task-negative (default mode) network and the cognitive control (frontoparietal) network would show dysconnectivity. Twenty-five SZ patient and 31 healthy control scans were collected using the customized 3T Siemens Skyra MRI scanner, previously used to collect data for the Human Connectome Project. Blood oxygen level dependent signal during the 0-back and 2-back conditions were extracted within a network-based parcelation scheme. Average functional connectivity was assessed within five brain networks: frontoparietal (FPN), default mode (DMN), cingulo-opercular (CON), dorsal attention (DAN), and ventral attention network; as well as between the DMN or FPN and other networks. For within-FPN connectivity, there was a significant interaction between n-back condition and group (p = 0.015), with decreased connectivity at 0-back in SZ subjects compared to controls. FPN-to-DMN connectivity also showed a significant condition × group effect (p = 0.003), with decreased connectivity at 0-back in SZ. Across groups, connectivity within the CON and DAN were increased during the 2-back condition, while DMN connectivity with either CON or DAN were decreased during the 2-back condition. Our findings support the role of the FPN, CON, and DAN in working memory and indicate that the pattern of FPN functional connectivity differs between SZ patients and control subjects during the course of a working memory task. PMID:29312020

Functional Connectivity of Cognitive Brain Networks in Schizophrenia during a Working Memory Task.

PubMed

Godwin, Douglass; Ji, Andrew; Kandala, Sridhar; Mamah, Daniel

2017-01-01

Task-based connectivity studies facilitate the understanding of how the brain functions during cognition, which is commonly impaired in schizophrenia (SZ). Our aim was to investigate functional connectivity during a working memory task in SZ. We hypothesized that the task-negative (default mode) network and the cognitive control (frontoparietal) network would show dysconnectivity. Twenty-five SZ patient and 31 healthy control scans were collected using the customized 3T Siemens Skyra MRI scanner, previously used to collect data for the Human Connectome Project. Blood oxygen level dependent signal during the 0-back and 2-back conditions were extracted within a network-based parcelation scheme. Average functional connectivity was assessed within five brain networks: frontoparietal (FPN), default mode (DMN), cingulo-opercular (CON), dorsal attention (DAN), and ventral attention network; as well as between the DMN or FPN and other networks. For within-FPN connectivity, there was a significant interaction between n -back condition and group ( p  = 0.015), with decreased connectivity at 0-back in SZ subjects compared to controls. FPN-to-DMN connectivity also showed a significant condition × group effect ( p  = 0.003), with decreased connectivity at 0-back in SZ. Across groups, connectivity within the CON and DAN were increased during the 2-back condition, while DMN connectivity with either CON or DAN were decreased during the 2-back condition. Our findings support the role of the FPN, CON, and DAN in working memory and indicate that the pattern of FPN functional connectivity differs between SZ patients and control subjects during the course of a working memory task.

Cholinergic modulation of cognitive processing: insights drawn from computational models

PubMed Central

Newman, Ehren L.; Gupta, Kishan; Climer, Jason R.; Monaghan, Caitlin K.; Hasselmo, Michael E.

2012-01-01

Acetylcholine plays an important role in cognitive function, as shown by pharmacological manipulations that impact working memory, attention, episodic memory, and spatial memory function. Acetylcholine also shows striking modulatory influences on the cellular physiology of hippocampal and cortical neurons. Modeling of neural circuits provides a framework for understanding how the cognitive functions may arise from the influence of acetylcholine on neural and network dynamics. We review the influences of cholinergic manipulations on behavioral performance in working memory, attention, episodic memory, and spatial memory tasks, the physiological effects of acetylcholine on neural and circuit dynamics, and the computational models that provide insight into the functional relationships between the physiology and behavior. Specifically, we discuss the important role of acetylcholine in governing mechanisms of active maintenance in working memory tasks and in regulating network dynamics important for effective processing of stimuli in attention and episodic memory tasks. We also propose that theta rhythm plays a crucial role as an intermediary between the physiological influences of acetylcholine and behavior in episodic and spatial memory tasks. We conclude with a synthesis of the existing modeling work and highlight future directions that are likely to be rewarding given the existing state of the literature for both empiricists and modelers. PMID:22707936

Verbal working memory-related functional connectivity alterations in boys with attention-deficit/hyperactivity disorder and the effects of methylphenidate.

PubMed

Wu, Zhao-Min; Bralten, Janita; An, Li; Cao, Qing-Jiu; Cao, Xiao-Hua; Sun, Li; Liu, Lu; Yang, Li; Mennes, Maarten; Zang, Yu-Feng; Franke, Barbara; Hoogman, Martine; Wang, Yu-Feng

2017-08-01

Few studies have investigated verbal working memory-related functional connectivity patterns in participants with attention-deficit/hyperactivity disorder (ADHD). Thus, we aimed to compare working memory-related functional connectivity patterns in healthy children and those with ADHD, and study effects of methylphenidate (MPH). Twenty-two boys with ADHD were scanned twice, under either MPH (single dose, 10 mg) or placebo, in a randomised, cross-over, counterbalanced placebo-controlled design. Thirty healthy boys were scanned once. We used fMRI during a numerical n-back task to examine functional connectivity patterns in case-control and MPH-placebo comparisons, using independent component analysis. There was no significant difference in behavioural performance between children with ADHD, treated with MPH or placebo, and healthy controls. Compared with controls, participants with ADHD under placebo showed increased functional connectivity within fronto-parietal and auditory networks, and decreased functional connectivity within the executive control network. MPH normalized the altered functional connectivity pattern and significantly enhanced functional connectivity within the executive control network, though in non-overlapping areas. Our study contributes to the identification of the neural substrates of working memory. Single dose of MPH normalized the altered brain functional connectivity network, but had no enhancing effect on (non-impaired) behavioural performance.

Noradrenaline transporter blockade increases fronto-parietal functional connectivity relevant for working memory.

PubMed

Hernaus, Dennis; Casales Santa, Marta Ma; Offermann, Jan Stefan; Van Amelsvoort, Thérèse

2017-04-01

Experimental animal work has demonstrated that dopamine and noradrenaline play an essential role in modulating prefrontal cortex-mediated networks underlying working memory performance. Studies of functional connectivity have been instrumental in extending such notions to humans but, so far, have almost exclusively focussed on pharmacological agents with a predominant dopaminergic mechanism of action. Here, we investigate the effect of a single dose of atomoxetine 60mg, a noradrenaline transporter inhibitor, on working memory performance and associated functional connectivity during an n-back task in 19 healthy male volunteers. Atomoxetine increased functional connectivity between right anterior insula and dorsolateral prefrontal cortex, precentral gyrus, posterior parietal cortex and precuneus during the high-working memory load condition of the n-back task. Increased atomoxetine-induced insula-dorsolateral prefrontal cortex functional connectivity during this condition correlated with decreased reaction time variability and was furthermore predicted by working memory capacity. These results show for the first time that noradrenaline transporter blockade-induced increases in cortical catecholamines accentuate fronto-parietal working memory-related network integrity. The observation of significant inter-subject variability in response to atomoxetine has implications for inverted-U frameworks of dopamine and noradrenaline function, which could be useful to predict drug effects in clinical disorders with variable treatment response. Copyright © 2017 Elsevier B.V. and ECNP. All rights reserved.

On the effect of memory in one-dimensional K=4 automata on networks

NASA Astrophysics Data System (ADS)

Alonso-Sanz, Ramón; Cárdenas, Juan Pablo

2008-12-01

The effect of implementing memory in cells of one-dimensional CA, and on nodes of various types of automata on networks with increasing degrees of random rewiring is studied in this article, paying particular attention to the case of four inputs. As a rule, memory induces a moderation in the rate of changing nodes and in the damage spreading, albeit in the latter case memory turns out to be ineffective in the control of the damage as the wiring network moves away from the ordered structure that features proper one-dimensional CA. This article complements the previous work done in the two-dimensional context.

Measuring Transactiving Memory Systems Using Network Analysis

ERIC Educational Resources Information Center

King, Kylie Goodell

2017-01-01

Transactive memory systems (TMSs) describe the structures and processes that teams use to share information, work together, and accomplish shared goals. First introduced over three decades ago, TMSs have been measured in a variety of ways. This dissertation proposes the use of network analysis in measuring TMS. This is accomplished by describing…

Increased working memory-related brain activity in middle-aged women with cognitive complaints.

PubMed

Dumas, Julie A; Kutz, Amanda M; McDonald, Brenna C; Naylor, Magdalena R; Pfaff, Ashley C; Saykin, Andrew J; Newhouse, Paul A

2013-04-01

Individuals who report subjective cognitive complaints but perform normally on neuropsychological tests might be at increased risk for pathological cognitive aging. The current study examined the effects of the presence of subjective cognitive complaints on functional brain activity during a working memory task in a sample of middle-aged postmenopausal women. Twenty-three postmenopausal women aged 50-60 completed a cognitive complaint battery of questionnaires. Using 20% of items endorsed as the threshold, 12 women were categorized as cognitive complainers (CC) and 11 were noncomplainers (NC). All subjects then took part in a functional magnetic resonance imaging scanning session during which they completed a visual-verbal N-back test of working memory. Results showed no difference in working memory performance between CC and NC groups. However, the CC group showed greater activation relative to the NC group in a broad network involved in working memory including the middle frontal gyrus (Brodmann area [BA] 9 and 10), the precuneus (BA 7), and the cingulate gyrus (BA 24 and 32). The CC group recruited additional regions of the working memory network compared with the NC group as the working memory load and difficulty of the task increased. This study showed brain activation differences during working memory performance in a middle-aged group of postmenopausal women with subjective cognitive complaints but without objective cognitive deficit. These findings suggest that subjective cognitive complaints in postmenopausal women might be associated with increased cortical activity during effort-demanding cognitive tasks. Copyright © 2013 Elsevier Inc. All rights reserved.

Altered Distant Synchronization of Background Network in Mild Cognitive Impairment during an Executive Function Task.

PubMed

Wang, Pengyun; Li, Rui; Yu, Jing; Huang, Zirui; Yan, Zhixiong; Zhao, Ke; Li, Juan

2017-01-01

Few studies to date have investigated the background network in the cognitive state relying on executive function in mild cognitive impairment (MCI) patients. Using the index of degree of centrality (DC), we explored distant synchronization of background network in MCI during a hybrid delayed-match-to-sample task (DMST), which mainly relies on the working memory component of executive function. We observed significant interactions between group and cognitive state in the bilateral posterior cingulate cortex (PCC) and the ventral subregion of precuneus. For normal control (NC) group, the long distance functional connectivity (FC) of the PCC/precuneus with the other regions of the brain was higher in rest state than that working memory state. For MCI patients, however, this pattern altered. There was no significant difference between rest and working memory state. The similar pattern was observed in the other cluster located in the right angular gyrus. To examine whether abnormal DC in PCC/precuneus and angular gyrus partially resulted from the deficit of FC between these regions and the other parts in the whole brain, we conducted a seed-based correlation analysis with these regions as seeds. The results indicated that the FC between bilateral PCC/precuneus and the right inferior parietal lobule (IPL) increased from rest to working memory state for NC participants. For MCI patients, however, there was no significant change between rest and working memory state. The similar pattern was observed for the FC between right angular gyrus and right anterior insula. However, there was no difference between MCI and NC groups in global efficiency and modularity. It may indicate a lack of efficient reorganization from rest state to a working memory state in the brain network of MCI patients. The present study demonstrates the altered distant synchronization of background network in MCI during a task relying on executive function. The results provide a new perspective regarding the neural mechanisms of executive function deficits in MCI patients, and extend our understanding of brain patterns in task-evoked cognitive states.

fMRI characterization of visual working memory recognition.

PubMed

Rahm, Benjamin; Kaiser, Jochen; Unterrainer, Josef M; Simon, Juliane; Bledowski, Christoph

2014-04-15

Encoding and maintenance of information in visual working memory have been extensively studied, highlighting the crucial and capacity-limiting role of fronto-parietal regions. In contrast, the neural basis of recognition in visual working memory has remained largely unspecified. Cognitive models suggest that recognition relies on a matching process that compares sensory information with the mental representations held in memory. To characterize the neural basis of recognition we varied both the need for recognition and the degree of similarity between the probe item and the memory contents, while independently manipulating memory load to produce load-related fronto-parietal activations. fMRI revealed a fractionation of working memory functions across four distributed networks. First, fronto-parietal regions were activated independent of the need for recognition. Second, anterior parts of load-related parietal regions contributed to recognition but their activations were independent of the difficulty of matching in terms of sample-probe similarity. These results argue against a key role of the fronto-parietal attention network in recognition. Rather the third group of regions including bilateral temporo-parietal junction, posterior cingulate cortex and superior frontal sulcus reflected demands on matching both in terms of sample-probe-similarity and the number of items to be compared. Also, fourth, bilateral motor regions and right superior parietal cortex showed higher activation when matching provided clear evidence for a decision. Together, the segregation between the well-known fronto-parietal activations attributed to attentional operations in working memory from those regions involved in matching supports the theoretical view of separable attentional and mnemonic contributions to working memory. Yet, the close theoretical and empirical correspondence to perceptual decision making may call for an explicit consideration of decision making mechanisms in conceptions of working memory. Copyright © 2013 Elsevier Inc. All rights reserved.

Working memory network plasticity after anterior temporal lobe resection: a longitudinal functional magnetic resonance imaging study

PubMed Central

Stretton, Jason; Sidhu, Meneka K.; Winston, Gavin P.; Bartlett, Philippa; McEvoy, Andrew W.; Symms, Mark R.; Koepp, Matthias J.; Thompson, Pamela J.

2014-01-01

Working memory is a crucial cognitive function that is disrupted in temporal lobe epilepsy. It is unclear whether this impairment is a consequence of temporal lobe involvement in working memory processes or due to seizure spread to extratemporal eloquent cortex. Anterior temporal lobe resection controls seizures in 50–80% of patients with drug-resistant temporal lobe epilepsy and the effect of surgery on working memory are poorly understood both at a behavioural and neural level. We investigated the impact of temporal lobe resection on the efficiency and functional anatomy of working memory networks. We studied 33 patients with unilateral medial temporal lobe epilepsy (16 left) before, 3 and 12 months after anterior temporal lobe resection. Fifteen healthy control subjects were also assessed in parallel. All subjects had neuropsychological testing and performed a visuospatial working memory functional magnetic resonance imaging paradigm on these three separate occasions. Changes in activation and deactivation patterns were modelled individually and compared between groups. Changes in task performance were included as regressors of interest to assess the efficiency of changes in the networks. Left and right temporal lobe epilepsy patients were impaired on preoperative measures of working memory compared to controls. Working memory performance did not decline following left or right temporal lobe resection, but improved at 3 and 12 months following left and, to a lesser extent, following right anterior temporal lobe resection. After left anterior temporal lobe resection, improved performance correlated with greater deactivation of the left hippocampal remnant and the contralateral right hippocampus. There was a failure of increased deactivation of the left hippocampal remnant at 3 months after left temporal lobe resection compared to control subjects, which had normalized 12 months after surgery. Following right anterior temporal lobe resection there was a progressive increase of activation in the right superior parietal lobe at 3 and 12 months after surgery. There was greater deactivation of the right hippocampal remnant compared to controls between 3 and 12 months after right anterior temporal lobe resection that was associated with lesser improvement in task performance. Working memory improved after anterior temporal lobe resection, particularly following left-sided resections. Postoperative working memory was reliant on the functional capacity of the hippocampal remnant and, following left resections, the functional reserve of the right hippocampus. These data suggest that working memory following temporal lobe resection is dependent on the engagement of the posterior medial temporal lobes and eloquent cortex. PMID:24691395

Selective updating of working memory content modulates meso-cortico-striatal activity.

PubMed

Murty, Vishnu P; Sambataro, Fabio; Radulescu, Eugenia; Altamura, Mario; Iudicello, Jennifer; Zoltick, Bradley; Weinberger, Daniel R; Goldberg, Terry E; Mattay, Venkata S

2011-08-01

Accumulating evidence from non-human primates and computational modeling suggests that dopaminergic signals arising from the midbrain (substantia nigra/ventral tegmental area) mediate striatal gating of the prefrontal cortex during the selective updating of working memory. Using event-related functional magnetic resonance imaging, we explored the neural mechanisms underlying the selective updating of information stored in working memory. Participants were scanned during a novel working memory task that parses the neurophysiology underlying working memory maintenance, overwriting, and selective updating. Analyses revealed a functionally coupled network consisting of a midbrain region encompassing the substantia nigra/ventral tegmental area, caudate, and dorsolateral prefrontal cortex that was selectively engaged during working memory updating compared to the overwriting and maintenance of working memory content. Further analysis revealed differential midbrain-dorsolateral prefrontal interactions during selective updating between low-performing and high-performing individuals. These findings highlight the role of this meso-cortico-striatal circuitry during the selective updating of working memory in humans, which complements previous research in behavioral neuroscience and computational modeling. Published by Elsevier Inc.

Effects of Stress and Task Difficulty on Working Memory and Cortical Networking.

PubMed

Kim, Yujin; Woo, Jihwan; Woo, Minjung

2017-12-01

This study investigated interactive effects of stress and task difficulty on working memory and cortico-cortical communication during memory encoding. Thirty-eight adolescent participants (mean age of 15.7 ± 1.5 years) completed easy and hard working memory tasks under low- and high-stress conditions. We analyzed the accuracy and reaction time (RT) of working memory performance and inter- and intrahemispheric electroencephalogram coherences during memory encoding. Working memory accuracy was higher, and RT shorter, in the easy versus the hard task. RT was shorter under the high-stress (TENS) versus low-stress (no-TENS) condition, while there was no difference in memory accuracy between the two stress conditions. For electroencephalogram coherence, we found higher interhemispheric coherence in all bands but only at frontal electrode sites in the easy versus the hard task. On the other hand, intrahemispheric coherence was higher in the left hemisphere in the easy (versus hard task) and higher in the right hemisphere (with one exception) in the hard (versus easy task). Inter- and intracoherences were higher in the low- versus high-stress condition. Significant interactions between task difficulty and stress condition were observed in coherences of the beta frequency band. The difference in coherence between low- and high-stress conditions was greater in the hard compared with the easy task, with lower coherence under the high-stress condition relative to the low-stress condition. Stress seemed to cause a decrease in cortical network communications between memory-relevant cortical areas as task difficulty increased.

A Tradeoff Between Accuracy and Flexibility in a Working Memory Circuit Endowed with Slow Feedback Mechanisms.

PubMed

Pereira, Jacinto; Wang, Xiao-Jing

2015-10-01

Recent studies have shown that reverberation underlying mnemonic persistent activity must be slow, to ensure the stability of a working memory system and to give rise to long neural transients capable of accumulation of information over time. Is the slower the underlying process, the better? To address this question, we investigated 3 slow biophysical mechanisms that are activity-dependent and prominently present in the prefrontal cortex: Depolarization-induced suppression of inhibition (DSI), calcium-dependent nonspecific cationic current (ICAN), and short-term facilitation. Using a spiking network model for spatial working memory, we found that these processes enhance the memory accuracy by counteracting noise-induced drifts, heterogeneity-induced biases, and distractors. Furthermore, the incorporation of DSI and ICAN enlarges the range of network's parameter values required for working memory function. However, when a progressively slower process dominates the network, it becomes increasingly more difficult to erase a memory trace. We demonstrate this accuracy-flexibility tradeoff quantitatively and interpret it using a state-space analysis. Our results supports the scenario where N-methyl-d-aspartate receptor-dependent recurrent excitation is the workhorse for the maintenance of persistent activity, whereas slow synaptic or cellular processes contribute to the robustness of mnemonic function in a tradeoff that potentially can be adjusted according to behavioral demands. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Training Working Memory in Childhood Enhances Coupling between Frontoparietal Control Network and Task-Related Regions.

PubMed

Barnes, Jessica J; Nobre, Anna Christina; Woolrich, Mark W; Baker, Kate; Astle, Duncan E

2016-08-24

Working memory is a capacity upon which many everyday tasks depend and which constrains a child's educational progress. We show that a child's working memory can be significantly enhanced by intensive computer-based training, relative to a placebo control intervention, in terms of both standardized assessments of working memory and performance on a working memory task performed in a magnetoencephalography scanner. Neurophysiologically, we identified significantly increased cross-frequency phase amplitude coupling in children who completed training. Following training, the coupling between the upper alpha rhythm (at 16 Hz), recorded in superior frontal and parietal cortex, became significantly coupled with high gamma activity (at ∼90 Hz) in inferior temporal cortex. This altered neural network activity associated with cognitive skill enhancement is consistent with a framework in which slower cortical rhythms enable the dynamic regulation of higher-frequency oscillatory activity related to task-related cognitive processes. Whether we can enhance cognitive abilities through intensive training is one of the most controversial topics of cognitive psychology in recent years. This is particularly controversial in childhood, where aspects of cognition, such as working memory, are closely related to school success and are implicated in numerous developmental disorders. We provide the first neurophysiological account of how working memory training may enhance ability in childhood, using a brain recording technique called magnetoencephalography. We borrowed an analysis approach previously used with intracranial recordings in adults, or more typically in other animal models, called "phase amplitude coupling." Copyright © 2016 Barnes et al.

Training Working Memory in Childhood Enhances Coupling between Frontoparietal Control Network and Task-Related Regions

PubMed Central

Barnes, Jessica J.; Nobre, Anna Christina; Woolrich, Mark W.; Baker, Kate

2016-01-01

Working memory is a capacity upon which many everyday tasks depend and which constrains a child's educational progress. We show that a child's working memory can be significantly enhanced by intensive computer-based training, relative to a placebo control intervention, in terms of both standardized assessments of working memory and performance on a working memory task performed in a magnetoencephalography scanner. Neurophysiologically, we identified significantly increased cross-frequency phase amplitude coupling in children who completed training. Following training, the coupling between the upper alpha rhythm (at 16 Hz), recorded in superior frontal and parietal cortex, became significantly coupled with high gamma activity (at ∼90 Hz) in inferior temporal cortex. This altered neural network activity associated with cognitive skill enhancement is consistent with a framework in which slower cortical rhythms enable the dynamic regulation of higher-frequency oscillatory activity related to task-related cognitive processes. SIGNIFICANCE STATEMENT Whether we can enhance cognitive abilities through intensive training is one of the most controversial topics of cognitive psychology in recent years. This is particularly controversial in childhood, where aspects of cognition, such as working memory, are closely related to school success and are implicated in numerous developmental disorders. We provide the first neurophysiological account of how working memory training may enhance ability in childhood, using a brain recording technique called magnetoencephalography. We borrowed an analysis approach previously used with intracranial recordings in adults, or more typically in other animal models, called “phase amplitude coupling.” PMID:27559180

Connectomic markers of disease expression, genetic risk and resilience in bipolar disorder

PubMed Central

Dima, D; Roberts, R E; Frangou, S

2016-01-01

Bipolar disorder (BD) is characterized by emotional dysregulation and cognitive deficits associated with abnormal connectivity between subcortical—primarily emotional processing regions—and prefrontal regulatory areas. Given the significant contribution of genetic factors to BD, studies in unaffected first-degree relatives can identify neural mechanisms of genetic risk but also resilience, thus paving the way for preventive interventions. Dynamic causal modeling (DCM) and random-effects Bayesian model selection were used to define and assess connectomic phenotypes linked to facial affect processing and working memory in a demographically matched sample of first-degree relatives carefully selected for resilience (n=25), euthymic patients with BD (n=41) and unrelated healthy controls (n=46). During facial affect processing, patients and relatives showed similarly increased frontolimbic connectivity; resilient relatives, however, evidenced additional adaptive hyperconnectivity within the ventral visual stream. During working memory processing, patients displayed widespread hypoconnectivity within the corresponding network. In contrast, working memory network connectivity in resilient relatives was comparable to that of controls. Our results indicate that frontolimbic dysfunction during affect processing could represent a marker of genetic risk to BD, and diffuse hypoconnectivity within the working memory network a marker of disease expression. The association of hyperconnectivity within the affect-processing network with resilience to BD suggests adaptive plasticity that allows for compensatory changes and encourages further investigation of this phenotype in genetic and early intervention studies. PMID:26731443

Connectomic markers of disease expression, genetic risk and resilience in bipolar disorder.

PubMed

Dima, D; Roberts, R E; Frangou, S

2016-01-05

Bipolar disorder (BD) is characterized by emotional dysregulation and cognitive deficits associated with abnormal connectivity between subcortical-primarily emotional processing regions-and prefrontal regulatory areas. Given the significant contribution of genetic factors to BD, studies in unaffected first-degree relatives can identify neural mechanisms of genetic risk but also resilience, thus paving the way for preventive interventions. Dynamic causal modeling (DCM) and random-effects Bayesian model selection were used to define and assess connectomic phenotypes linked to facial affect processing and working memory in a demographically matched sample of first-degree relatives carefully selected for resilience (n=25), euthymic patients with BD (n=41) and unrelated healthy controls (n=46). During facial affect processing, patients and relatives showed similarly increased frontolimbic connectivity; resilient relatives, however, evidenced additional adaptive hyperconnectivity within the ventral visual stream. During working memory processing, patients displayed widespread hypoconnectivity within the corresponding network. In contrast, working memory network connectivity in resilient relatives was comparable to that of controls. Our results indicate that frontolimbic dysfunction during affect processing could represent a marker of genetic risk to BD, and diffuse hypoconnectivity within the working memory network a marker of disease expression. The association of hyperconnectivity within the affect-processing network with resilience to BD suggests adaptive plasticity that allows for compensatory changes and encourages further investigation of this phenotype in genetic and early intervention studies.

Effects of levodopa on corticostriatal circuits supporting working memory in Parkinson's disease.

PubMed

Simioni, Alison C; Dagher, Alain; Fellows, Lesley K

2017-08-01

Working memory dysfunction is common in Parkinson's disease, even in its early stages, but its neural basis is debated. Working memory performance likely reflects a balance between corticostriatal dysfunction and compensatory mechanisms. We tested this hypothesis by examining working memory performance with a letter n-back task in 19 patients with mild-moderate Parkinson's disease and 20 demographically matched healthy controls. Parkinson's disease patients were tested after an overnight washout of their usual dopamine replacement therapy, and again after a standard dose of levodopa. FMRI was used to assess task-related activation and resting state functional connectivity; changes in BOLD signal were related to performance to disentangle pathological and compensatory processes. Parkinson's disease patients off dopamine replacement therapy displayed significantly reduced spatial extent of task-related activation in left prefrontal and bilateral parietal cortex, and poorer working memory performance, compared to controls. Amongst the Parkinson's disease patients off dopamine replacement therapy, relatively better performance was associated with greater activation of right dorsolateral prefrontal cortex compared to controls, consistent with compensatory right hemisphere recruitment. Administration of levodopa remediated the working memory deficit in the Parkinson's disease group, and resulted in a different pattern of performance-correlated activity, with a shift to greater left ventrolateral prefrontal cortex activation in patients on, compared to off dopamine replacement therapy. Levodopa also significantly increased resting-state functional connectivity between caudate and right parietal cortex (within the right fronto-parietal attentional network). The strength of this connectivity contributed to better performance in patients and controls, suggesting a general compensatory mechanism. These findings argue that Parkinson's disease patients can recruit additional neural resources, here, the right fronto-parietal network, to optimize working memory performance despite impaired corticostriatal function. Levodopa seems to both boost engagement of a task-specific prefrontal region, and strengthen a putative compensatory caudate-cortical network to support this executive function. Copyright © 2017 Elsevier Ltd. All rights reserved.

Granger causality analysis reveals distinct spatio-temporal connectivity patterns in motor and perceptual visuo-spatial working memory.

PubMed

Protopapa, Foteini; Siettos, Constantinos I; Evdokimidis, Ioannis; Smyrnis, Nikolaos

2014-01-01

We employed spectral Granger causality analysis on a full set of 56 electroencephalographic recordings acquired during the execution of either a 2D movement pointing or a perceptual (yes/no) change detection task with memory and non-memory conditions. On the basis of network characteristics across frequency bands, we provide evidence for the full dissociation of the corresponding cognitive processes. Movement-memory trial types exhibited higher degree nodes during the first 2 s of the delay period, mainly at central, left frontal and right-parietal areas. Change detection-memory trial types resulted in a three-peak temporal pattern of the total degree with higher degree nodes emerging mainly at central, right frontal, and occipital areas. Functional connectivity networks resulting from non-memory trial types were characterized by more sparse structures for both tasks. The movement-memory trial types encompassed an apparent coarse flow from frontal to parietal areas while the opposite flow from occipital, parietal to central and frontal areas was evident for the change detection-memory trial types. The differences among tasks and conditions were more profound in α (8-12 Hz) and β (12-30 Hz) and less in γ (30-45 Hz) band. Our results favor the hypothesis which considers spatial working memory as a by-product of specific mental processes that engages common brain areas under different network organizations.

Neural substrate of initiation of cross-modal working memory retrieval.

PubMed

Zhang, Yangyang; Hu, Yang; Guan, Shuchen; Hong, Xiaolong; Wang, Zhaoxin; Li, Xianchun

2014-01-01

Cross-modal working memory requires integrating stimuli from different modalities and it is associated with co-activation of distributed networks in the brain. However, how brain initiates cross-modal working memory retrieval remains not clear yet. In the present study, we developed a cued matching task, in which the necessity for cross-modal/unimodal memory retrieval and its initiation time were controlled by a task cue appeared in the delay period. Using functional magnetic resonance imaging (fMRI), significantly larger brain activations were observed in the left lateral prefrontal cortex (l-LPFC), left superior parietal lobe (l-SPL), and thalamus in the cued cross-modal matching trials (CCMT) compared to those in the cued unimodal matching trials (CUMT). However, no significant differences in the brain activations prior to task cue were observed for sensory stimulation in the l-LPFC and l-SPL areas. Although thalamus displayed differential responses to the sensory stimulation between two conditions, the differential responses were not the same with responses to the task cues. These results revealed that the frontoparietal-thalamus network participated in the initiation of cross-modal working memory retrieval. Secondly, the l-SPL and thalamus showed differential activations between maintenance and working memory retrieval, which might be associated with the enhanced demand for cognitive resources.

Real-time learning of predictive recognition categories that chunk sequences of items stored in working memory

PubMed Central

Kazerounian, Sohrob; Grossberg, Stephen

2014-01-01

How are sequences of events that are temporarily stored in a cognitive working memory unitized, or chunked, through learning? Such sequential learning is needed by the brain in order to enable language, spatial understanding, and motor skills to develop. In particular, how does the brain learn categories, or list chunks, that become selectively tuned to different temporal sequences of items in lists of variable length as they are stored in working memory, and how does this learning process occur in real time? The present article introduces a neural model that simulates learning of such list chunks. In this model, sequences of items are temporarily stored in an Item-and-Order, or competitive queuing, working memory before learning categorizes them using a categorization network, called a Masking Field, which is a self-similar, multiple-scale, recurrent on-center off-surround network that can weigh the evidence for variable-length sequences of items as they are stored in the working memory through time. A Masking Field hereby activates the learned list chunks that represent the most predictive item groupings at any time, while suppressing less predictive chunks. In a network with a given number of input items, all possible ordered sets of these item sequences, up to a fixed length, can be learned with unsupervised or supervised learning. The self-similar multiple-scale properties of Masking Fields interacting with an Item-and-Order working memory provide a natural explanation of George Miller's Magical Number Seven and Nelson Cowan's Magical Number Four. The article explains why linguistic, spatial, and action event sequences may all be stored by Item-and-Order working memories that obey similar design principles, and thus how the current results may apply across modalities. Item-and-Order properties may readily be extended to Item-Order-Rank working memories in which the same item can be stored in multiple list positions, or ranks, as in the list ABADBD. Comparisons with other models, including TRACE, MERGE, and TISK, are made. PMID:25339918

Cortical connectivity and memory performance in cognitive decline: A study via graph theory from EEG data.

PubMed

Vecchio, F; Miraglia, F; Quaranta, D; Granata, G; Romanello, R; Marra, C; Bramanti, P; Rossini, P M

2016-03-01

Functional brain abnormalities including memory loss are found to be associated with pathological changes in connectivity and network neural structures. Alzheimer's disease (AD) interferes with memory formation from the molecular level, to synaptic functions and neural networks organization. Here, we determined whether brain connectivity of resting-state networks correlate with memory in patients affected by AD and in subjects with mild cognitive impairment (MCI). One hundred and forty-four subjects were recruited: 70 AD (MMSE Mini Mental State Evaluation 21.4), 50 MCI (MMSE 25.2) and 24 healthy subjects (MMSE 29.8). Undirected and weighted cortical brain network was built to evaluate graph core measures to obtain Small World parameters. eLORETA lagged linear connectivity as extracted by electroencephalogram (EEG) signals was used to weight the network. A high statistical correlation between Small World and memory performance was found. Namely, higher Small World characteristic in EEG gamma frequency band during the resting state, better performance in short-term memory as evaluated by the digit span tests. Such Small World pattern might represent a biomarker of working memory impairment in older people both in physiological and pathological conditions. Copyright © 2015 IBRO. Published by Elsevier Ltd. All rights reserved.

Artificial neural networks as quantum associative memory

NASA Astrophysics Data System (ADS)

Hamilton, Kathleen; Schrock, Jonathan; Imam, Neena; Humble, Travis

We present results related to the recall accuracy and capacity of Hopfield networks implemented on commercially available quantum annealers. The use of Hopfield networks and artificial neural networks as content-addressable memories offer robust storage and retrieval of classical information, however, implementation of these models using currently available quantum annealers faces several challenges: the limits of precision when setting synaptic weights, the effects of spurious spin-glass states and minor embedding of densely connected graphs into fixed-connectivity hardware. We consider neural networks which are less than fully-connected, and also consider neural networks which contain multiple sparsely connected clusters. We discuss the effect of weak edge dilution on the accuracy of memory recall, and discuss how the multiple clique structure affects the storage capacity. Our work focuses on storage of patterns which can be embedded into physical hardware containing n < 1000 qubits. This work was supported by the United States Department of Defense and used resources of the Computational Research and Development Programs as Oak Ridge National Laboratory under Contract No. DE-AC0500OR22725 with the U. S. Department of Energy.

Working memory capacity and the functional connectome - insights from resting-state fMRI and voxelwise centrality mapping.

PubMed

Markett, Sebastian; Reuter, Martin; Heeren, Behrend; Lachmann, Bernd; Weber, Bernd; Montag, Christian

2018-02-01

The functional connectome represents a comprehensive network map of functional connectivity throughout the human brain. To date, the relationship between the organization of functional connectivity and cognitive performance measures is still poorly understood. In the present study we use resting-state functional magnetic resonance imaging (fMRI) data to explore the link between the functional connectome and working memory capacity in an individual differences design. Working memory capacity, which refers to the maximum amount of context information that an individual can retain in the absence of external stimulation, was assessed outside the MRI scanner and estimated based on behavioral data from a change detection task. Resting-state time series were analyzed by means of voxelwise degree and eigenvector centrality mapping, which are data-driven network analytic approaches for the characterization of functional connectivity. We found working memory capacity to be inversely correlated with both centrality in the right intraparietal sulcus. Exploratory analyses revealed that this relationship was putatively driven by an increase in negative connectivity strength of the structure. This resting-state connectivity finding fits previous task based activation studies that have shown that this area responds to manipulations of working memory load.

Efficiency at rest: magnetoencephalographic resting-state connectivity and individual differences in verbal working memory.

PubMed

del Río, David; Cuesta, Pablo; Bajo, Ricardo; García-Pacios, Javier; López-Higes, Ramón; del-Pozo, Francisco; Maestú, Fernando

2012-11-01

Inter-individual differences in cognitive performance are based on an efficient use of task-related brain resources. However, little is known yet on how these differences might be reflected on resting-state brain networks. Here we used Magnetoencephalography resting-state recordings to assess the relationship between a behavioral measurement of verbal working memory and functional connectivity as measured through Mutual Information. We studied theta (4-8 Hz), low alpha (8-10 Hz), high alpha (10-13 Hz), low beta (13-18 Hz) and high beta (18-30 Hz) frequency bands. A higher verbal working memory capacity was associated with a lower mutual information in the low alpha band, prominently among right-anterior and left-lateral sensors. The results suggest that an efficient brain organization in the domain of verbal working memory might be related to a lower resting-state functional connectivity across large-scale brain networks possibly involving right prefrontal and left perisylvian areas. Copyright © 2012 Elsevier B.V. All rights reserved.

Load matters: neural correlates of verbal working memory in children with autism spectrum disorder.

PubMed

Vogan, Vanessa M; Francis, Kaitlyn E; Morgan, Benjamin R; Smith, Mary Lou; Taylor, Margot J

2018-06-01

Autism spectrum disorder (ASD) is a pervasive neurodevelopmental disorder characterised by diminished social reciprocity and communication skills and the presence of stereotyped and restricted behaviours. Executive functioning deficits, such as working memory, are associated with core ASD symptoms. Working memory allows for temporary storage and manipulation of information and relies heavily on frontal-parietal networks of the brain. There are few reports on the neural correlates of working memory in youth with ASD. The current study identified the neural systems underlying verbal working memory capacity in youth with and without ASD using functional magnetic resonance imaging (fMRI). Fifty-seven youth, 27 with ASD and 30 sex- and age-matched typically developing (TD) controls (9-16 years), completed a one-back letter matching task (LMT) with four levels of difficulty (i.e. cognitive load) while fMRI data were recorded. Linear trend analyses were conducted to examine brain regions that were recruited as a function of increasing cognitive load. We found similar behavioural performance on the LMT in terms of reaction times, but in the two higher load conditions, the ASD youth had lower accuracy than the TD group. Neural patterns of activations differed significantly between TD and ASD groups. In TD youth, areas classically used for working memory, including the lateral and medial frontal, as well as superior parietal brain regions, increased in activation with increasing task difficulty, while areas related to the default mode network (DMN) showed decreasing activation (i.e., deactivation). The youth with ASD did not appear to use this opposing cognitive processing system; they showed little recruitment of frontal and parietal regions across the load but did show similar modulation of the DMN. In a working memory task, where the load was manipulated without changing executive demands, TD youth showed increasing recruitment with increasing load of the classic fronto-parietal brain areas and decreasing involvement in default mode regions. In contrast, although they modulated the default mode network, youth with ASD did not show the modulation of increasing brain activation with increasing load, suggesting that they may be unable to manage increasing verbal information. Impaired verbal working memory in ASD would interfere with the youths' success academically and socially. Thus, determining the nature of atypical neural processing could help establish or monitor working memory interventions for ASD.

Reorganization of functional brain networks mediates the improvement of cognitive performance following real-time neurofeedback training of working memory.

PubMed

Zhang, Gaoyan; Yao, Li; Shen, Jiahui; Yang, Yihong; Zhao, Xiaojie

2015-05-01

Working memory (WM) is essential for individuals' cognitive functions. Neuroimaging studies indicated that WM fundamentally relied on a frontoparietal working memory network (WMN) and a cinguloparietal default mode network (DMN). Behavioral training studies demonstrated that the two networks can be modulated by WM training. Different from the behavioral training, our recent study used a real-time functional MRI (rtfMRI)-based neurofeedback method to conduct WM training, demonstrating that WM performance can be significantly improved after successfully upregulating the activity of the target region of interest (ROI) in the left dorsolateral prefrontal cortex (Zhang et al., [2013]: PloS One 8:e73735); however, the neural substrate of rtfMRI-based WM training remains unclear. In this work, we assessed the intranetwork and internetwork connectivity changes of WMN and DMN during the training, and their correlations with the change of brain activity in the target ROI as well as with the improvement of post-training behavior. Our analysis revealed an "ROI-network-behavior" correlation relationship underlying the rtfMRI training. Further mediation analysis indicated that the reorganization of functional brain networks mediated the effect of self-regulation of the target brain activity on the improvement of cognitive performance following the neurofeedback training. The results of this study enhance our understanding of the neural basis of real-time neurofeedback and suggest a new direction to improve WM performance by regulating the functional connectivity in the WM related networks. © 2014 Wiley Periodicals, Inc.

Very Early Brain Damage Leads to Remodeling of the Working Memory System in Adulthood: A Combined fMRI/Tractography Study

PubMed Central

Karolis, Vyacheslav; Caldinelli, Chiara; Brittain, Philip J.; Kroll, Jasmin; Rodríguez-Toscano, Elisa; Tesse, Marcello; Colquhoun, Matthew; Howes, Oliver; Dell'Acqua, Flavio; Thiebaut de Schotten, Michel; Murray, Robin M.; Williams, Steven C.R.; Nosarti, Chiara

2015-01-01

The human brain can adapt to overcome injury even years after an initial insult. One hypothesis states that early brain injury survivors, by taking advantage of critical periods of high plasticity during childhood, should recover more successfully than those who suffer injury later in life. This hypothesis has been challenged by recent studies showing worse cognitive outcome in individuals with early brain injury, compared with individuals with later brain injury, with working memory particularly affected. We invited individuals who suffered perinatal brain injury (PBI) for an fMRI/diffusion MRI tractography study of working memory and hypothesized that, 30 years after the initial injury, working memory deficits in the PBI group would remain, despite compensatory activation in areas outside the typical working memory network. Furthermore we hypothesized that the amount of functional reorganization would be related to the level of injury to the dorsal cingulum tract, which connects medial frontal and parietal working memory structures. We found that adults who suffered PBI did not significantly differ from controls in working memory performance. They exhibited less activation in classic frontoparietal working memory areas and a relative overactivation of bilateral perisylvian cortex compared with controls. Structurally, the dorsal cingulum volume and hindrance-modulated orientational anisotropy was significantly reduced in the PBI group. Furthermore there was uniquely in the PBI group a significant negative correlation between the volume of this tract and activation in the bilateral perisylvian cortex and a positive correlation between this activation and task performance. This provides the first evidence of compensatory plasticity of the working memory network following PBI. SIGNIFICANCE STATEMENT Here we used the example of perinatal brain injury (PBI) associated with very preterm birth to study the brain's ability to adapt to injury sustained early in life. In adulthood, individuals with PBI did not show significant deficits in working memory, but exhibited less activation in typical frontoparietal working memory areas. They also showed a relative overactivation of nontask-specific brain areas (perisylvian cortex) compared with controls, and such activation was negatively correlated with the size of white matter pathways involved in working memory (dorsal cingulum). Furthermore, this “extra” activation was associated with better working memory performance and could represent a novel compensatory mechanism following PBI. Such information could inform the development of neuroscience-based cognitive interventions following PBI. PMID:26631462

Recognition of Telugu characters using neural networks.

PubMed

Sukhaswami, M B; Seetharamulu, P; Pujari, A K

1995-09-01

The aim of the present work is to recognize printed and handwritten Telugu characters using artificial neural networks (ANNs). Earlier work on recognition of Telugu characters has been done using conventional pattern recognition techniques. We make an initial attempt here of using neural networks for recognition with the aim of improving upon earlier methods which do not perform effectively in the presence of noise and distortion in the characters. The Hopfield model of neural network working as an associative memory is chosen for recognition purposes initially. Due to limitation in the capacity of the Hopfield neural network, we propose a new scheme named here as the Multiple Neural Network Associative Memory (MNNAM). The limitation in storage capacity has been overcome by combining multiple neural networks which work in parallel. It is also demonstrated that the Hopfield network is suitable for recognizing noisy printed characters as well as handwritten characters written by different "hands" in a variety of styles. Detailed experiments have been carried out using several learning strategies and results are reported. It is shown here that satisfactory recognition is possible using the proposed strategy. A detailed preprocessing scheme of the Telugu characters from digitized documents is also described.

Working Memory and Parent-Rated Components of Attention in Middle Childhood: A Behavioral Genetic Study

PubMed Central

Deater-Deckard, Kirby; Cutting, Laurie; Thompson, Lee A.; Petrill, Stephen A.

2012-01-01

The purpose of the current study was to investigate potential genetic and environmental correlations between working memory and three behavioral aspects of the attention network (i.e., executive, alerting, and orienting) using a twin design. Data were from 90 monozygotic (39% male) and 112 same-sex dizygotic (41% male) twins. Individual differences in working memory performance (digit span) and parent-rated measures of executive, alerting, and orienting attention included modest to moderate genetic variance, modest shared environmental variance, and modest to moderate nonshared environmental variance. As hypothesized, working memory performance was correlated with executive and alerting attention, but not orienting attention. The correlation between working memory, executive attention, and alerting attention was completely accounted for by overlapping genetic covariance, suggesting a common genetic mechanism or mechanisms underlying the links between working memory and certain parent-rated indicators of attentive behavior. PMID:21948215

Modality specificity in the cerebro-cerebellar neurocircuitry during working memory.

PubMed

Ng, H B Tommy; Kao, K-L Cathy; Chan, Y C; Chew, Effie; Chuang, K H; Chen, S H Annabel

2016-05-15

Previous studies have suggested cerebro-cerebellar circuitry in working memory. The present fMRI study aims to distinguish differential cerebro-cerebellar activation patterns in verbal and visual working memory, and employs a quantitative analysis to deterimine lateralization of the activation patterns observed. Consistent with Chen and Desmond (2005a,b) predictions, verbal working memory activated a cerebro-cerebellar circuitry that comprised left-lateralized language-related brain regions including the inferior frontal and posterior parietal areas, and subcortically, right-lateralized superior (lobule VI) and inferior cerebellar (lobule VIIIA/VIIB) areas. In contrast, a distributed network of bilateral inferior frontal and inferior temporal areas, and bilateral superior (lobule VI) and inferior (lobule VIIB) cerebellar areas, was recruited during visual working memory. Results of the study verified that a distinct cross cerebro-cerebellar circuitry underlies verbal working memory. However, a neural circuitry involving specialized brain areas in bilateral neocortical and bilateral cerebellar hemispheres subserving visual working memory is observed. Findings are discussed in the light of current models of working memory and data from related neuroimaging studies. Copyright © 2016 Elsevier B.V. All rights reserved.

The role of trauma-related distractors on neural systems for working memory and emotion processing in posttraumatic stress disorder

PubMed Central

Morey, Rajendra A.; Dolcos, Florin; Petty, Christopher M.; Cooper, Debra A.; Hayes, Jasmeet Pannu; LaBar, Kevin S.; McCarthy, Gregory

2009-01-01

The relevance of emotional stimuli to threat and survival confers a privileged role in their processing. In PTSD, the ability of trauma-related information to divert attention is especially pronounced. Information unrelated to the trauma may also be highly distracting when it shares perceptual features with trauma material. Our goal was to study how trauma-related environmental cues modulate working memory networks in PTSD. We examined neural activity in participants performing a visual working memory task while distracted by task-irrelevant trauma and non-trauma material. Recent post-9/11 veterans were divided into a PTSD group (n = 22) and a trauma-exposed control group (n = 20) based on the Davidson trauma scale. Using fMRI, we measured hemodynamic change in response to emotional (trauma-related) and neutral distraction presented during the active maintenance period of a delayed-response working memory task. The goal was to examine differences in functional networks associated with working memory (dorsolateral prefrontal cortex and lateral parietal cortex) and emotion processing (amygdala, ventrolateral prefrontal cortex, and fusiform gyrus). The PTSD group showed markedly different neural activity compared to the trauma-exposed control group in response to task-irrelevant visual distractors. Enhanced activity in ventral emotion processing regions was associated with trauma distractors in the PTSD group, whereas activity in brain regions associated with working memory and attention regions was disrupted by distractor stimuli independent of trauma content. Neural evidence for the impact of distraction on working memory is consistent with PTSD symptoms of hypervigilance and general distractibility during goal-directed cognitive processing. PMID:19091328

Association Between Sluggish Cognitive Tempo Symptoms and Attentional Network and Working Memory in Primary Schoolchildren.

PubMed

Camprodon-Rosanas, E; Ribas-Fitó, N; Batlle, S; Persavento, C; Alvarez-Pedrerol, M; Sunyer, J; Forns, J

2017-04-01

Few consistent data are available in relation to the cognitive and neuropsychological processes involved in sluggish cognitive tempo (SCT) symptoms. The objective of this study was to determine the association of working memory and attentional networks with SCT symptoms in primary schoolchildren. The participants were schoolchildren aged 7 to 10 years ( n = 183) from primary schools in Catalonia (Spain). All the participants completed a working memory task (n-back) and an attentional network task (ANT). Their parents completed an SCT-Child Behavior Checklist self-report and a questionnaire concerning sociodemographic variables. Teachers of the participants provided information on ADHD symptoms and learning determinants. SCT symptoms were correlated with lower scores in both the n-back and ANT. In multivariate regression analysis, SCT symptoms were associated with slower hit reaction times from the ANT. Our results suggest that SCT symptoms are associated with a neuropsychological profile that is different from the classical ADHD profile and characterized by slower reaction times.

Evidence for social working memory from a parametric functional MRI study.

PubMed

Meyer, Meghan L; Spunt, Robert P; Berkman, Elliot T; Taylor, Shelley E; Lieberman, Matthew D

2012-02-07

Keeping track of various amounts of social cognitive information, including people's mental states, traits, and relationships, is fundamental to navigating social interactions. However, to date, no research has examined which brain regions support variable amounts of social information processing ("social load"). We developed a social working memory paradigm to examine the brain networks sensitive to social load. Two networks showed linear increases in activation as a function of increasing social load: the medial frontoparietal regions implicated in social cognition and the lateral frontoparietal system implicated in nonsocial forms of working memory. Of these networks, only load-dependent medial frontoparietal activity was associated with individual differences in social cognitive ability (trait perspective-taking). Although past studies of nonsocial load have uniformly found medial frontoparietal activity decreases with increasing task demands, the current study demonstrates these regions do support increasing mental effort when such effort engages social cognition. Implications for the etiology of clinical disorders that implicate social functioning and potential interventions are discussed.

The impact of social activities, social networks, social support and social relationships on the cognitive functioning of healthy older adults: a systematic review.

PubMed

Kelly, Michelle E; Duff, Hollie; Kelly, Sara; McHugh Power, Joanna E; Brennan, Sabina; Lawlor, Brian A; Loughrey, David G

2017-12-19

Social relationships, which are contingent on access to social networks, promote engagement in social activities and provide access to social support. These social factors have been shown to positively impact health outcomes. In the current systematic review, we offer a comprehensive overview of the impact of social activities, social networks and social support on the cognitive functioning of healthy older adults (50+) and examine the differential effects of aspects of social relationships on various cognitive domains. We followed PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analysis) guidelines, and collated data from randomised controlled trials (RCTs), genetic and observational studies. Independent variables of interest included subjective measures of social activities, social networks, and social support, and composite measures of social relationships (CMSR). The primary outcome of interest was cognitive function divided into domains of episodic memory, semantic memory, overall memory ability, working memory, verbal fluency, reasoning, attention, processing speed, visuospatial abilities, overall executive functioning and global cognition. Thirty-nine studies were included in the review; three RCTs, 34 observational studies, and two genetic studies. Evidence suggests a relationship between (1) social activity and global cognition and overall executive functioning, working memory, visuospatial abilities and processing speed but not episodic memory, verbal fluency, reasoning or attention; (2) social networks and global cognition but not episodic memory, attention or processing speed; (3) social support and global cognition and episodic memory but not attention or processing speed; and (4) CMSR and episodic memory and verbal fluency but not global cognition. The results support prior conclusions that there is an association between social relationships and cognitive function but the exact nature of this association remains unclear. Implications of the findings are discussed and suggestions for future research provided. PROSPERO 2012: CRD42012003248 .

Opposite Effects of Working Memory on Subjective Visibility and Priming

ERIC Educational Resources Information Center

De Loof, Esther; Verguts, Tom; Fias, Wim; Van Opstal, Filip

2013-01-01

Cognitive theories on consciousness propose a strong link between consciousness and working memory (WM). This link is also present at the neural level: Both consciousness and WM have been implicated in a prefrontal parietal network. However, the link remains empirically unexplored. The present study investigates the relation between consciousness…

Functional Brain Network Abnormalities during Verbal Working Memory Performance in Adolescents and Young Adults with Dyslexia

ERIC Educational Resources Information Center

Wolf, Robert Christian; Sambataro, Fabio; Lohr, Christina; Steinbrink, Claudia; Martin, Claudia; Vasic, Nenad

2010-01-01

Behavioral and functional neuroimaging studies indicate deficits in verbal working memory (WM) and frontoparietal dysfunction in individuals with dyslexia. Additionally, structural brain abnormalities in dyslexics suggest a dysconnectivity of brain regions associated with phonological processing. However, little is known about the functional…

State-Space Analysis of Working Memory in Schizophrenia: An FBIRN Study

ERIC Educational Resources Information Center

Janoos, Firdaus; Brown, Gregory; Morocz, Istvan A.; Wells, William M., III

2013-01-01

The neural correlates of "working memory" (WM) in schizophrenia (SZ) have been extensively studied using the multisite fMRI data acquired by the Functional Biomedical Informatics Research Network (fBIRN) consortium. Although univariate and multivariate analysis methods have been variously employed to localize brain responses under differing task…

Nanophotonic rare-earth quantum memory with optically controlled retrieval.

PubMed

Zhong, Tian; Kindem, Jonathan M; Bartholomew, John G; Rochman, Jake; Craiciu, Ioana; Miyazono, Evan; Bettinelli, Marco; Cavalli, Enrico; Verma, Varun; Nam, Sae Woo; Marsili, Francesco; Shaw, Matthew D; Beyer, Andrew D; Faraon, Andrei

2017-09-29

Optical quantum memories are essential elements in quantum networks for long-distance distribution of quantum entanglement. Scalable development of quantum network nodes requires on-chip qubit storage functionality with control of the readout time. We demonstrate a high-fidelity nanophotonic quantum memory based on a mesoscopic neodymium ensemble coupled to a photonic crystal cavity. The nanocavity enables >95% spin polarization for efficient initialization of the atomic frequency comb memory and time bin-selective readout through an enhanced optical Stark shift of the comb frequencies. Our solid-state memory is integrable with other chip-scale photon source and detector devices for multiplexed quantum and classical information processing at the network nodes. Copyright © 2017 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works.

Using chaotic artificial neural networks to model memory in the brain

NASA Astrophysics Data System (ADS)

Aram, Zainab; Jafari, Sajad; Ma, Jun; Sprott, Julien C.; Zendehrouh, Sareh; Pham, Viet-Thanh

2017-03-01

In the current study, a novel model for human memory is proposed based on the chaotic dynamics of artificial neural networks. This new model explains a biological fact about memory which is not yet explained by any other model: There are theories that the brain normally works in a chaotic mode, while during attention it shows ordered behavior. This model uses the periodic windows observed in a previously proposed model for the brain to store and then recollect the information.

Working Memory and Neurofeedback.

PubMed

YuLeung To, Eric; Abbott, Kathy; Foster, Dale S; Helmer, D'Arcy

2016-01-01

Impairments in working memory are typically associated with impairments in other cognitive faculties such as attentional processes and short-term memory. This paper briefly introduces neurofeedback as a treatment modality in general, and, more specifically, we review several of the current modalities successfully used in neurofeedback (NF) for the treatment of working memory deficits. Two case studies are presented to illustrate how neurofeedback is applied in treatment. The development of Low Resolution Electromagnetic Tomography (LORETA) and its application in neurofeedback now makes it possible to specifically target deep cortical/subcortical brain structures. Developments in neuroscience concerning neural networks, combined with highly specific yet practical NF technologies, makes neurofeedback of particular interest to neuropsychological practice, including the emergence of specific methodologies for treating very difficult working memory (WM) problems.

Training the 21st-Century Worker: Policy Advice from the Dark Network of Implicit Memory. IBE Working Papers on Curriculum Issues No. 16

ERIC Educational Resources Information Center

Abadzi, Helen

2015-01-01

Research on memory functions and their applications is a vast field that has unfolded for decades; some important studies are sixty years old. However, the research has remained a well-kept secret of cognitive psychologists. Education faculties rarely teach memory specifics, so people working in education typically do not know about the above…

Selective attention on representations in working memory: cognitive and neural mechanisms.

PubMed

Ku, Yixuan

2018-01-01

Selective attention and working memory are inter-dependent core cognitive functions. It is critical to allocate attention on selected targets during the capacity-limited working memory processes to fulfill the goal-directed behavior. The trends of research on both topics are increasing exponentially in recent years, and it is considered that selective attention and working memory share similar underlying neural mechanisms. Different types of attention orientation in working memory are introduced by distinctive cues, and the means using retrospective cues are strengthened currently as it is manipulating the representation in memory, instead of the perceptual representation. The cognitive and neural mechanisms of the retro-cue effects are further reviewed, as well as the potential molecular mechanism. The frontal-parietal network that is involved in both attention and working memory is also the neural candidate for attention orientation during working memory. Neural oscillations in the gamma and alpha/beta oscillations may respectively be employed for the feedforward and feedback information transfer between the sensory cortices and the association cortices. Dopamine and serotonin systems might interact with each other subserving the communication between memory and attention. In conclusion, representations which attention shifts towards are strengthened, while representations which attention moves away from are degraded. Studies on attention orientation during working memory indicates the flexibility of the processes of working memory, and the beneficial way that overcome the limited capacity of working memory.

Selective attention on representations in working memory: cognitive and neural mechanisms

PubMed Central

2018-01-01

Selective attention and working memory are inter-dependent core cognitive functions. It is critical to allocate attention on selected targets during the capacity-limited working memory processes to fulfill the goal-directed behavior. The trends of research on both topics are increasing exponentially in recent years, and it is considered that selective attention and working memory share similar underlying neural mechanisms. Different types of attention orientation in working memory are introduced by distinctive cues, and the means using retrospective cues are strengthened currently as it is manipulating the representation in memory, instead of the perceptual representation. The cognitive and neural mechanisms of the retro-cue effects are further reviewed, as well as the potential molecular mechanism. The frontal-parietal network that is involved in both attention and working memory is also the neural candidate for attention orientation during working memory. Neural oscillations in the gamma and alpha/beta oscillations may respectively be employed for the feedforward and feedback information transfer between the sensory cortices and the association cortices. Dopamine and serotonin systems might interact with each other subserving the communication between memory and attention. In conclusion, representations which attention shifts towards are strengthened, while representations which attention moves away from are degraded. Studies on attention orientation during working memory indicates the flexibility of the processes of working memory, and the beneficial way that overcome the limited capacity of working memory. PMID:29629245

Distributed simulation using a real-time shared memory network

NASA Technical Reports Server (NTRS)

Simon, Donald L.; Mattern, Duane L.; Wong, Edmond; Musgrave, Jeffrey L.

1993-01-01

The Advanced Control Technology Branch of the NASA Lewis Research Center performs research in the area of advanced digital controls for aeronautic and space propulsion systems. This work requires the real-time implementation of both control software and complex dynamical models of the propulsion system. We are implementing these systems in a distributed, multi-vendor computer environment. Therefore, a need exists for real-time communication and synchronization between the distributed multi-vendor computers. A shared memory network is a potential solution which offers several advantages over other real-time communication approaches. A candidate shared memory network was tested for basic performance. The shared memory network was then used to implement a distributed simulation of a ramjet engine. The accuracy and execution time of the distributed simulation was measured and compared to the performance of the non-partitioned simulation. The ease of partitioning the simulation, the minimal time required to develop for communication between the processors and the resulting execution time all indicate that the shared memory network is a real-time communication technique worthy of serious consideration.

Prefrontal spatial working memory network predicts animal's decision making in a free choice saccade task

PubMed Central

Mochizuki, Kei

2015-01-01

While neurons in the lateral prefrontal cortex (PFC) encode spatial information during the performance of working memory tasks, they are also known to participate in subjective behavior such as spatial attention and action selection. In the present study, we analyzed the activity of primate PFC neurons during the performance of a free choice memory-guided saccade task in which the monkeys needed to choose a saccade direction by themselves. In trials when the receptive field location was subsequently chosen by the animal, PFC neurons with spatially selective visual response started to show greater activation before cue onset. This result suggests that the fluctuation of firing before cue presentation prematurely biased the representation of a certain spatial location and eventually encouraged the subsequent choice of that location. In addition, modulation of the activity by the animal's choice was observed only in neurons with high sustainability of activation and was also dependent on the spatial configuration of the visual cues. These findings were consistent with known characteristics of PFC neurons in information maintenance in spatial working memory function. These results suggest that precue fluctuation of spatial representation was shared and enhanced through the working memory network in the PFC and could finally influence the animal's free choice of saccade direction. The present study revealed that the PFC plays an important role in decision making in a free choice condition and that the dynamics of decision making are constrained by the network architecture embedded in this cortical area. PMID:26490287

Working memory activation of neural networks in the elderly as a function of information processing phase and task complexity.

PubMed

Charroud, Céline; Steffener, Jason; Le Bars, Emmanuelle; Deverdun, Jérémy; Bonafe, Alain; Abdennour, Meriem; Portet, Florence; Molino, François; Stern, Yaakov; Ritchie, Karen; Menjot de Champfleur, Nicolas; Akbaraly, Tasnime N

2015-11-01

Changes in working memory are sensitive indicators of both normal and pathological brain aging and associated disability. The present study aims to further understanding of working memory in normal aging using a large cohort of healthy elderly in order to examine three separate phases of information processing in relation to changes in task load activation. Using covariance analysis, increasing and decreasing neural activation was observed on fMRI in response to a delayed item recognition task in 337 cognitively healthy elderly persons as part of the CRESCENDO (Cognitive REServe and Clinical ENDOphenotypes) study. During three phases of the task (stimulation, retention, probe), increased activation was observed with increasing task load in bilateral regions of the prefrontal cortex, parietal lobule, cingulate gyrus, insula and in deep gray matter nuclei, suggesting an involvement of central executive and salience networks. Decreased activation associated with increasing task load was observed during the stimulation phase, in bilateral temporal cortex, parietal lobule, cingulate gyrus and prefrontal cortex. This spatial distribution of decreased activation is suggestive of the default mode network. These findings support the hypothesis of an increased activation in salience and central executive networks and a decreased activation in default mode network concomitant to increasing task load. Copyright © 2015 Elsevier Inc. All rights reserved.

Verbal working memory performance correlates with regional white matter structures in the frontoparietal regions.

PubMed

Takeuchi, Hikaru; Taki, Yasuyuki; Sassa, Yuko; Hashizume, Hiroshi; Sekiguchi, Atsushi; Fukushima, Ai; Kawashima, Ryuta

2011-10-01

Working memory is the limited capacity storage system involved in the maintenance and manipulation of information over short periods of time. Previous imaging studies have suggested that the frontoparietal regions are activated during working memory tasks; a putative association between the structure of the frontoparietal regions and working memory performance has been suggested based on the analysis of individuals with varying pathologies. This study aimed to identify correlations between white matter and individual differences in verbal working memory performance in normal young subjects. We performed voxel-based morphometry (VBM) analyses using T1-weighted structural images as well as voxel-based analyses of fractional anisotropy (FA) using diffusion tensor imaging. Using the letter span task, we measured verbal working memory performance in normal young adult men and women (mean age, 21.7 years, SD=1.44; 42 men and 13 women). We observed positive correlations between working memory performance and regional white matter volume (rWMV) in the frontoparietal regions. In addition, FA was found to be positively correlated with verbal working memory performance in a white matter region adjacent to the right precuneus. These regions are consistently recruited by working memory. Our findings suggest that, among normal young subjects, verbal working memory performance is associated with various regions that are recruited during working memory tasks, and this association is not limited to specific parts of the working memory network. Copyright © 2011 Elsevier Ltd. All rights reserved.

Working memory circuit as a function of increasing age in healthy adolescence: A systematic review and meta-analyses.

PubMed

Andre, Julia; Picchioni, Marco; Zhang, Ruibin; Toulopoulou, Timothea

2016-01-01

Working memory ability matures through puberty and early adulthood. Deficits in working memory are linked to the risk of onset of neurodevelopmental disorders such as schizophrenia, and there is a significant temporal overlap between the peak of first episode psychosis risk and working memory maturation. In order to characterize the normal working memory functional maturation process through this critical phase of cognitive development we conducted a systematic review and coordinate based meta-analyses of all the available primary functional magnetic resonance imaging studies (n = 382) that mapped WM function in healthy adolescents (10-17 years) and young adults (18-30 years). Activation Likelihood Estimation analyses across all WM tasks revealed increased activation with increasing subject age in the middle frontal gyrus (BA6) bilaterally, the left middle frontal gyrus (BA10), the left precuneus and left inferior parietal gyri (BA7; 40). Decreased activation with increasing age was found in the right superior frontal (BA8), left junction of postcentral and inferior parietal (BA3/40), and left limbic cingulate gyrus (BA31). These results suggest that brain activation during adolescence increased with age principally in higher order cortices, part of the core working memory network, while reductions were detected in more diffuse and potentially more immature neural networks. Understanding the process by which the brain and its cognitive functions mature through healthy adulthood may provide us with new clues to understanding the vulnerability to neurodevelopmental disorders.

Efficient reinforcement learning of a reservoir network model of parametric working memory achieved with a cluster population winner-take-all readout mechanism.

PubMed

Cheng, Zhenbo; Deng, Zhidong; Hu, Xiaolin; Zhang, Bo; Yang, Tianming

2015-12-01

The brain often has to make decisions based on information stored in working memory, but the neural circuitry underlying working memory is not fully understood. Many theoretical efforts have been focused on modeling the persistent delay period activity in the prefrontal areas that is believed to represent working memory. Recent experiments reveal that the delay period activity in the prefrontal cortex is neither static nor homogeneous as previously assumed. Models based on reservoir networks have been proposed to model such a dynamical activity pattern. The connections between neurons within a reservoir are random and do not require explicit tuning. Information storage does not depend on the stable states of the network. However, it is not clear how the encoded information can be retrieved for decision making with a biologically realistic algorithm. We therefore built a reservoir-based neural network to model the neuronal responses of the prefrontal cortex in a somatosensory delayed discrimination task. We first illustrate that the neurons in the reservoir exhibit a heterogeneous and dynamical delay period activity observed in previous experiments. Then we show that a cluster population circuit decodes the information from the reservoir with a winner-take-all mechanism and contributes to the decision making. Finally, we show that the model achieves a good performance rapidly by shaping only the readout with reinforcement learning. Our model reproduces important features of previous behavior and neurophysiology data. We illustrate for the first time how task-specific information stored in a reservoir network can be retrieved with a biologically plausible reinforcement learning training scheme. Copyright © 2015 the American Physiological Society.

Unsupervised learning in neural networks with short range synapses

NASA Astrophysics Data System (ADS)

Brunnet, L. G.; Agnes, E. J.; Mizusaki, B. E. P.; Erichsen, R., Jr.

2013-01-01

Different areas of the brain are involved in specific aspects of the information being processed both in learning and in memory formation. For example, the hippocampus is important in the consolidation of information from short-term memory to long-term memory, while emotional memory seems to be dealt by the amygdala. On the microscopic scale the underlying structures in these areas differ in the kind of neurons involved, in their connectivity, or in their clustering degree but, at this level, learning and memory are attributed to neuronal synapses mediated by longterm potentiation and long-term depression. In this work we explore the properties of a short range synaptic connection network, a nearest neighbor lattice composed mostly by excitatory neurons and a fraction of inhibitory ones. The mechanism of synaptic modification responsible for the emergence of memory is Spike-Timing-Dependent Plasticity (STDP), a Hebbian-like rule, where potentiation/depression is acquired when causal/non-causal spikes happen in a synapse involving two neurons. The system is intended to store and recognize memories associated to spatial external inputs presented as simple geometrical forms. The synaptic modifications are continuously applied to excitatory connections, including a homeostasis rule and STDP. In this work we explore the different scenarios under which a network with short range connections can accomplish the task of storing and recognizing simple connected patterns.

Ghosts in the machine: memory interference from the previous trial.

PubMed

Papadimitriou, Charalampos; Ferdoash, Afreen; Snyder, Lawrence H

2015-01-15

Previous memoranda can interfere with the memorization or storage of new information, a concept known as proactive interference. Studies of proactive interference typically use categorical memoranda and match-to-sample tasks with categorical measures such as the proportion of correct to incorrect responses. In this study we instead train five macaques in a spatial memory task with continuous memoranda and responses, allowing us to more finely probe working memory circuits. We first ask whether the memoranda from the previous trial result in proactive interference in an oculomotor delayed response task. We then characterize the spatial and temporal profile of this interference and ask whether this profile can be predicted by an attractor network model of working memory. We find that memory in the current trial shows a bias toward the location of the memorandum of the previous trial. The magnitude of this bias increases with the duration of the memory period within which it is measured. Our simulations using standard attractor network models of working memory show that these models easily replicate the spatial profile of the bias. However, unlike the behavioral findings, these attractor models show an increase in bias with the duration of the previous rather than the current memory period. To model a bias that increases with current trial duration we posit two separate memory stores, a rapidly decaying visual store that resists proactive interference effects and a sustained memory store that is susceptible to proactive interference. Copyright © 2015 the American Physiological Society.

Ghosts in the machine: memory interference from the previous trial

PubMed Central

Ferdoash, Afreen; Snyder, Lawrence H.

2014-01-01

Previous memoranda can interfere with the memorization or storage of new information, a concept known as proactive interference. Studies of proactive interference typically use categorical memoranda and match-to-sample tasks with categorical measures such as the proportion of correct to incorrect responses. In this study we instead train five macaques in a spatial memory task with continuous memoranda and responses, allowing us to more finely probe working memory circuits. We first ask whether the memoranda from the previous trial result in proactive interference in an oculomotor delayed response task. We then characterize the spatial and temporal profile of this interference and ask whether this profile can be predicted by an attractor network model of working memory. We find that memory in the current trial shows a bias toward the location of the memorandum of the previous trial. The magnitude of this bias increases with the duration of the memory period within which it is measured. Our simulations using standard attractor network models of working memory show that these models easily replicate the spatial profile of the bias. However, unlike the behavioral findings, these attractor models show an increase in bias with the duration of the previous rather than the current memory period. To model a bias that increases with current trial duration we posit two separate memory stores, a rapidly decaying visual store that resists proactive interference effects and a sustained memory store that is susceptible to proactive interference. PMID:25376781

Neural correlates of working memory training in HIV patients: study protocol for a randomized controlled trial.

PubMed

Chang, L; Løhaugen, G C; Douet, V; Miller, E N; Skranes, J; Ernst, T

2016-02-02

Potent combined antiretroviral therapy decreased the incidence and severity of HIV-associated neurocognitive disorders (HAND); however, no specific effective pharmacotherapy exists for HAND. Patients with HIV commonly have deficits in working memory and attention, which may negatively impact many other cognitive domains, leading to HAND. Since HAND may lead to loss of independence in activities of daily living and negative emotional well-being, and incur a high economic burden, effective treatments for HAND are urgently needed. This study aims to determine whether adaptive working memory training might improve cognitive functions and neural network efficiency and possibly decrease neuroinflammation. This study also aims to assess whether subjects with the LMX1A-rs4657412 TT(AA) genotype show greater training effects from working memory training than TC(AG) or CC(GG)-carriers. 60 HIV-infected and 60 seronegative control participants will be randomized to a double-blind active-controlled study, using adaptive versus non-adaptive Cogmed Working Memory Training® (CWMT), 20-25 sessions over 5-8 weeks. Each subject will be assessed with near- and far-transfer cognitive tasks, self-reported mood and executive function questionnaires, and blood-oxygenation level-dependent functional MRI during working memory (n-back) and visual attention (ball tracking) tasks, at baseline, 1-month, and 6-months after CWMT. Furthermore, genotyping for LMX1A-rs4657412 will be performed to identify whether subjects with the TT(AA)-genotype show greater gain or neural efficiency after CWMT than those with other genotypes. Lastly, cerebrospinal fluid will be obtained before and after CWMT to explore changes in levels of inflammatory proteins (cytokines and chemokines) and monoamines. Improving working memory in HIV patients, using CWMT, might slow the progression or delay the onset of HAND. Observation of decreased brain activation or normalized neural networks, using fMRI, after CWMT would lead to a better understanding of how neural networks are modulated by CWMT. Moreover, validating the greater training gain in subjects with the LMX1A-TT(AA) genotype could lead to a personalized approach for future working memory training studies. Demonstrating and understanding the neural correlates of the efficacy of CWMT in HIV patients could lead to a safe adjunctive therapy for HAND, and possibly other brain disorders. ClinicalTrial.gov, NCT02602418.

Neural circuits in auditory and audiovisual memory.

PubMed

Plakke, B; Romanski, L M

2016-06-01

Working memory is the ability to employ recently seen or heard stimuli and apply them to changing cognitive context. Although much is known about language processing and visual working memory, the neurobiological basis of auditory working memory is less clear. Historically, part of the problem has been the difficulty in obtaining a robust animal model to study auditory short-term memory. In recent years there has been neurophysiological and lesion studies indicating a cortical network involving both temporal and frontal cortices. Studies specifically targeting the role of the prefrontal cortex (PFC) in auditory working memory have suggested that dorsal and ventral prefrontal regions perform different roles during the processing of auditory mnemonic information, with the dorsolateral PFC performing similar functions for both auditory and visual working memory. In contrast, the ventrolateral PFC (VLPFC), which contains cells that respond robustly to auditory stimuli and that process both face and vocal stimuli may be an essential locus for both auditory and audiovisual working memory. These findings suggest a critical role for the VLPFC in the processing, integrating, and retaining of communication information. This article is part of a Special Issue entitled SI: Auditory working memory. Copyright © 2015 Elsevier B.V. All rights reserved.

Neural circuits in Auditory and Audiovisual Memory

PubMed Central

Plakke, B.; Romanski, L.M.

2016-01-01

Working memory is the ability to employ recently seen or heard stimuli and apply them to changing cognitive context. Although much is known about language processing and visual working memory, the neurobiological basis of auditory working memory is less clear. Historically, part of the problem has been the difficulty in obtaining a robust animal model to study auditory short-term memory. In recent years there has been neurophysiological and lesion studies indicating a cortical network involving both temporal and frontal cortices. Studies specifically targeting the role of the prefrontal cortex (PFC) in auditory working memory have suggested that dorsal and ventral prefrontal regions perform different roles during the processing of auditory mnemonic information, with the dorsolateral PFC performing similar functions for both auditory and visual working memory. In contrast, the ventrolateral PFC (VLPFC), which contains cells that respond robustly to auditory stimuli and that process both face and vocal stimuli may be an essential locus for both auditory and audiovisual working memory. These findings suggest a critical role for the VLPFC in the processing, integrating, and retaining of communication information. PMID:26656069

A Spiking Working Memory Model Based on Hebbian Short-Term Potentiation.

PubMed

Fiebig, Florian; Lansner, Anders

2017-01-04

A dominant theory of working memory (WM), referred to as the persistent activity hypothesis, holds that recurrently connected neural networks, presumably located in the prefrontal cortex, encode and maintain WM memory items through sustained elevated activity. Reexamination of experimental data has shown that prefrontal cortex activity in single units during delay periods is much more variable than predicted by such a theory and associated computational models. Alternative models of WM maintenance based on synaptic plasticity, such as short-term nonassociative (non-Hebbian) synaptic facilitation, have been suggested but cannot account for encoding of novel associations. Here we test the hypothesis that a recently identified fast-expressing form of Hebbian synaptic plasticity (associative short-term potentiation) is a possible mechanism for WM encoding and maintenance. Our simulations using a spiking neural network model of cortex reproduce a range of cognitive memory effects in the classical multi-item WM task of encoding and immediate free recall of word lists. Memory reactivation in the model occurs in discrete oscillatory bursts rather than as sustained activity. We relate dynamic network activity as well as key synaptic characteristics to electrophysiological measurements. Our findings support the hypothesis that fast Hebbian short-term potentiation is a key WM mechanism. Working memory (WM) is a key component of cognition. Hypotheses about the neural mechanism behind WM are currently under revision. Reflecting recent findings of fast Hebbian synaptic plasticity in cortex, we test whether a cortical spiking neural network model with such a mechanism can learn a multi-item WM task (word list learning). We show that our model can reproduce human cognitive phenomena and achieve comparable memory performance in both free and cued recall while being simultaneously compatible with experimental data on structure, connectivity, and neurophysiology of the underlying cortical tissue. These findings are directly relevant to the ongoing paradigm shift in the WM field. Copyright © 2017 Fiebig and Lansner.

A Spiking Working Memory Model Based on Hebbian Short-Term Potentiation

PubMed Central

Fiebig, Florian

2017-01-01

A dominant theory of working memory (WM), referred to as the persistent activity hypothesis, holds that recurrently connected neural networks, presumably located in the prefrontal cortex, encode and maintain WM memory items through sustained elevated activity. Reexamination of experimental data has shown that prefrontal cortex activity in single units during delay periods is much more variable than predicted by such a theory and associated computational models. Alternative models of WM maintenance based on synaptic plasticity, such as short-term nonassociative (non-Hebbian) synaptic facilitation, have been suggested but cannot account for encoding of novel associations. Here we test the hypothesis that a recently identified fast-expressing form of Hebbian synaptic plasticity (associative short-term potentiation) is a possible mechanism for WM encoding and maintenance. Our simulations using a spiking neural network model of cortex reproduce a range of cognitive memory effects in the classical multi-item WM task of encoding and immediate free recall of word lists. Memory reactivation in the model occurs in discrete oscillatory bursts rather than as sustained activity. We relate dynamic network activity as well as key synaptic characteristics to electrophysiological measurements. Our findings support the hypothesis that fast Hebbian short-term potentiation is a key WM mechanism. SIGNIFICANCE STATEMENT Working memory (WM) is a key component of cognition. Hypotheses about the neural mechanism behind WM are currently under revision. Reflecting recent findings of fast Hebbian synaptic plasticity in cortex, we test whether a cortical spiking neural network model with such a mechanism can learn a multi-item WM task (word list learning). We show that our model can reproduce human cognitive phenomena and achieve comparable memory performance in both free and cued recall while being simultaneously compatible with experimental data on structure, connectivity, and neurophysiology of the underlying cortical tissue. These findings are directly relevant to the ongoing paradigm shift in the WM field. PMID:28053032

Evidence for a double dissociation of articulatory rehearsal and non-articulatory maintenance of phonological information in human verbal working memory.

PubMed

Trost, Sarah; Gruber, Oliver

2012-01-01

Recent functional neuroimaging studies have provided evidence that human verbal working memory is represented by two complementary neural systems, a left lateralized premotor-parietal network implementing articulatory rehearsal and a presumably phylogenetically older bilateral anterior-prefrontal/inferior-parietal network subserving non-articulatory maintenance of phonological information. In order to corroborate these findings from functional neuroimaging, we performed a targeted behavioural study in patients with very selective and circumscribed brain lesions to key regions suggested to support these different subcomponents of human verbal working memory. Within a sample of over 500 neurological patients assessed with high-resolution structural magnetic resonance imaging, we identified 2 patients with corresponding brain lesions, one with an isolated lesion to Broca's area and the other with a selective lesion bilaterally to the anterior middle frontal gyrus. These 2 patients as well as groups of age-matched healthy controls performed two circuit-specific verbal working memory tasks. In this way, we systematically assessed the hypothesized selective behavioural effects of these brain lesions on the different subcomponents of verbal working memory in terms of a double dissociation. Confirming prior findings, the lesion to Broca's area led to reduced performance under articulatory rehearsal, whereas the non-articulatory maintenance of phonological information was unimpaired. Conversely, the bifrontopolar brain lesion was associated with impaired non-articulatory phonological working memory, whereas performance under articulatory rehearsal was unaffected. The present experimental neuropsychological study in patients with specific and circumscribed brain lesions confirms the hypothesized double dissociation of two complementary brain systems underlying verbal working memory in humans. In particular, the results demonstrate the functional relevance of the anterior prefrontal cortex for non-articulatory maintenance of phonological information and, in this way, provide further support for the evolutionary-based functional-neuroanatomical model of human working memory. Copyright © 2012 S. Karger AG, Basel.

Memory loss in Alzheimer's disease

PubMed Central

Jahn, Holger

2013-01-01

Loss of memory is among the first symptoms reported by patients suffering from Alzheimer's disease (AD) and by their caretakers. Working memory and long-term declarative memory are affected early during the course of the disease. The individual pattern of impaired memory functions correlates with parameters of structural or functional brain integrity. AD pathology interferes with the formation of memories from the molecular level to the framework of neural networks. The investigation of AD memory loss helps to identify the involved neural structures, such as the default mode network, the influence of epigenetic and genetic factors, such as ApoE4 status, and evolutionary aspects of human cognition. Clinically, the analysis of memory assists the definition of AD subtypes, disease grading, and prognostic predictions. Despite new AD criteria that allow the earlier diagnosis of the disease by inclusion of biomarkers derived from cerebrospinal fluid or hippocampal volume analysis, neuropsychological testing remains at the core of AD diagnosis. PMID:24459411

Dynamic reconfiguration of human brain functional networks through neurofeedback.

PubMed

Haller, Sven; Kopel, Rotem; Jhooti, Permi; Haas, Tanja; Scharnowski, Frank; Lovblad, Karl-Olof; Scheffler, Klaus; Van De Ville, Dimitri

2013-11-01

Recent fMRI studies demonstrated that functional connectivity is altered following cognitive tasks (e.g., learning) or due to various neurological disorders. We tested whether real-time fMRI-based neurofeedback can be a tool to voluntarily reconfigure brain network interactions. To disentangle learning-related from regulation-related effects, we first trained participants to voluntarily regulate activity in the auditory cortex (training phase) and subsequently asked participants to exert learned voluntary self-regulation in the absence of feedback (transfer phase without learning). Using independent component analysis (ICA), we found network reconfigurations (increases in functional network connectivity) during the neurofeedback training phase between the auditory target region and (1) the auditory pathway; (2) visual regions related to visual feedback processing; (3) insula related to introspection and self-regulation and (4) working memory and high-level visual attention areas related to cognitive effort. Interestingly, the auditory target region was identified as the hub of the reconfigured functional networks without a-priori assumptions. During the transfer phase, we again found specific functional connectivity reconfiguration between auditory and attention network confirming the specific effect of self-regulation on functional connectivity. Functional connectivity to working memory related networks was no longer altered consistent with the absent demand on working memory. We demonstrate that neurofeedback learning is mediated by widespread changes in functional connectivity. In contrast, applying learned self-regulation involves more limited and specific network changes in an auditory setup intended as a model for tinnitus. Hence, neurofeedback training might be used to promote recovery from neurological disorders that are linked to abnormal patterns of brain connectivity. Copyright © 2013 Elsevier Inc. All rights reserved.

The role of the episodic buffer in working memory for language processing.

PubMed

Rudner, Mary; Rönnberg, Jerker

2008-03-01

A body of work has accumulated to show that the cognitive process of binding information from different mnemonic and sensory sources as well as in different linguistic modalities can be fractionated from general executive functions in working memory both functionally and neurally. This process has been defined in terms of the episodic buffer (Baddeley in Trends Cogn Sci 4(11):417-423, 2000). This paper considers behavioural, neuropsychological and neuroimaging data that elucidate the role of the episodic buffer in language processing. We argue that the episodic buffer seems to be truly multimodal in function and that while formation of unitary multidimensional representations in the episodic buffer seems to engage posterior neural networks, maintenance of such representations is supported by frontal networks. Although, the episodic buffer is not necessarily supported by executive processes and seems to be supported by different neural networks, it may operate in tandem with the central executive during effortful language processing. There is also evidence to suggest engagement of the phonological loop during buffer processing. The hippocampus seems to play a role in formation but not maintenance of representations in the episodic buffer of working memory.

Dopaminergic and Cholinergic Modulations of Visual-Spatial Attention and Working Memory: Insights from Molecular Genetic Research and Implications for Adult Cognitive Development

ERIC Educational Resources Information Center

Stormer, Viola S.; Passow, Susanne; Biesenack, Julia; Li, Shu-Chen

2012-01-01

Attention and working memory are fundamental for selecting and maintaining behaviorally relevant information. Not only do both processes closely intertwine at the cognitive level, but they implicate similar functional brain circuitries, namely the frontoparietal and the frontostriatal networks, which are innervated by cholinergic and dopaminergic…

Morphometry and Connectivity of the Fronto-Parietal Verbal Working Memory Network in Development

ERIC Educational Resources Information Center

Ostby, Ylva; Tamnes, Christian K.; Fjell, Anders M.; Walhovd, Kristine B.

2011-01-01

Two distinctly different maturational processes--cortical thinning and white matter maturation--take place in the brain as we mature from late childhood to adulthood. To what extent does each contribute to the development of complex cognitive functions like working memory? The independent and joint contributions of cortical thickness of regions of…

The list-composition effect in memory for emotional and neutral pictures: Differential contribution of ventral and dorsal attention networks to successful encoding.

PubMed

Barnacle, Gemma E; Montaldi, Daniela; Talmi, Deborah; Sommer, Tobias

2016-09-01

The Emotional enhancement of memory (EEM) is observed in immediate free-recall memory tests when emotional and neutral stimuli are encoded and tested together ("mixed lists"), but surprisingly, not when they are encoded and tested separately ("pure lists"). Here our aim was to investigate whether the effect of list-composition (mixed versus pure lists) on the EEM is due to differential allocation of attention. We scanned participants with fMRI during encoding of semantically-related emotional (negative valence only) and neutral pictures. Analysis of memory performance data replicated previous work, demonstrating an interaction between list composition and emotional valence. In mixed lists, neural subsequent memory effects in the dorsal attention network were greater for neutral stimulus encoding, while neural subsequent memory effects for emotional stimuli were found in a region associated with the ventral attention network. These results imply that when life experiences include both emotional and neutral elements, memory for the latter is more highly correlated with neural activity representing goal-directed attention processing at encoding. Copyright © 2016. Published by Elsevier Ltd.

Cognitive Control Network Contributions to Memory-Guided Visual Attention.

PubMed

Rosen, Maya L; Stern, Chantal E; Michalka, Samantha W; Devaney, Kathryn J; Somers, David C

2016-05-01

Visual attentional capacity is severely limited, but humans excel in familiar visual contexts, in part because long-term memories guide efficient deployment of attention. To investigate the neural substrates that support memory-guided visual attention, we performed a set of functional MRI experiments that contrast long-term, memory-guided visuospatial attention with stimulus-guided visuospatial attention in a change detection task. Whereas the dorsal attention network was activated for both forms of attention, the cognitive control network(CCN) was preferentially activated during memory-guided attention. Three posterior nodes in the CCN, posterior precuneus, posterior callosal sulcus/mid-cingulate, and lateral intraparietal sulcus exhibited the greatest specificity for memory-guided attention. These 3 regions exhibit functional connectivity at rest, and we propose that they form a subnetwork within the broader CCN. Based on the task activation patterns, we conclude that the nodes of this subnetwork are preferentially recruited for long-term memory guidance of visuospatial attention. Published by Oxford University Press 2015. This work is written by (a) US Government employee(s) and is in the public domain in the US.

Prefrontal spatial working memory network predicts animal's decision making in a free choice saccade task.

PubMed

Mochizuki, Kei; Funahashi, Shintaro

2016-01-01

While neurons in the lateral prefrontal cortex (PFC) encode spatial information during the performance of working memory tasks, they are also known to participate in subjective behavior such as spatial attention and action selection. In the present study, we analyzed the activity of primate PFC neurons during the performance of a free choice memory-guided saccade task in which the monkeys needed to choose a saccade direction by themselves. In trials when the receptive field location was subsequently chosen by the animal, PFC neurons with spatially selective visual response started to show greater activation before cue onset. This result suggests that the fluctuation of firing before cue presentation prematurely biased the representation of a certain spatial location and eventually encouraged the subsequent choice of that location. In addition, modulation of the activity by the animal's choice was observed only in neurons with high sustainability of activation and was also dependent on the spatial configuration of the visual cues. These findings were consistent with known characteristics of PFC neurons in information maintenance in spatial working memory function. These results suggest that precue fluctuation of spatial representation was shared and enhanced through the working memory network in the PFC and could finally influence the animal's free choice of saccade direction. The present study revealed that the PFC plays an important role in decision making in a free choice condition and that the dynamics of decision making are constrained by the network architecture embedded in this cortical area. Copyright © 2016 the American Physiological Society.

Is Social Network a Protective Factor for Cognitive Impairment in US Chinese Older Adults? Findings from the PINE Study.

PubMed

Li, Mengting; Dong, Xinqi

2018-01-01

Social network has been identified as a protective factor for cognitive impairment. However, the relationship between social network and global and subdomains of cognitive function remains unclear. This study aims to provide an analytic framework to examine quantity, composition, and quality of social network and investigate the association between social network, global cognition, and cognitive domains among US Chinese older adults. Data were derived from the Population Study of Chinese Elderly (PINE), a community-engaged, population-based epidemiological study of US Chinese older adults aged 60 and above in the greater Chicago area, with a sample size of 3,157. Social network was assessed by network size, volume of contact, proportion kin, proportion female, proportion co-resident, and emotional closeness. Cognitive function was evaluated by global cognition, episodic memory, executive function, working memory, and Chinese Mini-Mental State Examination (C-MMSE). Linear regression and quantile regression were performed. Every 1-point increase in network size (b = 0.048, p < 0.001) and volume of contact (b = 0.049, p < 0.01) and every 1-point decrease in proportion kin (b = -0.240, p < 0.01) and proportion co-resident (b = -0.099, p < 0.05) were associated with higher level of global cognition. Similar trends were observed in specific cognitive domains, including episodic memory, working memory, executive function, and C-MMSE. However, emotional closeness was only significantly associated with C-MMSE (b = 0.076, p < 0.01). Social network has differential effects on female versus male older adults. This study found that social network dimensions have different relationships with global and domains of cognitive function. Quantitative and structural aspects of social network were essential to maintain an optimal level of cognitive function. Qualitative aspects of social network were protective factors for C-MMSE. It is necessary for public health practitioners to consider interventions that enhance different aspects of older adults' social network. © 2017 S. Karger AG, Basel.

Avalanches and generalized memory associativity in a network model for conscious and unconscious mental functioning

NASA Astrophysics Data System (ADS)

Siddiqui, Maheen; Wedemann, Roseli S.; Jensen, Henrik Jeldtoft

2018-01-01

We explore statistical characteristics of avalanches associated with the dynamics of a complex-network model, where two modules corresponding to sensorial and symbolic memories interact, representing unconscious and conscious mental processes. The model illustrates Freud's ideas regarding the neuroses and that consciousness is related with symbolic and linguistic memory activity in the brain. It incorporates the Stariolo-Tsallis generalization of the Boltzmann Machine in order to model memory retrieval and associativity. In the present work, we define and measure avalanche size distributions during memory retrieval, in order to gain insight regarding basic aspects of the functioning of these complex networks. The avalanche sizes defined for our model should be related to the time consumed and also to the size of the neuronal region which is activated, during memory retrieval. This allows the qualitative comparison of the behaviour of the distribution of cluster sizes, obtained during fMRI measurements of the propagation of signals in the brain, with the distribution of avalanche sizes obtained in our simulation experiments. This comparison corroborates the indication that the Nonextensive Statistical Mechanics formalism may indeed be more well suited to model the complex networks which constitute brain and mental structure.

Articulatory rehearsal in verbal working memory: a possible neurocognitive endophenotype that differentiates between schizophrenia and schizoaffective disorder.

PubMed

Gruber, Oliver; Gruber, Eva; Falkai, Peter

2006-09-11

Recent fMRI studies have identified brain systems underlying different components of working memory in healthy individuals. The aim of this study was to compare the functional integrity of these neural networks in terms of behavioural performance in patients with schizophrenia, schizoaffective disorder and healthy controls. In order to detect specific working memory deficits based on dysfunctions of underlying brain circuits we used the same verbal and visuospatial Sternberg item-recognition tasks as in previous neuroimaging studies. Clinical and performance data from matched groups consisting of 14 subjects each were statistically analyzed. Schizophrenic patients exhibited pronounced impairments of both verbal and visuospatial working memory, whereas verbal working memory performance was preserved in schizoaffective patients. The findings provide first evidence that dysfunction of a brain system subserving articulatory rehearsal could represent a biological marker which differentiates between schizophrenia and schizoaffective disorder.

Development of a computational model on the neural activity patterns of a visual working memory in a hierarchical feedforward Network

NASA Astrophysics Data System (ADS)

An, Soyoung; Choi, Woochul; Paik, Se-Bum

2015-11-01

Understanding the mechanism of information processing in the human brain remains a unique challenge because the nonlinear interactions between the neurons in the network are extremely complex and because controlling every relevant parameter during an experiment is difficult. Therefore, a simulation using simplified computational models may be an effective approach. In the present study, we developed a general model of neural networks that can simulate nonlinear activity patterns in the hierarchical structure of a neural network system. To test our model, we first examined whether our simulation could match the previously-observed nonlinear features of neural activity patterns. Next, we performed a psychophysics experiment for a simple visual working memory task to evaluate whether the model could predict the performance of human subjects. Our studies show that the model is capable of reproducing the relationship between memory load and performance and may contribute, in part, to our understanding of how the structure of neural circuits can determine the nonlinear neural activity patterns in the human brain.

N-back Working Memory Task: Meta-analysis of Normative fMRI Studies With Children.

PubMed

Yaple, Zachary; Arsalidou, Marie

2018-05-07

The n-back task is likely the most popular measure of working memory for functional magnetic resonance imaging (fMRI) studies. Despite accumulating neuroimaging studies with the n-back task and children, its neural representation is still unclear. fMRI studies that used the n-back were compiled, and data from children up to 15 years (n = 260) were analyzed using activation likelihood estimation. Results show concordance in frontoparietal regions recognized for their role in working memory as well as regions not typically highlighted as part of the working memory network, such as the insula. Findings are discussed in terms of developmental methodology and potential contribution to developmental theories of cognition. © 2018 Society for Research in Child Development.

Brain Activity and Network Interactions in the Impact of Internal Emotional Distraction.

PubMed

Iordan, A D; Dolcos, S; Dolcos, F

2018-06-14

Emotional distraction may come from the external world and from our mind, as internal distraction. Although external emotional distraction has been extensively investigated, less is known about the mechanisms associated with the impact of internal emotional distraction on cognitive performance, and those involved in coping with such distraction. These issues were investigated using a working memory task with emotional distraction, where recollected unpleasant autobiographical memories served as internal emotional distraction. Emotion regulation was manipulated by instructing participants to focus their attention either on or away from the emotional aspects of their memories. Behaviorally, focusing away from emotion was associated with better working memory performance than focusing on the recollected emotions. Functional MRI data showed reduced response in brain regions associated with the salience network, coupled with greater recruitment of executive prefrontal and memory-related temporoparietal regions, and with increased frontoparietal connectivity, when subjects focused on nonemotional contextual details of their memories. Finally, temporal dissociations were also identified between regions involved in self-referential (showing faster responses) versus context-related processing (showing delayed responses). These findings demonstrate that focused attention is an effective regulation strategy in coping with internal distraction, and are relevant for understanding clinical conditions where coping with distressing memories is dysfunctional.

How the amygdala affects emotional memory by altering brain network properties.

PubMed

Hermans, Erno J; Battaglia, Francesco P; Atsak, Piray; de Voogd, Lycia D; Fernández, Guillén; Roozendaal, Benno

2014-07-01

The amygdala has long been known to play a key role in supporting memory for emotionally arousing experiences. For example, classical fear conditioning depends on neural plasticity within this anterior medial temporal lobe region. Beneficial effects of emotional arousal on memory, however, are not restricted to simple associative learning. Our recollection of emotional experiences often includes rich representations of, e.g., spatiotemporal context, visceral states, and stimulus-response associations. Critically, such memory features are known to bear heavily on regions elsewhere in the brain. These observations led to the modulation account of amygdala function, which postulates that amygdala activation enhances memory consolidation by facilitating neural plasticity and information storage processes in its target regions. Rodent work in past decades has identified the most important brain regions and neurochemical processes involved in these modulatory actions, and neuropsychological and neuroimaging work in humans has produced a large body of convergent data. Importantly, recent methodological developments make it increasingly realistic to monitor neural interactions underlying such modulatory effects as they unfold. For instance, functional connectivity network modeling in humans has demonstrated how information exchanges between the amygdala and specific target regions occur within the context of large-scale neural network interactions. Furthermore, electrophysiological and optogenetic techniques in rodents are beginning to make it possible to quantify and even manipulate such interactions with millisecond precision. In this paper we will discuss that these developments will likely lead to an updated view of the amygdala as a critical nexus within large-scale networks supporting different aspects of memory processing for emotionally arousing experiences. Copyright © 2014 Elsevier Inc. All rights reserved.

Optically simulating a quantum associative memory

NASA Astrophysics Data System (ADS)

Howell, John C.; Yeazell, John A.; Ventura, Dan

2000-10-01

This paper discusses the realization of a quantum associative memory using linear integrated optics. An associative memory produces a full pattern of bits when presented with only a partial pattern. Quantum computers have the potential to store large numbers of patterns and hence have the ability to far surpass any classical neural-network realization of an associative memory. In this work two three-qubit associative memories will be discussed using linear integrated optics. In addition, corrupted, invented and degenerate memories are discussed.

Auditory short-term memory in the primate auditory cortex.

PubMed

Scott, Brian H; Mishkin, Mortimer

2016-06-01

Sounds are fleeting, and assembling the sequence of inputs at the ear into a coherent percept requires auditory memory across various time scales. Auditory short-term memory comprises at least two components: an active ׳working memory' bolstered by rehearsal, and a sensory trace that may be passively retained. Working memory relies on representations recalled from long-term memory, and their rehearsal may require phonological mechanisms unique to humans. The sensory component, passive short-term memory (pSTM), is tractable to study in nonhuman primates, whose brain architecture and behavioral repertoire are comparable to our own. This review discusses recent advances in the behavioral and neurophysiological study of auditory memory with a focus on single-unit recordings from macaque monkeys performing delayed-match-to-sample (DMS) tasks. Monkeys appear to employ pSTM to solve these tasks, as evidenced by the impact of interfering stimuli on memory performance. In several regards, pSTM in monkeys resembles pitch memory in humans, and may engage similar neural mechanisms. Neural correlates of DMS performance have been observed throughout the auditory and prefrontal cortex, defining a network of areas supporting auditory STM with parallels to that supporting visual STM. These correlates include persistent neural firing, or a suppression of firing, during the delay period of the memory task, as well as suppression or (less commonly) enhancement of sensory responses when a sound is repeated as a ׳match' stimulus. Auditory STM is supported by a distributed temporo-frontal network in which sensitivity to stimulus history is an intrinsic feature of auditory processing. This article is part of a Special Issue entitled SI: Auditory working memory. Published by Elsevier B.V.

A New Measure for Neural Compensation Is Positively Correlated With Working Memory and Gait Speed.

PubMed

Ji, Lanxin; Pearlson, Godfrey D; Hawkins, Keith A; Steffens, David C; Guo, Hua; Wang, Lihong

2018-01-01

Neuroimaging studies suggest that older adults may compensate for declines in brain function and cognition through reorganization of neural resources. A limitation of prior research is reliance on between-group comparisons of neural activation (e.g., younger vs. older), which cannot be used to assess compensatory ability quantitatively. It is also unclear about the relationship between compensatory ability with cognitive function or how other factors such as physical exercise modulates compensatory ability. Here, we proposed a data-driven method to semi-quantitatively measure neural compensation under a challenging cognitive task, and we then explored connections between neural compensation to cognitive engagement and cognitive reserve (CR). Functional and structural magnetic resonance imaging scans were acquired for 26 healthy older adults during a face-name memory task. Spatial independent component analysis (ICA) identified visual, attentional and left executive as core networks. Results show that the smaller the volumes of the gray matter (GM) structures within core networks, the more networks were needed to conduct the task ( r = -0.408, p = 0.035). Therefore, the number of task-activated networks controlling for the GM volume within core networks was defined as a measure of neural compensatory ability. We found that compensatory ability correlated with working memory performance ( r = 0.528, p = 0.035). Among subjects with good memory task performance, those with higher CR used fewer networks than subjects with lower CR. Among poor-performance subjects, those using more networks had higher CR. Our results indicated that using a high cognitive-demanding task to measure the number of activated neural networks could be a useful and sensitive measure of neural compensation in older adults.

Dynamic search and working memory in social recall.

PubMed

Hills, Thomas T; Pachur, Thorsten

2012-01-01

What are the mechanisms underlying search in social memory (e.g., remembering the people one knows)? Do the search mechanisms involve dynamic local-to-global transitions similar to semantic search, and are these transitions governed by the general control of attention, associated with working memory span? To find out, we asked participants to recall individuals from their personal social networks and measured each participant's working memory capacity. Additionally, participants provided social-category and contact-frequency information about the recalled individuals as well as information about the social proximity among the recalled individuals. On the basis of these data, we tested various computational models of memory search regarding their ability to account for the patterns in which participants recalled from social memory. Although recall patterns showed clustering based on social categories, models assuming dynamic transitions between representations cued by social proximity and frequency information predicted participants' recall patterns best-no additional explanatory power was gained from social-category information. Moreover, individual differences in the time between transitions were positively correlated with differences in working memory capacity. These results highlight the role of social proximity in structuring social memory and elucidate the role of working memory for maintaining search criteria during search within that structure.

Graph properties of synchronized cortical networks during visual working memory maintenance.

PubMed

Palva, Satu; Monto, Simo; Palva, J Matias

2010-02-15

Oscillatory synchronization facilitates communication in neuronal networks and is intimately associated with human cognition. Neuronal activity in the human brain can be non-invasively imaged with magneto- (MEG) and electroencephalography (EEG), but the large-scale structure of synchronized cortical networks supporting cognitive processing has remained uncharacterized. We combined simultaneous MEG and EEG (MEEG) recordings with minimum-norm-estimate-based inverse modeling to investigate the structure of oscillatory phase synchronized networks that were active during visual working memory (VWM) maintenance. Inter-areal phase-synchrony was quantified as a function of time and frequency by single-trial phase-difference estimates of cortical patches covering the entire cortical surfaces. The resulting networks were characterized with a number of network metrics that were then compared between delta/theta- (3-6 Hz), alpha- (7-13 Hz), beta- (16-25 Hz), and gamma- (30-80 Hz) frequency bands. We found several salient differences between frequency bands. Alpha- and beta-band networks were more clustered and small-world like but had smaller global efficiency than the networks in the delta/theta and gamma bands. Alpha- and beta-band networks also had truncated-power-law degree distributions and high k-core numbers. The data converge on showing that during the VWM-retention period, human cortical alpha- and beta-band networks have a memory-load dependent, scale-free small-world structure with densely connected core-like structures. These data further show that synchronized dynamic networks underlying a specific cognitive state can exhibit distinct frequency-dependent network structures that could support distinct functional roles. Copyright 2009 Elsevier Inc. All rights reserved.

Working Memory and Reasoning Benefit from Different Modes of Large-scale Brain Dynamics in Healthy Older Adults.

PubMed

Lebedev, Alexander V; Nilsson, Jonna; Lövdén, Martin

2018-07-01

Researchers have proposed that solving complex reasoning problems, a key indicator of fluid intelligence, involves the same cognitive processes as solving working memory tasks. This proposal is supported by an overlap of the functional brain activations associated with the two types of tasks and by high correlations between interindividual differences in performance. We replicated these findings in 53 older participants but also showed that solving reasoning and working memory problems benefits from different configurations of the functional connectome and that this dissimilarity increases with a higher difficulty load. Specifically, superior performance in a typical working memory paradigm ( n-back) was associated with upregulation of modularity (increased between-network segregation), whereas performance in the reasoning task was associated with effective downregulation of modularity. We also showed that working memory training promotes task-invariant increases in modularity. Because superior reasoning performance is associated with downregulation of modular dynamics, training may thus have fostered an inefficient way of solving the reasoning tasks. This could help explain why working memory training does little to promote complex reasoning performance. The study concludes that complex reasoning abilities cannot be reduced to working memory and suggests the need to reconsider the feasibility of using working memory training interventions to attempt to achieve effects that transfer to broader cognition.

Spatial and Temporal Episodic Memory Retrieval Recruit Dissociable Functional Networks in the Human Brain

ERIC Educational Resources Information Center

Ekstrom, Arne D.; Bookheimer, Susan Y.

2007-01-01

Imaging, electrophysiological studies, and lesion work have shown that the medial temporal lobe (MTL) is important for episodic memory; however, it is unclear whether different MTL regions support the spatial, temporal, and item elements of episodic memory. In this study we used fMRI to examine retrieval performance emphasizing different aspects…

Modulation of working memory load distinguishes individuals with and without balance impairments following mild traumatic brain injury.

PubMed

Woytowicz, Elizabeth J; Sours, Chandler; Gullapalli, Rao P; Rosenberg, Joseph; Westlake, Kelly P

2018-01-01

Balance and gait deficits can persist after mild traumatic brain injury (TBI), yet an understanding of the underlying neural mechanism remains limited. The purpose of this study was to investigate differences in attention network modulation in patients with and without balance impairments 2-8 weeks following mild TBI. Using functional magnetic resonance imaging, we compared activity and functional connectivity of cognitive brain regions of the default mode, central-executive and salience networks during a 2-back working memory task in participants with mild TBI and balance impairments (n = 7, age 47 ± 15 years) or no balance impairments (n = 7, age 47 ± 15 years). We first identified greater activation in the lateral occipital cortex in the balance impaired group. Second, we observed stronger connectivity of left pre-supplementary motor cortex in the balance impaired group during the working memory task, which was related to decreased activation of regions within the salience and central executive networks and greater suppression of the default mode network. Results suggest a link between impaired balance and modulation of cognitive resources in patients in mTBI. Findings also highlight the potential importance of moving beyond traditional balance assessments towards an integrative assessment of cognition and balance in this population.

The effect of motivation on working memory: an fMRI and SEM study.

PubMed

Szatkowska, Iwona; Bogorodzki, Piotr; Wolak, Tomasz; Marchewka, Artur; Szeszkowski, Wojciech

2008-09-01

This study investigated the effective connectivity between prefrontal regions of human brain supporting motivational influence on working memory. Functional magnetic resonance imaging (fMRI) and structural equation modeling (SEM) were used to examine the interaction between the lateral orbitofrontal (OFC), medial OFC, and dorsolateral prefrontal (DLPFC) regions in the left and right hemisphere during performance of the verbal 2-back working memory task under two reinforcement conditions. The "low-motivation" condition was not associated with monetary reinforcement, while the "high-motivation" condition involved the probability of winning a certain amount of money. In the "low-motivation" condition, the OFC regions in both hemispheres positively influenced the left DLPFC activity. In the "high-motivation" condition, the connectivity in the network including the right OFC regions and left DLPFC changed from positive to negative, whereas the positive connectivity in the network composed of the left OFC and left DLPFC became slightly enhanced compared with the "low-motivation" condition. However, only the connection between the right lateral OFC and left DLPFC showed a significant condition-dependent change in the strength of influence conveyed through the pathway. This change appears to be the functional correlate of motivational influence on verbal working memory.

Psychotic Experiences, Working Memory, and the Developing Brain: A Multimodal Neuroimaging Study

PubMed Central

Fonville, Leon; Cohen Kadosh, Kathrin; Drakesmith, Mark; Dutt, Anirban; Zammit, Stanley; Mollon, Josephine; Reichenberg, Abraham; Lewis, Glyn; Jones, Derek K.; David, Anthony S.

2015-01-01

Psychotic experiences (PEs) occur in the general population, especially in children and adolescents, and are associated with poor psychosocial outcomes, impaired cognition, and increased risk of transition to psychosis. It is unknown how the presence and persistence of PEs during early adulthood affects cognition and brain function. The current study assessed working memory as well as brain function and structure in 149 individuals, with and without PEs, drawn from a population cohort. Observer-rated PEs were classified as persistent or transient on the basis of longitudinal assessments. Working memory was assessed using the n-back task during fMRI. Dynamic causal modeling (DCM) was used to characterize frontoparietal network configuration and voxel-based morphometry was utilized to examine gray matter. Those with persistent, but not transient, PEs performed worse on the n-back task, compared with controls, yet showed no significant differences in regional brain activation or brain structure. DCM analyses revealed greater emphasis on frontal connectivity within a frontoparietal network in those with PEs compared with controls. We propose that these findings portray an altered configuration of working memory function in the brain, potentially indicative of an adaptive response to atypical development associated with the manifestation of PEs. PMID:26286920

An fMRI investigation of cerebellar function during verbal working memory in methadone maintenance patients.

PubMed

Marvel, Cherie L; Faulkner, Monica L; Strain, Eric C; Mintzer, Miriam Z; Desmond, John E

2012-03-01

Working memory is impaired in opioid-dependent individuals, yet the neural underpinnings of working memory in this population are largely unknown. Previous studies in healthy adults have demonstrated that working memory is supported by a network of brain regions that includes a cerebro-cerebellar circuit. The cerebellum, in particular, may be important for inner speech mechanisms that assist verbal working memory. This study used functional magnetic resonance imaging to examine brain activity associated with working memory in five opioid-dependent, methadone-maintained patients and five matched, healthy controls. An item recognition task was administered in two conditions: (1) a low working memory load "match" condition in which participants determined whether target letters presented at the beginning of the trial matched a probe item, and (2) a high working memory load "manipulation" condition in which participants counted two alphabetical letters forward of each of the targets and determined whether either of these new items matched a probe item. Response times and accuracy scores were not significantly different between the groups. FMRI analyses indicated that, in association with higher working memory load ("manipulation" condition), the patient group exhibited hyperactivity in the superior and inferior cerebellum and amygdala relative to that of controls. At a more liberal statistical threshold, patients exhibited hypoactivity in the left prefrontal and medial frontal/pre-SMA regions. These results indicate that verbal working memory in opioid-dependent individuals involves a disrupted cerebro-cerebellar circuit and shed light on the neuroanatomical basis of working memory impairments in this population.

An fMRI Investigation of Cerebellar Function During Verbal Working Memory in Methadone Maintenance Patients

PubMed Central

Marvel, Cherie L.; Faulkner, Monica L.; Strain, Eric C.; Mintzer, Miriam Z.; Desmond, John E.

2011-01-01

Working memory is impaired in opioid-dependent individuals, yet the neural underpinnings of working memory in this population are largely unknown. Previous studies in healthy adults have demonstrated that working memory is supported by a network of brain regions that includes a cerebro-cerebellar circuit. The cerebellum, in particular, may be important for inner speech mechanisms that assist verbal working memory. This study used functional magnetic resonance imaging (fMRI) to examine brain activity associated with working memory in 5 opioid-dependent, methadone-maintained patients and 5 matched, healthy controls. An item recognition task was administered in two conditions: 1) a low working memory load “match” condition in which participants determined whether target letters presented at the beginning of the trial matched a probe item, and 2) a high working memory load “manipulation” condition in which participants counted two alphabetical letters forward of each of the targets and determined whether either of these new items matched a probe item. Response times and accuracy scores were not significantly different between the groups. FMRI analyses indicated that, in association with higher working memory load (“manipulation” condition), the patient group exhibited hyperactivity in the superior and inferior cerebellum and amygdala relative to that of controls. At a more liberal statistical threshold, patients exhibited hypoactivity in the left prefrontal and medial frontal/pre-SMA regions. These results indicate that verbal working memory in opioid-dependent individuals involves a disrupted cerebro-cerebellar circuit, and shed light on the neuroanatomical basis of working memory impairments in this population. PMID:21892700

Think globally and solve locally: secondary memory-based network learning for automated multi-species function prediction

PubMed Central

2014-01-01

Background Network-based learning algorithms for automated function prediction (AFP) are negatively affected by the limited coverage of experimental data and limited a priori known functional annotations. As a consequence their application to model organisms is often restricted to well characterized biological processes and pathways, and their effectiveness with poorly annotated species is relatively limited. A possible solution to this problem might consist in the construction of big networks including multiple species, but this in turn poses challenging computational problems, due to the scalability limitations of existing algorithms and the main memory requirements induced by the construction of big networks. Distributed computation or the usage of big computers could in principle respond to these issues, but raises further algorithmic problems and require resources not satisfiable with simple off-the-shelf computers. Results We propose a novel framework for scalable network-based learning of multi-species protein functions based on both a local implementation of existing algorithms and the adoption of innovative technologies: we solve “locally” the AFP problem, by designing “vertex-centric” implementations of network-based algorithms, but we do not give up thinking “globally” by exploiting the overall topology of the network. This is made possible by the adoption of secondary memory-based technologies that allow the efficient use of the large memory available on disks, thus overcoming the main memory limitations of modern off-the-shelf computers. This approach has been applied to the analysis of a large multi-species network including more than 300 species of bacteria and to a network with more than 200,000 proteins belonging to 13 Eukaryotic species. To our knowledge this is the first work where secondary-memory based network analysis has been applied to multi-species function prediction using biological networks with hundreds of thousands of proteins. Conclusions The combination of these algorithmic and technological approaches makes feasible the analysis of large multi-species networks using ordinary computers with limited speed and primary memory, and in perspective could enable the analysis of huge networks (e.g. the whole proteomes available in SwissProt), using well-equipped stand-alone machines. PMID:24843788

Structural Synaptic Plasticity Has High Memory Capacity and Can Explain Graded Amnesia, Catastrophic Forgetting, and the Spacing Effect

PubMed Central

Knoblauch, Andreas; Körner, Edgar; Körner, Ursula; Sommer, Friedrich T.

2014-01-01

Although already William James and, more explicitly, Donald Hebb's theory of cell assemblies have suggested that activity-dependent rewiring of neuronal networks is the substrate of learning and memory, over the last six decades most theoretical work on memory has focused on plasticity of existing synapses in prewired networks. Research in the last decade has emphasized that structural modification of synaptic connectivity is common in the adult brain and tightly correlated with learning and memory. Here we present a parsimonious computational model for learning by structural plasticity. The basic modeling units are “potential synapses” defined as locations in the network where synapses can potentially grow to connect two neurons. This model generalizes well-known previous models for associative learning based on weight plasticity. Therefore, existing theory can be applied to analyze how many memories and how much information structural plasticity can store in a synapse. Surprisingly, we find that structural plasticity largely outperforms weight plasticity and can achieve a much higher storage capacity per synapse. The effect of structural plasticity on the structure of sparsely connected networks is quite intuitive: Structural plasticity increases the “effectual network connectivity”, that is, the network wiring that specifically supports storage and recall of the memories. Further, this model of structural plasticity produces gradients of effectual connectivity in the course of learning, thereby explaining various cognitive phenomena including graded amnesia, catastrophic forgetting, and the spacing effect. PMID:24858841

Modulating Intrinsic Connectivity: Adjacent Subregions within Supplementary Motor Cortex, Dorsolateral Prefrontal Cortex, and Parietal Cortex Connect to Separate Functional Networks during Task and Also Connect during Rest

PubMed Central

Roth, Jennifer K.; Johnson, Marcia K.; Tokoglu, Fuyuze; Murphy, Isabella; Constable, R. Todd

2014-01-01

Supplementary motor area (SMA), the inferior frontal junction (IFJ), superior frontal junction (SFJ) and parietal cortex are active in many cognitive tasks. In a previous study, we found that subregions of each of these major areas were differentially active in component processes of executive function during working memory tasks. In the present study, each of these subregions was used as a seed in a whole brain functional connectivity analysis of working memory and resting state data. These regions show functional connectivity to different networks, thus supporting the parcellation of these major regions into functional subregions. Many regions showing significant connectivity during the working memory residual data (with task events regressed from the data) were also significantly connected during rest suggesting that these network connections to subregions within major regions of cortex are intrinsic. For some of these connections, task demands modulate activity in these intrinsic networks. Approximately half of the connections significant during task were significant during rest, indicating that some of the connections are intrinsic while others are recruited only in the service of the task. Furthermore, the network connections to traditional ‘task positive’ and ‘task negative’ (a.k.a ‘default mode’) regions shift from positive connectivity to negative connectivity depending on task demands. These findings demonstrate that such task-identified subregions are part of distinct networks, and that these networks have different patterns of connectivity for task as they do during rest, engaging connections both to task positive and task negative regions. These results have implications for understanding the parcellation of commonly active regions into more specific functional networks. PMID:24637793

Neural mechanisms of interference control in working memory capacity.

PubMed

Bomyea, Jessica; Taylor, Charles T; Spadoni, Andrea D; Simmons, Alan N

2018-02-01

The extent to which one can use cognitive resources to keep information in working memory is known to rely on (1) active maintenance of target representations and (2) downregulation of interference from irrelevant representations. Neurobiologically, the global capacity of working memory is thought to depend on the prefrontal and parietal cortices; however, the neural mechanisms involved in controlling interference specifically in working memory capacity tasks remain understudied. In this study, 22 healthy participants completed a modified complex working memory capacity task (Reading Span) with trials of varying levels of interference control demands while undergoing functional MRI. Neural activity associated with interference control demands was examined separately during encoding and recall phases of the task. Results suggested a widespread network of regions in the prefrontal, parietal, and occipital cortices, and the cingulate and cerebellum associated with encoding, and parietal and occipital regions associated with recall. Results align with prior findings emphasizing the importance of frontoparietal circuits for working memory performance, including the role of the inferior frontal gyrus, cingulate, occipital cortex, and cerebellum in regulation of interference demands. © 2017 Wiley Periodicals, Inc.

Dopaminergic contributions to working memory-related brain activation in postmenopausal women.

PubMed

Dumas, Julie A; Filippi, Christopher G; Newhouse, Paul A; Naylor, Magdalena R

2017-02-01

The current study examined the effects of pharmacologic dopaminergic manipulations on working memory-related brain activation in postmenopausal women to further understand the neurochemistry underlying cognition after menopause. Eighteen healthy postmenopausal women, mean age 55.21 years, completed three study days with dopaminergic drug challenges during which they performed a functional magnetic resonance imaging visual verbal N-back test of working memory. Acute stimulation with 1.25 mg oral D2 agonist bromocriptine, acute blockade with 1.5 mg oral haloperidol, and matching placebo were administered randomly and blindly on three study days. We found that dopaminergic stimulation increased activation primarily in the posterior regions of the working memory network compared with dopaminergic blockade using a whole brain cluster-level corrected analysis. The dopaminergic medications did not affect working memory performance. Patterns of increased blood-oxygen-level dependent signal activation after dopaminergic stimulation were found in this study in posterior brain regions with no effect on working memory performance. Further studies should examine specific dopaminergic contributions to brain functioning in healthy postmenopausal women to determine the effects of the increased brain activation on cognition and behavior.

Memory Transformation Enhances Reinforcement Learning in Dynamic Environments.

PubMed

Santoro, Adam; Frankland, Paul W; Richards, Blake A

2016-11-30

Over the course of systems consolidation, there is a switch from a reliance on detailed episodic memories to generalized schematic memories. This switch is sometimes referred to as "memory transformation." Here we demonstrate a previously unappreciated benefit of memory transformation, namely, its ability to enhance reinforcement learning in a dynamic environment. We developed a neural network that is trained to find rewards in a foraging task where reward locations are continuously changing. The network can use memories for specific locations (episodic memories) and statistical patterns of locations (schematic memories) to guide its search. We find that switching from an episodic to a schematic strategy over time leads to enhanced performance due to the tendency for the reward location to be highly correlated with itself in the short-term, but regress to a stable distribution in the long-term. We also show that the statistics of the environment determine the optimal utilization of both types of memory. Our work recasts the theoretical question of why memory transformation occurs, shifting the focus from the avoidance of memory interference toward the enhancement of reinforcement learning across multiple timescales. As time passes, memories transform from a highly detailed state to a more gist-like state, in a process called "memory transformation." Theories of memory transformation speak to its advantages in terms of reducing memory interference, increasing memory robustness, and building models of the environment. However, the role of memory transformation from the perspective of an agent that continuously acts and receives reward in its environment is not well explored. In this work, we demonstrate a view of memory transformation that defines it as a way of optimizing behavior across multiple timescales. Copyright © 2016 the authors 0270-6474/16/3612228-15$15.00/0.

Selective transfer of visual working memory training on Chinese character learning.

PubMed

Opitz, Bertram; Schneiders, Julia A; Krick, Christoph M; Mecklinger, Axel

2014-01-01

Previous research has shown a systematic relationship between phonological working memory capacity and second language proficiency for alphabetic languages. However, little is known about the impact of working memory processes on second language learning in a non-alphabetic language such as Mandarin Chinese. Due to the greater complexity of the Chinese writing system we expect that visual working memory rather than phonological working memory exerts a unique influence on learning Chinese characters. This issue was explored in the present experiment by comparing visual working memory training with an active (auditory working memory training) control condition and a passive, no training control condition. Training induced modulations in language-related brain networks were additionally examined using functional magnetic resonance imaging in a pretest-training-posttest design. As revealed by pre- to posttest comparisons and analyses of individual differences in working memory training gains, visual working memory training led to positive transfer effects on visual Chinese vocabulary learning compared to both control conditions. In addition, we found sustained activation after visual working memory training in the (predominantly visual) left infero-temporal cortex that was associated with behavioral transfer. In the control conditions, activation either increased (active control condition) or decreased (passive control condition) without reliable behavioral transfer effects. This suggests that visual working memory training leads to more efficient processing and more refined responses in brain regions involved in visual processing. Furthermore, visual working memory training boosted additional activation in the precuneus, presumably reflecting mental image generation of the learned characters. We, therefore, suggest that the conjoint activity of the mid-fusiform gyrus and the precuneus after visual working memory training reflects an interaction of working memory and imagery processes with complex visual stimuli that fosters the coherent synthesis of a percept from a complex visual input in service of enhanced Chinese character learning. © 2013 Published by Elsevier Ltd.

Spatial working memory impairment in primary onset middle-age type 2 diabetes mellitus: An ethology and BOLD-fMRI study.

PubMed

Huang, Ran-Ran; Jia, Bao-Hui; Xie, Lei; Ma, Shu-Hua; Yin, Jing-Jing; Sun, Zong-Bo; Le, Hong-Bo; Xu, Wen-Can; Huang, Jin-Zhuang; Luo, Dong-Xue

2016-01-01

To explore mild cognitive dysfunction and/or spatial working memory impairment in patients with primary onset middle-age type 2 diabetes mellitus (T2DM] using ethology (behavior tests) and blood oxygen level-dependent functional magnetic resonance imaging (BOLD-fMRI). Eighteen primary onset T2DM patients and 18 matched subjects with normal blood glucose levels were all tested using the Montreal cognitive assessment scale test, the Wechsler Memory Scale Chinese-revised test, and scanned using BOLD-fMRI (1.5T, EPI sequence) while performing the n-back task to find the activation intensity of some cognition-related areas. The ethology results showed that T2DM patients had a mild cognitive impairment and memory dysfunction (P < 0.05). The fMRI scan identified a neural network consisting of bilateral dorsolateral prefrontal cortex (DLPFC), bilateral premotor area (PreMA), bilateral parietal lobe (PA), and anterior cingulate cortex (ACC) / supplementary motor area (SMA) that was activated during the n-back task, with right hemisphere dominance. However, only the right PA and ACC/SMA showed a load effect via quantitative analysis in the T2DM group; the activation intensity of most working memory-related brain areas for the T2DM group were lower than for the control group under three memory loads. Furthermore, we found that the activation intensity of some cognition-related areas, including the right insular lobe, left caudate nucleus, and bilateral hippocampus/parahippocampal gyrus were lower than the control group under the memory loads. Diabetes-related brain damage of primary onset middle-age T2DM patients with right DLPFC-posterior parietal lobe and parahippocampal gyrus default network causes impairment of spatial working memory and mild cognitive dysfunction. © 2015 Wiley Periodicals, Inc.

Neurophysiological capacity in a working memory task differentiates dependent from nondependent heavy drinkers and controls.

PubMed

Wesley, Michael J; Lile, Joshua A; Fillmore, Mark T; Porrino, Linda J

2017-06-01

Determining the neurobehavioral profiles that differentiate heavy drinkers who are and are not alcohol dependent will inform treatment efforts. Working memory is linked to substance use disorders and can serve as a representation of the demand placed on the neurophysiology associated with cognitive control. Behavior and brain activity (via fMRI) were recorded during an N-Back working memory task in controls (CTRL), nondependent heavy drinkers (A-ND) and dependent heavy drinkers (A-D). Typical and novel step-wise analyses examined profiles of working memory load and increasing task demand, respectively. Performance was significantly decreased in A-D during high working memory load (2-Back), compared to CTRL and A-ND. Analysis of brain activity during high load (0-Back vs. 2- Back) showed greater responses in the dorsal lateral and medial prefrontal cortices of A-D than CTRL, suggesting increased but failed compensation. The step-wise analysis revealed that the transition to Low Demand (0-Back to 1-Back) was associated with robust increases and decreases in cognitive control and default-mode brain regions, respectively, in A-D and A-ND but not CTRL. The transition to High Demand (1-Back to 2-Back) resulted in additional engagement of these networks in A-ND and CTRL, but not A-D. Heavy drinkers engaged working memory neural networks at lower demand than controls. As demand increased, nondependent heavy drinkers maintained control performance but relied on additional neurophysiological resources, and dependent heavy drinkers did not display further resource engagement and had poorer performance. These results support targeting these brain areas for treatment interventions. Copyright © 2017 Elsevier B.V. All rights reserved.

Age, sex, and performance influence the visuospatial working memory network in childhood.

PubMed

Spencer-Smith, Megan; Ritter, Barbara Catherine; Mürner-Lavanchy, Ines; El-Koussy, Marwan; Steinlin, Maja; Everts, Regula

2013-01-01

This study describes the influence of age, sex, and working memory (WM) performance on the visuospatial WM network. Thirty-nine healthy children (7-12 years) completed a dot location functional magnetic resonance imaging (fMRI) task. Percent signal change measured the intensity and laterality indices measured the asymmetry of activation in frontal and parietal brain regions. Old children showed greater intensity of activation in parietal regions than young children but no differences in lateralization were observed. Intensity of activation was similar across sex and WM performance groups. Girls and high WM performers showed more right-sided lateralization of parietal regions than boys and low WM performers.

Working Memory and Decision-Making in a Frontoparietal Circuit Model

PubMed Central

2017-01-01

Working memory (WM) and decision-making (DM) are fundamental cognitive functions involving a distributed interacting network of brain areas, with the posterior parietal cortex (PPC) and prefrontal cortex (PFC) at the core. However, the shared and distinct roles of these areas and the nature of their coordination in cognitive function remain poorly understood. Biophysically based computational models of cortical circuits have provided insights into the mechanisms supporting these functions, yet they have primarily focused on the local microcircuit level, raising questions about the principles for distributed cognitive computation in multiregional networks. To examine these issues, we developed a distributed circuit model of two reciprocally interacting modules representing PPC and PFC circuits. The circuit architecture includes hierarchical differences in local recurrent structure and implements reciprocal long-range projections. This parsimonious model captures a range of behavioral and neuronal features of frontoparietal circuits across multiple WM and DM paradigms. In the context of WM, both areas exhibit persistent activity, but, in response to intervening distractors, PPC transiently encodes distractors while PFC filters distractors and supports WM robustness. With regard to DM, the PPC module generates graded representations of accumulated evidence supporting target selection, while the PFC module generates more categorical responses related to action or choice. These findings suggest computational principles for distributed, hierarchical processing in cortex during cognitive function and provide a framework for extension to multiregional models. SIGNIFICANCE STATEMENT Working memory and decision-making are fundamental “building blocks” of cognition, and deficits in these functions are associated with neuropsychiatric disorders such as schizophrenia. These cognitive functions engage distributed networks with prefrontal cortex (PFC) and posterior parietal cortex (PPC) at the core. It is not clear, however, what the contributions of PPC and PFC are in light of the computations that subserve working memory and decision-making. We constructed a biophysical model of a reciprocally connected frontoparietal circuit that revealed shared and distinct functions for the PFC and PPC across working memory and decision-making tasks. Our parsimonious model connects circuit-level properties to cognitive functions and suggests novel design principles beyond those of local circuits for cognitive processing in multiregional brain networks. PMID:29114071

Working Memory and Decision-Making in a Frontoparietal Circuit Model.

PubMed

Murray, John D; Jaramillo, Jorge; Wang, Xiao-Jing

2017-12-13

Working memory (WM) and decision-making (DM) are fundamental cognitive functions involving a distributed interacting network of brain areas, with the posterior parietal cortex (PPC) and prefrontal cortex (PFC) at the core. However, the shared and distinct roles of these areas and the nature of their coordination in cognitive function remain poorly understood. Biophysically based computational models of cortical circuits have provided insights into the mechanisms supporting these functions, yet they have primarily focused on the local microcircuit level, raising questions about the principles for distributed cognitive computation in multiregional networks. To examine these issues, we developed a distributed circuit model of two reciprocally interacting modules representing PPC and PFC circuits. The circuit architecture includes hierarchical differences in local recurrent structure and implements reciprocal long-range projections. This parsimonious model captures a range of behavioral and neuronal features of frontoparietal circuits across multiple WM and DM paradigms. In the context of WM, both areas exhibit persistent activity, but, in response to intervening distractors, PPC transiently encodes distractors while PFC filters distractors and supports WM robustness. With regard to DM, the PPC module generates graded representations of accumulated evidence supporting target selection, while the PFC module generates more categorical responses related to action or choice. These findings suggest computational principles for distributed, hierarchical processing in cortex during cognitive function and provide a framework for extension to multiregional models. SIGNIFICANCE STATEMENT Working memory and decision-making are fundamental "building blocks" of cognition, and deficits in these functions are associated with neuropsychiatric disorders such as schizophrenia. These cognitive functions engage distributed networks with prefrontal cortex (PFC) and posterior parietal cortex (PPC) at the core. It is not clear, however, what the contributions of PPC and PFC are in light of the computations that subserve working memory and decision-making. We constructed a biophysical model of a reciprocally connected frontoparietal circuit that revealed shared and distinct functions for the PFC and PPC across working memory and decision-making tasks. Our parsimonious model connects circuit-level properties to cognitive functions and suggests novel design principles beyond those of local circuits for cognitive processing in multiregional brain networks. Copyright © 2017 the authors 0270-6474/17/3712167-20$15.00/0.

Effects of Ganglioside on Working Memory and the Default Mode Network in Individuals with Subjective Cognitive Impairment: A Randomized Controlled Trial.

PubMed

Jeon, Yujin; Kim, Binna; Kim, Jieun E; Kim, Bori R; Ban, Soonhyun; Jeong, Jee Hyang; Kwon, Oran; Rhie, Sandy Jeong; Ahn, Chang-Won; Kim, Jong-Hoon; Jung, Sung Ug; Park, Soo-Hyun; Lyoo, In Kyoon; Yoon, Sujung

2016-01-01

This randomized, double-blind, placebo-controlled trial examined whether the administration of ganglioside, an active ingredient of deer bone extract, can improve working memory performance by increasing gray matter volume and functional connectivity in the default mode network (DMN) in individuals with subjective cognitive impairment. Seventy-five individuals with subjective cognitive impairment were chosen to receive either ganglioside (330[Formula: see text][Formula: see text]g/day or 660[Formula: see text][Formula: see text]g/day) or a placebo for 8 weeks. Changes in working memory performance with treatment of either ganglioside or placebo were assessed as cognitive outcome measures. Using voxel-based morphometry and functional connectivity analyses, changes in gray matter volume and functional connectivity in the DMN were also assessed as brain outcome measures. Improvement in working memory performance was greater in the ganglioside group than in the placebo group. The ganglioside group, relative to the placebo group, showed greater increases in gray matter volume and functional connectivity in the DMN. A significant relationship between increased functional connectivity of the precuneus and improved working memory performance was observed in the ganglioside group. The current findings suggest that ganglioside has cognitive-enhancing effects in individuals with subjective cognitive impairment. Ganglioside-induced increases in gray matter volume and functional connectivity in the DMN may partly be responsible for the potential nootropic effects of ganglioside. The clinical trial was registered with ClinicalTrials.gov (identifier: NCT02379481).

Cognitive components of a mathematical processing network in 9-year-old children.

PubMed

Szűcs, Dénes; Devine, Amy; Soltesz, Fruzsina; Nobes, Alison; Gabriel, Florence

2014-07-01

We determined how various cognitive abilities, including several measures of a proposed domain-specific number sense, relate to mathematical competence in nearly 100 9-year-old children with normal reading skill. Results are consistent with an extended number processing network and suggest that important processing nodes of this network are phonological processing, verbal knowledge, visuo-spatial short-term and working memory, spatial ability and general executive functioning. The model was highly specific to predicting arithmetic performance. There were no strong relations between mathematical achievement and verbal short-term and working memory, sustained attention, response inhibition, finger knowledge and symbolic number comparison performance. Non-verbal intelligence measures were also non-significant predictors when added to our model. Number sense variables were non-significant predictors in the model and they were also non-significant predictors when entered into regression analysis with only a single visuo-spatial WM measure. Number sense variables were predicted by sustained attention. Results support a network theory of mathematical competence in primary school children and falsify the importance of a proposed modular 'number sense'. We suggest an 'executive memory function centric' model of mathematical processing. Mapping a complex processing network requires that studies consider the complex predictor space of mathematics rather than just focusing on a single or a few explanatory factors.

Cognitive components of a mathematical processing network in 9-year-old children

PubMed Central

Szűcs, Dénes; Devine, Amy; Soltesz, Fruzsina; Nobes, Alison; Gabriel, Florence

2014-01-01

We determined how various cognitive abilities, including several measures of a proposed domain-specific number sense, relate to mathematical competence in nearly 100 9-year-old children with normal reading skill. Results are consistent with an extended number processing network and suggest that important processing nodes of this network are phonological processing, verbal knowledge, visuo-spatial short-term and working memory, spatial ability and general executive functioning. The model was highly specific to predicting arithmetic performance. There were no strong relations between mathematical achievement and verbal short-term and working memory, sustained attention, response inhibition, finger knowledge and symbolic number comparison performance. Non-verbal intelligence measures were also non-significant predictors when added to our model. Number sense variables were non-significant predictors in the model and they were also non-significant predictors when entered into regression analysis with only a single visuo-spatial WM measure. Number sense variables were predicted by sustained attention. Results support a network theory of mathematical competence in primary school children and falsify the importance of a proposed modular ‘number sense’. We suggest an ‘executive memory function centric’ model of mathematical processing. Mapping a complex processing network requires that studies consider the complex predictor space of mathematics rather than just focusing on a single or a few explanatory factors. PMID:25089322

Unraveling Network-induced Memory Contention: Deeper Insights with Machine Learning

DOE PAGES

Groves, Taylor Liles; Grant, Ryan; Gonzales, Aaron; ...

2017-11-21

Remote Direct Memory Access (RDMA) is expected to be an integral communication mechanism for future exascale systems enabling asynchronous data transfers, so that applications may fully utilize CPU resources while simultaneously sharing data amongst remote nodes. We examine Network-induced Memory Contention (NiMC) on Infiniband networks. We expose the interactions between RDMA, main-memory and cache, when applications and out-of-band services compete for memory resources. We then explore NiMCs resulting impact on application-level performance. For a range of hardware technologies and HPC workloads, we quantify NiMC and show that NiMCs impact grows with scale resulting in up to 3X performance degradation atmore » scales as small as 8K processes even in applications that previously have been shown to be performance resilient in the presence of noise. In addition, this work examines the problem of predicting NiMC's impact on applications by leveraging machine learning and easily accessible performance counters. This approach provides additional insights about the root cause of NiMC and facilitates dynamic selection of potential solutions. Finally, we evaluated three potential techniques to reduce NiMCs impact, namely hardware offloading, core reservation and network throttling.« less

Unraveling Network-induced Memory Contention: Deeper Insights with Machine Learning

DOE Office of Scientific and Technical Information (OSTI.GOV)

Groves, Taylor Liles; Grant, Ryan; Gonzales, Aaron

Remote Direct Memory Access (RDMA) is expected to be an integral communication mechanism for future exascale systems enabling asynchronous data transfers, so that applications may fully utilize CPU resources while simultaneously sharing data amongst remote nodes. We examine Network-induced Memory Contention (NiMC) on Infiniband networks. We expose the interactions between RDMA, main-memory and cache, when applications and out-of-band services compete for memory resources. We then explore NiMCs resulting impact on application-level performance. For a range of hardware technologies and HPC workloads, we quantify NiMC and show that NiMCs impact grows with scale resulting in up to 3X performance degradation atmore » scales as small as 8K processes even in applications that previously have been shown to be performance resilient in the presence of noise. In addition, this work examines the problem of predicting NiMC's impact on applications by leveraging machine learning and easily accessible performance counters. This approach provides additional insights about the root cause of NiMC and facilitates dynamic selection of potential solutions. Finally, we evaluated three potential techniques to reduce NiMCs impact, namely hardware offloading, core reservation and network throttling.« less

Associations Between White Matter Microstructure and Infants’ Working Memory

PubMed Central

Short, Sarah J.; Elison, Jed T.; Goldman, Barbara Davis; Styner, Martin; Gu, Hongbin; Connelly, Mark; Maltbie, Eric; Woolson, Sandra; Lin, Weili; Gerig, Guido; Reznick, J. Steven; Gilmore, John H.

2013-01-01

Working memory emerges in infancy and plays a privileged role in subsequent adaptive cognitive development. The neural networks important for the development of working memory during infancy remain unknown. We used diffusion tensor imaging (DTI) and deterministic fiber tracking to characterize the microstructure of white matter fiber bundles hypothesized to support working memory in 12-month-old infants (n=73). Here we show robust associations between infants’ visuospatial working memory performance and microstructural characteristics of widespread white matter. Significant associations were found for white matter tracts that connect brain regions known to support working memory in older children and adults (genu, anterior and superior thalamic radiations, anterior cingulum, arcuate fasciculus, and the temporal-parietal segment). Better working memory scores were associated with higher FA and lower RD values in these selected white matter tracts. These tract-specific brain-behavior relationships accounted for a significant amount of individual variation above and beyond infants’ gestational age and developmental level, as measured with the Mullen Scales of Early Learning. Working memory was not associated with global measures of brain volume, as expected, and few associations were found between working memory and control white matter tracts. To our knowledge, this study is among the first demonstrations of brain-behavior associations in infants using quantitative tractography. The ability to characterize subtle individual differences in infant brain development associated with complex cognitive functions holds promise for improving our understanding of normative development, biomarkers of risk, experience-dependent learning and neuro-cognitive periods of developmental plasticity. PMID:22989623

Autoassociative memory retrieval and spontaneous activity bumps in small-world networks of integrate-and-fire neurons.

PubMed

Anishchenko, Anastasia; Treves, Alessandro

2006-10-01

The metric structure of synaptic connections is obviously an important factor in shaping the properties of neural networks, in particular the capacity to retrieve memories, with which are endowed autoassociative nets operating via attractor dynamics. Qualitatively, some real networks in the brain could be characterized as 'small worlds', in the sense that the structure of their connections is intermediate between the extremes of an orderly geometric arrangement and of a geometry-independent random mesh. Small worlds can be defined more precisely in terms of their mean path length and clustering coefficient; but is such a precise description useful for a better understanding of how the type of connectivity affects memory retrieval? We have simulated an autoassociative memory network of integrate-and-fire units, positioned on a ring, with the network connectivity varied parametrically between ordered and random. We find that the network retrieves previously stored memory patterns when the connectivity is close to random, and displays the characteristic behavior of ordered nets (localized 'bumps' of activity) when the connectivity is close to ordered. Recent analytical work shows that these two behaviors can coexist in a network of simple threshold-linear units, leading to localized retrieval states. We find that they tend to be mutually exclusive behaviors, however, with our integrate-and-fire units. Moreover, the transition between the two occurs for values of the connectivity parameter which are not simply related to the notion of small worlds.

Externally induced frontoparietal synchronization modulates network dynamics and enhances working memory performance.

PubMed

Violante, Ines R; Li, Lucia M; Carmichael, David W; Lorenz, Romy; Leech, Robert; Hampshire, Adam; Rothwell, John C; Sharp, David J

2017-03-14

Cognitive functions such as working memory (WM) are emergent properties of large-scale network interactions. Synchronisation of oscillatory activity might contribute to WM by enabling the coordination of long-range processes. However, causal evidence for the way oscillatory activity shapes network dynamics and behavior in humans is limited. Here we applied transcranial alternating current stimulation (tACS) to exogenously modulate oscillatory activity in a right frontoparietal network that supports WM. Externally induced synchronization improved performance when cognitive demands were high. Simultaneously collected fMRI data reveals tACS effects dependent on the relative phase of the stimulation and the internal cognitive processing state. Specifically, synchronous tACS during the verbal WM task increased parietal activity, which correlated with behavioral performance. Furthermore, functional connectivity results indicate that the relative phase of frontoparietal stimulation influences information flow within the WM network. Overall, our findings demonstrate a link between behavioral performance in a demanding WM task and large-scale brain synchronization.

Externally induced frontoparietal synchronization modulates network dynamics and enhances working memory performance

PubMed Central

Violante, Ines R; Li, Lucia M; Carmichael, David W; Lorenz, Romy; Leech, Robert; Hampshire, Adam; Rothwell, John C; Sharp, David J

2017-01-01

Cognitive functions such as working memory (WM) are emergent properties of large-scale network interactions. Synchronisation of oscillatory activity might contribute to WM by enabling the coordination of long-range processes. However, causal evidence for the way oscillatory activity shapes network dynamics and behavior in humans is limited. Here we applied transcranial alternating current stimulation (tACS) to exogenously modulate oscillatory activity in a right frontoparietal network that supports WM. Externally induced synchronization improved performance when cognitive demands were high. Simultaneously collected fMRI data reveals tACS effects dependent on the relative phase of the stimulation and the internal cognitive processing state. Specifically, synchronous tACS during the verbal WM task increased parietal activity, which correlated with behavioral performance. Furthermore, functional connectivity results indicate that the relative phase of frontoparietal stimulation influences information flow within the WM network. Overall, our findings demonstrate a link between behavioral performance in a demanding WM task and large-scale brain synchronization. DOI: http://dx.doi.org/10.7554/eLife.22001.001 PMID:28288700

Sharp wave/ripple network oscillations and learning-associated hippocampal maps.

PubMed

Csicsvari, Jozsef; Dupret, David

2014-02-05

Sharp wave/ripple (SWR, 150-250 Hz) hippocampal events have long been postulated to be involved in memory consolidation. However, more recent work has investigated SWRs that occur during active waking behaviour: findings that suggest that SWRs may also play a role in cell assembly strengthening or spatial working memory. Do such theories of SWR function apply to animal learning? This review discusses how general theories linking SWRs to memory-related function may explain circuit mechanisms related to rodent spatial learning and to the associated stabilization of new cognitive maps.

Real-time fMRI training-induced changes in regional connectivity mediating verbal working memory behavioral performance.

PubMed

Shen, J; Zhang, G; Yao, L; Zhao, X

2015-03-19

Working memory refers to the ability to temporarily store and manipulate information that is necessary for complex cognition activities. Previous studies have demonstrated that working memory capacity can be improved by behavioral training, and brain activities in the frontal and parietal cortices and the connections between these regions are also altered by training. Our recent neurofeedback training has proven that the regulation of the left dorsal lateral prefrontal cortex (DLPFC) activity using real-time functional magnetic resonance imaging (rtfMRI) can improve working memory performance. However, how working memory training promotes interaction between brain regions and whether this promotion correlates with performance improvement remain unclear. In this study, we employed structural equation modeling (SEM) to calculate the interactions between the regions within the working memory network during neurofeedback training. The results revealed that the direct effect of the frontoparietal connection in the left hemisphere was enhanced by the rtfMRI training. Specifically, the increase in the path from the left DLPFC to the left inferior parietal lobule (IPL) was positively correlated with improved performance in verbal working memory. These findings demonstrate the important role of the frontoparietal connection in working memory training and suggest that increases in frontoparietal connectivity might be a key factor associated with behavioral improvement. Copyright © 2015 IBRO. Published by Elsevier Ltd. All rights reserved.

From sensorimotor learning to memory cells in prefrontal and temporal association cortex: a neurocomputational study of disembodiment.

PubMed

Pulvermüller, Friedemann; Garagnani, Max

2014-08-01

Memory cells, the ultimate neurobiological substrates of working memory, remain active for several seconds and are most commonly found in prefrontal cortex and higher multisensory areas. However, if correlated activity in "embodied" sensorimotor systems underlies the formation of memory traces, why should memory cells emerge in areas distant from their antecedent activations in sensorimotor areas, thus leading to "disembodiment" (movement away from sensorimotor systems) of memory mechanisms? We modelled the formation of memory circuits in six-area neurocomputational architectures, implementing motor and sensory primary, secondary and higher association areas in frontotemporal cortices along with known between-area neuroanatomical connections. Sensorimotor learning driven by Hebbian neuroplasticity led to formation of cell assemblies distributed across the different areas of the network. These action-perception circuits (APCs) ignited fully when stimulated, thus providing a neural basis for long-term memory (LTM) of sensorimotor information linked by learning. Subsequent to ignition, activity vanished rapidly from APC neurons in sensorimotor areas but persisted in those in multimodal prefrontal and temporal areas. Such persistent activity provides a mechanism for working memory for actions, perceptions and symbols, including short-term phonological and semantic storage. Cell assembly ignition and "disembodied" working memory retreat of activity to multimodal areas are documented in the neurocomputational models' activity dynamics, at the level of single cells, circuits, and cortical areas. Memory disembodiment is explained neuromechanistically by APC formation and structural neuroanatomical features of the model networks, especially the central role of multimodal prefrontal and temporal cortices in bridging between sensory and motor areas. These simulations answer the "where" question of cortical working memory in terms of distributed APCs and their inner structure, which is, in part, determined by neuroanatomical structure. As the neurocomputational model provides a mechanistic explanation of how memory-related "disembodied" neuronal activity emerges in "embodied" APCs, it may be key to solving aspects of the embodiment debate and eventually to a better understanding of cognitive brain functions. Copyright © 2014 The Authors. Published by Elsevier Ltd.. All rights reserved.

Functional networks in parallel with cortical development associate with executive functions in children.

PubMed

Zhong, Jidan; Rifkin-Graboi, Anne; Ta, Anh Tuan; Yap, Kar Lai; Chuang, Kai-Hsiang; Meaney, Michael J; Qiu, Anqi

2014-07-01

Children begin performing similarly to adults on tasks requiring executive functions in late childhood, a transition that is probably due to neuroanatomical fine-tuning processes, including myelination and synaptic pruning. In parallel to such structural changes in neuroanatomical organization, development of functional organization may also be associated with cognitive behaviors in children. We examined 6- to 10-year-old children's cortical thickness, functional organization, and cognitive performance. We used structural magnetic resonance imaging (MRI) to identify areas with cortical thinning, resting-state fMRI to identify functional organization in parallel to cortical development, and working memory/response inhibition tasks to assess executive functioning. We found that neuroanatomical changes in the form of cortical thinning spread over bilateral frontal, parietal, and occipital regions. These regions were engaged in 3 functional networks: sensorimotor and auditory, executive control, and default mode network. Furthermore, we found that working memory and response inhibition only associated with regional functional connectivity, but not topological organization (i.e., local and global efficiency of information transfer) of these functional networks. Interestingly, functional connections associated with "bottom-up" as opposed to "top-down" processing were more clearly related to children's performance on working memory and response inhibition, implying an important role for brain systems involved in late childhood. © The Author 2013. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Entanglement of spin waves among four quantum memories.

PubMed

Choi, K S; Goban, A; Papp, S B; van Enk, S J; Kimble, H J

2010-11-18

Quantum networks are composed of quantum nodes that interact coherently through quantum channels, and open a broad frontier of scientific opportunities. For example, a quantum network can serve as a 'web' for connecting quantum processors for computation and communication, or as a 'simulator' allowing investigations of quantum critical phenomena arising from interactions among the nodes mediated by the channels. The physical realization of quantum networks generically requires dynamical systems capable of generating and storing entangled states among multiple quantum memories, and efficiently transferring stored entanglement into quantum channels for distribution across the network. Although such capabilities have been demonstrated for diverse bipartite systems, entangled states have not been achieved for interconnects capable of 'mapping' multipartite entanglement stored in quantum memories to quantum channels. Here we demonstrate measurement-induced entanglement stored in four atomic memories; user-controlled, coherent transfer of the atomic entanglement to four photonic channels; and characterization of the full quadripartite entanglement using quantum uncertainty relations. Our work therefore constitutes an advance in the distribution of multipartite entanglement across quantum networks. We also show that our entanglement verification method is suitable for studying the entanglement order of condensed-matter systems in thermal equilibrium.

Abnormal interactions of verbal- and spatial-memory networks in young people at familial high-risk for schizophrenia.

PubMed

Li, Xiaobo; Thermenos, Heidi W; Wu, Ziyan; Momura, Yoko; Wu, Kai; Keshavan, Matcheri; Seidman, Lawrence; DeLisi, Lynn E

2016-10-01

Working memory impairment (especially in verbal and spatial domains) is the core neurocognitive impairment in schizophrenia and the familial high-risk (FHR) population. Inconsistent results have been reported in clinical and neuroimaging studies examining the verbal- and spatial-memory deficits in the FHR subjects, due to sample differences and lack of understanding on interactions of the brain regions for processing verbal- and spatial-working memory. Functional MRI data acquired during a verbal- vs. spatial-memory task were included from 51 young adults [26 FHR and 25 controls]. Group comparisons were conducted in brain activation patterns responding to 1) verbal-memory condition (A), 2) spatial-memory condition (B), 3) verbal higher than spatial (A-B), 4) spatial higher than verbal (B-A), 5) conjunction of brain regions that were activated during both A and B (A∧B). Group difference of the laterality index (LI) in inferior frontal lobe for condition A was also assessed. Compared to controls, the FHR group exhibited significantly decreased brain activity in left inferior frontal during A, and significantly stronger involvement of ACC, PCC, paracentral gyrus for the contrast of A-B. The LI showed a trend of reduced left-higher-than-right pattern for verbal-memory processing in the HR group. Our findings suggest that in the entire functional brain network for working-memory processing, verbal information processing associated brain pathways are significantly altered in people at familial high risk for developing schizophrenia. Future studies will need to examine whether these alterations may indicate vulnerability for predicting the onset of Schizophrenia. Copyright © 2016 Elsevier B.V. All rights reserved.

Free-Space Quantum Communication with a Portable Quantum Memory

NASA Astrophysics Data System (ADS)

Namazi, Mehdi; Vallone, Giuseppe; Jordaan, Bertus; Goham, Connor; Shahrokhshahi, Reihaneh; Villoresi, Paolo; Figueroa, Eden

2017-12-01

The realization of an elementary quantum network that is intrinsically secure and operates over long distances requires the interconnection of several quantum modules performing different tasks. In this work, we report the realization of a communication network functioning in a quantum regime, consisting of four different quantum modules: (i) a random polarization qubit generator, (ii) a free-space quantum-communication channel, (iii) an ultralow-noise portable quantum memory, and (iv) a qubit decoder, in a functional elementary quantum network possessing all capabilities needed for quantum-information distribution protocols. We create weak coherent pulses at the single-photon level encoding polarization states |H ⟩ , |V ⟩, |D ⟩, and |A ⟩ in a randomized sequence. The random qubits are sent over a free-space link and coupled into a dual-rail room-temperature quantum memory and after storage and retrieval are analyzed in a four-detector polarization analysis akin to the requirements of the BB84 protocol. We also show ultralow noise and fully portable operation, paving the way towards memory-assisted all-environment free-space quantum cryptographic networks.

Neural Correlates Associated with Successful Working Memory Performance in Older Adults as Revealed by Spatial ICA

PubMed Central

Saliasi, Emi; Geerligs, Linda; Lorist, Monicque M.; Maurits, Natasha M.

2014-01-01

To investigate which neural correlates are associated with successful working memory performance, fMRI was recorded in healthy younger and older adults during performance on an n-back task with varying task demands. To identify functional networks supporting working memory processes, we used independent component analysis (ICA) decomposition of the fMRI data. Compared to younger adults, older adults showed a larger neural (BOLD) response in the more complex (2-back) than in the baseline (0-back) task condition, in the ventral lateral prefrontal cortex (VLPFC) and in the right fronto-parietal network (FPN). Our results indicated that a higher BOLD response in the VLPFC was associated with increased performance accuracy in older adults, in both the baseline and the more complex task condition. This ‘BOLD-performance’ relationship suggests that the neural correlates linked with successful performance in the older adults are not uniquely related to specific working memory processes present in the complex but not in the baseline task condition. Furthermore, the selective presence of this relationship in older but not in younger adults suggests that increased neural activity in the VLPFC serves a compensatory role in the aging brain which benefits task performance in the elderly. PMID:24911016

Visual Working Memory Load-Related Changes in Neural Activity and Functional Connectivity

PubMed Central

Li, Ling; Zhang, Jin-Xiang; Jiang, Tao

2011-01-01

Background Visual working memory (VWM) helps us store visual information to prepare for subsequent behavior. The neuronal mechanisms for sustaining coherent visual information and the mechanisms for limited VWM capacity have remained uncharacterized. Although numerous studies have utilized behavioral accuracy, neural activity, and connectivity to explore the mechanism of VWM retention, little is known about the load-related changes in functional connectivity for hemi-field VWM retention. Methodology/Principal Findings In this study, we recorded electroencephalography (EEG) from 14 normal young adults while they performed a bilateral visual field memory task. Subjects had more rapid and accurate responses to the left visual field (LVF) memory condition. The difference in mean amplitude between the ipsilateral and contralateral event-related potential (ERP) at parietal-occipital electrodes in retention interval period was obtained with six different memory loads. Functional connectivity between 128 scalp regions was measured by EEG phase synchronization in the theta- (4–8 Hz), alpha- (8–12 Hz), beta- (12–32 Hz), and gamma- (32–40 Hz) frequency bands. The resulting matrices were converted to graphs, and mean degree, clustering coefficient and shortest path length was computed as a function of memory load. The results showed that brain networks of theta-, alpha-, beta-, and gamma- frequency bands were load-dependent and visual-field dependent. The networks of theta- and alpha- bands phase synchrony were most predominant in retention period for right visual field (RVF) WM than for LVF WM. Furthermore, only for RVF memory condition, brain network density of theta-band during the retention interval were linked to the delay of behavior reaction time, and the topological property of alpha-band network was negative correlation with behavior accuracy. Conclusions/Significance We suggest that the differences in theta- and alpha- bands between LVF and RVF conditions in functional connectivity and topological properties during retention period may result in the decline of behavioral performance in RVF task. PMID:21789253

Brain Networks for Working Memory and Factors of Intelligence Assessed in Males and Females with fMRI and DTI

ERIC Educational Resources Information Center

Tang, C. Y.; Eaves, E. L.; Ng, J. C.; Carpenter, D. M.; Mai, X.; Schroeder, D. H.; Condon, C. A.; Colom, R.; Haier, R. J.

2010-01-01

Neuro-imaging studies of intelligence implicate the importance of a parietal-frontal network. One unresolved issue is whether this network underlies a general factor of intelligence ("g") or other specific cognitive factors. A second unresolved issue is whether males and females use different parts of this network. Here we obtained intelligence…

Carrying the past to the future: Distinct brain networks underlie individual differences in human spatial working memory capacity.

PubMed

Liu, Siwei; Poh, Jia-Hou; Koh, Hui Li; Ng, Kwun Kei; Loke, Yng Miin; Lim, Joseph Kai Wei; Chong, Joanna Su Xian; Zhou, Juan

2018-08-01

Spatial working memory (SWM) relies on the interplay of anatomically separated and interconnected large-scale brain networks. EEG studies often observe load-associated sustained negative activity during SWM retention. Yet, whether and how such sustained negative activity in retention relates to network-specific functional activation/deactivation and relates to individual differences in SWM capacity remain to be elucidated. To cover these gaps, we recorded concurrent EEG-fMRI data in 70 healthy young adults during the Sternberg delayed-match-to-sample SWM task with three memory load levels. To a subset of participants (N = 28) that performed the task properly and had artefact-free fMRI and EEG data, we employed a novel temporo-spatial principal component analysis to derive load-dependent negative slow wave (NSW) from retention-related event-related potentials. The associations between NSW responses with SWM capacity were divergent in the higher (N = 14) and lower (N = 14) SWM capacity groups. Specifically, larger load-related increase in NSW amplitude was associated with greater SWM capacity for the higher capacity group but lower SWM capacity for the lower capacity group. Furthermore, for the higher capacity group, larger NSW amplitude was related to greater activation in bilateral parietal areas of the fronto-parietal network (FPN) and greater deactivation in medial frontal gyrus and posterior mid-cingulate cortex of the default mode network (DMN) during retention. In contrast, the lower capacity group did not show similar pattern. Instead, greater NSW was linked to higher deactivation in right posterior middle temporal gyrus. Our findings shed light on the possible differential EEG-informed neural network mechanism during memory maintenance underlying individual differences in SWM capacity. Copyright © 2018 Elsevier Inc. All rights reserved.

Functional connectivity pattern during rest within the episodic memory network in association with episodic memory performance in bipolar disorder.

PubMed

Oertel-Knöchel, Viola; Reinke, Britta; Matura, Silke; Prvulovic, David; Linden, David E J; van de Ven, Vincent

2015-02-28

In this study, we sought to examine the intrinsic functional organization of the episodic memory network during rest in bipolar disorder (BD). The previous work suggests that deficits in intrinsic functional connectivity may account for impaired memory performance. We hypothesized that regions involved in episodic memory processing would reveal aberrant functional connectivity in patients with bipolar disorder. We examined 21 patients with BD and 21 healthy matched controls who underwent functional magnetic resonance imaging (fMRI) during a resting condition. We did a seed-based functional connectivity analysis (SBA), using the regions of the episodic memory network that showed a significantly different activation pattern during task-related fMRI as seeds. The functional connectivity scores (FC) were further correlated with episodic memory task performance. Our results revealed decreased FC scores within frontal areas and between frontal and temporal/hippocampal/limbic regions in BD patients in comparison with controls. We observed higher FC in BD patients compared with controls between frontal and limbic regions. The decrease in fronto-frontal functional connectivity in BD patients showed a significant positive association with episodic memory performance. The association between task-independent dysfunctional frontal-limbic FC and episodic memory performance may be relevant for current pathophysiological models of the disease. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

EEG-based research on brain functional networks in cognition.

PubMed

Wang, Niannian; Zhang, Li; Liu, Guozhong

2015-01-01

Recently, exploring the cognitive functions of the brain by establishing a network model to understand the working mechanism of the brain has become a popular research topic in the field of neuroscience. In this study, electroencephalography (EEG) was used to collect data from subjects given four different mathematical cognitive tasks: recite numbers clockwise and counter-clockwise, and letters clockwise and counter-clockwise to build a complex brain function network (BFN). By studying the connectivity features and parameters of those brain functional networks, it was found that the average clustering coefficient is much larger than its corresponding random network and the average shortest path length is similar to the corresponding random networks, which clearly shows the characteristics of the small-world network. The brain regions stimulated during the experiment are consistent with traditional cognitive science regarding learning, memory, comprehension, and other rational judgment results. The new method of complex networking involves studying the mathematical cognitive process of reciting, providing an effective research foundation for exploring the relationship between brain cognition and human learning skills and memory. This could help detect memory deficits early in young and mentally handicapped children, and help scientists understand the causes of cognitive brain disorders.

Optimizing NEURON Simulation Environment Using Remote Memory Access with Recursive Doubling on Distributed Memory Systems.

PubMed

Shehzad, Danish; Bozkuş, Zeki

2016-01-01

Increase in complexity of neuronal network models escalated the efforts to make NEURON simulation environment efficient. The computational neuroscientists divided the equations into subnets amongst multiple processors for achieving better hardware performance. On parallel machines for neuronal networks, interprocessor spikes exchange consumes large section of overall simulation time. In NEURON for communication between processors Message Passing Interface (MPI) is used. MPI_Allgather collective is exercised for spikes exchange after each interval across distributed memory systems. The increase in number of processors though results in achieving concurrency and better performance but it inversely affects MPI_Allgather which increases communication time between processors. This necessitates improving communication methodology to decrease the spikes exchange time over distributed memory systems. This work has improved MPI_Allgather method using Remote Memory Access (RMA) by moving two-sided communication to one-sided communication, and use of recursive doubling mechanism facilitates achieving efficient communication between the processors in precise steps. This approach enhanced communication concurrency and has improved overall runtime making NEURON more efficient for simulation of large neuronal network models.

Optimizing NEURON Simulation Environment Using Remote Memory Access with Recursive Doubling on Distributed Memory Systems

PubMed Central

Bozkuş, Zeki

2016-01-01

Increase in complexity of neuronal network models escalated the efforts to make NEURON simulation environment efficient. The computational neuroscientists divided the equations into subnets amongst multiple processors for achieving better hardware performance. On parallel machines for neuronal networks, interprocessor spikes exchange consumes large section of overall simulation time. In NEURON for communication between processors Message Passing Interface (MPI) is used. MPI_Allgather collective is exercised for spikes exchange after each interval across distributed memory systems. The increase in number of processors though results in achieving concurrency and better performance but it inversely affects MPI_Allgather which increases communication time between processors. This necessitates improving communication methodology to decrease the spikes exchange time over distributed memory systems. This work has improved MPI_Allgather method using Remote Memory Access (RMA) by moving two-sided communication to one-sided communication, and use of recursive doubling mechanism facilitates achieving efficient communication between the processors in precise steps. This approach enhanced communication concurrency and has improved overall runtime making NEURON more efficient for simulation of large neuronal network models. PMID:27413363

Dopaminergic contributions to working memory-related brain activation in postmenopausal women

PubMed Central

Dumas, Julie A.; Filippi, Christopher G.; Newhouse, Paul A.; Naylor, Magdalena R.

2016-01-01

Objective The current study examined the effects of pharmacologic dopaminergic manipulations on working memory-related brain activation in postmenopausal women to further understand the neurochemistry underlying cognition after menopause. Method Eighteen healthy postmenopausal women, mean age 55.21 years, completed three study days with dopaminergic drug challenges during which they performed an fMRI visual verbal N-back test of working memory. Acute stimulation with 1.25 mg oral D2 agonist bromocriptine, acute blockade with 1.5 mg oral haloperidol, and matching placebo were administered randomly and blindly on three study days. Results We found that dopaminergic stimulation increased activation primarily in the posterior regions of the working memory network compared to dopaminergic blockade using a whole brain cluster-level corrected analysis. The dopaminergic medications did not affect working memory performance. Conclusions Patterns of increased BOLD signal activation after dopaminergic stimulation were found in this study in posterior brain regions with no effect on working memory performance. Further studies should examine specific dopaminergic contributions to brain functioning in healthy postmenopausal women in order to determine the effects of the increased brain activation on cognition and behavior. PMID:27676634

Running wheel training does not change neurogenesis levels or alter working memory tasks in adult rats

PubMed Central

Rojas, Manuel J.; Cardenas P., Fernando

2017-01-01

Background Exercise can change cellular structure and connectivity (neurogenesis or synaptogenesis), causing alterations in both behavior and working memory. The aim of this study was to evaluate the effect of exercise on working memory and hippocampal neurogenesis in adult male Wistar rats using a T-maze test. Methods An experimental design with two groups was developed: the experimental group (n = 12) was subject to a forced exercise program for five days, whereas the control group (n = 9) stayed in the home cage. Six to eight weeks after training, the rats’ working memory was evaluated in a T-maze test and four choice days were analyzed, taking into account alternation as a working memory indicator. Hippocampal neurogenesis was evaluated by means of immunohistochemistry of BrdU positive cells. Results No differences between groups were found in the behavioral variables (alternation, preference index, time of response, time of trial or feeding), or in the levels of BrdU positive cells. Discussion Results suggest that although exercise may have effects on brain structure, a construct such as working memory may require more complex changes in networks or connections to demonstrate a change at behavioral level. PMID:28503368

Network resiliency through memory health monitoring and proactive management

DOEpatents

Andrade Costa, Carlos H.; Cher, Chen-Yong; Park, Yoonho; Rosenburg, Bryan S.; Ryu, Kyung D.

2017-11-21

A method for managing a network queue memory includes receiving sensor information about the network queue memory, predicting a memory failure in the network queue memory based on the sensor information, and outputting a notification through a plurality of nodes forming a network and using the network queue memory, the notification configuring communications between the nodes.

Altered intrinsic and extrinsic connectivity in schizophrenia.

PubMed

Zhou, Yuan; Zeidman, Peter; Wu, Shihao; Razi, Adeel; Chen, Cheng; Yang, Liuqing; Zou, Jilin; Wang, Gaohua; Wang, Huiling; Friston, Karl J

2018-01-01

Schizophrenia is a disorder characterized by functional dysconnectivity among distributed brain regions. However, it is unclear how causal influences among large-scale brain networks are disrupted in schizophrenia. In this study, we used dynamic causal modeling (DCM) to assess the hypothesis that there is aberrant directed (effective) connectivity within and between three key large-scale brain networks (the dorsal attention network, the salience network and the default mode network) in schizophrenia during a working memory task. Functional MRI data during an n-back task from 40 patients with schizophrenia and 62 healthy controls were analyzed. Using hierarchical modeling of between-subject effects in DCM with Parametric Empirical Bayes, we found that intrinsic (within-region) and extrinsic (between-region) effective connectivity involving prefrontal regions were abnormal in schizophrenia. Specifically, in patients (i) inhibitory self-connections in prefrontal regions of the dorsal attention network were decreased across task conditions; (ii) extrinsic connectivity between regions of the default mode network was increased; specifically, from posterior cingulate cortex to the medial prefrontal cortex; (iii) between-network extrinsic connections involving the prefrontal cortex were altered; (iv) connections within networks and between networks were correlated with the severity of clinical symptoms and impaired cognition beyond working memory. In short, this study revealed the predominance of reduced synaptic efficacy of prefrontal efferents and afferents in the pathophysiology of schizophrenia.

The effects of working memory training on functional brain network efficiency.

PubMed

Langer, Nicolas; von Bastian, Claudia C; Wirz, Helen; Oberauer, Klaus; Jäncke, Lutz

2013-10-01

The human brain is a highly interconnected network. Recent studies have shown that the functional and anatomical features of this network are organized in an efficient small-world manner that confers high efficiency of information processing at relatively low connection cost. However, it has been unclear how the architecture of functional brain networks is related to performance in working memory (WM) tasks and if these networks can be modified by WM training. Therefore, we conducted a double-blind training study enrolling 66 young adults. Half of the subjects practiced three WM tasks and were compared to an active control group practicing three tasks with low WM demand. High-density resting-state electroencephalography (EEG) was recorded before and after training to analyze graph-theoretical functional network characteristics at an intracortical level. WM performance was uniquely correlated with power in the theta frequency, and theta power was increased by WM training. Moreover, the better a person's WM performance, the more their network exhibited small-world topology. WM training shifted network characteristics in the direction of high performers, showing increased small-worldness within a distributed fronto-parietal network. Taken together, this is the first longitudinal study that provides evidence for the plasticity of the functional brain network underlying WM. Copyright © 2013 Elsevier Ltd. All rights reserved.

The effect of rehearsal rate and memory load on verbal working memory.

PubMed

Fegen, David; Buchsbaum, Bradley R; D'Esposito, Mark

2015-01-15

While many neuroimaging studies have investigated verbal working memory (WM) by manipulating memory load, the subvocal rehearsal rate at these various memory loads has generally been left uncontrolled. Therefore, the goal of this study was to investigate how mnemonic load and the rate of subvocal rehearsal modulate patterns of activity in the core neural circuits underlying verbal working memory. Using fMRI in healthy subjects, we orthogonally manipulated subvocal rehearsal rate and memory load in a verbal WM task with long 45-s delay periods. We found that middle frontal gyrus (MFG) and superior parietal lobule (SPL) exhibited memory load effects primarily early in the delay period and did not exhibit rehearsal rate effects. In contrast, we found that inferior frontal gyrus (IFG), premotor cortex (PM) and Sylvian-parietal-temporal region (area Spt) exhibited approximately linear memory load and rehearsal rate effects, with rehearsal rate effects lasting through the entire delay period. These results indicate that IFG, PM and area Spt comprise the core articulatory rehearsal areas involved in verbal WM, while MFG and SPL are recruited in a general supervisory role once a memory load threshold in the core rehearsal network has been exceeded. Copyright © 2014 Elsevier Inc. All rights reserved.

The Effect of Rehearsal Rate and Memory Load on Verbal Working Memory

PubMed Central

Fegen, David; Buchsbaum, Bradley R.; D’Esposito, Mark

2014-01-01

While many neuroimaging studies have investigated verbal working memory (WM) by manipulating memory load, the subvocal rehearsal rate at these various memory loads has generally been left uncontrolled. Therefore, the goal of this study was to investigate how mnemonic load and the rate of subvocal rehearsal modulate patterns of activity in the core neural circuits underlying verbal working memory. Using fMRI in healthy subjects, we orthogonally manipulated subvocal rehearsal rate and memory load in a verbal WM task with long 45-second delay periods. We found that middle frontal gyrus (MFG) and superior parietal lobule (SPL) exhibited memory load effects primarily early in the delay period and did not exhibit rehearsal rate effects. In contrast, we found that inferior frontal gyrus (IFG), premotor cortex (PM) and Sylvian-parietal-temporal region (area Spt) exhibited approximately linear memory load and rehearsal rate effects, with rehearsal rate effects lasting through the entire delay period. These results indicate that IFG, PM and area Spt comprise the core articulatory rehearsal areas involved in verbal WM, while MFG and SPL are recruited in a general supervisory role once a memory load threshold in the core rehearsal network has been exceeded. PMID:25467303

Reorganization of Functional Networks in Verbal Working Memory Circuitry in Early Midlife: The Impact of Sex and Menopausal Status.

PubMed

Jacobs, Emily G; Weiss, Blair; Makris, Nikos; Whitfield-Gabrieli, Sue; Buka, Stephen L; Klibanski, Anne; Goldstein, Jill M

2017-05-01

Converging preclinical and human evidence indicates that the decline in ovarian estradiol production during the menopausal transition may play a mechanistic role in the neuronal changes that occur early in the aging process. Here, we present findings from a population-based fMRI study characterizing regional and network-level differences in working memory (WM) circuitry in midlife men and women (N = 142; age range 46-53), as a function of sex and reproductive stage. Reproductive histories and hormonal evaluations were used to determine menopausal status. Participants performed a verbal WM task during fMRI scanning. Results revealed robust differences in task-evoked responses in dorsolateral prefrontal cortex and hippocampus as a function of women's reproductive stage, despite minimal variance in chronological age. Sex differences in regional activity and functional connectivity that were pronounced between men and premenopausal women were diminished for postmenopausal women. Critically, analyzing data without regard to sex or reproductive status obscured group differences in the circuit-level neural strategies associated with successful working memory performance. These findings underscore the importance of reproductive age and hormonal status, over and above chronological age, for understanding sex differences in the aging of memory circuitry. Further, these findings suggest that early changes in working memory circuitry are evident decades before the age range typically targeted in cognitive aging studies. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Robust image retrieval from noisy inputs using lattice associative memories

NASA Astrophysics Data System (ADS)

Urcid, Gonzalo; Nieves-V., José Angel; García-A., Anmi; Valdiviezo-N., Juan Carlos

2009-02-01

Lattice associative memories also known as morphological associative memories are fully connected feedforward neural networks with no hidden layers, whose computation at each node is carried out with lattice algebra operations. These networks are a relatively recent development in the field of associative memories that has proven to be an alternative way to work with sets of pattern pairs for which the storage and retrieval stages use minimax algebra. Different associative memory models have been proposed to cope with the problem of pattern recall under input degradations, such as occlusions or random noise, where input patterns can be composed of binary or real valued entries. In comparison to these and other artificial neural network memories, lattice algebra based memories display better performance for storage and recall capability; however, the computational techniques devised to achieve that purpose require additional processing or provide partial success when inputs are presented with undetermined noise levels. Robust retrieval capability of an associative memory model is usually expressed by a high percentage of perfect recalls from non-perfect input. The procedure described here uses noise masking defined by simple lattice operations together with appropriate metrics, such as the normalized mean squared error or signal to noise ratio, to boost the recall performance of either the min or max lattice auto-associative memories. Using a single lattice associative memory, illustrative examples are given that demonstrate the enhanced retrieval of correct gray-scale image associations from inputs corrupted with random noise.

Verbal Working Memory Is Related to the Acquisition of Cross-Linguistic Phonological Regularities.

PubMed

Bosma, Evelyn; Heeringa, Wilbert; Hoekstra, Eric; Versloot, Arjen; Blom, Elma

2017-01-01

Closely related languages share cross-linguistic phonological regularities, such as Frisian -âld [ͻ:t] and Dutch -oud [ʱut], as in the cognate pairs kâld [kͻ:t] - koud [kʱut] 'cold' and wâld [wͻ:t] - woud [wʱut] 'forest'. Within Bybee's (1995, 2001, 2008, 2010) network model, these regularities are, just like grammatical rules within a language, generalizations that emerge from schemas of phonologically and semantically related words. Previous research has shown that verbal working memory is related to the acquisition of grammar, but not vocabulary. This suggests that verbal working memory supports the acquisition of linguistic regularities. In order to test this hypothesis we investigated whether verbal working memory is also related to the acquisition of cross-linguistic phonological regularities. For three consecutive years, 5- to 8-year-old Frisian-Dutch bilingual children ( n = 120) were tested annually on verbal working memory and a Frisian receptive vocabulary task that comprised four cognate categories: (1) identical cognates, (2) non-identical cognates that either do or (3) do not exhibit a phonological regularity between Frisian and Dutch, and (4) non-cognates. The results showed that verbal working memory had a significantly stronger effect on cognate category (2) than on the other three cognate categories. This suggests that verbal working memory is related to the acquisition of cross-linguistic phonological regularities. More generally, it confirms the hypothesis that verbal working memory plays a role in the acquisition of linguistic regularities.

Livermore Big Artificial Neural Network Toolkit

DOE Office of Scientific and Technical Information (OSTI.GOV)

Essen, Brian Van; Jacobs, Sam; Kim, Hyojin

2016-07-01

LBANN is a toolkit that is designed to train artificial neural networks efficiently on high performance computing architectures. It is optimized to take advantages of key High Performance Computing features to accelerate neural network training. Specifically it is optimized for low-latency, high bandwidth interconnects, node-local NVRAM, node-local GPU accelerators, and high bandwidth parallel file systems. It is built on top of the open source Elemental distributed-memory dense and spars-direct linear algebra and optimization library that is released under the BSD license. The algorithms contained within LBANN are drawn from the academic literature and implemented to work within a distributed-memory framework.

Processing of visual semantic information to concrete words: temporal dynamics and neural mechanisms indicated by event-related brain potentials( ).

PubMed

van Schie, Hein T; Wijers, Albertus A; Mars, Rogier B; Benjamins, Jeroen S; Stowe, Laurie A

2005-05-01

Event-related brain potentials were used to study the retrieval of visual semantic information to concrete words, and to investigate possible structural overlap between visual object working memory and concreteness effects in word processing. Subjects performed an object working memory task that involved 5 s retention of simple 4-angled polygons (load 1), complex 10-angled polygons (load 2), and a no-load baseline condition. During the polygon retention interval subjects were presented with a lexical decision task to auditory presented concrete (imageable) and abstract (nonimageable) words, and pseudowords. ERP results are consistent with the use of object working memory for the visualisation of concrete words. Our data indicate a two-step processing model of visual semantics in which visual descriptive information of concrete words is first encoded in semantic memory (indicated by an anterior N400 and posterior occipital positivity), and is subsequently visualised via the network for object working memory (reflected by a left frontal positive slow wave and a bilateral occipital slow wave negativity). Results are discussed in the light of contemporary models of semantic memory.

Architecture of fluid intelligence and working memory revealed by lesion mapping.

PubMed

Barbey, Aron K; Colom, Roberto; Paul, Erick J; Grafman, Jordan

2014-03-01

Although cognitive neuroscience has made valuable progress in understanding the role of the prefrontal cortex in human intelligence, the functional networks that support adaptive behavior and novel problem solving remain to be well characterized. Here, we studied 158 human brain lesion patients to investigate the cognitive and neural foundations of key competencies for fluid intelligence and working memory. We administered a battery of neuropsychological tests, including the Wechsler Adult Intelligence Scale (WAIS) and the N-Back task. Latent variable modeling was applied to obtain error-free scores of fluid intelligence and working memory, followed by voxel-based lesion-symptom mapping to elucidate their neural substrates. The observed latent variable modeling and lesion results support an integrative framework for understanding the architecture of fluid intelligence and working memory and make specific recommendations for the interpretation and application of the WAIS and N-Back task to the study of fluid intelligence in health and disease.

Memory consolidation from seconds to weeks: a three-stage neural network model with autonomous reinstatement dynamics

PubMed Central

Fiebig, Florian; Lansner, Anders

2014-01-01

Declarative long-term memories are not created in an instant. Gradual stabilization and temporally shifting dependence of acquired declarative memories in different brain regions—called systems consolidation—can be tracked in time by lesion experiments. The observation of temporally graded retrograde amnesia (RA) following hippocampal lesions points to a gradual transfer of memory from hippocampus to neocortical long-term memory. Spontaneous reactivations of hippocampal memories, as observed in place cell reactivations during slow-wave-sleep, are supposed to drive neocortical reinstatements and facilitate this process. We propose a functional neural network implementation of these ideas and furthermore suggest an extended three-state framework that includes the prefrontal cortex (PFC). It bridges the temporal chasm between working memory percepts on the scale of seconds and consolidated long-term memory on the scale of weeks or months. We show that our three-stage model can autonomously produce the necessary stochastic reactivation dynamics for successful episodic memory consolidation. The resulting learning system is shown to exhibit classical memory effects seen in experimental studies, such as retrograde and anterograde amnesia (AA) after simulated hippocampal lesioning; furthermore the model reproduces peculiar biological findings on memory modulation, such as retrograde facilitation of memory after suppressed acquisition of new long-term memories—similar to the effects of benzodiazepines on memory. PMID:25071536

Cerebral networks of sustained attention and working memory: a functional magnetic resonance imaging study based on the Continuous Performance Test.

PubMed

Bartés-Serrallonga, M; Adan, A; Solé-Casals, J; Caldú, X; Falcón, C; Pérez-Pàmies, M; Bargalló, N; Serra-Grabulosa, J M

2014-04-01

One of the most used paradigms in the study of attention is the Continuous Performance Test (CPT). The identical pairs version (CPT-IP) has been widely used to evaluate attention deficits in developmental, neurological and psychiatric disorders. However, the specific locations and the relative distribution of brain activation in networks identified with functional imaging, varies significantly with differences in task design. To design a task to evaluate sustained attention using functional magnetic resonance imaging (fMRI), and thus to provide data for research concerned with the role of these functions. Forty right-handed, healthy students (50% women; age range: 18-25 years) were recruited. A CPT-IP implemented as a block design was used to assess sustained attention during the fMRI session. The behavioural results from the CPT-IP task showed a good performance in all subjects, higher than 80% of hits. fMRI results showed that the used CPT-IP task activates a network of frontal, parietal and occipital areas, and that these are related to executive and attentional functions. In relation to the use of the CPT to study of attention and working memory, this task provides normative data in healthy adults, and it could be useful to evaluate disorders which have attentional and working memory deficits.

Iterative free-energy optimization for recurrent neural networks (INFERNO).

PubMed

Pitti, Alexandre; Gaussier, Philippe; Quoy, Mathias

2017-01-01

The intra-parietal lobe coupled with the Basal Ganglia forms a working memory that demonstrates strong planning capabilities for generating robust yet flexible neuronal sequences. Neurocomputational models however, often fails to control long range neural synchrony in recurrent spiking networks due to spontaneous activity. As a novel framework based on the free-energy principle, we propose to see the problem of spikes' synchrony as an optimization problem of the neurons sub-threshold activity for the generation of long neuronal chains. Using a stochastic gradient descent, a reinforcement signal (presumably dopaminergic) evaluates the quality of one input vector to move the recurrent neural network to a desired activity; depending on the error made, this input vector is strengthened to hill-climb the gradient or elicited to search for another solution. This vector can be learned then by one associative memory as a model of the basal-ganglia to control the recurrent neural network. Experiments on habit learning and on sequence retrieving demonstrate the capabilities of the dual system to generate very long and precise spatio-temporal sequences, above two hundred iterations. Its features are applied then to the sequential planning of arm movements. In line with neurobiological theories, we discuss its relevance for modeling the cortico-basal working memory to initiate flexible goal-directed neuronal chains of causation and its relation to novel architectures such as Deep Networks, Neural Turing Machines and the Free-Energy Principle.

Working memory network alterations in high-functioning adolescents with an autism spectrum disorder.

PubMed

Barendse, Evelien M; Schreuder, Lisanne J; Thoonen, Geert; Hendriks, Marc P H; Kessels, Roy P C; Backes, Walter H; Aldenkamp, Albert P; Jansen, Jacobus F A

2018-02-01

People with autism spectrum disorder (ASD) typically have deficits in the working memory (WM) system. WM is found to be an essential chain in successfully navigating in the social world. We hypothesize that brain networks for WM have an altered network integrity in ASD compared to controls. Thirteen adolescents (one female) with autistic disorder (n = 1), Asperger's disorder (n = 7), or pervasive developmental disorder not otherwise specified (n = 5), and 13 typically developing healthy control adolescents (one female) participated in this study. Functional magnetic resonance imaging (MRI) was performed using an n-back task and in resting state. The analysis of the behavioral data revealed deficits in WM performance in ASD, but only when tested to the limit. Adolescents with ASD showed lower binary global efficiency in the WM network than the healthy control group with n-back and resting-state data. This correlated with diagnostic scores for total problems, reciprocity, and language. Adolescents with higher-functioning autism have difficulty with the WM system, which is typically compensated. Functional MRI markers of brain network organization in ASD are related to characteristics of autism as represented in diagnostic scores. Therefore, functional MRI provides neuronal correlates for memory difficulties in adolescents with ASD. © 2017 The Authors. Psychiatry and Clinical Neurosciences published by John Wiley & Sons Australia, Ltd on behalf of Japanese Society of Psychiatry and Neurology.

Auditory short-term memory in the primate auditory cortex

PubMed Central

Scott, Brian H.; Mishkin, Mortimer

2015-01-01

Sounds are fleeting, and assembling the sequence of inputs at the ear into a coherent percept requires auditory memory across various time scales. Auditory short-term memory comprises at least two components: an active ‘working memory’ bolstered by rehearsal, and a sensory trace that may be passively retained. Working memory relies on representations recalled from long-term memory, and their rehearsal may require phonological mechanisms unique to humans. The sensory component, passive short-term memory (pSTM), is tractable to study in nonhuman primates, whose brain architecture and behavioral repertoire are comparable to our own. This review discusses recent advances in the behavioral and neurophysiological study of auditory memory with a focus on single-unit recordings from macaque monkeys performing delayed-match-to-sample (DMS) tasks. Monkeys appear to employ pSTM to solve these tasks, as evidenced by the impact of interfering stimuli on memory performance. In several regards, pSTM in monkeys resembles pitch memory in humans, and may engage similar neural mechanisms. Neural correlates of DMS performance have been observed throughout the auditory and prefrontal cortex, defining a network of areas supporting auditory STM with parallels to that supporting visual STM. These correlates include persistent neural firing, or a suppression of firing, during the delay period of the memory task, as well as suppression or (less commonly) enhancement of sensory responses when a sound is repeated as a ‘match’ stimulus. Auditory STM is supported by a distributed temporo-frontal network in which sensitivity to stimulus history is an intrinsic feature of auditory processing. PMID:26541581

Response control networks are selectively modulated by attention to rare events and memory load regardless of the need for inhibition.

PubMed

Wijeakumar, Sobanawartiny; Magnotta, Vincent A; Buss, Aaron T; Ambrose, Joseph P; Wifall, Timothy A; Hazeltine, Eliot; Spencer, John P

2015-10-15

Recent evidence has sparked debate about the neural bases of response selection and inhibition. In the current study, we employed two reactive inhibition tasks, the Go/Nogo (GnG) and Simon tasks, to examine questions central to these debates. First, we investigated whether a fronto-cortical-striatal system was sensitive to the need for inhibition per se or the presentation of infrequent stimuli, by manipulating the proportion of trials that do not require inhibition (Go/Compatible trials) relative to trials that require inhibition (Nogo/Incompatible trials). A cortico-subcortical network composed of insula, putamen, and thalamus showed greater activation on salient and infrequent events, regardless of the need for inhibition. Thus, consistent with recent findings, key parts of the fronto-cortical-striatal system are engaged by salient events and do not appear to play a selective role in response inhibition. Second, we examined how the fronto-cortical-striatal system is modulated by working memory demands by varying the number of stimulus-response (SR) mappings. Right inferior parietal lobule showed decreasing activation as the number of SR mappings increased, suggesting that a form of associative memory - rather than working memory - might underlie performance in these tasks. A broad motor planning and control network showed similar trends that were also modulated by the number of motor responses required in each task. Finally, bilateral lingual gyri were more robustly engaged in the Simon task, consistent with the role of this area in shifts of visuo-spatial attention. The current study sheds light on how the fronto-cortical-striatal network is selectively engaged in reactive control tasks and how control is modulated by manipulations of attention and memory load. Copyright © 2015 Elsevier Inc. All rights reserved.

Spike frequency adaptation is a possible mechanism for control of attractor preference in auto-associative neural networks

NASA Astrophysics Data System (ADS)

Roach, James; Sander, Leonard; Zochowski, Michal

Auto-associative memory is the ability to retrieve a pattern from a small fraction of the pattern and is an important function of neural networks. Within this context, memories that are stored within the synaptic strengths of networks act as dynamical attractors for network firing patterns. In networks with many encoded memories, some attractors will be stronger than others. This presents the problem of how networks switch between attractors depending on the situation. We suggest that regulation of neuronal spike-frequency adaptation (SFA) provides a universal mechanism for network-wide attractor selectivity. Here we demonstrate in a Hopfield type attractor network that neurons minimal SFA will reliably activate in the pattern corresponding to a local attractor and that a moderate increase in SFA leads to the network to converge to the strongest attractor state. Furthermore, we show that on long time scales SFA allows for temporal sequences of activation to emerge. Finally, using a model of cholinergic modulation within the cortex we argue that dynamic regulation of attractor preference by SFA could be critical for the role of acetylcholine in attention or for arousal states in general. This work was supported by: NSF Graduate Research Fellowship Program under Grant No. DGE 1256260 (JPR), NSF CMMI 1029388 (MRZ) and NSF PoLS 1058034 (MRZ & LMS).

Comprehension and Navigation of Networked Hypertexts

ERIC Educational Resources Information Center

Blom, Helen; Segers, Eliane; Knoors, Harry; Hermans, Daan; Verhoeven, Ludo

2018-01-01

This study aims to investigate secondary school students' reading comprehension and navigation of networked hypertexts with and without a graphic overview compared to linear digital texts. Additionally, it was studied whether prior knowledge, vocabulary, verbal, and visual working memory moderated the relation between text design and…

Ghosts in the Machine II: Neural Correlates of Memory Interference from the Previous Trial.

PubMed

Papadimitriou, Charalampos; White, Robert L; Snyder, Lawrence H

2017-04-01

Previous memoranda interfere with working memory. For example, spatial memories are biased toward locations memorized on the previous trial. We predicted, based on attractor network models of memory, that activity in the frontal eye fields (FEFs) encoding a previous target location can persist into the subsequent trial and that this ghost will then bias the readout of the current target. Contrary to this prediction, we find that FEF memory representations appear biased away from (not toward) the previous target location. The behavioral and neural data can be reconciled by a model in which receptive fields of memory neurons converge toward remembered locations, much as receptive fields converge toward attended locations. Convergence increases the resources available to encode the relevant memoranda and decreases overall error in the network, but the residual convergence from the previous trial can give rise to an attractive behavioral bias on the next trial. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Working memory load modulation of parieto-frontal connections: evidence from dynamic causal modeling

PubMed Central

Ma, Liangsuo; Steinberg, Joel L.; Hasan, Khader M.; Narayana, Ponnada A.; Kramer, Larry A.; Moeller, F. Gerard

2011-01-01

Previous neuroimaging studies have shown that working memory load has marked effects on regional neural activation. However, the mechanism through which working memory load modulates brain connectivity is still unclear. In this study, this issue was addressed using dynamic causal modeling (DCM) based on functional magnetic resonance imaging (fMRI) data. Eighteen normal healthy subjects were scanned while they performed a working memory task with variable memory load, as parameterized by two levels of memory delay and three levels of digit load (number of digits presented in each visual stimulus). Eight regions of interest, i.e., bilateral middle frontal gyrus (MFG), anterior cingulate cortex (ACC), inferior frontal cortex (IFC), and posterior parietal cortex (PPC), were chosen for DCM analyses. Analysis of the behavioral data during the fMRI scan revealed that accuracy decreased as digit load increased. Bayesian inference on model structure indicated that a bilinear DCM in which memory delay was the driving input to bilateral PPC and in which digit load modulated several parieto-frontal connections was the optimal model. Analysis of model parameters showed that higher digit load enhanced connection from L PPC to L IFC, and lower digit load inhibited connection from R PPC to L ACC. These findings suggest that working memory load modulates brain connectivity in a parieto-frontal network, and may reflect altered neuronal processes, e.g., information processing or error monitoring, with the change in working memory load. PMID:21692148

Multi-voxel pattern classification differentiates personally experienced event memories from secondhand event knowledge.

PubMed

Chow, Tiffany E; Westphal, Andrew J; Rissman, Jesse

2018-04-11

Studies of autobiographical memory retrieval often use photographs to probe participants' memories for past events. Recent neuroimaging work has shown that viewing photographs depicting events from one's own life evokes a characteristic pattern of brain activity across a network of frontal, parietal, and medial temporal lobe regions that can be readily distinguished from brain activity associated with viewing photographs from someone else's life (Rissman, Chow, Reggente, and Wagner, 2016). However, it is unclear whether the neural signatures associated with remembering a personally experienced event are distinct from those associated with recognizing previously encountered photographs of an event. The present experiment used a novel functional magnetic resonance imaging (fMRI) paradigm to investigate putative differences in brain activity patterns associated with these distinct expressions of memory retrieval. Eighteen participants wore necklace-mounted digital cameras to capture events from their everyday lives over the course of three weeks. One week later, participants underwent fMRI scanning, where on each trial they viewed a sequence of photographs depicting either an event from their own life or from another participant's life and judged their memory for this event. Importantly, half of the trials featured photographic sequences that had been shown to participants during a laboratory session administered the previous day. Multi-voxel pattern analyses assessed the sensitivity of two brain networks of interest-as identified by a meta-analysis of prior autobiographical and laboratory-based memory retrieval studies-to the original source of the photographs (own life or other's life) and their experiential history as stimuli (previewed or non-previewed). The classification analyses revealed a striking dissociation: activity patterns within the autobiographical memory network were significantly more diagnostic than those within the laboratory-based network as to whether photographs depicted one's own personal experience (regardless of whether they had been previously seen), whereas activity patterns within the laboratory-based memory network were significantly more diagnostic than those within the autobiographical memory network as to whether photographs had been previewed (regardless of whether they were from the participant's own life). These results, also apparent in whole-brain searchlight classifications, provide evidence for dissociable patterns of activation across two putative memory networks as a function of whether real-world photographs trigger the retrieval of firsthand experiences or secondhand event knowledge. Copyright © 2018 Elsevier Inc. All rights reserved.

Abnormal neural activation patterns underlying working memory impairment in chronic phencyclidine-treated mice.

PubMed

Arime, Yosefu; Akiyama, Kazufumi

2017-01-01

Working memory impairment is a hallmark feature of schizophrenia and is thought be caused by dysfunctions in the prefrontal cortex (PFC) and associated brain regions. However, the neural circuit anomalies underlying this impairment are poorly understood. The aim of this study is to assess working memory performance in the chronic phencyclidine (PCP) mouse model of schizophrenia, and to identify the neural substrates of working memory. To address this issue, we conducted the following experiments for mice after withdrawal from chronic administration (14 days) of either saline or PCP (10 mg/kg): (1) a discrete paired-trial variable-delay task in T-maze to assess working memory, and (2) brain-wide c-Fos mapping to identify activated brain regions relevant to this task performance either 90 min or 0 min after the completion of the task, with each time point examined under working memory effort and basal conditions. Correct responses in the test phase of the task were significantly reduced across delays (5, 15, and 30 s) in chronic PCP-treated mice compared with chronic saline-treated controls, suggesting delay-independent impairments in working memory in the PCP group. In layer 2-3 of the prelimbic cortex, the number of working memory effort-elicited c-Fos+ cells was significantly higher in the chronic PCP group than in the chronic saline group. The main effect of working memory effort relative to basal conditions was to induce significantly increased c-Fos+ cells in the other layers of prelimbic cortex and the anterior cingulate and infralimbic cortex regardless of the different chronic regimens. Conversely, this working memory effort had a negative effect (fewer c-Fos+ cells) in the ventral hippocampus. These results shed light on some putative neural networks relevant to working memory impairments in mice chronically treated with PCP, and emphasize the importance of the layer 2-3 of the prelimbic cortex of the PFC.

Abnormal neural activation patterns underlying working memory impairment in chronic phencyclidine-treated mice

PubMed Central

Akiyama, Kazufumi

2017-01-01

Working memory impairment is a hallmark feature of schizophrenia and is thought be caused by dysfunctions in the prefrontal cortex (PFC) and associated brain regions. However, the neural circuit anomalies underlying this impairment are poorly understood. The aim of this study is to assess working memory performance in the chronic phencyclidine (PCP) mouse model of schizophrenia, and to identify the neural substrates of working memory. To address this issue, we conducted the following experiments for mice after withdrawal from chronic administration (14 days) of either saline or PCP (10 mg/kg): (1) a discrete paired-trial variable-delay task in T-maze to assess working memory, and (2) brain-wide c-Fos mapping to identify activated brain regions relevant to this task performance either 90 min or 0 min after the completion of the task, with each time point examined under working memory effort and basal conditions. Correct responses in the test phase of the task were significantly reduced across delays (5, 15, and 30 s) in chronic PCP-treated mice compared with chronic saline-treated controls, suggesting delay-independent impairments in working memory in the PCP group. In layer 2–3 of the prelimbic cortex, the number of working memory effort-elicited c-Fos+ cells was significantly higher in the chronic PCP group than in the chronic saline group. The main effect of working memory effort relative to basal conditions was to induce significantly increased c-Fos+ cells in the other layers of prelimbic cortex and the anterior cingulate and infralimbic cortex regardless of the different chronic regimens. Conversely, this working memory effort had a negative effect (fewer c-Fos+ cells) in the ventral hippocampus. These results shed light on some putative neural networks relevant to working memory impairments in mice chronically treated with PCP, and emphasize the importance of the layer 2–3 of the prelimbic cortex of the PFC. PMID:29253020

Stochastic Dynamics Underlying Cognitive Stability and Flexibility

PubMed Central

Ueltzhöffer, Kai; Armbruster-Genç, Diana J. N.; Fiebach, Christian J.

2015-01-01

Cognitive stability and flexibility are core functions in the successful pursuit of behavioral goals. While there is evidence for a common frontoparietal network underlying both functions and for a key role of dopamine in the modulation of flexible versus stable behavior, the exact neurocomputational mechanisms underlying those executive functions and their adaptation to environmental demands are still unclear. In this work we study the neurocomputational mechanisms underlying cue based task switching (flexibility) and distractor inhibition (stability) in a paradigm specifically designed to probe both functions. We develop a physiologically plausible, explicit model of neural networks that maintain the currently active task rule in working memory and implement the decision process. We simplify the four-choice decision network to a nonlinear drift-diffusion process that we canonically derive from a generic winner-take-all network model. By fitting our model to the behavioral data of individual subjects, we can reproduce their full behavior in terms of decisions and reaction time distributions in baseline as well as distractor inhibition and switch conditions. Furthermore, we predict the individual hemodynamic response timecourse of the rule-representing network and localize it to a frontoparietal network including the inferior frontal junction area and the intraparietal sulcus, using functional magnetic resonance imaging. This refines the understanding of task-switch-related frontoparietal brain activity as reflecting attractor-like working memory representations of task rules. Finally, we estimate the subject-specific stability of the rule-representing attractor states in terms of the minimal action associated with a transition between different rule states in the phase-space of the fitted models. This stability measure correlates with switching-specific thalamocorticostriatal activation, i.e., with a system associated with flexible working memory updating and dopaminergic modulation of cognitive flexibility. These results show that stochastic dynamical systems can implement the basic computations underlying cognitive stability and flexibility and explain neurobiological bases of individual differences. PMID:26068119

Verbal working memory-related neural network communication in schizophrenia.

PubMed

Kustermann, Thomas; Popov, Tzvetan; Miller, Gregory A; Rockstroh, Brigitte

2018-04-19

Impaired working memory (WM) in schizophrenia is associated with reduced hemodynamic and electromagnetic activity and altered network connectivity within and between memory-associated neural networks. The present study sought to determine whether schizophrenia involves disruption of a frontal-parietal network normally supporting WM and/or involvement of another brain network. Nineteen schizophrenia patients (SZ) and 19 healthy comparison subjects (HC) participated in a cued visual-verbal Sternberg task while dense-array EEG was recorded. A pair of item arrays each consisting of 2-4 consonants was presented bilaterally for 200 ms with a prior cue signaling the hemifield of the task-relevant WM set. A central probe letter 2,000 ms later prompted a choice reaction time decision about match/mismatch with the target WM set. Group and WM load effects on time domain and time-frequency domain 11-15 Hz alpha power were assessed for the cue-to-probe time window, and posterior 11-15 Hz alpha power and frontal 4-8 Hz theta power were assessed during the retention period. Directional connectivity was estimated via Granger causality, evaluating group differences in communication. SZ showed slower responding, lower accuracy, smaller overall time-domain alpha power increase, and less load-dependent alpha power increase. Midline frontal theta power increases did not vary by group or load. Network communication in SZ was characterized by temporal-to-posterior information flow, in contrast to bidirectional temporal-posterior communication in HC. Results indicate aberrant WM network activity supporting WM in SZ that might facilitate normal load-dependent and only marginally less accurate task performance, despite generally slower responding. © 2018 Society for Psychophysiological Research.

Successful Working Memory Processes and Cerebellum in an Elderly Sample: A Neuropsychological and fMRI Study

PubMed Central

Luis, Elkin O.; Arrondo, Gonzalo; Vidorreta, Marta; Martínez, Martin; Loayza, Francis; Fernández-Seara, María A.; Pastor, María A.

2015-01-01

Background Imaging studies help to understand the evolution of key cognitive processes related to aging, such as working memory (WM). This study aimed to test three hypotheses in older adults. First, that the brain activation pattern associated to WM processes in elderly during successful low load tasks is located in posterior sensory and associative areas; second, that the prefrontal and parietal cortex and basal ganglia should be more active during high-demand tasks; third, that cerebellar activations are related to high-demand cognitive tasks and have a specific lateralization depending on the condition. Methods We used a neuropsychological assessment with functional magnetic resonance imaging and a core N-back paradigm design that was maintained across the combination of four conditions of stimuli and two memory loads in a sample of twenty elderly subjects. Results During low-loads, activations were located in the visual ventral network. In high loads, there was an involvement of the basal ganglia and cerebellum in addition to the frontal and parietal cortices. Moreover, we detected an executive control role of the cerebellum in a relatively symmetric fronto-parietal network. Nevertheless, this network showed a predominantly left lateralization in parietal regions associated presumably with an overuse of verbal storage strategies. The differential activations between conditions were stimuli-dependent and were located in sensory areas. Conclusion Successful WM processes in the elderly population are accompanied by an activation pattern that involves cerebellar regions working together with a fronto-parietal network. PMID:26132286

How neuroscience can inform the study of individual differences in cognitive abilities

PubMed Central

McFarland, Dennis J.

2018-01-01

Theories of human mental abilities should be consistent with what is known in neuroscience. Currently tests of human mental abilities are modeled by cognitive constructs such as attention, working memory, and speed of information processing. These constructs are in turn related to a single general ability. However brains are very complex systems and whether most of the variability between the operations of different brains can be ascribed to a single factor is questionable. Research in neuroscience suggests that psychological processes such at perception, attention, decision and executive control are emergent properties of interacting distributed networks. The modules that make up these networks use similar computational processes that involve multiple forms of neural plasticity, each having different time constants. Accordingly these networks might best be characterized in terms of the information they process rather than in terms of abstract psychological processes such as working memory and executive control. PMID:28195556

Multilocus genetic profile in dopaminergic pathway modulates the striatum and working memory.

PubMed

Wang, Chao; Liu, Bing; Zhang, Xiaolong; Cui, Yue; Yu, Chunshui; Jiang, Tianzi

2018-03-29

Dopamine is critical in pathophysiology and therapy of schizophrenia. Many studies have reported altered dopaminergic activity in the dorsal but not ventral striatum in schizophrenia. Based on the largest genome-wide association study of schizophrenia to date, we calculated the polygenic risk score (PGRS) of each subject in a healthy general group, including all variations in the set of functionally related genes involved in dopamine neurotransmitter system. We aimed to test whether the genetic variations in the dopaminergic pathway that have been identified as associated with schizophrenia are related to the function of the striatum and to working memory. We found that a higher PGRS was significantly associated with impairment in working memory. Moreover, resting-state functional connectivity analysis revealed that as the polygenic risk score increased, the connections between left putamen and caudate and the default mode network grew stronger, while the connections with the fronto-parietal network grew weaker. Our findings may shed light on the biological mechanism underlying the "dopamine hypothesis" of schizophrenia and provide some implications regarding the polygenic effects on the dopaminergic activity in the risk for schizophrenia.

An Interactive Simulation Program for Exploring Computational Models of Auto-Associative Memory.

PubMed

Fink, Christian G

2017-01-01

While neuroscience students typically learn about activity-dependent plasticity early in their education, they often struggle to conceptually connect modification at the synaptic scale with network-level neuronal dynamics, not to mention with their own everyday experience of recalling a memory. We have developed an interactive simulation program (based on the Hopfield model of auto-associative memory) that enables the user to visualize the connections generated by any pattern of neural activity, as well as to simulate the network dynamics resulting from such connectivity. An accompanying set of student exercises introduces the concepts of pattern completion, pattern separation, and sparse versus distributed neural representations. Results from a conceptual assessment administered before and after students worked through these exercises indicate that the simulation program is a useful pedagogical tool for illustrating fundamental concepts of computational models of memory.

Generalized Hough Transform for Object Classification in the Maritime Domain

DTIC Science & Technology

2015-12-01

and memory storage problems of the GHT in this work . Neural networks have been used to provide excellent solutions to real-world problems in many...1 A. THESIS OBJECTIVE ...............................................................................1 B. RELATED WORK ...SIGNIFICANT CONTRIBUTIONS ......................................................47  B.  RECOMMENDATIONS FOR FUTURE WORK ................................48

Complex Networks in Psychological Models

NASA Astrophysics Data System (ADS)

Wedemann, R. S.; Carvalho, L. S. A. V. D.; Donangelo, R.

We develop schematic, self-organizing, neural-network models to describe mechanisms associated with mental processes, by a neurocomputational substrate. These models are examples of real world complex networks with interesting general topological structures. Considering dopaminergic signal-to-noise neuronal modulation in the central nervous system, we propose neural network models to explain development of cortical map structure and dynamics of memory access, and unify different mental processes into a single neurocomputational substrate. Based on our neural network models, neurotic behavior may be understood as an associative memory process in the brain, and the linguistic, symbolic associative process involved in psychoanalytic working-through can be mapped onto a corresponding process of reconfiguration of the neural network. The models are illustrated through computer simulations, where we varied dopaminergic modulation and observed the self-organizing emergent patterns at the resulting semantic map, interpreting them as different manifestations of mental functioning, from psychotic through to normal and neurotic behavior, and creativity.

Crew exploration vehicle (CEV) attitude control using a neural-immunology/memory network

NASA Astrophysics Data System (ADS)

Weng, Liguo; Xia, Min; Wang, Wei; Liu, Qingshan

2015-01-01

This paper addresses the problem of the crew exploration vehicle (CEV) attitude control. CEVs are NASA's next-generation human spaceflight vehicles, and they use reaction control system (RCS) jet engines for attitude adjustment, which calls for control algorithms for firing the small propulsion engines mounted on vehicles. In this work, the resultant CEV dynamics combines both actuation and attitude dynamics. Therefore, it is highly nonlinear and even coupled with significant uncertainties. To cope with this situation, a neural-immunology/memory network is proposed. It is inspired by the human memory and immune systems. The control network does not rely on precise system dynamics information. Furthermore, the overall control scheme has a simple structure and demands much less computation as compared with most existing methods, making it attractive for real-time implementation. The effectiveness of this approach is also verified via simulation.

pth moment exponential stability of stochastic memristor-based bidirectional associative memory (BAM) neural networks with time delays.

PubMed

Wang, Fen; Chen, Yuanlong; Liu, Meichun

2018-02-01

Stochastic memristor-based bidirectional associative memory (BAM) neural networks with time delays play an increasingly important role in the design and implementation of neural network systems. Under the framework of Filippov solutions, the issues of the pth moment exponential stability of stochastic memristor-based BAM neural networks are investigated. By using the stochastic stability theory, Itô's differential formula and Young inequality, the criteria are derived. Meanwhile, with Lyapunov approach and Cauchy-Schwarz inequality, we derive some sufficient conditions for the mean square exponential stability of the above systems. The obtained results improve and extend previous works on memristor-based or usual neural networks dynamical systems. Four numerical examples are provided to illustrate the effectiveness of the proposed results. Copyright © 2017 Elsevier Ltd. All rights reserved.

Structural Connectivity Changes Underlying Altered Working Memory Networks in Mild Cognitive Impairment: A Three-Way Image Fusion Analysis.

PubMed

Teipel, Stefan; Ehlers, Inga; Erbe, Anna; Holzmann, Carsten; Lau, Esther; Hauenstein, Karlheinz; Berger, Christoph

2015-01-01

Working memory impairment is among the earliest signs of cognitive decline in Alzheimer's disease (AD) and mild cognitive impairment (MCI). We aimed to study the functional and structural substrate of working memory impairment in early AD dementia and MCI. We studied a group of 12 MCI and AD subjects compared to 12 age- and gender-matched healthy elderly controls using diffusion tensor imaging (DTI), and functional magnetic resonance imaging (fMRI) during a 2-back versus 1-back letter recognition task. We performed a three-way image fusion analysis with joint independent component analysis of cortical activation during working memory, and DTI derived measures of fractional anisotropy (FA) and the mode of anisotropy. We found significant hypoactivation in posterior brain areas and relative hyperactivation in anterior brain areas during working memory in AD/MCI subjects compared to controls. Corresponding independent components from DTI data revealed reduced FA and reduced mode of anisotropy in intracortical projecting fiber tracts with posterior predominance and increased FA and increased mode along the corticospinal tract in AD/MCI compared to controls. Our findings suggest that impairments of structural fiber tract integrity accompany breakdown of posterior and relatively preserved anterior cortical activation during working memory performance in MCI/AD subjects. Copyright © 2014 by the American Society of Neuroimaging.

Episodic memory in aspects of large-scale brain networks

PubMed Central

Jeong, Woorim; Chung, Chun Kee; Kim, June Sic

2015-01-01

Understanding human episodic memory in aspects of large-scale brain networks has become one of the central themes in neuroscience over the last decade. Traditionally, episodic memory was regarded as mostly relying on medial temporal lobe (MTL) structures. However, recent studies have suggested involvement of more widely distributed cortical network and the importance of its interactive roles in the memory process. Both direct and indirect neuro-modulations of the memory network have been tried in experimental treatments of memory disorders. In this review, we focus on the functional organization of the MTL and other neocortical areas in episodic memory. Task-related neuroimaging studies together with lesion studies suggested that specific sub-regions of the MTL are responsible for specific components of memory. However, recent studies have emphasized that connectivity within MTL structures and even their network dynamics with other cortical areas are essential in the memory process. Resting-state functional network studies also have revealed that memory function is subserved by not only the MTL system but also a distributed network, particularly the default-mode network (DMN). Furthermore, researchers have begun to investigate memory networks throughout the entire brain not restricted to the specific resting-state network (RSN). Altered patterns of functional connectivity (FC) among distributed brain regions were observed in patients with memory impairments. Recently, studies have shown that brain stimulation may impact memory through modulating functional networks, carrying future implications of a novel interventional therapy for memory impairment. PMID:26321939

From Hippocampus to Whole-Brain: The Role of Integrative Processing in Episodic Memory Retrieval

PubMed Central

Geib, Benjamin R.; Stanley, Matthew L.; Dennis, Nancy A.; Woldorff, Marty G.; Cabeza, Roberto

2017-01-01

Multivariate functional connectivity analyses of neuroimaging data have revealed the importance of complex, distributed interactions between disparate yet interdependent brain regions. Recent work has shown that topological properties of functional brain networks are associated with individual and group differences in cognitive performance, including in episodic memory. After constructing functional whole-brain networks derived from an event-related fMRI study of memory retrieval, we examined differences in functional brain network architecture between forgotten and remembered words. This study yielded three main findings. First, graph theory analyses showed that successfully remembering compared to forgetting was associated with significant changes in the connectivity profile of the left hippocampus and a corresponding increase in efficient communication with the rest of the brain. Second, bivariate functional connectivity analyses indicated stronger interactions between the left hippocampus and a retrieval assembly for remembered versus forgotten items. This assembly included the left precuneus, left caudate, bilateral supramarginal gyrus, and the bilateral dorsolateral superior frontal gyrus. Integrative properties of the retrieval assembly were greater for remembered than forgotten items. Third, whole-brain modularity analyses revealed that successful memory retrieval was marginally significantly associated with a less segregated modular architecture in the network. The magnitude of the decreases in modularity between remembered and forgotten conditions was related to memory performance. These findings indicate that increases in integrative properties at the nodal, retrieval assembly, and whole-brain topological levels facilitate memory retrieval, while also underscoring the potential of multivariate brain connectivity approaches for providing valuable new insights into the neural bases of memory processes. PMID:28112460

Selective Reduction of AMPA Currents onto Hippocampal Interneurons Impairs Network Oscillatory Activity

PubMed Central

Le Magueresse, Corentin; Monyer, Hannah

2012-01-01

Reduction of excitatory currents onto GABAergic interneurons in the forebrain results in impaired spatial working memory and altered oscillatory network patterns in the hippocampus. Whether this phenotype is caused by an alteration in hippocampal interneurons is not known because most studies employed genetic manipulations affecting several brain regions. Here we performed viral injections in genetically modified mice to ablate the GluA4 subunit of the AMPA receptor in the hippocampus (GluA4HC−/− mice), thereby selectively reducing AMPA receptor-mediated currents onto a subgroup of hippocampal interneurons expressing GluA4. This regionally selective manipulation led to a strong spatial working memory deficit while leaving reference memory unaffected. Ripples (125–250 Hz) in the CA1 region of GluA4HC−/− mice had larger amplitude, slower frequency and reduced rate of occurrence. These changes were associated with an increased firing rate of pyramidal cells during ripples. The spatial selectivity of hippocampal pyramidal cells was comparable to that of controls in many respects when assessed during open field exploration and zigzag maze running. However, GluA4 ablation caused altered modulation of firing rate by theta oscillations in both interneurons and pyramidal cells. Moreover, the correlation between the theta firing phase of pyramidal cells and position was weaker in GluA4HC−/− mice. These results establish the involvement of AMPA receptor-mediated currents onto hippocampal interneurons for ripples and theta oscillations, and highlight potential cellular and network alterations that could account for the altered working memory performance. PMID:22675480

A Very Simple Strategy for Preparing External Stress-Free Two-Way Shape Memory Polymers by Making Use of Hydrogen Bonds.

PubMed

Fan, Long Fei; Rong, Min Zhi; Zhang, Ming Qiu; Chen, Xu Dong

2018-05-11

Development of two-way shape memory polymers that operate free of external force remains a great challenge. Here, the design criteria for this type of material are proposed, deriving a novel fabrication strategy accordingly, which employs conventional crosslinked polyurethane (PU) containing crystalline poly(ε-caprolactone) (PCL) as the proof-of-concept material. Having been simply trained by stretching and thermal treatment without additional ingredients and chemicals, the PU is coupled with a two-way shape memory effect. The core advancement of this study lies in the successful conversion of the inherent hydrogen bond network, which is often the easiest to overlook, into an internal stress provider. The temperature-dependent reversible melting/recrystallization of the crystalline phases elaborately works with the tensed hydrogen bond network, leading to implementation of the two-way shape memory effect. An average reversible strain of as high as ≈20% along the stretch direction is obtained through cooperation adjustment of chemical crosslinking density, crystallinity, and concentration of hydrogen bonds. Meanwhile, the highest internal tension offered by the hydrogen bond network is determined to be 0.10 MPa. Owing to the great convenience characterized by material selection, preparation, programming, and application, the current work may open up an avenue for production and usage of the smart material. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Building Intrusion Detection with a Wireless Sensor Network

NASA Astrophysics Data System (ADS)

Wälchli, Markus; Braun, Torsten

This paper addresses the detection and reporting of abnormal building access with a wireless sensor network. A common office room, offering space for two working persons, has been monitored with ten sensor nodes and a base station. The task of the system is to report suspicious office occupation such as office searching by thieves. On the other hand, normal office occupation should not throw alarms. In order to save energy for communication, the system provides all nodes with some adaptive short-term memory. Thus, a set of sensor activation patterns can be temporarily learned. The local memory is implemented as an Adaptive Resonance Theory (ART) neural network. Unknown event patterns detected on sensor node level are reported to the base station, where the system-wide anomaly detection is performed. The anomaly detector is lightweight and completely self-learning. The system can be run autonomously or it could be used as a triggering system to turn on an additional high-resolution system on demand. Our building monitoring system has proven to work reliably in different evaluated scenarios. Communication costs of up to 90% could be saved compared to a threshold-based approach without local memory.

Meeting the memory challenges of brain-scale network simulation.

PubMed

Kunkel, Susanne; Potjans, Tobias C; Eppler, Jochen M; Plesser, Hans Ekkehard; Morrison, Abigail; Diesmann, Markus

2011-01-01

The development of high-performance simulation software is crucial for studying the brain connectome. Using connectome data to generate neurocomputational models requires software capable of coping with models on a variety of scales: from the microscale, investigating plasticity, and dynamics of circuits in local networks, to the macroscale, investigating the interactions between distinct brain regions. Prior to any serious dynamical investigation, the first task of network simulations is to check the consistency of data integrated in the connectome and constrain ranges for yet unknown parameters. Thanks to distributed computing techniques, it is possible today to routinely simulate local cortical networks of around 10(5) neurons with up to 10(9) synapses on clusters and multi-processor shared-memory machines. However, brain-scale networks are orders of magnitude larger than such local networks, in terms of numbers of neurons and synapses as well as in terms of computational load. Such networks have been investigated in individual studies, but the underlying simulation technologies have neither been described in sufficient detail to be reproducible nor made publicly available. Here, we discover that as the network model sizes approach the regime of meso- and macroscale simulations, memory consumption on individual compute nodes becomes a critical bottleneck. This is especially relevant on modern supercomputers such as the Blue Gene/P architecture where the available working memory per CPU core is rather limited. We develop a simple linear model to analyze the memory consumption of the constituent components of neuronal simulators as a function of network size and the number of cores used. This approach has multiple benefits. The model enables identification of key contributing components to memory saturation and prediction of the effects of potential improvements to code before any implementation takes place. As a consequence, development cycles can be shorter and less expensive. Applying the model to our freely available Neural Simulation Tool (NEST), we identify the software components dominant at different scales, and develop general strategies for reducing the memory consumption, in particular by using data structures that exploit the sparseness of the local representation of the network. We show that these adaptations enable our simulation software to scale up to the order of 10,000 processors and beyond. As memory consumption issues are likely to be relevant for any software dealing with complex connectome data on such architectures, our approach and our findings should be useful for researchers developing novel neuroinformatics solutions to the challenges posed by the connectome project.

Network reconfiguration and working memory impairment in mesial temporal lobe epilepsy.

PubMed

Campo, Pablo; Garrido, Marta I; Moran, Rosalyn J; García-Morales, Irene; Poch, Claudia; Toledano, Rafael; Gil-Nagel, Antonio; Dolan, Raymond J; Friston, Karl J

2013-05-15

Mesial temporal lobe epilepsy (mTLE) is the most prevalent form of focal epilepsy, and hippocampal sclerosis (HS) is considered the most frequent associated pathological finding. Recent connectivity studies have shown that abnormalities, either structural or functional, are not confined to the affected hippocampus, but can be found in other connected structures within the same hemisphere, or even in the contralesional hemisphere. Despite the role of hippocampus in memory functions, most of these studies have explored network properties at resting state, and in some cases compared connectivity values with neuropsychological memory scores. Here, we measured magnetoencephalographic responses during verbal working memory (WM) encoding in left mTLE patients and controls, and compared their effective connectivity within a frontotemporal network using dynamic causal modelling. Bayesian model comparison indicated that the best model included bilateral, forward and backward connections, linking inferior temporal cortex (ITC), inferior frontal cortex (IFC), and the medial temporal lobe (MTL). Test for differences in effective connectivity revealed that patients exhibited decreased ipsilesional MTL-ITC backward connectivity, and increased bidirectional IFC-MTL connectivity in the contralesional hemisphere. Critically, a negative correlation was observed between these changes in patients, with decreases in ipsilesional coupling among temporal sources associated with increases contralesional frontotemporal interactions. Furthermore, contralesional frontotemporal interactions were inversely related to task performance and level of education. The results demonstrate that unilateral sclerosis induced local and remote changes in the dynamic organization of a distributed network supporting verbal WM. Crucially, pre-(peri) morbid factors (educational level) were reflected in both cognitive performance and (putative) compensatory changes in physiological coupling. Copyright © 2013 Elsevier Inc. All rights reserved.

Dynamical Origin of the Effective Storage Capacity in the Brain's Working Memory

NASA Astrophysics Data System (ADS)

Bick, Christian; Rabinovich, Mikhail I.

2009-11-01

The capacity of working memory (WM), a short-term buffer for information in the brain, is limited. We suggest a model for sequential WM that is based upon winnerless competition amongst representations of available informational items. Analytical results for the underlying mathematical model relate WM capacity and relative lateral inhibition in the corresponding neural network. This implies an upper bound for WM capacity, which is, under reasonable neurobiological assumptions, close to the “magical number seven.”

Dentate network activity is necessary for spatial working memory by supporting CA3 sharp-wave ripple generation and prospective firing of CA3 neurons.

PubMed

Sasaki, Takuya; Piatti, Verónica C; Hwaun, Ernie; Ahmadi, Siavash; Lisman, John E; Leutgeb, Stefan; Leutgeb, Jill K

2018-02-01

Complex spatial working memory tasks have been shown to require both hippocampal sharp-wave ripple (SWR) activity and dentate gyrus (DG) neuronal activity. We therefore asked whether DG inputs to CA3 contribute to spatial working memory by promoting SWR generation. Recordings from DG and CA3 while rats performed a dentate-dependent working memory task on an eight-arm radial maze revealed that the activity of dentate neurons and the incidence rate of SWRs both increased during reward consumption. We then found reduced reward-related CA3 SWR generation without direct input from dentate granule neurons. Furthermore, CA3 cells with place fields in not-yet-visited arms preferentially fired during SWRs at reward locations, and these prospective CA3 firing patterns were more pronounced for correct trials and were dentate-dependent. These results indicate that coordination of CA3 neuronal activity patterns by DG is necessary for the generation of neuronal firing patterns that support goal-directed behavior and memory.

Dopaminergic and cholinergic modulations of visual-spatial attention and working memory: insights from molecular genetic research and implications for adult cognitive development.

PubMed

Störmer, Viola S; Passow, Susanne; Biesenack, Julia; Li, Shu-Chen

2012-05-01

Attention and working memory are fundamental for selecting and maintaining behaviorally relevant information. Not only do both processes closely intertwine at the cognitive level, but they implicate similar functional brain circuitries, namely the frontoparietal and the frontostriatal networks, which are innervated by cholinergic and dopaminergic pathways. Here we review the literature on cholinergic and dopaminergic modulations of visual-spatial attention and visual working memory processes to gain insights on aging-related changes in these processes. Some extant findings have suggested that the cholinergic system plays a role in the orienting of attention to enable the detection and discrimination of visual information, whereas the dopaminergic system has mainly been associated with working memory processes such as updating and stabilizing representations. However, since visual-spatial attention and working memory processes are not fully dissociable, there is also evidence of interacting cholinergic and dopaminergic modulations of both processes. We further review gene-cognition association studies that have shown that individual differences in visual-spatial attention and visual working memory are associated with acetylcholine- and dopamine-relevant genes. The efficiency of these 2 transmitter systems declines substantially during healthy aging. These declines, in part, contribute to age-related deficits in attention and working memory functions. We report novel data showing an effect of dopamine COMT gene on spatial updating processes in older but not in younger adults, indicating potential magnification of genetic effects in old age.

Multi-Voxel Decoding and the Topography of Maintained Information During Visual Working Memory

PubMed Central

Lee, Sue-Hyun; Baker, Chris I.

2016-01-01

The ability to maintain representations in the absence of external sensory stimulation, such as in working memory, is critical for guiding human behavior. Human functional brain imaging studies suggest that visual working memory can recruit a network of brain regions from visual to parietal to prefrontal cortex. In this review, we focus on the maintenance of representations during visual working memory and discuss factors determining the topography of those representations. In particular, we review recent studies employing multi-voxel pattern analysis (MVPA) that demonstrate decoding of the maintained content in visual cortex, providing support for a “sensory recruitment” model of visual working memory. However, there is some evidence that maintained content can also be decoded in areas outside of visual cortex, including parietal and frontal cortex. We suggest that the ability to maintain representations during working memory is a general property of cortex, not restricted to specific areas, and argue that it is important to consider the nature of the information that must be maintained. Such information-content is critically determined by the task and the recruitment of specific regions during visual working memory will be both task- and stimulus-dependent. Thus, the common finding of maintained information in visual, but not parietal or prefrontal, cortex may be more of a reflection of the need to maintain specific types of visual information and not of a privileged role of visual cortex in maintenance. PMID:26912997

Lexical Processing and Organization in Bilingual First Language Acquisition: Guiding Future Research

PubMed Central

DeAnda, Stephanie; Poulin-Dubois, Diane; Zesiger, Pascal; Friend, Margaret

2016-01-01

A rich body of work in adult bilinguals documents an interconnected lexical network across languages, such that early word retrieval is language independent. This literature has yielded a number of influential models of bilingual semantic memory. However, extant models provide limited predictions about the emergence of lexical organization in bilingual first language acquisition (BFLA). Empirical evidence from monolingual infants suggests that lexical networks emerge early in development as children integrate phonological and semantic information. These findings tell us little about the interaction between two languages in the early bilingual memory. To date, an understanding of when and how languages interact in early bilingual development is lacking. In this literature review, we present research documenting lexical-semantic development across monolingual and bilingual infants. This is followed by a discussion of current models of bilingual language representation and organization and their ability to account for the available empirical evidence. Together, these theoretical and empirical accounts inform and highlight unexplored areas of research and guide future work on early bilingual memory. PMID:26866430

Same task, different strategies: How brain networks can be influenced by memory strategy

PubMed Central

Sanfratello, Lori; Caprihan, Arvind; Stephen, Julia M.; Knoefel, Janice E.; Adair, John C.; Qualls, Clifford; Lundy, S. Laura; Aine, Cheryl J.

2015-01-01

Previous functional neuroimaging studies demonstrated that different neural networks underlie different types of cognitive processing by engaging participants in particular tasks, such as verbal or spatial working memory (WM) tasks. However, we report here that even when a working memory task is defined as verbal or spatial, different types of memory strategies may be employed to complete it, with concomitant variations in brain activity. We developed a questionnaire to characterize the type of strategy used by individual members in a group of 28 young healthy participants (18–25 years) during a spatial WM task. A cluster analysis was performed to differentiate groups. We acquired functional magnetoencephalography (MEG) and structural diffusion tensor imaging (DTI) measures to characterize the brain networks associated with the use of different strategies. We found two types of strategies were utilized during the spatial WM task, a visuospatial and a verbal strategy, and brain regions and timecourses of activation differed between participants who used each. Task performance also varied by type of strategy used, with verbal strategies showing an advantage. In addition, performance on neuropsychological tests (indices from WAIS-IV, REY-D Complex Figure) correlated significantly with fractional anisotropy (FA) measures for the visuospatial strategy group in white matter tracts implicated in other WM/attention studies. We conclude that differences in memory strategy can have a pronounced effect on the locations and timing of brain activation, and that these differences need further investigation as a possible confounding factor for studies using group averaging as a means for summarizing results. PMID:24931401

Behavioral and Neural Correlates of Executive Function: Interplay between Inhibition and Updating Processes.

PubMed

Kim, Na Young; Wittenberg, Ellen; Nam, Chang S

2017-01-01

This study investigated the interaction between two executive function processes, inhibition and updating, through analyses of behavioral, neurophysiological, and effective connectivity metrics. Although, many studies have focused on behavioral effects of executive function processes individually, few studies have examined the dynamic causal interactions between these two functions. A total of twenty participants from a local university performed a dual task combing flanker and n-back experimental paradigms, and completed the Operation Span Task designed to measure working memory capacity. We found that both behavioral (accuracy and reaction time) and neurophysiological (P300 amplitude and alpha band power) metrics on the inhibition task (i.e., flanker task) were influenced by the updating load (n-back level) and modulated by working memory capacity. Using independent component analysis, source localization (DIPFIT), and Granger Causality analysis of the EEG time-series data, the present study demonstrated that manipulation of cognitive demand in a dual executive function task influenced the causal neural network. We compared connectivity across three updating loads (n-back levels) and found that experimental manipulation of working memory load enhanced causal connectivity of a large-scale neurocognitive network. This network contains the prefrontal and parietal cortices, which are associated with inhibition and updating executive function processes. This study has potential applications in human performance modeling and assessment of mental workload, such as the design of training materials and interfaces for those performing complex multitasking under stress.

Fast learning of simple perceptual discriminations reduces brain activation in working memory and in high-level auditory regions.

PubMed

Daikhin, Luba; Ahissar, Merav

2015-07-01

Introducing simple stimulus regularities facilitates learning of both simple and complex tasks. This facilitation may reflect an implicit change in the strategies used to solve the task when successful predictions regarding incoming stimuli can be formed. We studied the modifications in brain activity associated with fast perceptual learning based on regularity detection. We administered a two-tone frequency discrimination task and measured brain activation (fMRI) under two conditions: with and without a repeated reference tone. Although participants could not explicitly tell the difference between these two conditions, the introduced regularity affected both performance and the pattern of brain activation. The "No-Reference" condition induced a larger activation in frontoparietal areas known to be part of the working memory network. However, only the condition with a reference showed fast learning, which was accompanied by a reduction of activity in two regions: the left intraparietal area, involved in stimulus retention, and the posterior superior-temporal area, involved in representing auditory regularities. We propose that this joint reduction reflects a reduction in the need for online storage of the compared tones. We further suggest that this change reflects an implicit strategic shift "backwards" from reliance mainly on working memory networks in the "No-Reference" condition to increased reliance on detected regularities stored in high-level auditory networks.

Cognitive memory.

PubMed

Widrow, Bernard; Aragon, Juan Carlos

2013-05-01

Regarding the workings of the human mind, memory and pattern recognition seem to be intertwined. You generally do not have one without the other. Taking inspiration from life experience, a new form of computer memory has been devised. Certain conjectures about human memory are keys to the central idea. The design of a practical and useful "cognitive" memory system is contemplated, a memory system that may also serve as a model for many aspects of human memory. The new memory does not function like a computer memory where specific data is stored in specific numbered registers and retrieval is done by reading the contents of the specified memory register, or done by matching key words as with a document search. Incoming sensory data would be stored at the next available empty memory location, and indeed could be stored redundantly at several empty locations. The stored sensory data would neither have key words nor would it be located in known or specified memory locations. Sensory inputs concerning a single object or subject are stored together as patterns in a single "file folder" or "memory folder". When the contents of the folder are retrieved, sights, sounds, tactile feel, smell, etc., are obtained all at the same time. Retrieval would be initiated by a query or a prompt signal from a current set of sensory inputs or patterns. A search through the memory would be made to locate stored data that correlates with or relates to the prompt input. The search would be done by a retrieval system whose first stage makes use of autoassociative artificial neural networks and whose second stage relies on exhaustive search. Applications of cognitive memory systems have been made to visual aircraft identification, aircraft navigation, and human facial recognition. Concerning human memory, reasons are given why it is unlikely that long-term memory is stored in the synapses of the brain's neural networks. Reasons are given suggesting that long-term memory is stored in DNA or RNA. Neural networks are an important component of the human memory system, and their purpose is for information retrieval, not for information storage. The brain's neural networks are analog devices, subject to drift and unplanned change. Only with constant training is reliable action possible. Good training time is during sleep and while awake and making use of one's memory. A cognitive memory is a learning system. Learning involves storage of patterns or data in a cognitive memory. The learning process for cognitive memory is unsupervised, i.e. autonomous. Copyright © 2013 Elsevier Ltd. All rights reserved.

Examining the neural correlates of active and passive forms of verbal-spatial binding in working memory.

PubMed

Grot, Stéphanie; Leclerc, Marie-Eve; Luck, David

2018-05-23

We designed an fMRI study to pinpoint the neural correlates of active and passive binding in working memory. Participants were instructed to memorize three words and three spatial locations. In the passive binding condition, words and spatial locations were directly presented as bound. Conversely, in the active binding condition, words and spatial locations were presented as separated, and participants were directed to intentionally create associations between them. Our results showed that participants performed better on passive binding relative to active binding. FMRI analysis revealed that both binding conditions induced greater activity within the hippocampus. Additionally, our analyses divulged regions specifically engaged in passive and active binding. Altogether, these data allow us to propose the hippocampus as a central candidate for working memory binding. When needed, a frontal-parietal network can contribute to the rearrangement of information. These findings may inform theories of working memory binding. Copyright © 2018. Published by Elsevier B.V.

Cognitive Benefits of Online Social Networking for Healthy Older Adults.

PubMed

Myhre, Janelle W; Mehl, Matthias R; Glisky, Elizabeth L

2017-09-01

Research suggests that older adults who remain socially active and cognitively engaged have better cognitive function than those who are isolated and disengaged. This study examined the efficacy of learning and using an online social networking website, Facebook.com, as an intervention to maintain or enhance cognitive function in older adults. Forty-one older adults were assigned to learn and use Facebook (n = 14) or an online diary website (active control, n = 13) for 8 weeks or placed on a waitlist (n = 14). Outcome measures included neuropsychological tests of executive functions, memory, and processing speed and self-report questionnaires about social engagement. The Facebook group showed a significant increase in a composite measure of updating, an executive function factor associated with complex working memory tasks, compared to no significant change in the control groups. Other measures of cognitive function and social support showed no differential improvement in the Facebook group. Learning and using an online social networking site may provide specific benefits for complex working memory in a group of healthy older adults. This may reflect the particular cognitive demands associated with online social networking and/or the benefits of social engagement more generally. © The Author 2016. Published by Oxford University Press on behalf of The Gerontological Society of America. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Social memory engram in the hippocampus.

PubMed

Okuyama, Teruhiro

2018-04-01

Social memory is one of the crucial components of episodic memories. Gregarious animals living in societies utilize social memory to exhibit the appropriate social behaviors such as aggression, avoidance, cooperative behavior, and even mating behavior. However, the neural mechanisms underlying social memory in the hippocampus remains mysterious. Here, I review some evidence from work done in rodents and primates on the brain region(s) and circuits encoding and/or retrieving social memory, as well as a storage for social memory (i.e. social memory engram neurons). Based on our recent findings that neural ensemble in ventral CA1 sub-region of the hippocampus possesses social memory engram, I would discuss the neural network for social information processing in order to encode social memory; and its evolutionary conservation between rodents and human. Copyright © 2017 Elsevier Ireland Ltd and Japan Neuroscience Society. All rights reserved.

Stability and Hopf bifurcation in a simplified BAM neural network with two time delays.

PubMed

Cao, Jinde; Xiao, Min

2007-03-01

Various local periodic solutions may represent different classes of storage patterns or memory patterns, and arise from the different equilibrium points of neural networks (NNs) by applying Hopf bifurcation technique. In this paper, a bidirectional associative memory NN with four neurons and multiple delays is considered. By applying the normal form theory and the center manifold theorem, analysis of its linear stability and Hopf bifurcation is performed. An algorithm is worked out for determining the direction and stability of the bifurcated periodic solutions. Numerical simulation results supporting the theoretical analysis are also given.

Microlaser-based compact optical neuro-processors (Invited Paper)

NASA Astrophysics Data System (ADS)

Paek, Eung Gi; Chan, Winston K.; Zah, Chung-En; Cheung, Kwok-wai; Curtis, L.; Chang-Hasnain, Constance J.

1992-10-01

This paper reviews the recent progress in the development of holographic neural networks using surface-emitting laser diode arrays (SELDAs). Since the previous work on ultrafast holographic memory readout system and a robust incoherent correlator, progress has been made in several areas: the use of an array of monolithic `neurons' to reconstruct holographic memories; two-dimensional (2-D) wavelength-division multiplexing (WDM) for image transmission through a single-mode fiber; and finally, an associative memory using time- division multiplexing (TDM). Experimental demonstrations on these are presented.

How Verbal and Spatial Manipulation Networks Contribute to Calculation: An fMRI Study

ERIC Educational Resources Information Center

Zago, Laure; Petit, Laurent; Turbelin, Marie-Renee; Andersson, Frederic; Vigneau, Mathieu; Tzourio-Mazoyer, Nathalie

2008-01-01

The manipulation of numbers required during calculation is known to rely on working memory (WM) resources. Here, we investigated the respective contributions of verbal and/or spatial WM manipulation brain networks during the addition of four numbers performed by adults, using functional magnetic resonance imaging (fMRI). Both manipulation and…

Social Networking Sites and Cognitive Abilities: Do They Make You Smarter?

ERIC Educational Resources Information Center

Alloway, Tracy Packiam; Horton, John; Alloway, Ross G.; Dawson, Clare

2013-01-01

The purpose of the present study was to investigate the impact of social networking sites (SNS) on cognitive abilities and reported levels of social connectedness in adolescents. In order to provide a reliable measure of cognitive skills, standardized tests of verbal ability, working memory, and academic attainment were administered. Students also…

Impact of real-time fMRI working memory feedback training on the interactions between three core brain networks.

PubMed

Zhang, Qiushi; Zhang, Gaoyan; Yao, Li; Zhao, Xiaojie

2015-01-01

Working memory (WM) refers to the temporary holding and manipulation of information during the performance of a range of cognitive tasks, and WM training is a promising method for improving an individual's cognitive functions. Our previous work demonstrated that WM performance can be improved through self-regulation of dorsal lateral prefrontal cortex (PFC) activation using real-time functional magnetic resonance imaging (rtfMRI), which enables individuals to control local brain activities volitionally according to the neurofeedback. Furthermore, research concerning large-scale brain networks has demonstrated that WM training requires the engagement of several networks, including the central executive network (CEN), the default mode network (DMN) and the salience network (SN), and functional connectivity within the CEN and DMN can be changed by WM training. Although a switching role of the SN between the CEN and DMN has been demonstrated, it remains unclear whether WM training can affect the interactions between the three networks and whether a similar mechanism also exists during the training process. In this study, we investigated the dynamic functional connectivity between the three networks during the rtfMRI feedback training using independent component analysis (ICA) and correlation analysis. The results indicated that functional connectivity within and between the three networks were significantly enhanced by feedback training, and most of the changes were associated with the insula and correlated with behavioral improvements. These findings suggest that the insula plays a critical role in the reorganization of functional connectivity among the three networks induced by rtfMRI training and in WM performance, thus providing new insights into the mechanisms of high-level functions and the clinical treatment of related functional impairments.

Developing algorithm for the critical care physician scheduling

NASA Astrophysics Data System (ADS)

Lee, Hyojun; Pah, Adam; Amaral, Luis; Northwestern Memorial Hospital Collaboration

Understanding the social network has enabled us to quantitatively study social phenomena such as behaviors in adoption and propagation of information. However, most work has been focusing on networks of large heterogeneous communities, and little attention has been paid to how work-relevant information spreads within networks of small and homogeneous groups of highly trained individuals, such as physicians. Within the professionals, the behavior patterns and the transmission of information relevant to the job are dependent not only on the social network between the employees but also on the schedules and teams that work together. In order to systematically investigate the dependence of the spread of ideas and adoption of innovations on a work-environment network, we sought to construct a model for the interaction network of critical care physicians at Northwestern Memorial Hospital (NMH) based on their work schedules. We inferred patterns and hidden rules from past work schedules such as turnover rates. Using the characteristics of the work schedules of the physicians and their turnover rates, we were able to create multi-year synthetic work schedules for a generic intensive care unit. The algorithm for creating shift schedules can be applied to other schedule dependent networks ARO1.

Intracranial recordings and human memory.

PubMed

Johnson, Elizabeth L; Knight, Robert T

2015-04-01

Recent work involving intracranial recording during human memory performance provides superb spatiotemporal resolution on mnemonic processes. These data demonstrate that the cortical regions identified in neuroimaging studies of memory fall into temporally distinct networks and the hippocampal theta activity reported in animal memory literature also plays a central role in human memory. Memory is linked to activity at multiple interacting frequencies, ranging from 1 to 500Hz. High-frequency responses and coupling between different frequencies suggest that frontal cortex activity is critical to human memory processes, as well as a potential key role for the thalamus in neocortical oscillations. Future research will inform unresolved questions in the neuroscience of human memory and guide creation of stimulation protocols to facilitate function in the damaged brain. Copyright © 2014 Elsevier Ltd. All rights reserved.

From hippocampus to whole-brain: The role of integrative processing in episodic memory retrieval.

PubMed

Geib, Benjamin R; Stanley, Matthew L; Dennis, Nancy A; Woldorff, Marty G; Cabeza, Roberto

2017-04-01

Multivariate functional connectivity analyses of neuroimaging data have revealed the importance of complex, distributed interactions between disparate yet interdependent brain regions. Recent work has shown that topological properties of functional brain networks are associated with individual and group differences in cognitive performance, including in episodic memory. After constructing functional whole-brain networks derived from an event-related fMRI study of memory retrieval, we examined differences in functional brain network architecture between forgotten and remembered words. This study yielded three main findings. First, graph theory analyses showed that successfully remembering compared to forgetting was associated with significant changes in the connectivity profile of the left hippocampus and a corresponding increase in efficient communication with the rest of the brain. Second, bivariate functional connectivity analyses indicated stronger interactions between the left hippocampus and a retrieval assembly for remembered versus forgotten items. This assembly included the left precuneus, left caudate, bilateral supramarginal gyrus, and the bilateral dorsolateral superior frontal gyrus. Integrative properties of the retrieval assembly were greater for remembered than forgotten items. Third, whole-brain modularity analyses revealed that successful memory retrieval was marginally significantly associated with a less segregated modular architecture in the network. The magnitude of the decreases in modularity between remembered and forgotten conditions was related to memory performance. These findings indicate that increases in integrative properties at the nodal, retrieval assembly, and whole-brain topological levels facilitate memory retrieval, while also underscoring the potential of multivariate brain connectivity approaches for providing valuable new insights into the neural bases of memory processes. Hum Brain Mapp 38:2242-2259, 2017. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

Information flow in layered networks of non-monotonic units

NASA Astrophysics Data System (ADS)

Schittler Neves, Fabio; Martim Schubert, Benno; Erichsen, Rubem, Jr.

2015-07-01

Layered neural networks are feedforward structures that yield robust parallel and distributed pattern recognition. Even though much attention has been paid to pattern retrieval properties in such systems, many aspects of their dynamics are not yet well characterized or understood. In this work we study, at different temperatures, the memory activity and information flows through layered networks in which the elements are the simplest binary odd non-monotonic function. Our results show that, considering a standard Hebbian learning approach, the network information content has its maximum always at the monotonic limit, even though the maximum memory capacity can be found at non-monotonic values for small enough temperatures. Furthermore, we show that such systems exhibit rich macroscopic dynamics, including not only fixed point solutions of its iterative map, but also cyclic and chaotic attractors that also carry information.

Statistics and dynamics of attractor networks with inter-correlated patterns

NASA Astrophysics Data System (ADS)

Kropff, E.

2007-02-01

In an embodied feature representation view, the semantic memory represents concepts in the brain by the associated activation of the features that describe it, each one of them processed in a differentiated region of the cortex. This system has been modeled with a Potts attractor network. Several studies of feature representation show that the correlation between patterns plays a crucial role in semantic memory. The present work focuses on two aspects of the effect of correlations in attractor networks. In first place, it assesses how a Potts network can store a set of patterns with non-trivial correlations between them. This is done through a simple and biologically plausible modification to the classical learning rule. In second place, it studies the complexity of latching transitions between attractor states, and how this complexity can be controlled.

Scaling properties in time-varying networks with memory

NASA Astrophysics Data System (ADS)

Kim, Hyewon; Ha, Meesoon; Jeong, Hawoong

2015-12-01

The formation of network structure is mainly influenced by an individual node's activity and its memory, where activity can usually be interpreted as the individual inherent property and memory can be represented by the interaction strength between nodes. In our study, we define the activity through the appearance pattern in the time-aggregated network representation, and quantify the memory through the contact pattern of empirical temporal networks. To address the role of activity and memory in epidemics on time-varying networks, we propose temporal-pattern coarsening of activity-driven growing networks with memory. In particular, we focus on the relation between time-scale coarsening and spreading dynamics in the context of dynamic scaling and finite-size scaling. Finally, we discuss the universality issue of spreading dynamics on time-varying networks for various memory-causality tests.

Kinesthetic working memory and action control within the dorsal stream.

PubMed

Fiehler, Katja; Burke, Michael; Engel, Annerose; Bien, Siegfried; Rösler, Frank

2008-02-01

There is wide agreement that the "dorsal (action) stream" processes visual information for movement control. However, movements depend not only on vision but also on tactile and kinesthetic information (=haptics). Using functional magnetic resonance imaging, the present study investigates to what extent networks within the dorsal stream are also utilized for kinesthetic action control and whether they are also involved in kinesthetic working memory. Fourteen blindfolded participants performed a delayed-recognition task in which right-handed movements had to be encoded, maintained, and later recognized without any visual feedback. Encoding of hand movements activated somatosensory areas, superior parietal lobe (dorsodorsal stream), anterior intraparietal sulcus (aIPS) and adjoining areas (ventrodorsal stream), premotor cortex, and occipitotemporal cortex (ventral stream). Short-term maintenance of kinesthetic information elicited load-dependent activity in the aIPS and adjacent anterior portion of the superior parietal lobe (ventrodorsal stream) of the left hemisphere. We propose that the action representation system of the dorsodorsal and ventrodorsal stream is utilized not only for visual but also for kinesthetic action control. Moreover, the present findings demonstrate that networks within the ventrodorsal stream, in particular the left aIPS and closely adjacent areas, are also engaged in working memory maintenance of kinesthetic information.

Potentiation of motor sub-networks for motor control but not working memory: Interaction of dACC and SMA revealed by resting-state directed functional connectivity

PubMed Central

Diwadkar, Vaibhav A.; Asemi, Avisa; Burgess, Ashley; Chowdury, Asadur; Bressler, Steven L.

2017-01-01

The dorsal Anterior Cingulate Cortex (dACC) and the Supplementary Motor Area (SMA) are known to interact during motor coordination behavior. We previously discovered that the directional influences underlying this interaction in a visuo-motor coordination task are asymmetric, with the dACC→SMA influence being significantly greater than that in the reverse direction. To assess the specificity of this effect, here we undertook an analysis of the interaction between dACC and SMA in two distinct contexts. In addition to the motor coordination task, we also assessed these effects during a (n-back) working memory task. We applied directed functional connectivity analysis to these two task paradigms, and also to the rest condition of each paradigm, in which rest blocks were interspersed with task blocks. We report here that the previously known asymmetric interaction between dACC and SMA, with dACC→SMA dominating, was significantly larger in the motor coordination task than the memory task. Moreover the asymmetry between dACC and SMA was reversed during the rest condition of the motor coordination task, but not of the working memory task. In sum, the dACC→SMA influence was significantly greater in the motor task than the memory task condition, and the SMA→dACC influence was significantly greater in the motor rest than the memory rest condition. We interpret these results as suggesting that the potentiation of motor sub-networks during the motor rest condition supports the motor control of SMA by dACC during the active motor task condition. PMID:28278267

Implicity Defined Neural Networks for Sequence Labeling

DTIC Science & Technology

2017-02-13

popularity of the Long Short - Term Memory (LSTM) (Hochreiter and Schmidhuber, 1997) and variants such as the Gated Recurrent Unit (GRU) (Cho et al., 2014...bidirectional lstm and other neural network architectures. Neural Net- works 18(5):602–610. Sepp Hochreiter and Jürgen Schmidhuber. 1997. Long short - term ...hid- den states of the network to coupled together, allowing potential improvement on problems with complex, long -distance dependencies. Initial

Cross-frequency synchronization connects networks of fast and slow oscillations during visual working memory maintenance.

PubMed

Siebenhühner, Felix; Wang, Sheng H; Palva, J Matias; Palva, Satu

2016-09-26

Neuronal activity in sensory and fronto-parietal (FP) areas underlies the representation and attentional control, respectively, of sensory information maintained in visual working memory (VWM). Within these regions, beta/gamma phase-synchronization supports the integration of sensory functions, while synchronization in theta/alpha bands supports the regulation of attentional functions. A key challenge is to understand which mechanisms integrate neuronal processing across these distinct frequencies and thereby the sensory and attentional functions. We investigated whether such integration could be achieved by cross-frequency phase synchrony (CFS). Using concurrent magneto- and electroencephalography, we found that CFS was load-dependently enhanced between theta and alpha-gamma and between alpha and beta-gamma oscillations during VWM maintenance among visual, FP, and dorsal attention (DA) systems. CFS also connected the hubs of within-frequency-synchronized networks and its strength predicted individual VWM capacity. We propose that CFS integrates processing among synchronized neuronal networks from theta to gamma frequencies to link sensory and attentional functions.

Functional connectivity of hippocampal and prefrontal networks during episodic and spatial memory based on real-world environments.

PubMed

Robin, Jessica; Hirshhorn, Marnie; Rosenbaum, R Shayna; Winocur, Gordon; Moscovitch, Morris; Grady, Cheryl L

2015-01-01

Several recent studies have compared episodic and spatial memory in neuroimaging paradigms in order to understand better the contribution of the hippocampus to each of these tasks. In the present study, we build on previous findings showing common neural activation in default network areas during episodic and spatial memory tasks based on familiar, real-world environments (Hirshhorn et al. (2012) Neuropsychologia 50:3094-3106). Following previous demonstrations of the presence of functionally connected sub-networks within the default network, we performed seed-based functional connectivity analyses to determine how, depending on the task, the hippocampus and prefrontal cortex differentially couple with one another and with distinct whole-brain networks. We found evidence for a medial prefrontal-parietal network and a medial temporal lobe network, which were functionally connected to the prefrontal and hippocampal seeds, respectively, regardless of the nature of the memory task. However, these two networks were functionally connected with one another during the episodic memory task, but not during spatial memory tasks. Replicating previous reports of fractionation of the default network into stable sub-networks, this study also shows how these sub-networks may flexibly couple and uncouple with one another based on task demands. These findings support the hypothesis that episodic memory and spatial memory share a common medial temporal lobe-based neural substrate, with episodic memory recruiting additional prefrontal sub-networks. © 2014 Wiley Periodicals, Inc.

Spatial serial order processing in schizophrenia.

PubMed

Fraser, David; Park, Sohee; Clark, Gina; Yohanna, Daniel; Houk, James C

2004-10-01

The aim of this study was to examine serial order processing deficits in 21 schizophrenia patients and 16 age- and education-matched healthy controls. In a spatial serial order working memory task, one to four spatial targets were presented in a randomized sequence. Subjects were required to remember the locations and the order in which the targets were presented. Patients showed a marked deficit in ability to remember the sequences compared with controls. Increasing the number of targets within a sequence resulted in poorer memory performance for both control and schizophrenia subjects, but the effect was much more pronounced in the patients. Targets presented at the end of a long sequence were more vulnerable to memory error in schizophrenia patients. Performance deficits were not attributable to motor errors, but to errors in target choice. The results support the idea that the memory errors seen in schizophrenia patients may be due to saturating the working memory network at relatively low levels of memory load.

Examining the Efficacy of the Modified Story Memory Technique (mSMT) in Persons With TBI Using Functional Magnetic Resonance Imaging (fMRI): The TBI-MEM Trial.

PubMed

Chiaravalloti, Nancy D; Dobryakova, Ekaterina; Wylie, Glenn R; DeLuca, John

2015-01-01

New learning and memory deficits are common following traumatic brain injury (TBI). Yet few studies have examined the efficacy of memory retraining in TBI through the most methodologically vigorous randomized clinical trial. Our previous research has demonstrated that the modified Story Memory Technique (mSMT) significantly improves new learning and memory in multiple sclerosis. The present double-blind, placebo-controlled, randomized clinical trial examined changes in cerebral activation on functional magnetic resonance imaging following mSMT treatment in persons with TBI. Eighteen individuals with TBI were randomly assigned to treatment (n = 9) or placebo (n = 9) groups. Baseline and follow-up functional magnetic resonance imaging was collected during a list-learning task. Significant differences in cerebral activation from before to after treatment were noted in regions belonging to the default mode network and executive control network in the treatment group only. Results are interpreted in light of these networks. Activation differences between the groups likely reflect increased use of strategies taught during treatment. This study demonstrates a significant change in cerebral activation resulting from the mSMT in a TBI sample. Findings are consistent with previous work in multiple sclerosis. Behavioral interventions can show significant changes in the brain, validating clinical utility.

Social Networks and Memory over 15 Years of Followup in a Cohort of Older Australians: Results from the Australian Longitudinal Study of Ageing

PubMed Central

Giles, Lynne C.; Anstey, Kaarin J.; Walker, Ruth B.; Luszcz, Mary A.

2012-01-01

The purpose was to examine the relationship between different types of social networks and memory over 15 years of followup in a large cohort of older Australians who were cognitively intact at study baseline. Our specific aims were to investigate whether social networks were associated with memory, determine if different types of social networks had different relationships with memory, and examine if changes in memory over time differed according to types of social networks. We used five waves of data from the Australian Longitudinal Study of Ageing, and followed 706 participants with an average age of 78.6 years (SD 5.7) at baseline. The relationships between five types of social networks and changes in memory were assessed. The results suggested a gradient of effect; participants in the upper tertile of friends or overall social networks had better memory scores than those in the mid tertile, who in turn had better memory scores than participants in the lower tertile. There was evidence of a linear, but not quadratic, effect of time on memory, and an interaction between friends' social networks and time was apparent. Findings are discussed with respect to mechanisms that might explain the observed relationships between social networks and memory. PMID:22988510

The irrelevant speech effect and working memory load.

PubMed

Gisselgård, Jens; Petersson, Karl Magnus; Ingvar, Martin

2004-07-01

Irrelevant speech impairs the immediate serial recall of visually presented material. Previously, we have shown that the irrelevant speech effect (ISE) was associated with a relative decrease of regional blood flow in cortical regions subserving the verbal working memory, in particular the superior temporal cortex. In this extension of the previous study, the working memory load was increased and an increased activity as a response to irrelevant speech was noted in the dorsolateral prefrontal cortex. We suggest that the two studies together provide some basic insights as to the nature of the irrelevant speech effect. Firstly, no area in the brain can be ascribed as the single locus of the irrelevant speech effect. Instead, the functional neuroanatomical substrate to the effect can be characterized in terms of changes in networks of functionally interrelated areas. Secondly, the areas that are sensitive to the irrelevant speech effect are also generically activated by the verbal working memory task itself. Finally, the impact of irrelevant speech and related brain activity depends on working memory load as indicated by the differences between the present and the previous study. From a brain perspective, the irrelevant speech effect may represent a complex phenomenon that is a composite of several underlying mechanisms, which depending on the working memory load, include top-down inhibition as well as recruitment of compensatory support and control processes. We suggest that, in the low-load condition, a selection process by an inhibitory top-down modulation is sufficient, whereas in the high-load condition, at or above working memory span, auxiliary adaptive cognitive resources are recruited as compensation. Copyright 2004 Elsevier Inc.

Gaming is related to enhanced working memory performance and task-related cortical activity.

PubMed

Moisala, M; Salmela, V; Hietajärvi, L; Carlson, S; Vuontela, V; Lonka, K; Hakkarainen, K; Salmela-Aro, K; Alho, K

2017-01-15

Gaming experience has been suggested to lead to performance enhancements in a wide variety of working memory tasks. Previous studies have, however, mostly focused on adult expert gamers and have not included measurements of both behavioral performance and brain activity. In the current study, 167 adolescents and young adults (aged 13-24 years) with different amounts of gaming experience performed an n-back working memory task with vowels, with the sensory modality of the vowel stream switching between audition and vision at random intervals. We studied the relationship between self-reported daily gaming activity, working memory (n-back) task performance and related brain activity measured using functional magnetic resonance imaging (fMRI). The results revealed that the extent of daily gaming activity was related to enhancements in both performance accuracy and speed during the most demanding (2-back) level of the working memory task. This improved working memory performance was accompanied by enhanced recruitment of a fronto-parietal cortical network, especially the dorsolateral prefrontal cortex. In contrast, during the less demanding (1-back) level of the task, gaming was associated with decreased activity in the same cortical regions. Our results suggest that a greater degree of daily gaming experience is associated with better working memory functioning and task difficulty-dependent modulation in fronto-parietal brain activity already in adolescence and even when non-expert gamers are studied. The direction of causality within this association cannot be inferred with certainty due to the correlational nature of the current study. Copyright © 2016 Elsevier B.V. All rights reserved.

Sentence processing and verbal working memory in a white-matter-disconnection patient.

PubMed

Meyer, Lars; Cunitz, Katrin; Obleser, Jonas; Friederici, Angela D

2014-08-01

The Arcuate Fasciculus/Superior Longitudinal Fasciculus (AF/SLF) is the white-matter bundle that connects posterior superior temporal and inferior frontal cortex. Its causal functional role in sentence processing and verbal working memory is currently under debate. While impairments of sentence processing and verbal working memory often co-occur in patients suffering from AF/SLF damage, it is unclear whether these impairments result from shared white-matter damage to the verbal-working-memory network. The present study sought to specify the behavioral consequences of focal AF/SLF damage for sentence processing and verbal working memory, which were assessed in a single patient suffering from a cleft-like lesion spanning the deep left superior temporal gyrus, sparing most surrounding gray matter. While tractography suggests that the ventral fronto-temporal white-matter bundle is intact in this patient, the AF/SLF was not visible to tractography. In line with the hypothesis that the AF/SLF is causally involved in sentence processing, the patient׳s performance was selectively impaired on sentences that jointly involve both complex word orders and long word-storage intervals. However, the patient was unimpaired on sentences that only involved long word-storage intervals without involving complex word orders. On the contrary, the patient performed generally worse than a control group across standard verbal-working-memory tests. We conclude that the AF/SLF not only plays a causal role in sentence processing, linking regions of the left dorsal inferior frontal gyrus to the temporo-parietal region, but moreover plays a crucial role in verbal working memory, linking regions of the left ventral inferior frontal gyrus to the left temporo-parietal region. Together, the specific sentence-processing impairment and the more general verbal-working-memory impairment may imply that the AF/SLF subserves both sentence processing and verbal working memory, possibly pointing to the AF and SLF respectively supporting each. Copyright © 2014 Elsevier Ltd. All rights reserved.

A functional MRI study of working memory task in euthymic bipolar disorder: evidence for task-specific dysfunction.

PubMed

Monks, Paul J; Thompson, Jill M; Bullmore, Edward T; Suckling, John; Brammer, Michael J; Williams, Steve C R; Simmons, Andrew; Giles, Nicola; Lloyd, Adrian J; Harrison, C Louise; Seal, Marc; Murray, Robin M; Ferrier, I Nicol; Young, Allan H; Curtis, Vivienne A

2004-12-01

Even when euthymic bipolar disorder patients can have persistent deficits in working memory, but the neural basis of this deficit remains unclear. We undertook an functional magnetic resonance imaging investigation of euthymic bipolar disorder patients performing two working memory paradigms; the two-back and Sternberg tasks, selected to examine the central executive and the phonological loop respectively. We hypothesized that neuronal dysfunction would be specific to the network underlying the executive rather than the phonological loop component of working memory. Twelve right-handed euthymic bipolar I males receiving lithium carbonate monotherapy were matched with 12 controls. The two-back task comprised a single working memory load contrasted with baseline vigilance condition. The Sternberg paradigm used a parametric design incorporating variable working memory load with fixed delay between presentation of an array of items to be remembered and a target item. Functional activation data were acquired during performance of the tasks and were analysed to produce brain activation maps representing significant group differences in activation (ANOVA). Load-response curves were derived from the Sternberg task data set. There were no significant between-group differences (t-test) in performance of the two-back task, or in 2 x 5 group by memory load ANOVA for the performance data from Sternberg task. In the two-back task, compared with controls bipolar disorder patients showed reductions in bilateral frontal, temporal and parietal activation, and increased activations with the left precentral, right medial frontal and left supramarginal gyri. No between-group differences were observed in the Sternberg task at any working memory load. Our findings support the notion that, in euthymic bipolar disorder, failure to engage fronto-executive function underpins the core neuropsychological deficits. Blackwell Munksgaard, 2004

Breeding novel solutions in the brain: a model of Darwinian neurodynamics.

PubMed

Szilágyi, András; Zachar, István; Fedor, Anna; de Vladar, Harold P; Szathmáry, Eörs

2016-01-01

Background : The fact that surplus connections and neurons are pruned during development is well established. We complement this selectionist picture by a proof-of-principle model of evolutionary search in the brain, that accounts for new variations in theory space. We present a model for Darwinian evolutionary search for candidate solutions in the brain. Methods : We combine known components of the brain - recurrent neural networks (acting as attractors), the action selection loop and implicit working memory - to provide the appropriate Darwinian architecture. We employ a population of attractor networks with palimpsest memory. The action selection loop is employed with winners-share-all dynamics to select for candidate solutions that are transiently stored in implicit working memory. Results : We document two processes: selection of stored solutions and evolutionary search for novel solutions. During the replication of candidate solutions attractor networks occasionally produce recombinant patterns, increasing variation on which selection can act. Combinatorial search acts on multiplying units (activity patterns) with hereditary variation and novel variants appear due to (i) noisy recall of patterns from the attractor networks, (ii) noise during transmission of candidate solutions as messages between networks, and, (iii) spontaneously generated, untrained patterns in spurious attractors. Conclusions : Attractor dynamics of recurrent neural networks can be used to model Darwinian search. The proposed architecture can be used for fast search among stored solutions (by selection) and for evolutionary search when novel candidate solutions are generated in successive iterations. Since all the suggested components are present in advanced nervous systems, we hypothesize that the brain could implement a truly evolutionary combinatorial search system, capable of generating novel variants.

Decreased Efficiency of Task-Positive and Task-Negative Networks During Working Memory in Schizophrenia

PubMed Central

Metzak, Paul D.; Riley, Jennifer D.; Wang, Liang; Whitman, Jennifer C.; Ngan, Elton T. C.; Woodward, Todd S.

2012-01-01

Working memory (WM) is one of the most impaired cognitive processes in schizophrenia. Functional magnetic resonance imaging (fMRI) studies in this area have typically found a reduction in information processing efficiency but have focused on the dorsolateral prefrontal cortex. In the current study using the Sternberg Item Recognition Test, we consider networks of regions supporting WM and measure the activation of functionally connected neural networks over different WM load conditions. We used constrained principal component analysis with a finite impulse response basis set to compare the estimated hemodynamic response associated with different WM load condition for 15 healthy control subjects and 15 schizophrenia patients. Three components emerged, reflecting activated (task-positive) and deactivated (task-negative or default-mode) neural networks. Two of the components (with both task-positive and task-negative aspects) were load dependent, were involved in encoding and delay phases (one exclusively encoding and the other both encoding and delay), and both showed evidence for decreased efficiency in patients. The results suggest that WM capacity is reached sooner for schizophrenia patients as the overt levels of WM load increase, to the point that further increases in overt memory load do not increase fMRI activation, and lead to performance impairments. These results are consistent with an account holding that patients show reduced efficiency in task-positive and task-negative networks during WM and also partially support the shifted inverted-U-shaped curve theory of the relationship between WM load and fMRI activation in schizophrenia. PMID:21224491

Brain systems underlying attentional control and emotional distraction during working memory encoding.

PubMed

Ziaei, Maryam; Peira, Nathalie; Persson, Jonas

2014-02-15

Goal-directed behavior requires that cognitive operations can be protected from emotional distraction induced by task-irrelevant emotional stimuli. The brain processes involved in attending to relevant information while filtering out irrelevant information are still largely unknown. To investigate the neural and behavioral underpinnings of attending to task-relevant emotional stimuli while ignoring irrelevant stimuli, we used fMRI to assess brain responses during attentional instructed encoding within an emotional working memory (WM) paradigm. We showed that instructed attention to emotion during WM encoding resulted in enhanced performance, by means of increased memory performance and reduced reaction time, compared to passive viewing. A similar performance benefit was also demonstrated for recognition memory performance, although for positive pictures only. Functional MRI data revealed a network of regions involved in directed attention to emotional information for both positive and negative pictures that included medial and lateral prefrontal cortices, fusiform gyrus, insula, the parahippocampal gyrus, and the amygdala. Moreover, we demonstrate that regions in the striatum, and regions associated with the default-mode network were differentially activated for emotional distraction compared to neutral distraction. Activation in a sub-set of these regions was related to individual differences in WM and recognition memory performance, thus likely contributing to performing the task at an optimal level. The present results provide initial insights into the behavioral and neural consequences of instructed attention and emotional distraction during WM encoding. © 2013.

Is a Responsive Default Mode Network Required for Successful Working Memory Task Performance?

PubMed

Čeko, Marta; Gracely, John L; Fitzcharles, Mary-Ann; Seminowicz, David A; Schweinhardt, Petra; Bushnell, M Catherine

2015-08-19

In studies of cognitive processing using tasks with externally directed attention, regions showing increased (external-task-positive) and decreased or "negative" [default-mode network (DMN)] fMRI responses during task performance are dynamically responsive to increasing task difficulty. Responsiveness (modulation of fMRI signal by increasing load) has been linked directly to successful cognitive task performance in external-task-positive regions but not in DMN regions. To investigate whether a responsive DMN is required for successful cognitive performance, we compared healthy human subjects (n = 23) with individuals shown to have decreased DMN engagement (chronic pain patients, n = 28). Subjects performed a multilevel working-memory task (N-back) during fMRI. If a responsive DMN is required for successful performance, patients having reduced DMN responsiveness should show worsened performance; if performance is not reduced, their brains should show compensatory activation in external-task-positive regions or elsewhere. All subjects showed decreased accuracy and increased reaction times with increasing task level, with no significant group differences on either measure at any level. Patients had significantly reduced negative fMRI response (deactivation) of DMN regions (posterior cingulate/precuneus, medial prefrontal cortex). Controls showed expected modulation of DMN deactivation with increasing task difficulty. Patients showed significantly reduced modulation of DMN deactivation by task difficulty, despite their successful task performance. We found no evidence of compensatory neural recruitment in external-task-positive regions or elsewhere. Individual responsiveness of the external-task-positive ventrolateral prefrontal cortex, but not of DMN regions, correlated with task accuracy. These findings suggest that a responsive DMN may not be required for successful cognitive performance; a responsive external-task-positive network may be sufficient. We studied the relationship between responsiveness of the brain to increasing task demand and successful cognitive performance, using chronic pain patients as a probe. fMRI working memory studies show that two main cognitive networks ["external-task positive" and "default-mode network" (DMN)] are responsive to increasing task difficulty. The responsiveness of both of these brain networks is suggested to be required for successful task performance. The responsiveness of external-task-positive regions has been linked directly to successful cognitive task performance, as we also show here. However, pain patients show decreased engagement and responsiveness of the DMN but can perform a working memory task as well as healthy subjects, without demonstrable compensatory neural recruitment. Therefore, a responsive DMN might not be needed for successful cognitive performance. Copyright © 2015 the authors 0270-6474/15/3511596-11$15.00/0.

Whole-brain functional connectivity during acquisition of novel grammar: Distinct functional networks depend on language learning abilities.

PubMed

Kepinska, Olga; de Rover, Mischa; Caspers, Johanneke; Schiller, Niels O

2017-03-01

In an effort to advance the understanding of brain function and organisation accompanying second language learning, we investigate the neural substrates of novel grammar learning in a group of healthy adults, consisting of participants with high and average language analytical abilities (LAA). By means of an Independent Components Analysis, a data-driven approach to functional connectivity of the brain, the fMRI data collected during a grammar-learning task were decomposed into maps representing separate cognitive processes. These included the default mode, task-positive, working memory, visual, cerebellar and emotional networks. We further tested for differences within the components, representing individual differences between the High and Average LAA learners. We found high analytical abilities to be coupled with stronger contributions to the task-positive network from areas adjacent to bilateral Broca's region, stronger connectivity within the working memory network and within the emotional network. Average LAA participants displayed stronger engagement within the task-positive network from areas adjacent to the right-hemisphere homologue of Broca's region and typical to lower level processing (visual word recognition), and increased connectivity within the default mode network. The significance of each of the identified networks for the grammar learning process is presented next to a discussion on the established markers of inter-individual learners' differences. We conclude that in terms of functional connectivity, the engagement of brain's networks during grammar acquisition is coupled with one's language learning abilities. Copyright © 2016 Elsevier B.V. All rights reserved.

Variation in Parasympathetic Dysregulation Moderates Short-term Memory Problems in Childhood Attention-Deficit/Hyperactivity Disorder.

PubMed

Ward, Anthony R; Alarcón, Gabriela; Nigg, Joel T; Musser, Erica D

2015-11-01

Although attention deficit/hyperactivity disorder (ADHD) is associated with impairment in working memory and short-term memory, up to half of individual children with ADHD perform within a normative range. Heterogeneity in other ADHD-related mechanisms, which may compensate for or combine with cognitive weaknesses, is a likely explanation. One candidate is the robustness of parasympathetic regulation (as indexed by respiratory sinus arrhythmia; RSA). Theory and data suggest that a common neural network is likely tied to both heart-rate regulation and certain cognitive functions (including aspects of working and short-term memory). Cardiac-derived indices of parasympathetic reactivity were collected during short-term memory (STM) storage and rehearsal tasks from 243 children (116 ADHD, 127 controls). ADHD was associated with lower STM performance, replicating previous work. In addition, RSA reactivity moderated the association between STM and ADHD - both as a category and a dimension - independent of comorbidity. Specifically, conditional effects revealed that high levels of withdrawal interacted with weakened STM but high levels of augmentation moderated a positive association predicting ADHD. Thus, variations in parasympathetic reactivity may help explain neuropsychological heterogeneity in ADHD.

Cognitive Activation by Central Thalamic Stimulation: The Yerkes-Dodson Law Revisited.

PubMed Central

Mair, Robert G.; Onos, Kristen D.; Hembrook, Jacqueline R.

2011-01-01

Central thalamus regulates forebrain arousal, influencing activity in distributed neural networks that give rise to organized actions during alert, wakeful states. Central thalamus has been implicated in working memory by the effects of lesions and microinjected drugs in this part of the brain. Lesions and drugs that inhibit neural activity have been found to impair working memory. Drugs that increase activity have been found to enhance and impair memory depending on the dose tested. Electrical deep brain stimulation (DBS) similarly enhances working memory at low stimulating currents and impairs it at higher currents. These effects are time dependent. They were observed when DBS was applied during the memory delay (retention) or choice response (retrieval) but not earlier in trials during the sample (acquisition) phase. The effects of microinjected drugs and DBS are consistent with the Yerkes-Dodson law, which describes an inverted-U relationship between arousal and behavioral performance. Alternatively these results may reflect desensitization associated with higher levels of stimulation, spread of drugs or current to adjacent structures, or activation of less sensitive neurons or receptors at higher DBS currents or drug doses. PMID:22013395

Subtypes and comorbidity in mathematical learning disabilities: Multidimensional study of verbal and visual memory processes is key to understanding.

PubMed

Szűcs, D

2016-01-01

A large body of research suggests that mathematical learning disability (MLD) is related to working memory impairment. Here, I organize part of this literature through a meta-analysis of 36 studies with 665 MLD and 1049 control participants. I demonstrate that one subtype of MLD is associated with reading problems and weak verbal short-term and working memory. Another subtype of MLD does not have associated reading problems and is linked to weak visuospatial short-term and working memory. In order to better understand MLD we need to precisely define potentially modality-specific memory subprocesses and supporting executive functions, relevant for mathematical learning. This can be achieved by taking a multidimensional parametric approach systematically probing an extended network of cognitive functions. Rather than creating arbitrary subgroups and/or focus on a single factor, highly powered studies need to position individuals in a multidimensional parametric space. This will allow us to understand the multidimensional structure of cognitive functions and their relationship to mathematical performance. © 2016 Elsevier B.V. All rights reserved.

Male veterans with PTSD exhibit aberrant neural dynamics during working memory processing: an MEG study

PubMed Central

McDermott, Timothy J.; Badura-Brack, Amy S.; Becker, Katherine M.; Ryan, Tara J.; Khanna, Maya M.; Heinrichs-Graham, Elizabeth; Wilson, Tony W.

2016-01-01

Background Posttraumatic stress disorder (PTSD) is associated with executive functioning deficits, including disruptions in working memory. In this study, we examined the neural dynamics of working memory processing in veterans with PTSD and a matched healthy control sample using magnetoencephalography (MEG). Methods Our sample of recent combat veterans with PTSD and demographically matched participants without PTSD completed a working memory task during a 306-sensor MEG recording. The MEG data were preprocessed and transformed into the time-frequency domain. Significant oscillatory brain responses were imaged using a beamforming approach to identify spatiotemporal dynamics. Results Fifty-one men were included in our analyses: 27 combat veterans with PTSD and 24 controls. Across all participants, a dynamic wave of neural activity spread from posterior visual cortices to left frontotemporal regions during encoding, consistent with a verbal working memory task, and was sustained throughout maintenance. Differences related to PTSD emerged during early encoding, with patients exhibiting stronger α oscillatory responses than controls in the right inferior frontal gyrus (IFG). Differences spread to the right supramarginal and temporal cortices during later encoding where, along with the right IFG, they persisted throughout the maintenance period. Limitations This study focused on men with combat-related PTSD using a verbal working memory task. Future studies should evaluate women and the impact of various traumatic experiences using diverse tasks. Conclusion Posttraumatic stress disorder is associated with neurophysiological abnormalities during working memory encoding and maintenance. Veterans with PTSD engaged a bilateral network, including the inferior prefrontal cortices and supramarginal gyri. Right hemispheric neural activity likely reflects compensatory processing, as veterans with PTSD work to maintain accurate performance despite known cognitive deficits associated with the disorder. PMID:26645740

Synaptic augmentation in a cortical circuit model reproduces serial dependence in visual working memory

PubMed Central

D’Esposito, Mark

2017-01-01

Recent work has established that visual working memory is subject to serial dependence: current information in memory blends with that from the recent past as a function of their similarity. This tuned temporal smoothing likely promotes the stability of memory in the face of noise and occlusion. Serial dependence accumulates over several seconds in memory and deteriorates with increased separation between trials. While this phenomenon has been extensively characterized in behavior, its neural mechanism is unknown. In the present study, we investigate the circuit-level origins of serial dependence in a biophysical model of cortex. We explore two distinct kinds of mechanisms: stable persistent activity during the memory delay period and dynamic “activity-silent” synaptic plasticity. We find that networks endowed with both strong reverberation to support persistent activity and dynamic synapses can closely reproduce behavioral serial dependence. Specifically, elevated activity drives synaptic augmentation, which biases activity on the subsequent trial, giving rise to a spatiotemporally tuned shift in the population response. Our hybrid neural model is a theoretical advance beyond abstract mathematical characterizations, offers testable hypotheses for physiological research, and demonstrates the power of biological insights to provide a quantitative explanation of human behavior. PMID:29244810

Iconic memory and parietofrontal network: fMRI study using temporal integration.

PubMed

Saneyoshi, Ayako; Niimi, Ryosuke; Suetsugu, Tomoko; Kaminaga, Tatsuro; Yokosawa, Kazuhiko

2011-08-03

We investigated the neural basis of iconic memory using functional magnetic resonance imaging. The parietofrontal network of selective attention is reportedly relevant to readout from iconic memory. We adopted a temporal integration task that requires iconic memory but not selective attention. The results showed that the task activated the parietofrontal network, confirming that the network is involved in readout from iconic memory. We further tested a condition in which temporal integration was performed by visual short-term memory but not by iconic memory. However, no brain region revealed higher activation for temporal integration by iconic memory than for temporal integration by visual short-term memory. This result suggested that there is no localized brain region specialized for iconic memory per se.

Plastic modulation of episodic memory networks in the aging brain with cognitive decline.

PubMed

Bai, Feng; Yuan, Yonggui; Yu, Hui; Zhang, Zhijun

2016-07-15

Social-cognitive processing has been posited to underlie general functions such as episodic memory. Episodic memory impairment is a recognized hallmark of amnestic mild cognitive impairment (aMCI) who is at a high risk for dementia. Three canonical networks, self-referential processing, executive control processing and salience processing, have distinct roles in episodic memory retrieval processing. It remains unclear whether and how these sub-networks of the episodic memory retrieval system would be affected in aMCI. This task-state fMRI study constructed systems-level episodic memory retrieval sub-networks in 28 aMCI and 23 controls using two computational approaches: a multiple region-of-interest based approach and a voxel-level functional connectivity-based approach, respectively. These approaches produced the remarkably similar findings that the self-referential processing network made critical contributions to episodic memory retrieval in aMCI. More conspicuous alterations in self-referential processing of the episodic memory retrieval network were identified in aMCI. In order to complete a given episodic memory retrieval task, increases in cooperation between the self-referential processing network and other sub-networks were mobilized in aMCI. Self-referential processing mediate the cooperation of the episodic memory retrieval sub-networks as it may help to achieve neural plasticity and may contribute to the prevention and treatment of dementia. Copyright © 2016 Elsevier B.V. All rights reserved.

How activation, entanglement, and searching a semantic network contribute to event memory.

PubMed

Nelson, Douglas L; Kitto, Kirsty; Galea, David; McEvoy, Cathy L; Bruza, Peter D

2013-08-01

Free-association norms indicate that words are organized into semantic/associative neighborhoods within a larger network of words and links that bind the net together. We present evidence indicating that memory for a recent word event can depend on implicitly and simultaneously activating related words in its neighborhood. Processing a word during encoding primes its network representation as a function of the density of the links in its neighborhood. Such priming increases recall and recognition and can have long-lasting effects when the word is processed in working memory. Evidence for this phenomenon is reviewed in extralist-cuing, primed free-association, intralist-cuing, and single-item recognition tasks. The findings also show that when a related word is presented in order to cue the recall of a studied word, the cue activates the target in an array of related words that distract and reduce the probability of the target's selection. The activation of the semantic network produces priming benefits during encoding, and search costs during retrieval. In extralist cuing, recall is a negative function of cue-to-distractor strength, and a positive function of neighborhood density, cue-to-target strength, and target-to-cue strength. We show how these four measures derived from the network can be combined and used to predict memory performance. These measures play different roles in different tasks, indicating that the contribution of the semantic network varies with the context provided by the task. Finally, we evaluate spreading-activation and quantum-like entanglement explanations for the priming effects produced by neighborhood density.

Image watermarking capacity analysis based on Hopfield neural network

NASA Astrophysics Data System (ADS)

Zhang, Fan; Zhang, Hongbin

2004-11-01

In watermarking schemes, watermarking can be viewed as a form of communication problems. Almost all of previous works on image watermarking capacity are based on information theory, using Shannon formula to calculate the capacity of watermarking. In this paper, we present a blind watermarking algorithm using Hopfield neural network, and analyze watermarking capacity based on neural network. In our watermarking algorithm, watermarking capacity is decided by attraction basin of associative memory.

The role of autobiographical memory networks in the experience of negative emotions: how our remembered past elicits our current feelings.

PubMed

Philippe, Frederick L; Koestner, Richard; Lecours, Serge; Beaulieu-Pelletier, Genevieve; Bois, Katy

2011-12-01

The present research examined the role of autobiographical memory networks on negative emotional experiences. Results from 2 studies found support for an active but also discriminant role of autobiographical memories and their related networked memories on negative emotions. In addition, in line with self-determination theory, thwarting of the psychological needs for competence, autonomy, and relatedness was found to be the critical component of autobiographical memory affecting negative emotional experiences. Study 1 revealed that need thwarting in a specific autobiographical memory network related to the theme of loss was positively associated with depressive negative emotions, but not with other negative emotions. Study 2 showed within a prospective design a differential predictive validity between 2 autobiographical memory networks (an anger-related vs. a guilt-related memory) on situational anger reactivity with respect to unfair treatment. All of these results held after controlling for neuroticism (Studies 1 and 2), self-control (Study 2), and for the valence (Study 1) and emotions (Study 2) found in the measured autobiographical memory network. These findings highlight the ongoing emotional significance of representations of need thwarting in autobiographical memory networks. (c) 2011 APA, all rights reserved.

A model of individualized canonical microcircuits supporting cognitive operations

PubMed Central

Peterson, Andre D. H.; Haueisen, Jens; Knösche, Thomas R.

2017-01-01

Major cognitive functions such as language, memory, and decision-making are thought to rely on distributed networks of a large number of basic elements, called canonical microcircuits. In this theoretical study we propose a novel canonical microcircuit model and find that it supports two basic computational operations: a gating mechanism and working memory. By means of bifurcation analysis we systematically investigate the dynamical behavior of the canonical microcircuit with respect to parameters that govern the local network balance, that is, the relationship between excitation and inhibition, and key intrinsic feedback architectures of canonical microcircuits. We relate the local behavior of the canonical microcircuit to cognitive processing and demonstrate how a network of interacting canonical microcircuits enables the establishment of spatiotemporal sequences in the context of syntax parsing during sentence comprehension. This study provides a framework for using individualized canonical microcircuits for the construction of biologically realistic networks supporting cognitive operations. PMID:29200435

Lexical processing and organization in bilingual first language acquisition: Guiding future research.

PubMed

DeAnda, Stephanie; Poulin-Dubois, Diane; Zesiger, Pascal; Friend, Margaret

2016-06-01

A rich body of work in adult bilinguals documents an interconnected lexical network across languages, such that early word retrieval is language independent. This literature has yielded a number of influential models of bilingual semantic memory. However, extant models provide limited predictions about the emergence of lexical organization in bilingual first language acquisition (BFLA). Empirical evidence from monolingual infants suggests that lexical networks emerge early in development as children integrate phonological and semantic information. These findings tell us little about the interaction between 2 languages in early bilingual memory. To date, an understanding of when and how languages interact in early bilingual development is lacking. In this literature review, we present research documenting lexical-semantic development across monolingual and bilingual infants. This is followed by a discussion of current models of bilingual language representation and organization and their ability to account for the available empirical evidence. Together, these theoretical and empirical accounts inform and highlight unexplored areas of research and guide future work on early bilingual memory. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

Resisting attraction: Individual differences in executive control are associated with subject-verb agreement errors in production.

PubMed

Veenstra, Alma; Antoniou, Kyriakos; Katsos, Napoleon; Kissine, Mikhail

2018-04-19

We propose that attraction errors in agreement production (e.g., the key to the cabinets are missing) are related to two components of executive control: working memory and inhibitory control. We tested 138 children aged 10 to 12, an age when children are expected to produce high rates of errors. To increase the potential of individual variation in executive control skills, participants came from monolingual, bilingual, and bidialectal language backgrounds. Attraction errors were elicited with a picture description task in Dutch and executive control was measured with a digit span task, Corsi blocks task, switching task, and attentional networks task. Overall, higher rates of attraction errors were negatively associated with higher verbal working memory and, independently, with higher inhibitory control. To our knowledge, this is the first demonstration of the role of both working memory and inhibitory control in attraction errors in production. Implications for memory- and grammar-based models are discussed. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

Associative memory for online learning in noisy environments using self-organizing incremental neural network.

PubMed

Sudo, Akihito; Sato, Akihiro; Hasegawa, Osamu

2009-06-01

Associative memory operating in a real environment must perform well in online incremental learning and be robust to noisy data because noisy associative patterns are presented sequentially in a real environment. We propose a novel associative memory that satisfies these requirements. Using the proposed method, new associative pairs that are presented sequentially can be learned accurately without forgetting previously learned patterns. The memory size of the proposed method increases adaptively with learning patterns. Therefore, it suffers neither redundancy nor insufficiency of memory size, even in an environment in which the maximum number of associative pairs to be presented is unknown before learning. Noisy inputs in real environments are classifiable into two types: noise-added original patterns and faultily presented random patterns. The proposed method deals with two types of noise. To our knowledge, no conventional associative memory addresses noise of both types. The proposed associative memory performs as a bidirectional one-to-many or many-to-one associative memory and deals not only with bipolar data, but also with real-valued data. Results demonstrate that the proposed method's features are important for application to an intelligent robot operating in a real environment. The originality of our work consists of two points: employing a growing self-organizing network for an associative memory, and discussing what features are necessary for an associative memory for an intelligent robot and proposing an associative memory that satisfies those requirements.

The Longitudinal Trajectory of Default Mode Network Connectivity in Healthy Older Adults Varies As a Function of Age and Is Associated with Changes in Episodic Memory and Processing Speed.

PubMed

Staffaroni, Adam M; Brown, Jesse A; Casaletto, Kaitlin B; Elahi, Fanny M; Deng, Jersey; Neuhaus, John; Cobigo, Yann; Mumford, Paige S; Walters, Samantha; Saloner, Rowan; Karydas, Anna; Coppola, Giovanni; Rosen, Howie J; Miller, Bruce L; Seeley, William W; Kramer, Joel H

2018-03-14

The default mode network (DMN) supports memory functioning and may be sensitive to preclinical Alzheimer's pathology. Little is known, however, about the longitudinal trajectory of this network's intrinsic functional connectivity (FC). In this study, we evaluated longitudinal FC in 111 cognitively normal older human adults (ages 49-87, 46 women/65 men), 92 of whom had at least three task-free fMRI scans ( n = 353 total scans). Whole-brain FC and three DMN subnetworks were assessed: (1) within-DMN, (2) between anterior and posterior DMN, and (3) between medial temporal lobe network and posterior DMN. Linear mixed-effects models demonstrated significant baseline age × time interactions, indicating a nonlinear trajectory. There was a trend toward increasing FC between ages 50-66 and significantly accelerating declines after age 74. A similar interaction was observed for whole-brain FC. APOE status did not predict baseline connectivity or change in connectivity. After adjusting for network volume, changes in within-DMN connectivity were specifically associated with changes in episodic memory and processing speed but not working memory or executive functions. The relationship with processing speed was attenuated after covarying for white matter hyperintensities (WMH) and whole-brain FC, whereas within-DMN connectivity remained associated with memory above and beyond WMH and whole-brain FC. Whole-brain and DMN FC exhibit a nonlinear trajectory, with more rapid declines in older age and possibly increases in connectivity early in the aging process. Within-DMN connectivity is a marker of episodic memory performance even among cognitively healthy older adults. SIGNIFICANCE STATEMENT Default mode network and whole-brain connectivity, measured using task-free fMRI, changed nonlinearly as a function of age, with some suggestion of early increases in connectivity. For the first time, longitudinal changes in DMN connectivity were shown to correlate with changes in episodic memory, whereas volume changes in relevant brain regions did not. This relationship was not accounted for by white matter hyperintensities or mean whole-brain connectivity. Functional connectivity may be an early biomarker of changes in aging but should be used with caution given its nonmonotonic nature, which could complicate interpretation. Future studies investigating longitudinal network changes should consider whole-brain changes in connectivity. Copyright © 2018 the authors 0270-6474/18/382810-09$15.00/0.

Maternal IL-6 during pregnancy can be estimated from newborn brain connectivity and predicts future working memory in offspring.

PubMed

Rudolph, Marc D; Graham, Alice M; Feczko, Eric; Miranda-Dominguez, Oscar; Rasmussen, Jerod M; Nardos, Rahel; Entringer, Sonja; Wadhwa, Pathik D; Buss, Claudia; Fair, Damien A

2018-05-01

Several lines of evidence support the link between maternal inflammation during pregnancy and increased likelihood of neurodevelopmental and psychiatric disorders in offspring. This longitudinal study seeks to advance understanding regarding implications of systemic maternal inflammation during pregnancy, indexed by plasma interleukin-6 (IL-6) concentrations, for large-scale brain system development and emerging executive function skills in offspring. We assessed maternal IL-6 during pregnancy, functional magnetic resonance imaging acquired in neonates, and working memory (an important component of executive function) at 2 years of age. Functional connectivity within and between multiple neonatal brain networks can be modeled to estimate maternal IL-6 concentrations during pregnancy. Brain regions heavily weighted in these models overlap substantially with those supporting working memory in a large meta-analysis. Maternal IL-6 also directly accounts for a portion of the variance of working memory at 2 years of age. Findings highlight the association of maternal inflammation during pregnancy with the developing functional architecture of the brain and emerging executive function.

Neuroanatomic overlap between intelligence and cognitive factors: morphometry methods provide support for the key role of the frontal lobes.

PubMed

Colom, Roberto; Burgaleta, Miguel; Román, Francisco J; Karama, Sherif; Alvarez-Linera, Juan; Abad, Francisco J; Martínez, Kenia; Quiroga, Ma Ángeles; Haier, Richard J

2013-05-15

Evidence from neuroimaging studies suggests that intelligence differences may be supported by a parieto-frontal network. Research shows that this network is also relevant for cognitive functions such as working memory and attention. However, previous studies have not explicitly analyzed the commonality of brain areas between a broad array of intelligence factors and cognitive functions tested in the same sample. Here fluid, crystallized, and spatial intelligence, along with working memory, executive updating, attention, and processing speed were each measured by three diverse tests or tasks. These twenty-one measures were completed by a group of one hundred and four healthy young adults. Three cortical measures (cortical gray matter volume, cortical surface area, and cortical thickness) were regressed against psychological latent scores obtained from a confirmatory factor analysis for removing test and task specific variance. For cortical gray matter volume and cortical surface area, the main overlapping clusters were observed in the middle frontal gyrus and involved fluid intelligence and working memory. Crystallized intelligence showed an overlapping cluster with fluid intelligence and working memory in the middle frontal gyrus. The inferior frontal gyrus showed overlap for crystallized intelligence, spatial intelligence, attention, and processing speed. The fusiform gyrus in temporal cortex showed overlap for spatial intelligence and attention. Parietal and occipital areas did not show any overlap across intelligence and cognitive factors. Taken together, these findings underscore that structural features of gray matter in the frontal lobes support those aspects of intelligence related to basic cognitive processes. Copyright © 2013 Elsevier Inc. All rights reserved.

Triple representation of language, working memory, social and emotion processing in the cerebellum: convergent evidence from task and seed-based resting-state fMRI analyses in a single large cohort.

PubMed

Guell, Xavier; Gabrieli, John D E; Schmahmann, Jeremy D

2018-05-15

Delineation of functional topography is critical to the evolving understanding of the cerebellum's role in a wide range of nervous system functions. We used data from the Human Connectome Project (n = 787) to analyze cerebellar fMRI task activation (motor, working memory, language, social and emotion processing) and resting-state functional connectivity calculated from cerebral cortical seeds corresponding to the peak Cohen's d of each task contrast. The combination of exceptional statistical power, activation from both motor and multiple non-motor tasks in the same participants, and convergent resting-state networks in the same participants revealed novel aspects of the functional topography of the human cerebellum. Consistent with prior studies there were two distinct representations of motor activation. Newly revealed were three distinct representations each for working memory, language, social, and emotional task processing that were largely separate for these four cognitive and affective domains. In most cases, the task-based activations and the corresponding resting-network correlations were congruent in identifying the two motor representations and the three non-motor representations that were unique to working memory, language, social cognition, and emotion. The definitive localization and characterization of distinct triple representations for cognition and emotion task processing in the cerebellum opens up new basic science questions as to why there are triple representations (what different functions are enabled by the different representations?) and new clinical questions (what are the differing consequences of lesions to the different representations?). Copyright © 2018 Elsevier Inc. All rights reserved.

How to Compress Sequential Memory Patterns into Periodic Oscillations: General Reduction Rules

PubMed Central

Zhang, Kechen

2017-01-01

A neural network with symmetric reciprocal connections always admits a Lyapunov function, whose minima correspond to the memory states stored in the network. Networks with suitable asymmetric connections can store and retrieve a sequence of memory patterns, but the dynamics of these networks cannot be characterized as readily as that of the symmetric networks due to the lack of established general methods. Here, a reduction method is developed for a class of asymmetric attractor networks that store sequences of activity patterns as associative memories, as in a Hopfield network. The method projects the original activity pattern of the network to a low-dimensional space such that sequential memory retrievals in the original network correspond to periodic oscillations in the reduced system. The reduced system is self-contained and provides quantitative information about the stability and speed of sequential memory retrievals in the original network. The time evolution of the overlaps between the network state and the stored memory patterns can also be determined from extended reduced systems. The reduction procedure can be summarized by a few reduction rules, which are applied to several network models, including coupled networks and networks with time-delayed connections, and the analytical solutions of the reduced systems are confirmed by numerical simulations of the original networks. Finally, a local learning rule that provides an approximation to the connection weights involving the pseudoinverse is also presented. PMID:24877729

Visual Working Memory Capacity: From Psychophysics and Neurobiology to Individual Differences

PubMed Central

Luck, Steven J.; Vogel, Edward K.

2013-01-01

Visual working memory capacity is of great interest because it is strongly correlated with overall cognitive ability, can be understood at the level of neural circuits, and is easily measured. Recent studies have shown that capacity influences tasks ranging from saccade targeting to analogical reasoning. A debate has arisen over whether capacity is constrained by a limited number of discrete representations or by an infinitely divisible resource, but the empirical evidence and neural network models currently favor a discrete item limit. Capacity differs markedly across individuals and groups, and recent research indicates that some of these differences reflect true differences in storage capacity whereas others reflect variations in the ability to use memory capacity efficiently. PMID:23850263

JuxtaView - A tool for interactive visualization of large imagery on scalable tiled displays

USGS Publications Warehouse

Krishnaprasad, N.K.; Vishwanath, V.; Venkataraman, S.; Rao, A.G.; Renambot, L.; Leigh, J.; Johnson, A.E.; Davis, B.

2004-01-01

JuxtaView is a cluster-based application for viewing ultra-high-resolution images on scalable tiled displays. We present in JuxtaView, a new parallel computing and distributed memory approach for out-of-core montage visualization, using LambdaRAM, a software-based network-level cache system. The ultimate goal of JuxtaView is to enable a user to interactively roam through potentially terabytes of distributed, spatially referenced image data such as those from electron microscopes, satellites and aerial photographs. In working towards this goal, we describe our first prototype implemented over a local area network, where the image is distributed using LambdaRAM, on the memory of all nodes of a PC cluster driving a tiled display wall. Aggressive pre-fetching schemes employed by LambdaRAM help to reduce latency involved in remote memory access. We compare LambdaRAM with a more traditional memory-mapped file approach for out-of-core visualization. ?? 2004 IEEE.

Preventing academic difficulties in preterm children: a randomised controlled trial of an adaptive working memory training intervention - IMPRINT study.

PubMed

Pascoe, Leona; Roberts, Gehan; Doyle, Lex W; Lee, Katherine J; Thompson, Deanne K; Seal, Marc L; Josev, Elisha K; Nosarti, Chiara; Gathercole, Susan; Anderson, Peter J

2013-09-16

Very preterm children exhibit difficulties in working memory, a key cognitive ability vital to learning information and the development of academic skills. Previous research suggests that an adaptive working memory training intervention (Cogmed) may improve working memory and other cognitive and behavioural domains, although further randomised controlled trials employing long-term outcomes are needed, and with populations at risk for working memory deficits, such as children born preterm.In a cohort of extremely preterm (<28 weeks' gestation)/extremely low birthweight (<1000 g) 7-year-olds, we will assess the effectiveness of Cogmed in improving academic functioning 2 years' post-intervention. Secondary objectives are to assess the effectiveness of Cogmed in improving working memory and attention 2 weeks', 12 months' and 24 months' post-intervention, and to investigate training related neuroplasticity in working memory neural networks 2 weeks' post-intervention. This double-blind, placebo-controlled, randomised controlled trial aims to recruit 126 extremely preterm/extremely low birthweight 7-year-old children. Children attending mainstream school without major intellectual, sensory or physical impairments will be eligible. Participating children will undergo an extensive baseline cognitive assessment before being randomised to either an adaptive or placebo (non-adaptive) version of Cogmed. Cogmed is a computerised working memory training program consisting of 25 sessions completed over a 5 to 7 week period. Each training session takes approximately 35 minutes and will be completed in the child's home. Structural, diffusion and functional Magnetic Resonance Imaging, which is optional for participants, will be completed prior to and 2 weeks following the training period. Follow-up assessments focusing on academic skills (primary outcome), working memory and attention (secondary outcomes) will be conducted at 2 weeks', 12 months' and 24 months' post-intervention. To our knowledge, this study will be the first randomised controlled trial to (a) assess the effectiveness of Cogmed in school-aged extremely preterm/extremely low birthweight children, while incorporating advanced imaging techniques to investigate neural changes associated with adaptive working memory training, and (b) employ long-term follow-up to assess the potential benefit of improved working memory on academic functioning. If effective, Cogmed would serve as a valuable, available intervention for improving developmental outcomes for this population. Australian New Zealand Clinical Trials Registry ACTRN12612000124831.

Encoding, rehearsal, and recall in signers and speakers: shared network but differential engagement.

PubMed

Bavelier, D; Newman, A J; Mukherjee, M; Hauser, P; Kemeny, S; Braun, A; Boutla, M

2008-10-01

Short-term memory (STM), or the ability to hold verbal information in mind for a few seconds, is known to rely on the integrity of a frontoparietal network of areas. Here, we used functional magnetic resonance imaging to ask whether a similar network is engaged when verbal information is conveyed through a visuospatial language, American Sign Language, rather than speech. Deaf native signers and hearing native English speakers performed a verbal recall task, where they had to first encode a list of letters in memory, maintain it for a few seconds, and finally recall it in the order presented. The frontoparietal network described to mediate STM in speakers was also observed in signers, with its recruitment appearing independent of the modality of the language. This finding supports the view that signed and spoken STM rely on similar mechanisms. However, deaf signers and hearing speakers differentially engaged key structures of the frontoparietal network as the stages of STM unfold. In particular, deaf signers relied to a greater extent than hearing speakers on passive memory storage areas during encoding and maintenance, but on executive process areas during recall. This work opens new avenues for understanding similarities and differences in STM performance in signers and speakers.

Encoding, Rehearsal, and Recall in Signers and Speakers: Shared Network but Differential Engagement

PubMed Central

Newman, A. J.; Mukherjee, M.; Hauser, P.; Kemeny, S.; Braun, A.; Boutla, M.

2008-01-01

Short-term memory (STM), or the ability to hold verbal information in mind for a few seconds, is known to rely on the integrity of a frontoparietal network of areas. Here, we used functional magnetic resonance imaging to ask whether a similar network is engaged when verbal information is conveyed through a visuospatial language, American Sign Language, rather than speech. Deaf native signers and hearing native English speakers performed a verbal recall task, where they had to first encode a list of letters in memory, maintain it for a few seconds, and finally recall it in the order presented. The frontoparietal network described to mediate STM in speakers was also observed in signers, with its recruitment appearing independent of the modality of the language. This finding supports the view that signed and spoken STM rely on similar mechanisms. However, deaf signers and hearing speakers differentially engaged key structures of the frontoparietal network as the stages of STM unfold. In particular, deaf signers relied to a greater extent than hearing speakers on passive memory storage areas during encoding and maintenance, but on executive process areas during recall. This work opens new avenues for understanding similarities and differences in STM performance in signers and speakers. PMID:18245041

Jordan recurrent neural network versus IHACRES in modelling daily streamflows

NASA Astrophysics Data System (ADS)

Carcano, Elena Carla; Bartolini, Paolo; Muselli, Marco; Piroddi, Luigi

2008-12-01

SummaryA study of possible scenarios for modelling streamflow data from daily time series, using artificial neural networks (ANNs), is presented. Particular emphasis is devoted to the reconstruction of drought periods where water resource management and control are most critical. This paper considers two connectionist models: a feedforward multilayer perceptron (MLP) and a Jordan recurrent neural network (JNN), comparing network performance on real world data from two small catchments (192 and 69 km 2 in size) with irregular and torrential regimes. Several network configurations are tested to ensure a good combination of input features (rainfall and previous streamflow data) that capture the variability of the physical processes at work. Tapped delayed line (TDL) and memory effect techniques are introduced to recognize and reproduce temporal dependence. Results show a poor agreement when using TDL only, but a remarkable improvement can be obtained with JNN and its memory effect procedures, which are able to reproduce the system memory over a catchment in a more effective way. Furthermore, the IHACRES conceptual model, which relies on both rainfall and temperature input data, is introduced for comparative study. The results suggest that when good input data is unavailable, metric models perform better than conceptual ones and, in general, it is difficult to justify substantial conceptualization of complex processes.

A statistical mechanics approach to autopoietic immune networks

NASA Astrophysics Data System (ADS)

Barra, Adriano; Agliari, Elena

2010-07-01

In this work we aim to bridge theoretical immunology and disordered statistical mechanics. We introduce a model for the behavior of B-cells which naturally merges the clonal selection theory and the autopoietic network theory as a whole. From the analysis of its features we recover several basic phenomena such as low-dose tolerance, dynamical memory of antigens and self/non-self discrimination.

The functional neuroanatomy of multitasking: combining dual tasking with a short term memory task.

PubMed

Deprez, Sabine; Vandenbulcke, Mathieu; Peeters, Ron; Emsell, Louise; Amant, Frederic; Sunaert, Stefan

2013-09-01

Insight into the neural architecture of multitasking is crucial when investigating the pathophysiology of multitasking deficits in clinical populations. Presently, little is known about how the brain combines dual-tasking with a concurrent short-term memory task, despite the relevance of this mental operation in daily life and the frequency of complaints related to this process, in disease. In this study we aimed to examine how the brain responds when a memory task is added to dual-tasking. Thirty-three right-handed healthy volunteers (20 females, mean age 39.9 ± 5.8) were examined with functional brain imaging (fMRI). The paradigm consisted of two cross-modal single tasks (a visual and auditory temporal same-different task with short delay), a dual-task combining both single tasks simultaneously and a multi-task condition, combining the dual-task with an additional short-term memory task (temporal same-different visual task with long delay). Dual-tasking compared to both individual visual and auditory single tasks activated a predominantly right-sided fronto-parietal network and the cerebellum. When adding the additional short-term memory task, a larger and more bilateral frontoparietal network was recruited. We found enhanced activity during multitasking in components of the network that were already involved in dual-tasking, suggesting increased working memory demands, as well as recruitment of multitask-specific components including areas that are likely to be involved in online holding of visual stimuli in short-term memory such as occipito-temporal cortex. These results confirm concurrent neural processing of a visual short-term memory task during dual-tasking and provide evidence for an effective fMRI multitasking paradigm. © 2013 Elsevier Ltd. All rights reserved.

Hopfield neural network and optical fiber sensor as intelligent heart rate monitor

NASA Astrophysics Data System (ADS)

Mutter, Kussay Nugamesh

2018-01-01

This paper presents a design and fabrication of an intelligent fiber-optic sensor used for examining and monitoring heart rate activity. It is found in the literature that the use of fiber sensors as heart rate sensor is widely studied. However, the use of smart sensors based on Hopfield neural networks is very low. In this work, the sensor is a three fibers without cladding of about 1 cm, fed by laser light of 1550 nm of wavelength. The sensing portions are mounted with a micro sensitive diaphragm to transfer the pulse pressure on the left radial wrist. The influenced light intensity will be detected by a three photodetectors as inputs into the Hopfield neural network algorithm. The latter is a singlelayer auto-associative memory structure with a same input and output layers. The prior training weights are stored in the net memory for the standard recorded normal heart rate signals. The sensors' heads work on the reflection intensity basis. The novelty here is that the sensor uses a pulse pressure and Hopfield neural network in an integrity approach. The results showed a significant output measurements of heart rate and counting with a plausible error rate.

Recent developments of functional magnetic resonance imaging research for drug development in Alzheimer's disease.

PubMed

Hampel, Harald; Prvulovic, David; Teipel, Stefan J; Bokde, Arun L W

2011-12-01

The objective of this review is to evaluate recent advances in functional magnetic resonance imaging (fMRI) research in Alzheimer's disease for the development of therapeutic agents. The basic building block underpinning cognition is a brain network. The measured brain activity serves as an integrator of the various components, from genes to structural integrity, that impact the function of networks underpinning cognition. Specific networks can be interrogated using cognitive paradigms such as a learning task or a working memory task. In addition, recent advances in our understanding of neural networks allow one to investigate the function of a brain network by investigating the inherent coherency of the brain networks that can be measured during resting state. The coherent resting state networks allow testing in cognitively impaired patients that may not be possible with the use of cognitive paradigms. In particular the default mode network (DMN) includes the medial temporal lobe and posterior cingulate, two key regions that support episodic memory function and are impaired in the earliest stages of Alzheimer's disease (AD). By investigating the effects of a prospective drug compound on this network, it could illuminate the specificity of the compound with a network supporting memory function. This could provide valuable information on the methods of action at physiological and behaviourally relevant levels. Utilizing fMRI opens up new areas of research and a new approach for drug development, as it is an integrative tool to investigate entire networks within the brain. The network based approach provides a new independent method from previous ones to translate preclinical knowledge into the clinical domain. Copyright © 2011 Elsevier Ltd. All rights reserved.

Multisensory integration processing during olfactory-visual stimulation-An fMRI graph theoretical network analysis.

PubMed

Ripp, Isabelle; Zur Nieden, Anna-Nora; Blankenagel, Sonja; Franzmeier, Nicolai; Lundström, Johan N; Freiherr, Jessica

2018-05-07

In this study, we aimed to understand how whole-brain neural networks compute sensory information integration based on the olfactory and visual system. Task-related functional magnetic resonance imaging (fMRI) data was obtained during unimodal and bimodal sensory stimulation. Based on the identification of multisensory integration processing (MIP) specific hub-like network nodes analyzed with network-based statistics using region-of-interest based connectivity matrices, we conclude the following brain areas to be important for processing the presented bimodal sensory information: right precuneus connected contralaterally to the supramarginal gyrus for memory-related imagery and phonology retrieval, and the left middle occipital gyrus connected ipsilaterally to the inferior frontal gyrus via the inferior fronto-occipital fasciculus including functional aspects of working memory. Applied graph theory for quantification of the resulting complex network topologies indicates a significantly increased global efficiency and clustering coefficient in networks including aspects of MIP reflecting a simultaneous better integration and segregation. Graph theoretical analysis of positive and negative network correlations allowing for inferences about excitatory and inhibitory network architectures revealed-not significant, but very consistent-that MIP-specific neural networks are dominated by inhibitory relationships between brain regions involved in stimulus processing. © 2018 Wiley Periodicals, Inc.

From network heterogeneities to familiarity detection and hippocampal memory management

PubMed Central

Wang, Jane X.; Poe, Gina; Zochowski, Michal

2009-01-01

Hippocampal-neocortical interactions are key to the rapid formation of novel associative memories in the hippocampus and consolidation to long term storage sites in the neocortex. We investigated the role of network correlates during information processing in hippocampal-cortical networks. We found that changes in the intrinsic network dynamics due to the formation of structural network heterogeneities alone act as a dynamical and regulatory mechanism for stimulus novelty and familiarity detection, thereby controlling memory management in the context of memory consolidation. This network dynamic, coupled with an anatomically established feedback between the hippocampus and the neocortex, recovered heretofore unexplained properties of neural activity patterns during memory management tasks which we observed during sleep in multiunit recordings from behaving animals. Our simple dynamical mechanism shows an experimentally matched progressive shift of memory activation from the hippocampus to the neocortex and thus provides the means to achieve an autonomous off-line progression of memory consolidation. PMID:18999453

Mnemonic training reshapes brain networks to support superior memory

PubMed Central

Dresler, Martin; Shirer, William R.; Konrad, Boris N.; Müller, Nils C.J.; Wagner, Isabella C.; Fernández, Guillén; Czisch, Michael; Greicius, Michael D.

2017-01-01

Summary Memory skills strongly differ across the general population, however little is known about the brain characteristics supporting superior memory performance. Here, we assess functional brain network organization of 23 of the world’s most successful memory athletes and matched controls by fMRI during both task-free resting state baseline and active memory encoding. We demonstrate that in a group of naïve controls, functional connectivity changes induced by six weeks of mnemonic training were correlated with the network organization that distinguishes athletes from controls. During rest, this effect was mainly driven by connections between rather than within the visual, medial temporal lobe and default mode networks, whereas during task it was driven by connectivity within these networks. Similarity with memory athlete connectivity patterns predicted memory improvements up to 4 months after training. In conclusion, mnemonic training drives distributed rather than regional changes, reorganizing the brain’s functional network organization to enable superior memory performance. PMID:28279356

Distinct Neural Circuits Support Transient and Sustained Processes in Prospective Memory and Working Memory

PubMed Central

West, Robert; Braver, Todd

2009-01-01

Current theories are divided as to whether prospective memory (PM) involves primarily sustained processes such as strategic monitoring, or transient processes such as the retrieval of intentions from memory when a relevant cue is encountered. The current study examined the neural correlates of PM using a functional magnetic resonance imaging design that allows for the decomposition of brain activity into sustained and transient components. Performance of the PM task was primarily associated with sustained responses in a network including anterior prefrontal cortex (lateral Brodmann area 10), and these responses were dissociable from sustained responses associated with active maintenance in working memory. Additionally, the sustained responses in anterior prefrontal cortex correlated with faster response times for prospective responses. Prospective cues also elicited selective transient activity in a region of interest along the right middle temporal gyrus. The results support the conclusion that both sustained and transient processes contribute to efficient PM and provide novel constraints on the functional role of anterior PFC in higher-order cognition. PMID:18854581

Apolipoprotein E (APOE) genotype has dissociable effects on memory and attentional-executive network function in Alzheimer's disease.

PubMed

Wolk, David A; Dickerson, Bradford C

2010-06-01

The epsilon4 allele of the apolipoprotein E (APOE) gene is the major genetic risk factor for Alzheimer's disease (AD), but limited work has suggested that APOE genotype may modulate disease phenotype. Carriers of the epsilon4 allele have been reported to have greater medial temporal lobe (MTL) pathology and poorer memory than noncarriers. Less attention has focused on whether there are domains of cognition and neuroanatomical regions more affected in noncarriers. Further, a major potential confound of prior in vivo studies is the possibility of different rates of clinical misdiagnosis for carriers vs. noncarriers. We compared phenotypic differences in cognition and topography of regional cortical atrophy of epsilon4 carriers (n = 67) vs. noncarriers (n = 24) with mild AD from the Alzheimer's Disease Neuroimaging Initiative, restricted to those with a cerebrospinal fluid (CSF) molecular profile consistent with AD. Between-group comparisons were made for psychometric tests and morphometric measures of cortical thickness and hippocampal volume. Carriers displayed significantly greater impairment on measures of memory retention, whereas noncarriers were more impaired on tests of working memory, executive control, and lexical access. Consistent with this cognitive dissociation, carriers exhibited greater MTL atrophy, whereas noncarriers had greater frontoparietal atrophy. Performance deficits in particular cognitive domains were associated with disproportionate regional brain atrophy within nodes of cortical networks thought to subserve these cognitive processes. These convergent cognitive and neuroanatomic findings in individuals with a CSF molecular profile consistent with AD support the hypothesis that APOE genotype modulates the clinical phenotype of AD through influence on specific large-scale brain networks.

Functional Evidence for Memory Stabilization in Sensorimotor Adaptation: A 24-h Resting-State fMRI Study.

PubMed

Della-Maggiore, Valeria; Villalta, Jorge I; Kovacevic, Natasa; McIntosh, Anthony Randal

2017-03-01

Adaptation learning is crucial to maintain precise motor control in face of environmental perturbations. Although much progress has been made in understanding the psychophysics and neurophysiology of sensorimotor adaptation (SA), the time course of memory consolidation remains elusive. The lack of a reproducible gradient of memory resistance using protocols of retrograde interference has even led to the proposal that memories produced through SA do not consolidate. Here, we pursued an alternative approach using resting-state fMRI to track changes in functional connectivity (FC) induced by learning. Given that consolidation leads to long-term memory, we hypothesized that a change in FC that predicted long-term memory but not short-term memory would provide indirect evidence for memory stabilization. Six scans were acquired before, 15 min, 1, 3, 5.5, and 24 h after training on a center-out task under veridical or distorted visual feedback. The experimental group showed an increment in FC of a network including motor, premotor, posterior parietal cortex, cerebellum, and putamen that peaked at 5.5 h. Crucially, the strengthening of this network correlated positively with long-term retention but negatively with short-term retention. Our work provides evidence, suggesting that adaptation memories stabilize within a 6-h window, and points to different mechanisms subserving short- and long-term memory. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Youthful Brains in Older Adults: Preserved Neuroanatomy in the Default Mode and Salience Networks Contributes to Youthful Memory in Superaging.

PubMed

Sun, Felicia W; Stepanovic, Michael R; Andreano, Joseph; Barrett, Lisa Feldman; Touroutoglou, Alexandra; Dickerson, Bradford C

2016-09-14

Decline in cognitive skills, especially in memory, is often viewed as part of "normal" aging. Yet some individuals "age better" than others. Building on prior research showing that cortical thickness in one brain region, the anterior midcingulate cortex, is preserved in older adults with memory performance abilities equal to or better than those of people 20-30 years younger (i.e., "superagers"), we examined the structural integrity of two large-scale intrinsic brain networks in superaging: the default mode network, typically engaged during memory encoding and retrieval tasks, and the salience network, typically engaged during attention, motivation, and executive function tasks. We predicted that superagers would have preserved cortical thickness in critical nodes in these networks. We defined superagers (60-80 years old) based on their performance compared to young adults (18-32 years old) on the California Verbal Learning Test Long Delay Free Recall test. We found regions within the networks of interest where the cerebral cortex of superagers was thicker than that of typical older adults, and where superagers were anatomically indistinguishable from young adults; hippocampal volume was also preserved in superagers. Within the full group of older adults, thickness of a number of regions, including the anterior temporal cortex, rostral medial prefrontal cortex, and anterior midcingulate cortex, correlated with memory performance, as did the volume of the hippocampus. These results indicate older adults with youthful memory abilities have youthful brain regions in key paralimbic and limbic nodes of the default mode and salience networks that support attentional, executive, and mnemonic processes subserving memory function. Memory performance typically declines with age, as does cortical structural integrity, yet some older adults maintain youthful memory. We tested the hypothesis that superagers (older individuals with youthful memory performance) would exhibit preserved neuroanatomy in key brain networks subserving memory. We found that superagers not only perform similarly to young adults on memory testing, they also do not show the typical patterns of brain atrophy in certain regions. These regions are contained largely within two major intrinsic brain networks: the default mode network, implicated in memory encoding, storage, and retrieval, and the salience network, associated with attention and executive processes involved in encoding and retrieval. Preserved neuroanatomical integrity in these networks is associated with better memory performance among older adults. Copyright © 2016 Sun, Stepanovic et al.

Complex network structure influences processing in long-term and short-term memory.

PubMed

Vitevitch, Michael S; Chan, Kit Ying; Roodenrys, Steven

2012-07-01

Complex networks describe how entities in systems interact; the structure of such networks is argued to influence processing. One measure of network structure, clustering coefficient, C, measures the extent to which neighbors of a node are also neighbors of each other. Previous psycholinguistic experiments found that the C of phonological word-forms influenced retrieval from the mental lexicon (that portion of long-term memory dedicated to language) during the on-line recognition and production of spoken words. In the present study we examined how network structure influences other retrieval processes in long- and short-term memory. In a false-memory task-examining long-term memory-participants falsely recognized more words with low- than high-C. In a recognition memory task-examining veridical memories in long-term memory-participants correctly recognized more words with low- than high-C. However, participants in a serial recall task-examining redintegration in short-term memory-recalled lists comprised of high-C words more accurately than lists comprised of low-C words. These results demonstrate that network structure influences cognitive processes associated with several forms of memory including lexical, long-term, and short-term.

Resting state signatures of domain and demand-specific working memory performance.

PubMed

van Dam, Wessel O; Decker, Scott L; Durbin, Jeffery S; Vendemia, Jennifer M C; Desai, Rutvik H

2015-09-01

Working memory (WM) is one of the key constructs in understanding higher-level cognition. We examined whether patterns of activity in the resting state of individual subjects are correlated with their off-line working and short-term memory capabilities. Participants completed a resting-state fMRI scan and off-line working and short-term memory (STM) tests with both verbal and visual materials. We calculated fractional amplitude of low frequency fluctuations (fALFF) from the resting state data, and also computed connectivity between seeds placed in frontal and parietal lobes. Correlating fALFF values with behavioral measures showed that the fALFF values in a widespread fronto-parietal network during rest were positively correlated with a combined memory measure. In addition, STM showed a significant correlation with fALFF within the right angular gyrus and left middle occipital gyrus, whereas WM was correlated with fALFF values within the right IPS and left dorsomedial cerebellar cortex. Furthermore, verbal and visuospatial memory capacities were associated with dissociable patterns of low-frequency fluctuations. Seed-based connectivity showed correlations with the verbal WM measure in the left hemisphere, and with the visual WM measure in the right hemisphere. These findings contribute to our understanding of how differences in spontaneous low-frequency fluctuations at rest are correlated with differences in cognitive performance. Copyright © 2015 Elsevier Inc. All rights reserved.

Event-related rTMS at encoding affects differently deep and shallow memory traces.

PubMed

Innocenti, Iglis; Giovannelli, Fabio; Cincotta, Massimo; Feurra, Matteo; Polizzotto, Nicola R; Bianco, Giovanni; Cappa, Stefano F; Rossi, Simone

2010-10-15

The "level of processing" effect is a classical finding of the experimental psychology of memory. Actually, the depth of information processing at encoding predicts the accuracy of the subsequent episodic memory performance. When the incoming stimuli are analyzed in terms of their meaning (semantic, or deep, encoding), the memory performance is superior with respect to the case in which the same stimuli are analyzed in terms of their perceptual features (shallow encoding). As suggested by previous neuroimaging studies and by some preliminary findings with transcranial magnetic stimulation (TMS), the left prefrontal cortex may play a role in semantic processing requiring the allocation of working memory resources. However, it still remains unclear whether deep and shallow encoding share or not the same cortical networks, as well as how these networks contribute to the "level of processing" effect. To investigate the brain areas casually involved in this phenomenon, we applied event-related repetitive TMS (rTMS) during deep (semantic) and shallow (perceptual) encoding of words. Retrieval was subsequently tested without rTMS interference. RTMS applied to the left dorsolateral prefrontal cortex (DLPFC) abolished the beneficial effect of deep encoding on memory performance, both in terms of accuracy (decrease) and reaction times (increase). Neither accuracy nor reaction times were instead affected by rTMS to the right DLPFC or to an additional control site excluded by the memory process (vertex). The fact that online measures of semantic processing at encoding were unaffected suggests that the detrimental effect on memory performance for semantically encoded items took place in the subsequent consolidation phase. These results highlight the specific causal role of the left DLPFC among the wide left-lateralized cortical network engaged by long-term memory, suggesting that it probably represents a crucial node responsible for the improved memory performance induced by semantic processing. Copyright 2010 Elsevier Inc. All rights reserved.

Rapid Neocortical Dynamics: Cellular and Network Mechanisms

PubMed Central

Haider, Bilal; McCormick, David A.

2011-01-01

The highly interconnected local and large-scale networks of the neocortical sheet rapidly and dynamically modulate their functional connectivity according to behavioral demands. This basic operating principle of the neocortex is mediated by the continuously changing flow of excitatory and inhibitory synaptic barrages that not only control participation of neurons in networks but also define the networks themselves. The rapid control of neuronal responsiveness via synaptic bombardment is a fundamental property of cortical dynamics that may provide the basis of diverse behaviors, including sensory perception, motor integration, working memory, and attention. PMID:19409263

Increased functional connectivity within memory networks following memory rehabilitation in multiple sclerosis.

PubMed

Leavitt, Victoria M; Wylie, Glenn R; Girgis, Peter A; DeLuca, John; Chiaravalloti, Nancy D

2014-09-01

Identifying effective behavioral treatments to improve memory in persons with learning and memory impairment is a primary goal for neurorehabilitation researchers. Memory deficits are the most common cognitive symptom in multiple sclerosis (MS), and hold negative professional and personal consequences for people who are often in the prime of their lives when diagnosed. A 10-session behavioral treatment, the modified Story Memory Technique (mSMT), was studied in a randomized, placebo-controlled clinical trial. Behavioral improvements and increased fMRI activation were shown after treatment. Here, connectivity within the neural networks underlying memory function was examined with resting-state functional connectivity (RSFC) in a subset of participants from the clinical trial. We hypothesized that the treatment would result in increased integrity of connections within two primary memory networks of the brain, the hippocampal memory network, and the default network (DN). Seeds were placed in left and right hippocampus, and the posterior cingulate cortex. Increased connectivity was found between left hippocampus and cortical regions specifically involved in memory for visual imagery, as well as among critical hubs of the DN. These results represent the first evidence for efficacy of a behavioral intervention to impact the integrity of neural networks subserving memory functions in persons with MS.

Cross-frequency synchronization connects networks of fast and slow oscillations during visual working memory maintenance

PubMed Central

Siebenhühner, Felix; Wang, Sheng H; Palva, J Matias; Palva, Satu

2016-01-01

Neuronal activity in sensory and fronto-parietal (FP) areas underlies the representation and attentional control, respectively, of sensory information maintained in visual working memory (VWM). Within these regions, beta/gamma phase-synchronization supports the integration of sensory functions, while synchronization in theta/alpha bands supports the regulation of attentional functions. A key challenge is to understand which mechanisms integrate neuronal processing across these distinct frequencies and thereby the sensory and attentional functions. We investigated whether such integration could be achieved by cross-frequency phase synchrony (CFS). Using concurrent magneto- and electroencephalography, we found that CFS was load-dependently enhanced between theta and alpha–gamma and between alpha and beta-gamma oscillations during VWM maintenance among visual, FP, and dorsal attention (DA) systems. CFS also connected the hubs of within-frequency-synchronized networks and its strength predicted individual VWM capacity. We propose that CFS integrates processing among synchronized neuronal networks from theta to gamma frequencies to link sensory and attentional functions. DOI: http://dx.doi.org/10.7554/eLife.13451.001 PMID:27669146

Mechanisms and neuronal networks involved in reactive and proactive cognitive control of interference in working memory.

PubMed

Irlbacher, Kerstin; Kraft, Antje; Kehrer, Stefanie; Brandt, Stephan A

2014-10-01

Cognitive control can be reactive or proactive in nature. Reactive control mechanisms, which support the resolution of interference, start after its onset. Conversely, proactive control involves the anticipation and prevention of interference prior to its occurrence. The interrelation of both types of cognitive control is currently under debate: Are they mediated by different neuronal networks? Or are there neuronal structures that have the potential to act in a proactive as well as in a reactive manner? This review illustrates the way in which integrating knowledge gathered from behavioral studies, functional imaging, and human electroencephalography proves useful in answering these questions. We focus on studies that investigate interference resolution at the level of working memory representations. In summary, different mechanisms are instrumental in supporting reactive and proactive control. Distinct neuronal networks are involved, though some brain regions, especially pre-SMA, possess functions that are relevant to both control modes. Therefore, activation of these brain areas could be observed in reactive, as well as proactive control, but at different times during information processing. Copyright © 2014 Elsevier Ltd. All rights reserved.

The role of working memory and divided attention in metaphor interpretation.

PubMed

Iskandar, Sam; Baird, Anne D

2014-10-01

Although several types of figurative language exist, neuropsychological tests of non-literal language have focused on proverbs. Metaphors in the form X is (a) Y (e.g., The body's immunological response is a battle against disease.) place a lower demand on language skills and are more easily manipulated for novelty than proverbs. Forty healthy participants completed the Metaphor Interpretation Test (developed by the authors). The task includes 20 items chosen from a list of metaphors that were rated on several scales (e.g. imagery, aptness) in a study by Katz et al. (Metaphor Symb Act 3(4):191-214, 1988). Participants were asked to rate the familiarity and provide an explanation of each metaphor. A scoring system was developed to categorize answers into: abstract complete (AC), abstract partial (AP), concrete (CT), and other/unrelated (OT) types. Participants also completed short-term memory and divided attention tests. Overall, participants produced 56 % AC, 25.38 % AP, 7.88 % CT, and 10.88 % OT responses. It was found that a measure of verbal short-term memory span was the best predictor of performance on this task (adjusted R(2) = .369). It appears that short-term memory span, not working memory or divided attention, contributes most to providing abstract responses in explaining metaphors. This is in line with the idea that when one accesses the semantic network associated with a novel metaphor, one must hold this information in mind long enough to search for and link similar cognitive networks.

Clique-Based Neural Associative Memories with Local Coding and Precoding.

PubMed

Mofrad, Asieh Abolpour; Parker, Matthew G; Ferdosi, Zahra; Tadayon, Mohammad H

2016-08-01

Techniques from coding theory are able to improve the efficiency of neuroinspired and neural associative memories by forcing some construction and constraints on the network. In this letter, the approach is to embed coding techniques into neural associative memory in order to increase their performance in the presence of partial erasures. The motivation comes from recent work by Gripon, Berrou, and coauthors, which revisited Willshaw networks and presented a neural network with interacting neurons that partitioned into clusters. The model introduced stores patterns as small-size cliques that can be retrieved in spite of partial error. We focus on improving the success of retrieval by applying two techniques: doing a local coding in each cluster and then applying a precoding step. We use a slightly different decoding scheme, which is appropriate for partial erasures and converges faster. Although the ideas of local coding and precoding are not new, the way we apply them is different. Simulations show an increase in the pattern retrieval capacity for both techniques. Moreover, we use self-dual additive codes over field [Formula: see text], which have very interesting properties and a simple-graph representation.

Sequential memory: Binding dynamics.

PubMed

Afraimovich, Valentin; Gong, Xue; Rabinovich, Mikhail

2015-10-01

Temporal order memories are critical for everyday animal and human functioning. Experiments and our own experience show that the binding or association of various features of an event together and the maintaining of multimodality events in sequential order are the key components of any sequential memories-episodic, semantic, working, etc. We study a robustness of binding sequential dynamics based on our previously introduced model in the form of generalized Lotka-Volterra equations. In the phase space of the model, there exists a multi-dimensional binding heteroclinic network consisting of saddle equilibrium points and heteroclinic trajectories joining them. We prove here the robustness of the binding sequential dynamics, i.e., the feasibility phenomenon for coupled heteroclinic networks: for each collection of successive heteroclinic trajectories inside the unified networks, there is an open set of initial points such that the trajectory going through each of them follows the prescribed collection staying in a small neighborhood of it. We show also that the symbolic complexity function of the system restricted to this neighborhood is a polynomial of degree L - 1, where L is the number of modalities.

A simplified computational memory model from information processing.

PubMed

Zhang, Lanhua; Zhang, Dongsheng; Deng, Yuqin; Ding, Xiaoqian; Wang, Yan; Tang, Yiyuan; Sun, Baoliang

2016-11-23

This paper is intended to propose a computational model for memory from the view of information processing. The model, called simplified memory information retrieval network (SMIRN), is a bi-modular hierarchical functional memory network by abstracting memory function and simulating memory information processing. At first meta-memory is defined to express the neuron or brain cortices based on the biology and graph theories, and we develop an intra-modular network with the modeling algorithm by mapping the node and edge, and then the bi-modular network is delineated with intra-modular and inter-modular. At last a polynomial retrieval algorithm is introduced. In this paper we simulate the memory phenomena and functions of memorization and strengthening by information processing algorithms. The theoretical analysis and the simulation results show that the model is in accordance with the memory phenomena from information processing view.

Quantum neural networks: Current status and prospects for development

NASA Astrophysics Data System (ADS)

Altaisky, M. V.; Kaputkina, N. E.; Krylov, V. A.

2014-11-01

The idea of quantum artificial neural networks, first formulated in [34], unites the artificial neural network concept with the quantum computation paradigm. Quantum artificial neural networks were first systematically considered in the PhD thesis by T. Menneer (1998). Based on the works of Menneer and Narayanan [42, 43], Kouda, Matsui, and Nishimura [35, 36], Altaisky [2, 68], Zhou [67], and others, quantum-inspired learning algorithms for neural networks were developed, and are now used in various training programs and computer games [29, 30]. The first practically realizable scaled hardware-implemented model of the quantum artificial neural network is obtained by D-Wave Systems, Inc. [33]. It is a quantum Hopfield network implemented on the basis of superconducting quantum interference devices (SQUIDs). In this work we analyze possibilities and underlying principles of an alternative way to implement quantum neural networks on the basis of quantum dots. A possibility of using quantum neural network algorithms in automated control systems, associative memory devices, and in modeling biological and social networks is examined.

Dynamic Neural Networks Supporting Memory Retrieval

PubMed Central

St. Jacques, Peggy L.; Kragel, Philip A.; Rubin, David C.

2011-01-01

How do separate neural networks interact to support complex cognitive processes such as remembrance of the personal past? Autobiographical memory (AM) retrieval recruits a consistent pattern of activation that potentially comprises multiple neural networks. However, it is unclear how such large-scale neural networks interact and are modulated by properties of the memory retrieval process. In the present functional MRI (fMRI) study, we combined independent component analysis (ICA) and dynamic causal modeling (DCM) to understand the neural networks supporting AM retrieval. ICA revealed four task-related components consistent with the previous literature: 1) Medial Prefrontal Cortex (PFC) Network, associated with self-referential processes, 2) Medial Temporal Lobe (MTL) Network, associated with memory, 3) Frontoparietal Network, associated with strategic search, and 4) Cingulooperculum Network, associated with goal maintenance. DCM analysis revealed that the medial PFC network drove activation within the system, consistent with the importance of this network to AM retrieval. Additionally, memory accessibility and recollection uniquely altered connectivity between these neural networks. Recollection modulated the influence of the medial PFC on the MTL network during elaboration, suggesting that greater connectivity among subsystems of the default network supports greater re-experience. In contrast, memory accessibility modulated the influence of frontoparietal and MTL networks on the medial PFC network, suggesting that ease of retrieval involves greater fluency among the multiple networks contributing to AM. These results show the integration between neural networks supporting AM retrieval and the modulation of network connectivity by behavior. PMID:21550407

Is a Responsive Default Mode Network Required for Successful Working Memory Task Performance?

PubMed Central

Čeko, Marta; Gracely, John L.; Fitzcharles, Mary-Ann; Seminowicz, David A.; Schweinhardt, Petra

2015-01-01

In studies of cognitive processing using tasks with externally directed attention, regions showing increased (external-task-positive) and decreased or “negative” [default-mode network (DMN)] fMRI responses during task performance are dynamically responsive to increasing task difficulty. Responsiveness (modulation of fMRI signal by increasing load) has been linked directly to successful cognitive task performance in external-task-positive regions but not in DMN regions. To investigate whether a responsive DMN is required for successful cognitive performance, we compared healthy human subjects (n = 23) with individuals shown to have decreased DMN engagement (chronic pain patients, n = 28). Subjects performed a multilevel working-memory task (N-back) during fMRI. If a responsive DMN is required for successful performance, patients having reduced DMN responsiveness should show worsened performance; if performance is not reduced, their brains should show compensatory activation in external-task-positive regions or elsewhere. All subjects showed decreased accuracy and increased reaction times with increasing task level, with no significant group differences on either measure at any level. Patients had significantly reduced negative fMRI response (deactivation) of DMN regions (posterior cingulate/precuneus, medial prefrontal cortex). Controls showed expected modulation of DMN deactivation with increasing task difficulty. Patients showed significantly reduced modulation of DMN deactivation by task difficulty, despite their successful task performance. We found no evidence of compensatory neural recruitment in external-task-positive regions or elsewhere. Individual responsiveness of the external-task-positive ventrolateral prefrontal cortex, but not of DMN regions, correlated with task accuracy. These findings suggest that a responsive DMN may not be required for successful cognitive performance; a responsive external-task-positive network may be sufficient. SIGNIFICANCE STATEMENT We studied the relationship between responsiveness of the brain to increasing task demand and successful cognitive performance, using chronic pain patients as a probe. fMRI working memory studies show that two main cognitive networks [“external-task positive” and “default-mode network” (DMN)] are responsive to increasing task difficulty. The responsiveness of both of these brain networks is suggested to be required for successful task performance. The responsiveness of external-task-positive regions has been linked directly to successful cognitive task performance, as we also show here. However, pain patients show decreased engagement and responsiveness of the DMN but can perform a working memory task as well as healthy subjects, without demonstrable compensatory neural recruitment. Therefore, a responsive DMN might not be needed for successful cognitive performance. PMID:26290236

Constructing, Perceiving, and Maintaining Scenes: Hippocampal Activity and Connectivity

PubMed Central

Zeidman, Peter; Mullally, Sinéad L.; Maguire, Eleanor A.

2015-01-01

In recent years, evidence has accumulated to suggest the hippocampus plays a role beyond memory. A strong hippocampal response to scenes has been noted, and patients with bilateral hippocampal damage cannot vividly recall scenes from their past or construct scenes in their imagination. There is debate about whether the hippocampus is involved in the online processing of scenes independent of memory. Here, we investigated the hippocampal response to visually perceiving scenes, constructing scenes in the imagination, and maintaining scenes in working memory. We found extensive hippocampal activation for perceiving scenes, and a circumscribed area of anterior medial hippocampus common to perception and construction. There was significantly less hippocampal activity for maintaining scenes in working memory. We also explored the functional connectivity of the anterior medial hippocampus and found significantly stronger connectivity with a distributed set of brain areas during scene construction compared with scene perception. These results increase our knowledge of the hippocampus by identifying a subregion commonly engaged by scenes, whether perceived or constructed, by separating scene construction from working memory, and by revealing the functional network underlying scene construction, offering new insights into why patients with hippocampal lesions cannot construct scenes. PMID:25405941

Interaction between emotion and memory: importance of mammillary bodies damage in a mouse model of the alcoholic Korsakoff syndrome.

PubMed

Béracochéa, Daniel

2005-01-01

Chronic alcohol consumption (CAC) can lead to the Korsakoff syndrome (KS), a memory deficiency attributed to diencephalic damage and/or to medial temporal or cortical related dysfunction. The etiology of KS remains unclear. Most animal models of KS involve thiamine-deficient diets associated with pyrithiamine treatment. Here we present a mouse model of CAC-induced KS. We demonstrate that CAC-generated retrieval memory deficits in working/ episodic memory tasks, together with a reduction of fear reactivity, result from damage to the mammillary bodies (MB). Experimental lesions of MB in non-alcoholic mice produced the same memory and emotional impairments. Drugs having anxiogenic-like properties counteract such impairments produced by CAC or by MB lesions. We suggest (a) that MB are the essential components of a brain network underlying emotional processes, which would be critically important in the retrieval processes involved in working/ episodic memory tasks, and (b) that failure to maintain emotional arousal due to MB damage can be a main factor of CAC-induced memory deficits. Overall, our animal model fits well with general neuropsychological and anatomic impairments observed in KS.

Interaction Between Emotion and Memory: Importance of Mammillary Bodies Damage in a Mouse Model of the Alcoholic Korsakoff Syndrome

PubMed Central

Béracochéa, Daniel

2005-01-01

Chronic alcohol consumption (CAC) can lead to the Korsakoff syndrome (KS), a memory deficiency attributed to diencephalie damage and/or to medial temporal or cortical related dysfunction. The etiology of KS remains unclear. Most animal models of KS involve thiaminedeficient diets associated with pyrithiamine treatment. Here we present a mouse model of CAC-induced KS. We demonstrate that CAC-generated retrieval memory deficits in working/ episodic memory tasks, together with a reduction of fear reactivity, result from damage to the mammillary bodies (MB). Experimental lesions of MB in non-alcoholic mice produced the same memory and emotional impairments. Drugs having anxiogenic-like properties counteract such impairments produced by CAC or by MB lesions. We suggest (a) that MB are the essential components of a brain network underlying emotional processes, which would be critically important in the retrieval processes involved in working/ episodic memory tasks, and (b) that failure to maintain emotional arousal due to MB damage can be a main factor of CAC-induced memory deficits. Overall, our animal model fits well with general neuropsychological and anatomic impairments observed in KS. PMID:16444899

[Formula: see text]Working memory and attention in pediatric brain tumor patients treated with and without radiation therapy.

PubMed

Raghubar, Kimberly P; Mahone, E Mark; Yeates, Keith Owen; Cecil, Kim M; Makola, Monwabisi; Ris, M Douglas

2017-08-01

Children are at risk for cognitive difficulties following the diagnosis and treatment of a brain tumor. Longitudinal studies have consistently demonstrated declines on measures of intellectual functioning, and recently it has been proposed that specific neurocognitive processes underlie these changes, including working memory, processing speed, and attention. However, a fine-grained examination of the affected neurocognitive processes is required to inform intervention efforts. Radiation therapy (RT) impacts white matter integrity, likely affecting those cognitive processes supported by distributed neural networks. This study examined working memory and attention in children during the early delayed stages of recovery following surgical resection and RT. The participants included 27 children diagnosed with pediatric brain tumor, treated with (n = 12) or without (n = 15) RT, who completed experimental and standardized measures of working memory and attention (n-back and digit span tasks). Children treated with radiation performed less well than those who did not receive radiation on the n-back measure, though performance at the 0-back level was considerably poorer than would be expected for both groups, perhaps suggesting difficulties with more basic processes such as vigilance. Along these lines, marginal differences were noted on digit span forward. The findings are discussed with respect to models of attention and working memory, and the interplay between the two.

Working Memory-Related Effective Connectivity in Huntington's Disease Patients.

PubMed

Lahr, Jacob; Minkova, Lora; Tabrizi, Sarah J; Stout, Julie C; Klöppel, Stefan; Scheller, Elisa

2018-01-01

Huntington's disease (HD) is a genetically caused neurodegenerative disorder characterized by heterogeneous motor, psychiatric, and cognitive symptoms. Although motor symptoms may be the most prominent presentation, cognitive symptoms such as memory deficits and executive dysfunction typically co-occur. We used functional magnetic resonance imaging (fMRI) and task fMRI-based dynamic causal modeling (DCM) to evaluate HD-related changes in the neural network underlying working memory (WM). Sixty-four pre-symptomatic HD mutation carriers (preHD), 20 patients with early manifest HD symptoms (earlyHD), and 83 healthy control subjects performed an n -back fMRI task with two levels of WM load. Effective connectivity was assessed in five predefined regions of interest, comprising bilateral inferior parietal cortex, left anterior cingulate cortex, and bilateral dorsolateral prefrontal cortex. HD mutation carriers performed less accurately and more slowly at high WM load compared with the control group. While between-group comparisons of brain activation did not reveal differential recruitment of the cortical WM network in mutation carriers, comparisons of brain connectivity as identified with DCM revealed a number of group differences across the whole WM network. Most strikingly, we observed decreasing connectivity from several regions toward right dorsolateral prefrontal cortex (rDLPFC) in preHD and even more so in earlyHD. The deterioration in rDLPFC connectivity complements results from previous studies and might mirror beginning cortical neural decline at premanifest and early manifest stages of HD. We were able to characterize effective connectivity in a WM network of HD mutation carriers yielding further insight into patterns of cognitive decline and accompanying neural deterioration.

Neural basis for dynamic updating of object representation in visual working memory.

PubMed

Takahama, Sachiko; Miyauchi, Satoru; Saiki, Jun

2010-02-15

In real world, objects have multiple features and change dynamically. Thus, object representations must satisfy dynamic updating and feature binding. Previous studies have investigated the neural activity of dynamic updating or feature binding alone, but not both simultaneously. We investigated the neural basis of feature-bound object representation in a dynamically updating situation by conducting a multiple object permanence tracking task, which required observers to simultaneously process both the maintenance and dynamic updating of feature-bound objects. Using an event-related design, we separated activities during memory maintenance and change detection. In the search for regions showing selective activation in dynamic updating of feature-bound objects, we identified a network during memory maintenance that was comprised of the inferior precentral sulcus, superior parietal lobule, and middle frontal gyrus. In the change detection period, various prefrontal regions, including the anterior prefrontal cortex, were activated. In updating object representation of dynamically moving objects, the inferior precentral sulcus closely cooperates with a so-called "frontoparietal network", and subregions of the frontoparietal network can be decomposed into those sensitive to spatial updating and feature binding. The anterior prefrontal cortex identifies changes in object representation by comparing memory and perceptual representations rather than maintaining object representations per se, as previously suggested. Copyright 2009 Elsevier Inc. All rights reserved.

Optimizing one-shot learning with binary synapses.

PubMed

Romani, Sandro; Amit, Daniel J; Amit, Yali

2008-08-01

A network of excitatory synapses trained with a conservative version of Hebbian learning is used as a model for recognizing the familiarity of thousands of once-seen stimuli from those never seen before. Such networks were initially proposed for modeling memory retrieval (selective delay activity). We show that the same framework allows the incorporation of both familiarity recognition and memory retrieval, and estimate the network's capacity. In the case of binary neurons, we extend the analysis of Amit and Fusi (1994) to obtain capacity limits based on computations of signal-to-noise ratio of the field difference between selective and non-selective neurons of learned signals. We show that with fast learning (potentiation probability approximately 1), the most recently learned patterns can be retrieved in working memory (selective delay activity). A much higher number of once-seen learned patterns elicit a realistic familiarity signal in the presence of an external field. With potentiation probability much less than 1 (slow learning), memory retrieval disappears, whereas familiarity recognition capacity is maintained at a similarly high level. This analysis is corroborated in simulations. For analog neurons, where such analysis is more difficult, we simplify the capacity analysis by studying the excess number of potentiated synapses above the steady-state distribution. In this framework, we derive the optimal constraint between potentiation and depression probabilities that maximizes the capacity.

Hippocampal functional connectivity and episodic memory in early childhood

PubMed Central

Riggins, Tracy; Geng, Fengji; Blankenship, Sarah L.; Redcay, Elizabeth

2016-01-01

Episodic memory relies on a distributed network of brain regions, with the hippocampus playing a critical and irreplaceable role. Few studies have examined how changes in this network contribute to episodic memory development early in life. The present addressed this gap by examining relations between hippocampal functional connectivity and episodic memory in 4-and 6-year-old children (n=40). Results revealed similar hippocampal functional connectivity between age groups, which included lateral temporal regions, precuneus, and multiple parietal and prefrontal regions, and functional specialization along the longitudinal axis. Despite these similarities, developmental differences were also observed. Specifically, 3 (of 4) regions within the hippocampal memory network were positively associated with episodic memory in 6-year-old children, but negatively associated with episodic memory in 4-year-old children. In contrast, all 3 regions outside the hippocampal memory network were negatively associated with episodic memory in older children, but positively associated with episodic memory in younger children. These interactions are interpreted within an interactive specialization framework and suggest the hippocampus becomes functionally integrated with cortical regions that are part of the hippocampal memory network in adults and functionally segregated from regions unrelated to memory in adults, both of which are associated with age-related improvements in episodic memory ability. PMID:26900967

Hippocampal functional connectivity and episodic memory in early childhood.

PubMed

Riggins, Tracy; Geng, Fengji; Blankenship, Sarah L; Redcay, Elizabeth

2016-06-01

Episodic memory relies on a distributed network of brain regions, with the hippocampus playing a critical and irreplaceable role. Few studies have examined how changes in this network contribute to episodic memory development early in life. The present addressed this gap by examining relations between hippocampal functional connectivity and episodic memory in 4- and 6-year-old children (n=40). Results revealed similar hippocampal functional connectivity between age groups, which included lateral temporal regions, precuneus, and multiple parietal and prefrontal regions, and functional specialization along the longitudinal axis. Despite these similarities, developmental differences were also observed. Specifically, 3 (of 4) regions within the hippocampal memory network were positively associated with episodic memory in 6-year-old children, but negatively associated with episodic memory in 4-year-old children. In contrast, all 3 regions outside the hippocampal memory network were negatively associated with episodic memory in older children, but positively associated with episodic memory in younger children. These interactions are interpreted within an interactive specialization framework and suggest the hippocampus becomes functionally integrated with cortical regions that are part of the hippocampal memory network in adults and functionally segregated from regions unrelated to memory in adults, both of which are associated with age-related improvements in episodic memory ability. Copyright © 2016 The Authors. Published by Elsevier Ltd.. All rights reserved.

Statistical Mechanics Model of the Speed - Accuracy Tradeoff in Spatial and Lexical Memory

NASA Astrophysics Data System (ADS)

Kaufman, Miron; Allen, Philip

2000-03-01

The molar neural network model of P. Allen, M. Kaufman, A. F. Smith, R. E. Popper, Psychology and Aging 13, 501 (1998) and Experimental Aging Research, 24, 307 (1998) is extended to incorporate reaction times. In our model the entropy associated with a particular task determines the reaction time. We use this molar neural model to directly analyze experimental data on episodic (spatial) memory and semantic (lexical) memory tasks. In particular we are interested in the effect of aging on the two types of memory. We find that there is no difference in performance levels for lexical memory tasks between younger and older adults. In the case spatial memory tasks we find that aging has a detrimental effect on the performance level. This work is supported by NIH/NIA grant AG09282-06.

Targeted Memory Reactivation during Sleep Adaptively Promotes the Strengthening or Weakening of Overlapping Memories.

PubMed

Oyarzún, Javiera P; Morís, Joaquín; Luque, David; de Diego-Balaguer, Ruth; Fuentemilla, Lluís

2017-08-09

System memory consolidation is conceptualized as an active process whereby newly encoded memory representations are strengthened through selective memory reactivation during sleep. However, our learning experience is highly overlapping in content (i.e., shares common elements), and memories of these events are organized in an intricate network of overlapping associated events. It remains to be explored whether and how selective memory reactivation during sleep has an impact on these overlapping memories acquired during awake time. Here, we test in a group of adult women and men the prediction that selective memory reactivation during sleep entails the reactivation of associated events and that this may lead the brain to adaptively regulate whether these associated memories are strengthened or pruned from memory networks on the basis of their relative associative strength with the shared element. Our findings demonstrate the existence of efficient regulatory neural mechanisms governing how complex memory networks are shaped during sleep as a function of their associative memory strength. SIGNIFICANCE STATEMENT Numerous studies have demonstrated that system memory consolidation is an active, selective, and sleep-dependent process in which only subsets of new memories become stabilized through their reactivation. However, the learning experience is highly overlapping in content and thus events are encoded in an intricate network of related memories. It remains to be explored whether and how memory reactivation has an impact on overlapping memories acquired during awake time. Here, we show that sleep memory reactivation promotes strengthening and weakening of overlapping memories based on their associative memory strength. These results suggest the existence of an efficient regulatory neural mechanism that avoids the formation of cluttered memory representation of multiple events and promotes stabilization of complex memory networks. Copyright © 2017 the authors 0270-6474/17/377748-11$15.00/0.

Modular structure of functional networks in olfactory memory.

PubMed

Meunier, David; Fonlupt, Pierre; Saive, Anne-Lise; Plailly, Jane; Ravel, Nadine; Royet, Jean-Pierre

2014-07-15

Graph theory enables the study of systems by describing those systems as a set of nodes and edges. Graph theory has been widely applied to characterize the overall structure of data sets in the social, technological, and biological sciences, including neuroscience. Modular structure decomposition enables the definition of sub-networks whose components are gathered in the same module and work together closely, while working weakly with components from other modules. This processing is of interest for studying memory, a cognitive process that is widely distributed. We propose a new method to identify modular structure in task-related functional magnetic resonance imaging (fMRI) networks. The modular structure was obtained directly from correlation coefficients and thus retained information about both signs and weights. The method was applied to functional data acquired during a yes-no odor recognition memory task performed by young and elderly adults. Four response categories were explored: correct (Hit) and incorrect (False alarm, FA) recognition and correct and incorrect rejection. We extracted time series data for 36 areas as a function of response categories and age groups and calculated condition-based weighted correlation matrices. Overall, condition-based modular partitions were more homogeneous in young than elderly subjects. Using partition similarity-based statistics and a posteriori statistical analyses, we demonstrated that several areas, including the hippocampus, caudate nucleus, and anterior cingulate gyrus, belonged to the same module more frequently during Hit than during all other conditions. Modularity values were negatively correlated with memory scores in the Hit condition and positively correlated with bias scores (liberal/conservative attitude) in the Hit and FA conditions. We further demonstrated that the proportion of positive and negative links between areas of different modules (i.e., the proportion of correlated and anti-correlated areas) accounted for most of the observed differences in signed modularity. Taken together, our results provided some evidence that the neural networks involved in odor recognition memory are organized into modules and that these modular partitions are linked to behavioral performance and individual strategies. Copyright © 2014 Elsevier Inc. All rights reserved.

Hippocampal Network Modularity Is Associated With Relational Memory Dysfunction in Schizophrenia.

PubMed

Avery, Suzanne N; Rogers, Baxter P; Heckers, Stephan

2018-05-01

Functional dysconnectivity has been proposed as a major pathophysiological mechanism for cognitive dysfunction in schizophrenia. The hippocampus is a focal point of dysconnectivity in schizophrenia, with decreased hippocampal functional connectivity contributing to the marked memory deficits observed in patients. Normal memory function relies on the interaction of complex corticohippocampal networks. However, only recent technological advances have enabled the large-scale exploration of functional networks with accuracy and precision. We investigated the modularity of hippocampal resting-state functional networks in a sample of 45 patients with schizophrenia spectrum disorders and 38 healthy control subjects. Modularity was calculated for two distinct functional networks: a core hippocampal-medial temporal lobe cortex network and an extended hippocampal-cortical network. As hippocampal function differs along its longitudinal axis, follow-up analyses examined anterior and posterior networks separately. To explore effects of resting network function on behavior, we tested associations between modularity and relational memory ability. Age, sex, handedness, and parental education were similar between groups. Network modularity was lower in schizophrenia patients, especially in the posterior hippocampal network. Schizophrenia patients also showed markedly lower relational memory ability compared with control subjects. We found a distinct brain-behavior relationship in schizophrenia that differed from control subjects by network and anterior/posterior division-while relational memory in control subjects was associated with anterior hippocampal-cortical modularity, schizophrenia patients showed an association with posterior hippocampal-medial temporal lobe cortex network modularity. Our findings support a model of abnormal resting-state corticohippocampal network coherence in schizophrenia, which may contribute to relational memory deficits. Copyright © 2018 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.

Long-Term Memory Stabilized by Noise-Induced Rehearsal

PubMed Central

Wei, Yi

2014-01-01

Cortical networks can maintain memories for decades despite the short lifetime of synaptic strengths. Can a neural network store long-lasting memories in unstable synapses? Here, we study the effects of ongoing spike-timing-dependent plasticity (STDP) on the stability of memory patterns stored in synapses of an attractor neural network. We show that certain classes of STDP rules can stabilize all stored memory patterns despite a short lifetime of synapses. In our model, unstructured neural noise, after passing through the recurrent network connections, carries the imprint of all memory patterns in temporal correlations. STDP, combined with these correlations, leads to reinforcement of all stored patterns, even those that are never explicitly visited. Our findings may provide the functional reason for irregular spiking displayed by cortical neurons and justify models of system memory consolidation. Therefore, we propose that irregular neural activity is the feature that helps cortical networks maintain stable connections. PMID:25411507

Anatomical Modularity of Verbal Working Memory? Functional Anatomical Evidence from a Famous Patient with Short-Term Memory Deficits.

PubMed

Paulesu, Eraldo; Shallice, Tim; Danelli, Laura; Sberna, Maurizio; Frackowiak, Richard S J; Frith, Chris D

2017-01-01

Cognitive skills are the emergent property of distributed neural networks. The distributed nature of these networks does not necessarily imply a lack of specialization of the individual brain structures involved. However, it remains questionable whether discrete aspects of high-level behavior might be the result of localized brain activity of individual nodes within such networks. The phonological loop of working memory, with its simplicity, seems ideally suited for testing this possibility. Central to the development of the phonological loop model has been the description of patients with focal lesions and specific deficits. As much as the detailed description of their behavior has served to refine the phonological loop model, a classical anatomoclinical correlation approach with such cases falls short in telling whether the observed behavior is based on the functions of a neural system resembling that seen in normal subjects challenged with phonological loop tasks or whether different systems have taken over. This is a crucial issue for the cross correlation of normal cognition, normal physiology, and cognitive neuropsychology. Here we describe the functional anatomical patterns of JB, a historical patient originally described by Warrington et al. (1971), a patient with a left temporo-parietal lesion and selective short phonological store deficit. JB was studied with the H 2 15 O PET activation technique during a rhyming task, which primarily depends on the rehearsal system of the phonological loop. No residual function was observed in the left temporo-parietal junction, a region previously associated with the phonological buffer of working memory. However, Broca's area, the major counterpart of the rehearsal system, was the major site of activation during the rhyming task. Specific and autonomous activation of Broca's area in the absence of afferent inputs from the other major anatomical component of the phonological loop shows that a certain degree of functional independence or modularity exists in this distributed anatomical-cognitive system.

Anatomical Modularity of Verbal Working Memory? Functional Anatomical Evidence from a Famous Patient with Short-Term Memory Deficits

PubMed Central

Paulesu, Eraldo; Shallice, Tim; Danelli, Laura; Sberna, Maurizio; Frackowiak, Richard S. J.; Frith, Chris D.

2017-01-01

Cognitive skills are the emergent property of distributed neural networks. The distributed nature of these networks does not necessarily imply a lack of specialization of the individual brain structures involved. However, it remains questionable whether discrete aspects of high-level behavior might be the result of localized brain activity of individual nodes within such networks. The phonological loop of working memory, with its simplicity, seems ideally suited for testing this possibility. Central to the development of the phonological loop model has been the description of patients with focal lesions and specific deficits. As much as the detailed description of their behavior has served to refine the phonological loop model, a classical anatomoclinical correlation approach with such cases falls short in telling whether the observed behavior is based on the functions of a neural system resembling that seen in normal subjects challenged with phonological loop tasks or whether different systems have taken over. This is a crucial issue for the cross correlation of normal cognition, normal physiology, and cognitive neuropsychology. Here we describe the functional anatomical patterns of JB, a historical patient originally described by Warrington et al. (1971), a patient with a left temporo-parietal lesion and selective short phonological store deficit. JB was studied with the H215O PET activation technique during a rhyming task, which primarily depends on the rehearsal system of the phonological loop. No residual function was observed in the left temporo-parietal junction, a region previously associated with the phonological buffer of working memory. However, Broca's area, the major counterpart of the rehearsal system, was the major site of activation during the rhyming task. Specific and autonomous activation of Broca's area in the absence of afferent inputs from the other major anatomical component of the phonological loop shows that a certain degree of functional independence or modularity exists in this distributed anatomical-cognitive system. PMID:28567009

A simplified computational memory model from information processing

PubMed Central

Zhang, Lanhua; Zhang, Dongsheng; Deng, Yuqin; Ding, Xiaoqian; Wang, Yan; Tang, Yiyuan; Sun, Baoliang

2016-01-01

This paper is intended to propose a computational model for memory from the view of information processing. The model, called simplified memory information retrieval network (SMIRN), is a bi-modular hierarchical functional memory network by abstracting memory function and simulating memory information processing. At first meta-memory is defined to express the neuron or brain cortices based on the biology and graph theories, and we develop an intra-modular network with the modeling algorithm by mapping the node and edge, and then the bi-modular network is delineated with intra-modular and inter-modular. At last a polynomial retrieval algorithm is introduced. In this paper we simulate the memory phenomena and functions of memorization and strengthening by information processing algorithms. The theoretical analysis and the simulation results show that the model is in accordance with the memory phenomena from information processing view. PMID:27876847

Neural basis for generalized quantifier comprehension.

PubMed

McMillan, Corey T; Clark, Robin; Moore, Peachie; Devita, Christian; Grossman, Murray

2005-01-01

Generalized quantifiers like "all cars" are semantically well understood, yet we know little about their neural representation. Our model of quantifier processing includes a numerosity device, operations that combine number elements and working memory. Semantic theory posits two types of quantifiers: first-order quantifiers identify a number state (e.g. "at least 3") and higher-order quantifiers additionally require maintaining a number state actively in working memory for comparison with another state (e.g. "less than half"). We used BOLD fMRI to test the hypothesis that all quantifiers recruit inferior parietal cortex associated with numerosity, while only higher-order quantifiers recruit prefrontal cortex associated with executive resources like working memory. Our findings showed that first-order and higher-order quantifiers both recruit right inferior parietal cortex, suggesting that a numerosity component contributes to quantifier comprehension. Moreover, only probes of higher-order quantifiers recruited right dorsolateral prefrontal cortex, suggesting involvement of executive resources like working memory. We also observed activation of thalamus and anterior cingulate that may be associated with selective attention. Our findings are consistent with a large-scale neural network centered in frontal and parietal cortex that supports comprehension of generalized quantifiers.

Optical interconnection networks for high-performance computing systems

NASA Astrophysics Data System (ADS)

Biberman, Aleksandr; Bergman, Keren

2012-04-01

Enabled by silicon photonic technology, optical interconnection networks have the potential to be a key disruptive technology in computing and communication industries. The enduring pursuit of performance gains in computing, combined with stringent power constraints, has fostered the ever-growing computational parallelism associated with chip multiprocessors, memory systems, high-performance computing systems and data centers. Sustaining these parallelism growths introduces unique challenges for on- and off-chip communications, shifting the focus toward novel and fundamentally different communication approaches. Chip-scale photonic interconnection networks, enabled by high-performance silicon photonic devices, offer unprecedented bandwidth scalability with reduced power consumption. We demonstrate that the silicon photonic platforms have already produced all the high-performance photonic devices required to realize these types of networks. Through extensive empirical characterization in much of our work, we demonstrate such feasibility of waveguides, modulators, switches and photodetectors. We also demonstrate systems that simultaneously combine many functionalities to achieve more complex building blocks. We propose novel silicon photonic devices, subsystems, network topologies and architectures to enable unprecedented performance of these photonic interconnection networks. Furthermore, the advantages of photonic interconnection networks extend far beyond the chip, offering advanced communication environments for memory systems, high-performance computing systems, and data centers.

Brain regions that retain the spatial layout of tactile stimuli during working memory - A 'tactospatial sketchpad'?

PubMed

Schmidt, Timo Torsten; Blankenburg, Felix

2018-05-31

Working memory (WM) studies have been essential for ascertaining how the brain flexibly handles mentally represented information in the absence of sensory stimulation. Most studies on the memory of sensory stimulus features have focused, however, on the visual domain. Here, we report a human WM study in the tactile modality where participants had to memorize the spatial layout of patterned Braille-like stimuli presented to the index finger. We used a whole-brain searchlight approach in combination with multi-voxel pattern analysis (MVPA) to investigate tactile WM representations without a priori assumptions about which brain regions code tactospatial information. Our analysis revealed that posterior and parietal cortices, as well as premotor regions, retained information across the twelve-second delay phase. Interestingly, parts of this brain network were previously shown to also contain information of visuospatial WM. Also, by specifically testing somatosensory regions for WM representations, we observed content-specific activation patterns in primary somatosensory cortex (SI). Our findings demonstrate that tactile WM depends on a distributed network of brain regions in analogy to the representation of visuospatial information. Copyright © 2018. Published by Elsevier Inc.

Binding and strategic selection in working memory: a lifespan dissociation.

PubMed

Sander, Myriam C; Werkle-Bergner, Markus; Lindenberger, Ulman

2011-09-01

Working memory (WM) shows a gradual increase during childhood, followed by accelerating decline from adulthood to old age. To examine these lifespan differences more closely, we asked 34 children (10-12 years), 40 younger adults (20-25 years), and 39 older adults (70-75 years) to perform a color change detection task. Load levels and encoding durations were varied for displays including targets only (Experiment 1) or targets plus distracters (Experiment 2, investigating a subsample of Experiment 1). WM performance was lower in older adults and children than in younger adults. Longer presentation times were associated with better performance in all age groups, presumably reflecting increasing effects of strategic selection mechanisms on WM performance. Children outperformed older adults when encoding times were short, and distracter effects were larger in children and older adults than in younger adults. We conclude that strategic selection in WM develops more slowly during childhood than basic binding operations, presumably reflecting the delay in maturation of frontal versus medio-temporal brain networks. In old age, both sets of mechanisms decline, reflecting senescent change in both networks. We discuss similarities to episodic memory development and address open questions for future research.

Short-Term Memory in Orthogonal Neural Networks

NASA Astrophysics Data System (ADS)

White, Olivia L.; Lee, Daniel D.; Sompolinsky, Haim

2004-04-01

We study the ability of linear recurrent networks obeying discrete time dynamics to store long temporal sequences that are retrievable from the instantaneous state of the network. We calculate this temporal memory capacity for both distributed shift register and random orthogonal connectivity matrices. We show that the memory capacity of these networks scales with system size.

Identification of a Functional Connectome for Long-Term Fear Memory in Mice

PubMed Central

Wheeler, Anne L.; Teixeira, Cátia M.; Wang, Afra H.; Xiong, Xuejian; Kovacevic, Natasa; Lerch, Jason P.; McIntosh, Anthony R.; Parkinson, John; Frankland, Paul W.

2013-01-01

Long-term memories are thought to depend upon the coordinated activation of a broad network of cortical and subcortical brain regions. However, the distributed nature of this representation has made it challenging to define the neural elements of the memory trace, and lesion and electrophysiological approaches provide only a narrow window into what is appreciated a much more global network. Here we used a global mapping approach to identify networks of brain regions activated following recall of long-term fear memories in mice. Analysis of Fos expression across 84 brain regions allowed us to identify regions that were co-active following memory recall. These analyses revealed that the functional organization of long-term fear memories depends on memory age and is altered in mutant mice that exhibit premature forgetting. Most importantly, these analyses indicate that long-term memory recall engages a network that has a distinct thalamic-hippocampal-cortical signature. This network is concurrently integrated and segregated and therefore has small-world properties, and contains hub-like regions in the prefrontal cortex and thalamus that may play privileged roles in memory expression. PMID:23300432

A Long Short-Term Memory deep learning network for the prediction of epileptic seizures using EEG signals.

PubMed

Tsiouris, Κostas Μ; Pezoulas, Vasileios C; Zervakis, Michalis; Konitsiotis, Spiros; Koutsouris, Dimitrios D; Fotiadis, Dimitrios I

2018-05-17

The electroencephalogram (EEG) is the most prominent means to study epilepsy and capture changes in electrical brain activity that could declare an imminent seizure. In this work, Long Short-Term Memory (LSTM) networks are introduced in epileptic seizure prediction using EEG signals, expanding the use of deep learning algorithms with convolutional neural networks (CNN). A pre-analysis is initially performed to find the optimal architecture of the LSTM network by testing several modules and layers of memory units. Based on these results, a two-layer LSTM network is selected to evaluate seizure prediction performance using four different lengths of preictal windows, ranging from 15 min to 2 h. The LSTM model exploits a wide range of features extracted prior to classification, including time and frequency domain features, between EEG channels cross-correlation and graph theoretic features. The evaluation is performed using long-term EEG recordings from the open CHB-MIT Scalp EEG database, suggest that the proposed methodology is able to predict all 185 seizures, providing high rates of seizure prediction sensitivity and low false prediction rates (FPR) of 0.11-0.02 false alarms per hour, depending on the duration of the preictal window. The proposed LSTM-based methodology delivers a significant increase in seizure prediction performance compared to both traditional machine learning techniques and convolutional neural networks that have been previously evaluated in the literature. Copyright © 2018 Elsevier Ltd. All rights reserved.

Consciousness and the Prefrontal Parietal Network: Insights from Attention, Working Memory, and Chunking

PubMed Central

Bor, Daniel; Seth, Anil K.

2012-01-01

Consciousness has of late become a “hot topic” in neuroscience. Empirical work has centered on identifying potential neural correlates of consciousness (NCCs), with a converging view that the prefrontal parietal network (PPN) is closely associated with this process. Theoretical work has primarily sought to explain how informational properties of this cortical network could account for phenomenal properties of consciousness. However, both empirical and theoretical research has given less focus to the psychological features that may account for the NCCs. The PPN has also been heavily linked with cognitive processes, such as attention. We describe how this literature is under-appreciated in consciousness science, in part due to the increasingly entrenched assumption of a strong dissociation between attention and consciousness. We argue instead that there is more common ground between attention and consciousness than is usually emphasized: although objects can under certain circumstances be attended to in the absence of conscious access, attention as a content selection and boosting mechanism is an important and necessary aspect of consciousness. Like attention, working memory and executive control involve the interlinking of multiple mental objects and have also been closely associated with the PPN. We propose that this set of cognitive functions, in concert with attention, make up the core psychological components of consciousness. One related process, chunking, exploits logical or mnemonic redundancies in a dataset so that it can be recoded and a given task optimized. Chunking has been shown to activate PPN particularly robustly, even compared with other cognitively demanding tasks, such as working memory or mental arithmetic. It is therefore possible that chunking, as a tool to detect useful patterns within an integrated set of intensely processed (attended) information, has a central role to play in consciousness. Following on from this, we suggest that a key evolutionary purpose of consciousness may be to provide innovative solutions to complex or novel problems. PMID:22416238

Fluctuations and Noise in Stochastic Spread of Respiratory Infection Epidemics in Social Networks

NASA Astrophysics Data System (ADS)

Yulmetyev, Renat; Emelyanova, Natalya; Demin, Sergey; Gafarov, Fail; Hänggi, Peter; Yulmetyeva, Dinara

2003-05-01

For the analysis of epidemic and disease dynamics complexity, it is necessary to understand the basic principles and notions of its spreading in long-time memory media. Here we considering the problem from a theoretical and practical viewpoint, presenting the quantitative evidence confirming the existence of stochastic long-range memory and robust chaos in a real time series of respiratory infections of human upper respiratory track. In this work we present a new statistical method of analyzing the spread of grippe and acute respiratory track infections epidemic process of human upper respiratory track by means of the theory of discrete non-Markov stochastic processes. We use the results of our recent theory (Phys. Rev. E 65, 046107 (2002)) for the study of statistical effects of memory in real data series, describing the epidemic dynamics of human acute respiratory track infections and grippe. The obtained results testify to an opportunity of the strict quantitative description of the regular and stochastic components in epidemic dynamics of social networks with a view to time discreteness and effects of statistical memory.

Counterfactual thinking: an fMRI study on changing the past for a better future

PubMed Central

Ma, Ning; Ampe, Lisa; Baetens, Kris; Van Overwalle, Frank

2013-01-01

Recent studies suggest that a brain network mainly associated with episodic memory has a more general function in imagining oneself in another time, place or perspective (e.g. episodic future thought, theory of mind, default mode). If this is true, counterfactual thinking (e.g. ‘If I had left the office earlier, I wouldn’t have missed my train.’) should also activate this network. Present functional magnetic resonance imaging (fMRI) study explores the common and distinct neural activity of counterfactual and episodic thinking by directly comparing the imagining of upward counterfactuals (creating better outcomes for negative past events) with the re-experiencing of negative past events and the imagining of positive future events. Results confirm that episodic and counterfactual thinking share a common brain network, involving a core memory network (hippocampal area, temporal lobes, midline, and lateral parietal lobes) and prefrontal areas that might be related to mentalizing (medial prefrontal cortex) and performance monitoring (right prefrontal cortex). In contrast to episodic past and future thinking, counterfactual thinking recruits some of these areas more strongly and extensively, and additionally activates the bilateral inferior parietal lobe and posterior medial frontal cortex. We discuss these findings in view of recent fMRI evidence on the working of episodic memory and theory of mind. PMID:22403155

Neuroticism and conscientiousness respectively constrain and facilitate short-term plasticity within the working memory neural network.

PubMed

Dima, Danai; Friston, Karl J; Stephan, Klaas E; Frangou, Sophia

2015-10-01

Individual differences in cognitive efficiency, particularly in relation to working memory (WM), have been associated both with personality dimensions that reflect enduring regularities in brain configuration, and with short-term neural plasticity, that reflects task-related changes in brain connectivity. To elucidate the relationship of these two divergent mechanisms, we tested the hypothesis that personality dimensions, which reflect enduring aspects of brain configuration, inform about the neurobiological framework within which short-term, task-related plasticity, as measured by effective connectivity, can be facilitated or constrained. As WM consistently engages the dorsolateral prefrontal (DLPFC), parietal (PAR), and anterior cingulate cortex (ACC), we specified a WM network model with bidirectional, ipsilateral, and contralateral connections between these regions from a functional magnetic resonance imaging dataset obtained from 40 healthy adults while performing the 3-back WM task. Task-related effective connectivity changes within this network were estimated using Dynamic Causal Modelling. Personality was evaluated along the major dimensions of Neuroticism, Extraversion, Openness to Experience, Agreeableness, and Conscientiousness. Only two dimensions were relevant to task-dependent effective connectivity. Neuroticism and Conscientiousness respectively constrained and facilitated neuroplastic responses within the WM network. These results suggest individual differences in cognitive efficiency arise from the interplay between enduring and short-term plasticity in brain configuration. © 2015 Wiley Periodicals, Inc.

Learning about memory from (very) large scale hippocampal networks

NASA Astrophysics Data System (ADS)

Meshulam, Leenoy; Gauthier, Jeffrey; Brody, Carlos; Tank, David; Bialek, William

Recent technological progress has dramatically increased our access to the neural activity underlying memory-related tasks. These complex high-dimensional data call for theories that allow us to identify signatures of collective activity in the networks that are crucial for the emergence of cognitive functions. As an example, we study the neural activity in dorsal hippocampus as a mouse runs along a virtual linear track. One of the dominant features of this data is the activity of place cells, which fire when the animal visits particular locations. During the first stage of our work we used a maximum entropy framework to characterize the probability distribution of the joint activity patterns observed across ensembles of up to 100 cells. These models, which are equivalent to Ising models with competing interactions, make surprisingly accurate predictions for the activity of individual neurons given the state of the rest of the network, and this is true both for place cells and for non-place cells. Additionally, the model captures the high-order structure in the data, which cannot be explained by place-related activity alone. For the second stage of our work we study networks of 2000 neurons. To address this much larger system, we are exploring different methods of coarse graining, in the spirit of the renormalization group, searching for simplified models.

Maintaining the feelings of others in working memory is associated with activation of the left anterior insula and left frontal-parietal control network

PubMed Central

Lane, Richard D.; Alkozei, Anna; Bao, Jennifer; Smith, Courtney; Sanova, Anna; Nettles, Matthew; Killgore, William D. S.

2017-01-01

Abstract The maintenance of social/emotional information in working memory (SWM/EWM) has recently been the topic of multiple neuroimaging studies. However, some studies find that SWM/EWM involves a medial frontal-parietal network while others instead find lateral frontal-parietal activations similar to studies of verbal and visuospatial WM. In this study, we asked 26 healthy volunteers to complete an EWM task designed to examine whether different cognitive strategies— maintaining emotional images, words, or feelings— might account for these discrepant results. We also examined whether differences in EWM performance were related to general intelligence (IQ), emotional intelligence (EI), and emotional awareness (EA). We found that maintaining emotional feelings, even when accounting for neural activation attributable to maintaining emotional images/words, still activated a left lateral frontal-parietal network (including the anterior insula and posterior dorsomedial frontal cortex). We also found that individual differences in the ability to maintain feelings were positively associated with IQ and EA, but not with EI. These results suggest that maintaining the feelings of others (at least when perceived exteroceptively) involves similar frontal-parietal control networks to exteroceptive WM, and that it is similarly linked to IQ, but that it also may be an important component of EA. PMID:28158779

Synaptic efficacy shapes resource limitations in working memory.

PubMed

Krishnan, Nikhil; Poll, Daniel B; Kilpatrick, Zachary P

2018-06-01

Working memory (WM) is limited in its temporal length and capacity. Classic conceptions of WM capacity assume the system possesses a finite number of slots, but recent evidence suggests WM may be a continuous resource. Resource models typically assume there is no hard upper bound on the number of items that can be stored, but WM fidelity decreases with the number of items. We analyze a neural field model of multi-item WM that associates each item with the location of a bump in a finite spatial domain, considering items that span a one-dimensional continuous feature space. Our analysis relates the neural architecture of the network to accumulated errors and capacity limitations arising during the delay period of a multi-item WM task. Networks with stronger synapses support wider bumps that interact more, whereas networks with weaker synapses support narrower bumps that are more susceptible to noise perturbations. There is an optimal synaptic strength that both limits bump interaction events and the effects of noise perturbations. This optimum shifts to weaker synapses as the number of items stored in the network is increased. Our model not only provides a circuit-based explanation for WM capacity, but also speaks to how capacity relates to the arrangement of stored items in a feature space.

Robust Working Memory in an Asynchronously Spiking Neural Network Realized with Neuromorphic VLSI.

PubMed

Giulioni, Massimiliano; Camilleri, Patrick; Mattia, Maurizio; Dante, Vittorio; Braun, Jochen; Del Giudice, Paolo

2011-01-01

We demonstrate bistable attractor dynamics in a spiking neural network implemented with neuromorphic VLSI hardware. The on-chip network consists of three interacting populations (two excitatory, one inhibitory) of leaky integrate-and-fire (LIF) neurons. One excitatory population is distinguished by strong synaptic self-excitation, which sustains meta-stable states of "high" and "low"-firing activity. Depending on the overall excitability, transitions to the "high" state may be evoked by external stimulation, or may occur spontaneously due to random activity fluctuations. In the former case, the "high" state retains a "working memory" of a stimulus until well after its release. In the latter case, "high" states remain stable for seconds, three orders of magnitude longer than the largest time-scale implemented in the circuitry. Evoked and spontaneous transitions form a continuum and may exhibit a wide range of latencies, depending on the strength of external stimulation and of recurrent synaptic excitation. In addition, we investigated "corrupted" "high" states comprising neurons of both excitatory populations. Within a "basin of attraction," the network dynamics "corrects" such states and re-establishes the prototypical "high" state. We conclude that, with effective theoretical guidance, full-fledged attractor dynamics can be realized with comparatively small populations of neuromorphic hardware neurons.

Altered brain activation and functional connectivity in working memory related networks in patients with type 2 diabetes: An ICA-based analysis

PubMed Central

Zhang, Yang; Lu, Shan; Liu, Chunlei; Zhang, Huimei; Zhou, Xuanhe; Ni, Changlin; Qin, Wen; Zhang, Quan

2016-01-01

Type 2 diabetes mellitus (T2DM) can cause multidimensional cognitive deficits, among which working memory (WM) is usually involved at an early stage. However, the neural substrates underlying impaired WM in T2DM patients are still unclear. To clarify this issue, we utilized functional magnetic resonance imaging (fMRI) and independent component analysis to evaluate T2DM patients for alterations in brain activation and functional connectivity (FC) in WM networks and to determine their associations with cognitive and clinical variables. Twenty complication-free T2DM patients and 19 matched healthy controls (HCs) were enrolled, and fMRI data were acquired during a block-designed 1-back WM task. The WM metrics of the T2DM patients showed no differences compared with those of the HCs, except for a slightly lower accuracy rate in the T2DM patients. Compared with the HCs, the T2DM patients demonstrated increased activation within their WM fronto-parietal networks, and activation strength was significantly correlated with WM performance. The T2DM patients also showed decreased FC within and between their WM networks. Our results indicate that the functional integration of WM sub-networks was disrupted in the complication-free T2DM patients and that strengthened regional activity in fronto-parietal networks may compensate for the WM impairment caused by T2DM. PMID:27021340

Different Topological Properties of EEG-Derived Networks Describe Working Memory Phases as Revealed by Graph Theoretical Analysis

PubMed Central

Toppi, Jlenia; Astolfi, Laura; Risetti, Monica; Anzolin, Alessandra; Kober, Silvia E.; Wood, Guilherme; Mattia, Donatella

2018-01-01

Several non-invasive imaging methods have contributed to shed light on the brain mechanisms underlying working memory (WM). The aim of the present study was to depict the topology of the relevant EEG-derived brain networks associated to distinct operations of WM function elicited by the Sternberg Item Recognition Task (SIRT) such as encoding, storage, and retrieval in healthy, middle age (46 ± 5 years) adults. High density EEG recordings were performed in 17 participants whilst attending a visual SIRT. Neural correlates of WM were assessed by means of a combination of EEG signal processing methods (i.e., time-varying connectivity estimation and graph theory), in order to extract synthetic descriptors of the complex networks underlying the encoding, storage, and retrieval phases of WM construct. The group analysis revealed that the encoding phase exhibited a significantly higher small-world topology of EEG networks with respect to storage and retrieval in all EEG frequency oscillations, thus indicating that during the encoding of items the global network organization could “optimally” promote the information flow between WM sub-networks. We also found that the magnitude of such configuration could predict subject behavioral performance when memory load increases as indicated by the negative correlation between Reaction Time and the local efficiency values estimated during the encoding in the alpha band in both 4 and 6 digits conditions. At the local scale, the values of the degree index which measures the degree of in- and out- information flow between scalp areas were found to specifically distinguish the hubs within the relevant sub-networks associated to each of the three different WM phases, according to the different role of the sub-network of regions in the different WM phases. Our findings indicate that the use of EEG-derived connectivity measures and their related topological indices might offer a reliable and yet affordable approach to monitor WM components and thus theoretically support the clinical assessment of cognitive functions in presence of WM decline/impairment, as it occurs after stroke. PMID:29379425

Spreading activation in nonverbal memory networks.

PubMed

Foster, Paul S; Wakefield, Candias; Pryjmak, Scott; Roosa, Katelyn M; Branch, Kaylei K; Drago, Valeria; Harrison, David W; Ruff, Ronald

2017-09-01

Theories of spreading activation primarily involve semantic memory networks. However, the existence of separate verbal and visuospatial memory networks suggests that spreading activation may also occur in visuospatial memory networks. The purpose of the present investigation was to explore this possibility. Specifically, this study sought to create and describe the design frequency corpus and to determine whether this measure of visuospatial spreading activation was related to right hemisphere functioning and spreading activation in verbal memory networks. We used word frequencies taken from the Controlled Oral Word Association Test and design frequencies taken from the Ruff Figural Fluency Test as measures of verbal and visuospatial spreading activation, respectively. Average word and design frequencies were then correlated with measures of left and right cerebral functioning. The results indicated that a significant relationship exists between performance on a test of right posterior functioning (Block Design) and design frequency. A significant negative relationship also exists between spreading activation in semantic memory networks and design frequency. Based on our findings, the hypotheses were supported. Further research will need to be conducted to examine whether spreading activation exists in visuospatial memory networks as well as the parameters that might modulate this spreading activation, such as the influence of neurotransmitters.

Thalamic structures and associated cognitive functions: Relations with age and aging.

PubMed

Fama, Rosemary; Sullivan, Edith V

2015-07-01

The thalamus, with its cortical, subcortical, and cerebellar connections, is a critical node in networks supporting cognitive functions known to decline in normal aging, including component processes of memory and executive functions of attention and information processing. The macrostructure, microstructure, and neural connectivity of the thalamus changes across the adult lifespan. Structural and functional magnetic resonance imaging (MRI) and diffusion tensor imaging (DTI) have demonstrated, regional thalamic volume shrinkage and microstructural degradation, with anterior regions generally more compromised than posterior regions. The integrity of selective thalamic nuclei and projections decline with advancing age, particularly those in thalamofrontal, thalamoparietal, and thalamolimbic networks. This review presents studies that assess the relations between age and aging and the structure, function, and connectivity of the thalamus and associated neural networks and focuses on their relations with processes of attention, speed of information processing, and working and episodic memory. Copyright © 2015 Elsevier Ltd. All rights reserved.

Weak connections form an infinite number of patterns in the brain

NASA Astrophysics Data System (ADS)

Ren, Hai-Peng; Bai, Chao; Baptista, Murilo S.; Grebogi, Celso

2017-04-01

Recently, much attention has been paid to interpreting the mechanisms for memory formation in terms of brain connectivity and dynamics. Within the plethora of collective states a complex network can exhibit, we show that the phenomenon of Collective Almost Synchronisation (CAS), which describes a state with an infinite number of patterns emerging in complex networks for weak coupling strengths, deserves special attention. We show that a simulated neuron network with neurons weakly connected does produce CAS patterns, and additionally produces an output that optimally model experimental electroencephalograph (EEG) signals. This work provides strong evidence that the brain operates locally in a CAS regime, allowing it to have an unlimited number of dynamical patterns, a state that could explain the enormous memory capacity of the brain, and that would give support to the idea that local clusters of neurons are sufficiently decorrelated to independently process information locally.

SITRUS: Semantic Infrastructure for Wireless Sensor Networks

PubMed Central

Bispo, Kalil A.; Rosa, Nelson S.; Cunha, Paulo R. F.

2015-01-01

Wireless sensor networks (WSNs) are made up of nodes with limited resources, such as processing, bandwidth, memory and, most importantly, energy. For this reason, it is essential that WSNs always work to reduce the power consumption as much as possible in order to maximize its lifetime. In this context, this paper presents SITRUS (semantic infrastructure for wireless sensor networks), which aims to reduce the power consumption of WSN nodes using ontologies. SITRUS consists of two major parts: a message-oriented middleware responsible for both an oriented message communication service and a reconfiguration service; and a semantic information processing module whose purpose is to generate a semantic database that provides the basis to decide whether a WSN node needs to be reconfigurated or not. In order to evaluate the proposed solution, we carried out an experimental evaluation to assess the power consumption and memory usage of WSN applications built atop SITRUS. PMID:26528974

Fast Entanglement Establishment via Local Dynamics for Quantum Repeater Networks

NASA Astrophysics Data System (ADS)

Gyongyosi, Laszlo; Imre, Sandor

Quantum entanglement is a necessity for future quantum communication networks, quantum internet, and long-distance quantum key distribution. The current approaches of entanglement distribution require high-delay entanglement transmission, entanglement swapping to extend the range of entanglement, high-cost entanglement purification, and long-lived quantum memories. We introduce a fundamental protocol for establishing entanglement in quantum communication networks. The proposed scheme does not require entanglement transmission between the nodes, high-cost entanglement swapping, entanglement purification, or long-lived quantum memories. The protocol reliably establishes a maximally entangled system between the remote nodes via dynamics generated by local Hamiltonians. The method eliminates the main drawbacks of current schemes allowing fast entanglement establishment with a minimized delay. Our solution provides a fundamental method for future long-distance quantum key distribution, quantum repeater networks, quantum internet, and quantum-networking protocols. This work was partially supported by the GOP-1.1.1-11-2012-0092 project sponsored by the EU and European Structural Fund, by the Hungarian Scientific Research Fund - OTKA K-112125, and by the COST Action MP1006.

A Proposal of TLS Implementation for Cross Certification Model

NASA Astrophysics Data System (ADS)

Kaji, Tadashi; Fujishiro, Takahiro; Tezuka, Satoru

Today, TLS is widely used for achieving a secure communication system. And TLS is used PKI for server authentication and/or client authentication. However, its PKI environment, which is called as “multiple trust anchors environment,” causes the problem that the verifier has to maintain huge number of CA certificates in the ubiquitous network because the increase of terminals connected to the network brings the increase of CAs. However, most of terminals in the ubiquitous network will not have enough memory to hold such huge number of CA certificates. Therefore, another PKI environment, “cross certification environment”, is useful for the ubiquitous network. But, because current TLS is designed for the multiple trust anchors model, TLS cannot work efficiently on the cross-certification model. This paper proposes a TLS implementation method to support the cross certification model efficiently. Our proposal reduces the size of exchanged messages between the TLS client and the TLS server during the handshake process. Therefore, our proposal is suitable for implementing TLS in the terminals that do not have enough computing power and memory in ubiquitous network.

Copula Regression Analysis of Simultaneously Recorded Frontal Eye Field and Inferotemporal Spiking Activity during Object-Based Working Memory

PubMed Central

Hu, Meng; Clark, Kelsey L.; Gong, Xiajing; Noudoost, Behrad; Li, Mingyao; Moore, Tirin

2015-01-01

Inferotemporal (IT) neurons are known to exhibit persistent, stimulus-selective activity during the delay period of object-based working memory tasks. Frontal eye field (FEF) neurons show robust, spatially selective delay period activity during memory-guided saccade tasks. We present a copula regression paradigm to examine neural interaction of these two types of signals between areas IT and FEF of the monkey during a working memory task. This paradigm is based on copula models that can account for both marginal distribution over spiking activity of individual neurons within each area and joint distribution over ensemble activity of neurons between areas. Considering the popular GLMs as marginal models, we developed a general and flexible likelihood framework that uses the copula to integrate separate GLMs into a joint regression analysis. Such joint analysis essentially leads to a multivariate analog of the marginal GLM theory and hence efficient model estimation. In addition, we show that Granger causality between spike trains can be readily assessed via the likelihood ratio statistic. The performance of this method is validated by extensive simulations, and compared favorably to the widely used GLMs. When applied to spiking activity of simultaneously recorded FEF and IT neurons during working memory task, we observed significant Granger causality influence from FEF to IT, but not in the opposite direction, suggesting the role of the FEF in the selection and retention of visual information during working memory. The copula model has the potential to provide unique neurophysiological insights about network properties of the brain. PMID:26063909

Memory Dynamics in Cross-linked Actin Networks

NASA Astrophysics Data System (ADS)

Scheff, Danielle; Majumdar, Sayantan; Gardel, Margaret

Cells demonstrate the remarkable ability to adapt to mechanical stimuli through rearrangement of the actin cytoskeleton, a cross-linked network of actin filaments. In addition to its importance in cell biology, understanding this mechanical response provides strategies for creation of novel materials. A recent study has demonstrated that applied stress can encode mechanical memory in these networks through changes in network geometry, which gives rise to anisotropic shear response. Under later shear, the network is stiffer in the direction of the previously applied stress. However, the dynamics behind the encoding of this memory are unknown. To address this question, we explore the effect of varying either the rigidity of the cross-linkers or the length of actin filament on the time scales required for both memory encoding and over which it later decays. While previous experiments saw only a long-lived memory, initial results suggest another mechanism where memories relax relatively quickly. Overall, our study is crucial for understanding the process by which an external stress can impact network arrangement and thus the dynamics of memory formation.

System level mechanisms of adaptation, learning, memory formation and evolvability: the role of chaperone and other networks.

PubMed

Gyurko, David M; Soti, Csaba; Stetak, Attila; Csermely, Peter

2014-05-01

During the last decade, network approaches became a powerful tool to describe protein structure and dynamics. Here, we describe first the protein structure networks of molecular chaperones, then characterize chaperone containing sub-networks of interactomes called as chaperone-networks or chaperomes. We review the role of molecular chaperones in short-term adaptation of cellular networks in response to stress, and in long-term adaptation discussing their putative functions in the regulation of evolvability. We provide a general overview of possible network mechanisms of adaptation, learning and memory formation. We propose that changes of network rigidity play a key role in learning and memory formation processes. Flexible network topology provides ' learning-competent' state. Here, networks may have much less modular boundaries than locally rigid, highly modular networks, where the learnt information has already been consolidated in a memory formation process. Since modular boundaries are efficient filters of information, in the 'learning-competent' state information filtering may be much smaller, than after memory formation. This mechanism restricts high information transfer to the 'learning competent' state. After memory formation, modular boundary-induced segregation and information filtering protect the stored information. The flexible networks of young organisms are generally in a 'learning competent' state. On the contrary, locally rigid networks of old organisms have lost their 'learning competent' state, but store and protect their learnt information efficiently. We anticipate that the above mechanism may operate at the level of both protein-protein interaction and neuronal networks.

Memory, forgetting, and economic crisis: drug use and social fragmentation in an Argentine shantytown.

PubMed

Epele, Maria E

2010-03-01

Closely linked to the increase in psychotropic pill consumption, forgetting and remembering emerged from devastated social scenarios as a new local idiom among poor youth in the late 1990s and the new millennium. Drawing on ethnographic fieldwork carried out during the years of the deepest economic crisis in Argentina (2001-03), I argue that psychotropic pill consumption is associated with not only deteriorating economic conditions but also changes in the quality and price of cocaine, and in the scarcity and subsequent change of status of medications during the economic breakdown. Taking into account developments in the field of memory studies, I examine the relationship among political economy, social memory work, and changing drug-use practices. Regarding memory as a social practice, I argue that the growth of psychotropic pill consumption in the late 1990s can be understood through the interplay of Paul Ricoeur's notions regarding different kinds and levels of forgetting. By analyzing changing survival strategies, social network dismantlement, changing mortality patterns, and abusive police repression, I discuss how social fragmentation engendered by structural reforms has modified social memory work.

Oscillatory mechanisms of process binding in memory.

PubMed

Klimesch, Wolfgang; Freunberger, Roman; Sauseng, Paul

2010-06-01

A central topic in cognitive neuroscience is the question, which processes underlie large scale communication within and between different neural networks. The basic assumption is that oscillatory phase synchronization plays an important role for process binding--the transient linking of different cognitive processes--which may be considered a special type of large scale communication. We investigate this question for memory processes on the basis of different types of oscillatory synchronization mechanisms. The reviewed findings suggest that theta and alpha phase coupling (and phase reorganization) reflect control processes in two large memory systems, a working memory and a complex knowledge system that comprises semantic long-term memory. It is suggested that alpha phase synchronization may be interpreted in terms of processes that coordinate top-down control (a process guided by expectancy to focus on relevant search areas) and access to memory traces (a process leading to the activation of a memory trace). An analogous interpretation is suggested for theta oscillations and the controlled access to episodic memories. Copyright (c) 2009 Elsevier Ltd. All rights reserved.

Working memory brain activity and capacity link MAOA polymorphism to aggressive behavior during development

PubMed Central

Ziermans, T; Dumontheil, I; Roggeman, C; Peyrard-Janvid, M; Matsson, H; Kere, J; Klingberg, T

2012-01-01

A developmental increase in working memory capacity is an important part of cognitive development, and low working memory (WM) capacity is a risk factor for developing psychopathology. Brain activity represents a promising endophenotype for linking genes to behavior and for improving our understanding of the neurobiology of WM development. We investigated gene–brain–behavior relationships by focusing on 18 single-nucleotide polymorphisms (SNPs) located in six dopaminergic candidate genes (COMT, SLC6A3/DAT1, DBH, DRD4, DRD5, MAOA). Visuospatial WM (VSWM) brain activity, measured with functional magnetic resonance imaging, and VSWM capacity were assessed in a longitudinal study of typically developing children and adolescents. Behavioral problems were evaluated using the Child Behavior Checklist (CBCL). One SNP (rs6609257), located ∼6.6 kb downstream of the monoamine oxidase A gene (MAOA) on human chromosome X, significantly affected brain activity in a network of frontal, parietal and occipital regions. Increased activity in this network, but not in caudate nucleus or anterior prefrontal regions, was correlated with VSWM capacity, which in turn predicted externalizing (aggressive/oppositional) symptoms, with higher WM capacity associated with fewer externalizing symptoms. There were no direct significant correlations between rs6609257 and behavioral symptoms. These results suggest a mediating role of WM brain activity and capacity in linking the MAOA gene to aggressive behavior during development. PMID:22832821

Functional roles of the cingulo-frontal network in performance on working memory.

PubMed

Kondo, Hirohito; Morishita, Masanao; Osaka, Naoyuki; Osaka, Mariko; Fukuyama, Hidenao; Shibasaki, Hiroshi

2004-01-01

We examined the relationship between brain activities and task performance on working memory. A large-scale study was initially administered to identify good and poor performers using the operation span and reading span tasks. On the basis of those span scores, we divided 20 consenting participants into high- and low-span groups. In an fMRI study, the participants performed verification of arithmetic problems and retention of target words either concurrently or separately. The behavioral results showed that performance was better in the high-span group than in the low-span group under a dual-task condition, but not under two single-task conditions. The anterior cingulate cortex (ACC), left prefrontal cortex (PFC), left inferior frontal cortex, and bilateral parietal cortex were primarily activated for both span groups. We found that signal changes in the ACC were greater in the high-span group than in the low-span group under the dual-task condition, but not under the single-task conditions. Structural equation modeling indicated that an estimate of effective connectivity from the ACC to the left PFC was positive for the high-span group and negative for the-low span group, suggesting that closer cooperation between the two brain regions was strongly related to working memory performance. We conclude that central executive functioning for attention shifting is modulated by the cingulo-frontal network.

Working memory brain activity and capacity link MAOA polymorphism to aggressive behavior during development.

PubMed

Ziermans, T; Dumontheil, I; Roggeman, C; Peyrard-Janvid, M; Matsson, H; Kere, J; Klingberg, T

2012-02-28

A developmental increase in working memory capacity is an important part of cognitive development, and low working memory (WM) capacity is a risk factor for developing psychopathology. Brain activity represents a promising endophenotype for linking genes to behavior and for improving our understanding of the neurobiology of WM development. We investigated gene-brain-behavior relationships by focusing on 18 single-nucleotide polymorphisms (SNPs) located in six dopaminergic candidate genes (COMT, SLC6A3/DAT1, DBH, DRD4, DRD5, MAOA). Visuospatial WM (VSWM) brain activity, measured with functional magnetic resonance imaging, and VSWM capacity were assessed in a longitudinal study of typically developing children and adolescents. Behavioral problems were evaluated using the Child Behavior Checklist (CBCL). One SNP (rs6609257), located ~6.6 kb downstream of the monoamine oxidase A gene (MAOA) on human chromosome X, significantly affected brain activity in a network of frontal, parietal and occipital regions. Increased activity in this network, but not in caudate nucleus or anterior prefrontal regions, was correlated with VSWM capacity, which in turn predicted externalizing (aggressive/oppositional) symptoms, with higher WM capacity associated with fewer externalizing symptoms. There were no direct significant correlations between rs6609257 and behavioral symptoms. These results suggest a mediating role of WM brain activity and capacity in linking the MAOA gene to aggressive behavior during development.

Functional Connectivity among Spikes in Low Dimensional Space during Working Memory Task in Rat

PubMed Central

Tian, Xin

2014-01-01

Working memory (WM) is critically important in cognitive tasks. The functional connectivity has been a powerful tool for understanding the mechanism underlying the information processing during WM tasks. The aim of this study is to investigate how to effectively characterize the dynamic variations of the functional connectivity in low dimensional space among the principal components (PCs) which were extracted from the instantaneous firing rate series. Spikes were obtained from medial prefrontal cortex (mPFC) of rats with implanted microelectrode array and then transformed into continuous series via instantaneous firing rate method. Granger causality method is proposed to study the functional connectivity. Then three scalar metrics were applied to identify the changes of the reduced dimensionality functional network during working memory tasks: functional connectivity (GC), global efficiency (E) and casual density (CD). As a comparison, GC, E and CD were also calculated to describe the functional connectivity in the original space. The results showed that these network characteristics dynamically changed during the correct WM tasks. The measure values increased to maximum, and then decreased both in the original and in the reduced dimensionality. Besides, the feature values of the reduced dimensionality were significantly higher during the WM tasks than they were in the original space. These findings suggested that functional connectivity among the spikes varied dynamically during the WM tasks and could be described effectively in the low dimensional space. PMID:24658291

Robust quantum network architectures and topologies for entanglement distribution

NASA Astrophysics Data System (ADS)

Das, Siddhartha; Khatri, Sumeet; Dowling, Jonathan P.

2018-01-01

Entanglement distribution is a prerequisite for several important quantum information processing and computing tasks, such as quantum teleportation, quantum key distribution, and distributed quantum computing. In this work, we focus on two-dimensional quantum networks based on optical quantum technologies using dual-rail photonic qubits for the building of a fail-safe quantum internet. We lay out a quantum network architecture for entanglement distribution between distant parties using a Bravais lattice topology, with the technological constraint that quantum repeaters equipped with quantum memories are not easily accessible. We provide a robust protocol for simultaneous entanglement distribution between two distant groups of parties on this network. We also discuss a memory-based quantum network architecture that can be implemented on networks with an arbitrary topology. We examine networks with bow-tie lattice and Archimedean lattice topologies and use percolation theory to quantify the robustness of the networks. In particular, we provide figures of merit on the loss parameter of the optical medium that depend only on the topology of the network and quantify the robustness of the network against intermittent photon loss and intermittent failure of nodes. These figures of merit can be used to compare the robustness of different network topologies in order to determine the best topology in a given real-world scenario, which is critical in the realization of the quantum internet.

Electronic implementation of associative memory based on neural network models

NASA Technical Reports Server (NTRS)

Moopenn, A.; Lambe, John; Thakoor, A. P.

1987-01-01

An electronic embodiment of a neural network based associative memory in the form of a binary connection matrix is described. The nature of false memory errors, their effect on the information storage capacity of binary connection matrix memories, and a novel technique to eliminate such errors with the help of asymmetrical extra connections are discussed. The stability of the matrix memory system incorporating a unique local inhibition scheme is analyzed in terms of local minimization of an energy function. The memory's stability, dynamic behavior, and recall capability are investigated using a 32-'neuron' electronic neural network memory with a 1024-programmable binary connection matrix.

Long-term memory stabilized by noise-induced rehearsal.

PubMed

Wei, Yi; Koulakov, Alexei A

2014-11-19

Cortical networks can maintain memories for decades despite the short lifetime of synaptic strengths. Can a neural network store long-lasting memories in unstable synapses? Here, we study the effects of ongoing spike-timing-dependent plasticity (STDP) on the stability of memory patterns stored in synapses of an attractor neural network. We show that certain classes of STDP rules can stabilize all stored memory patterns despite a short lifetime of synapses. In our model, unstructured neural noise, after passing through the recurrent network connections, carries the imprint of all memory patterns in temporal correlations. STDP, combined with these correlations, leads to reinforcement of all stored patterns, even those that are never explicitly visited. Our findings may provide the functional reason for irregular spiking displayed by cortical neurons and justify models of system memory consolidation. Therefore, we propose that irregular neural activity is the feature that helps cortical networks maintain stable connections. Copyright © 2014 the authors 0270-6474/14/3415804-12$15.00/0.

Attention and Working Memory in Adolescents with Autism Spectrum Disorder: A Functional MRI Study.

PubMed

Rahko, Jukka S; Vuontela, Virve A; Carlson, Synnöve; Nikkinen, Juha; Hurtig, Tuula M; Kuusikko-Gauffin, Sanna; Mattila, Marja-Leena; Jussila, Katja K; Remes, Jukka J; Jansson-Verkasalo, Eira M; Aronen, Eeva T; Pauls, David L; Ebeling, Hanna E; Tervonen, Osmo; Moilanen, Irma K; Kiviniemi, Vesa J

2016-06-01

The present study examined attention and memory load-dependent differences in the brain activation and deactivation patterns between adolescents with autism spectrum disorders (ASDs) and typically developing (TD) controls using functional magnetic resonance imaging. Attentional (0-back) and working memory (WM; 2-back) processing and load differences (0 vs. 2-back) were analysed. WM-related areas activated and default mode network deactivated normally in ASDs as a function of task load. ASDs performed the attentional 0-back task similarly to TD controls but showed increased deactivation in cerebellum and right temporal cortical areas and weaker activation in other cerebellar areas. Increasing task load resulted in multiple responses in ASDs compared to TD and in inadequate modulation of brain activity in right insula, primary somatosensory, motor and auditory cortices. The changes during attentional task may reflect compensatory mechanisms enabling normal behavioral performance. The inadequate memory load-dependent modulation of activity suggests diminished compensatory potential in ASD.

Memory assisted free space quantum communication

NASA Astrophysics Data System (ADS)

Jordaan, Bertus; Namazi, Mehdi; Goham, Connor; Shahrokhshahi, Reihaneh; Vallone, Giuseppe; Villoresi, Paolo; Figueroa, Eden

2016-05-01

A quantum memory assisted node between different quantum channels has the capability to modify and synchronize its output, allowing for easy connectivity, and advanced cryptography protocols. We present the experimental progress towards the storage of single photon level pulses carrying random polarization qubits into a dual rail room temperature quantum memory (RTQM) after ~ 20m of free space propagation. The RTQM coherently stores the input pulses through electromagnetically induced transparency (EIT) of a warm 87 Rb vapor and filters the output by polarization elements and temperature-controlled etalon resonators. This allows the characterization of error rates for each polarization basis and the testing of the synchronization ability of the quantum memory. This work presents a steppingstone towards quantum key distribution and quantum repeater networks. The work was supported by the US-Navy Office of Naval Research, Grant Number N00141410801 and the Simons Foundation, Grant Number SBF241180.B. J. acknowledges financial assistance of the National Research Foundation (NRF) of South Africa.

Selective Entrainment of Theta Oscillations in the Dorsal Stream Causally Enhances Auditory Working Memory Performance.

PubMed

Albouy, Philippe; Weiss, Aurélien; Baillet, Sylvain; Zatorre, Robert J

2017-04-05

The implication of the dorsal stream in manipulating auditory information in working memory has been recently established. However, the oscillatory dynamics within this network and its causal relationship with behavior remain undefined. Using simultaneous MEG/EEG, we show that theta oscillations in the dorsal stream predict participants' manipulation abilities during memory retention in a task requiring the comparison of two patterns differing in temporal order. We investigated the causal relationship between brain oscillations and behavior by applying theta-rhythmic TMS combined with EEG over the MEG-identified target (left intraparietal sulcus) during the silent interval between the two stimuli. Rhythmic TMS entrained theta oscillation and boosted participants' accuracy. TMS-induced oscillatory entrainment scaled with behavioral enhancement, and both gains varied with participants' baseline abilities. These effects were not seen for a melody-comparison control task and were not observed for arrhythmic TMS. These data establish theta activity in the dorsal stream as causally related to memory manipulation. VIDEO ABSTRACT. Copyright © 2017 Elsevier Inc. All rights reserved.

Conditional bistability, a generic cellular mnemonic mechanism for robust and flexible working memory computations.

PubMed

Rodriguez, Guillaume; Sarazin, Matthieu; Clemente, Alexandra; Holden, Stephanie; Paz, Jeanne T; Delord, Bruno

2018-04-30

Persistent neural activity, the substrate of working memory, is thought to emerge from synaptic reverberation within recurrent networks. However, reverberation models do not robustly explain fundamental dynamics of persistent activity, including high-spiking irregularity, large intertrial variability, and state transitions. While cellular bistability may contribute to persistent activity, its rigidity appears incompatible with persistent activity labile characteristics. Here, we unravel in a cellular model a form of spike-mediated conditional bistability that is robust, generic and provides a rich repertoire of mnemonic computations. Under asynchronous synaptic inputs of the awakened state, conditional bistability generates spiking/bursting episodes, accounting for the irregularity, variability and state transitions characterizing persistent activity. This mechanism has likely been overlooked because of the sub-threshold input it requires and we predict how to assess it experimentally. Our results suggest a reexamination of the role of intrinsic properties in the collective network dynamics responsible for flexible working memory. SIGNIFICANCE STATEMENT This study unravels a novel form of intrinsic neuronal property, i.e. conditional bistability. We show that, thanks of its conditional character, conditional bistability favors the emergence of flexible and robust forms of persistent activity in PFC neural networks, in opposition to previously studied classical forms of absolute bistability. Specifically, we demonstrate for the first time that conditional bistability 1) is a generic biophysical spike-dependent mechanism of layer V pyramidal neurons in the PFC and that 2) it accounts for essential neurodynamical features for the organisation and flexibility of PFC persistent activity (the large irregularity and intertrial variability of the discharge and its organization under discrete stable states), which remain unexplained in a robust fashion by current models. Copyright © 2018 the authors.

Distributed Sensor Networks

DTIC Science & Technology

1979-09-30

University, Pittsburgh, Pennsylvania (1976). 14. R. L. Kirby, "ULISP for PDP-11s with Memory Management ," Report MCS-76-23763, University of Maryland...teletVpe or 9 raphIc S output. The recor iuL, po , uitist il so mon itot its owvn ( Onmand queue and a( knowlede commands Sent to It hN the UsCtr interfa I...kernel. By a net- work kernel we mean a multicomputer distributed operating system kernel that includes proces- sor schedulers, "core" memory managers , and

Associative memory in phasing neuron networks

DOE Office of Scientific and Technical Information (OSTI.GOV)

Nair, Niketh S; Bochove, Erik J.; Braiman, Yehuda

2014-01-01

We studied pattern formation in a network of coupled Hindmarsh-Rose model neurons and introduced a new model for associative memory retrieval using networks of Kuramoto oscillators. Hindmarsh-Rose Neural Networks can exhibit a rich set of collective dynamics that can be controlled by their connectivity. Specifically, we showed an instance of Hebb's rule where spiking was correlated with network topology. Based on this, we presented a simple model of associative memory in coupled phase oscillators.

Spreading activation in emotional memory networks and the cumulative effects of somatic markers.

PubMed

Foster, Paul S; Hubbard, Tyler; Campbell, Ransom W; Poole, Jonathan; Pridmore, Michael; Bell, Chris; Harrison, David W

2017-06-01

The theory of spreading activation proposes that the activation of a semantic memory node may spread along bidirectional associative links to other related nodes. Although this theory was originally proposed to explain semantic memory networks, a similar process may be said to exist with episodic or emotional memory networks. The Somatic Marker hypothesis proposes that remembering an emotional memory activates the somatic sensations associated with the memory. An integration of these two models suggests that as spreading activation in emotional memory networks increases, a greater number of associated somatic markers would become activated. This process would then result in greater changes in physiological functioning. We sought to investigate this possibility by having subjects recall words associated with sad and happy memories, in addition to a neutral condition. The average ages of the memories and the number of word memories recalled were then correlated with measures of heart rate and skin conductance. The results indicated significant positive correlations between the number of happy word memories and heart rate (r = .384, p = .022) and between the average ages of the sad memories and skin conductance (r = .556, p = .001). Unexpectedly, a significant negative relationship was found between the number of happy word memories and skin conductance (r = -.373, p = .025). The results provide partial support for our hypothesis, indicating that increasing spreading activation in emotional memory networks activates an increasing number of somatic markers and this is then reflected in greater physiological activity at the time of recalling the memories.

Hippocampal-targeted Theta-burst Stimulation Enhances Associative Memory Formation.

PubMed

Tambini, Arielle; Nee, Derek Evan; D'Esposito, Mark

2018-06-19

The hippocampus plays a critical role in episodic memory, among other cognitive functions. However, few tools exist to causally manipulate hippocampal function in healthy human participants. Recent work has targeted hippocampal-cortical networks by performing TMS to a region interconnected with the hippocampus, posterior inferior parietal cortex (pIPC). Such hippocampal-targeted TMS enhances associative memory and influences hippocampal functional connectivity. However, it is currently unknown which stages of mnemonic processing (encoding or retrieval) are affected by hippocampal-targeted TMS. Here, we examined whether hippocampal-targeted TMS influences the initial encoding of associations (vs. items) into memory. To selectively influence encoding and not retrieval, we performed continuous theta-burst TMS before participants encoded object-location associations and assessed memory after the direct effect of stimulation dissipated. Relative to control TMS and baseline memory, pIPC TMS enhanced associative memory success and confidence. Item memory was unaffected, demonstrating a selective influence on associative versus item memory. The strength of hippocampal-pIPC functional connectivity predicted TMS-related memory benefits, which was mediated by parahippocampal and retrosplenial cortices. Our findings indicate that hippocampal-targeted TMS can specifically modulate the encoding of new associations into memory without directly influencing retrieval processes and suggest that the ability to influence associative memory may be related to the fidelity of hippocampal TMS targeting. Our results support the notion that pIPC TMS may serve as a potential tool for manipulating hippocampal function in healthy participants. Nonetheless, future work combining hippocampal-targeted continuous theta-burst TMS with neuroimaging is needed to better understand the neural basis of TMS-induced memory changes.

Functional brain microstate predicts the outcome in a visuospatial working memory task.

PubMed

Muthukrishnan, Suriya-Prakash; Ahuja, Navdeep; Mehta, Nalin; Sharma, Ratna

2016-11-01

Humans have limited capacity of processing just up to 4 integrated items of information in the working memory. Thus, it is inevitable to commit more errors when challenged with high memory loads. However, the neural mechanisms that determine the accuracy of response at high memory loads still remain unclear. High temporal resolution of Electroencephalography (EEG) technique makes it the best tool to resolve the temporal dynamics of brain networks. EEG-defined microstate is the quasi-stable scalp electrical potential topography that represents the momentary functional state of brain. Thus, it has been possible to assess the information processing currently performed by the brain using EEG microstate analysis. We hypothesize that the EEG microstate preceding the trial could determine its outcome in a visuospatial working memory (VSWM) task. Twenty-four healthy participants performed a high memory load VSWM task, while their brain activity was recorded using EEG. Four microstate maps were found to represent the functional brain state prior to the trials in the VSWM task. One pre-trial microstate map was found to determine the accuracy of subsequent behavioural response. The intracranial generators of the pre-trial microstate map that determined the response accuracy were localized to the visuospatial processing areas at bilateral occipital, right temporal and limbic cortices. Our results imply that the behavioural outcome in a VSWM task could be determined by the intensity of activation of memory representations in the visuospatial processing brain regions prior to the trial. Copyright © 2016 Elsevier B.V. All rights reserved.

Neural correlates of visuospatial working memory in attention-deficit/hyperactivity disorder and healthy controls.

PubMed

van Ewijk, Hanneke; Weeda, Wouter D; Heslenfeld, Dirk J; Luman, Marjolein; Hartman, Catharina A; Hoekstra, Pieter J; Faraone, Stephen V; Franke, Barbara; Buitelaar, Jan K; Oosterlaan, Jaap

2015-08-30

Impaired visuospatial working memory (VSWM) is suggested to be a core neurocognitive deficit in attention-deficit/hyperactivity disorder (ADHD), yet the underlying neural activation patterns are poorly understood. Furthermore, it is unclear to what extent age and gender effects may play a role in VSWM-related brain abnormalities in ADHD. Functional magnetic resonance imaging (fMRI) data were collected from 109 individuals with ADHD (60% male) and 103 controls (53% male), aged 8-25 years, during a spatial span working memory task. VSWM-related brain activation was found in a widespread network, which was more widespread compared with N-back tasks used in the previous literature. Higher brain activation was associated with higher age and male gender. In comparison with controls, individuals with ADHD showed greater activation in the left inferior frontal gyrus (IFG) and the lateral frontal pole during memory load increase, effects explained by reduced activation on the low memory load in the IFG pars triangularis and increased activation during high load in the IFG pars opercularis. Age and gender effects did not differ between controls and individuals with ADHD. Results indicate that individuals with ADHD have difficulty in efficiently and sufficiently recruiting left inferior frontal brain regions with increasing task difficulty. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

`Unlearning' has a stabilizing effect in collective memories

NASA Astrophysics Data System (ADS)

Hopfield, J. J.; Feinstein, D. I.; Palmer, R. G.

1983-07-01

Crick and Mitchison1 have presented a hypothesis for the functional role of dream sleep involving an `unlearning' process. We have independently carried out mathematical and computer modelling of learning and `unlearning' in a collective neural network of 30-1,000 neurones. The model network has a content-addressable memory or `associative memory' which allows it to learn and store many memories. A particular memory can be evoked in its entirety when the network is stimulated by any adequate-sized subpart of the information of that memory2. But different memories of the same size are not equally easy to recall. Also, when memories are learned, spurious memories are also created and can also be evoked. Applying an `unlearning' process, similar to the learning processes but with a reversed sign and starting from a noise input, enhances the performance of the network in accessing real memories and in minimizing spurious ones. Although our model was not motivated by higher nervous function, our system displays behaviours which are strikingly parallel to those needed for the hypothesized role of `unlearning' in rapid eye movement (REM) sleep.

Changes in Neural Connectivity and Memory Following a Yoga Intervention for Older Adults: A Pilot Study.

PubMed

Eyre, Harris A; Acevedo, Bianca; Yang, Hongyu; Siddarth, Prabha; Van Dyk, Kathleen; Ercoli, Linda; Leaver, Amber M; Cyr, Natalie St; Narr, Katherine; Baune, Bernhard T; Khalsa, Dharma S; Lavretsky, Helen

2016-01-01

No study has explored the effect of yoga on cognitive decline and resting-state functional connectivity. This study explored the relationship between performance on memory tests and resting-state functional connectivity before and after a yoga intervention versus active control for subjects with mild cognitive impairment (MCI). Participants ( ≥ 55 y) with MCI were randomized to receive a yoga intervention or active "gold-standard" control (i.e., memory enhancement training (MET)) for 12 weeks. Resting-state functional magnetic resonance imaging was used to map correlations between brain networks and memory performance changes over time. Default mode networks (DMN), language and superior parietal networks were chosen as networks of interest to analyze the association with changes in verbal and visuospatial memory performance. Fourteen yoga and 11 MET participants completed the study. The yoga group demonstrated a statistically significant improvement in depression and visuospatial memory. We observed improved verbal memory performance correlated with increased connectivity between the DMN and frontal medial cortex, pregenual anterior cingulate cortex, right middle frontal cortex, posterior cingulate cortex, and left lateral occipital cortex. Improved verbal memory performance positively correlated with increased connectivity between the language processing network and the left inferior frontal gyrus. Improved visuospatial memory performance correlated inversely with connectivity between the superior parietal network and the medial parietal cortex. Yoga may be as effective as MET in improving functional connectivity in relation to verbal memory performance. These findings should be confirmed in larger prospective studies.

Language aptitude for pronunciation in advanced second language (L2) learners: behavioural predictors and neural substrates.

PubMed

Hu, Xiaochen; Ackermann, Hermann; Martin, Jason A; Erb, Michael; Winkler, Susanne; Reiterer, Susanne M

2013-12-01

Individual differences in second language (L2) aptitude have been assumed to depend upon a variety of cognitive and personality factors. Especially, the cognitive factor phonological working memory has been conceptualised as language learning device. However, strong associations between phonological working memory and L2 aptitude have been previously found in early-stage learners only, not in advanced learners. The current study aimed at investigating the behavioural and neurobiological predictors of advanced L2 learning. Our behavioural results showed that phonetic coding ability and empathy, but not phonological working memory, predict L2 pronunciation aptitude in advanced learners. Second, functional neuroimaging revealed this behavioural trait to be correlated with hemodynamic responses of the cerebral network of speech motor control and auditory-perceptual areas. We suggest that the acquisition of L2 pronunciation aptitude is a dynamic process, requiring a variety of neural resources at different processing stages over time. Copyright © 2012 Elsevier Inc. All rights reserved.

A multilayer perceptron solution to the match phase problem in rule-based artificial intelligence systems

NASA Technical Reports Server (NTRS)

Sartori, Michael A.; Passino, Kevin M.; Antsaklis, Panos J.

1992-01-01

In rule-based AI planning, expert, and learning systems, it is often the case that the left-hand-sides of the rules must be repeatedly compared to the contents of some 'working memory'. The traditional approach to solve such a 'match phase problem' for production systems is to use the Rete Match Algorithm. Here, a new technique using a multilayer perceptron, a particular artificial neural network model, is presented to solve the match phase problem for rule-based AI systems. A syntax for premise formulas (i.e., the left-hand-sides of the rules) is defined, and working memory is specified. From this, it is shown how to construct a multilayer perceptron that finds all of the rules which can be executed for the current situation in working memory. The complexity of the constructed multilayer perceptron is derived in terms of the maximum number of nodes and the required number of layers. A method for reducing the number of layers to at most three is also presented.

NMDA Receptors Subserve Persistent Neuronal Firing During Working Memory In Dorsolateral Prefrontal Cortex

PubMed Central

Wang, Min; Yang, Yang; Wang, Ching-Jung; Gamo, Nao J.; Jin, Lu E.; Mazer, James A.; Morrison, John H.; Wang, Xiao-Jing; Arnsten, Amy F.T.

2013-01-01

Summary Neurons in the primate dorsolateral prefrontal cortex (dlPFC) generate persistent firing in the absence of sensory stimulation, the foundation of mental representation. Persistent firing arises from recurrent excitation within a network of pyramidal Delay cells. Here, we examined glutamate receptor influences underlying persistent firing in primate dlPFC during a spatial working memory task. Computational models predicted dependence on NMDA receptor (NMDAR) NR2B stimulation, and Delay cell persistent firing was abolished by local NR2B NMDAR blockade or by systemic ketamine administration. AMPA receptors (AMPAR) contributed background depolarization to sustain network firing. In contrast, many Response cells -which likely predominate in rodent PFC- were sensitive to AMPAR blockade and increased firing following systemic ketamine, indicating that models of ketamine actions should be refined to reflect neuronal heterogeneity. The reliance of Delay cells on NMDAR may explain why insults to NMDARs in schizophrenia or Alzheimer’s Disease profoundly impair cognition. PMID:23439125

A locus coeruleus-norepinephrine account of individual differences in working memory capacity and attention control.

PubMed

Unsworth, Nash; Robison, Matthew K

2017-08-01

Studies examining individual differences in working memory capacity (WMC) have suggested that low WMC individuals have particular deficits in attention control processes compared to high WMC individuals. In the current article we suggest that part of the WMC-attention control relation is due to variation in the functioning of the locus coeruleus-norepinephrine system (LC-NE). Specifically, we suggest that because of dysregulation of LC-NE functioning, the fronto-parietal control network for low WMC individuals is only weakly activated, resulting in greater default-mode network activity (and greater mind-wandering) for low WMC individuals compared to high WMC individuals. This results in disrupted attention control and overall more erratic performance (more lapses of attention) for low WMC individuals than for high WMC individuals. This framework is used to examine previous studies of individual differences in WMC and attention control, and new evidence is examined on the basis of predictions of the framework to pupillary responses as an indirect marker of LC-NE functioning.

Neural network communication facilitates verbal working memory.

PubMed

Kustermann, Thomas; Rockstroh, Brigitte; Miller, Gregory A; Popov, Tzvetan

2018-05-28

Oscillatory brain activity in the theta, alpha, and gamma frequency ranges has been associated with working memory (WM). In addition to alpha and theta activity associated with WM retention, and gamma band activity with item encoding, activity in the alpha band is related to the deployment of attention resources and information. The present study sought to specify distinct roles of neuromagnetic 4-7 Hz theta, 9-13 Hz alpha, and 50-70 Hz gamma power modulation and communication in fronto-parietal networks during cued, hemifield-specific item presentation in a modified Sternberg verbal WM task in 14 student volunteers. Lateralized posterior alpha and gamma power during encoding suggest a preparatory role of alpha oscillations. Bilateral alpha power increases during maintenance reflect information retention for the non-lateralized probe response. Lateralized alpha power increase during encoding was apparently driven by a monotonic increase in fronto-parietal 6 Hz phase, suggesting a mechanism facilitating WM encoding and successful performance. Copyright © 2018 Elsevier B.V. All rights reserved.

Top-down and bottom-up attention-to-memory: mapping functional connectivity in two distinct networks that underlie cued and uncued recognition memory.

PubMed

Burianová, Hana; Ciaramelli, Elisa; Grady, Cheryl L; Moscovitch, Morris

2012-11-15

The objective of this study was to examine the functional connectivity of brain regions active during cued and uncued recognition memory to test the idea that distinct networks would underlie these memory processes, as predicted by the attention-to-memory (AtoM) hypothesis. The AtoM hypothesis suggests that dorsal parietal cortex (DPC) allocates effortful top-down attention to memory retrieval during cued retrieval, whereas ventral parietal cortex (VPC) mediates spontaneous bottom-up capture of attention by memory during uncued retrieval. To identify networks associated with these two processes, we conducted a functional connectivity analysis of a left DPC and a left VPC region, both identified by a previous analysis of task-related regional activations. We hypothesized that the two parietal regions would be functionally connected with distinct neural networks, reflecting their engagement in the differential mnemonic processes. We found two spatially dissociated networks that overlapped only in the precuneus. During cued trials, DPC was functionally connected with dorsal attention areas, including the superior parietal lobules, right precuneus, and premotor cortex, as well as relevant memory areas, such as the left hippocampus and the middle frontal gyri. During uncued trials, VPC was functionally connected with ventral attention areas, including the supramarginal gyrus, cuneus, and right fusiform gyrus, as well as the parahippocampal gyrus. In addition, activity in the DPC network was associated with faster response times for cued retrieval. This is the first study to show a dissociation of the functional connectivity of posterior parietal regions during episodic memory retrieval, characterized by a top-down AtoM network involving DPC and a bottom-up AtoM network involving VPC. Copyright © 2012 Elsevier Inc. All rights reserved.

Optimal Recall from Bounded Metaplastic Synapses: Predicting Functional Adaptations in Hippocampal Area CA3

PubMed Central

Savin, Cristina; Dayan, Peter; Lengyel, Máté

2014-01-01

A venerable history of classical work on autoassociative memory has significantly shaped our understanding of several features of the hippocampus, and most prominently of its CA3 area, in relation to memory storage and retrieval. However, existing theories of hippocampal memory processing ignore a key biological constraint affecting memory storage in neural circuits: the bounded dynamical range of synapses. Recent treatments based on the notion of metaplasticity provide a powerful model for individual bounded synapses; however, their implications for the ability of the hippocampus to retrieve memories well and the dynamics of neurons associated with that retrieval are both unknown. Here, we develop a theoretical framework for memory storage and recall with bounded synapses. We formulate the recall of a previously stored pattern from a noisy recall cue and limited-capacity (and therefore lossy) synapses as a probabilistic inference problem, and derive neural dynamics that implement approximate inference algorithms to solve this problem efficiently. In particular, for binary synapses with metaplastic states, we demonstrate for the first time that memories can be efficiently read out with biologically plausible network dynamics that are completely constrained by the synaptic plasticity rule, and the statistics of the stored patterns and of the recall cue. Our theory organises into a coherent framework a wide range of existing data about the regulation of excitability, feedback inhibition, and network oscillations in area CA3, and makes novel and directly testable predictions that can guide future experiments. PMID:24586137

Default Mode Network Interference in Mild Traumatic Brain Injury – A Pilot Resting State Study

PubMed Central

Sours, Chandler; Zhuo, Jiachen; Janowich, Jacqueline; Aarabi, Bizhan; Shanmuganathan, Kathirkamanthan; Gullapalli, Rao P

2013-01-01

In this study we investigated the functional connectivity in 23 Mild TBI (mTBI) patients with and without memory complaints using resting state fMRI in the sub-acute stage of injury as well as a group of control participants. Results indicate that mTBI patients with memory complaints performed significantly worse than patients without memory complaints on tests assessing memory from the Automated Neuropsychological Assessment Metrics (ANAM). Altered functional connectivity was observed between the three groups between the default mode network (DMN) and the nodes of the task positive network (TPN). Altered functional connectivity was also observed between both the TPN and DMN and nodes associated with the Salience Network (SN). Following mTBI there is a reduction in anti-correlated networks for both those with and without memory complaints for the DMN, but only a reduction in the anti-correlated network in mTBI patients with memory complaints for the TPN. Furthermore, an increased functional connectivity between the TPN and SN appears to be associated with reduced performance on memory assessments. Overall the results suggest that a disruption in the segregation of the DMN and the TPN at rest may be mediated through both a direct pathway of increased FC between various nodes of the TPN and DMN, and through an indirect pathway that links the TPN and DMN through nodes of the SN. This disruption between networks may cause a detrimental impact on memory functioning following mTBI, supporting the Default Mode Interference Hypothesis in the context of mTBI related memory deficits. PMID:23994210

Default mode network interference in mild traumatic brain injury - a pilot resting state study.

PubMed

Sours, Chandler; Zhuo, Jiachen; Janowich, Jacqueline; Aarabi, Bizhan; Shanmuganathan, Kathirkamanthan; Gullapalli, Rao P

2013-11-06

In this study we investigated the functional connectivity in 23 Mild TBI (mTBI) patients with and without memory complaints using resting state fMRI in the sub-acute stage of injury as well as a group of control participants. Results indicate that mTBI patients with memory complaints performed significantly worse than patients without memory complaints on tests assessing memory from the Automated Neuropsychological Assessment Metrics (ANAM). Altered functional connectivity was observed between the three groups between the default mode network (DMN) and the nodes of the task positive network (TPN). Altered functional connectivity was also observed between both the TPN and DMN and nodes associated with the Salience Network (SN). Following mTBI there is a reduction in anti-correlated networks for both those with and without memory complaints for the DMN, but only a reduction in the anti-correlated network in mTBI patients with memory complaints for the TPN. Furthermore, an increased functional connectivity between the TPN and SN appears to be associated with reduced performance on memory assessments. Overall the results suggest that a disruption in the segregation of the DMN and the TPN at rest may be mediated through both a direct pathway of increased FC between various nodes of the TPN and DMN, and through an indirect pathway that links the TPN and DMN through nodes of the SN. This disruption between networks may cause a detrimental impact on memory functioning following mTBI, supporting the Default Mode Interference Hypothesis in the context of mTBI related memory deficits. © 2013 Elsevier B.V. All rights reserved.

Networks of Memories

DTIC Science & Technology

2013-03-01

2000). The construction of  autobiographical   memories in the self­memory system. Psychological Review, 107(2), 261­288. Dennis, S., & Chapman, A. (2010...AFRL-OSR-VA-TR-2013-0131 Networks of Memories Simon Dennis, Mikhail Belkin Ohio State University March 2013 Final...Back (Rev. 8/98) 1 Networks of  Memories FA9550­09­1­0614 Professor Jay Myung PI: Simon Dennis Ohio State University February 15, 2013 2 Introduction

Self-organization and solution of shortest-path optimization problems with memristive networks

NASA Astrophysics Data System (ADS)

Pershin, Yuriy V.; Di Ventra, Massimiliano

2013-07-01

We show that memristive networks, namely networks of resistors with memory, can efficiently solve shortest-path optimization problems. Indeed, the presence of memory (time nonlocality) promotes self organization of the network into the shortest possible path(s). We introduce a network entropy function to characterize the self-organized evolution, show the solution of the shortest-path problem and demonstrate the healing property of the solution path. Finally, we provide an algorithm to solve the traveling salesman problem. Similar considerations apply to networks of memcapacitors and meminductors, and networks with memory in various dimensions.

Continuing the search for the engram: examining the mechanism of fear memories.

PubMed

Josselyn, Sheena A

2010-07-01

The goal of my research is to gain insight using rodent models into the fundamental molecular, cellular and systems that make up the base of memory formation. My work focuses on fear memories. Aberrant fear and/or anxiety may be at the heart of many psychiatric disorders. In this article, I review the results of my research group; these results show that particular neurons in the lateral amygdala, a brain region important for fear, are specifically involved in particular fear memories. We started by showing that the transcription factor CREB (cAMP/Ca(2+) response element binding protein) plays a key role in the formation of fear memories. Next, we used viral vectors to overexpress CREB in a subset of lateral amygdala neurons. This not only facilitated fear memory formation but also "drove" the memory into the neurons with relatively increased CREB function. Finally, we showed that selective ablation of the neurons overexpressing CREB in the lateral amygdala selectively erased the fear memory. These findings are the first to show disruption of a specific memory by disrupting select neurons within a distributed network.

Working Memory Load Strengthens Reward Prediction Errors.

PubMed

Collins, Anne G E; Ciullo, Brittany; Frank, Michael J; Badre, David

2017-04-19

Reinforcement learning (RL) in simple instrumental tasks is usually modeled as a monolithic process in which reward prediction errors (RPEs) are used to update expected values of choice options. This modeling ignores the different contributions of different memory and decision-making systems thought to contribute even to simple learning. In an fMRI experiment, we investigated how working memory (WM) and incremental RL processes interact to guide human learning. WM load was manipulated by varying the number of stimuli to be learned across blocks. Behavioral results and computational modeling confirmed that learning was best explained as a mixture of two mechanisms: a fast, capacity-limited, and delay-sensitive WM process together with slower RL. Model-based analysis of fMRI data showed that striatum and lateral prefrontal cortex were sensitive to RPE, as shown previously, but, critically, these signals were reduced when the learning problem was within capacity of WM. The degree of this neural interaction related to individual differences in the use of WM to guide behavioral learning. These results indicate that the two systems do not process information independently, but rather interact during learning. SIGNIFICANCE STATEMENT Reinforcement learning (RL) theory has been remarkably productive at improving our understanding of instrumental learning as well as dopaminergic and striatal network function across many mammalian species. However, this neural network is only one contributor to human learning and other mechanisms such as prefrontal cortex working memory also play a key role. Our results also show that these other players interact with the dopaminergic RL system, interfering with its key computation of reward prediction errors. Copyright © 2017 the authors 0270-6474/17/374332-11$15.00/0.

Resonator memories and optical novelty filters

NASA Astrophysics Data System (ADS)

Anderson, Dana Z.; Erle, Marie C.

Optical resonators having holographic elements are potential candidates for storing information that can be accessed through content addressable or associative recall. Closely related to the resonator memory is the optical novelty filter, which can detect the differences between a test object and a set of reference objects. We discuss implementations of these devices using continuous optical media such as photorefractive materials. The discussion is framed in the context of neural network models. There are both formal and qualitative similarities between the resonator memory and optical novelty filter and network models. Mode competition arises in the theory of the resonator memory, much as it does in some network models. We show that the role of the phenomena of "daydreaming" in the real-time programmable optical resonator is very much akin to the role of "unlearning" in neural network memories. The theory of programming the real-time memory for a single mode is given in detail. This leads to a discussion of the optical novelty filter. Experimental results for the resonator memory, the real-time programmable memory, and the optical tracking novelty filter are reviewed. We also point to several issues that need to be addressed in order to implement more formal models of neural networks.

Resonator Memories And Optical Novelty Filters

NASA Astrophysics Data System (ADS)

Anderson, Dana Z.; Erie, Marie C.

1987-05-01

Optical resonators having holographic elements are potential candidates for storing information that can be accessed through content-addressable or associative recall. Closely related to the resonator memory is the optical novelty filter, which can detect the differences between a test object and a set of reference objects. We discuss implementations of these devices using continuous optical media such as photorefractive ma-terials. The discussion is framed in the context of neural network models. There are both formal and qualitative similarities between the resonator memory and optical novelty filter and network models. Mode competition arises in the theory of the resonator memory, much as it does in some network models. We show that the role of the phenomena of "daydream-ing" in the real-time programmable optical resonator is very much akin to the role of "unlearning" in neural network memories. The theory of programming the real-time memory for a single mode is given in detail. This leads to a discussion of the optical novelty filter. Experimental results for the resonator memory, the real-time programmable memory, and the optical tracking novelty filter are reviewed. We also point to several issues that need to be addressed in order to implement more formal models of neural networks.

Spiking neural network simulation: memory-optimal synaptic event scheduling.

PubMed

Stewart, Robert D; Gurney, Kevin N

2011-06-01

Spiking neural network simulations incorporating variable transmission delays require synaptic events to be scheduled prior to delivery. Conventional methods have memory requirements that scale with the total number of synapses in a network. We introduce novel scheduling algorithms for both discrete and continuous event delivery, where the memory requirement scales instead with the number of neurons. Superior algorithmic performance is demonstrated using large-scale, benchmarking network simulations.

A New Local Bipolar Autoassociative Memory Based on External Inputs of Discrete Recurrent Neural Networks With Time Delay.

PubMed

Zhou, Caigen; Zeng, Xiaoqin; Luo, Chaomin; Zhang, Huaguang

In this paper, local bipolar auto-associative memories are presented based on discrete recurrent neural networks with a class of gain type activation function. The weight parameters of neural networks are acquired by a set of inequalities without the learning procedure. The global exponential stability criteria are established to ensure the accuracy of the restored patterns by considering time delays and external inputs. The proposed methodology is capable of effectively overcoming spurious memory patterns and achieving memory capacity. The effectiveness, robustness, and fault-tolerant capability are validated by simulated experiments.In this paper, local bipolar auto-associative memories are presented based on discrete recurrent neural networks with a class of gain type activation function. The weight parameters of neural networks are acquired by a set of inequalities without the learning procedure. The global exponential stability criteria are established to ensure the accuracy of the restored patterns by considering time delays and external inputs. The proposed methodology is capable of effectively overcoming spurious memory patterns and achieving memory capacity. The effectiveness, robustness, and fault-tolerant capability are validated by simulated experiments.

Working Memory for Serial Order Is Dysfunctional in Adults With a History of Developmental Dyscalculia: Evidence From Behavioral and Neuroimaging Data.

PubMed

Attout, Lucie; Salmon, Eric; Majerus, Steve

2015-01-01

Recent studies suggest that order working memory (WM) may be specifically associated with numerical abilities. This study explored behavioral performance and neural networks associated with verbal WM in adults with a history of developmental dyscalculia (DD). The DD group performed significantly poorer but with the same precision than the control group in order WM tasks and showed a lower activation of the right middle frontal gyrus during the order WM and the alphabetical order judgment tasks. This study suggests a persistent impairment in order WM in adults with DD, characterized by more general difficulties in controlled activation of order information.

Driving working memory with frequency-tuned noninvasive brain stimulation.

PubMed

Albouy, Philippe; Baillet, Sylvain; Zatorre, Robert J

2018-04-29

Frequency-tuned noninvasive brain stimulation is a recent approach in cognitive neuroscience that involves matching the frequency of transcranially applied electromagnetic fields to that of specific oscillatory components of the underlying neurophysiology. The objective of this method is to modulate ongoing/intrinsic brain oscillations, which correspond to rhythmic fluctuations of neural excitability, to causally change behavior. We review the impact of frequency-tuned noninvasive brain stimulation on the research field of human working memory. We argue that this is a powerful method to probe and understand the mechanisms of memory functions, targeting specifically task-related oscillatory dynamics, neuronal representations, and brain networks. We report the main behavioral and neurophysiological outcomes published to date, in particular, how functionally relevant oscillatory signatures in signal power and interregional connectivity yield causal changes of working memory abilities. We also present recent developments of the technique that aim to modulate cross-frequency coupling in polyrhythmic neural activity. Overall, the method has led to significant advances in our understanding of the mechanisms of systems neuroscience, and the role of brain oscillations in cognition and behavior. We also emphasize the translational impact of noninvasive brain stimulation techniques in the development of therapeutic approaches. © 2018 New York Academy of Sciences.

Effects of nicotine on electroencephalographic (EEG) and behavioural measures of visual working memory in non-smokers during a dual-task paradigm.

PubMed

Fisher, Derek J; Knobelsdorf, Amy; Jaworska, Natalia; Daniels, Richelle; Knott, Verner J

2013-01-01

Research in smokers has shown that nicotine may have the ability to improve certain aspects of cognitive performance, including working memory and attention, processes which implicate frontal and frontal-parietal brain networks. There is limited research on the cognitive effects of nicotine and their associated neural underpinnings in non-smokers. This study examined the effects of acute nicotine on a working memory task alone or combined with a visual detection task (single- and dual-task conditions) using electroencephalographic (EEG) recordings and behavioural performance measures. Twenty non-smokers (13 females; 7 males) received nicotine gum (6 mg) in a double-blind, randomized, placebo-controlled, repeated measures design. Spectral EEG, together with response speed and accuracy measures, were obtained while participants completed a series of N-Back tasks under single- and dual-task conditions. Nicotine failed to exert any significant effects on performance measures, however, EEG changes were observed, primarily in frontal recordings, which varied with memory load, task condition and hemisphere. These findings, discussed in relation to previous studies in smokers, support the notion that nicotine may modulate central executive systems and contribute to smoking behaviour. Copyright © 2012 Elsevier Inc. All rights reserved.

How Attention Can Create Synaptic Tags for the Learning of Working Memories in Sequential Tasks

PubMed Central

Rombouts, Jaldert O.; Bohte, Sander M.; Roelfsema, Pieter R.

2015-01-01

Intelligence is our ability to learn appropriate responses to new stimuli and situations. Neurons in association cortex are thought to be essential for this ability. During learning these neurons become tuned to relevant features and start to represent them with persistent activity during memory delays. This learning process is not well understood. Here we develop a biologically plausible learning scheme that explains how trial-and-error learning induces neuronal selectivity and working memory representations for task-relevant information. We propose that the response selection stage sends attentional feedback signals to earlier processing levels, forming synaptic tags at those connections responsible for the stimulus-response mapping. Globally released neuromodulators then interact with tagged synapses to determine their plasticity. The resulting learning rule endows neural networks with the capacity to create new working memory representations of task relevant information as persistent activity. It is remarkably generic: it explains how association neurons learn to store task-relevant information for linear as well as non-linear stimulus-response mappings, how they become tuned to category boundaries or analog variables, depending on the task demands, and how they learn to integrate probabilistic evidence for perceptual decisions. PMID:25742003

Psychophysiological whole-brain network clustering based on connectivity dynamics analysis in naturalistic conditions.

PubMed

Raz, Gal; Shpigelman, Lavi; Jacob, Yael; Gonen, Tal; Benjamini, Yoav; Hendler, Talma

2016-12-01

We introduce a novel method for delineating context-dependent functional brain networks whose connectivity dynamics are synchronized with the occurrence of a specific psychophysiological process of interest. In this method of context-related network dynamics analysis (CRNDA), a continuous psychophysiological index serves as a reference for clustering the whole-brain into functional networks. We applied CRNDA to fMRI data recorded during the viewing of a sadness-inducing film clip. The method reliably demarcated networks in which temporal patterns of connectivity related to the time series of reported emotional intensity. Our work successfully replicated the link between network connectivity and emotion rating in an independent sample group for seven of the networks. The demarcated networks have clear common functional denominators. Three of these networks overlap with distinct empathy-related networks, previously identified in distinct sets of studies. The other networks are related to sensorimotor processing, language, attention, and working memory. The results indicate that CRNDA, a data-driven method for network clustering that is sensitive to transient connectivity patterns, can productively and reliably demarcate networks that follow psychologically meaningful processes. Hum Brain Mapp 37:4654-4672, 2016. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Multilevel non-volatile data storage utilizing common current hysteresis of networked single walled carbon nanotubes

NASA Astrophysics Data System (ADS)

Hwang, Ihn; Wang, Wei; Hwang, Sun Kak; Cho, Sung Hwan; Kim, Kang Lib; Jeong, Beomjin; Huh, June; Park, Cheolmin

2016-05-01

The characteristic source-drain current hysteresis frequently observed in field-effect transistors with networked single walled carbon-nanotube (NSWNT) channels is problematic for the reliable switching and sensing performance of devices. But the two distinct current states of the hysteresis curve at a zero gate voltage can be useful for memory applications. In this work, we demonstrate a novel non-volatile transistor memory with solution-processed NSWNTs which are suitable for multilevel data programming and reading. A polymer passivation layer with a small amount of water employed on the top of the NSWNT channel serves as an efficient gate voltage dependent charge trapping and de-trapping site. A systematic investigation evidences that the water mixed in a polymer passivation solution is critical for reliable non-volatile memory operation. The optimized device is air-stable and temperature-resistive up to 80 °C and exhibits excellent non-volatile memory performance with an on/off current ratio greater than 104, a switching time less than 100 ms, data retention longer than 4000 s, and write/read endurance over 100 cycles. Furthermore, the gate voltage dependent charge injection mediated by water in the passivation layer allowed for multilevel operation of our memory in which 4 distinct current states were programmed repetitively and preserved over a long time period.The characteristic source-drain current hysteresis frequently observed in field-effect transistors with networked single walled carbon-nanotube (NSWNT) channels is problematic for the reliable switching and sensing performance of devices. But the two distinct current states of the hysteresis curve at a zero gate voltage can be useful for memory applications. In this work, we demonstrate a novel non-volatile transistor memory with solution-processed NSWNTs which are suitable for multilevel data programming and reading. A polymer passivation layer with a small amount of water employed on the top of the NSWNT channel serves as an efficient gate voltage dependent charge trapping and de-trapping site. A systematic investigation evidences that the water mixed in a polymer passivation solution is critical for reliable non-volatile memory operation. The optimized device is air-stable and temperature-resistive up to 80 °C and exhibits excellent non-volatile memory performance with an on/off current ratio greater than 104, a switching time less than 100 ms, data retention longer than 4000 s, and write/read endurance over 100 cycles. Furthermore, the gate voltage dependent charge injection mediated by water in the passivation layer allowed for multilevel operation of our memory in which 4 distinct current states were programmed repetitively and preserved over a long time period. Electronic supplementary information (ESI) available. See DOI: 10.1039/c6nr00505e

Caffeine impact on working memory-related network activation patterns in early stages of cognitive decline.

PubMed

Haller, Sven; Montandon, Marie-Louise; Rodriguez, Cristelle; Moser, Dominik; Toma, Simona; Hofmeister, Jeremy; Giannakopoulos, Panteleimon

2017-04-01

Recent evidence indicates that caffeine may have a beneficial effect on cognitive decline and dementia. The current investigation assessed the effect of acute caffeine administration on working memory during the earliest stage of cognitive decline in elderly participants. The study includes consecutive 45 elderly controls and 18 individuals with mild cognitive impairment (MCI, 71.6 ± 4.7 years, 7 females). During neuropsychological follow-up at 18 months, 24 controls remained stable (sCON, 70.0 ± 4.3 years, 11 women), while the remaining 21 showed subtle cognitive deterioration (dCON, 73.4 ± 5.9 years, 14 women). All participants underwent an established 2-back working task in a crossover design of 200 mg caffeine versus placebo. Data analysis included task-related general linear model and functional connectivity tensorial independent component analysis. Working memory behavioral performances did not differ between sCON and dCON, while MCI was slower and less accurate than both control groups (p < 0.05). The dCON group had a less pronounced effect of acute caffeine administration essentially restricted to the right hemisphere (p < 0.05 corrected) and reduced default mode network (DMN) deactivation compared to sCON (p < 0.01 corrected). dCON cases are characterized by decreased sensitivity to caffeine effects on brain activation and DMN deactivation. These complex fMRI patterns possibly reflect the instable status of these cases with intact behavioral performances despite already existing functional alterations in neocortical circuits.

Changes in Neural Connectivity and Memory Following a Yoga Intervention for Older Adults: A Pilot Study

PubMed Central

Eyre, Harris A.; Acevedo, Bianca; Yang, Hongyu; Siddarth, Prabha; Van Dyk, Kathleen; Ercoli, Linda; Leaver, Amber M.; Cyr, Natalie St.; Narr, Katherine; Baune, Bernhard T.; Khalsa, Dharma S.; Lavretsky, Helen

2016-01-01

Background: No study has explored the effect of yoga on cognitive decline and resting-state functional connectivity. Objectives: This study explored the relationship between performance on memory tests and resting-state functional connectivity before and after a yoga intervention versus active control for subjects with mild cognitive impairment (MCI). Methods: Participants ( ≥ 55 y) with MCI were randomized to receive a yoga intervention or active “gold-standard” control (i.e., memory enhancement training (MET)) for 12 weeks. Resting-state functional magnetic resonance imaging was used to map correlations between brain networks and memory performance changes over time. Default mode networks (DMN), language and superior parietal networks were chosen as networks of interest to analyze the association with changes in verbal and visuospatial memory performance. Results: Fourteen yoga and 11 MET participants completed the study. The yoga group demonstrated a statistically significant improvement in depression and visuospatial memory. We observed improved verbal memory performance correlated with increased connectivity between the DMN and frontal medial cortex, pregenual anterior cingulate cortex, right middle frontal cortex, posterior cingulate cortex, and left lateral occipital cortex. Improved verbal memory performance positively correlated with increased connectivity between the language processing network and the left inferior frontal gyrus. Improved visuospatial memory performance correlated inversely with connectivity between the superior parietal network and the medial parietal cortex. Conclusion:Yoga may be as effective as MET in improving functional connectivity in relation to verbal memory performance. These findings should be confirmed in larger prospective studies. PMID:27060939

Merlin - Massively parallel heterogeneous computing

NASA Technical Reports Server (NTRS)

Wittie, Larry; Maples, Creve

1989-01-01

Hardware and software for Merlin, a new kind of massively parallel computing system, are described. Eight computers are linked as a 300-MIPS prototype to develop system software for a larger Merlin network with 16 to 64 nodes, totaling 600 to 3000 MIPS. These working prototypes help refine a mapped reflective memory technique that offers a new, very general way of linking many types of computer to form supercomputers. Processors share data selectively and rapidly on a word-by-word basis. Fast firmware virtual circuits are reconfigured to match topological needs of individual application programs. Merlin's low-latency memory-sharing interfaces solve many problems in the design of high-performance computing systems. The Merlin prototypes are intended to run parallel programs for scientific applications and to determine hardware and software needs for a future Teraflops Merlin network.

Mnemonic convergence in social networks: The emergent properties of cognition at a collective level.

PubMed

Coman, Alin; Momennejad, Ida; Drach, Rae D; Geana, Andra

2016-07-19

The development of shared memories, beliefs, and norms is a fundamental characteristic of human communities. These emergent outcomes are thought to occur owing to a dynamic system of information sharing and memory updating, which fundamentally depends on communication. Here we report results on the formation of collective memories in laboratory-created communities. We manipulated conversational network structure in a series of real-time, computer-mediated interactions in fourteen 10-member communities. The results show that mnemonic convergence, measured as the degree of overlap among community members' memories, is influenced by both individual-level information-processing phenomena and by the conversational social network structure created during conversational recall. By studying laboratory-created social networks, we show how large-scale social phenomena (i.e., collective memory) can emerge out of microlevel local dynamics (i.e., mnemonic reinforcement and suppression effects). The social-interactionist approach proposed herein points to optimal strategies for spreading information in social networks and provides a framework for measuring and forging collective memories in communities of individuals.

Extended write combining using a write continuation hint flag

DOEpatents

Chen, Dong; Gara, Alan; Heidelberger, Philip; Ohmacht, Martin; Vranas, Pavlos

2013-06-04

A computing apparatus for reducing the amount of processing in a network computing system which includes a network system device of a receiving node for receiving electronic messages comprising data. The electronic messages are transmitted from a sending node. The network system device determines when more data of a specific electronic message is being transmitted. A memory device stores the electronic message data and communicating with the network system device. A memory subsystem communicates with the memory device. The memory subsystem stores a portion of the electronic message when more data of the specific message will be received, and the buffer combines the portion with later received data and moves the data to the memory device for accessible storage.

Past makes future: role of pFC in prediction.

PubMed

Fuster, Joaquín M; Bressler, Steven L

2015-04-01

The pFC enables the essential human capacities for predicting future events and preadapting to them. These capacities rest on both the structure and dynamics of the human pFC. Structurally, pFC, together with posterior association cortex, is at the highest hierarchical level of cortical organization, harboring neural networks that represent complex goal-directed actions. Dynamically, pFC is at the highest level of the perception-action cycle, the circular processing loop through the cortex that interfaces the organism with the environment in the pursuit of goals. In its predictive and preadaptive roles, pFC supports cognitive functions that are critical for the temporal organization of future behavior, including planning, attentional set, working memory, decision-making, and error monitoring. These functions have a common future perspective and are dynamically intertwined in goal-directed action. They all utilize the same neural infrastructure: a vast array of widely distributed, overlapping, and interactive cortical networks of personal memory and semantic knowledge, named cognits, which are formed by synaptic reinforcement in learning and memory acquisition. From this cortex-wide reservoir of memory and knowledge, pFC generates purposeful, goal-directed actions that are preadapted to predicted future events.

Concept typicality responses in the semantic memory network.

PubMed

Santi, Andrea; Raposo, Ana; Frade, Sofia; Marques, J Frederico

2016-12-01

For decades concept typicality has been recognized as critical to structuring conceptual knowledge, but only recently has typicality been applied in better understanding the processes engaged by the neurological network underlying semantic memory. This previous work has focused on one region within the network - the Anterior Temporal Lobe (ATL). The ATL responds negatively to concept typicality (i.e., the more atypical the item, the greater the activation in the ATL). To better understand the role of typicality in the entire network, we ran an fMRI study using a category verification task in which concept typicality was manipulated parametrically. We argue that typicality is relevant to both amodal feature integration centers as well as category-specific regions. Both the Inferior Frontal Gyrus (IFG) and ATL demonstrated a negative correlation with typicality, whereas inferior parietal regions showed positive effects. We interpret this in light of functional theories of these regions. Interactions between category and typicality were not observed in regions classically recognized as category-specific, thus, providing an argument against category specific regions, at least with fMRI. Copyright © 2016 Elsevier Ltd. All rights reserved.

Abnormal-induced theta activity supports early directed-attention network deficits in progressive MCI.

PubMed

Deiber, Marie-Pierre; Ibañez, Vicente; Missonnier, Pascal; Herrmann, François; Fazio-Costa, Lara; Gold, Gabriel; Giannakopoulos, Panteleimon

2009-09-01

The electroencephalography (EEG) theta frequency band reacts to memory and selective attention paradigms. Global theta oscillatory activity includes a posterior phase-locked component related to stimulus processing and a frontal-induced component modulated by directed attention. To investigate the presence of early deficits in the directed attention-related network in elderly individuals with mild cognitive impairment (MCI), time-frequency analysis at baseline was used to assess global and induced theta oscillatory activity (4-6Hz) during n-back working memory tasks in 29 individuals with MCI and 24 elderly controls (EC). At 1-year follow-up, 13 MCI patients were still stable and 16 had progressed. Baseline task performance was similar in stable and progressive MCI cases. Induced theta activity at baseline was significantly reduced in progressive MCI as compared to EC and stable MCI in all n-back tasks, which were similar in terms of directed attention requirements. While performance is maintained, the decrease of induced theta activity suggests early deficits in the directed-attention network in progressive MCI, whereas this network is functionally preserved in stable MCI.

EEG Cortical Connectivity Analysis of Working Memory Reveals Topological Reorganization in Theta and Alpha Bands

PubMed Central

Dai, Zhongxiang; de Souza, Joshua; Lim, Julian; Ho, Paul M.; Chen, Yu; Li, Junhua; Thakor, Nitish; Bezerianos, Anastasios; Sun, Yu

2017-01-01

Numerous studies have revealed various working memory (WM)-related brain activities that originate from various cortical regions and oscillate at different frequencies. However, multi-frequency band analysis of the brain network in WM in the cortical space remains largely unexplored. In this study, we employed a graph theoretical framework to characterize the topological properties of the brain functional network in the theta and alpha frequency bands during WM tasks. Twenty-eight subjects performed visual n-back tasks at two difficulty levels, i.e., 0-back (control task) and 2-back (WM task). After preprocessing, Electroencephalogram (EEG) signals were projected into the source space and 80 cortical brain regions were selected for further analysis. Subsequently, the theta- and alpha-band networks were constructed by calculating the Pearson correlation coefficients between the power series (obtained by concatenating the power values of all epochs in each session) of all pairs of brain regions. Graph theoretical approaches were then employed to estimate the topological properties of the brain networks at different WM tasks. We found higher functional integration in the theta band and lower functional segregation in the alpha band in the WM task compared with the control task. Moreover, compared to the 0-back task, altered regional centrality was revealed in the 2-back task in various brain regions that mainly resided in the frontal, temporal and occipital lobes, with distinct presentations in the theta and alpha bands. In addition, significant negative correlations were found between the reaction time with the average path length of the theta-band network and the local clustering of the alpha-band network, which demonstrates the potential for using the brain network metrics as biomarkers for predicting the task performance during WM tasks. PMID:28553215

EEG Cortical Connectivity Analysis of Working Memory Reveals Topological Reorganization in Theta and Alpha Bands.

PubMed

Dai, Zhongxiang; de Souza, Joshua; Lim, Julian; Ho, Paul M; Chen, Yu; Li, Junhua; Thakor, Nitish; Bezerianos, Anastasios; Sun, Yu

2017-01-01

Numerous studies have revealed various working memory (WM)-related brain activities that originate from various cortical regions and oscillate at different frequencies. However, multi-frequency band analysis of the brain network in WM in the cortical space remains largely unexplored. In this study, we employed a graph theoretical framework to characterize the topological properties of the brain functional network in the theta and alpha frequency bands during WM tasks. Twenty-eight subjects performed visual n -back tasks at two difficulty levels, i.e., 0-back (control task) and 2-back (WM task). After preprocessing, Electroencephalogram (EEG) signals were projected into the source space and 80 cortical brain regions were selected for further analysis. Subsequently, the theta- and alpha-band networks were constructed by calculating the Pearson correlation coefficients between the power series (obtained by concatenating the power values of all epochs in each session) of all pairs of brain regions. Graph theoretical approaches were then employed to estimate the topological properties of the brain networks at different WM tasks. We found higher functional integration in the theta band and lower functional segregation in the alpha band in the WM task compared with the control task. Moreover, compared to the 0-back task, altered regional centrality was revealed in the 2-back task in various brain regions that mainly resided in the frontal, temporal and occipital lobes, with distinct presentations in the theta and alpha bands. In addition, significant negative correlations were found between the reaction time with the average path length of the theta-band network and the local clustering of the alpha-band network, which demonstrates the potential for using the brain network metrics as biomarkers for predicting the task performance during WM tasks.

Spatial Working Memory Impairment in Patients with Non-neuropsychiatric Systemic Lupus Erythematosus: A Blood-oxygen-level Dependent Functional Magnetic Resonance Imaging Study.

PubMed

Zhu, Chun-Min; Ma, Ye; Xie, Lei; Huang, Jin-Zhuang; Sun, Zong-Bo; Duan, Shou-Xing; Lin, Zhi-Rong; Yin, Jing-Jing; Le, Hong-Bo; Sun, Dan-Miao; Xu, Wen-Can; Ma, Shu-Hua

2017-02-01

Using ethology and functional magnetic resonance imaging (fMRI) to explore mild cognitive dysfunction and spatial working memory (WM) impairment in patients with systemic lupus erythematosus (SLE) without overt neuropsychiatric symptoms (non-NPSLE) and to study whether any clinical biomarkers could serve as predictors of brain dysfunction in this disease. Eighteen non-NPSLE patients and 18 matched subjects were all tested using the Montreal cognitive assessment scale test and scanned using blood-oxygen-level dependent fMRI while performing the n-back task to investigate the activation intensity of some cognition-related areas. Ethology results showed that non-NPSLE patients had mild cognitive dysfunction and memory dysfunction (p < 0.05). The fMRI scan confirmed a neural network consisting of bilateral dorsolateral prefrontal cortex (DLPFC), premotor area, parietal lobe, and supplementary motor area (SMA)/anterior cingulate cortex (ACC) that was activated during the n-back task, with right hemisphere dominance. However, only the right SMA/ACC showed a load effect in the non-NPSLE group; the activation intensity of most WM-related brain areas for the non-NPSLE group was lower than for the control group under 3 memory loads. Further, we found that the activation intensity of some cognition-related areas, including the bilateral caudate nucleus/insula and hippocampus/parahippocampal gyrus were lower than the control group under the memory loads. An inverse correlation existed between individual activation intensity and disease duration. Non-NPSLE-related brain damage with right DLPFC-posterior parietal lobe and parahippocampal gyrus default network causes impairment of spatial WM and mild cognitive dysfunction. Patients with longer disease duration would be expected to exhibit increased central nervous system damage.

Episodic Memory Retrieval Benefits from a Less Modular Brain Network Organization

PubMed Central

2017-01-01

Most complex cognitive tasks require the coordinated interplay of multiple brain networks, but the act of retrieving an episodic memory may place especially heavy demands for communication between the frontoparietal control network (FPCN) and the default mode network (DMN), two networks that do not strongly interact with one another in many task contexts. We applied graph theoretical analysis to task-related fMRI functional connectivity data from 20 human participants and found that global brain modularity—a measure of network segregation—is markedly reduced during episodic memory retrieval relative to closely matched analogical reasoning and visuospatial perception tasks. Individual differences in modularity were correlated with memory task performance, such that lower modularity levels were associated with a lower false alarm rate. Moreover, the FPCN and DMN showed significantly elevated coupling with each other during the memory task, which correlated with the global reduction in brain modularity. Both networks also strengthened their functional connectivity with the hippocampus during the memory task. Together, these results provide a novel demonstration that reduced modularity is conducive to effective episodic retrieval, which requires close collaboration between goal-directed control processes supported by the FPCN and internally oriented self-referential processing supported by the DMN. SIGNIFICANCE STATEMENT Modularity, an index of the degree to which nodes of a complex system are organized into discrete communities, has emerged as an important construct in the characterization of brain connectivity dynamics. We provide novel evidence that the modularity of the human brain is reduced when individuals engage in episodic memory retrieval, relative to other cognitive tasks, and that this state of lower modularity is associated with improved memory performance. We propose a neural systems mechanism for this finding where the nodes of the frontoparietal control network and default mode network strengthen their interaction with one another during episodic retrieval. Such across-network communication likely facilitates effective access to internally generated representations of past event knowledge. PMID:28242796

Episodic Memory Retrieval Benefits from a Less Modular Brain Network Organization.

PubMed

Westphal, Andrew J; Wang, Siliang; Rissman, Jesse

2017-03-29

Most complex cognitive tasks require the coordinated interplay of multiple brain networks, but the act of retrieving an episodic memory may place especially heavy demands for communication between the frontoparietal control network (FPCN) and the default mode network (DMN), two networks that do not strongly interact with one another in many task contexts. We applied graph theoretical analysis to task-related fMRI functional connectivity data from 20 human participants and found that global brain modularity-a measure of network segregation-is markedly reduced during episodic memory retrieval relative to closely matched analogical reasoning and visuospatial perception tasks. Individual differences in modularity were correlated with memory task performance, such that lower modularity levels were associated with a lower false alarm rate. Moreover, the FPCN and DMN showed significantly elevated coupling with each other during the memory task, which correlated with the global reduction in brain modularity. Both networks also strengthened their functional connectivity with the hippocampus during the memory task. Together, these results provide a novel demonstration that reduced modularity is conducive to effective episodic retrieval, which requires close collaboration between goal-directed control processes supported by the FPCN and internally oriented self-referential processing supported by the DMN. SIGNIFICANCE STATEMENT Modularity, an index of the degree to which nodes of a complex system are organized into discrete communities, has emerged as an important construct in the characterization of brain connectivity dynamics. We provide novel evidence that the modularity of the human brain is reduced when individuals engage in episodic memory retrieval, relative to other cognitive tasks, and that this state of lower modularity is associated with improved memory performance. We propose a neural systems mechanism for this finding where the nodes of the frontoparietal control network and default mode network strengthen their interaction with one another during episodic retrieval. Such across-network communication likely facilitates effective access to internally generated representations of past event knowledge. Copyright © 2017 the authors 0270-6474/17/373523-09$15.00/0.

Functional Connectivity of Multiple Brain Regions Required for the Consolidation of Social Recognition Memory.

PubMed

Tanimizu, Toshiyuki; Kenney, Justin W; Okano, Emiko; Kadoma, Kazune; Frankland, Paul W; Kida, Satoshi

2017-04-12

Social recognition memory is an essential and basic component of social behavior that is used to discriminate familiar and novel animals/humans. Previous studies have shown the importance of several brain regions for social recognition memories; however, the mechanisms underlying the consolidation of social recognition memory at the molecular and anatomic levels remain unknown. Here, we show a brain network necessary for the generation of social recognition memory in mice. A mouse genetic study showed that cAMP-responsive element-binding protein (CREB)-mediated transcription is required for the formation of social recognition memory. Importantly, significant inductions of the CREB target immediate-early genes c-fos and Arc were observed in the hippocampus (CA1 and CA3 regions), medial prefrontal cortex (mPFC), anterior cingulate cortex (ACC), and amygdala (basolateral region) when social recognition memory was generated. Pharmacological experiments using a microinfusion of the protein synthesis inhibitor anisomycin showed that protein synthesis in these brain regions is required for the consolidation of social recognition memory. These findings suggested that social recognition memory is consolidated through the activation of CREB-mediated gene expression in the hippocampus/mPFC/ACC/amygdala. Network analyses suggested that these four brain regions show functional connectivity with other brain regions and, more importantly, that the hippocampus functions as a hub to integrate brain networks and generate social recognition memory, whereas the ACC and amygdala are important for coordinating brain activity when social interaction is initiated by connecting with other brain regions. We have found that a brain network composed of the hippocampus/mPFC/ACC/amygdala is required for the consolidation of social recognition memory. SIGNIFICANCE STATEMENT Here, we identify brain networks composed of multiple brain regions for the consolidation of social recognition memory. We found that social recognition memory is consolidated through CREB-meditated gene expression in the hippocampus, medial prefrontal cortex, anterior cingulate cortex (ACC), and amygdala. Importantly, network analyses based on c-fos expression suggest that functional connectivity of these four brain regions with other brain regions is increased with time spent in social investigation toward the generation of brain networks to consolidate social recognition memory. Furthermore, our findings suggest that hippocampus functions as a hub to integrate brain networks and generate social recognition memory, whereas ACC and amygdala are important for coordinating brain activity when social interaction is initiated by connecting with other brain regions. Copyright © 2017 the authors 0270-6474/17/374103-14$15.00/0.

Neuroanatomy of episodic and semantic memory in humans: a brief review of neuroimaging studies.

PubMed

García-Lázaro, Haydée G; Ramirez-Carmona, Rocio; Lara-Romero, Ruben; Roldan-Valadez, Ernesto

2012-01-01

One of the most basic functions in every individual and species is memory. Memory is the process by which information is saved as knowledge and retained for further use as needed. Learning is a neurobiological phenomenon by which we acquire certain information from the outside world and is a precursor to memory. Memory consists of the capacity to encode, store, consolidate, and retrieve information. Recently, memory has been defined as a network of connections whose function is primarily to facilitate the long-lasting persistence of learned environmental cues. In this review, we present a brief description of the current classifications of memory networks with a focus on episodic memory and its anatomical substrate. We also present a brief review of the anatomical basis of memory systems and the most commonly used neuroimaging methods to assess memory, illustrated with magnetic resonance imaging images depicting the hippocampus, temporal lobe, and hippocampal formation, which are the main brain structures participating in memory networks.

Chemical cross-linking of polypropylenes towards new shape memory polymers.

PubMed

Raidt, Thomas; Hoeher, Robin; Katzenberg, Frank; Tiller, Joerg C

2015-04-01

In this work, syndiotactic polypropylene (sPP) as well as isotactic polypropylene (iPP) are cross-linked to gain a shape memory effect. Both prepared PP networks exhibit maximum strains of 700%, stored strains of up to 680%, and recoveries of nearly 100%. While x-iPP is stable for many cycles, x-sPP ruptures after the first shape-memory cycle. It is shown by wide-angle X-ray scattering (WAXS) experiments that cross-linked iPP exhibits homoepitaxy in the temporary, stretched shape but in contrast to previous reports it contains a higher amount of daughter than mother crystals. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Real time unsupervised learning of visual stimuli in neuromorphic VLSI systems

NASA Astrophysics Data System (ADS)

Giulioni, Massimiliano; Corradi, Federico; Dante, Vittorio; Del Giudice, Paolo

2015-10-01

Neuromorphic chips embody computational principles operating in the nervous system, into microelectronic devices. In this domain it is important to identify computational primitives that theory and experiments suggest as generic and reusable cognitive elements. One such element is provided by attractor dynamics in recurrent networks. Point attractors are equilibrium states of the dynamics (up to fluctuations), determined by the synaptic structure of the network; a ‘basin’ of attraction comprises all initial states leading to a given attractor upon relaxation, hence making attractor dynamics suitable to implement robust associative memory. The initial network state is dictated by the stimulus, and relaxation to the attractor state implements the retrieval of the corresponding memorized prototypical pattern. In a previous work we demonstrated that a neuromorphic recurrent network of spiking neurons and suitably chosen, fixed synapses supports attractor dynamics. Here we focus on learning: activating on-chip synaptic plasticity and using a theory-driven strategy for choosing network parameters, we show that autonomous learning, following repeated presentation of simple visual stimuli, shapes a synaptic connectivity supporting stimulus-selective attractors. Associative memory develops on chip as the result of the coupled stimulus-driven neural activity and ensuing synaptic dynamics, with no artificial separation between learning and retrieval phases.

Real time unsupervised learning of visual stimuli in neuromorphic VLSI systems.

PubMed

Giulioni, Massimiliano; Corradi, Federico; Dante, Vittorio; del Giudice, Paolo

2015-10-14

Neuromorphic chips embody computational principles operating in the nervous system, into microelectronic devices. In this domain it is important to identify computational primitives that theory and experiments suggest as generic and reusable cognitive elements. One such element is provided by attractor dynamics in recurrent networks. Point attractors are equilibrium states of the dynamics (up to fluctuations), determined by the synaptic structure of the network; a 'basin' of attraction comprises all initial states leading to a given attractor upon relaxation, hence making attractor dynamics suitable to implement robust associative memory. The initial network state is dictated by the stimulus, and relaxation to the attractor state implements the retrieval of the corresponding memorized prototypical pattern. In a previous work we demonstrated that a neuromorphic recurrent network of spiking neurons and suitably chosen, fixed synapses supports attractor dynamics. Here we focus on learning: activating on-chip synaptic plasticity and using a theory-driven strategy for choosing network parameters, we show that autonomous learning, following repeated presentation of simple visual stimuli, shapes a synaptic connectivity supporting stimulus-selective attractors. Associative memory develops on chip as the result of the coupled stimulus-driven neural activity and ensuing synaptic dynamics, with no artificial separation between learning and retrieval phases.

Multi-Temporal Land Cover Classification with Long Short-Term Memory Neural Networks

NASA Astrophysics Data System (ADS)

Rußwurm, M.; Körner, M.

2017-05-01

Land cover classification (LCC) is a central and wide field of research in earth observation and has already put forth a variety of classification techniques. Many approaches are based on classification techniques considering observation at certain points in time. However, some land cover classes, such as crops, change their spectral characteristics due to environmental influences and can thus not be monitored effectively with classical mono-temporal approaches. Nevertheless, these temporal observations should be utilized to benefit the classification process. After extensive research has been conducted on modeling temporal dynamics by spectro-temporal profiles using vegetation indices, we propose a deep learning approach to utilize these temporal characteristics for classification tasks. In this work, we show how long short-term memory (LSTM) neural networks can be employed for crop identification purposes with SENTINEL 2A observations from large study areas and label information provided by local authorities. We compare these temporal neural network models, i.e., LSTM and recurrent neural network (RNN), with a classical non-temporal convolutional neural network (CNN) model and an additional support vector machine (SVM) baseline. With our rather straightforward LSTM variant, we exceeded state-of-the-art classification performance, thus opening promising potential for further research.

Training Attentional Control and Working Memory--Is Younger, Better?

ERIC Educational Resources Information Center

Wass, S. V.; Scerif, G.; Johnson, M. H.

2012-01-01

Authors have argued that various forms of interventions may be more effective in younger children. Is cognitive training also more effective, the earlier the training is applied? We review evidence suggesting that functional neural networks, including those subserving attentional control, may be more unspecialised and undifferentiated earlier in…

A systematic review of the neurobiological aspects of memory in the aging process

PubMed Central

de Oliveira, Eduardo Moreira; Kissaki, Priscilla Tiemi; Ordonez, Tiago Nascimento; Lima-Silva, Thaís Bento

2011-01-01

A systematic review of the neuroanatomical literature was performed to determine the neuropharmacological aspects most relevant to the study of memory processes. Articles were retrieved using the search terms "biology of memory", "memory and aging", "memory impairment", "elderly and memory," and their equivalents in Portuguese. Of the studies surveyed, five studies dealt with epidemiological and demographic issues, 12 were clinical trials i.e. were based on testing and implementation of instruments in human subjects, 33 studies were basic research involving studies of mice, rats and non-human primates, and biochemical and in vitro trials and finally, 52 studies were literature reviews or book chapters which in our view, fell into this category. Conclusions The work sought to highlight which neural networks are most involved in processing information, as well as their location within brain regions and the way in which neurotransmitters interact with each other for the formation of these memories. Moreover, it was shown how memory changes during the normal human aging process, both positively and negatively, by analyzing the morphological alterations that occur in the brain of aging individuals. PMID:29213758

Still searching for the engram.

PubMed

Eichenbaum, Howard

2016-09-01

For nearly a century, neurobiologists have searched for the engram-the neural representation of a memory. Early studies showed that the engram is widely distributed both within and across brain areas and is supported by interactions among large networks of neurons. Subsequent research has identified engrams that support memory within dedicated functional systems for habit learning and emotional memory, but the engram for declarative memories has been elusive. Nevertheless, recent years have brought progress from molecular biological approaches that identify neurons and networks that are necessary and sufficient to support memory, and from recording approaches and population analyses that characterize the information coded by large neural networks. These new directions offer the promise of revealing the engrams for episodic and semantic memories.

Self-government of complex reading and writing brains informed by cingulo-opercular network for adaptive control and working memory components for language learning.

PubMed

Richards, Todd L; Abbott, Robert D; Yagle, Kevin; Peterson, Dan; Raskind, Wendy; Berninger, Virginia W

2017-01-01

To understand mental self-government of the developing reading and writing brain, correlations of clustering coefficients on fMRI reading or writing tasks with BASC 2 Adaptivity ratings (time 1 only) or working memory components (time 1 before and time 2 after instruction previously shown to improve achievement and change magnitude of fMRI connectivity) were investigated in 39 students in grades 4 to 9 who varied along a continuum of reading and writing skills. A Philips 3T scanner measured connectivity during six leveled fMRI reading tasks (subword-letters and sounds, word-word-specific spellings or affixed words, syntax comprehension-with and without homonym foils or with and without affix foils, and text comprehension) and three fMRI writing tasks-writing next letter in alphabet, adding missing letter in word spelling, and planning for composing. The Brain Connectivity Toolbox generated clustering coefficients based on the cingulo-opercular (CO) network; after controlling for multiple comparisons and movement, significant fMRI connectivity clustering coefficients for CO were identified in 8 brain regions bilaterally (cingulate gyrus, superior frontal gyrus, middle frontal gyrus, inferior frontal gyrus, superior temporal gyrus, insula, cingulum-cingulate gyrus, and cingulum-hippocampus). BASC2 Parent Ratings for Adaptivity were correlated with CO clustering coefficients on three reading tasks (letter-sound, word affix judgments and sentence comprehension) and one writing task (writing next letter in alphabet). Before instruction, each behavioral working memory measure (phonology, orthography, morphology, and syntax coding, phonological and orthographic loops for integrating internal language and output codes, and supervisory focused and switching attention) correlated significantly with at least one CO clustering coefficient. After instruction, the patterning of correlations changed with new correlations emerging. Results show that the reading and writing brain's mental government, supported by both CO Adaptive Control and multiple working memory components, had changed in response to instruction during middle childhood/early adolescence.

Altered Intrinsic Hippocmapus Declarative Memory Network and Its Association with Impulsivity in Abstinent Heroin Dependent Subjects

PubMed Central

Zhai, Tian-Ye; Shao, Yong-Cong; Xie, Chun-Ming; Ye, En-Mao; Zou, Feng; Fu, Li-Ping; Li, Wen-Jun; Chen, Gang; Chen, Guang-Yu; Zhang, Zheng-Guo; Li, Shi-Jiang; Yang, Zheng

2014-01-01

Converging evidence suggests that addiction can be considered a disease of aberrant learning and memory with impulsive decision-making. In the past decades, numerous studies have demonstrated that drug addiction is involved in multiple memory systems such as classical conditioned drug memory, instrumental learning memory and the habitual learning memory. However, most of these studies have focused on the contributions of non-declarative memory, and declarative memory has largely been neglected in the research of addiction. Based on a recent finding that hippocampus, as a core functioning region of declarative memory, was proved biased the decision-making process based on past experiences by spreading associated reward values throughout memory. Our present study focused on the hippocampus. By utilizing seed-based network analysis on the resting-state functional MRI datasets with the seed hippocampus we tested how the intrinsic hippocampal memory network altered towards drug addiction, and examined how the functional connectivity strength within the altered hippocampal network correlated with behavioral index ‘impulsivity’. Our results demonstrated that HD group showed enhanced coherence between hippocampus which represents declarative memory system and non-declarative rewardguided learning memory system, and also showed attenuated intrinsic functional link between hippocampus and top-down control system, compared to the CN group. This alteration was furthered found to have behavioral significance over the behavioral index ‘impulsivity’ measured with Barratt Impulsiveness Scale (BIS). These results provide insights into the mechanism of declarative memory underlying the impulsive behavior in drug addiction. PMID:25008351

Dedifferentiation Does Not Account for Hyperconnectivity after Traumatic Brain Injury.

PubMed

Bernier, Rachel Anne; Roy, Arnab; Venkatesan, Umesh Meyyappan; Grossner, Emily C; Brenner, Einat K; Hillary, Frank Gerard

2017-01-01

Changes in functional network connectivity following traumatic brain injury (TBI) have received increasing attention in recent neuroimaging literature. This study sought to understand how disrupted systems adapt to injury during resting and goal-directed brain states. Hyperconnectivity has been a common finding, and dedifferentiation (or loss of segregation of networks) is one possible explanation for this finding. We hypothesized that individuals with TBI would show dedifferentiation of networks (as noted in other clinical populations) and these effects would be associated with cognitive dysfunction. Graph theory was implemented to examine functional connectivity during periods of task and rest in 19 individuals with moderate/severe TBI and 14 healthy controls (HCs). Using a functional brain atlas derived from 83 functional imaging studies, graph theory was used to examine network dynamics and determine whether dedifferentiation accounts for changes in connectivity. Regions of interest were assigned to one of three groups: task-positive, default mode, or other networks. Relationships between these metrics were then compared with performance on neuropsychological tests. Hyperconnectivity in TBI was most commonly observed as increased within-network connectivity. Network strengths within networks that showed differences between TBI and HCs were correlated with performance on five neuropsychological tests typically sensitive to deficits commonly reported in TBI. Hyperconnectivity within the default mode network (DMN) during task was associated with better performance on Digit Span Backward, a measure of working memory [ R 2 (18) = 0.28, p  = 0.02]. In other words, increased differentiation of networks during task was associated with better working memory. Hyperconnectivity within the task-positive network during rest was not associated with behavior. Negative correlation weights were not associated with behavior. The primary hypothesis that hyperconnectivity occurs through increased segregation of networks, rather than dedifferentiation, was not supported. Instead, enhanced connectivity post injury was observed within network. Results suggest that the relationship between increased connectivity and cognitive functioning may be both state (rest or task) and network dependent. High-cost network hubs were identical for both rest and task, and cost was negatively associated with performance on measures of psychomotor speed and set-shifting.

Electronic device aspects of neural network memories

NASA Technical Reports Server (NTRS)

Lambe, J.; Moopenn, A.; Thakoor, A. P.

1985-01-01

The basic issues related to the electronic implementation of the neural network model (NNM) for content addressable memories are examined. A brief introduction to the principles of the NNM is followed by an analysis of the information storage of the neural network in the form of a binary connection matrix and the recall capability of such matrix memories based on a hardware simulation study. In addition, materials and device architecture issues involved in the future realization of such networks in VLSI-compatible ultrahigh-density memories are considered. A possible space application of such devices would be in the area of large-scale information storage without mechanical devices.

Memory Network For Distributed Data Processors

NASA Technical Reports Server (NTRS)

Bolen, David; Jensen, Dean; Millard, ED; Robinson, Dave; Scanlon, George

1992-01-01

Universal Memory Network (UMN) is modular, digital data-communication system enabling computers with differing bus architectures to share 32-bit-wide data between locations up to 3 km apart with less than one millisecond of latency. Makes it possible to design sophisticated real-time and near-real-time data-processing systems without data-transfer "bottlenecks". This enterprise network permits transmission of volume of data equivalent to an encyclopedia each second. Facilities benefiting from Universal Memory Network include telemetry stations, simulation facilities, power-plants, and large laboratories or any facility sharing very large volumes of data. Main hub of UMN is reflection center including smaller hubs called Shared Memory Interfaces.

Identifying major depressive disorder using Hurst exponent of resting-state brain networks.

PubMed

Wei, Maobin; Qin, Jiaolong; Yan, Rui; Li, Haoran; Yao, Zhijian; Lu, Qing

2013-12-30

Resting-state functional magnetic resonance imaging (fMRI) studies of major depressive disorder (MDD) have revealed abnormalities of functional connectivity within or among the resting-state networks. They provide valuable insight into the pathological mechanisms of depression. However, few reports were involved in the "long-term memory" of fMRI signals. This study was to investigate the "long-term memory" of resting-state networks by calculating their Hurst exponents for identifying depressed patients from healthy controls. Resting-state networks were extracted from fMRI data of 20 MDD and 20 matched healthy control subjects. The Hurst exponent of each network was estimated by Range Scale analysis for further discriminant analysis. 95% of depressed patients and 85% of healthy controls were correctly classified by Support Vector Machine with an accuracy of 90%. The right fronto-parietal and default mode network constructed a deficit network (lower memory and more irregularity in MDD), while the left fronto-parietal, ventromedial prefrontal and salience network belonged to an excess network (longer memory in MDD), suggesting these dysfunctional networks may be related to a portion of the complex of emotional and cognitive disturbances. The abnormal "long-term memory" of resting-state networks associated with depression may provide a new possibility towards the exploration of the pathophysiological mechanisms of MDD. © 2013 Elsevier Ireland Ltd. All rights reserved.

A case of hyperthymesia: Rethinking the role of the amygdala in autobiographical memory

PubMed Central

Ally, Brandon A.; Hussey, Erin P.; Donahue, Manus J.

2012-01-01

Much controversy has been focused on the extent to which the amygdala belongs to the autobiographical memory core network. Early evidence suggested the amygdala played a vital role in emotional processing, likely helping to encode emotionally charged stimuli. However, recent work has highlighted the amygdala’s role in social and self-referential processing, leading to speculation that the amygdala likely supports the encoding and retrieval of autobiographical memory. Here, cognitive as well as structural and functional magnetic resonance imaging data was collected from an extremely rare individual with near-perfect autobiographical memory, or hyperthymesia. Right amygdala hypertrophy (approximately 20%) and enhanced amygdala-to-hippocampus connectivity (> 10 standard deviations) was observed in this volunteer relative to controls. Based on these findings and previous literature, we speculate that the amygdala likely charges autobiographical memories with emotional, social, and self-relevance. In heightened memory, this system may be hyperactive, allowing for many types of autobiographical information, including emotionally benign, to be more efficiently processed as self-relevant for encoding and storage. PMID:22519463

Altered Effective Connectivity of Hippocampus-Dependent Episodic Memory Network in mTBI Survivors

PubMed Central

2016-01-01

Traumatic brain injuries (TBIs) are generally recognized to affect episodic memory. However, less is known regarding how external force altered the way functionally connected brain structures of the episodic memory system interact. To address this issue, we adopted an effective connectivity based analysis, namely, multivariate Granger causality approach, to explore causal interactions within the brain network of interest. Results presented that TBI induced increased bilateral and decreased ipsilateral effective connectivity in the episodic memory network in comparison with that of normal controls. Moreover, the left anterior superior temporal gyrus (aSTG, the concept forming hub), left hippocampus (the personal experience binding hub), and left parahippocampal gyrus (the contextual association hub) were no longer network hubs in TBI survivors, who compensated for hippocampal deficits by relying more on the right hippocampus (underlying perceptual memory) and the right medial frontal gyrus (MeFG) in the anterior prefrontal cortex (PFC). We postulated that the overrecruitment of the right anterior PFC caused dysfunction of the strategic component of episodic memory, which caused deteriorating episodic memory in mTBI survivors. Our findings also suggested that the pattern of brain network changes in TBI survivors presented similar functional consequences to normal aging. PMID:28074162

Encoding mechano-memories in filamentous-actin networks

NASA Astrophysics Data System (ADS)

Majumdar, Sayantan; Foucard, Louis; Levine, Alex; Gardel, Margaret L.

History-dependent adaptation is a central feature of learning and memory. Incorporating such features into `adaptable materials' that can modify their mechanical properties in response to external cues, remains an outstanding challenge in materials science. Here, we study a novel mechanism of mechano-memory in cross-linked F-actin networks, the essential determinants of the mechanical behavior of eukaryotic cells. We find that the non-linear mechanical response of such networks can be reversibly programmed through induction of mechano-memories. In particular, the direction, magnitude, and duration of previously applied shear stresses can be encoded into the network architecture. The `memory' of the forcing history is long-lived, but it can be erased by force applied in the opposite direction. These results demonstrate that F-actin networks can encode analog read-write mechano-memories which can be used for adaptation to mechanical stimuli. We further show that the mechano-memory arises from changes in the nematic order of the constituent filaments. Our results suggest a new mechanism of mechanical sensing in eukaryotic cells and provide a strategy for designing a novel class of materials. S.M. acknowledges U. Chicago MRSEC for support through a Kadanoff-Rice fellowship.

Strengthened effective connectivity underlies transfer of working memory training to tests of short-term memory and attention.

PubMed

Kundu, Bornali; Sutterer, David W; Emrich, Stephen M; Postle, Bradley R

2013-05-15

Although long considered a natively endowed and fixed trait, working memory (WM) ability has recently been shown to improve with intensive training. What remains controversial and poorly understood, however, are the neural bases of these training effects and the extent to which WM training gains transfer to other cognitive tasks. Here we present evidence from human electrophysiology (EEG) and simultaneous transcranial magnetic stimulation and EEG that the transfer of WM training to other cognitive tasks is supported by changes in task-related effective connectivity in frontoparietal and parieto-occipital networks that are engaged by both the trained and transfer tasks. One consequence of this effect is greater efficiency of stimulus processing, as evidenced by changes in EEG indices of individual differences in short-term memory capacity and in visual search performance. Transfer to search-related activity provides evidence that something more fundamental than task-specific strategy or stimulus-specific representations has been learned. Furthermore, these patterns of training and transfer highlight the role of common neural systems in determining individual differences in aspects of visuospatial cognition.

Strengthened effective connectivity underlies transfer of working memory training to tests of short-term memory and attention

PubMed Central

Kundu, Bornali; Sutterer, David W.; Emrich, Stephen M.; Postle, Bradley R.

2013-01-01

Although long considered a natively endowed and fixed trait, working memory (WM) ability has recently been shown to improve with intensive training. What remains controversial and poorly understood, however, are the neural bases of these training effects, and the extent to which WM training gains transfer to other cognitive tasks. Here we present evidence from human electrophysiology (EEG) and simultaneous transcranial magnetic stimulation (TMS) and EEG that the transfer of WM training to other cognitive tasks is supported by changes in task-related effective connectivity in frontoparietal and parietooccipital networks that are engaged by both the trained and transfer tasks. One consequence of this effect is greater efficiency of stimulus processing, as evidenced by changes in EEG indices of individual differences in short-term memory capacity and in visual search performance. Transfer to search-related activity provides evidence that something more fundamental than task-specific strategy or stimulus-specific representations have been learned. Furthermore, these patterns of training and transfer highlight the role of common neural systems in determining individual differences in aspects of visuospatial cognition. PMID:23678114

PIYAS-proceeding to intelligent service oriented memory allocation for flash based data centric sensor devices in wireless sensor networks.

PubMed

Rizvi, Sanam Shahla; Chung, Tae-Sun

2010-01-01

Flash memory has become a more widespread storage medium for modern wireless devices because of its effective characteristics like non-volatility, small size, light weight, fast access speed, shock resistance, high reliability and low power consumption. Sensor nodes are highly resource constrained in terms of limited processing speed, runtime memory, persistent storage, communication bandwidth and finite energy. Therefore, for wireless sensor networks supporting sense, store, merge and send schemes, an efficient and reliable file system is highly required with consideration of sensor node constraints. In this paper, we propose a novel log structured external NAND flash memory based file system, called Proceeding to Intelligent service oriented memorY Allocation for flash based data centric Sensor devices in wireless sensor networks (PIYAS). This is the extended version of our previously proposed PIYA [1]. The main goals of the PIYAS scheme are to achieve instant mounting and reduced SRAM space by keeping memory mapping information to a very low size of and to provide high query response throughput by allocation of memory to the sensor data by network business rules. The scheme intelligently samples and stores the raw data and provides high in-network data availability by keeping the aggregate data for a longer period of time than any other scheme has done before. We propose effective garbage collection and wear-leveling schemes as well. The experimental results show that PIYAS is an optimized memory management scheme allowing high performance for wireless sensor networks.

Noise Tolerance of Attractor and Feedforward Memory Models

PubMed Central

Lim, Sukbin; Goldman, Mark S.

2017-01-01

In short-term memory networks, transient stimuli are represented by patterns of neural activity that persist long after stimulus offset. Here, we compare the performance of two prominent classes of memory networks, feedback-based attractor networks and feedforward networks, in conveying information about the amplitude of a briefly presented stimulus in the presence of gaussian noise. Using Fisher information as a metric of memory performance, we find that the optimal form of network architecture depends strongly on assumptions about the forms of nonlinearities in the network. For purely linear networks, we find that feedforward networks outperform attractor networks because noise is continually removed from feedforward networks when signals exit the network; as a result, feedforward networks can amplify signals they receive faster than noise accumulates over time. By contrast, attractor networks must operate in a signal-attenuating regime to avoid the buildup of noise. However, if the amplification of signals is limited by a finite dynamic range of neuronal responses or if noise is reset at the time of signal arrival, as suggested by recent experiments, we find that attractor networks can out-perform feedforward ones. Under a simple model in which neurons have a finite dynamic range, we find that the optimal attractor networks are forgetful if there is no mechanism for noise reduction with signal arrival but nonforgetful (perfect integrators) in the presence of a strong reset mechanism. Furthermore, we find that the maximal Fisher information for the feedforward and attractor networks exhibits power law decay as a function of time and scales linearly with the number of neurons. These results highlight prominent factors that lead to trade-offs in the memory performance of networks with different architectures and constraints, and suggest conditions under which attractor or feedforward networks may be best suited to storing information about previous stimuli. PMID:22091664

Learnable Models for Information Diffusion and its Associated User Behavior in Micro-blogosphere

DTIC Science & Technology

2012-08-30

According to the work of Even-Dar and Shapira (2007), we recall the definition of the ba- sic voter model on network G. In the model, each node of G...reason as follows. We started with the K distinct initial nodes and all the other nodes were neutral in the beginning. Recall that we set the average time... memory , running under Linux. Learning to predict opinion share and detect anti-majority opinionists in social networks 29 7 Conclusion Unlike the popular

Semantic and episodic memory of music are subserved by distinct neural networks.

PubMed

Platel, Hervé; Baron, Jean-Claude; Desgranges, Béatrice; Bernard, Frédéric; Eustache, Francis

2003-09-01

Numerous functional imaging studies have shown that retrieval from semantic and episodic memory is subserved by distinct neural networks. However, these results were essentially obtained with verbal and visuospatial material. The aim of this work was to determine the neural substrates underlying the semantic and episodic components of music using familiar and nonfamiliar melodic tunes. To study musical semantic memory, we designed a task in which the instruction was to judge whether or not the musical extract was felt as "familiar." To study musical episodic memory, we constructed two delayed recognition tasks, one containing only familiar and the other only nonfamiliar items. For each recognition task, half of the extracts (targets) were presented in the prior semantic task. The episodic and semantic tasks were to be contrasted by a comparison to two perceptive control tasks and to one another. Cerebral blood flow was assessed by means of the oxygen-15-labeled water injection method, using high-resolution PET. Distinct patterns of activations were found. First, regarding the episodic memory condition, bilateral activations of the middle and superior frontal gyri and precuneus (more prominent on the right side) were observed. Second, the semantic memory condition disclosed extensive activations in the medial and orbital frontal cortex bilaterally, the left angular gyrus, and predominantly the left anterior part of the middle temporal gyri. The findings from this study are discussed in light of the available neuropsychological data obtained in brain-damaged subjects and functional neuroimaging studies.

Flexible Kernel Memory

PubMed Central

Nowicki, Dimitri; Siegelmann, Hava

2010-01-01

This paper introduces a new model of associative memory, capable of both binary and continuous-valued inputs. Based on kernel theory, the memory model is on one hand a generalization of Radial Basis Function networks and, on the other, is in feature space, analogous to a Hopfield network. Attractors can be added, deleted, and updated on-line simply, without harming existing memories, and the number of attractors is independent of input dimension. Input vectors do not have to adhere to a fixed or bounded dimensionality; they can increase and decrease it without relearning previous memories. A memory consolidation process enables the network to generalize concepts and form clusters of input data, which outperforms many unsupervised clustering techniques; this process is demonstrated on handwritten digits from MNIST. Another process, reminiscent of memory reconsolidation is introduced, in which existing memories are refreshed and tuned with new inputs; this process is demonstrated on series of morphed faces. PMID:20552013

Mnemonic convergence in social networks: The emergent properties of cognition at a collective level

PubMed Central

Coman, Alin; Momennejad, Ida; Drach, Rae D.; Geana, Andra

2016-01-01

The development of shared memories, beliefs, and norms is a fundamental characteristic of human communities. These emergent outcomes are thought to occur owing to a dynamic system of information sharing and memory updating, which fundamentally depends on communication. Here we report results on the formation of collective memories in laboratory-created communities. We manipulated conversational network structure in a series of real-time, computer-mediated interactions in fourteen 10-member communities. The results show that mnemonic convergence, measured as the degree of overlap among community members’ memories, is influenced by both individual-level information-processing phenomena and by the conversational social network structure created during conversational recall. By studying laboratory-created social networks, we show how large-scale social phenomena (i.e., collective memory) can emerge out of microlevel local dynamics (i.e., mnemonic reinforcement and suppression effects). The social-interactionist approach proposed herein points to optimal strategies for spreading information in social networks and provides a framework for measuring and forging collective memories in communities of individuals. PMID:27357678

Nanophotonic rare-earth quantum memory with optically controlled retrieval

NASA Astrophysics Data System (ADS)

Zhong, Tian; Kindem, Jonathan M.; Bartholomew, John G.; Rochman, Jake; Craiciu, Ioana; Miyazono, Evan; Bettinelli, Marco; Cavalli, Enrico; Verma, Varun; Nam, Sae Woo; Marsili, Francesco; Shaw, Matthew D.; Beyer, Andrew D.; Faraon, Andrei

2017-09-01

Optical quantum memories are essential elements in quantum networks for long-distance distribution of quantum entanglement. Scalable development of quantum network nodes requires on-chip qubit storage functionality with control of the readout time. We demonstrate a high-fidelity nanophotonic quantum memory based on a mesoscopic neodymium ensemble coupled to a photonic crystal cavity. The nanocavity enables >95% spin polarization for efficient initialization of the atomic frequency comb memory and time bin-selective readout through an enhanced optical Stark shift of the comb frequencies. Our solid-state memory is integrable with other chip-scale photon source and detector devices for multiplexed quantum and classical information processing at the network nodes.

Cortex and Memory: Emergence of a New Paradigm

ERIC Educational Resources Information Center

Fuster, Joaquin M.

2009-01-01

Converging evidence from humans and nonhuman primates is obliging us to abandon conventional models in favor of a radically different, distributed-network paradigm of cortical memory. Central to the new paradigm is the concept of memory network or cognit--that is, a memory or an item of knowledge defined by a pattern of connections between neuron…

Still searching for the engram

PubMed Central

Eichenbaum, Howard

2016-01-01

For nearly a century neurobiologists have searched for the engram - the neural representation of a memory. Early studies showed that the engram is widely distributed both within and across brain areas and is supported by interactions among large networks of neurons. Subsequent research has identified engrams that support memory within dedicated functional systems for habit learning and emotional memory, but the engram for declarative memories has been elusive. Nevertheless, recent years have brought progress from molecular biological approaches that identify neurons and networks that are necessary and sufficient to support memory, and from recording approaches and population analyses that characterize the information coded by large neural networks. These new directions offer the promise of revealing the engrams for episodic and semantic memories. PMID:26944423

Physiological, Molecular and Genetic Mechanisms of Long-Term Habituation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Calin-Jageman, Robert J

Work funded on this grant has explored the mechanisms of long-term habituation, a ubiquitous form of learning that plays a key role in basic cognitive functioning. Specifically, behavioral, physiological, and molecular mechanisms of habituation have been explored using a simple model system, the tail-elicited siphon-withdrawal reflex (T-SWR) in the marine mollusk Aplysia californica. Substantial progress has been made on the first and third aims, providing some fundamental insights into the mechanisms by which memories are stored. We have characterized the physiological correlates of short- and long-term habituation. We found that short-term habituation is accompanied by a robust sensory adaptation, whereasmore » long-term habituation is accompanied by alterations in sensory and interneuron synaptic efficacy. Thus, our data indicates memories can be shifted between different sites in a neural network as they are consolidated from short to long term. At the molecular level, we have accomplished microarray analysis comparing gene expression in both habituated and control ganglia. We have identified a network of putatively regulated transcripts that seems particularly targeted towards synaptic changes (e.g. SNAP25, calmodulin) . We are now beginning additional work to confirm regulation of these transcripts and build a more detailed understanding of the cascade of molecular events leading to the permanent storage of long-term memories. On the third aim, we have fostered a nascent neuroscience program via a variety of successful initiatives. We have funded over 11 undergraduate neuroscience scholars, several of whom have been recognized at national and regional levels for their research. We have also conducted a pioneering summer research program for community college students which is helping enhance access of underrepresented groups to life science careers. Despite minimal progress on the second aim, this project has provided a) novel insight into the network mechanisms by which short-term memories are permanently stored, and b) a strong foundation for continued growth of an excellent undergraduate neuroscience program.« less

The mammillary bodies and memory: more than a hippocampal relay

PubMed Central

Vann, Seralynne D.; Nelson, Andrew J.D.

2015-01-01

Although the mammillary bodies were one of the first neural structures to be implicated in memory, it has long been assumed that their main function was to act primarily as a hippocampal relay, passing information on to the anterior thalamic nuclei and from there to the cingulate cortex. This view not only afforded the mammillary bodies no independent role in memory, it also neglected the potential significance of other, nonhippocampal, inputs to the mammillary bodies. Recent advances have transformed the picture, revealing that projections from the tegmental nuclei of Gudden, and not the hippocampal formation, are critical for sustaining mammillary body function. By uncovering a role for the mammillary bodies that is independent of its subicular inputs, this work signals the need to consider a wider network of structures that form the neural bases of episodic memory. PMID:26072239

Conducting-insulating transition in adiabatic memristive networks

NASA Astrophysics Data System (ADS)

Sheldon, Forrest C.; Di Ventra, Massimiliano

2017-01-01

The development of neuromorphic systems based on memristive elements—resistors with memory—requires a fundamental understanding of their collective dynamics when organized in networks. Here, we study an experimentally inspired model of two-dimensional disordered memristive networks subject to a slowly ramped voltage and show that they undergo a discontinuous transition in the conductivity for sufficiently high values of memory, as quantified by the memristive ON-OFF ratio. We investigate the consequences of this transition for the memristive current-voltage characteristics both through simulation and theory, and demonstrate the role of current-voltage duality in relating forward and reverse switching processes. Our work sheds considerable light on the statistical properties of memristive networks that are presently studied both for unconventional computing and as models of neural networks.

Competition between frontoparietal control and default networks supports social working memory and empathy

PubMed Central

Xin, Fei

2015-01-01

An extensive body of literature has indicated that there is increased activity in the frontoparietal control network (FPC) and decreased activity in the default mode network (DMN) during working memory (WM) tasks. The FPC and DMN operate in a competitive relationship during tasks requiring externally directed attention. However, the association between this FPC-DMN competition and performance in social WM tasks has rarely been reported in previous studies. To investigate this question, we measured FPC-DMN connectivity during resting state and two emotional face recognition WM tasks using the 2-back paradigm. Thirty-four individuals were instructed to perform the tasks based on either the expression [emotion (EMO)] or the identity (ID) of the same set of face stimuli. Consistent with previous studies, an increased anti-correlation between the FPC and DMN was observed during both tasks relative to the resting state. Specifically, this anti-correlation during the EMO task was stronger than during the ID task, as the former has a higher social load. Intriguingly, individual differences in self-reported empathy were significantly correlated with the FPC-DMN anti-correlation in the EMO task. These results indicate that the top-down signals from the FPC suppress the DMN to support social WM and empathy. PMID:25556209

Different neural activities support auditory working memory in musicians and bilinguals.

PubMed

Alain, Claude; Khatamian, Yasha; He, Yu; Lee, Yunjo; Moreno, Sylvain; Leung, Ada W S; Bialystok, Ellen

2018-05-17

Musical training and bilingualism benefit executive functioning and working memory (WM)-however, the brain networks supporting this advantage are not well specified. Here, we used functional magnetic resonance imaging and the n-back task to assess WM for spatial (sound location) and nonspatial (sound category) auditory information in musician monolingual (musicians), nonmusician bilinguals (bilinguals), and nonmusician monolinguals (controls). Musicians outperformed bilinguals and controls on the nonspatial WM task. Overall, spatial and nonspatial WM were associated with greater activity in dorsal and ventral brain regions, respectively. Increasing WM load yielded similar recruitment of the anterior-posterior attention network in all three groups. In both tasks and both levels of difficulty, musicians showed lower brain activity than controls in superior prefrontal frontal gyrus and dorsolateral prefrontal cortex (DLPFC) bilaterally, a finding that may reflect improved and more efficient use of neural resources. Bilinguals showed enhanced activity in language-related areas (i.e., left DLPFC and left supramarginal gyrus) relative to musicians and controls, which could be associated with the need to suppress interference associated with competing semantic activations from multiple languages. These findings indicate that the auditory WM advantage in musicians and bilinguals is mediated by different neural networks specific to each life experience. © 2018 New York Academy of Sciences.

Poly(Capro-Lactone) Networks as Actively Moving Polymers

NASA Astrophysics Data System (ADS)

Meng, Yuan

Shape-memory polymers (SMPs), as a subset of actively moving polymers, form an exciting class of materials that can store and recover elastic deformation energy upon application of an external stimulus. Although engineering of SMPs nowadays has lead to robust materials that can memorize multiple temporary shapes, and can be triggered by various stimuli such as heat, light, moisture, or applied magnetic fields, further commercialization of SMPs is still constrained by the material's incapability to store large elastic energy, as well as its inherent one-way shape-change nature. This thesis develops a series of model semi-crystalline shape-memory networks that exhibit ultra-high energy storage capacity, with accurately tunable triggering temperature; by introducing a second competing network, or reconfiguring the existing network under strained state, configurational chain bias can be effectively locked-in, and give rise to two-way shape-actuators that, in the absence of an external load, elongates upon cooling and reversibly contracts upon heating. We found that well-defined network architecture plays essential role on strain-induced crystallization and on the performance of cold-drawn shape-memory polymers. Model networks with uniform molecular weight between crosslinks, and specified functionality of each net-point, results in tougher, more elastic materials with a high degree of crystallinity and outstanding shape-memory properties. The thermal behavior of the model networks can be finely modified by introducing non-crystalline small molecule linkers that effectively frustrates the crystallization of the network strands. This resulted in shape-memory networks that are ultra-sensitive to heat, as deformed materials can be efficiently triggered to revert to its permanent state upon only exposure to body temperature. We also coupled the same reaction adopted to create the model network with conventional free-radical polymerization to prepare a dual-cure "double network" that behaves as a real thermal "actuator". This approach places sub-chains under different degrees of configurational bias within the network to utilize the material's propensity to undergo stress-induced crystallization. Reconfiguration of model shape-memory networks containing photo-sensitive linkages can also be employed to program two-way actuator. Chain reshuffling of a partially reconfigurable network is initiated upon exposure to light under specific strains. Interesting photo-induced creep and stress relaxation behaviors were demonstrated and understood based on a novel transient network model we derived. In summary, delicate manipulation of shape-memory network architectures addressed critical issues constraining the application of this type of functional polymer material. Strategies developed in this thesis may provide new opportunity to the field of shape-memory polymers.

A Quantum Network with Atoms and Photons

DTIC Science & Technology

2016-09-01

The long - term goal is to entangle distant atomic memories between ARL and JQI, and explore the possibility of entangling hybrid quantum memories . 2...ARL) environment. The long - term goal is to achieve a quantum repeater network capability for the US Army. Initially, a quantum channel between ARL and...SUBJECT  TERMS Quantum, atoms, photons, entanglement, teleportation, communications, network, memory 16. SECURITY CLASSIFICATION OF: 17. LIMITATION

A Quantum Network with Atoms and Photons

DTIC Science & Technology

2016-09-30

The long - term goal is to entangle distant atomic memories between ARL and JQI, and explore the possibility of entangling hybrid quantum memories . 2...ARL) environment. The long - term goal is to achieve a quantum repeater network capability for the US Army. Initially, a quantum channel between ARL and...SUBJECT  TERMS Quantum, atoms, photons, entanglement, teleportation, communications, network, memory 16. SECURITY CLASSIFICATION OF: 17. LIMITATION

On the Maximum Storage Capacity of the Hopfield Model

PubMed Central

Folli, Viola; Leonetti, Marco; Ruocco, Giancarlo

2017-01-01

Recurrent neural networks (RNN) have traditionally been of great interest for their capacity to store memories. In past years, several works have been devoted to determine the maximum storage capacity of RNN, especially for the case of the Hopfield network, the most popular kind of RNN. Analyzing the thermodynamic limit of the statistical properties of the Hamiltonian corresponding to the Hopfield neural network, it has been shown in the literature that the retrieval errors diverge when the number of stored memory patterns (P) exceeds a fraction (≈ 14%) of the network size N. In this paper, we study the storage performance of a generalized Hopfield model, where the diagonal elements of the connection matrix are allowed to be different from zero. We investigate this model at finite N. We give an analytical expression for the number of retrieval errors and show that, by increasing the number of stored patterns over a certain threshold, the errors start to decrease and reach values below unit for P ≫ N. We demonstrate that the strongest trade-off between efficiency and effectiveness relies on the number of patterns (P) that are stored in the network by appropriately fixing the connection weights. When P≫N and the diagonal elements of the adjacency matrix are not forced to be zero, the optimal storage capacity is obtained with a number of stored memories much larger than previously reported. This theory paves the way to the design of RNN with high storage capacity and able to retrieve the desired pattern without distortions. PMID:28119595

Neural circuit mechanisms of short-term memory

NASA Astrophysics Data System (ADS)

Goldman, Mark

Memory over time scales of seconds to tens of seconds is thought to be maintained by neural activity that is triggered by a memorized stimulus and persists long after the stimulus is turned off. This presents a challenge to current models of memory-storing mechanisms, because the typical time scales associated with cellular and synaptic dynamics are two orders of magnitude smaller than this. While such long time scales can easily be achieved by bistable processes that toggle like a flip-flop between a baseline and elevated-activity state, many neuronal systems have been observed experimentally to be capable of maintaining a continuum of stable states. For example, in neural integrator networks involved in the accumulation of evidence for decision making and in motor control, individual neurons have been recorded whose activity reflects the mathematical integral of their inputs; in the absence of input, these neurons sustain activity at a level proportional to the running total of their inputs. This represents an analog form of memory whose dynamics can be conceptualized through an energy landscape with a continuum of lowest-energy states. Such continuous attractor landscapes are structurally non-robust, in seeming violation of the relative robustness of biological memory systems. In this talk, I will present and compare different biologically motivated circuit motifs for the accumulation and storage of signals in short-term memory. Challenges to generating robust memory maintenance will be highlighted and potential mechanisms for ameliorating the sensitivity of memory networks to perturbations will be discussed. Funding for this work was provided by NIH R01 MH065034, NSF IIS-1208218, Simons Foundation 324260, and a UC Davis Ophthalmology Research to Prevent Blindness Grant.

Focalised stimulation using high definition transcranial direct current stimulation (HD-tDCS) to investigate declarative verbal learning and memory functioning.

PubMed

Nikolin, Stevan; Loo, Colleen K; Bai, Siwei; Dokos, Socrates; Martin, Donel M

2015-08-15

Declarative verbal learning and memory are known to be lateralised to the dominant hemisphere and to be subserved by a network of structures, including those located in frontal and temporal regions. These structures support critical components of verbal memory, including working memory, encoding, and retrieval. Their relative functional importance in facilitating declarative verbal learning and memory, however, remains unclear. To investigate the different functional roles of these structures in subserving declarative verbal learning and memory performance by applying a more focal form of transcranial direct current stimulation, "High Definition tDCS" (HD-tDCS). Additionally, we sought to examine HD-tDCS effects and electrical field intensity distributions using computer modelling. HD-tDCS was administered to the left dorsolateral prefrontal cortex (LDLPFC), planum temporale (PT), and left medial temporal lobe (LMTL) to stimulate the hippocampus, during learning on a declarative verbal memory task. Sixteen healthy participants completed a single blind, intra-individual cross-over, sham-controlled study which used a Latin Square experimental design. Cognitive effects on working memory and sustained attention were additionally examined. HD-tDCS to the LDLPFC significantly improved the rate of verbal learning (p=0.03, η(2)=0.29) and speed of responding during working memory performance (p=0.02, η(2)=0.35), but not accuracy (p=0.12, η(2)=0.16). No effect of tDCS on verbal learning, retention, or retrieval was found for stimulation targeted to the LMTL or the PT. Secondary analyses revealed that LMTL stimulation resulted in increased recency (p=0.02, η(2)=0.31) and reduced mid-list learning effects (p=0.01, η(2)=0.39), suggesting an inhibitory effect on learning. HD-tDCS to the LDLPFC facilitates the rate of verbal learning and improved efficiency of working memory may underlie performance effects. This focal method of administrating tDCS has potential for probing and enhancing cognitive functioning. Copyright © 2015 Elsevier Inc. All rights reserved.

Pharmacological enhancement of memory or cognition in normal subjects

PubMed Central

Lynch, Gary; Cox, Conor D.; Gall, Christine M.

2014-01-01

The possibility of expanding memory or cognitive capabilities above the levels in high functioning individuals is a topic of intense discussion among scientists and in society at large. The majority of animal studies use behavioral endpoint measures; this has produced valuable information but limited predictability for human outcomes. Accordingly, several groups are pursuing a complementary strategy with treatments targeting synaptic events associated with memory encoding or forebrain network operations. Transcription and translation figure prominently in substrate work directed at enhancement. Notably, the question of why new proteins would be needed for a now-forming memory given that learning-driven synthesis presumably occurred throughout the immediate past has been largely ignored. Despite this conceptual problem, and some controversy, recent studies have reinvigorated the idea that selective gene manipulation is a plausible route to enhancement. Efforts to improve memory by facilitating synaptic encoding of information have also progressed, in part due of breakthroughs on mechanisms that stabilize learning-related, long-term potentiation (LTP). These advances point to a reductionistic hypothesis for a diversity of experimental results on enhancement, and identify under-explored possibilities. Cognitive enhancement remains an elusive goal, in part due to the difficulty of defining the target. The popular view of cognition as a collection of definable computations seems to miss the fluid, integrative process experienced by high functioning individuals. The neurobiological approach obviates these psychological issues to directly test the consequences of improving throughput in networks underlying higher order behaviors. The few relevant studies testing drugs that selectively promote excitatory transmission indicate that it is possible to expand cortical networks engaged by complex tasks and that this is accompanied by capabilities not found in normal animals. PMID:24904313

The challenge of understanding the brain: where we stand in 2015

PubMed Central

Lisman, John

2015-01-01

Starting with the work of Cajal more than 100 years ago, neuroscience has sought to understand how the cells of the brain give rise to cognitive functions. How far has neuroscience progressed in this endeavor? This Perspective assesses progress in elucidating five basic brain processes: visual recognition, long-term memory, short-term memory, action selection, and motor control. Each of these processes entails several levels of analysis: the behavioral properties, the underlying computational algorithm, and the cellular/network mechanisms that implement that algorithm. At this juncture, while many questions remain unanswered, achievements in several areas of research have made it possible to relate specific properties of brain networks to cognitive functions. What has been learned reveals, at least in rough outline, how cognitive processes can be an emergent property of neurons and their connections. PMID:25996132

Light-Induced Temperature Transitions in Biodegradable Polymer and Nanorod Composites**

PubMed Central

Hribar, Kolin C.; Metter, Robert B.; Ifkovits, Jamie L.; Troxler, Thomas

2010-01-01

Shape-memory materials (including polymers, metals, and ceramics) are those that are processed into a temporary shape and respond to some external stimuli (e.g., temperature) to undergo a transition back to a permanent shape.[1, 2] Shape memory polymers are finding use in a range of applications from aerospace to fabrics, to biomedical devices and microsystem components.[3–5] For many applications, it would be beneficial to initiate heating with an external trigger (e.g., transdermal light exposure). In this work, we formulated composites of gold nanorods (<1% by volume) and biodegradable networks, where exposure to infrared light induced heating and consequently, shape transitions. The heating is repeatable and tunable based on nanorod concentration and light intensity and the nanorods did not alter the cytotoxicity or in vivo tissue response to the networks. PMID:19408258

A bio-inspired system for spatio-temporal recognition in static and video imagery

NASA Astrophysics Data System (ADS)

Khosla, Deepak; Moore, Christopher K.; Chelian, Suhas

2007-04-01

This paper presents a bio-inspired method for spatio-temporal recognition in static and video imagery. It builds upon and extends our previous work on a bio-inspired Visual Attention and object Recognition System (VARS). The VARS approach locates and recognizes objects in a single frame. This work presents two extensions of VARS. The first extension is a Scene Recognition Engine (SCE) that learns to recognize spatial relationships between objects that compose a particular scene category in static imagery. This could be used for recognizing the category of a scene, e.g., office vs. kitchen scene. The second extension is the Event Recognition Engine (ERE) that recognizes spatio-temporal sequences or events in sequences. This extension uses a working memory model to recognize events and behaviors in video imagery by maintaining and recognizing ordered spatio-temporal sequences. The working memory model is based on an ARTSTORE1 neural network that combines an ART-based neural network with a cascade of sustained temporal order recurrent (STORE)1 neural networks. A series of Default ARTMAP classifiers ascribes event labels to these sequences. Our preliminary studies have shown that this extension is robust to variations in an object's motion profile. We evaluated the performance of the SCE and ERE on real datasets. The SCE module was tested on a visual scene classification task using the LabelMe2 dataset. The ERE was tested on real world video footage of vehicles and pedestrians in a street scene. Our system is able to recognize the events in this footage involving vehicles and pedestrians.

Trait or state? A longitudinal neuropsychological evaluation and fMRI study in schizoaffective disorder.

PubMed

Madre, Merce; Radua, Joaquim; Landin-Romero, Ramon; Alonso-Lana, Silvia; Salvador, Raimond; Panicali, Francesco; Pomarol-Clotet, Edith; Amann, Benedikt L

2014-11-01

Schizoaffective patients can have neurocognitive deficits and default mode network dysfunction while being acutely ill. It remains unclear to what extent these abnormalities persist when they go into clinical remission. Memory and executive function were tested in 22 acutely ill schizoaffective patients; they also underwent fMRI scanning during performance of the n-back working memory test. The same measures were obtained after they had been in remission for ≥ 2 months. Twenty-two matched healthy individuals were also examined. In clinical remission, schizomanic patients showed an improvement of memory but not of executive function, while schizodepressive patients did not change in either domain. All schizoaffective patients in clinical remission showed memory and executive impairment compared to the controls. On fMRI, acutely ill schizomanic patients had reversible frontal hypo-activation when compared to clinical remission, while activation patterns in ill and remitted schizodepressive patients were similar. The whole group of schizoaffective patients in clinical remission showed a failure of de-activation in the medial frontal gyrus compared to the healthy controls. There was evidence for memory improvement and state dependent changes in activation in schizomanic patients across relapse and remission. Medial frontal failure of de-activation in remitted schizoaffective patients, which probably reflects default mode network dysfunction, appears to be a state independent feature of the illness. Copyright © 2014 Elsevier B.V. All rights reserved.

Associative memory and its cerebral correlates in Alzheimer's disease: Evidence for distinct deficits of relational and conjunctive memory

PubMed Central

Bastin, Christine; Bahri, Mohamed Ali; Miévis, Frédéric; Lemaire, Christian; Collette, Fabienne; Genon, Sarah; Simon, Jessica; Guillaume, Bénédicte; Diana, Rachel A.; Yonelinas, Andrew P.; Salmon, Eric

2014-01-01

This study investigated the impact of Alzheimer's disease (AD) on conjunctive and relational binding in episodic memory. Mild AD patients and controls had to remember item-color associations by imagining color either as a contextual association (relational memory) or as a feature of the item to be encoded (conjunctive memory). Patients' performance in each condition was correlated with cerebral metabolism measured by FDG-PET. The results showed that AD patients had an impaired capacity to remember item-color associations, with deficits in both relational and conjunctive memory. However, performance in the two kinds of associative memory varied independently across patients. Partial least square analyses revealed that poor conjunctive memory was related to hypometabolism in an anterior temporal-posterior fusiform brain network, whereas relational memory correlated with metabolism in regions of the default mode network. These findings support the hypothesis of distinct neural systems specialized in different types of associative memory and point to heterogeneous profiles of memory alteration in Alzheimer's disease as a function of damage to the respective neural networks. PMID:25172390

Spacewire router IP-core with priority adaptive routing

NASA Astrophysics Data System (ADS)

Shakhmatov, A. V.; Chekmarev, S. A.; Vergasov, M. Y.; Khanov, V. Kh

2015-10-01

Design of modern spacecraft focuses on using network principles of interaction on-board equipment, in particular in network SpaceWire. Routers are an integral part of most SpaceWire networks. The paper presents an adaptive routing algorithm with a prioritization, allowing more flexibility to manage the routing process. This algorithm is designed to transmit SpaceWire packets over a redundant network. Also a method is proposed for rapid restoration of working capacity after power by saving the routing table and the router configuration in an external non-volatile memory. The proposed solutions used to create IP-core router, and then tested in the FPGA device. The results illustrate the realizability and rationality of the proposed solutions.

Set selection dynamical system neural networks with partial memories, with applications to Sudoku and KenKen puzzles.

PubMed

Boreland, B; Clement, G; Kunze, H

2015-08-01

After reviewing set selection and memory model dynamical system neural networks, we introduce a neural network model that combines set selection with partial memories (stored memories on subsets of states in the network). We establish that feasible equilibria with all states equal to ± 1 correspond to answers to a particular set theoretic problem. We show that KenKen puzzles can be formulated as a particular case of this set theoretic problem and use the neural network model to solve them; in addition, we use a similar approach to solve Sudoku. We illustrate the approach in examples. As a heuristic experiment, we use online or print resources to identify the difficulty of the puzzles and compare these difficulties to the number of iterations used by the appropriate neural network solver, finding a strong relationship. Copyright © 2015 Elsevier Ltd. All rights reserved.

Working memory impairment in probands with schizoaffective disorder and first degree relatives of schizophrenia probands extend beyond deficits predicted by generalized neuropsychological impairment.

PubMed

Kristian Hill, S; Buchholz, Alison; Amsbaugh, Hayley; Reilly, James L; Rubin, Leah H; Gold, James M; Keefe, Richard S E; Pearlson, Godfrey D; Keshavan, Matcheri S; Tamminga, Carol A; Sweeney, John A

2015-08-01

Working memory impairment is well established in psychotic disorders. However, the relative magnitude, diagnostic specificity, familiality pattern, and degree of independence from generalized cognitive deficits across psychotic disorders remain unclear. Participants from the Bipolar and Schizophrenia Network on Intermediate Phenotypes (B-SNIP) study included probands with schizophrenia (N=289), psychotic bipolar disorder (N=227), schizoaffective disorder (N=165), their first-degree relatives (N=315, N=259, N=193, respectively), and healthy controls (N=289). All were administered the WMS-III Spatial Span working memory test and the Brief Assessment of Cognition in Schizophrenia (BACS) battery. All proband groups displayed significant deficits for both forward and backward span compared to controls. However, after covarying for generalized cognitive impairments (BACS composite), all proband groups showed a 74% or greater effect size reduction with only schizoaffective probands showing residual backward span deficits compared to controls. Significant familiality was seen in schizophrenia and bipolar pedigrees. In relatives, both forward and backward span deficits were again attenuated after covarying BACS scores and residual backward span deficits were seen in relatives of schizophrenia patients. Overall, both probands and relatives showed a similar pattern of robust working memory deficits that were largely attenuated when controlling for generalized cognitive deficits. Copyright © 2015 Elsevier B.V. All rights reserved.

Abnormal prefrontal and parietal activity linked to deficient active binding in working memory in schizophrenia.

PubMed

Grot, Stéphanie; Légaré, Virginie Petel; Lipp, Olivier; Soulières, Isabelle; Dolcos, Florin; Luck, David

2017-10-01

Working memory deficits have been widely reported in schizophrenia, and may result from inefficient binding processes. These processes, and their neural correlates, remain understudied in schizophrenia. Thus, we designed an FMRI study aimed at investigating the neural correlates of both passive and active binding in working memory in schizophrenia. Nineteen patients with schizophrenia and 23 matched controls were recruited to perform a working memory binding task, in which they were instructed to memorize three letters and three spatial locations. In the passive binding condition, letters and spatial locations were directly presented as bound. Conversely, in the active binding condition, words and spatial locations were presented as separated, and participants were instructed to intentionally create associations between them. Patients exhibited a similar performance to the controls for the passive binding condition, but a significantly lower performance for the active binding. FMRI analyses revealed that this active binding deficit was related to aberrant activity in the posterior parietal cortex and the ventrolateral prefrontal cortex. This study provides initial evidence of a specific deficit for actively binding information in schizophrenia, which is linked to dysfunctions in the neural networks underlying attention, manipulation of information, and encoding strategies. Together, our results suggest that all these dysfunctions may be targets for neuromodulation interventions known to improve cognitive deficits in schizophrenia. Copyright © 2017 Elsevier B.V. All rights reserved.

Offline memory reprocessing: involvement of the brain's default network in spontaneous thought processes.

PubMed

Wang, Kun; Yu, Chunshui; Xu, Lijuan; Qin, Wen; Li, Kuncheng; Xu, Lin; Jiang, Tianzi

2009-01-01

Spontaneous thought processes (STPs), also called daydreaming or mind-wandering, occur ubiquitously in daily life. However, the functional significance of STPs remains largely unknown. Using functional magnetic resonance imaging (fMRI), we first identified an STPs-network whose activity was positively correlated with the subjects' tendency of having STPs during a task-free state. The STPs-network was then found to be strongly associated with the default network, which has previously been established as being active during the task-free state. Interestingly, we found that offline reprocessing of previously memorized information further increased the activity of the STPs-network regions, although during a state with less STPs. In addition, we found that the STPs-network kept a dynamic balance between functional integration and functional separation among its component regions to execute offline memory reprocessing in STPs. These findings strengthen a view that offline memory reprocessing and STPs share the brain's default network, and thus implicate that offline memory reprocessing may be a predetermined function of STPs. This supports the perspective that memory can be consolidated and modified during STPs, and thus gives rise to a dynamic behavior dependent on both previous external and internal experiences.

A Facile and General Approach to Recoverable High-Strain Multishape Shape Memory Polymers.

PubMed

Li, Xingjian; Pan, Yi; Zheng, Zhaohui; Ding, Xiaobin

2018-03-01

Fabricating a single polymer network with no need to design complex structures to achieve an ideal combination of tunable high-strain multiple-shape memory effects and highly recoverable shape memory property is a great challenge for the real applications of advanced shape memory devices. Here, a facile and general approach to recoverable high-strain multishape shape memory polymers is presented via a random copolymerization of acrylate monomers and a chain-extended multiblock copolymer crosslinker. As-prepared shape memory networks show a large width at the half-peak height of the glass transition, far wider than current classical multishape shape memory polymers. A combination of tunable high-strain multishape memory effect and as high as 1000% recoverable strain in a single chemical-crosslinking network can be obtained. To the best of our knowledge, this is the first thermosetting material with a combination of highly recoverable strain and tunable high-strain multiple-shape memory effects. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Altered intrinsic hippocmapus declarative memory network and its association with impulsivity in abstinent heroin dependent subjects.

PubMed

Zhai, Tian-Ye; Shao, Yong-Cong; Xie, Chun-Ming; Ye, En-Mao; Zou, Feng; Fu, Li-Ping; Li, Wen-Jun; Chen, Gang; Chen, Guang-Yu; Zhang, Zheng-Guo; Li, Shi-Jiang; Yang, Zheng

2014-10-01

Converging evidence suggests that addiction can be considered a disease of aberrant learning and memory with impulsive decision-making. In the past decades, numerous studies have demonstrated that drug addiction is involved in multiple memory systems such as classical conditioned drug memory, instrumental learning memory and the habitual learning memory. However, most of these studies have focused on the contributions of non-declarative memory, and declarative memory has largely been neglected in the research of addiction. Based on a recent finding that hippocampus, as a core functioning region of declarative memory, was proved biased the decision-making process based on past experiences by spreading associated reward values throughout memory. Our present study focused on the hippocampus. By utilizing seed-based network analysis on the resting-state functional MRI datasets with the seed hippocampus we tested how the intrinsic hippocampal memory network altered toward drug addiction, and examined how the functional connectivity strength within the altered hippocampal network correlated with behavioral index 'impulsivity'. Our results demonstrated that HD group showed enhanced coherence between hippocampus which represents declarative memory system and non-declarative reward-guided learning memory system, and also showed attenuated intrinsic functional link between hippocampus and top-down control system, compared to the CN group. This alteration was furthered found to have behavioral significance over the behavioral index 'impulsivity' measured with Barratt Impulsiveness Scale (BIS). These results provide insights into the mechanism of declarative memory underlying the impulsive behavior in drug addiction. Copyright © 2014 Elsevier B.V. All rights reserved.

Silicon photonics for high-performance interconnection networks

NASA Astrophysics Data System (ADS)

Biberman, Aleksandr

2011-12-01

We assert in the course of this work that silicon photonics has the potential to be a key disruptive technology in computing and communication industries. The enduring pursuit of performance gains in computing, combined with stringent power constraints, has fostered the ever-growing computational parallelism associated with chip multiprocessors, memory systems, high-performance computing systems, and data centers. Sustaining these parallelism growths introduces unique challenges for on- and off-chip communications, shifting the focus toward novel and fundamentally different communication approaches. This work showcases that chip-scale photonic interconnection networks, enabled by high-performance silicon photonic devices, enable unprecedented bandwidth scalability with reduced power consumption. We demonstrate that the silicon photonic platforms have already produced all the high-performance photonic devices required to realize these types of networks. Through extensive empirical characterization in much of this work, we demonstrate such feasibility of waveguides, modulators, switches, and photodetectors. We also demonstrate systems that simultaneously combine many functionalities to achieve more complex building blocks. Furthermore, we leverage the unique properties of available silicon photonic materials to create novel silicon photonic devices, subsystems, network topologies, and architectures to enable unprecedented performance of these photonic interconnection networks and computing systems. We show that the advantages of photonic interconnection networks extend far beyond the chip, offering advanced communication environments for memory systems, high-performance computing systems, and data centers. Furthermore, we explore the immense potential of all-optical functionalities implemented using parametric processing in the silicon platform, demonstrating unique methods that have the ability to revolutionize computation and communication. Silicon photonics enables new sets of opportunities that we can leverage for performance gains, as well as new sets of challenges that we must solve. Leveraging its inherent compatibility with standard fabrication techniques of the semiconductor industry, combined with its capability of dense integration with advanced microelectronics, silicon photonics also offers a clear path toward commercialization through low-cost mass-volume production. Combining empirical validations of feasibility, demonstrations of massive performance gains in large-scale systems, and the potential for commercial penetration of silicon photonics, the impact of this work will become evident in the many decades that follow.

Elaboration versus suppression of cued memories: influence of memory recall instruction and success on parietal lobe, default network, and hippocampal activity.

PubMed

Gimbel, Sarah I; Brewer, James B

2014-01-01

Functional imaging studies of episodic memory retrieval consistently report task-evoked and memory-related activity in the medial temporal lobe, default network and parietal lobe subregions. Associated components of memory retrieval, such as attention-shifts, search, retrieval success, and post-retrieval processing also influence regional activity, but these influences remain ill-defined. To better understand how top-down control affects the neural bases of memory retrieval, we examined how regional activity responses were modulated by task goals during recall success or failure. Specifically, activity was examined during memory suppression, recall, and elaborative recall of paired-associates. Parietal lobe was subdivided into dorsal (BA 7), posterior ventral (BA 39), and anterior ventral (BA 40) regions, which were investigated separately to examine hypothesized distinctions in sub-regional functional responses related to differential attention-to-memory and memory strength. Top-down suppression of recall abolished memory strength effects in BA 39, which showed a task-negative response, and BA 40, which showed a task-positive response. The task-negative response in default network showed greater negatively-deflected signal for forgotten pairs when task goals required recall. Hippocampal activity was task-positive and was influenced by memory strength only when task goals required recall. As in previous studies, we show a memory strength effect in parietal lobe and hippocampus, but we show that this effect is top-down controlled and sensitive to whether the subject is trying to suppress or retrieve a memory. These regions are all implicated in memory recall, but their individual activity patterns show distinct memory-strength-related responses when task goals are varied. In parietal lobe, default network, and hippocampus, top-down control can override the commonly identified effects of memory strength.

Elaboration versus Suppression of Cued Memories: Influence of Memory Recall Instruction and Success on Parietal Lobe, Default Network, and Hippocampal Activity

PubMed Central

Gimbel, Sarah I.; Brewer, James B.

2014-01-01

Functional imaging studies of episodic memory retrieval consistently report task-evoked and memory-related activity in the medial temporal lobe, default network and parietal lobe subregions. Associated components of memory retrieval, such as attention-shifts, search, retrieval success, and post-retrieval processing also influence regional activity, but these influences remain ill-defined. To better understand how top-down control affects the neural bases of memory retrieval, we examined how regional activity responses were modulated by task goals during recall success or failure. Specifically, activity was examined during memory suppression, recall, and elaborative recall of paired-associates. Parietal lobe was subdivided into dorsal (BA 7), posterior ventral (BA 39), and anterior ventral (BA 40) regions, which were investigated separately to examine hypothesized distinctions in sub-regional functional responses related to differential attention-to-memory and memory strength. Top-down suppression of recall abolished memory strength effects in BA 39, which showed a task-negative response, and BA 40, which showed a task-positive response. The task-negative response in default network showed greater negatively-deflected signal for forgotten pairs when task goals required recall. Hippocampal activity was task-positive and was influenced by memory strength only when task goals required recall. As in previous studies, we show a memory strength effect in parietal lobe and hippocampus, but we show that this effect is top-down controlled and sensitive to whether the subject is trying to suppress or retrieve a memory. These regions are all implicated in memory recall, but their individual activity patterns show distinct memory-strength-related responses when task goals are varied. In parietal lobe, default network, and hippocampus, top-down control can override the commonly identified effects of memory strength. PMID:24586492

Occipital cortex of blind individuals is functionally coupled with executive control areas of frontal cortex.

PubMed

Deen, Ben; Saxe, Rebecca; Bedny, Marina

2015-08-01

In congenital blindness, the occipital cortex responds to a range of nonvisual inputs, including tactile, auditory, and linguistic stimuli. Are these changes in functional responses to stimuli accompanied by altered interactions with nonvisual functional networks? To answer this question, we introduce a data-driven method that searches across cortex for functional connectivity differences across groups. Replicating prior work, we find increased fronto-occipital functional connectivity in congenitally blind relative to blindfolded sighted participants. We demonstrate that this heightened connectivity extends over most of occipital cortex but is specific to a subset of regions in the inferior, dorsal, and medial frontal lobe. To assess the functional profile of these frontal areas, we used an n-back working memory task and a sentence comprehension task. We find that, among prefrontal areas with overconnectivity to occipital cortex, one left inferior frontal region responds to language over music. By contrast, the majority of these regions responded to working memory load but not language. These results suggest that in blindness occipital cortex interacts more with working memory systems and raise new questions about the function and mechanism of occipital plasticity.

Measuring the Performance of Attention Networks with the Dalhousie Computerized Attention Battery (DalCAB): Methodology and Reliability in Healthy Adults.

PubMed

Jones, Stephanie A H; Butler, Beverly C; Kintzel, Franziska; Johnson, Anne; Klein, Raymond M; Eskes, Gail A

2016-01-01

Attention is an important, multifaceted cognitive domain that has been linked to three distinct, yet interacting, networks: alerting, orienting, and executive control. The measurement of attention and deficits of attention within these networks is critical to the assessment of many neurological and psychiatric conditions in both research and clinical settings. The Dalhousie Computerized Attention Battery (DalCAB) was created to assess attentional functions related to the three attention networks using a range of tasks including: simple reaction time, go/no-go, choice reaction time, dual task, flanker, item and location working memory, and visual search. The current study provides preliminary normative data, test-retest reliability (intraclass correlations) and practice effects in DalCAB performance 24-h after baseline for healthy young adults (n = 96, 18-31 years). Performance on the DalCAB tasks demonstrated Good to Very Good test-retest reliability for mean reaction time, while accuracy and difference measures (e.g., switch costs, interference effects, and working memory load effects) were most reliable for tasks that require more extensive cognitive processing (e.g., choice reaction time, flanker, dual task, and conjunction search). Practice effects were common and pronounced at the 24-h interval. In addition, performance related to specific within-task parameters of the DalCAB sub-tests provides preliminary support for future formal assessment of the convergent validity of our interpretation of the DalCAB as a potential clinical and research assessment tool for measuring aspects of attention related to the alerting, orienting, and executive control networks.

Tools at Work: Facebook's March on Privacy

ERIC Educational Resources Information Center

Rethlefsen, Melissa L.

2010-01-01

May 31, 2010, was Quit Facebook Day. But although only around 35,000 of the 500 million Facebook users pledged to quit Facebook on Memorial Day, there's a sense of unease stirring with the social network's strategy. Congress has called for Facebook to explain its stance on the collection and sharing of user information (see…

Dysfunctional Neural Network of Spatial Working Memory Contributes to Developmental Dyscalculia

ERIC Educational Resources Information Center

Rotzer, S.; Loenneker, T.; Kucian, K.; Martin, E.; Klaver, P.; von Aster, M.

2009-01-01

The underlying neural mechanisms of developmental dyscalculia (DD) are still far from being clearly understood. Even the behavioral processes that generate or influence this heterogeneous disorder are a matter of controversy. To date, the few studies examining functional brain activation in children with DD mainly focus on number and counting…

Olfactory Fear Conditioning Induces Field Potential Potentiation in Rat Olfactory Cortex and Amygdala

ERIC Educational Resources Information Center

Messaoudi, Belkacem; Granjon, Lionel; Mouly, Anne-Marie; Sevelinges, Yannick; Gervais, Remi

2004-01-01

The widely used Pavlovian fear-conditioning paradigms used for studying the neurobiology of learning and memory have mainly used auditory cues as conditioned stimuli (CS). The present work assessed the neural network involved in olfactory fear conditioning, using olfactory bulb stimulation-induced field potential signal (EFP) as a marker of…