abnormal neural oscillations and synchrony in schizophrenia

Abnormal neural oscillations and synchrony in schizophrenia

Uhlhaas and Singer 2010 NRN

Prepared for Brain Dynamics Lab Journal Club

2010.03.09, 10:30p.m.

Kyongsik Yun, Ph.D. CandidateKAIST

yunks@kaist.edu

1

Neural oscillations and synchrony in cortical networks

The timing of rhythmic activity in cortical networks influences communication between neuronal populations.

LFP

Interconnected neurons

Action potentials

Effective communication

Preventing communication

2

Synchronization between neurons in local cortical networks depends on the occurrence of gamma oscillations

3BA17, anaesthetized cats, a drifting grating stimulus

Oscillations in the beta and gamma range establish synchronization with great precision in local cortical networks

Measurement of steady-state evoked potentials

4

A steady-state stimulation at a frequency of 20 Hz

Steady-state evoked potentials can probe the ability of neuronal networks to generate and maintain oscillatory activity in different frequency bands.

Evoked and induced oscillations reflect different aspects of information processing in cortical networks

5

Evoked activity reflects bottom-up sensory transmission (close temporal relationship with the incoming stimulus). Induced activity represents the internal dynamics of cortical networks (higher cognitive functions)

Neural oscillations and synchrony inschizophrenia

6

The presentation of click trains Visual oddball taskdysfunction in early sensory processes

Dysfunctional phase synchrony during Gestalt perception in schizophrenia

7

Phase synchrony

Control – ScZRed: +Green: -

Negative feedback inhibition of pyramidal cells by GABAergicinterneurons that express the Ca2+-binding protein parvalbumin

This phasic inhibition leads to the synchronization of spiking activity that can be recovered with a cross-correlogram

The network of GABAergic interneuronsacts as a pacemaker in the generation of high frequency oscillations by producing rhythmic inhibitory postsynaptic potentials.

A neocortical circuit involved in the generation of gamma-band oscillations

8

Cortico-cortical connections mediate long-distance synchronization

9

These data show that synchronization can occur over long distances with high precision and is crucially dependent on the integrity of cortico-cortical connections

Connectivity of the corpus callosum and its abnormalities in schizophrenia as reflected in

diffusion tensor imaging data

10

Patients with schizophrenia show significantly less organization (lower fractional anisotropy) in subdivisions of the corpus callosum than controls.

Fractional anisotropy values estimate the presence and coherence of oriented structures, such as myelinated axons.

p < 0.0055

p < 0.05

Expression of parvalbumin mRNA in layers 3–4 of the dlPFC is reduced in patients with schizophrenia

11

These findings suggest that the ability of parvalbumin-positive interneurons to express important genes is impaired in schizophrenia

Expression of parvalbuminmRNA

Reduction in gamma oscillations and parvalbumin-positive neurons in the mPFC in an animal model of schizophrenia

12

This methylazoxymethanol acetate (MAM) treated model reproduces the anatomical changes, behavioural deficits and altered neuronal information processing observed in ScZ patients.

Treated rats display a regionally specific reduction in the density of parvalbumin-positive neurons throughout the mPFC, Acg, and vSub.

The presentation of a tone induces a mild increase in prefrontal gamma (30–55 Hz) oscillations in saline- but not MAM-treated rats.

Methylazoxymethanol acetate (MAM)

Emergence of high-frequency oscillations and synchrony during the transition from adolescence to adulthood

13

Gamma oscillations increase significantly during the transition from adolescence to adulthood.

Cortical networks reorganize during the transition from adolescence to adulthood.

Uhlhaas et al. PNAS 2009

Changes in GABAA receptor-mediated neurotransmission in the monkey dlPFC during adolescence

14

A higher fraction of shorter mIPSPs in postpubertal animals than in prepubertal animals

As the decay time of IPSPs is a critical factor for the dominant frequency of oscillations in a network, these data provide one mechanism for the late maturation of high-frequency oscillations

30ms: 33Hz40ms: 25Hz

MonkeyPrepubertal: 15~17 monthsPostpubertal: 43~47 months