Impaired Motion Processing in Schizophrenia and the Attenuated Psychosis Syndrome: Etiological and Clinical Implications
Publication: American Journal of Psychiatry
Abstract
Objective:
The ability to perceive the motion of biological objects, such as faces, is a critical component of daily function and correlates with the ability to successfully navigate social situations (social cognition). Deficits in motion perception in schizophrenia were first demonstrated about 20 years ago but remain understudied, especially in the early, potentially prodromal, stages of the illness. The authors examined the neural bases of visual sensory processing impairments, including motion, in patients with schizophrenia (N=63) and attenuated psychosis (clinical high risk) (N=32) compared with age-matched healthy control subjects (N=67).
Method:
Electrophysiological recordings during stimulus and motion processing were analyzed using oscillatory (time frequency) approaches that differentiated motion-onset-evoked activity from stimulus-onset sensory-evoked responses. These were compared with functional MRI (fMRI) measures of motion processing.
Results:
Significant deficits in motion processing were observed across the two patient groups, and these deficits predicted impairments in both face-emotion recognition and cognitive function. In contrast to motion processing, sensory-evoked stimulus-onset responses were intact in patients with attenuated psychosis, and, further, the relative deficit in motion-onset responses compared with stimulus-onset responses predicted transition to schizophrenia. In patients with schizophrenia, motion detection deficits mapped to impaired activation in motion-sensitive visual cortex during fMRI. Additional visual impairments in patients with schizophrenia, not present in patients with attenuated psychosis, implicated other visual regions, including the middle occipital gyrus and pulvinar thalamic nucleus.
Conclusions:
The study findings emphasize the importance of sensory-level visual dysfunction in the etiology of schizophrenia and in the personal experience of individuals with the disorder and demonstrate that motion-processing deficits may predate illness onset and contribute to impaired function even in patients with attenuated psychosis.
The ability to perceive and process motion is central to everyday human functioning and contributes strongly to an individual’s ability to decode the emotion and intent of another person on the basis of facial expression (face emotion recognition) (1, 2). Motion discrimination ability is known to be heavily dependent on the function of visual sensory regions located in the mid-temporal cortex, which can be investigated physiologically using electrophysiological (3) and functional MRI (fMRI) approaches (4). In addition to its role in simple motion processing, the mid-temporal cortex area plays an important role in decoding facial expressions, suggesting that the decoding of emotion, even from static faces, may depend in part on processing of the implied motion inherent in the facial display (5).
Deficits in motion detection ability were first demonstrated in schizophrenia about 20 years ago (6). However, determination of the course of such deficits and identification of their underlying neural mechanisms remain areas of active investigation. Here, we investigated motion processing ability, along with other aspects of visual function, both in patients with schizophrenia and in patients who met criteria for attenuated psychosis syndrome, which is included in DSM-5 (7) as a condition for further study. In addition to showing attenuated symptoms of schizophrenia, individuals with attenuated psychosis syndrome show significant impairments in social and role functioning and markedly elevated risk for transitioning to schizophrenia (8).
In primates, the visual sensory cortex receives convergent information from several distinct subcortical pathways. The magnocellular pathway is uniquely sensitive to low-contrast, low-spatial-frequency stimuli, and stimulus motion. In contrast, the parvocellular system is specialized for the processing of high-spatial-frequency and high-contrast information (9). The retinotectal system, which projects from the retina to the superior colliculus and then to the pulvinar nucleus of the thalamus, is proposed to account for the phenomenon of blindsight following lesions in the primary visual cortex as well as for rapid activation in the amygdala in response to fearful faces (for a review, see reference 10).
Consistent with motion processing dysfunction, robust deficits in magnocellular function have been documented in schizophrenia using behavioral, electrophysiological, and fMRI methods and have been linked to underlying dysfunction of N-methyl-d-aspartate-mediated glutamatergic neurotransmission (for a review, see references 11–13). Impairments in visual processing are also concordant with postmortem structural studies that show consistent reductions of volume and neuron number in both the primary visual cortex (14) and the pulvinar (15). Occipital volumes are apparently unaffected in individuals with attenuated psychosis as a whole (16) but may differentiate individuals who transition to schizophrenia from those who do not (17).
Here, we analyzed electrophysiological responses derived from an optimized visual stimulation paradigm (which we refer to as the “JH-FLKR” paradigm) in patients with schizophrenia and patients with attenuated psychosis. Spectral decomposition (time frequency) analysis was used to isolate components of interest. In this paradigm, oscillatory activity related to initial stimulus onset occurs primarily at theta frequency (4–7 Hz) (18). By contrast, motion onset has been shown to evoke slower activity that mapped to the delta frequency range (1–4 Hz) (19). Steady-state visual evoked potentials elicited by alpha frequency (10 Hz) oscillatory stimuli were also measured. Steady-state visual evoked potentials have been shown to be reliably reduced in schizophrenia (for a review, see reference 20) but have not been studied in attenuated psychosis. In the present study, we obtained fMRI measures of motion processing from a subset of patients with schizophrenia.
Our aim was twofold: first, to investigate the integrity of visual processing dysfunction across two clinical groups—patients with schizophrenia and patients with attenuated psychosis—and second, to examine functional correlates of visual sensory impairments. Given recent findings that deficits in face emotion recognition precede illness onset and predict transition to schizophrenia (21, 22), we hypothesized that deficits in motion processing would likewise predate illness onset and correlate with impaired face emotion recognition and other aspects of cognitive processing in patients with schizophrenia and in patients with attenuated psychosis.
Method
Participants
Clinical subjects were recruited from the Nathan Kline Institute for Psychiatric Research (Orangeburg, N.Y.) and the New York State Psychiatric Institute at Columbia University. Control subjects were recruited from among staff and surrounding communities. The study was approved by the institutional review boards of these institutions, and written informed consent was obtained from all study subjects, who were compensated for their participation.
Participants were patients with schizophrenia who met DSM-5 criteria (N=63), patients with attenuated psychosis (N=32) who were diagnosed with the Structured Interview for Prodromal Syndromes (23), healthy volunteers who were of similar age to the schizophrenia group (older control subjects) (N=44), and healthy volunteers who were of similar age to the attenuated psychosis group (younger control subjects) (N=23) (Table 1; also see Table S1 in the online supplement ). All patients in the schizophrenia group were on stable dosages of medication. A subset of 21 patients with schizophrenia and 16 healthy control subjects participated in the fMRI study (for further details, see Table S2 in the online supplement ).
| Schizophrenia Group (N=63) | Older Healthy Control Group (N=44) | Attenuated Psychosis Group (N=32) | Younger Healthy Control Group (N=23) | |||||
|---|---|---|---|---|---|---|---|---|
| Characteristic | Mean | SD | Mean | SD | Mean | SD | Mean | SD |
| Age (years) | 41.2 | 11.2 | 33.3 | 7.5 | 21.9 | 3.7 | 24.6 | 4.4 |
| Education level (years) | 12.5 | 2.3 | 14.7 | 1.9 | 13.1 | 2.2 | 15.4 | 2.1 |
| Ammons Quick IQ Test | 97.7 | 8.8 | 102.5 | 11.1 | 97.3 | 13.1 | ||
| Participant socioeconomic status | 25.1 | 9.3 | 36.5 | 12.0 | 31.8 | 12.4 | 40.7 | 12.8 |
| Parental socioeconomic status | 47.0 | 13.7 | 44.3 | 14.8 | 45.6 | 11.7 | 49.4 | 12.8 |
| Illness duration (years) | 20.5 | 9.5 | ||||||
| Antipsychotic medication (chlorpromazine equivalents) | 754.5 | 717.8 | ||||||
| Penn Emotion Recognition Task | 28.0 | 5.6 | 34.9 | 2.3 | 34.0 | 2.9 | 34.6 | 2.5 |
| Positive and Negative Syndrome Scale | ||||||||
| Positive scale | 12.0 | 4.3 | ||||||
| Negative scale | 15.3 | 5.3 | ||||||
| Structured Interview for Prodromal Syndromes and Scale of Prodromal Symptoms | ||||||||
| Positive | 14.1 | 4.1 | ||||||
| Negative | 17.6 | 6.3 | ||||||
| Disorganization | 12.5 | 4.6 | ||||||
| General | 11.1 | 3.6 | ||||||
| MCCB domain | ||||||||
| Speed of processing | 33.0 | 11.9 | 43.2 | 11.9 | ||||
| Attention/vigilance | 35.4 | 13.8 | 42.6 | 9.7 | ||||
| Working memory | 35.9 | 12.8 | 43.9 | 9.4 | ||||
| Verbal learning | 36.7 | 7.5 | 45.8 | 8.3 | ||||
| Visual learning | 36.6 | 13.4 | 45.6 | 8.8 | ||||
| Reasoning and problem solving | 40.2 | 11.2 | 41.3 | 11.6 | ||||
a
The female:male ratios for the schizophrenia group, the older healthy control group, the attenuated psychosis group, and the younger healthy control group were 13:50, 14:30, 12:20, and 12:11, respectively. MCCB=MATRICS (Measurement and Treatment Research to Improve Cognition in Schizophrenia) Consensus Cognitive Battery.
Patients with attenuated psychosis were recruited from the Center of Prevention and Evaluation at Columbia University. Exclusion criteria were a history of threshold psychosis or a family history of psychosis, risk of harm to self or others incommensurate with outpatient care, any major medical or neurological disorder, and an IQ <70. Additionally, attenuated psychosis symptoms could not occur solely in the context of substance use or withdrawal or be better accounted for by another disorder. Two years after initial identification, six patients in the attenuated psychosis group (19%) received a diagnosis of schizophrenia.
Symptoms and Neuropsychological Measures
Psychiatric symptoms were evaluated using the Positive and Negative Syndrome Scale (PANSS) (24). Attenuated psychosis symptoms were assessed using the Scale of Prodromal Symptoms (23). General neuropsychological function was assessed with the MATRICS (Measurement and Treatment Research to Improve Cognition in Schizophrenia) Consensus Cognitive Battery (MCCB) (25) minus the social cognition domain. The MCCB was available for 52 patients with schizophrenia and 17 patients with attenuated psychosis. The overall MCCB score was calculated as the average of the six MATRICS domains. Face emotion recognition was assessed with the Penn Emotion Recognition Task (40 faces version) (26).
Coherent Motion Discrimination Task (Behavior)
Individual thresholds for coherent motion detection were determined using random dot kinetograms comprising a square patch (7.5°×7.5° visual angle) containing 120 randomly arranged gray dots (0.5°×0.5°, 65% contrast) on a darker (40% contrast) background (Figure 1A). The motion coherence for each trial was determined with the QUEST procedure, which computes a Bayesian estimate based on all previous trials to determine the optimal coherence level for threshold estimation for the following trial. Coherence thresholds (at 82% correct) were based on 100 trials. Analyses were carried out on motion sensitivity scores, which were calculated as 1 over the estimated coherence threshold for each study subject.
FIGURE 1. Behavioral, EEG, and Functional MRI (fMRI) Paradigmsa
aPanel A illustrates the behavioral motion discrimination task. On each trial, a proportion of dots moved coherently (left, right) for 1,000 ms, then participants were cued to indicate the direction of coherent motion. Panel B shows the stimulus sequence for the EEG task. Each trial began with presentation of one of three stimuli that remained static for 400 ms, drifted rightward (14° per second) for 200 ms and then (after an 800-ms delay) counterphase reversed at a rate of 10 Hz for 3,000 ms, thereby generating a steady-state visual evoked potential. Each study subject took part in 420 trials. Panel C shows the fMRI paradigm. Low-contrast concentric rings presented at fixation alternated between stationary and moving (expanding and contracting) stimuli in 20-second epochs. HSF=high spatial frequency; ITI=intertrial interval; LSF=low spatial frequency; s=seconds.
Electrophysiology
Stimuli and tasks.
Stimuli were gray-scale vertical sinusoidal gratings (3°×3° visual angle) composed of low spatial frequencies (0.8 cycles per degree [cpd]) at high (75%) luminance contrast, low spatial frequencies at low (8%) luminance contrast, or high spatial frequencies (5 cpd) at high luminance contrast (Figure 1B). Each trial began with presentation of one of the three stimuli, which remained static for 400 ms and then drifted rightward (14° per second) for 200 ms. After an 800-ms delay, during which the grating was static, the grating counterphase reversed at a rate of 10 Hz for 3,000 ms, thereby generating a steady-state visual evoked potential. The participant’s task was to fixate on the central cross and respond by using a button press when the central cross dimmed slightly (every 3–12 seconds). On average, patients with schizophrenia correctly detected 87.5% of the fixation dimming events, the attenuated psychosis group 91.3%, the young control group 90.7%, and the older control group 92.5%. Event-related activity was analyzed separately after stimulus onset, the onset of apparent motion, and the onset of steady-state visual evoked potentials (counterphase reversals). The use of this interleaved design and 5-second intertrial interval was designed to minimize habituation of motion-evoked activity while maximizing the number of trials.
Recordings and data analysis.
EEG activity was recorded continuously from 64 electrodes with either an Advanced Neuro Technology recording system with a Waveguard cap (recorded at the Nathan Kline Institute for Psychiatric Research) (27) or a Brain Vision system with a 10/10 system cap (recorded at the New York State Psychiatric Institute) (28). Data were digitized online at 512 Hz and recorded relative to a common reference during acquisition. Data were re-referenced offline to the average of all electrodes. The impedance of all electrodes was kept below 5 kΩ throughout the recording, and eye movements were monitored with bipolar electrodes on the left and right outer canthi.
An independent component analysis was performed for removal of blink-related artifacts. Epochs with amplitudes exceeding ±100 µV at any electrode were also excluded. On average, 17.8% of trials were excluded in the schizophrenia group, 11.8% in the attenuated psychosis group, 9.2% in the older control group, and 10.6% in the younger control group, resulting in 345, 370, 381, and 375 total accepted trials, respectively, for the study groups. Scalp topography and amplitudes of event-related neural activity were similar across recording sites (the Nathan Kline Institute for Psychiatric Research and the New York State Psychiatric Institute) for all populations (for further details, see Figure S1 in the online supplement ).
Event-related potentials were obtained by time locking to the onset of all stimuli and averaging across trials. The averaged event-related potentials were digitally low-pass filtered with a Gaussian finite impulse function (3 dB attenuation at 46 Hz) to remove high-frequency noise produced by muscle activity and external electrical sources. Time-frequency (evoked amplitude) measures were obtained by convolving the time-domain averaged event-related potentials with three-cycle Morlet wavelets over a 3,000-ms window beginning 1,000 ms before the initial onset of each stimulus. Evoked activity was extracted at each time point over 74 frequency scales from 0.48 to 27.6 Hz, incremented logarithmically. Data on steady-state visual evoked potentials were analyzed as a function of the driving stimulation frequency (10 Hz), and thus analysis of the steady-state visual evoked potentials was performed using fast Fourier transform. Fast Fourier transform power at 10 Hz was calculated using artifact-corrected epochs extending from 500 to 3,000 ms after onset of steady-state visual evoked potentials. All analyses were performed using MATLAB (MathWorks, Natick, Mass.), with the EEGLAB and ERPLAB toolboxes (29).
Stimulus-onset and motion-onset activity was calculated across four bilateral electrode sites corresponding to the peak amplitude region and quantified in the theta (4–7 Hz) and delta (1–4 Hz) frequency bands, respectively (for further details, see Figure S1 in the online supplement ). Measurement windows were centered on the peak delta and theta amplitude latencies based on combined data from each study group. This yielded post-stimulus onset theta windows of 150–250 ms and post-motion onset delta windows of 100–300 ms and 80–280 ms among the older and younger control groups, respectively. Corresponding time-domain event-related potential components (P1, N2) are shown in Figure S2 in the online supplement . Fast Fourier transform power of the steady-state visual evoked potential response was maximal in the alpha frequency band at 10 Hz, the driving and stimulation frequency, and was measured across three midline parieto-occipital sites.
fMRI
Stimuli and task.
Stimulus-sensitive and motion-sensitive cortical areas were identified using a previously described paradigm (4). Briefly, stimuli were low-contrast (12%) concentric rings presented at fixation (extending throughout a circular region measuring 15° in diameter) and expanding or contracting at a rate of 7° per second for 20 seconds, followed by 20 seconds during which the stimuli were static. A fixation cross was continuously present at the center of the display, and its luminance was slightly decreased every 4–10 seconds. Participants were instructed to indicate detection of this dimming via button press (Figure 1C).
Acquisition and data analysis.
T2*-weighted echo-planar images (time to repeat=2 seconds, echo time=38 ms, flip angle=90°) were acquired on a Siemens Tim Trio 3-T 80-cm bore head-only MRI system housed at the Nathan Kline Institute Center for Advanced Brain Imaging. Functional images (voxel size=4 mm3) were acquired on 32 contiguous axial slices. The Analysis of Functional NeuroImages software (https://afni.nimh.nih.gov) was used for all preprocessing and statistical testing. For anatomical localization, high-resolution (1 mm3) whole-brain structural images were acquired from each participant using an MPRAGE sequence. Functional images were registered to each participant’s anatomy and transformed into standardized Talairach stereotaxic space.
Data for each individual participant were analyzed using general linear model procedures that contrasted the hemodynamic response to epochs of moving stimuli compared with stationary stimuli. Individual motion parameter estimates were included in the model as regressors. The resulting beta weight maps were analyzed with analysis of variance (ANOVA) across all participants to identify motion-sensitive regions of interests. Group differences in cortical activation were then evaluated within each of these regions of interest with separate ANOVAs using individual beta weight maps. Significance levels and minimum cluster sizes were calculated using Monte Carlo simulations with a corrected p value set at <0.01.
Statistical Analyses of Electrophysiological Data
Between-group analyses were performed using multivariate analysis of variance with between-subject factors of clinical status (schizophrenia and attenuated psychosis), age group (older control group and younger control group), and testing site (the Nathan Kline Institute for Psychiatric Research and the New York State Psychiatric Institute). Within-subject factors of stimulus type (low spatial frequency with low contrast, low spatial frequency with high contrast, and high spatial frequency) and, where appropriate, hemisphere (left, right) were also included. Within-group correlations were calculated using Pearson’s r. Between-group correlations were calculated using partial r (rp) adjusted for group. Effect sizes (d) were interpreted according to conventions delineated by Cohen.
Results
Time-frequency plots by clinical status (schizophrenia and attenuated psychosis) and age group (older healthy control group and younger healthy control group) are shown in Figure 2. Separate analyses were conducted for delta, theta, and steady-state visual evoked potential responses.
FIGURE 2. Behavioral and EEG Responses by Groupa
a Panel A shows the evoked amplitude in response to stimulus and motion onset. Time-frequency plots (averaged across stimuli) are shown for healthy older control (HC) subjects, patients with schizophrenia (SZ), younger control (YC) subjects, and patients with attenuated psychosis (APS). Latency and frequency testing intervals are shown for delta (1–4 Hz) (solid rectangles) and theta (4–7 Hz) (dashed rectangles). The mean delta and theta amplitude for each group is presented in the bar plots. Panel B shows the steady-state visual evoked potential responses. Tracings of group-averaged fast Fourier transform power derived from steady-state visual evoked potentials, collapsed across stimulus types, are illustrated. Panels C and D show the motion sensitivity measures for each group and the correlation with delta amplitude and face emotion recognition (Penn Emotion Recognition Task) scores across the two groups of clinical subjects. ER40=Penn Emotion Recognition Task–40 Faces; ssVEP=steady-state visual evoked potental.
*p<0.01. **p<0.001.
Motion-Evoked (Delta) Activity
Motion-related delta activity differed significantly between clinical subjects and healthy control subjects (F=17.66, df=1, 152, p<0.001, d=0.68), with no significant main effect of age group (F=0.006, df=1, 152, p=0.938, d=0.02) or clinical status-by-age-group interaction (F=0.779, df=1, 152, p=0.379). Highly significant between-group differences were observed for both the schizophrenia group (t=2.71, df=105, p=0.008, d=0.54) and the attenuated psychosis group (t=3.45, df=53, p=0.001, d=0.96) compared with age-matched healthy control subjects (schizophrenia group compared with older control subjects and attenuated psychosis group compared with younger control subjects) (Figure 2A; for further details, see Table S3 in the online supplement ).
There was also a significant stimulus type-by-clinical status interaction (F=3.45, df=2, 151, p=0.034), reflecting greater deficits for low spatial frequency stimuli of both high-luminance contrast (t=4.50, df=160, p<0.001, d=0.72) and low-luminance contrast (t=4.50, df=160, p<0.001, d=0.53) compared with high-spatial-frequency stimuli (t=4.50, df=160, p<0.001, d=0.43), supporting differential magnocellular system involvement.
Finally, there was a small effect size (nonsignificant effect of testing site [F=3.75, df=1, 152, p=0.055, d=0.31]) that did not significantly interact with clinical status (F=0.012, df=1, 152, p=0.915) or age group (F=0.221, df=1, 152, p=0.639).
Stimulus-Onset (Theta) Activity
In contrast with motion-onset responses, stimulus-onset (theta) responses were not significantly different between clinical subjects and healthy control subjects overall (F=0.27, df=1, 152, p=0.607, d=0.08). However, there was a highly significant clinical status-by-age group interaction (F=9.14, df=1, 152, p=0.003), reflecting significantly reduced mean theta activity in patients with schizophrenia compared with older healthy control subjects (t=3.48, df=105, p<0.001, d=0.69) but preserved stimulus-onset responses in patients with attenuated psychosis (t=–1.41, df=53, p=0.164, d=0.39) (Figure 2A).
The effect of age group was significant (F=4.99, df=1, 152, p=0.027, d=0.36), reflecting larger responses in younger individuals compared with older individuals irrespective of their clinical status. The stimulus type-by-clinical or type-by-nonclinical interaction was not statistically significant (F=0.757, df=2, 151, p=0.470). There was no main effect of testing site (F=0.013, df=1, 152, p=0.911, d=0.02), site-by-age group interaction (p=0.173), or site-by-clinical status interaction (p=0.898) (for further details, see Table S3 in the online supplement ).
Steady-State Visual Evoked Potentials (Fast Fourier Transform) Power (Alpha)
As with theta, power for steady-state visual evoked potential was not significantly different between the patient and healthy control groups overall (F=2.20, df=1, 152, p=0.140, d=0.24) but did show a significant clinical status-by-age group interaction (F=6.20, df=1, 152, p=0.014), reflecting significant deficits in the schizophrenia group (t=3.16, df=105, p=0.002, d=0.63) but not in the attenuated psychosis group (t=–0.68, df=53, p=0.495, d=0.19) compared with age-matched control subjects (Figure 2B). The main effect of testing site (F=0.007, df=1, 152, p=0.932, d=0.01) and all interactions with testing site were nonsignificant (all p values >0.25).
Motion Sensitivity (Behavior)
As with delta, behavioral motion sensitivity (1/coherence threshold) differed significantly between clinical subjects and control subjects (F=20.02, df=1, 152, p<0.001, d=0.72), reflecting significant reductions both in patients with schizophrenia (p<0.001) and in patients with attenuated psychosis (p<0.01) compared with age-matched control subjects (Figure 2C). There was a significant main effect of age group (F=17.401, df=1, 152, p<0.001, d=0.66), reflecting better performance among younger individuals compared with older individuals; however, clinical status and age did not significantly interact (F=1.05, df=1, 152, p=0.305).
Although motion sensitivity differed as a function of testing site (F=5.03, df=1, 152, p=0.026, d=0.36), there was no interaction between site and clinical status (F=0.273, df=1, 152, p=0.602) or site and age (F=2.32, df=1, 152, p=0.130).
Across the schizophrenia and attenuated psychosis groups, the amplitude of both delta-evoked (r=0.309, p=0.002) and theta-evoked activity (r=0.290, p=0.004) correlated significantly with impaired motion sensitivity. Reduced motion sensitivity in the two clinical groups additionally correlated with impaired face emotion recognition (Penn Emotion Recognition Task) (r=0.385, p<0.001) (Figure 2D).
fMRI
During scanning, correct detections of fixation dimming events did not differ significantly between patients with schizophrenia (79%) and healthy control subjects (87%) (t=0.57, df=35, p=0.581, d=0.19).
Activation in the mid-temporal cortex in response to moving compared with stationary stimuli was reduced in patients with schizophrenia overall (F=6.54, df=1, 35, p=0.015, d=0.87). The main effect of hemisphere was also significant (F=18.09, df=1, 35, d=1.45, p=0.001), with greater activation in the right hemisphere. However, the group-by-hemisphere interaction was not statistically significant (F=0.757, df=1, 35, p=0.390). Finally, the mean activation in the mid-temporal cortex correlated significantly with motion-evoked delta activity across all groups (rp=0.573, p<0.001) and within the schizophrenia group (r=0.642, p=0.002) and the healthy comparison group (r=0.583, p=0.018) (Figure 3A).
FIGURE 3. Functional MRI Measures of Motion Perceptiona
a Panel A shows the activation in the mid-temporal cortex area (MT+). Regions of interest in the middle temporal cortex corresponding to the MT+ (right hemisphere [RH]) and in the bar graphs indicate the mean activation (beta parameter) elicited by the contrast of moving compared with static stimuli across hemispheres in the schizophrenia (SZ) and healthy control (HC) groups. Reduced MT+ activation correlated with diminished delta amplitude (low spatial frequency and low contrast stimuli) in response to motion onset (right scatterplot). Panel B shows the activation in the middle occipital gyrus (MOG). The mean activation in the MOG (left hemisphere) and correlation with diminished mean theta amplitude in response to stimulus onset are illustrated. Panel C shows the activation in the pulvinar nucleus (Pulv.). The mean pulvinar (right hemisphere) activation and correlation with steady-state visual evoked potential power at 10 Hz is shown. ssVEP=steady-state visual evoked potental.
*p<0.01. **p<.001.
Significant main effects of group were observed in the middle occipital gyrus in the left hemisphere (F=27.44, df=1, 35, p<0.001, d=1.79), which correlated with reduced mean theta amplitude across groups (rp=0.493, p=0.002) and within groups (schizophrenia group: r=0.485, p=0.026; control groups: r=0.518, p=0.040) (Figure 3B). Significant main effects of group were also observed in the right pulvinar of the thalamus (F=20.62, df=1, 35, p<0.001, d=1.55), which correlated with reduced steady-state visual evoked potential power both in schizophrenia patients (r=0.511, p=0.018) and in healthy comparison subjects (r=0.740, p=0.001) as well as across groups (rp=0.60, p<0.001) (Figure 3C).
Reduced activations were observed in additional occipital and frontal brain regions (for further details, see Table S4 in the online supplement ). However, no significant correlations were observed with any electrophysiological measures for these regions in any group (all p values >0.25).
Correlations With Neurocognitive Measures
Across the two patient groups (schizophrenia and attenuated psychosis), reduced motion-evoked delta activity correlated with lower overall composite scores on the MCCB (r=0.397, p=0.001) (Figure 4A) as well as lower scores on the visual learning domain (r=0.408, p<0.001) (Figure 4A), the attention/vigilance domain (r=0.271, p=0.024), and the speed of processing domain (r=0.392, p=0.001). Similarly, mean theta amplitude evoked by stimulus onset correlated with scores on the domains of visual learning (r=0.296, p=0.014) and processing speed (r=0.406, p=0.001) across all patients.
FIGURE 4. Correlation of Delta Amplitude With Neurocognitive Measures and Measures of Transitiona
a Panel A shows the correlation of delta amplitude with score on the MATRICS (Measurement and Treatment Research to Improve Cognition in Schizophrenia) Consensus Cognitive Battery (MCCB). Across the two clinical groups (schizophrenia [SZ] and attenuated psychosis [APS]), higher delta evoked amplitude in response to magnocellular-biased low spatial frequency and low-contrast stimuli correlated with higher scores (better performance) in the overall score (left) and in the visual learning domain (right) of the MCCB. Correlation values and regression lines are indicated across all study subjects. The within-group correlations were as follows: overall score, SZ group: r=0.336, p=0.015; APS group: r=0.476, p=0.053; visual learning score, SZ group: r=0.341, p=0.014; APS group: r=0.542, p=0.025. Panel B shows the delta and theta ratios for the APS group. Bar plots of the ratio of delta to theta amplitude in response to low spatial frequency and low-contrast stimuli are shown for patients with APS who transitioned to schizophrenia and for those who did not.
*p<0.01.
Transition to Schizophrenia
Of the 32 patients with attenuated psychosis, six transitioned to psychosis (all to schizophrenia) over a 2-year follow-up period. Among patients with attenuated psychosis, the ratio between delta and theta activity differed significantly between individuals who did and did not transition to schizophrenia (t=2.91, df=30, p=0.007, d=1.06) (Figure 4B), with a cutoff value of 0.7 (equivalent to a 99% confidence interval for the remaining participants) correctly predicting 100% of those who did transition but excluding 35% (N=9/26) of those who did not transition (likelihood ratio χ2=4.48, p=0.034).
Furthermore, across patients with attenuated psychosis, the delta and theta ratios correlated significantly with positive (r=−0.32, p=0.036), negative (r=−0.32, p=0.036), and general (r=−0.33, p=0.029) symptoms as ascertained using the Scale of Prodromal Symptoms. Finally, face emotion recognition scores (ascertained with the Penn Emotion Recognition Task) also significantly differentiated individuals who transitioned to schizophrenia from those who did not (t=2.25, df=30, p=0.045, d=0.82). By contrast, no significant differences were observed for either neurocognitive measures (ascertained with the MCCB) or symptom measures (ascertained with the Scale of Prodromal Symptoms).
Control Analyses
When separate ANOVAs were conducted by testing site, both motion-evoked delta activity (Nathan Kline Institute for Psychiatric Research: p=0.001; New York State Psychiatric Institute: p=0.008) and behavioral motion-sensitivity (Nathan Kline Institute for Psychiatric Research: p<0.001; New York State Psychiatric Institute: p=0.026) were independently significant for patients with schizophrenia or attenuated psychosis compared with age-matched control subjects at each site. For theta (Nathan Kline Institute for Psychiatric Research: p=0.011; New York State Psychiatric Institute: p=0.01) and steady-state visual evoked potential power (Nathan Kline Institute for Psychiatric Research: p=0.009; New York State Psychiatric Institute: p=0.018), differences between patients with schizophrenia and healthy control subjects were also independently significant at each site.
No significant differences by sex were observed either across or within sites. Additionally, no significant correlations were observed between any measure and medication dosage (assessed in chlorpromazine equivalents) (30).
Discussion
This study investigated the integrity of early visual processing both in patients with schizophrenia and in patients with attenuated psychosis and its linkage to cognitive function. The findings confirm the hypothesis that deficits in motion perception are present even before the onset of schizophrenia and are associated with impaired activation in motion-sensitive visual cortex (mid-temporal cortex area). Moreover, deficits in motion processing correlate significantly with impairments in face emotion recognition as well as with multiple domains of cognition in patients with schizophrenia and attenuated psychosis (Figure 2). Overall, these findings highlight the importance of sensory-level dysfunction in the personal experience and neuronal machinery not only in patients with schizophrenia (31) but also in individuals with attenuated psychosis who are at high risk of transitioning to schizophrenia.
In contrast to deficits in motion processing, patients with attenuated psychosis showed preservation of other aspects of early visual function that were also impaired in the schizophrenia group, demonstrating functional differences as well as similarities between the schizophrenia and attenuated psychosis syndromes. Specifically, the theta frequency response to stimulus onset was not impaired in patients with attenuated psychosis but was significantly reduced in patients with schizophrenia and correlated with impaired activation in the middle occipital gyrus (Figure 3B). Likewise, whereas the amplitude of the alpha frequency steady-state visual evoked potential in response to steady-state stimuli was intact in patients with attenuated psychosis, in patients with schizophrenia it was significantly diminished and correlated with reduced functional activation in the pulvinar nucleus (Figure 3C). This finding is consistent with the known role of the pulvinar in the generation of occipital alpha rhythms (32–34) as well as with studies showing that lesions of the pulvinar produce schizophrenia-like positive symptoms and language impairments in otherwise healthy individuals (35). Taken together, the discrepancy in deficit patterns between patients with attenuated psychosis and patients with schizophrenia suggests that further deterioration in visual cortical processing may occur during transition to schizophrenia, potentially leading to additional visual impairments and social cognitive decline.
Although sensory processing was once considered an intact simple function, research has increasingly demonstrated the importance of both auditory and visual sensory disturbances in the pathophysiology of schizophrenia. Impaired motion perception, in particular, has been associated with deficits in several perceptual and cognitive processes, including eye tracking, biological motion detection, and potential for theory of mind (for a review, see reference 1). The present findings further suggest that motion processing deficits are present and may contribute to disability, even in individuals with only attenuated psychotic symptoms.
Impaired motion sensitivity, measured behaviorally, correlated with neurophysiological (delta) measures of poor motion processing both in patients with attenuated psychosis and in patients with schizophrenia as well as with deficits in the ability to detect emotion based on facial expression (Figure 2D), a deficit that we (21) and others (36) have previously shown to be highly predictive of transition to schizophrenia. In the present study, static faces were used to evaluate correlations between visual sensory function and face emotion recognition. Nonetheless, the results encourage development of validated dynamic emotion paradigms with greater ecological validity (5) than that of currently available measures, such as the Penn Emotion Recognition Task, and further suggest that application of such batteries may help to differentiate individuals with attenuated psychosis or schizophrenia from healthy individuals. Finally, deficits in the neurophysiological response to motion onset predicted impaired scores on the MCCB domains of visual learning (Figure 4A), processing speed, and attention/vigilance among patients in the attenuated psychosis and schizophrenia groups, suggesting a significant contribution to impaired present function. Visual learning, for example, is significantly correlated with employability among patients with schizophrenia (37).
Consistent with the differential impairments in delta frequency responses compared with theta frequency responses in the attenuated psychosis group, the dissociation between these measures (delta and theta ratios) differed significantly between patients who transitioned to schizophrenia and those who did not (Figure 4B). Although this finding requires replication in a larger sample, the effect size of the difference (d=1.06) compares favorably with that of previously described biomarkers, such as the duration (d=0.71) and frequency (d=0.32) of mismatch negativity (38, 39). Moreover, other clinical measures, such as MCCB scores and symptoms, did not significantly predict conversion to schizophrenia in the present sample. Further studies are needed to evaluate the degree to which the predictive value of the delta and theta ratios adds to previously identified predictors, such as impairments in face emotion recognition, mismatch negativity, negative symptoms, and MRI-based measures.
In summary, visual as well as auditory sensory deficits have become increasingly established in schizophrenia, especially involving the ability to detect motion, which in turn affects both cognitive and emotion detection processes. We showed that such deficits are present even in individuals with an attenuated psychosis syndrome and contribute to functional impairments and symptoms. Although we have provided initial evidence that visual processing deficits may be predictive of transition to schizophrenia, our findings need to be confirmed in larger prospective cohorts.
Limitations
There are several limitations to this study. First, it was conducted across two recruitment sites, which may have introduced variance. Nevertheless, the main finding of reduced motion sensitivity and reduced motion-related delta activity across the two clinical cohorts (attenuated psychosis and schizophrenia) remained strongly significant, even when the sites were considered independently, suggesting relative cross-site reliability of the measure. Second, patients with schizophrenia were all receiving antipsychotic medication, which may have affected behavioral and neurophysiological measures. Nevertheless, no correlations with medication dosages were observed. Furthermore, the finding of equivalent deficits in motion processing both in at-risk patients with attenuated psychosis and in patients with schizophrenia argues strongly against a significant medication effect. Finally, given the small number of individuals who transitioned to psychosis, the prediction analyses must be considered exploratory. Nevertheless, effect sizes were comparable to those of other well-established measures, encouraging further confirmatory investigations.
Case Vignette
“Ms. A” was an 18-year-old student who was referred to the study by the Center of Prevention and Evaluation at Columbia University’s Department of Psychiatry and diagnosed with attenuated psychosis syndrome based on the Structured Interview for Prodromal Syndromes. Her score on the Scale of Prodromal Symptoms positive symptom scale was 14.0, which was similar to the mean score for the attenuated psychosis group as a whole. Both her negative symptom score (24.0) and her disorganization score (18.0) were higher than the group mean and fell outside the 95% confidence interval range observed for other study subjects. Within 2 years, she transitioned to schizophrenia.
At the time of her participation in our study, Ms. A was not receiving any medication and had completed 1 year of college. Her face emotion recognition (Emotion Recognition Task) score (34.6) and overall MCCB score (47.5) were comparable to those of the attenuated psychosis group as a whole, although she showed better performance compared with the group on auditory-based tasks, such as working memory (60.0) and verbal learning (65.0). Her MCCB scores for visual-based tasks, such as speed of processing (41.0) and visual learning (42.0), were within the range of scores observed for other study subjects, although her score for the attention/vigilance task (34.0) was outside the confidence interval range (37.8–47.5) for other patients with attenuated psychosis.
Ms. A’s motion-sensitivity thresholds were dramatically elevated, as reflected by the need for a 32.2% coherence (motion sensitivity of 3.1) in order to accurately detect motion direction, compared with a mean of 14.2% (SD=6.2%) for the attenuated psychosis group as a whole and 9.8% (SD=4.1%) for age-matched healthy control subjects. Consistent with this, Ms. A’s motion-induced delta-frequency response of 0.17 μV was outside the confidence intervals for the attenuated psychosis group as a whole (0.24–0.32 μV) and for age-matched healthy control subjects (0.32–0.45 μV). By contrast, her stimulus-onset-evoked theta frequency response (0.44 μV) was comparable to the response for the attenuated psychosis group (0.47 μV). Finally, the patient’s delta-theta ratio of 0.42 was outside the 95% confidence interval for age-matched control subjects (0.78–1.48) as well as for other patients with attenuated psychosis (0.56–0.99).
Measures of motion sensitivity and motion-induced delta activity are not routinely obtained in clinical practice but may contribute to impairments in visual function, such as visual learning and attention/vigilance (MCCB domains). The discrepancy between the electrophysiological response to stimulus motion (delta activity) compared with that of stimulus onset (theta activity) may serve as a predictor of transition to psychosis among individuals at clinical high risk due to the presence of attenuated positive symptoms.
Acknowledgments
The authors thank Gail Silipo, M.A., for assistance with participant recruitment, Raj Sangoi and Caxia Hu, M.S., for assistance with MRI scanning, and Isabel and Herb Stusser for their generous support.
Supplementary Material
File (appi.ajp.2018.18010072.ds001.pdf)
- View/Download
- 417.70 KB
References
1.
Chen Y: Abnormal visual motion processing in schizophrenia: a review of research progress. Schizophr Bull 2011; 37:709–715
2.
Berry DS: What can a moving face tell us? J Pers Soc Psychol 1990; 58:1004–1014
3.
Kuba M, Kubová Z, Kremlácek J, et al: Motion-onset VEPs: characteristics, methods, and diagnostic use. Vision Res 2007; 47:189–202
4.
Tootell RB, Reppas JB, Kwong KK, et al: Functional analysis of human MT and related visual cortical areas using magnetic resonance imaging. J Neurosci 1995; 15:3215–3230
5.
Bernstein M, Yovel G: Two neural pathways of face processing: a critical evaluation of current models. Neurosci Biobehav Rev 2015; 55:536–546
6.
Holzman PS: Recent studies of psychophysiology in schizophrenia. Schizophr Bull 1987; 13:49–75
7.
Association AP: Diagnostic and Statistical Manual of Mental Disorders, 5th ed. Washington, DC, American Psychiatric Publishing, 2013
8.
Carrión RE, Cornblatt BA, McLaughlin D, et al: Contributions of early cortical processing and reading ability to functional status in individuals at clinical high risk for psychosis. Schizophr Res 2015; 164:1–7
9.
Milner AD, Goodale MA: Two visual systems re-viewed. Neuropsychologia 2008; 46:774–785
10.
Tamietto M, Morrone MC: Visual plasticity: blindsight bridges anatomy and function in the visual system. Curr Biol 2016; 26:R70–R73
11.
Javitt DC: Neurophysiological models for new treatment development in schizophrenia: early sensory approaches. Ann N Y Acad Sci 2015; 1344:92–104
12.
Martínez A, Revheim N, Butler PD, et al: Impaired magnocellular/dorsal stream activation predicts impaired reading ability in schizophrenia. Neuroimage Clin 2012; 2:8–16
13.
Martínez A, Hillyard SA, Dias EC, et al: Magnocellular pathway impairment in schizophrenia: evidence from functional magnetic resonance imaging. J Neurosci 2008; 28:7492–7500
14.
Dorph-Petersen KA, Pierri JN, Wu Q, et al: Primary visual cortex volume and total neuron number are reduced in schizophrenia. J Comp Neurol 2007; 501:290–301
15.
Byne W, Fernandes J, Haroutunian V, et al: Reduction of right medial pulvinar volume and neuron number in schizophrenia. Schizophr Res 2007; 90:71–75
16.
Zhao C, Zhu J, Liu X, et al: Structural and functional brain abnormalities in schizophrenia: a cross-sectional study at different stages of the disease. Prog Neuropsychopharmacol Biol Psychiatry 2018; 83:27–32
17.
Ziermans TB, Schothorst PF, Schnack HG, et al: Progressive structural brain changes during development of psychosis. Schizophr Bull 2012; 38:519–530
18.
Mishra J, Martínez A, Schroeder CE, et al: Spatial attention boosts short-latency neural responses in human visual cortex. Neuroimage 2012; 59:1968–1978
19.
Pitzalis S, Strappini F, De Gasperis M, et al: Spatio-temporal brain mapping of motion-onset VEPs combined with fMRI and retinotopic maps. PLoS One 2012; 7:e35771
20.
Brenner CA, Krishnan GP, Vohs JL, et al: Steady state responses: electrophysiological assessment of sensory function in schizophrenia. Schizophr Bull 2009; 35:1065–1077
21.
Corcoran CM, Keilp JG, Kayser J, et al: Emotion recognition deficits as predictors of transition in individuals at clinical high risk for schizophrenia: a neurodevelopmental perspective. Psychol Med 2015; 45:2959–2973
22.
Healey KM, Penn DL, Perkins D, et al: Latent profile analysis and conversion to psychosis: characterizing subgroups to enhance risk prediction. Schizophr Bull 2018; 44:286–296
23.
Miller TJ, McGlashan TH, Rosen JL, et al: Prodromal assessment with the structured interview for prodromal syndromes and the Scale of Prodromal Symptoms: predictive validity, interrater reliability, and training to reliability. Schizophr Bull 2003; 29:703–715
24.
Kay S, Opler L, Fiszbein A: The Positive and Negative Syndrome Scale (PANSS) Manual. Toronto, Multi-Health Systems, 1992
25.
Nuechterlein KH, Green MF, Kern RS, et al: The MATRICS Consensus Cognitive Battery, part 1: test selection, reliability, and validity. Am J Psychiatry 2008; 165:203–213
26.
Taylor SF, MacDonald AW 3rd; Cognitive Neuroscience Treatment Research to Improve Cognition in Schizophrenia: Brain mapping biomarkers of socio-emotional processing in schizophrenia. Schizophr Bull 2012; 38:73–80
27.
Martínez A, Gaspar PA, Hillyard SA, et al: Neural oscillatory deficits in schizophrenia predict behavioral and neurocognitive impairments. Front Hum Neurosci 2015; 9:371
28.
Lee M, Sehatpour P, Dias EC, et al: A tale of two sites: differential impairment of frequency and duration mismatch negativity across a primarily inpatient versus a primarily outpatient site in schizophrenia. Schizophr Res 2018; 191:10–17
29.
Lopez-Calderon J, Luck SJ: ERPLAB: an open-source toolbox for the analysis of event-related potentials. Front Hum Neurosci 2014; 8:213
30.
Rose VL: APA Practice Guideline for the Treatment of Patients with Schizophrenia. Am Fam Physician 1997; 56:1217–1220
31.
Javitt DC, Freedman R: Sensory processing dysfunction in the personal experience and neuronal machinery of schizophrenia. Am J Psychiatry 2015; 172:17–31
32.
Zhou H, Schafer RJ, Desimone R: Pulvinar-cortex interactions in vision and attention. Neuron 2016; 89:209–220
33.
Goldman RI, Stern JM, Engel J Jr, et al: Simultaneous EEG and fMRI of the alpha rhythm. Neuroreport 2002; 13:2487–2492
34.
Liu Z, de Zwart JA, Yao B, et al: Finding thalamic BOLD correlates to posterior alpha EEG. Neuroimage 2012; 63:1060–1069
35.
Byne W, Hazlett EA, Buchsbaum MS, et al: The thalamus and schizophrenia: current status of research. Acta Neuropathol 2009; 117:347–368
36.
Addington J, Saeedi H, Addington D: Facial affect recognition: a mediator between cognitive and social functioning in psychosis? Schizophr Res 2006; 85:142–150
37.
August SM, Kiwanuka JN, McMahon RP, et al: The MATRICS Consensus Cognitive Battery (MCCB): clinical and cognitive correlates. Schizophr Res 2012; 134:76–82
38.
Perez VB, Woods SW, Roach BJ, et al: Automatic auditory processing deficits in schizophrenia and clinical high-risk patients: forecasting psychosis risk with mismatch negativity. Biol Psychiatry 2014; 75:459–469
39.
Bodatsch M, Brockhaus-Dumke A, Klosterkötter J, et al: Forecasting psychosis by event-related potentials-systematic review and specific meta-analysis. Biol Psychiatry 2015; 77:951–958
Information & Authors
Information
Published In
History
Received: 17 January 2018
Revision received: 1 April 2018
Revision received: 14 May 2018
Accepted: 29 May 2018
Published online: 3 October 2018
Published in print: December 01, 2018
Keywords
Authors
Competing Interests
Dr. Javitt serves on the scientific advisory boards of NeuroRx, Phytecs, and Promentis; he has received honoraria and travel compensation from Autifony, Cadence, Glytech, Forum, Lundbeck, NeuroRx, Pfizer, and Takeda; he is a shareholder in Amino Acid Solutions Incorporated, Glytech, and NeuroRx; and he holds patents for use of N-methyl-d-aspartate receptor antagonists in the treatment of neuropsychiatric disorders. All other authors report no financial relationships with commercial interests.
Funding Information
National Institute of Mental Health10.13039/100000025: DA03383
Supported by NIMH grants MH049334 (to Dr. Javitt) and DA03383 (to Dr. Javitt).Metrics & Citations
Metrics
Citations
Export Citations
If you have the appropriate software installed, you can download article citation data to the citation manager of your choice. Simply select your manager software from the list below and click Download.
For more information or tips please see 'Downloading to a citation manager' in the Help menu.
View Options
View options
PDF/EPUB
View PDF/EPUBGet Access
Login options
Already a subscriber? Access your subscription through your login credentials or your institution for full access to this article.
Personal login Institutional Login Open Athens loginNot a subscriber?
PsychiatryOnline subscription options offer access to the DSM-5-TR® library, books, journals, CME, and patient resources. This all-in-one virtual library provides psychiatrists and mental health professionals with key resources for diagnosis, treatment, research, and professional development.
Need more help? PsychiatryOnline Customer Service may be reached by emailing [email protected] or by calling 800-368-5777 (in the U.S.) or 703-907-7322 (outside the U.S.).