Investigating Thought Disorder in Schizophrenia: Evidence for Pathological Activation

Background

Previous research has yielded evidence for enhanced semantic priming in formal thought-disordered schizophrenia patients, a result that fits well with the hypothesis of disinhibited processes of spreading activation in this population.

Objective

The current study examined whether hyper priming among schizophrenia patients is an outcome of further spreading of activation of a node or a result of farther activation of nodes in the semantic network. We also try to shed light on the fate of this activation.

Methods

The present study tested this hypothesis by using semantic and identical priming in two different experiments. SOA (stimulus onset asynchrony) was manipulated (240 ms vs. 740 ms) within block. It is assumed that among healthy individuals, performance relies on a balance between activation and inhibition processes, contrary to in schizophrenic individuals. In order to examine this hypothesis, we compared formal thought-disordered schizophrenia patients, non thought-disordered schizophrenia patients, and healthy controls.

Results

For thought-disordered schizophrenia patients, we found a large positive semantic effect and identical priming effect (129 ms and 154 ms, respectively) only with short SOA. SOA and type of priming did not modulate priming effects in the control groups.

Conclusions

This result supports the claim that there is a lack of inhibitory processes among thought-disordered patients. Hyper priming in the thought-disorder group may be an outcome of hyper activation followed by rapid decay below baseline threshold.     

Dynamics of the semantic priming shift: behavioral experiments and cortical network model

Multiple semantic priming processes between several related and/or unrelated words are at work during the processing of sequences of words. Multiple priming generates rich dynamics of effects depending on the relationship between the target word and the first and/or second prime previously presented. The experimental literature suggests that during the on-line processing of the primes, the activation can shift from associates to the first prime to associates to the second prime. Though the semantic priming shift is central to the on-line and rapid updating of word meanings in the working memory, its precise dynamics are still poorly understood and it is still a challenge to model how it functions in the cerebral cortex. Four multiple priming experiments are proposed that cross-manipulate delays and association strength between the primes and the target. Results show for the first time that association strength determines complex dynamics of the semantic priming shift, ranging from an absence of a shift to a complete shift. A cortical network model of spike frequency adaptive neuron populations is proposed to account for the non-continuous evolution of the priming shift over time. It allows linking the dynamics of the priming shift assessed at the behavioral level to the non-linear dynamics of the firing rates of neurons populations.     

Social Priming Increases Nonverbal Expressive Behaviors in Schizophrenia

Semantic priming tasks are classically used to influence and implicitly promote target behaviors. Recently, several studies have demonstrated that prosocial semantic priming modulated feelings of social affiliation. The main aim of this study was to determine whether inducing feelings of social affiliation using priming tasks could modulate nonverbal social behaviors in schizophrenia. We used the Scrambled Sentence Task to prime schizophrenia patients according to three priming group conditions: pro-social, non-social or anti-social. Forty-five schizophrenia patients, diagnosed according to DSM-IV-TR, were randomly assigned to one of the three priming groups of 15 participants. We evaluated nonverbal social behaviors using the Motor-Affective subscale of the Motor-Affective-Social-Scale. Results showed that schizophrenia patients with pro-social priming had significantly more nonverbal behaviors than schizophrenia patients with anti-social and non-social priming conditions. Schizophrenia patient behaviors are affected by social priming. Our results have several clinical implications for the rehabilitation of social skills impairments frequently encountered among individuals with schizophrenia.     

Synaptic Potentiation Facilitates Memory-like Attractor Dynamics in Cultured In Vitro Hippocampal Networks

Collective rhythmic dynamics from neurons is vital for cognitive functions such as memory formation but how neurons self-organize to produce such activity is not well understood. Attractor-based computational models have been successfully implemented as a theoretical framework for memory storage in networks of neurons. Additionally, activity-dependent modification of synaptic transmission is thought to be the physiological basis of learning and memory. The goal of this study is to demonstrate that using a pharmacological treatment that has been shown to increase synaptic strength within in vitro networks of hippocampal neurons follows the dynamical postulates theorized by attractor models. We use a grid of extracellular electrodes to study changes in network activity after this perturbation and show that there is a persistent increase in overall spiking and bursting activity after treatment. This increase in activity appears to recruit more “errant” spikes into bursts. Phase plots indicate a conserved activity pattern suggesting that a synaptic potentiation perturbation to the attractor leaves it unchanged. Lastly, we construct a computational model to demonstrate that these synaptic perturbations can account for the dynamical changes seen within the network.     

A dynamical systems hypothesis of schizophrenia

We propose a top-down approach to the symptoms of schizophrenia based on a statistical dynamical framework. We show that a reduced depth in the basins of attraction of cortical attractor states destabilizes the activity at the network level due to the constant statistical fluctuations caused by the stochastic spiking of neurons. In integrate-and-fire network simulations, a decrease in the NMDA receptor conductances, which reduces the depth of the attractor basins, decreases the stability of short-term memory states and increases distractibility. The cognitive symptoms of schizophrenia such as distractibility, working memory deficits, or poor attention could be caused by this instability of attractor states in prefrontal cortical networks. Lower firing rates are also produced, and in the orbitofrontal and anterior cingulate cortex could account for the negative symptoms, including a reduction of emotions. Decreasing the GABA as well as the NMDA conductances produces not only switches between the attractor states, but also jumps from spontaneous activity into one of the attractors. We relate this to the positive symptoms of schizophrenia, including delusions, paranoia, and hallucinations, which may arise because the basins of attraction are shallow and there is instability in temporal lobe semantic memory networks, leading thoughts to move too freely round the attractor energy landscape.     

Semantic integration by pattern priming: experiment and cortical network model

Neural network models describe semantic priming effects by way of mechanisms of activation of neurons coding for words that rely strongly on synaptic efficacies between pairs of neurons. Biologically inspired Hebbian learning defines efficacy values as a function of the activity of pre- and post-synaptic neurons only. It generates only pair associations between words in the semantic network. However, the statistical analysis of large text databases points to the frequent occurrence not only of pairs of words (e.g., “the way”) but also of patterns of more than two words (e.g., “by the way”). The learning of these frequent patterns of words is not reducible to associations between pairs of words but must take into account the higher level of coding of three-word patterns. The processing and learning of pattern of words challenges classical Hebbian learning algorithms used in biologically inspired models of priming. The aim of the present study was to test the effects of patterns on the semantic processing of words and to investigate how an inter-synaptic learning algorithm succeeds at reproducing the experimental data. The experiment manipulates the frequency of occurrence of patterns of three words in a multiple-paradigm protocol. Results show for the first time that target words benefit more priming when embedded in a pattern with the two primes than when only associated with each prime in pairs. A biologically inspired inter-synaptic learning algorithm is tested that potentiates synapses as a function of the activation of more than two pre- and post-synaptic neurons. Simulations show that the network can learn patterns of three words to reproduce the experimental results.     

A feature-based neurocomputational model of semantic memory

According with a featural organization of semantic memory, this work is aimed at investigating, through an attractor network, the role of different kinds of features in the representation of concepts, both in normal and neurodegenerative conditions. We implemented new synaptic learning rules in order to take into account the role of partially shared features and of distinctive features with different saliency. The model includes semantic and lexical layers, coding, respectively for object features and word-forms. Connections among nodes are strongly asymmetrical. To account for the feature saliency, asymmetrical synapses were created using Hebbian rules of potentiation and depotentiation, setting different pre-synaptic and post-synaptic thresholds. A variable post-synaptic threshold, which automatically changed to reflect the feature frequency in different concepts (i.e., how many concepts share a feature), was used to account for partially shared features. The trained network solved naming tasks and word recognition tasks very well, exploiting the different role of salient versus marginal features in concept identification. In the case of damage, superordinate concepts were preserved better than the subordinate ones. Interestingly, the degradation of salient features, but not of marginal ones, prevented object identification. The model suggests that Hebbian rules, with adjustable post-synaptic thresholds, can provide a reliable semantic representation of objects exploiting the statistics of input features.     

Modeling abnormal priming in Alzheimer's patients with a free association network

Alzheimer's Disease irremediably alters the proficiency of word search and retrieval processes even at its early stages. Such disruption can sometimes be paradoxical in specific language tasks, for example semantic priming. Here we focus in the striking side-effect of hyperpriming in Alzheimer's Disease patients, which has been well-established in the literature for a long time. Previous studies have evidenced that modern network theory can become a powerful complementary tool to gain insight in cognitive phenomena. Here, we first show that network modeling is an appropriate approach to account for semantic priming in normal subjects. Then we turn to priming in degraded cognition: hyperpriming can be readily understood in the scope of a progressive degradation of the semantic network structure. We compare our simulation results with previous empirical observations in diseased patients finding a qualitative agreement. The network approach presented here can be used to accommodate current theories about impaired cognition, and towards a better understanding of lexical organization in healthy and diseased patients.     

Probabilistic decision making by slow reverberation in cortical circuits

Recent physiological studies of alert primates have revealed cortical neural correlates of key steps in a perceptual decision-making process. To elucidate synaptic mechanisms of decision making, I investigated a biophysically realistic cortical network model for a visual discrimination experiment. In the model, slow recurrent excitation and feedback inhibition produce attractor dynamics that amplify the difference between conflicting inputs and generates a binary choice. The model is shown to account for salient characteristics of the observed decision-correlated neural activity, as well as the animal's psychometric function and reaction times. These results suggest that recurrent excitation mediated by NMDA receptors provides a candidate cellular mechanism for the slow time integration of sensory stimuli and the formation of categorical choices in a decision-making neocortical network.     

Speech graphs provide a quantitative measure of thought disorder in psychosis

Background

Psychosis has various causes, including mania and schizophrenia. Since the differential diagnosis of psychosis is exclusively based on subjective assessments of oral interviews with patients, an objective quantification of the speech disturbances that characterize mania and schizophrenia is in order. In principle, such quantification could be achieved by the analysis of speech graphs. A graph represents a network with nodes connected by edges; in speech graphs, nodes correspond to words and edges correspond to semantic and grammatical relationships.

Methodology/Principal Findings

To quantify speech differences related to psychosis, interviews with schizophrenics, manics and normal subjects were recorded and represented as graphs. Manics scored significantly higher than schizophrenics in ten graph measures. Psychopathological symptoms such as logorrhea, poor speech, and flight of thoughts were grasped by the analysis even when verbosity differences were discounted. Binary classifiers based on speech graph measures sorted schizophrenics from manics with up to 93.8% of sensitivity and 93.7% of specificity. In contrast, sorting based on the scores of two standard psychiatric scales (BPRS and PANSS) reached only 62.5% of sensitivity and specificity.

Conclusions/Significance

The results demonstrate that alterations of the thought process manifested in the speech of psychotic patients can be objectively measured using graph-theoretical tools, developed to capture specific features of the normal and dysfunctional flow of thought, such as divergence and recurrence. The quantitative analysis of speech graphs is not redundant with standard psychometric scales but rather complementary, as it yields a very accurate sorting of schizophrenics and manics. Overall, the results point to automated psychiatric diagnosis based not on what is said, but on how it is said.     

A neural model of the dynamic activation of memory

We study an Attractor Neural Network that stores natural concepts, organized in semantic classes. The concepts are represented by distributed patterns over a space of attributes, and are related by both semantic and episodic associations. While semantic relations are expressed through an hierarchical coding over the attribute space, episodic links are realized via specific synaptic projections. Due to dynamic thresholds expressing neuronal fatigue, the network's behavior is characterized by convergence toward the concept patterns on a short time scale, and by transitions between the various patterns on a longer time scale. In its baseline, undamaged state, the network manifests semantic, episodic, and random transitions, and demonstrates the phenomen of priming. Modeling possible pathological changes, we have found that increasing the noise level or the rate of neuronal fatigue decreases the frequency of semantic transitions. When neurons characterized by large synaptic connectivity are deleted, semantic transitions decay before the episodic ones, in accordance with the findings in patients with Alzheimer's disease.     

The dynamical stability of reverberatory neural circuits

The concept of reverberation proposed by Lorente de Nó and Hebb is key to understanding strongly recurrent cortical networks. In particular, synaptic reverberation is now viewed as a likely mechanism for the active maintenance of working memory in the prefrontal cortex. Theoretically, this has spurred a debate as to how such a potentially explosive mechanism can provide stable working-memory function given the synaptic and cellular mechanisms at play in the cerebral cortex. We present here new evidence for the participation of NMDA receptors in the stabilization of persistent delay activity in a biophysical network model of conductance-based neurons. We show that the stability of working-memory function, and the required NMDA/AMPA ratio at recurrent excitatory synapses, depend on physiological properties of neurons and synaptic interactions, such as the time constants of excitation and inhibition, mutual inhibition between interneurons, differential NMDA receptor participation at excitatory projections to pyramidal neurons and interneurons, or the presence of slow intrinsic ion currents in pyramidal neurons. We review other mechanisms proposed to enhance the dynamical stability of synaptically generated attractor states of a reverberatory circuit. This recent work represents a necessary and significant step towards testing attractor network models by cortical electrophysiology.     

Towards biologically constrained attractor models of schizophrenia

Alterations in neuromodulation or synaptic transmission in biophysical attractor network models, as proposed by the dominant dopaminergic and glutamatergic theories of schizophrenia, successfully mimic working memory (WM) deficits in people with schizophrenia (PSZ). Yet, multiple, often opposing alterations in memory circuits can lead to the same behavioral patterns in these network models. Here, we critically revise the computational and experimental literature that links NMDAR hypofunction to WM precision loss in PSZ. We show in network simulations that currently available experimental evidence cannot set apart competing biophysical accounts. Critical points to resolve are the effects of increases vs. decreases in E/I ratio (e.g. through NMDAR blockade) on firing rate tuning and shared noise modulations and possible concomitant deficits in short-term plasticity. We argue that these concerted experimental and computational efforts will lead to a better understanding of the neurobiology underlying cognitive deficits in PSZ.     

Holding Multiple Items in Short Term Memory: A Neural Mechanism

Human short term memory has a capacity of several items maintained simultaneously. We show how the number of short term memory representations that an attractor network modeling a cortical local network can simultaneously maintain active is increased by using synaptic facilitation of the type found in the prefrontal cortex. We have been able to maintain 9 short term memories active simultaneously in integrate-and-fire simulations where the proportion of neurons in each population, the sparseness, is 0.1, and have confirmed the stability of such a system with mean field analyses. Without synaptic facilitation the system can maintain many fewer memories active in the same network. The system operates because of the effectively increased synaptic strengths formed by the synaptic facilitation just for those pools to which the cue is applied, and then maintenance of this synaptic facilitation in just those pools when the cue is removed by the continuing neuronal firing in those pools. The findings have implications for understanding how several items can be maintained simultaneously in short term memory, how this may be relevant to the implementation of language in the brain, and suggest new approaches to understanding and treating the decline in short term memory that can occur with normal aging.     

Affective Priming Using Facial Expressions Modulates Liking for Abstract Art

We examined the influence of affective priming on the appreciation of abstract artworks using an evaluative priming task. Facial primes (showing happiness, disgust or no emotion) were presented under brief (Stimulus Onset Asynchrony, SOA = 20ms) and extended (SOA = 300ms) conditions. Differences in aesthetic liking for abstract paintings depending on the emotion expressed in the preceding primes provided a measure of the priming effect. The results showed that, for the extended SOA, artworks were liked more when preceded by happiness primes and less when preceded by disgust primes. Facial expressions of happiness, though not of disgust, exerted similar effects in the brief SOA condition. Subjective measures and a forced-choice task revealed no evidence of prime awareness in the suboptimal condition. Our results are congruent with findings showing that the affective transfer elicited by priming biases evaluative judgments, extending previous research to the domain of aesthetic appreciation.     

Learning Word Meanings: Overnight Integration and Study Modality Effects

According to the complementary learning systems (CLS) account of word learning, novel words are rapidly acquired (learning system 1), but slowly integrated into the mental lexicon (learning system 2). This two-step learning process has been shown to apply to novel word forms. In this study, we investigated whether novel word meanings are also gradually integrated after acquisition by measuring the extent to which newly learned words were able to prime semantically related words at two different time points. In addition, we investigated whether modality at study modulates this integration process. Sixty-four adult participants studied novel words together with written or spoken definitions. These words did not prime semantically related words directly following study, but did so after a 24-hour delay. This significant increase in the magnitude of the priming effect suggests that semantic integration occurs over time. Overall, words that were studied with a written definition showed larger priming effects, suggesting greater integration for the written study modality. Although the process of integration, reflected as an increase in the priming effect over time, did not significantly differ between study modalities, words studied with a written definition showed the most prominent positive effect after a 24-hour delay. Our data suggest that semantic integration requires time, and that studying in written format benefits semantic integration more than studying in spoken format. These findings are discussed in light of the CLS theory of word learning.     

Effects of a single short exposure to blue light on cognitive performance

The aim of the present study is to explore the effects of a single short one-minute exposure to blue light on cognitive performance. For this purpose, 32 young adults (16 females, mean age 24.06 ± 1.88 years) took part in a within-subjects research design, under two conditions: blue light and no light. Under both conditions, they performed the lexical decision task (LDT) in order to assess the degree of automatic activation of semantic memory through an embedded semantic priming (reaction times to prime – reaction times to target), together with the Attention Network Test (ANT) to assess the efficiency of the alerting, executive and orienting networks. During the LDT, a significantly stronger semantic priming under the blue light condition compared to no light was observed, while during the ANT a significant difference in orienting network efficiency between conditions was observed. The present data appear to highlight that even a single short exposure to blue light has an effect on cognitive performance in young adults.     

Suggestion-Induced Modulation of Semantic Priming during Functional Magnetic Resonance Imaging

Using functional magnetic resonance imaging during a primed visual lexical decision task, we investigated the neural and functional mechanisms underlying modulations of semantic word processing through hypnotic suggestions aimed at altering lexical processing of primes. The priming task was to discriminate between target words and pseudowords presented 200 ms after the prime word which was semantically related or unrelated to the target. In a counterbalanced study design, each participant performed the task once at normal wakefulness and once after the administration of hypnotic suggestions to perceive the prime as a meaningless symbol of a foreign language. Neural correlates of priming were defined as significantly lower activations upon semantically related compared to unrelated trials. We found significant suggestive treatment-induced reductions in neural priming, albeit irrespective of the degree of suggestibility. Neural priming was attenuated upon suggestive treatment compared with normal wakefulness in brain regions supporting automatic (fusiform gyrus) and controlled semantic processing (superior and middle temporal gyri, pre- and postcentral gyri, and supplementary motor area). Hence, suggestions reduced semantic word processing by conjointly dampening both automatic and strategic semantic processes.     

Persistent activity in neural networks with dynamic synapses

Persistent activity states (attractors), observed in several neocortical areas after the removal of a sensory stimulus, are believed to be the neuronal basis of working memory. One of the possible mechanisms that can underlie persistent activity is recurrent excitation mediated by intracortical synaptic connections. A recent experimental study revealed that connections between pyramidal cells in prefrontal cortex exhibit various degrees of synaptic depression and facilitation. Here we analyze the effect of synaptic dynamics on the emergence and persistence of attractor states in interconnected neural networks. We show that different combinations of synaptic depression and facilitation result in qualitatively different network dynamics with respect to the emergence of the attractor states. This analysis raises the possibility that the framework of attractor neural networks can be extended to represent time-dependent stimuli.     

Subliminal semantic priming in speech

Numerous studies have reported subliminal repetition and semantic priming in the visual modality. We transferred this paradigm to the auditory modality. Prime awareness was manipulated by a reduction of sound intensity level. Uncategorized prime words (according to a post-test) were followed by semantically related, unrelated, or repeated target words (presented without intensity reduction) and participants performed a lexical decision task (LDT). Participants with slower reaction times in the LDT showed semantic priming (faster reaction times for semantically related compared to unrelated targets) and negative repetition priming (slower reaction times for repeated compared to semantically related targets). This is the first report of semantic priming in the auditory modality without conscious categorization of the prime.